Multiscale Framework for Assessing Critical Loads of Atmospheric Nitrogen Deposition for Aquatic Ecosystems in Wilderness Areas of the Western United States

NASA Astrophysics Data System (ADS)

Nanus, Leora; Clow, David; Saros, Jasmine; McMurray, Jill; Blett, Tamara; Sickman, James

2017-04-01

High-elevation aquatic ecosystems in Wilderness areas of the western United States are impacted by current and historic atmospheric nitrogen (N) deposition associated with local and regional air pollution. Documented effects include elevated surface water nitrate concentrations, increased algal productivity, and changes in diatom species assemblages. A predictive framework was developed for sensitive high-elevation basins across the western United States at multiple spatial scales including the Rocky Mountain Region (Rockies), the Greater Yellowstone Area (GYA), and Yosemite (YOSE) and Sequoia & Kings Canyon (SEKI) National Parks. Spatial trends in critical loads of N deposition for nutrient enrichment of aquatic ecosystems were quantified and mapped using a geostatistical approach, with modeled N deposition, topography, vegetation, geology, and climate as potential explanatory variables. Multiple predictive models were created using various combinations of explanatory variables; this approach allowed for better quantification of uncertainty and identification of areas most sensitive to high atmospheric N deposition (> 3 kg N ha-1 yr-1). For multiple spatial scales, the lowest critical loads estimates (<1.5 + 1 kg N ha-1 yr-1) occurred in high-elevation basins with steep slopes, sparse vegetation, and exposed bedrock and talus. Based on a nitrate threshold of 1 μmol L-1, estimated critical load exceedances (>1.5 + 1 kg N ha-1 yr-1) correspond with areas of high N deposition and vary spatially ranging from less than 20% to over 40% of the study area for the Rockies, GYA, YOSE, and SEKI. These predictive models and maps identify sensitive aquatic ecosystems that may be impacted by excess atmospheric N deposition and can be used to help protect against future anthropogenic disturbance. The approach presented here may be transferable to other remote and protected high-elevation ecosystems at multiple spatial scales that are sensitive to adverse effects of pollutant loading in the US and around the world.

Comparison of Bioclimatic, NDVI and Elevation variables in assessing extent of Commiphora wightii (Arnt.) Bhand.

NASA Astrophysics Data System (ADS)

Kulloli, R. N.; Kumar, S.

2014-11-01

Commiphora wightii (Arnt.) Bhand., is an important medicinal plant of Indian Medicine System (IMS) since ancient time. It is used in different ailments of obesity, arthritis, rheumatism and high cholesterol. Due to overexploitation its natural populations declined to large extent. IUCN has put it under Data Deficient (DD) category due to lack of data on its extent of occurrence in nature. Hence, the study was carried out using MaxEnt distribution modelling algorithm to estimate its geographic distribution and to identify potential habitats for its reintroduction. For modelling employed 68 presence locality data, 19 bioclimatic variables, Normalize Difference Vegetation Index (NDVI) and elevation data. These were tested for multicollinearity and those variables having r-value less than 0.8 were selected for further analysis, which was carried out in two ways i) Bioclimatic variables and elevation; ii) NDVI and elevation. Area Under the Curve (AUC) in both analysis was above 0.9 for all variables, indicating very high accuracy of prediction. Variables governing distribution of C. wightii in the analysis using bioclimatic and elevation data set are precipitation seasonality (56.6 %), annual precipitation (16.4 %) and elevation (14.7 %). Extent of occurrence of C.wightii predicted by model closely matched in the districts of Jaisalmer and Barmer. In the second analysis elevation (48.3 %), NDVI of June (11.1 %) and August (11.2 %) contributed for NDVI and Elevation data set. NDVI of June corresponds to its leafing phase while NDVI of August to flowering phase. Area of its occurrence predicted for NDVI and elevation data set are Bikaner, Churu, Jhunjhunun some part of Jodhpur which are completely sandy, where C. wightii is totally absent. Extent of occurrence was also validated in ground survey. Potential areas for its reintroduction were identified as Jaisalmer and Barmer districts in Indian arid zone.

Modeling tidal marsh distribution with sea-level rise: evaluating the role of vegetation, sediment, and upland habitat in marsh resiliency.

PubMed

Schile, Lisa M; Callaway, John C; Morris, James T; Stralberg, Diana; Parker, V Thomas; Kelly, Maggi

2014-01-01

Tidal marshes maintain elevation relative to sea level through accumulation of mineral and organic matter, yet this dynamic accumulation feedback mechanism has not been modeled widely in the context of accelerated sea-level rise. Uncertainties exist about tidal marsh resiliency to accelerated sea-level rise, reduced sediment supply, reduced plant productivity under increased inundation, and limited upland habitat for marsh migration. We examined marsh resiliency under these uncertainties using the Marsh Equilibrium Model, a mechanistic, elevation-based soil cohort model, using a rich data set of plant productivity and physical properties from sites across the estuarine salinity gradient. Four tidal marshes were chosen along this gradient: two islands and two with adjacent uplands. Varying century sea-level rise (52, 100, 165, 180 cm) and suspended sediment concentrations (100%, 50%, and 25% of current concentrations), we simulated marsh accretion across vegetated elevations for 100 years, applying the results to high spatial resolution digital elevation models to quantify potential changes in marsh distributions. At low rates of sea-level rise and mid-high sediment concentrations, all marshes maintained vegetated elevations indicative of mid/high marsh habitat. With century sea-level rise at 100 and 165 cm, marshes shifted to low marsh elevations; mid/high marsh elevations were found only in former uplands. At the highest century sea-level rise and lowest sediment concentrations, the island marshes became dominated by mudflat elevations. Under the same sediment concentrations, low salinity brackish marshes containing highly productive vegetation had slower elevation loss compared to more saline sites with lower productivity. A similar trend was documented when comparing against a marsh accretion model that did not model vegetation feedbacks. Elevation predictions using the Marsh Equilibrium Model highlight the importance of including vegetation responses to sea-level rise. These results also emphasize the importance of adjacent uplands for long-term marsh survival and incorporating such areas in conservation planning efforts.

Predicting cutthroat trout (Oncorhynchus clarkii) abundance in high-elevation streams: revisiting a model of translocation success

Treesearch

Michael K. Young; Paula M. Guenther-Gloss; Ashley D. Ficke

2005-01-01

Assessing viability of stream populations of cutthroat trout (Oncorhynchus clarkii) and identifying streams suitable for establishing populations are priorities in the western United States, and a model was recently developed to predict translocation success (as defined by an index of population size) of two subspecies based on mean July water...

Does more mean less? The value of information for conservation planning under sea level rise.

PubMed

Runting, Rebecca K; Wilson, Kerrie A; Rhodes, Jonathan R

2013-02-01

Many studies have explored the benefits of adopting more sophisticated modelling techniques or spatial data in terms of our ability to accurately predict ecosystem responses to global change. However, we currently know little about whether the improved predictions will actually lead to better conservation outcomes once the costs of gaining improved models or data are accounted for. This severely limits our ability to make strategic decisions for adaptation to global pressures, particularly in landscapes subject to dynamic change such as the coastal zone. In such landscapes, the global phenomenon of sea level rise is a critical consideration for preserving biodiversity. Here, we address this issue in the context of making decisions about where to locate a reserve system to preserve coastal biodiversity with a limited budget. Specifically, we determined the cost-effectiveness of investing in high-resolution elevation data and process-based models for predicting wetland shifts in a coastal region of South East Queensland, Australia. We evaluated the resulting priority areas for reserve selection to quantify the cost-effectiveness of investment in better quantifying biological and physical processes. We show that, in this case, it is considerably more cost effective to use a process-based model and high-resolution elevation data, even if this requires a substantial proportion of the project budget to be expended (up to 99% in one instance). The less accurate model and data set failed to identify areas of high conservation value, reducing the cost-effectiveness of the resultant conservation plan. This suggests that when developing conservation plans in areas where sea level rise threatens biodiversity, investing in high-resolution elevation data and process-based models to predict shifts in coastal ecosystems may be highly cost effective. A future research priority is to determine how this cost-effectiveness varies among different regions across the globe. © 2012 Blackwell Publishing Ltd.

Noise Prediction Models for Elevated Rail Transit Structures

DOT National Transportation Integrated Search

1975-08-01

The report presents the theoretical development of a model for the prediction of noise radiated by elevated structures on rail transit lines. In particular it deals with noise and vibration control for urban rail transit track and elevated noise and ...

Assessment of Required Accuracy of Digital Elevation Data for Hydrologic Modeling

NASA Technical Reports Server (NTRS)

Kenward, T.; Lettenmaier, D. P.

1997-01-01

The effect of vertical accuracy of Digital Elevation Models (DEMs) on hydrologic models is evaluated by comparing three DEMs and resulting hydrologic model predictions applied to a 7.2 sq km USDA - ARS watershed at Mahantango Creek, PA. The high resolution (5 m) DEM was resempled to a 30 m resolution using method that constrained the spatial structure of the elevations to be comparable with the USGS and SIR-C DEMs. This resulting 30 m DEM was used as the reference product for subsequent comparisons. Spatial fields of directly derived quantities, such as elevation differences, slope, and contributing area, were compared to the reference product, as were hydrologic model output fields derived using each of the three DEMs at the common 30 m spatial resolution.

Elevated preoperative blood pressures in adult surgical patients are highly predictive of elevated home blood pressures.

PubMed

Schonberger, Robert B; Nwozuzu, Adambeke; Zafar, Jill; Chen, Eric; Kigwana, Simon; Monteiro, Miriam M; Charchaflieh, Jean; Sophanphattana, Sophisa; Dai, Feng; Burg, Matthew M

2018-04-01

Blood pressure (BP) measurement during the presurgical assessment has been suggested as a way to improve longitudinal detection and treatment of hypertension. The relationship between BP measured during this assessment and home blood pressure (HBP), a better indicator of hypertension, is unknown. The purpose of the present study was to determine the positive predictive value of presurgical BP for predicting elevated HBP. We prospectively enrolled 200 patients at a presurgical evaluation clinic with clinic blood pressures (CBPs) ≥130/85 mm Hg, as measured using a previously validated automated upper-arm device (Welch Allyn Vital Sign Monitor 6000 Series), to undergo daily HBP monitoring (Omron Model BP742N) between the index clinic visit and their day of surgery. Elevated HBP was defined, per American Heart Association guidelines, as mean systolic HBP ≥135 mm Hg or mean diastolic HBP ≥85 mm Hg. Of the 200 participants, 188 (94%) returned their home blood pressure monitors with valid data. The median number of HBP recordings was 10 (interquartile range, 7-14). Presurgical CBP thresholds of 140/90, 150/95, and 160/100 mm Hg yielded positive predictive values (95% confidence interval) for elevated HBP of 84.1% (0.78-0.89), 87.5% (0.81-0.92), and 94.6% (0.87-0.99), respectively. In contrast, self-reported BP control, antihypertensive treatment, availability of primary care, and preoperative pain scores demonstrated poor agreement with elevated HBP. Elevated preoperative CBP is highly predictive of longitudinally elevated HBP. BP measurement during presurgical assessment may provide a way to improve longitudinal detection and treatment of hypertension. Copyright © 2018 American Heart Association. Published by Elsevier Inc. All rights reserved.

Optimal plant nitrogen use improves model representation of vegetation response to elevated CO2

NASA Astrophysics Data System (ADS)

Caldararu, Silvia; Kern, Melanie; Engel, Jan; Zaehle, Sönke

2017-04-01

Existing global vegetation models often cannot accurately represent observed ecosystem behaviour under transient conditions such as elevated atmospheric CO2, a problem that can be attributed to an inflexibility in model representation of plant responses. Plant optimality concepts have been proposed as a solution to this problem as they offer a way to represent plastic plant responses in complex models. Here we present a novel, next generation vegetation model which includes optimal nitrogen allocation to and within the canopy as well as optimal biomass allocation between above- and belowground components in response to nutrient and water availability. The underlying hypothesis is that plants adjust their use of nitrogen in response to environmental conditions and nutrient availability in order to maximise biomass growth. We show that for two FACE (Free Air CO2 enrichment) experiments, the Duke forest and Oak Ridge forest sites, the model can better predict vegetation responses over the duration of the experiment when optimal processes are included. Specifically, under elevated CO2 conditions, the model predicts a lower optimal leaf N concentration as well as increased biomass allocation to fine roots, which, combined with a redistribution of leaf N between the Rubisco and chlorophyll components, leads to a continued NPP response under high CO2, where models with a fixed canopy stoichiometry predict a quick onset of N limitation.Existing global vegetation models often cannot accurately represent observed ecosystem behaviour under transient conditions such as elevated atmospheric CO2, a problem that can be attributed to an inflexibility in model representation of plant responses. Plant optimality concepts have been proposed as a solution to this problem as they offer a way to represent plastic plant responses in complex models. Here we present a novel, next generation vegetation model which includes optimal nitrogen allocation to and within the canopy as well as optimal biomass allocation between above- and belowground components in response to nutrient and water availability. The underlying hypothesis is that plants adjust their use of nitrogen in response to environmental conditions and nutrient availability in order to maximise biomass growth. We show that for two FACE (Free Air CO2 enrichment) experiments, the Duke forest and Oak Ridge forest sites, the model can better predict vegetation responses over the duration of the experiment when optimal processes are included. Specifically, under elevated CO2 conditions, the model predicts a lower optimal leaf N concentration as well as increased biomass allocation to fine roots, which, combined with a redistribution of leaf N between the Rubisco and chlorophyll components, leads to a continued NPP response under high CO2, where models with a fixed canopy stoichiometry predict a quick onset of N limitation.

Improving salt marsh digital elevation model accuracy with full-waveform lidar and nonparametric predictive modeling

NASA Astrophysics Data System (ADS)

Rogers, Jeffrey N.; Parrish, Christopher E.; Ward, Larry G.; Burdick, David M.

2018-03-01

Salt marsh vegetation tends to increase vertical uncertainty in light detection and ranging (lidar) derived elevation data, often causing the data to become ineffective for analysis of topographic features governing tidal inundation or vegetation zonation. Previous attempts at improving lidar data collected in salt marsh environments range from simply computing and subtracting the global elevation bias to more complex methods such as computing vegetation-specific, constant correction factors. The vegetation specific corrections can be used along with an existing habitat map to apply separate corrections to different areas within a study site. It is hypothesized here that correcting salt marsh lidar data by applying location-specific, point-by-point corrections, which are computed from lidar waveform-derived features, tidal-datum based elevation, distance from shoreline and other lidar digital elevation model based variables, using nonparametric regression will produce better results. The methods were developed and tested using full-waveform lidar and ground truth for three marshes in Cape Cod, Massachusetts, U.S.A. Five different model algorithms for nonparametric regression were evaluated, with TreeNet's stochastic gradient boosting algorithm consistently producing better regression and classification results. Additionally, models were constructed to predict the vegetative zone (high marsh and low marsh). The predictive modeling methods used in this study estimated ground elevation with a mean bias of 0.00 m and a standard deviation of 0.07 m (0.07 m root mean square error). These methods appear very promising for correction of salt marsh lidar data and, importantly, do not require an existing habitat map, biomass measurements, or image based remote sensing data such as multi/hyperspectral imagery.

Predicting Individual Tree and Shrub Species Distributions with Empirically Derived Microclimate Surfaces in a Complex Mountain Ecosystem in Northern Idaho, USA

NASA Astrophysics Data System (ADS)

Holden, Z.; Cushman, S.; Evans, J.; Littell, J. S.

2009-12-01

The resolution of current climate interpolation models limits our ability to adequately account for temperature variability in complex mountainous terrain. We empirically derive 30 meter resolution models of June-October day and nighttime temperature and April nighttime Vapor Pressure Deficit (VPD) using hourly data from 53 Hobo dataloggers stratified by topographic setting in mixed conifer forests near Bonners Ferry, ID. 66%, of the variability in average June-October daytime temperature is explained by 3 variables (elevation, relative slope position and topographic roughness) derived from 30 meter digital elevation models. 69% of the variability in nighttime temperatures among stations is explained by elevation, relative slope position and topographic dissection (450 meter window). 54% of variability in April nighttime VPD is explained by elevation, soil wetness and the NDVIc derived from Landsat. We extract temperature and VPD predictions at 411 intensified Forest Inventory and Analysis plots (FIA). We use these variables with soil wetness and solar radiation indices derived from a 30 meter DEM to predict the presence and absence of 10 common forest tree species and 25 shrub species. Classification accuracies range from 87% for Pinus ponderosa , to > 97% for most other tree species. Shrub model accuracies are also high with greater than 90% accuracy for the majority of species. Species distribution models based on the physical variables that drive species occurrence, rather than their topographic surrogates, will eventually allow us to predict potential future distributions of these species with warming climate at fine spatial scales.

Regional Permafrost Probability Modelling in the northwestern Cordillera, 59°N - 61°N, Canada

NASA Astrophysics Data System (ADS)

Bonnaventure, P. P.; Lewkowicz, A. G.

2010-12-01

High resolution (30 x 30 m) permafrost probability models were created for eight mountainous areas in the Yukon and northernmost British Columbia. Empirical-statistical modelling based on the Basal Temperature of Snow (BTS) method was used to develop spatial relationships. Model inputs include equivalent elevation (a variable that incorporates non-uniform temperature change with elevation), potential incoming solar radiation and slope. Probability relationships between predicted BTS and permafrost presence were developed for each area using late-summer physical observations in pits, or by using year-round ground temperature measurements. A high-resolution spatial model for the region has now been generated based on seven of the area models. Each was applied to the entire region, and their predictions were then blended based on a distance decay function from the model source area. The regional model is challenging to validate independently because there are few boreholes in the region. However, a comparison of results to a recently established inventory of rock glaciers for the Yukon suggests its validity because predicted permafrost probabilities were 0.8 or greater for almost 90% of these landforms. Furthermore, the regional model results have a similar spatial pattern to those modelled independently in the eighth area, although predicted probabilities using the regional model are generally higher. The regional model predicts that permafrost underlies about half of the non-glaciated terrain in the region, with probabilities increasing regionally from south to north and from east to west. Elevation is significant, but not always linked in a straightforward fashion because of weak or inverted trends in permafrost probability below treeline. Above treeline, however, permafrost probabilities increase and approach 1.0 in very high elevation areas throughout the study region. The regional model shows many similarities to previous Canadian permafrost maps (Heginbottom and Radburn, 1992; Heginbottom et al., 1995) but is several orders of magnitude more detailed. It also exhibits some significant differences, including the presence of an area of valley-floor continuous permafrost around Beaver Creek near the Alaskan border in the west, as well as higher probabilities of permafrost in the central parts of the region near the boundaries of the sporadic and extensive discontinuous zones. In addition, parts of the northernmost portion of the region would be classified as sporadic discontinuous permafrost because of inversions in the terrestrial surface lapse rate which cause permafrost probabilities to decrease with elevation through the forest. These model predictions are expected to of direct use for infrastructure planning and northern development and can serve as a benchmark for future studies of permafrost distribution in the Yukon. References Heginbottom JR, Dubreuil MA and Haker PT. 1995. Canada Permafrost. (1:7,500,000 scale). In The National Atlas of Canada, 5th Edition, sheet MCR 4177. Ottawa: National Resources Canada. Heginbottom, J.A. and Radburn, L.K. 1992. Permafrost and ground ice conditions of northwestern Canada; Geological Survey of Canada, Map 1691A, scale 1:1,000,000. Digitized by S. Smith, Geological Survey of Canada.

Modeling the population dynamics of Culex quinquefasciatus (Diptera: Culcidae), along an elevational gradient in Hawaii

USGS Publications Warehouse

Ahumada, Jorge A.; LaPointe, Dennis; Samuel, Michael D.

2004-01-01

We present a population model to understand the effects of temperature and rainfall on the population dynamics of the southern house mosquito, Culex quinquefasciatus Say, along an elevational gradient in Hawaii. We use a novel approach to model the effects of temperature on population growth by dynamically incorporating developmental rate into the transition matrix, by using physiological ages of immatures instead of chronological age or stages. We also model the effects of rainfall on survival of immatures as the cumulative number of days below a certain rain threshold. Finally, we incorporate density dependence into the model as competition between immatures within breeding sites. Our model predicts the upper altitudinal distributions of Cx. quinquefasciatus on the Big Island of Hawaii for self-sustaining mosquito and migrating summer sink populations at 1,475 and 1,715 m above sea level, respectively. Our model predicts that mosquitoes at lower elevations can grow under a broader range of rainfall parameters than middle and high elevation populations. Density dependence in conjunction with the seasonal forcing imposed by temperature and rain creates cycles in the dynamics of the population that peak in the summer and early fall. The model provides a reasonable fit to the available data on mosquito abundance for the east side of Mauna Loa, Hawaii. The predictions of our model indicate the importance of abiotic conditions on mosquito dynamics and have important implications for the management of diseases transmitted by Cx. quinquefasciatus in Hawaii and elsewhere.

The role of abiotic conditions in shaping the long-term patterns of a high-elevation Argentine ant invasion

USGS Publications Warehouse

Krushelnycky, P.D.; Joe, S.M.; Medeiros, A.C.; Daehler, C.C.; Loope, L.L.

2005-01-01

Analysis of long-term patterns of invasion can reveal the importance of abiotic factors in influencing invasion dynamics, and can help predict future patterns of spread. In the case of the invasive Argentine ant (Linepithema humile), most prior studies have investigated this species' limitations in hot and dry climates. However, spatial and temporal patterns of spread involving two ant populations over the course of 30 years at a high elevation site in Hawaii suggest that cold and wet conditions have influenced both the ant's distribution and its rate of invasion. In Haleakala National Park on Maui, we found that a population invading at lower elevation is limited by increasing rainfall and presumably by associated decreasing temperatures. A second, higher elevation population has spread outward in all directions, but rates of spread in different directions appear to have been strongly influenced by differences in elevation and temperature. Patterns of foraging activity were strongly tied to soil temperatures, supporting the hypothesis that variation in temperature can influence rates of spread. Based on past patterns of spread, we predicted a total potential range that covers nearly 50% of the park and 75% of the park's subalpine habitats. We compared this rough estimate with point predictions derived from a degree-day model for Argentine ant colony reproduction, and found that the two independent predictions match closely when soil temperatures are used in the model. The cold, wet conditions that have influenced Argentine ant invasion at this site are likely to be influential at other locations in this species' current and future worldwide distribution. ?? 2005 Blackwell Publishing Ltd.

Assessing frost damages using dynamic models in walnut trees: exposure rather than vulnerability controls frost risks.

PubMed

Guillaume, Charrier; Isabelle, Chuine; Marc, Bonhomme; Thierry, Améglio

2018-05-01

Frost damages develop when exposure overtakes frost vulnerability. Frost risk assessment therefore needs dynamic simulation of frost hardiness using temperature and photoperiod in interaction with developmental stage. Two models, including or not the effect of photoperiod, were calibrated using five years of frost hardiness monitoring (2007-2012), in two locations (low and high elevation) for three walnut genotypes with contrasted phenology and maximum hardiness (Juglans regia cv Franquette, J. regia × nigra 'Early' and 'Late'). The photothermal model predicted more accurate values for all genotypes (efficiency = 0.879; Root Mean Standard Error Predicted (RMSEP) = 2.55 °C) than the thermal model (efficiency = 0.801; RMSEP = 3.24 °C). Predicted frost damages were strongly correlated to minimum temperature of the freezing events (ρ = -0.983) rather than actual frost hardiness (ρ = -0.515), or ratio of phenological stage completion (ρ = 0.336). Higher frost risks are consequently predicted during winter, at high elevation, whereas spring is only risky at low elevation in early genotypes exhibiting faster dehardening rate. However, early frost damages, although of lower value, may negatively affect fruit production the subsequent year (R 2  = 0.381, P = 0.057). These results highlight the interacting pattern between frost exposure and vulnerability at different scales and the necessity of intra-organ studies to understand the time course of frost vulnerability in flower buds along the winter. © 2017 John Wiley & Sons Ltd.

Assessing uncertainty in high-resolution spatial climate data across the US Northeast.

PubMed

Bishop, Daniel A; Beier, Colin M

2013-01-01

Local and regional-scale knowledge of climate change is needed to model ecosystem responses, assess vulnerabilities and devise effective adaptation strategies. High-resolution gridded historical climate (GHC) products address this need, but come with multiple sources of uncertainty that are typically not well understood by data users. To better understand this uncertainty in a region with a complex climatology, we conducted a ground-truthing analysis of two 4 km GHC temperature products (PRISM and NRCC) for the US Northeast using 51 Cooperative Network (COOP) weather stations utilized by both GHC products. We estimated GHC prediction error for monthly temperature means and trends (1980-2009) across the US Northeast and evaluated any landscape effects (e.g., elevation, distance from coast) on those prediction errors. Results indicated that station-based prediction errors for the two GHC products were similar in magnitude, but on average, the NRCC product predicted cooler than observed temperature means and trends, while PRISM was cooler for means and warmer for trends. We found no evidence for systematic sources of uncertainty across the US Northeast, although errors were largest at high elevations. Errors in the coarse-scale (4 km) digital elevation models used by each product were correlated with temperature prediction errors, more so for NRCC than PRISM. In summary, uncertainty in spatial climate data has many sources and we recommend that data users develop an understanding of uncertainty at the appropriate scales for their purposes. To this end, we demonstrate a simple method for utilizing weather stations to assess local GHC uncertainty and inform decisions among alternative GHC products.

Amazon rainforest responses to elevated CO2: Deriving model-based hypotheses for the AmazonFACE experiment

NASA Astrophysics Data System (ADS)

Rammig, A.; Fleischer, K.; Lapola, D.; Holm, J.; Hoosbeek, M.

2017-12-01

Increasing atmospheric CO2 concentration is assumed to have a stimulating effect ("CO2 fertilization effect") on forest growth and resilience. Empirical evidence, however, for the existence and strength of such a tropical CO2 fertilization effect is scarce and thus a major impediment for constraining the uncertainties in Earth System Model projections. The implications of the tropical CO2 effect are far-reaching, as it strongly influences the global carbon and water cycle, and hence future global climate. In the scope of the Amazon Free Air CO2 Enrichment (FACE) experiment, we addressed these uncertainties by assessing the CO2 fertilization effect at ecosystem scale. AmazonFACE is the first FACE experiment in an old-growth, highly diverse tropical rainforest. Here, we present a priori model-based hypotheses for the experiment derived from a set of 12 ecosystem models. Model simulations identified key uncertainties in our understanding of limiting processes and derived model-based hypotheses of expected ecosystem responses to elevated CO2 that can directly be tested during the experiment. Ambient model simulations compared satisfactorily with in-situ measurements of ecosystem carbon fluxes, as well as carbon, nitrogen, and phosphorus stocks. Models consistently predicted an increase in photosynthesis with elevated CO2, which declined over time due to developing limitations. The conversion of enhanced photosynthesis into biomass, and hence ecosystem carbon sequestration, varied strongly among the models due to different assumptions on nutrient limitation. Models with flexible allocation schemes consistently predicted an increased investment in belowground structures to alleviate nutrient limitation, in turn accelerating turnover rates of soil organic matter. The models diverged on the prediction for carbon accumulation after 10 years of elevated CO2, mainly due to contrasting assumptions in their phosphorus cycle representation. These differences define the expected response ratio to elevated CO2 at the AmazonFACE site and identify priorities for experimental work and model development.

Health informatics model for helminthiasis in Thailand.

PubMed

Nithikathkul, C; Trevanich, A; Wongsaroj, T; Wongsawad, C; Reungsang, P

2017-09-01

At the beginning of the new millennium, helminth infections continue to be prevalent, particularly among impoverished populations. This study attempts to create the first health informatics model of helminthiasis in Thailand. The authors investigate how a health informatics model could be used to predict the control and eradication in a national control campaign. Fish-borne helminthiasis caused by Opisthorchis viverrini remains a major public health problem in many parts of South-East Asia, including Thailand, Lao PDR, Vietnam and Cambodia. The epicentre of this disease is located in north-east Thailand, where high prevalence coexists with a high incidence of cholangiocarcinoma (CHCA). The current report was conducted to determine a mathematical model of surveillance for helminthiasis while also using a geographic information system. The fish-borne helminthiasis model or the predicted equation was Y1 = 3.028 + 0.020 (elevation) - 2.098 (clay). For soil-transmitted helminthiasis, the mathematical model or the predicted equation was Y2 = -1.559 + 0.005 (rainfall) + 0.004 (elevation) - 2.198 (clay). The Ministry of Public Health has concluded that mass treatment for helminthiasis in the Thai population, targeting high-risk individuals, may be a cost-effective way to allocate limited funds. This type of approach, as well as further study on the correlation of clinical symptoms with environmental and geographic information, may offer a novel strategy to the helminth crisis.

The Glacial BuzzSaw, Isostasy, and Global Crustal Models

NASA Astrophysics Data System (ADS)

Levander, A.; Oncken, O.; Niu, F.

2015-12-01

The glacial buzzsaw hypothesis predicts that maximum elevations in orogens at high latitudes are depressed relative to temperate latitudes, as maximum elevation and hypsography of glaciated orogens are functions of the glacial equilibrium line altitude (ELA) and the modern and last glacial maximum (LGM) snowlines. As a consequence crustal thickness, density, or both must change with increasing latitude to maintain isostatic balance. For Airy compensation crustal thickness should decrease toward polar latitudes, whereas for Pratt compensation crustal densities should increase. For similar convergence rates, higher latitude orogens should have higher grade, and presumably higher density rocks in the crustal column due to more efficient glacial erosion. We have examined a number of global and regional crustal models to see if these predictions appear in the models. Crustal thickness is straightforward to examine, crustal density less so. The different crustal models generally agree with one another, but do show some major differences. We used a standard tectonic classification scheme of the crust for data selection. The globally averaged orogens show crustal thicknesses that decrease toward high latitudes, almost reflecting topography, in both the individual crustal models and the models averaged together. The most convincing is the western hemisphere cordillera, where elevations and crustal thicknesses decrease toward the poles, and also toward lower latitudes (the equatorial minimum is at ~12oN). The elevation differences and Airy prediction of crustal thickness changes are in reasonable agreement in the North American Cordillera, but in South America the observed crustal thickness change is larger than the Airy prediction. The Alpine-Himalayan chain shows similar trends, however the strike of the chain makes interpretation ambiguous. We also examined cratons with ice sheets during the last glacial period to see if continental glaciation also thins the crust toward higher latitudes. The glaciated North American and European cratons show a trend of modest thinning (~3km), and glaciated western Asia minor thinning (~1.5 km). These values are at the level of model uncertainties, but we note that cratons without ice sheets during the last glacial period show substantially different patterns.

Living on the edge: adaptive and plastic responses of the tree Nothofagus pumilio to a long-term transplant experiment predict rear-edge upward expansion.

PubMed

Mathiasen, Paula; Premoli, Andrea C

2016-06-01

Current climate change affects the competitive ability and reproductive success of many species, leading to local extinctions, adjustment to novel local conditions by phenotypic plasticity or rapid adaptation, or tracking their optima through range shifts. However, many species have limited ability to expand to suitable areas. Altitudinal gradients, with abrupt changes in abiotic conditions over short distances, represent "natural experiments" for the evaluation of ecological and evolutionary responses under scenarios of climate change. Nothofagus pumilio is the tree species which dominates as pure stands the montane forests of Patagonia. We evaluated the adaptive value of variation in quantitative traits of N. pumilio under contrasting conditions of the altitudinal gradient with a long-term reciprocal transplant experimental design. While high-elevation plants show little response in plant, leaf, and phenological traits to the experimental trials, low-elevation ones show greater plasticity in their responses to changing environments, particularly at high elevation. Our results suggest a relatively reduced potential for evolutionary adaptation of high-elevation genotypes, and a greater evolutionary potential of low-elevation ones. Under global warming scenarios of forest upslope migration, high-elevation variants may be outperformed by low-elevation ones during this process, leading to the local extinction and/or replacement of these genotypes. These results challenge previous models and predictions expected under global warming for altitudinal gradients, on which the leading edge is considered to be the upper treeline forests.

A Methylmercury Prediction Too For Surface Waters Across The Contiguous United States (Invited)

NASA Astrophysics Data System (ADS)

Krabbenhoft, D. P.; Booth, N.; Lutz, M.; Fienen, M. N.; Saltman, T.

2009-12-01

About 20 years ago, researchers at a few locations across the globe discovered high levels of mercury in fish from remote settings lacking any obvious mercury source. We now know that for most locations atmospheric deposition is the dominant mercury source, and that mercury methylation is the key process that translates low mercury loading rates into relatively high levels in top predators of aquatic food webs. Presently, almost all US states have advisories for elevated levels of mercury in sport fish, and as a result there is considerable public awareness and concern for this nearly ubiquitous contaminant issue. In some states, “statewide” advisories have been issued because elevated fish mercury levels are so common, or the state has no effective way to monitor thousands of lakes, reservoirs, wetlands, and streams. As such, resource managers and public health officials have limited options for informing the public on of where elevated mercury concentrations in sport fish are more likely to occur than others. This project provides, for the first time, a national map of predicted (modeled) methylmercury concentrations in surface waters, which is the most toxic and bioaccumulative form of mercury in the environment. The map is the result of over two decades of research that resulted in the formulation of conceptual models of the mercury methylation process, which is strongly governed by environmental conditions - specifically hydrologic landscapes and water quality. The resulting predictive map shows clear regional trends in the distribution of methylmercury concentrations in surface waters. East of the Mississippi, the Gulf and southeastern Atlantic coast, the northeast, the lower Mississippi valley, and Great Lakes area are predicted to have generally higher environmental methylmercury levels. Higher-elevation, well-drained areas of Appalachia are predicted to have relatively lower methylmercury abundance. Other than the prairie pothole region, in the western US incessant regional patterns are less clear. However, the full range of predicted methylmercury levels are predicted to occur in western US watersheds. Lastly, although this map is being presented at the continental US scale, the principles used to generate the modeled results can easily applied to data sets that represent a range of geographic scales.

Development and evaluation of a reservoir model for the Chain of Lakes in Illinois

USGS Publications Warehouse

Domanski, Marian M.

2017-01-27

Forecasts of flows entering and leaving the Chain of Lakes reservoir on the Fox River in northeastern Illinois are critical information to water-resource managers who determine the optimal operation of the dam at McHenry, Illinois, to help minimize damages to property and loss of life because of flooding on the Fox River. In 2014, the U.S. Geological Survey; the Illinois Department of Natural Resources, Office of Water Resources; and National Weather Service, North Central River Forecast Center began a cooperative study to develop a system to enable engineers and planners to simulate and communicate flows and to prepare proactively for precipitation events in near real time in the upper Fox River watershed. The purpose of this report is to document the development and evaluation of the Chain of Lakes reservoir model developed in this study.The reservoir model for the Chain of Lakes was developed using the Hydrologic Engineering Center–Reservoir System Simulation program. Because of the complex relation between the dam headwater and reservoir pool elevations, the reservoir model uses a linear regression model that relates dam headwater elevation to reservoir pool elevation. The linear regression model was developed using 17 U.S. Geological Survey streamflow measurements, along with the gage height in the reservoir pool and the gage height at the dam headwater. The Nash-Sutcliffe model efficiency coefficients for all three linear regression model variables ranged from 0.90 to 0.98.The reservoir model performance was evaluated by graphically comparing simulated and observed reservoir pool elevation time series during nine periods of high pool elevation. In addition, the peak elevations during these time periods were graphically compared to the closest-in-time observed pool elevation peak. The mean difference in the simulated and observed peak elevations was -0.03 feet, with a standard deviation of 0.19 feet. The Nash-Sutcliffe coefficient for peak prediction was calculated as 0.94. Evaluation of the model based on accuracy of peak prediction and the ability to simulate an elevation time series showed the performance of the model was satisfactory.

Evaluating the sensitivity of an ice sheet model to changes in bed elevation and inclusion of membrane stresses

NASA Astrophysics Data System (ADS)

Aschwanden, Andy; Bueler, Ed; Khroulev, Constantine

2010-05-01

To predict Greenland's contribution to global sea level rise in the next few centuries with some confidence, an accurate representation of its current state is crucial. Simulations of the present state of Greenland using the "Parallel Ice Sheet Model" (PISM) capture the essential flow features but overestimate the current volume by about 30%. Possible sources of error include (1) limited understanding of physical processes involved, (2) the choice of approximations made by the numerical model, (3) values of tunable parameters, and (4) uncertainties in boundary conditions. The response of an ice sheet model to given forcing contains the above mentioned error sources, with unknown weights. In this work we focus on a small subset, namely errors arising from uncertainties in bed elevation and whether or not membrane stresses are included in the stress balance. CReSIS provides recently updated bedrock maps for Greenland include high-resolution data for Jacobshavn Isbræ and Petermann Glacier. We present a four-way comparison between the original BEDMAP, the new CReSIS bedrock data, a non-sliding shallow ice model, and hybrid model which includes the shallow shelf approximation as a sliding law. Large gradients possibly found in high-resolution bedrock elevation are expected to make a hybrid model the more appropriate choice. To elucidate this question, runs are performed on a unprecedented high spatial resolution of 2km for the whole ice sheet. Finally, model predictions are evaluated against observed quantities such as surface velocities, ice thickness, and temperature profiles in bore holes using different metrics.

Application of nonlinear deterministic decomposition to the prediction and energy dissipation of long-crested irregular ocean surface waves

NASA Astrophysics Data System (ADS)

Meza Conde, Eustorgio

The Hybrid Wave Model (HWM) is a deterministic nonlinear wave model developed for the computation of wave properties in the vicinity of ocean wave measurements. The HWM employs both Mode-Coupling and Phase Modulation Methods to model the wave-wave interactions in an ocean wave field. Different from other nonlinear wave models, the HWM decouples the nonlinear wave interactions from ocean wave field measurements and decomposes the wave field into a set of free-wave components. In this dissertation the HWM is applied to the prediction of wave elevation from pressure measurements and to the quantification of energy during breaking of long-crested irregular surface waves. 1.A transient wave train was formed in a two-dimensional wave flume by sequentially generating a series of waves from high to low frequencies that superposed at a downstream location. The predicted wave elevation using the HWM based on the pressure measurement of a very steep transient wave train is in excellent agreement with the corresponding elevation measurement, while that using Linear Wave Theory (LWT) has relatively large discrepancies. Furthermore, the predicted elevation using the HWM is not sensitive to the choice of the cutoff frequency, while that using LWT is very sensitive. 2.Several transient wave trains containing an isolated plunging or spilling breaker at a prescribed location were generated in a two-dimensional wave flume using the same superposition technique. Surface elevation measurements of each transient wave train were made at locations before and after breaking. Applying the HWM nonlinear deterministic decomposition to the measured elevation, the free-wave components comprising the transient wave train were derived. By comparing the free-wave spectra before and after breaking it is found that energy loss was almost exclusively from wave components at frequencies higher than the spectral peak frequency. Even though the wave components near the peak frequency are the largest, they do not significantly gain or lose energy after breaking. It was also observed that wave components of frequencies significantly below or near the peak frequency gain a small portion of energy lost by the high-frequency waves. These findings may have important implications to the ocean wave energy budget.

Forest restoration as a strategy to mitigate climate impacts on wildfire, vegetation, and water in semiarid forests.

PubMed

O'Donnell, Frances C; Flatley, William T; Springer, Abraham E; Fulé, Peter Z

2018-06-25

Climate change and wildfire are interacting to drive vegetation change and potentially reduce water quantity and quality in the southwestern United States, Forest restoration is a management approach that could mitigate some of these negative outcomes. However, little information exists on how restoration combined with climate change might influence hydrology across large forest landscapes that incorporate multiple vegetation types and complex fire regimes. We combined spatially explicit vegetation and fire modeling with statistical water and sediment yield models for a large forested landscape (335,000 ha) on the Kaibab Plateau in northern Arizona, USA. Our objective was to assess the impacts of climate change and forest restoration on the future fire regime, forest vegetation, and watershed outputs. Our model results predict that the combination of climate change and high-severity fire will drive forest turnover, biomass declines, and compositional change in future forests. Restoration treatments may reduce the area burned in high-severity fires and reduce conversions from forested to non-forested conditions. Even though mid-elevation forests are the targets of restoration, the treatments are expected to delay the decline of high-elevation spruce-fir, aspen, and mixed conifer forests by reducing the occurrence of high-severity fires that may spread across ecoregions. We estimate that climate-induced vegetation changes will result in annual runoff declines of up to 10%, while restoration reduced or reversed this decline. The hydrologic model suggests that mid-elevation forests, which are the targets of restoration treatments, provide around 80% of runoff in this system and the conservation of mid- to high-elevation forests types provides the greatest benefit in terms of water conservation. We also predict that restoration treatments will conserve water quality by reducing patches of high-severity fire that are associated with high sediment yield. Restoration treatments are a management strategy that may reduce undesirable outcomes for multiple ecosystem services. © 2018 by the Ecological Society of America.

A GIS model predicting potential distributions of a lineage: a test case on hermit spiders (Nephilidae: Nephilengys).

PubMed

Năpăruş, Magdalena; Kuntner, Matjaž

2012-01-01

Although numerous studies model species distributions, these models are almost exclusively on single species, while studies of evolutionary lineages are preferred as they by definition study closely related species with shared history and ecology. Hermit spiders, genus Nephilengys, represent an ecologically important but relatively species-poor lineage with a globally allopatric distribution. Here, we model Nephilengys global habitat suitability based on known localities and four ecological parameters. We geo-referenced 751 localities for the four most studied Nephilengys species: N. cruentata (Africa, New World), N. livida (Madagascar), N. malabarensis (S-SE Asia), and N. papuana (Australasia). For each locality we overlaid four ecological parameters: elevation, annual mean temperature, annual mean precipitation, and land cover. We used linear backward regression within ArcGIS to select two best fit parameters per species model, and ModelBuilder to map areas of high, moderate and low habitat suitability for each species within its directional distribution. For Nephilengys cruentata suitable habitats are mid elevation tropics within Africa (natural range), a large part of Brazil and the Guianas (area of synanthropic spread), and even North Africa, Mediterranean, and Arabia. Nephilengys livida is confined to its known range with suitable habitats being mid-elevation natural and cultivated lands. Nephilengys malabarensis, however, ranges across the Equator throughout Asia where the model predicts many areas of high ecological suitability in the wet tropics. Its directional distribution suggests the species may potentially spread eastwards to New Guinea where the suitable areas of N. malabarensis largely surpass those of the native N. papuana, a species that prefers dry forests of Australian (sub)tropics. Our model is a customizable GIS tool intended to predict current and future potential distributions of globally distributed terrestrial lineages. Its predictive potential may be tested in foreseeing species distribution shifts due to habitat destruction and global climate change.

A GIS Model Predicting Potential Distributions of a Lineage: A Test Case on Hermit Spiders (Nephilidae: Nephilengys)

PubMed Central

Năpăruş, Magdalena; Kuntner, Matjaž

2012-01-01

Background Although numerous studies model species distributions, these models are almost exclusively on single species, while studies of evolutionary lineages are preferred as they by definition study closely related species with shared history and ecology. Hermit spiders, genus Nephilengys, represent an ecologically important but relatively species-poor lineage with a globally allopatric distribution. Here, we model Nephilengys global habitat suitability based on known localities and four ecological parameters. Methodology/Principal Findings We geo-referenced 751 localities for the four most studied Nephilengys species: N. cruentata (Africa, New World), N. livida (Madagascar), N. malabarensis (S-SE Asia), and N. papuana (Australasia). For each locality we overlaid four ecological parameters: elevation, annual mean temperature, annual mean precipitation, and land cover. We used linear backward regression within ArcGIS to select two best fit parameters per species model, and ModelBuilder to map areas of high, moderate and low habitat suitability for each species within its directional distribution. For Nephilengys cruentata suitable habitats are mid elevation tropics within Africa (natural range), a large part of Brazil and the Guianas (area of synanthropic spread), and even North Africa, Mediterranean, and Arabia. Nephilengys livida is confined to its known range with suitable habitats being mid-elevation natural and cultivated lands. Nephilengys malabarensis, however, ranges across the Equator throughout Asia where the model predicts many areas of high ecological suitability in the wet tropics. Its directional distribution suggests the species may potentially spread eastwards to New Guinea where the suitable areas of N. malabarensis largely surpass those of the native N. papuana, a species that prefers dry forests of Australian (sub)tropics. Conclusions Our model is a customizable GIS tool intended to predict current and future potential distributions of globally distributed terrestrial lineages. Its predictive potential may be tested in foreseeing species distribution shifts due to habitat destruction and global climate change. PMID:22238692

Growth in elevated CO(2) can both increase and decrease photochemistry and photoinhibition of photosynthesis in a predictable manner. Dactylis glomerata grown in two levels of nitrogen nutrition.

PubMed

Hymus, G J; Baker, N R; Long, S P

2001-11-01

Biochemically based models of C(3) photosynthesis can be used to predict that when photosynthesis is limited by the amount of Rubisco, increasing atmospheric CO(2) partial pressure (pCO(2)) will increase light-saturated linear electron flow through photosystem II (J(t)). This is because the stimulation of electron flow to the photosynthetic carbon reduction cycle (J(c)) will be greater than the competitive suppression of electron flow to the photorespiratory carbon oxidation cycle (J(o)). Where elevated pCO(2) increases J(t), then the ratio of absorbed energy dissipated photochemically to that dissipated non-photochemically will rise. These predictions were tested on Dactylis glomerata grown in fully controlled environments, at either ambient (35 Pa) or elevated (65 Pa) pCO(2), and at two levels of nitrogen nutrition. As was predicted, for D. glomerata grown in high nitrogen, J(t) was significantly higher in plants grown and measured at elevated pCO(2) than for plants grown and measured at ambient pCO(2). This was due to a significant increase in J(c) exceeding any suppression of J(o). This increase in photochemistry at elevated pCO(2) protected against photoinhibition at high light. For plants grown at low nitrogen, J(t) was significantly lower in plants grown and measured at elevated pCO(2) than for plants grown and measured at ambient pCO(2). Elevated pCO(2) again suppressed J(o); however growth in elevated pCO(2) resulted in an acclimatory decrease in leaf Rubisco content that removed any stimulation of J(c). Consistent with decreased photochemistry, for leaves grown at low nitrogen, the recovery from a 3-h photoinhibitory treatment was slower at elevated pCO(2).

Cross-scale assessment of potential habitat shifts in a rapidly changing climate

USGS Publications Warehouse

Jarnevich, Catherine S.; Holcombe, Tracy R.; Bella, Elizabeth S.; Carlson, Matthew L.; Graziano, Gino; Lamb, Melinda; Seefeldt, Steven S.; Morisette, Jeffrey T.

2014-01-01

We assessed the ability of climatic, environmental, and anthropogenic variables to predict areas of high-risk for plant invasion and consider the relative importance and contribution of these predictor variables by considering two spatial scales in a region of rapidly changing climate. We created predictive distribution models, using Maxent, for three highly invasive plant species (Canada thistle, white sweetclover, and reed canarygrass) in Alaska at both a regional scale and a local scale. Regional scale models encompassed southern coastal Alaska and were developed from topographic and climatic data at a 2 km (1.2 mi) spatial resolution. Models were applied to future climate (2030). Local scale models were spatially nested within the regional area; these models incorporated physiographic and anthropogenic variables at a 30 m (98.4 ft) resolution. Regional and local models performed well (AUC values > 0.7), with the exception of one species at each spatial scale. Regional models predict an increase in area of suitable habitat for all species by 2030 with a general shift to higher elevation areas; however, the distribution of each species was driven by different climate and topographical variables. In contrast local models indicate that distance to right-of-ways and elevation are associated with habitat suitability for all three species at this spatial level. Combining results from regional models, capturing long-term distribution, and local models, capturing near-term establishment and distribution, offers a new and effective tool for highlighting at-risk areas and provides insight on how variables acting at different scales contribute to suitability predictions. The combinations also provides easy comparison, highlighting agreement between the two scales, where long-term distribution factors predict suitability while near-term do not and vice versa.

Three Gorges Dam: Impact of Water Level Changes on the Density of Schistosome-Transmitting Snail Oncomelania hupensis in Dongting Lake Area, China

PubMed Central

Wu, Jin-Yi; Zhou, Yi-Biao; Chen, Yue; Liang, Song; Li, Lin-Han; Zheng, Sheng-Bang; Zhu, Shao-ping; Ren, Guang-Hui; Song, Xiu-Xia; Jiang, Qing-Wu

2015-01-01

Background Schistosomiasis remains an important public health issue in China and worldwide. Oncomelania hupensis is the unique intermediate host of schistosoma japonicum, and its change influences the distribution of S. japonica. The Three Gorges Dam (TGD) has substantially changed the ecology and environment in the Dongting Lake region. This study investigated the impact of water level and elevation on the survival and habitat of the snails. Methods Data were collected for 16 bottomlands around 4 hydrological stations, which included water, density of living snails (form the Anxiang Station for Schistosomiasis Control) and elevation (from Google Earth). Based on the elevation, sixteen bottomlands were divided into 3 groups. ARIMA models were built to predict the density of living snails in different elevation areas. Results Before closure of TGD, 7 out of 9 years had a water level beyond the warning level at least once at Anxiang hydrological station, compared with only 3 out of 10 years after closure of TGD. There were two severe droughts that happened in 2006 and 2011, with much fewer number of flooding per year compared with other study years. Overall, there was a correlation between water level changing and density of living snails variation in all the elevations areas. The density of living snails in all elevations areas was decreasing after the TGD was built. The relationship between number of flooding per year and the density of living snails was more pronounced in the medium and high elevation areas; the density of living snails kept decreasing from 2003 to 2014. In low elevation area however, the density of living snails decreased after 2003 first and turned to increase after 2011. Our ARIMA prediction models indicated that the snails would not disappear in the Dongting Lake region in the next 7 years. In the low elevation area, the density of living snails would increase slightly, and then stabilize after the year 2017. In the medium elevation region, the change of the density of living snails would be more obvious and would increase till the year 2020. In the high elevation area, the density of living snails would remain stable after the year 2015. Conclusion The TGD influenced water levels and reduced the risk of flooding and the density of living snails in the study region. Based on our prediction models, the density of living snails in all elevations tends to be stabilized. Control of S. japonica would continue to be an important task in the study area in the coming decade. PMID:26114956

A Modified Johnson-Cook Model for Sheet Metal Forming at Elevated Temperatures and Its Application for Cooled Stress-Strain Curve and Spring-Back Prediction

NASA Astrophysics Data System (ADS)

Duc-Toan, Nguyen; Tien-Long, Banh; Young-Suk, Kim; Dong-Won, Jung

2011-08-01

In this study, a modified Johnson-Cook (J-C) model and an innovated method to determine (J-C) material parameters are proposed to predict more correctly stress-strain curve for tensile tests in elevated temperatures. A MATLAB tool is used to determine material parameters by fitting a curve to follow Ludwick's hardening law at various elevated temperatures. Those hardening law parameters are then utilized to determine modified (J-C) model material parameters. The modified (J-C) model shows the better prediction compared to the conventional one. As the first verification, an FEM tensile test simulation based on the isotropic hardening model for boron sheet steel at elevated temperatures was carried out via a user-material subroutine, using an explicit finite element code, and compared with the measurements. The temperature decrease of all elements due to the air cooling process was then calculated when considering the modified (J-C) model and coded to VUMAT subroutine for tensile test simulation of cooling process. The modified (J-C) model showed the good agreement between the simulation results and the corresponding experiments. The second investigation was applied for V-bending spring-back prediction of magnesium alloy sheets at elevated temperatures. Here, the combination of proposed J-C model with modified hardening law considering the unusual plastic behaviour for magnesium alloy sheet was adopted for FEM simulation of V-bending spring-back prediction and shown the good comparability with corresponding experiments.

Higher risk of gastrointestinal parasite infection at lower elevation suggests possible constraints in the distributional niche of Alpine marmots.

PubMed

Zanet, Stefania; Miglio, Giacomo; Ferrari, Caterina; Bassano, Bruno; Ferroglio, Ezio; von Hardenberg, Achaz

2017-01-01

Alpine marmots Marmota marmota occupy a narrow altitudinal niche within high elevation alpine environments. For animals living at such high elevations where resources are limited, parasitism represents a potential major cost in life history. Using occupancy models, we tested if marmots living at higher elevation have a reduced risk of being infected with gastro-intestinal helminths, possibly compensating the lower availability of resources (shorter feeding season, longer snow cover and lower temperature) than marmots inhabiting lower elevations. Detection probability of eggs and oncospheres of two gastro-intestinal helminthic parasites, Ascaris laevis and Ctenotaenia marmotae, sampled in marmot feces, was used as a proxy of parasite abundance. As predicted, the models showed a negative relationship between elevation and parasite detectability (i.e. abundance) for both species, while there appeared to be a negative effect of solar radiance only for C. marmotae. Site-occupancy models are used here for the first time to model the constrains of gastrointestinal parasitism on a wild species and the relationship existing between endoparasites and environmental factors in a population of free-living animals. The results of this study suggest the future use of site-occupancy models as a viable tool to account for parasite imperfect detection in eco-parasitological studies, and give useful insights to further investigate the hypothesis of the contribution of parasite infection in constraining the altitudinal niche of Alpine marmots.

Evapotranspiration sensitivity to air temperature across a snow-influenced watershed: Space-for-time substitution versus integrated watershed modeling

NASA Astrophysics Data System (ADS)

Jepsen, S. M.; Harmon, T. C.; Ficklin, D. L.; Molotch, N. P.; Guan, B.

2018-01-01

Changes in long-term, montane actual evapotranspiration (ET) in response to climate change could impact future water supplies and forest species composition. For scenarios of atmospheric warming, predicted changes in long-term ET tend to differ between studies using space-for-time substitution (STS) models and integrated watershed models, and the influence of spatially varying factors on these differences is unclear. To examine this, we compared warming-induced (+2 to +6 °C) changes in ET simulated by an STS model and an integrated watershed model across zones of elevation, substrate available water capacity, and slope in the snow-influenced upper San Joaquin River watershed, Sierra Nevada, USA. We used the Soil Water and Assessment Tool (SWAT) for the watershed modeling and a Budyko-type relationship for the STS modeling. Spatially averaged increases in ET from the STS model increasingly surpassed those from the SWAT model in the higher elevation zones of the watershed, resulting in 2.3-2.6 times greater values from the STS model at the watershed scale. In sparse, deep colluvium or glacial soils on gentle slopes, the SWAT model produced ET increases exceeding those from the STS model. However, watershed areas associated with these conditions were too localized for SWAT to produce spatially averaged ET-gains comparable to the STS model. The SWAT model results nevertheless demonstrate that such soils on high-elevation, gentle slopes will form ET "hot spots" exhibiting disproportionately large increases in ET, and concomitant reductions in runoff yield, in response to warming. Predicted ET responses to warming from STS models and integrated watershed models may, in general, substantially differ (e.g., factor of 2-3) for snow-influenced watersheds exhibiting an elevational gradient in substrate water holding capacity and slope. Long-term water supplies in these settings may therefore be more resilient to warming than STS model predictions would suggest.

Late Pleistocene temperature, hydrology, and glaciation in equatorial East Africa

NASA Astrophysics Data System (ADS)

Russell, J. M.; Verschuren, D.; Kelly, M. A.; Loomis, S. E.; Jackson, M. S.; Morrill, C.; S Sinninghe Damsté, J.; Doughty, A. M.; De Cort, G.; Olago, D.; Street-Perrott, F. A.

2016-12-01

In the coming century the world's high tropical mountains are predicted to experience a magnitude of climate change second only to the Arctic due to amplification of warming with elevation in the tropics. Proxy data suggest that substantial changes in tropical temperature and hydroclimate also occurred during the last deglaciation, the most recent time period when rising atmospheric CO2 concentrations caused large changes in global climate. Determining whether the rate of temperature change with elevation (the lapse rate) was different from today during the Last Glacial Maximum (LGM) is therefore critical to understanding the future of tropical mountain environments and resources. Here we present a new 25,000-year temperature reconstruction based upon organic geochemical analyses of sediment cores from Lake Rutundu (3,078 m asl), Mount Kenya, East Africa. Through comparison with regional reconstructions of lower elevation temperature, we show that LGM cooling was amplified with elevation and hence that the lapse rate was significantly steeper than today. Comparison of our lapse rate reconstructions with equilibrium line altitude reconstructions from glacial moraines indicates that temperature, rather than precipitation, was the dominant control on tropical alpine glacier fluctuations at this time scale. Nevertheless, our results have important implications for the tropical hydrological cycle, as changes in the lapse rate are intimately linked with changes in atmospheric water vapour concentrations. Indeed, we attribute the steeper lapse rate to drying of the tropical ice-age atmosphere, a hypothesis supported by palaeoclimate models. However, comparison of our data to these simulations indicates that state-of-the-art models significantly underestimate tropical temperature changes at high elevation and therefore the lapse-rate change. Consequently, future high-elevation tropical warming may be even greater than currently predicted.

A four-kallikrein panel for the prediction of repeat prostate biopsy: data from the European Randomized Study of Prostate Cancer screening in Rotterdam, Netherlands.

PubMed

Gupta, A; Roobol, M J; Savage, C J; Peltola, M; Pettersson, K; Scardino, P T; Vickers, A J; Schröder, F H; Lilja, H

2010-08-24

Most men with elevated levels of prostate-specific antigen (PSA) do not have prostate cancer, leading to a large number of unnecessary biopsies. A statistical model based on a panel of four kallikreins has been shown to predict the outcome of a first prostate biopsy. In this study, we apply the model to an independent data set of men with previous negative biopsy but persistently elevated PSA. The study cohort consisted of 925 men with a previous negative prostate biopsy and elevated PSA (>or=3 ng ml(-1)), with 110 prostate cancers detected (12%). A previously published statistical model was applied, with recalibration to reflect the lower positive biopsy rates on rebiopsy. The full-kallikrein panel had higher discriminative accuracy than PSA and DRE alone, with area under the curve (AUC) improving from 0.58 (95% confidence interval (CI): 0.52, 0.64) to 0.68 (95% CI: 0.62, 0.74), P<0.001, and high-grade cancer (Gleason >or=7) at biopsy with AUC improving from 0.76 (95% CI: 0.64, 0.89) to 0.87 (95% CI: 0.81, 0.94), P=0.003). Application of the panel to 1000 men with persistently elevated PSA after initial negative biopsy, at a 15% risk threshold would reduce the number of biopsies by 712; would miss (or delay) the diagnosis of 53 cancers, of which only 3 would be Gleason 7 and the rest Gleason 6 or less. Our data constitute an external validation of a previously published model. The four-kallikrein panel predicts the result of repeat prostate biopsy in men with elevated PSA while dramatically decreasing unnecessary biopsies.

Isothermal Fatigue, Damage Accumulation, and Life Prediction of a Woven PMC

NASA Technical Reports Server (NTRS)

Gyekenyesi, Andrew L.

1998-01-01

This dissertation focuses on the characterization of the fully reversed fatigue behavior exhibited by a carbon fiber/polyimide resin, woven laminate at room and elevated temperatures. Nondestructive video edge view microscopy and destructive sectioning techniques were used to study the microscopic damage mechanisms that evolved. The residual elastic stiffness was monitored and recorded throughout the fatigue life of the coupon. In addition, residual compressive strength tests were conducted on fatigue coupons with various degrees of damage as quantified by stiffness reduction. Experimental results indicated that the monotonic tensile properties were only minimally influenced by temperature, while the monotonic compressive and fully reversed fatigue properties displayed noticeable reductions due to the elevated temperature. The stiffness degradation, as a function of cycles, consisted of three stages; a short-lived high degradation period, a constant degradation rate segment composing the majority of the life, and a final stage demonstrating an increasing rate of degradation up to failure. Concerning the residual compressive strength tests at room and elevated temperatures, the elevated temperature coupons appeared much more sensitive to damage. At elevated temperatures, coupons experienced a much larger loss in compressive strength when compared to room temperature coupons with equivalent damage. The fatigue damage accumulation law proposed for the model incorporates a scalar representation for damage, but admits a multiaxial, anisotropic evolutionary law. The model predicts the current damage (as quantified by residual stiffness) and remnant life of a composite that has undergone a known load at temperature. The damage/life model is dependent on the applied multiaxial stress state as well as temperature. Comparisons between the model and data showed good predictive capabilities concerning stiffness degradation and cycles to failure.

Mass tree mortality leads to mangrove peat collapse at Bay Islands, Honduras after Hurricane Mitch

USGS Publications Warehouse

Cahoon, D.R.; Hensel, P.; Rybczyk, J.; McKee, K.L.; Proffitt, C.E.; Perez, B.C.

2003-01-01

We measured sediment elevation and accretion dynamics in mangrove forests on the islands of Guanaja and Roatan, Honduras, impacted by Hurricane Mitch in 1998 to determine if collapse of underlying peat was occurring as a result of mass tree mortality. Little is known about the balance between production and decomposition of soil organic matter in the maintenance of sediment elevation of mangrove forests with biogenic soils. Sediment elevation change measured with the rod surface elevation table from 18 months to 33 months after the storm differed significantly among low, medium and high wind impact sites. Mangrove forests suffering minimal to partial mortality gained elevation at a rate (5 mm yeara??1) greater than vertical accretion (2 mm yeara??1) measured from artificial soil marker horizons, suggesting that root production contributed to sediment elevation. Basin forests that suffered mass tree mortality experienced peat collapse of about 11 mm yeara??1 as a result of decomposition of dead root material and sediment compaction. Low soil shear strength and lack of root growth accompanied elevation decreases. Model simulations using the Relative Elevation Model indicate that peat collapse in the high impact basin mangrove forest would be 37 mm yeara??1 for the 2 years immediately after the storm, as root material decomposed. In the absence of renewed root growth, the model predicts that peat collapse will continue for at least 8 more years at a rate (7 mm yeara??1) similar to that measured (11 mm yeara??1). Mass tree mortality caused rapid elevation loss. Few trees survived and recovery of the high impact forest will thus depend primarily on seedling recruitment. Because seedling establishment is controlled in large part by sediment elevation in relation to tide height, continued peat collapse could further impair recovery rates.

Vegetation cover, tidal amplitude and land area predict short-term marsh vulnerability in Coastal Louisiana

USGS Publications Warehouse

Schoolmaster, Donald; Stagg, Camille L.; Sharp, Leigh Anne; McGinnis, Tommy S.; Wood, Bernard; Piazza, Sarai

2018-01-01

The loss of coastal marshes is a topic of great concern, because these habitats provide tangible ecosystem services and are at risk from sea-level rise and human activities. In recent years, significant effort has gone into understanding and modeling the relationships between the biological and physical factors that contribute to marsh stability. Simulation-based process models suggest that marsh stability is the product of a complex feedback between sediment supply, flooding regime and vegetation response, resulting in elevation gains sufficient to match the combination of relative sea-level rise and losses from erosion. However, there have been few direct, empirical tests of these models, because long-term datasets that have captured sufficient numbers of marsh loss events in the context of a rigorous monitoring program are rare. We use a multi-year data set collected by the Coastwide Reference Monitoring System (CRMS) that includes transitions of monitored vegetation plots to open water to build and test a predictive model of near-term marsh vulnerability. We found that despite the conclusions of previous process models, elevation change had no ability to predict the transition of vegetated marsh to open water. However, we found that the processes that drive elevation change were significant predictors of transitions. Specifically, vegetation cover in prior year, land area in the surrounding 1 km2 (an estimate of marsh fragmentation), and the interaction of tidal amplitude and position in tidal frame were all significant factors predicting marsh loss. This suggests that 1) elevation change is likely better a predictor of marsh loss at time scales longer than we consider in this study and 2) the significant predictive factors affect marsh vulnerability through pathways other than elevation change, such as resistance to erosion. In addition, we found that, while sensitivity of marsh vulnerability to the predictive factors varied spatially across coastal Louisiana, vegetation cover in prior year was the best single predictor of subsequent loss in most sites followed by changes in percent land and tidal amplitude. The model’s predicted land loss rates correlated well with land loss rates derived from satellite data, although agreement was spatially variable. These results indicate 1) monitoring the loss of small scale vegetation plots can inform patterns of land loss at larger scales 2) the drivers of land loss vary spatially across coastal Louisiana, and 3) relatively simple models have potential as highly informative tools for bioassessment, directing future research, and management planning.

Moving on from rigid plant stoichiometry: Optimal canopy nitrogen allocation within a novel land surface model

NASA Astrophysics Data System (ADS)

Caldararu, S.; Kern, M.; Engel, J.; Zaehle, S.

2016-12-01

Despite recent advances in global vegetation models, we still lack the capacity to predict observed vegetation responses to experimental environmental changes such as elevated CO2, increased temperature or nutrient additions. In particular for elevated CO2 (FACE) experiments, studies have shown that this is related in part to the models' inability to represent plastic changes in nutrient use and biomass allocation. We present a newly developed vegetation model which aims to overcome these problems by including optimality processes to describe nitrogen (N) and carbon allocation within the plant. We represent nitrogen allocation to the canopy and within the canopy between photosynthetic components as an optimal processes which aims to maximize net primary production (NPP) of the plant. We also represent biomass investment into aboveground and belowground components (root nitrogen uptake , biological N fixation) as an optimal process that maximizes plant growth by considering plant carbon and nutrient demands as well as acquisition costs. The model can now represent plastic changes in canopy N content and chlorophyll and Rubisco concentrations as well as in belowground allocation both on seasonal and inter-annual time scales. Specifically, we show that under elevated CO2 conditions, the model predicts a lower optimal leaf N concentration, which, combined with a redistribution of leaf N between the Rubisco and chlorophyll components, leads to a continued NPP response under high CO2, where models with a fixed canopy stoichiometry would predicts a quick onset of N limitation. In general, our model aims to include physiologically-based plant processes and avoid arbitrarily imposed parameters and thresholds in order to improve our predictive capability of vegetation responses under changing environmental conditions.

Pretreatment data is highly predictive of liver chemistry signals in clinical trials.

PubMed

Cai, Zhaohui; Bresell, Anders; Steinberg, Mark H; Silberg, Debra G; Furlong, Stephen T

2012-01-01

The goal of this retrospective analysis was to assess how well predictive models could determine which patients would develop liver chemistry signals during clinical trials based on their pretreatment (baseline) information. Based on data from 24 late-stage clinical trials, classification models were developed to predict liver chemistry outcomes using baseline information, which included demographics, medical history, concomitant medications, and baseline laboratory results. Predictive models using baseline data predicted which patients would develop liver signals during the trials with average validation accuracy around 80%. Baseline levels of individual liver chemistry tests were most important for predicting their own elevations during the trials. High bilirubin levels at baseline were not uncommon and were associated with a high risk of developing biochemical Hy's law cases. Baseline γ-glutamyltransferase (GGT) level appeared to have some predictive value, but did not increase predictability beyond using established liver chemistry tests. It is possible to predict which patients are at a higher risk of developing liver chemistry signals using pretreatment (baseline) data. Derived knowledge from such predictions may allow proactive and targeted risk management, and the type of analysis described here could help determine whether new biomarkers offer improved performance over established ones.

Linking occupancy surveys with habitat characteristics to estimate abundance and distribution in an endangered cryptic bird

USGS Publications Warehouse

Crampton, Lisa H.; Brinck, Kevin W.; Pias, Kyle E.; Heindl, Barbara A. P.; Savre, Thomas; Diegmann, Julia S.; Paxton, Eben H.

2017-01-01

Accurate estimates of the distribution and abundance of endangered species are crucial to determine their status and plan recovery options, but such estimates are often difficult to obtain for species with low detection probabilities or that occur in inaccessible habitats. The Puaiohi (Myadestes palmeri) is a cryptic species endemic to Kauaʻi, Hawai‘i, and restricted to high elevation ravines that are largely inaccessible. To improve current population estimates, we developed an approach to model distribution and abundance of Puaiohi across their range by linking occupancy surveys to habitat characteristics, territory density, and landscape attributes. Occupancy per station ranged from 0.17 to 0.82, and was best predicted by the number and vertical extent of cliffs, cliff slope, stream width, and elevation. To link occupancy estimates with abundance, we used territory mapping data to estimate the average number of territories per survey station (0.44 and 0.66 territories per station in low and high occupancy streams, respectively), and the average number of individuals per territory (1.9). We then modeled Puaiohi occupancy as a function of two remote-sensed measures of habitat (stream sinuosity and elevation) to predict occupancy across its entire range. We combined predicted occupancy with estimates of birds per station to produce a global population estimate of 494 (95% CI 414–580) individuals. Our approach is a model for using multiple independent sources of information to accurately track population trends, and we discuss future directions for modeling abundance of this, and other, rare species.

Assessing model sensitivity and uncertainty across multiple Free-Air CO2 Enrichment experiments.

NASA Astrophysics Data System (ADS)

Cowdery, E.; Dietze, M.

2015-12-01

As atmospheric levels of carbon dioxide levels continue to increase, it is critical that terrestrial ecosystem models can accurately predict ecological responses to the changing environment. Current predictions of net primary productivity (NPP) in response to elevated atmospheric CO2 concentrations are highly variable and contain a considerable amount of uncertainty. It is necessary that we understand which factors are driving this uncertainty. The Free-Air CO2 Enrichment (FACE) experiments have equipped us with a rich data source that can be used to calibrate and validate these model predictions. To identify and evaluate the assumptions causing inter-model differences we performed model sensitivity and uncertainty analysis across ambient and elevated CO2 treatments using the Data Assimilation Linked Ecosystem Carbon (DALEC) model and the Ecosystem Demography Model (ED2), two process-based models ranging from low to high complexity respectively. These modeled process responses were compared to experimental data from the Kennedy Space Center Open Top Chamber Experiment, the Nevada Desert Free Air CO2 Enrichment Facility, the Rhinelander FACE experiment, the Wyoming Prairie Heating and CO2 Enrichment Experiment, the Duke Forest Face experiment and the Oak Ridge Experiment on CO2 Enrichment. By leveraging data access proxy and data tilling services provided by the BrownDog data curation project alongside analysis modules available in the Predictive Ecosystem Analyzer (PEcAn), we produced automated, repeatable benchmarking workflows that are generalized to incorporate different sites and ecological models. Combining the observed patterns of uncertainty between the two models with results of the recent FACE-model data synthesis project (FACE-MDS) can help identify which processes need further study and additional data constraints. These findings can be used to inform future experimental design and in turn can provide informative starting point for data assimilation.

Using landscape analysis to assess and model tsunami damage in Aceh province, Sumatra

Treesearch

Louis R. Iverson; Anantha Prasad

2007-01-01

The nearly unprecedented loss of life resulting from the earthquake and tsunami of December 26,2004, was greatest in the province of Aceh, Sumatra (Indonesia). We evaluated tsunami damage and built empirical vulnerability models of damage/no damage based on elevation, distance from shore, vegetation, and exposure. We found that highly predictive models are possible and...

Biomechanical evaluation of heel elevation on load transfer — experimental measurement and finite element analysis

NASA Astrophysics Data System (ADS)

Luximon, Yan; Luximon, Ameersing; Yu, Jia; Zhang, Ming

2012-02-01

In spite of ill-effects of high heel shoes, they are widely used for women. Hence, it is essential to understand the load transfer biomechanics in order to design better fit and comfortable shoes. In this study, both experimental measurement and finite element analysis were used to evaluate the biomechanical effects of heel height on foot load transfer. A controlled experiment was conducted using custom-designed platforms. Under different weight-bearing conditions, peak plantar pressure, contact area and center of pressure were analyzed. A three-dimensional finite element foot model was used to simulate the high-heel support and to predict the internal stress distributions and deformations for different heel heights. Results from both experiment and model indicated that heel elevations had significant effects on all variables. When heel elevation increased, the center of pressure shifted from the midfoot region to the forefoot region, the contact area was reduced by 26% from 0 to 10.2 cm heel and the internal stress of foot bones increased. Prediction results also showed that the strain and total tension force of plantar fascia was minimum at 5.1 cm heel condition. This study helps to better understand the biomechanical behavior of foot, and to provide better suggestions for design parameters of high heeled shoes.

A panel of kallikrein markers can reduce unnecessary biopsy for prostate cancer: data from the European Randomized Study of Prostate Cancer Screening in Göteborg, Sweden

PubMed Central

Vickers, Andrew J; Cronin, Angel M; Aus, Gunnar; Pihl, Carl-Gustav; Becker, Charlotte; Pettersson, Kim; Scardino, Peter T; Hugosson, Jonas; Lilja, Hans

2008-01-01

Background Prostate-specific antigen (PSA) is widely used to detect prostate cancer. The low positive predictive value of elevated PSA results in large numbers of unnecessary prostate biopsies. We set out to determine whether a multivariable model including four kallikrein forms (total, free, and intact PSA, and human kallikrein 2 (hK2)) could predict prostate biopsy outcome in previously unscreened men with elevated total PSA. Methods The study cohort comprised 740 men in Göteborg, Sweden, undergoing biopsy during the first round of the European Randomized study of Screening for Prostate Cancer. We calculated the area-under-the-curve (AUC) for predicting prostate cancer at biopsy. AUCs for a model including age and PSA (the 'laboratory' model) and age, PSA and digital rectal exam (the 'clinical' model) were compared with those for models that also included additional kallikreins. Results Addition of free and intact PSA and hK2 improved AUC from 0.68 to 0.83 and from 0.72 to 0.84, for the laboratory and clinical models respectively. Using a 20% risk of prostate cancer as the threshold for biopsy would have reduced the number of biopsies by 424 (57%) and missed only 31 out of 152 low-grade and 3 out of 40 high-grade cancers. Conclusion Multiple kallikrein forms measured in blood can predict the result of biopsy in previously unscreened men with elevated PSA. A multivariable model can determine which men should be advised to undergo biopsy and which might be advised to continue screening, but defer biopsy until there was stronger evidence of malignancy. PMID:18611265

Higher risk of gastrointestinal parasite infection at lower elevation suggests possible constraints in the distributional niche of Alpine marmots

PubMed Central

Ferrari, Caterina; Bassano, Bruno; Ferroglio, Ezio; von Hardenberg, Achaz

2017-01-01

Alpine marmots Marmota marmota occupy a narrow altitudinal niche within high elevation alpine environments. For animals living at such high elevations where resources are limited, parasitism represents a potential major cost in life history. Using occupancy models, we tested if marmots living at higher elevation have a reduced risk of being infected with gastro-intestinal helminths, possibly compensating the lower availability of resources (shorter feeding season, longer snow cover and lower temperature) than marmots inhabiting lower elevations. Detection probability of eggs and oncospheres of two gastro-intestinal helminthic parasites, Ascaris laevis and Ctenotaenia marmotae, sampled in marmot feces, was used as a proxy of parasite abundance. As predicted, the models showed a negative relationship between elevation and parasite detectability (i.e. abundance) for both species, while there appeared to be a negative effect of solar radiance only for C. marmotae. Site-occupancy models are used here for the first time to model the constrains of gastrointestinal parasitism on a wild species and the relationship existing between endoparasites and environmental factors in a population of free-living animals. The results of this study suggest the future use of site-occupancy models as a viable tool to account for parasite imperfect detection in eco-parasitological studies, and give useful insights to further investigate the hypothesis of the contribution of parasite infection in constraining the altitudinal niche of Alpine marmots. PMID:28763517

Evaluating Productivity Predictions Under Elevated CO2 Conditions: Multi-Model Benchmarking Across FACE Experiments

NASA Astrophysics Data System (ADS)

Cowdery, E.; Dietze, M.

2016-12-01

As atmospheric levels of carbon dioxide levels continue to increase, it is critical that terrestrial ecosystem models can accurately predict ecological responses to the changing environment. Current predictions of net primary productivity (NPP) in response to elevated atmospheric CO2 concentration are highly variable and contain a considerable amount of uncertainty.The Predictive Ecosystem Analyzer (PEcAn) is an informatics toolbox that wraps around an ecosystem model and can be used to help identify which factors drive uncertainty. We tested a suite of models (LPJ-GUESS, MAESPA, GDAY, CLM5, DALEC, ED2), which represent a range from low to high structural complexity, across a range of Free-Air CO2 Enrichment (FACE) experiments: the Kennedy Space Center Open Top Chamber Experiment, the Rhinelander FACE experiment, the Duke Forest FACE experiment and the Oak Ridge Experiment on CO2 Enrichment. These tests were implemented in a novel benchmarking workflow that is automated, repeatable, and generalized to incorporate different sites and ecological models. Observational data from the FACE experiments represent a first test of this flexible, extensible approach aimed at providing repeatable tests of model process representation.To identify and evaluate the assumptions causing inter-model differences we used PEcAn to perform model sensitivity and uncertainty analysis, not only to assess the components of NPP, but also to examine system processes such nutrient uptake and and water use. Combining the observed patterns of uncertainty between multiple models with results of the recent FACE-model data synthesis project (FACE-MDS) can help identify which processes need further study and additional data constraints. These findings can be used to inform future experimental design and in turn can provide informative starting point for data assimilation.

Mapping the current and potential distribution of red spruce in Virginia: implications for the restoration of degraded high elevation habitat

Treesearch

Heather Griscom; Helmut Kraenzle; Zachary. Bortolot

2010-01-01

The objective of our project is to create a habitat suitability model to predict potential and future red spruce forest distributions. This model will be used to better understand the influence of climate change on red spruce distribution and to help guide forest restoration efforts.

A geospatial framework for improving the vertical accuracy of elevation models in Florida's coastal Everglades

NASA Astrophysics Data System (ADS)

Cooper, H.; Zhang, C.; Sirianni, M.

2016-12-01

South Florida relies upon the health of the Everglades, the largest subtropical wetland in North America, as a vital source of water. Since the late 1800's, this imperiled ecosystem has been highly engineered to meet human needs of flood control and water use. The Comprehensive Everglades Restoration Plan (CERP) was initiated in 2000 to restore original water flows to the Everglades and improve overall ecosystem health, while also aiming to achieve balance with human water usage. Due to subtle changes in the Everglades terrain, better vertical accuracy elevation data are needed to model groundwater and surface water levels that are integral to monitoring the effects of restoration under impacts such as sea-level rise. The current best available elevation datasets for the coastal Everglades include High Accuracy Elevation Data (HAED) and Florida Department of Emergency Management (FDEM) Light Detection and Ranging (LiDAR). However, the horizontal resolution of the HAED data is too coarse ( 400 m) for fine scale mapping, and the LiDAR data does not contain an accuracy assessment for coastal Everglades' vegetation communities. The purpose of this study is to develop a framework for generating better vertical accuracy and horizontal resolution Digital Elevation Models in the Flamingo District of Everglades National Park. In the framework, field work is conducted to collect RTK GPS and total station elevation measurements for mangrove swamp, coastal prairies, and freshwater marsh, and the proposed accuracy assessment and elevation modeling methodology is integrated with a Geographical Information System (GIS). It is anticipated that this study will provide more accurate models of the soil substrate elevation that can be used by restoration planners to better predict the future state of the Everglades ecosystem.

Factors associated with elevated plateau pressure in patients with acute lung injury receiving lower tidal volume ventilation.

PubMed

Prescott, Hallie C; Brower, Roy G; Cooke, Colin R; Phillips, Gary; O'Brien, James M

2013-03-01

Lung-protective ventilation with lower tidal volume and lower plateau pressure improves mortality in patients with acute lung injury and acute respiratory distress syndrome. We sought to determine the incidence of elevated plateau pressure in acute lung injury /acute respiratory distress syndrome patients receiving lower tidal volume ventilation and to determine the factors that predict elevated plateau pressure in these patients. We used data from 1398 participants in Acute Respiratory Distress Syndrome Network trials, who received lower tidal volume ventilation (≤ 6.5mL/kg predicted body weight). We considered patients with a plateau pressure greater than 30cm H2O and/or a tidal volume less than 5.5mL/kg predicted body weight on study day 1 to have "elevated plateau pressure." We used logistic regression to identify baseline clinical variables associated with elevated plateau pressure and to develop a model to predict elevated plateau pressure using a subset of 1,188 patients. We validated the model in the 210 patients not used for model development. Medical centers participating in Acute Respiratory Distress Syndrome Network clinical trials. None. Of the 1,398 patients in our study, 288 (20.6%) had elevated plateau pressure on day 1. Severity of illness indices and demographic factors (younger age, greater body mass index, and non-white race) were independently associated with elevated plateau pressure. The multivariable logistic regression model for predicting elevated plateau pressure had an area under the receiving operator characteristic curve of 0.71 for both the developmental and the validation subsets. acute lung injury patients receiving lower tidal volume ventilation often have a plateau pressure that exceeds Acute Respiratory Distress Syndrome Network goals. Race, body mass index, and severity of lung injury are each independently associated with elevated plateau pressure. Selecting a smaller initial tidal volume for non-white patients and patients with higher severity of illness may decrease the incidence of elevated plateau pressure. Prospective studies are needed to evaluate this approach.

Time dependent reliability model incorporating continuum damage mechanics for high-temperature ceramics

NASA Technical Reports Server (NTRS)

Duffy, Stephen F.; Gyekenyesi, John P.

1989-01-01

Presently there are many opportunities for the application of ceramic materials at elevated temperatures. In the near future ceramic materials are expected to supplant high temperature metal alloys in a number of applications. It thus becomes essential to develop a capability to predict the time-dependent response of these materials. The creep rupture phenomenon is discussed, and a time-dependent reliability model is outlined that integrates continuum damage mechanics principles and Weibull analysis. Several features of the model are presented in a qualitative fashion, including predictions of both reliability and hazard rate. In addition, a comparison of the continuum and the microstructural kinetic equations highlights a strong resemblance in the two approaches.

Can arsenic occurrence rate in bedrock aquifers be predicted?

USGS Publications Warehouse

Yang, Qiang; Jung, Hun Bok; Marvinney, Robert G.; Culbertson, Charles W.; Zheng, Yan

2012-01-01

A high percentage (31%) of groundwater samples from bedrock aquifers in the greater Augusta area, Maine was found to contain greater than 10 μg L–1 of arsenic. Elevated arsenic concentrations are associated with bedrock geology, and more frequently observed in samples with high pH, low dissolved oxygen, and low nitrate. These associations were quantitatively compared by statistical analysis. Stepwise logistic regression models using bedrock geology and/or water chemistry parameters are developed and tested with external data sets to explore the feasibility of predicting groundwater arsenic occurrence rates (the percentages of arsenic concentrations higher than 10 μg L–1) in bedrock aquifers. Despite the under-prediction of high arsenic occurrence rates, models including groundwater geochemistry parameters predict arsenic occurrence rates better than those with bedrock geology only. Such simple models with very few parameters can be applied to obtain a preliminary arsenic risk assessment in bedrock aquifers at local to intermediate scales at other localities with similar geology.

Can arsenic occurrence rates in bedrock aquifers be predicted?

PubMed Central

Yang, Qiang; Jung, Hun Bok; Marvinney, Robert G.; Culbertson, Charles W.; Zheng, Yan

2012-01-01

A high percentage (31%) of groundwater samples from bedrock aquifers in the greater Augusta area, Maine was found to contain greater than 10 µg L−1 of arsenic. Elevated arsenic concentrations are associated with bedrock geology, and more frequently observed in samples with high pH, low dissolved oxygen, and low nitrate. These associations were quantitatively compared by statistical analysis. Stepwise logistic regression models using bedrock geology and/or water chemistry parameters are developed and tested with external data sets to explore the feasibility of predicting groundwater arsenic occurrence rates (the percentages of arsenic concentrations higher than 10 µg L−1) in bedrock aquifers. Despite the under-prediction of high arsenic occurrence rates, models including groundwater geochemistry parameters predict arsenic occurrence rates better than those with bedrock geology only. Such simple models with very few parameters can be applied to obtain a preliminary arsenic risk assessment in bedrock aquifers at local to intermediate scales at other localities with similar geology. PMID:22260208

Distribution models for koalas in South Australia using citizen science-collected data

PubMed Central

Sequeira, Ana M M; Roetman, Philip E J; Daniels, Christopher B; Baker, Andrew K; Bradshaw, Corey J A

2014-01-01

The koala (Phascolarctos cinereus) occurs in the eucalypt forests of eastern and southern Australia and is currently threatened by habitat fragmentation, climate change, sexually transmitted diseases, and low genetic variability throughout most of its range. Using data collected during the Great Koala Count (a 1-day citizen science project in the state of South Australia), we developed generalized linear mixed-effects models to predict habitat suitability across South Australia accounting for potential errors associated with the dataset. We derived spatial environmental predictors for vegetation (based on dominant species of Eucalyptus or other vegetation), topographic water features, rain, elevation, and temperature range. We also included predictors accounting for human disturbance based on transport infrastructure (sealed and unsealed roads). We generated random pseudo-absences to account for the high prevalence bias typical of citizen-collected data. We accounted for biased sampling effort along sealed and unsealed roads by including an offset for distance to transport infrastructures. The model with the highest statistical support (wAICc ∼ 1) included all variables except rain, which was highly correlated with elevation. The same model also explained the highest deviance (61.6%), resulted in high R2(m) (76.4) and R2(c) (81.0), and had a good performance according to Cohen's κ (0.46). Cross-validation error was low (∼ 0.1). Temperature range, elevation, and rain were the best predictors of koala occurrence. Our models predict high habitat suitability in Kangaroo Island, along the Mount Lofty Ranges, and at the tips of the Eyre, Yorke and Fleurieu Peninsulas. In the highest-density region (5576 km2) of the Adelaide–Mount Lofty Ranges, a density–suitability relationship predicts a population of 113,704 (95% confidence interval: 27,685–199,723; average density = 5.0–35.8 km−2). We demonstrate the power of citizen science data for predicting species' distributions provided that the statistical approaches applied account for some uncertainties and potential biases. A future improvement to citizen science surveys to provide better data on search effort is that smartphone apps could be activated at the start of the search. The results of our models provide preliminary ranges of habitat suitability and population size for a species for which previous data have been difficult or impossible to gather otherwise. PMID:25360252

Distribution models for koalas in South Australia using citizen science-collected data.

PubMed

Sequeira, Ana M M; Roetman, Philip E J; Daniels, Christopher B; Baker, Andrew K; Bradshaw, Corey J A

2014-06-01

The koala (Phascolarctos cinereus) occurs in the eucalypt forests of eastern and southern Australia and is currently threatened by habitat fragmentation, climate change, sexually transmitted diseases, and low genetic variability throughout most of its range. Using data collected during the Great Koala Count (a 1-day citizen science project in the state of South Australia), we developed generalized linear mixed-effects models to predict habitat suitability across South Australia accounting for potential errors associated with the dataset. We derived spatial environmental predictors for vegetation (based on dominant species of Eucalyptus or other vegetation), topographic water features, rain, elevation, and temperature range. We also included predictors accounting for human disturbance based on transport infrastructure (sealed and unsealed roads). We generated random pseudo-absences to account for the high prevalence bias typical of citizen-collected data. We accounted for biased sampling effort along sealed and unsealed roads by including an offset for distance to transport infrastructures. The model with the highest statistical support (wAIC c ∼ 1) included all variables except rain, which was highly correlated with elevation. The same model also explained the highest deviance (61.6%), resulted in high R (2)(m) (76.4) and R (2)(c) (81.0), and had a good performance according to Cohen's κ (0.46). Cross-validation error was low (∼ 0.1). Temperature range, elevation, and rain were the best predictors of koala occurrence. Our models predict high habitat suitability in Kangaroo Island, along the Mount Lofty Ranges, and at the tips of the Eyre, Yorke and Fleurieu Peninsulas. In the highest-density region (5576 km(2)) of the Adelaide-Mount Lofty Ranges, a density-suitability relationship predicts a population of 113,704 (95% confidence interval: 27,685-199,723; average density = 5.0-35.8 km(-2)). We demonstrate the power of citizen science data for predicting species' distributions provided that the statistical approaches applied account for some uncertainties and potential biases. A future improvement to citizen science surveys to provide better data on search effort is that smartphone apps could be activated at the start of the search. The results of our models provide preliminary ranges of habitat suitability and population size for a species for which previous data have been difficult or impossible to gather otherwise.

Leveraging North Carolina's QL2 Lidar to Quantify Sensitivity of National Water Model Derived Flood Inundation Extent to DEM Resolution

NASA Astrophysics Data System (ADS)

Lovette, J. P.; Lenhardt, W. C.; Blanton, B.; Duncan, J. M.; Stillwell, L.

2017-12-01

The National Water Model (NWM) has provided a novel framework for near real time flood inundation mapping across CONUS at a 10m resolution. In many regions, this spatial scale is quickly being surpassed through the collection of high resolution lidar (1 - 3m). As one of the leading states in data collection for flood inundation mapping, North Carolina is currently improving their previously available 20 ft statewide elevation product to a Quality Level 2 (QL2) product with a nominal point spacing of 0.7 meters. This QL2 elevation product increases the ground points by roughly ten times over the previous statewide lidar product, and by over 250 times when compared to the 10m NED elevation grid. When combining these new lidar data with the discharge estimates from the NWM, we can further improve statewide flood inundation maps and predictions of at-risk areas. In the context of flood risk management, these improved predictions with higher resolution elevation models consistently represent an improvement on coarser products. Additionally, the QL2 lidar also includes coarse land cover classification data for each point return, opening the possibility for expanding analysis beyond the use of only digital elevation models (e.g. improving estimates of surface roughness, identifying anthropogenic features in floodplains, characterizing riparian zones, etc.). Using the NWM Height Above Nearest Drainage approach, we compare flood inundation extents derived from multiple lidar-derived grid resolutions to assess the tradeoff between precision and computational load in North Carolina's coastal river basins. The elevation data distributed through the state's new lidar collection program provide spatial resolutions ranging from 5-50 feet, with most inland areas also including a 3 ft product. Data storage increases by almost two orders of magnitude across this range, as does processing load. In order to further assess the validity of the higher resolution elevation products on flood inundation, we examine the NWM outputs from Hurricane Matthew, which devastated southeastern North Carolina in October 2016. When compared with numerous surveyed high water marks across the coastal plain, this assessment provides insight on the impacts of grid resolution on flood inundation extent.

Modeling soil respiration and variations of source components using a multi-factor global climate change experiment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Xiongwen; Post, Wilfred M; Norby, Richard J

2011-01-01

Soil respiration is an important component of the global carbon cycle and is highly responsive to changes in soil temperature and moisture. Accurate prediction of soil respiration and its changes under future climatic conditions requires a clear understanding of the processes involved. In spite of this, most current empirical soil respiration models incorporate just few of the underlying mechanisms that may influence its response. In this study, a new partial process-based component model built on source components of soil respiration was tested using data collected from a multi-factor climate change experiment that manipulates CO2 concentrations, temperature and precipitation. These resultsmore » were then compared to results generated using several other established models. The component model we tested performed well across different treatments of global climate change. In contrast, some other models, which worked well predicting ambient environmental conditions, were unable to predict the changes under different climate change treatments. Based on the component model, the relative proportions of heterotrophic respiration (Rh) in the total soil respiration at different treatments varied from 0.33 to 0.85. There is a significant increase in the proportion of Rh under the elevated atmospheric CO2 concentration in comparison ambient conditions. The dry treatment resulted in higher proportion of Rh at elevated CO2 and ambient T than under elevated CO2 and elevated T. Also, the ratios between root growth and root maintenance respiration varied across different treatments. Neither increased temperature nor elevated atmospheric CO2 changed Q10 values significantly, while the average Q10 value at wet sites was significantly higher than it at dry sites. There was a higher possibility of increased soil respiration under drying relative to wetting conditions across all treatments based on monthly data, indicating that soil respiration may also be related to soil moisture at previous time periods. Our results reveal that the extent, time delay and contribution of different source components need to be included into mechanistic/processes-based soil respiration models at corresponding scale.« less

The ability of the 2013 ACC/AHA cardiovascular risk score to identify rheumatoid arthritis patients with high coronary artery calcification scores

PubMed Central

Kawai, Vivian K.; Chung, Cecilia P.; Solus, Joseph F.; Oeser, Annette; Raggi, Paolo; Stein, C. Michael

2014-01-01

Objective Patients with rheumatoid arthritis (RA) have increased risk of atherosclerotic cardiovascular disease (ASCVD) that is underestimated by the Framingham risk score (FRS). We hypothesized that the 2013 ACC/AHA 10-year risk score would perform better than the FRS and the Reynolds risk score (RRS) in identifying RA patients known to have elevated cardiovascular risk based on high coronary artery calcification (CAC) scores. Methods Among 98 RA patients eligible for risk stratification using the ACC/AHA score we identified 34 patients with high CAC (≥ 300 Agatston units or ≥75th percentile) and compared the ability of the 10-year FRS, RRS and the ACC/AHA risk scores to correctly assign these patients to an elevated risk category. Results All three risk scores were higher in patients with high CAC (P values <0.05). The percentage of patients with high CAC correctly assigned to the elevated risk category was similar among the three scores (FRS 32%, RRS 32%, ACC/AHA 41%) (P=0.233). The c-statistics for the FRS, RRS and ACC/AHA risk scores predicting the presence of high CAC were 0.65, 0.66, and 0.65, respectively. Conclusions The ACC/AHA 10-year risk score does not offer any advantage compared to the traditional FRS and RRS in the identification of RA patients with elevated risk as determined by high CAC. The ACC/AHA risk score assigned almost 60% of patients with high CAC into a low risk category. Risk scores and standard risk prediction models used in the general population do not adequately identify many RA patients with elevated cardiovascular risk. PMID:25371313

Pretreatment data is highly predictive of liver chemistry signals in clinical trials

PubMed Central

Cai, Zhaohui; Bresell, Anders; Steinberg, Mark H; Silberg, Debra G; Furlong, Stephen T

2012-01-01

Purpose The goal of this retrospective analysis was to assess how well predictive models could determine which patients would develop liver chemistry signals during clinical trials based on their pretreatment (baseline) information. Patients and methods Based on data from 24 late-stage clinical trials, classification models were developed to predict liver chemistry outcomes using baseline information, which included demographics, medical history, concomitant medications, and baseline laboratory results. Results Predictive models using baseline data predicted which patients would develop liver signals during the trials with average validation accuracy around 80%. Baseline levels of individual liver chemistry tests were most important for predicting their own elevations during the trials. High bilirubin levels at baseline were not uncommon and were associated with a high risk of developing biochemical Hy’s law cases. Baseline γ-glutamyltransferase (GGT) level appeared to have some predictive value, but did not increase predictability beyond using established liver chemistry tests. Conclusion It is possible to predict which patients are at a higher risk of developing liver chemistry signals using pretreatment (baseline) data. Derived knowledge from such predictions may allow proactive and targeted risk management, and the type of analysis described here could help determine whether new biomarkers offer improved performance over established ones. PMID:23226004

Seed origin and warming constrain lodgepole pine recruitment, slowing the pace of population range shifts

USGS Publications Warehouse

Conlisk, Erin; Castanha, Cristina; Germino, Matthew; Veblen, Thomas T.; Smith, Jeremy M.; Moyes, Andrew B.; Kueppers, Lara M.

2018-01-01

Understanding how climate warming will affect the demographic rates of different ecotypes is critical to predicting shifts in species distributions. Here we present results from a common garden, climate change experiment in which we measured seedling recruitment of lodgepole pine, a widespread North American conifer that is also planted globally. Seeds from a low-elevation provenance had greater recruitment to their third year (by 323%) than seeds from a high-elevation provenance across sites within and above its native elevation range and across climate manipulations. Heating reduced (by 49%) recruitment to the third year of both low- and high-elevation seed sources across the elevation gradient, while watering alleviated some of the negative effects of heating (108% increase in watered plots). Demographic models based on recruitment data from the climate manipulations and long-term observations of adult populations revealed that heating could effectively halt modeled upslope range expansion except when combined with watering. Simulating fire and rapid post-fire forest recovery at lower elevations accelerated lodgepole pine expansion into the alpine, but did not alter final abundance rankings among climate scenarios. Regardless of climate scenario, greater recruitment of low-elevation seeds compensated for longer dispersal distances to treeline, assuming colonization was allowed to proceed over multiple centuries. Our results show that ecotypes from lower elevations within a species’ range could enhance recruitment and facilitate upslope range shifts with climate change.

Distribution pattern of reptiles along an eastern Himalayan elevation gradient, India

NASA Astrophysics Data System (ADS)

Chettri, Basundhara; Bhupathy, Subramanian; Acharya, Bhoj Kumar

2010-01-01

We examined the spatial distribution pattern of reptiles in an eastern Himalayan elevation gradient. The factors governing the distribution have been assessed with emphasis on the mid-domain effect. We surveyed reptiles along the elevation gradient (300-4800 m) of the Teesta valley in Sikkim, Eastern Himalaya, India using time constrained visual encounter survey. A total of 42 species of reptiles were observed during the study, and the species richness peaked at 500-1000 m with no species beyond 3000 m. The observed pattern was consistent with estimated richness, both showing significant negative relation with elevation. Lizards showed a linear decline with elevation, whereas snakes followed a non-linear relation with peak at 500-1000 m. Observed species richness deviated significantly from that predicted by a mid-domain null model. The regression between empirical and simulated richness was not significant for total reptiles as well as lizards and snakes separately. Most species distributed in the high elevation extended towards lower elevation, but low elevation species (around 50%) were restricted below 1000 m. Deviation of empirical from predicted richness indicates that the distributions of reptile species were least governed by geographic hard boundaries. Climatic factors especially temperature explained much variation of reptiles along the Himalayan elevation gradient. Most reptiles were narrowly distributed, especially those found in low elevation indicating the importance of tropical low-land forests in the conservation of reptiles in Eastern Himalayas.

The effects of topography on magma chamber deformation models: Application to Mt. Etna and radar interferometry

NASA Astrophysics Data System (ADS)

Williams, Charles A.; Wadge, Geoff

We have used a three-dimensional elastic finite element model to examine the effects of topography on the surface deformation predicted by models of magma chamber deflation. We used the topography of Mt. Etna to control the geometry of our model, and compared the finite element results to those predicted by an analytical solution for a pressurized sphere in an elastic half-space. Topography has a significant effect on the predicted surface deformation for both displacement profiles and synthetic interferograms. Not only are the predicted displacement magnitudes significantly different, but also the map-view patterns of displacement. It is possible to match the predicted displacement magnitudes fairly well by adjusting the elevation of a reference surface; however, the horizontal pattern of deformation is still significantly different. Thus, inversions based on constant-elevation reference surfaces may not properly estimate the horizontal position of a magma chamber. We have investigated an approach where the elevation of the reference surface varies for each computation point, corresponding to topography. For vertical displacements and tilts this method provides a good fit to the finite element results, and thus may form the basis for an inversion scheme. For radial displacements, a constant reference elevation provides a better fit to the numerical results.

Development of a Hydrodynamic and Transport model of Bellingham Bay in Support of Nearshore Habitat Restoration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Taiping; Yang, Zhaoqing; Khangaonkar, Tarang

2010-04-22

In this study, a hydrodynamic model based on the unstructured-grid finite volume coastal ocean model (FVCOM) was developed for Bellingham Bay, Washington. The model simulates water surface elevation, velocity, temperature, and salinity in a three-dimensional domain that covers the entire Bellingham Bay and adjacent water bodies, including Lummi Bay, Samish Bay, Padilla Bay, and Rosario Strait. The model was developed using Pacific Northwest National Laboratory’s high-resolution Puget Sound and Northwest Straits circulation and transport model. A sub-model grid for Bellingham Bay and adjacent coastal waters was extracted from the Puget Sound model and refined in Bellingham Bay using bathymetric lightmore » detection and ranging (LIDAR) and river channel cross-section data. The model uses tides, river inflows, and meteorological inputs to predict water surface elevations, currents, salinity, and temperature. A tidal open boundary condition was specified using standard National Oceanic and Atmospheric Administration (NOAA) predictions. Temperature and salinity open boundary conditions were specified based on observed data. Meteorological forcing (wind, solar radiation, and net surface heat flux) was obtained from NOAA real observations and National Center for Environmental Prediction North American Regional Analysis outputs. The model was run in parallel with 48 cores using a time step of 2.5 seconds. It took 18 hours of cpu time to complete 26 days of simulation. The model was calibrated with oceanographic field data for the period of 6/1/2009 to 6/26/2009. These data were collected specifically for the purpose of model development and calibration. They include time series of water-surface elevation, currents, temperature, and salinity as well as temperature and salinity profiles during instrument deployment and retrieval. Comparisons between model predictions and field observations show an overall reasonable agreement in both temporal and spatial scales. Comparisons of root mean square error values for surface elevation, velocity, temperature, and salinity time series are 0.11 m, 0.10 m/s, 1.28oC, and 1.91 ppt, respectively. The model was able to reproduce the salinity and temperature stratifications inside Bellingham Bay. Wetting and drying processes in tidal flats in Bellingham Bay, Samish Bay, and Padilla Bay were also successfully simulated. Both model results and observed data indicated that water surface elevations inside Bellingham Bay are highly correlated to tides. Circulation inside the bay is weak and complex and is affected by various forcing mechanisms, including tides, winds, freshwater inflows, and other local forcing factors. The Bellingham Bay model solution was successfully linked to the NOAA oil spill trajectory simulation model “General NOAA Operational Modeling Environment (GNOME).” Overall, the Bellingham Bay model has been calibrated reasonably well and can be used to provide detailed hydrodynamic information in the bay and adjacent water bodies. While there is room for further improvement with more available data, the calibrated hydrodynamic model provides useful hydrodynamic information in Bellingham Bay and can be used to support sediment transport and water quality modeling as well as assist in the design of nearshore restoration scenarios.« less

Temperature Measurement and Numerical Prediction in Machining Inconel 718.

PubMed

Díaz-Álvarez, José; Tapetado, Alberto; Vázquez, Carmen; Miguélez, Henar

2017-06-30

Thermal issues are critical when machining Ni-based superalloy components designed for high temperature applications. The low thermal conductivity and extreme strain hardening of this family of materials results in elevated temperatures around the cutting area. This elevated temperature could lead to machining-induced damage such as phase changes and residual stresses, resulting in reduced service life of the component. Measurement of temperature during machining is crucial in order to control the cutting process, avoiding workpiece damage. On the other hand, the development of predictive tools based on numerical models helps in the definition of machining processes and the obtainment of difficult to measure parameters such as the penetration of the heated layer. However, the validation of numerical models strongly depends on the accurate measurement of physical parameters such as temperature, ensuring the calibration of the model. This paper focuses on the measurement and prediction of temperature during the machining of Ni-based superalloys. The temperature sensor was based on a fiber-optic two-color pyrometer developed for localized temperature measurements in turning of Inconel 718. The sensor is capable of measuring temperature in the range of 250 to 1200 °C. Temperature evolution is recorded in a lathe at different feed rates and cutting speeds. Measurements were used to calibrate a simplified numerical model for prediction of temperature fields during turning.

Demographic projection of high-elevation white pines infected with white pine blister rust: a nonlinear disease model

Treesearch

S. G. Field; A. W. Schoettle; J. G. Klutsch; S. J. Tavener; M. F. Antolin

2012-01-01

Matrix population models have long been used to examine and predict the fate of threatened populations. However, the majority of these efforts concentrate on long-term equilibrium dynamics of linear systems and their underlying assumptions and, therefore, omit the analysis of transience. Since management decisions are typically concerned with the short term (

Numerical Investigation of the Turbulent Wind Flow Through Elevated Windbreak

NASA Astrophysics Data System (ADS)

Agarwal, Ashish; Irtaza, Hassan

2018-06-01

Analysis of airflow through elevated windbreaks is presented in this paper. Permeable nets and impermeable film increases considerable wind forces on the windbreaks which is susceptible to damage during high wind. A comprehensive numerical investigation has been carried out to analyze the effects of wind on standalone elevated windbreak clad with various permeable nets and an impermeable film. The variation of airflow behavior around and through permeable nets and airflow behavior around impermeable film were also been investigated. Computational fluid dynamics techniques using Reynolds Averaged Navier-Stokes equations has been used to predict the wind force coefficient and thus wind forces on panels supporting permeable nets and impermeable film for turbulent wind flow. Elevated windbreak panels were analyzed for seven different permeable nets having various solidity ratio, specific permeability and aerodynamic resistant coefficients. The permeable nets were modelled as porous jump media obeying Forchheimer's law and an impermeable film modelled as rigid wall.

Numerical Investigation of the Turbulent Wind Flow Through Elevated Windbreak

NASA Astrophysics Data System (ADS)

Agarwal, Ashish; Irtaza, Hassan

2018-04-01

Analysis of airflow through elevated windbreaks is presented in this paper. Permeable nets and impermeable film increases considerable wind forces on the windbreaks which is susceptible to damage during high wind. A comprehensive numerical investigation has been carried out to analyze the effects of wind on standalone elevated windbreak clad with various permeable nets and an impermeable film. The variation of airflow behavior around and through permeable nets and airflow behavior around impermeable film were also been investigated. Computational fluid dynamics techniques using Reynolds Averaged Navier-Stokes equations has been used to predict the wind force coefficient and thus wind forces on panels supporting permeable nets and impermeable film for turbulent wind flow. Elevated windbreak panels were analyzed for seven different permeable nets having various solidity ratio, specific permeability and aerodynamic resistant coefficients. The permeable nets were modelled as porous jump media obeying Forchheimer's law and an impermeable film modelled as rigid wall.

Effects of elevated atmospheric carbon dioxide on biomass and carbon accumulation in a model regenerating longleaf pine community.

PubMed

Runion, G B; Davis, M A; Pritchard, S G; Prior, S A; Mitchell, R J; Torbert, H A; Rogers, H H; Dute, R R

2006-01-01

Plant species vary in response to atmospheric CO2 concentration due to differences in physiology, morphology, phenology, and symbiotic relationships. These differences make it very difficult to predict how plant communities will respond to elevated CO2. Such information is critical to furthering our understanding of community and ecosystem responses to global climate change. To determine how a simple plant community might respond to elevated CO2, a model regenerating longleaf pine community composed of five species was exposed to two CO2 regimes (ambient, 365 micromol mol(-1) and elevated, 720 micromol mol(-1)) for 3 yr. Total above- and belowground biomass was 70 and 49% greater, respectively, in CO2-enriched plots. Carbon (C) content followed a response pattern similar to biomass, resulting in a significant increase of 13.8 Mg C ha(-1) under elevated CO2. Responses of individual species, however, varied. Longleaf pine (Pinus palustris Mill.) was primarily responsible for the positive response to CO2 enrichment. Wiregrass (Aristida stricta Michx.), rattlebox (Crotalaria rotundifolia Walt. Ex Gmel.), and butterfly weed (Asclepias tuberosa L.) exhibited negative above- and belowground biomass responses to elevated CO2, while sand post oak (Quercus margaretta Ashe) did not differ significantly between CO2 treatments. As with pine, C content followed patterns similar to biomass. Elevated CO2 resulted in alterations in community structure. Longleaf pine comprised 88% of total biomass in CO2-enriched plots, but only 76% in ambient plots. In contrast, wiregrass, rattlebox, and butterfly weed comprised 19% in ambient CO2 plots, but only 8% under high CO2. Therefore, while longleaf pine may perform well in a high CO2 world, other members of this community may not compete as well, which could alter community function. Effects of elevated CO2 on plant communities are complex, dynamic, and difficult to predict, clearly demonstrating the need for more research in this important area of global change science.

Evaluating the Impact of Global Warming on Water Balance of Maize by High-precision Controlled Experiment and MLCan model

NASA Astrophysics Data System (ADS)

Ma, Y.; Song, X.; Kumar, P.; Wu, Y.; Woo, D.; Le, P. V.; Ma, C.

2016-12-01

Increased temperature affects the agricultural hydrologic cycle not only by changing precipitation levels, evapotranspiration and the magnitude and timing of run-off, but also by impacting water flows and soil water dynamics. Accurate prediction of hydrologic change under global warming requires high-precision experiment and mathematical model to determine water interaction between interfaces in the soil-plant-atmosphere continuum. In this study, the weighting lysimeter and chamber were coupled to monitor water balance component dynamics of maize under controlled ambient temperature and elevated temperature of 2°C conditions. A mechanistic multilayer canopy-soil-root system model (MLCan) was used to predict hydrologic fluxes variation under different elevated temperature scenarios after calibration with experimental results. The results showed that maize growth period reduced 8 days under increased temperature of 2°C. The mean daily evapotranspiration, soil water storage change, and drainage was 2.66 mm, -2.75 mm, and 0.22 mm under controlled temperature condition, respectively. When temperature was elevated by 2°C, the average daily ET for maize significantly increased about 6.7% (p<0.05). However, there were non-significant impacts of increased temperature on the daily soil water storage change and drainage (p>0.05). Quantification of changes in water balance components induced by temperature increase for maize is critical for optimizing irrigation water management practices and improving water use efficiency.

a Maximum Entropy Model of the Bearded Capuchin Monkey Habitat Incorporating Topography and Spectral Unmixing Analysis

NASA Astrophysics Data System (ADS)

Howard, A. M.; Bernardes, S.; Nibbelink, N.; Biondi, L.; Presotto, A.; Fragaszy, D. M.; Madden, M.

2012-07-01

Movement patterns of bearded capuchin monkeys (Cebus (Sapajus) libidinosus) in northeastern Brazil are likely impacted by environmental features such as elevation, vegetation density, or vegetation type. Habitat preferences of these monkeys provide insights regarding the impact of environmental features on species ecology and the degree to which they incorporate these features in movement decisions. In order to evaluate environmental features influencing movement patterns and predict areas suitable for movement, we employed a maximum entropy modelling approach, using observation points along capuchin monkey daily routes as species presence points. We combined these presence points with spatial data on important environmental features from remotely sensed data on land cover and topography. A spectral mixing analysis procedure was used to generate fraction images that represent green vegetation, shade and soil of the study area. A Landsat Thematic Mapper scene of the area of study was geometrically and atmospherically corrected and used as input in a Minimum Noise Fraction (MNF) procedure and a linear spectral unmixing approach was used to generate the fraction images. These fraction images and elevation were the environmental layer inputs for our logistic MaxEnt model of capuchin movement. Our models' predictive power (test AUC) was 0.775. Areas of high elevation (>450 m) showed low probabilities of presence, and percent green vegetation was the greatest overall contributor to model AUC. This work has implications for predicting daily movement patterns of capuchins in our field site, as suitability values from our model may relate to habitat preference and facility of movement.

Spinal loads as influenced by external loads: a combined in vivo and in silico investigation.

PubMed

Zander, Thomas; Dreischarf, Marcel; Schmidt, Hendrik; Bergmann, Georg; Rohlmann, Antonius

2015-02-26

Knowledge of in vivo spinal loads and muscle forces remains limited but is necessary for spinal biomechanical research. To assess the in vivo spinal loads, measurements with telemeterised vertebral body replacements were performed in four patients. The following postures were investigated: (a) standing with arms hanging down on sides, (b) holding dumbbells to subject the patient to a vertical load, and (c) the forward elevation of arms for creating an additional flexion moment. The same postures were simulated by an inverse static model for validation purposes, to predict muscle forces, and to assess the spinal loads in subjects without implants. Holding dumbbells on sides increased implant forces by the magnitude of the weight of the dumbbells. In contrast, elevating the arms yielded considerable implant forces with a high correlation between the external flexion moment and the implant force. Predictions agreed well with experimental findings, especially for forward elevation of arms. Flexion moments were mainly compensated by erector spinae muscles. The implant altered the kinematics and, thus, the spinal loads. Elevation of both arms in vivo increased spinal axial forces by approximately 100N; each additional kg of dumbbell weight held in the hands increased the spinal axial forces by 60N. Model predictions suggest that in the intact situation, the force increase is one-third greater for these loads. In vivo measurements are essential for the validation of analytical models, and the combination of both methods can reveal unquantifiable data such as the spinal loads in the intact non-instrumented situation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Evaluation of wintertime precipitation forecasts over the Australian Snowy Mountains

NASA Astrophysics Data System (ADS)

Huang, Yi; Chubb, Thomas; Sarmadi, Fahimeh; Siems, Steven T.; Manton, Michael J.; Franklin, Charmaine N.; Ebert, Elizabeth

2018-07-01

This study evaluates the Australian Community Climate and Earth-System Simulator (ACCESS) Numerical Weather Prediction system in forecasting precipitation across the Australian Snowy Mountains for two cool seasons. Metrics based on seasonal accumulated and daily precipitation show that the model is able to reproduce the observed domain-mean accumulated precipitation reasonably well (with a slight overestimation), but this is, in part, due to a compensation of various errors. Both the frequency and intensity of the heavy precipitation days (domain-mean daily precipitation >5 mm day-1) are overrepresented, particularly over the complex terrain and high-elevation areas, whereas the frequency of the very light precipitation days (domain-mean daily precipitation <1 mm day-1) is underestimated, primarily over lower-elevation areas both upwind and downwind of the mountains. Most of the precipitation is forecasted by the grid-scale precipitation scheme, with appreciable snowfalls predicted over the high elevations. The model also demonstrates appreciable skill in reproducing the synoptic regimes. The proportion of the forecast precipitation for each regime is comparable to the observations, although the orographic enhancement over the western slopes of the mountains is more pronounced in the forecasts, particularly for the wetter regimes. An examination on the effect of the lower-atmosphere stability suggests that most of the precipitation (50-70% over the high elevations) is produced under the "unblocked" condition, which is diagnosed 31% of the time. The remainder is produced under the "blocked" condition. Combined with a case study, potential sources of error associated with the forecast precipitation biases are also discussed.

Predicting 30-Day Hospital Readmissions in Acute Myocardial Infarction: The AMI "READMITS" (Renal Function, Elevated Brain Natriuretic Peptide, Age, Diabetes Mellitus, Nonmale Sex, Intervention with Timely Percutaneous Coronary Intervention, and Low Systolic Blood Pressure) Score.

PubMed

Nguyen, Oanh Kieu; Makam, Anil N; Clark, Christopher; Zhang, Song; Das, Sandeep R; Halm, Ethan A

2018-04-17

Readmissions after hospitalization for acute myocardial infarction (AMI) are common. However, the few currently available AMI readmission risk prediction models have poor-to-modest predictive ability and are not readily actionable in real time. We sought to develop an actionable and accurate AMI readmission risk prediction model to identify high-risk patients as early as possible during hospitalization. We used electronic health record data from consecutive AMI hospitalizations from 6 hospitals in north Texas from 2009 to 2010 to derive and validate models predicting all-cause nonelective 30-day readmissions, using stepwise backward selection and 5-fold cross-validation. Of 826 patients hospitalized with AMI, 13% had a 30-day readmission. The first-day AMI model (the AMI "READMITS" score) included 7 predictors: renal function, elevated brain natriuretic peptide, age, diabetes mellitus, nonmale sex, intervention with timely percutaneous coronary intervention, and low systolic blood pressure, had an optimism-corrected C-statistic of 0.73 (95% confidence interval, 0.71-0.74) and was well calibrated. The full-stay AMI model, which included 3 additional predictors (use of intravenous diuretics, anemia on discharge, and discharge to postacute care), had an optimism-corrected C-statistic of 0.75 (95% confidence interval, 0.74-0.76) with minimally improved net reclassification and calibration. Both AMI models outperformed corresponding multicondition readmission models. The parsimonious AMI READMITS score enables early prospective identification of high-risk AMI patients for targeted readmissions reduction interventions within the first 24 hours of hospitalization. A full-stay AMI readmission model only modestly outperformed the AMI READMITS score in terms of discrimination, but surprisingly did not meaningfully improve reclassification. © 2018 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

Field scale test of multi-dimensional flow and morphodynamic simulations used for restoration design analysis

USGS Publications Warehouse

McDonald, Richard R.; Nelson, Jonathan M.; Fosness, Ryan L.; Nelson, Peter O.; Constantinescu, George; Garcia, Marcelo H.; Hanes, Dan

2016-01-01

Two- and three-dimensional morphodynamic simulations are becoming common in studies of channel form and process. The performance of these simulations are often validated against measurements from laboratory studies. Collecting channel change information in natural settings for model validation is difficult because it can be expensive and under most channel forming flows the resulting channel change is generally small. Several channel restoration projects designed in part to armor large meanders with several large spurs constructed of wooden piles on the Kootenai River, ID, have resulted in rapid bed elevation change following construction. Monitoring of these restoration projects includes post- restoration (as-built) Digital Elevation Models (DEMs) as well as additional channel surveys following high channel forming flows post-construction. The resulting sequence of measured bathymetry provides excellent validation data for morphodynamic simulations at the reach scale of a real river. In this paper we test the performance a quasi-three-dimensional morphodynamic simulation against the measured elevation change. The resulting simulations predict the pattern of channel change reasonably well but many of the details such as the maximum scour are under predicted.

Generation of real-time mode high-resolution water vapor fields from GPS observations

NASA Astrophysics Data System (ADS)

Yu, Chen; Penna, Nigel T.; Li, Zhenhong

2017-02-01

Pointwise GPS measurements of tropospheric zenith total delay can be interpolated to provide high-resolution water vapor maps which may be used for correcting synthetic aperture radar images, for numeral weather prediction, and for correcting Network Real-time Kinematic GPS observations. Several previous studies have addressed the importance of the elevation dependency of water vapor, but it is often a challenge to separate elevation-dependent tropospheric delays from turbulent components. In this paper, we present an iterative tropospheric decomposition interpolation model that decouples the elevation and turbulent tropospheric delay components. For a 150 km × 150 km California study region, we estimate real-time mode zenith total delays at 41 GPS stations over 1 year by using the precise point positioning technique and demonstrate that the decoupled interpolation model generates improved high-resolution tropospheric delay maps compared with previous tropospheric turbulence- and elevation-dependent models. Cross validation of the GPS zenith total delays yields an RMS error of 4.6 mm with the decoupled interpolation model, compared with 8.4 mm with the previous model. On converting the GPS zenith wet delays to precipitable water vapor and interpolating to 1 km grid cells across the region, validations with the Moderate Resolution Imaging Spectroradiometer near-IR water vapor product show 1.7 mm RMS differences by using the decoupled model, compared with 2.0 mm for the previous interpolation model. Such results are obtained without differencing the tropospheric delays or water vapor estimates in time or space, while the errors are similar over flat and mountainous terrains, as well as for both inland and coastal areas.

Sierra Nevada snowpack and runoff prediction integrating basin-wide wireless-sensor network data

NASA Astrophysics Data System (ADS)

Yoon, Y.; Conklin, M. H.; Bales, R. C.; Zhang, Z.; Zheng, Z.; Glaser, S. D.

2016-12-01

We focus on characterizing snowpack and estimating runoff from snowmelt in high elevation area (>2100 m) in Sierra Nevada for daily (for use in, e.g. flood and hydropower forecasting), seasonal (supply prediction), and decadal (long-term planning) time scale. Here, basin-wide wireless-sensor network data (ARHO, http://glaser.berkeley.edu/wsn/) is integrated into the USGS Precipitation-Runoff Modeling System (PRMS), and a case study of the American River basin is presented. In the American River basin, over 140 wireless sensors have been planted in 14 sites considering elevation gradient, slope, aspect, and vegetation density, which provides spatially distributed snow depth, temperature, solar radiation, and soil moisture from 2013. 800 m daily gridded dataset (PRISM) is used as the climate input for the PRMS. Model parameters are obtained from various sources (e.g., NLCD 2011, SSURGO, and NED) with a regionalization method and GIS analysis. We use a stepwise framework for a model calibration to improve model performance and localities of estimates. For this, entire basin is divided into 12 subbasins that include full natural flow measurements. The study period is between 1982 and 2014, which contains three major storm events and recent severe drought. Simulated snow depth and snow water equivalent (SWE) are initially compared with the water year 2014 ARHO observations. The overall results show reasonable agreements having the Nash-Sutcliffe efficiency coefficient (NS) of 0.7, ranged from 0.3 to 0.86. However, the results indicate a tendency to underestimate the SWE in a high elevation area compared with ARHO observations, which is caused by the underestimated PRISM precipitation data. Precipitation at gauge-sparse regions (e.g., high elevation area), in general, cannot be well represented in gridded datasets. Streamflow estimates of the basin outlet have NS of 0.93, percent bias of 7.8%, and normalized root mean square error of 3.6% for the monthly time scale.

Modeling Elevation and Aspect Controls on Emerging Ecohydrologic Processes and Ecosystem Patterns Using the Component-based Landlab Framework

NASA Astrophysics Data System (ADS)

Nudurupati, S. S.; Istanbulluoglu, E.; Adams, J. M.; Hobley, D. E. J.; Gasparini, N. M.; Tucker, G. E.; Hutton, E. W. H.

2014-12-01

Topography plays a commanding role on the organization of ecohydrologic processes and resulting vegetation patterns. In southwestern United States, climate conditions lead to terrain aspect- and elevation-controlled ecosystems, with mesic north-facing and xeric south-facing vegetation types; and changes in biodiversity as a function of elevation from shrublands in low desert elevations, to mixed grass/shrublands in mid elevations, and forests at high elevations and ridge tops. These observed patterns have been attributed to differences in topography-mediated local soil moisture availability, micro-climatology, and life history processes of plants that control chances of plant establishment and survival. While ecohydrologic models represent local vegetation dynamics in sufficient detail up to sub-hourly time scales, plant life history and competition for space and resources has not been adequately represented in models. In this study we develop an ecohydrologic cellular automata model within the Landlab component-based modeling framework. This model couples local vegetation dynamics (biomass production, death) and plant establishment and competition processes for resources and space. This model is used to study the vegetation organization in a semiarid New Mexico catchment where elevation and hillslope aspect play a defining role on plant types. Processes that lead to observed plant types across the landscape are examined by initializing the domain with randomly assigned plant types and systematically changing model parameters that couple plant response with soil moisture dynamics. Climate perturbation experiments are conducted to examine the plant response in space and time. Understanding the inherently transient ecohydrologic systems is critical to improve predictions of climate change impacts on ecosystems.

Refraction of microwave signals by water vapor

NASA Technical Reports Server (NTRS)

Goldfinger, A. D.

1980-01-01

Tropospheric water vapor causes a refractive path length effect which is typically 5-10% of the 'dry' tropospheric effect and as large as several meters at elevation angles below 5 deg. The vertical water vapor profile is quite variable, and measurements of intensive atmospheric parameters such as temperature and humidity limited to the surface do not adequately predict the refractive effect. It is suggested that a water vapor refraction model that is a function of the amount of precipitable water alone can be successful at low elevation angles. From an extensive study of numerical ray tracings through radiosonde balloon data, such a model has been constructed. The model predicts the effect at all latitudes and elevation angles between 2 and 10 deg to an accuracy of better than 4% (11 cm at 3 deg elevation angle).

A General, Synthetic Model for Predicting Biodiversity Gradients from Environmental Geometry.

PubMed

Gross, Kevin; Snyder-Beattie, Andrew

2016-10-01

Latitudinal and elevational biodiversity gradients fascinate ecologists, and have inspired dozens of explanations. The geometry of the abiotic environment is sometimes thought to contribute to these gradients, yet evaluations of geometric explanations are limited by a fragmented understanding of the diversity patterns they predict. This article presents a mathematical model that synthesizes multiple pathways by which environmental geometry can drive diversity gradients. The model characterizes species ranges by their environmental niches and limits on range sizes and places those ranges onto the simplified geometries of a sphere or cone. The model predicts nuanced and realistic species-richness gradients, including latitudinal diversity gradients with tropical plateaus and mid-latitude inflection points and elevational diversity gradients with low-elevation diversity maxima. The model also illustrates the importance of a mid-environment effect that augments species richness at locations with intermediate environments. Model predictions match multiple empirical biodiversity gradients, depend on ecological traits in a testable fashion, and formally synthesize elements of several geometric models. Together, these results suggest that previous assessments of geometric hypotheses should be reconsidered and that environmental geometry may play a deeper role in driving biodiversity gradients than is currently appreciated.

Prostate-specific antigen velocity in a prospective prostate cancer screening study of men with genetic predisposition.

PubMed

Mikropoulos, Christos; Selkirk, Christina G Hutten; Saya, Sibel; Bancroft, Elizabeth; Vertosick, Emily; Dadaev, Tokhir; Brendler, Charles; Page, Elizabeth; Dias, Alexander; Evans, D Gareth; Rothwell, Jeanette; Maehle, Lovise; Axcrona, Karol; Richardson, Kate; Eccles, Diana; Jensen, Thomas; Osther, Palle J; van Asperen, Christi J; Vasen, Hans; Kiemeney, Lambertus A; Ringelberg, Janneke; Cybulski, Cezary; Wokolorczyk, Dominika; Hart, Rachel; Glover, Wayne; Lam, Jimmy; Taylor, Louise; Salinas, Monica; Feliubadaló, Lidia; Oldenburg, Rogier; Cremers, Ruben; Verhaegh, Gerald; van Zelst-Stams, Wendy A; Oosterwijk, Jan C; Cook, Jackie; Rosario, Derek J; Buys, Saundra S; Conner, Tom; Domchek, Susan; Powers, Jacquelyn; Ausems, Margreet Gem; Teixeira, Manuel R; Maia, Sofia; Izatt, Louise; Schmutzler, Rita; Rhiem, Kerstin; Foulkes, William D; Boshari, Talia; Davidson, Rosemarie; Ruijs, Marielle; Helderman-van den Enden, Apollonia Tjm; Andrews, Lesley; Walker, Lisa; Snape, Katie; Henderson, Alex; Jobson, Irene; Lindeman, Geoffrey J; Liljegren, Annelie; Harris, Marion; Adank, Muriel A; Kirk, Judy; Taylor, Amy; Susman, Rachel; Chen-Shtoyerman, Rakefet; Pachter, Nicholas; Spigelman, Allan; Side, Lucy; Zgajnar, Janez; Mora, Josefina; Brewer, Carole; Gadea, Neus; Brady, Angela F; Gallagher, David; van Os, Theo; Donaldson, Alan; Stefansdottir, Vigdis; Barwell, Julian; James, Paul A; Murphy, Declan; Friedman, Eitan; Nicolai, Nicola; Greenhalgh, Lynn; Obeid, Elias; Murthy, Vedang; Copakova, Lucia; McGrath, John; Teo, Soo-Hwang; Strom, Sara; Kast, Karin; Leongamornlert, Daniel A; Chamberlain, Anthony; Pope, Jenny; Newlin, Anna C; Aaronson, Neil; Ardern-Jones, Audrey; Bangma, Chris; Castro, Elena; Dearnaley, David; Eyfjord, Jorunn; Falconer, Alison; Foster, Christopher S; Gronberg, Henrik; Hamdy, Freddie C; Johannsson, Oskar; Khoo, Vincent; Lubinski, Jan; Grindedal, Eli Marie; McKinley, Joanne; Shackleton, Kylie; Mitra, Anita V; Moynihan, Clare; Rennert, Gad; Suri, Mohnish; Tricker, Karen; Moss, Sue; Kote-Jarai, Zsofia; Vickers, Andrew; Lilja, Hans; Helfand, Brian T; Eeles, Rosalind A

2018-01-01

Prostate-specific antigen (PSA) and PSA-velocity (PSAV) have been used to identify men at risk of prostate cancer (PrCa). The IMPACT study is evaluating PSA screening in men with a known genetic predisposition to PrCa due to BRCA1/2 mutations. This analysis evaluates the utility of PSA and PSAV for identifying PrCa and high-grade disease in this cohort. PSAV was calculated using logistic regression to determine if PSA or PSAV predicted the result of prostate biopsy (PB) in men with elevated PSA values. Cox regression was used to determine whether PSA or PSAV predicted PSA elevation in men with low PSAs. Interaction terms were included in the models to determine whether BRCA status influenced the predictiveness of PSA or PSAV. 1634 participants had ⩾3 PSA readings of whom 174 underwent PB and 45 PrCas diagnosed. In men with PSA >3.0 ng ml -l , PSAV was not significantly associated with presence of cancer or high-grade disease. PSAV did not add to PSA for predicting time to an elevated PSA. When comparing BRCA1/2 carriers to non-carriers, we found a significant interaction between BRCA status and last PSA before biopsy (P=0.031) and BRCA2 status and PSAV (P=0.024). However, PSAV was not predictive of biopsy outcome in BRCA2 carriers. PSA is more strongly predictive of PrCa in BRCA carriers than non-carriers. We did not find evidence that PSAV aids decision-making for BRCA carriers over absolute PSA value alone.

Prostate-specific antigen velocity in a prospective prostate cancer screening study of men with genetic predisposition

PubMed Central

Mikropoulos, Christos; Selkirk, Christina G Hutten; Saya, Sibel; Bancroft, Elizabeth; Vertosick, Emily; Dadaev, Tokhir; Brendler, Charles; Page, Elizabeth; Dias, Alexander; Evans, D Gareth; Rothwell, Jeanette; Maehle, Lovise; Axcrona, Karol; Richardson, Kate; Eccles, Diana; Jensen, Thomas; Osther, Palle J; van Asperen, Christi J; Vasen, Hans; Kiemeney, Lambertus A; Ringelberg, Janneke; Cybulski, Cezary; Wokolorczyk, Dominika; Hart, Rachel; Glover, Wayne; Lam, Jimmy; Taylor, Louise; Salinas, Monica; Feliubadaló, Lidia; Oldenburg, Rogier; Cremers, Ruben; Verhaegh, Gerald; van Zelst-Stams, Wendy A; Oosterwijk, Jan C; Cook, Jackie; Rosario, Derek J; Buys, Saundra S; Conner, Tom; Domchek, Susan; Powers, Jacquelyn; Ausems, Margreet GEM; Teixeira, Manuel R; Maia, Sofia; Izatt, Louise; Schmutzler, Rita; Rhiem, Kerstin; Foulkes, William D; Boshari, Talia; Davidson, Rosemarie; Ruijs, Marielle; Helderman-van den Enden, Apollonia TJM; Andrews, Lesley; Walker, Lisa; Snape, Katie; Henderson, Alex; Jobson, Irene; Lindeman, Geoffrey J; Liljegren, Annelie; Harris, Marion; Adank, Muriel A; Kirk, Judy; Taylor, Amy; Susman, Rachel; Chen-Shtoyerman, Rakefet; Pachter, Nicholas; Spigelman, Allan; Side, Lucy; Zgajnar, Janez; Mora, Josefina; Brewer, Carole; Gadea, Neus; Brady, Angela F; Gallagher, David; van Os, Theo; Donaldson, Alan; Stefansdottir, Vigdis; Barwell, Julian; James, Paul A; Murphy, Declan; Friedman, Eitan; Nicolai, Nicola; Greenhalgh, Lynn; Obeid, Elias; Murthy, Vedang; Copakova, Lucia; McGrath, John; Teo, Soo-Hwang; Strom, Sara; Kast, Karin; Leongamornlert, Daniel A; Chamberlain, Anthony; Pope, Jenny; Newlin, Anna C; Aaronson, Neil; Ardern-Jones, Audrey; Bangma, Chris; Castro, Elena; Dearnaley, David; Eyfjord, Jorunn; Falconer, Alison; Foster, Christopher S; Gronberg, Henrik; Hamdy, Freddie C; Johannsson, Oskar; Khoo, Vincent; Lubinski, Jan; Grindedal, Eli Marie; McKinley, Joanne; Shackleton, Kylie; Mitra, Anita V; Moynihan, Clare; Rennert, Gad; Suri, Mohnish; Tricker, Karen; Moss, Sue; Kote-Jarai, Zsofia; Vickers, Andrew; Lilja, Hans; Helfand, Brian T; Eeles, Rosalind A

2018-01-01

Background: Prostate-specific antigen (PSA) and PSA-velocity (PSAV) have been used to identify men at risk of prostate cancer (PrCa). The IMPACT study is evaluating PSA screening in men with a known genetic predisposition to PrCa due to BRCA1/2 mutations. This analysis evaluates the utility of PSA and PSAV for identifying PrCa and high-grade disease in this cohort. Methods: PSAV was calculated using logistic regression to determine if PSA or PSAV predicted the result of prostate biopsy (PB) in men with elevated PSA values. Cox regression was used to determine whether PSA or PSAV predicted PSA elevation in men with low PSAs. Interaction terms were included in the models to determine whether BRCA status influenced the predictiveness of PSA or PSAV. Results: 1634 participants had ⩾3 PSA readings of whom 174 underwent PB and 45 PrCas diagnosed. In men with PSA >3.0 ng ml−l, PSAV was not significantly associated with presence of cancer or high-grade disease. PSAV did not add to PSA for predicting time to an elevated PSA. When comparing BRCA1/2 carriers to non-carriers, we found a significant interaction between BRCA status and last PSA before biopsy (P=0.031) and BRCA2 status and PSAV (P=0.024). However, PSAV was not predictive of biopsy outcome in BRCA2 carriers. Conclusions: PSA is more strongly predictive of PrCa in BRCA carriers than non-carriers. We did not find evidence that PSAV aids decision-making for BRCA carriers over absolute PSA value alone. PMID:29301143

Elevated CO2 and temperature increase soil C losses from a soybean-maize ecosystem.

PubMed

Black, Christopher K; Davis, Sarah C; Hudiburg, Tara W; Bernacchi, Carl J; DeLucia, Evan H

2017-01-01

Warming temperatures and increasing CO 2 are likely to have large effects on the amount of carbon stored in soil, but predictions of these effects are poorly constrained. We elevated temperature (canopy: +2.8 °C; soil growing season: +1.8 °C; soil fallow: +2.3 °C) for 3 years within the 9th-11th years of an elevated CO 2 (+200 ppm) experiment on a maize-soybean agroecosystem, measured respiration by roots and soil microbes, and then used a process-based ecosystem model (DayCent) to simulate the decadal effects of warming and CO 2 enrichment on soil C. Both heating and elevated CO 2 increased respiration from soil microbes by ~20%, but heating reduced respiration from roots and rhizosphere by ~25%. The effects were additive, with no heat × CO 2 interactions. Particulate organic matter and total soil C declined over time in all treatments and were lower in elevated CO 2 plots than in ambient plots, but did not differ between heat treatments. We speculate that these declines indicate a priming effect, with increased C inputs under elevated CO 2 fueling a loss of old soil carbon. Model simulations of heated plots agreed with our observations and predicted loss of ~15% of soil organic C after 100 years of heating, but simulations of elevated CO 2 failed to predict the observed C losses and instead predicted a ~4% gain in soil organic C under any heating conditions. Despite model uncertainty, our empirical results suggest that combined, elevated CO 2 and temperature will lead to long-term declines in the amount of carbon stored in agricultural soils. © 2016 John Wiley & Sons Ltd.

Effects of uncertain topographic input data on two-dimensional flow modeling in a gravel-bed river

USGS Publications Warehouse

Legleiter, C.J.; Kyriakidis, P.C.; McDonald, R.R.; Nelson, J.M.

2011-01-01

Many applications in river research and management rely upon two-dimensional (2D) numerical models to characterize flow fields, assess habitat conditions, and evaluate channel stability. Predictions from such models are potentially highly uncertain due to the uncertainty associated with the topographic data provided as input. This study used a spatial stochastic simulation strategy to examine the effects of topographic uncertainty on flow modeling. Many, equally likely bed elevation realizations for a simple meander bend were generated and propagated through a typical 2D model to produce distributions of water-surface elevation, depth, velocity, and boundary shear stress at each node of the model's computational grid. Ensemble summary statistics were used to characterize the uncertainty associated with these predictions and to examine the spatial structure of this uncertainty in relation to channel morphology. Simulations conditioned to different data configurations indicated that model predictions became increasingly uncertain as the spacing between surveyed cross sections increased. Model sensitivity to topographic uncertainty was greater for base flow conditions than for a higher, subbankfull flow (75% of bankfull discharge). The degree of sensitivity also varied spatially throughout the bend, with the greatest uncertainty occurring over the point bar where the flow field was influenced by topographic steering effects. Uncertain topography can therefore introduce significant uncertainty to analyses of habitat suitability and bed mobility based on flow model output. In the presence of such uncertainty, the results of these studies are most appropriately represented in probabilistic terms using distributions of model predictions derived from a series of topographic realizations. Copyright 2011 by the American Geophysical Union.

Soluble CD40L Is a Useful Marker to Predict Future Strokes in Patients With Minor Stroke and Transient Ischemic Attack.

PubMed

Li, Jiejie; Wang, Yilong; Lin, Jinxi; Wang, David; Wang, Anxin; Zhao, Xingquan; Liu, Liping; Wang, Chunxue; Wang, Yongjun

2015-07-01

Elevated soluble CD40 ligand (sCD40L) was shown to be related to cardiovascular events, but the role of sCD40L in predicting recurrent stroke remains unclear. Baseline sCD40L levels were measured in 3044 consecutive patients with acute minor stroke and transient ischemic attack, who had previously been enrolled in the Clopidogrel in High-Risk Patients With Acute Nondisabling Cerebrovascular Events (CHANCE) trial. Cox proportional-hazards model was used to assess the association of sCD40L with recurrent stroke. Patients in the top tertile of sCD40L levels had increased risk of recurrent stroke comparing with those in the bottom tertile, after adjusted for conventional confounding factors (hazard ratio, 1.49; 95% confidence interval, 1.11-2.00; P=0.008). The patients with elevated levels of both sCD40L and high-sensitive C-reactive protein also had increased risk of recurrent stroke (hazard ratio, 1.81; 95% confidence interval, 1.23-2.68; P=0.003). Elevated sCD40L levels independently predict recurrent stroke in patients with minor stroke and transient ischemic attack. URL: http://www.clinicaltrials.gov. Unique identifier: NCT00979589. © 2015 American Heart Association, Inc.

Seed origin and warming constrain lodgepole pine recruitment, slowing the pace of population range shifts

DOE Office of Scientific and Technical Information (OSTI.GOV)

Conlisk, Erin; Castanha, Cristina; Germino, Matthew J.

Understanding how climate warming will affect the demographic rates of different ecotypes is critical to predicting shifts in species distributions. In this study, we present results from a common garden, climate change experiment in which we measured seedling recruitment of lodgepole pine, a widespread North American conifer that is also planted globally. Seeds from a low-elevation provenance had more than three-fold greater recruitment to their third year than seeds from a high-elevation provenance across sites within and above its native elevation range and across climate manipulations. Heating halved recruitment to the third year of both low- and high-elevation seed sourcesmore » across the elevation gradient, while watering more than doubled recruitment, alleviating some of the negative effects of heating. Demographic models based on recruitment data from the climate manipulations and long-term observations of adult populations revealed that heating could effectively halt modeled upslope range expansion except when combined with watering. Simulating fire and rapid postfire forest recovery at lower elevations accelerated lodgepole pine expansion into the alpine, but did not alter final abundance rankings among climate scenarios. Regardless of climate scenario, greater recruitment of low-elevation seeds compensated for longer dispersal distances to treeline, assuming colonization was allowed to proceed over multiple centuries. In conclusion, our results show that ecotypes from lower elevations within a species’ range could enhance recruitment and facilitate upslope range shifts with climate change.« less

Seed origin and warming constrain lodgepole pine recruitment, slowing the pace of population range shifts

DOE PAGES

Conlisk, Erin; Castanha, Cristina; Germino, Matthew J.; ...

2017-07-26

Understanding how climate warming will affect the demographic rates of different ecotypes is critical to predicting shifts in species distributions. In this study, we present results from a common garden, climate change experiment in which we measured seedling recruitment of lodgepole pine, a widespread North American conifer that is also planted globally. Seeds from a low-elevation provenance had more than three-fold greater recruitment to their third year than seeds from a high-elevation provenance across sites within and above its native elevation range and across climate manipulations. Heating halved recruitment to the third year of both low- and high-elevation seed sourcesmore » across the elevation gradient, while watering more than doubled recruitment, alleviating some of the negative effects of heating. Demographic models based on recruitment data from the climate manipulations and long-term observations of adult populations revealed that heating could effectively halt modeled upslope range expansion except when combined with watering. Simulating fire and rapid postfire forest recovery at lower elevations accelerated lodgepole pine expansion into the alpine, but did not alter final abundance rankings among climate scenarios. Regardless of climate scenario, greater recruitment of low-elevation seeds compensated for longer dispersal distances to treeline, assuming colonization was allowed to proceed over multiple centuries. In conclusion, our results show that ecotypes from lower elevations within a species’ range could enhance recruitment and facilitate upslope range shifts with climate change.« less

Direct numerical simulations of temporally developing hydrocarbon shear flames at elevated pressure: effects of the equation of state and the unity Lewis number assumption

NASA Astrophysics Data System (ADS)

Korucu, Ayse; Miller, Richard

2016-11-01

Direct numerical simulations (DNS) of temporally developing shear flames are used to investigate both equation of state (EOS) and unity-Lewis (Le) number assumption effects in hydrocarbon flames at elevated pressure. A reduced Kerosene / Air mechanism including a semi-global soot formation/oxidation model is used to study soot formation/oxidation processes in a temporarlly developing hydrocarbon shear flame operating at both atmospheric and elevated pressures for the cubic Peng-Robinson real fluid EOS. Results are compared to simulations using the ideal gas law (IGL). The results show that while the unity-Le number assumption with the IGL EOS under-predicts the flame temperature for all pressures, with the real fluid EOS it under-predicts the flame temperature for 1 and 35 atm and over-predicts the rest. The soot mass fraction, Ys, is only under-predicted for the 1 atm flame for both IGL and real gas fluid EOS models. While Ys is over-predicted for elevated pressures with IGL EOS, for the real gas EOS Ys's predictions are similar to results using a non-unity Le model derived from non-equilibrium thermodynamics and real diffusivities. Adopting the unity Le assumption is shown to cause misprediction of Ys, the flame temperature, and the mass fractions of CO, H and OH.

Using Remote Sensing and High-Resolution Digital Elevation Models to Identify Potential Erosional Hotspots Along River Channels During High Discharge Storm Events

NASA Astrophysics Data System (ADS)

Orland, E. D.; Amidon, W. H.

2017-12-01

As global warming intensifies, large precipitation events and associated floods are becoming increasingly common. Channel adjustments during floods can occur by both erosion and deposition of sediment, often damaging infrastructure in the process. There is thus a need for predictive models that can help managers identify river reaches that are most prone to adjustment during storms. Because rivers in post-glacial landscapes often flow over a mixture of bedrock and alluvial substrates, the identification of bedrock vs. alluvial channel reaches is an important first step in predicting vulnerability to channel adjustment during flood events, especially because bedrock channels are unlikely to adjust significantly, even during floods. This study develops a semi-automated approach to predicting channel substrate using a high-resolution LiDAR-derived digital elevation model (DEM). The study area is the Middlebury River in Middlebury, VT-a well-studied watershed with a wide variety of channel substrates, including reaches with documented channel adjustments during recent flooding events. Multiple metrics were considered for reference—such as channel width and drainage area—but the study utilized channel slope as a key parameter for identifying morphological variations within the Middlebury River. Using data extracted from the DEM, a power law was fit to selected slope and drainage area values for each branch in order to model idealized slope-drainage area relationships, which were then compared with measured slope-drainage area relationships. Differences in measured slope minus predicted slope (called delta-slope) are shown to help predict river channel substrate. Compared with field observations, higher delta-slope values correlate with more stable, boulder rich channels or bedrock gorges; conversely the lowest delta-slope values correlate with flat, sediment rich alluvial channels. The delta-slope metric thus serves as a reliable first-order predictor of channel substrate in the Middlebury River, which in turn can be used to help identify local reaches that are most vulnerable to channel adjustment during large flood events.

Real-Time Prediction of Temperature Elevation During Robotic Bone Drilling Using the Torque Signal.

PubMed

Feldmann, Arne; Gavaghan, Kate; Stebinger, Manuel; Williamson, Tom; Weber, Stefan; Zysset, Philippe

2017-09-01

Bone drilling is a surgical procedure commonly required in many surgical fields, particularly orthopedics, dentistry and head and neck surgeries. While the long-term effects of thermal bone necrosis are unknown, the thermal damage to nerves in spinal or otolaryngological surgeries might lead to partial paralysis. Previous models to predict the temperature elevation have been suggested, but were not validated or have the disadvantages of computation time and complexity which does not allow real time predictions. Within this study, an analytical temperature prediction model is proposed which uses the torque signal of the drilling process to model the heat production of the drill bit. A simple Green's disk source function is used to solve the three dimensional heat equation along the drilling axis. Additionally, an extensive experimental study was carried out to validate the model. A custom CNC-setup with a load cell and a thermal camera was used to measure the axial drilling torque and force as well as temperature elevations. Bones with different sets of bone volume fraction were drilled with two drill bits ([Formula: see text]1.8 mm and [Formula: see text]2.5 mm) and repeated eight times. The model was calibrated with 5 of 40 measurements and successfully validated with the rest of the data ([Formula: see text]C). It was also found that the temperature elevation can be predicted using only the torque signal of the drilling process. In the future, the model could be used to monitor and control the drilling process of surgeries close to vulnerable structures.

Forest response to elevated CO2 is conserved across a broad range of productivity

Treesearch

R. Norby; E. DeLucia; B. Gielen; C. Calfapietra; C. Giardina; J. King; J. Ledford; H. McCarthy; D. Moore; R. Ceulemans; P. De Angelis; A. C. Finzi; D. F. Karnosky; M. E. Kubiske; M. Lukac; K. S. Pregitzer; G. E. Scarascia-Mugnozza; W. Schlesinger and R. Oren.

2005-01-01

Climate change predictions derived from coupled carbon-climate models are highly dependent on assumptions about feedbacks between the biosphere and atmosphere. One critical feedback occurs if C uptake by the biosphere increases in response to the fossil-fuel driven increase in atmospheric [CO2] ("CO2 fertilization...

The need for sustained and integrated high-resolution mapping of dynamic coastal environments

USGS Publications Warehouse

Stockdon, Hilary F.; Lillycrop, Jeff W.; Howd, Peter A.; Wozencraft, Jennifer M.

2007-01-01

The evolution of the United States' coastal zone response to both human activities and natural processes is dynamic. Coastal resource and population protection requires understanding, in detail, the processes needed for change as well as the physical setting. Sustained coastal area mapping allows change to be documented and baseline conditions to be established, as well as future behavior to be predicted in conjunction with physical process models. Hyperspectral imagers and airborne lidars, as well as other recent mapping technology advances, allow rapid national scale land use information and high-resolution elevation data collection. Coastal hazard risk evaluation has critical dependence on these rich data sets. A fundamental storm surge model parameter in predicting flooding location, for example, is coastal elevation data, and a foundation in identifying the most vulnerable populations and resources is land use maps. A wealth of information for physical change process study, coastal resource and community management and protection, and coastal area hazard vulnerability determination, is available in a comprehensive national coastal mapping plan designed to take advantage of recent mapping technology progress and data distribution, management, and collection.

Temperature Measurement and Numerical Prediction in Machining Inconel 718

PubMed Central

Tapetado, Alberto; Vázquez, Carmen; Miguélez, Henar

2017-01-01

Thermal issues are critical when machining Ni-based superalloy components designed for high temperature applications. The low thermal conductivity and extreme strain hardening of this family of materials results in elevated temperatures around the cutting area. This elevated temperature could lead to machining-induced damage such as phase changes and residual stresses, resulting in reduced service life of the component. Measurement of temperature during machining is crucial in order to control the cutting process, avoiding workpiece damage. On the other hand, the development of predictive tools based on numerical models helps in the definition of machining processes and the obtainment of difficult to measure parameters such as the penetration of the heated layer. However, the validation of numerical models strongly depends on the accurate measurement of physical parameters such as temperature, ensuring the calibration of the model. This paper focuses on the measurement and prediction of temperature during the machining of Ni-based superalloys. The temperature sensor was based on a fiber-optic two-color pyrometer developed for localized temperature measurements in turning of Inconel 718. The sensor is capable of measuring temperature in the range of 250 to 1200 °C. Temperature evolution is recorded in a lathe at different feed rates and cutting speeds. Measurements were used to calibrate a simplified numerical model for prediction of temperature fields during turning. PMID:28665312

Probabilistic prediction of barrier-island response to hurricanes

USGS Publications Warehouse

Plant, Nathaniel G.; Stockdon, Hilary F.

2012-01-01

Prediction of barrier-island response to hurricane attack is important for assessing the vulnerability of communities, infrastructure, habitat, and recreational assets to the impacts of storm surge, waves, and erosion. We have demonstrated that a conceptual model intended to make qualitative predictions of the type of beach response to storms (e.g., beach erosion, dune erosion, dune overwash, inundation) can be reformulated in a Bayesian network to make quantitative predictions of the morphologic response. In an application of this approach at Santa Rosa Island, FL, predicted dune-crest elevation changes in response to Hurricane Ivan explained about 20% to 30% of the observed variance. An extended Bayesian network based on the original conceptual model, which included dune elevations, storm surge, and swash, but with the addition of beach and dune widths as input variables, showed improved skill compared to the original model, explaining 70% of dune elevation change variance and about 60% of dune and shoreline position change variance. This probabilistic approach accurately represented prediction uncertainty (measured with the log likelihood ratio), and it outperformed the baseline prediction (i.e., the prior distribution based on the observations). Finally, sensitivity studies demonstrated that degrading the resolution of the Bayesian network or removing data from the calibration process reduced the skill of the predictions by 30% to 40%. The reduction in skill did not change conclusions regarding the relative importance of the input variables, and the extended model's skill always outperformed the original model.

Transport and Dispersion Model Predictions of Elevated Source Tracer Experiments in the Copenhagen Area: Comparisons of Hazard Prediction and Assessment Capability (HPAC) and National Atmospheric Release Advisory Center (NARAC) Emergency Response Model Predictions

DTIC Science & Technology

2006-07-01

Blue --) and NARAC (Red -) for two elevated releases ( MvM 3 and MvM 15) considered in the model-to-model study [2]. MvM 3 was a gas release (SF6...carried out under stable conditions with a boundary layer height of 100 m and release height of 80 m, while MvM 15 was a particle release carried out...release scenarios: MvM 3 at 30 and 60 Minutes and MvM 15 at 120 and 180 minutes. Each release shows significant NARAC underpredictions with

Modeling forest ecosystem responses to elevated carbon dioxide and ozone using artificial neural networks.

PubMed

Larsen, Peter E; Cseke, Leland J; Miller, R Michael; Collart, Frank R

2014-10-21

Rising atmospheric levels of carbon dioxide and ozone will impact productivity and carbon sequestration in forest ecosystems. The scale of this process and the potential economic consequences provide an incentive for the development of models to predict the types and rates of ecosystem responses and feedbacks that result from and influence of climate change. In this paper, we use phenotypic and molecular data derived from the Aspen Free Air CO2 Enrichment site (Aspen-FACE) to evaluate modeling approaches for ecosystem responses to changing conditions. At FACE, it was observed that different aspen clones exhibit clone-specific responses to elevated atmospheric levels of carbon dioxide and ozone. To identify the molecular basis for these observations, we used artificial neural networks (ANN) to examine above and below-ground community phenotype responses to elevated carbon dioxide, elevated ozone and gene expression profiles. The aspen community models generated using this approach identified specific genes and subnetworks of genes associated with variable sensitivities for aspen clones. The ANN model also predicts specific co-regulated gene clusters associated with differential sensitivity to elevated carbon dioxide and ozone in aspen species. The results suggest ANN is an effective approach to predict relevant gene expression changes resulting from environmental perturbation and provides useful information for the rational design of future biological experiments. Copyright © 2014 Elsevier Ltd. All rights reserved.

A comparison between index of entropy and catastrophe theory methods for mapping groundwater potential in an arid region.

PubMed

Al-Abadi, Alaa M; Shahid, Shamsuddin

2015-09-01

In this study, index of entropy and catastrophe theory methods were used for demarcating groundwater potential in an arid region using weighted linear combination techniques in geographical information system (GIS) environment. A case study from Badra area in the eastern part of central of Iraq was analyzed and discussed. Six factors believed to have influence on groundwater occurrence namely elevation, slope, aquifer transmissivity and storativity, soil, and distance to fault were prepared as raster thematic layers to facility integration into GIS environment. The factors were chosen based on the availability of data and local conditions of the study area. Both techniques were used for computing weights and assigning ranks vital for applying weighted linear combination approach. The results of application of both modes indicated that the most influential groundwater occurrence factors were slope and elevation. The other factors have relatively smaller values of weights implying that these factors have a minor role in groundwater occurrence conditions. The groundwater potential index (GPI) values for both models were classified using natural break classification scheme into five categories: very low, low, moderate, high, and very high. For validation of generated GPI, the relative operating characteristic (ROC) curves were used. According to the obtained area under the curve, the catastrophe model with 78 % prediction accuracy was found to perform better than entropy model with 77 % prediction accuracy. The overall results indicated that both models have good capability for predicting groundwater potential zones.

Combining Satellite Measurements and Numerical Flood Prediction Models to Save Lives and Property from Flooding

NASA Astrophysics Data System (ADS)

Saleh, F.; Garambois, P. A.; Biancamaria, S.

2017-12-01

Floods are considered the major natural threats to human societies across all continents. Consequences of floods in highly populated areas are more dramatic with losses of human lives and substantial property damage. This risk is projected to increase with the effects of climate change, particularly sea-level rise, increasing storm frequencies and intensities and increasing population and economic assets in such urban watersheds. Despite the advances in computational resources and modeling techniques, significant gaps exist in predicting complex processes and accurately representing the initial state of the system. Improving flood prediction models and data assimilation chains through satellite has become an absolute priority to produce accurate flood forecasts with sufficient lead times. The overarching goal of this work is to assess the benefits of the Surface Water Ocean Topography SWOT satellite data from a flood prediction perspective. The near real time methodology is based on combining satellite data from a simulator that mimics the future SWOT data, numerical models, high resolution elevation data and real-time local measurement in the New York/New Jersey area.

Mapping Critical Loads of Atmospheric Nitrogen Deposition in the Rocky Mountains, USA

NASA Astrophysics Data System (ADS)

Nanus, L.; Clow, D. W.; Stephens, V. C.; Saros, J. E.

2010-12-01

Atmospheric nitrogen (N) deposition can adversely affect sensitive aquatic ecosystems at high-elevations in the western United States. Critical loads are the amount of deposition of a given pollutant that an ecosystem can receive below which ecological effects are thought not to occur. GIS-based landscape models were used to create maps for high-elevation areas across the Rocky Mountain region showing current atmospheric deposition rates of nitrogen (N), critical loads of N, and exceedances of critical loads of N. Atmospheric N deposition maps for the region were developed at 400 meter resolution using gridded precipitation data and spatially interpolated chemical concentrations in rain and snow. Critical loads maps were developed based on chemical thresholds corresponding to observed ecological effects, and estimated ecosystem sensitivities calculated from basin characteristics. Diatom species assemblages were used as an indicator of ecosystem health to establish critical loads of N. Chemical thresholds (concentrations) were identified for surface waters by using a combination of in-situ growth experiments and observed spatial patterns in surface-water chemistry and diatom species assemblages across an N deposition gradient. Ecosystem sensitivity was estimated using a multiple-linear regression approach in which observed surface water nitrate concentrations at 530 sites were regressed against estimates of inorganic N deposition and basin characteristics (topography, soil type and amount, bedrock geology, vegetation type) to develop predictive models of surface water chemistry. Modeling results indicated that the significant explanatory variables included percent slope, soil permeability, and vegetation type (including barren land, shrub, and grassland) and were used to predict high-elevation surface water nitrate concentrations across the Rocky Mountains. Chemical threshold concentrations were substituted into an inverted form of the model equations and applied to estimate critical loads for each stream reach within a basin, from which critical loads maps were created. Atmospheric N deposition maps were overlaid on the critical loads maps to identify areas in the Rocky Mountain region where critical loads are being exceeded, or where they may do so in the future. This approach may be transferable to other high-elevation areas of the United States and the world.

Mapping SOC (Soil Organic Carbon) using LiDAR-derived vegetation indices in a random forest regression model

NASA Astrophysics Data System (ADS)

Will, R. M.; Glenn, N. F.; Benner, S. G.; Pierce, J. L.; Spaete, L.; Li, A.

2015-12-01

Quantifying SOC (Soil Organic Carbon) storage in complex terrain is challenging due to high spatial variability. Generally, the challenge is met by transforming point data to the entire landscape using surrogate, spatially-distributed, variables like elevation or precipitation. In many ecosystems, remotely sensed information on above-ground vegetation (e.g. NDVI) is a good predictor of below-ground carbon stocks. In this project, we are attempting to improve this predictive method by incorporating LiDAR-derived vegetation indices. LiDAR provides a mechanism for improved characterization of aboveground vegetation by providing structural parameters such as vegetation height and biomass. In this study, a random forest model is used to predict SOC using a suite of LiDAR-derived vegetation indices as predictor variables. The Reynolds Creek Experimental Watershed (RCEW) is an ideal location for a study of this type since it encompasses a strong elevation/precipitation gradient that supports lower biomass sagebrush ecosystems at low elevations and forests with more biomass at higher elevations. Sagebrush ecosystems composed of Wyoming, Low and Mountain Sagebrush have SOC values ranging from .4 to 1% (top 30 cm), while higher biomass ecosystems composed of aspen, juniper and fir have SOC values approaching 4% (top 30 cm). Large differences in SOC have been observed between canopy and interspace locations and high resolution vegetation information is likely to explain plot scale variability in SOC. Mapping of the SOC reservoir will help identify underlying controls on SOC distribution and provide insight into which processes are most important in determining SOC in semi-arid mountainous regions. In addition, airborne LiDAR has the potential to characterize vegetation communities at a high resolution and could be a tool for improving estimates of SOC at larger scales.

The Navy’s Application of Ocean Forecasting to Decision Support

DTIC Science & Technology

2014-09-01

Prediction Center (OPC) website for graphics or the National Operational Model Archive and Distribution System ( NOMADS ) for data files. Regional...inputs: » GLOBE = Global Land One-km Base Elevation » WVS = World Vector Shoreline » DBDB2 = Digital Bathymetry Data Base 2 minute resolution » DBDBV... Digital Bathymetry Data Base variable resolution Oceanography | Vol. 27, No.3130 Very High-Resolution Coastal Circulation Models Nearshore

Dormancy release of Norway spruce under climatic warming: testing ecophysiological models of bud burst with a whole-tree chamber experiment.

PubMed

Hänninen, Heikki; Slaney, Michelle; Linder, Sune

2007-02-01

Ecophysiological models predicting timing of bud burst were tested with data gathered from 40-year-old Norway spruce (Picea abies (L.) Karst.) trees growing in northern Sweden in whole-tree chambers under climatic conditions predicted to prevail in 2100. Norway spruce trees, with heights between 5 and 7 m, were enclosed in individual chambers that provided a factorial combination of ambient (365 micromol mol-1) or elevated (700 micromol mol-1) atmospheric CO2 concentration, [CO2], and ambient or elevated air temperature. Temperature elevation above ambient ranged from +2.8 degrees C in summer to +5.6 degrees C in winter. Compared with control trees, elevated air temperature hastened bud burst by 2 to 3 weeks, whereas elevated [CO2] had no effect on the timing of bud burst. A simple model based on the assumption that bud rest completion takes place on a fixed calendar day predicted timing of bud burst more accurately than two more complicated models in which bud rest completion is caused by accumulated chilling. Together with some recent studies, the results suggest that, in adult trees, some additional environmental cues besides chilling are required for bud rest completion. Although it appears that these additional factors will protect trees under predicted climatic warming conditions, increased risk of frost damage associated with earlier bud burst cannot be ruled out. Inconsistent and partially anomalous results obtained in the model fitting show that, in addition to phenological data gathered under field conditions, more specific data from growth chamber and greenhouse experiments are needed for further development and testing of the models.

Effects of oxygen on responses to heating in two lizard species sampled along an elevational gradient.

PubMed

DuBois, P Mason; Shea, Tanner K; Claunch, Natalie M; Taylor, Emily N

2017-08-01

Thermal tolerance is an important variable in predictive models about the effects of global climate change on species distributions, yet the physiological mechanisms responsible for reduced performance at high temperatures in air-breathing vertebrates are not clear. We conducted an experiment to examine how oxygen affects three variables exhibited by ectotherms as they heat-gaping threshold, panting threshold, and loss of righting response (the latter indicating the critical thermal maximum)-in two lizard species along an elevational (and therefore environmental oxygen partial pressure) gradient. Oxygen partial pressure did not impact these variables in either species. We also exposed lizards at each elevation to severely hypoxic gas to evaluate their responses to hypoxia. Severely low oxygen partial pressure treatments significantly reduced the gaping threshold, panting threshold, and critical thermal maximum. Further, under these extreme hypoxic conditions, these variables were strongly and positively related to partial pressure of oxygen. In an elevation where both species overlapped, the thermal tolerance of the high elevation species was less affected by hypoxia than that of the low elevation species, suggesting the high elevation species may be adapted to lower oxygen partial pressures. In the high elevation species, female lizards had higher thermal tolerance than males. Our data suggest that oxygen impacts the thermal tolerance of lizards, but only under severely hypoxic conditions, possibly as a result of hypoxia-induced anapyrexia. Copyright © 2017. Published by Elsevier Ltd.

A case history of using high-resolution LiDAR data to support archaeological prediction models in a low-relief area

NASA Astrophysics Data System (ADS)

Pacskó, Vivien; Székely, Balázs; Stibrányi, Máté; Koma, Zsófia

2016-04-01

Hungary is situated in the crossroad of several large-scale infrastructural pathways like transnational pipelines and transcontinental motorways. At the same time the country is rich in known and potential archaeological sites. Archaeological prediction techniques aided by remote sensing are intended to help increase preparedness for archaeological surveying and rescue activities in response to planned new infrastructural developments (e.g., a new pipeline), as they try to estimate the number of potential archaeological sites, area to be surveyed, potential cost and time needed for these activities. In very low-relief areas microtopographic forms may indicate sites, high-resolution LiDAR DTMs are suitable for their detection. Main sources of archaeological prediction models are known archaeological sites, where optimal environmental conditions of settling down existed at historic ages. Hydrological characteristics, relief, geology, vegetation cover and soil are considered to be as most important natural factors. Sorting of the factors and accuracy of the sampling differentiate our models. Resolution of an inductive model depends on the spatial properties of the integrated data: a raster data set can be generated that contains probability values and the reliability of the estimation. The information content of the predictive model is highly influenced by the resolution of the used digital terrain model (DTM): its derivatives (slope, aspect, topographic features) are important inputs of the modelling. The quality of the DTM is even more important in low-relief areas as microtopographic features may indicate archaeological sites. The conventional digital elevation models (SRTM, ASTER GDEM) provide unsatisfying resolution (both in horizontal and vertical senses) as they are rather digital surface models containing the vegetation and the built-up structures. Processed multiecho LiDAR data can be used instead. Our study area is situated in the foothills of the Transdanubian Range characterized by NNW-SSE directed valleys. One of the largest valleys is a conspicuously straight valley section of the River Sárvíz between Székesfehérvár and Szekszárd. Archaeological surveys revealed various settlement remains since the Neolithic. LiDAR data acquisition has been carried out in the framework of an EUFAR project supported by the European Union. Although the weather conditions were not optimal during the flight, sophisticated processing (carried out with of OPALS software) removed most of the artifacts. The resulting 1 m resolution digital terrain model (DTM) has been used to out. This DTM and the known archaeological site locations were integrated in a GIS system for qualitative and quantitative analysis. The processing aimed at analyzing elevation patterns of archaeological sites: local microtopographic features have been outlined and local low-relief elevation data have been extracted and analysed along the Sárvíz valley. Sites have been grouped according to the age of the artifacts identified by the quick-look archaeological walkthrough surveys. The topographic context of these elevation patterns were compared to the relative relief positions of the sites. Some ages groups have confined elevation ranges that may indicate hydrological/climate dependency of the settlement site selection, whereas some long-lived sites can also be identified, typically further away from the local erosional base. Extremely low-relief areas are supposed to have had swampy or partly inundated environmental conditions in ancient times; these areas were unsuitable for human settlement for long time periods. Such areas can be typically attributed by low predictive probabilities, whereas small mounds, patches of topographic unevenness would get higher model probabilities. The final the models can be used for focused field surveys that can improve our archaeological knowledge of the area. The data used were acquired in the framework of the EUFAR ARMSRACE project (to MS), the studies were carried out in project OTKA NK83400 financed by the Hungarian Scientific Research Fund. BS contributed as an Alexander von Humboldt Research Fellow.

Differential in surface elevation change across mangrove forests in the intertidal zone

NASA Astrophysics Data System (ADS)

Fu, Haifeng; Wang, Wenqing; Ma, Wei; Wang, Mao

2018-07-01

A better understanding of surface elevation changes in different mangrove forests would improve our predictions of sea-level rise impacts, not only upon mangrove species distributions in the intertidal zone, but also on the functioning of these wetlands. Here, a two-year (2015-2017) dataset derived from 18 RSET-MH (rod surface elevation table-marker horizon) stations at Dongzhaigang Bay, Hainan, China, was analyzed to investigate how surface elevation changes differed across mangrove species zones. The current SET data indicated a rather high rate (9.6 mm y-1, on average) of surface elevation gain that was mostly consistent with that (8.1 mm y-1, on average) inferred from either the 137Cs or 210Pb dating of sediment cores. In addition, these surface elevation changes were sensitive to elevation in the intertidal zone and differed significantly between the two study sites (Sanjiang and Houpai). Mangrove species inhabiting the lower intertidal zone tended to experience greater surface elevation change at Sanjiang, which agrees with the general view that sedimentation and elevation gains are driven by elevation in the intertidal zone (i.e., greater when positioned lower in the intertidal profile). However, at Houpai, both surface elevation change and surface accretion showed the opposite trend (i.e., greater when positioned higher in the intertidal profile). This study's results indicate that the pattern of surface elevation changes across the intertidal profile maybe inconsistent due to intricate biophysical controls. Therefore, instead of using a constant rate, models should presume a topography that evolves at differing rates of surface elevation change in different species zones across the intertidal profile when predicting the impacts of sea-level rise on mangrove distributions.

Season-ahead water quality forecasts for the Schuylkill River, Pennsylvania

NASA Astrophysics Data System (ADS)

Block, P. J.; Leung, K.

2013-12-01

Anticipating and preparing for elevated water quality parameter levels in critical water sources, using weather forecasts, is not uncommon. In this study, we explore the feasibility of extending this prediction scale to a season-ahead for the Schuylkill River in Philadelphia, utilizing both statistical and dynamical prediction models, to characterize the season. This advance information has relevance for recreational activities, ecosystem health, and water treatment, as the Schuylkill provides 40% of Philadelphia's water supply. The statistical model associates large-scale climate drivers with streamflow and water quality parameter levels; numerous variables from NOAA's CFSv2 model are evaluated for the dynamical approach. A multi-model combination is also assessed. Results indicate moderately skillful prediction of average summertime total coliform and wintertime turbidity, using season-ahead oceanic and atmospheric variables, predominantly from the North Atlantic Ocean. Models predicting the number of elevated turbidity events across the wintertime season are also explored.

Predictive habitat models derived from nest-box occupancy for the endangered Carolina northern flying squirrel in the southern Appalachians

Treesearch

W. Mark Ford; Andrew M. Evans; Richard H. Odom; Jane L. Rodrigue; Christine A. Kelly; Nicole Abaid; Corinne A. Diggins; Douglas Newcomb

2015-01-01

In the southern Appalachians, artificial nest-boxes are used to survey for the endangered Carolina northern flying squirrel (CNFS; Glaucomys sabrinus coloratus), a disjunct subspecies associated with high elevation (>1385 m) forests. Using environmental parameters diagnostic of squirrel habitat, we created 35 a priori occupancy...

An integrated model of environmental effects on growth, carbohydrate balance, and mortality of Pinus ponderosa forests in the southern Rocky Mountains.

PubMed

Tague, Christina L; McDowell, Nathan G; Allen, Craig D

2013-01-01

Climate-induced tree mortality is an increasing concern for forest managers around the world. We used a coupled hydrologic and ecosystem carbon cycling model to assess temperature and precipitation impacts on productivity and survival of ponderosa pine (Pinus ponderosa). Model predictions were evaluated using observations of productivity and survival for three ponderosa pine stands located across an 800 m elevation gradient in the southern Rocky Mountains, USA, during a 10-year period that ended in a severe drought and extensive tree mortality at the lowest elevation site. We demonstrate the utility of a relatively simple representation of declines in non-structural carbohydrate (NSC) as an approach for estimating patterns of ponderosa pine vulnerability to drought and the likelihood of survival along an elevation gradient. We assess the sensitivity of simulated net primary production, NSC storage dynamics, and mortality to site climate and soil characteristics as well as uncertainty in the allocation of carbon to the NSC pool. For a fairly wide set of assumptions, the model estimates captured elevational gradients and temporal patterns in growth and biomass. Model results that best predict mortality risk also yield productivity, leaf area, and biomass estimates that are qualitatively consistent with observations across the sites. Using this constrained set of parameters, we found that productivity and likelihood of survival were equally dependent on elevation-driven variation in temperature and precipitation. Our results demonstrate the potential for a coupled hydrology-ecosystem carbon cycling model that includes a simple model of NSC dynamics to predict drought-related mortality. Given that increases in temperature and in the frequency and severity of drought are predicted for a broad range of ponderosa pine and other western North America conifer forest habitats, the model potentially has broad utility for assessing ecosystem vulnerabilities.

An integrated model of environmental effects on growth, carbohydrate balance, and mortality of Pinus ponderosa forests in the southern Rocky Mountains

USGS Publications Warehouse

Tague, Christina L.; McDowell, Nathan G.; Allen, Craig D.

2013-01-01

Climate-induced tree mortality is an increasing concern for forest managers around the world. We used a coupled hydrologic and ecosystem carbon cycling model to assess temperature and precipitation impacts on productivity and survival of ponderosa pine (Pinus ponderosa). Model predictions were evaluated using observations of productivity and survival for three ponderosa pine stands located across an 800 m elevation gradient in the southern Rocky Mountains, USA, during a 10-year period that ended in a severe drought and extensive tree mortality at the lowest elevation site. We demonstrate the utility of a relatively simple representation of declines in non-structural carbohydrate (NSC) as an approach for estimating patterns of ponderosa pine vulnerability to drought and the likelihood of survival along an elevation gradient. We assess the sensitivity of simulated net primary production, NSC storage dynamics, and mortality to site climate and soil characteristics as well as uncertainty in the allocation of carbon to the NSC pool. For a fairly wide set of assumptions, the model estimates captured elevational gradients and temporal patterns in growth and biomass. Model results that best predict mortality risk also yield productivity, leaf area, and biomass estimates that are qualitatively consistent with observations across the sites. Using this constrained set of parameters, we found that productivity and likelihood of survival were equally dependent on elevation-driven variation in temperature and precipitation. Our results demonstrate the potential for a coupled hydrology-ecosystem carbon cycling model that includes a simple model of NSC dynamics to predict drought-related mortality. Given that increases in temperature and in the frequency and severity of drought are predicted for a broad range of ponderosa pine and other western North America conifer forest habitats, the model potentially has broad utility for assessing ecosystem vulnerabilities.

An Integrated Model of Environmental Effects on Growth, Carbohydrate Balance, and Mortality of Pinus ponderosa Forests in the Southern Rocky Mountains

PubMed Central

Tague, Christina L.; McDowell, Nathan G.; Allen, Craig D.

2013-01-01

Climate-induced tree mortality is an increasing concern for forest managers around the world. We used a coupled hydrologic and ecosystem carbon cycling model to assess temperature and precipitation impacts on productivity and survival of ponderosa pine (Pinus ponderosa). Model predictions were evaluated using observations of productivity and survival for three ponderosa pine stands located across an 800 m elevation gradient in the southern Rocky Mountains, USA, during a 10-year period that ended in a severe drought and extensive tree mortality at the lowest elevation site. We demonstrate the utility of a relatively simple representation of declines in non-structural carbohydrate (NSC) as an approach for estimating patterns of ponderosa pine vulnerability to drought and the likelihood of survival along an elevation gradient. We assess the sensitivity of simulated net primary production, NSC storage dynamics, and mortality to site climate and soil characteristics as well as uncertainty in the allocation of carbon to the NSC pool. For a fairly wide set of assumptions, the model estimates captured elevational gradients and temporal patterns in growth and biomass. Model results that best predict mortality risk also yield productivity, leaf area, and biomass estimates that are qualitatively consistent with observations across the sites. Using this constrained set of parameters, we found that productivity and likelihood of survival were equally dependent on elevation-driven variation in temperature and precipitation. Our results demonstrate the potential for a coupled hydrology-ecosystem carbon cycling model that includes a simple model of NSC dynamics to predict drought-related mortality. Given that increases in temperature and in the frequency and severity of drought are predicted for a broad range of ponderosa pine and other western North America conifer forest habitats, the model potentially has broad utility for assessing ecosystem vulnerabilities. PMID:24282532

Ecophysiological importance of cloud immersion in a relic spruce-fir forest at elevational limits, southern Appalachian Mountains, USA.

PubMed

Berry, Z Carter; Smith, William K

2013-11-01

Climate warming predicts changes to the frequency and height of cloud-immersion events in mountain communities. Threatened southern Appalachian spruce-fir forests have been suggested to persist because of frequent periods of cloud immersion. These relic forests exist on only seven mountaintop areas, grow only above ca. 1,500 m elevation (maximum 2,037 m), and harbor the endemic Abies fraseri. To predict future distribution, we examined the ecophysiological effects of cloud immersion on saplings of A. fraseri and Picea rubens at their upper and lower elevational limits. Leaf photosynthesis, conductance, transpiration, xylem water potentials, and general abiotic variables were measured simultaneously on individuals at the top (1,960 m) and bottom (1,510 m) of their elevation limits on numerous clear and cloud-immersed days throughout the growing season. The high elevation sites had 1.5 as many cloud-immersed days (75 % of days) as the low elevation sites (56 % of days). Cloud immersion resulted in higher photosynthesis, leaf conductance, and xylem water potentials, particularly during afternoon measurements. Leaf conductance remained higher throughout the day with corresponding increases in photosynthesis and transpiration, despite low photon flux density levels, leading to an increase in water potentials from morning to afternoon. The endemic A. fraseri had a greater response in carbon gain and water balance in response to cloud immersion. Climate models predict warmer temperatures with a decrease in the frequency of cloud immersion for this region, leading to an environment on these peaks similar to elevations where spruce-fir communities currently do not exist. Because spruce-fir communities may rely on cloud immersion for improved carbon gain and water conservation, an upslope shift is likely if cloud ceilings rise. Their ultimate survival will likely depend on the magnitude of changes in cloud regimes.

Developing a topographic model to predict the northern hardwood forest type within Carolina northern flying squirrel (Glaucomys sabrinus coloratus) recovery areas of the southern Appalachians

USGS Publications Warehouse

Evans, Andrew; Odom, Richard H.; Resler, Lynn M.; Ford, W. Mark; Prisley, Stephen

2014-01-01

The northern hardwood forest type is an important habitat component for the endangered Carolina northern flying squirrel (CNFS; Glaucomys sabrinus coloratus) for den sites and corridor habitats between boreo-montane conifer patches foraging areas. Our study related terrain data to presence of northern hardwood forest type in the recovery areas of CNFS in the southern Appalachian Mountains of western North Carolina, eastern Tennessee, and southwestern Virginia. We recorded overstory species composition and terrain variables at 338 points, to construct a robust, spatially predictive model. Terrain variables analyzed included elevation, aspect, slope gradient, site curvature, and topographic exposure. We used an information-theoretic approach to assess seven models based on associations noted in existing literature as well as an inclusive global model. Our results indicate that, on a regional scale, elevation, aspect, and topographic exposure index (TEI) are significant predictors of the presence of the northern hardwood forest type in the southern Appalachians. Our elevation + TEI model was the best approximating model (the lowest AICc score) for predicting northern hardwood forest type correctly classifying approximately 78% of our sample points. We then used these data to create region-wide predictive maps of the distribution of the northern hardwood forest type within CNFS recovery areas.

A Systematic Review of Global Drivers of Ant Elevational Diversity

PubMed Central

Szewczyk, Tim; McCain, Christy M.

2016-01-01

Ant diversity shows a variety of patterns across elevational gradients, though the patterns and drivers have not been evaluated comprehensively. In this systematic review and reanalysis, we use published data on ant elevational diversity to detail the observed patterns and to test the predictions and interactions of four major diversity hypotheses: thermal energy, the mid-domain effect, area, and the elevational climate model. Of sixty-seven published datasets from the literature, only those with standardized, comprehensive sampling were used. Datasets included both local and regional ant diversity and spanned 80° in latitude across six biogeographical provinces. We used a combination of simulations, linear regressions, and non-parametric statistics to test multiple quantitative predictions of each hypothesis. We used an environmentally and geometrically constrained model as well as multiple regression to test their interactions. Ant diversity showed three distinct patterns across elevations: most common were hump-shaped mid-elevation peaks in diversity, followed by low-elevation plateaus and monotonic decreases in the number of ant species. The elevational climate model, which proposes that temperature and precipitation jointly drive diversity, and area were partially supported as independent drivers. Thermal energy and the mid-domain effect were not supported as primary drivers of ant diversity globally. The interaction models supported the influence of multiple drivers, though not a consistent set. In contrast to many vertebrate taxa, global ant elevational diversity patterns appear more complex, with the best environmental model contingent on precipitation levels. Differences in ecology and natural history among taxa may be crucial to the processes influencing broad-scale diversity patterns. PMID:27175999

Improved global prediction of 300 nautical mile mean free air anomalies

NASA Technical Reports Server (NTRS)

Cruz, J. Y.

1982-01-01

Current procedures used for the global prediction of 300nm mean anomalies starting from known values of 1 deg by 1 deg mean anomalies yield unreasonable prediction results when applied to 300nm blocks which have a rapidly varying gravity anomaly field and which contain relatively few observed 60nm blocks. Improvement of overall 300nm anomaly prediction is first achieved by using area-weighted as opposed to unweighted averaging of the 25 generated 60nm mean anomalies inside the 300nm block. Then, improvement of prediction over rough 300nm blocks is realized through the use of fully known 1 deg by 1 deg mean elevations, taking advantage of the correlation that locally exists between 60nm mean anomalies and 60nm mean elevations inside the 300nm block. An improved prediction model which adapts itself to the roughness of the local anomaly field is found to be the model of Least Squares Collocation with systematic parameters, the systematic parameter being the slope b which is a type of Bouguer slope expressing the correlation that locally exists between 60nm mean anomalies and 60nm mean elevations.

The potential distribution of Phlebotomus papatasi (Diptera: Psychodidae) in Libya based on ecological niche model.

PubMed

Abdel-Dayem, M S; Annajar, B B; Hanafi, H A; Obenauer, P J

2012-05-01

The increased cases of cutaneous leishmaniasis vectored by Phlebotomus papatasi (Scopoli) in Libya have driven considerable effort to develop a predictive model for the potential geographical distribution of this disease. We collected adult P. papatasi from 17 sites in Musrata and Yefern regions of Libya using four different attraction traps. Our trap results and literature records describing the distribution of P. papatasi were incorporated into a MaxEnt algorithm prediction model that used 22 environmental variables. The model showed a high performance (AUC = 0.992 and 0.990 for training and test data, respectively). High suitability for P. papatasi was predicted to be largely confined to the coast at altitudes <600 m. Regions south of 300 degrees N latitude were calculated as unsuitable for this species. Jackknife analysis identified precipitation as having the most significant predictive power, while temperature and elevation variables were less influential. The National Leishmaniasis Control Program in Libya may find this information useful in their efforts to control zoonotic cutaneous leishmaniasis. Existing records are strongly biased toward a few geographical regions, and therefore, further sand fly collections are warranted that should include documentation of such factors as soil texture and humidity, land cover, and normalized difference vegetation index (NDVI) data to increase the model's predictive power.

Topographic, latitudinal and climatic distribution of Pinus coulteri: geographic range limits are not at the edge of the climate envelope

USGS Publications Warehouse

Chardon, Nathalie I.; Cornwell, William K.; Flint, Lorraine E.; Flint, Alan L.; Ackerly, David D.

2015-01-01

With changing climate, many species are projected to move poleward or to higher elevations to track suitable climates. The prediction that species will move poleward assumes that geographically marginal populations are at the edge of the species' climatic range. We studied Pinus coulteri from the center to the northern (poleward) edge of its range, and examined three scenarios regarding the relationship between the geographic and climatic margins of a species' range. We used herbarium and iNaturalist.org records to identify P. coulteri sites, generated a species distribution model based on temperature, precipitation, climatic water deficit, and actual evapotranspiration, and projected suitability under future climate scenarios. In fourteen populations from the central to northern portions of the range, we conducted field studies and recorded elevation, slope and aspect (to estimate solar insolation) to examine relationships between local and regional distributions. We found that northern populations of P. coulteri do not occupy the cold or wet edge of the species' climatic range; mid-latitude, high elevation populations occupy the cold margin. Aspect and insolation of P. coulteri populations changed significantly across latitudes and elevations. Unexpectedly, northern, low-elevation stands occupy north-facing aspects and receive low insolation, while central, high-elevation stands grow on more south-facing aspects that receive higher insolation. Modeled future climate suitability is projected to be highest in the central, high elevation portion of the species range, and in low-lying coastal regions under some scenarios, with declining suitability in northern areas under most future scenarios. For P. coulteri, the lack of high elevation habitat combined with a major dispersal barrier may limit northward movement in response to a warming climate. Our analyses demonstrate the importance of distinguishing geographically vs. climatically marginal populations, and the importance of quantitative analysis of the realized climate space to understand species range limits.

The prognostic utility of baseline alpha-fetoprotein for hepatocellular carcinoma patients.

PubMed

Silva, Jack P; Gorman, Richard A; Berger, Nicholas G; Tsai, Susan; Christians, Kathleen K; Clarke, Callisia N; Mogal, Harveshp; Gamblin, T Clark

2017-12-01

Alpha-fetoprotein (AFP) has a valuable role in postoperative surveillance for hepatocellular carcinoma (HCC) recurrence. The utility of pretreatment or baseline AFP remains controversial. The present study hypothesized that elevated baseline AFP levels are associated with worse overall survival in HCC patients. Adult HCC patients were identified using the National Cancer Database (2004-2013). Patients were stratified according to baseline AFP measurements into the following groups: Negative (<20), Borderline (20-199), Elevated (200-1999), and Highly Elevated (>2000). The primary outcome was overall survival (OS), which was analyzed by log-rank test and graphed using Kaplan-Meier method. Multivariate regression modeling was used to determine hazard ratios (HR) for OS. Of 41 107 patients identified, 15 809 (33.6%) were Negative. Median overall survival was highest in the Negative group, followed by Borderline, Elevated, and Highly Elevated (28.7 vs 18.9 vs 8.8 vs 3.2 months; P < 0.001). On multivariate analysis, overall survival hazard ratios for the Borderline, Elevated, and Highly Elevated groups were 1.18 (P = 0.267), 1.94 (P < 0.001), and 1.77 (P = 0.007), respectively (reference Negative). Baseline AFP independently predicted overall survival in HCC patients regardless of treatment plan. A baseline AFP value is a simple and effective method to assist in expected survival for HCC patients. © 2017 Wiley Periodicals, Inc.

Improving spatial prediction of Schistosoma haematobium prevalence in southern Ghana through new remote sensors and local water access profiles.

PubMed

Kulinkina, Alexandra V; Walz, Yvonne; Koch, Magaly; Biritwum, Nana-Kwadwo; Utzinger, Jürg; Naumova, Elena N

2018-06-04

Schistosomiasis is a water-related neglected tropical disease. In many endemic low- and middle-income countries, insufficient surveillance and reporting lead to poor characterization of the demographic and geographic distribution of schistosomiasis cases. Hence, modeling is relied upon to predict areas of high transmission and to inform control strategies. We hypothesized that utilizing remotely sensed (RS) environmental data in combination with water, sanitation, and hygiene (WASH) variables could improve on the current predictive modeling approaches. Schistosoma haematobium prevalence data, collected from 73 rural Ghanaian schools, were used in a random forest model to investigate the predictive capacity of 15 environmental variables derived from RS data (Landsat 8, Sentinel-2, and Global Digital Elevation Model) with fine spatial resolution (10-30 m). Five methods of variable extraction were tested to determine the spatial linkage between school-based prevalence and the environmental conditions of potential transmission sites, including applying the models to known human water contact locations. Lastly, measures of local water access and groundwater quality were incorporated into RS-based models to assess the relative importance of environmental and WASH variables. Predictive models based on environmental characterization of specific locations where people contact surface water bodies offered some improvement as compared to the traditional approach based on environmental characterization of locations where prevalence is measured. A water index (MNDWI) and topographic variables (elevation and slope) were important environmental risk factors, while overall, groundwater iron concentration predominated in the combined model that included WASH variables. The study helps to understand localized drivers of schistosomiasis transmission. Specifically, unsatisfactory water quality in boreholes perpetuates reliance of surface water bodies, indirectly increasing schistosomiasis risk and resulting in rapid reinfection (up to 40% prevalence six months following preventive chemotherapy). Considering WASH-related risk factors in schistosomiasis prediction can help shift the focus of control strategies from treating symptoms to reducing exposure.

Vegetation turnover and nitrogen feedback drive temperate forest carbon sequestration in response to elevated CO[2]. A multi-model structural analysis

NASA Astrophysics Data System (ADS)

Walker, A. P.; Zaehle, S.; Medlyn, B. E.; De Kauwe, M. G.; Asao, S.; Hickler, T.; Lomas, M. R.; Pak, B. C.; Parton, W. J.; Quegan, S.; Ricciuto, D. M.; Wang, Y.; Warlind, D.; Norby, R. J.

2013-12-01

Predicting forest carbon (C) sequestration requires understanding the processes leading to rates of biomass C accrual (net primary productivity; NPP) and loss (turnover). In temperate forest ecosystems, experiments and models have shown that feedback via progressive nitrogen limitation (PNL) is a key driver of NPP responses to elevated CO[2]. In this analysis we show that while still important, PNL may not be as severe a constraint on NPP as indicated by some studies and that the response of turnover to elevated CO[2] could be as important, especially in the near to medium term. Seven terrestrial ecosystem and biosphere models that couple C and N cycles with varying assumptions and complexity were used to simulate responses over 300 years to a step change in CO[2] to 550 ppmv. Simulations were run for the evergreen needleleaf Duke forest and the deciduous broadleaf Oak Ridge forest FACE experiments. Whether or not a model simulated PNL under elevated CO[2] depended on model structure and the timescale of observation. Avoiding PNL depended on mechanisms that reduced ecosystem N losses. The two key assumptions that reduced N losses were whether plant N uptake was based on plant N demand and whether ecosystem N losses (volatisation and leaching) were dependent on the concentration of N in the soil solution. Assumptions on allocation and turnover resulted in very different responses of turnover to elevated CO[2], which had profound implications for C sequestration. For example, at equilibrium CABLE2.0 predicted an increase in vegetation C sequestration despite decreased NPP, while O-CN predicted much less vegetation C sequestration than would be expected from predicted NPP increases alone. Generally elevated CO[2] favoured a shift in C partitioning towards longer lived wood biomass, which increased vegetation turnover and enhanced C sequestration. Enhanced wood partitioning was overlaid by increases or decreases in self-thinning depended on whether self-thinning was simply a function of forest structure, or structure and NPP. Self-thinning assumptions altered equilibrium C sequestration and were extremely important for the immediate transient response and near-term prediction of C sequestration.

Calibration of Two-dimensional Floodplain Modeling in the Atchafalaya River Basin Using SAR Interferometry

NASA Technical Reports Server (NTRS)

Jung, Hahn Chul; Jasinski, Michael; Kim, Jin-Woo; Shum, C. K.; Bates, Paul; Lee, Hgongki; Neal, Jeffrey; Alsdorf, Doug

2012-01-01

Two-dimensional (2D) satellite imagery has been increasingly employed to improve prediction of floodplain inundation models. However, most focus has been on validation of inundation extent, with little attention on the 2D spatial variations of water elevation and slope. The availability of high resolution Interferometric Synthetic Aperture Radar (InSAR) imagery offers unprecedented opportunity for quantitative validation of surface water heights and slopes derived from 2D hydrodynamic models. In this study, the LISFLOOD-ACC hydrodynamic model is applied to the central Atchafalaya River Basin, Louisiana, during high flows typical of spring floods in the Mississippi Delta region, for the purpose of demonstrating the utility of InSAR in coupled 1D/2D model calibration. Two calibration schemes focusing on Manning s roughness are compared. First, the model is calibrated in terms of water elevations at a single in situ gage during a 62 day simulation period from 1 April 2008 to 1 June 2008. Second, the model is calibrated in terms of water elevation changes calculated from ALOS PALSAR interferometry during 46 days of the image acquisition interval from 16 April 2008 to 1 June 2009. The best-fit models show that the mean absolute errors are 3.8 cm for a single in situ gage calibration and 5.7 cm/46 days for InSAR water level calibration. The optimum values of Manning's roughness coefficients are 0.024/0.10 for the channel/floodplain, respectively, using a single in situ gage, and 0.028/0.10 for channel/floodplain the using SAR. Based on the calibrated water elevation changes, daily storage changes within the size of approx 230 sq km of the model area are also calculated to be of the order of 107 cubic m/day during high water of the modeled period. This study demonstrates the feasibility of SAR interferometry to support 2D hydrodynamic model calibration and as a tool for improved understanding of complex floodplain hydrodynamics

The impact of dynamic topography on the bedrock elevation and volume of the Pliocene Antarctic Ice Sheet

NASA Astrophysics Data System (ADS)

Austermann, Jacqueline; Pollard, David; Mitrovica, Jerry X.; Moucha, Robert; Forte, Alessandro M.; DeConto, Robert M.

2015-04-01

Reconstructions of the Antarctic ice sheet over long timescales (i.e. Myrs) require estimates of bedrock elevation through time. Ice sheet models have accounted, with varying levels of sophistication, for changes in the bedrock elevation due to glacial isostatic adjustment (GIA), but they have neglected other processes that may perturb topography. One notable example is dynamic topography, the deflection of the solid surface of the Earth due to convective flow within the mantle. Numerically predicted changes in dynamic topography have been used to correct paleo shorelines for this departure from eustasy, but the effect of such changes on ice sheet stability is unknown. In this study we use numerical predictions of time-varying dynamic topography to reconstruct bedrock elevation below the Antarctic ice sheet during the mid Pliocene warm period (~3 Ma). Moreover, we couple this reconstruction to a three-dimensional ice sheet model to explore the impact of dynamic topography on the evolution of the Antarctic ice sheet since the Pliocene. Our modeling indicates significant uplift in the area of the Transantarctic Mountains (TAM) and the adjacent Wilkes basin. This predicted uplift, which is at the lower end of geological inferences of uplift of the TAM, implies a lower elevation of the basin in the Pliocene. Relative to simulations that do not include dynamic topography, the lower elevation leads to a smaller Antarctic Ice Sheet volume and a more significant retreat of the grounding line in the Wilkes basin, both of which are consistent with offshore sediment core data. We conclude that reconstructions of the Antarctic Ice Sheet during the mid-Pliocene warm period should be based on bedrock elevation models that include the impact of both GIA and dynamic topography.

Decadal Recruitment and Mortality of Ponderosa pine Predicted for the 21st Century Under five Downscaled Climate Change Scenarios

NASA Astrophysics Data System (ADS)

Ironside, K. E.; Cole, K. L.; Eischeid, J. K.; Garfin, G. M.; Shaw, J. D.; Cobb, N. S.

2008-12-01

Ponderosa pine (Pinus ponderosa var. scopulorum) is the dominant conifer in higher elevation regions of the southwestern United States. Because this species is so prominent, southwestern montane ecosystems will be significantly altered if this species is strongly affected by future climate changes. These changes could be highly challenging for land management agencies. In order to model the consequences of future climates, 20th Century recruitment events and mortality for ponderosa pine were characterized using measures of seasonal water balance (precipitation - potential evapotranspiration). These relationships, assuming they will remain unchanged, were then used to predict 21st Century changes in ponderosa pine occurrence in the southwest. Twenty-one AR4 IPCC General Circulation Model (GCM) A1B simulation results were ranked on their ability to simulate the later 20th Century (1950-2000 AD) precipitation seasonality, spatial patterns, and quantity in the western United States. Among the top ranked GCMs, five were selected for downscaling to a 4 km grid that represented a range in predictions in terms of changes in water balance. Predicted decadal changes in southwestern ponderosa pine for the 21st Century for these five climate change scenarios were calculated using a multiple quadratic logistic regression model. Similar models of other western tree species (Pinus edulis, Yucca brevifolia) predicted severe contractions, especially in the southern half of their ranges. However, the results for Ponderosa pine suggested future expansions throughout its range to both higher and lower elevations, as well as very significant expansions northward.

Forecasted Flood Depth Grids Providing Early Situational Awareness to FEMA during the 2017 Atlantic Hurricane Season

NASA Astrophysics Data System (ADS)

Jones, M.; Longenecker, H. E., III

2017-12-01

The 2017 hurricane season brought the unprecedented landfall of three Category 4 hurricanes (Harvey, Irma and Maria). FEMA is responsible for coordinating the federal response and recovery efforts for large disasters such as these. FEMA depends on timely and accurate depth grids to estimate hazard exposure, model damage assessments, plan flight paths for imagery acquisition, and prioritize response efforts. In order to produce riverine or coastal depth grids based on observed flooding, the methodology requires peak crest water levels at stream gauges, tide gauges, high water marks, and best-available elevation data. Because peak crest data isn't available until the apex of a flooding event and high water marks may take up to several weeks for field teams to collect for a large-scale flooding event, final observed depth grids are not available to FEMA until several days after a flood has begun to subside. Within the last decade NOAA's National Weather Service (NWS) has implemented the Advanced Hydrologic Prediction Service (AHPS), a web-based suite of accurate forecast products that provide hydrograph forecasts at over 3,500 stream gauge locations across the United States. These forecasts have been newly implemented into an automated depth grid script tool, using predicted instead of observed water levels, allowing FEMA access to flood hazard information up to 3 days prior to a flooding event. Water depths are calculated from the AHPS predicted flood stages and are interpolated at 100m spacing along NHD hydrolines within the basin of interest. A water surface elevation raster is generated from these water depths using an Inverse Distance Weighted interpolation. Then, elevation (USGS NED 30m) is subtracted from the water surface elevation raster so that the remaining values represent the depth of predicted flooding above the ground surface. This automated process requires minimal user input and produced forecasted depth grids that were comparable to post-event observed depth grids and remote sensing-derived flood extents for the 2017 hurricane season. These newly available forecasted models were used for pre-event response planning and early estimated hazard exposure counts, allowing FEMA to plan for and stand up operations several days sooner than previously possible.

Predicted high-water elevations for selected flood events at the Albert Pike Recreation Area, Ouachita National Forest

Treesearch

D.A. Marion

2012-01-01

The hydraulic characteristics are determined for the June 11, 2010, flood on the Little Missouri River at the Albert Pike Recreation Area in Arkansas. These characteristics are then used to predict the high-water elevations for the 10-, 25-, 50-, and 100-year flood events in the Loop B, C, and D Campgrounds of the recreation area. The peak discharge and related...

Bidirectional-Compounding Effects of Rumination and Negative Emotion in Predicting Impulsive Behavior: Implications for Emotional Cascades.

PubMed

Selby, Edward A; Kranzler, Amy; Panza, Emily; Fehling, Kara B

2016-04-01

Influenced by chaos theory, the emotional cascade model proposes that rumination and negative emotion may promote each other in a self-amplifying cycle that increases over time. Accordingly, exponential-compounding effects may better describe the relationship between rumination and negative emotion when they occur in impulsive persons, and predict impulsive behavior. Forty-seven community and undergraduate participants who reported frequent engagement in impulsive behaviors monitored their ruminative thoughts and negative emotion multiple times daily for two weeks using digital recording devices. Hypotheses were tested using cross-lagged mixed model analyses. Findings indicated that rumination predicted subsequent elevations in rumination that lasted over extended periods of time. Rumination and negative emotion predicted increased levels of each other at subsequent assessments, and exponential functions for these associations were supported. Results also supported a synergistic effect between rumination and negative emotion, predicting larger elevations in subsequent rumination and negative emotion than when one variable alone was elevated. Finally, there were synergistic effects of rumination and negative emotion in predicting number of impulsive behaviors subsequently reported. These findings are consistent with the emotional cascade model in suggesting that momentary rumination and negative emotion progressively propagate and magnify each other over time in impulsive people, promoting impulsive behavior. © 2014 Wiley Periodicals, Inc.

Investigating broadband variability of the TeV blazar 1ES 1959+650

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aliu, E.; Archambault, S.; Arlen, T.

We summarize broadband observations of the TeV-emitting blazar 1ES 1959 650, including optical R-band observations by the robotic telescopes Super-LOTIS and iTelescope, UV observations by Swift UVOT, X-ray observations by the Swift X-ray Telescope, high-energy gamma-ray observations with the Fermi Large Area Telescope, and very-high-energy (VHE) gamma-ray observations by VERITAS above 315 GeV, all taken between 2012 April 17 and 2012 June 1 (MJD 56034 and 56079). The contemporaneous variability of the broadband spectral energy distribution is explored in the context of a simple synchrotron self Compton (SSC) model. In the SSC emission scenario, we find that the parameters requiredmore » to represent the high state are significantly different than those in the low state. Motivated by possible evidence of gas in the vicinity of the blazar, we also investigate a reflected emission model to describe the observed variability pattern. This model assumes that the non-thermal emission from the jet is reflected by a nearby cloud of gas, allowing the reflected emission to re-enter the blob and produce an elevated gamma-ray state with no simultaneous elevated synchrotron flux. The model applied here, although not required to explain the observed variability pattern, represents one possible scenario which can describe the observations. As applied to an elevated VHE state of 66% of the Crab Nebula flux, observed on a single night during the observation period, the reflected emission scenario does not support a purely leptonic non-thermal emission mechanism. The reflected model does, however, predict a reflected photon field with sufficient energy to enable elevated gamma-ray emission via pion production with protons of energies between 10 and 100 TeV.« less

INVESTIGATING BROADBAND VARIABILITY OF THE TeV BLAZAR 1ES 1959+650

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aliu, E.; Archambault, S.; Arlen, T.

We summarize broadband observations of the TeV-emitting blazar 1ES 1959+650, including optical R-band observations by the robotic telescopes Super-LOTIS and iTelescope, UV observations by Swift Ultraviolet and Optical Telescope, X-ray observations by the Swift X-ray Telescope, high-energy gamma-ray observations with the Fermi Large Area Telescope, and very-high-energy (VHE) gamma-ray observations by VERITAS above 315 GeV, all taken between 2012 April 17 and 2012 June 1 (MJD 56034 and 56079). The contemporaneous variability of the broadband spectral energy distribution is explored in the context of a simple synchrotron self Compton (SSC) model. In the SSC emission scenario, we find that themore » parameters required to represent the high state are significantly different than those in the low state. Motivated by possible evidence of gas in the vicinity of the blazar, we also investigate a reflected emission model to describe the observed variability pattern. This model assumes that the non-thermal emission from the jet is reflected by a nearby cloud of gas, allowing the reflected emission to re-enter the blob and produce an elevated gamma-ray state with no simultaneous elevated synchrotron flux. The model applied here, although not required to explain the observed variability pattern, represents one possible scenario which can describe the observations. As applied to an elevated VHE state of 66% of the Crab Nebula flux, observed on a single night during the observation period, the reflected emission scenario does not support a purely leptonic non-thermal emission mechanism. The reflected emission model does, however, predict a reflected photon field with sufficient energy to enable elevated gamma-ray emission via pion production with protons of energies between 10 and 100 TeV.« less

INVESTIGATING BROADBAND VARIABILITY OF THE TeV BLAZAR 1ES 1959+650

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aliu, E.; Archambault, S.; Arlen, T.

We summarize broadband observations of the TeV-emitting blazar 1ES 1959+650, including optical R-band observations by the robotic telescopes Super-LOTIS and iTelescope, UV observations by Swift Ultraviolet and Optical Telescope, X-ray observations by the Swift X-ray Telescope, high-energy gamma-ray observations with the Fermi Large Area Telescope, and very-high-energy (VHE) gamma-ray observations by VERITAS above 315 GeV, all taken between 2012 April 17 and 2012 June 1 (MJD 56034 and 56079). The contemporaneous variability of the broadband spectral energy distribution is explored in the context of a simple synchrotron self Compton (SSC) model. In the SSC emission scenario, we find that themore » parameters required to represent the high state are significantly different than those in the low state. Motivated by possible evidence of gas in the vicinity of the blazar, we also investigate a reflected emission model to describe the observed variability pattern. This model assumes that the non-thermal emission from the jet is reflected by a nearby cloud of gas, allowing the reflected emission to re-enter the blob and produce an elevated gamma-ray state with no simultaneous elevated synchrotron flux. The model applied here, although not required to explain the observed variability pattern, represents one possible scenario which can describe the observations. As applied to an elevated VHE state of 66% of the Crab Nebula flux, observed on a single night during the observation period, the reflected emission scenario does not support a purely leptonic non-thermal emission mechanism. The reflected emission model does, however, predict a reflected photon field with sufficient energy to enable elevated gamma-ray emission via pion production with protons of energies between 10 and 100 TeV.« less

Investigating broadband variability of the TeV blazar 1ES 1959+650

DOE PAGES

Aliu, E.; Archambault, S.; Arlen, T.; ...

2014-12-03

We summarize broadband observations of the TeV-emitting blazar 1ES 1959 650, including optical R-band observations by the robotic telescopes Super-LOTIS and iTelescope, UV observations by Swift UVOT, X-ray observations by the Swift X-ray Telescope, high-energy gamma-ray observations with the Fermi Large Area Telescope, and very-high-energy (VHE) gamma-ray observations by VERITAS above 315 GeV, all taken between 2012 April 17 and 2012 June 1 (MJD 56034 and 56079). The contemporaneous variability of the broadband spectral energy distribution is explored in the context of a simple synchrotron self Compton (SSC) model. In the SSC emission scenario, we find that the parameters requiredmore » to represent the high state are significantly different than those in the low state. Motivated by possible evidence of gas in the vicinity of the blazar, we also investigate a reflected emission model to describe the observed variability pattern. This model assumes that the non-thermal emission from the jet is reflected by a nearby cloud of gas, allowing the reflected emission to re-enter the blob and produce an elevated gamma-ray state with no simultaneous elevated synchrotron flux. The model applied here, although not required to explain the observed variability pattern, represents one possible scenario which can describe the observations. As applied to an elevated VHE state of 66% of the Crab Nebula flux, observed on a single night during the observation period, the reflected emission scenario does not support a purely leptonic non-thermal emission mechanism. The reflected model does, however, predict a reflected photon field with sufficient energy to enable elevated gamma-ray emission via pion production with protons of energies between 10 and 100 TeV.« less

Modeling the spatiotemporal dynamics of light and heat propagation for in vivo optogenetics

PubMed Central

Stujenske, Joseph M.; Spellman, Timothy; Gordon, Joshua A.

2015-01-01

Summary Despite the increasing use of optogenetics in vivo, the effects of direct light exposure to brain tissue are understudied. Of particular concern is the potential for heat induced by prolonged optical stimulation. We demonstrate that high intensity light, delivered through an optical fiber, is capable of elevating firing rate locally, even in the absence of opsin expression. Predicting the severity and spatial extent of any temperature increase during optogenetic stimulation is therefore of considerable importance. Here we describe a realistic model that simulates light and heat propagation during optogenetic experiments. We validated the model by comparing predicted and measured temperature changes in vivo. We further demonstrate the utility of this model by comparing predictions for various wavelengths of light and fiber sizes, as well as testing methods for reducing heat effects on neural targets in vivo. PMID:26166563

Predicting the Geothermal Heat Flux in Greenland: A Machine Learning Approach

NASA Astrophysics Data System (ADS)

Rezvanbehbahani, Soroush; Stearns, Leigh A.; Kadivar, Amir; Walker, J. Doug; van der Veen, C. J.

2017-12-01

Geothermal heat flux (GHF) is a crucial boundary condition for making accurate predictions of ice sheet mass loss, yet it is poorly known in Greenland due to inaccessibility of the bedrock. Here we use a machine learning algorithm on a large collection of relevant geologic features and global GHF measurements and produce a GHF map of Greenland that we argue is within ˜15% accuracy. The main features of our predicted GHF map include a large region with high GHF in central-north Greenland surrounding the NorthGRIP ice core site, and hot spots in the Jakobshavn Isbræ catchment, upstream of Petermann Gletscher, and near the terminus of Nioghalvfjerdsfjorden glacier. Our model also captures the trajectory of Greenland movement over the Icelandic plume by predicting a stripe of elevated GHF in central-east Greenland. Finally, we show that our model can produce substantially more accurate predictions if additional measurements of GHF in Greenland are provided.

Predicting the probability of elevated nitrate concentrations in the Puget Sound Basin: Implications for aquifer susceptibility and vulnerability

USGS Publications Warehouse

Tesoriero, A.J.; Voss, F.D.

1997-01-01

The occurrence and distribution of elevated nitrate concentrations (≥ 3 mg/l) in ground water in the Puget Sound Basin, Washington, were determined by examining existing data from more than 3000 wells. Models that estimate the probability that a well has an elevated nitrate concentration were constructed by relating the occurrence of elevated nitrate concentrations to both natural and anthropogenic variables using logistic regression. The variables that best explain the occurrence of elevated nitrate concentrations were well depth, surficial geology, and the percentage of urban and agricultural land within a radius of 3.2 kilometers of the well. From these relations, logistic regression models were developed to assess aquifer susceptibility (relative ease with which contaminants will reach aquifer) and ground-water vulnerability (relative ease with which contaminants will reach aquifer for a given set of land-use practices). Both models performed well at predicting the probability of elevated nitrate concentrations in an independent data set. This approach to assessing aquifer susceptibility and ground-water vulnerability has the advantages of having both model variables and coefficient values determined on the basis of existing water quality information and does not depend on the assignment of variables and weighting factors based on qualitative criteria.

Modeling Water-Surface Elevations and Virtual Shorelines for the Colorado River in Grand Canyon, Arizona

USGS Publications Warehouse

Magirl, Christopher S.; Breedlove, Michael J.; Webb, Robert H.; Griffiths, Peter G.

2008-01-01

Using widely-available software intended for modeling rivers, a new one-dimensional hydraulic model was developed for the Colorado River through Grand Canyon from Lees Ferry to Diamond Creek. Solving one-dimensional equations of energy and continuity, the model predicts stage for a known steady-state discharge at specific locations, or cross sections, along the river corridor. This model uses 2,680 cross sections built with high-resolution digital topography of ground locations away from the river flowing at a discharge of 227 m3/s; synthetic bathymetry was created for topography submerged below the 227 m3/s water surface. The synthetic bathymetry was created by adjusting the water depth at each cross section up or down until the model?s predicted water-surface elevation closely matched a known water surface. This approach is unorthodox and offers a technique to construct one-dimensional hydraulic models of bedrock-controlled rivers where bathymetric data have not been collected. An analysis of this modeling approach shows that while effective in enabling a useful model, the synthetic bathymetry can differ from the actual bathymetry. The known water-surface profile was measured using elevation data collected in 2000 and 2002, and the model can simulate discharges up to 5,900 m3/s. In addition to the hydraulic model, GIS-based techniques were used to estimate virtual shorelines and construct inundation maps. The error of the hydraulic model in predicting stage is within 0.4 m for discharges less than 1,300 m3/s. Between 1,300-2,500 m3/s, the model accuracy is about 1.0 m, and for discharges between 2,500-5,900 m3/s, the model accuracy is on the order of 1.5 m. In the absence of large floods on the flow-regulated Colorado River in Grand Canyon, the new hydraulic model and the accompanying inundation maps are a useful resource for researchers interested in water depths, shorelines, and stage-discharge curves for flows within the river corridor with 2002 topographic conditions.

Vulnerability of recently recharged groundwater in principal aquifers of the United States to nitrate contamination

USGS Publications Warehouse

Gurdak, Jason J.; Qi, Sharon L.

2012-01-01

Recently recharged water (defined here as <60 years old) is generally the most vulnerable part of a groundwater resource to nonpoint-source nitrate contamination. Understanding at the appropriate scale the interactions of natural and anthropogenic controlling factors that influence nitrate occurrence in recently recharged groundwater is critical to support best management and policy decisions that are often made at the aquifer to subaquifer scale. New logistic regression models were developed using data from the U.S. Geological Survey's National Water-Quality Assessment (NAWQA) program and National Water Information System for 17 principal aquifers of the U.S. to identify important source, transport, and attenuation factors that control nonpoint source nitrate concentrations greater than relative background levels in recently recharged groundwater and were used to predict the probability of detecting elevated nitrate in areas beyond the sampling network. Results indicate that dissolved oxygen, crops and irrigated cropland, fertilizer application, seasonally high water table, and soil properties that affect infiltration and denitrification are among the most important factors in predicting elevated nitrate concentrations. Important differences in controlling factors and spatial predictions were identified in the principal aquifer and national-scale models and support the conclusion that similar spatial scales are needed between informed groundwater management and model development.

Potential habitat distribution for the freshwater diatom Didymosphenia geminata in the continental US

USGS Publications Warehouse

Kumar, S.; Spaulding, S.A.; Stohlgren, T.J.; Hermann, K.A.; Schmidt, T.S.; Bahls, L.L.

2009-01-01

The diatom Didymosphenia geminata is a single-celled alga found in lakes, streams, and rivers. Nuisance blooms of D geminata affect the diversity, abundance, and productivity of other aquatic organisms. Because D geminata can be transported by humans on waders and other gear, accurate spatial prediction of habitat suitability is urgently needed for early detection and rapid response, as well as for evaluation of monitoring and control programs. We compared four modeling methods to predict D geminata's habitat distribution; two methods use presence-absence data (logistic regression and classification and regression tree [CART]), and two involve presence data (maximum entropy model [Maxent] and genetic algorithm for rule-set production [GARP]). Using these methods, we evaluated spatially explicit, bioclimatic and environmental variables as predictors of diatom distribution. The Maxent model provided the most accurate predictions, followed by logistic regression, CART, and GARP. The most suitable habitats were predicted to occur in the western US, in relatively cool sites, and at high elevations with a high base-flow index. The results provide insights into the factors that affect the distribution of D geminata and a spatial basis for the prediction of nuisance blooms. ?? The Ecological Society of America.

Elevated depressive symptoms enhance reflexive but not reflective auditory category learning.

PubMed

Maddox, W Todd; Chandrasekaran, Bharath; Smayda, Kirsten; Yi, Han-Gyol; Koslov, Seth; Beevers, Christopher G

2014-09-01

In vision an extensive literature supports the existence of competitive dual-processing systems of category learning that are grounded in neuroscience and are partially-dissociable. The reflective system is prefrontally-mediated and uses working memory and executive attention to develop and test rules for classifying in an explicit fashion. The reflexive system is striatally-mediated and operates by implicitly associating perception with actions that lead to reinforcement. Although categorization is fundamental to auditory processing, little is known about the learning systems that mediate auditory categorization and even less is known about the effects of individual difference in the relative efficiency of the two learning systems. Previous studies have shown that individuals with elevated depressive symptoms show deficits in reflective processing. We exploit this finding to test critical predictions of the dual-learning systems model in audition. Specifically, we examine the extent to which the two systems are dissociable and competitive. We predicted that elevated depressive symptoms would lead to reflective-optimal learning deficits but reflexive-optimal learning advantages. Because natural speech category learning is reflexive in nature, we made the prediction that elevated depressive symptoms would lead to superior speech learning. In support of our predictions, individuals with elevated depressive symptoms showed a deficit in reflective-optimal auditory category learning, but an advantage in reflexive-optimal auditory category learning. In addition, individuals with elevated depressive symptoms showed an advantage in learning a non-native speech category structure. Computational modeling suggested that the elevated depressive symptom advantage was due to faster, more accurate, and more frequent use of reflexive category learning strategies in individuals with elevated depressive symptoms. The implications of this work for dual-process approach to auditory learning and depression are discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.

Elevated Depressive Symptoms Enhance Reflexive but not Reflective Auditory Category Learning

PubMed Central

Maddox, W. Todd; Chandrasekaran, Bharath; Smayda, Kirsten; Yi, Han-Gyol; Koslov, Seth; Beevers, Christopher G.

2014-01-01

In vision an extensive literature supports the existence of competitive dual-processing systems of category learning that are grounded in neuroscience and are partially-dissociable. The reflective system is prefrontally-mediated and uses working memory and executive attention to develop and test rules for classifying in an explicit fashion. The reflexive system is striatally-mediated and operates by implicitly associating perception with actions that lead to reinforcement. Although categorization is fundamental to auditory processing, little is known about the learning systems that mediate auditory categorization and even less is known about the effects of individual difference in the relative efficiency of the two learning systems. Previous studies have shown that individuals with elevated depressive symptoms show deficits in reflective processing. We exploit this finding to test critical predictions of the dual-learning systems model in audition. Specifically, we examine the extent to which the two systems are dissociable and competitive. We predicted that elevated depressive symptoms would lead to reflective-optimal learning deficits but reflexive-optimal learning advantages. Because natural speech category learning is reflexive in nature, we made the prediction that elevated depressive symptoms would lead to superior speech learning. In support of our predictions, individuals with elevated depressive symptoms showed a deficit in reflective-optimal auditory category learning, but an advantage in reflexive-optimal auditory category learning. In addition, individuals with elevated depressive symptoms showed an advantage in learning a non-native speech category structure. Computational modeling suggested that the elevated depressive symptom advantage was due to faster, more accurate, and more frequent use of reflexive category learning strategies in individuals with elevated depressive symptoms. The implications of this work for dual-process approach to auditory learning and depression are discussed. PMID:25041936

Elevated Plasma CXCL12α Is Associated with a Poorer Prognosis in Pulmonary Arterial Hypertension

PubMed Central

Li, Lili; O’Connell, Caroline; Codd, Mary; Lawrie, Allan; Morton, Allison; Kiely, David G.; Condliffe, Robin; Elliot, Charles; McLoughlin, Paul; Gaine, Sean

2015-01-01

Rationale Recent work in preclinical models suggests that signalling via the pro-angiogenic and pro-inflammatory cytokine, CXCL12 (SDF-1), plays an important pathogenic role in pulmonary hypertension (PH). The objective of this study was to establish whether circulating concentrations of CXCL12α were elevated in patients with PAH and related to mortality. Methods Plasma samples were collected from patients with idiopathic pulmonary arterial hypertension (IPAH) and PAH associated with connective tissue diseases (CTD-PAH) attending two pulmonary hypertension referral centres (n = 95) and from age and gender matched healthy controls (n = 44). Patients were subsequently monitored throughout a period of five years. Results CXCL12α concentrations were elevated in PAH groups compared to controls (P<0.05) and receiver-operating-characteristic analysis showed that plasma CXCL12α concentrations discriminated patients from healthy controls (AUC 0.80, 95% confidence interval 0.73-0.88). Kaplan Meier analysis indicated that elevated plasma CXCL12α concentration was associated with reduced survival (P<0.01). Multivariate Cox proportional hazards model showed that elevated CXCL12α independently predicted (P<0.05) earlier death in PAH with a hazard ratio (95% confidence interval) of 2.25 (1.01-5.00). In the largest subset by WHO functional class (Class 3, 65% of patients) elevated CXCL12α independently predicted (P<0.05) earlier death, hazard ratio 2.27 (1.05-4.89). Conclusions Our data show that elevated concentrations of circulating CXCL12α in PAH predicted poorer survival. Furthermore, elevated circulating CXCL12α was an independent risk factor for death that could potentially be included in a prognostic model and guide therapy. PMID:25856504

Elevated plasma CXCL12α is associated with a poorer prognosis in pulmonary arterial hypertension.

PubMed

McCullagh, Brian N; Costello, Christine M; Li, Lili; O'Connell, Caroline; Codd, Mary; Lawrie, Allan; Morton, Allison; Kiely, David G; Condliffe, Robin; Elliot, Charles; McLoughlin, Paul; Gaine, Sean

2015-01-01

Recent work in preclinical models suggests that signalling via the pro-angiogenic and pro-inflammatory cytokine, CXCL12 (SDF-1), plays an important pathogenic role in pulmonary hypertension (PH). The objective of this study was to establish whether circulating concentrations of CXCL12α were elevated in patients with PAH and related to mortality. Plasma samples were collected from patients with idiopathic pulmonary arterial hypertension (IPAH) and PAH associated with connective tissue diseases (CTD-PAH) attending two pulmonary hypertension referral centres (n = 95) and from age and gender matched healthy controls (n = 44). Patients were subsequently monitored throughout a period of five years. CXCL12α concentrations were elevated in PAH groups compared to controls (P<0.05) and receiver-operating-characteristic analysis showed that plasma CXCL12α concentrations discriminated patients from healthy controls (AUC 0.80, 95% confidence interval 0.73-0.88). Kaplan Meier analysis indicated that elevated plasma CXCL12α concentration was associated with reduced survival (P<0.01). Multivariate Cox proportional hazards model showed that elevated CXCL12α independently predicted (P<0.05) earlier death in PAH with a hazard ratio (95% confidence interval) of 2.25 (1.01-5.00). In the largest subset by WHO functional class (Class 3, 65% of patients) elevated CXCL12α independently predicted (P<0.05) earlier death, hazard ratio 2.27 (1.05-4.89). Our data show that elevated concentrations of circulating CXCL12α in PAH predicted poorer survival. Furthermore, elevated circulating CXCL12α was an independent risk factor for death that could potentially be included in a prognostic model and guide therapy.

Rover Slip Validation and Prediction Algorithm

NASA Technical Reports Server (NTRS)

Yen, Jeng

2009-01-01

A physical-based simulation has been developed for the Mars Exploration Rover (MER) mission that applies a slope-induced wheel-slippage to the rover location estimator. Using the digital elevation map from the stereo images, the computational method resolves the quasi-dynamic equations of motion that incorporate the actual wheel-terrain speed to estimate the gross velocity of the vehicle. Based on the empirical slippage measured by the Visual Odometry software of the rover, this algorithm computes two factors for the slip model by minimizing the distance of the predicted and actual vehicle location, and then uses the model to predict the next drives. This technique, which has been deployed to operate the MER rovers in the extended mission periods, can accurately predict the rover position and attitude, mitigating the risk and uncertainties in the path planning on high-slope areas.

Geomorphically based predictive mapping of soil thickness in upland watersheds

NASA Astrophysics Data System (ADS)

Pelletier, Jon D.; Rasmussen, Craig

2009-09-01

The hydrologic response of upland watersheds is strongly controlled by soil (regolith) thickness. Despite the need to quantify soil thickness for input into hydrologic models, there is currently no widely used, geomorphically based method for doing so. In this paper we describe and illustrate a new method for predictive mapping of soil thicknesses using high-resolution topographic data, numerical modeling, and field-based calibration. The model framework works directly with input digital elevation model data to predict soil thicknesses assuming a long-term balance between soil production and erosion. Erosion rates in the model are quantified using one of three geomorphically based sediment transport models: nonlinear slope-dependent transport, nonlinear area- and slope-dependent transport, and nonlinear depth- and slope-dependent transport. The model balances soil production and erosion locally to predict a family of solutions corresponding to a range of values of two unconstrained model parameters. A small number of field-based soil thickness measurements can then be used to calibrate the local value of those unconstrained parameters, thereby constraining which solution is applicable at a particular study site. As an illustration, the model is used to predictively map soil thicknesses in two small, ˜0.1 km2, drainage basins in the Marshall Gulch watershed, a semiarid drainage basin in the Santa Catalina Mountains of Pima County, Arizona. Field observations and calibration data indicate that the nonlinear depth- and slope-dependent sediment transport model is the most appropriate transport model for this site. The resulting framework provides a generally applicable, geomorphically based tool for predictive mapping of soil thickness using high-resolution topographic data sets.

A Coupled Community-Level Assessment of Social and Physical Vulnerability to Hurricane Disasters

NASA Astrophysics Data System (ADS)

Kim, J. H.; Sutley, E. J.; Chowdhury, A. G.; Hamideh, S.

2017-12-01

A significant portion of the U.S. building inventory exists in hurricane- and flood-prone regions. The accompanying storm surge and rising water levels often result in the inundation of residential homes, particularly those occupied by low income households and forcing displacement. In order to mitigate potential damages, a popular design technique is to elevate the structure using piers or piles to above the base flood elevation. This is observed for single-family and multi-family homes, including manufactured homes and post-disaster temporary housing, albeit at lower elevations. Although this design alleviates potential flood damage, it affects the wind-structure interaction by subjecting the structure to higher wind speeds due to its increased height and also having a path for the wind to pass underneath the structure potentially creating new vulnerabilities to wind loading. The current ASCE 7 Standard (2016) does not include a methodology for addressing the modified aerodynamics and estimating wind loads for elevated structures, and thus the potential vulnerability during high wind events is unaccounted for in design. Using experimentally measured wind pressures on elevated and non-elevated residential building models, tax data, and census data, a coupled vulnerability assessment is performed at the community-level. Galveston, Texas is selected as the case study community. Using the coupled assessment model, a hindcast of 2008 Hurricane Ike is used for predicting physical damage and household dislocation. The predicted results are compared with the actual outcomes of the 2008 hurricane disaster. Recommendations are made (1) for code adoption based on the experimentally measured wind loads, and (2) for mitigation actions and policies that would could decrease population dislocation and promote recovery.

Simulating forest productivity along a neotropical elevational transect: temperature variation and carbon use efficiency

NASA Astrophysics Data System (ADS)

Marthews, T.; Malhi, Y.; Girardin, C.; Silva-Espejo, J.; Aragão, L.; Metcalfe, D.; Rapp, J.; Mercado, L.; Fisher, R.; Galbraith, D.; Fisher, J.; Salinas-Revilla, N.; Friend, A.; Restrepo-Coupe, N.; Williams, R.

2012-04-01

A better understanding of the mechanisms controlling the magnitude and sign of carbon components in tropical forest ecosystems is important for reliable estimation of this important regional component of the global carbon cycle. We used the JULES vegetation model to simulate all components of the carbon balance at six sites along an Andes-Amazon transect across Peru and Brazil and compared the results to published field measurements. In the upper montane zone the model predicted a vegetation dieback, indicating a need for better parameterisation of cloud forest vegetation. In the lower montane and lowland zones simulated ecosystem productivity and respiration were predicted with reasonable accuracy, although not always within the error bounds of the observations. Model-predicted carbon use efficiency in this transect surprisingly did not increase with elevation, but remained close to the 'temperate' value 0.5. This may be explained by elevational changes in the balance between growth and maintenance respiration within the forest canopy, as controlled by both temperature- and pressure-mediated processes.

A hydroclimatological approach to predicting regional landslide probability using Landlab

NASA Astrophysics Data System (ADS)

Strauch, Ronda; Istanbulluoglu, Erkan; Nudurupati, Sai Siddhartha; Bandaragoda, Christina; Gasparini, Nicole M.; Tucker, Gregory E.

2018-02-01

We develop a hydroclimatological approach to the modeling of regional shallow landslide initiation that integrates spatial and temporal dimensions of parameter uncertainty to estimate an annual probability of landslide initiation based on Monte Carlo simulations. The physically based model couples the infinite-slope stability model with a steady-state subsurface flow representation and operates in a digital elevation model. Spatially distributed gridded data for soil properties and vegetation classification are used for parameter estimation of probability distributions that characterize model input uncertainty. Hydrologic forcing to the model is through annual maximum daily recharge to subsurface flow obtained from a macroscale hydrologic model. We demonstrate the model in a steep mountainous region in northern Washington, USA, over 2700 km2. The influence of soil depth on the probability of landslide initiation is investigated through comparisons among model output produced using three different soil depth scenarios reflecting the uncertainty of soil depth and its potential long-term variability. We found elevation-dependent patterns in probability of landslide initiation that showed the stabilizing effects of forests at low elevations, an increased landslide probability with forest decline at mid-elevations (1400 to 2400 m), and soil limitation and steep topographic controls at high alpine elevations and in post-glacial landscapes. These dominant controls manifest themselves in a bimodal distribution of spatial annual landslide probability. Model testing with limited observations revealed similarly moderate model confidence for the three hazard maps, suggesting suitable use as relative hazard products. The model is available as a component in Landlab, an open-source, Python-based landscape earth systems modeling environment, and is designed to be easily reproduced utilizing HydroShare cyberinfrastructure.

Pinus taeda forest growth predictions in the 21st century vary with site mean annual temperature and site quality.

PubMed

Gonzalez-Benecke, Carlos A; Teskey, Robert O; Dinon-Aldridge, Heather; Martin, Timothy A

2017-11-01

Climate projections from 20 downscaled global climate models (GCMs) were used with the 3-PG model to predict the future productivity and water use of planted loblolly pine (Pinus taeda) growing across the southeastern United States. Predictions were made using Representative Concentration Pathways (RCP) 4.5 and 8.5. These represent scenarios in which total radiative forcing stabilizes before 2100 (RCP 4.5) or continues increasing throughout the century (RCP 8.5). Thirty-six sites evenly distributed across the native range of the species were used in the analysis. These sites represent a range in current mean annual temperature (14.9-21.6°C) and precipitation (1,120-1,680 mm/year). The site index of each site, which is a measure of growth potential, was varied to represent different levels of management. The 3-PG model predicted that aboveground biomass growth and net primary productivity will increase by 10%-40% in many parts of the region in the future. At cooler sites, the relative growth increase was greater than at warmer sites. By running the model with the baseline [CO 2 ] or the anticipated elevated [CO 2 ], the effect of CO 2 on growth was separated from that of other climate factors. The growth increase at warmer sites was due almost entirely to elevated [CO 2 ]. The growth increase at cooler sites was due to a combination of elevated [CO 2 ] and increased air temperature. Low site index stands had a greater relative increase in growth under the climate change scenarios than those with a high site index. Water use increased in proportion to increases in leaf area and productivity but precipitation was still adequate, based on the downscaled GCM climate projections. We conclude that an increase in productivity can be expected for a large majority of the planted loblolly pine stands in the southeastern United States during this century. © 2017 John Wiley & Sons Ltd.

Taking the pulse of mountains: Ecosystem responses to climatic variability

USGS Publications Warehouse

Fagre, Daniel B.; Peterson, David L.; Hessl, Amy E.

2003-01-01

An integrated program of ecosystem modeling and field studies in the mountains of the Pacific Northwest (U.S.A.) has quantified many of the ecological processes affected by climatic variability. Paleoecological and contemporary ecological data in forest ecosystems provided model parameterization and validation at broad spatial and temporal scales for tree growth, tree regeneration and treeline movement. For subalpine tree species, winter precipitation has a strong negative correlation with growth; this relationship is stronger at higher elevations and west-side sites (which have more precipitation). Temperature affects tree growth at some locations with respect to length of growing season (spring) and severity of drought at drier sites (summer). Furthermore, variable but predictable climate-growth relationships across elevation gradients suggest that tree species respond differently to climate at different locations, making a uniform response of these species to future climatic change unlikely. Multi-decadal variability in climate also affects ecosystem processes. Mountain hemlock growth at high-elevation sites is negatively correlated with winter snow depth and positively correlated with the winter Pacific Decadal Oscillation (PDO) index. At low elevations, the reverse is true. Glacier mass balance and fire severity are also linked to PDO. Rapid establishment of trees in subalpine ecosystems during this century is increasing forest cover and reducing meadow cover at many subalpine locations in the western U.S.A. and precipitation (snow depth) is a critical variable regulating conifer expansion. Lastly, modeling potential future ecosystem conditions suggests that increased climatic variability will result in increasing forest fire size and frequency, and reduced net primary productivity in drier, east-side forest ecosystems. As additional empirical data and modeling output become available, we will improve our ability to predict the effects of climatic change across a broad range of climates and mountain ecosystems in the northwestern U.S.A.

Volumetric pattern analysis of fuselage-mounted airborne antennas. Ph.D. Thesis; [prediction analysis techniques for antenna radiation patterns of microwave antennas on commercial aircraft

NASA Technical Reports Server (NTRS)

Yu, C. L.

1976-01-01

A volumetric pattern analysis of fuselage-mounted airborne antennas at high frequencies was investigated. The primary goal of the investigation was to develop a numerical solution for predicting radiation patterns of airborne antennas in an accurate and efficient manner. An analytical study of airborne antenna pattern problems is presented in which the antenna is mounted on the fuselage near the top or bottom. Since this is a study of general-type commercial aircraft, the aircraft was modeled in its most basic form. The fuselage was assumed to be an infinitely long perfectly conducting elliptic cylinder in its cross-section and a composite elliptic cylinder in its elevation profile. The wing, cockpit, stabilizers (horizontal and vertical) and landing gear are modeled by "N" sided bent or flat plates which can be arbitrarily attached to the fuselage. The volumetric solution developed utilizes two elliptic cylinders, namely, the roll plane and elevation plane models to approximate the principal surface profile (longitudinal and transverse) at the antenna location. With the belt concept and the aid of appropriate coordinate system transformations the solution can be used to predict the volumetric patterns of airborne antennas in an accurate and efficient manner. Applications of this solution to various airborne antenna problems show good agreement with scale model measurements. Extensive data are presented for a microwave landing antenna system.

Comparison of empirical and data driven hydrometeorological hazard models on coastal cities of São Paulo, Brazil

NASA Astrophysics Data System (ADS)

Koga-Vicente, A.; Friedel, M. J.

2010-12-01

Every year thousands of people are affected by floods and landslide hazards caused by rainstorms. The problem is more serious in tropical developing countries because of the susceptibility as a result of the high amount of available energy to form storms, and the high vulnerability due to poor economic and social conditions. Predictive models of hazards are important tools to manage this kind of risk. In this study, a comparison of two different modeling approaches was made for predicting hydrometeorological hazards in 12 cities on the coast of São Paulo, Brazil, from 1994 to 2003. In the first approach, an empirical multiple linear regression (MLR) model was developed and used; the second approach used a type of unsupervised nonlinear artificial neural network called a self-organized map (SOM). By using twenty three independent variables of susceptibility (precipitation, soil type, slope, elevation, and regional atmospheric system scale) and vulnerability (distribution and total population, income and educational characteristics, poverty intensity, human development index), binary hazard responses were obtained. Model performance by cross-validation indicated that the respective MLR and SOM model accuracy was about 67% and 80%. Prediction accuracy can be improved by the addition of information, but the SOM approach is preferred because of sparse data and highly nonlinear relations among the independent variables.

Recent advances in modeling the propagation noise in high-rise cities

NASA Astrophysics Data System (ADS)

Li, Kai Ming

2005-04-01

In the past few decades, we have witnessed a rapid growth in mechanized transport and transportation systems. We live in a transport-dominated society which has led to a marked improvement in dispersal of land use and to the increased opportunity for the separate development of residential, commercial, and industrial areas. In dense and high-rise cities, various modes of land transportation are the primary source of noise. The problem of transportation noise is not confined by political or social frontiers. It affects the rich who may live in a quiet residential area but who must make full use of transport to maintain their affluent existence, as well as the less fortunate who must live close to a highway, a major road, or an elevated railway line. A systematic development of the capability for accurate predictions of the propagation of land transportation noise in dense high-rise cities is highly desirable. This paper summarizes the current models for predicting sound fields in urban environments and gives an overview of the recent advances of various numerical models to predict the sound field in urban environments. [Work supported by the Research Grants Council of the Hong Kong SAR Government and the Hong Kong Polytechnic University.

Metrics for assessing the performance of morphodynamic models of braided rivers at event and reach scales

NASA Astrophysics Data System (ADS)

Williams, Richard; Measures, Richard; Hicks, Murray; Brasington, James

2017-04-01

Advances in geomatics technologies have transformed the monitoring of reach-scale (100-101 km) river morphodynamics. Hyperscale Digital Elevation Models (DEMs) can now be acquired at temporal intervals that are commensurate with the frequencies of high-flow events that force morphological change. The low vertical errors associated with such DEMs enable DEMs of Difference (DoDs) to be generated to quantify patterns of erosion and deposition, and derive sediment budgets using the morphological approach. In parallel with reach-scale observational advances, high-resolution, two-dimensional, physics-based numerical morphodynamic models are now computationally feasible for unsteady, reach-scale simulations. In light of this observational and predictive progress, there is a need to identify appropriate metrics that can be extracted from DEMs and DoDs to assess model performance. Nowhere is this more pertinent than in braided river environments, where numerous mobile channels that intertwine around mid-channel bars result in complex patterns of erosion and deposition, thus making model assessment particularly challenging. This paper identifies and evaluates a range of morphological and morphological-change metrics that can be used to assess predictions of braided river morphodynamics at the timescale of single storm events. A depth-averaged, mixed-grainsize Delft3D morphodynamic model was used to simulate morphological change during four discrete high-flow events, ranging from 91 to 403 m3s-1, along a 2.5 x 0.7 km reach of the braided, gravel-bed Rees River, New Zealand. Pre- and post-event topographic surveys, using a fusion of Terrestrial Laser Scanning and optical-empirical bathymetric mapping, were used to produce 0.5 m resolution DEMs and DoDs. The pre- and post-event DEMs for a moderate (227m3s-1) high-flow event were used to calibrate the model. DEMs and DoDs from the other three high-flow events were used for model assessment using two approaches. First, "morphological" metrics were applied to compare observed and predicted post-event DEMs. These metrics include measures of confluence and bifurcation node density, bar shape, braiding intensity, and topographic comparisons using a form of the Brier Skill Score and cumulative frequency distributions of rugosity. Second, "morphological change" metrics were used to compare observed and predicted morphological change. These metrics included the extent of the morphologically active area, pairwise comparisons of morphological change (using kappa and fuzzy kappa statistics), and comparisons between vertical morphological change magnitude and elevation distribution. Results indicate that those metrics that assess characteristic features of braiding, rather than making direct comparisons, are most useful for assessing reach-scale braided river morphodynamic models. Together, the metrics indicate that there was a general affinity between observed and predicted braided river morphodynamics, both during small and large magnitude high-flow events. These results thus demonstrate how high-resolution, reach-scale, natural experiment datasets can be used to assess the efficacy of morphological models in predicting realistic patterns of erosion and deposition. This lays the foundation for the development and assessment of decadal scale morphodynamic models and their use in adaptive river basin management.

A simple hypothesis of how leaf and canopy-level transpiration and assimilation respond to elevated CO2 reveals distinct response patterns between disturbed and undisturbed vegetation

NASA Astrophysics Data System (ADS)

Donohue, Randall J.; Roderick, Michael L.; McVicar, Tim R.; Yang, Yuting

2017-01-01

Elevated CO2 increases leaf-level water-use efficiency (ω) almost universally. How canopy-level transpiration and assimilation fluxes respond to increased ω is currently unclear. We present a simple, resource-availability-based hypothesis of how equilibrium (or mature) leaf and canopy transpiration and assimilation rates, along with leaf area index (L), respond to elevated CO2. We quantify this hypothesis in the form of a model and test it against observations from eight Free Air CO2 Enrichment sites that span a wide range of resource availabilities. Sites were grouped according to vegetation disturbance status. We find the model adequately accounts for the responses of undisturbed vegetation (R2 = 0.73, 11% error) but cannot account for the responses of disturbed vegetation (R2 = 0.47, 17% error). At undisturbed sites, the responses of L and of leaf and canopy transpiration vary predictably (7% error) with resource availability, whereas the leaf assimilation response is less predictable. In contrast, the L and transpiration flux responses at the disturbed (mostly forested) sites are highly variable and are not strongly related to resource availability. Initial analyses suggest that they are more strongly related to regrowth age than to resource availability. We conclude that (i) our CO2 response hypothesis is valid for capturing the responses of undisturbed vegetation only, (ii) that the responses of disturbed vegetation are distinctly different from undisturbed vegetation, and (iii) that these differences need to be accounted for when predicting the effects of elevated CO2 on land surface processes generally, and on leaf area and water fluxes in particular.

Towards a general framework for predicting threat status of data-deficient species from phylogenetic, spatial and environmental information.

PubMed

Jetz, Walter; Freckleton, Robert P

2015-02-19

In taxon-wide assessments of threat status many species remain not included owing to lack of data. Here, we present a novel spatial-phylogenetic statistical framework that uses a small set of readily available or derivable characteristics, including phylogenetically imputed body mass and remotely sensed human encroachment, to provide initial baseline predictions of threat status for data-deficient species. Applied to assessed mammal species worldwide, the approach effectively identifies threatened species and predicts the geographical variation in threat. For the 483 data-deficient species, the models predict highly elevated threat, with 69% 'at-risk' species in this set, compared with 22% among assessed species. This results in 331 additional potentially threatened mammals, with elevated conservation importance in rodents, bats and shrews, and countries like Colombia, Sulawesi and the Philippines. These findings demonstrate the future potential for combining phylogenies and remotely sensed data with species distributions to identify species and regions of conservation concern. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Predictive value of high sensitivity CRP in patients with diastolic heart failure.

PubMed

Michowitz, Yoav; Arbel, Yaron; Wexler, Dov; Sheps, David; Rogowski, Ori; Shapira, Itzhak; Berliner, Shlomo; Keren, Gad; George, Jacob; Roth, Arie

2008-04-25

C-reactive protein (CRP) has been tested in patients with systolic heart failure (HF) and mixed results have been obtained with regards to its potential predictive value. However, the role of C-reactive protein (CRP) in patients with diastolic HF is not established. We studied the predictive role of high sensitivity CRP (hsCRP) in patients with diastolic HF. HsCRP levels were measured in a cohort of CHF outpatients, 77 patients with diastolic HF and 217 patients with systolic HF. Concentrations were compared to a large cohort of healthy population (n=7701) and associated with the HF admissions and mortality of the patients. Levels of hsCRP did not differ between patients with systolic and diastolic HF and were significantly elevated compared to the cohort of healthy subjects even after adjustment to various clinical parameters (p<0.0001). In patients with diastolic HF, hsCRP levels associated with New York Heart Association functional class (NYHA-FC) (r=0.31 p=0.01). On univariate Cox regression model hsCRP levels independently predicted hospitalizations in patients with systolic but not diastolic HF (p=0.047). HsCRP concentrations are elevated in patients with diastolic HF and correlate with disease severity; their prognostic value in this patient population should be further investigated.

United States Department of Agriculture-Agricultural Research Service stored-grain areawide integrated pest management program.

PubMed

Flinn, Paul W; Hagstrum, David W; Reed, Carl; Phillips, Tom W

2003-01-01

The USDA Agricultural Research Service (ARS) funded a demonstration project (1998-2002) for areawide IPM for stored wheat in Kansas and Oklahoma. This project was a collaboration of researchers at the ARS Grain Marketing and Production Research Center in Manhattan, Kansas, Kansas State University, and Oklahoma State University. The project utilized two elevator networks, one in each state, for a total of 28 grain elevators. These elevators stored approximately 31 million bushels of wheat, which is approximately 1.2% of the annual national production. Stored wheat was followed as it moved from farm to the country elevator and finally to the terminal elevator. During this study, thousands of grain samples were taken in concrete elevator silos. Wheat stored at elevators was frequently infested by several insect species, which sometimes reached high numbers and damaged the grain. Fumigation using aluminum phosphide pellets was the main method for managing these insect pests in elevators in the USA. Fumigation decisions tended to be based on past experience with controlling stored-grain insects, or were calendar based. Integrated pest management (IPM) requires sampling and risk benefit analysis. We found that the best sampling method for estimating insect density, without turning the grain from one bin to another, was the vacuum probe sampler. Decision support software, Stored Grain Advisor Pro (SGA Pro) was developed that interprets insect sampling data, and provides grain managers with a risk analysis report detailing which bins are at low, moderate or high risk for insect-caused economic losses. Insect density was predicted up to three months in the future based on current insect density, grain temperature and moisture. Because sampling costs money, there is a trade-off between frequency of sampling and the cost of fumigation. The insect growth model in SGA Pro reduces the need to sample as often, thereby making the program more cost-effective. SGA Pro was validated during the final year of the areawide program. Based on data from 533 bins, SGA Pro accurately predicted which bins were at low, moderate or high risk. Only in two out of 533 bins did SGA Pro incorrectly predict bins as being low risk and, in both cases, insect density was only high (> two insects kg(-1)) at the surface, which suggested recent immigration. SGA Pro is superior to calendar-based management because it ensures that grain is only treated when insect densities exceed economic thresholds (two insects kg(-1)). This approach will reduce the frequency of fumigation while maintaining high grain quality. Minimizing the use of fumigant improves worker safety and reduces both control costs and harm to the environment.

Assessing deep-seated landslide susceptibility using 3-D groundwater and slope-stability analyses, southwestern Seattle, Washington

USGS Publications Warehouse

Brien, Dianne L.; Reid, Mark E.

2008-01-01

In Seattle, Washington, deep-seated landslides on bluffs along Puget Sound have historically caused extensive damage to land and structures. These large failures are controlled by three-dimensional (3-D) variations in strength and pore-water pressures. We assess the slope stability of part of southwestern Seattle using a 3-D limit-equilibrium analysis coupled with a 3-D groundwater flow model. Our analyses use a high-resolution digital elevation model (DEM) combined with assignment of strength and hydraulic properties based on geologic units. The hydrogeology of the Seattle area consists of a layer of permeable glacial outwash sand that overlies less permeable glacial lacustrine silty clay. Using a 3-D groundwater model, MODFLOW-2000, we simulate a water table above the less permeable units and calibrate the model to observed conditions. The simulated pore-pressure distribution is then used in a 3-D slope-stability analysis, SCOOPS, to quantify the stability of the coastal bluffs. For wet winter conditions, our analyses predict that the least stable areas are steep hillslopes above Puget Sound, where pore pressures are elevated in the outwash sand. Groundwater flow converges in coastal reentrants, resulting in elevated pore pressures and destabilization of slopes. Regions predicted to be least stable include the areas in or adjacent to three mapped historically active deep-seated landslides. The results of our 3-D analyses differ significantly from a slope map or results from one-dimensional (1-D) analyses.

Large-scale modelling permafrost distribution in Ötztal, Pitztal and Kaunertal (Tyrol)

NASA Astrophysics Data System (ADS)

Hoinkes, S.; Sailer, R.; Lehning, M.; Steinkogler, W.

2012-04-01

Permafrost is an important element of the global cryosphere, which is seriously affected by climate change. Due to the fact that permafrost is a mostly invisible phenomenon, the area-wide distribution is not properly known. Point measurements are conducted to get information, whether permafrost is present at certain places or not. For an area wide distribution mapping, models have to be built and applied. Different kinds of permafrost distribution models already exist, which are based on different approaches and complexities. Differences in model approaches are mainly due to scaling issues, availability of input data and type of output parameters. In the presented work, we want to map and model the distribution of permafrost in the most elevated parts of the Ötztal, Pitztal and Kaunertal, which are situated in the Eastern European Alps and cover an area of approximately 750 km2. As air temperature is believed to be the best and simplest proxy for energy balance in mountainous regions, we took only the mean annual air temperature from the interpolated ÖKLIM dataset of the Central Institute of Meteorology and Geodynamics to calculate areas with possible presence of permafrost. In a second approach we took a high resolution digital elevation model (DEM) derived by air-borne laser scanning and calculated possible areas with permafrost based on elevation and aspect only which is an established approach among the permafrost community since years. These two simple approaches are compared with each other and in order to validate the model we will compare the outputs with point measurements such as temperature recorded at the snow-soil interface (BTS), continuous temperature data, rock glacier inventories, geophysical measurements. We show that the model based on the mean annual air temperature (≤ -2°C) only, would predict less permafrost in the northerly exposed slopes and in lower elevation than the model based on elevation and aspect. In the southern aspects, more permafrost areas are predicted, but the overall pattern of permafrost distribution is similar. Regarding the input parameters, their different spatial resolutions and the complex topography in high alpine terrain these differences in the results are evident. In a next step these two very simple approaches will be compared to a more complex hydro-meteorological three-dimensional simulation (ALPINE3D). First a one-dimensional model will be used to model permafrost presence at certain points and to calibrate the model parameters, further the model will be applied for the whole investigation area. The model output will be a map of probable permafrost distribution, where energy balance, topography, snow cover, (sub)surface material and land cover is playing a major role.

Solar radiation and functional traits explain the decline of forest primary productivity along a tropical elevation gradient.

PubMed

Fyllas, Nikolaos M; Bentley, Lisa Patrick; Shenkin, Alexander; Asner, Gregory P; Atkin, Owen K; Díaz, Sandra; Enquist, Brian J; Farfan-Rios, William; Gloor, Emanuel; Guerrieri, Rossella; Huasco, Walter Huaraca; Ishida, Yoko; Martin, Roberta E; Meir, Patrick; Phillips, Oliver; Salinas, Norma; Silman, Miles; Weerasinghe, Lasantha K; Zaragoza-Castells, Joana; Malhi, Yadvinder

2017-06-01

One of the major challenges in ecology is to understand how ecosystems respond to changes in environmental conditions, and how taxonomic and functional diversity mediate these changes. In this study, we use a trait-spectra and individual-based model, to analyse variation in forest primary productivity along a 3.3 km elevation gradient in the Amazon-Andes. The model accurately predicted the magnitude and trends in forest productivity with elevation, with solar radiation and plant functional traits (leaf dry mass per area, leaf nitrogen and phosphorus concentration, and wood density) collectively accounting for productivity variation. Remarkably, explicit representation of temperature variation with elevation was not required to achieve accurate predictions of forest productivity, as trait variation driven by species turnover appears to capture the effect of temperature. Our semi-mechanistic model suggests that spatial variation in traits can potentially be used to estimate spatial variation in productivity at the landscape scale. © 2017 John Wiley & Sons Ltd/CNRS.

Interactions of elevation, aspect, and slope in models of forest species composition and productivity

Treesearch

Albert R. Stage; Christian Salas

2007-01-01

We present a linear model for the interacting effects of elevation, aspect, and slope for use in predicting forest productivity or species composition. The model formulation we propose integrates interactions of these three factors in a mathematical expression representing their combined effect in terms of a cosine function of aspect with a phase shift and amplitude...

Temperature effects on deformation and serration behavior of high-entropy alloys (HEAs)

DOE PAGES

Antonaglia, J.; Xie, X.; Tang, Z.; ...

2014-09-16

Many materials are known to deform under shear in an intermittent way with slip avalanches detected as acoustic emission and serrations in the stress–strain curves. Similar serrations have recently been observed in a new class of materials, called high-entropy alloys (HEAs). Here, we discuss the serration behaviors of several HEAs from cryogenic to elevated temperatures. The experimental results of slow compression and tension tests are compared with the predictions of a slip-avalanche model for the deformation of a broad range of solids. The results shed light on the deformation processes in HEAs. Temperature effects on the distributions of stress dropsmore » and the decrease of the cutoff (i.e., of the largest observed slip size) for increasing temperature qualitatively agree with the model predictions. As a result, the model is used to quantify the serration characteristics of HEAs, and pertinent implications are discussed.« less

Latin hypercube approach to estimate uncertainty in ground water vulnerability

USGS Publications Warehouse

Gurdak, J.J.; McCray, J.E.; Thyne, G.; Qi, S.L.

2007-01-01

A methodology is proposed to quantify prediction uncertainty associated with ground water vulnerability models that were developed through an approach that coupled multivariate logistic regression with a geographic information system (GIS). This method uses Latin hypercube sampling (LHS) to illustrate the propagation of input error and estimate uncertainty associated with the logistic regression predictions of ground water vulnerability. Central to the proposed method is the assumption that prediction uncertainty in ground water vulnerability models is a function of input error propagation from uncertainty in the estimated logistic regression model coefficients (model error) and the values of explanatory variables represented in the GIS (data error). Input probability distributions that represent both model and data error sources of uncertainty were simultaneously sampled using a Latin hypercube approach with logistic regression calculations of probability of elevated nonpoint source contaminants in ground water. The resulting probability distribution represents the prediction intervals and associated uncertainty of the ground water vulnerability predictions. The method is illustrated through a ground water vulnerability assessment of the High Plains regional aquifer. Results of the LHS simulations reveal significant prediction uncertainties that vary spatially across the regional aquifer. Additionally, the proposed method enables a spatial deconstruction of the prediction uncertainty that can lead to improved prediction of ground water vulnerability. ?? 2007 National Ground Water Association.

Fragmentation and thermal risks from climate change interact to affect persistence of native trout in the Colorado River basin.

PubMed

Roberts, James J; Fausch, Kurt D; Peterson, Douglas P; Hooten, Mevin B

2013-05-01

Impending changes in climate will interact with other stressors to threaten aquatic ecosystems and their biota. Native Colorado River cutthroat trout (CRCT; Oncorhynchus clarkii pleuriticus) are now relegated to 309 isolated high-elevation (>1700 m) headwater stream fragments in the Upper Colorado River Basin, owing to past nonnative trout invasions and habitat loss. Predicted changes in climate (i.e., temperature and precipitation) and resulting changes in stochastic physical disturbances (i.e., wildfire, debris flow, and channel drying and freezing) could further threaten the remaining CRCT populations. We developed an empirical model to predict stream temperatures at the fragment scale from downscaled climate projections along with geomorphic and landscape variables. We coupled these spatially explicit predictions of stream temperature with a Bayesian Network (BN) model that integrates stochastic risks from fragmentation to project persistence of CRCT populations across the upper Colorado River basin to 2040 and 2080. Overall, none of the populations are at risk from acute mortality resulting from high temperatures during the warmest summer period. In contrast, only 37% of populations have a ≥90% chance of persistence for 70 years (similar to the typical benchmark for conservation), primarily owing to fragmentation. Populations in short stream fragments <7 km long, and those at the lowest elevations, are at the highest risk of extirpation. Therefore, interactions of stochastic disturbances with fragmentation are projected to be greater threats than warming for CRCT populations. The reason for this paradox is that past nonnative trout invasions and habitat loss have restricted most CRCT populations to high-elevation stream fragments that are buffered from the potential consequences of warming, but at risk of extirpation from stochastic events. The greatest conservation need is for management to increase fragment lengths to forestall these risks. © 2013 Blackwell Publishing Ltd.

Fragmentation and thermal risks from climate change interact to affect persistence of native trout in the Colorado River basin

USGS Publications Warehouse

Roberts, James J.; Fausch, Kurt D.; Peterson, Douglas P.; Hooten, Mevin B.

2013-01-01

Impending changes in climate will interact with other stressors to threaten aquatic ecosystems and their biota. Native Colorado River cutthroat trout (CRCT; Oncorhynchus clarkii pleuriticus) are now relegated to 309 isolated high-elevation (>1700 m) headwater stream fragments in the Upper Colorado River Basin, owing to past nonnative trout invasions and habitat loss. Predicted changes in climate (i.e., temperature and precipitation) and resulting changes in stochastic physical disturbances (i.e., wildfire, debris flow, and channel drying and freezing) could further threaten the remaining CRCT populations. We developed an empirical model to predict stream temperatures at the fragment scale from downscaled climate projections along with geomorphic and landscape variables. We coupled these spatially explicit predictions of stream temperature with a Bayesian Network (BN) model that integrates stochastic risks from fragmentation to project persistence of CRCT populations across the upper Colorado River basin to 2040 and 2080. Overall, none of the populations are at risk from acute mortality resulting from high temperatures during the warmest summer period. In contrast, only 37% of populations have a greater than or equal to 90% chance of persistence for 70 years (similar to the typical benchmark for conservation), primarily owing to fragmentation. Populations in short stream fragments <7 km long, and those at the lowest elevations, are at the highest risk of extirpation. Therefore, interactions of stochastic disturbances with fragmentation are projected to be greater threats than warming for CRCT populations. The reason for this paradox is that past nonnative trout invasions and habitat loss have restricted most CRCT populations to high-elevation stream fragments that are buffered from the potential consequences of warming, but at risk of extirpation from stochastic events. The greatest conservation need is for management to increase fragment lengths to forestall these risks. 

Fatigue damage characterization of braided and woven fiber reinforced polymer matrix composites at room and elevated temperatures

NASA Astrophysics Data System (ADS)

Montesano, John

The use of polymer matrix composites (PMC) for manufacturing primary load-bearing structural components has significantly increased in many industrial applications. Specifically in the aerospace industry, PMCs are also being considered for elevated temperature applications. Current aerospace-grade composite components subjected to fatigue loading are over-designed due to insufficient understanding of the material failure processes, and due to the lack of available generic fatigue prediction models. A comprehensive literature survey reveals that there are few fatigue studies conducted on woven and braided fabric reinforced PMC materials, and even fewer at elevated temperatures. It is therefore the objective of this study to characterize and subsequently model the elevated temperature fatigue behaviour of a triaxial braided PMC, and to investigate the elevated temperature fatigue properties of two additional woven PMCs. An extensive experimental program is conducted using a unique test protocol on the braided and woven composites, which consists of static and fatigue testing at various test temperatures. The development of mechanically-induced damage is monitored using a combination of non-destructive techniques which included infrared thermography, fiber optic sensors and edge replication. The observed microscopic damage development is quantified and correlated to the exhibited macroscopic material behaviour at all test temperatures. The fiber-dominated PMC materials considered in this study did not exhibit notable time- or temperature-dependent static properties. However, fatigue tests reveal that the local damage development is in fact notably influenced by temperature. The elevated temperature environment increases the toughness of the thermosetting polymers, which results in consistently slower fatigue crack propagation rates for the respective composite materials. This has a direct impact on the stiffness degradation rate and the fatigue lives for the braided and woven composites under investigation. The developed analytical fatigue damage prediction model, which is based on actual observed damage mechanisms, accurately predicted the development of damage and the corresponding stiffness degradation for the braided PMC, for all test temperatures. An excellent correlation was found between the experimental and the predicted results to within a 2% accuracy. The prediction model adequately captured the local temperature-induced phenomenon exhibited by the braided PMC material. The results presented in this study are novel for a braided composite material subjected to elevated temperature fatigue.

Coupled ion redistribution and electronic breakdown in low-alkali boroaluminosilicate glass

DOE Office of Scientific and Technical Information (OSTI.GOV)

Choi, Doo Hyun, E-mail: cooldoo@add.re.kr; Randall, Clive, E-mail: car4@psu.edu; Furman, Eugene, E-mail: euf1@psu.edu

2015-08-28

Dielectrics with high electrostatic energy storage must have exceptionally high dielectric breakdown strength at elevated temperatures. Another important consideration in designing a high performance dielectric is understanding the thickness and temperature dependence of breakdown strengths. Here, we develop a numerical model which assumes a coupled ionic redistribution and electronic breakdown is applied to predict the breakdown strength of low-alkali glass. The ionic charge transport of three likely charge carriers (Na{sup +}, H{sup +}/H{sub 3}O{sup +}, Ba{sup 2+}) was used to calculate the ionic depletion width in low-alkali boroaluminosilicate which can further be used for the breakdown modeling. This model predictsmore » the breakdown strengths in the 10{sup 8}–10{sup 9 }V/m range and also accounts for the experimentally observed two distinct thickness dependent regions for breakdown. Moreover, the model successfully predicts the temperature dependent breakdown strength for low-alkali glass from room temperature up to 150 °C. This model showed that breakdown strengths were governed by minority charge carriers in the form of ionic transport (mostly sodium) in these glasses.« less

Elevated pulmonary artery systolic pressure predicts heart failure admissions in African Americans: Jackson Heart Study.

PubMed

Choudhary, Gaurav; Jankowich, Matthew; Wu, Wen-Chih

2014-07-01

Although elevated pulmonary artery systolic pressure (PASP) is associated with heart failure (HF), whether PASP measurement can help predict future HF admissions is not known, especially in African Americans who are at increased risk for HF. We hypothesized that elevated PASP is associated with increased risk of HF admission and improves HF prediction in African American population. We conducted a longitudinal analysis using the Jackson Heart Study cohort (n=3125; 32.2% men) with baseline echocardiography-derived PASP and follow-up for HF admissions. Hazard ratio for HF admission was estimated using Cox proportional hazard model adjusted for variables in the Atherosclerosis Risk in Community (ARIC) HF prediction model. During a median follow-up of 3.46 years, 3.42% of the cohort was admitted for HF. Subjects with HF had a higher PASP (35.6±11.4 versus 27.6±6.9 mm Hg; P<0.001). The hazard of HF admission increased with higher baseline PASP (adjusted hazard ratio per 10 mm Hg increase in PASP: 2.03; 95% confidence interval, 1.67-2.48; adjusted hazard ratio for highest [≥33 mm Hg] versus lowest quartile [<24 mm Hg] of PASP: 2.69; 95% confidence interval, 1.43-5.06) and remained significant irrespective of history of HF or preserved/reduced ejection fraction. Addition of PASP to the ARIC model resulted in a significant improvement in model discrimination (area under the curve=0.82 before versus 0.84 after; P=0.03) and improved net reclassification index (11-15%) using PASP as a continuous or dichotomous (cutoff=33 mm Hg) variable. Elevated PASP predicts HF admissions in African Americans and may aid in early identification of at-risk subjects for aggressive risk factor modification. © 2014 American Heart Association, Inc.

Changes in Depressive Symptoms and Subsequent Risk of Stroke in the Cardiovascular Health Study

PubMed Central

Gilsanz, Paola; Kubzansky, Laura D.; Tchetgen Tchetgen, Eric J.; Wang, Qianyi; Kawachi, Ichiro; Patton, Kristen K.; Fitzpatrick, Annette L.; Kop, Willem J.; Longstreth, W.T.; Glymour, M. Maria

2016-01-01

Background and Purpose Depression is associated with stroke, but the effects of changes in depressive symptoms on stroke risk are not well understood. This study examined whether depressive symptom changes across two successive annual assessments were associated with incident stroke the following year. Methods We used visit data from 4,319 participants of the Cardiovascular Health Study who were stroke-free at baseline to examine whether changes in depressive symptoms classified across two consecutive annual assessments predicted incident first stroke during the subsequent year. Depressive symptoms were assessed using the 10-item Center for Epidemiologic Studies Depression scale (CES-D; high vs. low at ≥10). Survival models were inverse probability weighted to adjust for demographics, health behaviors, medical conditions, past depressive symptoms, censoring, and survival. Results During follow-up, 334 strokes occurred. Relative to stable low scores of depressive symptoms, improved depression symptoms were associated with almost no excess risk of stroke (aHR=1.02; 95% CI: 0.66–1.58). New-onset symptoms were non-significantly associated with elevated stroke risk (aHR=1.44; 95% CI: 0.97–2.14) while persistently high depressive symptoms were associated with elevated adjusted hazard of all-cause stroke (aHR=1.65; 95% CI: 1.06–2.56). No evidence for effect modification by race, age, or sex was found. Conclusions Persistently high symptoms of depression predicted elevated hazard of stroke. Participants with improved depressive symptoms had no elevation in stroke risk. Such findings suggest that strategies to reduce depressive symptoms may ameliorate stroke risk. PMID:27924053

An Elevated Reservoir of Air Pollutants over the Mid-Atlantic States During the 2011 DISCOVER-AQ Campaign: Airborne Measurements and Numerical Simulations

NASA Technical Reports Server (NTRS)

He, Hao; Loughner, Christopher P.; Stehr, Jeffrey W.; Arkinson, Heather L.; Brent, Lacey C.; Follette-Cook, Melanie B.; Tzortziou, Maria A.; Pickering, Kenneth E.; Thompson, Anne M.; Martins, Douglas K.;

A Constitutive Model for the Inelastic Multiaxial Cyclic Response of a Nickel Base Superalloy Rene 80. Ph.D. Thesis. Final Report

NASA Technical Reports Server (NTRS)

Ramaswamy, V. G.

1986-01-01

The objective was to develop unified constitutive equations which can model a variety of nonlinear material phenomena observed in Rene 80 at elevated temperatures. A constitutive model was developed based on back stress and drag stress. The tensorial back stress was used to model directional effects; whereas, the scalar drag stress was used to model isotropic effects and cyclic hardening or softening. A flow equation and evolution equations for the state variables were developed in multiaxial form. Procedures were developed to generate the material parameters. The model predicted very well the monotonic tensile, cyclic, creep, and stress relaxation behavior of Rene 80 at 982 C. The model was then extended to 871, 760, and 538 C. It was shown that strain rate dependent behavior at high temperatures and strain rate independent behavior at the lower temperatures could be predicted very well. A large number of monotonic tensile, creep, stress relation, and cyclic experiments were predicted. The multiaxial capabilities of the model were verified extensively for combined tension/torsion experiments. The prediction of the model agreed very well for proportional, nonproportional, and pure shear cyclic loading conditions at 982 and 871 C.

Water Futures for Cold Mountain Ecohydrology under Climate Change - Results from the North American Cordilleran Transect

NASA Astrophysics Data System (ADS)

Rasouli, K.; Pomeroy, J. W.; Fang, X.; Whitfield, P. H.; Marks, D. G.; Janowicz, J. R.

2017-12-01

A transect comprising three intensively researched mountain headwater catchments stretching from the northern US to northern Canada provides the basis to downscale climate models outputs for mountain hydrology and insight for an assessment of water futures under changing climate and vegetation using a physically based hydrological model. Reynolds Mountain East, Idaho; Marmot Creek, Alberta and Wolf Creek, Yukon are high mountain catchments dominated by forests and alpine shrub and grass vegetation with long-term snow, hydrometric and meteorological observations and extensive ecohydrological process studies. The physically based, modular, flexible and object-oriented Cold Regions Hydrological Modelling Platform (CRHM) was used to create custom spatially distributed hydrological models for these three catchments. Model parameterisations were based on knowledge of hydrological processes, basin physiography, soils and vegetation with minimal or no calibration from streamflow measurements. The models were run over multidecadal periods using high-elevation meteorological observations to assess the recent ecohydrological functioning of these catchments. The results showed unique features in each catchment, from snowdrift-fed aspen pocket forests in Reynolds Mountain East, to deep late-lying snowdrifts at treeline larch forests in Marmot Creek, and snow-trapping shrub tundra overlying discontinuous permafrost in Wolf Creek. The meteorological observations were then perturbed using the changes in monthly temperature and precipitation predicted by the NARCCAP modelling outputs for the mid-21st C. In all catchments there is a dramatic decline in snow redistribution and sublimation by wind and of snow interception by and sublimation from evergreen canopies that is associated with warmer winters. Reduced sublimation loss only partially compensated for greater rainfall fractions of precipitation. Under climate change, snowmelt was earlier and slower and at the lowest elevations and latitudes produced less proportion of runoff from snowmelt. Transient vegetation changes counteracted increasing streamflow yields from climate change partly due to increased snow retention by enhanced vegetation heights at high elevations and reduced vegetation canopy coverage at low elevations.

Dominant factors controlling glacial and interglacial variations in the treeline elevation in tropical Africa

PubMed Central

Wu, Haibin; Guiot, Joël; Brewer, Simon; Guo, Zhengtang; Peng, Changhui

2007-01-01

The knowledge of tropical palaeoclimates is crucial for understanding global climate change, because it is a test bench for general circulation models that are ultimately used to predict future global warming. A longstanding issue concerning the last glacial maximum in the tropics is the discrepancy between the decrease in sea-surface temperatures reconstructed from marine proxies and the high-elevation decrease in land temperatures estimated from indicators of treeline elevation. In this study, an improved inverse vegetation modeling approach is used to quantitatively reconstruct palaeoclimate and to estimate the effects of different factors (temperature, precipitation, and atmospheric CO2 concentration) on changes in treeline elevation based on a set of pollen data covering an altitudinal range from 100 to 3,140 m above sea level in Africa. We show that lowering of the African treeline during the last glacial maximum was primarily triggered by regional drying, especially at upper elevations, and was amplified by decreases in atmospheric CO2 concentration and perhaps temperature. This contrasts with scenarios for the Holocene and future climates, in which the increase in treeline elevation will be dominated by temperature. Our results suggest that previous temperature changes inferred from tropical treeline shifts may have been overestimated for low-CO2 glacial periods, because the limiting factors that control changes in treeline elevation differ between glacial and interglacial periods. PMID:17535920

Dominant factors controlling glacial and interglacial variations in the treeline elevation in tropical Africa.

PubMed

Wu, Haibin; Guiot, Joël; Brewer, Simon; Guo, Zhengtang; Peng, Changhui

2007-06-05

The knowledge of tropical palaeoclimates is crucial for understanding global climate change, because it is a test bench for general circulation models that are ultimately used to predict future global warming. A longstanding issue concerning the last glacial maximum in the tropics is the discrepancy between the decrease in sea-surface temperatures reconstructed from marine proxies and the high-elevation decrease in land temperatures estimated from indicators of treeline elevation. In this study, an improved inverse vegetation modeling approach is used to quantitatively reconstruct palaeoclimate and to estimate the effects of different factors (temperature, precipitation, and atmospheric CO(2) concentration) on changes in treeline elevation based on a set of pollen data covering an altitudinal range from 100 to 3,140 m above sea level in Africa. We show that lowering of the African treeline during the last glacial maximum was primarily triggered by regional drying, especially at upper elevations, and was amplified by decreases in atmospheric CO(2) concentration and perhaps temperature. This contrasts with scenarios for the Holocene and future climates, in which the increase in treeline elevation will be dominated by temperature. Our results suggest that previous temperature changes inferred from tropical treeline shifts may have been overestimated for low-CO(2) glacial periods, because the limiting factors that control changes in treeline elevation differ between glacial and interglacial periods.

Potential effects of climate change on members of the Palaeotropical pitcher plant family Nepenthaceae.

PubMed

Gray, Laura K; Clarke, Charles; Wint, G R William; Moran, Jonathan A

2017-01-01

Anthropogenic climate change is predicted to have profound effects on species distributions over the coming decades. In this paper, we used maximum entropy modelling (Maxent) to estimate the effects of projected changes in climate on extent of climatically-suitable habitat for two Nepenthes pitcher plant species in Borneo. The model results predicted an increase in area of climatically-suitable habitat for the lowland species Nepenthes rafflesiana by 2100; in contrast, the highland species Nepenthes tentaculata was predicted to undergo significant loss of climatically-suitable habitat over the same period. Based on the results of the models, we recommend that research be undertaken into practical mitigation strategies, as approximately two-thirds of Nepenthes are restricted to montane habitats. Highland species with narrow elevational ranges will be at particularly high risk, and investigation into possible mitigation strategies should be focused on them.

Potential effects of climate change on members of the Palaeotropical pitcher plant family Nepenthaceae

PubMed Central

Gray, Laura K.; Clarke, Charles; Wint, G. R. William

2017-01-01

Anthropogenic climate change is predicted to have profound effects on species distributions over the coming decades. In this paper, we used maximum entropy modelling (Maxent) to estimate the effects of projected changes in climate on extent of climatically-suitable habitat for two Nepenthes pitcher plant species in Borneo. The model results predicted an increase in area of climatically-suitable habitat for the lowland species Nepenthes rafflesiana by 2100; in contrast, the highland species Nepenthes tentaculata was predicted to undergo significant loss of climatically-suitable habitat over the same period. Based on the results of the models, we recommend that research be undertaken into practical mitigation strategies, as approximately two-thirds of Nepenthes are restricted to montane habitats. Highland species with narrow elevational ranges will be at particularly high risk, and investigation into possible mitigation strategies should be focused on them. PMID:28817596

Estimation and mapping of above-ground biomass of mangrove forests and their replacement land uses in the Philippines using Sentinel imagery

NASA Astrophysics Data System (ADS)

Castillo, Jose Alan A.; Apan, Armando A.; Maraseni, Tek N.; Salmo, Severino G.

2017-12-01

The recent launch of the Sentinel-1 (SAR) and Sentinel-2 (multispectral) missions offers a new opportunity for land-based biomass mapping and monitoring especially in the tropics where deforestation is highest. Yet, unlike in agriculture and inland land uses, the use of Sentinel imagery has not been evaluated for biomass retrieval in mangrove forest and the non-forest land uses that replaced mangroves. In this study, we evaluated the ability of Sentinel imagery for the retrieval and predictive mapping of above-ground biomass of mangroves and their replacement land uses. We used Sentinel SAR and multispectral imagery to develop biomass prediction models through the conventional linear regression and novel Machine Learning algorithms. We developed models each from SAR raw polarisation backscatter data, multispectral bands, vegetation indices, and canopy biophysical variables. The results show that the model based on biophysical variable Leaf Area Index (LAI) derived from Sentinel-2 was more accurate in predicting the overall above-ground biomass. In contrast, the model which utilised optical bands had the lowest accuracy. However, the SAR-based model was more accurate in predicting the biomass in the usually deficient to low vegetation cover non-forest replacement land uses such as abandoned aquaculture pond, cleared mangrove and abandoned salt pond. These models had 0.82-0.83 correlation/agreement of observed and predicted value, and root mean square error of 27.8-28.5 Mg ha-1. Among the Sentinel-2 multispectral bands, the red and red edge bands (bands 4, 5 and 7), combined with elevation data, were the best variable set combination for biomass prediction. The red edge-based Inverted Red-Edge Chlorophyll Index had the highest prediction accuracy among the vegetation indices. Overall, Sentinel-1 SAR and Sentinel-2 multispectral imagery can provide satisfactory results in the retrieval and predictive mapping of the above-ground biomass of mangroves and the replacement non-forest land uses, especially with the inclusion of elevation data. The study demonstrates encouraging results in biomass mapping of mangroves and other coastal land uses in the tropics using the freely accessible and relatively high-resolution Sentinel imagery.

Gain degradation and amplitude scintillation due to tropospheric turbulence

NASA Technical Reports Server (NTRS)

Theobold, D. M.; Hodge, D. B.

1978-01-01

It is shown that a simple physical model is adequate for the prediction of the long term statistics of both the reduced signal levels and increased peak-to-peak fluctuations. The model is based on conventional atmospheric turbulence theory and incorporates both amplitude and angle of arrival fluctuations. This model predicts the average variance of signals observed under clear air conditions at low elevation angles on earth-space paths at 2, 7.3, 20 and 30 GHz. Design curves based on this model for gain degradation, realizable gain, amplitude fluctuation as a function of antenna aperture size, frequency, and either terrestrial path length or earth-space path elevation angle are presented.

Despotism and risk of infanticide influence grizzly bear den-site selection.

PubMed

Libal, Nathan S; Belant, Jerrold L; Leopold, Bruce D; Wang, Guiming; Owen, Patricia A

2011-01-01

Given documented social dominance and intraspecific predation in bear populations, the ideal despotic distribution model and sex hypothesis of sexual segregation predict adult female grizzly bears (Ursus arctos) will avoid areas occupied by adult males to reduce risk of infanticide. Under ideal despotic distribution, juveniles should similarly avoid adult males to reduce predation risk. Den-site selection and use is an important component of grizzly bear ecology and may be influenced by multiple factors, including risk from conspecifics. To test the role of predation risk and the sex hypothesis of sexual segregation, we compared adult female (n = 142), adult male (n = 36), and juvenile (n = 35) den locations in Denali National Park and Preserve, Alaska, USA. We measured elevation, aspect, slope, and dominant land cover for each den site, and used maximum entropy modeling to determine which variables best predicted den sites. We identified the global model as the best-fitting model for adult female (area under curve (AUC) = 0.926) and elevation as the best predictive variable for adult male (AUC = 0.880) den sites. The model containing land cover and elevation best-predicted juvenile (AUC = 0.841) den sites. Adult females spatially segregated from adult males, with dens characterized by higher elevations (mean= 1,412 m, SE = 52) and steeper slopes (mean = 21.9°, SE = 1.1) than adult male (elevation: mean = 1,209 m, SE = 76; slope: mean = 15.6°, SE = 1.9) den sites. Juveniles used a broad range of landscape attributes but did not avoid adult male denning areas. Observed spatial segregation by adult females supports the sex hypothesis of sexual segregation and we suggest is a mechanism to reduce risk of infanticide. Den site selection of adult males is likely related to distribution of food resources during spring.

Evaluating Air-Quality Models: Review and Outlook.

NASA Astrophysics Data System (ADS)

Weil, J. C.; Sykes, R. I.; Venkatram, A.

1992-10-01

Over the past decade, much attention has been devoted to the evaluation of air-quality models with emphasis on model performance in predicting the high concentrations that are important in air-quality regulations. This paper stems from our belief that this practice needs to be expanded to 1) evaluate model physics and 2) deal with the large natural or stochastic variability in concentration. The variability is represented by the root-mean- square fluctuating concentration (c about the mean concentration (C) over an ensemble-a given set of meteorological, source, etc. conditions. Most air-quality models used in applications predict C, whereas observations are individual realizations drawn from an ensemble. For cC large residuals exist between predicted and observed concentrations, which confuse model evaluations.This paper addresses ways of evaluating model physics in light of the large c the focus is on elevated point-source models. Evaluation of model physics requires the separation of the mean model error-the difference between the predicted and observed C-from the natural variability. A residual analysis is shown to be an elective way of doing this. Several examples demonstrate the usefulness of residuals as well as correlation analyses and laboratory data in judging model physics.In general, c models and predictions of the probability distribution of the fluctuating concentration (c), (c, are in the developmental stage, with laboratory data playing an important role. Laboratory data from point-source plumes in a convection tank show that (c approximates a self-similar distribution along the plume center plane, a useful result in a residual analysis. At pmsent,there is one model-ARAP-that predicts C, c, and (c for point-source plumes. This model is more computationally demanding than other dispersion models (for C only) and must be demonstrated as a practical tool. However, it predicts an important quantity for applications- the uncertainty in the very high and infrequent concentrations. The uncertainty is large and is needed in evaluating operational performance and in predicting the attainment of air-quality standards.

Modeling behavioral thermoregulation in a climate change sentinel.

PubMed

Moyer-Horner, Lucas; Mathewson, Paul D; Jones, Gavin M; Kearney, Michael R; Porter, Warren P

2015-12-01

When possible, many species will shift in elevation or latitude in response to rising temperatures. However, before such shifts occur, individuals will first tolerate environmental change and then modify their behavior to maintain heat balance. Behavioral thermoregulation allows animals a range of climatic tolerances and makes predicting geographic responses under future warming scenarios challenging. Because behavioral modification may reduce an individual's fecundity by, for example, limiting foraging time and thus caloric intake, we must consider the range of behavioral options available for thermoregulation to accurately predict climate change impacts on individual species. To date, few studies have identified mechanistic links between an organism's daily activities and the need to thermoregulate. We used a biophysical model, Niche Mapper, to mechanistically model microclimate conditions and thermoregulatory behavior for a temperature-sensitive mammal, the American pika (Ochotona princeps). Niche Mapper accurately simulated microclimate conditions, as well as empirical metabolic chamber data for a range of fur properties, animal sizes, and environmental parameters. Niche Mapper predicted pikas would be behaviorally constrained because of the need to thermoregulate during the hottest times of the day. We also showed that pikas at low elevations could receive energetic benefits by being smaller in size and maintaining summer pelage during longer stretches of the active season under a future warming scenario. We observed pika behavior for 288 h in Glacier National Park, Montana, and thermally characterized their rocky, montane environment. We found that pikas were most active when temperatures were cooler, and at sites characterized by high elevations and north-facing slopes. Pikas became significantly less active across a suite of behaviors in the field when temperatures surpassed 20°C, which supported a metabolic threshold predicted by Niche Mapper. In general, mechanistic predictions and empirical observations were congruent. This research is unique in providing both an empirical and mechanistic description of the effects of temperature on a mammalian sentinel of climate change, the American pika. Our results suggest that previously underinvestigated characteristics, specifically fur properties and body size, may play critical roles in pika populations' response to climate change. We also demonstrate the potential importance of considering behavioral thermoregulation and microclimate variability when predicting animal responses to climate change.

Machine learning for prediction of 30-day mortality after ST elevation myocardial infraction: An Acute Coronary Syndrome Israeli Survey data mining study.

PubMed

Shouval, Roni; Hadanny, Amir; Shlomo, Nir; Iakobishvili, Zaza; Unger, Ron; Zahger, Doron; Alcalai, Ronny; Atar, Shaul; Gottlieb, Shmuel; Matetzky, Shlomi; Goldenberg, Ilan; Beigel, Roy

2017-11-01

Risk scores for prediction of mortality 30-days following a ST-segment elevation myocardial infarction (STEMI) have been developed using a conventional statistical approach. To evaluate an array of machine learning (ML) algorithms for prediction of mortality at 30-days in STEMI patients and to compare these to the conventional validated risk scores. This was a retrospective, supervised learning, data mining study. Out of a cohort of 13,422 patients from the Acute Coronary Syndrome Israeli Survey (ACSIS) registry, 2782 patients fulfilled inclusion criteria and 54 variables were considered. Prediction models for overall mortality 30days after STEMI were developed using 6 ML algorithms. Models were compared to each other and to the Global Registry of Acute Coronary Events (GRACE) and Thrombolysis In Myocardial Infarction (TIMI) scores. Depending on the algorithm, using all available variables, prediction models' performance measured in an area under the receiver operating characteristic curve (AUC) ranged from 0.64 to 0.91. The best models performed similarly to the Global Registry of Acute Coronary Events (GRACE) score (0.87 SD 0.06) and outperformed the Thrombolysis In Myocardial Infarction (TIMI) score (0.82 SD 0.06, p<0.05). Performance of most algorithms plateaued when introduced with 15 variables. Among the top predictors were creatinine, Killip class on admission, blood pressure, glucose level, and age. We present a data mining approach for prediction of mortality post-ST-segment elevation myocardial infarction. The algorithms selected showed competence in prediction across an increasing number of variables. ML may be used for outcome prediction in complex cardiology settings. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Habitat features and predictive habitat modeling for the Colorado chipmunk in southern New Mexico

USGS Publications Warehouse

Rivieccio, M.; Thompson, B.C.; Gould, W.R.; Boykin, K.G.

2003-01-01

Two subspecies of Colorado chipmunk (state threatened and federal species of concern) occur in southern New Mexico: Tamias quadrivittatus australis in the Organ Mountains and T. q. oscuraensis in the Oscura Mountains. We developed a GIS model of potentially suitable habitat based on vegetation and elevation features, evaluated site classifications of the GIS model, and determined vegetation and terrain features associated with chipmunk occurrence. We compared GIS model classifications with actual vegetation and elevation features measured at 37 sites. At 60 sites we measured 18 habitat variables regarding slope, aspect, tree species, shrub species, and ground cover. We used logistic regression to analyze habitat variables associated with chipmunk presence/absence. All (100%) 37 sample sites (28 predicted suitable, 9 predicted unsuitable) were classified correctly by the GIS model regarding elevation and vegetation. For 28 sites predicted suitable by the GIS model, 18 sites (64%) appeared visually suitable based on habitat variables selected from logistic regression analyses, of which 10 sites (36%) were specifically predicted as suitable habitat via logistic regression. We detected chipmunks at 70% of sites deemed suitable via the logistic regression models. Shrub cover, tree density, plant proximity, presence of logs, and presence of rock outcrop were retained in the logistic model for the Oscura Mountains; litter, shrub cover, and grass cover were retained in the logistic model for the Organ Mountains. Evaluation of predictive models illustrates the need for multi-stage analyses to best judge performance. Microhabitat analyses indicate prospective needs for different management strategies between the subspecies. Sensitivities of each population of the Colorado chipmunk to natural and prescribed fire suggest that partial burnings of areas inhabited by Colorado chipmunks in southern New Mexico may be beneficial. These partial burnings may later help avoid a fire that could substantially reduce habitat of chipmunks over a mountain range.

Selected approaches for rational drug design and high throughput screening to identify anti-cancer molecules.

PubMed

Hedvat, Michael; Emdad, Luni; Das, Swadesh K; Kim, Keetae; Dasgupta, Santanu; Thomas, Shibu; Hu, Bin; Zhu, Shan; Dash, Rupesh; Quinn, Bridget A; Oyesanya, Regina A; Kegelman, Timothy P; Sokhi, Upneet K; Sarkar, Siddik; Erdogan, Eda; Menezes, Mitchell E; Bhoopathi, Praveen; Wang, Xiang-Yang; Pomper, Martin G; Wei, Jun; Wu, Bainan; Stebbins, John L; Diaz, Paul W; Reed, John C; Pellecchia, Maurizio; Sarkar, Devanand; Fisher, Paul B

2012-11-01

Structure-based modeling combined with rational drug design, and high throughput screening approaches offer significant potential for identifying and developing lead compounds with therapeutic potential. The present review focuses on these two approaches using explicit examples based on specific derivatives of Gossypol generated through rational design and applications of a cancer-specificpromoter derived from Progression Elevated Gene-3. The Gossypol derivative Sabutoclax (BI-97C1) displays potent anti-tumor activity against a diverse spectrum of human tumors. The model of the docked structure of Gossypol bound to Bcl-XL provided a virtual structure-activity-relationship where appropriate modifications were predicted on a rational basis. These structure-based studies led to the isolation of Sabutoclax, an optically pure isomer of Apogossypol displaying superior efficacy and reduced toxicity. These studies illustrate the power of combining structure-based modeling with rational design to predict appropriate derivatives of lead compounds to be empirically tested and evaluated for bioactivity. Another approach to cancer drug discovery utilizes a cancer-specific promoter as readouts of the transformed state. The promoter region of Progression Elevated Gene-3 is such a promoter with cancer-specific activity. The specificity of this promoter has been exploited as a means of constructing cancer terminator viruses that selectively kill cancer cells and as a systemic imaging modality that specifically visualizes in vivo cancer growth with no background from normal tissues. Screening of small molecule inhibitors that suppress the Progression Elevated Gene-3-promoter may provide relevant lead compounds for cancer therapy that can be combined with further structure-based approaches leading to the development of novel compounds for cancer therapy.

Quantitative model of the growth of floodplains by vertical accretion

USGS Publications Warehouse

Moody, J.A.; Troutman, B.M.

2000-01-01

A simple one-dimensional model is developed to quantitatively predict the change in elevation, over a period of decades, for vertically accreting floodplains. This unsteady model approximates the monotonic growth of a floodplain as an incremental but constant increase of net sediment deposition per flood for those floods of a partial duration series that exceed a threshold discharge corresponding to the elevation of the floodplain. Sediment deposition from each flood increases the elevation of the floodplain and consequently the magnitude of the threshold discharge resulting in a decrease in the number of floods and growth rate of the floodplain. Floodplain growth curves predicted by this model are compared to empirical growth curves based on dendrochronology and to direct field measurements at five floodplain sites. The model was used to predict the value of net sediment deposition per flood which best fits (in a least squares sense) the empirical and field measurements; these values fall within the range of independent estimates of the net sediment deposition per flood based on empirical equations. These empirical equations permit the application of the model to estimate of floodplain growth for other floodplains throughout the world which do not have detailed data of sediment deposition during individual floods. Copyright (C) 2000 John Wiley and Sons, Ltd.

Development of a finite element model of female foot for high-heeled shoe design.

PubMed

Yu, Jia; Cheung, Jason Tak-Man; Fan, Yubo; Zhang, Yan; Leung, Aaron Kam-Lun; Zhang, Ming

2008-01-01

Wearing high-heeled shoes may produce deleterious effects on the musculoskeletal system while elevation of the shoe heel with arch insole insert is used as a treatment strategy for plantar fasciitis. Due to limitations of the experimental approaches, direct measurements of internal stress/strain of the foot are impossible or invasive. This study aims at developing a finite element model for evaluating the biomechanical effects of high-heeled support on the ankle-foot complex. A 3D anatomically detailed FE model of the female foot and ankle together with a high-heeled support was developed and used to investigate the plantar contact pressure and internal loading responses of the bony and soft tissue structures of the foot with varying heel heights during simulated balanced standing. In the balanced standing position with high-heeled support, a pronounced increase in von Mises stress at the first metatarsophalangeal (MTP) joint was predicted. The strain on plantar fascia decreased compared to the flat horizontal support and valgus deformity of the hallux was not significant. The increased stress in forefoot especially at the first MTP segment during prolonged high-heeled standing may contribute to progressive hallux valgus (HV) deformity. However, the reduced tensile strain in the plantar fascia with heel elevation may help relieve plantar fasciitis related pain and inflammation.

Conservation status assessment of an endangered insular raptor: the Sharp-shinned Hawk in Puerto Rico

USGS Publications Warehouse

Gallardo, Julio C.; Vilella, Francisco

2017-01-01

Sharp‐shinned Hawks (Accipiter striatus) are forest raptors that are widely distributed in the Americas. A subspecies endemic to Puerto Rico (A. s. venator) is listed as endangered and restricted to mature and old secondary montane forests and shade coffee plantations. However, recent information about the population status and distribution of Puerto Rican Sharp‐shinned Hawks is lacking. We developed a spatial geographic distribution model for Sharp‐shinned Hawks in Puerto Rico from 33 locations collected during four breeding seasons (2013–2016) using biologically relevant landscape variables (aspect, canopy closure, elevation, rainfall, slope, and terrain roughness). Elevation accounted for 89.8% of the model fit and predicted that the greatest probability of occurrence of Sharp‐shinned Hawks in Puerto Rico (> 60%) was at elevations above 900 m. Based on our model, an estimated 56.1 km2 of habitat exists in Puerto Rico with a high probability of occurrence. This total represents ~0.6% of the island's area. Public lands included 43.8% of habitat with high probability of occurrence (24.6 km2), 96% of which was located within four protected areas. Our results suggest that Sharp‐shinned Hawks are rare in Puerto Rico and restricted to the higher elevations of the Cordillera Central. Additional research is needed to identify and address ecological limiting factors, and recovery actions are needed to avoid the extinction of this endemic island raptor.

Rapid high performance liquid chromatography method development with high prediction accuracy, using 5cm long narrow bore columns packed with sub-2microm particles and Design Space computer modeling.

PubMed

Fekete, Szabolcs; Fekete, Jeno; Molnár, Imre; Ganzler, Katalin

2009-11-06

Many different strategies of reversed phase high performance liquid chromatographic (RP-HPLC) method development are used today. This paper describes a strategy for the systematic development of ultrahigh-pressure liquid chromatographic (UHPLC or UPLC) methods using 5cmx2.1mm columns packed with sub-2microm particles and computer simulation (DryLab((R)) package). Data for the accuracy of computer modeling in the Design Space under ultrahigh-pressure conditions are reported. An acceptable accuracy for these predictions of the computer models is presented. This work illustrates a method development strategy, focusing on time reduction up to a factor 3-5, compared to the conventional HPLC method development and exhibits parts of the Design Space elaboration as requested by the FDA and ICH Q8R1. Furthermore this paper demonstrates the accuracy of retention time prediction at elevated pressure (enhanced flow-rate) and shows that the computer-assisted simulation can be applied with sufficient precision for UHPLC applications (p>400bar). Examples of fast and effective method development in pharmaceutical analysis, both for gradient and isocratic separations are presented.

Elevated HbA1c and Fasting Plasma Glucose in Predicting Diabetes Incidence Among Older Adults

PubMed Central

Lipska, Kasia J.; Inzucchi, Silvio E.; Van Ness, Peter H.; Gill, Thomas M.; Kanaya, Alka; Strotmeyer, Elsa S.; Koster, Annemarie; Johnson, Karen C.; Goodpaster, Bret H.; Harris, Tamara; De Rekeneire, Nathalie

2013-01-01

OBJECTIVE To determine which measures—impaired fasting glucose (IFG), elevated HbA1c, or both—best predict incident diabetes in older adults. RESEARCH DESIGN AND METHODS From the Health, Aging, and Body Composition study, we selected individuals without diabetes, and we defined IFG (100–125 mg/dL) and elevated HbA1c (5.7–6.4%) per American Diabetes Association guidelines. Incident diabetes was based on self-report, use of antihyperglycemic medicines, or HbA1c ≥6.5% during 7 years of follow-up. Logistic regression analyses were adjusted for age, sex, race, site, BMI, smoking, blood pressure, and physical activity. Discrimination and calibration were assessed for models with IFG and with both IFG and elevated HbA1c. RESULTS Among 1,690 adults (mean age 76.5, 46% men, 32% black), 183 (10.8%) developed diabetes over 7 years. Adjusted odds ratios of diabetes were 6.2 (95% CI 4.4–8.8) in those with IFG (versus those with fasting plasma glucose [FPG] <100 mg/dL) and 11.3 (7.8–16.4) in those with elevated HbA1c (versus those with HbA1c <5.7%). When FPG and HbA1c were considered together, odds ratios were 3.5 (1.9–6.3) in those with IFG only, 8.0 (4.8–13.2) in those with elevated HbA1c only, and 26.2 (16.3–42.1) in those with both IFG and elevated HbA1c (versus those with normal FPG and HbA1c). Addition of elevated HbA1c to the model with IFG resulted in improved discrimination and calibration. CONCLUSIONS Older adults with both IFG and elevated HbA1c have a substantially increased odds of developing diabetes over 7 years. Combined screening with FPG and HbA1c may identify older adults at very high risk for diabetes. PMID:24135387

Social cognitive correlates of physical activity among persons with multiple sclerosis: Influence of depressive symptoms.

PubMed

Ensari, Ipek; Kinnett-Hopkins, Dominique; Motl, Robert W

2017-10-01

Physical inactivity and elevated depressive symptoms are both highly prevalent and correlated among persons with multiple sclerosis (MS). Variables from Social Cognitive Theory (SCT) might be differentially correlated with physical activity in persons with MS who have elevated depressive symptoms. This study investigated the influence of elevated depressive symptoms on correlates of physical activity based on SCT in persons with MS. Participants (mean age = 50.3 years, 87% female, 69% Caucasian) completed questionnaires on physical activity, depressive symptoms, self-efficacy, social support, outcome expectations, functional limitations, and goal setting. The questionnaires were delivered and returned through the U.S. Postal Service. The sample (N = 551) was divided into 2 subgroups (i.e., elevated vs non-elevated levels of depressive symptoms) for statistical analyses. Bivariate correlations and stepwise multiple regressions were conducted using SPSS. Self-efficacy (r = 0.16), functional limitations (r = 0.22) and goal-setting (r = 0.42) were significantly (p < 0.05) associated with physical activity among the elevated depressive sample. The regression analysis indicated that self-efficacy predicted physical activity in Step 1 (β = 0.16, p < 0.05), but was no longer significant when goal-setting (β = 0.06, p > 0.05) entered the model. All social cognitive variables were significantly associated with physical activity levels (r = 0.16-0.40, p < 0.001) among the non-elevated depressive sample. Self-efficacy predicted physical activity in Step 1 (β = 0.24, p < 0.001), but it was no longer significant once goal-setting, functional limitations, and self-evaluative outcome expectations entered the model. Based on SCT, self-efficacy and goal-setting represent possible targets of behavior interventions for increasing physical activity among persons with MS who have elevated depressive symptoms. There is a larger set of targets among those with MS who do not have elevated symptoms. Copyright © 2017 Elsevier Inc. All rights reserved.

Differential risk for late adolescent conduct problems and mood dysregulation among children with early externalizing behavior problems.

PubMed

Okado, Yuko; Bierman, Karen L

2015-05-01

To investigate the differential emergence of antisocial behaviors and mood dysregulation among children with externalizing problems, the present study prospectively followed 317 high-risk children with early externalizing problems from school entry (ages 5-7) to late adolescence (ages 17-19). Latent class analysis conducted on their conduct and mood symptoms in late adolescence revealed three distinct patterns of symptoms, characterized by: 1) criminal offenses, conduct disorder symptoms, and elevated anger ("conduct problems"), 2) elevated anger, dysphoric mood, and suicidal ideation ("mood dysregulation"), and 3) low levels of severe conduct and mood symptoms. A diathesis-stress model predicting the first two outcomes was tested. Elevated overt aggression at school entry uniquely predicted conduct problems in late adolescence, whereas elevated emotion dysregulation at school entry uniquely predicted mood dysregulation in late adolescence. Experiences of low parental warmth and peer rejection in middle childhood moderated the link between early emotion dysregulation and later mood dysregulation but did not moderate the link between early overt aggression and later conduct problems. Thus, among children with early externalizing behavior problems, increased risk for later antisocial behavior or mood dysfunction may be identifiable in early childhood based on levels of overt aggression and emotion dysregulation. For children with early emotion dysregulation, however, increased risk for mood dysregulation characterized by anger, dysphoric mood, and suicidality--possibly indicative of disruptive mood dysregulation disorder--emerges only in the presence of low parental warmth and/or peer rejection during middle childhood.

Landslide-susceptibility analysis using light detection and ranging-derived digital elevation models and logistic regression models: a case study in Mizunami City, Japan

NASA Astrophysics Data System (ADS)

Wang, Liang-Jie; Sawada, Kazuhide; Moriguchi, Shuji

2013-01-01

To mitigate the damage caused by landslide disasters, different mathematical models have been applied to predict landslide spatial distribution characteristics. Although some researchers have achieved excellent results around the world, few studies take the spatial resolution of the database into account. Four types of digital elevation model (DEM) ranging from 2 to 20 m derived from light detection and ranging technology to analyze landslide susceptibility in Mizunami City, Gifu Prefecture, Japan, are presented. Fifteen landslide-causative factors are considered using a logistic-regression approach to create models for landslide potential analysis. Pre-existing landslide bodies are used to evaluate the performance of the four models. The results revealed that the 20-m model had the highest classification accuracy (71.9%), whereas the 2-m model had the lowest value (68.7%). In the 2-m model, 89.4% of the landslide bodies fit in the medium to very high categories. For the 20-m model, only 83.3% of the landslide bodies were concentrated in the medium to very high classes. When the cell size decreases from 20 to 2 m, the area under the relative operative characteristic increases from 0.68 to 0.77. Therefore, higher-resolution DEMs would provide better results for landslide-susceptibility mapping.

Forecasting Impacts of Climate Change on Indicators of British Columbia's Biodiversity

NASA Astrophysics Data System (ADS)

Holmes, Keith Richard

Understanding the relationships between biodiversity and climate is essential for predicting the impact of climate change on broad-scale landscape processes. Utilizing indirect indicators of biodiversity derived from remotely sensed imagery, we present an approach to forecast shifts in the spatial distribution of biodiversity. Indirect indicators, such as remotely sensed plant productivity metrics, representing landscape seasonality, minimum growth, and total greenness have been linked to species richness over broad spatial scales, providing unique capacity for biodiversity modeling. Our goal is to map future spatial distributions of plant productivity metrics based on expected climate change and to quantify anticipated change to park habitat in British Columbia. Using an archival dataset sourced from the Advanced Very High Resolution Radiometer (AVHRR) satellite from the years 1987 to 2007 at 1km spatial resolution, corresponding historical climate data, and regression tree modeling, we developed regional models of the relationships between climate and annual productivity growth. Historical interconnections between climate and annual productivity were coupled with three climate change scenarios modeled by the Canadian Centre for Climate Modeling and Analysis (CCCma) to predict and map productivity components to the year 2065. Results indicate we can expect a warmer and wetter environment, which may lead to increased productivity in the north and higher elevations. Overall, seasonality is expected to decrease and greenness productivity metrics are expected to increase. The Coastal Mountains and high elevation edge habitats across British Columbia are forecasted to experience the greatest amount of change. In the future, protected areas may have potential higher greenness and lower seasonality as represented by indirect biodiversity indicators. The predictive model highlights potential gaps in protection along the central interior and Rocky Mountains. Protected areas are expected to experience the greatest change with indirect indicators located along mountainous elevations of British Columbia. Our indirect indicator approach to predict change in biodiversity provides resource managers with information to mitigate and adapt to future habitat dynamics. Spatially specific recommendations from our dataset provide information necessary for management. For instance, knowing there is a projected depletion of habitat representation in the East Rocky Mountains, sensitive species in the threatened Mountain Hemlock ecozone, or preservation of rare habitats in the decreasing greenness of the southern interior region is essential information for managers tasked with long term biodiversity conservation. Forecasting productivity levels, linked to the distribution of species richness, presents a novel approach for understanding the future implications of climate change on broad scale biodiversity.

Statistical modelling predicts almost complete loss of major periglacial processes in Northern Europe by 2100.

PubMed

Aalto, Juha; Harrison, Stephan; Luoto, Miska

2017-09-11

The periglacial realm is a major part of the cryosphere, covering a quarter of Earth's land surface. Cryogenic land surface processes (LSPs) control landscape development, ecosystem functioning and climate through biogeochemical feedbacks, but their response to contemporary climate change is unclear. Here, by statistically modelling the current and future distributions of four major LSPs unique to periglacial regions at fine scale, we show fundamental changes in the periglacial climate realm are inevitable with future climate change. Even with the most optimistic CO 2 emissions scenario (Representative Concentration Pathway (RCP) 2.6) we predict a 72% reduction in the current periglacial climate realm by 2050 in our climatically sensitive northern Europe study area. These impacts are projected to be especially severe in high-latitude continental interiors. We further predict that by the end of the twenty-first century active periglacial LSPs will exist only at high elevations. These results forecast a future tipping point in the operation of cold-region LSP, and predict fundamental landscape-level modifications in ground conditions and related atmospheric feedbacks.Cryogenic land surface processes characterise the periglacial realm and control landscape development and ecosystem functioning. Here, via statistical modelling, the authors predict a 72% reduction of the periglacial realm in Northern Europe by 2050, and almost complete disappearance by 2100.

The Effect of Topographic Shadowing by Ice on Irradiance in the Greenland Ice Sheet Ablation Zone

NASA Astrophysics Data System (ADS)

Leidman, S. Z.; Rennermalm, A. K.; Ryan, J.; Cooper, M. G.; Smith, L. C.

2017-12-01

Accurately predicting runoff contributions to global sea level rise requires more refined surface mass balance (SMB) models of the Greenland Ice Sheet (GrIS). Topographic shadowing has shown to be important in the SMB of snow-covered regions, yet SMB models for the GrIS generally ignore how surface topography affects spatial variability of incoming solar radiation on a surface. In the ablation zone of Southwest Greenland, deeply incised supraglacial drainage features, fracturing, and large-scale bed deformation result in extensive areas of rough surface topography. This topography blocks direct radiation such that shadowed areas receive less energy for melting while other topographic features such as peaks recieve more energy. In this study, we quantify how shadowing from local topography features changes incoming solar radiation. We apply the ArcGIS Pro Solar Radiation Toolset to calculate the direct and diffuse irradiance in sunlit and shadowed areas by determining the sun's movement for every half hour increment of 2016. Multiple digital elevation models (DEMs) with spatial resolutions ranging from 0.06 to 5m were derived from fixed wing and quadcopter UAV imagery collected in summer 2016 and the ArcticDEM dataset. Our findings show that shadowing significantly decreases irradiance compared to smoothed surfaces where local topography is removed. This decrease is exponentially proportional to the DEM pixel sized with 5m DEMs only able to capture a small percentage of the effect. Applying these calculations to the ArcticDEM to cover a larger study area indicates that decreases in irradiance are nonlinearly proportional to elevation with highly crevassed areas showing a larger effect from shadowing. Even so, shading at higher elevations reduces irradiance enough to result in several centimeters snow water equivalence (SWE) per year of over-prediction of runoff in SMB models. Furthermore, analysis of solar radiation products shows that shadowing predicts albedo variability far better than a range of variables derived from UAV imagery mosaics including slope, aspect, elevation, or the distance to dark surface features. In summary, implementation of the effect of shadowing on irradiance should therefore be considered for accurate surface mass balance calculations for the Greenland ice sheet.

Climatic correlates of tree mortality in water- and energy-limited forests

USGS Publications Warehouse

Das, Adrian J.; Stephenson, Nathan L.; Flint, Alan; Das, Tapash; van Mantgem, Phillip J.

2013-01-01

Recent increases in tree mortality rates across the western USA are correlated with increasing temperatures, but mechanisms remain unresolved. Specifically, increasing mortality could predominantly be a consequence of temperature-induced increases in either (1) drought stress, or (2) the effectiveness of tree-killing insects and pathogens. Using long-term data from California’s Sierra Nevada mountain range, we found that in water-limited (low-elevation) forests mortality was unambiguously best modeled by climatic water deficit, consistent with the first mechanism. In energy-limited (high-elevation) forests deficit models were only equivocally better than temperature models, suggesting that the second mechanism is increasingly important in these forests. We could not distinguish between models predicting mortality using absolute versus relative changes in water deficit, and these two model types led to different forecasts of mortality vulnerability under future climate scenarios. Our results provide evidence for differing climatic controls of tree mortality in water- and energy-limited forests, while highlighting the need for an improved understanding of tree mortality processes.

Climatic correlates of tree mortality in water- and energy-limited forests.

PubMed

Das, Adrian J; Stephenson, Nathan L; Flint, Alan; Das, Tapash; van Mantgem, Phillip J

2013-01-01

Recent increases in tree mortality rates across the western USA are correlated with increasing temperatures, but mechanisms remain unresolved. Specifically, increasing mortality could predominantly be a consequence of temperature-induced increases in either (1) drought stress, or (2) the effectiveness of tree-killing insects and pathogens. Using long-term data from California's Sierra Nevada mountain range, we found that in water-limited (low-elevation) forests mortality was unambiguously best modeled by climatic water deficit, consistent with the first mechanism. In energy-limited (high-elevation) forests deficit models were only equivocally better than temperature models, suggesting that the second mechanism is increasingly important in these forests. We could not distinguish between models predicting mortality using absolute versus relative changes in water deficit, and these two model types led to different forecasts of mortality vulnerability under future climate scenarios. Our results provide evidence for differing climatic controls of tree mortality in water- and energy-limited forests, while highlighting the need for an improved understanding of tree mortality processes.

Climatic Correlates of Tree Mortality in Water- and Energy-Limited Forests

PubMed Central

Das, Adrian J.; Stephenson, Nathan L.; Flint, Alan; Das, Tapash; van Mantgem, Phillip J.

2013-01-01

Recent increases in tree mortality rates across the western USA are correlated with increasing temperatures, but mechanisms remain unresolved. Specifically, increasing mortality could predominantly be a consequence of temperature-induced increases in either (1) drought stress, or (2) the effectiveness of tree-killing insects and pathogens. Using long-term data from California’s Sierra Nevada mountain range, we found that in water-limited (low-elevation) forests mortality was unambiguously best modeled by climatic water deficit, consistent with the first mechanism. In energy-limited (high-elevation) forests deficit models were only equivocally better than temperature models, suggesting that the second mechanism is increasingly important in these forests. We could not distinguish between models predicting mortality using absolute versus relative changes in water deficit, and these two model types led to different forecasts of mortality vulnerability under future climate scenarios. Our results provide evidence for differing climatic controls of tree mortality in water- and energy-limited forests, while highlighting the need for an improved understanding of tree mortality processes. PMID:23936118

Lithospheric buoyancy and continental intraplate stresses

USGS Publications Warehouse

Zoback, M.L.; Mooney, W.D.

2003-01-01

Lithospheric buoyancy, the product of lithospheric density and thickness, is an important physical property that influences both the long-term stability of continents and their state of stress. We have determined lithospheric buoyancy by applying the simple isostatic model of Lachenbruch and Morgan (1990). We determine the crustal portion of lithospheric buoyancy using the USGS global database of more than 1700 crustal structure determinations (Mooney et al., 2002), which demonstrates that a simple relationship between crustal thickness and surface elevation does not exist. In fact, major regions of the crust at or near sea level (0-200 m elevation) have crustal thicknesses that vary between 25 and 55 km. Predicted elevations due to the crustal component of buoyancy in the model exceed observed elevations in nearly all cases (97% of the data), consistent with the existence of a cool lithospheric mantle lid that is denser than the asthenosphere on which it floats. The difference between the observed and predicted crustal elevation is assumed to be equal to the decrease in elevation produced by the negative buoyancy of the mantle lid. Mantle lid thickness was first estimated from the mantle buoyancy and a mean lid density computed using a basal crust temperature determined from extrapolation of surface heat flow, assuming a linear thermal gradient in the mantle lid. The resulting values of total lithosphere thickness are in good agreement with thicknesses estimated from seismic data, except beneath cratonic regions where they are only 40-60% of the typical estimates (200-350 km) derived from seismic data. This inconsistency is compatible with petrologic data and tomography and geoid analyses that have suggested that cratonic mantle lids are ??? 1% less dense than mantle lids elsewhere. By lowering the thermally determined mean mantle lid density in cratons by 1%, our model reproduces the observed 200-350+ km cratonic lithospheric thickness. We then computed gravitational potential energy by taking a vertical integral over the computed lithosphere density. Our computed values suggest that the thick roots beneath cratons lead to strong negative potential energy differences relative to surrounding regions, and hence exert compressive stresses superimposed on the intraplate stresses derived from plate boundary forces. Forces related to this lithosphere structure thus may explain the dominance of reverse-faulting earthquakes in cratons. Areas of high elevation and a thin mantle lid (e.g., western U.S. Basin and Range, East African rift, and Baikal rift) are predicted to be in extension, consistent with the observed stress regime in these areas.

Use of regression‐based models to map sensitivity of aquatic resources to atmospheric deposition in Yosemite National Park, USA

USGS Publications Warehouse

Clow, David W.; Nanus, Leora; Huggett, Brian

2010-01-01

An abundance of exposed bedrock, sparse soil and vegetation, and fast hydrologic flushing rates make aquatic ecosystems in Yosemite National Park susceptible to nutrient enrichment and episodic acidification due to atmospheric deposition of nitrogen (N) and sulfur (S). In this study, multiple linear regression (MLR) models were created to estimate fall‐season nitrate and acid neutralizing capacity (ANC) in surface water in Yosemite wilderness. Input data included estimated winter N deposition, fall‐season surface‐water chemistry measurements at 52 sites, and basin characteristics derived from geographic information system layers of topography, geology, and vegetation. The MLR models accounted for 84% and 70% of the variance in surface‐water nitrate and ANC, respectively. Explanatory variables (and the sign of their coefficients) for nitrate included elevation (positive) and the abundance of neoglacial and talus deposits (positive), unvegetated terrain (positive), alluvium (negative), and riparian (negative) areas in the basins. Explanatory variables for ANC included basin area (positive) and the abundance of metamorphic rocks (positive), unvegetated terrain (negative), water (negative), and winter N deposition (negative) in the basins. The MLR equations were applied to 1407 stream reaches delineated in the National Hydrography Data Set for Yosemite, and maps of predicted surface‐water nitrate and ANC concentrations were created. Predicted surface‐water nitrate concentrations were highest in small, high‐elevation cirques, and concentrations declined downstream. Predicted ANC concentrations showed the opposite pattern, except in high‐elevation areas underlain by metamorphic rocks along the Sierran Crest, which had relatively high predicted ANC (>200 μeq L−1). Maps were created to show where basin characteristics predispose aquatic resources to nutrient enrichment and acidification effects from N and S deposition. The maps can be used to help guide development of water‐quality programs designed to monitor and protect natural resources in national parks.

Contribution of river floods, hurricanes, and cold fronts to elevation change in a deltaic floodplain, northern Gulf of Mexico, USA

NASA Astrophysics Data System (ADS)

Bevington, Azure E.; Twilley, Robert R.; Sasser, Charles E.; Holm, Guerry O.

2017-05-01

Deltas are globally important locations of diverse ecosystems, human settlement, and economic activity that are threatened by reductions in sediment delivery, accelerated sea level rise, and subsidence. Here we investigated the relative contribution of river flooding, hurricanes, and cold fronts on elevation change in the prograding Wax Lake Delta (WLD). Sediment surface elevation was measured across 87 plots, eight times from February 2008 to August 2011. The high peak discharge river floods in 2008 and 2011 resulted in the greatest mean net elevation gain of 5.4 to 4.9 cm over each flood season, respectively. The highest deltaic wetland sediment retention (13.5% of total sediment discharge) occurred during the 2008 river flood despite lower total and peak discharge compared to 2011. Hurricanes Gustav and Ike resulted in a total net elevation gain of 1.2 cm, but the long-term contribution of hurricane derived sediments to deltaic wetlands was estimated to be just 22% of the long-term contribution of large river floods. Winter cold front passage resulted in a net loss in elevation that is equal to the elevation gain from lower discharge river floods and was consistent across years. This amount of annual loss in elevation from cold fronts could effectively negate the long-term land building capacity within the delta without the added elevation gain from both high and low discharge river floods. The current lack of inclusion of cold front elevation loss in most predictive numerical models likely overestimates the land building capacity in areas that experience similar forcings to WLD.

High-resolution vertical profiles of groundwater electrical conductivity (EC) and chloride from direct-push EC logs

NASA Astrophysics Data System (ADS)

Bourke, Sarah A.; Hermann, Kristian J.; Hendry, M. Jim

2017-11-01

Elevated groundwater salinity associated with produced water, leaching from landfills or secondary salinity can degrade arable soils and potable water resources. Direct-push electrical conductivity (EC) profiling enables rapid, relatively inexpensive, high-resolution in-situ measurements of subsurface salinity, without requiring core collection or installation of groundwater wells. However, because the direct-push tool measures the bulk EC of both solid and liquid phases (ECa), incorporation of ECa data into regional or historical groundwater data sets requires the prediction of pore water EC (ECw) or chloride (Cl-) concentrations from measured ECa. Statistical linear regression and physically based models for predicting ECw and Cl- from ECa profiles were tested on a brine plume in central Saskatchewan, Canada. A linear relationship between ECa/ECw and porosity was more accurate for predicting ECw and Cl- concentrations than a power-law relationship (Archie's Law). Despite clay contents of up to 96%, the addition of terms to account for electrical conductance in the solid phase did not improve model predictions. In the absence of porosity data, statistical linear regression models adequately predicted ECw and Cl- concentrations from direct-push ECa profiles (ECw = 5.48 ECa + 0.78, R 2 = 0.87; Cl- = 1,978 ECa - 1,398, R 2 = 0.73). These statistical models can be used to predict ECw in the absence of lithologic data and will be particularly useful for initial site assessments. The more accurate linear physically based model can be used to predict ECw and Cl- as porosity data become available and the site-specific ECw-Cl- relationship is determined.

Climate change and tree-line ecosystems in the Sierra Nevada: Habitat suitability modelling to inform high-elevation forest dynamics monitoring

USGS Publications Warehouse

Moore, Peggy E.; Alvarez, Otto; McKinney, Shawn T.; Li, Wenkai; Brooks, Matthew L.; Guo, Qinghua

2017-01-01

Whitebark pine and foxtail pine serve foundational roles in the subalpine zone of the Sierra Nevada. They provide the dominant structure in tree-line forests and regulate key ecosystem processes and community dynamics. Climate change models suggest that there will be changes in temperature regimes and in the timing and magnitude of precipitation within the current distribution of these species, and these changes may alter the species’ distributional limits. Other stressors include the non-native pathogen white pine blister rust and mountain pine beetle, which have played a role in the decline of whitebark pine throughout much of its range. The National Park Service is monitoring status and trends of these species. This report provides complementary information in the form of habitat suitability models to predict climate change impacts on the future distribution of these species within Sierra Nevada national parks.We used maximum entropy modeling to build habitat suitability models by relating species occurrence to environmental variables. Species occurrence was available from 328 locations for whitebark pine and 244 for foxtail pine across the species’ distributions within the parks. We constructed current climate surfaces for modeling by interpolating data from weather stations. Climate surfaces included mean, minimum, and maximum temperature and total precipitation for January, April, July, and October. We downscaled five general circulation models for the 2050s and the 2090s from ~125 km2 to 1 km2 under both an optimistic and an extreme climate scenario to bracket potential climatic change and its influence on projected suitable habitat. To describe anticipated changes in the distribution of suitable habitat, we compared, for each species, climate scenario, and time period, the current models with future models in terms of proportional change in habitat size, elevation distribution, model center points, and where habitat is predicted to expand or contract.Overall, models indicated that suitable habitats for whitebark and foxtail pine are more likely to shift geographically within the parks by 2100 rather than decline precipitously. This implies park managers might focus conservation efforts on stressors other than climate change, working toward species resilience in the face of threats from introduced disease and elevated native insect damage. More specifically, further understanding of the incidence and severity of white pine blister rust and other stressors in high elevation white pines would help assess vulnerability from threats other than climate change.

The Impact of 3D Data Quality on Improving GNSS Performance Using City Models Initial Simulations

NASA Astrophysics Data System (ADS)

Ellul, C.; Adjrad, M.; Groves, P.

2016-10-01

There is an increasing demand for highly accurate positioning information in urban areas, to support applications such as people and vehicle tracking, real-time air quality detection and navigation. However systems such as GPS typically perform poorly in dense urban areas. A number of authors have made use of 3D city models to enhance accuracy, obtaining good results, but to date the influence of the quality of the 3D city model on these results has not been tested. This paper addresses the following question: how does the quality, and in particular the variation in height, level of generalization and completeness and currency of a 3D dataset, impact the results obtained for the preliminary calculations in a process known as Shadow Matching, which takes into account not only where satellite signals are visible on the street but also where they are predicted to be absent. We describe initial simulations to address this issue, examining the variation in elevation angle - i.e. the angle above which the satellite is visible, for three 3D city models in a test area in London, and note that even within one dataset using different available height values could cause a difference in elevation angle of up to 29°. Missing or extra buildings result in an elevation variation of around 85°. Variations such as these can significantly influence the predicted satellite visibility which will then not correspond to that experienced on the ground, reducing the accuracy of the resulting Shadow Matching process.

Fatigue Life Prediction of Fiber-Reinforced Ceramic-Matrix Composites with Different Fiber Preforms at Room and Elevated Temperatures

PubMed Central

Li, Longbiao

2016-01-01

In this paper, the fatigue life of fiber-reinforced ceramic-matrix composites (CMCs) with different fiber preforms, i.e., unidirectional, cross-ply, 2D (two dimensional), 2.5D and 3D CMCs at room and elevated temperatures in air and oxidative environments, has been predicted using the micromechanics approach. An effective coefficient of the fiber volume fraction along the loading direction (ECFL) was introduced to describe the fiber architecture of preforms. The statistical matrix multicracking model and fracture mechanics interface debonding criterion were used to determine the matrix crack spacing and interface debonded length. Under cyclic fatigue loading, the fiber broken fraction was determined by combining the interface wear model and fiber statistical failure model at room temperature, and interface/fiber oxidation model, interface wear model and fiber statistical failure model at elevated temperatures, based on the assumption that the fiber strength is subjected to two-parameter Weibull distribution and the load carried by broken and intact fibers satisfies the Global Load Sharing (GLS) criterion. When the broken fiber fraction approaches the critical value, the composites fatigue fracture. PMID:28773332

Left ventricular ejection fraction to predict early mortality in patients with non-ST-segment elevation acute coronary syndromes.

PubMed

Bosch, Xavier; Théroux, Pierre

2005-08-01

Improvement in risk stratification of patients with non-ST-segment elevation acute coronary syndrome (ACS) is a gateway to a more judicious treatment. This study examines whether the routine determination of left ventricular ejection fraction (EF) adds significant prognostic information to currently recommended stratifiers. Several predictors of inhospital mortality were prospectively characterized in a registry study of 1104 consecutive patients, for whom an EF was determined, who were admitted for an ACS. Multiple regression models were constructed using currently recommended clinical, electrocardiographic, and blood marker stratifiers, and values of EF were incorporated into the models. Age, ST-segment shifts, elevation of cardiac markers, and the Thrombolysis in Myocardial Infarction (TIMI) risk score all predicted mortality (P < .0001). Adding EF into the model improved the prediction of mortality (C statistic 0.73 vs 0.67). The odds of death increased by a factor of 1.042 for each 1% decrement in EF. By receiver operating curves, an EF cutoff of 48% provided the best predictive value. Mortality rates were 3.3 times higher within each TIMI risk score stratum in patients with an EF of 48% or lower as compared with those with higher. The TIMI risk score predicts inhospital mortality in a broad population of patients with ACS. The further consideration of EF adds significant prognostic information.

Evolution of plasticity and adaptive responses to climate change along climate gradients.

PubMed

Kingsolver, Joel G; Buckley, Lauren B

2017-08-16

The relative contributions of phenotypic plasticity and adaptive evolution to the responses of species to recent and future climate change are poorly understood. We combine recent (1960-2010) climate and phenotypic data with microclimate, heat balance, demographic and evolutionary models to address this issue for a montane butterfly, Colias eriphyle , along an elevational gradient. Our focal phenotype, wing solar absorptivity, responds plastically to developmental (pupal) temperatures and plays a central role in thermoregulatory adaptation in adults. Here, we show that both the phenotypic and adaptive consequences of plasticity vary with elevation. Seasonal changes in weather generate seasonal variation in phenotypic selection on mean and plasticity of absorptivity, especially at lower elevations. In response to climate change in the past 60 years, our models predict evolutionary declines in mean absorptivity (but little change in plasticity) at high elevations, and evolutionary increases in plasticity (but little change in mean) at low elevation. The importance of plasticity depends on the magnitude of seasonal variation in climate relative to interannual variation. Our results suggest that selection and evolution of both trait means and plasticity can contribute to adaptive response to climate change in this system. They also illustrate how plasticity can facilitate rather than retard adaptive evolutionary responses to directional climate change in seasonal environments. © 2017 The Author(s).

Functional hierarchy underlies preferential connectivity disturbances in schizophrenia.

PubMed

Yang, Genevieve J; Murray, John D; Wang, Xiao-Jing; Glahn, David C; Pearlson, Godfrey D; Repovs, Grega; Krystal, John H; Anticevic, Alan

2016-01-12

Schizophrenia may involve an elevated excitation/inhibition (E/I) ratio in cortical microcircuits. It remains unknown how this regulatory disturbance maps onto neuroimaging findings. To address this issue, we implemented E/I perturbations within a neural model of large-scale functional connectivity, which predicted hyperconnectivity following E/I elevation. To test predictions, we examined resting-state functional MRI in 161 schizophrenia patients and 164 healthy subjects. As predicted, patients exhibited elevated functional connectivity that correlated with symptom levels, and was most prominent in association cortices, such as the fronto-parietal control network. This pattern was absent in patients with bipolar disorder (n = 73). To account for the pattern observed in schizophrenia, we integrated neurobiologically plausible, hierarchical differences in association vs. sensory recurrent neuronal dynamics into our model. This in silico architecture revealed preferential vulnerability of association networks to E/I imbalance, which we verified empirically. Reported effects implicate widespread microcircuit E/I imbalance as a parsimonious mechanism for emergent inhomogeneous dysconnectivity in schizophrenia.

Functional hierarchy underlies preferential connectivity disturbances in schizophrenia

PubMed Central

Yang, Genevieve J.; Murray, John D.; Wang, Xiao-Jing; Glahn, David C.; Pearlson, Godfrey D.; Repovs, Grega; Krystal, John H.; Anticevic, Alan

2016-01-01

Schizophrenia may involve an elevated excitation/inhibition (E/I) ratio in cortical microcircuits. It remains unknown how this regulatory disturbance maps onto neuroimaging findings. To address this issue, we implemented E/I perturbations within a neural model of large-scale functional connectivity, which predicted hyperconnectivity following E/I elevation. To test predictions, we examined resting-state functional MRI in 161 schizophrenia patients and 164 healthy subjects. As predicted, patients exhibited elevated functional connectivity that correlated with symptom levels, and was most prominent in association cortices, such as the fronto-parietal control network. This pattern was absent in patients with bipolar disorder (n = 73). To account for the pattern observed in schizophrenia, we integrated neurobiologically plausible, hierarchical differences in association vs. sensory recurrent neuronal dynamics into our model. This in silico architecture revealed preferential vulnerability of association networks to E/I imbalance, which we verified empirically. Reported effects implicate widespread microcircuit E/I imbalance as a parsimonious mechanism for emergent inhomogeneous dysconnectivity in schizophrenia. PMID:26699491

Risk of fire occurrence in arid and semi-arid ecosystems of Iran: an investigation using Bayesian belief networks.

PubMed

Bashari, Hossein; Naghipour, Ali Asghar; Khajeddin, Seyed Jamaleddin; Sangoony, Hamed; Tahmasebi, Pejman

2016-09-01

Identifying areas that have a high risk of burning is a main component of fire management planning. Although the available tools can predict the fire risks, these are poor in accommodating uncertainties in their predictions. In this study, we accommodated uncertainty in wildfire prediction using Bayesian belief networks (BBNs). An influence diagram was developed to identify the factors influencing wildfire in arid and semi-arid areas of Iran, and it was populated with probabilities to produce a BBNs model. The behavior of the model was tested using scenario and sensitivity analysis. Land cover/use, mean annual rainfall, mean annual temperature, elevation, and livestock density were recognized as the main variables determining wildfire occurrence. The produced model had good accuracy as its ROC area under the curve was 0.986. The model could be applied in both predictive and diagnostic analysis for answering "what if" and "how" questions. The probabilistic relationships within the model can be updated over time using observation and monitoring data. The wildfire BBN model may be updated as new knowledge emerges; hence, it can be used to support the process of adaptive management.

A neighborhood statistics model for predicting stream pathogen indicator levels.

PubMed

Pandey, Pramod K; Pasternack, Gregory B; Majumder, Mahbubul; Soupir, Michelle L; Kaiser, Mark S

2015-03-01

Because elevated levels of water-borne Escherichia coli in streams are a leading cause of water quality impairments in the U.S., water-quality managers need tools for predicting aqueous E. coli levels. Presently, E. coli levels may be predicted using complex mechanistic models that have a high degree of unchecked uncertainty or simpler statistical models. To assess spatio-temporal patterns of instream E. coli levels, herein we measured E. coli, a pathogen indicator, at 16 sites (at four different times) within the Squaw Creek watershed, Iowa, and subsequently, the Markov Random Field model was exploited to develop a neighborhood statistics model for predicting instream E. coli levels. Two observed covariates, local water temperature (degrees Celsius) and mean cross-sectional depth (meters), were used as inputs to the model. Predictions of E. coli levels in the water column were compared with independent observational data collected from 16 in-stream locations. The results revealed that spatio-temporal averages of predicted and observed E. coli levels were extremely close. Approximately 66 % of individual predicted E. coli concentrations were within a factor of 2 of the observed values. In only one event, the difference between prediction and observation was beyond one order of magnitude. The mean of all predicted values at 16 locations was approximately 1 % higher than the mean of the observed values. The approach presented here will be useful while assessing instream contaminations such as pathogen/pathogen indicator levels at the watershed scale.

Elevation as a proxy for mosquito-borne Zika virus transmission in the Americas.

PubMed

Watts, Alexander G; Miniota, Jennifer; Joseph, Heather A; Brady, Oliver J; Kraemer, Moritz U G; Grills, Ardath W; Morrison, Stephanie; Esposito, Douglas H; Nicolucci, Adriano; German, Matthew; Creatore, Maria I; Nelson, Bradley; Johansson, Michael A; Brunette, Gary; Hay, Simon I; Khan, Kamran; Cetron, Marty

2017-01-01

When Zika virus (ZIKV) first began its spread from Brazil to other parts of the Americas, national-level travel notices were issued, carrying with them significant economic consequences to affected countries. Although regions of some affected countries were likely unsuitable for mosquito-borne transmission of ZIKV, the absence of high quality, timely surveillance data made it difficult to confidently demarcate infection risk at a sub-national level. In the absence of reliable data on ZIKV activity, a pragmatic approach was needed to identify subnational geographic areas where the risk of ZIKV infection via mosquitoes was expected to be negligible. To address this urgent need, we evaluated elevation as a proxy for mosquito-borne ZIKV transmission. For sixteen countries with local ZIKV transmission in the Americas, we analyzed (i) modelled occurrence of the primary vector for ZIKV, Aedes aegypti, (ii) human population counts, and (iii) reported historical dengue cases, specifically across 100-meter elevation levels between 1,500m and 2,500m. Specifically, we quantified land area, population size, and the number of observed dengue cases above each elevation level to identify a threshold where the predicted risks of encountering Ae. aegypti become negligible. Above 1,600m, less than 1% of each country's total land area was predicted to have Ae. aegypti occurrence. Above 1,900m, less than 1% of each country's resident population lived in areas where Ae. aegypti was predicted to occur. Across all 16 countries, 1.1% of historical dengue cases were reported above 2,000m. These results suggest low potential for mosquito-borne ZIKV transmission above 2,000m in the Americas. Although elevation is a crude predictor of environmental suitability for ZIKV transmission, its constancy made it a pragmatic input for policy decision-making during this public health emergency.

Modeling evapotranspiration based on plant hydraulic theory can predict spatial variability across an elevation gradient and link to biogeochemical fluxes

NASA Astrophysics Data System (ADS)

Mackay, D. S.; Frank, J.; Reed, D.; Whitehouse, F.; Ewers, B. E.; Pendall, E.; Massman, W. J.; Sperry, J. S.

2012-04-01

In woody plant systems transpiration is often the dominant component of total evapotranspiration, and so it is key to understanding water and energy cycles. Moreover, transpiration is tightly coupled to carbon and nutrient fluxes, and so it is also vital to understanding spatial variability of biogeochemical fluxes. However, the spatial variability of transpiration and its links to biogeochemical fluxes, within- and among-ecosystems, has been a challenge to constrain because of complex feedbacks between physical and biological controls. Plant hydraulics provides an emerging theory with the rigor needed to develop testable hypotheses and build useful models for scaling these coupled fluxes from individual plants to regional scales. This theory predicts that vegetative controls over water, energy, carbon, and nutrient fluxes can be determined from the limitation of plant water transport through the soil-xylem-stomata pathway. Limits to plant water transport can be predicted from measurable plant structure and function (e.g., vulnerability to cavitation). We present a next-generation coupled transpiration-biogeochemistry model based on this emerging theory. The model, TREEScav, is capable of predicting transpiration, along with carbon and nutrient flows, constrained by plant structure and function. The model incorporates tightly coupled mechanisms of the demand and supply of water through the soil-xylem-stomata system, with the feedbacks to photosynthesis and utilizable carbohydrates. The model is evaluated by testing it against transpiration and carbon flux data along an elevation gradient of woody plants comprising sagebrush steppe, mid-elevation lodgepole pine forests, and subalpine spruce/fir forests in the Rocky Mountains. The model accurately predicts transpiration and carbon fluxes as measured from gas exchange, sap flux, and eddy covariance towers. The results of this work demonstrate that credible spatial predictions of transpiration and related biogeochemical fluxes will be possible at regional scales using relatively easily obtained vegetation structural and functional information.

Ecological Model to Predict Potential Habitats of Oncomelania hupensis, the Intermediate Host of Schistosoma japonicum in the Mountainous Regions, China.

PubMed

Zhu, Hong-Ru; Liu, Lu; Zhou, Xiao-Nong; Yang, Guo-Jing

2015-01-01

Schistosomiasis japonica is a parasitic disease that remains endemic in seven provinces in the People's Republic of China (P.R. China). One of the most important measures in the process of schistosomiasis elimination in P.R. China is control of Oncomelania hupensis, the unique intermediate host snail of Schistosoma japonicum. Compared with plains/swamp and lake regions, the hilly/mountainous regions of schistosomiasis endemic areas are more complicated, which makes the snail survey difficult to conduct precisely and efficiently. There is a pressing call to identify the snail habitats of mountainous regions in an efficient and cost-effective manner. Twelve out of 56 administrative villages distributed with O. hupensis in Eryuan, Yunnan Province, were randomly selected to set up the ecological model. Thirty out of the rest of 78 villages (villages selected for building model were excluded from the villages for validation) in Eryuan and 30 out of 89 villages in Midu, Yunnan Province were selected via a chessboard method for model validation, respectively. Nine-year-average Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) as well as Digital Elevation Model (DEM) covering Eryuan and Midu were extracted from MODIS and ASTER satellite images, respectively. Slope, elevation and the distance from every village to its nearest stream were derived from DEM. Suitable survival environment conditions for snails were defined by comparing historical snail presence data and remote sensing derived images. According to the suitable conditions for snails, environment factors, i.e. NDVI, LST, elevation, slope and the distance from every village to its nearest stream, were integrated into an ecological niche model to predict O. hupensis potential habitats in Eryuan and Midu. The evaluation of the model was assessed by comparing the model prediction and field investigation. Then, the consistency rate of model validation was calculated in Eryuan and Midu Counties, respectively. The final ecological niche model for potential O. hupensis habitats prediction comprised the following environmental factors, namely: NDVI (≥ 0.446), LST (≥ 22.70°C), elevation (≤ 2,300 m), slope (≤ 11°) and the distance to nearest stream (≤ 1,000 m). The potential O. hupensis habitats in Eryuan distributed in the Lancang River basin and O. hupensis in Midu shows a trend of clustering in the north and spotty distribution in the south. The consistency rates of the ecological niche model in Eryuan and Midu were 76.67% and 83.33%, respectively. The ecological niche model integrated with NDVI, LST, elevation, slope and distance from every village to its nearest stream adequately predicted the snail habitats in the mountainous regions.

Methodology Developed for Modeling the Fatigue Crack Growth Behavior of Single-Crystal, Nickel-Base Superalloys

NASA Technical Reports Server (NTRS)

1996-01-01

Because of their superior high-temperature properties, gas generator turbine airfoils made of single-crystal, nickel-base superalloys are fast becoming the standard equipment on today's advanced, high-performance aerospace engines. The increased temperature capabilities of these airfoils has allowed for a significant increase in the operating temperatures in turbine sections, resulting in superior propulsion performance and greater efficiencies. However, the previously developed methodologies for life-prediction models are based on experience with polycrystalline alloys and may not be applicable to single-crystal alloys under certain operating conditions. One of the main areas where behavior differences between single-crystal and polycrystalline alloys are readily apparent is subcritical fatigue crack growth (FCG). The NASA Lewis Research Center's work in this area enables accurate prediction of the subcritical fatigue crack growth behavior in single-crystal, nickel-based superalloys at elevated temperatures.

Dynamic Temporal Relations between Anxious and Depressive Symptoms across Adolescence

PubMed Central

Kouros, Chrystyna D.; Quasem, Susanna; Garber, Judy

2015-01-01

Symptoms of anxiety and depression are prevalent among adolescents and associated with impairment in multiple domains of functioning. Moreover, anxiety and depression frequently co-occur, with estimated comorbidity rates as high as 75%. Whereas previous research has shown that anxiety symptoms predict increased depressive symptoms over time, the relation between depressive symptoms and later anxiety symptoms has been inconsistent. The present study examined dynamic relations between anxiety and depressive symptoms across adolescence, and explored whether these longitudinal relations were moderated by maternal history of anxiety, family relationship quality, or children’s attributional style. Participants included 240 children (M age = 11.86 years; 53.9% female) and their mothers who were assessed annually for six years. Children reported on their depressive symptoms and mothers reported on their child’s anxiety symptoms. Dynamic latent change score models indicated that anxiety symptoms predicted subsequent elevations in depressive symptoms over time. Depressive symptoms predicted subsequent elevations in anxiety symptoms among children who had mothers with a history of anxiety, reported low family relationship quality, or had high levels of negative attributions. Thus, whereas anxiety symptoms were a robust predictor of later depressive symptoms during adolescence, contextual and individual factors may be important to consider when examining relations between depressive symptoms and subsequent change in anxiety symptoms. PMID:23880385

Critical Loads of Atmospheric Nitrogen Deposition for Aquatic Ecosystems in Yosemite and Sequoia and Kings Canyon National Parks

NASA Astrophysics Data System (ADS)

Nanus, L.; Clow, D. W.; Sickman, J. O.

2016-12-01

High-elevation aquatic ecosystems in Yosemite (YOSE) and Sequoia and Kings Canyon (SEKI) National Parks are impacted by atmospheric nitrogen (N) deposition associated with local and regional air pollution. Documented effects include elevated surface water nitrate concentrations, increased algal productivity, and changes in diatom species assemblages. Annual wet inorganic N deposition maps, developed at 1-km resolution for YOSE and SEKI to quantify N deposition to sensitive high-elevation ecosystems, range from 1.0 to over 5.0 kg N ha-1 yr-1. Critical loads of N deposition for nutrient enrichment of aquatic ecosystems were quantified and mapped using a geostatistical approach, with N deposition, topography, vegetation, geology, and climate as potential explanatory variables. Multiple predictive models were created using various combinations of explanatory variables; this approach allowed us to better quantify uncertainty and more accurately identify the areas most sensitive to atmospherically deposited N. The lowest critical loads estimates and highest exceedances identified within YOSE and SEKI occurred in high-elevation basins with steep slopes, sparse vegetation, and areas of neoglacial till and talus. These results are consistent with previous analyses in the Rocky Mountains, and highlight the sensitivity of alpine ecosystems to atmospheric N deposition.

Spatial prediction of landslide hazard using discriminant analysis and GIS

Treesearch

Peter V. Gorsevski; Paul Gessler; Randy B. Foltz

2000-01-01

Environmental attributes relevant for spatial prediction of landslides triggered by rain and snowmelt events were derived from digital elevation model (DEM). Those data in conjunction with statistics and geographic information system (GIS) provided a detailed basis for spatial prediction of landslide hazard. The spatial prediction of landslide hazard in this paper is...

Quantification of the impact of precipitation spatial distribution uncertainty on predictive uncertainty of a snowmelt runoff model

NASA Astrophysics Data System (ADS)

Jacquin, A. P.

2012-04-01

This study is intended to quantify the impact of uncertainty about precipitation spatial distribution on predictive uncertainty of a snowmelt runoff model. This problem is especially relevant in mountain catchments with a sparse precipitation observation network and relative short precipitation records. The model analysed is a conceptual watershed model operating at a monthly time step. The model divides the catchment into five elevation zones, where the fifth zone corresponds to the catchment's glaciers. Precipitation amounts at each elevation zone i are estimated as the product between observed precipitation at a station and a precipitation factor FPi. If other precipitation data are not available, these precipitation factors must be adjusted during the calibration process and are thus seen as parameters of the model. In the case of the fifth zone, glaciers are seen as an inexhaustible source of water that melts when the snow cover is depleted.The catchment case study is Aconcagua River at Chacabuquito, located in the Andean region of Central Chile. The model's predictive uncertainty is measured in terms of the output variance of the mean squared error of the Box-Cox transformed discharge, the relative volumetric error, and the weighted average of snow water equivalent in the elevation zones at the end of the simulation period. Sobol's variance decomposition (SVD) method is used for assessing the impact of precipitation spatial distribution, represented by the precipitation factors FPi, on the models' predictive uncertainty. In the SVD method, the first order effect of a parameter (or group of parameters) indicates the fraction of predictive uncertainty that could be reduced if the true value of this parameter (or group) was known. Similarly, the total effect of a parameter (or group) measures the fraction of predictive uncertainty that would remain if the true value of this parameter (or group) was unknown, but all the remaining model parameters could be fixed. In this study, first order and total effects of the group of precipitation factors FP1- FP4, and the precipitation factor FP5, are calculated separately. First order and total effects of the group FP1- FP4 are much higher than first order and total effects of the factor FP5, which are negligible This situation is due to the fact that the actual value taken by FP5 does not have much influence in the contribution of the glacier zone to the catchment's output discharge, mainly limited by incident solar radiation. In addition to this, first order effects indicate that, in average, nearly 25% of predictive uncertainty could be reduced if the true values of the precipitation factors FPi could be known, but no information was available on the appropriate values for the remaining model parameters. Finally, the total effects of the precipitation factors FP1- FP4 are close to 41% in average, implying that even if the appropriate values for the remaining model parameters could be fixed, predictive uncertainty would be still quite high if the spatial distribution of precipitation remains unknown. Acknowledgements: This research was funded by FONDECYT, Research Project 1110279.

A Community Perspective on the Effects of Climate Change on Species Distributions in the Boreal Forest of the Northeastern United States

NASA Astrophysics Data System (ADS)

Morelli, T. L.; DeLuca, W. V.; Duclos, T. R.; Foster, J. R.; Siren, A. P.

2016-12-01

The way that climate change will impact species ranges through habitat change and modify species interactions is not well enough understood. We took a community view of the climate-vulnerable, biologically-important spruce-fir forest ecosystem of the northeastern U.S., examining if and how species are responding to warming and changing precipitation patterns. We examined how fluctuations in temperature and snowpack influence distributional shifts along elevational and latitudinal gradients; for example, milder winter conditions may allow generalist carnivores such as bobcats to access boreal forest habitat, increasing direct and indirect competition with Canada lynx and American marten for prey. In another example of climate-driven predation shifts, upslope shifts of American red squirrels may increase predation rates on vulnerable montane songbirds. We combined data from weather stations with model-based high resolution data to obtain information on historical and present climate variables. We forecasted spruce-fir forest extent using landscape and ecosystem models under a combination of global circulation model projections and representative concentration pathways for the northern Appalachians. Presence and abundance data from animal surveys were used to build occupancy models to assess the habitat, climate, and species relationships. Species responded individually with geographic variation in response within and across species. Some species closely tracked climate changes, whereas others showed no response, or even responses such as shifts southward that were counter to what would be expected. For example, although low elevation boreal bird species showed evidence of expanding upslope, most high elevation species expanded downslope. This work highlights the need to take a mechanistic perspective of species responses to climate change and avoid generalizations of simple shifts northward and upward. Understanding how climate change affects community dynamics will improve predictions of how individual species will respond to climate change. These predictions then provide information about how distributional shifts will occur in a biologically critical ecosystem and if there will be climate change refugia they can target for management.

A Comparative Study on Johnson Cook, Modified Zerilli-Armstrong and Arrhenius-Type Constitutive Models to Predict High-Temperature Flow Behavior of Ti-6Al-4V Alloy in α + β Phase

NASA Astrophysics Data System (ADS)

Cai, Jun; Wang, Kuaishe; Han, Yingying

2016-03-01

True stress and true strain values obtained from isothermal compression tests over a wide temperature range from 1,073 to 1,323 K and a strain rate range from 0.001 to 1 s-1 were employed to establish the constitutive equations based on Johnson Cook, modified Zerilli-Armstrong (ZA) and strain-compensated Arrhenius-type models, respectively, to predict the high-temperature flow behavior of Ti-6Al-4V alloy in α + β phase. Furthermore, a comparative study has been made on the capability of the three models to represent the elevated temperature flow behavior of Ti-6Al-4V alloy. Suitability of the three models was evaluated by comparing both the correlation coefficient R and the average absolute relative error (AARE). The results showed that the Johnson Cook model is inadequate to provide good description of flow behavior of Ti-6Al-4V alloy in α + β phase domain, while the predicted values of modified ZA model and the strain-compensated Arrhenius-type model could agree well with the experimental values except under some deformation conditions. Meanwhile, the modified ZA model could track the deformation behavior more accurately than other model throughout the entire temperature and strain rate range.

A fluctuating plume dispersion model for the prediction of odour-impact frequencies from continuous stationary sources

NASA Astrophysics Data System (ADS)

Mussio, P.; Gnyp, A. W.; Henshaw, P. F.

A fluctuating plume dispersion model has been developed to facilitate the prediction of odour-impact frequencies in the communities surrounding elevated point sources. The model was used to predict the frequencies of occurrence of odours of various magnitudes for 1 h periods. In addition, the model predicted the maximum odour level. The model was tested with an extensive set of data collected in the residential areas surrounding the paint shop of an automotive assembly plant. Most of the perceived odours in the vicinity of the 64, 46 m high stacks ranged between 2 and 7 odour units and generally persisted for less than 30 s. Ninety-eight different field determinations of odour impact frequencies within 1 km of the plant were conducted during the course of the study. To simplify evaluation, the frequencies of occurrence of different odour levels were summed to give the total frequency of occurrence of all readily detectable (>2 OU) odours. The model provided excellent simulation of the total frequencies of occurrence where the odour was frequent (i.e . readily detectable more than 30% of the time). At lower frequencies of occurrence the model prediction was poor. The stability class did not seem to affect the model's ability to predict field frequency values. However, the model provided excellent predictions of the maximum odour levels without being sensitive to either stability class or distance from the source. Ninety-five percent of the predicted maximum values were within a factor of two of the measured field maximum values.

Predicting arsenic concentrations in groundwater of San Luis Valley, Colorado: implications for individual-level lifetime exposure assessment.

PubMed

James, Katherine A; Meliker, Jaymie R; Buttenfield, Barbara E; Byers, Tim; Zerbe, Gary O; Hokanson, John E; Marshall, Julie A

2014-08-01

Consumption of inorganic arsenic in drinking water at high levels has been associated with chronic diseases. Risk is less clear at lower levels of arsenic, in part due to difficulties in estimating exposure. Herein we characterize spatial and temporal variability of arsenic concentrations and develop models for predicting aquifer arsenic concentrations in the San Luis Valley, Colorado, an area of moderately elevated arsenic in groundwater. This study included historical water samples with total arsenic concentrations from 595 unique well locations. A longitudinal analysis established temporal stability in arsenic levels in individual wells. The mean arsenic levels for a random sample of 535 wells were incorporated into five kriging models to predict groundwater arsenic concentrations at any point in time. A separate validation dataset (n = 60 wells) was used to identify the model with strongest predictability. Findings indicate that arsenic concentrations are temporally stable (r = 0.88; 95 % CI 0.83-0.92 for samples collected from the same well 15-25 years apart) and the spatial model created using ordinary kriging best predicted arsenic concentrations (ρ = 0.72 between predicted and observed validation data). These findings illustrate the value of geostatistical modeling of arsenic and suggest the San Luis Valley is a good region for conducting epidemiologic studies of groundwater metals because of the ability to accurately predict variation in groundwater arsenic concentrations.

Use of a food web model to evaluate the factors responsible for high PCB fish concentrations in Lake Ellasjøen, a high arctic lake.

PubMed

Gewurtz, Sarah B; Gandhi, Nilima; Christensen, Guttorm N; Evenset, Anita; Gregor, Dennis; Diamond, Miriam L

2009-03-01

Lake Ellasjøen, located in the Norwegian high arctic, contains the highest concentrations of polychlorinated biphenyls (PCBs) ever recorded in fish and sediment from high arctic lakes, and concentrations are more than 10 times greater than in nearby Lake Øyangen. These elevated concentrations in Ellasjøen have been previously attributed, in part, to contaminant loadings from seabirds that use Ellasjøen, but not Øyangen, as a resting area. However, other factors, such as food web structure, organism growth rate, weight, lipid content, lake morphology, and nutrient inputs from the seabird guano, also differ between the two systems. The aim of this study is to evaluate the relative influence of these factors as explanatory variables for the higher PCB fish concentrations in Ellasjøen compared with Øyangen, using both a food web model and empirical data. The model is based on previously developed models but parameterized for Lakes Ellasjøen and Øyangen using measured data wherever possible. The model was applied to five representative PCB congeners (PCB 105, 118, 138, 153, and 180) using measured sediment and water concentrations as input data and evaluated with previously collected food web data. Modeled concentrations are within a factor of two of measured concentrations in 60% and 40% of the cases in Lakes Ellasjøen and Øyangen, respectively, and within a factor of 10 in 100% of the cases in both lakes. In many cases, this is comparable to the variability associated with the data as well as the efficacy of the predictions of other food web model applications. We next used the model to quantify the relative importance of five major differences between Ellasjøen and Øyangen by replacing variables representing each of these factors in the Ellasjøen model with those from Øyangen, in separate simulations. The model predicts that the elevated PCB concentrations in Ellasjøen water and sediment account for 49%-58% of differences in modeled fish PCB concentrations between lakes. These elevated sediment and, to a lesser extent, water concentrations in Ellasjøen are due to PCB loadings from seabird guano. However, sediment-water fugacity ratios of PCBs are consistently greater in Ellasjøen compared with Øyangen, which suggests that internal lake processes also contribute to differences in sediment and water concentrations. We hypothesize that the nutrients associated with guano influence sediment-water fugacity ratios of PCBs by increasing the stock of pelagic algae. As both these algae and the guano settle, their organic carbon content is degraded faster than PCBs, which causes an extra magnification step in Ellasjøen before these detrital particles are consumed by benthic organisms, which are in turn consumed by fish. The model predicts that the remaining approximately 50% of the differences in PCB concentrations observed between the fish of these lakes are due to other subtle differences in their food web structures. In conclusion, based on the results of a food web model, we found that the most dominant factors influencing the higher PCB fish concentrations in Lake Ellasjøen compared with Øyangen are the higher sediment and water concentrations in Ellasjøen, caused by seabird guano. Together, sediment and water are predicted to account for 49%-58% of differences in fish concentrations between lakes. Although seabird guano provides a source of nutrients to the lake, in addition to contaminants, empirical data and indirect model results suggest that nutrients are not leading to decreased bioaccumulation, in contrast to what has been observed in temperate, pelagic food webs. The results of this study emphasize the importance of considering even small differences in food web structure when comparing bioaccumulation in two lakes; although the food web structures of Ellasjøen and Øyangen differ only slightly, the model predicts that these differences account for most of the remaining approximately 50% of the differences in PCB fish concentrations between the two lakes. This study further demonstrates the utility of food web models as we were able to predict and tease apart the influence of various factors responsible for the elevated concentrations in the fish from Lake Ellasjøen, which would have been difficult using the field data alone.

Water-surface elevations for the high tide of December 15, 1977, in the Puget Sound region, Washington

USGS Publications Warehouse

Nelson, L.M.

1985-01-01

An unusually high oceanic tide on December 15, 1977, caused flooding of lowlying, nearshore parts of western Washington, including several areas in the Puget Sound region. At Seattle, the December 15 high tide of 14.8 feet above MLLW (mean lower low water datum; 8.55 feet above the National Geodetic Vertical Daltum of 1929, or NGVD) was 0.1 foot higher than the 100-year high tide. At Neah Bay, near the western end of the Straits of Juan de Fuca, however, the high tide of 8.77 feet MLLW (4.55 feet NGVD) on that date was 3.2 feet lower than the 100-year high tide. This study has identified the observed December 15 high-tide elevations at many locations in the Puget Sound region. The observed high tide then was much higher than predicted in most of the Puget Sound region, primarily as the result of a very low barametric pressure. Little damage from wind waves was reported. Elevation profiles for the predicted and observed high tides on December 15 and for several other selected tide levels indicate an increase in the maximum height in the inland direction, except near Port Angeles, and show abrupt changes in tidal elevations at three constrictions - Admiralty Inlet, Tacoma Narrows, and Deception Pass. (USGS)

How Do Tides and Tsunamis Interact in a Highly Energetic Channel? The Case of Canal Chacao, Chile

NASA Astrophysics Data System (ADS)

Winckler, Patricio; Sepúlveda, Ignacio; Aron, Felipe; Contreras-López, Manuel

2017-12-01

This study aims at understanding the role of tidal level, speed, and direction in tsunami propagation in highly energetic tidal channels. The main goal is to comprehend whether tide-tsunami interactions enhance/reduce elevation, currents speeds, and arrival times, when compared to pure tsunami models and to simulations in which tides and tsunamis are linearly superimposed. We designed various numerical experiments to compute the tsunami propagation along Canal Chacao, a highly energetic channel in the Chilean Patagonia lying on a subduction margin prone to megathrust earthquakes. Three modeling approaches were implemented under the same seismic scenario: a tsunami model with a constant tide level, a series of six composite models in which independent tide and tsunami simulations are linearly superimposed, and a series of six tide-tsunami nonlinear interaction models (full models). We found that hydrodynamic patterns differ significantly among approaches, being the composite and full models sensitive to both the tidal phase at which the tsunami is triggered and the local depth of the channel. When compared to full models, composite models adequately predicted the maximum surface elevation, but largely overestimated currents. The amplitude and arrival time of the tsunami-leading wave computed with the full model was found to be strongly dependent on the direction of the tidal current and less responsive to the tide level and the tidal current speed. These outcomes emphasize the importance of addressing more carefully the interactions of tides and tsunamis on hazard assessment studies.

Periodic limb movements of sleep: empirical and theoretical evidence supporting objective at-home monitoring

PubMed Central

Moro, Marilyn; Goparaju, Balaji; Castillo, Jelina; Alameddine, Yvonne; Bianchi, Matt T

2016-01-01

Introduction Periodic limb movements of sleep (PLMS) may increase cardiovascular and cerebrovascular morbidity. However, most people with PLMS are either asymptomatic or have nonspecific symptoms. Therefore, predicting elevated PLMS in the absence of restless legs syndrome remains an important clinical challenge. Methods We undertook a retrospective analysis of demographic data, subjective symptoms, and objective polysomnography (PSG) findings in a clinical cohort with or without obstructive sleep apnea (OSA) from our laboratory (n=443 with OSA, n=209 without OSA). Correlation analysis and regression modeling were performed to determine predictors of periodic limb movement index (PLMI). Markov decision analysis with TreeAge software compared strategies to detect PLMS: in-laboratory PSG, at-home testing, and a clinical prediction tool based on the regression analysis. Results Elevated PLMI values (>15 per hour) were observed in >25% of patients. PLMI values in No-OSA patients correlated with age, sex, self-reported nocturnal leg jerks, restless legs syndrome symptoms, and hypertension. In OSA patients, PLMI correlated only with age and self-reported psychiatric medications. Regression models indicated only a modest predictive value of demographics, symptoms, and clinical history. Decision modeling suggests that at-home testing is favored as the pretest probability of PLMS increases, given plausible assumptions regarding PLMS morbidity, costs, and assumed benefits of pharmacological therapy. Conclusion Although elevated PLMI values were commonly observed, routinely acquired clinical information had only weak predictive utility. As the clinical importance of elevated PLMI continues to evolve, it is likely that objective measures such as PSG or at-home PLMS monitors will prove increasingly important for clinical and research endeavors. PMID:27540316

Prognostic value of choline and betaine depends on intestinal microbiota-generated metabolite trimethylamine-N-oxide.

PubMed

Wang, Zeneng; Tang, W H Wilson; Buffa, Jennifer A; Fu, Xiaoming; Britt, Earl B; Koeth, Robert A; Levison, Bruce S; Fan, Yiying; Wu, Yuping; Hazen, Stanley L

2014-04-01

Recent metabolomics and animal model studies show trimethylamine-N-oxide (TMAO), an intestinal microbiota-dependent metabolite formed from dietary trimethylamine-containing nutrients such as phosphatidylcholine (PC), choline, and carnitine, is linked to coronary artery disease pathogenesis. Our aim was to examine the prognostic value of systemic choline and betaine levels in stable cardiac patients. We examined the relationship between fasting plasma choline and betaine levels and risk of major adverse cardiac events (MACE = death, myocardial infraction, stroke) in relation to TMAO over 3 years of follow-up in 3903 sequential stable subjects undergoing elective diagnostic coronary angiography. In our study cohort, median (IQR) TMAO, choline, and betaine levels were 3.7 (2.4-6.2)μM, 9.8 (7.9-12.2)μM, and 41.1 (32.5-52.1)μM, respectively. Modest but statistically significant correlations were noted between TMAO and choline (r = 0.33, P < 0.001) and less between TMAO and betaine (r = 0.09, P < 0.001). Higher plasma choline and betaine levels were associated with a 1.9-fold and 1.4-fold increased risk of MACE, respectively (Quartiles 4 vs. 1; P < 0.01, each). Following adjustments for traditional cardiovascular risk factors and high-sensitivity C-reactive protein, elevated choline [1.34 (1.03-1.74), P < 0.05], and betaine levels [1.33 (1.03-1.73), P < 0.05] each predicted increased MACE risk. Neither choline nor betaine predicted MACE risk when TMAO was added to the adjustment model, and choline and betaine predicted future risk for MACE only when TMAO was elevated. Elevated plasma levels of choline and betaine are each associated with incident MACE risk independent of traditional risk factors. However, high choline and betaine levels are only associated with higher risk of future MACE with concomitant increase in TMAO.

Prognostic value of choline and betaine depends on intestinal microbiota-generated metabolite trimethylamine-N-oxide

PubMed Central

Wang, Zeneng; Tang, W. H. Wilson; Buffa, Jennifer A.; Fu, Xiaoming; Britt, Earl B.; Koeth, Robert A.; Levison, Bruce S.; Fan, Yiying; Wu, Yuping; Hazen, Stanley L.

2014-01-01

Aims Recent metabolomics and animal model studies show trimethylamine-N-oxide (TMAO), an intestinal microbiota-dependent metabolite formed from dietary trimethylamine-containing nutrients such as phosphatidylcholine (PC), choline, and carnitine, is linked to coronary artery disease pathogenesis. Our aim was to examine the prognostic value of systemic choline and betaine levels in stable cardiac patients. Methods and results We examined the relationship between fasting plasma choline and betaine levels and risk of major adverse cardiac events (MACE = death, myocardial infraction, stroke) in relation to TMAO over 3 years of follow-up in 3903 sequential stable subjects undergoing elective diagnostic coronary angiography. In our study cohort, median (IQR) TMAO, choline, and betaine levels were 3.7 (2.4–6.2)μM, 9.8 (7.9–12.2)μM, and 41.1 (32.5–52.1)μM, respectively. Modest but statistically significant correlations were noted between TMAO and choline (r = 0.33, P < 0.001) and less between TMAO and betaine (r = 0.09, P < 0.001). Higher plasma choline and betaine levels were associated with a 1.9-fold and 1.4-fold increased risk of MACE, respectively (Quartiles 4 vs. 1; P < 0.01, each). Following adjustments for traditional cardiovascular risk factors and high-sensitivity C-reactive protein, elevated choline [1.34 (1.03–1.74), P < 0.05], and betaine levels [1.33 (1.03–1.73), P < 0.05] each predicted increased MACE risk. Neither choline nor betaine predicted MACE risk when TMAO was added to the adjustment model, and choline and betaine predicted future risk for MACE only when TMAO was elevated. Conclusion Elevated plasma levels of choline and betaine are each associated with incident MACE risk independent of traditional risk factors. However, high choline and betaine levels are only associated with higher risk of future MACE with concomitant increase in TMAO. PMID:24497336

Effects of Climate Change on Habitat Availability and Configuration for an Endemic Coastal Alpine Bird

PubMed Central

Jackson, Michelle M.; Gergel, Sarah E.; Martin, Kathy

2015-01-01

North America’s coastal mountains are particularly vulnerable to climate change, yet harbour a number of endemic species. With little room “at the top” to track shifting climate envelopes, alpine species may be especially negatively affected by climate-induced habitat fragmentation. We ask how climate change will affect the total amount, mean patch size, and number of patches of suitable habitat for Vancouver Island White-tailed Ptarmigan (Lagopus leucura saxatilis; VIWTP), a threatened, endemic alpine bird. Using a Random Forest model and a unique dataset consisting of citizen science observations combined with field surveys, we predict the distribution and configuration of potential suitable summer habitat for VIWTP under baseline and future (2020s, 2050s, and 2080s) climates using three general circulation models and two greenhouse gas scenarios. VIWTP summer habitat is predicted to decline by an average of 25%, 44%, and 56% by the 2020s, 2050s, and 2080s, respectively, under the low greenhouse gas scenario and 27%, 59%, and 74% under the high scenario. Habitat patches are predicted to become fragmented, with a 52–79% reduction in mean patch size. The average elevation of suitable habitat patches is expected to increase, reflecting a loss of patches at lower elevations. Thus ptarmigan are in danger of being “squeezed off the mountain”, as their remaining suitable habitat will be increasingly confined to mountaintops in the center of the island. The extent to which ptarmigan will be able to persist in increasingly fragmented habitat is unclear. Much will depend on their ability to move throughout a more heterogeneous landscape, utilize smaller breeding areas, and survive increasingly variable climate extremes. Our results emphasize the importance of continued monitoring and protection for high elevation specialist species, and suggest that White-tailed Ptarmigan should be considered an indicator species for alpine ecosystems in the face of climate change. PMID:26529306

Storm Surge Modeling of Typhoon Haiyan at the Naval Oceanographic Office Using Delft3D

NASA Astrophysics Data System (ADS)

Gilligan, M. J.; Lovering, J. L.

2016-02-01

The Naval Oceanographic Office provides estimates of the rise in sea level along the coast due to storm surge associated with tropical cyclones, typhoons, and hurricanes. Storm surge modeling and prediction helps the US Navy by providing a threat assessment tool to help protect Navy assets and provide support for humanitarian assistance/disaster relief efforts. Recent advancements in our modeling capabilities include the use of the Delft3D modeling suite as part of a Naval Research Laboratory (NRL) developed Coastal Surge Inundation Prediction System (CSIPS). Model simulations were performed on Typhoon Haiyan, which made landfall in the Philippines in November 2013. Comparisons of model simulations using forecast and hindcast track data highlight the importance of accurate storm track information for storm surge predictions. Model runs using the forecast track prediction and hindcast track information give maximum storm surge elevations of 4 meters and 6.1 meters, respectively. Model results for the hindcast simulation were compared with data published by the JSCE-PICE Joint survey for locations in San Pedro Bay (SPB) and on the Eastern Samar Peninsula (ESP). In SPB, where wind-induced set-up predominates, the model run using the forecast track predicted surge within 2 meters in 38% of survey locations and within 3 meters in 59% of the locations. When the hindcast track was used, the model predicted within 2 meters in 77% of the locations and within 3 meters in 95% of the locations. The model was unable to predict the high surge reported along the ESP produced by infragravity wave-induced set-up, which is not simulated in the model. Additional modeling capabilities incorporating infragravity waves are required to predict storm surge accurately along open coasts with steep bathymetric slopes, such as those seen in island arcs.

Particle-tracking investigation of the retention of sucker larvae emerging from spawning grounds in Upper Klamath Lake, Oregon

USGS Publications Warehouse

Wood, Tamara M.; Wherry, Susan A.; Simon, David C.; Markle, Douglas F.

2014-01-01

This study had two objectives: (1) to use the results of an individual-based particle-tracking model of larval sucker dispersal through the Williamson River delta and Upper Klamath Lake, Oregon, to interpret field data collected throughout Upper Klamath and Agency Lakes, and (2) to use the model to investigate the retention of sucker larvae in the system as a function of Williamson River flow, wind, and lake elevation. This is a follow-up study to work reported in Wood and others (2014) in which the hydrodynamic model of Upper Klamath Lake was combined with an individual-based, particle-tracking model of larval fish entering the lake from spawning areas in the Williamson River. In the previous study, the performance of the model was evaluated through comparison with field data comprising larval sucker distribution collected in 2009 by The Nature Conservancy, Oregon State University (OSU), and the U.S. Geological Survey, primarily from the (at that time) recently reconnected Williamson River Delta and along the eastern shoreline of Upper Klamath Lake, surrounding the old river mouth. The previous study demonstrated that the validation of the model with field data was moderately successful and that the model was useful for describing the broad patterns of larval dispersal from the river, at least in the areas surrounding the river channel immediately downstream of the spawning areas and along the shoreline where larvae enter the lake. In this study, field data collected by OSU throughout the main body of Upper Klamath Lake, and not just around the Williamson River Delta, were compared to model simulation results. Because the field data were collected throughout the lake, it was necessary to include in the simulations larvae spawned at eastern shoreline springs that were not included in the earlier studies. A complicating factor was that the OSU collected data throughout the main body of the lake in 2011 and 2012, after the end of several years of larval drift collection in the Williamson River by the U.S. Geological Survey. Those larval drift data provided necessary boundary-condition information for the earlier studies, but there were no measured boundary conditions for larval input into model simulations during the years of this study (2011−12). Therefore, we developed a method to estimate a time series of larval drift in the Williamson River, and of the emergence of larvae from the gravel at the eastern shoreline springs, that captured the approximate timing of the larval pulse of the Lost River sucker (Deltistes luxatus) and shortnose sucker (Chasmistes brevirostris) and the relative magnitude of the pulses by species and spawning location. The method is not able to predict larval drift on any given day, but it can reasonably predict the approximate temporal progression of the larval drift through the season, based on counts of adult suckers returning to spawn. The accuracy in the timing of the larval pulses is not better than about plus or minus 5 days. Model results and field data were consistent in the basic progression of both catch per unit effort (CPUE) and larval length through time. The model simulation results also duplicated some of the characteristics of the spatial patterns of density in the field data, notably the tendency for high larval densities closer to the eastern and western shorelines. However, the model simulations could not explain high densities in the northern part of the lake or far into Ball Bay, locations that are far from the source of larvae in the Williamson River or eastern shoreline springs (as measured along the predominant transport pathways simulated in the model). This suggests the possibility of unaccounted-for spawning areas in the northern part of the lake and also that the period during which larvae are transported passively by the currents is shorter than the 46 days simulated in the model. Similarly, the progression of larval lengths in the field data is not a simple progression from smaller to larger fish away from sources in the river and springs, as simulated by the particle-tracking model; the smallest fish were caught at different times near the Williamson River, in the northwestern part of the lake, and in the southernmost part of the lake. This again suggests that fish may be spawning at places other than the river and eastern springs, that our understanding of larval transport is incomplete, or both. The model was used to run 96 numerical “experiments” in which lake elevation, river discharge, and wind forcing were varied systematically in order to investigate the sensitivity of particle retention to each variable, and with particular emphasis on the idea of managing lake elevation to control emigration. The estimates of particle retention cannot be equated directly to retention of fish larvae, primarily because there was no mortality included in the simulations, but the relative comparison of retention and emigration around the matrix of experimental conditions provided several “big picture” results: - Variables that cannot be controlled—winds and discharge—had the largest effect on retention. For example, at the lowest river discharge (20 cubic meters per second), simulated retention was high regardless of wind or lake elevation, whereas at the highest river discharge (100 cubic meters per second), retention was low regardless of wind or lake elevation. - When river discharge and wind were held constant, a higher elevation delayed the onset of the most rapid exit of particles by 1 (from the springs) to 4 (from the river) days, but did not determine overall retention. Only under the combination of conditions consisting of low discharge (50 cubic meters per second or less) and strong wind reversals for several days was there a consistent effect of lake elevation on overall retention several weeks into the simulation, and, under those conditions, retention was at the high end of the possible range regardless of lake elevation. - Under most combinations of conditions tested, after particles had been in the system for several days, the complex interaction between wind, elevation, and river discharge resulted in particle pathways, and therefore retention, being highly variable and unpredictable, at which point controlling lake elevation could not produce a predictable result. Therefore, on the basis of the model predictions, managing lake elevation probably is not a way to reliably provide any particular level of retention.

Prognostic value, clinical effectiveness and cost-effectiveness of high sensitivity C-reactive protein as a marker in primary prevention of major cardiac events.

PubMed

Schnell-Inderst, Petra; Schwarzer, Ruth; Göhler, Alexander; Grandi, Norma; Grabein, Kristin; Stollenwerk, Björn; Klauß, Volker; Wasem, Jürgen; Siebert, Uwe

2009-05-12

In a substantial portion of patients (= 25%) with coronary heart disease (CHD), a myocardial infarction or sudden cardiac death without prior symptoms is the first manifestation of disease. The use of new risk predictors for CHD such as the high-sensitivity C-reactive Protein (hs-CRP) in addition to established risk factors could improve prediction of CHD. As a consequence of the altered risk assessment, modified preventive actions could reduce the number of cardiac death and non-fatal myocardial infarction. Does the additional information gained through the measurement of hs-CRP in asymptomatic patients lead to a clinically relevant improvement in risk prediction as compared to risk prediction based on traditional risk factors and is this cost-effective? A literature search of the electronic databases of the German Institute of Medical Documentation and Information (DIMDI) was conducted. Selection, data extraction, assessment of the study-quality and synthesis of information was conducted according to the methods of evidence-based medicine. Eight publications about predictive value, one publication on the clinical efficacy and three health-economic evaluations were included. In the seven study populations of the prediction studies, elevated CRP-levels were almost always associated with a higher risk of cardiovascular events and non-fatal myocardial infarctions or cardiac death and severe cardiovascular events. The effect estimates (odds ratio (OR), relative risk (RR), hazard ratio (HR)), once adjusted for traditional risk factors, demonstrated a moderate, independent association between hs-CRP and cardiac and cardiovascular events that fell in the range of 0.7 to 2.47. In six of the seven studies, a moderate increase in the area under the curve (AUC) could be detected by adding hs-CRP as a predictor to regression models in addition to established risk factors though in three cases this was not statistically significant. The difference [in the AUC] between the models with and without hs-CRP fell between 0.00 and 0.023 with a median of 0.003. A decision-analytic modeling study reported a gain in life-expectancy for those using statin therapy for populations with elevated hs-CRP levels and normal lipid levels as compared to statin therapy for those with elevated lipid levels (approximately 6.6 months gain in life-expectancy for 58 year olds). Two decision-analytic models (three publications) on cost-effectiveness reported incremental cost-effectiveness ratios between Euro 8,700 and 50,000 per life year gained for the German context and between 52,000 and 708,000 for the US context. The empirical input data for the model is highly uncertain. No sufficient evidence is available to support the notion that hs-CRP-values should be measured during the global risk assessment for CAD or cardiovascular disease in addition to the traditional risk factors. The additional measurement of the hs-CRP-level increases the incremental predictive value of the risk prediction. It has not yet been clarified whether this increase is clinically relevant resulting in reduction of cardiovascular morbidity and mortality. For people with medium cardiovascular risk (5 to 20% in ten years) additional measurement of hs-CRP seems most likely to be clinical relevant to support the decision as to whether or not additional statin therapy should be initiated for primary prevention. Statin therapy can reduce the occurrence of cardiovascular events for asymptomatic individuals with normal lipid and elevated hs-CRP levels. However, this is not enough to provide evidence for a clinical benefit of hs-CRP-screening. The cost-effectiveness of general hs-CRP-screening as well as screening among only those with normal lipid levels remains unknown at present.

Elevated red cell distribution width contributes to a poor prognosis in patients with esophageal carcinoma.

PubMed

Wan, Guo-Xing; Chen, Ping; Cai, Xiao-Jun; Li, Lin-Jun; Yu, Xiong-Jie; Pan, Dong-Feng; Wang, Xian-He; Wang, Xuan-Bin; Cao, Feng-Jun

2016-01-15

The red cell distribution width (RDW) has also been reported to reliably reflect the inflammation and nutrition status and predict the prognosis across several types of cancer, however, the prognostic value of RDW in esophageal carcinoma has seldom been studied. A retrospective study was performed to assess the prognostic value of RDW in patients with esophageal carcinoma by the Kaplan-Meier analysis and multivariate Cox regression proportional hazard model. All enrolled patients were divided into high RDW group (≧15%) and low RDW group (<15%) according to the detected RDW values. Clinical and laboratory data from a total of 179 patients with esophageal carcinoma were retrieved. With a median follow-up of 21months, the high RDW group exhibited a shorter disease-free survival (DFS) (p<0.001) and an unfavorable overall survival (OS) (p<0.001) in the univariate analysis. The multivariate analysis revealed that elevated RDW at diagnosis was an independent prognostic factor for shorter PFS (p=0.043, HR=1.907, 95% CI=1.020-3.565) and poor OS (p=0.042, HR=1.895, 95% CI=1.023-3.508) after adjustment with other cancer-related prognostic factors. The present study suggests that elevated preoperative RDW(≧15%) at the diagnosis may independently predict poorer disease-free and overall survival among patients with esophageal carcinoma. Copyright © 2015 Elsevier B.V. All rights reserved.

Can urine dipstick predict an elevated serum creatinine?

PubMed

Shah, Kaushal; Kilian, Barbara; Hsieh, Wei-Jen; Kyrillou, Emily; Hedge, Vishal; Newman, David H

2010-06-01

Chart review studies have suggested that point-of-care urine dipstick testing may accurately predict an elevation in serum creatinine (Cr). We aimed to prospectively evaluate the test characteristics of proteinuria/hematuria in predicting elevated serum Cr. A prospective, observational study was conducted between March 2007 and June 2008 at 2 affiliated, urban hospitals with an annual emergency department census of 150,000. Patients undergoing laboratory urinalysis, point-of-care urine dipstick, and a serum chemistry panel were enrolled. Trained research assistants collected data on consecutive patients 18 hours per day using preformatted data forms and entry into an anonymized Access (Microsoft, Seattle, Wash) database. Demographic baseline variables including age, sex, chief complaint, vital signs, and source of sample (catheter vs "clean catch") were also collected. An elevated Cr level was defined as greater than 1.3 based on the laboratory reference range. Standard statistical methods were used to calculate diagnostic test operating characteristics of proteinuria or hematuria as a predictor of elevated serum Cr. Five thousand four hundred sixteen subjects were enrolled with 28.3% male and a mean age of 50.2 years. Elevated serum Cr greater than 1.3 mg/dL was found in 13.9% (755/5416) of subjects. The sensitivity of either proteinuria or hematuria for elevated Cr was 82.5% (95% confidence interval [CI], 80%-85%) and specificity was 34.4% (95% CI, 33%-36%). Positive predictive value was 16.9% (95% CI, 16%-18%) and negative predictive value was 92.4% (95% CI, 91-94%). The likelihood ratio for a positive test was 1.3 (95% CI, 1.1-1.5), and the likelihood ratio for a negative test was 0.5 (95% CI, 0.3-0.8). Although negative predictive value was high, the presence of proteinuria/hematuria was only moderately predictive of elevated serum Cr level. Copyright (c) 2010 Elsevier Inc. All rights reserved.

Utilization of small changes in serum creatinine with clinical risk factors to assess the risk of AKI in critically lll adults.

PubMed

Cruz, Dinna N; Ferrer-Nadal, Asunción; Piccinni, Pasquale; Goldstein, Stuart L; Chawla, Lakhmir S; Alessandri, Elisa; Belluomo Anello, Clara; Bohannon, Will; Bove, Tiziana; Brienza, Nicola; Carlini, Mauro; Forfori, Francesco; Garzotto, Francesco; Gramaticopolo, Silvia; Iannuzzi, Michele; Montini, Luca; Pelaia, Paolo; Ronco, Claudio

2014-04-01

Disease biomarkers require appropriate clinical context to be used effectively. Combining clinical risk factors, in addition to small changes in serum creatinine, has been proposed to improve the assessment of AKI. This notion was developed in order to identify the risk of AKI early in a patient's clinical course. We set out to assess the performance of this combination approach. A secondary analysis of data from a prospective multicenter intensive care unit cohort study (September 2009 to April 2010) was performed. Patients at high risk using this combination approach were defined as an early increase in serum creatinine of 0.1-0.4 mg/dl, depending on number of clinical factors predisposing to AKI. AKI was defined and staged using the Acute Kidney Injury Network criteria. The primary outcome was evolution to severe AKI (Acute Kidney Injury Network stages 2 and 3) within 7 days in the intensive care unit. Of 506 patients, 214 (42.2%) patients had early creatinine elevation and were deemed at high risk for AKI. This group was more likely to subsequently develop the primary endpoint (16.4% versus 1.0% [not at high risk], P<0.001). The sensitivity of this grouping for severe AKI was 92%, the specificity was 62%, the positive predictive value was 16%, and the negative predictive value was 99%. After adjustment for Sequential Organ Failure Assessment score, serum creatinine, and hazard tier for AKI, early creatinine elevation remained an independent predictor for severe AKI (adjusted relative risk, 12.86; 95% confidence interval, 3.52 to 46.97). Addition of early creatinine elevation to the best clinical model improved prediction of the primary outcome (area under the receiver operating characteristic curve increased from 0.75 to 0.83, P<0.001). Critically ill patients at high AKI risk, based on the combination of clinical factors and early creatinine elevation, are significantly more likely to develop severe AKI. As initially hypothesized, the high-risk combination group methodology can be used to identify patients at low risk for severe AKI in whom AKI biomarker testing may be expected to have low yield. The high risk combination group methodology could potentially allow clinicians to optimize biomarker use.

A practical tool for estimating subsurface LNAPL distributions and transmissivity using current and historical fluid levels in groundwater wells: Effects of entrapped and residual LNAPL

NASA Astrophysics Data System (ADS)

Lenhard, R. J.; Rayner, J. L.; Davis, G. B.

2017-10-01

A model is presented to account for elevation-dependent residual and entrapped LNAPL above and below, respectively, the water-saturated zone when predicting subsurface LNAPL specific volume (fluid volume per unit area) and transmissivity from current and historic fluid levels in wells. Physically-based free, residual, and entrapped LNAPL saturation distributions and LNAPL relative permeabilities are integrated over a vertical slice of the subsurface to yield the LNAPL specific volumes and transmissivity. The model accounts for effects of fluctuating water tables. Hypothetical predictions are given for different porous media (loamy sand and clay loam), fluid levels in wells, and historic water-table fluctuations. It is shown the elevation range from the LNAPL-water interface in a well to the upper elevation where the free LNAPL saturation approaches zero is the same for a given LNAPL thickness in a well regardless of porous media type. Further, the LNAPL transmissivity is largely dependent on current fluid levels in wells and not historic levels. Results from the model can aid developing successful LNAPL remediation strategies and improving the design and operation of remedial activities. Results of the model also can aid in accessing the LNAPL recovery technology endpoint, based on the predicted transmissivity.

Machine learning of structural magnetic resonance imaging predicts psychopathic traits in adolescent offenders.

PubMed

Steele, Vaughn R; Rao, Vikram; Calhoun, Vince D; Kiehl, Kent A

2017-01-15

Classification models are becoming useful tools for finding patterns in neuroimaging data sets that are not observable to the naked eye. Many of these models are applied to discriminating clinical groups such as schizophrenic patients from healthy controls or from patients with bipolar disorder. A more nuanced model might be to discriminate between levels of personality traits. Here, as a proof of concept, we take an initial step toward developing prediction models to differentiate individuals based on a personality disorder: psychopathy. We included three groups of adolescent participants: incarcerated youth with elevated psychopathic traits (i.e., callous and unemotional traits and conduct disordered traits; n=71), incarcerated youth with low psychopathic traits (n=72), and non-incarcerated youth as healthy controls (n=21). Support vector machine (SVM) learning models were developed to separate these groups using an out-of-sample cross-validation method on voxel-based morphometry (VBM) data. Regions of interest from the paralimbic system, identified in an independent forensic sample, were successful in differentiating youth groups. Models seeking to classify incarcerated individuals to have high or low psychopathic traits achieved 69.23% overall accuracy. As expected, accuracy increased in models differentiating healthy controls from individuals with high psychopathic traits (82.61%) and low psychopathic traits (80.65%). Here we have laid the foundation for using neural correlates of personality traits to identify group membership within and beyond psychopathy. This is only the first step, of many, toward prediction models using neural measures as a proxy for personality traits. As these methods are improved, prediction models with neural measures of personality traits could have far-reaching impact on diagnosis, treatment, and prediction of future behavior. Copyright © 2015 Elsevier Inc. All rights reserved.

Machine Learning of Structural Magnetic Resonance Imaging Predicts Psychopathic Traits in Adolescent Offenders

PubMed Central

Steele, Vaughn R.; Rao, Vikram; Calhoun, Vince D.; Kiehl, Kent A.

2015-01-01

Classification models are becoming useful tools for finding patterns in neuroimaging data sets that are not observable to the naked eye. Many of these models are applied to discriminating clinical groups such as schizophrenic patients from healthy controls or from patients with bipolar disorder. A more nuanced model might be to discriminate between levels of personality traits. Here, as a proof-of-concept, we take an initial step toward developing prediction models to differentiate individuals based on a personality disorder: psychopathy. We included three groups of adolescent participants: incarcerated youth with elevated psychopathic traits (i.e., callous and unemotional traits and conduct disordered traits; n = 71), incarcerated youth with low psychopathic traits (n =72), and non-incarcerated youth as healthy controls (n = 21). Support vector machine (SVM) learning models were developed to separate these groups using an out-of-sample cross-validation method on voxel-based morphometry (VBM) data. Regions-of-interest from the paralimbic system, identified in an independent forensic sample, were successful in differentiating youth groups. Models seeking to classify incarcerated individuals to have high or low psychopathic traits achieved 69.23% overall accuracy. As expected, accuracy increased in models differentiating healthy controls from individuals with high psychopathic traits (82.61%) and low psychopathic traits (80.65%). Here we have laid the foundation for using neural correlates of personality traits to identify group membership within and beyond psychopathy. This is only the first step, of many, toward prediction models using neural measures as a proxy for personality traits. As these methods are improved, prediction models with neural measures of personality traits could have far-reaching impact on diagnosis, treatment, and prediction of future behavior. PMID:26690808

Differential Risk for Late Adolescent Conduct Problems and Mood Dysregulation Among Children with Early Externalizing Behavior Problems

PubMed Central

Bierman, Karen L.

2016-01-01

To investigate the differential emergence of antisocial behaviors and mood dysregulation among children with externalizing problems, the present study prospectively followed 317 high-risk children with early externalizing problems from school entry (ages 5–7) to late adolescence (ages 17–19). Latent class analysis conducted on their conduct and mood symptoms in late adolescence revealed three distinct patterns of symptoms, characterized by: 1) criminal offenses, conduct disorder symptoms, and elevated anger (“conduct problems”), 2) elevated anger, dysphoric mood, and suicidal ideation (“mood dysregulation”), and 3) low levels of severe conduct and mood symptoms. A diathesis-stress model predicting the first two outcomes was tested. Elevated overt aggression at school entry uniquely predicted conduct problems in late adolescence, whereas elevated emotion dysregulation at school entry uniquely predicted mood dysregulation in late adolescence. Experiences of low parental warmth and peer rejection in middle childhood moderated the link between early emotion dysregulation and later mood dysregulation but did not moderate the link between early overt aggression and later conduct problems. Thus, among children with early externalizing behavior problems, increased risk for later antisocial behavior or mood dysfunction may be identifiable in early childhood based on levels of overt aggression and emotion dysregulation. For children with early emotion dysregulation, however, increased risk for mood dysregulation characterized by anger, dysphoric mood, and suicidality – possibly indicative of disruptive mood dysregulation disorder – emerges only in the presence of low parental warmth and/or peer rejection during middle childhood. PMID:25183553

Simulation of Tracer Concentration Data in the Brush Creek Drainage Flow Using an Integrated Puff Model.

NASA Astrophysics Data System (ADS)

Rao, K. Shankar; Eckman, Richard M.; Hosker, Rayford P., Jr.

1989-07-01

During the 1984 ASCOT field study in Brush Creek Valley, two perfluorocarbon tracers were released into the nocturnal drainage flow at two different heights. The resulting surface concentrations were sampled at 90 sites, and vertical concentration profiles at 11 sites. These detailed tracer measurements provide a valuable dataset for developing and testing models of pollutant transport and dispersion in valleys.In this paper, we present the results of Gaussian puff model simulations of the tracer releases in Brush Creek Valley. The model was modified to account for the restricted lateral dispersion in the valley, and for the gross elevation differences between the release site and the receptors. The variable wind fields needed to transport the puffs were obtained by interpolation between wind profiles measured using tethered balloons at five along-valley sites. Direct turbulence measurements were used to estimate diffusion. Subsidence in the valley flow was included for elevated releases.Two test simulations-covering different nights, tracers, and release heights-were performed. The predicted hourly concentrations were compared with observations at 51 ground-level locations. At most sites, the predicted and observed concentrations agree within a factor of 2 to 6. For the elevated release simulation, the observed mean concentration is 40 pL/L, the predicted mean is 21 pL/L, the correlation coefficient between the observed and predicted concentrations is 0.24, and the index of agreement is 0.46. For the surface release simulation, the observed mean is 85 pL/L, and the predicted mean is 73 pL/L. The correlation coefficient is 0.23, and the index of agreement is 0.42. The results suggest that this modified puff model can be used as a practical tool for simulating pollutant transport and dispersion in deep valleys.

Wetland Accretion Rate Model of Ecosystem Resilience (WARMER) and its application to habitat sustainability for endangered species in the San Francisco Estuary

USGS Publications Warehouse

Swanson, Kathleen M.; Drexler, Judith Z.; Schoellhamer, David H.; Thorne, Karen M.; Casazza, Michael L.; Overton, Cory T.; Callaway, John C.; Takekawa, John Y.

2014-01-01

Salt marsh faunas are constrained by specific habitat requirements for marsh elevation relative to sea level and tidal range. As sea level rises, changes in relative elevation of the marsh plain will have differing impacts on the availability of habitat for marsh obligate species. The Wetland Accretion Rate Model for Ecosystem Resilience (WARMER) is a 1-D model of elevation that incorporates both biological and physical processes of vertical marsh accretion. Here, we use WARMER to evaluate changes in marsh surface elevation and the impact of these elevation changes on marsh habitat for specific species of concern. Model results were compared to elevation-based habitat criteria developed for marsh vegetation, the endangered California clapper rail (Rallus longirostris obsoletus), and the endangered salt marsh harvest mouse (Reithrodontomys raviventris) to determine the response of marsh habitat for each species to predicted >1-m sea-level rise by 2100. Feedback between vertical accretion mechanisms and elevation reduced the effect of initial elevation in the modeled scenarios. Elevation decreased nonlinearly with larger changes in elevation during the latter half of the century when the rate of sea-level rise increased. Model scenarios indicated that changes in elevation will degrade habitat quality within salt marshes in the San Francisco Estuary, and degradation will accelerate in the latter half of the century as the rate of sea-level rise accelerates. A sensitivity analysis of the model results showed that inorganic sediment accumulation and the rate of sea-level rise had the greatest influence over salt marsh sustainability.

Application of a prediction model for work-related sensitisation in bakery workers.

PubMed

Meijer, E; Suarthana, E; Rooijackers, J; Grobbee, D E; Jacobs, J H; Meijster, T; de Monchy, J G R; van Otterloo, E; van Rooy, F G B G J; Spithoven, J J G; Zaat, V A C; Heederik, D J J

2010-10-01

Identification of work-related allergy, particularly work-related asthma, in a (nationwide) medical surveillance programme among bakery workers requires an effective and efficient strategy. Bakers at high risk of having work-related allergy were indentified by use of a questionnaire-based prediction model for work-related sensitisation. The questionnaire was applied among 5,325 participating bakers. Sequential diagnostic investigations were performed only in those with an elevated risk. Performance of the model was evaluated in 674 randomly selected bakers who participated in the medical surveillance programme and the validation study. Clinical investigations were evaluated in the first 73 bakers referred at high risk. Overall 90% of bakers at risk of having asthma could be identified. Individuals at low risk showed 0.3-3.8% work-related respiratory symptoms, medication use or absenteeism. Predicting flour sensitisation by a simple questionnaire and score chart seems more effective at detecting work-related allergy than serology testing followed by clinical investigation in all immunoglobulin E class II-positive individuals. This prediction based stratification procedure appeared effective in detecting work-related allergy among bakers and can accurately be used for periodic examination, especially in small enterprises where delivery of adequate care is difficult. This approach may contribute to cost reduction.

Modeling of groundwater productivity in northeastern Wasit Governorate, Iraq using frequency ratio and Shannon's entropy models

NASA Astrophysics Data System (ADS)

Al-Abadi, Alaa M.

2017-05-01

In recent years, delineation of groundwater productivity zones plays an increasingly important role in sustainable management of groundwater resource throughout the world. In this study, groundwater productivity index of northeastern Wasit Governorate was delineated using probabilistic frequency ratio (FR) and Shannon's entropy models in framework of GIS. Eight factors believed to influence the groundwater occurrence in the study area were selected and used as the input data. These factors were elevation (m), slope angle (degree), geology, soil, aquifer transmissivity (m2/d), storativity (dimensionless), distance to river (m), and distance to faults (m). In the first step, borehole location inventory map consisting of 68 boreholes with relatively high yield (>8 l/sec) was prepared. 47 boreholes (70 %) were used as training data and the remaining 21 (30 %) were used for validation. The predictive capability of each model was determined using relative operating characteristic technique. The results of the analysis indicate that the FR model with a success rate of 87.4 % and prediction rate 86.9 % performed slightly better than Shannon's entropy model with success rate of 84.4 % and prediction rate of 82.4 %. The resultant groundwater productivity index was classified into five classes using natural break classification scheme: very low, low, moderate, high, and very high. The high-very high classes for FR and Shannon's entropy models occurred within 30 % (217 km2) and 31 % (220 km2), respectively indicating low productivity conditions of the aquifer system. From final results, both of the models were capable to prospect GWPI with very good results, but FR was better in terms of success and prediction rates. Results of this study could be helpful for better management of groundwater resources in the study area and give planners and decision makers an opportunity to prepare appropriate groundwater investment plans.

Potential Effects of Climate Change on the Distribution of Cold-Tolerant Evergreen Broadleaved Woody Plants in the Korean Peninsula.

PubMed

Koo, Kyung Ah; Kong, Woo-Seok; Nibbelink, Nathan P; Hopkinson, Charles S; Lee, Joon Ho

2015-01-01

Climate change has caused shifts in species' ranges and extinctions of high-latitude and altitude species. Most cold-tolerant evergreen broadleaved woody plants (shortened to cold-evergreens below) are rare species occurring in a few sites in the alpine and subalpine zones in the Korean Peninsula. The aim of this research is to 1) identify climate factors controlling the range of cold-evergreens in the Korean Peninsula; and 2) predict the climate change effects on the range of cold-evergreens. We used multimodel inference based on combinations of climate variables to develop distribution models of cold-evergreens at a physiognomic-level. Presence/absence data of 12 species at 204 sites and 6 climatic factors, selected from among 23 candidate variables, were used for modeling. Model uncertainty was estimated by mapping a total variance calculated by adding the weighted average of within-model variation to the between-model variation. The range of cold-evergreens and model performance were validated by true skill statistics, the receiver operating characteristic curve and the kappa statistic. Climate change effects on the cold-evergreens were predicted according to the RCP 4.5 and RCP 8.5 scenarios. Multimodel inference approach excellently projected the spatial distribution of cold-evergreens (AUC = 0.95, kappa = 0.62 and TSS = 0.77). Temperature was a dominant factor in model-average estimates, while precipitation was minor. The climatic suitability increased from the southwest, lowland areas, to the northeast, high mountains. The range of cold-evergreens declined under climate change. Mountain-tops in the south and most of the area in the north remained suitable in 2050 and 2070 under the RCP 4.5 projection and 2050 under the RCP 8.5 projection. Only high-elevations in the northeastern Peninsula remained suitable under the RCP 8.5 projection. A northward and upper-elevational range shift indicates change in species composition at the alpine and subalpine ecosystems in the Korean Peninsula.

Potential Effects of Climate Change on the Distribution of Cold-Tolerant Evergreen Broadleaved Woody Plants in the Korean Peninsula

PubMed Central

Koo, Kyung Ah; Kong, Woo-Seok; Nibbelink, Nathan P.; Hopkinson, Charles S.; Lee, Joon Ho

2015-01-01

Climate change has caused shifts in species’ ranges and extinctions of high-latitude and altitude species. Most cold-tolerant evergreen broadleaved woody plants (shortened to cold-evergreens below) are rare species occurring in a few sites in the alpine and subalpine zones in the Korean Peninsula. The aim of this research is to 1) identify climate factors controlling the range of cold-evergreens in the Korean Peninsula; and 2) predict the climate change effects on the range of cold-evergreens. We used multimodel inference based on combinations of climate variables to develop distribution models of cold-evergreens at a physiognomic-level. Presence/absence data of 12 species at 204 sites and 6 climatic factors, selected from among 23 candidate variables, were used for modeling. Model uncertainty was estimated by mapping a total variance calculated by adding the weighted average of within-model variation to the between-model variation. The range of cold-evergreens and model performance were validated by true skill statistics, the receiver operating characteristic curve and the kappa statistic. Climate change effects on the cold-evergreens were predicted according to the RCP 4.5 and RCP 8.5 scenarios. Multimodel inference approach excellently projected the spatial distribution of cold-evergreens (AUC = 0.95, kappa = 0.62 and TSS = 0.77). Temperature was a dominant factor in model-average estimates, while precipitation was minor. The climatic suitability increased from the southwest, lowland areas, to the northeast, high mountains. The range of cold-evergreens declined under climate change. Mountain-tops in the south and most of the area in the north remained suitable in 2050 and 2070 under the RCP 4.5 projection and 2050 under the RCP 8.5 projection. Only high-elevations in the northeastern Peninsula remained suitable under the RCP 8.5 projection. A northward and upper-elevational range shift indicates change in species composition at the alpine and subalpine ecosystems in the Korean Peninsula. PMID:26262755

A new seamless, high-resolution digital elevation model of the San Francisco Bay-Delta Estuary, California

USGS Publications Warehouse

Fregoso, Theresa A.; Wang, Rueen-Fang; Ateljevich, Eli; Jaffe, Bruce E.

2017-06-14

Climate change, sea-level rise, and human development have contributed to the changing geomorphology of the San Francisco Bay - Delta (Bay-Delta) Estuary system. The need to predict scenarios of change led to the development of a new seamless, high-resolution digital elevation model (DEM) of the Bay – Delta that can be used by modelers attempting to understand potential future changes to the estuary system. This report details the three phases of the creation of this DEM. The first phase took a bathymetric-only DEM created in 2005 by the U.S. Geological Survey (USGS), refined it with additional data, and identified areas that would benefit from new surveys. The second phase began a USGS collaboration with the California Department of Water Resources (DWR) that updated a 2012 DWR seamless bathymetric/topographic DEM of the Bay-Delta with input from the USGS and modifications to fit the specific needs of USGS modelers. The third phase took the work from phase 2 and expanded the coverage area in the north to include the Yolo Bypass up to the Fremont Weir, the Sacramento River up to Knights Landing, and the American River up to the Nimbus Dam, and added back in the elevations for interior islands. The constant evolution of the Bay-Delta will require continuous updates to the DEM of the Delta, and there still are areas with older data that would benefit from modern surveys. As a result, DWR plans to continue updating the DEM.

Trait rumination and response to negative evaluative lab-induced stress: neuroendocrine, affective, and cognitive outcomes.

PubMed

Vrshek-Schallhorn, Suzanne; Velkoff, Elizabeth A; Zinbarg, Richard E

2018-04-06

Theoretical models of depression posit that, under stress, elevated trait rumination predicts more pronounced or prolonged negative affective and neuroendocrine responses, and that trait rumination hampers removing irrelevant negative information from working memory. We examined several gaps regarding these models in the context of lab-induced stress. Non-depressed undergraduates completed a rumination questionnaire and either a negative-evaluative Trier Social Stress Test (n = 55) or a non-evaluative control condition (n = 69), followed by a modified Sternberg affective working memory task assessing the extent to which irrelevant negative information can be emptied from working memory. We measured shame, negative and positive affect, and salivary cortisol four times. Multilevel growth curve models showed rumination and stress interactively predicted cortisol reactivity; however, opposite predictions, greater rumination was associated with blunted cortisol reactivity to stress. Elevated trait rumination interacted with stress to predict augmented shame reactivity. Rumination and stress did not significantly interact to predict working memory performance, but under control conditions, rumination predicted greater difficulty updating working memory. Results support a vulnerability-stress model of trait rumination with heightened shame reactivity and cortisol dysregulation rather than hyper-reactivity in non-depressed emerging adults, but we cannot provide evidence that working memory processes are critical immediately following acute stress.

Accounting for Selectivity Bias and Correlation Across the Sequence From Elevated Blood Pressure to Hypertension Diagnosis and Treatment.

PubMed

Gordon-Larsen, Penny; Attard, Samantha M; Howard, Annie Green; Popkin, Barry M; Zhang, Bing; Du, Shufa; Guilkey, David K

2017-12-08

It is unknown whether efforts to reduce hypertension burden in countries with very high prevalence, would be more effective if directed at hypertension diagnosis vs. treatment. Most analyses do not address bias and correlation across the sequence from elevated blood pressure (BP) to hypertension diagnosis and treatment, leading to potentially misleading findings. Using data spanning 18 years of the China Health and Nutrition Survey (n = 18,926; ages 18-75 years), we used an innovative 3-step, integrated system of equations to predict the sequence from: (i) elevated BP (systolic/diastolic BP ≥ 140/90 mm Hg) to (ii) diagnosed hypertension conditional on elevated BP, and to (iii) treatment (medication use) conditional on diagnosis, accounting for measured and unmeasured individual- and community-level confounders at each of the 3 steps. We compared results to separate traditional logistic regression models without control for unmeasured confounding. Using our 3-step model, elevated BP increased from 12.6% and 8.5% (1991) to 36.8% and 29% (2009) in men and women, respectively, but diagnosis remained under 50%. We found widening disparities in hypertension diagnosis (higher hypertension at lower vs. higher education (difference of 2% in 1991 that widened to 5% in 2009)) and narrowing disparities in education (difference of 6% in 1991 to 4% in 2009) and insurance status (difference of 7% in 1991 to 2% in 2009) for treatment. Our 3-step model improved model fit over traditionally used models. Our findings highlight serious barriers to hypertension diagnosis in Chinese adults, particularly among men and individuals of low attained education. © American Journal of Hypertension, Ltd 2017. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Comparing and evaluating model estimates of background ozone in surface air over North America

NASA Astrophysics Data System (ADS)

Oberman, J.; Fiore, A. M.; Lin, M.; Zhang, L.; Jacob, D. J.; Naik, V.; Horowitz, L. W.

2011-12-01

Tropospheric ozone adversely affects human health and vegetation, and is thus a criteria pollutant regulated by the U.S. Environmental Protection Agency (EPA) under the National Ambient Air Quality Standard (NAAQS). Ozone is produced in the atmosphere via photo-oxidation of volatile organic compounds (VOCs) and carbon monoxide (CO) in the presence of nitrogen oxides (NOx). The present EPA approach considers health risks associated with exposure to ozone enhancement above the policy-relevant background (PRB), which is currently defined as the surface concentration of ozone that would exist without North American anthropogenic emissions. PRB thus includes production by natural precursors, production by precursors emitted on foreign continents, and transport of stratospheric ozone into surface air. As PRB is not an observable quantity, it must be estimated using numerical models. We compare PRB estimates for the year 2006 from the GFDL Atmospheric Model 3 (AM3) chemistry-climate model (CCM) and the GEOS-Chem (GC) chemical transport model (CTM). We evaluate the skill of the models in reproducing total surface ozone observed at the U.S. Clean Air Status and Trends Network (CASTNet), dividing the stations into low-elevation (< 1.5 km in altitude, primarily eastern) and high-elevation (> 1.5 km in altitude, all western) subgroups. At the low-elevation sites AM3 estimates of PRB (38±9 ppbv in spring, 27±9 ppbv in summer) are higher than GC (27±7 ppbv in spring, 21±8 ppbv in summer) in both seasons. Analysis at these sites is complicated by a positive bias in AM3 total ozone with respect to the observed total ozone, the source of which is yet unclear. At high-elevation sites, AM3 PRB is higher in the spring (47±8 ppbv) than in the summer (33±8 ppbv). In contrast, GC simulates little seasonal variation at high elevation sites (39±5 ppbv in spring vs. 38±7 ppbv in summer). Seasonal average total ozone at these sites was within 4 ppbv of the observations for both spring and summer in both models. The high elevation springtime maximum in PRB predicted by AM3 likely reflects stronger exchange between the surface and the free troposphere relative to GC, including a larger influence of stratospheric ozone. Higher summertime PRB in GC may be associated with differences in how the models treat the lightning NOx source (~10 times higher in GC over the Southwest U.S.). Biomass burning emissions (treated differently in the two models) contribute to episodic PRB enhancements in AM3 over the Midwest and East Coast. We conclude that further multi-model studies, including additional models, could provide the EPA with a more robust estimate of PRB, particularly if designed to isolate the relative roles of emissions, chemistry and transport, and evaluated with observation-based constraints wherever possible.

Assessment of Glacial Isostatic Adjustment in Greenland using GPS

NASA Astrophysics Data System (ADS)

Khan, S. A.; Bevis, M. G.; Sasgen, I.; van Dam, T. M.; Wahr, J. M.; Wouters, B.; Bamber, J. L.; Willis, M. J.; Knudsen, P.; Helm, V.; Kuipers Munneke, P.; Muresan, I. S.

2015-12-01

The Greenland GPS network (GNET) was constructed to provide a new means to assess viscoelastic and elastic adjustments driven by past and present-day changes in ice mass. Here we assess existing glacial isostatic adjustments (GIA) predictions by analysing 1995-2015 data from 61 continuous GPS receivers located along the margin of the Greenland ice sheet. Since GPS receivers measure both the GIA and elastic signals, we isolate GIA, by removing the elastic adjustments of the lithosphere due to present-day mass changes using high-resolution fields of ice surface elevation change derived from satellite and airborne altimetry measurements (ERS1/2, ICESat, ATM, ENVISAT, and CryoSat-2). For most GPS stations, our observed GIA rates contradict GIA predictions; particularly, we find huge uplift rates in southeast Greenland of up to 14 mm/yr while models predict rates of 0-2 mm/yr. Our results suggest possible improvements of GIA predictions, and hence of the poorly constrained ice load history and Earth structure models for Greenland.

Predicting patterns of non-native plant invasions in Yosemite National Park, California, USA

USGS Publications Warehouse

Underwood, E.C.; Klinger, R.; Moore, P.E.

2004-01-01

One of the major issues confronting management of parks and reserves is the invasion of non-native plant species. Yosemite National Park is one of the largest and best-known parks in the United States, harbouring significant cultural and ecological resources. Effective management of non-natives would be greatly assisted by information on their potential distribution that can be generated by predictive modelling techniques. Our goal was to identify key environmental factors that were correlated with the percent cover of non-native species and then develop a predictive model using the Genetic Algorithm for Rule-set Production technique. We performed a series of analyses using community-level data on species composition in 236 plots located throughout the park. A total of 41 non-native species were recorded which occurred in 23.7% of the plots. Plots with non-natives occurred most frequently at low- to mid-elevations, in flat areas with other herbaceous species. Based on the community-level results, we selected elevation, slope, and vegetation structure as inputs into the GARP model to predict the environmental niche of non-native species. Verification of results was performed using plot data reserved from the model, which calculated the correct prediction of non-native species occurrence as 76%. The majority of the western, lower-elevation portion of the park was predicted to have relatively low levels of non-native species occurrence, with highest concentrations predicted at the west and south entrances and in the Yosemite Valley. Distribution maps of predicted occurrences will be used by management to: efficiently target monitoring of non-native species, prioritize control efforts according to the likelihood of non-native occurrences, and inform decisions relating to the management of non-native species in postfire environments. Our approach provides a valuable tool for assisting decision makers to better manage non-native species, which can be readily adapted to target non-native species in other locations.

Photogrammetry for environmental monitoring: the use of drones and hydrological models for detection of soil contaminated by copper.

PubMed

Capolupo, Alessandra; Pindozzi, Stefania; Okello, Collins; Fiorentino, Nunzio; Boccia, Lorenzo

2015-05-01

Campania Region of Southern Italy has a complex environmental situation, due to geogenic and anthropogenic soil pollution. Some of the pollutants such as copper are mobilized in the organic matter. It has been shown that wetlands provide physical as well as biogeochemical barriers against pollutants. Therefore, the objective of this study was to introduce and test an innovative approach able to predict copper accumulation points at plot scales, using a combination of aerial photos, taken by drones, micro-rill network modelling and wetland prediction indices usually used at catchment scales. Data were collected from an area measuring 4500 m(2) in Trentola Ducenta locality of Caserta Province of southern Italy. The photos processing with a fifth generation software for photogrammetry resulted in a high resolution Digital Elevation Model (DEM), used to study micro-rill processes. The DEM was also used to test the ability of Topographic Index (TI) and the Clima-Topographic Index (CTI) to predict copper sedimentation points at plot scale (0.1-10 ha) by comparing the map of the predicted and the actual copper distribution in the field. The DEM obtained with a resolution of 30 mm showed a high potential for the study of micro-rill processes and TI and CTI indices were able to predict zones of copper accumulation at a plot scale. Copyright © 2015 Elsevier B.V. All rights reserved.

Elevated CO2 compensates for water stress in northern red oak

Treesearch

Patricia T. Tomlinson; Paul D. Anderson

1996-01-01

Global climate change models predict decreased rainfall in association with elevated CO2 in the western Lakes States region. Currently, the western edge of northern red oak (Quercus rubra L.) distribution coincides with the most xeric conditions of its ecological range. Decreased rainfall and water availability could alter...

Social anxiety and work status: the role of negative metacognitive beliefs, symptom severity and cognitive-behavioural factors.

PubMed

Nordahl, Henrik; Wells, Adrian

2017-06-24

Psychological health has a profound effect on personal and occupational functioning with Social Anxiety Symptoms in particular having a major effect on ability to work. Recent initiatives have focused on treating psychological illness with cognitive-behavioural models with a view to increasing return to work. However, the psychological correlates of work status amongst individuals with elevated mental health symptoms such as social anxiety are under-explored. This study reports a test of unique predictors of work status drawing on variables that have been given centre stage in cognitive-behavioural models and in the metacognitive model of psychological disorder. The sample consisted of high socially anxious individuals who reported to be working (n = 102) or receiving disability benefits (n = 102). A comparison of these groups showed that those out of work and receiving benefits had greater symptom severity, higher avoidance and use of safety behaviours, greater self-consciousness, and elevated negative metacognitive beliefs and beliefs about the need to control thoughts. However, when the covariance's between these variables were controlled, only negative metacognitive beliefs significantly predicted out-of-work status. Our finding might be important because CBT does not focus on metacognitive beliefs, but targets components that in our analysis had no unique predictive value for work status.

Assessment of a numerical model to reproduce event-scale erosion and deposition distributions in a braided river.

PubMed

Williams, R D; Measures, R; Hicks, D M; Brasington, J

2016-08-01

Numerical morphological modeling of braided rivers, using a physics-based approach, is increasingly used as a technique to explore controls on river pattern and, from an applied perspective, to simulate the impact of channel modifications. This paper assesses a depth-averaged nonuniform sediment model (Delft3D) to predict the morphodynamics of a 2.5 km long reach of the braided Rees River, New Zealand, during a single high-flow event. Evaluation of model performance primarily focused upon using high-resolution Digital Elevation Models (DEMs) of Difference, derived from a fusion of terrestrial laser scanning and optical empirical bathymetric mapping, to compare observed and predicted patterns of erosion and deposition and reach-scale sediment budgets. For the calibrated model, this was supplemented with planform metrics (e.g., braiding intensity). Extensive sensitivity analysis of model functions and parameters was executed, including consideration of numerical scheme for bed load component calculations, hydraulics, bed composition, bed load transport and bed slope effects, bank erosion, and frequency of calculations. Total predicted volumes of erosion and deposition corresponded well to those observed. The difference between predicted and observed volumes of erosion was less than the factor of two that characterizes the accuracy of the Gaeuman et al. bed load transport formula. Grain size distributions were best represented using two φ intervals. For unsteady flows, results were sensitive to the morphological time scale factor. The approach of comparing observed and predicted morphological sediment budgets shows the value of using natural experiment data sets for model testing. Sensitivity results are transferable to guide Delft3D applications to other rivers.

Predicting Greater Prairie-Chicken Lek Site Suitability to Inform Conservation Actions

PubMed Central

Hovick, Torre J.; Dahlgren, David K.; Papeş, Monica; Elmore, R. Dwayne; Pitman, James C.

2015-01-01

The demands of a growing human population dictates that expansion of energy infrastructure, roads, and other development frequently takes place in native rangelands. Particularly, transmission lines and roads commonly divide rural landscapes and increase fragmentation. This has direct and indirect consequences on native wildlife that can be mitigated through thoughtful planning and proactive approaches to identifying areas of high conservation priority. We used nine years (2003–2011) of Greater Prairie-Chicken (Tympanuchus cupido) lek locations totaling 870 unique leks sites in Kansas and seven geographic information system (GIS) layers describing land cover, topography, and anthropogenic structures to model habitat suitability across the state. The models obtained had low omission rates (<0.18) and high area under the curve scores (AUC >0.81), indicating high model performance and reliability of predicted habitat suitability for Greater Prairie-Chickens. We found that elevation was the most influential in predicting lek locations, contributing three times more predictive power than any other variable. However, models were improved by the addition of land cover and anthropogenic features (transmission lines, roads, and oil and gas structures). Overall, our analysis provides a hierarchal understanding of Greater Prairie-Chicken habitat suitability that is broadly based on geomorphological features followed by land cover suitability. We found that when land features and vegetation cover are suitable for Greater Prairie-Chickens, fragmentation by anthropogenic sources such as roadways and transmission lines are a concern. Therefore, it is our recommendation that future human development in Kansas avoid areas that our models identified as highly suitable for Greater Prairie-Chickens and focus development on land cover types that are of lower conservation concern. PMID:26317349

Predicting Greater Prairie-Chicken Lek Site Suitability to Inform Conservation Actions.

PubMed

Hovick, Torre J; Dahlgren, David K; Papeş, Monica; Elmore, R Dwayne; Pitman, James C

2015-01-01

The demands of a growing human population dictates that expansion of energy infrastructure, roads, and other development frequently takes place in native rangelands. Particularly, transmission lines and roads commonly divide rural landscapes and increase fragmentation. This has direct and indirect consequences on native wildlife that can be mitigated through thoughtful planning and proactive approaches to identifying areas of high conservation priority. We used nine years (2003-2011) of Greater Prairie-Chicken (Tympanuchus cupido) lek locations totaling 870 unique leks sites in Kansas and seven geographic information system (GIS) layers describing land cover, topography, and anthropogenic structures to model habitat suitability across the state. The models obtained had low omission rates (<0.18) and high area under the curve scores (AUC >0.81), indicating high model performance and reliability of predicted habitat suitability for Greater Prairie-Chickens. We found that elevation was the most influential in predicting lek locations, contributing three times more predictive power than any other variable. However, models were improved by the addition of land cover and anthropogenic features (transmission lines, roads, and oil and gas structures). Overall, our analysis provides a hierarchal understanding of Greater Prairie-Chicken habitat suitability that is broadly based on geomorphological features followed by land cover suitability. We found that when land features and vegetation cover are suitable for Greater Prairie-Chickens, fragmentation by anthropogenic sources such as roadways and transmission lines are a concern. Therefore, it is our recommendation that future human development in Kansas avoid areas that our models identified as highly suitable for Greater Prairie-Chickens and focus development on land cover types that are of lower conservation concern.

Study on real-time elevator brake failure predictive system

NASA Astrophysics Data System (ADS)

Guo, Jun; Fan, Jinwei

2013-10-01

This paper presented a real-time failure predictive system of the elevator brake. Through inspecting the running state of the coil by a high precision long range laser triangulation non-contact measurement sensor, the displacement curve of the coil is gathered without interfering the original system. By analyzing the displacement data using the diagnostic algorithm, the hidden danger of the brake system can be discovered in time and thus avoid the according accident.

The Canadian Hydrological Model (CHM): A multi-scale, variable-complexity hydrological model for cold regions

NASA Astrophysics Data System (ADS)

Marsh, C.; Pomeroy, J. W.; Wheater, H. S.

2016-12-01

There is a need for hydrological land surface schemes that can link to atmospheric models, provide hydrological prediction at multiple scales and guide the development of multiple objective water predictive systems. Distributed raster-based models suffer from an overrepresentation of topography, leading to wasted computational effort that increases uncertainty due to greater numbers of parameters and initial conditions. The Canadian Hydrological Model (CHM) is a modular, multiphysics, spatially distributed modelling framework designed for representing hydrological processes, including those that operate in cold-regions. Unstructured meshes permit variable spatial resolution, allowing coarse resolutions at low spatial variability and fine resolutions as required. Model uncertainty is reduced by lessening the necessary computational elements relative to high-resolution rasters. CHM uses a novel multi-objective approach for unstructured triangular mesh generation that fulfills hydrologically important constraints (e.g., basin boundaries, water bodies, soil classification, land cover, elevation, and slope/aspect). This provides an efficient spatial representation of parameters and initial conditions, as well as well-formed and well-graded triangles that are suitable for numerical discretization. CHM uses high-quality open source libraries and high performance computing paradigms to provide a framework that allows for integrating current state-of-the-art process algorithms. The impact of changes to model structure, including individual algorithms, parameters, initial conditions, driving meteorology, and spatial/temporal discretization can be easily tested. Initial testing of CHM compared spatial scales and model complexity for a spring melt period at a sub-arctic mountain basin. The meshing algorithm reduced the total number of computational elements and preserved the spatial heterogeneity of predictions.

Will the Effects of Sea-Level Rise Create Ecological Traps for Pacific Island Seabirds?

PubMed

Reynolds, Michelle H; Courtot, Karen N; Berkowitz, Paul; Storlazzi, Curt D; Moore, Janet; Flint, Elizabeth

2015-01-01

More than 18 million seabirds nest on 58 Pacific islands protected within vast U.S. Marine National Monuments (1.9 million km2). However, most of these seabird colonies are on low-elevation islands and sea-level rise (SLR) and accompanying high-water perturbations are predicted to escalate with climate change. To understand how SLR may impact protected islands and insular biodiversity, we modeled inundation and wave-driven flooding of a globally important seabird rookery in the subtropical Pacific. We acquired new high-resolution Digital Elevation Models (DEMs) and used the Delft3D wave model and ArcGIS to model wave heights and inundation for a range of SLR scenarios (+0.5, +1.0, +1.5, and +2.0 m) at Midway Atoll. Next, we classified vegetation to delineate habitat exposure to inundation and identified how breeding phenology, colony synchrony, and life history traits affect species-specific sensitivity. We identified 3 of 13 species as highly vulnerable to SLR in the Hawaiian Islands and quantified their atoll-wide distribution (Laysan albatross, Phoebastria immutabilis; black-footed albatross, P. nigripes; and Bonin petrel, Pterodroma hypoleuca). Our models of wave-driven flooding forecast nest losses up to 10% greater than passive inundation models at +1.0 m SLR. At projections of + 2.0 m SLR, approximately 60% of albatross and 44% of Bonin petrel nests were overwashed displacing more than 616,400 breeding albatrosses and petrels. Habitat loss due to passive SLR may decrease the carrying capacity of some islands to support seabird colonies, while sudden high-water events directly reduce survival and reproduction. This is the first study to simulate wave-driven flooding and the combined impacts of SLR, groundwater rise, and storm waves on seabird colonies. Our results highlight the need for early climate change planning and restoration of higher elevation seabird refugia to prevent low-lying protected islands from becoming ecological traps in the face of rising sea levels.

Will the effects of sea-level rise create ecological traps for Pacific Island seabirds?

USGS Publications Warehouse

Reynolds, Michelle H.; Courtot, Karen; Berkowitz, Paul; Storlazzi, Curt; Moore, Janet; Flint, Elizabeth

2015-01-01

More than 18 million seabirds nest on 58 Pacific islands protected within vast U.S. Marine National Monuments (1.9 million km2). However, most of these seabird colonies are on low-elevation islands and sea-level rise (SLR) and accompanying high-water perturbations are predicted to escalate with climate change. To understand how SLR may impact protected islands and insular biodiversity, we modeled inundation and wave-driven flooding of a globally important seabird rookery in the subtropical Pacific. We acquired new high-resolution Digital Elevation Models (DEMs) and used the Delft3D wave model and ArcGIS to model wave heights and inundation for a range of SLR scenarios (+0.5, +1.0, +1.5, and +2.0 m) at Midway Atoll. Next, we classified vegetation to delineate habitat exposure to inundation and identified how breeding phenology, colony synchrony, and life history traits affect species-specific sensitivity. We identified 3 of 13 species as highly vulnerable to SLR in the Hawaiian Islands and quantified their atoll-wide distribution (Laysan albatross, Phoebastria immutabilis; black-footed albatross, P. nigripes; and Bonin petrel, Pterodroma hypoleuca). Our models of wave-driven flooding forecast nest losses up to 10% greater than passive inundation models at +1.0 m SLR. At projections of + 2.0 m SLR, approximately 60% of albatross and 44% of Bonin petrel nests were overwashed displacing more than 616,400 breeding albatrosses and petrels. Habitat loss due to passive SLR may decrease the carrying capacity of some islands to support seabird colonies, while sudden high-water events directly reduce survival and reproduction. This is the first study to simulate wave-driven flooding and the combined impacts of SLR, groundwater rise, and storm waves on seabird colonies. Our results highlight the need for early climate change planning and restoration of higher elevation seabird refugia to prevent low-lying protected islands from becoming ecological traps in the face of rising sea levels.

Will the Effects of Sea-Level Rise Create Ecological Traps for Pacific Island Seabirds?

PubMed Central

Reynolds, Michelle H.; Courtot, Karen N.; Berkowitz, Paul; Storlazzi, Curt D.; Moore, Janet; Flint, Elizabeth

2015-01-01

More than 18 million seabirds nest on 58 Pacific islands protected within vast U.S. Marine National Monuments (1.9 million km2). However, most of these seabird colonies are on low-elevation islands and sea-level rise (SLR) and accompanying high-water perturbations are predicted to escalate with climate change. To understand how SLR may impact protected islands and insular biodiversity, we modeled inundation and wave-driven flooding of a globally important seabird rookery in the subtropical Pacific. We acquired new high-resolution Digital Elevation Models (DEMs) and used the Delft3D wave model and ArcGIS to model wave heights and inundation for a range of SLR scenarios (+0.5, +1.0, +1.5, and +2.0 m) at Midway Atoll. Next, we classified vegetation to delineate habitat exposure to inundation and identified how breeding phenology, colony synchrony, and life history traits affect species-specific sensitivity. We identified 3 of 13 species as highly vulnerable to SLR in the Hawaiian Islands and quantified their atoll-wide distribution (Laysan albatross, Phoebastria immutabilis; black-footed albatross, P. nigripes; and Bonin petrel, Pterodroma hypoleuca). Our models of wave-driven flooding forecast nest losses up to 10% greater than passive inundation models at +1.0 m SLR. At projections of + 2.0 m SLR, approximately 60% of albatross and 44% of Bonin petrel nests were overwashed displacing more than 616,400 breeding albatrosses and petrels. Habitat loss due to passive SLR may decrease the carrying capacity of some islands to support seabird colonies, while sudden high-water events directly reduce survival and reproduction. This is the first study to simulate wave-driven flooding and the combined impacts of SLR, groundwater rise, and storm waves on seabird colonies. Our results highlight the need for early climate change planning and restoration of higher elevation seabird refugia to prevent low-lying protected islands from becoming ecological traps in the face of rising sea levels. PMID:26398209

Improving ecophysiological simulation models to predict the impact of elevated atmospheric CO2 concentration on crop productivity

PubMed Central

Yin, Xinyou

2013-01-01

Background Process-based ecophysiological crop models are pivotal in assessing responses of crop productivity and designing strategies of adaptation to climate change. Most existing crop models generally over-estimate the effect of elevated atmospheric [CO2], despite decades of experimental research on crop growth response to [CO2]. Analysis A review of the literature indicates that the quantitative relationships for a number of traits, once expressed as a function of internal plant nitrogen status, are altered little by the elevated [CO2]. A model incorporating these nitrogen-based functional relationships and mechanisms simulated photosynthetic acclimation to elevated [CO2], thereby reducing the chance of over-estimating crop response to [CO2]. Robust crop models to have small parameterization requirements and yet generate phenotypic plasticity under changing environmental conditions need to capture the carbon–nitrogen interactions during crop growth. Conclusions The performance of the improved models depends little on the type of the experimental facilities used to obtain data for parameterization, and allows accurate projections of the impact of elevated [CO2] and other climatic variables on crop productivity. PMID:23388883

Serum biomarkers of bone metabolism in castration-resistant prostate cancer patients with skeletal metastases: results from SWOG 0421.

PubMed

Lara, Primo N; Ely, Benjamin; Quinn, David I; Mack, Philip C; Tangen, Catherine; Gertz, Erik; Twardowski, Przemyslaw W; Goldkorn, Amir; Hussain, Maha; Vogelzang, Nicholas J; Thompson, Ian M; Van Loan, Marta D

2014-04-01

Prior studies suggest that elevated markers of bone turnover are prognostic for poor survival in castration-resistant prostate cancer (CRPC). The predictive role of these markers relative to bone-targeted therapy is unknown. We prospectively evaluated the prognostic and predictive value of bone biomarkers in sera from CRPC patients treated on a placebo-controlled phase III trial of docetaxel with or without the bone targeted endothelin-A receptor antagonist atrasentan (SWOG S0421). Markers for bone resorption (N-telopeptide and pyridinoline) and formation (C-terminal collagen propeptide and bone alkaline phosphatase) were assayed in pretreatment and serial sera. Cox proportional hazards regression models were fit for overall survival. Models were fit with main effects for marker levels and with/without terms for marker-treatment interaction, adjusted for clinical variables, to assess the prognostic and predictive value of atrasentan. Analysis was adjusted for multiple comparisons. Two-sided P values were calculated using the Wald test. Sera from 778 patients were analyzed. Elevated baseline levels of each of the markers were associated with worse survival (P < .001). Increasing marker levels by week nine of therapy were also associated with subsequent poor survival (P < .001). Patients with the highest marker levels (upper 25th percentile for all markers) not only had a poor prognosis (hazard ratio [HR] = 4.3; 95% confidence interval [CI] = 2.41 to 7.65; P < .001) but also had a survival benefit from atrasentan (HR = 0.33; 95% CI = 0.15 to 0.71; median survival = 13 [atrasentan] vs 5 months [placebo]; P interaction = .005). Serum bone metabolism markers have statistically significant independent prognostic value in CRPC. Importantly, a small group of patients (6%) with highly elevated markers of bone turnover appear to preferentially benefit from atrasentan therapy.

The Dengue Virus Mosquito Vector Aedes aegypti at High Elevation in México

PubMed Central

Lozano-Fuentes, Saul; Hayden, Mary H.; Welsh-Rodriguez, Carlos; Ochoa-Martinez, Carolina; Tapia-Santos, Berenice; Kobylinski, Kevin C.; Uejio, Christopher K.; Zielinski-Gutierrez, Emily; Monache, Luca Delle; Monaghan, Andrew J.; Steinhoff, Daniel F.; Eisen, Lars

2012-01-01

México has cities (e.g., México City and Puebla City) located at elevations > 2,000 m and above the elevation ceiling below which local climates allow the dengue virus mosquito vector Aedes aegypti to proliferate. Climate warming could raise this ceiling and place high-elevation cities at risk for dengue virus transmission. To assess the elevation ceiling for Ae. aegypti and determine the potential for using weather/climate parameters to predict mosquito abundance, we surveyed 12 communities along an elevation/climate gradient from Veracruz City (sea level) to Puebla City (∼2,100 m). Ae. aegypti was commonly encountered up to 1,700 m and present but rare from 1,700 to 2,130 m. This finding extends the known elevation range in México by > 300 m. Mosquito abundance was correlated with weather parameters, including temperature indices. Potential larval development sites were abundant in Puebla City and other high-elevation communities, suggesting that Ae. aegypti could proliferate should the climate become warmer. PMID:22987656

Assessments on landslide susceptibility in the Tseng-wen reservoir watershed, Taiwan

NASA Astrophysics Data System (ADS)

Chen, Yu-Chin; Chen, Yung-Chau; Chen, Wen-Fu

2014-05-01

Typhoon Morakot under the strong influence of southwestern monsoon wind struck Taiwan on 8 August 2009, and dumped record-breaking rains in southern Taiwan. It triggered enormous landslides in mountains and severe flooding in low-lying areas. In addition, it destroyed or damaged houses, agricultural fields, roads, bridges, and other infrastructure facilities, causing massive economic loss and, more tragically, human casualties. In order to evaluate landslide hazard and risk assessment, it is important to understand the potential sites of landslide and their spatial distribution. Multi-temporal satellite images and geo-spatial data are used to build landslide susceptibility map for the post-disaster in the Tseng-wen reservoir watershed in this research. Elevation, slope, aspect, NDVI (normalized differential vegetation index), relief, roughness, distance to river, and distance to road are the considered factors for estimating landslide susceptibility. Maximum hourly rainfall and total rainfall, accompanied with typhoon event, are selected as the trigger factors of landslide events. Logistic regression analysis is adopted as the statistical method to model landslide susceptibility. The assessed susceptibility is represented in 4 levels which are high, high-intermediate, intermediate, and low level, respectively. Landslide spatial distribution can be depicted as a landslide susceptibility map with respect to each considered influence factors for a specified susceptible level. The landslide areas are about 358 ha and 1,485 ha before and after typhoon Morakot. The new landslide area, induced by typhoon Morakot, is as almost 4 times as the landslide area before typhoon Morakot. In addition, there is about 44.56% landslide area elevation ranging from 500m to 1000m and about 57.22% average slope ranging from 30° to 45° of landslide area. Furthermore, the devastating landslides were happened at those sites close to rivers, exposed area, and area with big land cover change (high human development). Among considered factors, slope, distance to river, NDVI, and maximum hourly rainfall are the major influence factors for landslide susceptibility. The results show that the accuracy of predicted landslide area is 74.74% and AUC is 0.82 corresponding to typhoon Morakot. Comparing model predicted with actual landslide areas, it shows that the predicted accuracy is 93% for high or high-intermediate level landslide area. It suggests that a landslide susceptibility map, depicted by this assessment model, is applicable on landslide prediction.

Slant path rain attenuation and path diversity statistics obtained through radar modeling of rain structure

NASA Technical Reports Server (NTRS)

Goldhirsh, J.

1984-01-01

Single and joint terminal slant path attenuation statistics at frequencies of 28.56 and 19.04 GHz have been derived, employing a radar data base obtained over a three-year period at Wallops Island, VA. Statistics were independently obtained for path elevation angles of 20, 45, and 90 deg for purposes of examining how elevation angles influences both single-terminal and joint probability distributions. Both diversity gains and autocorrelation function dependence on site spacing and elevation angles were determined employing the radar modeling results. Comparisons with other investigators are presented. An independent path elevation angle prediction technique was developed and demonstrated to fit well with the radar-derived single and joint terminal radar-derived cumulative fade distributions at various elevation angles.

Modeling Aspect Controlled Formation of Seasonally Frozen Ground on Montane Hillslopes: a Case Study from Gordon Gulch, Colorado

NASA Astrophysics Data System (ADS)

Rush, M.; Rajaram, H.; Anderson, R. S.; Anderson, S. P.

2017-12-01

The Intergovernmental Panel on Climate Change (2013) warns that high-elevation ecosystems are extremely vulnerable to climate change due to short growing seasons, thin soils, sparse vegetation, melting glaciers, and thawing permafrost. Many permafrost-free regions experience seasonally frozen ground. The spatial distribution of frozen soil exerts a strong control on subsurface flow and transport processes by reducing soil permeability and impeding infiltration. Accordingly, evolution of the extent and duration of frozen ground may alter streamflow seasonality, groundwater flow paths, and subsurface storage, presenting a need for coupled thermal-hydrologic models to project hydrologic responses to climate warming in high-elevation regions. To be useful as predictive tools, such models should incorporate the heterogeneity of solar insolation, vegetation, and snowpack dynamics. We present a coupled thermal-hydrologic modeling study against the backdrop of field observations from Gordon Gulch, a seasonally snow-covered montane catchment in the Colorado Front Range in the Boulder Creek Critical Zone Observatory. The field site features two instrumented hillslopes with opposing aspects: the snowpack on the north-facing slope persists throughout much of the winter season, while the snowpack on the south-facing slope is highly ephemeral. We implemented a surface energy balance and snowpack accumulation and ablation model that is coupled to the subsurface flow and transport code PFLOTRAN-ICE to predict the hydrologic consequences of aspect-controlled frozen soil formation during water years 2013-2016. Preliminary model results demonstrate the occurrence of seasonally-frozen ground on the north-facing slope that directs snowmelt to the stream by way of shallow subsurface flow paths. The absence of persistently frozen ground on the south-facing slope allows deeper infiltration of snowmelt recharge. The differences in subsurface flow paths also suggest strong aspect-controlled heterogeneities in nitrate export and differences in geomorphic processes such as frost creep.

Estimating soot emissions from an elevated flare

NASA Astrophysics Data System (ADS)

Almanza, Victor; Sosa, Gustavo

2009-11-01

Combustion aerosols are one of the major concerns in flaring operations, due to both health and environmental hazards. Preliminary results are presented for a 2D transient simulation of soot formation in a reacting jet with exit velocity of 130 m/s under a 5 m/s crossflow released from a 50 m high elevated flare and a 50 cm nozzle. Combustion dynamics was simulated with OpenFOAM. Gas-phase non-premixed combustion was modeled with the Chalmers PaSR approach and a κ-ɛ turbulence model. For soot formation, Moss model was used and the ISAT algorithm for solving the chemistry. Sulfur chemistry was considered to account for the sourness of the fuel. Gas composition is 10 % H2S and 90 % C2H4. A simplified Glassman reaction mechanism was used for this purpose. Results show that soot levels are sensitive to the sulfur present in the fuel, since it was observed a slight decrease in the soot volume fraction. NSC is the current oxidation model for soot formation. Predicted temperature is high (about 2390 K), perhaps due to soot-radiation interaction is not considered yet, but a radiation model implementation is on progress, as well as an oxidation mechanism that accounts for OH radical. Flame length is about 50 m.

Estimating the high-arsenic domestic-well population in the conterminous United States

USGS Publications Warehouse

Ayotte, Joseph; Medalie, Laura; Qi, Sharon L.; Backer, Lorraine C.; Nolan, Bernard T.

2017-01-01

Arsenic concentrations from 20 450 domestic wells in the U.S. were used to develop a logistic regression model of the probability of having arsenic >10 μg/L (“high arsenic”), which is presented at the county, state, and national scales. Variables representing geologic sources, geochemical, hydrologic, and physical features were among the significant predictors of high arsenic. For U.S. Census blocks, the mean probability of arsenic >10 μg/L was multiplied by the population using domestic wells to estimate the potential high-arsenic domestic-well population. Approximately 44.1 M people in the U.S. use water from domestic wells. The population in the conterminous U.S. using water from domestic wells with predicted arsenic concentration >10 μg/L is 2.1 M people (95% CI is 1.5 to 2.9 M). Although areas of the U.S. were underrepresented with arsenic data, predictive variables available in national data sets were used to estimate high arsenic in unsampled areas. Additionally, by predicting to all of the conterminous U.S., we identify areas of high and low potential exposure in areas of limited arsenic data. These areas may be viewed as potential areas to investigate further or to compare to more detailed local information. Linking predictive modeling to private well use information nationally, despite the uncertainty, is beneficial for broad screening of the population at risk from elevated arsenic in drinking water from private wells.

Correlation between continent area and elevation

NASA Astrophysics Data System (ADS)

Zhang, Y.

2004-12-01

This presentation is motivated by the following questions: (1) What factors determine the mean elevation and thickness of an individual continent? (2) How to explain the positive correlation between the mean height and area of individual continent? (3) Given total continental crust volume, what determines the mean thickness (and hence total area) of all continents? For example, Mean thickness of all continents is about 41 km. Mean land elevation is 874 m, and mean elevation of all continents (including land areas and continental shelves and slopes to 1000 meters below sea level) is about 800 m. Could mean continental thickness have doubled and continental area have halved in the geologic past? I present a first-order model to address these issues assuming that continental mean height is the steady state height controlled by uplift and erosion. The model predicts that it takes longer time to erode a larger continent. Hence mean continental height at steady state increases as continental area increases. This prediction is consistent with the general trend between present-day continental elevation and area (except for Antarctica), and can fit the trend well. This is the first time the relation between continental area and mean elevation is quantitatively explained. The model is further applied to investigate variations of mean thickness of continental crust over the last 600 Myr over which the continental crust mass and seawater volume are assumed to be constant. Because a change in the number of continents leads to change in the area of continents, it is predicted that the mean continental thickness increases as the number of continents decreases. Nevertheless, the thickness variation is small, amounts to about 10% from one continent to six continents. Change in the number of continents leads to a sea level fluctuation of about 0.3 km, with the lowest sea level coinciding with times of supercontinents. This prediction is consistent with prominent lows in sea level curves at the times of Pangea and Rodinia. It is concluded that the number of continents played a major role in Phanerozoic sea level changes.

A novel neuroimaging model to predict early neurological deterioration after acute ischemic stroke.

PubMed

Huang, Yen-Chu; Tsai, Yuan-Hsiung; Lee, Jiann-Der; Yang, Jen-Tsung; Pan, Yi-Ting

2018-05-16

In acute ischemic stroke, early neurological deterioration (END) may occur in up to one-third of patients. However, there is still no satisfying or comprehensive predictive model for all the stroke subtypes. We propose a practical model to predict END using magnetic resonance imaging (MRI). Patients with anterior circulation infarct were recruited and they underwent an MRI within 24 hours of stroke onset. END was defined as an elevation of ≥2 points on the National Institute of Health Stroke Scale (NIHSS) within 72 hours of stroke onset. We examined the relationships of END to individual END models, including: A, infarct swelling; B, small subcortical infarct; C, mismatch; and D, recurrence. There were 163 patients recruited and 43 (26.4%) of them had END. The END models A, B and C significantly predicted END respectively after adjusting for confounding factors (p=0.022, p=0.007 and p<0.001 respectively). In END model D, we examined all imaging predictors of Recurrence Risk Estimator (RRE) individually and only the "multiple acute infarcts" pattern was significantly associated with END (p=0.032). When applying END models A, B, C and D, they successfully predicted END (p<0.001; odds ratio: 17.5[95% confidence interval: 5.1-60.8]), with 93.0% sensitivity, 60.0% specificity, 45.5% positive predictive value and 96.0% negative predictive value. The results demonstrate that the proposed model could predict END in all stroke subtypes of anterior circulation infarction. It provides a practical model for clinical physicians to select high-risk patients for more aggressive treatment to prevent END. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Long-term shifts in the phenology of rare and endemic Rocky Mountain plants.

PubMed

Munson, Seth M; Sher, Anna A

2015-08-01

• Mountainous regions support high plant productivity, diversity, and endemism, yet are highly vulnerable to climate change. Historical records and model predictions show increasing temperatures across high elevation regions including the Southern Rocky Mountains, which can have a strong influence on the performance and distribution of montane plant species. Rare plant species can be particularly vulnerable to climate change because of their limited abundance and distribution.• We tracked the phenology of rare and endemic species, which are identified as imperiled, across three different habitat types with herbarium records to determine if flowering time has changed over the last century, and if phenological change was related to shifts in climate.• We found that the flowering date of rare species has accelerated 3.1 d every decade (42 d total) since the late 1800s, with plants in sagebrush interbasins showing the strongest accelerations in phenology. High winter temperatures were associated with the acceleration of phenology in low elevation sagebrush and barren river habitats, whereas high spring temperatures explained accelerated phenology in the high elevation alpine habitat. In contrast, high spring temperatures delayed the phenology of plant species in the two low-elevation habitats and precipitation had mixed effects depending on the season.• These results provide evidence for large shifts in the phenology of rare Rocky Mountain plants related to climate, which can have strong effects on plant fitness, the abundance of associated wildlife, and the future of plant conservation in mountainous regions. © 2015 Botanical Society of America, Inc.

Predicting Depression among Patients with Diabetes Using Longitudinal Data. A Multilevel Regression Model.

PubMed

Jin, H; Wu, S; Vidyanti, I; Di Capua, P; Wu, B

2015-01-01

This article is part of the Focus Theme of Methods of Information in Medicine on "Big Data and Analytics in Healthcare". Depression is a common and often undiagnosed condition for patients with diabetes. It is also a condition that significantly impacts healthcare outcomes, use, and cost as well as elevating suicide risk. Therefore, a model to predict depression among diabetes patients is a promising and valuable tool for providers to proactively assess depressive symptoms and identify those with depression. This study seeks to develop a generalized multilevel regression model, using a longitudinal data set from a recent large-scale clinical trial, to predict depression severity and presence of major depression among patients with diabetes. Severity of depression was measured by the Patient Health Questionnaire PHQ-9 score. Predictors were selected from 29 candidate factors to develop a 2-level Poisson regression model that can make population-average predictions for all patients and subject-specific predictions for individual patients with historical records. Newly obtained patient records can be incorporated with historical records to update the prediction model. Root-mean-square errors (RMSE) were used to evaluate predictive accuracy of PHQ-9 scores. The study also evaluated the classification ability of using the predicted PHQ-9 scores to classify patients as having major depression. Two time-invariant and 10 time-varying predictors were selected for the model. Incorporating historical records and using them to update the model may improve both predictive accuracy of PHQ-9 scores and classification ability of the predicted scores. Subject-specific predictions (for individual patients with historical records) achieved RMSE about 4 and areas under the receiver operating characteristic (ROC) curve about 0.9 and are better than population-average predictions. The study developed a generalized multilevel regression model to predict depression and demonstrated that using generalized multilevel regression based on longitudinal patient records can achieve high predictive ability.

Generation of High Resolution Water Vapour Fields from GPS Observations and Integration With ECMWF and MODIS

NASA Astrophysics Data System (ADS)

Yu, C.; Li, Z.; Penna, N. T.

2016-12-01

Precipitable water vapour (PWV) can be routinely retrieved from ground-based GPS arrays in all-weather conditions and also in real-time. But to provide dense spatial coverage maps, for example for calibrating SAR images, for correcting atmospheric effects in Network RTK GPS positioning and which may be used for numerical weather prediction, the pointwise GPS PWV measurements must be interpolated. Several previous interpolation studies have addressed the importance of the elevation dependency of water vapour, but it is often a challenge to separate elevation-dependent tropospheric delays from turbulent components. We present a tropospheric turbulence iterative decomposition model that decouples the total PWV into (i) a stratified component highly correlated with topography which therefore delineates the vertical troposphere profile, and (ii) a turbulent component resulting from disturbance processes (e.g., severe weather) in the troposphere which trigger uncertain patterns in space and time. We will demonstrate that the iterative decoupled interpolation model generates improved dense tropospheric water vapour fields compared with elevation dependent models, with similar accuracies obtained over both flat and mountainous terrain, as well as for both inland and coastal areas. We will also show that our GPS-based model may be enhanced with ECMWF zenith tropospheric delay and MODIS PWV, producing multi-data sources high temporal-spatial resolution PWV fields. These fields were applied to Sentinel-1 SAR interferograms over the Los Angeles region, for which a maximum noise reduction due to atmosphere artifacts reached 85%. The results reveal that the turbulent troposphere noise, especially those in a SAR image, often occupy more than 50% of the total zenith tropospheric delay and exert systematic, rather than random patterns.

The current distribution, predictive modeling, and restoration potential of red spruce in West Virginia

Treesearch

Gregory Nowacki; Dan Wendt

2010-01-01

The environmental relationships of red spruce (Picea rubens Sarg.) were assessed in east-central West Virginia. Although many significant relationships existed, red spruce was most strongly associated with elevation, climate, and soil moisture factors. Specifically, red spruce was positively associated with elevation, number of frost days, mean...

Robust diagnosis of non-Hodgkin lymphoma phenotypes validated on gene expression data from different laboratories.

PubMed

Bhanot, Gyan; Alexe, Gabriela; Levine, Arnold J; Stolovitzky, Gustavo

2005-01-01

A major challenge in cancer diagnosis from microarray data is the need for robust, accurate, classification models which are independent of the analysis techniques used and can combine data from different laboratories. We propose such a classification scheme originally developed for phenotype identification from mass spectrometry data. The method uses a robust multivariate gene selection procedure and combines the results of several machine learning tools trained on raw and pattern data to produce an accurate meta-classifier. We illustrate and validate our method by applying it to gene expression datasets: the oligonucleotide HuGeneFL microarray dataset of Shipp et al. (www.genome.wi.mit.du/MPR/lymphoma) and the Hu95Av2 Affymetrix dataset (DallaFavera's laboratory, Columbia University). Our pattern-based meta-classification technique achieves higher predictive accuracies than each of the individual classifiers , is robust against data perturbations and provides subsets of related predictive genes. Our techniques predict that combinations of some genes in the p53 pathway are highly predictive of phenotype. In particular, we find that in 80% of DLBCL cases the mRNA level of at least one of the three genes p53, PLK1 and CDK2 is elevated, while in 80% of FL cases, the mRNA level of at most one of them is elevated.

Predictive value of serum sST2 in preschool wheezers for development of asthma with high FeNO.

PubMed

Ketelaar, M E; van de Kant, K D; Dijk, F N; Klaassen, E M; Grotenboer, N S; Nawijn, M C; Dompeling, E; Koppelman, G H

2017-11-01

Wheezing is common in childhood. However, current prediction models of pediatric asthma have only modest accuracy. Novel biomarkers and definition of subphenotypes may improve asthma prediction. Interleukin-1-receptor-like-1 (IL1RL1 or ST2) is a well-replicated asthma gene and associates with eosinophilia. We investigated whether serum sST2 predicts asthma and asthma with elevated exhaled NO (FeNO), compared to the commonly used Asthma Prediction Index (API). Using logistic regression modeling, we found that serum sST2 levels in 2-3 years-old wheezers do not predict doctors' diagnosed asthma at age 6 years. Instead, sST2 predicts a subphenotype of asthma characterized by increased levels of FeNO, a marker for eosinophilic airway inflammation. Herein, sST2 improved the predictive value of the API (AUC=0.70, 95% CI 0.56-0.84), but had also significant predictive value on its own (AUC=0.65, 95% CI 0.52-0.79). Our study indicates that sST2 in preschool wheezers has predictive value for the development of eosinophilic airway inflammation in asthmatic children at school age. © 2017 EAACI and John Wiley and Sons A/S. Published by John Wiley and Sons Ltd.

Spatial patterns of simulated transpiration response to climate variability in a snow dominated mountain ecosystem

USGS Publications Warehouse

Christensen, L.; Tague, C.L.; Baron, Jill S.

2008-01-01

Transpiration is an important component of soil water storage and stream-flow and is linked with ecosystem productivity, species distribution, and ecosystem health. In mountain environments, complex topography creates heterogeneity in key controls on transpiration as well as logistical challenges for collecting representative measurements. In these settings, ecosystem models can be used to account for variation in space and time of the dominant controls on transpiration and provide estimates of transpiration patterns and their sensitivity to climate variability and change. The Regional Hydro-Ecological Simulation System (RHESSys) model was used to assess elevational differences in sensitivity of transpiration rates to the spatiotemporal variability of climate variables across the Upper Merced River watershed, Yosemite Valley, California, USA. At the basin scale, predicted annual transpiration was lowest in driest and wettest years, and greatest in moderate precipitation years (R2 = 0.32 and 0.29, based on polynomial regression of maximum snow depth and annual precipitation, respectively). At finer spatial scales, responsiveness of transpiration rates to climate differed along an elevational gradient. Low elevations (1200-1800 m) showed little interannual variation in transpiration due to topographically controlled high soil moistures along the river corridor. Annual conifer stand transpiration at intermediate elevations (1800-2150 m) responded more strongly to precipitation, resulting in a unimodal relationship between transpiration and precipitation where highest transpiration occurred during moderate precipitation levels, regardless of annual air temperatures. Higher elevations (2150-2600 m) maintained this trend, but air temperature sensitivities were greater. At these elevations, snowfall provides enough moisture for growth, and increased temperatures influenced transpiration. Transpiration at the highest elevations (2600-4000 m) showed strong sensitivity to air temperature, little sensitivity to precipitation. Model results suggest elevational differences in vegetation water use and sensitivity to climate were significant and will likely play a key role in controlling responses and vulnerability of Sierra Nevada ecosystems to climate change. Copyright ?? 2008 John Wiley & Sons, Ltd.

Increase in the CO2 exchange rate of leaves of Ilex rotunda with elevated atmospheric CO2 concentration in an urban canyon

NASA Astrophysics Data System (ADS)

Takagi, M.; Gyokusen, Koichiro; Saito, Akira

It was found that the atmospheric carbon dioxide (CO2) concentration in an urban canyon in Fukuoka city, Japan during August 1997 was about 30 µmol mol-1 higher than that in the suburbs. When fully exposed to sunlight, in situ the rate of photosynthesis in single leaves of Ilex rotunda planted in the urban canyon was higher when the atmospheric CO2 concentration was elevated. A biochemically based model was able to predict the in situ rate of photosynthesis well. The model also predicted an increase in the daily CO2 exchange rate for leaves in the urban canyon with an increase in atmospheric CO2 concentration. However, in situ such an increase in the daily CO2 exchange rate may be offset by diminished sunlight, a higher air temperature and a lower relative humidity. Thus, the daily CO2 exchange rate predicted using the model based soleley on the environmental conditions prevailing in the urban canyon was lower than that predicted based only on environmental factors found in the suburbs.

Temperate forest impacts on maritime snowpacks across an elevation gradient: An assessment of the snow surface energy balance and airborne lidar derived forest structure

NASA Astrophysics Data System (ADS)

Roth, T. R.; Nolin, A. W.

2016-12-01

Temperate forests modify snow evolution patterns both spatially and temporally relative to open areas. Dense, warm forests both impede snow accumulation through increased canopy snow interception and increase sub-canopy longwave energy inputs onto the snow surface. These process modifications vary in magnitude and duration depending on climatic, topographic and forest characteristics. Here we present results from a four year study of paired forested and open sites at three elevations, Low - 1150 m, Mid - 1325 m and High - 1465 m. Snowpacks are deeper and last up to 3-4 weeks longer at the Low and Mid elevation Open sites relative to the adjacent Forest sites. Conversely, at the High Forest site, snow is retained 2-4 weeks longer than the Open site. This change in snowpack depth and persistence is attributed to deposition patterns at higher elevations and forest structure differences that alter the canopy interception efficiency and the sub-canopy energy balance. Canopy interception efficiency (CIE) in the Low and Mid Forest sites, over the duration of the study were 79% and 76% of the total event snowfall, whereas CIE was 31% at the High Forest site. Longwave radiation in forested environments is the primary energy component across each elevation band due to the warm winter environment and forest presence, accounting for 82%, 88%, and 59% of the energy balance at the Low, Mid, and High Forest sites, respectively. High wind speeds in the High elevation Open site significantly increases the turbulent energy and creates preferential snowfall deposition in the nearby Forest site. These results show the importance of understanding the effects of forest cover on sub-canopy snowpack evolution and highlight the need for improved forest cover model representation to accurately predict water resources in maritime forests.

Modeling vegetation community responses to sea-level rise on Barrier Island systems: A case study on the Cape Canaveral Barrier Island complex, Florida, USA

PubMed Central

Foster, Tammy E.; Stolen, Eric D.; Hall, Carlton R.; Schaub, Ronald; Duncan, Brean W.; Hunt, Danny K.; Drese, John H.

2017-01-01

Society needs information about how vegetation communities in coastal regions will be impacted by hydrologic changes associated with climate change, particularly sea level rise. Due to anthropogenic influences which have significantly decreased natural coastal vegetation communities, it is important for us to understand how remaining natural communities will respond to sea level rise. The Cape Canaveral Barrier Island complex (CCBIC) on the east central coast of Florida is within one of the most biologically diverse estuarine systems in North America and has the largest number of threatened and endangered species on federal property in the contiguous United States. The high level of biodiversity is susceptible to sea level rise. Our objective was to model how vegetation communities along a gradient ranging from hydric to upland xeric on CCBIC will respond to three sea level rise scenarios (0.2 m, 0.4 m, and 1.2 m). We used a probabilistic model of the current relationship between elevation and vegetation community to determine the impact sea level rise would have on these communities. Our model correctly predicted the current proportions of vegetation communities on CCBIC based on elevation. Under all sea level rise scenarios the model predicted decreases in mesic and xeric communities, with the greatest losses occurring in the most xeric communities. Increases in total area of salt marsh were predicted with a 0.2 and 0.4 m rise in sea level. With a 1.2 m rise in sea level approximately half of CCBIC’s land area was predicted to transition to open water. On the remaining land, the proportions of most of the vegetation communities were predicted to remain similar to that of current proportions, but there was a decrease in proportion of the most xeric community (oak scrub) and an increase in the most hydric community (salt marsh). Our approach provides a first approximation of the impacts of sea level rise on terrestrial vegetation communities, including important xeric upland communities, as a foundation for management decisions and future modeling. PMID:28796807

1-Meter Digital Elevation Model specification

USGS Publications Warehouse

Arundel, Samantha T.; Archuleta, Christy-Ann M.; Phillips, Lori A.; Roche, Brittany L.; Constance, Eric W.

2015-10-21

In January 2015, the U.S. Geological Survey National Geospatial Technical Operations Center began producing the 1-Meter Digital Elevation Model data product. This new product was developed to provide high resolution bare-earth digital elevation models from light detection and ranging (lidar) elevation data and other elevation data collected over the conterminous United States (lower 48 States), Hawaii, and potentially Alaska and the U.S. territories. The 1-Meter Digital Elevation Model consists of hydroflattened, topographic bare-earth raster digital elevation models, with a 1-meter x 1-meter cell size, and is available in 10,000-meter x 10,000-meter square blocks with a 6-meter overlap. This report details the specifications required for the production of the 1-Meter Digital Elevation Model.

Modeling total cholesterol as predictor of mortality: the low-cholesterol paradox.

PubMed

Wesley, David; Cox, Hugh F

2011-01-01

Elevated total cholesterol is well-established as a risk factor for coronary artery disease and cardiovascular mortality. However, less attention is paid to the association between low cholesterol levels and mortality--the low cholesterol paradox. In this paper, restricted cubic splines (RCS) and complex survey methodology are used to show the low-cholesterol paradox is present in the laboratory, examination, and mortality follow-up data from the Third National Health and Nutrition Examination Survey (NHANES III). A series of Cox proportional hazard models, demonstrate that RCS are necessary to incorporate desired covariates while avoiding the use of categorical variables. Valid concerns regarding the accuracy of such predictive models are discussed. The one certain conclusion is that low cholesterol levels are markers for excess mortality, just as are high levels. Restricted cubic splines provide the necessary flexibility to demonstrate the U-shaped relationship between cholesterol and mortality without resorting to binning results. Cox PH models perform well at identifying associations between risk factors and outcomes of interest such as mortality. However, the predictions from such a model may not be as accurate as common statistics suggest and predictive models should be used with caution.

A practical tool for estimating subsurface LNAPL distributions and transmissivity using current and historical fluid levels in groundwater wells: Effects of entrapped and residual LNAPL.

PubMed

Lenhard, R J; Rayner, J L; Davis, G B

2017-10-01

A model is presented to account for elevation-dependent residual and entrapped LNAPL above and below, respectively, the water-saturated zone when predicting subsurface LNAPL specific volume (fluid volume per unit area) and transmissivity from current and historic fluid levels in wells. Physically-based free, residual, and entrapped LNAPL saturation distributions and LNAPL relative permeabilities are integrated over a vertical slice of the subsurface to yield the LNAPL specific volumes and transmissivity. The model accounts for effects of fluctuating water tables. Hypothetical predictions are given for different porous media (loamy sand and clay loam), fluid levels in wells, and historic water-table fluctuations. It is shown the elevation range from the LNAPL-water interface in a well to the upper elevation where the free LNAPL saturation approaches zero is the same for a given LNAPL thickness in a well regardless of porous media type. Further, the LNAPL transmissivity is largely dependent on current fluid levels in wells and not historic levels. Results from the model can aid developing successful LNAPL remediation strategies and improving the design and operation of remedial activities. Results of the model also can aid in accessing the LNAPL recovery technology endpoint, based on the predicted transmissivity. Copyright © 2017 Commonwealth Scientific and Industrial Research Organisation - Copyright 2017. Published by Elsevier B.V. All rights reserved.

Landslide model performance in a high resolution small-scale landscape

NASA Astrophysics Data System (ADS)

De Sy, V.; Schoorl, J. M.; Keesstra, S. D.; Jones, K. E.; Claessens, L.

2013-05-01

The frequency and severity of shallow landslides in New Zealand threatens life and property, both on- and off-site. The physically-based shallow landslide model LAPSUS-LS is tested for its performance in simulating shallow landslide locations induced by a high intensity rain event in a small-scale landscape. Furthermore, the effect of high resolution digital elevation models on the performance was tested. The performance of the model was optimised by calibrating different parameter values. A satisfactory result was achieved with a high resolution (1 m) DEM. Landslides, however, were generally predicted lower on the slope than mapped erosion scars. This discrepancy could be due to i) inaccuracies in the DEM or in other model input data such as soil strength properties; ii) relevant processes for this environmental context that are not included in the model; or iii) the limited validity of the infinite length assumption in the infinite slope stability model embedded in the LAPSUS-LS. The trade-off between a correct prediction of landslides versus stable cells becomes increasingly worse with coarser resolutions; and model performance decreases mainly due to altering slope characteristics. The optimal parameter combinations differ per resolution. In this environmental context the 1 m resolution topography resembles actual topography most closely and landslide locations are better distinguished from stable areas than for coarser resolutions. More gain in model performance could be achieved by adding landslide process complexities and parameter heterogeneity of the catchment.

Gravitational spreading of Danu, Freyja and Maxwell Montes, Venus

NASA Astrophysics Data System (ADS)

Smrekar, Suzanne E.; Solomon, Sean C.

1991-06-01

The potential energy of elevated terrain tends to drive the collapse of the topography. This process of gravitational spreading is likely to be more important on Venus than on Earth because the higher surface temperature weakens the crust. The highest topography on Venus is Ishtar Terra. The high plateau of Lakshmi Planum has an average elevation of 3 km above mean planetary radius, and is surrounded by mountain belts. Freyja, Danu, and Maxwell Montes rise, on average, an additional 3, 0.5, and 5 km above the plateau, respectively. Recent high resolution Magellan radar images of this area, east of approx. 330 deg E, reveal widespread evidence for gravity spreading. Some observational evidence is described for gravity spreading and the implications are discussed in terms of simple mechanical models. Several simple models predict that gravity spreading should be an important process on Venus. One difficulty in using remote observations to infer interior properties is that the observed features may not have formed in response to stresses which are still active. Several causes of surface topography are briefly examined.

Affective Traits in Schizophrenia and Schizotypy

PubMed Central

Horan, William P.; Blanchard, Jack J.; Clark, Lee Anna; Green, Michael F.

2008-01-01

This article reviews empirical studies of affective traits in individuals with schizophrenia spectrum disorders, population-based investigations of vulnerability to psychosis, and genetic and psychometric high-risk samples. The review focuses on studies that use self-report trait questionnaires to assess Negative Affectivity (NA) and Positive Affectivity (PA), which are conceptualized in contemporary models of personality as broad, temperamentally-based dispositions to experience corresponding emotional states. Individuals with schizophrenia report a pattern of stably elevated NA and low PA throughout the illness course. Among affected individuals, these traits are associated with variability in several clinically important features, including functional outcome, quality of life, and stress reactivity. Furthermore, evidence that elevated NA and low PA (particularly the facet of anhedonia) predict the development of psychosis and are detectable in high-risk samples suggests that these traits play a role in vulnerability to schizophrenia, though they are implicated in other forms of psychopathology as well. Results are discussed in terms of their implications for treatment, etiological models, and future research to advance the study of affective traits in schizophrenia and schizotypy. PMID:18667393

Evaluating the relative impact of climate and economic changes on forest and agricultural ecosystem services in mountain regions.

PubMed

Briner, Simon; Elkin, Ché; Huber, Robert

2013-11-15

Provisioning of ecosystem services (ES) in mountainous regions is predicted to be influenced by i) the direct biophysical impacts of climate change, ii) climate mediated land use change, and iii) socioeconomic driven changes in land use. The relative importance and the spatial distribution of these factors on forest and agricultural derived ES, however, is unclear, making the implementation of ES management schemes difficult. Using an integrated economic-ecological modeling framework, we evaluated the impact of these driving forces on the provision of forest and agricultural ES in a mountain region of southern Switzerland. Results imply that forest ES will be strongly influenced by the direct impact of climate change, but that changes in land use will have a comparatively small impact. The simulation of direct impacts of climate change affects forest ES at all elevations, while land use changes can only be found at high elevations. In contrast, changes to agricultural ES were found to be primarily due to shifts in economic conditions that alter land use and land management. The direct influence of climate change on agriculture is only predicted to be substantial at high elevations, while socioeconomic driven shifts in land use are projected to affect agricultural ES at all elevations. Our simulation results suggest that policy schemes designed to mitigate the negative impact of climate change on forests should focus on suitable adaptive management plans, accelerating adaptation processes for currently forested areas. To maintain provision of agricultural ES policy needs to focus on economic conditions rather than on supporting adaptation to new climate. Copyright © 2013 Elsevier Ltd. All rights reserved.

An analysis of cropland mask choice and ancillary data for annual corn yield forecasting using MODIS data

NASA Astrophysics Data System (ADS)

Shao, Yang; Campbell, James B.; Taff, Gregory N.; Zheng, Baojuan

2015-06-01

The Midwestern United States is one of the world's most important corn-producing regions. Monitoring and forecasting of corn yields in this intensive agricultural region are important activities to support food security, commodity markets, bioenergy industries, and formation of national policies. This study aims to develop forecasting models that have the capability to provide mid-season prediction of county-level corn yields for the entire Midwestern United States. We used multi-temporal MODIS NDVI (normalized difference vegetation index) 16-day composite data as the primary input, with digital elevation model (DEM) and parameter-elevation relationships on independent slopes model (PRISM) climate data as additional inputs. The DEM and PRISM data, along with three types of cropland masks were tested and compared to evaluate their impacts on model predictive accuracy. Our results suggested that the use of general cropland masks (e.g., summer crop or cultivated crops) generated similar results compared with use of an annual corn-specific mask. Leave-one-year-out cross-validation resulted in an average R2 of 0.75 and RMSE value of 1.10 t/ha. Using a DEM as an additional model input slightly improved performance, while inclusion of PRISM climate data appeared not to be important for our regional corn-yield model. Furthermore, our model has potential for real-time/early prediction. Our corn yield esitmates are available as early as late July, which is an improvement upon previous corn-yield prediction models. In addition to annual corn yield forecasting, we examined model uncertainties through spatial and temporal analysis of the model's predictive error distribution. The magnitude of predictive error (by county) appears to be associated with the spatial patterns of corn fields in the study area.

Effects of elevated mean and extremely high temperatures on the physio-ecological characteristics of geographically distinctive populations of Cunninghamia lanceolata

NASA Astrophysics Data System (ADS)

Zhou, Ting; Jia, Xiaorong; Liao, Huixuan; Peng, Shijia; Peng, Shaolin

2016-12-01

Conventional models for predicting species distribution under global warming scenarios often treat one species as a homogeneous whole. In the present study, we selected Cunninghamia lanceolata (C. lanceolata), a widely distributed species in China, to investigate the physio-ecological responses of five populations under different temperature regimes. The results demonstrate that increased mean temperatures induce increased growth performance among northern populations, which exhibited the greatest germination capacity and largest increase in the overlap between the growth curve and the monthly average temperature. However,tolerance of the southern population to extremely high temperatures was stronger than among the population from the northern region,shown by the best growth and the most stable photosynthetic system of the southern population under extremely high temperature. This result indicates that the growth advantage among northern populations due to increased mean temperatures may be weakened by lower tolerance to extremely high temperatures. This finding is antithetical to the predicted results. The theoretical coupling model constructed here illustrates that the difference in growth between populations at high and low latitudes and altitudes under global warming will decrease because of the frequent occurrence of extremely high temperatures.

Troponin elevation in severe sepsis and septic shock: the role of left ventricular diastolic dysfunction and right ventricular dilatation*.

PubMed

Landesberg, Giora; Jaffe, Allan S; Gilon, Dan; Levin, Phillip D; Goodman, Sergey; Abu-Baih, Abed; Beeri, Ronen; Weissman, Charles; Sprung, Charles L; Landesberg, Amir

2014-04-01

Serum troponin concentrations predict mortality in almost every clinical setting they have been examined, including sepsis. However, the causes for troponin elevations in sepsis are poorly understood. We hypothesized that detailed investigation of myocardial dysfunction by echocardiography can provide insight into the possible causes of troponin elevation and its association with mortality in sepsis. Prospective, analytic cohort study. Tertiary academic institute. A cohort of ICU patients with severe sepsis or septic shock. Advanced echocardiography using global strain, strain-rate imaging and 3D left and right ventricular volume analyses in addition to the standard echocardiography, and concomitant high-sensitivity troponin-T measurement in patients with severe sepsis or septic shock. Two hundred twenty-five echocardiograms and concomitant high-sensitivity troponin-T measurements were performed in a cohort of 106 patients within the first days of severe sepsis or septic shock (2.1 ± 1.4 measurements/patient). Combining echocardiographic and clinical variables, left ventricular diastolic dysfunction defined as increased mitral E-to-strain-rate e'-wave ratio, right ventricular dilatation (increased right ventricular end-systolic volume index), high Acute Physiology and Chronic Health Evaluation-II score, and low glomerular filtration rate best correlated with elevated log-transformed concomitant high-sensitivity troponin-T concentrations (mixed linear model: t = 3.8, 3.3, 2.8, and -2.1 and p = 0.001, 0.0002, 0.006, and 0.007, respectively). Left ventricular systolic dysfunction determined by reduced strain-rate s'-wave or low ejection fraction did not significantly correlate with log(concomitant high-sensitivity troponin-T). Forty-one patients (39%) died in-hospital. Right ventricular end-systolic volume index and left ventricular strain-rate e'-wave predicted in-hospital mortality, independent of Acute Physiology and Chronic Health Evaluation-II score (logistic regression: Wald = 8.4, 6.6, and 9.8 and p = 0.004, 0.010, and 0.001, respectively). Concomitant high-sensitivity troponin-T predicted mortality in univariate analysis (Wald = 8.4; p = 0.004), but not when combined with right ventricular end-systolic volume index and strain-rate e'-wave in the multivariate analysis (Wald = 2.3, 4.6, and 6.2 and p = 0.13, 0.032, and 0.012, respectively). Left ventricular diastolic dysfunction and right ventricular dilatation are the echocardiographic variables correlating best with concomitant high-sensitivity troponin-T concentrations. Left ventricular diastolic and right ventricular systolic dysfunction seem to explain the association of troponin with mortality in severe sepsis and septic shock.

Tungsten fiber reinforced copper matrix composites: A review

NASA Technical Reports Server (NTRS)

Mcdanels, David L.

1989-01-01

Tungsten fiber reinforced copper matrix (W/Cu) composites have served as an ideal model system with which to analyze the properties of metal matrix composites. A series of research programs were conducted to investigate the stress-strain behavior of W/Cu composites; the effect of fiber content on the strength, modulus, and conductivity of W/Cu composites; and the effect of alloying elements on the behavior of tungsten wire and of W/Cu composites. Later programs investigated the stress-rupture, creep, and impact behavior of these composites at elevated temperatures. Analysis of the results of these programs as allows prediction of the effects of fiber properties, matrix properties, and fiber content on the properties of W/Cu composites. These analyses form the basis for the rule-of-mixtures prediction of composite properties which was universally adopted as the criteria for measuring composite efficiency. In addition, the analyses allows extrapolation of potential properties of other metal matrix composites and are used to select candidate fibers and matrices for development of tungsten fiber reinforced superalloy composite materials for high temperature aircraft and rocket engine turbine applications. The W/Cu composite efforts are summarized, some of the results obtained are described, and an update is provided on more recent work using W/Cu composites as high strength, high thermal conductivity composite materials for high heat flux, elevated temperature applications.

Evaluation of a childhood lead questionnaire in predicting elevated blood lead levels in a rural community.

PubMed

Muñiz, Marco A; Dundas, Robert; Mahoney, Martin C

2003-01-01

The accuracy of a lead screening questionnaire in predicting elevated blood lead levels was examined in a pediatric practice in a rural part of New York state. A retrospective chart review was used to collect data on children ages 9 to 24 months who presented for well-child visits. Children with both questionnaire and lead level results available in the chart were included in the study (n = 171). The mean blood lead level among all children was 1.6 microg/dl (median = 2.0 microg/dl, range 0 to 24 microg/dl). Four children (2.3%) had elevated lead levels (greater than 10 microg/dl), with levels for two of these children being greater than 20 microg/dl. Although our lead screening questionnaire was expanded from the standard 1991 CDC questionnaire by the inclusion of six additional items, it was not especially useful in predicting elevated blood lead levels above 10 microg/dl. However, the questionnaire exhibited some utility in predicting marked elevations in blood lead levels (over 20 microg/dl). Although results in other geographic areas might differ, the lead questionnaire may have value by enhancing parents' awareness of potential lead hazards in their children's environment and may prove to be more useful in areas of high risk to lead exposure.

Hydrologic modeling as a predictive basis for ecological restoration of salt marshes

USGS Publications Warehouse

Roman, C.T.; Garvine, R.W.; Portnoy, J.W.

1995-01-01

Roads, bridges, causeways, impoundments, and dikes in the coastal zone often restrict tidal flow to salt marsh ecosystems. A dike with tide control structures, located at the mouth of the Herring River salt marsh estuarine system (Wellfleet, Massachusetts) since 1908, has effectively restricted tidal exchange, causing changes in marsh vegetation composition, degraded water quality, and reduced abundance of fish and macroinvertebrate communities. Restoration of this estuary by reintroduction of tidal exchange is a feasible management alternative. However, restoration efforts must proceed with caution as residential dwellings and a golf course are located immediately adjacent to and in places within the tidal wetland. A numerical model was developed to predict tide height levels for numerous alternative openings through the Herring River dike. Given these model predictions and knowledge of elevations of flood-prone areas, it becomes possible to make responsible decisions regarding restoration. Moreover, tidal flooding elevations relative to the wetland surface must be known to predict optimum conditions for ecological recovery. The tide height model has a universal role, as demonstrated by successful application at a nearby salt marsh restoration site in Provincetown, Massachusetts. Salt marsh restoration is a valuable management tool toward maintaining and enhancing coastal zone habitat diversity. The tide height model presented in this paper will enable both scientists and resource professionals to assign a degree of predictability when designing salt marsh restoration programs.

Spatial abundance models and seasonal distribution for guanaco (Lama guanicoe) in central Tierra del Fuego, Argentina.

PubMed

Flores, Celina E; Deferrari, Guillermo; Collado, Leonardo; Escobar, Julio; Schiavini, Adrián

2018-01-01

Spatially explicit modelling allows to estimate population abundance and predict species' distribution in relation to environmental factors. Abiotic factors are the main determinants of a herbivore´s response to environmental heterogeneity on large spatiotemporal scales. We assessed the influence of elevation, geographic location and distance to the coast on the seasonal abundance and distribution of guanaco (Lama guanicoe) in central Tierra del Fuego, by means of spatially explicit modelling. The estimated abundance was 23,690 individuals for the non-breeding season and 33,928 individuals for the breeding season. The factors influencing distribution and abundance revealed to be the elevation for the non-breeding season, and the distance to the coast and geographic location for the breeding season. The southwest of the study area presented seasonal abundance variation and the southeast and northeast presented high abundance during both seasons. The elevation would be the driving factor of guanaco distribution, as individuals move to lower areas during the non-breeding season and ascend to high areas during the breeding season. Our results confirm that part of the guanaco population performs seasonal migratory movements and that the main valleys present important wintering habitats for guanacos as well as up-hill zones during summer. This type of study would help to avoid problems of scale mismatch and achieve better results in management actions and is an example of how to assess important seasonal habitats from evaluations of abundance and distribution patterns.

Spatial abundance models and seasonal distribution for guanaco (Lama guanicoe) in central Tierra del Fuego, Argentina

PubMed Central

Deferrari, Guillermo; Collado, Leonardo; Escobar, Julio; Schiavini, Adrián

2018-01-01

Spatially explicit modelling allows to estimate population abundance and predict species’ distribution in relation to environmental factors. Abiotic factors are the main determinants of a herbivore´s response to environmental heterogeneity on large spatiotemporal scales. We assessed the influence of elevation, geographic location and distance to the coast on the seasonal abundance and distribution of guanaco (Lama guanicoe) in central Tierra del Fuego, by means of spatially explicit modelling. The estimated abundance was 23,690 individuals for the non-breeding season and 33,928 individuals for the breeding season. The factors influencing distribution and abundance revealed to be the elevation for the non-breeding season, and the distance to the coast and geographic location for the breeding season. The southwest of the study area presented seasonal abundance variation and the southeast and northeast presented high abundance during both seasons. The elevation would be the driving factor of guanaco distribution, as individuals move to lower areas during the non-breeding season and ascend to high areas during the breeding season. Our results confirm that part of the guanaco population performs seasonal migratory movements and that the main valleys present important wintering habitats for guanacos as well as up-hill zones during summer. This type of study would help to avoid problems of scale mismatch and achieve better results in management actions and is an example of how to assess important seasonal habitats from evaluations of abundance and distribution patterns. PMID:29782523

Elevated temperature alters carbon cycling in a model microbial community

NASA Astrophysics Data System (ADS)

Mosier, A.; Li, Z.; Thomas, B. C.; Hettich, R. L.; Pan, C.; Banfield, J. F.

2013-12-01

Earth's climate is regulated by biogeochemical carbon exchanges between the land, oceans and atmosphere that are chiefly driven by microorganisms. Microbial communities are therefore indispensible to the study of carbon cycling and its impacts on the global climate system. In spite of the critical role of microbial communities in carbon cycling processes, microbial activity is currently minimally represented or altogether absent from most Earth System Models. Method development and hypothesis-driven experimentation on tractable model ecosystems of reduced complexity, as presented here, are essential for building molecularly resolved, benchmarked carbon-climate models. Here, we use chemoautotropic acid mine drainage biofilms as a model community to determine how elevated temperature, a key parameter of global climate change, regulates the flow of carbon through microbial-based ecosystems. This study represents the first community proteomics analysis using tandem mass tags (TMT), which enable accurate, precise, and reproducible quantification of proteins. We compare protein expression levels of biofilms growing over a narrow temperature range expected to occur with predicted climate changes. We show that elevated temperature leads to up-regulation of proteins involved in amino acid metabolism and protein modification, and down-regulation of proteins involved in growth and reproduction. Closely related bacterial genotypes differ in their response to temperature: Elevated temperature represses carbon fixation by two Leptospirillum genotypes, whereas carbon fixation is significantly up-regulated at higher temperature by a third closely related genotypic group. Leptospirillum group III bacteria are more susceptible to viral stress at elevated temperature, which may lead to greater carbon turnover in the microbial food web through the release of viral lysate. Overall, this proteogenomics approach revealed the effects of climate change on carbon cycling pathways and other microbial activities. When scaled to more complex ecosystems and integrated into Earth System Models, this approach could significantly improve predictions of global carbon-climate feedbacks. Experiments such as these are a critical first step designed at understanding climate change impacts in order to better predict ecosystem adaptations, assess the viability of mitigation strategies, and inform relevant policy decisions.

Defense traits in the long-lived Great Basin bristlecone pine and resistance to the native herbivore mountain pine beetle

Treesearch

Barbara J. Bentz; Sharon A. Hood; Matt Hansen; Jim Vandygriff; Karen E. Mock

2016-01-01

Mountain pine beetle (MPB, Dendroctonus ponderosae) is a significant mortality agent of Pinus, and climate-driven range expansion is occurring. Pinus defenses in recently invaded areas, including high elevations, are predicted to be lower than in areas with longer term MPB presence. MPB was recently observed in high-elevation forests of the Great Basin (GB)...

Forest productivity varies with soil moisture more than temperature in a small montane watershed

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wei, Liang; Zhou, Hang; Link, Timothy E

Mountainous terrain creates variability in microclimate, including nocturnal cold air drainage and resultant temperature inversions. Driven by the elevational temperature gradient, vapor pressure deficit (VPD) also varies with elevation. Soil depth and moisture availability often increase from ridgetop to valley bottom. These variations complicate predictions of forest productivity and other biological responses. We analyzed spatiotemporal air temperature (T) and VPD variations in a forested, 27-km 2 catchment that varied from 1000 to 1650 m in elevation. Temperature inversions occurred on 76% of mornings in the growing season. The inversion had a clear upper boundary at midslope (~1370 m a.s.l.). Vapormore » pressure was relatively constant across elevations, therefore VPD was mainly controlled by T in the watershed. Here, we assessed the impact of microclimate and soil moisture on tree height, forest productivity, and carbon stable isotopes (δ 13C) using a physiological forest growth model (3-PG). Simulated productivity and tree height were tested against observations derived from lidar data. The effects on photosynthetic gas-exchange of dramatic elevational variations in T and VPD largely cancelled as higher temperature (increasing productivity) accompanies higher VPD (reducing productivity). Although it was not measured, the simulations suggested that realistic elevational variations in soil moisture predicted the observed decline in productivity with elevation. Therefore, in this watershed, the model parameterization should have emphasized soil moisture rather than precise descriptions of temperature inversions.« less

Forest productivity varies with soil moisture more than temperature in a small montane watershed

DOE PAGES

Wei, Liang; Zhou, Hang; Link, Timothy E; ...

2018-05-16

Mountainous terrain creates variability in microclimate, including nocturnal cold air drainage and resultant temperature inversions. Driven by the elevational temperature gradient, vapor pressure deficit (VPD) also varies with elevation. Soil depth and moisture availability often increase from ridgetop to valley bottom. These variations complicate predictions of forest productivity and other biological responses. We analyzed spatiotemporal air temperature (T) and VPD variations in a forested, 27-km 2 catchment that varied from 1000 to 1650 m in elevation. Temperature inversions occurred on 76% of mornings in the growing season. The inversion had a clear upper boundary at midslope (~1370 m a.s.l.). Vapormore » pressure was relatively constant across elevations, therefore VPD was mainly controlled by T in the watershed. Here, we assessed the impact of microclimate and soil moisture on tree height, forest productivity, and carbon stable isotopes (δ 13C) using a physiological forest growth model (3-PG). Simulated productivity and tree height were tested against observations derived from lidar data. The effects on photosynthetic gas-exchange of dramatic elevational variations in T and VPD largely cancelled as higher temperature (increasing productivity) accompanies higher VPD (reducing productivity). Although it was not measured, the simulations suggested that realistic elevational variations in soil moisture predicted the observed decline in productivity with elevation. Therefore, in this watershed, the model parameterization should have emphasized soil moisture rather than precise descriptions of temperature inversions.« less

Creep-fatigue interaction at high temperature; Proceedings of the Symposium, 112th ASME Winter Annual Meeting, Atlanta, GA, Dec. 1-6, 1991

NASA Astrophysics Data System (ADS)

Haritos, George K.; Ochoa, O. O.

Various papers on creep-fatigue interaction at high temperature are presented. Individual topics addressed include: analysis of elevated temperature fatigue crack growth mechanisms in Alloy 718, physically based microcrack propagation laws for creep-fatigue-environment interaction, in situ SEM observation of short fatigue crack growth in Waspaloy at 700 C under cyclic and dwell conditions, evolution of creep-fatigue life prediction models, TMF design considerations in turbine airfoils of advanced turbine engines. Also discussed are: high temperature fatigue life prediction computer code based on the total strain version of strainrange partitioning, atomic theory of thermodynamics of internal variables, geometrically nonlinear analysis of interlaminar stresses in unsymmetrically laminated plates subjected to uniform thermal loading, experimental investigation of creep crack tip deformation using moire interferometry. (For individual items see A93-31336 to A93-31344)

Sensitivity of predicted scaling and permeability in Enhanced Geothermal Systems to Thermodynamic Data and Activity Models

NASA Astrophysics Data System (ADS)

Hingerl, Ferdinand F.; Wagner, Thomas; Kulik, Dmitrii A.; Kosakowski, Georg; Driesner, Thomas; Thomsen, Kaj

2010-05-01

A consortium of research groups from ETH Zurich, EPF Lausanne, the Paul Scherrer Institut and the University of Bonn collaborates in a comprehensive program of basic research on key aspects of the Enhanced Geothermal Systems (EGSs). As part of this GEOTHERM project (www.geotherm.ethz.ch), we concentrate on the fundamental investigation of thermodynamic models suitable for describing fluid-rock interactions at geothermal conditions. Predictions of the fluid-rock interaction in EGS still face several major challenges. Slight variations in the input thermodynamic and kinetic parameters may result in significant differences in the predicted mineral solubilities and stable assemblage. Realistic modeling of mineral precipitation in turn has implications onto our understanding of the permeability evolution of the geothermal reservoir, as well as the scaling in technical installations. In order to reasonably model an EGS, thermodynamic databases and activity models must be tailored to geothermal conditions. We therefore implemented in GEMS code the Pitzer formalism, which is the standard model used for computing thermodynamic excess properties of brines at elevated temperatures and pressures. This model, however, depends on a vast amount of interaction parameters, which are to a substantial extend unknown. Furthermore, a high order polynomial temperature interpolation makes extrapolation unreliable if not impossible. As an alternative we additionally implemented the EUNIQUAC activity model. EUNIQUAC requires fewer empirical fit parameters (only binary interaction parameters needed) and uses simpler and more stable temperature and pressure extrapolations. This results in an increase in computation speed, which is of crucial importance when performing coupled long term simulations of geothermal reservoirs. To achieve better performance under geothermal conditions, we are currently partly reformulating EUNIQUAC and refitting the existing parameter set. First results of the Pitzer-EUNIQUAC benchmark applied to relevant aqueous solutions at elevated temperature, pressure and ionic strength will be presented.

Spatial models reveal the microclimatic buffering capacity of old-growth forests

PubMed Central

Frey, Sarah J. K.; Hadley, Adam S.; Johnson, Sherri L.; Schulze, Mark; Jones, Julia A.; Betts, Matthew G.

2016-01-01

Climate change is predicted to cause widespread declines in biodiversity, but these predictions are derived from coarse-resolution climate models applied at global scales. Such models lack the capacity to incorporate microclimate variability, which is critical to biodiversity microrefugia. In forested montane regions, microclimate is thought to be influenced by combined effects of elevation, microtopography, and vegetation, but their relative effects at fine spatial scales are poorly known. We used boosted regression trees to model the spatial distribution of fine-scale, under-canopy air temperatures in mountainous terrain. Spatial models predicted observed independent test data well (r = 0.87). As expected, elevation strongly predicted temperatures, but vegetation and microtopography also exerted critical effects. Old-growth vegetation characteristics, measured using LiDAR (light detection and ranging), appeared to have an insulating effect; maximum spring monthly temperatures decreased by 2.5°C across the observed gradient in old-growth structure. These cooling effects across a gradient in forest structure are of similar magnitude to 50-year forecasts of the Intergovernmental Panel on Climate Change and therefore have the potential to mitigate climate warming at local scales. Management strategies to conserve old-growth characteristics and to curb current rates of primary forest loss could maintain microrefugia, enhancing biodiversity persistence in mountainous systems under climate warming. PMID:27152339

Spatial models reveal the microclimatic buffering capacity of old-growth forests.

PubMed

Frey, Sarah J K; Hadley, Adam S; Johnson, Sherri L; Schulze, Mark; Jones, Julia A; Betts, Matthew G

2016-04-01

Climate change is predicted to cause widespread declines in biodiversity, but these predictions are derived from coarse-resolution climate models applied at global scales. Such models lack the capacity to incorporate microclimate variability, which is critical to biodiversity microrefugia. In forested montane regions, microclimate is thought to be influenced by combined effects of elevation, microtopography, and vegetation, but their relative effects at fine spatial scales are poorly known. We used boosted regression trees to model the spatial distribution of fine-scale, under-canopy air temperatures in mountainous terrain. Spatial models predicted observed independent test data well (r = 0.87). As expected, elevation strongly predicted temperatures, but vegetation and microtopography also exerted critical effects. Old-growth vegetation characteristics, measured using LiDAR (light detection and ranging), appeared to have an insulating effect; maximum spring monthly temperatures decreased by 2.5°C across the observed gradient in old-growth structure. These cooling effects across a gradient in forest structure are of similar magnitude to 50-year forecasts of the Intergovernmental Panel on Climate Change and therefore have the potential to mitigate climate warming at local scales. Management strategies to conserve old-growth characteristics and to curb current rates of primary forest loss could maintain microrefugia, enhancing biodiversity persistence in mountainous systems under climate warming.

Geomorphic and climate influences on soil organic carbon concentration at large catchment scales

NASA Astrophysics Data System (ADS)

Hancock, G. R.; Martinez, C.; Wells, T.; Dever, C.; Willgoose, G. R.; Bissett, A.

2013-12-01

Soils represent the largest terrestrial sink of carbon on Earth. Managing the soil organic carbon (SOC) pool is becoming increasingly important in light of growing concerns over global food security and the climatic effects of anthropogenic CO2 emissions. The development of accurate predictive SOC models are an important step for both land resource managers and policy makers alike. Presently, a number of SOC models are available which incorporate environmental data to produce SOC estimates. The accuracy of these models varies significantly over a range of landscapes due to the highly complex nature of SOC dynamics. Fundamental gaps exist in our understanding of SOC controls. To date, studies of SOC controls, and the subsequent models derived from their findings have focussed mainly on North American and European landscapes. Additionally, SOC studies often focus on the paddock to small catchment scale. Consequently, information about SOC in Australian landscapes and at the larger scale is limited. This study examines controls over SOC across a large catchment of approximately 600 km2 in the Upper Hunter Valley, New South Wales, Australia. The aim was to develop a predictive model for use across a range of catchment sizes and climate. Here it was found that elevation (derived from DEMs) and vegetation (above ground biomass quantified by remote sensing were the primary controls of SOC. SOC was seen to increase with elevation and NDVI. This relationship is believed to be a reflection of rainfall patterns across the study area and plant growth potential. Further, a relationship was observed between SOC and the environmental tracer 137Cs which suggests that SOC and 137Cs move through catchment via similar sediment transport mechanisms. Therefore loss of SOC by erosion and gain by deposition may be necessary to be accounted for in any SOC budget. Model validation indicated that the use of simple linear relationships could predict SOC based on rainfall and vegetation (above ground biomass as quantified by remote sensing). The results suggest that simple landscape and climate models have the potential to predict the spatial distribution of SOC. The findings of this study emphasise the importance of tailoring SOC models to the appropriate scale.

Elevation as a proxy for mosquito-borne Zika virus transmission in the Americas

PubMed Central

Miniota, Jennifer; Joseph, Heather A.; Brady, Oliver J.; Kraemer, Moritz U. G.; Grills, Ardath W.; Morrison, Stephanie; Esposito, Douglas H.; Nicolucci, Adriano; German, Matthew; Creatore, Maria I.; Nelson, Bradley; Johansson, Michael A.; Brunette, Gary; Hay, Simon I.

2017-01-01

Introduction When Zika virus (ZIKV) first began its spread from Brazil to other parts of the Americas, national-level travel notices were issued, carrying with them significant economic consequences to affected countries. Although regions of some affected countries were likely unsuitable for mosquito-borne transmission of ZIKV, the absence of high quality, timely surveillance data made it difficult to confidently demarcate infection risk at a sub-national level. In the absence of reliable data on ZIKV activity, a pragmatic approach was needed to identify subnational geographic areas where the risk of ZIKV infection via mosquitoes was expected to be negligible. To address this urgent need, we evaluated elevation as a proxy for mosquito-borne ZIKV transmission. Methods For sixteen countries with local ZIKV transmission in the Americas, we analyzed (i) modelled occurrence of the primary vector for ZIKV, Aedes aegypti, (ii) human population counts, and (iii) reported historical dengue cases, specifically across 100-meter elevation levels between 1,500m and 2,500m. Specifically, we quantified land area, population size, and the number of observed dengue cases above each elevation level to identify a threshold where the predicted risks of encountering Ae. aegypti become negligible. Results Above 1,600m, less than 1% of each country’s total land area was predicted to have Ae. aegypti occurrence. Above 1,900m, less than 1% of each country’s resident population lived in areas where Ae. aegypti was predicted to occur. Across all 16 countries, 1.1% of historical dengue cases were reported above 2,000m. Discussion These results suggest low potential for mosquito-borne ZIKV transmission above 2,000m in the Americas. Although elevation is a crude predictor of environmental suitability for ZIKV transmission, its constancy made it a pragmatic input for policy decision-making during this public health emergency. PMID:28542540

The application of geostationary propagation models to non-geostationary propagation measurements

NASA Astrophysics Data System (ADS)

Haddock, Paul Christopher

Atmospheric attenuation becomes evident above 10 GHz due to the absorption of microwave energy from the molecular motion of the atmospheric constituents. Atmospheric effects on satellite communications systems operating at frequencies greater than 10 GHz become more pronounced. Most geostationary (GEO) climate models, which predict the fading statistics for earth-space telecommunications, have satellite elevation angle as one of the input parameters. There has been an interest in the industry to apply the propagation models developed for the GEO satellites to the non-geostationary (NGO) satellite case. With the NGO satellites, the elevation angle to the satellite is time-variable, and as a result the earth-space propagation medium is time varying. We can calculate the expected probability that a satellite, in a given orbit, will be found at a given elevation angle as a percentage of the year based on the satellite orbital elements, the minimum elevation angle allowed in the constellation operation plan, and the constellation configuration. From this calculation, we can develop an empirical fit to a given probability density function (PDF) to account for the distribution of elevation angles. This PDF serves as a weighting function for the elevation input into the GEO climate model to produce the overall fading statistics for the NGO case. In this research, a Ka-band total power radiometer was developed to measure the down-dwelling incoherent radiant electromagnetic energy from the atmosphere. This whole sky sampling radiometer collected 1 year of radiometric measurements. These observations occurred at varying elevation and azimuthal angles, in close proximity to a weak water vapor absorption line. By referencing the output power of the radiometer to known radiometric emissions and by performing frequent internal calibrations, the developed radiometer provided long term highly accurate and stable low-level derived attenuation measurements. By correlating the 1 year of atmospheric measurements to the modified GEO climate model, the hypothesis is tested. That by application of the proper elevation weighting factors, the GEO model is applicable to the NGO case, where the time-varying angle changes are occurring on a short-time period. Finally, we look at the joint statistics of multiple link failures. Using the 1 year of observed attenuations for multiple sky sections, we show that for a given sky section what the probability is that its attenuation level will be equaled or exceeded for each of the remaining sky sections.

Developing Present-day Proxy Cases Based on NARVAL Data for Investigating Low Level Cloud Responses to Future Climate Change.

NASA Astrophysics Data System (ADS)

Reilly, Stephanie

2017-04-01

The energy budget of the entire global climate is significantly influenced by the presence of boundary layer clouds. The main aim of the High Definition Clouds and Precipitation for Advancing Climate Prediction (HD(CP)2) project is to improve climate model predictions by means of process studies of clouds and precipitation. This study makes use of observed elevated moisture layers as a proxy of future changes in tropospheric humidity. The associated impact on radiative transfer triggers fast responses in boundary layer clouds, providing a framework for investigating this phenomenon. The investigation will be carried out using data gathered during the Next-generation Aircraft Remote-sensing for VALidation (NARVAL) South campaigns. Observational data will be combined with ECMWF reanalysis data to derive the large scale forcings for the Large Eddy Simulations (LES). Simulations will be generated for a range of elevated moisture layers, spanning a multi-dimensional phase space in depth, amplitude, elevation, and cloudiness. The NARVAL locations will function as anchor-points. The results of the large eddy simulations and the observations will be studied and compared in an attempt to determine how simulated boundary layer clouds react to changes in radiative transfer from the free troposphere. Preliminary LES results will be presented and discussed.

Dramatic response to climate change in the Southwest: Robert Whittaker's 1963 Arizona Mountain plant transect revisited

PubMed Central

Brusca, Richard C; Wiens, John F; Meyer, Wallace M; Eble, Jeff; Franklin, Kim; Overpeck, Jonathan T; Moore, Wendy

2013-01-01

Models analyzing how Southwestern plant communities will respond to climate change predict that increases in temperature will lead to upward elevational shifts of montane species. We tested this hypothesis by reexamining Robert Whittaker's 1963 plant transect in the Santa Catalina Mountains of southern Arizona, finding that this process is already well underway. Our survey, five decades after Whittaker's, reveals large changes in the elevational ranges of common montane plants, while mean annual rainfall has decreased over the past 20 years, and mean annual temperatures increased 0.25°C/decade from 1949 to 2011 in the Tucson Basin. Although elevational changes in species are individualistic, significant overall upward movement of the lower elevation boundaries, and elevational range contractions, have occurred. This is the first documentation of significant upward shifts of lower elevation range boundaries in Southwestern montane plant species over decadal time, confirming that previous hypotheses are correct in their prediction that mountain communities in the Southwest will be strongly impacted by warming, and that the Southwest is already experiencing a rapid vegetation change. PMID:24223270

Lysophosphatidic Acid and Apolipoprotein A1 Predict Increased Risk of Developing World Trade Center Lung Injury: A Nested Case-Control Study

PubMed Central

Tsukiji, Jun; Cho, Soo Jung; Echevarria, Ghislaine C.; Kwon, Sophia; Joseph, Phillip; Schenck, Edward J.; Naveed, Bushra; Prezant, David J.; Rom, William N.; Schmidt, Ann Marie; Weiden, Michael D.; Nolan, Anna

2014-01-01

Rationale Metabolic syndrome, inflammatory and vascular injury markers measured in serum after WTC exposures predict abnormal FEV1. We hypothesized that elevated LPA levels predict FEV1

Putting mechanisms into crop production models.

PubMed

Boote, Kenneth J; Jones, James W; White, Jeffrey W; Asseng, Senthold; Lizaso, Jon I

2013-09-01

Crop growth models dynamically simulate processes of C, N and water balance on daily or hourly time-steps to predict crop growth and development and at season-end, final yield. Their ability to integrate effects of genetics, environment and crop management have led to applications ranging from understanding gene function to predicting potential impacts of climate change. The history of crop models is reviewed briefly, and their level of mechanistic detail for assimilation and respiration, ranging from hourly leaf-to-canopy assimilation to daily radiation-use efficiency is discussed. Crop models have improved steadily over the past 30-40 years, but much work remains. Improvements are needed for the prediction of transpiration response to elevated CO₂ and high temperature effects on phenology and reproductive fertility, and simulation of root growth and nutrient uptake under stressful edaphic conditions. Mechanistic improvements are needed to better connect crop growth to genetics and to soil fertility, soil waterlogging and pest damage. Because crop models integrate multiple processes and consider impacts of environment and management, they have excellent potential for linking research from genomics and allied disciplines to crop responses at the field scale, thus providing a valuable tool for deciphering genotype by environment by management effects. © 2013 John Wiley & Sons Ltd.

Effects of elevated temperature on the viscoplastic modeling of graphite/polymeric composites

NASA Technical Reports Server (NTRS)

Gates, Thomas S.

1991-01-01

To support the development of new materials for the design of next generation supersonic transports, a research program is underway at NASA to assess the long term durability of advanced polymer matrix composites (PMC's). One of main objectives of the program was to explore the effects of elevated temperature (23 to 200 C) on the constitutive model's material parameters. To achieve this goal, test data on the observed nonlinear, stress-strain behavior of IM7/5260 and IM7/8320 composites under tension and compression loading were collected and correlated against temperature. These tests, conducted under isothermal conditions using variable strain rates, included such phenomena as stress relaxation and short term creep. The second major goal was the verification of the model by comparison of analytical predictions and test results for off axis and angle ply laminates. Correlation between test and predicted behavior was performed for specimens of both material systems over a range of temperatures. Results indicated that the model provided reasonable predictions of material behavior in load or strain controlled tests. Periods of loading, unloading, stress relaxation, and creep were accounted for.

Application of dynamical systems theory to the high angle of attack dynamics of the F-14

NASA Technical Reports Server (NTRS)

Jahnke, Craig C.; Culick, Fred E. C.

1990-01-01

Dynamical systems theory has been used to study the nonlinear dynamics of the F-14. An eight degree of freedom model that does not include the control system present in operational F-14s has been analyzed. The aerodynamic model, supplied by NASA, includes nonlinearities as functions of the angles of attack and sideslip, the rotation rate, and the elevator deflection. A continuation method has been used to calculate the steady states of the F-14 as continuous functions of the control surface deflections. Bifurcations of these steady states have been used to predict the onset of wing rock, spiral divergence, and jump phenomena which cause the aircraft to enter a spin. A simple feedback control system was designed to eliminate the wing rock and spiral divergence instabilities. The predictions were verified with numerical simulations.

Predicting Plant Diversity Patterns in Madagascar: Understanding the Effects of Climate and Land Cover Change in a Biodiversity Hotspot

PubMed Central

Brown, Kerry A.; Parks, Katherine E.; Bethell, Colin A.; Johnson, Steig E.; Mulligan, Mark

2015-01-01

Climate and land cover change are driving a major reorganization of terrestrial biotic communities in tropical ecosystems. In an effort to understand how biodiversity patterns in the tropics will respond to individual and combined effects of these two drivers of environmental change, we use species distribution models (SDMs) calibrated for recent climate and land cover variables and projected to future scenarios to predict changes in diversity patterns in Madagascar. We collected occurrence records for 828 plant genera and 2186 plant species. We developed three scenarios, (i.e., climate only, land cover only and combined climate-land cover) based on recent and future climate and land cover variables. We used this modelling framework to investigate how the impacts of changes to climate and land cover influenced biodiversity across ecoregions and elevation bands. There were large-scale climate- and land cover-driven changes in plant biodiversity across Madagascar, including both losses and gains in diversity. The sharpest declines in biodiversity were projected for the eastern escarpment and high elevation ecosystems. Sharp declines in diversity were driven by the combined climate-land cover scenarios; however, there were subtle, region-specific differences in model outputs for each scenario, where certain regions experienced relatively higher species loss under climate or land cover only models. We strongly caution that predicted future gains in plant diversity will depend on the development and maintenance of dispersal pathways that connect current and future suitable habitats. The forecast for Madagascar’s plant diversity in the face of future environmental change is worrying: regional diversity will continue to decrease in response to the combined effects of climate and land cover change, with habitats such as ericoid thickets and eastern lowland and sub-humid forests particularly vulnerable into the future. PMID:25856241

Predicting plant diversity patterns in Madagascar: understanding the effects of climate and land cover change in a biodiversity hotspot.

PubMed

Brown, Kerry A; Parks, Katherine E; Bethell, Colin A; Johnson, Steig E; Mulligan, Mark

2015-01-01

Climate and land cover change are driving a major reorganization of terrestrial biotic communities in tropical ecosystems. In an effort to understand how biodiversity patterns in the tropics will respond to individual and combined effects of these two drivers of environmental change, we use species distribution models (SDMs) calibrated for recent climate and land cover variables and projected to future scenarios to predict changes in diversity patterns in Madagascar. We collected occurrence records for 828 plant genera and 2186 plant species. We developed three scenarios, (i.e., climate only, land cover only and combined climate-land cover) based on recent and future climate and land cover variables. We used this modelling framework to investigate how the impacts of changes to climate and land cover influenced biodiversity across ecoregions and elevation bands. There were large-scale climate- and land cover-driven changes in plant biodiversity across Madagascar, including both losses and gains in diversity. The sharpest declines in biodiversity were projected for the eastern escarpment and high elevation ecosystems. Sharp declines in diversity were driven by the combined climate-land cover scenarios; however, there were subtle, region-specific differences in model outputs for each scenario, where certain regions experienced relatively higher species loss under climate or land cover only models. We strongly caution that predicted future gains in plant diversity will depend on the development and maintenance of dispersal pathways that connect current and future suitable habitats. The forecast for Madagascar's plant diversity in the face of future environmental change is worrying: regional diversity will continue to decrease in response to the combined effects of climate and land cover change, with habitats such as ericoid thickets and eastern lowland and sub-humid forests particularly vulnerable into the future.

A Modified Mechanical Threshold Stress Constitutive Model for Austenitic Stainless Steels

NASA Astrophysics Data System (ADS)

Prasad, K. Sajun; Gupta, Amit Kumar; Singh, Yashjeet; Singh, Swadesh Kumar

2016-12-01

This paper presents a modified mechanical threshold stress (m-MTS) constitutive model. The m-MTS model incorporates variable athermal and dynamic strain aging (DSA) Components to accurately predict the flow stress behavior of austenitic stainless steels (ASS)-316 and 304. Under strain rate variations between 0.01-0.0001 s-1, uniaxial tensile tests were conducted at temperatures ranging from 50-650 °C to evaluate the material constants of constitutive models. The test results revealed the high dependence of flow stress on strain, strain rate and temperature. In addition, it was observed that DSA occurred at elevated temperatures and very low strain rates, causing an increase in flow stress. While the original MTS model is capable of predicting the flow stress behavior for ASS, statistical parameters point out the inefficiency of the model when compared to other models such as Johnson Cook model, modified Zerilli-Armstrong (m-ZA) model, and modified Arrhenius-type equations (m-Arr). Therefore, in order to accurately model both the DSA and non-DSA regimes, the original MTS model was modified by incorporating variable athermal and DSA components. The suitability of the m-MTS model was assessed by comparing the statistical parameters. It was observed that the m-MTS model was highly accurate for the DSA regime when compared to the existing models. However, models like m-ZA and m-Arr showed better results for the non-DSA regime.

Influence of forest roads standards and networks on water yield as predicted by the distributed hydrology-soil-vegetation model

Treesearch

Salli F. Dymond; W. Michael Aust; Steven P. Prisley; Mark H. Eisenbies; James M. Vose

2013-01-01

Throughout the country, foresters are continually looking at the effects of logging and forest roads on stream discharge and overall stream health. In the Pacific Northwest, a distributed hydrology-soil-vegetation model (DHSVM) has been used to predict the effects of logging on peak discharge in mountainous regions. DHSVM uses elevation, meteorological, vegetation, and...

Flow behaviour and constitutive modelling of a ferritic stainless steel at elevated temperatures

NASA Astrophysics Data System (ADS)

Zhao, Jingwei; Jiang, Zhengyi; Zu, Guoqing; Du, Wei; Zhang, Xin; Jiang, Laizhu

2016-05-01

The flow behaviour of a ferritic stainless steel (FSS) was investigated by a Gleeble 3500 thermal-mechanical test simulator over the temperature range of 900-1100 °C and strain rate range of 1-50 s-1. Empirical and phenomenological constitutive models were established, and a comparative study was made on the predictability of them. The results indicate that the flow stress decreases with increasing the temperature and decreasing the strain rate. High strain rate may cause a drop in flow stress after a peak value due to the adiabatic heating. The Zener-Hollomon parameter depends linearly on the flow stress, and decreases with raising the temperature and reducing the strain rate. Significant deviations occur in the prediction of flow stress by the Johnson-Cook (JC) model, indicating that the JC model cannot accurately track the flow behaviour of the FSS during hot deformation. Both the multiple-linear and the Arrhenius-type models can track the flow behaviour very well under the whole hot working conditions, and have much higher accuracy in predicting the flow behaviour than that of the JC model. The multiple-linear model is recommended in the current work due to its simpler structure and less time needed for solving the equations relative to the Arrhenius-type model.

Thermal regimes of Rocky Mountain lakes warm with climate change

PubMed Central

Roberts, James J.

2017-01-01

Anthropogenic climate change is causing a wide range of stresses in aquatic ecosystems, primarily through warming thermal conditions. Lakes, in response to these changes, are experiencing increases in both summer temperatures and ice-free days. We used continuous records of lake surface temperature and air temperature to create statistical models of daily mean lake surface temperature to assess thermal changes in mountain lakes. These models were combined with downscaled climate projections to predict future thermal conditions for 27 high-elevation lakes in the southern Rocky Mountains. The models predict a 0.25°C·decade-1 increase in mean annual lake surface temperature through the 2080s, which is greater than warming rates of streams in this region. Most striking is that on average, ice-free days are predicted to increase by 5.9 days ·decade-1, and summer mean lake surface temperature is predicted to increase by 0.47°C·decade-1. Both could profoundly alter the length of the growing season and potentially change the structure and function of mountain lake ecosystems. These results highlight the changes expected of mountain lakes and stress the importance of incorporating climate-related adaptive strategies in the development of resource management plans. PMID:28683083

Thermal regimes of Rocky Mountain lakes warm with climate change

USGS Publications Warehouse

Roberts, James J.; Fausch, Kurt D.; Schmidt, Travis S.; Walters, David M.

2017-01-01

Anthropogenic climate change is causing a wide range of stresses in aquatic ecosystems, primarily through warming thermal conditions. Lakes, in response to these changes, are experiencing increases in both summer temperatures and ice-free days. We used continuous records of lake surface temperature and air temperature to create statistical models of daily mean lake surface temperature to assess thermal changes in mountain lakes. These models were combined with downscaled climate projections to predict future thermal conditions for 27 high-elevation lakes in the southern Rocky Mountains. The models predict a 0.25°C·decade-1increase in mean annual lake surface temperature through the 2080s, which is greater than warming rates of streams in this region. Most striking is that on average, ice-free days are predicted to increase by 5.9 days ·decade-1, and summer mean lake surface temperature is predicted to increase by 0.47°C·decade-1. Both could profoundly alter the length of the growing season and potentially change the structure and function of mountain lake ecosystems. These results highlight the changes expected of mountain lakes and stress the importance of incorporating climate-related adaptive strategies in the development of resource management plans.

Thermal regimes of Rocky Mountain lakes warm with climate change.

PubMed

Roberts, James J; Fausch, Kurt D; Schmidt, Travis S; Walters, David M

2017-01-01

Anthropogenic climate change is causing a wide range of stresses in aquatic ecosystems, primarily through warming thermal conditions. Lakes, in response to these changes, are experiencing increases in both summer temperatures and ice-free days. We used continuous records of lake surface temperature and air temperature to create statistical models of daily mean lake surface temperature to assess thermal changes in mountain lakes. These models were combined with downscaled climate projections to predict future thermal conditions for 27 high-elevation lakes in the southern Rocky Mountains. The models predict a 0.25°C·decade-1 increase in mean annual lake surface temperature through the 2080s, which is greater than warming rates of streams in this region. Most striking is that on average, ice-free days are predicted to increase by 5.9 days ·decade-1, and summer mean lake surface temperature is predicted to increase by 0.47°C·decade-1. Both could profoundly alter the length of the growing season and potentially change the structure and function of mountain lake ecosystems. These results highlight the changes expected of mountain lakes and stress the importance of incorporating climate-related adaptive strategies in the development of resource management plans.

Rethinking impulsivity in suicide.

PubMed

Klonsky, E David; May, Alexis

2010-12-01

Elevated impulsivity is thought to facilitate the transition from suicidal thoughts to suicidal behavior. Therefore, impulsivity should distinguish those who have attempted suicide (attempters) from those who have only considered suicide (ideators-only). This hypothesis was examined in three large nonclinical samples: (1) 2,011 military recruits, (2) 1,296 college students, and (3) 399 high school students. In sample 1, contrary to traditional models of suicide risk, a unidimensional measure of impulsivity failed to distinguish attempters from ideators-only. In samples 2 and 3, which were administered a multidimensional measure of impulsivity (i.e., the UPPS impulsive behavior scale; Whiteside & Lynam, 2001), different impulsivity-related traits characterized attempters and ideators-only. Whereas both attempters and ideators-only exhibited high urgency (the tendency to act impulsive in the face of negative emotions), only attempters exhibited poor premeditation (a diminished ability to think through the consequences of one's actions). Neither attempters nor ideators-only exhibited high sensation seeking or lack of perseverance. Future research should continue to distinguish impulsivity-related traits that predict suicide ideation from those that predict suicide attempts, and models of suicide risk should be revised accordingly.

Modeling hydrodynamics, water quality, and benthic processes to predict ecological effects in Narragansett Bay

EPA Science Inventory

The environmental fluid dynamics code (EFDC) was used to study the three dimensional (3D) circulation, water quality, and ecology in Narragansett Bay, RI. Predictions of the Bay hydrodynamics included the behavior of the water surface elevation, currents, salinity, and temperatur...

Associations between adiposity indicators and elevated blood pressure among Chinese children and adolescents.

PubMed

Dong, B; Wang, Z; Wang, H-J; Ma, J

2015-04-01

Adiposity is closely related to elevated blood pressure (BP); however, which adiposity indicator is the best predictor of elevated BP among children and adolescents is unclear. To clarify this, 99,366 participants aged 7-17 years from the Chinese National Survey on Students' Constitution and Health in 2010 were included in this study. The adiposity indicators, including weight, body mass index (BMI), waist circumference, waist-to-height ratio (WHtR), hip circumference, body adiposity index (BAI), waist-to-hip ratio (WHR) and skinfold thickness, were converted into z-scores before use. The associations between elevated BP and adiposity indicators z-scores were assessed by using logistic regression model and area under the receiver operating characteristic curve (AUC). In general, BAI, BMI and WHtR z-scores were superior for predicting elevated BP compared with weight, waist circumference, hip circumference, WHR and skinfold thickness z-scores. In both sexes, BMI z-score revealed slightly higher AUCs than other indicators. Our findings suggest that general adiposity indicators were equivalent, if not superior, to abdominal adiposity indicators to predict elevated BP. BMI could be a better predictor of elevated BP than other studied adiposity indicators in children.

Ability among adolescents for the metabolic syndrome to predict elevations in factors associated with type 2 diabetes and cardiovascular disease: data from the national health and nutrition examination survey 1999-2006.

PubMed

DeBoer, Mark D; Gurka, Matthew J

2010-08-01

The aim of this study was to compare currently proposed sets of pediatric metabolic syndrome criteria for the ability to predict elevations in "surrogate" factors that are associated with metabolic syndrome and with future cardiovascular disease and type 2 diabetes mellitus. These surrogate factors were fasting insulin, hemoglobin A1c (HbA1c), high-sensitivity C-reactive protein (hsCRP), and uric acid. Waist circumference (WC), blood pressure, triglycerides, high-density lipoprotein cholesterol (HDL-C), fasting glucose, fasting insulin, HbA1c, hsCRP, and uric acid measurements were obtained from 2,624 adolescent (12-18 years old) participants of the 1999-2006 National Health and Nutrition Examination Surveys. We identified children with metabolic syndrome as defined by six commonly used sets of pediatric metabolic syndrome criteria. We then defined elevations in the surrogate factors as values in the top 5% for the cohort and calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for each set of metabolic syndrome criteria and for each surrogate factor. Current pediatric metabolic syndrome criteria exhibited variable sensitivity and specificity for surrogate predictions. Metabolic syndrome criteria had the highest sensitivity for predicting fasting insulin (40-70%), followed by uric acid (31-54%), hsCRP (13-31%), and HbA1c (7-21%). The criteria of de Ferranti (which includes children with WC >75(th) percentile, compared to all other sets including children with WC >90(th) percentile) exhibited the highest sensitivity for predicting each of the surrogates, with only modest decrease in specificity compared to the other sets of criteria. However, the de Ferranti criteria also exhibited the lowest PPV values. Conversely, the pediatric International Diabetes Federation criteria exhibited the lowest sensitivity and the highest specificity. Pediatric metabolic syndrome criteria exhibit moderate sensitivity for detecting elevations in surrogate factors associated with metabolic syndrome and with risk for future disease. Inclusion of children with more modestly elevated WC improved sensitivity.

Indirect field technology for detecting areas object of illegal spills harmful to human health: application of drones, photogrammetry and hydrological models.

PubMed

Capolupo, Alessandra; Pindozzi, Stefania; Okello, Collins; Boccia, Lorenzo

2014-12-01

The accumulation of heavy metals in agricultural soils is a serious environmental problem. The Campania region in southern Italy has higher levels of cancer risk, presumably due to the accumulation of geogenic and anthropogenic soil pollutants, some of which have been incorporated into organic matter. The aim of this study was to introduce and test an innovative, field-applicable methodology to detect heavy metal accumulation using drone-based photogrammetry and microrill network modelling, specifically to generate wetlands wetlands prediction indices normally applied at large catchment scales, such as a large geographic basin. The processing of aerial photos taken using a hexacopter equipped with fifth-generation software for photogrammetry allowed the generation of a digital elevation model (DEM) with a resolution as high as 30 mm. Not only this provided a high potential for the study of micro-rill processes, but it was also useful for testing and comparing the capability of the topographic index (TI) and the clima-topographic index (CTI) to predict heavy metal sedimentation points at scales from 0.1 to 10 ha. Our results indicate that the TI and CTI indices can be used to predict points of heavy metal accumulation for small field catchments.

Coupling centennial-scale shoreline change to sea-level rise and coastal morphology in the Gulf of Mexico using a Bayesian network

USGS Publications Warehouse

Plant, Nathaniel G.

2016-01-01

Predictions of coastal evolution driven by episodic and persistent processes associated with storms and relative sea-level rise (SLR) are required to test our understanding, evaluate our predictive capability, and to provide guidance for coastal management decisions. Previous work demonstrated that the spatial variability of long-term shoreline change can be predicted using observed SLR rates, tide range, wave height, coastal slope, and a characterization of the geomorphic setting. The shoreline is not suf- ficient to indicate which processes are important in causing shoreline change, such as overwash that depends on coastal dune elevations. Predicting dune height is intrinsically important to assess future storm vulnerability. Here, we enhance shoreline-change predictions by including dune height as a vari- able in a statistical modeling approach. Dune height can also be used as an input variable, but it does not improve the shoreline-change prediction skill. Dune-height input does help to reduce prediction uncer- tainty. That is, by including dune height, the prediction is more precise but not more accurate. Comparing hindcast evaluations, better predictive skill was found when predicting dune height (0.8) compared with shoreline change (0.6). The skill depends on the level of detail of the model and we identify an optimized model that has high skill and minimal overfitting. The predictive model can be implemented with a range of forecast scenarios, and we illustrate the impacts of a higher future sea-level. This scenario shows that the shoreline change becomes increasingly erosional and more uncertain. Predicted dune heights are lower and the dune height uncertainty decreases.

Physical fitness predicts technical-tactical and time-motion profile in simulated Judo and Brazilian Jiu-Jitsu matches.

PubMed

Coswig, Victor S; Gentil, Paulo; Bueno, João C A; Follmer, Bruno; Marques, Vitor A; Del Vecchio, Fabrício B

2018-01-01

Among combat sports, Judo and Brazilian Jiu-Jitsu (BJJ) present elevated physical fitness demands from the high-intensity intermittent efforts. However, information regarding how metabolic and neuromuscular physical fitness is associated with technical-tactical performance in Judo and BJJ fights is not available. This study aimed to relate indicators of physical fitness with combat performance variables in Judo and BJJ. The sample consisted of Judo ( n  = 16) and BJJ ( n  = 24) male athletes. At the first meeting, the physical tests were applied and, in the second, simulated fights were performed for later notational analysis. The main findings indicate: (i) high reproducibility of the proposed instrument and protocol used for notational analysis in a mobile device; (ii) differences in the technical-tactical and time-motion patterns between modalities; (iii) performance-related variables are different in Judo and BJJ; and (iv) regression models based on metabolic fitness variables may account for up to 53% of the variances in technical-tactical and/or time-motion variables in Judo and up to 31% in BJJ, whereas neuromuscular fitness models can reach values up to 44 and 73% of prediction in Judo and BJJ, respectively. When all components are combined, they can explain up to 90% of high intensity actions in Judo. In conclusion, performance prediction models in simulated combat indicate that anaerobic, aerobic and neuromuscular fitness variables contribute to explain time-motion variables associated with high intensity and technical-tactical variables in Judo and BJJ fights.

Environmental Drivers and Predicted Risk of Bacillary Dysentery in Southwest China.

PubMed

Zhang, Han; Si, Yali; Wang, Xiaofeng; Gong, Peng

2017-07-14

Bacillary dysentery has long been a considerable health problem in southwest China, however, the quantitative relationship between anthropogenic and physical environmental factors and the disease is not fully understand. It is also not clear where exactly the bacillary dysentery risk is potentially high. Based on the result of hotspot analysis, we generated training samples to build a spatial distribution model. Univariate analyses, autocorrelation and multi-collinearity examinations and stepwise selection were then applied to screen the potential causative factors. Multiple logistic regressions were finally applied to quantify the effects of key factors. A bootstrapping strategy was adopted while fitting models. The model was evaluated by area under the receiver operating characteristic curve (AUC), Kappa and independent validation samples. Hotspot counties were mainly mountainous lands in southwest China. Higher risk of bacillary dysentery was found associated with underdeveloped socio-economy, proximity to farmland or water bodies, higher environmental temperature, medium relative humidity and the distribution of the Tibeto-Burman ethnicity. A predictive risk map with high accuracy (88.19%) was generated. The high-risk areas are mainly located in the mountainous lands where the Tibeto-Burman people live, especially in the basins, river valleys or other flat places in the mountains with relatively lower elevation and a warmer climate. In the high-risk areas predicted by this study, improving the economic development, investment in health care and the construction of infrastructures for safe water supply, waste treatment and sewage disposal, and improving health related education could reduce the disease risk.

Environmental Drivers and Predicted Risk of Bacillary Dysentery in Southwest China

PubMed Central

Si, Yali; Gong, Peng

2017-01-01

Bacillary dysentery has long been a considerable health problem in southwest China, however, the quantitative relationship between anthropogenic and physical environmental factors and the disease is not fully understand. It is also not clear where exactly the bacillary dysentery risk is potentially high. Based on the result of hotspot analysis, we generated training samples to build a spatial distribution model. Univariate analyses, autocorrelation and multi-collinearity examinations and stepwise selection were then applied to screen the potential causative factors. Multiple logistic regressions were finally applied to quantify the effects of key factors. A bootstrapping strategy was adopted while fitting models. The model was evaluated by area under the receiver operating characteristic curve (AUC), Kappa and independent validation samples. Hotspot counties were mainly mountainous lands in southwest China. Higher risk of bacillary dysentery was found associated with underdeveloped socio-economy, proximity to farmland or water bodies, higher environmental temperature, medium relative humidity and the distribution of the Tibeto-Burman ethnicity. A predictive risk map with high accuracy (88.19%) was generated. The high-risk areas are mainly located in the mountainous lands where the Tibeto-Burman people live, especially in the basins, river valleys or other flat places in the mountains with relatively lower elevation and a warmer climate. In the high-risk areas predicted by this study, improving the economic development, investment in health care and the construction of infrastructures for safe water supply, waste treatment and sewage disposal, and improving health related education could reduce the disease risk. PMID:28708077

Computational modeling of river flow using bathymetry collected with an experimental, water-penetrating, green LiDAR

NASA Astrophysics Data System (ADS)

Kinzel, P. J.; Legleiter, C. J.; Nelson, J. M.

2009-12-01

Airborne bathymetric Light Detection and Ranging (LiDAR) systems designed for coastal and marine surveys are increasingly being deployed in fluvial environments. While the adaptation of this technology to rivers and streams would appear to be straightforward, currently technical challenges remain with regard to achieving high levels of vertical accuracy and precision when mapping bathymetry in shallow fluvial settings. Collectively these mapping errors have a direct bearing on hydraulic model predictions made using these data. We compared channel surveys conducted along the Platte River, Nebraska, and the Trinity River, California, using conventional ground-based methods with those made with the hybrid topographic/bathymetric Experimental Advanced Airborne Research LiDAR (EAARL). In the turbid and braided Platte River, a bathymetric-waveform processing algorithm was shown to enhance the definition of thalweg channels over a more simplified, first-surface waveform processing algorithm. Consequently flow simulations using data processed with the shallow bathymetric algorithm resulted in improved prediction of wetted area relative to the first-surface algorithm, when compared to the wetted area in concurrent aerial imagery. However, when compared to using conventionally collected data for flow modeling, the inundation extent was over predicted with the EAARL topography due to higher bed elevations measured by the LiDAR. In the relatively clear, meandering Trinity River, bathymetric processing algorithms were capable of defining a 3 meter deep pool. However, a similar bias in depth measurement was observed, with the LiDAR measuring the elevation of the river bottom above its actual position, resulting in a predicted water surface higher than that measured by field data. This contribution addresses the challenge of making bathymetric measurements with the EAARL in different environmental conditions encountered in fluvial settings, explores technical issues related to reliably detecting the water surface and river bottom, and illustrates the impact of using LiDAR data and current processing techniques to produce above and below water topographic surfaces for hydraulic modeling and habitat applications.

A High Resolution Tropical Cyclone Power Outage Forecasting Model for the Continental United States

NASA Astrophysics Data System (ADS)

Pino, J. V.; Quiring, S. M.; Guikema, S.; Shashaani, S.; Linger, S.; Backhaus, S.

2017-12-01

Tropical cyclones cause extensive damage to the power infrastructure system throughout the United States. This damage can leave millions without power for extended periods of time, as most recently seen with Hurricane Matthew (2016). Accurate and timely prediction of power outages are essential for utility companies, emergency management agencies, and governmental organizations. Here we present a high-resolution (250 m x 250 m) hurricane power outage model for the United States. The model uses only publicly-available data to make predictions. It uses forecasts of storm variables such as maximum 3-second wind gust, duration of strong winds > 20 m s-2, soil moisture, and precipitation. It also incorporates static environmental variables such as elevation characteristics, land cover type, population density, tree species data, and root zone depth. A web tool was established for use by the Department of Energy (DOE) so that the model can be used for real-time outage forecasting or for synthetic tropical cyclones as an exercise in emergency management. This web tool provides DOE decision-makers with high impact analytic results and products that can be disseminated to federal, local, and state agencies. The results then aid utility companies in their pre- and post-storm activities, thus decreasing restoration times and lowering costs.

Assessing Coupled Social Ecological Flood Vulnerability from Uttarakhand, India, to the State of New York with Google Earth Engine

NASA Astrophysics Data System (ADS)

Tellman, B.; Schwarz, B.

2014-12-01

This talk describes the development of a web application to predict and communicate vulnerability to floods given publicly available data, disaster science, and geotech cloud capabilities. The proof of concept in Google Earth Engine API with initial testing on case studies in New York and Utterakhand India demonstrates the potential of highly parallelized cloud computing to model socio-ecological disaster vulnerability at high spatial and temporal resolution and in near real time. Cloud computing facilitates statistical modeling with variables derived from large public social and ecological data sets, including census data, nighttime lights (NTL), and World Pop to derive social parameters together with elevation, satellite imagery, rainfall, and observed flood data from Dartmouth Flood Observatory to derive biophysical parameters. While more traditional, physically based hydrological models that rely on flow algorithms and numerical methods are currently unavailable in parallelized computing platforms like Google Earth Engine, there is high potential to explore "data driven" modeling that trades physics for statistics in a parallelized environment. A data driven approach to flood modeling with geographically weighted logistic regression has been initially tested on Hurricane Irene in southeastern New York. Comparison of model results with observed flood data reveals a 97% accuracy of the model to predict flooded pixels. Testing on multiple storms is required to further validate this initial promising approach. A statistical social-ecological flood model that could produce rapid vulnerability assessments to predict who might require immediate evacuation and where could serve as an early warning. This type of early warning system would be especially relevant in data poor places lacking the computing power, high resolution data such as LiDar and stream gauges, or hydrologic expertise to run physically based models in real time. As the data-driven model presented relies on globally available data, the only real time data input required would be typical data from a weather service, e.g. precipitation or coarse resolution flood prediction. However, model uncertainty will vary locally depending upon the resolution and frequency of observed flood and socio-economic damage impact data.

Disentangling contributions of bar attendance, drinking, and other factors to elevated acute alcohol problems on the U.S.-Mexico border.

PubMed

Mills, Britain A; Caetano, Raul; Vaeth, Patrice A C; Reingle Gonzalez, Jennifer M

2015-11-01

Levels of drinking are unusually elevated among young adults on the U.S.-Mexico border, and this elevation can be largely explained by young border residents' unusually high frequency of bar attendance. However, this explanation complicates interpretation of high alcohol problem rates that have also been observed in this group. Because bar environments can lower the threshold for many types of problems, the extent to which elevated alcohol problems among young border residents can be attributed to drinking per se-versus this common drinking context-is not clear. Data were collected from multistage cluster samples of adult Mexican Americans on and off the U.S.-Mexico border (current drinker N = 1,351). After developing structural models of acute alcohol problems, estimates were subjected to path decompositions to disentangle the common and distinct contributions of drinking and bar attendance to problem disparities on and off the border. Additionally, models were estimated under varying degrees of adjustment to gauge the sensitivity of the results to sociodemographic, social-cognitive, and environmental sources of confounding. Consistent with previous findings for both drinking and other problem measures, acute alcohol problems were particularly elevated among young adults on the border. This elevation was entirely explained by a single common pathway involving bar attendance frequency and drinking. Bar attendance did not predict acute alcohol problems independently of drinking, and its effect was not moderated by border proximity or age. The common indirect effect and its component effects (of border youth on bar attendance, of bar attendance on drinking, and of drinking on problems) were surprisingly robust to adjustment for confounding in all parts of the model (e.g., fully adjusted indirect effect: b = 0.11, SE = 0.04, p < 0.01). Bar attendance and associated increases in drinking play a key, unique role in the high levels of acute alcohol problems among the border's young adult population that cannot be entirely explained by sociodemographic or social-cognitive characteristics of young border residents, by contextual effects of bars on problems, or by broader neighborhood factors. Bar attendance in particular may represent an early modifiable risk factor that can be targeted to reduce alcohol problem disparities in the region. Copyright © 2015 by the Research Society on Alcoholism.

A generic approach for the development of short-term predictions of Escherichia coli and biotoxins in shellfish

PubMed Central

Schmidt, Wiebke; Evers-King, Hayley L.; Campos, Carlos J. A.; Jones, Darren B.; Miller, Peter I.; Davidson, Keith; Shutler, Jamie D.

2018-01-01

Microbiological contamination or elevated marine biotoxin concentrations within shellfish can result in temporary closure of shellfish aquaculture harvesting, leading to financial loss for the aquaculture business and a potential reduction in consumer confidence in shellfish products. We present a method for predicting short-term variations in shellfish concentrations of Escherichia coli and biotoxin (okadaic acid and its derivates dinophysistoxins and pectenotoxins). The approach was evaluated for 2 contrasting shellfish harvesting areas. Through a meta-data analysis and using environmental data (in situ, satellite observations and meteorological nowcasts and forecasts), key environmental drivers were identified and used to develop models to predict E. coli and biotoxin concentrations within shellfish. Models were trained and evaluated using independent datasets, and the best models were identified based on the model exhibiting the lowest root mean square error. The best biotoxin model was able to provide 1 wk forecasts with an accuracy of 86%, a 0% false positive rate and a 0% false discovery rate (n = 78 observations) when used to predict the closure of shellfish beds due to biotoxin. The best E. coli models were used to predict the European hygiene classification of the shellfish beds to an accuracy of 99% (n = 107 observations) and 98% (n = 63 observations) for a bay (St Austell Bay) and an estuary (Turnaware Bar), respectively. This generic approach enables high accuracy short-term farm-specific forecasts, based on readily accessible environmental data and observations. PMID:29805719

Using satellite remote sensing to model and map the distribution of Bicknell's thrush (Catharus bicknelli) in the White Mountains of New Hampshire

NASA Astrophysics Data System (ADS)

Hale, Stephen Roy

Landsat-7 Enhanced Thematic Mapper satellite imagery was used to model Bicknell's Thrush (Catharus bicknelli) distribution in the White Mountains of New Hampshire. The proof-of-concept was established for using satellite imagery in species-habitat modeling, where for the first time imagery spectral features were used to estimate a species-habitat model variable. The model predicted rising probabilities of thrush presence with decreasing dominant vegetation height, increasing elevation, and decreasing distance to nearest Fir Sapling cover type. To solve the model at all locations required regressor estimates at every pixel, which were not available for the dominant vegetation height and elevation variables. Topographically normalized imagery features Normalized Difference Vegetation Index and Band 1 (blue) were used to estimate dominant vegetation height using multiple linear regression; and a Digital Elevation Model was used to estimate elevation. Distance to nearest Fir Sapling cover type was obtained for each pixel from a land cover map specifically constructed for this project. The Bicknell's Thrush habitat model was derived using logistic regression, which produced the probability of detecting a singing male based on the pattern of model covariates. Model validation using Bicknell's Thrush data not used in model calibration, revealed that the model accurately estimated thrush presence at probabilities ranging from 0 to <0.40 and from 0.50 to <0.60. Probabilities from 0.40 to <0.50 and greater than 0.60 significantly underestimated and overestimated presence, respectively. Applying the model to the study area illuminated an important implication for Bicknell's Thrush conservation. The model predicted increasing numbers of presences and increasing relative density with rising elevation, with which exists a concomitant decrease in land area. Greater land area of lower density habitats may account for more total individuals and reproductive output than higher density less abundant land area. Efforts to conserve areas of highest individual density under the assumption that density reflects habitat quality could target the smallest fraction of the total population.

Significance of Thermal Fluvial Incision and Bedrock Transfer due to Ice Advection on Greenland Ice Sheet Topography

NASA Astrophysics Data System (ADS)

Crozier, J. A.; Karlstrom, L.; Yang, K.

2017-12-01

Ice sheet surface topography reflects a complicated combination of processes that act directly upon the surface and that are products of ice advection. Using recently-available high resolution ice velocity, imagery, ice surface elevation, and bedrock elevation data sets, we seek to determine the domain of significance of two important processes - thermal fluvial incision and transfer of bedrock topography through the ice sheet - on controlling surface topography in the ablation zone. Evaluating such controls is important for understanding how melting of the GIS surface during the melt season may be directly imprinted in topography through supraglacial drainage networks, and indirectly imprinted through its contribution to basal sliding that affects bedrock transfer. We use methods developed by (Karlstrom and Yang, 2016) to identify supraglacial stream networks on the GIS, and use high resolution surface digital elevation models as well as gridded ice velocity and melt rate models to quantify surface processes. We implement a numerically efficient Fourier domain bedrock transfer function (Gudmundsson, 2003) to predict surface topography due to ice advection over bedrock topography obtained from radar. Despite a number of simplifying assumptions, the bedrock transfer function predicts the observed ice sheet surface in most regions of the GIS with ˜90% accuracy, regardless of the presence or absence of supraglacial drainage networks. This supports the hypothesis that bedrock is the most significant driver of ice surface topography on wavelengths similar to ice thickness. Ice surface topographic asymmetry on the GIS is common, with slopes in the direction of ice flow steeper than those faced opposite to ice flow, consistent with bedrock transfer theory. At smaller wavelengths, topography consistent with fluvial erosion by surface hydrologic features is evident. We quantify the effect of ice advection versus fluvial thermal erosion on supraglacial longitudinal stream profiles, as a function of location on the GIS (hence ice thickness and background melt rate) using spectral techniques to quantify longitudinal stream profiles. This work should provide a predictive guide for which processes are responsible for ice sheet topography scales from several m (DEM resolution) up to several ice thicknesses.

Leaf Area Index Drives Soil Water Availability and Extreme Drought-Related Mortality under Elevated CO2 in a Temperate Grassland Model System

PubMed Central

Manea, Anthony; Leishman, Michelle R.

2014-01-01

The magnitude and frequency of climatic extremes, such as drought, are predicted to increase under future climate change conditions. However, little is known about how other factors such as CO2 concentration will modify plant community responses to these extreme climatic events, even though such modifications are highly likely. We asked whether the response of grasslands to repeat extreme drought events is modified by elevated CO2, and if so, what are the underlying mechanisms? We grew grassland mesocosms consisting of 10 co-occurring grass species common to the Cumberland Plain Woodland of western Sydney under ambient and elevated CO2 and subjected them to repeated extreme drought treatments. The 10 species included a mix of C3, C4, native and exotic species. We hypothesized that a reduction in the stomatal conductance of the grasses under elevated CO2 would be offset by increases in the leaf area index thus the retention of soil water and the consequent vulnerability of the grasses to extreme drought would not differ between the CO2 treatments. Our results did not support this hypothesis: soil water content was significantly lower in the mesocosms grown under elevated CO2 and extreme drought-related mortality of the grasses was greater. The C4 and native grasses had significantly higher leaf area index under elevated CO2 levels. This offset the reduction in the stomatal conductance of the exotic grasses as well as increased rainfall interception, resulting in reduced soil water content in the elevated CO2 mesocosms. Our results suggest that projected increases in net primary productivity globally of grasslands in a high CO2 world may be limited by reduced soil water availability in the future. PMID:24632832

Leaf area index drives soil water availability and extreme drought-related mortality under elevated CO2 in a temperate grassland model system.

PubMed

Manea, Anthony; Leishman, Michelle R

2014-01-01

The magnitude and frequency of climatic extremes, such as drought, are predicted to increase under future climate change conditions. However, little is known about how other factors such as CO2 concentration will modify plant community responses to these extreme climatic events, even though such modifications are highly likely. We asked whether the response of grasslands to repeat extreme drought events is modified by elevated CO2, and if so, what are the underlying mechanisms? We grew grassland mesocosms consisting of 10 co-occurring grass species common to the Cumberland Plain Woodland of western Sydney under ambient and elevated CO2 and subjected them to repeated extreme drought treatments. The 10 species included a mix of C3, C4, native and exotic species. We hypothesized that a reduction in the stomatal conductance of the grasses under elevated CO2 would be offset by increases in the leaf area index thus the retention of soil water and the consequent vulnerability of the grasses to extreme drought would not differ between the CO2 treatments. Our results did not support this hypothesis: soil water content was significantly lower in the mesocosms grown under elevated CO2 and extreme drought-related mortality of the grasses was greater. The C4 and native grasses had significantly higher leaf area index under elevated CO2 levels. This offset the reduction in the stomatal conductance of the exotic grasses as well as increased rainfall interception, resulting in reduced soil water content in the elevated CO2 mesocosms. Our results suggest that projected increases in net primary productivity globally of grasslands in a high CO2 world may be limited by reduced soil water availability in the future.

Effect of elevated [CO2 ] on yield, intra-plant nutrient dynamics, and grain quality of rice cultivars in Eastern India.

PubMed

Jena, Usha Rani; Swain, Dillip Kumar; Hazra, K K; Maity, Mrinal K

2018-05-16

Climate models predict an increase in global temperature in response to a doubling of atmospheric [CO 2 ] that may impact future rice production and quality. In this study, the effect of elevated [CO 2 ] on yield, nutrient acquisition and utilization, and grain quality of rice genotypes was investigated in subtropical climate of eastern India (Kharagpur). Three environments (open field, ambient, and elevated [CO 2 ]) were tested using four rice cultivars of eastern India. Under elevated [CO 2 ] (25% higher), yield of high yielding cultivars (HYCs) viz. IR 36, Swarna, and Swarna sub1 was significantly reduced (11-13%), whereas the yield increased (6-9%) for Badshabhog, a low-yielding aromatic cultivar. Elevated [CO 2 ] significantly enhanced K uptake (14-21%), but did not influence the uptake of total N and P. The nutrient harvest index and use efficiency values in HYCs were reduced under elevated [CO 2 ] indicating that nutrients translocation from source to sink (grain) was significantly reduced. An increase in alkali spreading value (10%) and reduction in grain protein (2-3%) and iron (5-6%) was also observed upon [CO 2 ] elevation. The study highlights the importance of nutrient management (increasing N rate for HYCs) and selective breeding of tolerant cultivar in minimizing the adverse effect of elevated [CO 2 ] on rice yield and quality. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Two-dimensional streamflow simulations of the Jordan River, Midvale and West Jordan, Utah

USGS Publications Warehouse

Kenney, Terry A.; Freeman, Michael L.

2011-01-01

The Jordan River in Midvale and West Jordan, Utah, flows adjacent to two U.S. Environmental Protection Agency Superfund sites: Midvale Slag and Sharon Steel. At both sites, geotechnical caps extend to the east bank of the river. The final remediation tasks for these sites included the replacement of a historic sheet-pile dam and the stabilization of the river banks adjacent to the Superfund sites. To assist with these tasks, two hydraulic modeling codes contained in the U.S. Geological Survey (USGS) Multi-Dimensional Surface-Water Modeling System (MD_SWMS), System for Transport and River Modeling (SToRM) and Flow and Sediment Transport and Morphological Evolution of Channels (FaSTMECH), were used to provide predicted water-surface elevations, velocities, and boundary shear-stress values throughout the study reach of the Jordan River. A SToRM model of a 0.7 mile subreach containing the sheet-pile dam was used to compare water-surface elevations and velocities associated with the sheet-pile dam and a proposed replacement structure. Maps showing water-surface elevation and velocity differences computed from simulations of the historic sheet-pile dam and the proposed replacement structure topographies for streamflows of 500 and 1,000 cubic feet per second (ft3/s) were created. These difference maps indicated that the velocities associated with the proposed replacement structure topographies were less than or equal to those associated with the historic sheet-pile dam. Similarly, water-surface elevations associated with the proposed replacement structure topographies were all either greater than or equal to water-surface elevations associated with the sheet-pile dam. A FaSTMECH model was developed for the 2.5-mile study reach to aid engineers in bank stabilization designs. Predicted water-surface elevations, velocities and shear-stress values were mapped on an aerial photograph of the study reach to place these parameters in a spatial context. Profile plots of predicted cross-stream average water-surface elevations and cross-stream maximum and average velocities showed how these parameters change along the study reach for two simulated discharges of 1,040 ft3/s and 2,790 ft3/s. The profile plots for the simulated streamflow of 1,040 ft3/s show that the highest velocities are associated with the constructed sheet-pile replacement structure. Results for the simulated streamflow of 2,790 ft3/s indicate that the geometry of the 7800 South Bridge causes more backwater and higher velocities than the constructed sheet-pile replacement structure.

Examining conifer canopy structural complexity across forest ages and elevations with LiDAR data

Treesearch

Van R. Kane; Jonathan D. Bakker; Robert J. McGaughey; James A. Lutz; Rolf F. Gersonde; Jerry F. Franklin

2010-01-01

LiDAR measurements of canopy structure can be used to classify forest stands into structural stages to study spatial patterns of canopy structure, identify habitat, or plan management actions. A key assumption in this process is that differences in canopy structure based on forest age and elevation are consistent with predictions from models of stand development. Three...

River Discharge and Bathymetry Estimation from Hydraulic Inversion of Surface Currents and Water Surface Elevation Observations

NASA Astrophysics Data System (ADS)

Simeonov, J.; Holland, K. T.

2015-12-01

We developed an inversion model for river bathymetry and discharge estimation based on measurements of surface currents, water surface elevation and shoreline coordinates. The model uses a simplification of the 2D depth-averaged steady shallow water equations based on a streamline following system of coordinates and assumes spatially uniform bed friction coefficient and eddy viscosity. The spatial resolution of the predicted bathymetry is related to the resolution of the surface currents measurements. The discharge is determined by minimizing the difference between the predicted and the measured streamwise variation of the total head. The inversion model was tested using in situ and remote sensing measurements of the Kootenai River east of Bonners Ferry, ID. The measurements were obtained in August 2010 when the discharge was about 223 m3/s and the maximum river depth was about 6.5 m. Surface currents covering a 10 km reach with 8 m spatial resolution were estimated from airborne infrared video and were converted to depth-averaged currents using acoustic Doppler current profiler (ADCP) measurements along eight cross-stream transects. The streamwise profile of the water surface elevation was measured using real-time kinematic GPS from a drifting platform. The value of the friction coefficient was obtained from forward calibration simulations that minimized the difference between the predicted and measured velocity and water level along the river thalweg. The predicted along/cross-channel water depth variation was compared to the depth measured with a multibeam echo sounder. The rms error between the measured and predicted depth along the thalweg was found to be about 60cm and the estimated discharge was 5% smaller than the discharge measured by the ADCP.

Long-term prediction test procedure for most ICs, based on linear response theory

NASA Technical Reports Server (NTRS)

Litovchenko, V.; Ivakhnenko, I.

1991-01-01

Experimentally, thermal annealing is known to be a factor which enables a number of different integrated circuits (IC's) to recover their operating characteristics after suffering radiation damage in the space radiation environment; thus, decreasing and limiting long term cumulative total-dose effects. This annealing is also known to be accelerated at elevated temperatures both during and after irradiation. Linear response theory (LRT) was applied, and a linear response function (LRF) to predict the radiation/annealing response of sensitive parameters of IC's for long term (several months or years) exposure to the space radiation environment were constructed. Compressing the annealing process from several years in orbit to just a few hours or days in the laboratory is achieved by subjecting the IC to elevated temperatures or by increasing the typical spaceflight dose rate by several orders of magnitude for simultaneous radiation/annealing only. The accomplishments are as follows: (1) the test procedure to make predictions of the radiation response was developed; (2) the calculation of the shift in the threshold potential due to the charge distribution in the oxide was written; (3) electron tunneling processes from the bulk Si to the oxide region in an MOS IC were estimated; (4) in order to connect the experimental annealing data to the theoretical model, constants of the model of the basic annealing process were established; (5) experimental data obtained at elevated temperatures were analyzed; (6) time compression and reliability of predictions for the long term region were shown; (7) a method to compress test time and to make predictions of response for the nonlinear region was proposed; and (8) nonlinearity of the LRF with respect to log(t) was calculated theoretically from a model.

Simulation of Water-Surface Elevations and Velocity Distributions at the U.S. Highway 13 Bridge over the Tar River at Greenville, North Carolina, Using One- and Two-Dimensional Steady-State Hydraulic Models

USGS Publications Warehouse

Wagner, Chad R.

2007-01-01

The use of one-dimensional hydraulic models currently is the standard method for estimating velocity fields through a bridge opening for scour computations and habitat assessment. Flood-flow contraction through bridge openings, however, is hydrodynamically two dimensional and often three dimensional. Although there is awareness of the utility of two-dimensional models to predict the complex hydraulic conditions at bridge structures, little guidance is available to indicate whether a one- or two-dimensional model will accurately estimate the hydraulic conditions at a bridge site. The U.S. Geological Survey, in cooperation with the North Carolina Department of Transportation, initiated a study in 2004 to compare one- and two-dimensional model results with field measurements at complex riverine and tidal bridges in North Carolina to evaluate the ability of each model to represent field conditions. The field data consisted of discharge and depth-averaged velocity profiles measured with an acoustic Doppler current profiler and surveyed water-surface profiles for two high-flow conditions. For the initial study site (U.S. Highway 13 over the Tar River at Greenville, North Carolina), the water-surface elevations and velocity distributions simulated by the one- and two-dimensional models showed appreciable disparity in the highly sinuous reach upstream from the U.S. Highway 13 bridge. Based on the available data from U.S. Geological Survey streamgaging stations and acoustic Doppler current profiler velocity data, the two-dimensional model more accurately simulated the water-surface elevations and the velocity distributions in the study reach, and contracted-flow magnitudes and direction through the bridge opening. To further compare the results of the one- and two-dimensional models, estimated hydraulic parameters (flow depths, velocities, attack angles, blocked flow width) for measured high-flow conditions were used to predict scour depths at the U.S. Highway 13 bridge by using established methods. Comparisons of pier-scour estimates from both models indicated that the scour estimates from the two-dimensional model were as much as twice the depth of the estimates from the one-dimensional model. These results can be attributed to higher approach velocities and the appreciable flow angles at the piers simulated by the two-dimensional model and verified in the field. Computed flood-frequency estimates of the 10-, 50-, 100-, and 500-year return-period floods on the Tar River at Greenville were also simulated with both the one- and two-dimensional models. The simulated water-surface profiles and velocity fields of the various return-period floods were used to compare the modeling approaches and provide information on what return-period discharges would result in road over-topping and(or) pressure flow. This information is essential in the design of new and replacement structures. The ability to accurately simulate water-surface elevations and velocity magnitudes and distributions at bridge crossings is essential in assuring that bridge plans balance public safety with the most cost-effective design. By compiling pertinent bridge-site characteristics and relating them to the results of several model-comparison studies, the framework for developing guidelines for selecting the most appropriate model for a given bridge site can be accomplished.

A simple validated method for predicting the risk of hospitalization for worsening of heart failure in ambulatory patients: the Redin-SCORE.

PubMed

Álvarez-García, Jesús; Ferrero-Gregori, Andreu; Puig, Teresa; Vázquez, Rafael; Delgado, Juan; Pascual-Figal, Domingo; Alonso-Pulpón, Luis; González-Juanatey, José R; Rivera, Miguel; Worner, Fernando; Bardají, Alfredo; Cinca, Juan

2015-08-01

Prevention of hospital readmissions is one of the main objectives in the management of patients with heart failure (HF). Most of the models predicting readmissions are based on data extracted from hospitalized patients rather than from outpatients. Our objective was to develop a validated score predicting 1-month and 1-year risk of readmission for worsening of HF in ambulatory patients. A cohort of 2507 ambulatory patients with chronic HF was prospectively followed for a median of 3.3 years. Clinical, echocardiographic, ECG, and biochemical variables were used in a competing risk regression analysis to construct a risk score for readmissions due to worsening of HF. Thereafter, the score was externally validated using a different cohort of 992 patients with chronic HF (MUSIC registry). Predictors of 1-month readmission were the presence of elevated natriuretic peptides, left ventricular (LV) HF signs, and estimated glomerular filtration rate (eGFR) <60 mL/min/m(2) . Predictors of 1-year readmission were elevated natriuretic peptides, anaemia, left atrial size >26 mm/m(2) , heart rate >70 b.p.m., LV HF signs, and eGFR <60 mL/min/m(2) . The C-statistics for the models were 0.72 and 0.66, respectively. The cumulative incidence function distinguished low-risk (<1% event rate) and high-risk groups (>5% event rate) for 1-month HF readmission. Likewise, low-risk (7.8%), intermediate-risk (15.6%) and high-risk groups (26.1%) were identified for 1-year HF readmission risk. The C-statistics remained consistent after the external validation (<5% loss of discrimination). The Redin-SCORE predicts early and late readmission for worsening of HF using proven prognostic variables that are routinely collected in outpatient management of chronic HF. © 2015 The Authors. European Journal of Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology.

Assessing coastal wetland vulnerability to sea-level rise along the northern Gulf of Mexico coast: Gaps and opportunities for developing a coordinated regional sampling network

PubMed Central

Griffith, Kereen T.; Larriviere, Jack C.; Feher, Laura C.; Cahoon, Donald R.; Enwright, Nicholas M.; Oster, David A.; Tirpak, John M.; Woodrey, Mark S.; Collini, Renee C.; Baustian, Joseph J.; Breithaupt, Joshua L.; Cherry, Julia A.; Conrad, Jeremy R.; Cormier, Nicole; Coronado-Molina, Carlos A.; Donoghue, Joseph F.; Graham, Sean A.; Harper, Jennifer W.; Hester, Mark W.; Howard, Rebecca J.; Krauss, Ken W.; Kroes, Daniel E.; Lane, Robert R.; McKee, Karen L.; Mendelssohn, Irving A.; Middleton, Beth A.; Moon, Jena A.; Piazza, Sarai C.; Rankin, Nicole M.; Sklar, Fred H.; Steyer, Greg D.; Swanson, Kathleen M.; Swarzenski, Christopher M.; Vervaeke, William C.; Willis, Jonathan M.; Wilson, K. Van

2017-01-01

Coastal wetland responses to sea-level rise are greatly influenced by biogeomorphic processes that affect wetland surface elevation. Small changes in elevation relative to sea level can lead to comparatively large changes in ecosystem structure, function, and stability. The surface elevation table-marker horizon (SET-MH) approach is being used globally to quantify the relative contributions of processes affecting wetland elevation change. Historically, SET-MH measurements have been obtained at local scales to address site-specific research questions. However, in the face of accelerated sea-level rise, there is an increasing need for elevation change network data that can be incorporated into regional ecological models and vulnerability assessments. In particular, there is a need for long-term, high-temporal resolution data that are strategically distributed across ecologically-relevant abiotic gradients. Here, we quantify the distribution of SET-MH stations along the northern Gulf of Mexico coast (USA) across political boundaries (states), wetland habitats, and ecologically-relevant abiotic gradients (i.e., gradients in temperature, precipitation, elevation, and relative sea-level rise). Our analyses identify areas with high SET-MH station densities as well as areas with notable gaps. Salt marshes, intermediate elevations, and colder areas with high rainfall have a high number of stations, while salt flat ecosystems, certain elevation zones, the mangrove-marsh ecotone, and hypersaline coastal areas with low rainfall have fewer stations. Due to rapid rates of wetland loss and relative sea-level rise, the state of Louisiana has the most extensive SET-MH station network in the region, and we provide several recent examples where data from Louisiana’s network have been used to assess and compare wetland vulnerability to sea-level rise. Our findings represent the first attempt to examine spatial gaps in SET-MH coverage across abiotic gradients. Our analyses can be used to transform a broadly disseminated and unplanned collection of SET-MH stations into a coordinated and strategic regional network. This regional network would provide data for predicting and preparing for the responses of coastal wetlands to accelerated sea-level rise and other aspects of global change. PMID:28902904

Assessing coastal wetland vulnerability to sea-level rise along the northern Gulf of Mexico coast: Gaps and opportunities for developing a coordinated regional sampling network

USGS Publications Warehouse

Osland, Michael J.; Griffith, Kereen T.; Larriviere, Jack C.; Feher, Laura C.; Cahoon, Donald R.; Enwright, Nicholas M.; Oster, David A.; Tirpak, John M.; Woodrey, Mark S.; Collini, Renee C.; Baustian, Joseph J.; Breithaupt, Joshua L.; Cherry, Julia A; Conrad, Jeremy R.; Cormier, Nicole; Coronado-Molina, Carlos A.; Donoghue, Joseph F.; Graham, Sean A.; Harper, Jennifer W.; Hester, Mark W.; Howard, Rebecca J.; Krauss, Ken W.; Kroes, Daniel; Lane, Robert R.; Mckee, Karen L.; Mendelssohn, Irving A.; Middleton, Beth A.; Moon, Jena A.; Piazza, Sarai; Rankin, Nicole M.; Sklar, Fred H.; Steyer, Gregory D.; Swanson, Kathleen M.; Swarzenski, Christopher M.; Vervaeke, William; Willis, Jonathan M; Van Wilson, K.

2017-01-01

Coastal wetland responses to sea-level rise are greatly influenced by biogeomorphic processes that affect wetland surface elevation. Small changes in elevation relative to sea level can lead to comparatively large changes in ecosystem structure, function, and stability. The surface elevation table-marker horizon (SET-MH) approach is being used globally to quantify the relative contributions of processes affecting wetland elevation change. Historically, SET-MH measurements have been obtained at local scales to address site-specific research questions. However, in the face of accelerated sea-level rise, there is an increasing need for elevation change network data that can be incorporated into regional ecological models and vulnerability assessments. In particular, there is a need for long-term, high-temporal resolution data that are strategically distributed across ecologically-relevant abiotic gradients. Here, we quantify the distribution of SET-MH stations along the northern Gulf of Mexico coast (USA) across political boundaries (states), wetland habitats, and ecologically-relevant abiotic gradients (i.e., gradients in temperature, precipitation, elevation, and relative sea-level rise). Our analyses identify areas with high SET-MH station densities as well as areas with notable gaps. Salt marshes, intermediate elevations, and colder areas with high rainfall have a high number of stations, while salt flat ecosystems, certain elevation zones, the mangrove-marsh ecotone, and hypersaline coastal areas with low rainfall have fewer stations. Due to rapid rates of wetland loss and relative sea-level rise, the state of Louisiana has the most extensive SET-MH station network in the region, and we provide several recent examples where data from Louisiana’s network have been used to assess and compare wetland vulnerability to sea-level rise. Our findings represent the first attempt to examine spatial gaps in SET-MH coverage across abiotic gradients. Our analyses can be used to transform a broadly disseminated and unplanned collection of SET-MH stations into a coordinated and strategic regional network. This regional network would provide data for predicting and preparing for the responses of coastal wetlands to accelerated sea-level rise and other aspects of global change.

Assessing coastal wetland vulnerability to sea-level rise along the northern Gulf of Mexico coast: Gaps and opportunities for developing a coordinated regional sampling network.

PubMed

Osland, Michael J; Griffith, Kereen T; Larriviere, Jack C; Feher, Laura C; Cahoon, Donald R; Enwright, Nicholas M; Oster, David A; Tirpak, John M; Woodrey, Mark S; Collini, Renee C; Baustian, Joseph J; Breithaupt, Joshua L; Cherry, Julia A; Conrad, Jeremy R; Cormier, Nicole; Coronado-Molina, Carlos A; Donoghue, Joseph F; Graham, Sean A; Harper, Jennifer W; Hester, Mark W; Howard, Rebecca J; Krauss, Ken W; Kroes, Daniel E; Lane, Robert R; McKee, Karen L; Mendelssohn, Irving A; Middleton, Beth A; Moon, Jena A; Piazza, Sarai C; Rankin, Nicole M; Sklar, Fred H; Steyer, Greg D; Swanson, Kathleen M; Swarzenski, Christopher M; Vervaeke, William C; Willis, Jonathan M; Wilson, K Van

2017-01-01

Coastal wetland responses to sea-level rise are greatly influenced by biogeomorphic processes that affect wetland surface elevation. Small changes in elevation relative to sea level can lead to comparatively large changes in ecosystem structure, function, and stability. The surface elevation table-marker horizon (SET-MH) approach is being used globally to quantify the relative contributions of processes affecting wetland elevation change. Historically, SET-MH measurements have been obtained at local scales to address site-specific research questions. However, in the face of accelerated sea-level rise, there is an increasing need for elevation change network data that can be incorporated into regional ecological models and vulnerability assessments. In particular, there is a need for long-term, high-temporal resolution data that are strategically distributed across ecologically-relevant abiotic gradients. Here, we quantify the distribution of SET-MH stations along the northern Gulf of Mexico coast (USA) across political boundaries (states), wetland habitats, and ecologically-relevant abiotic gradients (i.e., gradients in temperature, precipitation, elevation, and relative sea-level rise). Our analyses identify areas with high SET-MH station densities as well as areas with notable gaps. Salt marshes, intermediate elevations, and colder areas with high rainfall have a high number of stations, while salt flat ecosystems, certain elevation zones, the mangrove-marsh ecotone, and hypersaline coastal areas with low rainfall have fewer stations. Due to rapid rates of wetland loss and relative sea-level rise, the state of Louisiana has the most extensive SET-MH station network in the region, and we provide several recent examples where data from Louisiana's network have been used to assess and compare wetland vulnerability to sea-level rise. Our findings represent the first attempt to examine spatial gaps in SET-MH coverage across abiotic gradients. Our analyses can be used to transform a broadly disseminated and unplanned collection of SET-MH stations into a coordinated and strategic regional network. This regional network would provide data for predicting and preparing for the responses of coastal wetlands to accelerated sea-level rise and other aspects of global change.

Coastal marsh response to historical and future sea-level acceleration

USGS Publications Warehouse

Kirwan, M.; Temmerman, S.

2009-01-01

We consider the response of marshland to accelerations in the rate of sea-level rise by utilizing two previously described numerical models of marsh elevation. In a model designed for the Scheldt Estuary (Belgium-SW Netherlands), a feedback between inundation depth and suspended sediment concentrations allows marshes to quickly adjust their elevation to a change in sea-level rise rate. In a model designed for the North Inlet Estuary (South Carolina), a feedback between inundation and vegetation growth allows similar adjustment. Although the models differ in their approach, we find that they predict surprisingly similar responses to sea-level change. Marsh elevations adjust to a step change in the rate of sea-level rise in about 100 years. In the case of a continuous acceleration in the rate of sea-level rise, modeled accretion rates lag behind sea-level rise rates by about 20 years, and never obtain equilibrium. Regardless of the style of acceleration, the models predict approximately 6-14 cm of marsh submergence in response to historical sea-level acceleration, and 3-4 cm of marsh submergence in response to a projected scenario of sea-level rise over the next century. While marshes already low in the tidal frame would be susceptible to these depth changes, our modeling results suggest that factors other than historical sea-level acceleration are more important for observations of degradation in most marshes today.

Decreased C-reactive protein levels in Alzheimer disease.

PubMed

O'Bryant, Sid E; Waring, Stephen C; Hobson, Valerie; Hall, James R; Moore, Carol B; Bottiglieri, Teodoro; Massman, Paul; Diaz-Arrastia, Ramon

2010-03-01

C-reactive protein (CRP) is an acute-phase reactant that has been found to be associated with Alzheimer disease (AD) in histopathological and longitudinal studies; however, little data exist regarding serum CRP levels in patients with established AD. The current study evaluated CRP levels in 192 patients diagnosed with probable AD (mean age = 75.8 +/- 8.2 years; 50% female) as compared to 174 nondemented controls (mean age = 70.6 +/- 8.2 years; 63% female). Mean CRP levels were found to be significantly decreased in AD (2.9 microg/mL) versus controls (4.9 microg/mL; P = .003). In adjusted models, elevated CRP significantly predicted poorer (elevated) Clinical Dementia Rating Scale sum of boxes (CDR SB) scores in patients with AD. In controls, CRP was negatively associated with Mini-Mental State Examination (MMSE) scores and positively associated with CDR SB scores. These findings, together with previously published results, are consistent with the hypothesis that midlife elevations in CRP are associated with increased risk of AD development though elevated CRP levels are not useful for prediction in the immediate prodrome years before AD becomes clinically manifest. However, for a subgroup of patients with AD, elevated CRP continues to predict increased dementia severity suggestive of a possible proinflammatory endophenotype in AD.

Decreased C-Reactive Protein Levels in Alzheimer Disease

PubMed Central

O’Bryant, Sid E.; Waring, Stephen C.; Hobson, Valerie; Hall, James R.; Moore, Carol B.; Bottiglieri, Teodoro; Massman, Paul; Diaz-Arrastia, Ramon

2011-01-01

C-reactive protein (CRP) is an acute-phase reactant that has been found to be associated with Alzheimer disease (AD) in histo-pathological and longitudinal studies; however, little data exist regarding serum CRP levels in patients with established AD. The current study evaluated CRP levels in 192 patients diagnosed with probable AD (mean age = 75.8 ± 8.2 years; 50% female) as compared to 174 nondemented controls (mean age = 70.6 ± 8.2 years; 63% female). Mean CRP levels were found to be significantly decreased in AD (2.9 µg/mL) versus controls (4.9 µg/mL; P = .003). In adjusted models, elevated CRP significantly predicted poorer (elevated) Clinical Dementia Rating Scale sum of boxes (CDR SB) scores in patients with AD. In controls, CRP was negatively associated with Mini-Mental State Examination (MMSE) scores and positively associated with CDR SB scores. These findings, together with previously published results, are consistent with the hypothesis that midlife elevations in CRP are associated with increased risk of AD development though elevated CRP levels are not useful for prediction in the immediate prodrome years before AD becomes clinically manifest. However, for a subgroup of patients with AD, elevated CRP continues to predict increased dementia severity suggestive of a possible proinflammatory endophenotype in AD. PMID:19933496

Transactional Relations Between Marital Functioning and Depressive Symptoms

PubMed Central

Kouros, Chrystyna D.; Cummings, E. Mark

2012-01-01

The present study investigated dynamic, longitudinal associations between depressive symptoms and marital processes. Two hundred ninety-six couples reported on marital satisfaction, marital conflict, and depressive symptoms yearly for three years. Observational measures of marital conflict were also collected. Results suggested that different domains of marital functioning related to husbands’ versus wives’ symptoms. For husbands, transactional relations between marital satisfaction and depressive symptoms were identified: high levels of depressive symptoms predicted subsequent decreases in marital satisfaction, and decreased marital satisfaction predicted subsequent elevations in symptoms over time. For wives, high levels of marital conflict predicted subsequent elevations in symptoms over time. Cross-partner results indicated that husbands’ depressive symptoms were also related to subsequent declines in wives’ marital satisfaction. Results are discussed with regard to theoretical perspectives on the marital functioning-depression link and directions for future research are outlined. PMID:21219284

Stochastic analysis of particle movement over a dune bed

USGS Publications Warehouse

Lee, Baum K.; Jobson, Harvey E.

1977-01-01

Stochastic models are available that can be used to predict the transport and dispersion of bed-material sediment particles in an alluvial channel. These models are based on the proposition that the movement of a single bed-material sediment particle consists of a series of steps of random length separated by rest periods of random duration and, therefore, application of the models requires a knowledge of the probability distributions of the step lengths, the rest periods, the elevation of particle deposition, and the elevation of particle erosion. The procedure was tested by determining distributions from bed profiles formed in a large laboratory flume with a coarse sand as the bed material. The elevation of particle deposition and the elevation of particle erosion can be considered to be identically distributed, and their distribution can be described by either a ' truncated Gaussian ' or a ' triangular ' density function. The conditional probability distribution of the rest period given the elevation of particle deposition closely followed the two-parameter gamma distribution. The conditional probability distribution of the step length given the elevation of particle erosion and the elevation of particle deposition also closely followed the two-parameter gamma density function. For a given flow, the scale and shape parameters describing the gamma probability distributions can be expressed as functions of bed-elevation. (Woodard-USGS)

Bridging gaps: On the performance of airborne LiDAR to model wood mouse-habitat structure relationships in pine forests.

PubMed

Jaime-González, Carlos; Acebes, Pablo; Mateos, Ana; Mezquida, Eduardo T

2017-01-01

LiDAR technology has firmly contributed to strengthen the knowledge of habitat structure-wildlife relationships, though there is an evident bias towards flying vertebrates. To bridge this gap, we investigated and compared the performance of LiDAR and field data to model habitat preferences of wood mouse (Apodemus sylvaticus) in a Mediterranean high mountain pine forest (Pinus sylvestris). We recorded nine field and 13 LiDAR variables that were summarized by means of Principal Component Analyses (PCA). We then analyzed wood mouse's habitat preferences using three different models based on: (i) field PCs predictors, (ii) LiDAR PCs predictors; and (iii) both set of predictors in a combined model, including a variance partitioning analysis. Elevation was also included as a predictor in the three models. Our results indicate that LiDAR derived variables were better predictors than field-based variables. The model combining both data sets slightly improved the predictive power of the model. Field derived variables indicated that wood mouse was positively influenced by the gradient of increasing shrub cover and negatively affected by elevation. Regarding LiDAR data, two LiDAR PCs, i.e. gradients in canopy openness and complexity in forest vertical structure positively influenced wood mouse, although elevation interacted negatively with the complexity in vertical structure, indicating wood mouse's preferences for plots with lower elevations but with complex forest vertical structure. The combined model was similar to the LiDAR-based model and included the gradient of shrub cover measured in the field. Variance partitioning showed that LiDAR-based variables, together with elevation, were the most important predictors and that part of the variation explained by shrub cover was shared. LiDAR derived variables were good surrogates of environmental characteristics explaining habitat preferences by the wood mouse. Our LiDAR metrics represented structural features of the forest patch, such as the presence and cover of shrubs, as well as other characteristics likely including time since perturbation, food availability and predation risk. Our results suggest that LiDAR is a promising technology for further exploring habitat preferences by small mammal communities.

Arsenic concentrations, related environmental factors, and the predicted probability of elevated arsenic in groundwater in Pennsylvania

USGS Publications Warehouse

Gross, Eliza L.; Low, Dennis J.

2013-01-01

Logistic regression models were created to predict and map the probability of elevated arsenic concentrations in groundwater statewide in Pennsylvania and in three intrastate regions to further improve predictions for those three regions (glacial aquifer system, Gettysburg Basin, Newark Basin). Although the Pennsylvania and regional predictive models retained some different variables, they have common characteristics that can be grouped by (1) geologic and soils variables describing arsenic sources and mobilizers, (2) geochemical variables describing the geochemical environment of the groundwater, and (3) locally specific variables that are unique to each of the three regions studied and not applicable to statewide analysis. Maps of Pennsylvania and the three intrastate regions were produced that illustrate that areas most at risk are those with geology and soils capable of functioning as an arsenic source or mobilizer and geochemical groundwater conditions able to facilitate redox reactions. The models have limitations because they may not characterize areas that have localized controls on arsenic mobility. The probability maps associated with this report are intended for regional-scale use and may not be accurate for use at the field scale or when considering individual wells.

Fatigue Life Prediction of 2D Woven Ceramic-Matrix Composites at Room and Elevated Temperatures

NASA Astrophysics Data System (ADS)

Longbiao, Li

2017-03-01

In this paper, the fatigue life of 2D woven ceramic-matrix composites, i.e., SiC/SiC, SiC/Si-N-C, SiC/Si-B4C, and Nextel 610™/Aluminosilicate, at room and elevated temperatures has been predicted using the micromechanics approach. An effective coefficient of the fiber volume fraction along the loading direction (ECFL) was introduced to describe the fiber architecture of preforms. The Budiansky-Hutchinson-Evans shear-lag model was used to describe the microstress field of the damaged composite considering fibers failure. The statistical matrix multicracking model and fracture mechanics interface debonding criterion were used to determine the matrix crack spacing and interface debonded length. The interface shear stress and fibers strength degradation model and oxidation region propagation model have been adopted to analyze the fatigue and oxidation effects on fatigue life of the composite, which is controlled by interface frictional slip and diffusion of oxygen gas through matrix multicrackings. Under cyclic fatigue loading, the fibers broken fraction was determined by combining the interface/fiber oxidation model, interface wear model and fibers statistical failure model at elevated temperatures, based on the assumption that the fiber strength is subjected to two-parameter Weibull distribution and the load carried by broken and intact fibers satisfy the Global Load Sharing (GLS) criterion. When the broken fibers fraction approaches to the critical value, the composites fatigue fractures. The fatigue life S- N curves of 2D SiC/SiC, SiC/Si-N-C, SiC/Si-B4C, and Nextel 610™/Aluminosilicate composites at room temperature and 800, 1000 and 1200 °C in air and steam have been predicted.

Predictive mapping of soil organic carbon in wet cultivated lands using classification-tree based models: the case study of Denmark.

PubMed

Bou Kheir, Rania; Greve, Mogens H; Bøcher, Peder K; Greve, Mette B; Larsen, René; McCloy, Keith

2010-05-01

Soil organic carbon (SOC) is one of the most important carbon stocks globally and has large potential to affect global climate. Distribution patterns of SOC in Denmark constitute a nation-wide baseline for studies on soil carbon changes (with respect to Kyoto protocol). This paper predicts and maps the geographic distribution of SOC across Denmark using remote sensing (RS), geographic information systems (GISs) and decision-tree modeling (un-pruned and pruned classification trees). Seventeen parameters, i.e. parent material, soil type, landscape type, elevation, slope gradient, slope aspect, mean curvature, plan curvature, profile curvature, flow accumulation, specific catchment area, tangent slope, tangent curvature, steady-state wetness index, Normalized Difference Vegetation Index (NDVI), Normalized Difference Wetness Index (NDWI) and Soil Color Index (SCI) were generated to statistically explain SOC field measurements in the area of interest (Denmark). A large number of tree-based classification models (588) were developed using (i) all of the parameters, (ii) all Digital Elevation Model (DEM) parameters only, (iii) the primary DEM parameters only, (iv), the remote sensing (RS) indices only, (v) selected pairs of parameters, (vi) soil type, parent material and landscape type only, and (vii) the parameters having a high impact on SOC distribution in built pruned trees. The best constructed classification tree models (in the number of three) with the lowest misclassification error (ME) and the lowest number of nodes (N) as well are: (i) the tree (T1) combining all of the parameters (ME=29.5%; N=54); (ii) the tree (T2) based on the parent material, soil type and landscape type (ME=31.5%; N=14); and (iii) the tree (T3) constructed using parent material, soil type, landscape type, elevation, tangent slope and SCI (ME=30%; N=39). The produced SOC maps at 1:50,000 cartographic scale using these trees are highly matching with coincidence values equal to 90.5% (Map T1/Map T2), 95% (Map T1/Map T3) and 91% (Map T2/Map T3). The overall accuracies of these maps once compared with field observations were estimated to be 69.54% (Map T1), 68.87% (Map T2) and 69.41% (Map T3). The proposed tree models are relatively simple, and may be also applied to other areas. Copyright 2010 Elsevier Ltd. All rights reserved.

Temperature Prediction Model for Bone Drilling Based on Density Distribution and In Vivo Experiments for Minimally Invasive Robotic Cochlear Implantation.

PubMed

Feldmann, Arne; Anso, Juan; Bell, Brett; Williamson, Tom; Gavaghan, Kate; Gerber, Nicolas; Rohrbach, Helene; Weber, Stefan; Zysset, Philippe

2016-05-01

Surgical robots have been proposed ex vivo to drill precise holes in the temporal bone for minimally invasive cochlear implantation. The main risk of the procedure is damage of the facial nerve due to mechanical interaction or due to temperature elevation during the drilling process. To evaluate the thermal risk of the drilling process, a simplified model is proposed which aims to enable an assessment of risk posed to the facial nerve for a given set of constant process parameters for different mastoid bone densities. The model uses the bone density distribution along the drilling trajectory in the mastoid bone to calculate a time dependent heat production function at the tip of the drill bit. Using a time dependent moving point source Green's function, the heat equation can be solved at a certain point in space so that the resulting temperatures can be calculated over time. The model was calibrated and initially verified with in vivo temperature data. The data was collected in minimally invasive robotic drilling of 12 holes in four different sheep. The sheep were anesthetized and the temperature elevations were measured with a thermocouple which was inserted in a previously drilled hole next to the planned drilling trajectory. Bone density distributions were extracted from pre-operative CT data by averaging Hounsfield values over the drill bit diameter. Post-operative [Formula: see text]CT data was used to verify the drilling accuracy of the trajectories. The comparison of measured and calculated temperatures shows a very good match for both heating and cooling phases. The average prediction error of the maximum temperature was less than 0.7 °C and the average root mean square error was approximately 0.5 °C. To analyze potential thermal damage, the model was used to calculate temperature profiles and cumulative equivalent minutes at 43 °C at a minimal distance to the facial nerve. For the selected drilling parameters, temperature elevation profiles and cumulative equivalent minutes suggest that thermal elevation of this minimally invasive cochlear implantation surgery may pose a risk to the facial nerve, especially in sclerotic or high density mastoid bones. Optimized drilling parameters need to be evaluated and the model could be used for future risk evaluation.

The First Prediction of a Rift Valley Fever Outbreak

NASA Technical Reports Server (NTRS)

Anyamba, Assaf; Chretien, Jean-Paul; Small, Jennifer; Tucker, Compton J.; Formenty, Pierre; Richardson, Jason H.; Britch, Seth C.; Schnabel, David C.; Erickson, Ralph L.; Linthicum, Kenneth J.

2009-01-01

El Nino/Southern Oscillation (ENSO) related anomalies were analyzed using a combination of satellite measurements of elevated sea surface temperatures, and subsequent elevated rainfall and satellite derived normalized difference vegetation index data. A Rift Valley fever risk mapping model using these climate data predicted areas where outbreaks of Rift Valley fever in humans and animals were expected and occurred in the Horn of Africa from December 2006 to May 2007. The predictions were subsequently confirmed by entomological and epidemiological field investigations of virus activity in the areas identified as at risk. Accurate spatial and temporal predictions of disease activity, as it occurred first in southern Somalia and then through much of Kenya before affecting northern Tanzania, provided a 2 to 6 week period of warning for the Horn of Africa that facilitated disease outbreak response and mitigation activities. This is the first prospective prediction of a Rift Valley fever outbreak.

Prediction of a Rift Valley fever outbreak

PubMed Central

Anyamba, Assaf; Chretien, Jean-Paul; Small, Jennifer; Tucker, Compton J.; Formenty, Pierre B.; Richardson, Jason H.; Britch, Seth C.; Schnabel, David C.; Erickson, Ralph L.; Linthicum, Kenneth J.

2009-01-01

El Niño/Southern Oscillation related climate anomalies were analyzed by using a combination of satellite measurements of elevated sea-surface temperatures and subsequent elevated rainfall and satellite-derived normalized difference vegetation index data. A Rift Valley fever (RVF) risk mapping model using these climate data predicted areas where outbreaks of RVF in humans and animals were expected and occurred in the Horn of Africa from December 2006 to May 2007. The predictions were subsequently confirmed by entomological and epidemiological field investigations of virus activity in the areas identified as at risk. Accurate spatial and temporal predictions of disease activity, as it occurred first in southern Somalia and then through much of Kenya before affecting northern Tanzania, provided a 2 to 6 week period of warning for the Horn of Africa that facilitated disease outbreak response and mitigation activities. To our knowledge, this is the first prospective prediction of a RVF outbreak. PMID:19144928

Adherence to Bergmann's rule by lizards may depend on thermoregulatory mode: support from a nocturnal gecko.

PubMed

Penniket, Sophie; Cree, Alison

2015-06-01

Bergmann's rule predicts an increase in body size with decreasing environmental temperature; however, the converse pattern has been found in the majority of lizards studied to date. For these ectotherms, small body size may provide thermal benefits (rapid heat uptake when basking), which would be highly advantageous in cold environments. Yet such an advantage may not exist in nocturnal lizards (which do not avidly bask), in which Bergmann's rule has not been closely studied. We have examined whether the body size of a primarily nocturnal gecko, Woodworthia "Otago/Southland" changed with elevation and operative temperature (determined using physical copper models). In a laboratory study, we investigated whether thermoregulatory mode (heliothermy or thigmothermy) alters the effect of body size on heating and cooling rates. This gecko followed Bergmann's rule, thereby showing the opposite of the dominant pattern in diurnal lizards. Size at maturity, maximum size of adults and size at birth were larger at higher elevations and at lower operative temperatures. Using physical models, we found that large body size can confer thermal benefits for nocturnal lizards that remain within diurnal retreats. Bergmann's rule should not be dismissed for all lizards. Our results clearly support Bergmann's rule for at least one thigmothermic species, for which large body size may provide thermal benefits. Future studies on Bergmann's rule in lizards should consider thermoregulatory mode. We advocate that this ecogeographic rule be examined in relation to operative temperature measured at field sites. Finally, we predict that climate warming may weaken the relationship between body size and elevation in this gecko.

A climatology and preliminary investigation of predictability of pristine nocturnal convective initiation in the central United States

NASA Astrophysics Data System (ADS)

Stelten, Sean; Gallus, William

2017-04-01

The prediction of convective initiation remains a challenge to forecasters in the central United States, especially for elevated events at night. This study examines a subset of 287 nocturnal elevated convective initiation events that occurred without direct influence from surface boundaries or pre-existing convection over a four-month period during the summer of 2015 (May, June, July, and August). Events were first classified into one of four types based on apparent formation mechanisms and location relative to any low-level jet. A climatology of each of the four types was performed focusing on general spatial tendencies over the central United States and initiation timing trends. Additionally, analysis of initiation elevation was performed. Simulations from five convection-allowing models available during the Plains Elevated Convection At Night (PECAN) field campaign, along with four versions of a 4km horizontal grid spacing Weather Research and Forecasting (WRF) model using different planetary boundary layer (PBL) parameterizations, were used to examine predictability of these types of convective initiation. The climatology revealed a dual-peak pattern for initiation timing with one peak near 0400 UTC and another 0700 UTC, and it was found that the dual peak structure was present for all four types of events, suggesting that the evolution of the low-level jet was not directly responsible for the twin peaks. Subtle differences in location and elevation of the initiation for the different types were identified. The convection-allowing models run during the PECAN project were found to be more deficient with location than timing. Threat scores typically averaged around 0.3 for the models, with false alarm ratios and hit rates both averaging around 0.5 to 0.6 for the various models. Initiation occurring within the low-level jet but far from a surface front was the one type that was occasionally missed by all five models examined. Once case for each of the four types was then simulated with four different configurations of a 4 km horizontal grid spacing WRF model. These WRF runs showed similar location errors and problems with initiating convection at a lower altitude than observed as was found from the simulations performed during PECAN. Three of the four PBL schemes behaved similarly, but one, the ACM2, was often an outlier, failing to indicate the convective initiation.

Development of a normal tissue complication probability (NTCP) model for radiation-induced hypothyroidism in nasopharyngeal carcinoma patients.

PubMed

Luo, Ren; Wu, Vincent W C; He, Binghui; Gao, Xiaoying; Xu, Zhenxi; Wang, Dandan; Yang, Zhining; Li, Mei; Lin, Zhixiong

2018-05-18

The objectives of this study were to build a normal tissue complication probability (NTCP) model of radiation-induced hypothyroidism (RHT) for nasopharyngeal carcinoma (NPC) patients and to compare it with other four published NTCP models to evaluate its efficacy. Medical notes of 174 NPC patients after radiotherapy were reviewed. Biochemical hypothyroidism was defined as an elevated level of serum thyroid-stimulating hormone (TSH) value with a normal or decreased level of serum free thyroxine (fT4) after radiotherapy. Logistic regression with leave-one-out cross-validation was performed to establish the NTCP model. Model performance was evaluated and compared by the area under the receiver operating characteristic curve (AUC) in our NPC cohort. With a median follow-up of 24 months, 39 (22.4%) patients developed biochemical hypothyroidism. Gender, chemotherapy, the percentage thyroid volume receiving more than 50 Gy (V 50 ), and the maximum dose of the pituitary (P max ) were identified as the most predictive factors for RHT. A NTCP model based on these four parameters were developed. The model comparison was made in our NPC cohort and our NTCP model performed better in RHT prediction than the other four models. This study developed a four-variable NTCP model for biochemical hypothyroidism in NPC patients post-radiotherapy. Our NTCP model for RHT presents a high prediction capability. This is a retrospective study without registration.

Testing simulations of intra- and inter-annual variation in the plant production response to elevated CO(2) against measurements from an 11-year FACE experiment on grazed pasture.

PubMed

Li, Frank Yonghong; Newton, Paul C D; Lieffering, Mark

2014-01-01

Ecosystem models play a crucial role in understanding and evaluating the combined impacts of rising atmospheric CO2 concentration and changing climate on terrestrial ecosystems. However, we are not aware of any studies where the capacity of models to simulate intra- and inter-annual variation in responses to elevated CO2 has been tested against long-term experimental data. Here we tested how well the ecosystem model APSIM/AgPasture was able to simulate the results from a free air carbon dioxide enrichment (FACE) experiment on grazed pasture. At this FACE site, during 11 years of CO2 enrichment, a wide range in annual plant production response to CO2 (-6 to +28%) was observed. As well as running the full model, which includes three plant CO2 response functions (plant photosynthesis, nitrogen (N) demand and stomatal conductance), we also tested the influence of these three functions on model predictions. Model/data comparisons showed that: (i) overall the model over-predicted the mean annual plant production response to CO2 (18.5% cf 13.1%) largely because years with small or negative responses to CO2 were not well simulated; (ii) in general seasonal and inter-annual variation in plant production responses to elevated CO2 were well represented by the model; (iii) the observed CO2 enhancement in overall mean legume content was well simulated but year-to-year variation in legume content was poorly captured by the model; (iv) the best fit of the model to the data required all three CO2 response functions to be invoked; (v) using actual legume content and reduced N fixation rate under elevated CO2 in the model provided the best fit to the experimental data. We conclude that in temperate grasslands the N dynamics (particularly the legume content and N fixation activity) play a critical role in pasture production responses to elevated CO2 , and are processes for model improvement. © 2013 John Wiley & Sons Ltd.

Does a decade of elevated [CO2] affect a desert perennial plant community?

PubMed

Newingham, Beth A; Vanier, Cheryl H; Kelly, Lauren J; Charlet, Therese N; Smith, Stanley D

2014-01-01

Understanding the effects of elevated [CO2 ] on plant community structure is crucial to predicting ecosystem responses to global change. Early predictions suggested that productivity in deserts would increase via enhanced water-use efficiency under elevated [CO2], but the response of intact arid plant communities to elevated [CO2 ] is largely unknown. We measured changes in perennial plant community characteristics (cover, species richness and diversity) after 10 yr of elevated [CO2] exposure in an intact Mojave Desert community at the Nevada Desert Free-Air CO2 Enrichment (FACE) Facility. Contrary to expectations, total cover, species richness, and diversity were not affected by elevated [CO2]. Over the course of the experiment, elevated [CO2] had no effect on changes in cover of the evergreen C3 shrub, Larrea tridentata; alleviated decreases in cover of the C4 bunchgrass, Pleuraphis rigida; and slightly reduced the cover of C3 drought-deciduous shrubs. Thus, we generally found no effect of elevated [CO2] on plant communities in this arid ecosystem. Extended drought, slow plant growth rates, and highly episodic germination and recruitment of new individuals explain the lack of strong perennial plant community shifts after a decade of elevated [CO2]. © 2013 The Authors. New Phytologist © 2013 New Phytologist Trust.

Experimental and analytical transonic flutter characteristics of a geared-elevator configuration

NASA Technical Reports Server (NTRS)

Ruhlin, C. L.; Doggett, R. V., Jr.; Gregory, R. A.

1980-01-01

The flutter model represented the aft fuselage and empennage of a proposed supersonic transport airplane and had an all movable horizontal tail with a geared elevator. It was tested mounted from a sting in the transonic dynamics tunnel. Symmetric flutter boundaries were determined experimentally at Mach numbers from 0.7 to 1.14 for a geared elevator configuration (gear ratio of 2.8 to 1.0) and an ungeared elevator configuration (gear ratio of 1.0 to 1.0). Gearing the elevator increased the experimental flutter dynamic pressures about 20 percent. Flutter calculations were made for the geared elevator configuration by using two analytical methods based on subsonic lifting surface theory. Both methods analyzed the stabilizer and elevator as a single, deforming surface, but one method also allowed the elevator to be analyzed as hinged from the stabilizer. All analyses predicted lower flutter dynamic pressures than experiment with best agreement (within 12 percent) for the hinged elevator method. Considering the model as mounted from a flexible rather than rigid sting in the analyses, had only a slight effect on the flutter results but was significant in that a sting related vibration mode was identified as a potentially flutter critical mode.

Sumatra-Andaman Megathrust Earthquake Slip: Insights From Mechanical Modeling of ICESat Surface Deformation Measurements

NASA Astrophysics Data System (ADS)

Harding, D. J.; Miuller, J. R.

2005-12-01

Modeling the kinematics of the 2004 Great Sumatra-Andaman earthquake is limited in the northern two-thirds of the rupture zone by a scarcity of near-rupture geodetic deformation measurements. Precisely repeated Ice, Cloud, and Land Elevation Satellite (ICESat) profiles across the Andaman and Nicobar Islands provide a means to more fully document the spatial pattern of surface vertical displacements and thus better constrain geomechanical modeling of the slip distribution. ICESat profiles that total ~45 km in length cross Car Nicobar, Kamorta, and Katchall in the Nicobar chain. Within the Andamans, the coverage includes ~350 km on North, Central, and South Andaman Islands along two NNE and NNW-trending profiles that provide elevations on both the east and west coasts of the island chain. Two profiles totaling ~80 km in length cross South Sentinel Island, and one profile ~10 km long crosses North Sentinel Island. With an average laser footprint spacing of 175 m, the total coverage provides over 2700 georeferenced surface elevations measurements for each operations period. Laser backscatter waveforms recorded for each footprint enable detection of forest canopy top and underlying ground elevations with decimeter vertical precision. Surface elevation change is determined from elevation profiles, acquired before and after the earthquake, that are repeated with a cross-track separation of less than 100 m by precision pointing of the ICESat spacecraft. Apparent elevation changes associated with cross-track offsets are corrected according to local slopes calculated from multiple post-earthquake repeated profiles. The surface deformation measurements recorded by ICESat are generally consistent with the spatial distribution of uplift predicted by a preliminary slip distribution model. To predict co-seismic surface deformation, we apply a slip distribution, derived from the released energy distribution computed by Ishii et al. (2005), as the displacement discontinuity boundary condition on the Sumatra-Andaman subduction interface fault. The direction of slip on the fault surface is derived from the slip directions computed by Tsai et al. (in review) for centroid moment tensor focal mechanisms spatially distributed along the rupture. The slip model will be refined to better correspond to the observed surface deformation as additional results from the ICESat profiles become available.

Effects of high CO2 levels on dynamic photosynthesis: carbon gain, mechanisms, and environmental interactions.

PubMed

Tomimatsu, Hajime; Tang, Yanhong

2016-05-01

Understanding the photosynthetic responses of terrestrial plants to environments with high levels of CO2 is essential to address the ecological effects of elevated atmospheric CO2. Most photosynthetic models used for global carbon issues are based on steady-state photosynthesis, whereby photosynthesis is measured under constant environmental conditions; however, terrestrial plant photosynthesis under natural conditions is highly dynamic, and photosynthetic rates change in response to rapid changes in environmental factors. To predict future contributions of photosynthesis to the global carbon cycle, it is necessary to understand the dynamic nature of photosynthesis in relation to high CO2 levels. In this review, we summarize the current body of knowledge on the photosynthetic response to changes in light intensity under experimentally elevated CO2 conditions. We found that short-term exposure to high CO2 enhances photosynthetic rate, reduces photosynthetic induction time, and reduces post-illumination CO2 burst, resulting in increased leaf carbon gain during dynamic photosynthesis. However, long-term exposure to high CO2 during plant growth has varying effects on dynamic photosynthesis. High levels of CO2 increase the carbon gain in photosynthetic induction in some species, but have no significant effects in other species. Some studies have shown that high CO2 levels reduce the biochemical limitation on RuBP regeneration and Rubisco activation during photosynthetic induction, whereas the effects of high levels of CO2 on stomatal conductance differ among species. Few studies have examined the influence of environmental factors on effects of high levels of CO2 on dynamic photosynthesis. We identified several knowledge gaps that should be addressed to aid future predictions of photosynthesis in high-CO2 environments.

Performance of a coupled lagged ensemble weather and river runoff prediction model system for the Alpine Ammer River catchment

NASA Astrophysics Data System (ADS)

Smiatek, G.; Kunstmann, H.; Werhahn, J.

2012-04-01

The Ammer River catchment located in the Bavarian Ammergau Alps and alpine forelands, Germany, represents with elevations reaching 2185 m and annual mean precipitation between1100 and 2000 mm a very demanding test ground for a river runoff prediction system. Large flooding events in 1999 and 2005 motivated the development of a physically based prediction tool in this area. Such a tool is the coupled high resolution numerical weather and river runoff forecasting system AM-POE that is being studied in several configurations in various experiments starting from the year 2005. Corner stones of the coupled system are the hydrological water balance model WaSiM-ETH run at 100 m grid resolution, the numerical weather prediction model (NWP) MM5 driven at 3.5 km grid cell resolution and the Perl Object Environment (POE) framework. POE implements the input data download from various sources, the input data provision via SOAP based WEB services as well as the runs of the hydrology model both with observed and with NWP predicted meteorology input. The one way coupled system utilizes a lagged ensemble prediction system (EPS) taking into account combination of recent and previous NWP forecasts. Results obtained in the years 2005-2011 reveal that river runoff simulations depict high correlation with observed runoff when driven with monitored observations in hindcast experiments. The ability to runoff forecasts is depending on lead times in the lagged ensemble prediction and shows still limitations resulting from errors in timing and total amount of the predicted precipitation in the complex mountainous area. The presentation describes the system implementation, and demonstrates the application of the POE framework in networking, distributed computing and in the setup of various experiments as well as long term results of the system application in the years 2005 - 2011.

Imbalance of gut microbiome and intestinal epithelial barrier dysfunction in patients with high blood pressure

PubMed Central

Kim, Seungbum; Goel, Ruby; Kumar, Ashok; Qi, Yanfei; Lobaton, Gil; Hosaka, Koji; Mohammed, Mohammed; Handberg, Eileen M.; Richards, Elaine M.; Pepine, Carl J.; Raizada, Mohan K.

2018-01-01

Recent evidence indicates a link between gut pathology and microbiome with hypertension (HTN) in animal models. However, whether this association exists in humans is unknown. Thus, our objectives in the present study were to test the hypotheses that high blood pressure (BP) patients have distinct gut microbiomes and that gut–epithelial barrier function markers and microbiome composition could predict systolic BP (SBP). Fecal samples, analyzed by shotgun metagenomics, displayed taxonomic and functional changes, including altered butyrate production between patients with high BP and reference subjects. Significant increases in plasma of intestinal fatty acid binding protein (I-FABP), lipopolysaccharide (LPS), and augmented gut-targetting proinflammatory T helper 17 (Th17) cells in high BP patients demonstrated increased intestinal inflammation and permeability. Zonulin, a gut epithelial tight junction protein regulator, was markedly elevated, further supporting gut barrier dysfunction in high BP. Zonulin strongly correlated with SBP (R2 = 0.5301, P<0.0001). Two models predicting SBP were built using stepwise linear regression analysis of microbiome data and circulating markers of gut health, and validated in a separate cohort by prediction of SBP from zonulin in plasma (R2 = 0.4608, P<0.0001). The mouse model of HTN, chronic angiotensin II (Ang II) infusion, was used to confirm the effects of butyrate and gut barrier function on the cardiovascular system and BP. These results support our conclusion that intestinal barrier dysfunction and microbiome function are linked to HTN in humans. They suggest that manipulation of gut microbiome and its barrier functions could be the new therapeutic and diagnostic avenues for HTN. PMID:29507058

Predictive habitat models derived from nest-box occupancy for the endangered Carolina northern flying squirrel in the southern Appalachians

USGS Publications Warehouse

Ford, W. Mark; Evans, A.M.; Odom, Richard H.; Rodrigue, Jane L.; Kelly, C.A.; Abaid, Nicole; Diggins, Corinne A.; Newcomb, Doug

2016-01-01

In the southern Appalachians, artificial nest-boxes are used to survey for the endangered Carolina northern flying squirrel (CNFS; Glaucomys sabrinus coloratus), a disjunct subspecies associated with high elevation (>1385 m) forests. Using environmental parameters diagnostic of squirrel habitat, we created 35 a priori occupancy models in the program PRESENCE for boxes surveyed in western North Carolina, 1996-2011. Our best approximating model showed CNFS denning associated with sheltered landforms and montane conifers, primarily red spruce Picea rubens. As sheltering decreased, decreasing distance to conifers was important. Area with a high probability (>0.5) of occupancy was distributed over 18662 ha of habitat, mostly across 10 mountain ranges. Because nest-box surveys underrepresented areas >1750 m and CNFS forage in conifers, we combined areas of high occupancy with conifer GIS coverages to create an additional distribution model of likely habitat. Regionally, above 1385 m, we determined that 31795 ha could be occupied by CNFS. Known occupied patches ranged from

Integrating Windblown Dust Forecasts with Public Safety and Health Systems

NASA Astrophysics Data System (ADS)

Sprigg, W. A.

2014-12-01

Experiments in real-time prediction of desert dust emissions and downstream plume concentrations (~ 3.5 km near-surface spatial resolution) succeed to the point of challenging public safety and public health services to beta test a dust storm warning and advisory system in lowering risks of highway and airline accidents and illnesses such as asthma and valley fever. Key beta test components are: high-resolution models of dust emission, entrainment and diffusion, integrated with synoptic weather observations and forecasts; satellite-based detection and monitoring of soil properties on the ground and elevated above; high space and time resolution for health surveillance and transportation advisories.

Using LiDAR datasets to improve HSPF water quality modeling in the Red River of the North Basin

NASA Astrophysics Data System (ADS)

Burke, M. P.; Foreman, C. S.

2013-12-01

The Red River of the North Basin (RRB), located in the lakebed of ancient glacial Lake Agassiz, comprises one of the flattest landscapes in North America. The topography of the basin, coupled with the Red River's direction of flow from south to north results in a system that is highly susceptible to flooding. The magnitude and frequency of flood events in the RRB has prompted several multijurisdictional projects and mitigation efforts. In response to the devastating 1997 flood, an International Joint Commission sponsored task force established the need for accurate elevation data to help improve flood forecasting and better understand risks. This led to the International Water Institute's Red River Basin Mapping Initiative, and the acquisition LiDAR Data for the entire US portion of the RRB. The resulting 1 meter bare earth digital elevation models have been used to improve hydraulic and hydrologic modeling within the RRB, with focus on flood prediction and mitigation. More recently, these LiDAR datasets have been incorporated into Hydrological Simulation Program-FORTRAN (HSPF) model applications to improve water quality predictions in the MN portion of the RRB. RESPEC is currently building HSPF model applications for five of MN's 8-digit HUC watersheds draining to the Red River, including: the Red Lake River, Clearwater River, Sandhill River, Two Rivers, and Tamarac River watersheds. This work is being conducted for the Minnesota Pollution Control Agency (MPCA) as part of MN's statewide watershed approach to restoring and protecting water. The HSPF model applications simulate hydrology (discharge, stage), as well as a number of water quality constituents (sediment, temperature, organic and inorganic nitrogen, total ammonia, organic and inorganic phosphorus, dissolved oxygen and biochemical oxygen demand, and algae) continuously for the period 1995-2009 and are formulated to provide predictions at points of interest within the watersheds, such as observation gages, management boundaries, compliance points, and impaired water body endpoints. Incorporation of the LiDAR datasets has been critical to representing the topographic characteristics that impact hydrologic and water quality processes in the extremely flat, heavily drained sub-basins of the RRB. Beyond providing more detailed elevation and slope measurements, the high resolution LiDAR datasets have helped to identify drainage alterations due to agricultural practices, as well as improve representation of channel geometry. Additionally, when available, LiDAR based hydraulic models completed as part of the RRB flood mitigation efforts, are incorporated to further improve flow routing. The MPCA will ultimately use these HSPF models to aid in Total Maximum Daily Load (TMDL) development, permit development/compliance, analysis of Best Management Practice (BMP) implementation scenarios, and other watershed planning and management objectives. LiDAR datasets are an essential component of the water quality models build for the watersheds within the RRB and would greatly benefit water quality modeling efforts in similarly characterized areas.

Predicting the safety and efficacy of buffer therapy to raise tumour pHe: an integrative modelling study.

PubMed

Martin, N K; Robey, I F; Gaffney, E A; Gillies, R J; Gatenby, R A; Maini, P K

2012-03-27

Clinical positron emission tomography imaging has demonstrated the vast majority of human cancers exhibit significantly increased glucose metabolism when compared with adjacent normal tissue, resulting in an acidic tumour microenvironment. Recent studies demonstrated reducing this acidity through systemic buffers significantly inhibits development and growth of metastases in mouse xenografts. We apply and extend a previously developed mathematical model of blood and tumour buffering to examine the impact of oral administration of bicarbonate buffer in mice, and the potential impact in humans. We recapitulate the experimentally observed tumour pHe effect of buffer therapy, testing a model prediction in vivo in mice. We parameterise the model to humans to determine the translational safety and efficacy, and predict patient subgroups who could have enhanced treatment response, and the most promising combination or alternative buffer therapies. The model predicts a previously unseen potentially dangerous elevation in blood pHe resulting from bicarbonate therapy in mice, which is confirmed by our in vivo experiments. Simulations predict limited efficacy of bicarbonate, especially in humans with more aggressive cancers. We predict buffer therapy would be most effectual: in elderly patients or individuals with renal impairments; in combination with proton production inhibitors (such as dichloroacetate), renal glomular filtration rate inhibitors (such as non-steroidal anti-inflammatory drugs and angiotensin-converting enzyme inhibitors), or with an alternative buffer reagent possessing an optimal pK of 7.1-7.2. Our mathematical model confirms bicarbonate acts as an effective agent to raise tumour pHe, but potentially induces metabolic alkalosis at the high doses necessary for tumour pHe normalisation. We predict use in elderly patients or in combination with proton production inhibitors or buffers with a pK of 7.1-7.2 is most promising.

Improving Frozen Precipitation Density Estimation in Land Surface Modeling

NASA Astrophysics Data System (ADS)

Sparrow, K.; Fall, G. M.

2017-12-01

The Office of Water Prediction (OWP) produces high-value water supply and flood risk planning information through the use of operational land surface modeling. Improvements in diagnosing frozen precipitation density will benefit the NWS's meteorological and hydrological services by refining estimates of a significant and vital input into land surface models. A current common practice for handling the density of snow accumulation in a land surface model is to use a standard 10:1 snow-to-liquid-equivalent ratio (SLR). Our research findings suggest the possibility of a more skillful approach for assessing the spatial variability of precipitation density. We developed a 30-year SLR climatology for the coterminous US from version 3.22 of the Daily Global Historical Climatology Network - Daily (GHCN-D) dataset. Our methods followed the approach described by Baxter (2005) to estimate mean climatological SLR values at GHCN-D sites in the US, Canada, and Mexico for the years 1986-2015. In addition to the Baxter criteria, the following refinements were made: tests were performed to eliminate SLR outliers and frequent reports of SLR = 10, a linear SLR vs. elevation trend was fitted to station SLR mean values to remove the elevation trend from the data, and detrended SLR residuals were interpolated using ordinary kriging with a spherical semivariogram model. The elevation values of each station were based on the GMTED 2010 digital elevation model and the elevation trend in the data was established via linear least squares approximation. The ordinary kriging procedure was used to interpolate the data into gridded climatological SLR estimates for each calendar month at a 0.125 degree resolution. To assess the skill of this climatology, we compared estimates from our SLR climatology with observations from the GHCN-D dataset to consider the potential use of this climatology as a first guess of frozen precipitation density in an operational land surface model. The difference in model derived estimates and GHCN-D observations were assessed using time-series graphs of 2016-2017 winter season SLR observations and climatological estimates, as well as calculating RMSE and variance between estimated and observed values.

Unusually high soil nitrogen oxide emissions influence air quality in a high-temperature agricultural region

PubMed Central

Oikawa, P. Y.; Ge, C.; Wang, J.; Eberwein, J. R.; Liang, L. L.; Allsman, L. A.; Grantz, D. A.; Jenerette, G. D.

2015-01-01

Fertilized soils have large potential for production of soil nitrogen oxide (NOx=NO+NO2), however these emissions are difficult to predict in high-temperature environments. Understanding these emissions may improve air quality modelling as NOx contributes to formation of tropospheric ozone (O3), a powerful air pollutant. Here we identify the environmental and management factors that regulate soil NOx emissions in a high-temperature agricultural region of California. We also investigate whether soil NOx emissions are capable of influencing regional air quality. We report some of the highest soil NOx emissions ever observed. Emissions vary nonlinearly with fertilization, temperature and soil moisture. We find that a regional air chemistry model often underestimates soil NOx emissions and NOx at the surface and in the troposphere. Adjusting the model to match NOx observations leads to elevated tropospheric O3. Our results suggest management can greatly reduce soil NOx emissions, thereby improving air quality. PMID:26556236

Elevated carbon dioxide is predicted to promote coexistence among competing species in a trait-based model

DOE PAGES

Ali, Ashehad A.; Medlyn, Belinda E.; Aubier, Thomas G.; ...

2015-10-06

Differential species responses to atmospheric CO 2 concentration (C a) could lead to quantitative changes in competition among species and community composition, with flow-on effects for ecosystem function. However, there has been little theoretical analysis of how elevated C a (eC a) will affect plant competition, or how composition of plant communities might change. Such theoretical analysis is needed for developing testable hypotheses to frame experimental research. Here, we investigated theoretically how plant competition might change under eC a by implementing two alternative competition theories, resource use theory and resource capture theory, in a plant carbon and nitrogen cycling model.more » The model makes several novel predictions for the impact of eC a on plant community composition. Using resource use theory, the model predicts that eC a is unlikely to change species dominance in competition, but is likely to increase coexistence among species. Using resource capture theory, the model predicts that eC a may increase community evenness. Collectively, both theories suggest that eC a will favor coexistence and hence that species diversity should increase with eC a. Our theoretical analysis leads to a novel hypothesis for the impact of eC a on plant community composition. In this study, the hypothesis has potential to help guide the design and interpretation of eC a experiments.« less

Space-time extreme wind waves: Observation and analysis of shapes and heights

NASA Astrophysics Data System (ADS)

Benetazzo, Alvise; Barbariol, Francesco; Bergamasco, Filippo; Carniel, Sandro; Sclavo, Mauro

2016-04-01

We analyze here the temporal shape and the maximal height of extreme wind waves, which were obtained from an observational space-time sample of sea surface elevations during a mature and short-crested sea state (Benetazzo et al., 2015). Space-time wave data are processed to detect the largest waves of specific 3-D wave groups close to the apex of their development. First, maximal elevations of the groups are discussed within the framework of space-time (ST) extreme statistical models of random wave fields (Adler and Taylor, 2007; Benetazzo et al., 2015; Fedele, 2012). Results of ST models are also compared with observations and predictions of maxima based on time series of sea surface elevations. Second, the time profile of the extreme waves around the maximal crest height is analyzed and compared with the expectations of the linear (Boccotti, 1983) and second-order nonlinear extension (Arena, 2005) of the Quasi-Determinism (QD) theory. Main purpose is to verify to what extent, using the QD model results, one can estimate the shape and the crest-to-trough height of large waves in a random ST wave field. From the results presented, it emerges that, apart from the displacements around the crest apex, sea surface elevations of very high waves are greatly dispersed around a mean profile. Yet the QD model furnishes, on average, a fair prediction of the wave height of the maximal waves, especially when nonlinearities are taken into account. Moreover, the combination of ST and QD model predictions allow establishing, for a given sea condition, a framework for the representation of waves with very large crest heights. The results have also the potential to be implemented in a phase-averaged numerical wave model (see abstract EGU2016-14008 and Barbariol et al., 2015). - Adler, R.J., Taylor, J.E., 2007. Random fields and geometry. Springer, New York (USA), 448 pp. - Arena, F., 2005. On non-linear very large sea wave groups. Ocean Eng. 32, 1311-1331. - Barbariol, F., Alves, J.H.G.., Benetazzo, A., Bergamasco, F., Bertotti, L., Carniel, S., Cavaleri, L., Chao, Y.Y., Chawla, A., Ricchi, A., Sclavo, M., Tolman, H., 2015. Space-Time Wave Extremes in WAVEWATCH III: Implementation and Validation for the Adriatic Sea Case Study, in: 14th International Workshop on Wave Hindcasting and Forecasting. November, 8-13, Key West, Florida (USA). - Benetazzo, A., Barbariol, F., Bergamasco, F., Torsello, A., Carniel, S., Sclavo, M., 2015. Observation of extreme sea waves in a space-time ensemble. J. Phys. Oceanogr. 45, 2261-2275. - Boccotti, P., 1983. Some new results on statistical properties of wind waves. Appl. Ocean Res. 5, 134-140. - Fedele, F., 2012. Space-Time Extremes in Short-Crested Storm Seas. J. Phys. Oceanogr. 42, 1601-1615.

Empirical evaluation of spatial and non-spatial European-scale multimedia fate models: results and implications for chemical risk assessment.

PubMed

Armitage, James M; Cousins, Ian T; Hauck, Mara; Harbers, Jasper V; Huijbregts, Mark A J

2007-06-01

Multimedia environmental fate models are commonly-applied tools for assessing the fate and distribution of contaminants in the environment. Owing to the large number of chemicals in use and the paucity of monitoring data, such models are often adopted as part of decision-support systems for chemical risk assessment. The purpose of this study was to evaluate the performance of three multimedia environmental fate models (spatially- and non-spatially-explicit) at a European scale. The assessment was conducted for four polycyclic aromatic hydrocarbons (PAHs) and hexachlorobenzene (HCB) and compared predicted and median observed concentrations using monitoring data collected for air, water, sediments and soils. Model performance in the air compartment was reasonable for all models included in the evaluation exercise as predicted concentrations were typically within a factor of 3 of the median observed concentrations. Furthermore, there was good correspondence between predictions and observations in regions that had elevated median observed concentrations for both spatially-explicit models. On the other hand, all three models consistently underestimated median observed concentrations in sediment and soil by 1-3 orders of magnitude. Although regions with elevated median observed concentrations in these environmental media were broadly identified by the spatially-explicit models, the magnitude of the discrepancy between predicted and median observed concentrations is of concern in the context of chemical risk assessment. These results were discussed in terms of factors influencing model performance such as the steady-state assumption, inaccuracies in emission estimates and the representativeness of monitoring data.

Life prediction methodology for thermal-mechanical fatigue and elevated temperature creep design

NASA Astrophysics Data System (ADS)

Annigeri, Ravindra

Nickel-based superalloys are used for hot section components of gas turbine engines. Life prediction techniques are necessary to assess service damage in superalloy components resulting from thermal-mechanical fatigue (TMF) and elevated temperature creep. A new TMF life model based on continuum damage mechanics has been developed and applied to IN 738 LC substrate material with and without coating. The model also characterizes TMF failure in bulk NiCoCrAlY overlay and NiAl aluminide coatings. The inputs to the TMF life model are mechanical strain range, hold time, peak cycle temperatures and maximum stress measured from the stabilized or mid-life hysteresis loops. A viscoplastic model is used to predict the stress-strain hysteresis loops. A flow rule used in the viscoplastic model characterizes the inelastic strain rate as a function of the applied stress and a set of three internal stress variables known as back stress, drag stress and limit stress. Test results show that the viscoplastic model can reasonably predict time-dependent stress-strain response of the coated material and stress relaxation during hold times. In addition to the TMF life prediction methodology, a model has been developed to characterize the uniaxial and multiaxial creep behavior. An effective stress defined as the applied stress minus the back stress is used to characterize the creep recovery and primary creep behavior. The back stress has terms representing strain hardening, dynamic recovery and thermal recovery. Whenever the back stress is greater than the applied stress, the model predicts a negative creep rate observed during multiple stress and multiple temperature cyclic tests. The model also predicted the rupture time and the remaining life that are important for life assessment. The model has been applied to IN 738 LC, Mar-M247, bulk NiCoCrAlY overlay coating and 316 austenitic stainless steel. The proposed model predicts creep response with a reasonable accuracy for wide range of loading cases such as uniaxial tension, tension-torsion and tension-internal pressure loading.

Role of the membrane cortex in neutrophil deformation in small pipets.

PubMed Central

Zhelev, D V; Needham, D; Hochmuth, R M

1994-01-01

The simplest model for a neutrophil in its "passive" state views the cell as consisting of a liquid-like cytoplasmic region surrounded by a membrane. The cell surface is in a state of isotropic contraction, which causes the cell to assume a spherical shape. This contraction is characterized by the cortical tension. The cortical tension shows a weak area dilation dependence, and it determines the elastic properties of the cell for small curvature deformations. At high curvature deformations in small pipets (with internal radii less than 1 micron), the measured critical suction pressure for cell flow into the pipet is larger than its estimate from the law of Laplace. A model is proposed where the region consisting of the cytoplasm membrane and the underlying cortex (having a finite thickness) is introduced at the cell surface. The mechanical properties of this region are characterized by the apparent cortical tension (defined as a free contraction energy per unit area) and the apparent bending modulus (introduced as a bending free energy per unit area) of its middle plane. The model predicts that for small curvature deformations (in pipets having radii larger than 1.2 microns) the role of the cortical thickness and the resistance for bending of the membrane-cortex complex is negligible. For high curvature deformations, they lead to elevated suction pressures above the values predicted from the law of Laplace. The existence of elevated suction pressures for pipets with radii from 1 micron down to 0.24 micron is found experimentally. The measured excess suction pressures cannot be explained only by the modified law of Laplace (for a cortex with finite thickness and negligible bending resistance), because it predicts unacceptable high cortical thicknesses (from 0.3 to 0.7 micron). It is concluded that the membrane-cortex complex has an apparent bending modulus from 1 x 10(-18) to 2 x 10(-18) J for a cortex with a thickness from 0.1 micron down to values much smaller than the radius of the smallest pipet (0.24 micron) used in this study. Images FIGURE 1 PMID:7948682

Evaluating coastal landscape response to sea-level rise in the northeastern United States: approach and methods

USGS Publications Warehouse

Lentz, Erika E.; Stippa, Sawyer R.; Thieler, E. Robert; Plant, Nathaniel G.; Gesch, Dean B.; Horton, Radley M.

2014-02-13

The U.S. Geological Survey is examining effects of future sea-level rise on the coastal landscape from Maine to Virginia by producing spatially explicit, probabilistic predictions using sea-level projections, vertical land movement rates (due to isostacy), elevation data, and land-cover data. Sea-level-rise scenarios used as model inputs are generated by using multiple sources of information, including Coupled Model Intercomparison Project Phase 5 models following representative concentration pathways 4.5 and 8.5 in the Intergovernmental Panel on Climate Change Fifth Assessment Report. A Bayesian network is used to develop a predictive coastal response model that integrates the sea-level, elevation, and land-cover data with assigned probabilities that account for interactions with coastal geomorphology as well as the corresponding ecological and societal systems it supports. The effects of sea-level rise are presented as (1) level of landscape submergence and (2) coastal response type characterized as either static (that is, inundation) or dynamic (that is, landform or landscape change). Results are produced at a spatial scale of 30 meters for four decades (the 2020s, 2030s, 2050s, and 2080s). The probabilistic predictions can be applied to landscape management decisions based on sea-level-rise effects as well as on assessments of the prediction uncertainty and need for improved data or fundamental understanding. This report describes the methods used to produce predictions, including information on input datasets; the modeling approach; model outputs; data-quality-control procedures; and information on how to access the data and metadata online.

The Economics of Root Distributions of Terrestrial Biomes in Response to Elevated CO2

NASA Astrophysics Data System (ADS)

Lu, M.; Hedin, L. O. O.

2017-12-01

Belowground root distributions of terrestrial biomes are central to understanding soil biogeochemical processes and land carbon sink. Yet models are thus far not able to predict root distributions across plant functional groups and major biomes, limiting our ability to predict the response of land systems to elevated CO2 concentration. Of particular concern is the apparent lack of stimulation of the aboveground carbon sink despite 30% increase of atmospheric CO2 over the past half-century, and despite the clear acceleration of the land carbon sink over the same period. This apparent discrepancy in land ecosystem response has led to the proposition that changes in belowground root dynamics might be responsible for the overlooked land sink. We here present a new modeling approach for predicting the response of root biomass and soil carbon storage to increased CO2. Our approach considers the first-principle mechanisms and tradeoffs by which plants and plant roots invest carbon to gain belowground resources, in collaboration with distinct root symbioses. We allow plants to locally compete for nutrients, with the ability to allocate biomass at different depths in the soil profile. We parameterized our model using an unprecedented global dataset of root traits, and validated our biome-level predictions with a recently updated global root biomass database. Our results support the idea that plants "dig deeper" when exposed to increased CO2, and we offer an economic-based mechanism for predicting the plant root response across soil conditions, plant functional groups and major biomes. Our model also recreates the observed responses across a range of free-air CO2 enrichment experiments, including a distinct response between plants associated with ectomycorrhizal and arbuscular mycorrhizal fungi. Most broadly, our findings suggest that roots may be increasingly important in the land carbon sink, and call for a greater effort to quantify belowground responses to elevated atmospheric CO2.

Evaluating Coastal Landscape Response to Sea-Level Rise in the Northeastern United States - Approach and Methods

NASA Technical Reports Server (NTRS)

Lentz, Erika E.; Stippa, Sawyer R.; Thieler, E. Robert; Plant, Nathaniel G.; Gesch, Dean B.; Horton, Radley M.

2015-01-01

The U.S. Geological Survey is examining effects of future sea-level rise on the coastal landscape from Maine to Virginia by producing spatially explicit, probabilistic predictions using sea-level projections, vertical land movement rates (due to isostacy), elevation data, and land-cover data. Sea-level-rise scenarios used as model inputs are generated by using multiple sources of information, including Coupled Model Intercomparison Project Phase 5 models following representative concentration pathways 4.5 and 8.5 in the Intergovernmental Panel on Climate Change Fifth Assessment Report. A Bayesian network is used to develop a predictive coastal response model that integrates the sea-level, elevation, and land-cover data with assigned probabilities that account for interactions with coastal geomorphology as well as the corresponding ecological and societal systems it supports. The effects of sea-level rise are presented as (1) level of landscape submergence and (2) coastal response type characterized as either static (that is, inundation) or dynamic (that is, landform or landscape change). Results are produced at a spatial scale of 30 meters for four decades (the 2020s, 2030s, 2050s, and 2080s). The probabilistic predictions can be applied to landscape management decisions based on sea-level-rise effects as well as on assessments of the prediction uncertainty and need for improved data or fundamental understanding. This report describes the methods used to produce predictions, including information on input datasets; the modeling approach; model outputs; data-quality-control procedures; and information on how to access the data and metadata online.

Determination of mean gravity anomalies in the Taiwan Island

NASA Technical Reports Server (NTRS)

Chang, Ruey-Gang

1989-01-01

The fitting and proper regression coefficients were made of one hundred seventeen 10 x 10' blocks with observed gravity data and corresponding elevation in the Taiwan Island. To compare five different predicted models, and the proper one for the mean gravity anomalies were determined. The predicted gravity anomalies of the non-observed gravity blocks were decided when the coefficients obtained through the model with the weighted mean method. It was suggested that the mean gravity anomalies of 10 x 10' blocks should be made when comprehensive the observed and predicted data.

Long-Term Mortality Consequences of Childhood Family Context in Liaoning, China, 1749-1909

PubMed Central

Campbell, Cameron Dougall; Lee, James Z

2009-01-01

We examine the effects on adult and old age mortality of childhood living arrangements and other aspects of family context in early life. We focus on features of family context that have already been shown to be associated with infant or child mortality in historical and developing country populations. We apply discrete-time event-history analysis to longitudinal, individual-level household register data for a rural population in northeast China from the eighteenth and nineteenth centuries. Loss of a mother in childhood, a short preceding birth interval, and high maternal age were all associated with elevated mortality risks later in life. Such effects persist in a model with fixed effects that account for unobserved characteristics of the community and household. An important implication of these results is that in high mortality populations, features of early life family context that are associated with elevated infant and child mortality may also predict adverse mortality outcomes in adulthood. PMID:19278765

Species richness and patterns of invasion in plants, birds, and fishes in the United States

USGS Publications Warehouse

Stohlgren, Thomas J.; Barnett, David; Flather, Curtis; Fuller, Pamela L.; Peterjohn, Bruce G.; Kartesz, John; Master, Lawrence L.

2006-01-01

We quantified broad-scale patterns of species richness and species density (mean # species/km2) for native and non-indigenous plants, birds, and fishes in the continental USA and Hawaii. We hypothesized that the species density of native and non-indigenous taxa would generally decrease in northern latitudes and higher elevations following declines in potential evapotranspiration, mean temperature, and precipitation. County data on plants (n = 3004 counties) and birds (n=3074 counties), and drainage (6 HUC) data on fishes (n = 328 drainages) showed that the densities of native and non-indigenous species were strongly positively correlated for plant species (r = 0.86, P < 0.0001), bird species (r = 0.93, P<0.0001), and fish species (r = 0.41, P<0.0001). Multiple regression models showed that the densities of native plant and bird species could be strongly predicted (adj. R2 = 0.66 in both models) at county levels, but fish species densities were less predictable at drainage levels (adj. R2 = 0.31,P<0.0001). Similarly, non-indigenous plant and bird species densities were strongly predictable (adj. R2 = 0.84 and 0.91 respectively), but non-indigenous fish species density was less predictable (adj. R2 = 0.38). County level hotspots of native and non-indigenous plants, birds, and fishes were located in low elevation areas close to the coast with high precipitation and productivity (vegetation carbon). We show that (1) native species richness can be moderately well predicted with abiotic factors; (2) human populations have tended to settle in areas rich in native species; and (3) the richness and density of non-indigenous plant, bird, and fish species can be accurately predicted from biotic and abiotic factors largely because they are positively correlated to native species densities. We conclude that while humans facilitate the initial establishment, invasions of non-indigenous species, the spread and subsequent distributions of non-indigenous species may be controlled largely by environmental factors.

Injection, transport, and deposition of tephra during event 5 at Redoubt Volcano, 23 March, 2009

USGS Publications Warehouse

Mastin, Larry G.; Schwaiger, Hans F.; Schneider, David; Wallace, Kristi; Schaefer, Janet; Denlinger, Roger P.

2013-01-01

Among the events of the 2009 eruption at Redoubt Volcano, Alaska, event 5 was the best documented by radar, satellite imagery, and deposit mapping. We use the new Eulerian tephra transport model Ash3d to simulate transport and deposition of event 5 tephra at distances up to 350 km. The eruption, which started at about 1230 UTC on 23 March, 2009, sent a plume from the vent elevation (estimated at 2.3 ± 0.1 km above sea level or a.s.l.) to about 16 ± 2 km above sea level in 5 min. The plume was a few kilometers higher than would be expected for the estimated average mass eruption rate and atmospheric conditions, possibly due to release of most of the eruptive mass in the first half of the 20-minute event. The eruption injected tephra into a wind field of high shear, with weak easterly winds below ~ 3 km elevation, strong southerly winds at 6–10 km and weak westerlies above ~ 16 km. Model simulations in this wind field predicted development of a northward-migrating inverted “v”-shaped cloud with a southwest-trending arm at a few kilometers elevation, which was not visible in IR satellite images due to cloud cover, and a southeast-trending arm at > 10 km elevation that was clearly visible. Simulations also predicted a deposit distribution that strongly depended on plume height: a plume height below 15 km predicted ash deposits that were located west of those mapped, whereas good agreement was reached with a modeled plume height of 15–18 km. Field sampling of the deposit found it to contain abundant tephra aggregates, which accelerated the removal of tephra from the atmosphere. We were able to reasonably approximate the effect of aggregation on the deposit mass distribution by two methods: (1) adjusting the grain-size distribution, taking the erupted mass < = 0.063 mm in diameter and distributing it evenly into bins of coarser size; and (2) moving 80–90% of the mass < = 0.063 mm into a single particle bin ranging in size from 0.25 to 1 mm. These methods produced an area inside the 100 g m− 2 isomass lines that was within a few tens of percent of mapped area; however they under-predicted deposit mass at very proximal (< 50 km) and very distal (> 250 km) locations. Modeled grain-size distributions at sample locations are also generally coarser than observed. The mismatch may result from a combination of limitations in field sampling, approximations inherent in the model, errors in the numerical wind field, and aggregation of particles larger than 0.063 mm.

Groundwater–surface water mixing shifts ecological assembly processes and stimulates organic carbon turnover

DOE PAGES

Stegen, James C.; Fredrickson, James K.; Wilkins, Michael J.; ...

2016-04-07

Environmental transition zones are associated with geochemical gradients that overcome energy limitations to microbial metabolism, resulting in biogeochemical hot spots and moments. Riverine systems where groundwater mixes with surface water (the hyporheic zone) are spatially complex and temporally dynamic, making development of predictive models challenging. Spatial and temporal variations in hyporheic zone microbial communities are a key, but understudied, component of riverine biogeochemical function. To investigate the coupling among groundwater-surface water mixing, microbial communities, and biogeochemistry we applied ecological theory, aqueous biogeochemistry, DNA sequencing, and ultra-high resolution organic carbon profiling to field samples collected across times and locations representing amore » broad range of mixing conditions. Mixing of groundwater and surface water resulted in a shift from transport-driven stochastic dynamics to a deterministic microbial structure associated with elevated biogeochemical rates. While the dynamics of the hyporheic make predictive modeling a challenge, we provide new knowledge that can improve the tractability of such models.« less

High temporal resolution modeling of the impact of rain, tides, and sea level rise on water table flooding in the Arch Creek basin, Miami-Dade County Florida USA.

PubMed

Sukop, Michael C; Rogers, Martina; Guannel, Greg; Infanti, Johnna M; Hagemann, Katherine

2018-03-01

Modeling of groundwater levels in a portion of the low-lying coastal Arch Creek basin in northern Miami-Dade County in Southeast Florida USA, which is subject to repetitive flooding, reveals that rain-induced short-term water table rises can be viewed as a primary driver of flooding events under current conditions. Areas below 0.9m North American Vertical Datum (NAVD) elevation are particularly vulnerable and areas below 1.5m NAVD are vulnerable to exceptionally large rainfall events. Long-term water table rise is evident in the groundwater data, and the rate appears to be consistent with local rates of sea level rise. Linear extrapolation of long-term observed groundwater levels to 2060 suggest roughly a doubling of the number of days when groundwater levels exceed 0.9m NAVD and a threefold increase in the number of days when levels exceed 1.5m NAVD. Projected sea level rise of 0.61m by 2060 together with increased rainfall lead to a model prediction of frequent groundwater-related flooding in areas<0.9m NAVD. However, current simulations do not consider the range of rainfall events that have led to water table elevations>1.5m NAVD and widespread flooding of the area in the past. Tidal fluctuations in the water table are predicted to be more pronounced within 600m of a tidally influenced water control structure that is hydrodynamically connected to Biscayne Bay. The inland influence of tidal fluctuations appears to increase with increased sea level, but the principal driver of high groundwater levels under the 2060 scenario conditions remains groundwater recharge due to rainfall events. Copyright © 2017 Elsevier B.V. All rights reserved.

Predicting landslide vegetation in patches on landscape gradients in Puerto Rico

USGS Publications Warehouse

Myster, R.W.; Thomlinson, J.R.; Larsen, M.C.

1997-01-01

We explored the predictive value of common landscape characteristics for landslide vegetative stages in the Luquillo Experimental Forest of Puerto Rico using four different analyses. Maximum likelihood logistic regression showed that aspect, age, and substrate type could be used to predict vegetative structural stage. In addition it showed that the structural complexity of the vegetation was greater in landslides (1) facing the southeast (away from the dominant wind direction of recent hurricanes), (2) that were older, and (3) that had volcaniclastic rather than dioritic substrate. Multiple regression indicated that both elevation and age could be used to predict the current vegetation, and that vegetation complexity was greater both at lower elevation and in older landslides. Pearson product-moment correlation coefficients showed that (1) the presence of volcaniclastic substrate in landslides was negatively correlated with aspect, age, and elevation, (2) that road association and age were positively correlated, and (3) that slope was negatively correlated with area. Finally, principal components analysis showed that landslides were differentiated on axes defined primarily by age, aspect class, and elevation in the positive direction, and by volcaniclastic substrate in the negative direction. Because several statistical techniques indicated that age, aspect, elevation, and substrate were important in determining vegetation complexity on landslides, we conclude that landslide succession is influenced by variation in these landscape traits. In particular, we would expect to find more successional development on landslides which are older, face away from hurricane winds, are at lower elevation, and are on volcaniclastic substrate. Finally, our results lead into a hierarchical conceptual model of succession on landscapes where the biota respond first to either gradients or disturbance depending on their relative severity, and then to more local biotic mechanisms such as dispersal, predation and competition.

Predicting forest road surface erosion and storm runoff from high-elevation sites

Treesearch

J. M. Grace III

2017-01-01

Forest roads are a concern in management because they represent areas of elevated risks associated with soil erosion and storm runoff connectivity to stream systems. Storm runoff emanating from forest roads and their connectivity to downslope resources can be influenced by a myriad of factors, including storm characteristics, management practices, and the interaction...

Daily hydro- and morphodynamic simulations at Duck, NC, USA using Delft3D

NASA Astrophysics Data System (ADS)

Penko, Allison; Veeramony, Jay; Palmsten, Margaret; Bak, Spicer; Brodie, Katherine; Hesser, Tyler

2017-04-01

Operational forecasting of the coastal nearshore has wide ranging societal and humanitarian benefits, specifically for the prediction of natural hazards due to extreme storm events. However, understanding the model limitations and uncertainty is as equally important as the predictions themselves. By comparing and contrasting the predictions of multiple high-resolution models in a location with near real-time collection of observations, we are able to perform a vigorous analysis of the model results in order to achieve more robust and certain predictions. In collaboration with the U.S. Army Corps of Engineers Field Research Facility (USACE FRF) as part of the Coastal Model Test Bed (CMTB) project, we have set up Delft3D at Duck, NC, USA to run in near-real time, driven by measured wave data at the boundary. The CMTB at the USACE FRF allows for the unique integration of operational wave, circulation, and morphology models with real-time observations. The FRF has an extensive array of in-situ and remotely sensed oceanographic, bathymetric, and meteorological data that is broadcast in near-real time onto a publically accessible server. Wave, current, and bed elevation instruments are permanently installed across the model domain including 2 waverider buoys in 17-m and 26-m water depths at 3.5-km and 17-km offshore, respectively, that record directional wave data every 30-min. Here, we present the workflow and output of the Delft3D hydro- and morphodynamic simulations at Duck, and show the tactical benefits and operational potential of such a system. A nested Delft3D simulation runs a parent grid that extends 12-km in the along-shore and 3.5-km in the cross-shore with 50-m resolution and a maximum depth of approximately 17-m. The bathymetry for the parent grid was obtained from a regional digital elevation model (DEM) generated by the Federal Emergency Management Agency (FEMA). The inner nested grid extends 1.8-km in the along-shore and 1-km in the cross-shore with 5-m resolution and a maximum depth of approximately 8-m. The inner nested grid initial model bathymetry is set to either the predicted bathymetry from the previous day's simulation or a survey, whichever is more recent. Delft3D-WAVE runs in the parent grid and is driven with the real-time spectral wave measurements from the waverider buoy in 17-m depth. The spectral output from Delft3D-WAVE in the parent grid is then used as the boundary condition for the inner nested high-resolution grid, in which the coupled Delft3D wave-flow-morphology model is run. The model results are then compared to the wave, current, and bathymetry observations collected at the FRF as well as other models that are run in the CMTB.

Elevated postvoid residual urine volume predicting recurrence of urinary tract infections in toilet-trained children.

PubMed

Chang, Shang-Jen; Tsai, Li-Ping; Hsu, Chun-Kai; Yang, Stephen S

2015-07-01

The aim of this study was to examine whether toilet-trained children with a history of febrile urinary tract infection (fUTI) and elevated postvoid residual (PVR) urine volume according to a recently published PVR nomogram were at greater risk of UTI recurrence. One month after recovery from febrile UTI, constipation was diagnosed according to the Rome III criteria, and lower urinary tract (LUT) function was evaluated with two sets of uroflowmetry and PVR by ultrasonography. For children aged ≦ 6 and ≧ 7 years, elevated PVR is defined as >20 and >10 ml, respectively. Cox proportion hazards regression was used to evaluate the risk factors for recurrence of UTI. Between 2005 and 2011, 60 children aged 6.5 ± 2.5 years (boy:girl ratio 27:33) were enrolled for analysis. Univariate analysis showed that recurrent febrile UTI was more commonly observed in children with elevated PVR [repetitive elevated PVR: hazard ratio (HR) 5.75, 95% confidence interval (CI) 1.41-23.4; one elevated PVR: HR 4.53, 95% CI 1.01-20.2] and high-grade vesicoureteral reflux (VUR; HR 4.53, 95% CI 1.46-14.07). Multivariate analysis showed that younger age (HR 1.37, 95% CI 1.03-1.82, p < 0.01) and elevated PVR (HR 2.88, 95% CI 1.44-5.73, p = 0.01) were significant, independent risk factors for recurrent febrile UTI--but not gender, presence of high-grade VUR and constipation. Elevated PVR defined by the new PVR nomogram predicted recurrent UTI in children with history of febrile UTI. Care should be taken to manage children with elevated PVR.

Changes in highly sensitive alpha-fetoprotein for the prediction of the outcome in patients with hepatocellular carcinoma after hepatectomy.

PubMed

Toyoda, Hidenori; Kumada, Takashi; Tada, Toshifumi; Ito, Takanori; Maeda, Atsuyuki; Kaneoka, Yuji; Kagebayashi, Chiaki; Satomura, Shinji

2014-06-01

We investigated changes in highly sensitive lens culinaris agglutinin A-reactive fraction of alpha-fetoprotein (hsAFP-L3) measured using a novel method and its predictive ability for prognosis in patients with hepatocellular carcinoma (HCC) who underwent curative hepatectomy, comparing to other HCC tumor markers, that is, AFP, des-gamma-carboxy prothrombin (DCP), and AFP-L3 measured with conventional method (cAFP-L3). AFP, DCP, and AFP-L3 including both cAFP-L3 and hsAFP-L3 were measured before and after curative hepatectomy in 187 patients. The percentage of patients with elevated tumor marker levels pre- and postoperatively was compared, and recurrence-free and overall survival rates were analyzed based on changes in tumor markers. The percentages of patients with elevated AFP, DCP, and cAFP-L3 decreased postoperatively. In contrast, the percentage of patients with elevated hsAFP-L3 did not decrease postoperatively. Both recurrence-free and overall survival rates were significantly lower in patients whose tumor marker levels remained elevated postoperatively than patients without tumor marker elevation postoperatively. Recurrence-free and overall survival rates of patients in whom hsAFP-L3 became elevated postoperatively despite normal preoperative hsAFP-L3 levels were significantly lower than those of patients with normal hsAFP-L3 postoperatively, and were similar to those of patients with persistent elevation. Preoperative elevations of AFP, DCP, and cAFP normalized in many patients postoperatively, but not for hsAFP-L3. The elevation of hsAFP-L3 identifies patients with poor prognosis despite the normalization of AFP and DCP. © 2014 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

Predicting two-year mortality from discharge after acute coronary syndrome: An internationally-based risk score.

PubMed

Pocock, Stuart J; Huo, Yong; Van de Werf, Frans; Newsome, Simon; Chin, Chee Tang; Vega, Ana Maria; Medina, Jesús; Bueno, Héctor

2017-08-01

Long-term risk of post-discharge mortality associated with acute coronary syndrome remains a concern. The development of a model to reliably estimate two-year mortality risk from hospital discharge post-acute coronary syndrome will help guide treatment strategies. EPICOR (long-tErm follow uP of antithrombotic management patterns In acute CORonary syndrome patients, NCT01171404) and EPICOR Asia (EPICOR Asia, NCT01361386) are prospective observational studies of 23,489 patients hospitalized for an acute coronary syndrome event, who survived to discharge and were then followed up for two years. Patients were enrolled from 28 countries across Europe, Latin America and Asia. Risk scoring for two-year all-cause mortality risk was developed using identified predictive variables and forward stepwise Cox regression. Goodness-of-fit and discriminatory power was estimated. Within two years of discharge 5.5% of patients died. We identified 17 independent mortality predictors: age, low ejection fraction, no coronary revascularization/thrombolysis, elevated serum creatinine, poor EQ-5D score, low haemoglobin, previous cardiac or chronic obstructive pulmonary disease, elevated blood glucose, on diuretics or an aldosterone inhibitor at discharge, male sex, low educational level, in-hospital cardiac complications, low body mass index, ST-segment elevation myocardial infarction diagnosis, and Killip class. Geographic variation in mortality risk was seen following adjustment for other predictive variables. The developed risk-scoring system provided excellent discrimination ( c-statistic=0.80, 95% confidence interval=0.79-0.82) with a steep gradient in two-year mortality risk: >25% (top decile) vs. ~1% (bottom quintile). A simplified risk model with 11 predictors gave only slightly weaker discrimination ( c-statistic=0.79, 95% confidence interval =0.78-0.81). This risk score for two-year post-discharge mortality in acute coronary syndrome patients ( www.acsrisk.org ) can facilitate identification of high-risk patients and help guide tailored secondary prevention measures.

Geomorphic controls on elevational gradients of species richness.

PubMed

Bertuzzo, Enrico; Carrara, Francesco; Mari, Lorenzo; Altermatt, Florian; Rodriguez-Iturbe, Ignacio; Rinaldo, Andrea

2016-02-16

Elevational gradients of biodiversity have been widely investigated, and yet a clear interpretation of the biotic and abiotic factors that determine how species richness varies with elevation is still elusive. In mountainous landscapes, habitats at different elevations are characterized by different areal extent and connectivity properties, key drivers of biodiversity, as predicted by metacommunity theory. However, most previous studies directly correlated species richness to elevational gradients of potential drivers, thus neglecting the interplay between such gradients and the environmental matrix. Here, we investigate the role of geomorphology in shaping patterns of species richness. We develop a spatially explicit zero-sum metacommunity model where species have an elevation-dependent fitness and otherwise neutral traits. Results show that ecological dynamics over complex terrains lead to the null expectation of a hump-shaped elevational gradient of species richness, a pattern widely observed empirically. Local species richness is found to be related to the landscape elevational connectivity, as quantified by a newly proposed metric that applies tools of complex network theory to measure the closeness of a site to others with similar habitat. Our theoretical results suggest clear geomorphic controls on elevational gradients of species richness and support the use of the landscape elevational connectivity as a null model for the analysis of the distribution of biodiversity.

Geomorphic controls on elevational gradients of species richness

PubMed Central

Bertuzzo, Enrico; Carrara, Francesco; Mari, Lorenzo; Altermatt, Florian; Rodriguez-Iturbe, Ignacio; Rinaldo, Andrea

2016-01-01

Elevational gradients of biodiversity have been widely investigated, and yet a clear interpretation of the biotic and abiotic factors that determine how species richness varies with elevation is still elusive. In mountainous landscapes, habitats at different elevations are characterized by different areal extent and connectivity properties, key drivers of biodiversity, as predicted by metacommunity theory. However, most previous studies directly correlated species richness to elevational gradients of potential drivers, thus neglecting the interplay between such gradients and the environmental matrix. Here, we investigate the role of geomorphology in shaping patterns of species richness. We develop a spatially explicit zero-sum metacommunity model where species have an elevation-dependent fitness and otherwise neutral traits. Results show that ecological dynamics over complex terrains lead to the null expectation of a hump-shaped elevational gradient of species richness, a pattern widely observed empirically. Local species richness is found to be related to the landscape elevational connectivity, as quantified by a newly proposed metric that applies tools of complex network theory to measure the closeness of a site to others with similar habitat. Our theoretical results suggest clear geomorphic controls on elevational gradients of species richness and support the use of the landscape elevational connectivity as a null model for the analysis of the distribution of biodiversity. PMID:26831107

Mapping Topoclimate and Microclimate in the Monarch Butterfly Biosphere Reserve, Mexico

NASA Astrophysics Data System (ADS)

Weiss, S. B.

2006-12-01

Overwintering monarch butterflies in Mexico select areas of the high elevation Oyamel fir -pine forest providing a canopy that protects them from extremes of cold, heat, sun, and wind. These exacting microclimatic conditions are found in relatively small areas of forest with appropriate topography and canopy cover. The major goal of this investigation is to map topoclimatic and microclimatic conditions within the Monarch Butterfly Biosphere Reserve by combining temperature monitoring (iButton Thermochrons), hemispherical canopy photography, multiple regression, and GIS modeling. Temperature measurements included base weather stations and arrays of Thermochrons (on the north-side of trees at 2m height) across local topographic and canopy cover gradients. Topoclimatic models of minimum temperatures included topographic position, slope, and elevation, and predicted that thermal belts on slopes and cold air drainage into canyons create local minimum temperature gradients of 2°C. Topoclimatic models of maximum temperatures models included elevation, topographic position, and relative solar exposure, with local gradients of 3°C. These models, which are independent of forest canopy structure, were then projected across the entire region. Forest canopy structure, including direct and diffuse solar radiation, was assessed with hemispherical photography at each Thermochron site. Canopy cover affected minimum temperatures primarily on the calmest, coldest nights. Maximum temperatures were predicted by direct radiation below the canopy. Fine- scale grids (25 m spacing) at three overwintering sites characterized effects of canopy gaps and edges on temperature and wind exposure. The effects of temperature variation were considered for lipid loss rates, ability to take flight, and freezing mortality. Lipid loss rates were estimated by measured hourly temperatures. Many of the closed canopy sites allowed for substantial lipid reserves at the end of the season (March 15), but increases in average temperature could effectively deplete lipids by that time. The large influence of canopy cover on daytime maximum temperatures demonstrates that forest thinning directly reduces habitat suitability. Monarchs' flight behavior under warmer conditions suggests that daytime temperatures drive the dynamics of monarch distribution within colonies. Thinning also decreases nighttime minimum temperatures, and increases wind exposure. These results create a basis for quantitative understanding of the combinations of topography and forest structure that provide high quality overwintering habitat.

The effect of energy accumulation and boundary slip on laminar flow between rotating plates

NASA Astrophysics Data System (ADS)

Wu, Zhenpeng; Zeng, Liangcai; Chen, Keying; Jin, Xiaohong; Wu, Shiqian

2018-02-01

The poor operating conditions of fluid lubrication equipment during the start-up process are due to the resistance of the high-viscosity lubricating liquid. Moreover, the excessive reduction in fluid viscosity due to the elevated temperature resulting from power consumption during prolonged operation is not conducive to the generation of dynamic pressure. In this study, we examine the effect of energy accumulation and boundary slip on the laminar flow of a liquid between a pair of rotating plates. The experiments are conducted using a rotary rheometer, with polymethyl methacrylate (PMMA) as the thermal insulation material and polytetrafluoroethylene (PTFE) as the slip drag reduction material, and a three-dimensional simulation model is established. This model is derived by combining the energy equation including the slip length and the heat conduction equation. Thus, the temperature changes over time are predicted by this model, and the model accuracy is verified by experiments. The results reveal the following points: 1) boundary slips function as a drag reduction mechanism for short-time continuous operation; 2) under prolonged operation, the slip reduces the extent of the oil viscosity decrease and clear control of the elevated temperature by the boundary slip is observed.

A one-dimensional model of subsurface hillslope flow

Treesearch

Jason C. Fisher

1997-01-01

Abstract - A one-dimensional, finite difference model of saturated subsurface flow within a hillslope was developed. The model uses rainfall, elevation data, a hydraulic conductivity, and a storage coefficient to predict the saturated thickness in time and space. The model was tested against piezometric data collected in a swale located in the headwaters of the North...

Vector movement underlies avian malaria at upper elevation in Hawaii: implications for transmission of human malaria.

PubMed

Freed, Leonard A; Cann, Rebecca L

2013-11-01

With climate warming, malaria in humans and birds at upper elevations is an emerging infectious disease because development of the parasite in the mosquito vector and vector life history are both temperature dependent. An enhanced-mosquito-movement model from climate warming predicts increased transmission of malaria at upper elevation sites that are too cool for parasite development in the mosquito vector. We evaluate this model with avian malaria (Plasmodium relictum) at 1,900-m elevation on the Island of Hawaii, with air temperatures too low for sporogony in the vector (Culex quinquefasciatus). On a well-defined site over a 14-year period, 10 of 14 species of native and introduced birds became infected, several epizootics occurred, and the increase in prevalence was driven more by resident species than by mobile species that could have acquired their infections at lower elevations. Greater movement of infectious mosquitoes from lower elevations now permits avian malaria to spread at 1,900 m in Hawaii, in advance of climate warming at that elevation. The increase in malaria at upper elevations due to dispersal of infectious mosquitoes is a real alternative to temperature for the increased incidence of human malaria in tropical highlands.

Uncertainty Assessment and Weight Map Generation for Efficient Fusion of Tandem-X and CARTOSAT-1 Dems

NASA Astrophysics Data System (ADS)

Bagheri, H.; Schmitt, M.; Zhu, X. X.

2017-05-01

Recently, with InSAR data provided by the German TanDEM-X mission, a new global, high-resolution Digital Elevation Model (DEM) has been produced by the German Aerospace Center (DLR) with unprecedented height accuracy. However, due to SAR-inherent sensor specifics, its quality decreases over urban areas, making additional improvement necessary. On the other hand, DEMs derived from optical remote sensing imagery, such as Cartosat-1 data, have an apparently greater resolution in urban areas, making their fusion with TanDEM-X elevation data a promising perspective. The objective of this paper is two-fold: First, the height accuracies of TanDEM-X and Cartosat-1 elevation data over different land types are empirically evaluated in order to analyze the potential of TanDEM-XCartosat- 1 DEM data fusion. After the quality assessment, urban DEM fusion using weighted averaging is investigated. In this experiment, both weight maps derived from the height error maps delivered with the DEM data, as well as more sophisticated weight maps predicted by a procedure based on artificial neural networks (ANNs) are compared. The ANN framework employs several features that can describe the height residual performance to predict the weights used in the subsequent fusion step. The results demonstrate that especially the ANN-based framework is able to improve the quality of the final DEM through data fusion.

Prediction of sub-surface 37 Ar concentrations at locations in the Northwestern United States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fritz, Bradley G.; Aalseth, Craig E.; Back, Henning O.

The Comprehensive Nuclear Test-Ban Treaty, which is intended to prevent nuclear weapon testing, includes a verification regime, which provides monitoring to identify potential nuclear testing. The presence of elevated 37Ar is one way to identify subsurface nuclear testing. However, the naturally occurring formation of 37Ar in the subsurface adds a complicating factor. Prediction of the naturally occurring concentration of 37Ar can help to determine if a measured 37Ar concentration is elevated. The naturally occurring 37Ar background concentration has been shown to vary between less than 1 mBq/m3 to greater than 100 mBq/m3 (Riedmann and Purtschert 2011). Here, we evaluate amore » model for predicting the average concentration of 37Ar at any depth under transient barometric pressures, and compare it with measurements. This model is shown to compare favorably with concentrations of 37Ar measured at multiple locations in the Northwestern United States.« less

CALIPSO Satellite Lidar Identification Of Elevated Dust Over Australia Compared With Air Quality Model PM60 Forecasts

NASA Technical Reports Server (NTRS)

Young, Stuart A.; Vaughan, Mark; Omar, Ali; Liu, Zhaoyan; Lee, Sunhee; Hu, Youngxiang; Cope, Martin

2008-01-01

Global measurements of the vertical distribution of clouds and aerosols have been recorded by the lidar on board the CALIPSO (Cloud Aerosol Lidar Infrared Pathfinder Satellite Observations) satellite since June 2006. Such extensive, height-resolved measurements provide a rare and valuable opportunity for developing, testing and validating various atmospheric models, including global climate, numerical weather prediction, chemical transport and air quality models. Here we report on the initial results of an investigation into the performance of the Australian Air Quality Forecast System (AAQFS) model in forecasting the distribution of elevated dust over the Australian region. The model forecasts of PM60 dust distribution are compared with the CALIPSO lidar Vertical Feature Mask (VFM) data product. The VFM classifies contiguous atmospheric regions of enhanced backscatter as either cloud or aerosols. Aerosols are further classified into six subtypes. By comparing forecast PM60 concentration profiles to the spatial distribution of dust reported in the CALIPSO VFM, we can assess the model s ability to predict the occurrence and the vertical and horizontal extents of dust events within the study area.

Land use regression modelling of air pollution in high density high rise cities: A case study in Hong Kong.

PubMed

Lee, Martha; Brauer, Michael; Wong, Paulina; Tang, Robert; Tsui, Tsz Him; Choi, Crystal; Cheng, Wei; Lai, Poh-Chin; Tian, Linwei; Thach, Thuan-Quoc; Allen, Ryan; Barratt, Benjamin

2017-08-15

Land use regression (LUR) is a common method of predicting spatial variability of air pollution to estimate exposure. Nitrogen dioxide (NO 2 ), nitric oxide (NO), fine particulate matter (PM 2.5 ), and black carbon (BC) concentrations were measured during two sampling campaigns (April-May and November-January) in Hong Kong (a prototypical high-density high-rise city). Along with 365 potential geospatial predictor variables, these concentrations were used to build two-dimensional land use regression (LUR) models for the territory. Summary statistics for combined measurements over both campaigns were: a) NO 2 (Mean=106μg/m 3 , SD=38.5, N=95), b) NO (M=147μg/m 3 , SD=88.9, N=40), c) PM 2.5 (M=35μg/m 3 , SD=6.3, N=64), and BC (M=10.6μg/m 3 , SD=5.3, N=76). Final LUR models had the following statistics: a) NO 2 (R 2 =0.46, RMSE=28μg/m 3 ) b) NO (R 2 =0.50, RMSE=62μg/m 3 ), c) PM 2.5 (R 2 =0.59; RMSE=4μg/m 3 ), and d) BC (R 2 =0.50, RMSE=4μg/m 3 ). Traditional LUR predictors such as road length, car park density, and land use types were included in most models. The NO 2 prediction surface values were highest in Kowloon and the northern region of Hong Kong Island (downtown Hong Kong). NO showed a similar pattern in the built-up region. Both PM 2.5 and BC predictions exhibited a northwest-southeast gradient, with higher concentrations in the north (close to mainland China). For BC, the port was also an area of elevated predicted concentrations. The results matched with existing literature on spatial variation in concentrations of air pollutants and in relation to important emission sources in Hong Kong. The success of these models suggests LUR is appropriate in high-density, high-rise cities. Copyright © 2017 Elsevier B.V. All rights reserved.

Instrumental record of debris flow initiation during natural rainfall: Implications for modeling slope stability

USGS Publications Warehouse

Montgomery, D.R.; Schmidt, K.M.; Dietrich, W.E.; McKean, J.

2009-01-01

The middle of a hillslope hollow in the Oregon Coast Range failed and mobilized as a debris flow during heavy rainfall in November 1996. Automated pressure transducers recorded high spatial variability of pore water pressure within the area that mobilized as a debris flow, which initiated where local upward flow from bedrock developed into overlying colluvium. Postfailure observations of the bedrock surface exposed in the debris flow scar reveal a strong spatial correspondence between elevated piezometric response and water discharging from bedrock fractures. Measurements of apparent root cohesion on the basal (Cb) and lateral (Cl) scarp demonstrate substantial local variability, with areally weighted values of Cb = 0.1 and Cl = 4.6 kPa. Using measured soil properties and basal root strength, the widely used infinite slope model, employed assuming slope parallel groundwater flow, provides a poor prediction of hydrologie conditions at failure. In contrast, a model including lateral root strength (but neglecting lateral frictional strength) gave a predicted critical value of relative soil saturation that fell within the range defined by the arithmetic and geometric mean values at the time of failure. The 3-D slope stability model CLARA-W, used with locally observed pore water pressure, predicted small areas with lower factors of safety within the overall slide mass at sites consistent with field observations of where the failure initiated. This highly variable and localized nature of small areas of high pore pressure that can trigger slope failure means, however, that substantial uncertainty appears inevitable for estimating hydrologie conditions within incipient debris flows under natural conditions. Copyright 2009 by the American Geophysical Union.

Biot-Gassmann theory for velocities of gas hydrate-bearing sediments

USGS Publications Warehouse

Lee, M.W.

2002-01-01

Elevated elastic velocities are a distinct physical property of gas hydrate-bearing sediments. A number of velocity models and equations (e.g., pore-filling model, cementation model, effective medium theories, weighted equations, and time-average equations) have been used to describe this effect. In particular, the weighted equation and effective medium theory predict reasonably well the elastic properties of unconsolidated gas hydrate-bearing sediments. A weakness of the weighted equation is its use of the empirical relationship of the time-average equation as one element of the equation. One drawback of the effective medium theory is its prediction of unreasonably higher shear-wave velocity at high porosities, so that the predicted velocity ratio does not agree well with the observed velocity ratio. To overcome these weaknesses, a method is proposed, based on Biot-Gassmann theories and assuming the formation velocity ratio (shear to compressional velocity) of an unconsolidated sediment is related to the velocity ratio of the matrix material of the formation and its porosity. Using the Biot coefficient calculated from either the weighted equation or from the effective medium theory, the proposed method accurately predicts the elastic properties of unconsolidated sediments with or without gas hydrate concentration. This method was applied to the observed velocities at the Mallik 2L-39 well, Mackenzie Delta, Canada.

Numerical simulation of the paleohydrology of glacial Lake Oshkosh, eastern Wisconsin, USA

USGS Publications Warehouse

Clark, J.A.; Befus, K.M.; Hooyer, T.S.; Stewart, P.W.; Shipman, T.D.; Gregory, C.T.; Zylstra, D.J.

2008-01-01

Proglacial lakes, formed during retreat of the Laurentide ice sheet, evolved quickly as outlets became ice-free and the earth deformed through glacial isostatic adjustment. With high-resolution digital elevation models (DEMs) and GIS methods, it is possible to reconstruct the evolution of surface hydrology. When a DEM deforms through time as predicted by our model of viscoelastic earth relaxation, the entire surface hydrologic system with its lakes, outlets, shorelines and rivers also evolves without requiring assumptions of outlet position. The method is applied to proglacial Lake Oshkosh in Wisconsin (13,600 to 12,900??cal yr BP). Comparison of predicted to observed shoreline tilt indicates the ice sheet was about 400??m thick over the Great Lakes region. During ice sheet recession, each of the five outlets are predicted to uplift more than 100??m and then subside approximately 30??m. At its maximum extent, Lake Oshkosh covered 6600??km2 with a volume of 111??km3. Using the Hydrologic Engineering Center-River Analysis System model, flow velocities during glacial outburst floods up to 9??m/s and peak discharge of 140,000??m3/s are predicted, which could drain 33.5??km3 of lake water in 10??days and transport boulders up to 3??m in diameter. ?? 2007 University of Washington.

Levee crest elevation profiles derived from airborne lidar-based high resolution digital elevation models in south Louisiana

USGS Publications Warehouse

Palaseanu-Lovejoy, Monica; Thatcher, Cindy A.; Barras, John A.

2014-01-01

This study explores the feasibility of using airborne lidar surveys to construct high-resolution digital elevation models (DEMs) and develop an automated procedure to extract levee longitudinal elevation profiles for both federal levees in Atchafalaya Basin and local levees in Lafourche Parish, south Lousiana. This approach can successfully accommodate a high degree of levee sinuosity and abrupt changes in levee orientation (direction) in planar coordinates, variations in levee geometries, and differing DEM resolutions. The federal levees investigated in Atchafalaya Basin have crest elevations between 5.3 and 12 m while the local counterparts in Lafourche Parish are between 0.76 and 2.3 m. The vertical uncertainty in the elevation data is considered when assessing federal crest elevation against the U.S. Army Corps of Engineers minimum height requirements to withstand the 100-year flood. Only approximately 5% of the crest points of the two federal levees investigated in the Atchafalaya Basin region met this requirement.

Development and Preliminary Performance of a Risk Factor Screen to Predict Posttraumatic Psychological Disorder After Trauma Exposure

PubMed Central

Carlson, Eve B.; Palmieri, Patrick A.; Spain, David A.

2017-01-01

Objective We examined data from a prospective study of risk factors that increase vulnerability or resilience, exacerbate distress, or foster recovery to determine whether risk factors accurately predict which individuals will later have high posttraumatic (PT) symptom levels and whether brief measures of risk factors also accurately predict later symptom elevations. Method Using data from 129 adults exposed to traumatic injury of self or a loved one, we conducted receiver operating characteristic (ROC) analyses of 14 risk factors assessed by full-length measures, determined optimal cutoff scores and calculated predictive performance for the nine that were most predictive. For five risk factors, we identified sets of items that accounted for 90% of variance in total scores and calculated predictive performance for sets of brief risk measures. Results A set of nine risk factors assessed by full measures identified 89% of those who later had elevated PT symptoms (sensitivity) and 78% of those who did not (specificity). A set of four brief risk factor measures assessed soon after injury identified 86% of those who later had elevated PT symptoms and 72% of those who did not. Conclusions Use of sets of brief risk factor measures shows promise of accurate prediction of PT psychological disorder and probable PTSD or depression. Replication of predictive accuracy is needed in a new and larger sample. PMID:28622811

Physical fitness predicts technical-tactical and time-motion profile in simulated Judo and Brazilian Jiu-Jitsu matches

PubMed Central

Gentil, Paulo; Bueno, João C.A.; Follmer, Bruno; Marques, Vitor A.; Del Vecchio, Fabrício B.

2018-01-01

Background Among combat sports, Judo and Brazilian Jiu-Jitsu (BJJ) present elevated physical fitness demands from the high-intensity intermittent efforts. However, information regarding how metabolic and neuromuscular physical fitness is associated with technical-tactical performance in Judo and BJJ fights is not available. This study aimed to relate indicators of physical fitness with combat performance variables in Judo and BJJ. Methods The sample consisted of Judo (n = 16) and BJJ (n = 24) male athletes. At the first meeting, the physical tests were applied and, in the second, simulated fights were performed for later notational analysis. Results The main findings indicate: (i) high reproducibility of the proposed instrument and protocol used for notational analysis in a mobile device; (ii) differences in the technical-tactical and time-motion patterns between modalities; (iii) performance-related variables are different in Judo and BJJ; and (iv) regression models based on metabolic fitness variables may account for up to 53% of the variances in technical-tactical and/or time-motion variables in Judo and up to 31% in BJJ, whereas neuromuscular fitness models can reach values up to 44 and 73% of prediction in Judo and BJJ, respectively. When all components are combined, they can explain up to 90% of high intensity actions in Judo. Discussion In conclusion, performance prediction models in simulated combat indicate that anaerobic, aerobic and neuromuscular fitness variables contribute to explain time-motion variables associated with high intensity and technical-tactical variables in Judo and BJJ fights. PMID:29844991

Probabilistic estimation of dune retreat on the Gold Coast, Australia

USGS Publications Warehouse

Palmsten, Margaret L.; Splinter, Kristen D.; Plant, Nathaniel G.; Stockdon, Hilary F.

2014-01-01

Sand dunes are an important natural buffer between storm impacts and development backing the beach on the Gold Coast of Queensland, Australia. The ability to forecast dune erosion at a prediction horizon of days to a week would allow efficient and timely response to dune erosion in this highly populated area. Towards this goal, we modified an existing probabilistic dune erosion model for use on the Gold Coast. The original model was trained using observations of dune response from Hurricane Ivan on Santa Rosa Island, Florida, USA (Plant and Stockdon 2012. Probabilistic prediction of barrier-island response to hurricanes, Journal of Geophysical Research, 117(F3), F03015). The model relates dune position change to pre-storm dune elevations, dune widths, and beach widths, along with storm surge and run-up using a Bayesian network. The Bayesian approach captures the uncertainty of inputs and predictions through the conditional probabilities between variables. Three versions of the barrier island response Bayesian network were tested for use on the Gold Coast. One network has the same structure as the original and was trained with the Santa Rosa Island data. The second network has a modified design and was trained using only pre- and post-storm data from 1988-2009 for the Gold Coast. The third version of the network has the same design as the second version of the network and was trained with the combined data from the Gold Coast and Santa Rosa Island. The two networks modified for use on the Gold Coast hindcast dune retreat with equal accuracy. Both networks explained 60% of the observed dune retreat variance, which is comparable to the skill observed by Plant and Stockdon (2012) in the initial Bayesian network application at Santa Rosa Island. The new networks improved predictions relative to application of the original network on the Gold Coast. Dune width was the most important morphologic variable in hindcasting dune retreat, while hydrodynamic variables, surge and run-up elevation, were also important

The nonlinear relationship between cerebrospinal fluid Aβ42 and tau in preclinical Alzheimer's disease.

PubMed

de Leon, Mony J; Pirraglia, Elizabeth; Osorio, Ricardo S; Glodzik, Lidia; Saint-Louis, Les; Kim, Hee-Jin; Fortea, Juan; Fossati, Silvia; Laska, Eugene; Siegel, Carole; Butler, Tracy; Li, Yi; Rusinek, Henry; Zetterberg, Henrik; Blennow, Kaj

2018-01-01

Cerebrospinal fluid (CSF) studies consistently show that CSF levels of amyloid-beta 1-42 (Aβ42) are reduced and tau levels increased prior to the onset of cognitive decline related to Alzheimer's disease (AD). However, the preclinical prediction accuracy for low CSF Aβ42 levels, a surrogate for brain Aβ42 deposits, is not high. Moreover, the pathology data suggests a course initiated by tauopathy contradicting the contemporary clinical view of an Aβ initiated cascade. CSF Aβ42 and tau data from 3 normal aging cohorts (45-90 years) were combined to test both cross-sectional (n = 766) and longitudinal (n = 651) hypotheses: 1) that the relationship between CSF levels of Aβ42 and tau are not linear over the adult life-span; and 2) that non-linear models improve the prediction of cognitive decline. Supporting the hypotheses, the results showed that a u-shaped quadratic fit (Aβ2) best describes the relationship for CSF Aβ42 with CSF tau levels. Furthermore we found that the relationship between Aβ42 and tau changes with age-between 45 and 70 years there is a positive linear association, whereas between 71 and 90 years there is a negative linear association between Aβ42 and tau. The quadratic effect appears to be unique to Aβ42, as Aβ38 and Aβ40 showed only positive linear relationships with age and CSF tau. Importantly, we observed the prediction of cognitive decline was improved by considering both high and low levels of Aβ42. Overall, these data suggest an earlier preclinical stage than currently appreciated, marked by CSF elevations in tau and accompanied by either elevations or reductions in Aβ42. Future studies are needed to examine potential mechanisms such as failing CSF clearance as a common factor elevating CSF Aβxx analyte levels prior to Aβ42 deposition in brain.

A prediction model of signal degradation in LMSS for urban areas

NASA Technical Reports Server (NTRS)

Matsudo, Takashi; Minamisono, Kenichi; Karasawa, Yoshio; Shiokawa, Takayasu

1993-01-01

A prediction model of signal degradation in a Land Mobile Satellite Service (LMSS) for urban areas is proposed. This model treats shadowing effects caused by buildings statistically and can predict a Cumulative Distribution Function (CDF) of signal diffraction losses in urban areas as a function of system parameters such as frequency and elevation angle and environmental parameters such as number of building stories and so on. In order to examine the validity of the model, we compared the percentage of locations where diffraction losses were smaller than 6 dB obtained by the CDF with satellite visibility measured by a radiometer. As a result, it was found that this proposed model is useful for estimating the feasibility of providing LMSS in urban areas.

Subglacial efficiency and storage modified by the temporal pattern of high-elevation meltwater input

NASA Astrophysics Data System (ADS)

Andrews, L. C.; Dow, C. F.; Poinar, K.; Nowicki, S.

2017-12-01

Ice flow in marginal region of the Greenland Ice Sheet dynamically responds to summer melting as surface meltwater is routed through the supraglacial hydrologic system to the bed of the ice sheet via crevasses and moulins. Given the expected increases in surface melt production and extent, and the potential for high elevation surface-to-bed connections, it is imperative to understand how meltwater delivered to the bed from different high-elevation supraglacial storage features affects the evolution of the subglacial hydrologic system and associated ice dynamics. Here, we use the two-dimensional subglacial hydrologic model, GLaDS, which includes distributed and channelized water flow, to test how the subglacial system of an idealized outlet glacier responds to cases of high-elevation firn-aquifer-type and supraglacial-lake-type englacial drainage over the course of 5 years. Model outputs driven by these high elevation drainage types are compared to steady-state model results, where the subglacial system only receives the 1980-2016 mean MERRA-2 runoff via low-elevation moulins. Across all experiments, the subglacial hydrologic system displays inter-annual memory, resulting in multiyear declines in subglacial pressure during the onset of seasonal melting and growth of subglacial channels. The gradual addition of water in firn-aquifer-type drainage scenarios resulted in small increases in subglacial water storage but limited changes in subglacial efficiency and channelization. Rapid, supraglacial-lake-type drainage resulted in short-term local increases in subglacial water pressure and storage, which gave way to spatially extensive decreases in subglacial pressure and downstream channelization. These preliminary results suggest that the character of high-elevation englacial drainage can have a strong, and possibly outsized, control on subglacial efficiency throughout the ablation zone. Therefore, understanding both how high elevation meltwater is stored supraglacially and the probability of crevassing at high elevations will play an important role in how the subglacial system, proglacial discharge and ice motion will respond to future increases in surface melt production and runoff.

Subglacial efficiency and storage modified by the temporal pattern of high-elevation meltwater input

NASA Astrophysics Data System (ADS)

Ackley, S. F.; Maksym, T.; Stammerjohn, S. E.; Gao, Y.; Weissling, B.

2016-12-01

Ice flow in marginal region of the Greenland Ice Sheet dynamically responds to summer melting as surface meltwater is routed through the supraglacial hydrologic system to the bed of the ice sheet via crevasses and moulins. Given the expected increases in surface melt production and extent, and the potential for high elevation surface-to-bed connections, it is imperative to understand how meltwater delivered to the bed from different high-elevation supraglacial storage features affects the evolution of the subglacial hydrologic system and associated ice dynamics. Here, we use the two-dimensional subglacial hydrologic model, GLaDS, which includes distributed and channelized water flow, to test how the subglacial system of an idealized outlet glacier responds to cases of high-elevation firn-aquifer-type and supraglacial-lake-type englacial drainage over the course of 5 years. Model outputs driven by these high elevation drainage types are compared to steady-state model results, where the subglacial system only receives the 1980-2016 mean MERRA-2 runoff via low-elevation moulins. Across all experiments, the subglacial hydrologic system displays inter-annual memory, resulting in multiyear declines in subglacial pressure during the onset of seasonal melting and growth of subglacial channels. The gradual addition of water in firn-aquifer-type drainage scenarios resulted in small increases in subglacial water storage but limited changes in subglacial efficiency and channelization. Rapid, supraglacial-lake-type drainage resulted in short-term local increases in subglacial water pressure and storage, which gave way to spatially extensive decreases in subglacial pressure and downstream channelization. These preliminary results suggest that the character of high-elevation englacial drainage can have a strong, and possibly outsized, control on subglacial efficiency throughout the ablation zone. Therefore, understanding both how high elevation meltwater is stored supraglacially and the probability of crevassing at high elevations will play an important role in how the subglacial system, proglacial discharge and ice motion will respond to future increases in surface melt production and runoff.

Plastic Deformation of Micromachined Silicon Diaphragms with a Sealed Cavity at High Temperatures

PubMed Central

Ren, Juan; Ward, Michael; Kinnell, Peter; Craddock, Russell; Wei, Xueyong

2016-01-01

Single crystal silicon (SCS) diaphragms are widely used as pressure sensitive elements in micromachined pressure sensors. However, for harsh environments applications, pure silicon diaphragms are hardly used because of the deterioration of SCS in both electrical and mechanical properties. To survive at the elevated temperature, the silicon structures must work in combination with other advanced materials, such as silicon carbide (SiC) or silicon on insulator (SOI), for improved performance and reduced cost. Hence, in order to extend the operating temperatures of existing SCS microstructures, this work investigates the mechanical behavior of pressurized SCS diaphragms at high temperatures. A model was developed to predict the plastic deformation of SCS diaphragms and was verified by the experiments. The evolution of the deformation was obtained by studying the surface profiles at different anneal stages. The slow continuous deformation was considered as creep for the diaphragms with a radius of 2.5 mm at 600 °C. The occurrence of plastic deformation was successfully predicted by the model and was observed at the operating temperature of 800 °C and 900 °C, respectively. PMID:26861332

Linking morphology and motion: a test of a four-bar mechanism in seahorses.

PubMed

Roos, Gert; Leysen, Heleen; Van Wassenbergh, Sam; Herrel, Anthony; Jacobs, Patric; Dierick, Manuel; Aerts, Peter; Adriaens, Dominique

2009-01-01

Syngnathid fishes (seahorses, pipefish, and sea dragons) possess a highly modified cranium characterized by a long and tubular snout with minute jaws at its end. Previous studies indicated that these species are extremely fast suction feeders with their feeding strike characterized by a rapid elevation of the head accompanied by rotation of the hyoid. A planar four-bar model is proposed to explain the coupled motion of the neurocranium and the hyoid. Because neurocranial elevation as well as hyoid rotation are crucial for the feeding mechanism in previously studied Syngnathidae, a detailed evaluation of this model is needed. In this study, we present kinematic data of the feeding strike in the seahorse Hippocampus reidi. We combined these data with a detailed morphological analysis of the important linkages and joints involved in rotation of the neurocranium and the hyoid, and we compared the kinematic measurements with output of a theoretical four-bar model. The kinematic analysis shows that neurocranial rotation never preceded hyoid rotation, thus indicating that hyoid rotation triggers the explosive feeding strike. Our data suggest that while neurocranium and hyoid initially (first 1.5 ms) behave as predicted by the four-bar model, eventually, the hyoid rotation is underestimated by the model. Shortening, or a posterior displacement of the sternohyoid muscle (of which the posterior end is confluent with the hypaxial muscles in H. reidi), probably explains the discrepancy between the model and our kinematic measurements. As a result, while four-bar modeling indicates a clear coupling between hyoid rotation and neurocranial elevation, the detailed morphological determination of the linkages and joints of this four-bar model remain crucial in order to fully understand this mechanism in seahorse feeding.

Correlates of AUDIT risk status for male and female college students.

PubMed

Demartini, Kelly S; Carey, Kate B

2009-01-01

The current study identified gender-specific correlates of hazardous drinker status as defined by the AUDIT. A total of 462 college student volunteers completed the study in 2006. The sample was predominantly Caucasian (75%) and female (55%). Participants completed a survey assessing demographics, alcohol use patterns, and health indices. Scores of 8 or more on the AUDIT defined the at-risk subsample. Logistic regression models determined which variables predicted AUDIT risk status for men and women. The at-risk participants reported higher alcohol use and related problems, elevated sleep problems and lower health ratings. High typical blood alcohol concentration (BAC), lifetime drug use, and psychosocial problems predicted risk status for males. Binge frequency and psychosocial problems predicted risk status for females. Different behavioral profiles emerged for men and women identified as hazardous drinkers on the AUDIT. The efficacy of brief alcohol interventions could be enhanced by addressing these behavioral correlates.

Hot Deformation Behavior and Flow Stress Prediction of TC4-DT Alloy in Single-Phase Region and Dual-Phase Regions

NASA Astrophysics Data System (ADS)

Liu, Jianglin; Zeng, Weidong; Zhu, Yanchun; Yu, Hanqing; Zhao, Yongqing

2015-05-01

Isothermal compression tests of TC4-DT titanium alloy at the deformation temperature ranging from 1181 to 1341 K covering α + β phase field and β-phase field, the strain rate ranging from 0.01 to 10.0 s-1 and the height reduction of 70% were conducted on a Gleeble-3500 thermo-mechanical simulator. The experimental true stress-true strain data were employed to develop the strain-compensated Arrhenius-type flow stress model and artificial neural network (ANN) model; the predictability of two models was quantified in terms of correlation coefficient ( R) and average absolute relative error (AARE). The R and AARE for the Arrhenius-type flow stress model were 0.9952 and 5.78%, which were poorer linear relation and more deviation than 0.9997 and 1.04% for the feed-forward back-propagation ANN model, respectively. The results indicated that the trained ANN model was more efficient and accurate in predicting the flow behavior for TC4-DT titanium alloy at elevated temperature deformation than the strain-compensated Arrhenius-type constitutive equations. The constitutive relationship compensating strain could track the experimental data across the whole hot working domain other than that at high strain rates (≥1 s-1). The microstructure analysis illustrated that the deformation mechanisms existed at low strain rates (≤0.1 s-1), where dynamic recrystallization occurred, were far different from that at high strain rates (≥1 s-1) that presented bands of flow localization and cracking along grain boundary.

DNDO Report: Predicting Solar Modulation Potentials for Modeling Cosmic Background Radiation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Behne, Patrick Alan

The modeling of the detectability of special nuclear material (SNM) at ports and border crossings requires accurate knowledge of the background radiation at those locations. Background radiation originates from two main sources, cosmic and terrestrial. Cosmic background is produced by high-energy galactic cosmic rays (GCR) entering the atmosphere and inducing a cascade of particles that eventually impact the earth’s surface. The solar modulation potential represents one of the primary inputs to modeling cosmic background radiation. Usosokin et al. formally define solar modulation potential as “the mean energy loss [per unit charge] of a cosmic ray particle inside the heliosphere…” Modulationmore » potential, a function of elevation, location, and time, shares an inverse relationship with cosmic background radiation. As a result, radiation detector thresholds require adjustment to account for differing background levels, caused partly by differing solar modulations. Failure to do so can result in higher rates of false positives and failed detection of SNM for low and high levels of solar modulation potential, respectively. This study focuses on solar modulation’s time dependence, and seeks the best method to predict modulation for future dates using Python. To address the task of predicting future solar modulation, we utilize both non-linear least squares sinusoidal curve fitting and cubic spline interpolation. This material will be published in transactions of the ANS winter meeting of November, 2016.« less

Elevated moisture stimulates carbon loss from mineral soils by releasing protected organic matter.

PubMed

Huang, Wenjuan; Hall, Steven J

2017-11-24

Moisture response functions for soil microbial carbon (C) mineralization remain a critical uncertainty for predicting ecosystem-climate feedbacks. Theory and models posit that C mineralization declines under elevated moisture and associated anaerobic conditions, leading to soil C accumulation. Yet, iron (Fe) reduction potentially releases protected C, providing an under-appreciated mechanism for C destabilization under elevated moisture. Here we incubate Mollisols from ecosystems under C 3 /C 4 plant rotations at moisture levels at and above field capacity over 5 months. Increased moisture and anaerobiosis initially suppress soil C mineralization, consistent with theory. However, after 25 days, elevated moisture stimulates cumulative gaseous C-loss as CO 2 and CH 4 to >150% of the control. Stable C isotopes show that mineralization of older C 3 -derived C released following Fe reduction dominates C losses. Counter to theory, elevated moisture may significantly accelerate C losses from mineral soils over weeks to months-a critical mechanistic deficiency of current Earth system models.

The Reference Elevation Model of Antarctica (REMA): A High Resolution, Time-Stamped Digital Elevation Model for the Antarctic Ice Sheet

NASA Astrophysics Data System (ADS)

Howat, I.; Noh, M. J.; Porter, C. C.; Smith, B. E.; Morin, P. J.

2017-12-01

We are creating the Reference Elevation Model of Antarctica (REMA), a continuous, high resolution (2-8 m), high precision (accuracy better than 1 m) reference surface for a wide range of glaciological and geodetic applications. REMA will be constructed from stereo-photogrammetric Digital Surface Models (DSM) extracted from pairs of submeter resolution DigitalGlobe satellite imagery and vertically registred to precise elevations from near-coincident airborne LiDAR, ground-based GPS surveys and Cryosat-2 radar altimetry. Both a seamless mosaic and individual, time-stamped DSM strips, collected primarily between 2012 and 2016, will be distributed to enable change measurement. These data will be used for mapping bed topography from ice thickness, measuring ice thickness changes, constraining ice flow and geodynamic models, mapping glacial geomorphology, terrain corrections and filtering of remote sensing observations, and many other science tasks. Is will also be critical for mapping ice traverse routes, landing sites and other field logistics planning. REMA will also provide a critical elevation benchmark for future satellite altimetry missions including ICESat-2. Here we report on REMA production progress, initial accuracy assessment and data availability.

Modeling and life prediction methodology for Titanium Matrix Composites subjected to mission profiles

NASA Technical Reports Server (NTRS)

Mirdamadi, M.; Johnson, W. S.

1994-01-01

Titanium matrix composites (TMC) are being evaluated as structural materials for elevated temperature applications in future generation hypersonic vehicles. In such applications, TMC components are subjected to complex thermomechanical loading profiles at various elevated temperatures. Therefore, thermomechanical fatigue (TMF) testing, using a simulated mission profile, is essential for evaluation and development of life prediction methodologies. The objective of the research presented in this paper was to evaluate the TMF response of the (0/90)2s SCS-6/Timetal-21S subjected to a generic hypersonic flight profile and its portions with a temperature ranging from -130 C to 816 C. It was found that the composite modulus, prior to rapid degradation, had consistent values for all the profiles tested. A micromechanics based analysis was used to predict the stress-strain response of the laminate and of the constituents in each ply during thermomechanical loading conditions by using only constituent properties as input. The fiber was modeled as elastic with transverse orthotropic and temperature dependent properties. The matrix was modeled using a thermoviscoplastic constitutive relation. In the analysis, the composite modulus degradation was assumed to result from matrix cracking and was modeled by reducing the matrix modulus. Fatigue lives of the composite subjected to the complex generic hypersonic flight profile were well correlated using the predicted stress in 0 degree fibers.

Niche modeling predictions of the potential distribution of Marmota himalayana, the host animal of plague in Yushu County of Qinghai.

PubMed

Lu, Liang; Ren, Zhoupeng; Yue, Yujuan; Yu, Xiaotao; Lu, Shan; Li, Guichang; Li, Hailong; Wei, Jianchun; Liu, Jingli; Mu, You; Hai, Rong; Yang, Yonghai; Wei, Rongjie; Kan, Biao; Wang, Hu; Wang, Jinfeng; Wang, Zuyun; Liu, Qiyong; Xu, Jianguo

2016-02-24

After the earthquake on 14, April 2010 at Yushu in China, a plague epidemic hosted by Himalayan marmot (Marmota himalayana) became a major public health concern during the reconstruction period. A rapid assessment of the distribution of Himalayan marmot in the area was urgent. The aims of this study were to analyze the relationship between environmental factors and the distribution of burrow systems of the marmot and to predict the distribution of marmots. Two types of marmot burrows (hibernation and temporary) in Yushu County were investigated from June to September in 2011. The location of every burrow was recorded with a global positioning system receiver. An ecological niche model was used to determine the relationship between the burrow occurrence data and environmental variables, such as land surface temperature (LST) in winter and summer, normalized difference vegetation index (NDVI) in winter and summer, elevation, and soil type. The predictive accuracies of the models were assessed by the area under the curve of the receiving operator curve. The models for hibernation and temporary burrows both performed well. The contribution orders of the variables were LST in winter and soil type, NDVI in winter and elevation for the hibernation burrow model, and LST in summer, NDVI in summer, soil type and elevation in the temporary burrow model. There were non-linear relationships between the probability of burrow presence and LST, NDVI and elevation. LST of 14 and 23 °C, NDVI of 0.22 and 0.60, and 4100 m were inflection points. A substantially higher probability of burrow presence was observed in swamp soil and dark felty soil than in other soil types. The potential area for hibernation burrows was 5696 km(2) (37.7% of Yushu County), and the area for temporary burrows was 7711 km(2) (51.0% of Yushu County). The results suggested that marmots preferred warm areas with relatively low altitudes and good vegetation conditions in Yushu County. Based on these results, the present research is useful in understanding the niche selection and distribution pattern of marmots in this region.

The Impact of Elevated Temperatures on Continental Carbon Cycling in the Paleogene

NASA Astrophysics Data System (ADS)

Pancost, R. D.; Handley, L.; Taylor, K. W.; Collinson, M. E.; Weijers, J.; Talbot, H. M.; Hollis, C. J.; Grogan, D. S.; Whiteside, J. H.

2010-12-01

Recent climate and biogeochemical modelling suggests that methane flux from wetlands and soils was greater during past greenhouse climates, due to a combination of higher continental temperatures, an enhanced hydrological cycle, and elevated primary production. Here, we examine continental environments in the Paleogene using a range of biomarker proxies (complemented by palaeobotanical approaches), including air temperatures derived from the distribution of soil bacterial glycerol dialkyl glycerol tetraethers (the MBT/CBT proxy), as well as evidence from wetland and lacustrine settings for enhanced methane cycling. Previously published and new MBT/CBT records parallel sea surface temperature records, suggesting elevated continental temperatures during the Eocene even at mid- to high latitudes (New Zealand, 20-28°C; the Arctic, 17°C; across the Sierra Nevada, 15-25°C; and SE England, 20-30°C). Such temperatures are broadly consistent with paleobotanical records and would have directly led to increased methane production via the metabolic impact of temperature on rates of methanogenesis. To test this, we have determined the distributions and carbon isotopic compositions of archaeal ether lipids and bacterial hopanoids in thermally immature Eocene lignites. In particular, the Cobham lignite, deposited in SE England and spanning the PETM, is characterised by markedly higher concentrations of both methanogen and methanotroph biomarkers compared to modern and Holocene temperate peats. Elevated temperatures, by fostering either stratification and/or decreased oxygen solubility, could have also led to enhanced methane production in Paleogene lakes. Both the Messel Shale (Germany) and Green River Formation, specifically the Parachute Creek oil shale horizons (Utah and Wyoming), are characterised by strongly reducing conditions (including euxinic conditions in the latter), as well as abundant methanogen and methanotroph biomarkers. Such results confirm model predictions of elevated Eocene methane levels relative to the Holocene (x10), but suggest that even these could be underestimates as they do not take into account lacustrine production and are generally characterised by lower high latitude temperatures than proxies suggest.

Circulating asymmetric dimethylarginine and the risk of preeclampsia: a meta-analysis based on 1338 participants.

PubMed

Yuan, Jing; Wang, Xinguo; Xie, Yudou; Wang, Yuzhi; Dong, Lei; Li, Hong; Zhu, Tongyu

2017-07-04

Patients with preeclampsia have higher circulating asymmetric dimethylarginine (ADMA). However, whether circulating ADMA is elevated before the diagnosis of preeclampsia has not been determined. A meta-analysis of observational studies that reported circulating ADMA level before the onset of preeclampsia was performed. Pubmed and Embase were searched. Standardized mean differences (SMD) with 95% confidence intervals (CI) were used to estimate the differences in circulating ADMA. A random effect model or a fixed effect model was applied depending on the heterogeneity. The predictive efficacy of circulating ADMA for the incidence of preeclampsia was also explored. Eleven comparisons with 1338 pregnant women were included. The pooled results showed that the circulating ADMA was significantly higher in women who subsequently developed preeclampsia as compared with those did not (SMD: 0.71, p < 0.001) with a moderate heterogeneity (I2 = 43%). Stratified analyses suggested elevation of circulating ADMA is more remarkable in studies with GA of ADMA sampling ≥ 20 weeks (SMD: 0.89, p < 0.01) as compared those with GA of ADMA sampling < 20 weeks (SMD: 0.56, p < 0.01; p for subgroup interaction = 0.03). Differences of maternal age, study design, and ADMA measurement methods did not significantly affect the results. Only two studies evaluated the potential predicting ability of circulating ADMA for subsequent preeclampsia, and retrieved moderate predictive efficacy. Circulating ADMA is elevated before the development of preeclampsia. Studies are needed to evaluate the predictive efficacy of ADMA for the incidence of preeclampsia.

Incidence and predictive factors of transaminase elevation in patients consulting for dengue fever in Cayenne Hospital, French Guiana.

PubMed

Djossou, Félix; Vesin, Guillaume; Walter, Gaelle; Epelboin, Loïc; Mosnier, Emilie; Bidaud, Bastien; Abboud, Philippe; Okandze, Antoine; Mattheus, Severine; Elenga, Narcisse; Demar, Magalie; Malvy, Denis; Nacher, Mathieu

2016-02-01

The objective of the study was to determine the incidence of transaminase elevation during dengue, and its predictive factors. In 2013, a longitudinal study was performed using data from all cases of dengue seen in Cayenne Hospital. Cox proportional modeling was used. Signs of major transaminase elevation were defined as an increase in aspartate amino transferase (AST) or alanine amino transferase (ALT) concentration over 10 times the normal value (10N). There were 1574 patients and 13 249 person-days of follow-up. The incidence rate for signs of transaminase elevation (10N) was 0.55 per 100 person-days. Six patients had major transaminase elevation with AST>1000 units (0.43 per 1000 patient-days), and 73 patients (4.6%) developed transaminase elevation with AST >10N. The variables independently associated with major transaminase elevation were hyponatremia, low platelets, dehydration, hematocrit increase, food intolerance, positive nonstructural protein 1 (NS1), age over 15 years and the notion of paracetamol intake. Although very frequent, the incidence of major transaminase elevation was lower than reported elsewhere perhaps because of good access to care, or of the particular serotype causing this epidemic. The patients with transaminase elevation tended to be older, more severe and taking paracetamol. . © The Author 2016. Published by Oxford University Press on behalf of Royal Society of Tropical Medicine and Hygiene. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Erythrocyte sedimentation rate as baseline predictor for the development of uveitis in children with juvenile idiopathic arthritis.

PubMed

Haasnoot, Arenda J W; van Tent-Hoeve, Maretta; Wulffraat, Nico M; Schalij-Delfos, Nicoline E; Los, Leonoor I; Armbrust, Wineke; Zuithoff, Nicolaas P A; de Boer, Joke H

2015-02-01

To analyze inflammatory parameters as possible predictors for the development of uveitis in juvenile idiopathic arthritis (JIA) patients. Further, to analyze the predictive value of demographic and clinical factors at the onset of arthritis. Retrospective cohort study. In 358 children with oligoarthritis and rheumatoid factor-negative polyarthritis, erythrocyte sedimentation rate (ESR), C-reactive protein, leukocyte count, presence of antinuclear antibodies (ANA), presence of human leukocyte antigen (HLA-)B27, age of onset of JIA, and sex were analyzed for their predictive value for the onset of uveitis. One hundred forty-seven patients (41%) were diagnosed with chronic anterior uveitis. Young age of onset, presence of ANA, and elevated ESR appeared to be predictive factors according to univariate analyses (P = .029, P = .007, and P = 5E(-4), respectively). According to multivariate analysis, young age of onset and elevated ESR appeared to be predictive after adjusting for the other relevant factors (P = .004 and P = .001, respectively). A prediction model was developed. Elevated ESR appears to be a predictor for the occurrence of uveitis in patients with JIA. Since ESR is already routinely tested in patients with recently diagnosed arthritis, its use as a biomarker can easily be implemented in daily practice. Copyright © 2015 Elsevier Inc. All rights reserved.

Improving the Spatial Prediction of Soil Organic Carbon Stocks in a Complex Tropical Mountain Landscape by Methodological Specifications in Machine Learning Approaches.

PubMed

Ließ, Mareike; Schmidt, Johannes; Glaser, Bruno

2016-01-01

Tropical forests are significant carbon sinks and their soils' carbon storage potential is immense. However, little is known about the soil organic carbon (SOC) stocks of tropical mountain areas whose complex soil-landscape and difficult accessibility pose a challenge to spatial analysis. The choice of methodology for spatial prediction is of high importance to improve the expected poor model results in case of low predictor-response correlations. Four aspects were considered to improve model performance in predicting SOC stocks of the organic layer of a tropical mountain forest landscape: Different spatial predictor settings, predictor selection strategies, various machine learning algorithms and model tuning. Five machine learning algorithms: random forests, artificial neural networks, multivariate adaptive regression splines, boosted regression trees and support vector machines were trained and tuned to predict SOC stocks from predictors derived from a digital elevation model and satellite image. Topographical predictors were calculated with a GIS search radius of 45 to 615 m. Finally, three predictor selection strategies were applied to the total set of 236 predictors. All machine learning algorithms-including the model tuning and predictor selection-were compared via five repetitions of a tenfold cross-validation. The boosted regression tree algorithm resulted in the overall best model. SOC stocks ranged between 0.2 to 17.7 kg m-2, displaying a huge variability with diffuse insolation and curvatures of different scale guiding the spatial pattern. Predictor selection and model tuning improved the models' predictive performance in all five machine learning algorithms. The rather low number of selected predictors favours forward compared to backward selection procedures. Choosing predictors due to their indiviual performance was vanquished by the two procedures which accounted for predictor interaction.

Do all leaf photosynthesis parameters of rice acclimate to elevated CO2 , elevated temperature, and their combination, in FACE environments?

PubMed

Cai, Chuang; Li, Gang; Yang, Hailong; Yang, Jiaheng; Liu, Hong; Struik, Paul C; Luo, Weihong; Yin, Xinyou; Di, Lijun; Guo, Xuanhe; Jiang, Wenyu; Si, Chuanfei; Pan, Genxing; Zhu, Jianguo

2018-04-01

Leaf photosynthesis of crops acclimates to elevated CO 2 and temperature, but studies quantifying responses of leaf photosynthetic parameters to combined CO 2 and temperature increases under field conditions are scarce. We measured leaf photosynthesis of rice cultivars Changyou 5 and Nanjing 9108 grown in two free-air CO 2 enrichment (FACE) systems, respectively, installed in paddy fields. Each FACE system had four combinations of two levels of CO 2 (ambient and enriched) and two levels of canopy temperature (no warming and warmed by 1.0-2.0°C). Parameters of the C 3 photosynthesis model of Farquhar, von Caemmerer and Berry (the FvCB model), and of a stomatal conductance (g s ) model were estimated for the four conditions. Most photosynthetic parameters acclimated to elevated CO 2 , elevated temperature, and their combination. The combination of elevated CO 2 and temperature changed the functional relationships between biochemical parameters and leaf nitrogen content for Changyou 5. The g s model significantly underestimated g s under the combination of elevated CO 2 and temperature by 19% for Changyou 5 and by 10% for Nanjing 9108 if no acclimation was assumed. However, our further analysis applying the coupled g s -FvCB model to an independent, previously published FACE experiment showed that including such an acclimation response of g s hardly improved prediction of leaf photosynthesis under the four combinations of CO 2 and temperature. Therefore, the typical procedure that crop models using the FvCB and g s models are parameterized from plants grown under current ambient conditions may not result in critical errors in projecting productivity of paddy rice under future global change. © 2017 John Wiley & Sons Ltd.

Numerical modeling of oil shale fragmentation experiments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kuszmaul, J.S.

The economic development of modified in situ oil shale retorting will benefit from the ability to design a blasting scheme that creates a rubble bed of uniform permeability. Preparing such a design depends upon successfully predicting how a given explosive charge and firing sequence will fracture the oil shale. Numerical models are used to predict the extent of damage caused by a particular explosive charge. Recent single-blastwell cratering tests provided experimental measurements of the extent of damage induced by an explosion. Measuring rock damage involved crater excavation, rubble screening, crater elevation surveys, and posttest extraction of cores. These measurements weremore » compared to the damage calculated by the numerical model. Core analyses showed that the damage varied greatly from layer to layer. The numerical results also show this effect, indicating that rock damage is highly dependent on oil shale grade. The computer simulation also calculated particle velocities and dynamic stress amplitudes in the rock; predicted values agree with experimental measurements. Calculated rock fragmentation compared favorably with fragmentation measured by crater excavation and by core analysis. Because coring provides direct inspection of rock fragmentation, the use of posttest coring in future experiments is recommended.« less

Assessment of Mars Pathfinder landing site predictions

USGS Publications Warehouse

Golombek, M.P.; Moore, H.J.; Haldemann, A.F.C.; Parker, T.J.; Schofield, J.T.

1999-01-01

Remote sensing data at scales of kilometers and an Earth analog were used to accurately predict the characteristics of the Mars Pathfinder landing site at a scale of meters. The surface surrounding the Mars Pathfinder lander in Ares Vallis appears consistent with orbital interpretations, namely, that it would be a rocky plain composed of materials deposited by catastrophic floods. The surface and observed maximum clast size appears similar to predictions based on an analogous surface of the Ephrata Fan in the Channeled Scabland of Washington state. The elevation of the site measured by relatively small footprint delay-Doppler radar is within 100 m of that determined by two-way ranging and Doppler tracking of the spacecraft. The nearly equal elevations of the Mars Pathfinder and Viking Lander 1 sites allowed a prediction of the atmospheric conditions with altitude (pressure, temperature, and winds) that were well within the entry, descent, and landing design margins. High-resolution (~38 m/pixel) Viking Orbiter 1 images showed a sparsely cratered surface with small knobs with relatively low slopes, consistent with observations of these features from the lander. Measured rock abundance is within 10% of that expected from Viking orbiter thermal observations and models. The fractional area covered by large, potentially hazardous rocks observed is similar to that estimated from model rock distributions based on data from the Viking landing sites, Earth analog sites, and total rock abundance. The bulk and fine-component thermal inertias measured from orbit are similar to those calculated from the observed rock size-frequency distribution. A simple radar echo model based on the reflectivity of the soil (estimated from its bulk density), and the measured fraction of area covered by rocks was used to approximate the quasi-specular and diffuse components of the Earth-based radar echos. Color and albedo orbiter data were used to predict the relatively dust free or unweathered surface around the Pathfinder lander compared to the Viking landing sites. Comparisons with the experiences of selecting the Viking landing sites demonstrate the enormous benefit the Viking data and its analyses and models had on the successful predictions of the Pathfinder site. The Pathfinder experience demonstrates that, in certain locations, geologic processes observed in orbiter data can be used to infer surface characteristics where those processes dominate over other processes affecting the Martian surface layer. Copyright 1999 by the American Geophysical Union.

Temperature elevation in the fetus from electromagnetic exposure during magnetic resonance imaging

NASA Astrophysics Data System (ADS)

Kikuchi, Satoru; Saito, Kazuyuki; Takahashi, Masaharu; Ito, Koichi

2010-04-01

This study computationally assessed the temperature elevations due to electromagnetic wave energy deposition during magnetic resonance imaging in non-pregnant and pregnant woman models. We used a thermal model with thermoregulatory response of the human body for our calculations. We also considered the effect of blood temperature variation on body core temperature. In a thermal equilibrium state, the temperature elevations in the intrinsic tissues of the woman and fetal tissues were 0.85 and 0.61 °C, respectively, at a whole-body averaged specific absorption rate of 2.0 W kg-1, which is the restriction value of the International Electrotechnical Commission for the normal operating mode. As predicted, these values are below the temperature elevation of 1.5 °C that is expected to be teratogenic. However, these values exceeded the recommended temperature elevation limit of 0.5 °C by the International Commission on Non-Ionizing Radiation Protection. We also assessed the irradiation time required for a temperature elevation of 0.5 °C at the aforementioned specific absorption rate. As a result, the calculated irradiation time was 40 min.

Near-surface temperature lapse rates in a mountainous catchment in the Chilean Andes

NASA Astrophysics Data System (ADS)

Ayala; Schauwecker, S.; Pellicciotti, F.; McPhee, J. P.

2011-12-01

In mountainous areas, and in the Chilean Andes in particular, the irregular and sparse distribution of recording stations resolves insufficiently the variability of climatic factors such as precipitation, temperature and relative humidity. Assumptions about air temperature variability in space and time have a strong effect on the performance of hydrologic models that represent snow processes such as accumulation and ablation. These processes have large diurnal variations, and assumptions that average over longer time periods (days, weeks or months) may reduce the predictive capacity of these models under different climatic conditions from those for which they were calibrated. They also introduce large uncertainties when such models are used to predict processes with strong subdiurnal variability such as snowmelt dynamics. In many applications and modeling exercises, temperature is assumed to decrease linearly with elevation, using the free-air moist adiabatic lapse rate (MALR: 0.0065°C/m). Little evidence is provided for this assumption, however, and recent studies have shown that use of lapse rates that are uniform in space and constant in time is not appropriate. To explore the validity of this approach, near-surface (2 m) lapse rates were calculated and analyzed at different temporal resolution, based on a new data set of spatially distributed temperature sensors setup in a high elevation catchment of the dry Andes of Central Chile (approx. 33°S). Five minutes temperature data were collected between January 2011 and April 2011 in the Ojos de Agua catchment, using two Automatic Weather Stations (AWSs) and 13 T-loggers (Hobo H8 Pro Temp with external data logger), ranging in altitude from 2230 to 3590 m.s.l.. The entire catchment was snow free during our experiment. We use this unique data set to understand the main controls over temperature variability in time and space, and test whether lapse rates can be used to describe the spatial variations of air temperature in a high elevation catchment. Our main result is that the assumption of a MALR is appropriate to describe the average variability of temperature over the entire measurement period (and possibly for daily scales), but that hourly near-surface lapse rates vary considerably and can deviate strongly from the MALR. This diurnal variability in lapse rates is associated with changes in wind direction and variations in wind velocity. Shallow lapse rates, in particular, occur during the morning, in correspondence to low wind speeds and change in wind direction from katabatic wind to valley wind and are associated with a weaker correlation between air temperature and elevation, while steeper lapse rates (meaning by this that temperature decreases more with elevation) closer to the MALR are typical of the afternoon hours from 13.00 on (and correspond to high wind speed), and are representative of a more linear dependency between air temperature and elevation. The steepest LRs, however, occur in the evening at 20.00-21.00, when wind velocity drops again and wind direction changes from valley wind to katabatic wind. It is clear that the wind regime is the main controls on LRs variability, and it is important to validate these findings with data sets from a second season.

ECG Criteria to Differentiate Between Takotsubo (Stress) Cardiomyopathy and Myocardial Infarction.

PubMed

Frangieh, Antonio H; Obeid, Slayman; Ghadri, Jelena-Rima; Imori, Yoichi; D'Ascenzo, Fabrizio; Kovac, Marc; Ruschitzka, Frank; Lüscher, Thomas F; Duru, Firat; Templin, Christian

2016-06-13

ECG criteria differentiating Takotsubo cardiomyopathy (TTC) from mainly anterior myocardial infarction (MI) have been suggested; however, this was in small patient populations. Twelve-lead admission ECGs of consecutive 200 TTC and 200 MI patients were compared in dichotomized groups based on the presence or absence of ST-elevation MI (STEMI versus STE-TTC and non-ST elevation MI versus non ST-elevation-TTC). When comparing STEMI and STE-TTC, ST-elevation in -aVR was characteristic of STE-TTC with a sensitivity/specificity of 43% and 95%, positive predictive value (PPV) 91%, and a negative predictive value (NPV) 62% (P<0.001); when ST-elevation in -aVR is accompanied by ST-elevation in inferior leads, sensitivity/specificity were 14% and 98% (PPV was 89% and NPV 52%) (P=0.001), and 12% and 100% when associated with ST-elevation in anteroseptal leads (PPV 100%, NPV 52%) (P<0.001). On the other hand, STEMI was characterized by ST-elevation in aVR (sensitivity/specificity of 31% and 95% P<0.001, PPV 85% and NPV 59%) and ST-depression in V2-V3-V4 (sensitivity/specificity of 24% and 100% P<0.001, PPV 100% and NPV 76%). When comparing non-ST elevation MI and non ST-elevation-TTC, T-inversion in leads I-aVL-V5-V6 had a sensitivity/specificity of 17% and 97% for non ST-elevation-TTC (PPV 83% and NPV 55%) (P<0.001), and ST-elevation in -aVR with T-inversion in any lead was also specific for non ST-elevation-TTC (sensitivity/specificity of 8% and 100%, PPV 100% and NPV 53%) (P=0.006). In non-ST elevation MI patients, the presence of ST-depression in V2-V3 was specific (sensitivity/specificity of 11% and 99%, PPV 91% and NPV 51%) (P=0.01). ECG on admission can differentiate between TTC and acute MI, with high specificity and positive predictive value. URL: https://www.clinicaltrials.gov/. Unique identifier: NCT01947621. © 2016 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

Different effort constructs and effort-reward imbalance: effects on employee well-being in ancillary health care workers.

PubMed

van Vegchel, N; de Jonge, J; Meijer, T; Hamers, J P

2001-04-01

The present study investigates the relationship between Effort-Reward Imbalance (ERI) and employee well-being, using three different concepts of efforts (i.e. psychological demands, physical demands and emotional demands). The ERI model had been used as a theoretical framework, indicating that work stress is related to high efforts (i.e. job demands) and low occupational rewards (e.g. money, esteem and security/career opportunities). The ERI model also predicts that, in overcommitted workers, effects of ERI on employee well-being are stronger compared with their less committed counterparts. A cross-sectional survey among 167 ancillary health care workers of two nursing homes was conducted. Multiple univariate logistic regression analyses were used to test the relationship between ERI and employee well-being. Results of the logistic regression analyses showed that employees with both high (psychological, physical and emotional) efforts and low rewards had higher risks of psychosomatic health complaints, physical health symptoms and job dissatisfaction (odds ratios (ORs) ranged from 5.09 to 18.55). Moreover, employees who reported both high efforts and high rewards had elevated risks of physical symptoms and exhaustion (ORs ranged from 6.17 to 9.39). No support was found for the hypothesis on the moderating effect of overcommitment. Results show some support for the ERI model; ancillary health care workers with high effort/low reward imbalance had elevated risks of poor employee well-being. In addition, results show that the combination of high efforts and high rewards is important for employee well-being. Finally, some practical implications are discussed to combat work stress in health care work.

Airborne observations reveal elevational gradient in tropical forest isoprene emissions.

PubMed

Gu, Dasa; Guenther, Alex B; Shilling, John E; Yu, Haofei; Huang, Maoyi; Zhao, Chun; Yang, Qing; Martin, Scot T; Artaxo, Paulo; Kim, Saewung; Seco, Roger; Stavrakou, Trissevgeni; Longo, Karla M; Tóta, Julio; de Souza, Rodrigo Augusto Ferreira; Vega, Oscar; Liu, Ying; Shrivastava, Manish; Alves, Eliane G; Santos, Fernando C; Leng, Guoyong; Hu, Zhiyuan

2017-05-23

Isoprene dominates global non-methane volatile organic compound emissions, and impacts tropospheric chemistry by influencing oxidants and aerosols. Isoprene emission rates vary over several orders of magnitude for different plants, and characterizing this immense biological chemodiversity is a challenge for estimating isoprene emission from tropical forests. Here we present the isoprene emission estimates from aircraft eddy covariance measurements over the Amazonian forest. We report isoprene emission rates that are three times higher than satellite top-down estimates and 35% higher than model predictions. The results reveal strong correlations between observed isoprene emission rates and terrain elevations, which are confirmed by similar correlations between satellite-derived isoprene emissions and terrain elevations. We propose that the elevational gradient in the Amazonian forest isoprene emission capacity is determined by plant species distributions and can substantially explain isoprene emission variability in tropical forests, and use a model to demonstrate the resulting impacts on regional air quality.

Using Imaging Spectrometry measurements of Ecosystem Composition to constrain Regional Predictions of Carbon, Water and Energy Fluxes

NASA Astrophysics Data System (ADS)

Anderson, C.; Bond-Lamberty, B. P.; Huang, M.; Xu, Y.; Stegen, J.

2016-12-01

Ecosystem composition is a key attribute of terrestrial ecosystems, influencing the fluxes of carbon, water, and energy between the land surface and the atmosphere. The description of current ecosystem composition has traditionally come from relatively few ground-based inventories of the plant canopy, but are spatially limited and do not provide a comprehensive picture of ecosystem composition at regional or global scales. In this analysis, imaging spectrometry measurements, collected as part of the HyspIRI Preparatory Mission, are used to provide spatially-resolved estimates of plant functional type composition providing an important constraint on terrestrial biosphere model predictions of carbon, water and energy fluxes across the heterogeneous landscapes of the Californian Sierras. These landscapes include oak savannas, mid-elevation mixed pines, fir-cedar forests, and high elevation pines. Our results show that imaging spectrometry measurements can be successfully used to estimate regional-scale variation in ecosystem composition and resulting spatial heterogeneity in patterns of carbon, water and energy fluxes and ecosystem dynamics. Simulations at four flux tower sites within the study region yield patterns of seasonal and inter-annual variation in carbon and water fluxes that have comparable accuracy to simulations initialized from ground-based inventory measurements. Finally, results indicate that during the 2012-2015 Californian drought, regional net carbon fluxes fell by 84%, evaporation and transpiration fluxes fell by 53% and 33% respectively, and sensible heat increase by 51%. This study provides a framework for assimilating near-future global satellite imagery estimates of ecosystem composition with terrestrial biosphere models, constraining and improving their predictions of large-scale ecosystem dynamics and functioning.

Using Imaging Spectrometry measurements of Ecosystem Composition to constrain Regional Predictions of Carbon, Water and Energy Fluxes

NASA Astrophysics Data System (ADS)

Antonarakis, A. S.; Bogan, S.; Moorcroft, P. R.

2017-12-01

Ecosystem composition is a key attribute of terrestrial ecosystems, influencing the fluxes of carbon, water, and energy between the land surface and the atmosphere. The description of current ecosystem composition has traditionally come from relatively few ground-based inventories of the plant canopy, but are spatially limited and do not provide a comprehensive picture of ecosystem composition at regional or global scales. In this analysis, imaging spectrometry measurements, collected as part of the HyspIRI Preparatory Mission, are used to provide spatially-resolved estimates of plant functional type composition providing an important constraint on terrestrial biosphere model predictions of carbon, water and energy fluxes across the heterogeneous landscapes of the Californian Sierras. These landscapes include oak savannas, mid-elevation mixed pines, fir-cedar forests, and high elevation pines. Our results show that imaging spectrometry measurements can be successfully used to estimate regional-scale variation in ecosystem composition and resulting spatial heterogeneity in patterns of carbon, water and energy fluxes and ecosystem dynamics. Simulations at four flux tower sites within the study region yield patterns of seasonal and inter-annual variation in carbon and water fluxes that have comparable accuracy to simulations initialized from ground-based inventory measurements. Finally, results indicate that during the 2012-2015 Californian drought, regional net carbon fluxes fell by 84%, evaporation and transpiration fluxes fell by 53% and 33% respectively, and sensible heat increase by 51%. This study provides a framework for assimilating near-future global satellite imagery estimates of ecosystem composition with terrestrial biosphere models, constraining and improving their predictions of large-scale ecosystem dynamics and functioning.

Utility of Immature Granulocyte Percentage in Pediatric Appendicitis

PubMed Central

Mathews, Eleanor K.; Griffin, Russell L.; Mortellaro, Vincent; Beierle, Elizabeth A.; Harmon, Carroll M.; Chen, Mike K.; Russell, Robert T.

2014-01-01

Background Acute appendicitis is the most common cause of abdominal surgery in children. Adjuncts are utilized to help clinicians predict acute or perforated appendicitis, which may affect treatment decisions. Automated hematologic analyzers can perform more accurate automated differentials including immature granulocyte percentages (IG%). Elevated IG% has demonstrated improved accuracy for predicting sepsis in the neonatal population than traditional immature to total neutrophil count (I/T) ratios. We intended to assess the additional discriminatory ability of IG% to traditionally assessed parameters in the differentiation between acute and perforated appendicitis. Materials and Methods We identified all patients with appendicitis from July 2012 to June 2013 by ICD-9 code. Charts were reviewed for relevant demographic, clinical, and outcome data, which were compared between acute and perforated appendicitis groups using Fischer’s exact and t-test for categorical and continuous variables, respectively. We utilized an adjusted logistic regression model utilizing clinical lab values to predict the odds of perforated appendicitis. Results 251 patients were included in the analysis. Those with perforated appendicitis had a higher white blood cell (WBC) count (p=0.0063), C-reactive protein (CRP) (p<0.0001), and IG% (p=0.0299). In the adjusted model, only elevated CRP (OR 3.46, 95% CI 1.40-8.54) and presence of left shift (OR 2.66, 95% CI 1.09-6.46) were significant predictors of perforated appendicitis. The c-statistic of the final model was 0.70, suggesting fair discriminatory ability in predicting perforated appendicitis. Conclusions IG% did not provide any additional benefit to elevated CRP and presence of left shift in the differentiation between acute and perforated appendicitis. PMID:24793450

Predicting the persistence of coastal wetlands to global change stressors

USGS Publications Warehouse

Guntenspergen, G.; McKee, K.; Cahoon, D.; Grace, J.; Megonigal, P.

2006-01-01

Despite progress toward understanding the response of coastal wetlands to increases in relative sea-level rise and an improved understanding of the effect of elevated CO2 on plant species allocation patterns, we are limited in our ability to predict the response of coastal wetlands to the effects associated with global change. Static simulations of the response of coastal wetlands to sea-level rise using LIDAR and GIS lack the biological and physical feedback mechanisms present in such systems. Evidence from current research suggests that biotic processes are likely to have a major influence on marsh vulnerability to future accelerated rates of sea-level rise and the influence of biotic processes likely varies depending on hydrogeomorphic setting and external stressors. We have initiated a new research approach using a series of controlled mesocosm and field experiments, landscape scale studies, a comparative network of brackish coastal wetland monitoring sites and a suite of predictive models that address critical questions regarding the vulnerability of coastal brackish wetland systems to global change. Specifically, this research project evaluates the interaction of sea level rise and elevated CO2 concentrations with flooding, nutrient enrichment and disturbance effects. The study is organized in a hierarchical structure that links mesocosm, field, landscape and biogeographic levels so as to provide important new information that recognizes that coastal wetland systems respond to multiple interacting drivers and feedback effects controlling wetland surface elevation, habitat stability and ecosystem function. We also present a new statistical modelling technique (Structural Equation Modelling) that synthesizes and integrates our environmental and biotic measures in a predictive framework that forecasts ecosystem change and informs managers to consider adaptive shifts in strategies for the sustainable management of coastal wetlands.

A model for the plastic flow of landslides

USGS Publications Warehouse

Savage, William Z.; Smith, William K.

1986-01-01

To further the understanding of the mechanics of landslide flow, we present a model that predicts many of the observed attributes of landslides. The model is based on an integration of the hyperbolic differential equations for stress and velocity fields in a two-dimensional, inclined, semi-infinite half-space of Coulomb plastic material under elevated pore pressure and gravity. Our landslide model predicts commonly observed features. For example, compressive (passive), plug, or extending (active) flow will occur under appropriate longitudinal strain rates. Also, the model predicts that longitudinal stresses increase elliptically with depth to the basal slide plane, and that stress and velocity characteristics, surfaces along which discontinuities in stress and velocity are propagated, are coincident. Finally, the model shows how thrust and normal faults develop at the landslide surface in compressive and extending flow.

Statistical modeling of landslide hazard using GIS

Treesearch

Peter V. Gorsevski; Randy B. Foltz; Paul E. Gessler; Terrance W. Cundy

2001-01-01

A model for spatial prediction of landslide hazard was applied to a watershed affected by landslide events that occurred during the winter of 1995-96, following heavy rains, and snowmelt. Digital elevation data with 22.86 m x 22.86 m resolution was used for deriving topographic attributes used for modeling. The model is based on the combination of logistic regression...

The integration of geophysical and enhanced Moderate Resolution Imaging Spectroradiometer Normalized Difference Vegetation Index data into a rule-based, piecewise regression-tree model to estimate cheatgrass beginning of spring growth

USGS Publications Warehouse

Boyte, Stephen P.; Wylie, Bruce K.; Major, Donald J.; Brown, Jesslyn F.

2015-01-01

Cheatgrass exhibits spatial and temporal phenological variability across the Great Basin as described by ecological models formed using remote sensing and other spatial data-sets. We developed a rule-based, piecewise regression-tree model trained on 99 points that used three data-sets – latitude, elevation, and start of season time based on remote sensing input data – to estimate cheatgrass beginning of spring growth (BOSG) in the northern Great Basin. The model was then applied to map the location and timing of cheatgrass spring growth for the entire area. The model was strong (R2 = 0.85) and predicted an average cheatgrass BOSG across the study area of 29 March–4 April. Of early cheatgrass BOSG areas, 65% occurred at elevations below 1452 m. The highest proportion of cheatgrass BOSG occurred between mid-April and late May. Predicted cheatgrass BOSG in this study matched well with previous Great Basin cheatgrass green-up studies.

Thermal constraints to the sporogonic development and altitudinal distribution of avian malaria Plasmodium relictum in Hawai'i.

PubMed

LaPointe, Dennis A; Goff, M Lee; Atkinson, Carter T

2010-04-01

More than half of the Hawaiian honeycreepers (Drepanidinae) known from historical records are now extinct. Introduced mosquito-borne disease, in particular the avian malaria Plasmodium relictum , has been incriminated as a leading cause of extinction during the 20th century and a major limiting factor in the recovery of remaining species populations. Today, most native Hawaiian bird species reach their highest densities and diversity in high elevation (>1,800 m above sea level) forests. We determined the thermal requirements for sporogonic development of P. relictum in the natural vector, Culex quinquefasciatus , and assessed the current distribution of native bird species in light of this information. Sporogonic development was completed at constant laboratory and mean field temperatures between 30 and 17 C, but development, prevalence, and intensity decreased significantly below 21 C. Using a degree-day (DD) model, we estimated a minimum threshold temperature of 12.97 C and a thermal requirement of 86.2 DD as necessary to complete development. Predicted (adiabatic lapse-rate) and observed summer threshold isotherm (13 C) correspond to the elevation of high forest refuges on the islands of Maui and Hawai'i. Our data support the hypothesis that avian malaria currently restricts the altitudinal distribution of Hawaiian honeycreeper populations and provide an ecological explanation for the absence of disease at high elevation.

Flood-hazard mapping in Honduras in response to Hurricane Mitch

USGS Publications Warehouse

Mastin, M.C.

2002-01-01

The devastation in Honduras due to flooding from Hurricane Mitch in 1998 prompted the U.S. Agency for International Development, through the U.S. Geological Survey, to develop a country-wide systematic approach of flood-hazard mapping and a demonstration of the method at selected sites as part of a reconstruction effort. The design discharge chosen for flood-hazard mapping was the flood with an average return interval of 50 years, and this selection was based on discussions with the U.S. Agency for International Development and the Honduran Public Works and Transportation Ministry. A regression equation for estimating the 50-year flood discharge using drainage area and annual precipitation as the explanatory variables was developed, based on data from 34 long-term gaging sites. This equation, which has a standard error of prediction of 71.3 percent, was used in a geographic information system to estimate the 50-year flood discharge at any location for any river in the country. The flood-hazard mapping method was demonstrated at 15 selected municipalities. High-resolution digital-elevation models of the floodplain were obtained using an airborne laser-terrain mapping system. Field verification of the digital elevation models showed that the digital-elevation models had mean absolute errors ranging from -0.57 to 0.14 meter in the vertical dimension. From these models, water-surface elevation cross sections were obtained and used in a numerical, one-dimensional, steady-flow stepbackwater model to estimate water-surface profiles corresponding to the 50-year flood discharge. From these water-surface profiles, maps of area and depth of inundation were created at the 13 of the 15 selected municipalities. At La Lima only, the area and depth of inundation of the channel capacity in the city was mapped. At Santa Rose de Aguan, no numerical model was created. The 50-year flood and the maps of area and depth of inundation are based on the estimated 50-year storm tide.

Declines in low-elevation subalpine tree populations outpace growth in high-elevation populations with warming

DOE PAGES

Conlisk, Erin; Castanha, Cristina; Germino, Matthew J.; ...

2017-02-08

Species distribution shifts in response to climate change require that recruitment increase beyond current range boundaries. For trees with long life spans, the importance of climate-sensitive seedling establishment to the pace of range shifts has not been demonstrated quantitatively. Using spatially explicit, stochastic population models combined with data from long-term forest surveys, we explored whether the climate-sensitivity of recruitment observed in climate manipulation experiments was sufficient to alter populations and elevation ranges of two widely distributed, high-elevation North American conifers. Empirically observed, warming-driven declines in recruitment led to rapid modelled population declines at the low-elevation, ‘warm edge’ of subalpine forestmore » and slow emergence of populations beyond the high-elevation, ‘cool edge’. Because population declines in the forest occurred much faster than population emergence in the alpine, we observed range contraction for both species. For Engelmann spruce, this contraction was permanent over the modelled time horizon, even in the presence of increased moisture. For limber pine, lower sensitivity to warming may facilitate persistence at low elevations – especially in the presence of increased moisture – and rapid establishment above tree line, and, ultimately, expansion into the alpine. Synthesis. Assuming 21st century warming and no additional moisture, population dynamics in high-elevation forests led to transient range contractions for limber pine and potentially permanent range contractions for Engelmann spruce. Thus, limitations to seedling recruitment with warming can constrain the pace of subalpine tree range shifts.« less

Declines in low-elevation subalpine tree populations outpace growth in high-elevation populations with warming

DOE Office of Scientific and Technical Information (OSTI.GOV)

Conlisk, Erin; Castanha, Cristina; Germino, Matthew J.

Species distribution shifts in response to climate change require that recruitment increase beyond current range boundaries. For trees with long life spans, the importance of climate-sensitive seedling establishment to the pace of range shifts has not been demonstrated quantitatively. Using spatially explicit, stochastic population models combined with data from long-term forest surveys, we explored whether the climate-sensitivity of recruitment observed in climate manipulation experiments was sufficient to alter populations and elevation ranges of two widely distributed, high-elevation North American conifers. Empirically observed, warming-driven declines in recruitment led to rapid modelled population declines at the low-elevation, ‘warm edge’ of subalpine forestmore » and slow emergence of populations beyond the high-elevation, ‘cool edge’. Because population declines in the forest occurred much faster than population emergence in the alpine, we observed range contraction for both species. For Engelmann spruce, this contraction was permanent over the modelled time horizon, even in the presence of increased moisture. For limber pine, lower sensitivity to warming may facilitate persistence at low elevations – especially in the presence of increased moisture – and rapid establishment above tree line, and, ultimately, expansion into the alpine. Synthesis. Assuming 21st century warming and no additional moisture, population dynamics in high-elevation forests led to transient range contractions for limber pine and potentially permanent range contractions for Engelmann spruce. Thus, limitations to seedling recruitment with warming can constrain the pace of subalpine tree range shifts.« less

Declines in low-elevation subalpine tree populations outpace growth in high-elevation populations with warming

USGS Publications Warehouse

Conlisk, Erin; Castanha, Cristina; Germino, Matthew J.; Veblen, Thomas T; Smith, Jeremy M.; Kueppers, Lara M.

2017-01-01

Species distribution shifts in response to climate change require that recruitment increase beyond current range boundaries. For trees with long life spans, the importance of climate-sensitive seedling establishment to the pace of range shifts has not been demonstrated quantitatively.Using spatially explicit, stochastic population models combined with data from long-term forest surveys, we explored whether the climate-sensitivity of recruitment observed in climate manipulation experiments was sufficient to alter populations and elevation ranges of two widely distributed, high-elevation North American conifers.Empirically observed, warming-driven declines in recruitment led to rapid modelled population declines at the low-elevation, ‘warm edge’ of subalpine forest and slow emergence of populations beyond the high-elevation, ‘cool edge’. Because population declines in the forest occurred much faster than population emergence in the alpine, we observed range contraction for both species. For Engelmann spruce, this contraction was permanent over the modelled time horizon, even in the presence of increased moisture. For limber pine, lower sensitivity to warming may facilitate persistence at low elevations – especially in the presence of increased moisture – and rapid establishment above tree line, and, ultimately, expansion into the alpine.Synthesis. Assuming 21st century warming and no additional moisture, population dynamics in high-elevation forests led to transient range contractions for limber pine and potentially permanent range contractions for Engelmann spruce. Thus, limitations to seedling recruitment with warming can constrain the pace of subalpine tree range shifts.

Waist circumference and the metabolic syndrome predict the development of elevated albuminuria in non-diabetic subjects: the DESIR Study.

PubMed

Bonnet, Fabrice; Marre, Michel; Halimi, Jean-Michel; Stengel, Bénédicte; Lange, Céline; Laville, Martine; Tichet, Jean; Balkau, Beverley

2006-06-01

Metabolic determinants of microalbuminuria remain poorly understood in non-diabetic individuals and particularly in women. We investigated in both sexes whether an elevated waist circumference (WC) or the presence of the metabolic syndrome (MetS) predict the development of elevated albuminuria at 6 years. We studied 2738 subjects from the DESIR cohort without microalbuminuria or diabetes at baseline and who were followed up for 6 years. At 6 years, 254 individuals [9.3%; 95% confidence interval (CI) 8.2-10.4%] had developed elevated albuminuria (> or = 20 mg/l), which was significantly and positively associated with WC and blood pressure, but not with fasting glucose, lipids or body mass index in either sex. In both sexes, subjects with a high WC or with MetS at baseline were more likely to develop elevated albuminuria at 6 years compared with those with a normal WC or absence of MetS. In multivariate logistic analysis, WC as a continuous variable or a WC of 94 cm or greater for men and a WC greater than 88 cm for women were predictive of the development of elevated albuminuria, after adjusting for age, hypertension, the use of angiotensin-converting enzyme inhibitors, fibrinogen and glycaemia. MetS was a risk factor for elevated albuminuria in men (odds ratio 1.87; 95% CI 1.25-2.81), with differences according to the MetS definition. Abdominal adiposity is related to the development of elevated albuminuria in both sexes, suggesting that the measurement of WC may improve the identification of non-diabetic individuals at risk of developing microalbuminuria and emphasizing the interest of screening for albuminuria among those with MetS.

INFLUENCE OF MATERIAL MODELS ON PREDICTING THE FIRE BEHAVIOR OF STEEL COLUMNS.

PubMed

Choe, Lisa; Zhang, Chao; Luecke, William E; Gross, John L; Varma, Amit H

2017-01-01

Finite-element (FE) analysis was used to compare the high-temperature responses of steel columns with two different stress-strain models: the Eurocode 3 model and the model proposed by National Institute of Standards and Technology (NIST). The comparisons were made in three different phases. The first phase compared the critical buckling temperatures predicted using forty seven column data from five different laboratories. The slenderness ratios varied from 34 to 137, and the applied axial load was 20-60 % of the room-temperature capacity. The results showed that the NIST model predicted the buckling temperature as or more accurately than the Eurocode 3 model for four of the five data sets. In the second phase, thirty unique FE models were developed to analyze the W8×35 and W14×53 column specimens with the slenderness ratio about 70. The column specimens were tested under steady-heating conditions with a target temperature in the range of 300-600 °C. The models were developed by combining the material model, temperature distributions in the specimens, and numerical scheme for non-linear analyses. Overall, the models with the NIST material properties and the measured temperature variations showed the results comparable to the test data. The deviations in the results from two different numerical approaches (modified Newton Raphson vs. arc-length) were negligible. The Eurocode 3 model made conservative predictions on the behavior of the column specimens since its retained elastic moduli are smaller than those of the NIST model at elevated temperatures. In the third phase, the column curves calibrated using the NIST model was compared with those prescribed in the ANSI/AISC-360 Appendix 4. The calibrated curve significantly deviated from the current design equation with increasing temperature, especially for the slenderness ratio from 50 to 100.

Landscape-scale consequences of differential tree mortality from catastrophic wind disturbance in the Amazon.

PubMed

Rifai, Sami W; Urquiza Muñoz, José D; Negrón-Juárez, Robinson I; Ramírez Arévalo, Fredy R; Tello-Espinoza, Rodil; Vanderwel, Mark C; Lichstein, Jeremy W; Chambers, Jeffrey Q; Bohlman, Stephanie A

2016-10-01

Wind disturbance can create large forest blowdowns, which greatly reduces live biomass and adds uncertainty to the strength of the Amazon carbon sink. Observational studies from within the central Amazon have quantified blowdown size and estimated total mortality but have not determined which trees are most likely to die from a catastrophic wind disturbance. Also, the impact of spatial dependence upon tree mortality from wind disturbance has seldom been quantified, which is important because wind disturbance often kills clusters of trees due to large treefalls killing surrounding neighbors. We examine (1) the causes of differential mortality between adult trees from a 300-ha blowdown event in the Peruvian region of the northwestern Amazon, (2) how accounting for spatial dependence affects mortality predictions, and (3) how incorporating both differential mortality and spatial dependence affect the landscape level estimation of necromass produced from the blowdown. Standard regression and spatial regression models were used to estimate how stem diameter, wood density, elevation, and a satellite-derived disturbance metric influenced the probability of tree death from the blowdown event. The model parameters regarding tree characteristics, topography, and spatial autocorrelation of the field data were then used to determine the consequences of non-random mortality for landscape production of necromass through a simulation model. Tree mortality was highly non-random within the blowdown, where tree mortality rates were highest for trees that were large, had low wood density, and were located at high elevation. Of the differential mortality models, the non-spatial models overpredicted necromass, whereas the spatial model slightly underpredicted necromass. When parameterized from the same field data, the spatial regression model with differential mortality estimated only 7.5% more dead trees across the entire blowdown than the random mortality model, yet it estimated 51% greater necromass. We suggest that predictions of forest carbon loss from wind disturbance are sensitive to not only the underlying spatial dependence of observations, but also the biological differences between individuals that promote differential levels of mortality. © 2016 by the Ecological Society of America.

High-resolution DEM Effects on Geophysical Flow Models

NASA Astrophysics Data System (ADS)

Williams, M. R.; Bursik, M. I.; Stefanescu, R. E. R.; Patra, A. K.

2014-12-01

Geophysical mass flow models are numerical models that approximate pyroclastic flow events and can be used to assess the volcanic hazards certain areas may face. One such model, TITAN2D, approximates granular-flow physics based on a depth-averaged analytical model using inputs of basal and internal friction, material volume at a coordinate point, and a GIS in the form of a digital elevation model (DEM). The volume of modeled material propagates over the DEM in a way that is governed by the slope and curvature of the DEM surface and the basal and internal friction angles. Results from TITAN2D are highly dependent upon the inputs to the model. Here we focus on a single input: the DEM, which can vary in resolution. High resolution DEMs are advantageous in that they contain more surface details than lower-resolution models, presumably allowing modeled flows to propagate in a way more true to the real surface. However, very high resolution DEMs can create undesirable artifacts in the slope and curvature that corrupt flow calculations. With high-resolution DEMs becoming more widely available and preferable for use, determining the point at which high resolution data is less advantageous compared to lower resolution data becomes important. We find that in cases of high resolution, integer-valued DEMs, very high-resolution is detrimental to good model outputs when moderate-to-low (<10-15°) slope angles are involved. At these slope angles, multiple adjacent DEM cell elevation values are equal due to the need for the DEM to approximate the low slope with a limited set of integer values for elevation. The first derivative of the elevation surface thus becomes zero. In these cases, flow propagation is inhibited by these spurious zero-slope conditions. Here we present evidence for this "terracing effect" from 1) a mathematically defined simulated elevation model, to demonstrate the terracing effects of integer valued data, and 2) a real-world DEM where terracing must be addressed. We discuss the effect on the flow model output and present possible solutions for rectification of the problem.

A new model to predict diffusive self-heating during composting incorporating the reaction engineering approach (REA) framework.

PubMed

Putranto, Aditya; Chen, Xiao Dong

2017-05-01

During composting, self-heating may occur due to the exothermicities of the chemical and biological reactions. An accurate model for predicting maximum temperature is useful in predicting whether the phenomena would occur and to what extent it would have undergone. Elevated temperatures would lead to undesirable situations such as the release of large amount of toxic gases or sometimes would even lead to spontaneous combustion. In this paper, we report a new model for predicting the profiles of temperature, concentration of oxygen, moisture content and concentration of water vapor during composting. The model, which consists of a set of equations of conservation of heat and mass transfer as well as biological heating term, employs the reaction engineering approach (REA) framework to describe the local evaporation/condensation rate quantitatively. A good agreement between the predicted and experimental data of temperature during composting of sewage sludge is observed. The modeling indicates that the maximum temperature is achieved after some 46weeks of composting. Following this period, the temperature decreases in line with a significant decrease in moisture content and a tremendous increase in concentration of water vapor, indicating the massive cooling effect due to water evaporation. The spatial profiles indicate that the maximum temperature is approximately located at the middle-bottom of the compost piles. Towards the upper surface of the piles, the moisture content and concentration of water vapor decreases due to the moisture transfer to the surrounding. The newly proposed model can be used as reliable simulation tool to explore several geometry configurations and operating conditions for avoiding elevated temperature build-up and self-heating during industrial composting. Copyright © 2017 Elsevier Ltd. All rights reserved.

Lead-contaminated imported tamarind candy and children's blood lead levels.

PubMed

Lynch, R A; Boatright, D T; Moss, S K

2000-01-01

In 1999, an investigation implicated tamarind candy as the potential source of lead exposure for a child with a significantly elevated blood lead level (BLL). The Oklahoma City-County Health Department tested two types of tamarind suckers and their packaging for lead content. More than 50% of the tested suckers exceeded the US Food and Drug Administration (FDA) Level of Concern for lead in this type of product. The authors calculated that a child consuming one-quarter to one-half of either of the two types of suckers in a day would exceed the maximum FDA Provis onal Tolerable Intake for lead. High lead concentrations in the two types of wrappers suggested leaching as a potential source of contamination. The authors used the Environmental Protection Agency's Integrated Exposure Uptake Biokinetic (IEUBK) model to predict the effects of consumption of contaminated tamarind suckers on populat on BLLs. The IEUBK model predicted that consumption of either type of sucker at a rate of one per day would result in dramatic increases in mean BLLs for children ages 6-84 months in Oklahoma and in the percentage of children wth elevated BLLs (> or =10 micrograms per deciliter [microg/dL]). The authors conclude that consumption of these products represents a potential public health threat. In addition, a history of lead contamination in imported tamarind products suggests that import control measures may not be completely effective in preventing additional lead exposure.

A High Resolution, Integrated Approach to Modeling Climate Change Impacts to a Mountain Headwaters Catchment using ParFlow

NASA Astrophysics Data System (ADS)

Pribulick, C. E.; Maxwell, R. M.; Williams, K. H.; Carroll, R. W. H.

2014-12-01

Prediction of environmental response to global climate change is paramount for regions that rely upon snowpack for their dominant water supply. Temperature increases are anticipated to be greater at higher elevations perturbing hydrologic systems that provide water to millions of downstream users. In this study, the relationships between large-scale climatic change and the corresponding small-scale hydrologic processes of mountainous terrain are investigated in the East River headwaters catchment near Gothic, CO. This catchment is emblematic of many others within the upper Colorado River Basin and covers an area of 250 square kilometers, has a topographic relief of 1420 meters, an average elevation of 3266 meters and has varying stream characteristics. This site allows for the examination of the varying effect of climate-induced changes on the hydrologic response of three different characteristic components of the catchment: a steep high-energy mountain system, a medium-grade lower-energy system and a low-grade low-energy meandering floodplain. To capture the surface and subsurface heterogeneity of this headwaters system the basin has been modeled at a 10-meter resolution using ParFlow, a parallel, integrated hydrologic model. Driven by meteorological forcing, ParFlow is able to capture land surface processes and represents surface and subsurface interactions through saturated and variably saturated heterogeneous flow. Data from Digital Elevation Models (DEMs), land cover, permeability, geologic and soil maps, and on-site meteorological stations, were prepared, analyzed and input into ParFlow as layers with a grid size comprised of 1403 by 1685 cells to best represent the small-scale, high resolution model domain. Water table depth, soil moisture, soil temperature, snowpack, runoff and local energy budget values provide useful insight into the catchments response to the Intergovernmental Panel on Climate Change (IPCC) temperature projections. In the near term, coupling this watershed model with one describing a diverse suite of subsurface elemental cycling pathways, including carbon and nitrogen, will provide an improved understanding of the response of the subsurface ecosystems to hydrologic transitions induced as a result of global climate change.

Factors influencing U.S. canine heartworm (Dirofilaria immitis) prevalence.

PubMed

Wang, Dongmei; Bowman, Dwight D; Brown, Heidi E; Harrington, Laura C; Kaufman, Phillip E; McKay, Tanja; Nelson, Charles Thomas; Sharp, Julia L; Lund, Robert

2014-06-06

This paper examines the individual factors that influence prevalence rates of canine heartworm in the contiguous United States. A data set provided by the Companion Animal Parasite Council, which contains county-by-county results of over nine million heartworm tests conducted during 2011 and 2012, is analyzed for predictive structure. The goal is to identify the factors that are important in predicting high canine heartworm prevalence rates. The factors considered in this study are those envisioned to impact whether a dog is likely to have heartworm. The factors include climate conditions (annual temperature, precipitation, and relative humidity), socio-economic conditions (population density, household income), local topography (surface water and forestation coverage, elevation), and vector presence (several mosquito species). A baseline heartworm prevalence map is constructed using estimated proportions of positive tests in each county of the United States. A smoothing algorithm is employed to remove localized small-scale variation and highlight large-scale structures of the prevalence rates. Logistic regression is used to identify significant factors for predicting heartworm prevalence. All of the examined factors have power in predicting heartworm prevalence, including median household income, annual temperature, county elevation, and presence of the mosquitoes Aedes trivittatus, Aedes sierrensis and Culex quinquefasciatus. Interactions among factors also exist. The factors identified are significant in predicting heartworm prevalence. The factor list is likely incomplete due to data deficiencies. For example, coyotes and feral dogs are known reservoirs of heartworm infection. Unfortunately, no complete data of their populations were available. The regression model considered is currently being explored to forecast future values of heartworm prevalence.

Factors influencing U.S. canine heartworm (Dirofilaria immitis) prevalence

PubMed Central

2014-01-01

Background This paper examines the individual factors that influence prevalence rates of canine heartworm in the contiguous United States. A data set provided by the Companion Animal Parasite Council, which contains county-by-county results of over nine million heartworm tests conducted during 2011 and 2012, is analyzed for predictive structure. The goal is to identify the factors that are important in predicting high canine heartworm prevalence rates. Methods The factors considered in this study are those envisioned to impact whether a dog is likely to have heartworm. The factors include climate conditions (annual temperature, precipitation, and relative humidity), socio-economic conditions (population density, household income), local topography (surface water and forestation coverage, elevation), and vector presence (several mosquito species). A baseline heartworm prevalence map is constructed using estimated proportions of positive tests in each county of the United States. A smoothing algorithm is employed to remove localized small-scale variation and highlight large-scale structures of the prevalence rates. Logistic regression is used to identify significant factors for predicting heartworm prevalence. Results All of the examined factors have power in predicting heartworm prevalence, including median household income, annual temperature, county elevation, and presence of the mosquitoes Aedes trivittatus, Aedes sierrensis and Culex quinquefasciatus. Interactions among factors also exist. Conclusions The factors identified are significant in predicting heartworm prevalence. The factor list is likely incomplete due to data deficiencies. For example, coyotes and feral dogs are known reservoirs of heartworm infection. Unfortunately, no complete data of their populations were available. The regression model considered is currently being explored to forecast future values of heartworm prevalence. PMID:24906567

Topobathymetric elevation model development using a new methodology: Coastal National Elevation Database

USGS Publications Warehouse

Danielson, Jeffrey J.; Poppenga, Sandra K.; Brock, John C.; Evans, Gayla A.; Tyler, Dean; Gesch, Dean B.; Thatcher, Cindy A.; Barras, John

2016-01-01

During the coming decades, coastlines will respond to widely predicted sea-level rise, storm surge, and coastalinundation flooding from disastrous events. Because physical processes in coastal environments are controlled by the geomorphology of over-the-land topography and underwater bathymetry, many applications of geospatial data in coastal environments require detailed knowledge of the near-shore topography and bathymetry. In this paper, an updated methodology used by the U.S. Geological Survey Coastal National Elevation Database (CoNED) Applications Project is presented for developing coastal topobathymetric elevation models (TBDEMs) from multiple topographic data sources with adjacent intertidal topobathymetric and offshore bathymetric sources to generate seamlessly integrated TBDEMs. This repeatable, updatable, and logically consistent methodology assimilates topographic data (land elevation) and bathymetry (water depth) into a seamless coastal elevation model. Within the overarching framework, vertical datum transformations are standardized in a workflow that interweaves spatially consistent interpolation (gridding) techniques with a land/water boundary mask delineation approach. Output gridded raster TBDEMs are stacked into a file storage system of mosaic datasets within an Esri ArcGIS geodatabase for efficient updating while maintaining current and updated spatially referenced metadata. Topobathymetric data provide a required seamless elevation product for several science application studies, such as shoreline delineation, coastal inundation mapping, sediment-transport, sea-level rise, storm surge models, and tsunami impact assessment. These detailed coastal elevation data are critical to depict regions prone to climate change impacts and are essential to planners and managers responsible for mitigating the associated risks and costs to both human communities and ecosystems. The CoNED methodology approach has been used to construct integrated TBDEM models in Mobile Bay, the northern Gulf of Mexico, San Francisco Bay, the Hurricane Sandy region, and southern California.

Discontinuous submarine groundwater discharge in a tidally influenced coastal aquifer

NASA Astrophysics Data System (ADS)

Abarca, E.; Karam, H.; Hemond, H.; Harvey, C. F.

2011-12-01

Ocean forces have a critical impact on the magnitude and temporal evolution of Submarine Groundwater Discharge (SGD). Here, we analyze the groundwater discharge response to changes in the tidal signal at Waquoit Bay, Cape Cod, Massachusetts. We present a conceptual and numerical model that predicts that both fresh and saltwater components of SGD are interrupted by rising tides. During that period, saltwater infiltration pushes freshwater down and landward. Freshwater is stored in the aquifer, increasing the groundwater head, and is released during the receding tide. Discontinuous freshwater discharge occurs during both neap and spring tidal cycles even though the total discharge is higher during a neap tidal cycle. Evidence of this interruption of SGD can be found in geophysical and temperature measurements of the intertidal subsurface zone at Waquoit Bay. The long-term temporal and spatial evolution of fresh and saltwater fluxes shows that freshwater discharge tracks the mean and minimum tide elevation. The intertidal saltwater discharge is controlled by the high tide elevation whereas the deep saltwater discharge increases with falling low tide elevation.

An integrated approach to flood hazard assessment on alluvial fans using numerical modeling, field mapping, and remote sensing

USGS Publications Warehouse

Pelletier, J.D.; Mayer, L.; Pearthree, P.A.; House, P.K.; Demsey, K.A.; Klawon, J.K.; Vincent, K.R.

2005-01-01

Millions of people in the western United States live near the dynamic, distributary channel networks of alluvial fans where flood behavior is complex and poorly constrained. Here we test a new comprehensive approach to alluvial-fan flood hazard assessment that uses four complementary methods: two-dimensional raster-based hydraulic modeling, satellite-image change detection, fieldbased mapping of recent flood inundation, and surficial geologic mapping. Each of these methods provides spatial detail lacking in the standard method and each provides critical information for a comprehensive assessment. Our numerical model simultaneously solves the continuity equation and Manning's equation (Chow, 1959) using an implicit numerical method. It provides a robust numerical tool for predicting flood flows using the large, high-resolution Digital Elevation Models (DEMs) necessary to resolve the numerous small channels on the typical alluvial fan. Inundation extents and flow depths of historic floods can be reconstructed with the numerical model and validated against field- and satellite-based flood maps. A probabilistic flood hazard map can also be constructed by modeling multiple flood events with a range of specified discharges. This map can be used in conjunction with a surficial geologic map to further refine floodplain delineation on fans. To test the accuracy of the numerical model, we compared model predictions of flood inundation and flow depths against field- and satellite-based flood maps for two recent extreme events on the southern Tortolita and Harquahala piedmonts in Arizona. Model predictions match the field- and satellite-based maps closely. Probabilistic flood hazard maps based on the 10 yr, 100 yr, and maximum floods were also constructed for the study areas using stream gage records and paleoflood deposits. The resulting maps predict spatially complex flood hazards that strongly reflect small-scale topography and are consistent with surficial geology. In contrast, FEMA Flood Insurance Rate Maps (FIRMs) based on the FAN model predict uniformly high flood risk across the study areas without regard for small-scale topography and surficial geology. ?? 2005 Geological Society of America.

Prediction of a Therapeutic Dose for Buagafuran, a Potent Anxiolytic Agent by Physiologically Based Pharmacokinetic/Pharmacodynamic Modeling Starting from Pharmacokinetics in Rats and Human.

PubMed

Yang, Fen; Wang, Baolian; Liu, Zhihao; Xia, Xuejun; Wang, Weijun; Yin, Dali; Sheng, Li; Li, Yan

2017-01-01

Physiologically based pharmacokinetic (PBPK)/pharmacodynamic (PD) models can contribute to animal-to-human extrapolation and therapeutic dose predictions. Buagafuran is a novel anxiolytic agent and phase I clinical trials of buagafuran have been completed. In this paper, a potentially effective dose for buagafuran of 30 mg t.i.d. in human was estimated based on the human brain concentration predicted by a PBPK/PD modeling. The software GastroPlus TM was used to build the PBPK/PD model for buagafuran in rat which related the brain tissue concentrations of buagafuran and the times of animals entering the open arms in the pharmacological model of elevated plus-maze. Buagafuran concentrations in human plasma were fitted and brain tissue concentrations were predicted by using a human PBPK model in which the predicted plasma profiles were in good agreement with observations. The results provided supportive data for the rational use of buagafuran in clinic.

Volumetric visualization of multiple-return LIDAR data: Using voxels

USGS Publications Warehouse

Stoker, Jason M.

2009-01-01

Elevation data are an important component in the visualization and analysis of geographic information. The creation and display of 3D models representing bare earth, vegetation, and surface structures have become a major focus of light detection and ranging (lidar) remote sensing research in the past few years. Lidar is an active sensor that records the distance, or range, of a laser usually fi red from an airplane, helicopter, or satellite. By converting the millions of 3D lidar returns from a system into bare ground, vegetation, or structural elevation information, extremely accurate, high-resolution elevation models can be derived and produced to visualize and quantify scenes in three dimensions. These data can be used to produce high-resolution bare-earth digital elevation models; quantitative estimates of vegetative features such as canopy height, canopy closure, and biomass; and models of urban areas such as building footprints and 3D city models.

Investigating Effects of Monsoon Winds on Hydrodynamics in the South China Sea

NASA Astrophysics Data System (ADS)

Chua, V. P.

2013-12-01

The South China Sea is a large marginal sea surrounded by land masses and island chains, and characterized by complex bathymetry and irregular coastlines. The circulation in South China Sea is subjected to seasonal and inter-annual variations of tidal and meteorological conditions. The effects of monsoon winds on hydrodynamics is investigated by applying spectral and harmonic analysis on surface elevation and wind data at stations located in the South China Sea. The analysis indicates varying responses to the seasonal monsoon depending on the location of the station. At Kaohsiung (located in northern South China Sea off Taiwan coast), tides from the Pacific Ocean and the southwest monsoon winds are found to be dominant mechanisms. The Kota Kinabalu and Bintulu stations, located to the east of South China Sea off Borneo coast, are influenced by low energy complex winds, and the shallow bottom bathymetry at these locations leads to tidal energy damping compared to other stations. The tidal dynamics at Tioman, located in southern South China Sea off Malaysia coast, are most responsive to the effects of the northeast monsoon. The complexity of our problem together with the limited amount of available data in the region presents a challenging research topic. An unstructured-grid SUNTANS model is employed to perform three-dimensional simulations of the circulation in South China Sea. Skill assessment of the model is performed by comparing model predictions of the surface elevations and currents with observations. The results suggest that the quality of the model prediction is highly dependent on horizontal grid resolution and coastline accuracy. The model may be used in future applications to investigate seasonal and inter-annual variations in hydrodynamics.

Predictive Models and Computational Toxicology

EPA Science Inventory

Understanding the potential health risks posed by environmental chemicals is a significant challenge elevated by the large number of diverse chemicals with generally uncharacterized exposures, mechanisms, and toxicities. The ToxCast computational toxicology research program was l...

Plant population differentiation and climate change: responses of grassland species along an elevational gradient.

PubMed

Frei, Esther R; Ghazoul, Jaboury; Matter, Philippe; Heggli, Martin; Pluess, Andrea R

2014-02-01

Mountain ecosystems are particularly susceptible to climate change. Characterizing intraspecific variation of alpine plants along elevational gradients is crucial for estimating their vulnerability to predicted changes. Environmental conditions vary with elevation, which might influence plastic responses and affect selection pressures that lead to local adaptation. Thus, local adaptation and phenotypic plasticity among low and high elevation plant populations in response to climate, soil and other factors associated with elevational gradients might underlie different responses of these populations to climate warming. Using a transplant experiment along an elevational gradient, we investigated reproductive phenology, growth and reproduction of the nutrient-poor grassland species Ranunculus bulbosus, Trifolium montanum and Briza media. Seeds were collected from low and high elevation source populations across the Swiss Alps and grown in nine common gardens at three different elevations with two different soil depths. Despite genetic differentiation in some traits, the results revealed no indication of local adaptation to the elevation of population origin. Reproductive phenology was advanced at lower elevation in low and high elevation populations of all three species. Growth and reproduction of T. montanum and B. media were hardly affected by garden elevation and soil depth. In R. bulbosus, however, growth decreased and reproductive investment increased at higher elevation. Furthermore, soil depth influenced growth and reproduction of low elevation R. bulbosus populations. We found no evidence for local adaptation to elevation of origin and hardly any differences in the responses of low and high elevation populations. However, the consistent advanced reproductive phenology observed in all three species shows that they have the potential to plastically respond to environmental variation. We conclude that populations might not be forced to migrate to higher elevations as a consequence of climate warming, as plasticity will buffer the detrimental effects of climate change in the three investigated nutrient-poor grassland species. © 2013 John Wiley & Sons Ltd.

Improving the Spatial Prediction of Soil Organic Carbon Stocks in a Complex Tropical Mountain Landscape by Methodological Specifications in Machine Learning Approaches

PubMed Central

Schmidt, Johannes; Glaser, Bruno

2016-01-01

Tropical forests are significant carbon sinks and their soils’ carbon storage potential is immense. However, little is known about the soil organic carbon (SOC) stocks of tropical mountain areas whose complex soil-landscape and difficult accessibility pose a challenge to spatial analysis. The choice of methodology for spatial prediction is of high importance to improve the expected poor model results in case of low predictor-response correlations. Four aspects were considered to improve model performance in predicting SOC stocks of the organic layer of a tropical mountain forest landscape: Different spatial predictor settings, predictor selection strategies, various machine learning algorithms and model tuning. Five machine learning algorithms: random forests, artificial neural networks, multivariate adaptive regression splines, boosted regression trees and support vector machines were trained and tuned to predict SOC stocks from predictors derived from a digital elevation model and satellite image. Topographical predictors were calculated with a GIS search radius of 45 to 615 m. Finally, three predictor selection strategies were applied to the total set of 236 predictors. All machine learning algorithms—including the model tuning and predictor selection—were compared via five repetitions of a tenfold cross-validation. The boosted regression tree algorithm resulted in the overall best model. SOC stocks ranged between 0.2 to 17.7 kg m-2, displaying a huge variability with diffuse insolation and curvatures of different scale guiding the spatial pattern. Predictor selection and model tuning improved the models’ predictive performance in all five machine learning algorithms. The rather low number of selected predictors favours forward compared to backward selection procedures. Choosing predictors due to their indiviual performance was vanquished by the two procedures which accounted for predictor interaction. PMID:27128736

Evaluation of flood inundation in Crystal Springs Creek, Portland, Oregon

USGS Publications Warehouse

Stonewall, Adam; Hess, Glen

2016-05-25

Efforts to improve fish passage have resulted in the replacement of six culverts in Crystal Springs Creek in Portland, Oregon. Two more culverts are scheduled to be replaced at Glenwood Street and Bybee Boulevard (Glenwood/Bybee project) in 2016. Recently acquired data have allowed for a more comprehensive understanding of the hydrology of the creek and the topography of the watershed. To evaluate the impact of the culvert replacements and recent hydrologic data, a Hydrologic Engineering Center-River Analysis System hydraulic model was developed to estimate water-surface elevations during high-flow events. Longitudinal surface-water profiles were modeled to evaluate current conditions and future conditions using the design plans for the culverts to be installed in 2016. Additional profiles were created to compare with the results from the most recent flood model approved by the Federal Emergency Management Agency for Crystal Springs Creek and to evaluate model sensitivity.Model simulation results show that water-surface elevations during high-flow events will be lower than estimates from previous models, primarily due to lower estimates of streamflow associated with the 0.01 and 0.002 annual exceedance probability (AEP) events. Additionally, recent culvert replacements have resulted in less ponding behind crossings. Similarly, model simulation results show that the proposed replacement culverts at Glenwood Street and Bybee Boulevard will result in lower water-surface elevations during high-flow events upstream of the proposed project. Wider culverts will allow more water to pass through crossings, resulting in slightly higher water-surface elevations downstream of the project during high-flows than water-surface elevations that would occur under current conditions. For the 0.01 AEP event, the water-surface elevations downstream of the Glenwood/Bybee project will be an average of 0.05 ft and a maximum of 0.07 ft higher than current conditions. Similarly, for the 0.002 AEP event, the water-surface elevations will be an average of 0.04 ft and a maximum of 0.19 ft higher than current conditions.

Using High-Resolution Satellite Aerosol Optical Depth To Estimate Daily PM2.5 Geographical Distribution in Mexico City.

PubMed

Just, Allan C; Wright, Robert O; Schwartz, Joel; Coull, Brent A; Baccarelli, Andrea A; Tellez-Rojo, Martha María; Moody, Emily; Wang, Yujie; Lyapustin, Alexei; Kloog, Itai

2015-07-21

Recent advances in estimating fine particle (PM2.5) ambient concentrations use daily satellite measurements of aerosol optical depth (AOD) for spatially and temporally resolved exposure estimates. Mexico City is a dense megacity that differs from other previously modeled regions in several ways: it has bright land surfaces, a distinctive climatological cycle, and an elevated semi-enclosed air basin with a unique planetary boundary layer dynamic. We extend our previous satellite methodology to the Mexico City area, a region with higher PM2.5 than most U.S. and European urban areas. Using a novel 1 km resolution AOD product from the MODIS instrument, we constructed daily predictions across the greater Mexico City area for 2004-2014. We calibrated the association of AOD to PM2.5 daily using municipal ground monitors, land use, and meteorological features. Predictions used spatial and temporal smoothing to estimate AOD when satellite data were missing. Our model performed well, resulting in an out-of-sample cross-validation R(2) of 0.724. Cross-validated root-mean-squared prediction error (RMSPE) of the model was 5.55 μg/m(3). This novel model reconstructs long- and short-term spatially resolved exposure to PM2.5 for epidemiological studies in Mexico City.

Using high-resolution satellite aerosol optical depth to estimate daily PM2.5 geographical distribution in Mexico City

PubMed Central

Just, Allan C.; Wright, Robert O.; Schwartz, Joel; Coull, Brent A.; Baccarelli, Andrea A.; Tellez-Rojo, Martha María; Moody, Emily; Wang, Yujie; Lyapustin, Alexei; Kloog, Itai

2015-01-01

Recent advances in estimating fine particle (PM2.5) ambient concentrations use daily satellite measurements of aerosol optical depth (AOD) for spatially and temporally resolved exposure estimates. Mexico City is a dense megacity that differs from other previously modeled regions in several ways: it has bright land surfaces, a distinctive climatological cycle, and an elevated semi-enclosed air basin with a unique planetary boundary layer dynamic. We extend our previous satellite methodology to the Mexico City area, a region with higher PM2.5 than most US and European urban areas. Using a novel 1 km resolution AOD product from the MODIS instrument, we constructed daily predictions across the greater Mexico City area for 2004–2014. We calibrated the association of AOD to PM2.5 daily using municipal ground monitors, land use, and meteorological features. Predictions used spatial and temporal smoothing to estimate AOD when satellite data were missing. Our model performed well, resulting in an out-of-sample cross validation R2 of 0.724. Cross-validated root mean squared prediction error (RMSPE) of the model was 5.55 μg/m3. This novel model reconstructs long- and short-term spatially resolved exposure to PM2.5 for epidemiological studies in Mexico City. PMID:26061488

Soil respiration patterns and rates at three Taiwanese forest plantations: dependence on elevation, temperature, precipitation, and litterfall.

PubMed

Huang, Yu-Hsuan; Hung, Chih-Yu; Lin, I-Rhy; Kume, Tomonori; Menyailo, Oleg V; Cheng, Chih-Hsin

2017-11-15

Soil respiration contributes to a large quantity of carbon emissions in the forest ecosystem. In this study, the soil respiration rates at three Taiwanese forest plantations (two lowland and one mid-elevation) were investigated. We aimed to determine how soil respiration varies between lowland and mid-elevation forest plantations and identify the relative importance of biotic and abiotic factors affecting soil respiration. The results showed that the temporal patterns of soil respiration rates were mainly influenced by soil temperature and soil water content, and a combined soil temperature and soil water content model explained 54-80% of the variation. However, these two factors affected soil respiration differently. Soil temperature positively contributed to soil respiration, but a bidirectional relationship between soil respiration and soil water content was revealed. Higher soil moisture content resulted in higher soil respiration rates at the lowland plantations but led to adverse effects at the mid-elevation plantation. The annual soil respiration rates were estimated as 14.3-20.0 Mg C ha -1  year -1 at the lowland plantations and 7.0-12.2 Mg C ha -1  year -1 at the mid-elevation plantation. When assembled with the findings of previous studies, the annual soil respiration rates increased with the mean annual temperature and litterfall but decreased with elevation and the mean annual precipitation. A conceptual model of the biotic and abiotic factors affecting the spatial and temporal patterns of the soil respiration rate was developed. Three determinant factors were proposed: (i) elevation, (ii) stand characteristics, and (iii) soil temperature and soil moisture. The results indicated that changes in temperature and precipitation significantly affect soil respiration. Because of the high variability of soil respiration, more studies and data syntheses are required to accurately predict soil respiration in Taiwanese forests.

Prediction of groundwater flowing well zone at An-Najif Province, central Iraq using evidential belief functions model and GIS.

PubMed

Al-Abadi, Alaa M; Pradhan, Biswajeet; Shahid, Shamsuddin

2015-10-01

The objective of this study is to delineate groundwater flowing well zone potential in An-Najif Province of Iraq in a data-driven evidential belief function model developed in a geographical information system (GIS) environment. An inventory map of 68 groundwater flowing wells was prepared through field survey. Seventy percent or 43 wells were used for training the evidential belief functions model and the reset 30 % or 19 wells were used for validation of the model. Seven groundwater conditioning factors mostly derived from RS were used, namely elevation, slope angle, curvature, topographic wetness index, stream power index, lithological units, and distance to the Euphrates River in this study. The relationship between training flowing well locations and the conditioning factors were investigated using evidential belief functions technique in a GIS environment. The integrated belief values were classified into five categories using natural break classification scheme to predict spatial zoning of groundwater flowing well, namely very low (0.17-0.34), low (0.34-0.46), moderate (0.46-0.58), high (0.58-0.80), and very high (0.80-0.99). The results show that very low and low zones cover 72 % (19,282 km(2)) of the study area mostly clustered in the central part, the moderate zone concentrated in the west part covers 13 % (3481 km(2)), and the high and very high zones extended over the northern part cover 15 % (3977 km(2)) of the study area. The vast spatial extension of very low and low zones indicates that groundwater flowing wells potential in the study area is low. The performance of the evidential belief functions spatial model was validated using the receiver operating characteristic curve. A success rate of 0.95 and a prediction rate of 0.94 were estimated from the area under relative operating characteristics curves, which indicate that the developed model has excellent capability to predict groundwater flowing well zones. The produced map of groundwater flowing well zones could be used to identify new wells and manage groundwater storage in a sustainable manner.

SeaTrack: Ground station orbit prediction and planning software for sea-viewing satellites

NASA Technical Reports Server (NTRS)

Lambert, Kenneth S.; Gregg, Watson W.; Hoisington, Charles M.; Patt, Frederick S.

1993-01-01

An orbit prediction software package (Sea Track) was designed to assist High Resolution Picture Transmission (HRPT) stations in the acquisition of direct broadcast data from sea-viewing spacecraft. Such spacecraft will be common in the near future, with the launch of the Sea viewing Wide Field-of-view Sensor (SeaWiFS) in 1994, along with the continued Advanced Very High Resolution Radiometer (AVHRR) series on NOAA platforms. The Brouwer-Lyddane model was chosen for orbit prediction because it meets the needs of HRPT tracking accuracies, provided orbital elements can be obtained frequently (up to within 1 week). Sea Track requires elements from the U.S. Space Command (NORAD Two-Line Elements) for the satellite's initial position. Updated Two-Line Elements are routinely available from many electronic sources (some are listed in the Appendix). Sea Track is a menu-driven program that allows users to alter input and output formats. The propagation period is entered by a start date and end date with times in either Greenwich Mean Time (GMT) or local time. Antenna pointing information is provided in tabular form and includes azimuth/elevation pointing angles, sub-satellite longitude/latitude, acquisition of signal (AOS), loss of signal (LOS), pass orbit number, and other pertinent pointing information. One version of Sea Track (non-graphical) allows operation under DOS (for IBM-compatible personal computers) and UNIX (for Sun and Silicon Graphics workstations). A second, graphical, version displays orbit tracks, and azimuth-elevation for IBM-compatible PC's, but requires a VGA card and Microsoft FORTRAN.

Stream macroinvertebrate response models for bioassessment metrics: addressing the issue of spatial scale

USGS Publications Warehouse

White, Ian R.; Kennen, Jonathan G.; May, Jason T.; Brown, Larry R.; Cuffney, Thomas F.; Jones, Kimberly A.; Orlando, James L.

2014-01-01

We developed independent predictive disturbance models for a full regional data set and four individual ecoregions (Full Region vs. Individual Ecoregion models) to evaluate effects of spatial scale on the assessment of human landscape modification, on predicted response of stream biota, and the effect of other possible confounding factors, such as watershed size and elevation, on model performance. We selected macroinvertebrate sampling sites for model development (n = 591) and validation (n = 467) that met strict screening criteria from four proximal ecoregions in the northeastern U.S.: North Central Appalachians, Ridge and Valley, Northeastern Highlands, and Northern Piedmont. Models were developed using boosted regression tree (BRT) techniques for four macroinvertebrate metrics; results were compared among ecoregions and metrics. Comparing within a region but across the four macroinvertebrate metrics, the average richness of tolerant taxa (RichTOL) had the highest R2 for BRT models. Across the four metrics, final BRT models had between four and seven explanatory variables and always included a variable related to urbanization (e.g., population density, percent urban, or percent manmade channels), and either a measure of hydrologic runoff (e.g., minimum April, average December, or maximum monthly runoff) and(or) a natural landscape factor (e.g., riparian slope, precipitation, and elevation), or a measure of riparian disturbance. Contrary to our expectations, Full Region models explained nearly as much variance in the macroinvertebrate data as Individual Ecoregion models, and taking into account watershed size or elevation did not appear to improve model performance. As a result, it may be advantageous for bioassessment programs to develop large regional models as a preliminary assessment of overall disturbance conditions as long as the range in natural landscape variability is not excessive.

Stream Macroinvertebrate Response Models for Bioassessment Metrics: Addressing the Issue of Spatial Scale

PubMed Central

Waite, Ian R.; Kennen, Jonathan G.; May, Jason T.; Brown, Larry R.; Cuffney, Thomas F.; Jones, Kimberly A.; Orlando, James L.

2014-01-01

We developed independent predictive disturbance models for a full regional data set and four individual ecoregions (Full Region vs. Individual Ecoregion models) to evaluate effects of spatial scale on the assessment of human landscape modification, on predicted response of stream biota, and the effect of other possible confounding factors, such as watershed size and elevation, on model performance. We selected macroinvertebrate sampling sites for model development (n = 591) and validation (n = 467) that met strict screening criteria from four proximal ecoregions in the northeastern U.S.: North Central Appalachians, Ridge and Valley, Northeastern Highlands, and Northern Piedmont. Models were developed using boosted regression tree (BRT) techniques for four macroinvertebrate metrics; results were compared among ecoregions and metrics. Comparing within a region but across the four macroinvertebrate metrics, the average richness of tolerant taxa (RichTOL) had the highest R2 for BRT models. Across the four metrics, final BRT models had between four and seven explanatory variables and always included a variable related to urbanization (e.g., population density, percent urban, or percent manmade channels), and either a measure of hydrologic runoff (e.g., minimum April, average December, or maximum monthly runoff) and(or) a natural landscape factor (e.g., riparian slope, precipitation, and elevation), or a measure of riparian disturbance. Contrary to our expectations, Full Region models explained nearly as much variance in the macroinvertebrate data as Individual Ecoregion models, and taking into account watershed size or elevation did not appear to improve model performance. As a result, it may be advantageous for bioassessment programs to develop large regional models as a preliminary assessment of overall disturbance conditions as long as the range in natural landscape variability is not excessive. PMID:24675770

Spatial analysis and statistical modelling of snow cover dynamics in the Central Himalayas, Nepal

NASA Astrophysics Data System (ADS)

Weidinger, Johannes; Gerlitz, Lars; Böhner, Jürgen

2017-04-01

General circulation models are able to predict large scale climate variations in global dimensions, however small scale dynamic characteristics, such as snow cover and its temporal variations in high mountain regions, are not represented sufficiently. Detailed knowledge about shifts in seasonal ablation times and spatial distribution of snow cover are crucial for various research interests. Since high mountain areas, for instance the Central Himalayas in Nepal, are generally remote, it is difficult to obtain data in high spatio-temporal resolutions. Regional climate models and downscaling techniques are implemented to compensate coarse resolution. Furthermore earth observation systems, such as MODIS, also permit bridging this gap to a certain extent. They offer snow (cover) data in daily temporal and medium spatial resolution of around 500 m, which can be applied as evaluation and training data for dynamical hydrological and statistical analyses. Within this approach two snow distribution models (binary snow cover and fractional snow cover) as well as one snow recession model were implemented for a research domain in the Rolwaling Himal in Nepal, employing the random forest technique, which represents a state of the art machine learning algorithm. Both bottom-up strategies provide inductive reasoning to derive rules for snow related processes out of climate (temperature, precipitation and irradiance) and climate-related topographic data sets (elevation, aspect and convergence index) obtained by meteorological network stations, remote sensing products (snow cover - MOD10-A1 and land surface temperatures - MOD11-A1) along with GIS. Snow distribution is predicted reliably on a daily basis in the research area, whereas further effort is necessary for predicting daily snow cover recession processes adequately. Swift changes induced by clear sky conditions with high insolation rates are well represented, whereas steady snow loss still needs continuing effort. All approaches underline the technical difficulties of snow cover modelling during the monsoon season, in accordance with previous studies. The developed methods in combination with continuous in situ measurements provide a basis for further downscaling approaches.

Analysis and characterization of the vertical wind profile in UAE

NASA Astrophysics Data System (ADS)

Lee, W.; Ghedira, H.; Ouarda, T.; Gherboudj, I.

2011-12-01

In this study, temporal and spatial analysis of the vertical wind profiles in the UAE has been performed to estimate wind resource potential. Due to the very limited number of wind masts (only two wind masts in the UAE, operational for less than three years), the wind potential analysis will be mainly derived from numerical-based models. Additional wind data will be derived from the UAE met stations network (at 10 m elevation) managed by the UAE National Center of Meteorology and Seismology. However, since wind turbines are generally installed at elevations higher than 80 m, it is vital to extrapolate wind speed correctly from low heights to wind turbine hub heights to predict potential wind energy properly. To do so, firstly two boundary layer based models, power law and logarithmic law, were tested to find the best fitting model. Power law is expressed as v/v0 =(H/H0)^α and logarithmic law is represented as v/v0 =[ln(H/Z0))/(ln(H0/Z0)], where V is the wind speed [m/s] at height H [m] and V0 is the known wind speed at a reference height H0. The exponent (α) coefficient is an empirically derived value depending on the atmospheric stability and z0 is the roughness coefficient length [m] that depends on topography, land roughness and spacing. After testing the two models, spatial and temporal analysis for wind profile was performed. Many studies about wind in different regions have shown that wind profile parameters have hourly, monthly and seasonal variations. Therefore, it can be examined whether UAE wind characteristics follow general wind characteristics observed in other regions or have specific wind features due to its regional condition. About 3 years data from August 2008 to February 2011 with 10-minutes resolution were used to derive monthly variation. The preliminary results(Fig.1) show that during that period, wind profile parameters like alpha from power law and roughness length from logarithmic law have monthly variation. Both alpha and roughness have low values during summer and high values during winter. This variation is mainly explained by the direct effect of air temperature on atmospheric stability. When the surface temperature becomes high, air is mixed well in atmospheric boundary layer. This phenomenon leads to vertically low wind speed change indicating low wind profile parameter. On the contrary, cold surface temperature prevents air from being mixed well in the boundary layer. This analysis is applied to different regions to see the spatial characteristics of wind in UAE. As a next step, a mesoscale model coupled with UAE roughness maps will be used to predict elevated wind speed. A micro-scale modeling approach will be also used to capture small-scale wind speed variability. This data will be combined with the NCMS data and tailored to the UAE by modeling the effects due to local changes in terrain elevation and local surface roughness changes and obstacles.

Climate change impacts on high-elevation hydroelectricity in California

NASA Astrophysics Data System (ADS)

Madani, Kaveh; Guégan, Marion; Uvo, Cintia B.

2014-03-01

While only about 30% of California's usable water storage capacity lies at higher elevations, high-elevation (above 300 m) hydropower units generate, on average, 74% of California's in-state hydroelectricity. In general, high-elevation plants have small man-made reservoirs and rely mainly on snowpack. Their low built-in storage capacity is a concern with regard to climate warming. Snowmelt is expected to shift to earlier in the year, and the system may not be able to store sufficient water for release in high-demand periods. Previous studies have explored the climate warming effects on California's high-elevation hydropower by focusing on the supply side (exploring the effects of hydrological changes on generation and revenues) ignoring the warming effects on hydroelectricity demand and pricing. This study extends the previous work by simultaneous consideration of climate change effects on high-elevation hydropower supply and pricing in California. The California's Energy-Based Hydropower Optimization Model (EBHOM 2.0) is applied to evaluate the adaptability of California's high-elevation hydropower system to climate warming, considering the warming effects on hydroelectricity supply and pricing. The model's results relative to energy generation, energy spills, reservoir energy storage, and average shadow prices of energy generation and storage capacity expansion are examined and discussed. These results are compared with previous studies to emphasize the need to consider climate change effects on hydroelectricity demand and pricing when exploring the effects of climate change on hydropower operations.

The influence of coarse-scale environmental features on current and predicted future distributions of narrow-range endemic crayfish populations

USGS Publications Warehouse

Dyer, Joseph J.; Brewer, Shannon K.; Worthington, Thomas A.; Bergey, Elizabeth A.

2013-01-01

1.A major limitation to effective management of narrow-range crayfish populations is the paucity of information on the spatial distribution of crayfish species and a general understanding of the interacting environmental variables that drive current and future potential distributional patterns. 2.Maximum Entropy Species Distribution Modeling Software (MaxEnt) was used to predict the current and future potential distributions of four endemic crayfish species in the Ouachita Mountains. Current distributions were modelled using climate, geology, soils, land use, landform and flow variables thought to be important to lotic crayfish. Potential changes in the distribution were forecast by using models trained on current conditions and projecting onto the landscape predicted under climate-change scenarios. 3.The modelled distribution of the four species closely resembled the perceived distribution of each species but also predicted populations in streams and catchments where they had not previously been collected. Soils, elevation and winter precipitation and temperature most strongly related to current distributions and represented 6587% of the predictive power of the models. Model accuracy was high for all models, and model predictions of new populations were verified through additional field sampling. 4.Current models created using two spatial resolutions (1 and 4.5km2) showed that fine-resolution data more accurately represented current distributions. For three of the four species, the 1-km2 resolution models resulted in more conservative predictions. However, the modelled distributional extent of Orconectes leptogonopodus was similar regardless of data resolution. Field validations indicated 1-km2 resolution models were more accurate than 4.5-km2 resolution models. 5.Future projected (4.5-km2 resolution models) model distributions indicated three of the four endemic species would have truncated ranges with low occurrence probabilities under the low-emission scenario, whereas two of four species would be severely restricted in range under moderatehigh emissions. Discrepancies in the two emission scenarios probably relate to the exclusion of behavioural adaptations from species-distribution models. 6.These model predictions illustrate possible impacts of climate change on narrow-range endemic crayfish populations. The predictions do not account for biotic interactions, migration, local habitat conditions or species adaptation. However, we identified the constraining landscape features acting on these populations that provide a framework for addressing habitat needs at a fine scale and developing targeted and systematic monitoring programmes.