Creative use of pilot points to address site and regional scale heterogeneity in a variable-density model

USGS Publications Warehouse

Dausman, Alyssa M.; Doherty, John; Langevin, Christian D.

2010-01-01

Pilot points for parameter estimation were creatively used to address heterogeneity at both the well field and regional scales in a variable-density groundwater flow and solute transport model designed to test multiple hypotheses for upward migration of fresh effluent injected into a highly transmissive saline carbonate aquifer. Two sets of pilot points were used within in multiple model layers, with one set of inner pilot points (totaling 158) having high spatial density to represent hydraulic conductivity at the site, while a second set of outer points (totaling 36) of lower spatial density was used to represent hydraulic conductivity further from the site. Use of a lower spatial density outside the site allowed (1) the total number of pilot points to be reduced while maintaining flexibility to accommodate heterogeneity at different scales, and (2) development of a model with greater areal extent in order to simulate proper boundary conditions that have a limited effect on the area of interest. The parameters associated with the inner pilot points were log transformed hydraulic conductivity multipliers of the conductivity field obtained by interpolation from outer pilot points. The use of this dual inner-outer scale parameterization (with inner parameters constituting multipliers for outer parameters) allowed smooth transition of hydraulic conductivity from the site scale, where greater spatial variability of hydraulic properties exists, to the regional scale where less spatial variability was necessary for model calibration. While the model is highly parameterized to accommodate potential aquifer heterogeneity, the total number of pilot points is kept at a minimum to enable reasonable calibration run times.

Simulations of Dynamo and Magnetorotational Instability in Madison Plasma Experiments and Astrophysical Disks

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

Ebrahimi, Fatima

Magnetic fields are observed to exist on all scales in many astrophysical sources such as stars, galaxies, and accretion discs. Understanding the origin of large scale magnetic fields, whereby the field emerges on spatial scales large compared to the fluctuations, has been a particularly long standing challenge. Our physics objective are: 1) what are the minimum ingredients for large-scale dynamo growth? 2) could a large-scale magnetic field grow out of turbulence and sustained despite the presence of dissipation? These questions are fundamental for understanding the large-scale dynamo in both laboratory and astrophysical plasmas. Here, we report major new findings inmore » the area of Large-Scale Dynamo (magnetic field generation).« less

Predictors of malaria infection in a wild bird population: landscape-level analyses reveal climatic and anthropogenic factors.

PubMed

Gonzalez-Quevedo, Catalina; Davies, Richard G; Richardson, David S

2014-09-01

How the environment influences the transmission and prevalence of disease in a population of hosts is a key aspect of disease ecology. The role that environmental factors play in host-pathogen systems has been well studied at large scales, that is, differences in pathogen pressures among separate populations of hosts or across land masses. However, despite considerable understanding of how environmental conditions vary at fine spatial scales, the effect of these parameters on host-pathogen dynamics at such scales has been largely overlooked. Here, we used a combination of molecular screening and GIS-based analysis to investigate how environmental factors determine the distribution of malaria across the landscape in a population of Berthelot's pipit (Anthus berthelotii, Bolle 1862) on the island of Tenerife (Canary Islands, Spain) using spatially explicit models that account for spatial autocorrelation. Minimum temperature of the coldest month was found to be the most important predictor of malaria infection at the landscape scale across this population. Additionally, anthropogenic factors such as distance to artificial water reservoirs and distance to poultry farms were important predictors of malaria. A model including these factors, and the interaction between distance to artificial water reservoirs and minimum temperature, best explained the distribution of malaria infection in this system. These results suggest that levels of malaria infection in this endemic species may be artificially elevated by the impact of humans. Studies such as the one described here improve our understanding of how environmental factors, and their heterogeneity, affect the distribution of pathogens within wild populations. The results demonstrate the importance of measuring fine-scale variation - and not just regional effects - to understand how environmental variation can influence wildlife diseases. Such understanding is important for predicting the future spread and impact of disease and may help inform disease management programmes as well as the conservation of specific host species. © 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society.

Regional Assessment of Remote Forests and Black Bear Habitat from Forest Resource Surveys

Treesearch

Victor A. Rudis; John B. Tansey

1995-01-01

We developed a spatially explicit modeling approach, using a county-scaled remote forest (i.e., forested area reserved from or having no direct human interference) assessment derived from 1984-1990 forest resource inventory data and a 1984 black bear (Ursus americantus) range map for 12 states in the southern United States.We defined minimum suitable and optimal black...

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

LaGory, K. E.; Walston, L. J.; Goulet, C

The decline of many snake populations is attributable to habitat loss, and knowledge of habitat use is critical to their conservation. Resource characteristics (e.g., relative availability of different habitat types, soils, and slopes) within a landscape are scale-dependent and may not be equal across multiple spatial scales. Thus, it is important to identify the relevant spatial scales at which resource selection occurs. We conducted a radiotelemetry study of eastern hognose snake (Heterodon platirhinos) home range size and resource use at different hierarchical spatial scales. We present the results for 8 snakes radiotracked during a 2-year study at New Boston Airmore » Force Station (NBAFS) in southern New Hampshire, USA, where the species is listed by the state as endangered. Mean home range size (minimum convex polygon) at NBAFS (51.7 {+-} 14.7 ha) was similar to that reported in other parts of the species range. Radiotracked snakes exhibited different patterns of resource use at different spatial scales. At the landscape scale (selection of locations within the landscape), snakes overutilized old-field and forest edge habitats and underutilized forested habitats and wetlands relative to availability. At this scale, snakes also overutilized areas containing sandy loam soils and areas with lower slope (mean slope = 5.2% at snake locations vs. 6.7% at random locations). We failed to detect some of these patterns of resource use at the home range scale (i.e., within the home range). Our ability to detect resource selection by the snakes only at the landscape scale is likely the result of greater heterogeneity in macrohabitat features at the broader landscape scale. From a management perspective, future studies of habitat selection for rare species should include measurement of available habitat at spatial scales larger than the home range. We suggest that the maintenance of open early successional habitats as a component of forested landscapes will be critical for the persistence of eastern hognose snake populations in the northeastern United States.« less

Effect of spatial averaging on multifractal properties of meteorological time series

NASA Astrophysics Data System (ADS)

Hoffmann, Holger; Baranowski, Piotr; Krzyszczak, Jaromir; Zubik, Monika

2016-04-01

Introduction The process-based models for large-scale simulations require input of agro-meteorological quantities that are often in the form of time series of coarse spatial resolution. Therefore, the knowledge about their scaling properties is fundamental for transferring locally measured fluctuations to larger scales and vice-versa. However, the scaling analysis of these quantities is complicated due to the presence of localized trends and non-stationarities. Here we assess how spatially aggregating meteorological data to coarser resolutions affects the data's temporal scaling properties. While it is known that spatial aggregation may affect spatial data properties (Hoffmann et al., 2015), it is unknown how it affects temporal data properties. Therefore, the objective of this study was to characterize the aggregation effect (AE) with regard to both temporal and spatial input data properties considering scaling properties (i.e. statistical self-similarity) of the chosen agro-meteorological time series through multifractal detrended fluctuation analysis (MFDFA). Materials and Methods Time series coming from years 1982-2011 were spatially averaged from 1 to 10, 25, 50 and 100 km resolution to assess the impact of spatial aggregation. Daily minimum, mean and maximum air temperature (2 m), precipitation, global radiation, wind speed and relative humidity (Zhao et al., 2015) were used. To reveal the multifractal structure of the time series, we used the procedure described in Baranowski et al. (2015). The diversity of the studied multifractals was evaluated by the parameters of time series spectra. In order to analyse differences in multifractal properties to 1 km resolution grids, data of coarser resolutions was disaggregated to 1 km. Results and Conclusions Analysing the spatial averaging on multifractal properties we observed that spatial patterns of the multifractal spectrum (MS) of all meteorological variables differed from 1 km grids and MS-parameters were biased by -29.1 % (precipitation; width of MS) up to >4 % (min. Temperature, Radiation; asymmetry of MS). Also, the spatial variability of MS parameters was strongly affected at the highest aggregation (100 km). Obtained results confirm that spatial data aggregation may strongly affect temporal scaling properties. This should be taken into account when upscaling for large-scale studies. Acknowledgements The study was conducted within FACCE MACSUR. Please see Baranowski et al. (2015) for details on funding. References Baranowski, P., Krzyszczak, J., Sławiński, C. et al. (2015). Climate Research 65, 39-52. Hoffman, H., G. Zhao, L.G.J. Van Bussel et al. (2015). Climate Research 65, 53-69. Zhao, G., Siebert, S., Rezaei E. et al. (2015). Agricultural and Forest Meteorology 200, 156-171.

FLO1K, global maps of mean, maximum and minimum annual streamflow at 1 km resolution from 1960 through 2015

NASA Astrophysics Data System (ADS)

Barbarossa, Valerio; Huijbregts, Mark A. J.; Beusen, Arthur H. W.; Beck, Hylke E.; King, Henry; Schipper, Aafke M.

2018-03-01

Streamflow data is highly relevant for a variety of socio-economic as well as ecological analyses or applications, but a high-resolution global streamflow dataset is yet lacking. We created FLO1K, a consistent streamflow dataset at a resolution of 30 arc seconds (~1 km) and global coverage. FLO1K comprises mean, maximum and minimum annual flow for each year in the period 1960-2015, provided as spatially continuous gridded layers. We mapped streamflow by means of artificial neural networks (ANNs) regression. An ensemble of ANNs were fitted on monthly streamflow observations from 6600 monitoring stations worldwide, i.e., minimum and maximum annual flows represent the lowest and highest mean monthly flows for a given year. As covariates we used the upstream-catchment physiography (area, surface slope, elevation) and year-specific climatic variables (precipitation, temperature, potential evapotranspiration, aridity index and seasonality indices). Confronting the maps with independent data indicated good agreement (R2 values up to 91%). FLO1K delivers essential data for freshwater ecology and water resources analyses at a global scale and yet high spatial resolution.

A novel on-line spatial-temporal k-anonymity method for location privacy protection from sequence rules-based inference attacks.

PubMed

Zhang, Haitao; Wu, Chenxue; Chen, Zewei; Liu, Zhao; Zhu, Yunhong

2017-01-01

Analyzing large-scale spatial-temporal k-anonymity datasets recorded in location-based service (LBS) application servers can benefit some LBS applications. However, such analyses can allow adversaries to make inference attacks that cannot be handled by spatial-temporal k-anonymity methods or other methods for protecting sensitive knowledge. In response to this challenge, first we defined a destination location prediction attack model based on privacy-sensitive sequence rules mined from large scale anonymity datasets. Then we proposed a novel on-line spatial-temporal k-anonymity method that can resist such inference attacks. Our anti-attack technique generates new anonymity datasets with awareness of privacy-sensitive sequence rules. The new datasets extend the original sequence database of anonymity datasets to hide the privacy-sensitive rules progressively. The process includes two phases: off-line analysis and on-line application. In the off-line phase, sequence rules are mined from an original sequence database of anonymity datasets, and privacy-sensitive sequence rules are developed by correlating privacy-sensitive spatial regions with spatial grid cells among the sequence rules. In the on-line phase, new anonymity datasets are generated upon LBS requests by adopting specific generalization and avoidance principles to hide the privacy-sensitive sequence rules progressively from the extended sequence anonymity datasets database. We conducted extensive experiments to test the performance of the proposed method, and to explore the influence of the parameter K value. The results demonstrated that our proposed approach is faster and more effective for hiding privacy-sensitive sequence rules in terms of hiding sensitive rules ratios to eliminate inference attacks. Our method also had fewer side effects in terms of generating new sensitive rules ratios than the traditional spatial-temporal k-anonymity method, and had basically the same side effects in terms of non-sensitive rules variation ratios with the traditional spatial-temporal k-anonymity method. Furthermore, we also found the performance variation tendency from the parameter K value, which can help achieve the goal of hiding the maximum number of original sensitive rules while generating a minimum of new sensitive rules and affecting a minimum number of non-sensitive rules.

A novel on-line spatial-temporal k-anonymity method for location privacy protection from sequence rules-based inference attacks

PubMed Central

Wu, Chenxue; Liu, Zhao; Zhu, Yunhong

2017-01-01

Analyzing large-scale spatial-temporal k-anonymity datasets recorded in location-based service (LBS) application servers can benefit some LBS applications. However, such analyses can allow adversaries to make inference attacks that cannot be handled by spatial-temporal k-anonymity methods or other methods for protecting sensitive knowledge. In response to this challenge, first we defined a destination location prediction attack model based on privacy-sensitive sequence rules mined from large scale anonymity datasets. Then we proposed a novel on-line spatial-temporal k-anonymity method that can resist such inference attacks. Our anti-attack technique generates new anonymity datasets with awareness of privacy-sensitive sequence rules. The new datasets extend the original sequence database of anonymity datasets to hide the privacy-sensitive rules progressively. The process includes two phases: off-line analysis and on-line application. In the off-line phase, sequence rules are mined from an original sequence database of anonymity datasets, and privacy-sensitive sequence rules are developed by correlating privacy-sensitive spatial regions with spatial grid cells among the sequence rules. In the on-line phase, new anonymity datasets are generated upon LBS requests by adopting specific generalization and avoidance principles to hide the privacy-sensitive sequence rules progressively from the extended sequence anonymity datasets database. We conducted extensive experiments to test the performance of the proposed method, and to explore the influence of the parameter K value. The results demonstrated that our proposed approach is faster and more effective for hiding privacy-sensitive sequence rules in terms of hiding sensitive rules ratios to eliminate inference attacks. Our method also had fewer side effects in terms of generating new sensitive rules ratios than the traditional spatial-temporal k-anonymity method, and had basically the same side effects in terms of non-sensitive rules variation ratios with the traditional spatial-temporal k-anonymity method. Furthermore, we also found the performance variation tendency from the parameter K value, which can help achieve the goal of hiding the maximum number of original sensitive rules while generating a minimum of new sensitive rules and affecting a minimum number of non-sensitive rules. PMID:28767687

Aroma types of flue-cured tobacco in China: spatial distribution and association with climatic factors

NASA Astrophysics Data System (ADS)

Yang, Chao; Wu, Wei; Wu, Shu-Cheng; Liu, Hong-Bin; Peng, Qing

2014-02-01

Aroma types of flue-cured tobacco (FCT) are classified into light, medium, and heavy in China. However, the spatial distribution of FCT aroma types and the relationships among aroma types, chemical parameters, and climatic variables were still unknown at national scale. In the current study, multi-year averaged chemical parameters (total sugars, reducing sugars, nicotine, total nitrogen, chloride, and K2O) of FCT samples with grade of C3F and climatic variables (mean, minimum and maximum temperatures, rainfall, relative humidity, and sunshine hours) during the growth periods were collected from main planting areas across China. Significant relationships were found between chemical parameters and climatic variables ( p < 0.05). A spatial distribution map of FCT aroma types were produced using support vector machine algorithms and chemical parameters. Significant differences in chemical parameters and climatic variables were observed among the three aroma types based on one-way analysis of variance ( p < 0.05). Areas with light aroma type had significantly lower values of mean, maximum, and minimum temperatures than regions with medium and heavy aroma types ( p < 0.05). Areas with heavy aroma type had significantly lower values of rainfall and relative humidity and higher values of sunshine hours than regions with light and medium aroma types ( p < 0.05). The output produced by classification and regression trees showed that sunshine hours, rainfall, and maximum temperature were the most important factors affecting FCT aroma types at national scale.

Sources of errors and uncertainties in the assessment of forest soil carbon stocks at different scales-review and recommendations.

PubMed

Vanguelova, E I; Bonifacio, E; De Vos, B; Hoosbeek, M R; Berger, T W; Vesterdal, L; Armolaitis, K; Celi, L; Dinca, L; Kjønaas, O J; Pavlenda, P; Pumpanen, J; Püttsepp, Ü; Reidy, B; Simončič, P; Tobin, B; Zhiyanski, M

2016-11-01

Spatially explicit knowledge of recent and past soil organic carbon (SOC) stocks in forests will improve our understanding of the effect of human- and non-human-induced changes on forest C fluxes. For SOC accounting, a minimum detectable difference must be defined in order to adequately determine temporal changes and spatial differences in SOC. This requires sufficiently detailed data to predict SOC stocks at appropriate scales within the required accuracy so that only significant changes are accounted for. When designing sampling campaigns, taking into account factors influencing SOC spatial and temporal distribution (such as soil type, topography, climate and vegetation) are needed to optimise sampling depths and numbers of samples, thereby ensuring that samples accurately reflect the distribution of SOC at a site. Furthermore, the appropriate scales related to the research question need to be defined: profile, plot, forests, catchment, national or wider. Scaling up SOC stocks from point sample to landscape unit is challenging, and thus requires reliable baseline data. Knowledge of the associated uncertainties related to SOC measures at each particular scale and how to reduce them is crucial for assessing SOC stocks with the highest possible accuracy at each scale. This review identifies where potential sources of errors and uncertainties related to forest SOC stock estimation occur at five different scales-sample, profile, plot, landscape/regional and European. Recommendations are also provided on how to reduce forest SOC uncertainties and increase efficiency of SOC assessment at each scale.

A basin-scale approach to estimating stream temperatures of tributaries to the lower Klamath River, California

USGS Publications Warehouse

Flint, L.E.; Flint, A.L.

2008-01-01

Stream temperature is an important component of salmonid habitat and is often above levels suitable for fish survival in the Lower Klamath River in northern California. The objective of this study was to provide boundary conditions for models that are assessing stream temperature on the main stem for the purpose of developing strategies to manage stream conditions using Total Maximum Daily Loads. For model input, hourly stream temperatures for 36 tributaries were estimated for 1 Jan. 2001 through 31 Oct. 2004. A basin-scale approach incorporating spatially distributed energy balance data was used to estimate the stream temperatures with measured air temperature and relative humidity data and simulated solar radiation, including topographic shading and corrections for cloudiness. Regression models were developed on the basis of available stream temperature data to predict temperatures for unmeasured periods of time and for unmeasured streams. The most significant factor in matching measured minimum and maximum stream temperatures was the seasonality of the estimate. Adding minimum and maximum air temperature to the regression model improved the estimate, and air temperature data over the region are available and easily distributed spatially. The addition of simulated solar radiation and vapor saturation deficit to the regression model significantly improved predictions of maximum stream temperature but was not required to predict minimum stream temperature. The average SE in estimated maximum daily stream temperature for the individual basins was 0.9 ?? 0.6??C at the 95% confidence interval. Copyright ?? 2008 by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America. All rights reserved.

Spectral Dimensionality and Scale of Urban Radiance

NASA Technical Reports Server (NTRS)

Small, Christopher

2001-01-01

Characterization of urban radiance and reflectance is important for understanding the effects of solar energy flux on the urban environment as well as for satellite mapping of urban settlement patterns. Spectral mixture analyses of Landsat and Ikonos imagery suggest that the urban radiance field can very often be described with combinations of three or four spectral endmembers. Dimensionality estimates of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) radiance measurements of urban areas reveal the existence of 30 to 60 spectral dimensions. The extent to which broadband imagery collected by operational satellites can represent the higher dimensional mixing space is a function of both the spatial and spectral resolution of the sensor. AVIRIS imagery offers the spatial and spectral resolution necessary to investigate the scale dependence of the spectral dimensionality. Dimensionality estimates derived from Minimum Noise Fraction (MNF) eigenvalue distributions show a distinct scale dependence for AVIRIS radiance measurements of Milpitas, California. Apparent dimensionality diminishes from almost 40 to less than 10 spectral dimensions between scales of 8000 m and 300 m. The 10 to 30 m scale of most features in urban mosaics results in substantial spectral mixing at the 20 m scale of high altitude AVIRIS pixels. Much of the variance at pixel scales is therefore likely to result from actual differences in surface reflectance at pixel scales. Spatial smoothing and spectral subsampling of AVIRIS spectra both result in substantial loss of information and reduction of apparent dimensionality, but the primary spectral endmembers in all cases are analogous to those found in global analyses of Landsat and Ikonos imagery of other urban areas.

Spatial consistency of Chinook salmon redd distribution within and among years in the Cowlitz River, Washington

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

Klett, Katherine J.; Torgersen, Christian; Henning, Julie

2013-04-28

We investigated the spawning patterns of Chinook salmon Oncorhynchus tshawytscha on the lower Cowlitz River, Washington (USA) using a unique set of fine- and coarse-scale 35 temporal and spatial data collected during bi-weekly aerial surveys conducted in 1991-2009 (500 m to 28 km resolution) and 2008-2009 (100-500 m resolution). Redd locations were mapped from a helicopter during 2008 and 2009 with a hand-held global positioning system (GPS) synchronized with in-flight audio recordings. We examined spatial patterns of Chinook salmon redd reoccupation among and within years in relation to segment-scale geomorphic features. Chinook salmon spawned in the same sections each yearmore » with little variation among years. On a coarse scale, five years (1993, 1998, 2000, 2002, and 2009) were compared for reoccupation. Redd locations were highly correlated among years resulting in a minimum correlation coefficient of 0.90 (adjusted P = 0.002). Comparisons on a fine scale (500 m) between 2008 and 2009 also revealed a high degree of consistency among redd locations (P < 0.001). On a finer temporal scale, we observed that salmon spawned in the same sections during the first and last week (2008: P < 0.02; and 2009: P < 0.001). Redds were clustered in both 2008 and 2009 (P < 0.001). Regression analysis with a generalized linear model at the 500-m scale indicated that river kilometer and channel bifurcation were positively associated with redd density, whereas sinuosity was negatively associated with redd density. Collecting data on specific redd locations with a GPS during aerial surveys was logistically feasible and cost effective and greatly enhanced the spatial precision of Chinook salmon spawning surveys.« less

Detecting changes resulting from human pressure in a naturally quick-changing and heterogeneous environment: Spatial and temporal scales of variability in coastal lagoons

NASA Astrophysics Data System (ADS)

Pérez-Ruzafa, A.; Marcos, C.; Pérez-Ruzafa, I. M.; Barcala, E.; Hegazi, M. I.; Quispe, J.

2007-10-01

To detect changes in ecosystems due to human impact, experimental designs must include replicates at the appropriate scale to avoid pseudoreplication. Although coastal lagoons, with their highly variable environmental factors and biological assemblages, are relatively well-studied systems, very little is known about their natural scales of variation. In this study, we investigate the spatio-temporal scales of variability in the Mar Menor coastal lagoon (SE Spain) using structured hierarchical sampling designs, mixed and permutational multi-variate analyses of variance, and ordination multi-variate analyses applied to hydrographical parameters, nutrients, chlorophyll a and ichthyoplankton in the water column, and to macrophyte and fish benthic assemblages. Lagoon processes in the Mar Menor show heterogeneous patterns at different temporal and spatial scales. The water column characteristics (including nutrient concentration) showed small-scale spatio-temporal variability, from 10 0 to 10 1 km and from fortnightly to seasonally. Biological features (chlorophyll a concentration and ichthyoplankton assemblage descriptors) showed monthly changes and spatial patterns at the scale of 10 0 (chlorophyll a) - 10 1 km (ichthyoplankton). Benthic assemblages (macrophytes and fishes) showed significant differences between types of substrates in the same locality and between localities, according to horizontal gradients related with confinement in the lagoon, at the scale of 10 0-10 1 km. The vertical zonation of macrophyte assemblages (at scales of 10 1-10 2 cm) overlaps changes in substrata and horizontal gradients. Seasonal patterns in vegetation biomass were not significant, but the significant interaction between Locality and Season indicated that the seasons of maximum and minimum biomass depend on local environmental conditions. Benthic fish assemblages showed no significant patterns at the monthly scale but did show seasonal patterns.

Satellite-based characterization of climatic conditions before large-scale general flowering events in Peninsular Malaysia

PubMed Central

Azmy, Muna Maryam; Hashim, Mazlan; Numata, Shinya; Hosaka, Tetsuro; Noor, Nur Supardi Md.; Fletcher, Christine

2016-01-01

General flowering (GF) is a unique phenomenon wherein, at irregular intervals, taxonomically diverse trees in Southeast Asian dipterocarp forests synchronize their reproduction at the community level. Triggers of GF, including drought and low minimum temperatures a few months previously has been limitedly observed across large regional scales due to lack of meteorological stations. Here, we aim to identify the climatic conditions that trigger large-scale GF in Peninsular Malaysia using satellite sensors, Tropical Rainfall Measuring Mission (TRMM) and Moderate Resolution Imaging Spectroradiometer (MODIS), to evaluate the climatic conditions of focal forests. We observed antecedent drought, low temperature and high photosynthetic radiation conditions before large-scale GF events, suggesting that large-scale GF events could be triggered by these factors. In contrast, we found higher-magnitude GF in forests where lower precipitation preceded large-scale GF events. GF magnitude was also negatively influenced by land surface temperature (LST) for a large-scale GF event. Therefore, we suggest that spatial extent of drought may be related to that of GF forests, and that the spatial pattern of LST may be related to that of GF occurrence. With significant new findings and other results that were consistent with previous research we clarified complicated environmental correlates with the GF phenomenon. PMID:27561887

Satellite-based characterization of climatic conditions before large-scale general flowering events in Peninsular Malaysia.

PubMed

Azmy, Muna Maryam; Hashim, Mazlan; Numata, Shinya; Hosaka, Tetsuro; Noor, Nur Supardi Md; Fletcher, Christine

2016-08-26

General flowering (GF) is a unique phenomenon wherein, at irregular intervals, taxonomically diverse trees in Southeast Asian dipterocarp forests synchronize their reproduction at the community level. Triggers of GF, including drought and low minimum temperatures a few months previously has been limitedly observed across large regional scales due to lack of meteorological stations. Here, we aim to identify the climatic conditions that trigger large-scale GF in Peninsular Malaysia using satellite sensors, Tropical Rainfall Measuring Mission (TRMM) and Moderate Resolution Imaging Spectroradiometer (MODIS), to evaluate the climatic conditions of focal forests. We observed antecedent drought, low temperature and high photosynthetic radiation conditions before large-scale GF events, suggesting that large-scale GF events could be triggered by these factors. In contrast, we found higher-magnitude GF in forests where lower precipitation preceded large-scale GF events. GF magnitude was also negatively influenced by land surface temperature (LST) for a large-scale GF event. Therefore, we suggest that spatial extent of drought may be related to that of GF forests, and that the spatial pattern of LST may be related to that of GF occurrence. With significant new findings and other results that were consistent with previous research we clarified complicated environmental correlates with the GF phenomenon.

Multimodal integration of fMRI and EEG data for high spatial and temporal resolution analysis of brain networks

PubMed Central

Mantini, D.; Marzetti, L.; Corbetta, M.; Romani, G.L.; Del Gratta, C.

2017-01-01

Two major non-invasive brain mapping techniques, electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), have complementary advantages with regard to their spatial and temporal resolution. We propose an approach based on the integration of EEG and fMRI, enabling the EEG temporal dynamics of information processing to be characterized within spatially well-defined fMRI large-scale networks. First, the fMRI data are decomposed into networks by means of spatial independent component analysis (sICA), and those associated with intrinsic activity and/or responding to task performance are selected using information from the related time-courses. Next, the EEG data over all sensors are averaged with respect to event timing, thus calculating event-related potentials (ERPs). The ERPs are subjected to temporal ICA (tICA), and the resulting components are localized with the weighted minimum norm (WMNLS) algorithm using the task-related fMRI networks as priors. Finally, the temporal contribution of each ERP component in the areas belonging to the fMRI large-scale networks is estimated. The proposed approach has been evaluated on visual target detection data. Our results confirm that two different components, commonly observed in EEG when presenting novel and salient stimuli respectively, are related to the neuronal activation in large-scale networks, operating at different latencies and associated with different functional processes. PMID:20052528

High resolution remote sensing of densely urbanised regions: a case study of Hong Kong.

PubMed

Nichol, Janet E; Wong, Man Sing

2009-01-01

Data on the urban environment such as climate or air quality is usually collected at a few point monitoring stations distributed over a city. However, the synoptic viewpoint of satellites where a whole city is visible on a single image permits the collection of spatially comprehensive data at city-wide scale. In spite of rapid developments in remote sensing systems, deficiencies in image resolution and algorithm development still exist for applications such as air quality monitoring and urban heat island analysis. This paper describes state-of-the-art techniques for enhancing and maximising the spatial detail available from satellite images, and demonstrates their applications to the densely urbanised environment of Hong Kong. An Emissivity Modulation technique for spatial enhancement of thermal satellite images permits modelling of urban microclimate in combination with other urban structural parameters at local scale. For air quality monitoring, a Minimum Reflectance Technique (MRT) has been developed for MODIS 500 m images. The techniques described can promote the routine utilization of remotely sensed images for environmental monitoring in cities of the 21(st) century.

High Resolution Remote Sensing of Densely Urbanised Regions: a Case Study of Hong Kong

PubMed Central

Nichol, Janet E.; Wong, Man Sing

2009-01-01

Data on the urban environment such as climate or air quality is usually collected at a few point monitoring stations distributed over a city. However, the synoptic viewpoint of satellites where a whole city is visible on a single image permits the collection of spatially comprehensive data at city-wide scale. In spite of rapid developments in remote sensing systems, deficiencies in image resolution and algorithm development still exist for applications such as air quality monitoring and urban heat island analysis. This paper describes state-of-the-art techniques for enhancing and maximising the spatial detail available from satellite images, and demonstrates their applications to the densely urbanised environment of Hong Kong. An Emissivity Modulation technique for spatial enhancement of thermal satellite images permits modelling of urban microclimate in combination with other urban structural parameters at local scale. For air quality monitoring, a Minimum Reflectance Technique (MRT) has been developed for MODIS 500 m images. The techniques described can promote the routine utilization of remotely sensed images for environmental monitoring in cities of the 21st century. PMID:22408549

Nonsingular, big-bounce cosmology from spinor-torsion coupling

NASA Astrophysics Data System (ADS)

Popławski, Nikodem

2012-05-01

The Einstein-Cartan-Sciama-Kibble theory of gravity removes the constraint of general relativity that the affine connection be symmetric by regarding its antisymmetric part, the torsion tensor, as a dynamical variable. The minimal coupling between the torsion tensor and Dirac spinors generates a spin-spin interaction which is significant in fermionic matter at extremely high densities. We show that such an interaction averts the unphysical big-bang singularity, replacing it with a cusp-like bounce at a finite minimum scale factor, before which the Universe was contracting. This scenario also explains why the present Universe at largest scales appears spatially flat, homogeneous and isotropic.

Defining the minimum temporal and spatial scales available from a new 72-month Nimbus-7 Earth Radiation Budget climate data set

NASA Technical Reports Server (NTRS)

Randel, D. L.; Campbell, G. G.; Vonder Haar, T. H.; Smith, L.

1986-01-01

Scale factors and assumptions which were applied in calculations of global radiation budget parameters based on ERB data are discussed. The study was performed to examine the relationship between the composite global ERB map that can be generated every six days using all available data and the actual average global ERB. The wide field of view ERB instrument functioned for the first 19 months of the Nimbus-7 life, and furnished sufficient data for calculating actual ERB averages. The composite was most accurate in regions with the least variation in radiation budget.

[Minimum Standards for the Spatial Accessibility of Primary Care: A Systematic Review].

PubMed

Voigtländer, S; Deiters, T

2015-12-01

Regional disparities of access to primary care are substantial in Germany, especially in terms of spatial accessibility. However, there is no legally or generally binding minimum standard for the spatial accessibility effort that is still acceptable. Our objective is to analyse existing minimum standards, the methods used as well as their empirical basis. A systematic literature review was undertaken of publications regarding minimum standards for the spatial accessibility of primary care based on a title word and keyword search using PubMed, SSCI/Web of Science, EMBASE and Cochrane Library. 8 minimum standards from the USA, Germany and Austria could be identified. All of them specify the acceptable spatial accessibility effort in terms of travel time; almost half include also distance(s). The travel time maximum, which is acceptable, is 30 min and it tends to be lower in urban areas. Primary care is, according to the identified minimum standards, part of the local area (Nahbereich) of so-called central places (Zentrale Orte) providing basic goods and services. The consideration of means of transport, e. g. public transport, is heterogeneous. The standards are based on empirical studies, consultation with service providers, practical experiences, and regional planning/central place theory as well as on legal or political regulations. The identified minimum standards provide important insights into the effort that is still acceptable regarding spatial accessibility, i. e. travel time, distance and means of transport. It seems reasonable to complement the current planning system for outpatient care, which is based on provider-to-population ratios, by a gravity-model method to identify places as well as populations with insufficient spatial accessibility. Due to a lack of a common minimum standard we propose - subject to further discussion - to begin with a threshold based on the spatial accessibility limit of the local area, i. e. 30 min to the next primary care provider for at least 90% of the regional population. The exceeding of the threshold would necessitate a discussion of a health care deficit and in line with this a potential need for intervention, e. g. in terms of alternative forms of health care provision. © Georg Thieme Verlag KG Stuttgart · New York.

A probabilistic approach to quantifying spatial patterns of flow regimes and network-scale connectivity

NASA Astrophysics Data System (ADS)

Garbin, Silvia; Alessi Celegon, Elisa; Fanton, Pietro; Botter, Gianluca

2017-04-01

The temporal variability of river flow regime is a key feature structuring and controlling fluvial ecological communities and ecosystem processes. In particular, streamflow variability induced by climate/landscape heterogeneities or other anthropogenic factors significantly affects the connectivity between streams with notable implication for river fragmentation. Hydrologic connectivity is a fundamental property that guarantees species persistence and ecosystem integrity in riverine systems. In riverine landscapes, most ecological transitions are flow-dependent and the structure of flow regimes may affect ecological functions of endemic biota (i.e., fish spawning or grazing of invertebrate species). Therefore, minimum flow thresholds must be guaranteed to support specific ecosystem services, like fish migration, aquatic biodiversity and habitat suitability. In this contribution, we present a probabilistic approach aiming at a spatially-explicit, quantitative assessment of hydrologic connectivity at the network-scale as derived from river flow variability. Dynamics of daily streamflows are estimated based on catchment-scale climatic and morphological features, integrating a stochastic, physically based approach that accounts for the stochasticity of rainfall with a water balance model and a geomorphic recession flow model. The non-exceedance probability of ecologically meaningful flow thresholds is used to evaluate the fragmentation of individual stream reaches, and the ensuing network-scale connectivity metrics. A multi-dimensional Poisson Process for the stochastic generation of rainfall is used to evaluate the impact of climate signature on reach-scale and catchment-scale connectivity. The analysis shows that streamflow patterns and network-scale connectivity are influenced by the topology of the river network and the spatial variability of climatic properties (rainfall, evapotranspiration). The framework offers a robust basis for the prediction of the impact of land-use/land-cover changes and river regulation on network-scale connectivity.

EEG source reconstruction reveals frontal-parietal dynamics of spatial conflict processing.

PubMed

Cohen, Michael X; Ridderinkhof, K Richard

2013-01-01

Cognitive control requires the suppression of distracting information in order to focus on task-relevant information. We applied EEG source reconstruction via time-frequency linear constrained minimum variance beamforming to help elucidate the neural mechanisms involved in spatial conflict processing. Human subjects performed a Simon task, in which conflict was induced by incongruence between spatial location and response hand. We found an early (∼200 ms post-stimulus) conflict modulation in stimulus-contralateral parietal gamma (30-50 Hz), followed by a later alpha-band (8-12 Hz) conflict modulation, suggesting an early detection of spatial conflict and inhibition of spatial location processing. Inter-regional connectivity analyses assessed via cross-frequency coupling of theta (4-8 Hz), alpha, and gamma power revealed conflict-induced shifts in cortical network interactions: Congruent trials (relative to incongruent trials) had stronger coupling between frontal theta and stimulus-contrahemifield parietal alpha/gamma power, whereas incongruent trials had increased theta coupling between medial frontal and lateral frontal regions. These findings shed new light into the large-scale network dynamics of spatial conflict processing, and how those networks are shaped by oscillatory interactions.

Local-scale spatial modelling for interpolating climatic temperature variables to predict agricultural plant suitability

NASA Astrophysics Data System (ADS)

Webb, Mathew A.; Hall, Andrew; Kidd, Darren; Minansy, Budiman

2016-05-01

Assessment of local spatial climatic variability is important in the planning of planting locations for horticultural crops. This study investigated three regression-based calibration methods (i.e. traditional versus two optimized methods) to relate short-term 12-month data series from 170 temperature loggers and 4 weather station sites with data series from nearby long-term Australian Bureau of Meteorology climate stations. The techniques trialled to interpolate climatic temperature variables, such as frost risk, growing degree days (GDDs) and chill hours, were regression kriging (RK), regression trees (RTs) and random forests (RFs). All three calibration methods produced accurate results, with the RK-based calibration method delivering the most accurate validation measures: coefficients of determination ( R 2) of 0.92, 0.97 and 0.95 and root-mean-square errors of 1.30, 0.80 and 1.31 °C, for daily minimum, daily maximum and hourly temperatures, respectively. Compared with the traditional method of calibration using direct linear regression between short-term and long-term stations, the RK-based calibration method improved R 2 and reduced root-mean-square error (RMSE) by at least 5 % and 0.47 °C for daily minimum temperature, 1 % and 0.23 °C for daily maximum temperature and 3 % and 0.33 °C for hourly temperature. Spatial modelling indicated insignificant differences between the interpolation methods, with the RK technique tending to be the slightly better method due to the high degree of spatial autocorrelation between logger sites.

Using Satellite Imagery to Assess Large-Scale Habitat Characteristics of Adirondack Park, New York, USA

NASA Astrophysics Data System (ADS)

McClain, Bobbi J.; Porter, William F.

2000-11-01

Satellite imagery is a useful tool for large-scale habitat analysis; however, its limitations need to be tested. We tested these limitations by varying the methods of a habitat evaluation for white-tailed deer ( Odocoileus virginianus) in the Adirondack Park, New York, USA, utilizing harvest data to create and validate the assessment models. We used two classified images, one with a large minimum mapping unit but high accuracy and one with no minimum mapping unit but slightly lower accuracy, to test the sensitivity of the evaluation to these differences. We tested the utility of two methods of assessment, habitat suitability index modeling, and pattern recognition modeling. We varied the scale at which the models were applied by using five separate sizes of analysis windows. Results showed that the presence of a large minimum mapping unit eliminates important details of the habitat. Window size is relatively unimportant if the data are averaged to a large resolution (i.e., township), but if the data are used at the smaller resolution, then the window size is an important consideration. In the Adirondacks, the proportion of hardwood and softwood in an area is most important to the spatial dynamics of deer populations. The low occurrence of open area in all parts of the park either limits the effect of this cover type on the population or limits our ability to detect the effect. The arrangement and interspersion of cover types were not significant to deer populations.

Multiple neutral density measurements in the lower thermosphere with cold-cathode ionization gauges

NASA Astrophysics Data System (ADS)

Lehmacher, G. A.; Gaulden, T. M.; Larsen, M. F.; Craven, J. D.

2013-01-01

Cold-cathode ionization gauges were used for rocket-borne measurements of total neutral density and temperature in the aurorally forced lower thermosphere between 90 and 200 km. A commercial gauge was adapted as a low-cost instrument with a spherical antechamber for measurements in molecular flow conditions. Three roll-stabilized payloads on different trajectories each carried two instruments for measurements near the ram flow direction along the respective upleg and downleg segments of a flight path, and six density profiles were obtained within a period of 22 min covering spatial separations up to 200 km. The density profiles were integrated below 125 km to yield temperatures. The mean temperature structure was similar for all six profiles with two mesopause minima near 110 and 101 km, however, for the downleg profiles, the upper minimum was warmer and the lower minimum was colder by 20-30 K indicating significant variability over horizontal scales of 100-200 km. The upper temperature minimum coincided with maximum horizontal winds speeds, exceeding 170 m/s.

THE EVOLUTION OF RESTRAINT IN BACTERIAL BIOFILMS UNDER NONTRANSITIVE COMPETITION

PubMed Central

Prado, Federico; Kerr, Benjamin

2009-01-01

Theoretical and empirical evidence indicates that competing species can coexist if dispersal, migration, and competitive interactions occur over relatively small spatial scales. In particular, spatial structure appears to be critical to certain communities with nontransitive competition. A typical nontransitive system involves three competing species that satisfy a relationship similar to the children’s game of rock–paper–scissors. Although the ecological dynamics of nontransitive systems in spatially structured communities have received some attention, fewer studies have incorporated evolutionary change. Here we investigate evolution within toxic bacterial biofilms using an agent-based simulation that represents a nontransitive community containing three populations of Escherichia coli. In structured, nontransitive communities, strains evolve that do not maximize their competitive ability: They do not reduce their probability of death to a minimum or increase their toxicity to a maximum. That is, types evolve that exercise restraint. We show that nontransitivity and spatial structure (in the form of localized interactions) are both necessary for the evolution of restraint in these biofilms. PMID:18039324

The evolution of restraint in bacterial biofilms under nontransitive competition.

PubMed

Prado, Federico; Kerr, Benjamin

2008-03-01

Theoretical and empirical evidence indicates that competing species can coexist if dispersal, migration, and competitive interactions occur over relatively small spatial scales. In particular, spatial structure appears to be critical to certain communities with nontransitive competition. A typical nontransitive system involves three competing species that satisfy a relationship similar to the children's game of rock-paper-scissors. Although the ecological dynamics of nontransitive systems in spatially structured communities have received some attention, fewer studies have incorporated evolutionary change. Here we investigate evolution within toxic bacterial biofilms using an agent-based simulation that represents a nontransitive community containing three populations of Escherichia coli. In structured, nontransitive communities, strains evolve that do not maximize their competitive ability: They do not reduce their probability of death to a minimum or increase their toxicity to a maximum. That is, types evolve that exercise restraint. We show that nontransitivity and spatial structure (in the form of localized interactions) are both necessary for the evolution of restraint in these biofilms.

Relevance of multiple spatial scales in habitat models: A case study with amphibians and grasshoppers

NASA Astrophysics Data System (ADS)

Altmoos, Michael; Henle, Klaus

2010-11-01

Habitat models for animal species are important tools in conservation planning. We assessed the need to consider several scales in a case study for three amphibian and two grasshopper species in the post-mining landscapes near Leipzig (Germany). The two species groups were selected because habitat analyses for grasshoppers are usually conducted on one scale only whereas amphibians are thought to depend on more than one spatial scale. First, we analysed how the preference to single habitat variables changed across nested scales. Most environmental variables were only significant for a habitat model on one or two scales, with the smallest scale being particularly important. On larger scales, other variables became significant, which cannot be recognized on lower scales. Similar preferences across scales occurred in only 13 out of 79 cases and in 3 out of 79 cases the preference and avoidance for the same variable were even reversed among scales. Second, we developed habitat models by using a logistic regression on every scale and for all combinations of scales and analysed how the quality of habitat models changed with the scales considered. To achieve a sufficient accuracy of the habitat models with a minimum number of variables, at least two scales were required for all species except for Bufo viridis, for which a single scale, the microscale, was sufficient. Only for the European tree frog ( Hyla arborea), at least three scales were required. The results indicate that the quality of habitat models increases with the number of surveyed variables and with the number of scales, but costs increase too. Searching for simplifications in multi-scaled habitat models, we suggest that 2 or 3 scales should be a suitable trade-off, when attempting to define a suitable microscale.

Climate Change and Conservation Planning in California: The San Francisco Bay Area Upland Habitat Goals Approach

NASA Astrophysics Data System (ADS)

Branciforte, R.; Weiss, S. B.; Schaefer, N.

2008-12-01

Climate change threatens California's vast and unique biodiversity. The Bay Area Upland Habitat Goals is a comprehensive regional biodiversity assessment of the 9 counties surrounding San Francisco Bay, and is designing conservation land networks that will serve to protect, manage, and restore that biodiversity. Conservation goals for vegetation, rare plants, mammals, birds, fish, amphibians, reptiles, and invertebrates are set, and those goals are met using the optimization algorithm MARXAN. Climate change issues are being considered in the assessment and network design in several ways. The high spatial variability at mesoclimatic and topoclimatic scales in California creates high local biodiversity, and provides some degree of local resiliency to macroclimatic change. Mesoclimatic variability from 800 m scale PRISM climatic norms is used to assess "mesoclimate spaces" in distinct mountain ranges, so that high mesoclimatic variability, especially local extremes that likely support range limits of species and potential climatic refugia, can be captured in the network. Quantitative measures of network resiliency to climate change include the spatial range of key temperature and precipitation variables within planning units. Topoclimatic variability provides a finer-grained spatial patterning. Downscaling to the topoclimatic scale (10-50 m scale) includes modeling solar radiation across DEMs for predicting maximum temperature differentials, and topographic position indices for modeling minimum temperature differentials. PRISM data are also used to differentiate grasslands into distinct warm and cool types. The overall conservation strategy includes local and regional connectivity so that range shifts can be accommodated.

Are the traditional large-scale drought indices suitable for shallow water wetlands? An example in the Everglades.

PubMed

Zhao, Dehua; Wang, Penghe; Zuo, Jie; Zhang, Hui; An, Shuqing; Ramesh, Reddy K

2017-08-01

Numerous drought indices have been developed over the past several decades. However, few studies have focused on the suitability of indices for studies of ephemeral wetlands. The objective is to answer the following question: can the traditional large-scale drought indices characterize drought severity in shallow water wetlands such as the Everglades? The question was approached from two perspectives: the available water quantity and the response of wetland ecosystems to drought. The results showed the unsuitability of traditional large-scale drought indices for characterizing the actual available water quantity based on two findings. (1) Large spatial variations in precipitation (P), potential evapotranspiration (PE), water table depth (WTD) and the monthly water storage change (SC) were observed in the Everglades; notably, the spatial variation in SC, which reflects the monthly water balance, was 1.86 and 1.62 times larger than the temporal variation between seasons and between years, respectively. (2) The large-scale water balance measured based on the water storage variation had an average indicating efficiency (IE) of only 60.01% due to the redistribution of interior water. The spatial distribution of variations in the Normalized Different Vegetation Index (NDVI) in the 2011 dry season showed significantly positive, significantly negative and weak correlations with the minimum WTD in wet prairies, graminoid prairies and sawgrass wetlands, respectively. The significant and opposite correlations imply the unsuitability of the traditional large-scale drought indices in evaluating the effect of drought on shallow water wetlands. Copyright © 2017 Elsevier Ltd. All rights reserved.

Isolating contour information from arbitrary images

NASA Technical Reports Server (NTRS)

Jobson, Daniel J.

1989-01-01

Aspects of natural vision (physiological and perceptual) serve as a basis for attempting the development of a general processing scheme for contour extraction. Contour information is assumed to be central to visual recognition skills. While the scheme must be regarded as highly preliminary, initial results do compare favorably with the visual perception of structure. The scheme pays special attention to the construction of a smallest scale circular difference-of-Gaussian (DOG) convolution, calibration of multiscale edge detection thresholds with the visual perception of grayscale boundaries, and contour/texture discrimination methods derived from fundamental assumptions of connectivity and the characteristics of printed text. Contour information is required to fall between a minimum connectivity limit and maximum regional spatial density limit at each scale. Results support the idea that contour information, in images possessing good image quality, is (centered at about 10 cyc/deg and 30 cyc/deg). Further, lower spatial frequency channels appear to play a major role only in contour extraction from images with serious global image defects.

Studies and Application of Remote Sensing Retrieval Method of Soil Moisture Content in Land Parcel Units in Irrigation Area

NASA Astrophysics Data System (ADS)

Zhu, H.; Zhao, H. L.; Jiang, Y. Z.; Zang, W. B.

2018-05-01

Soil moisture is one of the important hydrological elements. Obtaining soil moisture accurately and effectively is of great significance for water resource management in irrigation area. During the process of soil moisture content retrieval with multiremote sensing data, multi- remote sensing data always brings multi-spatial scale problems which results in inconformity of soil moisture content retrieved by remote sensing in different spatial scale. In addition, agricultural water use management has suitable spatial scale of soil moisture information so as to satisfy the demands of dynamic management of water use and water demand in certain unit. We have proposed to use land parcel unit as the minimum unit to do soil moisture content research in agricultural water using area, according to soil characteristics, vegetation coverage characteristics in underlying layer, and hydrological characteristic into the basis of study unit division. We have proposed division method of land parcel units. Based on multi thermal infrared and near infrared remote sensing data, we calculate the ndvi and tvdi index and make a statistical model between the tvdi index and soil moisture of ground monitoring station. Then we move forward to study soil moisture remote sensing retrieval method on land parcel unit scale. And the method has been applied in Hetao irrigation area. Results show that compared with pixel scale the soil moisture content in land parcel unit scale has displayed stronger correlation with true value. Hence, remote sensing retrieval method of soil moisture content in land parcel unit scale has shown good applicability in Hetao irrigation area. We converted the research unit into the scale of land parcel unit. Using the land parcel units with unified crops and soil attributes as the research units more complies with the characteristics of agricultural water areas, avoids the problems such as decomposition of mixed pixels and excessive dependence on high-resolution data caused by the research units of pixels, and doesn't involve compromises in the spatial scale and simulating precision like the grid simulation. When the application needs are met, the production efficiency of products can also be improved at a certain degree.

Signature of present and projected climate change at an urban scale: The case of Addis Ababa

NASA Astrophysics Data System (ADS)

Arsiso, Bisrat Kifle; Mengistu Tsidu, Gizaw; Stoffberg, Gerrit Hendrik

2018-06-01

Understanding climate change and variability at an urban scale is essential for water resource management, land use planning, development of adaption plans, mitigation of air and water pollution. However, there are serious challenges to meet these goals due to unavailability of observed and/or simulated high resolution spatial and temporal climate data. The statistical downscaling of general circulation climate model, for instance, is usually driven by sparse observational data hindering the use of downscaled data to investigate urban scale climate variability and change in the past. Recently, these challenges are partly resolved by concerted international effort to produce global and high spatial resolution climate data. In this study, the 1 km2 high resolution NIMR-HadGEM2-AO simulations for future projections under Representative Concentration Pathways (RCP4.5 and RCP8.5) scenarios and gridded observations provided by Worldclim data center are used to assess changes in rainfall, minimum and maximum temperature expected under the two scenarios over Addis Ababa city. The gridded 1 km2 observational data set for the base period (1950-2000) is compared to observation from a meteorological station in the city in order to assess its quality for use as a reference (baseline) data. The comparison revealed that the data set has a very good quality. The rainfall anomalies under RCPs scenarios are wet in the 2030s (2020-2039), 2050s (2040-2069) and 2080s (2070-2099). Both minimum and maximum temperature anomalies under RCPs are successively getting warmer during these periods. Thus, the projected changes under RCPs scenarios show a general increase in rainfall and temperatures with strong variabilities in rainfall during rainy season implying level of difficulty in water resource use and management as well as land use planning and management.

Problems in evaluating regional and local trends in temperature: An example from eastern Colorado, USA

USGS Publications Warehouse

Pielke, R.A.; Stohlgren, T.; Schell, L.; Parton, W.; Doesken, N.; Redmond, K.; Moeny, J.; McKee, T.; Kittel, T.G.F.

2002-01-01

We evaluated long-term trends in average maximum and minimum temperatures, threshold temperatures, and growing season in eastern Colorado, USA, to explore the potential shortcomings of many climate-change studies that either: (1) generalize regional patterns from single stations, single seasons, or a few parameters over short duration from averaging dissimilar stations: or (2) generalize an average regional pattern from coarse-scale general circulation models. Based on 11 weather stations, some trends were weakly regionally consistent with previous studies of night-time temperature warming. Long-term (80 + years) mean minimum temperatures increased significantly (P < 0.2) in about half the stations in winter, spring, and autumn and six stations had significant decreases in the number of days per year with temperatures ??? - 17.8 ??C (???0??F). However, spatial and temporal variation in the direction of change was enormous for all the other weather parameters tested, and, in the majority of tests, few stations showed significant trends (even at P < 0.2). In summer, four stations had significant increases and three stations had significant decreases in minimum temperatures, producing a strongly mixed regional signal. Trends in maximum temperature varied seasonally and geographically, as did trends in threshold temperature days ???32.2??C (???90??F) or days ???37.8??C (???100??F). There was evidence of a subregional cooling in autumn's maximum temperatures, with five stations showing significant decreasing trends. There were many geographic anomalies where neighbouring weather stations differed greatly in the magnitude of change or where they had significant and opposite trends. We conclude that sub-regional spatial and seasonal variation cannot be ignored when evaluating the direction and magnitude of climate change. It is unlikely that one or a few weather stations are representative of regional climate trends, and equally unlikely that regionally projected climate change from coarse-scale general circulation models will accurately portray trends at sub-regional scales. However, the assessment of a group of stations for consistent more qualitative trends (such as the number of days less than - 17.8??C, such as we found) provides a reasonably robust procedure to evaluate climate trends and variability. Copyright ?? 2002 Royal Meteorological Society.

Geospatial Information Informs Bonobo (pan Paniscus) Conservation Efforts in the Democratic Republic of the Congo

NASA Astrophysics Data System (ADS)

Nackoney, J.; Hickey, J.; Williams, D.; Facheux, C.; Dupain, J.

2014-12-01

The bonobo (Pan paniscus), a great ape that is endemic to the Democratic Republic of the Congo (DRC), has been listed as Endangered on the IUCN Red List since 2007. Hunting and habitat loss are primary threats. Two recent wars and ongoing conflicts in the DRC have resulted in political and economic instability that hampers on-the-ground work, thereby accentuating the importance of spatial data and maps as tools for monitoring threats remotely and prioritizing locations for safeguarding bonobo habitat. Several regional and rangewide efforts have leveraged the utility of existing spatial data to help focus limited resources for effective broad-scale conservation of these great apes. At local scales, we developed spatial models to identify locations of highest hunting pressure, predict future human settlement and agricultural expansion, map areas of highest conservation value to bonobos, and identify the connective corridors linking them. We identified 42 least-disturbed wildland blocks meeting the minimum home range size needed for bonobos, and 32 potential corridors. At the range-wide scale, we developed a first range-wide spatial model of suitable conditions for the bonobo; this was a major contribution to the development of a Bonobo Conservation Strategy for 2012-2022, recently published by IUCN. The model used a forest edge density metric and other biotic and abiotic variables in conjunction with bonobo nest data collected during 2003-2010 by over 40 bonobo researchers. Approximately 28% of the range was predicted suitable; of that, about 27.5% was located in official protected areas. Highlighting these examples, this presentation will discuss the conservation status of bonobos and how spatial data and models are being utilized for the formation of strategic conservation plans.

Mitigating nonlinearity in full waveform inversion using scaled-Sobolev pre-conditioning

NASA Astrophysics Data System (ADS)

Zuberi, M. AH; Pratt, R. G.

2018-04-01

The Born approximation successfully linearizes seismic full waveform inversion if the background velocity is sufficiently accurate. When the background velocity is not known it can be estimated by using model scale separation methods. A frequently used technique is to separate the spatial scales of the model according to the scattering angles present in the data, by using either first- or second-order terms in the Born series. For example, the well-known `banana-donut' and the `rabbit ear' shaped kernels are, respectively, the first- and second-order Born terms in which at least one of the scattering events is associated with a large angle. Whichever term of the Born series is used, all such methods suffer from errors in the starting velocity model because all terms in the Born series assume that the background Green's function is known. An alternative approach to Born-based scale separation is to work in the model domain, for example, by Gaussian smoothing of the update vectors, or some other approach for separation by model wavenumbers. However such model domain methods are usually based on a strict separation in which only the low-wavenumber updates are retained. This implies that the scattered information in the data is not taken into account. This can lead to the inversion being trapped in a false (local) minimum when sharp features are updated incorrectly. In this study we propose a scaled-Sobolev pre-conditioning (SSP) of the updates to achieve a constrained scale separation in the model domain. The SSP is obtained by introducing a scaled Sobolev inner product (SSIP) into the measure of the gradient of the objective function with respect to the model parameters. This modified measure seeks reductions in the L2 norm of the spatial derivatives of the gradient without changing the objective function. The SSP does not rely on the Born prediction of scale based on scattering angles, and requires negligible extra computational cost per iteration. Synthetic examples from the Marmousi model show that the constrained scale separation using SSP is able to keep the background updates in the zone of attraction of the global minimum, in spite of using a poor starting model in which conventional methods fail.

Detecting cm-scale hot spot over 24-km-long single-mode fiber by using differential pulse pair BOTDA based on double-peak spectrum.

PubMed

Diakaridia, Sanogo; Pan, Yue; Xu, Pengbai; Zhou, Dengwang; Wang, Benzhang; Teng, Lei; Lu, Zhiwei; Ba, Dexin; Dong, Yongkang

2017-07-24

In distributed Brillouin optical fiber sensor when the length of the perturbation to be detected is much smaller than the spatial resolution that is defined by the pulse width, the measured Brillouin gain spectrum (BGS) experiences two or multiple peaks. In this work, we propose and demonstrate a technique using differential pulse pair Brillouin optical time-domain analysis (DPP-BOTDA) based on double-peak BGS to enhance small-scale events detection capability, where two types of single mode fiber (main fiber and secondary fiber) with 116 MHz Brillouin frequency shift (BFS) difference have been used. We have realized detection of a 5-cm hot spot at the far end of 24-km single mode fiber by employing a 50-cm spatial resolution DPP-BOTDA with only 1GS/s sampling rate (corresponding to 10 cm/point). The BFS at the far end of 24-km sensing fiber has been measured with 0.54 MHz standard deviation which corresponds to a 0.5°C temperature accuracy. This technique is simple and cost effective because it is implemented using the similar experimental setup of the standard BOTDA, however, it should be noted that the consecutive small-scale events have to be separated by a minimum length corresponding to the spatial resolution defined by the pulse width difference.

Cross-scale modeling of surface temperature and tree seedling establishment inmountain landscapes

USGS Publications Warehouse

Dingman, John; Sweet, Lynn C.; McCullough, Ian M.; Davis, Frank W.; Flint, Alan L.; Franklin, Janet; Flint, Lorraine E.

2013-01-01

Abstract: Introduction: Estimating surface temperature from above-ground field measurements is important for understanding the complex landscape patterns of plant seedling survival and establishment, processes which occur at heights of only several centimeters. Currently, future climate models predict temperature at 2 m above ground, leaving ground-surface microclimate not well characterized. Methods: Using a network of field temperature sensors and climate models, a ground-surface temperature method was used to estimate microclimate variability of minimum and maximum temperature. Temperature lapse rates were derived from field temperature sensors and distributed across the landscape capturing differences in solar radiation and cold air drainages modeled at a 30-m spatial resolution. Results: The surface temperature estimation method used for this analysis successfully estimated minimum surface temperatures on north-facing, south-facing, valley, and ridgeline topographic settings, and when compared to measured temperatures yielded an R2 of 0.88, 0.80, 0.88, and 0.80, respectively. Maximum surface temperatures generally had slightly more spatial variability than minimum surface temperatures, resulting in R2 values of 0.86, 0.77, 0.72, and 0.79 for north-facing, south-facing, valley, and ridgeline topographic settings. Quasi-Poisson regressions predicting recruitment of Quercus kelloggii (black oak) seedlings from temperature variables were significantly improved using these estimates of surface temperature compared to air temperature modeled at 2 m. Conclusion: Predicting minimum and maximum ground-surface temperatures using a downscaled climate model coupled with temperature lapse rates estimated from field measurements provides a method for modeling temperature effects on plant recruitment. Such methods could be applied to improve projections of species’ range shifts under climate change. Areas of complex topography can provide intricate microclimates that may allow species to redistribute locally as climate changes.

EEG Source Reconstruction Reveals Frontal-Parietal Dynamics of Spatial Conflict Processing

PubMed Central

Cohen, Michael X; Ridderinkhof, K. Richard

2013-01-01

Cognitive control requires the suppression of distracting information in order to focus on task-relevant information. We applied EEG source reconstruction via time-frequency linear constrained minimum variance beamforming to help elucidate the neural mechanisms involved in spatial conflict processing. Human subjects performed a Simon task, in which conflict was induced by incongruence between spatial location and response hand. We found an early (∼200 ms post-stimulus) conflict modulation in stimulus-contralateral parietal gamma (30–50 Hz), followed by a later alpha-band (8–12 Hz) conflict modulation, suggesting an early detection of spatial conflict and inhibition of spatial location processing. Inter-regional connectivity analyses assessed via cross-frequency coupling of theta (4–8 Hz), alpha, and gamma power revealed conflict-induced shifts in cortical network interactions: Congruent trials (relative to incongruent trials) had stronger coupling between frontal theta and stimulus-contrahemifield parietal alpha/gamma power, whereas incongruent trials had increased theta coupling between medial frontal and lateral frontal regions. These findings shed new light into the large-scale network dynamics of spatial conflict processing, and how those networks are shaped by oscillatory interactions. PMID:23451201

Merging Station Observations with Large-Scale Gridded Data to Improve Hydrological Predictions over Chile

NASA Astrophysics Data System (ADS)

Peng, L.; Sheffield, J.; Verbist, K. M. J.

2016-12-01

Hydrological predictions at regional-to-global scales are often hampered by the lack of meteorological forcing data. The use of large-scale gridded meteorological data is able to overcome this limitation, but these data are subject to regional biases and unrealistic values at local scale. This is especially challenging in regions such as Chile, where climate exhibits high spatial heterogeneity as a result of long latitude span and dramatic elevation changes. However, regional station-based observational datasets are not fully exploited and have the potential of constraining biases and spatial patterns. This study aims at adjusting precipitation and temperature estimates from the Princeton University global meteorological forcing (PGF) gridded dataset to improve hydrological simulations over Chile, by assimilating 982 gauges from the Dirección General de Aguas (DGA). To merge station data with the gridded dataset, we use a state-space estimation method to produce optimal gridded estimates, considering both the error of the station measurements and the gridded PGF product. The PGF daily precipitation, maximum and minimum temperature at 0.25° spatial resolution are adjusted for the period of 1979-2010. Precipitation and temperature gauges with long and continuous records (>70% temporal coverage) are selected, while the remaining stations are used for validation. The leave-one-out cross validation verifies the robustness of this data assimilation approach. The merged dataset is then used to force the Variable Infiltration Capacity (VIC) hydrological model over Chile at daily time step which are compared to the observations of streamflow. Our initial results show that the station-merged PGF precipitation effectively captures drizzle and the spatial pattern of storms. Overall the merged dataset has significant improvements compared to the original PGF with reduced biases and stronger inter-annual variability. The invariant spatial pattern of errors between the station data and the gridded product opens up the possibility of merging real-time satellite and intermittent gauge observations to produce more accurate real-time hydrological predictions.

Thermospheric O/N2 in the Sunlit Disk From More Than Five Years of GUVI/TIMED Observations

NASA Astrophysics Data System (ADS)

Craven, J. D.; Christensen, A. B.; Paxton, L. J.

2007-12-01

GUVI indirect observations of the thermospheric column density ratio, O/N2, in the sunlit hemisphere have been made on a nearly continuous basis from day 50 of 2002 to the present as part of the TIMED spacecraft mission. The basic large-scale spatial structure includes variations with local time (greater values in the morning), Universal Time (modulation at high latitudes due to the offset magnetic dipole), and season (greater values in the local winter hemisphere). These differences are seen to fade in the approach to solar minimum. Superposed on this reasonably well-behaved background structure are the complex, transient perturbations driven by auroral substorms and geomagnetic storms. The spatial and temporal variations are summarized in part by time-lapse movies

SPURS-2: Multi-month and multi-scale observations of upper ocean salinity in a rain-dominated salinity minimum region.

NASA Astrophysics Data System (ADS)

Rainville, L.; Farrar, J. T.; Shcherbina, A.; Centurioni, L. R.

2017-12-01

The Salinity Processes in the Upper-ocean Regional Study (SPURS) is a program aimed at understanding the patterns and variability of sea surface salinity. Following the first SPURS program in an evaporation-dominated region (2012-2013), the SPURS-2 program targeted wide range of spatial and temporal scales associated with processes controlling salinity in the rain-dominated Eastern Pacific Fresh Pool. Autonomous instruments were delivered in August and September 2016 using research vessels conducted observations over one complete annual cycle. The SPURS-2 field program used coordinated observations from many different autonomous platforms, and a mix of Lagrangian and Eulerian approaches. Here we discuss the motivation, implementation, and the early of SPURS-2.

Flame Stabilization on Microscopic Scale of Wet Biogas with Microflame

NASA Astrophysics Data System (ADS)

Ida, Tamio; Fuchihata, Manabu; Mizuno, Satoru

Harvesting, transportation, energy conversion and the high-efficient utilization, cascade method and market formation besides become with the indispensable element in order to utilize the biomass resource. There are two type biogases; it is gasified gas from dried biomass by partially combustion and wet biogas from wet biomass by methane fermentation, especially from the livestock excrement resources. This paper discusses an experimental study for flame stabilization on microscopic scale with wet biogas (mainly 0.6CH4+0.4CO2). In this study, the microflame with the wet biogas fuels are formed by the diffusion flame on the coppered straight pipes of inner diameter 0.02mm ˜ 1.5mm. This study is obtained stability mapping on microscopic scale of formed microflame by wet biogas fuels. The flame stability limit conditions on microscopic scale of wet biogas is drawn with blow off and extinction flame double limit lines. It is suggested that minimum mixing spatial scale change by the each mixing ratio of the wet biogas.

Weather Types, temperature and relief relationship in the Iberian Peninsula: A regional adiabatic processes under directional weather types

NASA Astrophysics Data System (ADS)

Peña Angulo, Dhais; Trigo, Ricardo; Cortesi, Nicola; Gonzalez-Hidalgo, Jose Carlos

2016-04-01

We have analyzed at monthly scale the spatial distribution of Pearson correlation between monthly mean of maximum (Tmax) and minimum (Tmin) temperatures with weather types (WTs) in the Iberian Peninsula (IP), represent them in a high spatial resolution grid (10km x 10km) from MOTEDAS dataset (Gonzalez-Hidalgo et al., 2015a). The WT classification was that developed by Jenkinson and Collison, adapted to the Iberian Peninsula by Trigo and DaCamara, using Sea Level Pressure data from NCAR/NCEP Reanalysis dataset (period 1951-2010). The spatial distribution of Pearson correlations shows a clear zonal gradient in Tmax under the zonal advection produced in westerly (W) and easterly (E) flows, with negative correlation in the coastland where the air mass come from but positive correlation to the inland areas. The same is true under North-West (NW), North-East (NE), South-West (SW) and South-East (SE) WTs. These spatial gradients are coherent with the spatial distribution of the main mountain chain and offer an example of regional adiabatic phenomena that affect the entire IP (Peña-Angulo et al., 2015b). These spatial gradients have not been observed in Tmin. We suggest that Tmin values are less sensitive to changes in Sea Level Pressure and more related to local factors. These directional WT present a monthly frequency over 10 days and could be a valuable tool for downscaling processes. González-Hidalgo J.C., Peña-Angulo D., Brunetti M., Cortesi, C. (2015a): MOTEDAS: a new monthly temperature database for mainland Spain and the trend in temperature (1951-2010). International Journal of Climatology 31, 715-731. DOI: 10.1002/joc.4298 Peña-Angulo, D., Trigo, R., Cortesi, C., González-Hidalgo, J.C. (2015b): The influence of weather types on the monthly average maximum and minimum temperatures in the Iberian Peninsula. Submitted to Hydrology and Earth System Sciences.

Joint Entropy for Space and Spatial Frequency Domains Estimated from Psychometric Functions of Achromatic Discrimination

PubMed Central

Silveira, Vladímir de Aquino; Souza, Givago da Silva; Gomes, Bruno Duarte; Rodrigues, Anderson Raiol; Silveira, Luiz Carlos de Lima

2014-01-01

We used psychometric functions to estimate the joint entropy for space discrimination and spatial frequency discrimination. Space discrimination was taken as discrimination of spatial extent. Seven subjects were tested. Gábor functions comprising unidimensionalsinusoidal gratings (0.4, 2, and 10 cpd) and bidimensionalGaussian envelopes (1°) were used as reference stimuli. The experiment comprised the comparison between reference and test stimulithat differed in grating's spatial frequency or envelope's standard deviation. We tested 21 different envelope's standard deviations around the reference standard deviation to study spatial extent discrimination and 19 different grating's spatial frequencies around the reference spatial frequency to study spatial frequency discrimination. Two series of psychometric functions were obtained for 2%, 5%, 10%, and 100% stimulus contrast. The psychometric function data points for spatial extent discrimination or spatial frequency discrimination were fitted with Gaussian functions using the least square method, and the spatial extent and spatial frequency entropies were estimated from the standard deviation of these Gaussian functions. Then, joint entropy was obtained by multiplying the square root of space extent entropy times the spatial frequency entropy. We compared our results to the theoretical minimum for unidimensional Gábor functions, 1/4π or 0.0796. At low and intermediate spatial frequencies and high contrasts, joint entropy reached levels below the theoretical minimum, suggesting non-linear interactions between two or more visual mechanisms. We concluded that non-linear interactions of visual pathways, such as the M and P pathways, could explain joint entropy values below the theoretical minimum at low and intermediate spatial frequencies and high contrasts. These non-linear interactions might be at work at intermediate and high contrasts at all spatial frequencies once there was a substantial decrease in joint entropy for these stimulus conditions when contrast was raised. PMID:24466158

Joint entropy for space and spatial frequency domains estimated from psychometric functions of achromatic discrimination.

PubMed

Silveira, Vladímir de Aquino; Souza, Givago da Silva; Gomes, Bruno Duarte; Rodrigues, Anderson Raiol; Silveira, Luiz Carlos de Lima

2014-01-01

We used psychometric functions to estimate the joint entropy for space discrimination and spatial frequency discrimination. Space discrimination was taken as discrimination of spatial extent. Seven subjects were tested. Gábor functions comprising unidimensionalsinusoidal gratings (0.4, 2, and 10 cpd) and bidimensionalGaussian envelopes (1°) were used as reference stimuli. The experiment comprised the comparison between reference and test stimulithat differed in grating's spatial frequency or envelope's standard deviation. We tested 21 different envelope's standard deviations around the reference standard deviation to study spatial extent discrimination and 19 different grating's spatial frequencies around the reference spatial frequency to study spatial frequency discrimination. Two series of psychometric functions were obtained for 2%, 5%, 10%, and 100% stimulus contrast. The psychometric function data points for spatial extent discrimination or spatial frequency discrimination were fitted with Gaussian functions using the least square method, and the spatial extent and spatial frequency entropies were estimated from the standard deviation of these Gaussian functions. Then, joint entropy was obtained by multiplying the square root of space extent entropy times the spatial frequency entropy. We compared our results to the theoretical minimum for unidimensional Gábor functions, 1/4π or 0.0796. At low and intermediate spatial frequencies and high contrasts, joint entropy reached levels below the theoretical minimum, suggesting non-linear interactions between two or more visual mechanisms. We concluded that non-linear interactions of visual pathways, such as the M and P pathways, could explain joint entropy values below the theoretical minimum at low and intermediate spatial frequencies and high contrasts. These non-linear interactions might be at work at intermediate and high contrasts at all spatial frequencies once there was a substantial decrease in joint entropy for these stimulus conditions when contrast was raised.

TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958-2015.

PubMed

Abatzoglou, John T; Dobrowski, Solomon Z; Parks, Sean A; Hegewisch, Katherine C

2018-01-09

We present TerraClimate, a dataset of high-spatial resolution (1/24°, ~4-km) monthly climate and climatic water balance for global terrestrial surfaces from 1958-2015. TerraClimate uses climatically aided interpolation, combining high-spatial resolution climatological normals from the WorldClim dataset, with coarser resolution time varying (i.e., monthly) data from other sources to produce a monthly dataset of precipitation, maximum and minimum temperature, wind speed, vapor pressure, and solar radiation. TerraClimate additionally produces monthly surface water balance datasets using a water balance model that incorporates reference evapotranspiration, precipitation, temperature, and interpolated plant extractable soil water capacity. These data provide important inputs for ecological and hydrological studies at global scales that require high spatial resolution and time varying climate and climatic water balance data. We validated spatiotemporal aspects of TerraClimate using annual temperature, precipitation, and calculated reference evapotranspiration from station data, as well as annual runoff from streamflow gauges. TerraClimate datasets showed noted improvement in overall mean absolute error and increased spatial realism relative to coarser resolution gridded datasets.

TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958-2015

NASA Astrophysics Data System (ADS)

Abatzoglou, John T.; Dobrowski, Solomon Z.; Parks, Sean A.; Hegewisch, Katherine C.

2018-01-01

We present TerraClimate, a dataset of high-spatial resolution (1/24°, ~4-km) monthly climate and climatic water balance for global terrestrial surfaces from 1958-2015. TerraClimate uses climatically aided interpolation, combining high-spatial resolution climatological normals from the WorldClim dataset, with coarser resolution time varying (i.e., monthly) data from other sources to produce a monthly dataset of precipitation, maximum and minimum temperature, wind speed, vapor pressure, and solar radiation. TerraClimate additionally produces monthly surface water balance datasets using a water balance model that incorporates reference evapotranspiration, precipitation, temperature, and interpolated plant extractable soil water capacity. These data provide important inputs for ecological and hydrological studies at global scales that require high spatial resolution and time varying climate and climatic water balance data. We validated spatiotemporal aspects of TerraClimate using annual temperature, precipitation, and calculated reference evapotranspiration from station data, as well as annual runoff from streamflow gauges. TerraClimate datasets showed noted improvement in overall mean absolute error and increased spatial realism relative to coarser resolution gridded datasets.

Spatial variability of organic layer thickness and carbon stocks in mature boreal forest stands--implications and suggestions for sampling designs.

PubMed

Kristensen, Terje; Ohlson, Mikael; Bolstad, Paul; Nagy, Zoltan

2015-08-01

Accurate field measurements from inventories across fine spatial scales are critical to improve sampling designs and to increase the precision of forest C cycling modeling. By studying soils undisturbed from active forest management, this paper gives a unique insight in the naturally occurring variability of organic layer C and provides valuable references against which subsequent and future sampling schemes can be evaluated. We found that the organic layer C stocks displayed great short-range variability with spatial autocorrelation distances ranging from 0.86 up to 2.85 m. When spatial autocorrelations are known, we show that a minimum of 20 inventory samples separated by ∼5 m is needed to determine the organic layer C stock with a precision of ±0.5 kg C m(-2). Our data also demonstrates a strong relationship between the organic layer C stock and horizon thickness (R (2) ranging from 0.58 to 0.82). This relationship suggests that relatively inexpensive measurements of horizon thickness can supplement soil C sampling, by reducing the number of soil samples collected, or to enhance the spatial resolution of organic layer C mapping.

Holographic grating relaxation technique for soft matter science

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

Lesnichii, Vasilii, E-mail: vasilii.lesnichii@physchem.uni-freiburg.de; ITMO University, Kronverksky prospekt 49, Saint-Petersburg 197101; Kiessling, Andy

2016-06-17

The holographic grating relaxation technique also known as forced Rayleigh scattering consists basically in writing a holographic grating in the specimen of interest and monitoring its diffraction efficiency as a function of time, from which valuable information on mass or heat transfer and photoinduced transformations can be extracted. In a more detailed view, the shape of the relaxation curve and the relaxation rate as a function of the grating period were found to be affected by the architecture of diffusing species (molecular probes) that constitute the grating, as well as that of the environment they diffuse in, thus making itmore » possible to access and study spatial heterogeneity of materials and different modes of e.g., polymer motion. Minimum displacements and spatial domains approachable by the technique are in nanometer range, well below spatial periods of holographic gratings. In the present paper, several cases of holographic relaxation in heterogeneous media and complex motions are exemplified. Nano- to micro-structures or inhomogeneities comparable in spatial scale with holographic gratings manifest themselves in relaxation experiments via non-exponential decay (stepwise or stretched), spatial-period-dependent apparent diffusion coefficient, or unusual dependence of diffusion coefficient on molecular volume of diffusing probes.« less

Assessment of Rainfall Estimates Using a Standard Z-R Relationship and the Probability Matching Method Applied to Composite Radar Data in Central Florida

NASA Technical Reports Server (NTRS)

Crosson, William L.; Duchon, Claude E.; Raghavan, Ravikumar; Goodman, Steven J.

1996-01-01

Precipitation estimates from radar systems are a crucial component of many hydrometeorological applications, from flash flood forecasting to regional water budget studies. For analyses on large spatial scales and long timescales, it is frequently necessary to use composite reflectivities from a network of radar systems. Such composite products are useful for regional or national studies, but introduce a set of difficulties not encountered when using single radars. For instance, each contributing radar has its own calibration and scanning characteristics, but radar identification may not be retained in the compositing procedure. As a result, range effects on signal return cannot be taken into account. This paper assesses the accuracy with which composite radar imagery can be used to estimate precipitation in the convective environment of Florida during the summer of 1991. Results using Z = 30OR(sup 1.4) (WSR-88D default Z-R relationship) are compared with those obtained using the probability matching method (PMM). Rainfall derived from the power law Z-R was found to he highly biased (+90%-l10%) compared to rain gauge measurements for various temporal and spatial integrations. Application of a 36.5-dBZ reflectivity threshold (determined via the PMM) was found to improve the performance of the power law Z-R, reducing the biases substantially to 20%-33%. Correlations between precipitation estimates obtained with either Z-R relationship and mean gauge values are much higher for areal averages than for point locations. Precipitation estimates from the PMM are an improvement over those obtained using the power law in that biases and root-mean-square errors are much lower. The minimum timescale for application of the PMM with the composite radar dataset was found to be several days for area-average precipitation. The minimum spatial scale is harder to quantify, although it is concluded that it is less than 350 sq km. Implications relevant to the WSR-88D system are discussed.

Detection of the relationship between peak temperature and extreme precipitation

NASA Astrophysics Data System (ADS)

Yu, Y.; Liu, J.; Zhiyong, Y.

2017-12-01

Under the background of climate change and human activities, the characteristics and pattern of precipitation have changed significantly in many regions. As the political and cultural center of China, the structure and character of precipitation in Jingjinji District has varied dramatically in recent years. In this paper, the daily precipitation data throughout the period 1960-2013 are selected for analyzing the spatial-temporal variability of precipitation. The results indicate that the frequency and intensity of precipitation presents an increasing trend. Based on the precipitation data, the maximum, minimum and mean precipitation in different temporal and spatial scales is calculated respectively. The temporal and spatial variation of temperature is obtained by using statistical methods. The relationship between temperature and precipitation in different range is analyzed. The curve relates daily precipitation extremes with local temperatures has a peak structure, increasing at the low-medium range of temperature variations but decreasing at high temperatures. The relationship between extreme precipitation is stronger in downtown than that in suburbs.

27 CFR 19.184 - Scale tank minimum graduations.

Code of Federal Regulations, 2012 CFR

2012-04-01

... graduations. 19.184 Section 19.184 Alcohol, Tobacco Products and Firearms ALCOHOL AND TOBACCO TAX AND TRADE... Requirements Tank Requirements § 19.184 Scale tank minimum graduations. (a) The beams or dials on scale tanks used for tax determination must have minimum graduations not greater than the following: Quantity to be...

27 CFR 19.184 - Scale tank minimum graduations.

Code of Federal Regulations, 2013 CFR

2013-04-01

... graduations. 19.184 Section 19.184 Alcohol, Tobacco Products and Firearms ALCOHOL AND TOBACCO TAX AND TRADE... Requirements Tank Requirements § 19.184 Scale tank minimum graduations. (a) The beams or dials on scale tanks used for tax determination must have minimum graduations not greater than the following: Quantity to be...

27 CFR 19.184 - Scale tank minimum graduations.

Code of Federal Regulations, 2011 CFR

2011-04-01

... graduations. 19.184 Section 19.184 Alcohol, Tobacco Products and Firearms ALCOHOL AND TOBACCO TAX AND TRADE... Requirements Tank Requirements § 19.184 Scale tank minimum graduations. (a) The beams or dials on scale tanks used for tax determination must have minimum graduations not greater than the following: Quantity to be...

27 CFR 19.184 - Scale tank minimum graduations.

Code of Federal Regulations, 2014 CFR

2014-04-01

... graduations. 19.184 Section 19.184 Alcohol, Tobacco Products and Firearms ALCOHOL AND TOBACCO TAX AND TRADE... Requirements Tank Requirements § 19.184 Scale tank minimum graduations. (a) The beams or dials on scale tanks used for tax determination must have minimum graduations not greater than the following: Quantity to be...

Spatial correlation analysis of urban traffic state under a perspective of community detection

NASA Astrophysics Data System (ADS)

Yang, Yanfang; Cao, Jiandong; Qin, Yong; Jia, Limin; Dong, Honghui; Zhang, Aomuhan

2018-05-01

Understanding the spatial correlation of urban traffic state is essential for identifying the evolution patterns of urban traffic state. However, the distribution of traffic state always has characteristics of large spatial span and heterogeneity. This paper adapts the concept of community detection to the correlation network of urban traffic state and proposes a new perspective to identify the spatial correlation patterns of traffic state. In the proposed urban traffic network, the nodes represent road segments, and an edge between a pair of nodes is added depending on the result of significance test for the corresponding correlation of traffic state. Further, the process of community detection in the urban traffic network (named GWPA-K-means) is applied to analyze the spatial dependency of traffic state. The proposed method extends the traditional K-means algorithm in two steps: (i) redefines the initial cluster centers by two properties of nodes (the GWPA value and the minimum shortest path length); (ii) utilizes the weight signal propagation process to transfer the topological information of the urban traffic network into a node similarity matrix. Finally, numerical experiments are conducted on a simple network and a real urban road network in Beijing. The results show that GWPA-K-means algorithm is valid in spatial correlation analysis of traffic state. The network science and community structure analysis perform well in describing the spatial heterogeneity of traffic state on a large spatial scale.

Spatial variations of sea level along the coast of Thailand: Impacts of extreme land subsidence, earthquakes and the seasonal monsoon

NASA Astrophysics Data System (ADS)

Saramul, Suriyan; Ezer, Tal

2014-11-01

The study addresses two important issues associated with sea level along the coasts of Thailand: first, the fast sea level rise and its spatial variation, and second, the monsoonal-driven seasonal variations in sea level. Tide gauge data that are more extensive than in past studies were obtained from several different local and global sources, and relative sea level rise (RSLR) rates were obtained from two different methods, linear regressions and non-linear Empirical Mode Decomposition/Hilbert-Huang Transform (EMD/HHT) analysis. The results show extremely large spatial variations in RSLR, with rates varying from ~ 1 mm y-1 to ~ 20 mm y-1; the maximum RSLR is found in the upper Gulf of Thailand (GOT) near Bangkok, where local land subsidence due to groundwater extraction dominates the trend. Furthermore, there are indications that RSLR rates increased significantly in all locations after the 2004 Sumatra-Andaman Earthquake and the Indian Ocean tsunami that followed, so that recent RSLR rates seem to have less spatial differences than in the past, but with high rates of ~ 20-30 mm y-1 almost everywhere. The seasonal sea level cycle was found to be very different between stations in the GOT, which have minimum sea level in June-July, and stations in the Andaman Sea, which have minimum sea level in February. The seasonal sea-level variations in the GOT are driven mostly by large-scale wind-driven set-up/set-down processes associated with the seasonal monsoon and have amplitudes about ten times larger than either typical steric changes at those latitudes or astronomical annual tides.

Design Considerations of Polishing Lap for Computer-Controlled Cylindrical Polishing Process

NASA Technical Reports Server (NTRS)

Khan, Gufran S.; Gubarev, Mikhail; Arnold, William; Ramsey, Brian D.

2009-01-01

This paper establishes a relationship between the polishing process parameters and the generation of mid spatial-frequency error. The consideration of the polishing lap design to optimize the process in order to keep residual errors to a minimum and optimization of the process (speeds, stroke, etc.) and to keep the residual mid spatial-frequency error to a minimum, is also presented.

Node Deployment with k-Connectivity in Sensor Networks for Crop Information Full Coverage Monitoring

PubMed Central

Liu, Naisen; Cao, Weixing; Zhu, Yan; Zhang, Jingchao; Pang, Fangrong; Ni, Jun

2016-01-01

Wireless sensor networks (WSNs) are suitable for the continuous monitoring of crop information in large-scale farmland. The information obtained is great for regulation of crop growth and achieving high yields in precision agriculture (PA). In order to realize full coverage and k-connectivity WSN deployment for monitoring crop growth information of farmland on a large scale and to ensure the accuracy of the monitored data, a new WSN deployment method using a genetic algorithm (GA) is here proposed. The fitness function of GA was constructed based on the following WSN deployment criteria: (1) nodes must be located in the corresponding plots; (2) WSN must have k-connectivity; (3) WSN must have no communication silos; (4) the minimum distance between node and plot boundary must be greater than a specific value to prevent each node from being affected by the farmland edge effect. The deployment experiments were performed on natural farmland and on irregular farmland divided based on spatial differences of soil nutrients. Results showed that both WSNs gave full coverage, there were no communication silos, and the minimum connectivity of nodes was equal to k. The deployment was tested for different values of k and transmission distance (d) to the node. The results showed that, when d was set to 200 m, as k increased from 2 to 4 the minimum connectivity of nodes increases and is equal to k. When k was set to 2, the average connectivity of all nodes increased in a linear manner with the increase of d from 140 m to 250 m, and the minimum connectivity does not change. PMID:27941704

Efficient and equitable spatial allocation of renewable power plants at the country scale

NASA Astrophysics Data System (ADS)

Drechsler, Martin; Egerer, Jonas; Lange, Martin; Masurowski, Frank; Meyerhoff, Jürgen; Oehlmann, Malte

2017-09-01

Globally, the production of renewable energy is undergoing rapid growth. One of the most pressing issues is the appropriate allocation of renewable power plants, as the question of where to produce renewable electricity is highly controversial. Here we explore this issue through analysis of the efficient and equitable spatial allocation of wind turbines and photovoltaic power plants in Germany. We combine multiple methods, including legal analysis, economic and energy modelling, monetary valuation and numerical optimization. We find that minimum distances between renewable power plants and human settlements should be as small as is legally possible. Even small reductions in efficiency lead to large increases in equity. By considering electricity grid expansion costs, we find a more even allocation of power plants across the country than is the case when grid expansion costs are neglected.

An investigation of ionospheric upper transition height variations at low and equatorial latitudes deduced from combined COSMIC and C/NOFS measurements

NASA Astrophysics Data System (ADS)

Yang, Changjun; Zhao, Biqiang; Zhu, Jie; Yue, Xinan; Wan, Weixing

2017-10-01

In this study we propose the combination of topside in-situ ion density data from the Communication/Navigation Outage Forecast System (C/NOFS) along with the electron density profile measurement from Constellation Observing System for Meteorology, Ionosphere & Climate (COSMIC) satellites Radio Occultation (RO) for studying the spatial and temporal variations of the ionospheric upper transition height (hT) and the oxygen ion (O+) density scale height. The latitudinal, local time and seasonal distributions of upper transition height show more consistency between hT re-calculated by the profile of the O+ using an α-Chapman function with linearly variable scale height and that determined from direct in-situ ion composition measurements, than with constant scale height and only the COSMIC data. The discrepancy in the values of hT between the C/NOFS measurement and that derived by the combination of COSMIC and C/NOFS satellites observations with variable scale height turns larger as the solar activity decreases, which suggests that the photochemistry and the electrodynamics of the equatorial ionosphere during the extreme solar minimum period produce abnormal structures in the vertical plasma distribution. The diurnal variation of scale heights (Hm) exhibits a minimum after sunrise and a maximum around noon near the geomagnetic equator. Further, the values of Hm exhibit a maximum in the summer hemisphere during daytime, whereas in the winter hemisphere the maximum is during night. Those features of Hm consistently indicate the prominent role of the vertical electromagnetic (E × B) drift in the equatorial ionosphere.

An investigation of ionospheric upper transition height variations at low and equatorial latitudes deduced from combined COSMIC and C/NOFS measurements

NASA Astrophysics Data System (ADS)

Zhao, Biqiang

2017-04-01

In this study we propose the combination of topside in-situ ion density data from the Communication/Navigation Outage Forecast System (C/NOFS) along with the electron density profile measurement from Constellation Observing System for Meteorology, Ionosphere & Climate (COSMIC) satellites Radio Occultation (RO) for studying the spatial and temporal variations of the ionospheric upper transition height (hT) and the oxygen ion (O+) density scale height. The latitudinal, local time and seasonal distributions of upper transition height show more consistency between hT re-calculated by the profile of the O+ using an a-Chapman function with linearly variable scale height and that determined from direct in-situ ion composition measurements, than with constant scale height and only the COSMIC data. The discrepancy in the values of hT between the C/NOFS measurement and that derived by the combination of COSMIC and C/NOFS satellites observations with variable scale height turns larger as the solar activity decreases, which suggests that the photochemistry and the electrodynamics of the equatorial ionosphere during the extreme solar minimum period produce abnormal structures in the vertical plasma distribution. The diurnal variation of scale heights (Hm) exhibits a minimum after sunrise and a maximum around noon near the geomagnetic equator. Further, the values of Hm exhibit a maximum in the summer hemisphere during daytime, whereas in the winter hemisphere the maximum is during night. Those features of Hm consistently indicate the prominent role of the vertical electromagnetic (E×B) drift in the equatorial ionosphere.

Development and Evaluation of High-Resolution Climate Simulations Over the Mountainous Northeastern United States

NASA Technical Reports Server (NTRS)

Winter, Jonathan M.; Beckage, Brian; Bucini, Gabriela; Horton, Radley M.; Clemins, Patrick J.

2016-01-01

The mountain regions of the northeastern United States are a critical socioeconomic resource for Vermont, New York State, New Hampshire, Maine, and southern Quebec. While global climate models (GCMs) are important tools for climate change risk assessment at regional scales, even the increased spatial resolution of statistically downscaled GCMs (commonly approximately 1/ 8 deg) is not sufficient for hydrologic, ecologic, and land-use modeling of small watersheds within the mountainous Northeast. To address this limitation, an ensemble of topographically downscaled, high-resolution (30"), daily 2-m maximum air temperature; 2-m minimum air temperature; and precipitation simulations are developed for the mountainous Northeast by applying an additional level of downscaling to intermediately downscaled (1/ 8 deg) data using high-resolution topography and station observations. First, observed relationships between 2-m air temperature and elevation and between precipitation and elevation are derived. Then, these relationships are combined with spatial interpolation to enhance the resolution of intermediately downscaled GCM simulations. The resulting topographically downscaled dataset is analyzed for its ability to reproduce station observations. Topographic downscaling adds value to intermediately downscaled maximum and minimum 2-m air temperature at high-elevation stations, as well as moderately improves domain-averaged maximum and minimum 2-m air temperature. Topographic downscaling also improves mean precipitation but not daily probability distributions of precipitation. Overall, the utility of topographic downscaling is dependent on the initial bias of the intermediately downscaled product and the magnitude of the elevation adjustment. As the initial bias or elevation adjustment increases, more value is added to the topographically downscaled product.

Adaptation of a pattern-scaling approach for assessment of local (village/valley) scale water resources and related vulnerabilities in the Upper Indus Basin

NASA Astrophysics Data System (ADS)

Forsythe, Nathan; Kilsby, Chris G.; Fowler, Hayley J.; Archer, David R.

2010-05-01

The water resources of the Upper Indus Basin (UIB) are of the utmost importance to the economic wellbeing of Pakistan. The irrigated agriculture made possible by Indus river runoff underpins the food security for Pakistan's nearly 200 million people. Contributions from hydropower account for more than one fifth of peak installed electrical generating capacity in a country where widespread, prolonged load-shedding handicaps business activity and industrial development. Pakistan's further socio-economic development thus depends largely on optimisation of its precious water resources. Confident, accurate seasonal predictions of water resource availability coupled with sound understanding of interannual variability are urgent insights needed by development planners and infrastructure managers at all levels. This study focuses on the challenge of providing meaningful quantitative information at the village/valley scale in the upper reaches of the UIB. Proceeding by progressive reductions in scale, the typology of the observed UIB hydrological regimes -- glacial, nival and pluvial -- are examined with special emphasis on interannual variability for individual seasons. Variations in discharge (runoff) are compared to observations of climate parameters (temperature, precipitation) and available spatial data (elevation, snow cover and snow-water-equivalent). The first scale presented is composed of the large-scale, long-record gauged UIB tributary basins. The Pakistan Water and Power Development Authority (WAPDA) has maintained these stations for several decades in order to monitor seasonal flows and accumulate data for design of further infrastructure. Data from basins defined by five gauging stations on the Indus, Hunza, Gilgit and Astore rivers are examined. The second scale presented is a set of smaller gauged headwater catchments with short records. These gauges were installed by WAPDA and its partners amongst the international development agencies to assess potential sites for medium-scale infrastructure projects. These catchments are placed in their context within the hydrological regime classification using the spatial data and (remote sensing) observations as well as river gauging measurements. The study assesses the degree of similarity with the larger basins of the same hydrological regime. This assessment focuses on the measured response to observed climate variable anomalies. The smallest scale considered is comprised of a number of case studies at the ungauged village/valley scale. These examples are based on the delineation of areas to which specific communities (villages) have customary (riparian) water rights. These examples were suggested by non-governmental organisations working on grassroots economic development initiatives and small-scale infrastructure projects in the region. The direct observations available for these subcatchments are limited to spatial data (elevation, snow parameters). The challenge at this level is to accurately extrapolate areal values (precipitation, temperature, runoff) from point observations at the basin scale. The study assesses both the degree of similarity in the distribution of spatial parameters to the larger gauged basins and the interannual variability (spatial heterogeneity) of remotely-sensed snow cover and snow-water-equivalent at this subcatchment scale. Based upon the characterisation of spatial and interannual variability at these three spatial scales, the challenges facing local water resource managers and infrastructure operators are enumerated. Local vulnerabilities include, but are not limited to, varying thresholds in irrigation water requirements based on crop-type, minimum base flows for micro-hydropower generation during winter (high load) months and relatively small but growing demand for domestic water usage. In conclusion the study posits potential strategies for managing interannual variability and potential emerging trends. Suggested strategies are guided by the principles of low-risk adaptation, participative decision making and local capacity building.

Compatibility of separatrix density scaling for divertor detachment with H-mode pedestal operation in DIII-D

NASA Astrophysics Data System (ADS)

Leonard, A. W.; McLean, A. G.; Makowski, M. A.; Stangeby, P. C.

2017-08-01

The midplane separatrix density is characterized in response to variations in upstream parallel heat flux density and central density through deuterium gas injection. The midplane density is determined from a high spatial resolution Thomson scattering diagnostic at the midplane with power balance analysis to determine the separatrix location. The heat flux density is varied by scans of three parameters, auxiliary heating, toroidal field with fixed plasma current, and plasma current with fixed safety factor, q 95. The separatrix density just before divertor detachment onset is found to scale consistent with the two-point model when radiative dissipation is taken into account. The ratio of separatrix to pedestal density, n e,sep/n e,ped varies from  ⩽30% to  ⩾60% over the dataset, helping to resolve the conflicting scaling of core plasma density limit and divertor detachment onset. The scaling of the separatrix density at detachment onset is combined with H-mode power threshold scaling to obtain a scaling ratio of minimum n e,sep/n e,ped expected in future devices.

The evolution of altruism in spatial threshold public goods games via an insurance mechanism

NASA Astrophysics Data System (ADS)

Zhang, Jianlei; Zhang, Chunyan

2015-05-01

The persistence of cooperation in public goods situations has become an important puzzle for researchers. This paper considers the threshold public goods games where the option of insurance is provided for players from the standpoint of diversification of risk, envisaging the possibility of multiple strategies in such scenarios. In this setting, the provision point is defined in terms of the minimum number of contributors in one threshold public goods game, below which the game fails. In the presence of risk and insurance, more contributions are motivated if (1) only cooperators can opt to be insured and thus their contribution loss in the aborted games can be (partly or full) covered by the insurance; (2) insured cooperators obtain larger compensation, at lower values of the threshold point (the required minimum number of contributors). Moreover, results suggest the dominance of insured defectors who get a better promotion by more profitable benefits from insurance. We provide results of extensive computer simulations in the realm of spatial games (random regular networks and scale-free networks here), and support this study with analytical results for well-mixed populations. Our study is expected to establish a causal link between the widespread altruistic behaviors and the existing insurance system.

Temporal and spatial variability of aeolian sand transport: Implications for field measurements

NASA Astrophysics Data System (ADS)

Ellis, Jean T.; Sherman, Douglas J.; Farrell, Eugene J.; Li, Bailiang

2012-01-01

Horizontal variability is often cited as one source of disparity between observed and predicted rates of aeolian mass flux, but few studies have quantified the magnitude of this variability. Two field projects were conducted to evaluate meter-scale spatial and temporal in the saltation field. In Shoalhaven Heads, NSW, Australia a horizontal array of passive-style sand traps were deployed on a beach for 600 or 1200 s across a horizontal span of 0.80 m. In Jericoacoara, Brazil, traps spanning 4 m were deployed for 180 and 240 s. Five saltation sensors (miniphones) spaced 1 m apart were also deployed at Jericoacoara. Spatial variation in aeolian transport rates over small spatial and short temporal scales was substantial. The measured transport rates ( Q) obtained from the passive traps ranged from 0.70 to 32.63 g/m/s. When considering all traps, the coefficient of variation ( CoV) values ranged from 16.6% to 67.8%, and minimum and maximum range of variation coefficient ( RVC) values were 106.1% to 152.5% and 75.1% to 90.8%, respectively. The miniphone Q and CoV averaged 47.1% and 4.1% for the 1260 s data series, which was subsequently sub-sampled at 60-630 s intervals to simulate shorter deployment times. A statistically significant ( p < 0.002), inverselinear relationship was found between sample duration and CoV and between Q and CoV, the latter relationship also considering data from previous studies.

SSS variability inferred from recent SMOS reprocessing at CATDS

NASA Astrophysics Data System (ADS)

Boutin, Jacqueline; Vergely, Jean-Luc; Marchand, Stéphane; Tarot, Stéphane; Hasson, Audrey; Reverdin, Gilles

2017-04-01

The Soil Moisture and Ocean Salinity (SMOS) satellite mission has monitored sea surface salinity (SSS) over the global ocean for over 7 years. In this poster, we present results obtained at the LOCEAN/ACRI-st expertise center using recent CATDS (Centre Aval de Traitement des Données) SMOS RE05 reprocessing., We find that correction for systematic errors and removal of data contaminated by ice and radio frequency interferences in fresh regions (river mouths, high latitudes) has been improved with respect to SMOS CATDS RE04 reprocessing. We analyze SSS variability as observed by SMOS on a wide range of spatial and temporal scales using various statistical indicators such as mean, median, standard deviation, minimum, maximum values and spectral analysis. We compare them with ARGO interpolated fields (In Situ Analysis System fields) at global scale and with ship SSS transects from the GOSUD and ORE SSS data base. This allows us 1) to demonstrate and quantify the improvement of SMOS SSS fields with respect to earlier versions and 2) to study SSS variability, especially at spatial scales between 50km and 600km not well covered globally by in situ network. The complementarity of this information with respect to SMAP (Soil Moisture Active Passive) SSS fields will be discussed.

Mediterranean dryland Mosaic: The effect of scale on core area metrics

NASA Astrophysics Data System (ADS)

Alhamad, Mohammad Noor; Alrababah, Mohammad

2014-05-01

Quantifying landscape spatial pattern is essential to understanding the relationship between landscape structure and ecological functions and process. Many landscape metrics have been developed to quantify spatial heterogeneity. Landscape metrics have been employed to measure the impact of humans on landscapes. We examined the response of four core areas metrics to a large range of grain sizes in Mediterranean dryland landscapes. The investigated metrics were (1) mean core area (CORE-MN), (2) area weighted mean core area (CORE-AM) , (3) total core area (TCA) and (4) core area percentage of landscape (CPLAND) within six land use types (urban, agriculture, olive orchids, forestry, shrubland and rangeland). Agriculture areas showed the highest value for minimum TCA (2779.4 ha) within the tested grain sizes, followed by rangeland (1778.3 ha) and Forest (1488.5 ha). On the other hand, shrubland showed the lowest TCA (8.0 ha). The minimum CPLAND values were ranged from 0.002 for shrubland to 0.682 for agriculture land use. The maximum CORE-MN among the tested land use type at all levels of grain sizes was exhibited by agriculture land use type (519.759 ha). The core area metrics showed three types of behavior in response to changing grain size in all landuse types. CORE-MN showed predictable relationship, best explained by non-linear responses to changing grain size (R2=0.99). Both TCA and CPLAND exhibited domain of scale effect in response to changing grain size. The threshold behavior for TCA and CPLAND was at the 4 x 4 grain size (about 1.3 ha). However, CORE-AM exhibited erratic behavior. The unique domain of scale-like behavior may be attributed to the unique characteristics of dryland Mediterranean landscapes; where both natural processes and ancient human activities play a great role in shaping the apparent pattern of the landscape

Spatial variability structure of soil CO2 emission and soil physical and chemical properties characterized by fractal dimension in sugarcane areas

NASA Astrophysics Data System (ADS)

Bicalho, E. S.; Teixeira, D. B.; Panosso, A. R.; Perillo, L. I.; Iamaguti, J. L.; Pereira, G. T.; La Scala, N., Jr.

2012-04-01

Soil CO2 emission (FCO2) is influenced by chemical, physical and biological factors that affect the production of CO2 in the soil and its transport to the atmosphere, varying in time and space depending on environmental conditions, including the management of agricultural area. The aim of this study was to investigate the structure of spatial variability of FCO2 and soil properties by using fractal dimension (DF), derived from isotropic variograms at different scales, and construction of fractograms. The experimental area consisted of a regular grid of 60 × 60 m on sugarcane area under green management, containing 141 points spaced at minimum distances ranging from 0.5 to 10 m. Soil CO2 emission, soil temperature and soil moisture were evaluated over a period of 7 days, and soil chemical and physical properties were determined by sampling at a depth of 0.0 to 0.1 m. FCO2 showed an overall average of 1.51 µmol m-2 s-1, correlated significantly (p < 0.05) with soil physical factors such as soil bulk density, air-filled pore space, macroporosity and microporosity. Significant DF values were obtained in the characterization of FCO2 in medium and large scales (from 20 m). Variations in DF with the scale, which is the fractogram, indicate that the structure of FCO2 variability is similar to that observed for the soil temperature and total pore volume, and reverse for the other soil properties, except for macroporosity, sand content, soil organic matter, carbon stock, C/N ratio and CEC, which fractograms were not significantly correlated to the FCO2 fractogram. Thus, the structure of spatial variability for most soil properties, characterized by fractogram, presents a significant relationship with the structure of spatial variability of FCO2, generally with similar or dissimilar behavior, indicating the possibility of using the fractogram as tool to better observe the behavior of the spatial dependence of the variables along the scale.

Mapping wildfire danger at regional scale with an index model integrating coarse spatial resolution remote sensing data

NASA Astrophysics Data System (ADS)

ChéRet, VéRonique; Denux, Jean Philippe

2007-06-01

Wildfires are a prevalent natural hazard in the south of France. Planners need a permanent fire danger assessment valid for several years over a territory as large and heterogeneous as Midi-Pyrénées region. To this end, we developed an expert knowledge-based index model adapted to the specific features of the study area. The fire danger depends on two complementary elements: spatial occurrence and fire intensity. Among the GIS layers identified as input variables for modeling, vegetation fire susceptibility is one of the most influent. However, the main difficulty at this scale is the scarcity or the lack of exhaustiveness of the data. In this respect, remote sensing imagery is capable of providing relevant information. We proposed to calculate an annual relative greenness index (annual RGRE) that reflects vegetation dryness in summer. We processed times series of Normalized Difference Vegetation Index (NDVI) from SPOT-VEGETATION images over the last six available years (1998 to 2003). The first step was to verify that these images characterize vegetation types and highlight intraannual and interannual response variability. It is then possible to identify phenological stages corresponding to the maximum NDVI (and therefore to maximum photosynthetic activity) during the growing season, the minimum NDVI at the end of the growing season and the minimum NDVI during winter period. These phenology metrics ground the annual RGRE calculation. Values obtained for each observation year show significant correlation (r2 = 0.70) with the De Martonne aridity index calculated for the same period. A synthesis of yearly index was integrated in the model as a variable that expresses fire susceptibility.

Spatially valid data of atmospheric deposition of heavy metals and nitrogen derived by moss surveys for pollution risk assessments of ecosystems.

PubMed

Schröder, Winfried; Nickel, Stefan; Schönrock, Simon; Meyer, Michaela; Wosniok, Werner; Harmens, Harry; Frontasyeva, Marina V; Alber, Renate; Aleksiayenak, Julia; Barandovski, Lambe; Carballeira, Alejo; Danielsson, Helena; de Temmermann, Ludwig; Godzik, Barbara; Jeran, Zvonka; Karlsson, Gunilla Pihl; Lazo, Pranvera; Leblond, Sebastien; Lindroos, Antti-Jussi; Liiv, Siiri; Magnússon, Sigurður H; Mankovska, Blanka; Martínez-Abaigar, Javier; Piispanen, Juha; Poikolainen, Jarmo; Popescu, Ion V; Qarri, Flora; Santamaria, Jesus Miguel; Skudnik, Mitja; Špirić, Zdravko; Stafilov, Trajce; Steinnes, Eiliv; Stihi, Claudia; Thöni, Lotti; Uggerud, Hilde Thelle; Zechmeister, Harald G

2016-06-01

For analysing element input into ecosystems and associated risks due to atmospheric deposition, element concentrations in moss provide complementary and time-integrated data at high spatial resolution every 5 years since 1990. The paper reviews (1) minimum sample sizes needed for reliable, statistical estimation of mean values at four different spatial scales (European and national level as well as landscape-specific level covering Europe and single countries); (2) trends of heavy metal (HM) and nitrogen (N) concentrations in moss in Europe (1990-2010); (3) correlations between concentrations of HM in moss and soil specimens collected across Norway (1990-2010); and (4) canopy drip-induced site-specific variation of N concentration in moss sampled in seven European countries (1990-2013). While the minimum sample sizes on the European and national level were achieved without exception, for some ecological land classes and elements, the coverage with sampling sites should be improved. The decline in emission and subsequent atmospheric deposition of HM across Europe has resulted in decreasing HM concentrations in moss between 1990 and 2010. In contrast, hardly any changes were observed for N in moss between 2005, when N was included into the survey for the first time, and 2010. In Norway, both, the moss and the soil survey data sets, were correlated, indicating a decrease of HM concentrations in moss and soil. At the site level, the average N deposition inside of forests was almost three times higher than the average N deposition outside of forests.

Fundamental limits to the accuracy of deuterium isotopes for identifying the spatial origin of migratory animals

USGS Publications Warehouse

Farmer, A.; Cade, B.S.; Torres-Dowdall, J.

2008-01-01

Deuterium isotope analyses have revolutionized the study of migratory connectivity because global gradients of deuterium in precipitation (??DP) are expressed on a continental scale. Several authors have constructed continental scale base maps of ??DP to provide a spatial reference for studying the movement patterns of migratory species and, although they are very useful, these maps present a static, 40-year average view of the landscape that ignores much underlying inter-annual variation. To more fully understand the consequences of this underlying variation, we analyzed the GNIP deuterium data, the source for all current ??DP maps, to estimate the minimum separation in ??DP (and latitude) necessary to conclude with a given level of confidence that distinct ??DP values represent different geographic sites. Extending analyses of ??DP successfully to deuterium in tissues of living organisms, e.g., feathers in migratory birds (??DF), is dependent on the existence of geographic separation of ??DP, where every geographic location has a distribution of values associated with temporal variability in ??DP. Analyses were conducted for three distinct geographic regions: North America, eastern North America (east of longitude 100??W), and Argentina. At the 80% confidence level, the minimum separation values were 12, 7, and 14?? of latitude (equivalent to 53, 31, and 32???) for North America, eastern North America, and Argentina, respectively. Hence, in eastern North America, for example, one may not be able to accurately assign individual samples to sites separated by less than about 7?? of latitude as the distributions of ??DP were not distinct at latitudes <7?? apart. Moreover, two samples that differ by less than 31??? cannot be confidently said to originate from different latitudes. These estimates of minimum separation for ??DP do not include other known sources of variation in feather deuterium (??D F) and hence are a first order approximation that may be useful, in the absence of more specific information for the system of interest, for planning and interpreting the results of new stable isotope studies. ?? 2008 Springer-Verlag.

Damped regional-scale stress inversions: Methodology and examples for southern California and the Coalinga aftershock sequence

USGS Publications Warehouse

Hardebeck, J.L.; Michael, A.J.

2006-01-01

We present a new focal mechanism stress inversion technique to produce regional-scale models of stress orientation containing the minimum complexity necessary to fit the data. Current practice is to divide a region into small subareas and to independently fit a stress tensor to the focal mechanisms of each subarea. This procedure may lead to apparent spatial variability that is actually an artifact of overfitting noisy data or nonuniquely fitting data that does not completely constrain the stress tensor. To remove these artifacts while retaining any stress variations that are strongly required by the data, we devise a damped inversion method to simultaneously invert for stress in all subareas while minimizing the difference in stress between adjacent subareas. This method is conceptually similar to other geophysical inverse techniques that incorporate damping, such as seismic tomography. In checkerboard tests, the damped inversion removes the stress rotation artifacts exhibited by an undamped inversion, while resolving sharper true stress rotations than a simple smoothed model or a moving-window inversion. We show an example of a spatially damped stress field for southern California. The methodology can also be used to study temporal stress changes, and an example for the Coalinga, California, aftershock sequence is shown. We recommend use of the damped inversion technique for any study examining spatial or temporal variations in the stress field.

Inverse modelling of fluvial sediment connectivity identifies characteristics and spatial distribution of sediment sources in a large river network.

NASA Astrophysics Data System (ADS)

Schmitt, R. J. P.; Bizzi, S.; Kondolf, G. M.; Rubin, Z.; Castelletti, A.

2016-12-01

Field and laboratory evidence indicates that the spatial distribution of transport in both alluvial and bedrock rivers is an adaptation to sediment supply. Sediment supply, in turn, depends on spatial distribution and properties (e.g., grain sizes and supply rates) of individual sediment sources. Analyzing the distribution of transport capacity in a river network could hence clarify the spatial distribution and properties of sediment sources. Yet, challenges include a) identifying magnitude and spatial distribution of transport capacity for each of multiple grain sizes being simultaneously transported, and b) estimating source grain sizes and supply rates, both at network scales. Herein, we approach the problem of identifying the spatial distribution of sediment sources and the resulting network sediment fluxes in a major, poorly monitored tributary (80,000 km2) of the Mekong. Therefore, we apply the CASCADE modeling framework (Schmitt et al. (2016)). CASCADE calculates transport capacities and sediment fluxes for multiple grainsizes on the network scale based on remotely-sensed morphology and modelled hydrology. CASCADE is run in an inverse Monte Carlo approach for 7500 random initializations of source grain sizes. In all runs, supply of each source is inferred from the minimum downstream transport capacity for the source grain size. Results for each realization are compared to sparse available sedimentary records. Only 1 % of initializations reproduced the sedimentary record. Results for these realizations revealed a spatial pattern in source supply rates, grain sizes, and network sediment fluxes that correlated well with map-derived patterns in lithology and river-morphology. Hence, we propose that observable river hydro-morphology contains information on upstream source properties that can be back-calculated using an inverse modeling approach. Such an approach could be coupled to more detailed models of hillslope processes in future to derive integrated models of hillslope production and fluvial transport processes, which is particularly useful to identify sediment provenance in poorly monitored river basins.

Segmentation and clustering as complementary sources of information

NASA Astrophysics Data System (ADS)

Dale, Michael B.; Allison, Lloyd; Dale, Patricia E. R.

2007-03-01

This paper examines the effects of using a segmentation method to identify change-points or edges in vegetation. It identifies coherence (spatial or temporal) in place of unconstrained clustering. The segmentation method involves change-point detection along a sequence of observations so that each cluster formed is composed of adjacent samples; this is a form of constrained clustering. The protocol identifies one or more models, one for each section identified, and the quality of each is assessed using a minimum message length criterion, which provides a rational basis for selecting an appropriate model. Although the segmentation is less efficient than clustering, it does provide other information because it incorporates textural similarity as well as homogeneity. In addition it can be useful in determining various scales of variation that may apply to the data, providing a general method of small-scale pattern analysis.

Variation in the Mississippi River Plume from Data Synthesis of Model Outputs and MODIS Imagery

NASA Astrophysics Data System (ADS)

Fitzpatrick, C.; Kolker, A.; Chu, P. Y.

2017-12-01

Understanding the Mississippi River (MR) plume's interaction with the open ocean is crucial for understanding many processes in the Gulf of Mexico. Though the Mississippi River and its delta and plume have been studied extensively, recent archives of model products and satellite imagery have allowed us to highlight patterns in plume behavior over the last two decades through large scale data synthesis. Using 8 years of USGS discharge data and Landsat imagery, we identified the spatial extent, geographic patterns, depth, and freshwater concentration of the MR plume across seasons and years. Using 20 years of HYCOM (HYbrid Coordinate Ocean Model) analysis and reanalysis model output, and several years of NGOFS FVCOM model outputs, we mapped the minimum and maximum spatial area of the MR plume, and its varied extent east and west. From the synthesis and analysis of these data, the statistical probability of the MR plume's spatial area and geographical extent were computed. Measurements of the MR plume and its response to river discharge may predict future behavior and provide a path forward to understanding MR plume influence on nearby ecosystems.

Static Analysis of Large-Scale Multibody System Using Joint Coordinates and Spatial Algebra Operator

PubMed Central

Omar, Mohamed A.

2014-01-01

Initial transient oscillations inhibited in the dynamic simulations responses of multibody systems can lead to inaccurate results, unrealistic load prediction, or simulation failure. These transients could result from incompatible initial conditions, initial constraints violation, and inadequate kinematic assembly. Performing static equilibrium analysis before the dynamic simulation can eliminate these transients and lead to stable simulation. Most exiting multibody formulations determine the static equilibrium position by minimizing the system potential energy. This paper presents a new general purpose approach for solving the static equilibrium in large-scale articulated multibody. The proposed approach introduces an energy drainage mechanism based on Baumgarte constraint stabilization approach to determine the static equilibrium position. The spatial algebra operator is used to express the kinematic and dynamic equations of the closed-loop multibody system. The proposed multibody system formulation utilizes the joint coordinates and modal elastic coordinates as the system generalized coordinates. The recursive nonlinear equations of motion are formulated using the Cartesian coordinates and the joint coordinates to form an augmented set of differential algebraic equations. Then system connectivity matrix is derived from the system topological relations and used to project the Cartesian quantities into the joint subspace leading to minimum set of differential equations. PMID:25045732

Static analysis of large-scale multibody system using joint coordinates and spatial algebra operator.

PubMed

Omar, Mohamed A

2014-01-01

Initial transient oscillations inhibited in the dynamic simulations responses of multibody systems can lead to inaccurate results, unrealistic load prediction, or simulation failure. These transients could result from incompatible initial conditions, initial constraints violation, and inadequate kinematic assembly. Performing static equilibrium analysis before the dynamic simulation can eliminate these transients and lead to stable simulation. Most exiting multibody formulations determine the static equilibrium position by minimizing the system potential energy. This paper presents a new general purpose approach for solving the static equilibrium in large-scale articulated multibody. The proposed approach introduces an energy drainage mechanism based on Baumgarte constraint stabilization approach to determine the static equilibrium position. The spatial algebra operator is used to express the kinematic and dynamic equations of the closed-loop multibody system. The proposed multibody system formulation utilizes the joint coordinates and modal elastic coordinates as the system generalized coordinates. The recursive nonlinear equations of motion are formulated using the Cartesian coordinates and the joint coordinates to form an augmented set of differential algebraic equations. Then system connectivity matrix is derived from the system topological relations and used to project the Cartesian quantities into the joint subspace leading to minimum set of differential equations.

An adaptive framework to differentiate receiving water quality impacts on a multi-scale level.

PubMed

Blumensaat, F; Tränckner, J; Helm, B; Kroll, S; Dirckx, G; Krebs, P

2013-01-01

The paradigm shift in recent years towards sustainable and coherent water resources management on a river basin scale has changed the subject of investigations to a multi-scale problem representing a great challenge for all actors participating in the management process. In this regard, planning engineers often face an inherent conflict to provide reliable decision support for complex questions with a minimum of effort. This trend inevitably increases the risk to base decisions upon uncertain and unverified conclusions. This paper proposes an adaptive framework for integral planning that combines several concepts (flow balancing, water quality monitoring, process modelling, multi-objective assessment) to systematically evaluate management strategies for water quality improvement. As key element, an S/P matrix is introduced to structure the differentiation of relevant 'pressures' in affected regions, i.e. 'spatial units', which helps in handling complexity. The framework is applied to a small, but typical, catchment in Flanders, Belgium. The application to the real-life case shows: (1) the proposed approach is adaptive, covers problems of different spatial and temporal scale, efficiently reduces complexity and finally leads to a transparent solution; and (2) water quality and emission-based performance evaluation must be done jointly as an emission-based performance improvement does not necessarily lead to an improved water quality status, and an assessment solely focusing on water quality criteria may mask non-compliance with emission-based standards. Recommendations derived from the theoretical analysis have been put into practice.

Species survival and scaling laws in hostile and disordered environments

NASA Astrophysics Data System (ADS)

Rocha, Rodrigo P.; Figueiredo, Wagner; Suweis, Samir; Maritan, Amos

2016-10-01

In this work we study the likelihood of survival of single-species in the context of hostile and disordered environments. Population dynamics in this environment, as modeled by the Fisher equation, is characterized by negative average growth rate, except in some random spatially distributed patches that may support life. In particular, we are interested in the phase diagram of the survival probability and in the critical size problem, i.e., the minimum patch size required for surviving in the long-time dynamics. We propose a measure for the critical patch size as being proportional to the participation ratio of the eigenvector corresponding to the largest eigenvalue of the linearized Fisher dynamics. We obtain the (extinction-survival) phase diagram and the probability distribution function (PDF) of the critical patch sizes for two topologies, namely, the one-dimensional system and the fractal Peano basin. We show that both topologies share the same qualitative features, but the fractal topology requires higher spatial fluctuations to guarantee species survival. We perform a finite-size scaling and we obtain the associated scaling exponents. In addition, we show that the PDF of the critical patch sizes has an universal shape for the 1D case in terms of the model parameters (diffusion, growth rate, etc.). In contrast, the diffusion coefficient has a drastic effect on the PDF of the critical patch sizes of the fractal Peano basin, and it does not obey the same scaling law of the 1D case.

Separating foliar physiology from morphology reveals the relative roles of vertically structured transpiration factors within red maple crowns and limitations of larger scale models

PubMed Central

Bauerle, William L.; Bowden, Joseph D.

2011-01-01

A spatially explicit mechanistic model, MAESTRA, was used to separate key parameters affecting transpiration to provide insights into the most influential parameters for accurate predictions of within-crown and within-canopy transpiration. Once validated among Acer rubrum L. genotypes, model responses to different parameterization scenarios were scaled up to stand transpiration (expressed per unit leaf area) to assess how transpiration might be affected by the spatial distribution of foliage properties. For example, when physiological differences were accounted for, differences in leaf width among A. rubrum L. genotypes resulted in a 25% difference in transpiration. An in silico within-canopy sensitivity analysis was conducted over the range of genotype parameter variation observed and under different climate forcing conditions. The analysis revealed that seven of 16 leaf traits had a ≥5% impact on transpiration predictions. Under sparse foliage conditions, comparisons of the present findings with previous studies were in agreement that parameters such as the maximum Rubisco-limited rate of photosynthesis can explain ∼20% of the variability in predicted transpiration. However, the spatial analysis shows how such parameters can decrease or change in importance below the uppermost canopy layer. Alternatively, model sensitivity to leaf width and minimum stomatal conductance was continuous along a vertical canopy depth profile. Foremost, transpiration sensitivity to an observed range of morphological and physiological parameters is examined and the spatial sensitivity of transpiration model predictions to vertical variations in microclimate and foliage density is identified to reduce the uncertainty of current transpiration predictions. PMID:21617246

Spatial Patterns of Soil Respiration Links Above and Belowground Processes along a Boreal Aspen Fire Chronosequence

PubMed Central

Das Gupta, Sanatan; Mackenzie, M. Derek

2016-01-01

Fire in boreal ecosystems is known to affect CO2 efflux from forest soils, which is commonly termed soil respiration (Rs). However, there is limited information on how fire and recovery from this disturbance affects spatial variation in Rs. The main objective of this study was to quantify the spatial variability of Rs over the growing season in a boreal aspen (Populus tremuloides Michx.) fire chronosequence. The chronosequence included three stands in northern Alberta; a post fire stand (1 year old, PF), a stand at canopy closure (9 years old, CC), and a mature stand (72 years old, MA). Soil respiration, temperature and moisture were measured monthly from May to August using an intensive spatial sampling protocol (n = 42, minimum lag = 2 m). Key aboveground and belowground properties were measured one time at each sampling point. No spatial structure was detected in Rs of the PF stand during the peak growing season (June and July), whereas Rs was auto-correlated at a scale of < 6 m in the CC and MA stands. The PF stand had the lowest mean Rs (4.60 μmol C m-2 s-1) followed by the CC (5.41 μmol C m-2 s-1), and the MA (7.32 μmol C m-2 s-1) stand. Forest floor depth was the only aboveground factor that influenced the spatial pattern of Rs in all three stands and was strongest in the PF stand. Enzyme activity and fine root biomass, on the other hand, were the significant belowground factors driving the spatial pattern of Rs in the CC and MA stands. Persistent joint aboveground and belowground control on Rs in the CC and MA stands indicates a tight spatial coupling, which was not observed in the PF stand. Overall, the current study suggests that fire in the boreal aspen ecosystem alters the spatial structure of Rs and that fine scale heterogeneity develops quickly as stands reach the canopy closure phase (<10 years). PMID:27832089

Spatial Patterns of Soil Respiration Links Above and Belowground Processes along a Boreal Aspen Fire Chronosequence.

PubMed

Das Gupta, Sanatan; Mackenzie, M Derek

2016-01-01

Fire in boreal ecosystems is known to affect CO2 efflux from forest soils, which is commonly termed soil respiration (Rs). However, there is limited information on how fire and recovery from this disturbance affects spatial variation in Rs. The main objective of this study was to quantify the spatial variability of Rs over the growing season in a boreal aspen (Populus tremuloides Michx.) fire chronosequence. The chronosequence included three stands in northern Alberta; a post fire stand (1 year old, PF), a stand at canopy closure (9 years old, CC), and a mature stand (72 years old, MA). Soil respiration, temperature and moisture were measured monthly from May to August using an intensive spatial sampling protocol (n = 42, minimum lag = 2 m). Key aboveground and belowground properties were measured one time at each sampling point. No spatial structure was detected in Rs of the PF stand during the peak growing season (June and July), whereas Rs was auto-correlated at a scale of < 6 m in the CC and MA stands. The PF stand had the lowest mean Rs (4.60 μmol C m-2 s-1) followed by the CC (5.41 μmol C m-2 s-1), and the MA (7.32 μmol C m-2 s-1) stand. Forest floor depth was the only aboveground factor that influenced the spatial pattern of Rs in all three stands and was strongest in the PF stand. Enzyme activity and fine root biomass, on the other hand, were the significant belowground factors driving the spatial pattern of Rs in the CC and MA stands. Persistent joint aboveground and belowground control on Rs in the CC and MA stands indicates a tight spatial coupling, which was not observed in the PF stand. Overall, the current study suggests that fire in the boreal aspen ecosystem alters the spatial structure of Rs and that fine scale heterogeneity develops quickly as stands reach the canopy closure phase (<10 years).

Estimating occupancy and predicting numbers of gray wolf packs in Montana using hunter surveys

USGS Publications Warehouse

Rich, Lindsey N.; Russell, Robin E.; Glenn, Elizabeth M.; Mitchell, Michael S.; Gude, Justin A.; Podruzny, Kevin M.; Sime, Carolyn A.; Laudon, Kent; Ausband, David E.; Nichols, James D.

2013-01-01

Reliable knowledge of the status and trend of carnivore populations is critical to their conservation and management. Methods for monitoring carnivores, however, are challenging to conduct across large spatial scales. In the Northern Rocky Mountains, wildlife managers need a time- and cost-efficient method for monitoring gray wolf (Canis lupus) populations. Montana Fish, Wildlife and Parks (MFWP) conducts annual telephone surveys of >50,000 deer and elk hunters. We explored how survey data on hunters' sightings of wolves could be used to estimate the occupancy and distribution of wolf packs and predict their abundance in Montana for 2007–2009. We assessed model utility by comparing our predictions to MFWP minimum known number of wolf packs. We minimized false positive detections by identifying a patch as occupied if 2–25 wolves were detected by ≥3 hunters. Overall, estimates of the occupancy and distribution of wolf packs were generally consistent with known distributions. Our predictions of the total area occupied increased from 2007 to 2009 and predicted numbers of wolf packs were approximately 1.34–1.46 times the MFWP minimum counts for each year of the survey. Our results indicate that multi-season occupancy models based on public sightings can be used to monitor populations and changes in the spatial distribution of territorial carnivores across large areas where alternative methods may be limited by personnel, time, accessibility, and budget constraints.

Statistical downscaling of mean temperature, maximum temperature, and minimum temperature on the Loess Plateau, China

NASA Astrophysics Data System (ADS)

Jiang, L.

2017-12-01

Climate change is considered to be one of the greatest environmental threats. Global climate models (GCMs) are the primary tool used for studying climate change. However, GCMs are limited because of their coarse spatial resolution and inability to resolve important sub-grid scale features such as terrain and clouds. Statistical downscaling methods can be used to downscale large-scale variables to local-scale. In this study, we assess the applicability of the Statistical Downscaling Model (SDSM) in downscaling the outputs from Beijing Normal University Earth System Model (BNU-ESM). The study focus on the the Loess Plateau, China, and the variables for downscaling include daily mean temperature (TMEAN), maximum temperature (TMAX) and minimum temperature (TMIN). The results show that SDSM performs well for these three climatic variables on the Loess Plateau. After downscaling, the root mean square errors for TMEAN, TMAX, TMIN for BNU-ESM were reduced by 70.9%, 75.1%, and 67.2%, respectively. All the rates of change in TMEAN, TMAX and TMIN during the 21st century decreased after SDSM downscaling. We also show that SDSM can effectively reduce uncertainty, compared with the raw model outputs. TMEAN uncertainty was reduced by 27.1%, 26.8%, and 16.3% for the future scenarios of RCP 2.6, RCP 4.5 and RCP 8.5, respectively. The corresponding reductions in uncertainty were 23.6%, 30.7%, and 18.7% for TMAX; 37.6%, 31.8%, and 23.2% for TMIN.

A high-resolution European dataset for hydrologic modeling

NASA Astrophysics Data System (ADS)

Ntegeka, Victor; Salamon, Peter; Gomes, Goncalo; Sint, Hadewij; Lorini, Valerio; Thielen, Jutta

2013-04-01

There is an increasing demand for large scale hydrological models not only in the field of modeling the impact of climate change on water resources but also for disaster risk assessments and flood or drought early warning systems. These large scale models need to be calibrated and verified against large amounts of observations in order to judge their capabilities to predict the future. However, the creation of large scale datasets is challenging for it requires collection, harmonization, and quality checking of large amounts of observations. For this reason, only a limited number of such datasets exist. In this work, we present a pan European, high-resolution gridded dataset of meteorological observations (EFAS-Meteo) which was designed with the aim to drive a large scale hydrological model. Similar European and global gridded datasets already exist, such as the HadGHCND (Caesar et al., 2006), the JRC MARS-STAT database (van der Goot and Orlandi, 2003) and the E-OBS gridded dataset (Haylock et al., 2008). However, none of those provide similarly high spatial resolution and/or a complete set of variables to force a hydrologic model. EFAS-Meteo contains daily maps of precipitation, surface temperature (mean, minimum and maximum), wind speed and vapour pressure at a spatial grid resolution of 5 x 5 km for the time period 1 January 1990 - 31 December 2011. It furthermore contains calculated radiation, which is calculated by using a staggered approach depending on the availability of sunshine duration, cloud cover and minimum and maximum temperature, and evapotranspiration (potential evapotranspiration, bare soil and open water evapotranspiration). The potential evapotranspiration was calculated using the Penman-Monteith equation with the above-mentioned meteorological variables. The dataset was created as part of the development of the European Flood Awareness System (EFAS) and has been continuously updated throughout the last years. The dataset variables are used as inputs to the hydrological calibration and validation of EFAS as well as for establishing long-term discharge "proxy" climatologies which can then in turn be used for statistical analysis to derive return periods or other time series derivatives. In addition, this dataset will be used to assess climatological trends in Europe. Unfortunately, to date no baseline dataset at the European scale exists to test the quality of the herein presented data. Hence, a comparison against other existing datasets can therefore only be an indication of data quality. Due to availability, a comparison was made for precipitation and temperature only, arguably the most important meteorological drivers for hydrologic models. A variety of analyses was undertaken at country scale against data reported to EUROSTAT and E-OBS datasets. The comparison revealed that while the datasets showed overall similar temporal and spatial patterns, there were some differences in magnitudes especially for precipitation. It is not straightforward to define the specific cause for these differences. However, in most cases the comparatively low observation station density appears to be the principal reason for the differences in magnitude.

Long Distance Movements and Disjunct Spatial Use of Harbor Seals (Phoca vitulina) in the Inland Waters of the Pacific Northwest

PubMed Central

Peterson, Sarah H.; Lance, Monique M.; Jeffries, Steven J.; Acevedo-Gutiérrez, Alejandro

2012-01-01

Background Worldwide, adult harbor seals (Phoca vitulina) typically limit their movements and activity to <50 km from their primary haul-out site. As a result, the ecological impact of harbor seals is viewed as limited to relatively small spatial scales. Harbor seals in the Pacific Northwest are believed to remain <30 km from their primary haul-out site, one of several contributing factors to the current stock designation. However, movement patterns within the region are not well understood because previous studies have used radio-telemetry, which has range limitations. Our objective was to use satellite-telemetry to determine the regional spatial scale of movements. Methodology/Principal Findings Satellite tags were deployed on 20 adult seals (n=16 males and 4 females) from two rocky reefs and a mudflat-bay during April–May 2007. Standard filtering algorithms were used to remove outliers, resulting in an average (± SD) of 693 (±377) locations per seal over 110 (±32) days. A particle filter was implemented to interpolate locations temporally and decrease erroneous locations on land. Minimum over-water distances were calculated between filtered locations and each seal's capture site to show movement of seals over time relative to their capture site, and we estimated utilization distributions from kernel density analysis to reflect spatial use. Eight males moved >100 km from their capture site at least once, two of which traveled round trip to and from the Pacific coast, a total distance >400 km. Disjunct spatial use patterns observed provide new insight into general harbor seal behavior. Conclusions/Significance Long-distance movements and disjunct spatial use of adult harbor seals have not been reported for the study region and are rare worldwide in such a large proportion of tagged individuals. Thus, the ecological influence of individual seals may reach farther than previously assumed. PMID:22723925

Opposing Seasonal Trends in Seawater pH and Aragonite Saturation State on the Bermuda Coral Reef Platform Reveal Complex Controls on Seawater Chemistry by Biological and Physical Processes

NASA Astrophysics Data System (ADS)

Andersson, A. J.; Bates, N. R.; dePutron, S.; Collins, A.; Neely, K.; Best, M.; Noyes, T.

2011-12-01

To accurately predict future consequences of ocean acidification on coastal environments and ecosystems, it is critical to understand present conditions and variability. As part of the Bermuda ocean acidification and coral reef investigation (BEACON), significant efforts have been dedicated to characterize the complete surface seawater carbonic-acid system at different temporal and spatial scales on the Bermuda coral reef platform to understand current levels and variability in seawater CO2 parameters, reef metabolism, and future potential changes arising from ocean acidification. A four years monthly time-series of seawater carbonic-acid parameters at eight different locations on the Bermuda coral reef platform reveals strong seasonal patterns in dissolved inorganic carbon (DIC), total alkalinity (TA), pH, pCO2, and [HCO3-], and somewhat weaker trends in [CO32-] and saturation state with respect to CaCO3 minerals. Strong spatial gradients are also observed in DIC and TA during summertime owing to reef metabolism, but no or weak spatial gradients of these parameters are observed in the wintertime. Interestingly, maximum pH-sws (~8.15) is observed during wintertime when minimum aragonite saturation state (<3.0) is observed. In contrast, minimum pH-sws (~7.95) is observed in the summertime when maximum aragonite saturation state (>3.70) is observed. The observed trends and gradients point to complex relationships and interactions between seawater chemistry, biology and physics that need to be considered in the context of ocean acidification and in making future predictions on the effects of this perturbation on coral reefs and coastal ecosystems.

Actual evapotranspiration and deficit: Biologically meaningful correlates of vegetation distribution across spatial scales

USGS Publications Warehouse

Stephenson, N.L.

1998-01-01

Correlative approaches to understanding the climatic controls of vegetation distribution have exhibited at least two important weaknesses: they have been conceptually divorced across spatial scales, and their climatic parameters have not necessarily represented aspects of climate of broad physiological importance to plants. Using examples from the literature and from the Sierra Nevada of California, I argue that two water balance parameters-actual evapotranspiration (AET) and deficit (D)-are biologically meaningful, are well correlated with the distribution of vegetation types, and exhibit these qualities over several orders of magnitude of spatial scale (continental to local). I reach four additional conclusions. (1) Some pairs of climatic parameters presently in use are functionally similar to AET and D; however, AET and D may be easier to interpret biologically. (2) Several well-known climatic parameters are biologically less meaningful or less important than AET and D, and consequently are poorer correlates of the distribution of vegetation types. Of particular interest, AET is a much better correlate of the distributions of coniferous and deciduous forests than minimum temperature. (3) The effects of evaporative demand and water availability on a site's water balance are intrinsically different. For example, the 'dry' experienced by plants on sunward slopes (high evaporative demand) is not comparable to the 'dry' experienced by plants on soils with low water-holding capacities (low water availability), and these differences are reflected in vegetation patterns. (4) Many traditional topographic moisture scalars-those that additively combine measures related to evaporative demand and water availability are not necessarily meaningful for describing site conditions as sensed by plants; the same holds for measured soil moisture. However, using AET and D in place of moisture scalars and measured soil moisture can solve these problems.

The Effects of Data Gaps on the Calculated Monthly Mean Maximum and Minimum Temperatures in the Continental United States: A Spatial and Temporal Study.

NASA Astrophysics Data System (ADS)

Stooksbury, David E.; Idso, Craig D.; Hubbard, Kenneth G.

1999-05-01

Gaps in otherwise regularly scheduled observations are often referred to as missing data. This paper explores the spatial and temporal impacts that data gaps in the recorded daily maximum and minimum temperatures have on the calculated monthly mean maximum and minimum temperatures. For this analysis 138 climate stations from the United States Historical Climatology Network Daily Temperature and Precipitation Data set were selected. The selected stations had no missing maximum or minimum temperature values during the period 1951-80. The monthly mean maximum and minimum temperatures were calculated for each station for each month. For each month 1-10 consecutive days of data from each station were randomly removed. This was performed 30 times for each simulated gap period. The spatial and temporal impact of the 1-10-day data gaps were compared. The influence of data gaps is most pronounced in the continental regions during the winter and least pronounced in the southeast during the summer. In the north central plains, 10-day data gaps during January produce a standard deviation value greater than 2°C about the `true' mean. In the southeast, 10-day data gaps in July produce a standard deviation value less than 0.5°C about the mean. The results of this study will be of value in climate variability and climate trend research as well as climate assessment and impact studies.

Large-Scale Multiantenna Multisine Wireless Power Transfer

NASA Astrophysics Data System (ADS)

Huang, Yang; Clerckx, Bruno

2017-11-01

Wireless Power Transfer (WPT) is expected to be a technology reshaping the landscape of low-power applications such as the Internet of Things, Radio Frequency identification (RFID) networks, etc. Although there has been some progress towards multi-antenna multi-sine WPT design, the large-scale design of WPT, reminiscent of massive MIMO in communications, remains an open challenge. In this paper, we derive efficient multiuser algorithms based on a generalizable optimization framework, in order to design transmit sinewaves that maximize the weighted-sum/minimum rectenna output DC voltage. The study highlights the significant effect of the nonlinearity introduced by the rectification process on the design of waveforms in multiuser systems. Interestingly, in the single-user case, the optimal spatial domain beamforming, obtained prior to the frequency domain power allocation optimization, turns out to be Maximum Ratio Transmission (MRT). In contrast, in the general weighted sum criterion maximization problem, the spatial domain beamforming optimization and the frequency domain power allocation optimization are coupled. Assuming channel hardening, low-complexity algorithms are proposed based on asymptotic analysis, to maximize the two criteria. The structure of the asymptotically optimal spatial domain precoder can be found prior to the optimization. The performance of the proposed algorithms is evaluated. Numerical results confirm the inefficiency of the linear model-based design for the single and multi-user scenarios. It is also shown that as nonlinear model-based designs, the proposed algorithms can benefit from an increasing number of sinewaves.

Sound production due to large-scale coherent structures

NASA Technical Reports Server (NTRS)

Gatski, T. B.

1979-01-01

The acoustic pressure fluctuations due to large-scale finite amplitude disturbances in a free turbulent shear flow are calculated. The flow is decomposed into three component scales; the mean motion, the large-scale wave-like disturbance, and the small-scale random turbulence. The effect of the large-scale structure on the flow is isolated by applying both a spatial and phase average on the governing differential equations and by initially taking the small-scale turbulence to be in energetic equilibrium with the mean flow. The subsequent temporal evolution of the flow is computed from global energetic rate equations for the different component scales. Lighthill's theory is then applied to the region with the flowfield as the source and an observer located outside the flowfield in a region of uniform velocity. Since the time history of all flow variables is known, a minimum of simplifying assumptions for the Lighthill stress tensor is required, including no far-field approximations. A phase average is used to isolate the pressure fluctuations due to the large-scale structure, and also to isolate the dynamic process responsible. Variation of mean square pressure with distance from the source is computed to determine the acoustic far-field location and decay rate, and, in addition, spectra at various acoustic field locations are computed and analyzed. Also included are the effects of varying the growth and decay of the large-scale disturbance on the sound produced.

Searching for a Cosmological Preferred Direction with 147 Rotationally Supported Galaxies

NASA Astrophysics Data System (ADS)

Zhou, Yong; Zhao, Zhi-Chao; Chang, Zhe

2017-10-01

It is well known that the Milgrom’s modified Newtonian dynamics (MOND) explains well the mass discrepancy problem in galaxy rotation curves. The MOND predicts a universal acceleration scale below which the Newtonian dynamics is still invalid. We get the universal acceleration scale of 1.02 × 10-10 m s-2 by using the Spitzer Photometry and Accurate Rotation Curves (SPARC) data set. Milgrom suggested that the acceleration scale may be a fingerprint of cosmology on local dynamics and related to the Hubble constant g † ˜ cH 0. In this paper, we use the hemisphere comparison method with the SPARC data set to investigate possible spatial anisotropy on the acceleration scale. It is found that the hemisphere of the maximum acceleration scale is in the direction (l,b)=(175\\buildrel{\\circ}\\over{.} {5}-{10^\\circ }+{6^\\circ }, -6\\buildrel{\\circ}\\over{.} {5}-{3^\\circ }+{9^\\circ }) with g †,max = 1.10 × 10-10 m s-2, while the hemisphere of the minimum acceleration scale is in the opposite direction (l,b)=(355\\buildrel{\\circ}\\over{.} {5}-{10^\\circ }+{6^\\circ }, 6\\buildrel{\\circ}\\over{.} {5}-{9^\\circ }+{3^\\circ }) with g †,min = 0.76 × 10-10 m s-2. The level of anisotropy reaches up to 0.37 ± 0.04. Robust tests show that such an anisotropy cannot be reproduced by a statistically isotropic data set. We also show that the spatial anisotropy on the acceleration scale is less correlated with the non-uniform distribution of the SPARC data points in the sky. In addition, we confirm that the anisotropy of the acceleration scale does not depend significantly on other physical parameters of the SPARC galaxies. It is interesting to note that the maximum anisotropy direction found in this paper is close with other cosmological preferred directions, particularly the direction of the “Australia dipole” for the fine structure constant.

Benefits of incorporating spatial organisation of catchments for a semi-distributed hydrological model

NASA Astrophysics Data System (ADS)

Schumann, Andreas; Oppel, Henning

2017-04-01

To represent the hydrological behaviour of catchments a model should reproduce/reflect the hydrologically most relevant catchment characteristics. These are heterogeneously distributed within a watershed but often interrelated and subject of a certain spatial organisation. Since common models are mostly based on fundamental assumptions about hydrological processes, the reduction of variance of catchment properties as well as the incorporation of the spatial organisation of the catchment is desirable. We have developed a method that combines the idea of the width-function used for determination of the geomorphologic unit hydrograph with information about soil or topography. With this method we are able to assess the spatial organisation of selected catchment characteristics. An algorithm was developed that structures a watershed into sub-basins and other spatial units to minimise its heterogeneity. The outcomes of this algorithm are used for the spatial setup of a semi-distributed model. Since the spatial organisation of a catchment is not bound to a single characteristic, we have to embed information of multiple catchment properties. For this purpose we applied a fuzzy-based method to combine the spatial setup for multiple single characteristics into a union, optimal spatial differentiation. Utilizing this method, we are able to propose a spatial structure for a semi-distributed hydrological model, comprising the definition of sub-basins and a zonal classification within each sub-basin. Besides the improved spatial structuring, the performed analysis ameliorates modelling in another way. The spatial variability of catchment characteristics, which is considered by a minimum of heterogeneity in the zones, can be considered in a parameter constrained calibration scheme in a case study both options were used to explore the benefits of incorporating the spatial organisation and derived parameter constraints for the parametrisation of a HBV-96 model. We use two benchmark model setups (lumped and semi-distributed by common approaches) to address the benefits for different time and spatial scales. Moreover, the benefits for calibration effort, model performance in validation periods and process extrapolation are shown.

National-scale cropland mapping based on spectral-temporal features and outdated land cover information.

PubMed

Waldner, François; Hansen, Matthew C; Potapov, Peter V; Löw, Fabian; Newby, Terence; Ferreira, Stefanus; Defourny, Pierre

2017-01-01

The lack of sufficient ground truth data has always constrained supervised learning, thereby hindering the generation of up-to-date satellite-derived thematic maps. This is all the more true for those applications requiring frequent updates over large areas such as cropland mapping. Therefore, we present a method enabling the automated production of spatially consistent cropland maps at the national scale, based on spectral-temporal features and outdated land cover information. Following an unsupervised approach, this method extracts reliable calibration pixels based on their labels in the outdated map and their spectral signatures. To ensure spatial consistency and coherence in the map, we first propose to generate seamless input images by normalizing the time series and deriving spectral-temporal features that target salient cropland characteristics. Second, we reduce the spatial variability of the class signatures by stratifying the country and by classifying each stratum independently. Finally, we remove speckle with a weighted majority filter accounting for per-pixel classification confidence. Capitalizing on a wall-to-wall validation data set, the method was tested in South Africa using a 16-year old land cover map and multi-sensor Landsat time series. The overall accuracy of the resulting cropland map reached 92%. A spatially explicit validation revealed large variations across the country and suggests that intensive grain-growing areas were better characterized than smallholder farming systems. Informative features in the classification process vary from one stratum to another but features targeting the minimum of vegetation as well as short-wave infrared features were consistently important throughout the country. Overall, the approach showed potential for routinely delivering consistent cropland maps over large areas as required for operational crop monitoring.

National-scale cropland mapping based on spectral-temporal features and outdated land cover information

PubMed Central

Hansen, Matthew C.; Potapov, Peter V.; Löw, Fabian; Newby, Terence; Ferreira, Stefanus; Defourny, Pierre

2017-01-01

The lack of sufficient ground truth data has always constrained supervised learning, thereby hindering the generation of up-to-date satellite-derived thematic maps. This is all the more true for those applications requiring frequent updates over large areas such as cropland mapping. Therefore, we present a method enabling the automated production of spatially consistent cropland maps at the national scale, based on spectral-temporal features and outdated land cover information. Following an unsupervised approach, this method extracts reliable calibration pixels based on their labels in the outdated map and their spectral signatures. To ensure spatial consistency and coherence in the map, we first propose to generate seamless input images by normalizing the time series and deriving spectral-temporal features that target salient cropland characteristics. Second, we reduce the spatial variability of the class signatures by stratifying the country and by classifying each stratum independently. Finally, we remove speckle with a weighted majority filter accounting for per-pixel classification confidence. Capitalizing on a wall-to-wall validation data set, the method was tested in South Africa using a 16-year old land cover map and multi-sensor Landsat time series. The overall accuracy of the resulting cropland map reached 92%. A spatially explicit validation revealed large variations across the country and suggests that intensive grain-growing areas were better characterized than smallholder farming systems. Informative features in the classification process vary from one stratum to another but features targeting the minimum of vegetation as well as short-wave infrared features were consistently important throughout the country. Overall, the approach showed potential for routinely delivering consistent cropland maps over large areas as required for operational crop monitoring. PMID:28817618

Evaluating historical climate and hydrologic trends in the Central Appalachian region of the United States

NASA Astrophysics Data System (ADS)

Gaertner, B. A.; Zegre, N.

2015-12-01

Climate change is surfacing as one of the most important environmental and social issues of the 21st century. Over the last 100 years, observations show increasing trends in global temperatures and intensity and frequency of precipitation events such as flooding, drought, and extreme storms. Global circulation models (GCM) show similar trends for historic and future climate indicators, albeit with geographic and topographic variability at regional and local scale. In order to assess the utility of GCM projections for hydrologic modeling, it is important to quantify how robust GCM outputs are compared to robust historical observations at finer spatial scales. Previous research in the United States has primarily focused on the Western and Northeastern regions due to dominance of snow melt for runoff and aquifer recharge but the impact of climate warming in the mountainous central Appalachian Region is poorly understood. In this research, we assess the performance of GCM-generated historical climate compared to historical observations primarily in the context of forcing data for macro-scale hydrologic modeling. Our results show significant spatial heterogeneity of modeled climate indices when compared to observational trends at the watershed scale. Observational data is showing considerable variability within maximum temperature and precipitation trends, with consistent increases in minimum temperature. The geographic, temperature, and complex topographic gradient throughout the central Appalachian region is likely the contributing factor in temperature and precipitation variability. Variable climate changes are leading to more severe and frequent climate events such as temperature extremes and storm events, which can have significant impacts on our drinking water supply, infrastructure, and health of all downstream communities.

A Place-Oriented, Mixed-Level Regionalization Method for Constructing Geographic Areas in Health Data Dissemination and Analysis

PubMed Central

Mu, Lan; Wang, Fahui; Chen, Vivien W.; Wu, Xiao-Cheng

2015-01-01

Similar geographic areas often have great variations in population size. In health data management and analysis, it is desirable to obtain regions of comparable population by decomposing areas of large population (to gain more spatial variability) and merging areas of small population (to mask privacy of data). Based on the Peano curve algorithm and modified scale-space clustering, this research proposes a mixed-level regionalization (MLR) method to construct geographic areas with comparable population. The method accounts for spatial connectivity and compactness, attributive homogeneity, and exogenous criteria such as minimum (and approximately equal) population or disease counts. A case study using Louisiana cancer data illustrates the MLR method and its strengths and limitations. A major benefit of the method is that most upper level geographic boundaries can be preserved to increase familiarity of constructed areas. Therefore, the MLR method is more human-oriented and place-based than computer-oriented and space-based. PMID:26251551

Results on the spatial resolution of repetitive transcranial magnetic stimulation for cortical language mapping during object naming in healthy subjects.

PubMed

Sollmann, Nico; Hauck, Theresa; Tussis, Lorena; Ille, Sebastian; Maurer, Stefanie; Boeckh-Behrens, Tobias; Ringel, Florian; Meyer, Bernhard; Krieg, Sandro M

2016-10-24

The spatial resolution of repetitive navigated transcranial magnetic stimulation (rTMS) for language mapping is largely unknown. Thus, to determine a minimum spatial resolution of rTMS for language mapping, we evaluated the mapping sessions derived from 19 healthy volunteers for cortical hotspots of no-response errors. Then, the distances between hotspots (stimulation points with a high error rate) and adjacent mapping points (stimulation points with low error rates) were evaluated. Mean distance values of 13.8 ± 6.4 mm (from hotspots to ventral points, range 0.7-30.7 mm), 10.8 ± 4.8 mm (from hotspots to dorsal points, range 2.0-26.5 mm), 16.6 ± 4.8 mm (from hotspots to apical points, range 0.9-27.5 mm), and 13.8 ± 4.3 mm (from hotspots to caudal points, range 2.0-24.2 mm) were measured. According to the results, the minimum spatial resolution of rTMS should principally allow for the identification of a particular gyrus, and according to the literature, it is in good accordance with the spatial resolution of direct cortical stimulation (DCS). Since measurement was performed between hotspots and adjacent mapping points and not on a finer-grained basis, we only refer to a minimum spatial resolution. Furthermore, refinement of our results within the scope of a prospective study combining rTMS and DCS for resolution measurement during language mapping should be the next step.

Wildfire risk assessment in a typical Mediterranean wildland-urban interface of Greece.

PubMed

Mitsopoulos, Ioannis; Mallinis, Giorgos; Arianoutsou, Margarita

2015-04-01

The purpose of this study was to assess spatial wildfire risk in a typical Mediterranean wildland-urban interface (WUI) in Greece and the potential effect of three different burning condition scenarios on the following four major wildfire risk components: burn probability, conditional flame length, fire size, and source-sink ratio. We applied the Minimum Travel Time fire simulation algorithm using the FlamMap and ArcFuels tools to characterize the potential response of the wildfire risk to a range of different burning scenarios. We created site-specific fuel models of the study area by measuring the field fuel parameters in representative natural fuel complexes, and we determined the spatial extent of the different fuel types and residential structures in the study area using photointerpretation procedures of large scale natural color orthophotographs. The results included simulated spatially explicit fire risk components along with wildfire risk exposure analysis and the expected net value change. Statistical significance differences in simulation outputs between the scenarios were obtained using Tukey's significance test. The results of this study provide valuable information for decision support systems for short-term predictions of wildfire risk potential and inform wildland fire management of typical WUI areas in Greece.

Wildfire Risk Assessment in a Typical Mediterranean Wildland-Urban Interface of Greece

NASA Astrophysics Data System (ADS)

Mitsopoulos, Ioannis; Mallinis, Giorgos; Arianoutsou, Margarita

2015-04-01

The purpose of this study was to assess spatial wildfire risk in a typical Mediterranean wildland-urban interface (WUI) in Greece and the potential effect of three different burning condition scenarios on the following four major wildfire risk components: burn probability, conditional flame length, fire size, and source-sink ratio. We applied the Minimum Travel Time fire simulation algorithm using the FlamMap and ArcFuels tools to characterize the potential response of the wildfire risk to a range of different burning scenarios. We created site-specific fuel models of the study area by measuring the field fuel parameters in representative natural fuel complexes, and we determined the spatial extent of the different fuel types and residential structures in the study area using photointerpretation procedures of large scale natural color orthophotographs. The results included simulated spatially explicit fire risk components along with wildfire risk exposure analysis and the expected net value change. Statistical significance differences in simulation outputs between the scenarios were obtained using Tukey's significance test. The results of this study provide valuable information for decision support systems for short-term predictions of wildfire risk potential and inform wildland fire management of typical WUI areas in Greece.

The effect of warmer winters on the demography of an outbreak insect is hidden by intraspecific competition

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

Goodsman, Devin W.; Grosklos, Guenchik; Aukema, Brian H.

Warmer climates are predicted to increase bark beetle outbreak frequency, severity, and range. Even in favorable climates, however, outbreaks can decelerate due to resource limitation, which necessitates the inclusion of competition for limited resources in analyses of climatic effects on populations. We evaluated several hypotheses of how climate impacts mountain pine beetle reproduction using an extensive 9-year dataset, in which nearly 10,000 trees were sampled across a region of approximately 90,000 km 2, that was recently invaded by the mountain pine beetle in Alberta, Canada. Our analysis supports the hypothesis of a positive effect of warmer winter temperatures on mountainmore » pine beetle overwinter survival and provides evidence that the increasing trend in minimum winter temperatures over time in North America is an important driver of increased mountain pine beetle reproduction across the region. Although we demonstrate a consistent effect of warmer minimum winter temperatures on mountain pine beetle reproductive rates that is evident at the landscape and regional scales, this effect is overwhelmed by the effect of competition for resources within trees at the site level. Our results suggest that detection of the effects of a warming climate on bark beetle populations at small spatial scales may be difficult without accounting for negative density dependence due to competition for resources.« less

The effect of warmer winters on the demography of an outbreak insect is hidden by intraspecific competition.

PubMed

Goodsman, Devin W; Grosklos, Guenchik; Aukema, Brian H; Whitehouse, Caroline; Bleiker, Katherine P; McDowell, Nate G; Middleton, Richard S; Xu, Chonggang

2018-05-29

Warmer climates are predicted to increase bark beetle outbreak frequency, severity, and range. Even in favorable climates, however, outbreaks can decelerate due to resource limitation, which necessitates the inclusion of competition for limited resources in analyses of climatic effects on populations. We evaluated several hypotheses of how climate impacts mountain pine beetle reproduction using an extensive 9-year dataset, in which nearly 10,000 trees were sampled across a region of approximately 90,000 km 2 , that was recently invaded by the mountain pine beetle in Alberta, Canada. Our analysis supports the hypothesis of a positive effect of warmer winter temperatures on mountain pine beetle overwinter survival and provides evidence that the increasing trend in minimum winter temperatures over time in North America is an important driver of increased mountain pine beetle reproduction across the region. Although we demonstrate a consistent effect of warmer minimum winter temperatures on mountain pine beetle reproductive rates that is evident at the landscape and regional scales, this effect is overwhelmed by the effect of competition for resources within trees at the site level. Our results suggest that detection of the effects of a warming climate on bark beetle populations at small spatial scales may be difficult without accounting for negative density dependence due to competition for resources. © 2018 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

The effect of warmer winters on the demography of an outbreak insect is hidden by intraspecific competition

DOE PAGES

Goodsman, Devin W.; Grosklos, Guenchik; Aukema, Brian H.; ...

2018-05-29

Warmer climates are predicted to increase bark beetle outbreak frequency, severity, and range. Even in favorable climates, however, outbreaks can decelerate due to resource limitation, which necessitates the inclusion of competition for limited resources in analyses of climatic effects on populations. We evaluated several hypotheses of how climate impacts mountain pine beetle reproduction using an extensive 9-year dataset, in which nearly 10,000 trees were sampled across a region of approximately 90,000 km 2, that was recently invaded by the mountain pine beetle in Alberta, Canada. Our analysis supports the hypothesis of a positive effect of warmer winter temperatures on mountainmore » pine beetle overwinter survival and provides evidence that the increasing trend in minimum winter temperatures over time in North America is an important driver of increased mountain pine beetle reproduction across the region. Although we demonstrate a consistent effect of warmer minimum winter temperatures on mountain pine beetle reproductive rates that is evident at the landscape and regional scales, this effect is overwhelmed by the effect of competition for resources within trees at the site level. Our results suggest that detection of the effects of a warming climate on bark beetle populations at small spatial scales may be difficult without accounting for negative density dependence due to competition for resources.« less

The Analytical Limits of Modeling Short Diffusion Timescales

NASA Astrophysics Data System (ADS)

Bradshaw, R. W.; Kent, A. J.

2016-12-01

Chemical and isotopic zoning in minerals is widely used to constrain the timescales of magmatic processes such as magma mixing and crystal residence, etc. via diffusion modeling. Forward modeling of diffusion relies on fitting diffusion profiles to measured compositional gradients. However, an individual measurement is essentially an average composition for a segment of the gradient defined by the spatial resolution of the analysis. Thus there is the potential for the analytical spatial resolution to limit the timescales that can be determined for an element of given diffusivity, particularly where the scale of the gradient approaches that of the measurement. Here we use a probabilistic modeling approach to investigate the effect of analytical spatial resolution on estimated timescales from diffusion modeling. Our method investigates how accurately the age of a synthetic diffusion profile can be obtained by modeling an "unknown" profile derived from discrete sampling of the synthetic compositional gradient at a given spatial resolution. We also include the effects of analytical uncertainty and the position of measurements relative to the diffusion gradient. We apply this method to the spatial resolutions of common microanalytical techniques (LA-ICP-MS, SIMS, EMP, NanoSIMS). Our results confirm that for a given diffusivity, higher spatial resolution gives access to shorter timescales, and that each analytical spacing has a minimum timescale, below which it overestimates the timescale. For example, for Ba diffusion in plagioclase at 750 °C timescales are accurate (within 20%) above 10, 100, 2,600, and 71,000 years at 0.3, 1, 5, and 25 mm spatial resolution, respectively. For Sr diffusion in plagioclase at 750 °C, timescales are accurate above 0.02, 0.2, 4, and 120 years at the same spatial resolutions. Our results highlight the importance of selecting appropriate analytical techniques to estimate accurate diffusion-based timescales.

On unravelling mechanism of interplay between cloud and large scale circulation: a grey area in climate science

NASA Astrophysics Data System (ADS)

De, S.; Agarwal, N. K.; Hazra, Anupam; Chaudhari, Hemantkumar S.; Sahai, A. K.

2018-04-01

The interaction between cloud and large scale circulation is much less explored area in climate science. Unfolding the mechanism of coupling between these two parameters is imperative for improved simulation of Indian summer monsoon (ISM) and to reduce imprecision in climate sensitivity of global climate model. This work has made an effort to explore this mechanism with CFSv2 climate model experiments whose cloud has been modified by changing the critical relative humidity (CRH) profile of model during ISM. Study reveals that the variable CRH in CFSv2 has improved the nonlinear interactions between high and low frequency oscillations in wind field (revealed as internal dynamics of monsoon) and modulates realistically the spatial distribution of interactions over Indian landmass during the contrasting monsoon season compared to the existing CRH profile of CFSv2. The lower tropospheric wind error energy in the variable CRH simulation of CFSv2 appears to be minimum due to the reduced nonlinear convergence of error to the planetary scale range from long and synoptic scales (another facet of internal dynamics) compared to as observed from other CRH experiments in normal and deficient monsoons. Hence, the interplay between cloud and large scale circulation through CRH may be manifested as a change in internal dynamics of ISM revealed from scale interactive quasi-linear and nonlinear kinetic energy exchanges in frequency as well as in wavenumber domain during the monsoon period that eventually modify the internal variance of CFSv2 model. Conversely, the reduced wind bias and proper modulation of spatial distribution of scale interaction between the synoptic and low frequency oscillations improve the eastward and northward extent of water vapour flux over Indian landmass that in turn give feedback to the realistic simulation of cloud condensates attributing improved ISM rainfall in CFSv2.

The Effect Of Pixel Size On The Detection Rate Of Early Pulmonary Sarcoidosis In Digital Chest Radiographic Systems

NASA Astrophysics Data System (ADS)

MacMahon, Heber; Vyborny, Carl; Powell, Gregory; Doi, Kunio; Metz, Charles E.

1984-08-01

In digital radiography the pixel size used determines the potential spatial resolution of the system. The need for spatial resolution varies depending on the subject matter imaged. In many areas, including the chest, the minimum spatial resolution requirements have not been determined. Sarcoidosis is a disease which frequently causes subtle interstitial infiltrates in the lungs. As the initial step in an investigation designed to determine the minimum pixel size required in digital chest radiographic systems, we have studied 1 mm pixel digitized images on patients with early pulmonary sarcoidosis. The results of this preliminary study suggest that neither mild interstitial pulmonary infiltrates nor other abnormalities such as pneumothoraces may be detected reliably with 1 mm pixel digital images.

Tree spatial structure, host composition and resource availability influence mirid density or black pod prevalence in cacao agroforests in Cameroon.

PubMed

Gidoin, Cynthia; Babin, Régis; Bagny Beilhe, Leïla; Cilas, Christian; ten Hoopen, Gerben Martijn; Bieng, Marie Ange Ngo

2014-01-01

Combining crop plants with other plant species in agro-ecosystems is one way to enhance ecological pest and disease regulation mechanisms. Resource availability and microclimatic variation mechanisms affect processes related to pest and pathogen life cycles. These mechanisms are supported both by empirical research and by epidemiological models, yet their relative importance in a real complex agro-ecosystem is still not known. Our aim was thus to assess the independent effects and the relative importance of different variables related to resource availability and microclimatic variation that explain pest and disease occurrence at the plot scale in real complex agro-ecosystems. The study was conducted in cacao (Theobroma cacao) agroforests in Cameroon, where cocoa production is mainly impacted by the mirid bug, Sahlbergella singularis, and black pod disease, caused by Phytophthora megakarya. Vegetation composition and spatial structure, resource availability and pest and disease occurrence were characterized in 20 real agroforest plots. Hierarchical partitioning was used to identify the causal variables that explain mirid density and black pod prevalence. The results of this study show that cacao agroforests can be differentiated on the basis of vegetation composition and spatial structure. This original approach revealed that mirid density decreased when a minimum number of randomly distributed forest trees were present compared with the aggregated distribution of forest trees, or when forest tree density was low. Moreover, a decrease in mirid density was also related to decreased availability of sensitive tissue, independently of the effect of forest tree structure. Contrary to expectations, black pod prevalence decreased with increasing cacao tree abundance. By revealing the effects of vegetation composition and spatial structure on mirids and black pod, this study opens new perspectives for the joint agro-ecological management of cacao pests and diseases at the plot scale, through the optimization of the spatial structure and composition of the vegetation.

Tree Spatial Structure, Host Composition and Resource Availability Influence Mirid Density or Black Pod Prevalence in Cacao Agroforests in Cameroon

PubMed Central

Gidoin, Cynthia; Babin, Régis; Bagny Beilhe, Leïla; Cilas, Christian; ten Hoopen, Gerben Martijn; Bieng, Marie Ange Ngo

2014-01-01

Combining crop plants with other plant species in agro-ecosystems is one way to enhance ecological pest and disease regulation mechanisms. Resource availability and microclimatic variation mechanisms affect processes related to pest and pathogen life cycles. These mechanisms are supported both by empirical research and by epidemiological models, yet their relative importance in a real complex agro-ecosystem is still not known. Our aim was thus to assess the independent effects and the relative importance of different variables related to resource availability and microclimatic variation that explain pest and disease occurrence at the plot scale in real complex agro-ecosystems. The study was conducted in cacao (Theobroma cacao) agroforests in Cameroon, where cocoa production is mainly impacted by the mirid bug, Sahlbergella singularis, and black pod disease, caused by Phytophthora megakarya. Vegetation composition and spatial structure, resource availability and pest and disease occurrence were characterized in 20 real agroforest plots. Hierarchical partitioning was used to identify the causal variables that explain mirid density and black pod prevalence. The results of this study show that cacao agroforests can be differentiated on the basis of vegetation composition and spatial structure. This original approach revealed that mirid density decreased when a minimum number of randomly distributed forest trees were present compared with the aggregated distribution of forest trees, or when forest tree density was low. Moreover, a decrease in mirid density was also related to decreased availability of sensitive tissue, independently of the effect of forest tree structure. Contrary to expectations, black pod prevalence decreased with increasing cacao tree abundance. By revealing the effects of vegetation composition and spatial structure on mirids and black pod, this study opens new perspectives for the joint agro-ecological management of cacao pests and diseases at the plot scale, through the optimization of the spatial structure and composition of the vegetation. PMID:25313514

[Object-oriented segmentation and classification of forest gap based on QuickBird remote sensing image.

PubMed

Mao, Xue Gang; Du, Zi Han; Liu, Jia Qian; Chen, Shu Xin; Hou, Ji Yu

2018-01-01

Traditional field investigation and artificial interpretation could not satisfy the need of forest gaps extraction at regional scale. High spatial resolution remote sensing image provides the possibility for regional forest gaps extraction. In this study, we used object-oriented classification method to segment and classify forest gaps based on QuickBird high resolution optical remote sensing image in Jiangle National Forestry Farm of Fujian Province. In the process of object-oriented classification, 10 scales (10-100, with a step length of 10) were adopted to segment QuickBird remote sensing image; and the intersection area of reference object (RA or ) and intersection area of segmented object (RA os ) were adopted to evaluate the segmentation result at each scale. For segmentation result at each scale, 16 spectral characteristics and support vector machine classifier (SVM) were further used to classify forest gaps, non-forest gaps and others. The results showed that the optimal segmentation scale was 40 when RA or was equal to RA os . The accuracy difference between the maximum and minimum at different segmentation scales was 22%. At optimal scale, the overall classification accuracy was 88% (Kappa=0.82) based on SVM classifier. Combining high resolution remote sensing image data with object-oriented classification method could replace the traditional field investigation and artificial interpretation method to identify and classify forest gaps at regional scale.

Morphodynamics of Migration Surveyed at Large Spatial and Temporal Scales

NASA Astrophysics Data System (ADS)

Aalto, R.; Schwendel, A.; Nicholas, A. P.

2012-04-01

The controls on rivers migration are diverse and often complex. One way forwards is to select study rivers that meet certain simplifying conditions: near-pristine (no anthropogenic complications), large size and rapid mobility (resulting in significant change viewable in Landsat imagery), limited geological complexity (no bedrock), steady hydrology (relatively little variation in discharge and sediment load), and simplified base level control (no tides or other substantial perturbations). Such systems could then be measured at appropriate spatial and temporal scales to extract the reach-scale dynamics while averaging out the more stochastic behaviour of individual meander bends. Such an approach requires both special rivers and novel techniques, which we have investigated and present here. The two explored examples are the near-pristine Beni River basin in northern Bolivia (800 km channel length) and the similarly natural Fly-Strickland River basin in Papua New Guinea (400 km channel length) - large, tropical sand-bedded rivers that meet the above criteria. First, we conducted a GIS analysis of migration using image collections that include 1950s military aerial reconnaissance -- this allowed us to characterize mobility decades before the first Landsat satellite was launched. Following this approach, we characterized migration rate, sinuosity, and other parameters at the reach scale of 10km and the temporal scale of 50+ years, with clear patterns of rate and morphology emerging as a function of location within the systems. We conducted extensive fieldwork to explore potential controls on these patterns, with the focus of this talk being the results from DGPS surveys of river and valley slope. The length scale of these rivers, the density of the forested floodplains, and the hostility of the environments precluded the use of standard RTK-DGPS methods. Instead, we employed three novel techniques for long baseline (100s of km) DGPS surveys: OmniStar HP/XP GLONASS kinematic RT-DGPS (sub-decimetre), filtered static RT-DGPS using OmniStar VBS (sub-metre), and post-processed DGPS using newly available Precise Point Positioning methods (sub-metre). We compare these novel DGPS techniques simultaneously (recent 2011 and 2010 surveys) and over time (our 2004, 2001, and 1999 surveys), presenting an assessment of their utility for long baseline surveys of large rivers. Additionally, we present a comparison to water surface profiles developed from the raw version of the 2001 SRTM DEM, with the water elevations determined from MINIMUM 1-arc-second values (not the average 3-arc-second values previously released) - this is the first evaluation of such 'minimum' data of which we are aware. The field surveys ultimately produced quality elevation profiles that allow us to characterize and investigate the strong relationships of both reach-scale migration rate and sinuosity to water surface slope - empirical results realized over time and length scales that serve to average out stochastic noise at the bend scale.

Development of a gridded meteorological dataset over Java island, Indonesia 1985-2014.

PubMed

Yanto; Livneh, Ben; Rajagopalan, Balaji

2017-05-23

We describe a gridded daily meteorology dataset consisting of precipitation, minimum and maximum temperature over Java Island, Indonesia at 0.125°×0.125° (~14 km) resolution spanning 30 years from 1985-2014. Importantly, this data set represents a marked improvement from existing gridded data sets over Java with higher spatial resolution, derived exclusively from ground-based observations unlike existing satellite or reanalysis-based products. Gap-infilling and gridding were performed via the Inverse Distance Weighting (IDW) interpolation method (radius, r, of 25 km and power of influence, α, of 3 as optimal parameters) restricted to only those stations including at least 3,650 days (~10 years) of valid data. We employed MSWEP and CHIRPS rainfall products in the cross-validation. It shows that the gridded rainfall presented here produces the most reasonable performance. Visual inspection reveals an increasing performance of gridded precipitation from grid, watershed to island scale. The data set, stored in a network common data form (NetCDF), is intended to support watershed-scale and island-scale studies of short-term and long-term climate, hydrology and ecology.

Continuity vs. the Crowd-Tradeoffs Between Continuous and Intermittent Citizen Hydrology Streamflow Observations.

PubMed

Davids, Jeffrey C; van de Giesen, Nick; Rutten, Martine

2017-07-01

Hydrologic data has traditionally been collected with permanent installations of sophisticated and accurate but expensive monitoring equipment at limited numbers of sites. Consequently, observation frequency and costs are high, but spatial coverage of the data is limited. Citizen Hydrology can possibly overcome these challenges by leveraging easily scaled mobile technology and local residents to collect hydrologic data at many sites. However, understanding of how decreased observational frequency impacts the accuracy of key streamflow statistics such as minimum flow, maximum flow, and runoff is limited. To evaluate this impact, we randomly selected 50 active United States Geological Survey streamflow gauges in California. We used 7 years of historical 15-min flow data from 2008 to 2014 to develop minimum flow, maximum flow, and runoff values for each gauge. To mimic lower frequency Citizen Hydrology observations, we developed a bootstrap randomized subsampling with replacement procedure. We calculated the same statistics, and their respective distributions, from 50 subsample iterations with four different subsampling frequencies ranging from daily to monthly. Minimum flows were estimated within 10% for half of the subsample iterations at 39 (daily) and 23 (monthly) of the 50 sites. However, maximum flows were estimated within 10% at only 7 (daily) and 0 (monthly) sites. Runoff volumes were estimated within 10% for half of the iterations at 44 (daily) and 12 (monthly) sites. Watershed flashiness most strongly impacted accuracy of minimum flow, maximum flow, and runoff estimates from subsampled data. Depending on the questions being asked, lower frequency Citizen Hydrology observations can provide useful hydrologic information.

Downscaling to the Climate Near the Ground: Measurements and Modeling Along the Macro-, Meso-, Topo-, and Microclimate Hierarchy

NASA Astrophysics Data System (ADS)

van de Ven, C.; Weiss, S. B.

2009-12-01

Most climate models are expressed at regional scales, with resolutions on the scales of kilometers. When used for ecological modeling, these climate models help explain only broad-scale trends, such as latitudinal and upslope migration of plants. However, more refined ecological models require down-scaled climate data at ecologically relevant spatial scales, and the goal of this presentation is to demonstrate robust downscaling methods. For example, in the White Mountains, eastern California, tree species, including bristlecone pine (Pinus longaeva) are seen moving not just upslope, but also sideways across aspects, and downslope into areas characterized by cold air drainage. Macroclimate in the White Mountains is semi-arid, residing in the rain shadow of the Sierra Nevada. Macroclimate is modified by mesoscale effects of mountain ranges, where climate becomes wetter and colder with elevation, the temperature decreasing according to the regionally and temporally-specific lapse rate. Local topography further modifies climate, where slope angle, aspect, and topographic position further impact the temperature at a given site. Finally, plants experience extremely localized microclimate, where surrounding vegetation provide differing degrees of shade. We measured and modeled topoclimate across the White Mountains using iButton Thermochron temperature data loggers during late summer in 2006 and 2008, and have documented effects of microclimatic temperature differences between sites in the open and shaded by shrubs. Starting with PRISM 800m data, we derived mesoscale lapse rates. Then, we calculated temperature differentials between each Thermochron and a long-term weather station in the middle of the range at Crooked Creek Valley. We modeled month-specific minimum temperature differentials by regressing the Thermochron-weather station minimum temperature differentials with various topographic parameters. Topographic position, the absolute value of topographic position, and slope combined to provide a very close fit (r2>0.9) to measured inversions of >8°C. Although topoclimatic maximum temperature models have been more elusive, regressions with degree hours greater than zero (DH>0) have been modeled with September insolation and slope (r2=0.7). In paired experiments, Thermochrons also recorded the temperature differences between the environment under sagebrush (Artemisia tridentata) and in the open, with an average minimum temperature difference of 2.1°C, and maximum temperature difference of 4.5°C. When we incorporate hourly weather station data, the strength of the inversion is weakened by wind, higher relative humidity, and cloudiness. This hierarchical modeling provides a template for downscaling climate and weather to ecologically relevant scales.

Rising above the Minimum Wage.

ERIC Educational Resources Information Center

Even, William; Macpherson, David

An in-depth analysis was made of how quickly most people move up the wage scale from minimum wage, what factors influence their progress, and how minimum wage increases affect wage growth above the minimum. Very few workers remain at the minimum wage over the long run, according to this study of data drawn from the 1977-78 May Current Population…

G-NEST: A gene neighborhood scoring tool to identify co-conserved, co-expressed genes

USDA-ARS?s Scientific Manuscript database

In previous studies, gene neighborhoods--spatial clusters of co-expressed genes in the genome--have been defined using arbitrary rules such as requiring adjacency, a minimum number of genes, a fixed window size, or a minimum expression level. In the current study, we developed a Gene Neighborhood Sc...

Spatial and temporal variability in minimum temperature trends in the western U.S. sagebrush steppe

USDA-ARS?s Scientific Manuscript database

Climate is a major driver of ecosystem dynamics. In recent years there has been considerable interest in future climate change and potential impacts on ecosystems and management options. In this paper, we analyzed minimum monthly temperature (T min) for ten rural locations in the western sagebrush...

Development of a Heterogenic Distributed Environment for Spatial Data Processing Using Cloud Technologies

NASA Astrophysics Data System (ADS)

Garov, A. S.; Karachevtseva, I. P.; Matveev, E. V.; Zubarev, A. E.; Florinsky, I. V.

2016-06-01

We are developing a unified distributed communication environment for processing of spatial data which integrates web-, desktop- and mobile platforms and combines volunteer computing model and public cloud possibilities. The main idea is to create a flexible working environment for research groups, which may be scaled according to required data volume and computing power, while keeping infrastructure costs at minimum. It is based upon the "single window" principle, which combines data access via geoportal functionality, processing possibilities and communication between researchers. Using an innovative software environment the recently developed planetary information system (http://cartsrv.mexlab.ru/geoportal) will be updated. The new system will provide spatial data processing, analysis and 3D-visualization and will be tested based on freely available Earth remote sensing data as well as Solar system planetary images from various missions. Based on this approach it will be possible to organize the research and representation of results on a new technology level, which provides more possibilities for immediate and direct reuse of research materials, including data, algorithms, methodology, and components. The new software environment is targeted at remote scientific teams, and will provide access to existing spatial distributed information for which we suggest implementation of a user interface as an advanced front-end, e.g., for virtual globe system.

Spatial and Temporal Means and Variability of Arctic Sea Ice Climate Indicators from Satellite Data

NASA Astrophysics Data System (ADS)

Peng, G.; Meier, W.; Bliss, A. C.; Steele, M.; Dickinson, S.

2017-12-01

Arctic sea ice has been undergoing rapid and accelerated loss since satellite-based measurements became available in late 1970s, especially the summer ice coverage. For the Arctic as a whole, the long-term trend for the annual sea ice extent (SIE) minimum is about -13.5±2.93 % per decade change relative to the 1979-2015 climate average, while the trends of the annual SIE minimum for the local regions can range from 0 to up to -42 % per decade. This presentation aims to examine and baseline spatial and temporal means and variability of Arctic sea ice climate indicators, such as the annual SIE minimum and maximum, snow/ice melt onset, etc., from a consistent, inter-calibrated, long-term time series of remote sensing sea ice data for understanding regional vulnerability and monitoring ice state for climate adaptation and risk mitigation.

Spatial distribution of soil organic carbon and total nitrogen based on GIS and geostatistics in a small watershed in a hilly area of northern China.

PubMed

Peng, Gao; Bing, Wang; Guangpo, Geng; Guangcan, Zhang

2013-01-01

The spatial variability of soil organic carbon (SOC) and total nitrogen (STN) levels is important in both global carbon-nitrogen cycle and climate change research. There has been little research on the spatial distribution of SOC and STN at the watershed scale based on geographic information systems (GIS) and geostatistics. Ninety-seven soil samples taken at depths of 0-20 cm were collected during October 2010 and 2011 from the Matiyu small watershed (4.2 km(2)) of a hilly area in Shandong Province, northern China. The impacts of different land use types, elevation, vegetation coverage and other factors on SOC and STN spatial distributions were examined using GIS and a geostatistical method, regression-kriging. The results show that the concentration variations of SOC and STN in the Matiyu small watershed were moderate variation based on the mean, median, minimum and maximum, and the coefficients of variation (CV). Residual values of SOC and STN had moderate spatial autocorrelations, and the Nugget/Sill were 0.2% and 0.1%, respectively. Distribution maps of regression-kriging revealed that both SOC and STN concentrations in the Matiyu watershed decreased from southeast to northwest. This result was similar to the watershed DEM trend and significantly correlated with land use type, elevation and aspect. SOC and STN predictions with the regression-kriging method were more accurate than those obtained using ordinary kriging. This research indicates that geostatistical characteristics of SOC and STN concentrations in the watershed were closely related to both land-use type and spatial topographic structure and that regression-kriging is suitable for investigating the spatial distributions of SOC and STN in the complex topography of the watershed.

Spatial Distribution of Soil Organic Carbon and Total Nitrogen Based on GIS and Geostatistics in a Small Watershed in a Hilly Area of Northern China

PubMed Central

Peng, Gao; Bing, Wang; Guangpo, Geng; Guangcan, Zhang

2013-01-01

The spatial variability of soil organic carbon (SOC) and total nitrogen (STN) levels is important in both global carbon-nitrogen cycle and climate change research. There has been little research on the spatial distribution of SOC and STN at the watershed scale based on geographic information systems (GIS) and geostatistics. Ninety-seven soil samples taken at depths of 0–20 cm were collected during October 2010 and 2011 from the Matiyu small watershed (4.2 km2) of a hilly area in Shandong Province, northern China. The impacts of different land use types, elevation, vegetation coverage and other factors on SOC and STN spatial distributions were examined using GIS and a geostatistical method, regression-kriging. The results show that the concentration variations of SOC and STN in the Matiyu small watershed were moderate variation based on the mean, median, minimum and maximum, and the coefficients of variation (CV). Residual values of SOC and STN had moderate spatial autocorrelations, and the Nugget/Sill were 0.2% and 0.1%, respectively. Distribution maps of regression-kriging revealed that both SOC and STN concentrations in the Matiyu watershed decreased from southeast to northwest. This result was similar to the watershed DEM trend and significantly correlated with land use type, elevation and aspect. SOC and STN predictions with the regression-kriging method were more accurate than those obtained using ordinary kriging. This research indicates that geostatistical characteristics of SOC and STN concentrations in the watershed were closely related to both land-use type and spatial topographic structure and that regression-kriging is suitable for investigating the spatial distributions of SOC and STN in the complex topography of the watershed. PMID:24391791

Estimates of spatial and temporal variation of energy crops biomass yields in the US

NASA Astrophysics Data System (ADS)

Song, Y.; Jain, A. K.; Landuyt, W.; Kheshgi, H. S.

2013-12-01

Perennial grasses, such as switchgrass (Panicum viragatum) and Miscanthus (Miscanthus x giganteus) have been identified for potential use as biomass feedstocks in the US. Current research on perennial grass biomass production has been evaluated on small-scale plots. However, the extent to which this potential can be realized at a landscape-scale will depend on the biophysical potential to grow these grasses with minimum possible amount of land that needs to be diverted from food to fuel production. To assess this potential three questions about the biomass yield for these grasses need to be answered: (1) how the yields for different grasses are varied spatially and temporally across the US; (2) whether the yields are temporally stable or not; and (3) how the spatial and temporal trends in yields of these perennial grasses are controlled by limiting factors, including soil type, water availability, climate, and crop varieties. To answer these questions, the growth processes of the perennial grasses are implemented into a coupled biophysical, physiological and biogeochemical model (ISAM). The model has been applied to quantitatively investigate the spatial and temporal trends in biomass yields for over the period 1980 -2010 in the US. The bioenergy grasses considered in this study include Miscanthus, Cave-in-Rock switchgrass and Alamo switchgrass. The effects of climate, soil and topography on the spatial and temporal trends of biomass yields are quantitatively analyzed using principal component analysis and GIS based geographically weighted regression. The spatial temporal trend results are evaluated further to classify each part of the US into four homogeneous potential yield zones: high and stable yield zone (HS), high but unstable yield zone (HU), low and stable yield zone (LS) and low but unstable yield zone (LU). Our preliminary results indicate that the yields for perennial grasses among different zones are strongly related to the different controlling factors. For example, the yield in HS zone is depended on soil and topography factors. However, the yields in HU zone are more controlled by climate factors, leading to a large uncertainty in yield potential of bioenergy grasses under future climate change.

Scale Properties of Anisotropic and Isotropic Turbulence in the Urban Surface Layer

NASA Astrophysics Data System (ADS)

Liu, Hao; Yuan, Renmin; Mei, Jie; Sun, Jianning; Liu, Qi; Wang, Yu

2017-11-01

The scale properties of anisotropic and isotropic turbulence in the urban surface layer are investigated. A dimensionless anisotropic tensor is introduced and the turbulent tensor anisotropic coefficient, defined as C, where C = 3d3 + 1 (d3 is the minimum eigenvalue of the tensor) is used to characterize the turbulence anisotropy or isotropy. Turbulence is isotropic when C ≈ 1, and anisotropic when C ≪ 1. Three-dimensional velocity data collected using a sonic anemometer are analyzed to obtain the anisotropic characteristics of atmospheric turbulence in the urban surface layer, and the tensor anisotropic coefficient of turbulent eddies at different spatial scales calculated. The analysis shows that C is strongly dependent on atmospheric stability ξ = (z-zd)/L_{{it{MO}}}, where z is the measurement height, zd is the displacement height, and L_{{it{MO}}} is the Obukhov length. The turbulence at a specific scale in unstable conditions (i.e., ξ < 0) is closer to isotropic than that at the same scale under stable conditions. The maximum isotropic scale of turbulence is determined based on the characteristics of the power spectrum in three directions. Turbulence does not behave isotropically when the eddy scale is greater than the maximum isotropic scale, whereas it is horizontally isotropic at relatively large scales. The maximum isotropic scale of turbulence is compared to the outer scale of temperature, which is obtained by fitting the temperature fluctuation spectrum using the von Karman turbulent model. The results show that the outer scale of temperature is greater than the maximum isotropic scale of turbulence.

Adaptive multiresolution modeling of groundwater flow in heterogeneous porous media

NASA Astrophysics Data System (ADS)

Malenica, Luka; Gotovac, Hrvoje; Srzic, Veljko; Andric, Ivo

2016-04-01

Proposed methodology was originally developed by our scientific team in Split who designed multiresolution approach for analyzing flow and transport processes in highly heterogeneous porous media. The main properties of the adaptive Fup multi-resolution approach are: 1) computational capabilities of Fup basis functions with compact support capable to resolve all spatial and temporal scales, 2) multi-resolution presentation of heterogeneity as well as all other input and output variables, 3) accurate, adaptive and efficient strategy and 4) semi-analytical properties which increase our understanding of usually complex flow and transport processes in porous media. The main computational idea behind this approach is to separately find the minimum number of basis functions and resolution levels necessary to describe each flow and transport variable with the desired accuracy on a particular adaptive grid. Therefore, each variable is separately analyzed, and the adaptive and multi-scale nature of the methodology enables not only computational efficiency and accuracy, but it also describes subsurface processes closely related to their understood physical interpretation. The methodology inherently supports a mesh-free procedure, avoiding the classical numerical integration, and yields continuous velocity and flux fields, which is vitally important for flow and transport simulations. In this paper, we will show recent improvements within the proposed methodology. Since "state of the art" multiresolution approach usually uses method of lines and only spatial adaptive procedure, temporal approximation was rarely considered as a multiscale. Therefore, novel adaptive implicit Fup integration scheme is developed, resolving all time scales within each global time step. It means that algorithm uses smaller time steps only in lines where solution changes are intensive. Application of Fup basis functions enables continuous time approximation, simple interpolation calculations across different temporal lines and local time stepping control. Critical aspect of time integration accuracy is construction of spatial stencil due to accurate calculation of spatial derivatives. Since common approach applied for wavelets and splines uses a finite difference operator, we developed here collocation one including solution values and differential operator. In this way, new improved algorithm is adaptive in space and time enabling accurate solution for groundwater flow problems, especially in highly heterogeneous porous media with large lnK variances and different correlation length scales. In addition, differences between collocation and finite volume approaches are discussed. Finally, results show application of methodology to the groundwater flow problems in highly heterogeneous confined and unconfined aquifers.

Characterizing Air Temperature Changes in the Tarim Basin over 1960–2012

PubMed Central

Peng, Dongmei; Wang, Xiujun; Zhao, Chenyi; Wu, Xingren; Jiang, Fengqing; Chen, Pengxiang

2014-01-01

There has been evidence of warming rate varying largely over space and between seasons. However, little has been done to evaluate the spatial and temporal variability of air temperature in the Tarim Basin, northwest China. In this study, we collected daily air temperature from 19 meteorological stations for the period of 1960–2012, and analyzed annual mean temperature (AMT), the annual minimum (Tmin) and maximum temperature (Tmax), and mean temperatures of all twelve months and four seasons and their anomalies. Trend analyses, standard deviation of the detrended anomaly (SDDA) and correlations were carried out to characterize the spatial and temporal variability of various mean air temperatures. Our data showed that increasing trend was much greater in the Tmin (0.55°C/10a) than in the AMT (0.25°C/10a) and Tmax (0.12°C/10a), and the fluctuation followed the same order. There were large spatial variations in the increasing trends of both AMT (from −0.09 to 0.43 °C/10a) and Tmin (from 0.15 to 1.12°C/10a). Correlation analyses indicated that AMT had a significantly linear relationship with Tmin and the mean temperatures of four seasons. There were also pronounced changes in the monthly air temperature from November to March at decadal time scale. The seasonality (i.e., summer and winter difference) of air temperature was stronger during the period of 1960–1979 than over the recent three decades. Our preliminary analyses indicated that local environmental conditions (such as elevation) might be partly responsible for the spatial variability, and large scale climate phenomena might have influences on the temporal variability of air temperature in the Tarim Basin. In particular, there was a significant correlation between index of El Niño-Southern Oscillation (ENSO) and air temperature of May (P = 0.004), and between the index of Pacific Decadal Oscillation (PDO) and air temperature of July (P = 0.026) over the interannual to decadal time scales. PMID:25375648

Process, pattern and scale: hydrogeomorphology and plant diversity in forested wetlands across multiple spatial scales

NASA Astrophysics Data System (ADS)

Alexander, L.; Hupp, C. R.; Forman, R. T.

2002-12-01

Many geodisturbances occur across large spatial scales, spanning entire landscapes and creating ecological phenomena in their wake. Ecological study at large scales poses special problems: (1) large-scale studies require large-scale resources, and (2) sampling is not always feasible at the appropriate scale, and researchers rely on data collected at smaller scales to interpret patterns across broad regions. A criticism of landscape ecology is that findings at small spatial scales are "scaled up" and applied indiscriminately across larger spatial scales. In this research, landscape scaling is addressed through process-pattern relationships between hydrogeomorphic processes and patterns of plant diversity in forested wetlands. The research addresses: (1) whether patterns and relationships between hydrogeomorphic, vegetation, and spatial variables can transcend scale; and (2) whether data collected at small spatial scales can be used to describe patterns and relationships across larger spatial scales. Field measurements of hydrologic, geomorphic, spatial, and vegetation data were collected or calculated for 15- 1-ha sites on forested floodplains of six (6) Chesapeake Bay Coastal Plain streams over a total area of about 20,000 km2. Hydroperiod (day/yr), floodplain surface elevation range (m), discharge (m3/s), stream power (kg-m/s2), sediment deposition (mm/yr), relative position downstream and other variables were used in multivariate analyses to explain differences in species richness, tree diversity (Shannon-Wiener Diversity Index H'), and plant community composition at four spatial scales. Data collected at the plot (400-m2) and site- (c. 1-ha) scales are applied to and tested at the river watershed and regional spatial scales. Results indicate that plant species richness and tree diversity (Shannon-Wiener diversity index H') can be described by hydrogeomorphic conditions at all scales, but are best described at the site scale. Data collected at plot and site scales are tested for spatial heterogeneity across the Chesapeake Bay Coastal Plain using a geostatistical variogram, and multiple regression analysis is used to relate plant diversity, spatial, and hydrogeomorphic variables across Coastal Plain regions and hydrologic regimes. Results indicate that relationships between hydrogeomorphic processes and patterns of plant diversity at finer scales can proxy relationships at coarser scales in some, not all, cases. Findings also suggest that data collected at small scales can be used to describe trends across broader scales under limited conditions.

Time-cumulated visible and infrared radiance histograms used as descriptors of surface and cloud variations

NASA Technical Reports Server (NTRS)

Seze, Genevieve; Rossow, William B.

1991-01-01

The spatial and temporal stability of the distributions of satellite-measured visible and infrared radiances, caused by variations in clouds and surfaces, are investigated using bidimensional and monodimensional histograms and time-composite images. Similar analysis of the histograms of the original and time-composite images provides separation of the contributions of the space and time variations to the total variations. The variability of both the surfaces and clouds is found to be larger at scales much larger than the minimum resolved by satellite imagery. This study shows that the shapes of these histograms are distinctive characteristics of the different climate regimes and that particular attributes of these histograms can be related to several general, though not universal, properties of clouds and surface variations at regional and synoptic scales. There are also significant exceptions to these relationships in particular climate regimes. The characteristics of these radiance histograms provide a stable well defined descriptor of the cloud and surface properties.

Diffusive dynamics of nanoparticles in ultra-confined media

DOE PAGES

Jacob, Jack Deodato; Conrad, Jacinta; Krishnamoorti, Ramanan; ...

2015-08-10

Differential dynamic microscopy (DDM) was used to investigate the diffusive dynamics of nanoparticles of diameter 200 400 nm that were strongly confined in a periodic square array of cylindrical nanoposts. The minimum distance between posts was 1.3 5 times the diameter of the nanoparticles. The image structure functions obtained from the DDM analysis were isotropic and could be fit by a stretched exponential function. The relaxation time scaled diffusively across the range of wave vectors studied, and the corresponding scalar diffusivities decreased monotonically with increased confinement. The decrease in diffusivity could be described by models for hindered diffusion that accountedmore » for steric restrictions and hydrodynamic interactions. The stretching exponent decreased linearly as the nanoparticles were increasingly confined by the posts. Altogether, these results are consistent with a picture in which strongly confined nanoparticles experience a heterogeneous spatial environment arising from hydrodynamics and volume exclusion on time scales comparable to cage escape, leading to multiple relaxation processes and Fickian but non-Gaussian diffusive dynamics.« less

A framework for mapping tree species combining hyperspectral and LiDAR data: Role of selected classifiers and sensor across three spatial scales

NASA Astrophysics Data System (ADS)

Ghosh, Aniruddha; Fassnacht, Fabian Ewald; Joshi, P. K.; Koch, Barbara

2014-02-01

Knowledge of tree species distribution is important worldwide for sustainable forest management and resource evaluation. The accuracy and information content of species maps produced using remote sensing images vary with scale, sensor (optical, microwave, LiDAR), classification algorithm, verification design and natural conditions like tree age, forest structure and density. Imaging spectroscopy reduces the inaccuracies making use of the detailed spectral response. However, the scale effect still has a strong influence and cannot be neglected. This study aims to bridge the knowledge gap in understanding the scale effect in imaging spectroscopy when moving from 4 to 30 m pixel size for tree species mapping, keeping in mind that most current and future hyperspectral satellite based sensors work with spatial resolution around 30 m or more. Two airborne (HyMAP) and one spaceborne (Hyperion) imaging spectroscopy dataset with pixel sizes of 4, 8 and 30 m, respectively were available to examine the effect of scale over a central European forest. The forest under examination is a typical managed forest with relatively homogenous stands featuring mostly two canopy layers. Normalized digital surface model (nDSM) derived from LiDAR data was used additionally to examine the effect of height information in tree species mapping. Six different sets of predictor variables (reflectance value of all bands, selected components of a Minimum Noise Fraction (MNF), Vegetation Indices (VI) and each of these sets combined with LiDAR derived height) were explored at each scale. Supervised kernel based (Support Vector Machines) and ensemble based (Random Forest) machine learning algorithms were applied on the dataset to investigate the effect of the classifier. Iterative bootstrap-validation with 100 iterations was performed for classification model building and testing for all the trials. For scale, analysis of overall classification accuracy and kappa values indicated that 8 m spatial resolution (reaching kappa values of over 0.83) slightly outperformed the results obtained from 4 m for the study area and five tree species under examination. The 30 m resolution Hyperion image produced sound results (kappa values of over 0.70), which in some areas of the test site were comparable with the higher spatial resolution imagery when qualitatively assessing the map outputs. Considering input predictor sets, MNF bands performed best at 4 and 8 m resolution. Optical bands were found to be best for 30 m spatial resolution. Classification with MNF as input predictors produced better visual appearance of tree species patches when compared with reference maps. Based on the analysis, it was concluded that there is no significant effect of height information on tree species classification accuracies for the present framework and study area. Furthermore, in the examined cases there was no single best choice among the two classifiers across scales and predictors. It can be concluded that tree species mapping from imaging spectroscopy for forest sites comparable to the one under investigation is possible with reliable accuracies not only from airborne but also from spaceborne imaging spectroscopy datasets.

Statistical downscaling of mean temperature, maximum temperature, and minimum temperature on the Loess Plateau, China

NASA Astrophysics Data System (ADS)

Lin, Jiang; Miao, Chiyuan

2017-04-01

Climate change is considered to be one of the greatest environmental threats. This has urged scientific communities to focus on the hot topic. Global climate models (GCMs) are the primary tool used for studying climate change. However, GCMs are limited because of their coarse spatial resolution and inability to resolve important sub-grid scale features such as terrain and clouds. Statistical downscaling methods can be used to downscale large-scale variables to local-scale. In this study, we assess the applicability of the widely used Statistical Downscaling Model (SDSM) for the Loess Plateau, China. The observed variables included daily mean temperature (TMEAN), maximum temperature (TMAX) and minimum temperature (TMIN) from 1961 to 2005. The and the daily atmospheric data were taken from reanalysis data from 1961 to 2005, and global climate model outputs from Beijing Normal University Earth System Model (BNU-ESM) from 1961 to 2099 and from observations . The results show that SDSM performs well for these three climatic variables on the Loess Plateau. After downscaling, the root mean square errors for TMEAN, TMAX, TMIN for BNU-ESM were reduced by 70.9%, 75.1%, and 67.2%, respectively. All the rates of change in TMEAN, TMAX and TMIN during the 21st century decreased after SDSM downscaling. We also show that SDSM can effectively reduce uncertainty, compared with the raw model outputs. TMEAN uncertainty was reduced by 27.1%, 26.8%, and 16.3% for the future scenarios of RCP 2.6, RCP 4.5 and RCP 8.5, respectively. The corresponding reductions in uncertainty were 23.6%, 30.7%, and 18.7% for TMAX, ; and 37.6%, 31.8%, and 23.2% for TMIN.

Thermal effects in photomask engineering and nano-thermometry

NASA Astrophysics Data System (ADS)

Chu, Dachen

Electron Beam Lithography (EBL) in photomask fabrication results in heating of the resist films. The local heating can change the chemical properties of resist, leading to placement errors. The heating induced error has been believed to be increasingly significant as the transistor minimum feature size approaches the sub 100 nm region. A Green's function approach has been developed to calculate four-dimensional temperature profiles in complex structures such as the multi-layer work-pieces being exposed in EBL. The model is being used to characterize different ebeam writing strategies to find the optimum. To provide the parameters for the model, two independent techniques have been employed: a thin film electrode method and a laser thermal-reflectance method. Unlike earlier results from polyimide films, no appreciable anisotropy was observed in thermal conductivities for the polymeric resists tested. Gold/nickel thin film thermocouples with minimum junction area of 100nm by 100nm were fabricated and calibrated. These thermocouple demonstrated a 400ns response time when heated by a 10ns laser pulse. Using these nano thermocouples, transient resist heating temperature profiles were for the first time measured at room temperature. Experimental results showed a good agreement with the Green's function model. We also observed a tradeoff in the scaling of thermocouple sensors. The smaller thermocouples may provide higher spatial and temporal resolutions but have poorer temperature resolution. In conclusion, we both modeled and measured the resist heating in EBL. In short exposure time (˜1us or less) the resist heating is nearly adiabatic, while in longer time the heating is dominated by substrate. Nano scale metallic thermocouples were explored and tradeoff was observed in dimension scaling.

Kinetics of pattern formation in symmetric diblock copolymer melts

NASA Astrophysics Data System (ADS)

Ren, Yongzhi; Müller, Marcus

2018-05-01

In equilibrium, copolymers self-assemble into spatially modulated phases with long-range order. When the system is quenched far below the order-disorder transition temperature, however, such an idealized, defect-free structure is difficult to obtain in experiments and simulations, instead a fingerprint-like structure forms. The relaxation toward long-range order is very protracted because it involves numerous thermally activated processes, and the rugged free-energy landscape has been likened to that of glass-forming systems. Using large-scale particle-based simulations of high-aspect-ratio, quasi-two-dimensional systems with periodic boundary condition, we study the kinetics of structure formation in symmetric, lamella-forming diblock copolymers after a quench from the disordered state. We characterize the ordering process by the correlation length of the lamellar structure and its Euler characteristic and observe that the growth of the correlation length and the rate of change of the Euler characteristic significantly slow down in the range of incompatibilities, 15 ≤ χN ≤ 20, studied. The increase of the time scale of ordering is, however, gradual. The density fields of snapshots of the particle-based simulations are used as starting values for self-consistent field theory (SCFT) calculations. The latter converge to the local, metastable minimum of the free-energy basin. This combination of particle-based simulations and SCFT calculations allows us to relate an instantaneous configuration of the particle-based model to a corresponding metastable free-energy minimum of SCFT—the inherent morphology—and we typically observe that a change of a free-energy basin is associated with a change of the Euler characteristic of the particle-based morphology, i.e., changes of free-energy basins are correlated to changes of the domain topology. Subsequently, we employ the string method in conjunction with SCFT to study the minimum free-energy paths (MFEPs) of changes of the domain topology. Since the time scales of relaxing toward the inherent morphology within a free-energy basin and jumps between free-energy basins are not well separated, the MFEP may overestimate the barriers encountered in the course of ordering.

Three-dimensional cell to tissue development process

NASA Technical Reports Server (NTRS)

Goodwin, Thomas J. (Inventor); Parker, Clayton R. (Inventor)

2008-01-01

An improved three-dimensional cell to tissue development process using a specific time varying electromagnetic force, pulsed, square wave, with minimum fluid shear stress, freedom for 3-dimensional spatial orientation of the suspended particles and localization of particles with differing or similar sedimentation properties in a similar spatial region.

Spatio-temporal Trends of Climate Variability in North Carolina

NASA Astrophysics Data System (ADS)

Sayemuzzaman, Mohammad

Climatic trends in spatial and temporal variability of maximum temperature (Tmax), minimum temperature (Tmin), mean temperature (Tmean) and precipitation were evaluated for 249 ground-based stations in North Carolina for 1950-2009. The Mann-Kendall (MK), the Theil-Sen Approach (TSA) and the Sequential Mann-Kendall (SQMK) tests were applied to quantify the significance of trend, magnitude of trend and the trend shift, respectively. The lag-1 serial correlation and double mass curve techniques were used to address the data independency and homogeneity. The pre-whitening technique was used to eliminate the effect of auto correlation of the data series. The difference between minimum and maximum temperatures, and so the diurnal temperature range (DTR), at some stations was found to be decreasing on both an annual and a seasonal basis, with an overall increasing trend in the mean temperature. For precipitation, a statewide increasing trend in fall (highest in November) and decreasing trend in winter (highest in February) were detected. No pronounced increasing/decreasing trends were detected in annual, spring, and summer precipitation time series. Trend analysis on a spatial scale (for three physiographic regions: mountain, piedmont and coastal) revealed mixed results. Coastal zone exhibited increasing mean temperature (warming) trend as compared to other locations whereas mountain zone showed decreasing trend (cooling). Three main moisture components (precipitation, total cloud cover, and soil moisture) and the two major atmospheric circulation modes (North Atlantic Oscillation and Southern Oscillation) were used for correlative analysis purposes with the temperature (specifically with DTR) and precipitation trends. It appears that the moisture components are associated with DTR more than the circulation modes in North Carolina.

Ring-widths of the above tree-line shrub Rhododendron reveal the change of minimum winter temperature over the past 211 years in Southwestern China

NASA Astrophysics Data System (ADS)

Bi, Yingfeng; Xu, Jianchu; Yang, Jinchao; Li, Zongshan; Gebrekirstos, Aster; Liang, Eryuan; Zhang, Shibao; Yang, Yang; Yang, Yongping; Yang, Xuefei

2017-06-01

Changes in minimum winter temperature (MWT) and their potential effects on plant growth and development have been gaining increased scientific attention. To better understand these changes across long temporal scales, the present study used dendroclimatological techniques to assess variations in MWT in Southwestern China. Using data from Rhododendron species distributed in areas above the tree-line, a regional composite chronology was generated for a 341-year period. Based on the significant negative correlation between MWT values and ring-width, the most reliable parts of this chronological data were then used to reconstruct MWT values for the past 211 years. This reconstructed MWT series showed decadal to multi-decadal fluctuations. Three distinct cold periods prevailed during 1823-1858, 1882-1891 and 1922-1965, while four warm intervals occurred in 1800-1822, 1858-1881, 1892-1921 and 1966-2011. Our reconstructed MWT reveals a warming trend over the most recent eight decades, which is in agreement with instrumental observations. However, the MWT values and rate of warming over the past seven decades did not exceed those found in the reconstructed temperature data for the past 211 years. Spatial correlations reveal that the MWT in Southwest China is strongly associated with regional temperatures in the Eastern and Central Himalaya, Northern China, and the Indian Peninsula. Larger scale climate oscillations of the Western Pacific and Northern Indian Ocean as well as the North Atlantic Oscillation probably influenced the region's temperature in the past.

Calibration of medium-resolution monochrome cathode ray tube displays for the purpose of board examinations.

PubMed

Evanoff, M G; Roehrig, H; Giffords, R S; Capp, M P; Rovinelli, R J; Hartmann, W H; Merritt, C

2001-06-01

This report discusses calibration and set-up procedures for medium-resolution monochrome cathode ray tubes (CRTs) taken in preparation of the oral portion of the board examination of the American Board of Radiology (ABR). The board examinations took place in more than 100 rooms of a hotel. There was one display-station (a computer and the associated CRT display) in each of the hotel rooms used for the examinations. The examinations covered the radiologic specialties cardiopulmonary, musculoskeletal, gastrointestinal, vascular, pediatric, and genitourinary. The software used for set-up and calibration was the VeriLUM 4.0 package from Image Smiths in Germantown, MD. The set-up included setting minimum luminance and maximum luminance, as well as positioning of the CRT in each examination room with respect to reflections of roomlights. The calibration for the grey scale rendition was done meeting the Digital Imaging and communication in Medicine (DICOM) 14 Standard Display Function. We describe these procedures, and present the calibration data in. tables and graphs, listing initial values of minimum luminance, maximum luminance, and grey scale rendition (DICOM 14 standard display function). Changes of these parameters over the duration of the examination were observed and recorded on 11 monitors in a particular room. These changes strongly suggest that all calibrated CRTs be monitored over the duration of the examination. In addition, other CRT performance data affecting image quality such as spatial resolution should be included in set-up and image quality-control procedures.

On the distribution of scaling hydraulic parameters in a spatially anisotropic banana field

NASA Astrophysics Data System (ADS)

Regalado, Carlos M.

2005-06-01

When modeling soil hydraulic properties at field scale it is desirable to approximate the variability in a given area by means of some scaling transformations which relate spatially variable local hydraulic properties to global reference characteristics. Seventy soil cores were sampled within a drip irrigated banana plantation greenhouse on a 14×5 array of 2.5 m×5 m rectangles at 15 cm depth, to represent the field scale variability of flow related properties. Saturated hydraulic conductivity and water retention characteristics were measured in these 70 soil cores. van Genuchten water retention curves (WRC) with optimized m ( m≠1-1/ n) were fitted to the WR data and a general Mualem-van Genuchten model was used to predict hydraulic conductivity functions for each soil core. A scaling law, of the form ν=ανi*, was fitted to soil hydraulic data, such that the original hydraulic parameters νi were scaled down to a reference curve with parameters νi*. An analytical expression, in terms of Beta functions, for the average suction value, hc, necessary to apply the above scaling method, was obtained. A robust optimization procedure with fast convergence to the global minimum is used to find the optimum hc, such that dispersion is minimized in the scaled data set. Via the Box-Cox transformation P(τ)=(αiτ-1)/τ, Box-Cox normality plots showed that scaling factors for the suction ( αh) and hydraulic conductivity ( αk) were approximately log-normally distributed (i.e. τ=0), as it would be expected for such dynamic properties involving flow. By contrast static soil related properties as αθ were found closely Gaussian, although a power τ=3/4 was best for approaching normality. Application of four different normality tests (Anderson-Darling, Shapiro-Wilk, Kolmogorov-Smirnov and χ2 goodness-of-fit tests) rendered some contradictory results among them, thus suggesting that this widely extended practice is not recommended for providing a suitable probability density function for the scaling parameters, αi. Some indications for the origin of these disagreements, in terms of population size and test constraints, are pointed out. Visual inspection of normal probability plots can also lead to erroneous results. The scaling parameters αθ and αK show a sinusoidal spatial variation coincident with the underlying alignment of banana plants on the field. Such anisotropic distribution is explained in terms of porosity variations due to processes promoting soil degradation as surface desiccation and soil compaction, induced by tillage and localized irrigation of banana plants, and it is quantified by means of cross-correlograms.

Practical implementation of channelized hotelling observers: effect of ROI size

NASA Astrophysics Data System (ADS)

Ferrero, Andrea; Favazza, Christopher P.; Yu, Lifeng; Leng, Shuai; McCollough, Cynthia H.

2017-03-01

Fundamental to the development and application of channelized Hotelling observer (CHO) models is the selection of the region of interest (ROI) to evaluate. For assessment of medical imaging systems, reducing the ROI size can be advantageous. Smaller ROIs enable a greater concentration of interrogable objects in a single phantom image, thereby providing more information from a set of images and reducing the overall image acquisition burden. Additionally, smaller ROIs may promote better assessment of clinical patient images as different patient anatomies present different ROI constraints. To this end, we investigated the minimum ROI size that does not compromise the performance of the CHO model. In this study, we evaluated both simulated images and phantom CT images to identify the minimum ROI size that resulted in an accurate figure of merit (FOM) of the CHO's performance. More specifically, the minimum ROI size was evaluated as a function of the following: number of channels, spatial frequency and number of rotations of the Gabor filters, size and contrast of the object, and magnitude of the image noise. Results demonstrate that a minimum ROI size exists below which the CHO's performance is grossly inaccurate. The minimum ROI size is shown to increase with number of channels and be dictated by truncation of lower frequency filters. We developed a model to estimate the minimum ROI size as a parameterized function of the number of orientations and spatial frequencies of the Gabor filters, providing a guide for investigators to appropriately select parameters for model observer studies.

Practical implementation of Channelized Hotelling Observers: Effect of ROI size.

PubMed

Ferrero, Andrea; Favazza, Christopher P; Yu, Lifeng; Leng, Shuai; McCollough, Cynthia H

2017-03-01

Fundamental to the development and application of channelized Hotelling observer (CHO) models is the selection of the region of interest (ROI) to evaluate. For assessment of medical imaging systems, reducing the ROI size can be advantageous. Smaller ROIs enable a greater concentration of interrogable objects in a single phantom image, thereby providing more information from a set of images and reducing the overall image acquisition burden. Additionally, smaller ROIs may promote better assessment of clinical patient images as different patient anatomies present different ROI constraints. To this end, we investigated the minimum ROI size that does not compromise the performance of the CHO model. In this study, we evaluated both simulated images and phantom CT images to identify the minimum ROI size that resulted in an accurate figure of merit (FOM) of the CHO's performance. More specifically, the minimum ROI size was evaluated as a function of the following: number of channels, spatial frequency and number of rotations of the Gabor filters, size and contrast of the object, and magnitude of the image noise. Results demonstrate that a minimum ROI size exists below which the CHO's performance is grossly inaccurate. The minimum ROI size is shown to increase with number of channels and be dictated by truncation of lower frequency filters. We developed a model to estimate the minimum ROI size as a parameterized function of the number of orientations and spatial frequencies of the Gabor filters, providing a guide for investigators to appropriately select parameters for model observer studies.

Baseflow physical characteristics differ at multiple spatial scales in stream networks across diverse biomes

Treesearch

Janine Ruegg; Walter K. Dodds; Melinda D. Daniels; Ken R. Sheehan; Christina L. Baker; William B. Bowden; Kaitlin J. Farrell; Michael B. Flinn; Tamara K. Harms; Jeremy B. Jones; Lauren E. Koenig; John S. Kominoski; William H. McDowell; Samuel P. Parker; Amy D. Rosemond; Matt T. Trentman; Matt Whiles; Wilfred M. Wollheim

2016-01-01

ContextSpatial scaling of ecological processes is facilitated by quantifying underlying habitat attributes. Physical and ecological patterns are often measured at disparate spatial scales limiting our ability to quantify ecological processes at broader spatial scales using physical attributes.

A Search for Plasma "Fingers" in the Io Torus

NASA Astrophysics Data System (ADS)

Jaggar, S.; Schneider, N. M.; Bagenal, F.; Trauger, J. T.

1996-09-01

We have compared model and data images of the Io plasma torus to test the radial diffusion model of Yang et al. (J. Geophys. Res., Vol 99, p. 8755, 1994). They predict that radial diffusion takes the form of `fingers' of dense plasma flowing outward due to the centrifugal force. Furthermore, they show that the spatial scale of these significant longitudinal variations is approximately 15(o) . The observations used in this study were obtained using a 2.4m telescope at Las Campanas Observatory using a narrowband filter to isolate emissions from S(++) at 9531 Angstroms. S(++) images are dominated by emission from the warm torus where outward radial transport is expected. Although S(+) images are brighter, they are contaminated by emission from the cold torus where fingers are not expected. We used the Colorado Io Torus Emission Package (CITEP)(Taylor et al., J. Geophys. Res., Vol. 100, p. 19541, 1995) to simulate images of the torus with fingers. CITEP is a comprehensive program which incorporates accurate atomic physics, plasma physics and magnetic field models to simulate the brightness and morphology or torus emissions. We used a Voyager empirical model (Bagenal, J. Geophys. Res., Vol. 99, p. 11043, 1994) modulated by a sinusoidal longitudinal density variation with a 15(o) period and an amplitude proportional to the density at that L-shell. We compared simulated images with data to determine the minimum density contrast necessary to make fingers detectable. We place an upper limit on the density contrast of +/- 20% on a 15(o) spatial scale. We conclude that either the density contrast of this mode of transport is small, or other processes are more important for radial transport. This constraint can also be used in other radial diffusion models which predict density variations on this spatial scale. This work has been supported by NASA's Planetary Astronomy and Planetary Atmospheres programs.

Extreme climatic events drive mammal irruptions: regression analysis of 100-year trends in desert rainfall and temperature

PubMed Central

Greenville, Aaron C; Wardle, Glenda M; Dickman, Chris R

2012-01-01

Extreme climatic events, such as flooding rains, extended decadal droughts and heat waves have been identified increasingly as important regulators of natural populations. Climate models predict that global warming will drive changes in rainfall and increase the frequency and severity of extreme events. Consequently, to anticipate how organisms will respond we need to document how changes in extremes of temperature and rainfall compare to trends in the mean values of these variables and over what spatial scales the patterns are consistent. Using the longest historical weather records available for central Australia – 100 years – and quantile regression methods, we investigate if extreme climate events have changed at similar rates to median events, if annual rainfall has increased in variability, and if the frequency of large rainfall events has increased over this period. Specifically, we compared local (individual weather stations) and regional (Simpson Desert) spatial scales, and quantified trends in median (50th quantile) and extreme weather values (5th, 10th, 90th, and 95th quantiles). We found that median and extreme annual minimum and maximum temperatures have increased at both spatial scales over the past century. Rainfall changes have been inconsistent across the Simpson Desert; individual weather stations showed increases in annual rainfall, increased frequency of large rainfall events or more prolonged droughts, depending on the location. In contrast to our prediction, we found no evidence that intra-annual rainfall had become more variable over time. Using long-term live-trapping records (22 years) of desert small mammals as a case study, we demonstrate that irruptive events are driven by extreme rainfalls (>95th quantile) and that increases in the magnitude and frequency of extreme rainfall events are likely to drive changes in the populations of these species through direct and indirect changes in predation pressure and wildfires. PMID:23170202

Understanding large-scale, long-term larval connectivity patterns: The case of the Northern Line Islands in the Central Pacific Ocean

PubMed Central

Mari, Lorenzo; Bonaventura, Luca; Storto, Andrea; Melià, Paco; Gatto, Marino; Masina, Simona

2017-01-01

Protecting key hotspots of marine biodiversity is essential to maintain ecosystem services at large spatial scales. Protected areas serve not only as sources of propagules colonizing other habitats, but also as receptors, thus acting as protected nurseries. To quantify the geographical extent and the temporal persistence of ecological benefits resulting from protection, we investigate larval connectivity within a remote archipelago, characterized by a strong spatial gradient of human impact from pristine to heavily exploited: the Northern Line Islands (NLIs), including part of the Pacific Remote Islands Marine National Monument (PRI-MNM). Larvae are described as passive Lagrangian particles transported by oceanic currents obtained from a oceanographic reanalysis. We compare different simulation schemes and compute connectivity measures (larval exchange probabilities and minimum/average larval dispersal distances from target islands). To explore the role of PRI-MNM in protecting marine organisms with pelagic larval stages, we drive millions of individual-based simulations for various Pelagic Larval Durations (PLDs), in all release seasons, and over a two-decades time horizon (1991–2010). We find that connectivity in the NLIs is spatially asymmetric and displays significant intra- and inter-annual variations. The islands belonging to PRI-MNM act more as sinks than sources of larvae, and connectivity is higher during the winter-spring period. In multi-annual analyses, yearly averaged southward connectivity significantly and negatively correlates with climatological anomalies (El Niño). This points out a possible system fragility and susceptibility to global warming. Quantitative assessments of large-scale, long-term marine connectivity patterns help understand region-specific, ecologically relevant interactions between islands. This is fundamental for devising scientifically-based protection strategies, which must be space- and time-varying to cope with the challenges posed by the concurrent pressures of human exploitation and global climate change. PMID:28809937

Understanding large-scale, long-term larval connectivity patterns: The case of the Northern Line Islands in the Central Pacific Ocean.

PubMed

Mari, Lorenzo; Bonaventura, Luca; Storto, Andrea; Melià, Paco; Gatto, Marino; Masina, Simona; Casagrandi, Renato

2017-01-01

Protecting key hotspots of marine biodiversity is essential to maintain ecosystem services at large spatial scales. Protected areas serve not only as sources of propagules colonizing other habitats, but also as receptors, thus acting as protected nurseries. To quantify the geographical extent and the temporal persistence of ecological benefits resulting from protection, we investigate larval connectivity within a remote archipelago, characterized by a strong spatial gradient of human impact from pristine to heavily exploited: the Northern Line Islands (NLIs), including part of the Pacific Remote Islands Marine National Monument (PRI-MNM). Larvae are described as passive Lagrangian particles transported by oceanic currents obtained from a oceanographic reanalysis. We compare different simulation schemes and compute connectivity measures (larval exchange probabilities and minimum/average larval dispersal distances from target islands). To explore the role of PRI-MNM in protecting marine organisms with pelagic larval stages, we drive millions of individual-based simulations for various Pelagic Larval Durations (PLDs), in all release seasons, and over a two-decades time horizon (1991-2010). We find that connectivity in the NLIs is spatially asymmetric and displays significant intra- and inter-annual variations. The islands belonging to PRI-MNM act more as sinks than sources of larvae, and connectivity is higher during the winter-spring period. In multi-annual analyses, yearly averaged southward connectivity significantly and negatively correlates with climatological anomalies (El Niño). This points out a possible system fragility and susceptibility to global warming. Quantitative assessments of large-scale, long-term marine connectivity patterns help understand region-specific, ecologically relevant interactions between islands. This is fundamental for devising scientifically-based protection strategies, which must be space- and time-varying to cope with the challenges posed by the concurrent pressures of human exploitation and global climate change.

Using maximum entropy to predict suitable habitat for the endangered dwarf wedgemussel in the Maryland Coastal Plain

USGS Publications Warehouse

Campbell, Cara; Hilderbrand, Robert H.

2017-01-01

Species distribution modelling can be useful for the conservation of rare and endangered species. Freshwater mussel declines have thinned species ranges producing spatially fragmented distributions across large areas. Spatial fragmentation in combination with a complex life history and heterogeneous environment makes predictive modelling difficult.A machine learning approach (maximum entropy) was used to model occurrences and suitable habitat for the federally endangered dwarf wedgemussel, Alasmidonta heterodon, in Maryland's Coastal Plain catchments. Landscape-scale predictors (e.g. land cover, land use, soil characteristics, geology, flow characteristics, and climate) were used to predict the suitability of individual stream segments for A. heterodon.The best model contained variables at three scales: minimum elevation (segment scale), percentage Tertiary deposits, low intensity development, and woody wetlands (sub-catchment), and percentage low intensity development, pasture/hay agriculture, and average depth to the water table (catchment). Despite a very small sample size owing to the rarity of A. heterodon, cross-validated prediction accuracy was 91%.Most predicted suitable segments occur in catchments not known to contain A. heterodon, which provides opportunities for new discoveries or population restoration. These model predictions can guide surveys toward the streams with the best chance of containing the species or, alternatively, away from those streams with little chance of containing A. heterodon.Developed reaches had low predicted suitability for A. heterodon in the Coastal Plain. Urban and exurban sprawl continues to modify stream ecosystems in the region, underscoring the need to preserve existing populations and to discover and protect new populations.

Future Extreme Heat Scenarios to Enable the Assessment of Climate Impacts on Public Health over the Coterminous U.S

NASA Astrophysics Data System (ADS)

Quattrochi, D. A.; Crosson, W. L.; Al-Hamdan, M. Z.; Estes, M. G., Jr.

2013-12-01

In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. This research seeks to provide historical and future measures of climate-driven extreme heat events to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The focus of research is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM outputs, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons for 2040 and 2090 are compared to the recent past period of 1981-2000. We characterize regional-scale temperature and humidity conditions using GCM outputs for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM outputs are analyzed to develop a ';heat stress climatology' based on statistics of extreme heat indicators. Differences between the two future and the past period are used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes are combined with the historical meteorological data, which is hourly and at a spatial scale (12 km) much finer than that of GCMs, to create future climate realizations. From these realizations, we compute the daily heat stress measures and related spatially-specific climatological fields, such as the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices, and a new heat stress variable developed as part of this research that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. Outputs are aggregated to the county level, which is a popular scale of analysis for public health interests. County-level statistics are made available to public health researchers by the Centers for Disease Control and Prevention (CDC) via the Wide-ranging Online Data for Epidemiologic Research (WONDER) system. This addition of heat stress measures to CDC WONDER allows decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. Through CDC WONDER, users are able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S.

Future Extreme Heat Scenarios to Enable the Assessment of Climate Impacts on Public Health over the Coterminous U.S.

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Crosson, William L.; Al-Hamdan, Mohammad Z.; Estes, Maurice G., Jr.

2013-01-01

In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. This research seeks to provide historical and future measures of climate-driven extreme heat events to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The focus of research is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM outputs, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons for 2040 and 2090 are compared to the recent past period of 1981- 2000. We characterize regional-scale temperature and humidity conditions using GCM outputs for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM outputs are analyzed to develop a 'heat stress climatology' based on statistics of extreme heat indicators. Differences between the two future and the past period are used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes are combined with the historical meteorological data, which is hourly and at a spatial scale (12 km), to create future climate realizations. From these realizations, we compute the daily heat stress measures and related spatially-specific climatological fields, such as the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices and a new heat stress variable developed as part of this research that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. Outputs are aggregated to the county level, which is a popular scale of analysis for public health interests. County-level statistics are made available to public health researchers by the Centers for Disease Control and Prevention (CDC) via the Wideranging Online Data for Epidemiologic Research (WONDER) system. This addition of heat stress measures to CDC WONDER allows decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. Through CDC WONDER, users are able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S

Linking Excessive Heat with Daily Heat-Related Mortality over the Coterminous United States

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Crosson, William L.; Al-Hamdan, Mohammad Z.; Estes, Maurice G., Jr.

2014-01-01

In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. This research seeks to provide historical and future measures of climate-driven extreme heat events to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The focus of research is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM outputs, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons for 2040 and 2090 are compared to the recent past period of 1981- 2000. We characterize regional-scale temperature and humidity conditions using GCM outputs for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM outputs are analyzed to develop a 'heat stress climatology' based on statistics of extreme heat indicators. Differences between the two future and the past period are used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes are combined with the historical meteorological data, which is hourly and at a spatial scale (12 km) much finer than that of GCMs, to create future climate realizations. From these realizations, we compute the daily heat stress measures and related spatially-specific climatological fields, such as the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices, and a new heat stress variable developed as part of this research that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. Outputs are aggregated to the county level, which is a popular scale of analysis for public health interests. County-level statistics are made available to public health researchers by the Centers for Disease Control and Prevention (CDC) via the Wide-ranging Online Data for Epidemiologic Research (WONDER) system. This addition of heat stress measures to CDC WONDER allows decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. Through CDC WONDER, users are able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S.

Eta Carinae: What We have learned recently with HST/STIS, VLT/UVES and VLTI: What We Might Learn with VLT/VLTI across the 2008/9 Minimum

NASA Technical Reports Server (NTRS)

Gull, Theodore R.

2005-01-01

Eta Carinae, the LBV that we have learned to love and hate, has revealed many clues of its character over the past seven years by studies with HST and VLT. Based upon X-Ray, optical and IR observations, Eta Carinae is convincingly a massive binary system that uniquely has major nebular ejecta that are connected with historical outbursts. We have successhlly followed the stellar and nebular changes over the 5.5 year cycle, especially with STIS and RXTE, and across the spectroscopic minimum in 2003.5 with STIS, CHANDRA, RXTE, FUSE, and VLT/UVES. The HST/STIS high spatial resolution, combined with appropriate spectral resolving powers from 1150 to 10300 A, has revealed much about the Central Source and especially the spatially resolved extended stellar atmosphere and the ejecta, known as the Homunculus. Indeed the neutral, dusty outer Homunculus, ejected in the 1840s, envelops the newly discovered ionized Little Homunculus, ejected in the 1890s. In line of sight, multiple hot clumps, both ionized and neutral, are seen in absorption and provide much information on the physical conditions of these massive ejecta. Against the nebular-scattered starlight, wind and nebular absorptions provide views at different angles from line of sight. The VLT/UVES studies from 2002 through 2004 provided very important time-sampled spectra of both the star as seen directly and as seen by the SE lobe viewing the polar region of the star. The VLTI 2.2 micron measures of the central source are consistent with a prolate spheroid with its axis extending along the axis of the Homunculus. This is consistent with the noticeably larger wind mass and higher terminal velocity along the axis of the Homunculus compared to that measured in line of sight at about 45 degrees from the polar axes. We understand the system to be a massive primary with an O or WR companion in a very highly elliptical orbit. The spectroscopic minimum occurs during periastron, when the greatly extended primary atmosphere and wind bottles up the ionizing uv radiation of the companion star. This transient drop in uv photons leads to recombination of much of the wind structure and of the nearby ejecta. Doubly-ionized elements (iron, neon, argon, vanadium) recombine to singly ionized forms and extended structures on the scales of below 0.03 arcseconds to an arcsecond change, appear, or disappear. With the loss of the STIS on HST, ground-based observations, especially with high spatial-resolution facilities, including the VLT and VLTI will be key to further studies across the minimum centered on 2009.0. Now is the time to plan for these studies.

Rapid localized deactivation of self-assembled monolayers by propagation-controlled laser-induced plasma and its application to self-patterning of electronics and biosensors

NASA Astrophysics Data System (ADS)

Kim, Jongsu; Kwon, Seung-Gab; Back, Seunghyun; Kang, Bongchul

2018-03-01

We present a novel laser-induced surface treatment process to rapidly control the spatial wettabilities of various functional solutions with submicron to micron resolutions. Ultrathin hydrophobic self-assembled monolayers (SAMs) that little absorb typical laser lights due to short penetration depth were selectively deactivated by instantaneous interaction with laser-induced metallic plasmas. The spatial region of the deactivated SAM, which corresponds to process resolution, is adjustable by controlling the spatial propagation of the plasma. This method leads to the parallel formation of hydrophilic functional solutions on glass substrates with a minimum resolution on the submicron scale. To show its feasibility in device engineering fields, this method was applied to the cost-effective fabrication of electronics and biosensors. Rapid self-patterning of electronic and biological functional solutions (silver nanoparticle solution and streptavidin protein solution) was successfully realized by selective deactivation of two different SAMs (tridecafluoro-1,1,2,2-tetrahydrooctyltrichlorosilane (FOTS) for electronics and the hetero-hybrid SAM (octadecyltrichlorosilane (OTS)/2-[methoxy(polyethyleneoxy)propyl] trichlorosilane (PEG)) for biosensors). As a result, this method can be exploited for the rapid and low-cost fabrication of various thin film devices such as electronics, biosensors, energy, displays, and photonics.

Statistical Downscaling and Bias Correction of Climate Model Outputs for Climate Change Impact Assessment in the U.S. Northeast

NASA Technical Reports Server (NTRS)

Ahmed, Kazi Farzan; Wang, Guiling; Silander, John; Wilson, Adam M.; Allen, Jenica M.; Horton, Radley; Anyah, Richard

2013-01-01

Statistical downscaling can be used to efficiently downscale a large number of General Circulation Model (GCM) outputs to a fine temporal and spatial scale. To facilitate regional impact assessments, this study statistically downscales (to 1/8deg spatial resolution) and corrects the bias of daily maximum and minimum temperature and daily precipitation data from six GCMs and four Regional Climate Models (RCMs) for the northeast United States (US) using the Statistical Downscaling and Bias Correction (SDBC) approach. Based on these downscaled data from multiple models, five extreme indices were analyzed for the future climate to quantify future changes of climate extremes. For a subset of models and indices, results based on raw and bias corrected model outputs for the present-day climate were compared with observations, which demonstrated that bias correction is important not only for GCM outputs, but also for RCM outputs. For future climate, bias correction led to a higher level of agreements among the models in predicting the magnitude and capturing the spatial pattern of the extreme climate indices. We found that the incorporation of dynamical downscaling as an intermediate step does not lead to considerable differences in the results of statistical downscaling for the study domain.

Evaluation of the spatial and temporal measurement requirements of remote sensors for monitoring regional air pollution episodes

NASA Technical Reports Server (NTRS)

Burke, H. H. K.; Bowley, C. J.; Barnes, J. C.

1979-01-01

The spatial and temporal measurement requirements of satellite sensors for monitoring regional air pollution episodes were evaluated. Use was made of two sets of data from the Sulfate Regional Experiment (SURE), which provided the first ground-based aerosol measurements from a regional-scale station network. The sulfate data were analyzed for two air pollution episode cases. The results of the analysis indicate that the key considerations required for episode mapping from satellite sensors are the following: (1) detection of sulfate levels exceeding 20 micron-g/cu m; (2) capability to view a broad area (of the order of 1500 km swath) because of regional extent of pollution episodes; (3) spatial resolution sufficient to detect variations in sulfate levels of greater than 10 micron-g/cu m over distances of the order of 50 to 75 km; (4) repeat coverage at least on a daily basis; and (5) satellite observations during the mid to late morning local time, when the sulfate levels have begun to increase after the early morning minimum levels, and convective-type cloud cover has not yet increased to the amount reached later in the afternoon. Analysis of the satellite imagery shows that convective clouds can obscure haze patterns. Additional parameters based on spectral analysis include wavelength and bandwidth requirements.

Testing Taylor’s hypothesis in Amazonian rainfall fields during the WETAMC/LBA experiment

NASA Astrophysics Data System (ADS)

Poveda, Germán; Zuluaga, Manuel D.

2005-11-01

Taylor's hypothesis (TH) for rainfall fields states that the spatial correlation of rainfall intensity at two points at the same instant of time can be equated with the temporal correlation at two instants of time at some fixed location. The validity of TH is tested in a set of 12 storms developed in Rondonia, southwestern Amazonia, Brazil, during the January-February 1999 Wet Season Atmospheric Meso-scale Campaign. The time Eulerian and Lagrangian Autocorrelation Functions (ACF) are estimated, as well as the time-averaged space ACF, using radar rainfall rates of storms spanning between 3.2 and 23 h, measured at 7-10-min time resolution, over a circle of 100 km radius, at 2 km spatial resolution. TH does not hold in 9 out of the 12 studied storms, due to their erratic trajectories and very low values of zonal wind velocity at 700 hPa, independently from underlying atmospheric stability conditions. TH was shown to hold for 3 storms, up to a cutoff time scale of 10-15 min, which is closely related to observed features of the life cycle of convective cells in the region. Such cutoff time scale in Amazonian storms is much shorter than the 40 min identified in mid-latitude convective storms, due to much higher values of CAPE and smaller values of storm speed in Amazonian storms as compared to mid-latitude ones, which in turn contribute to a faster destruction of the rainfall field isotropy. Storms satisfying TH undergo smooth linear trajectories over space, and exhibit the highest negative values of maximum, mean and minimum zonal wind velocity at 700 hPa, within narrow ranges of atmospheric stability conditions. Non-dimensional parameters involving CAPE (maximum, mean and minimum) and CINE (mean) are identified during the storms life cycle, for which TH holds: CAPE mean/CINE mean = [30-35], CAPE max/CINE mean = [32-40], and CAPE min/CINE mean = [22-28]. These findings are independent upon the timing of storms within the diurnal cycle. Also, the estimated Eulerian time ACF's decay faster than the time-averaged space and the Lagrangian time ACF's, irrespectively of TH validity. The Eulerian ACF's exhibit shorter e-folding times, reflecting smaller correlations over short time scales, but also shorter scale of fluctuation, reflecting less persistence in time than over space. No significant associations (linear, exponential or power law) were found between estimated e-folding times and scale of fluctuation, with all estimates of CAPE and CINE. Secondary correlation maxima appear between 50 and 70 min in the Lagrangian time ACF's for storms satisfying TH. No differences were found in the behavior of each of the three ACF's for storms developed during either the Easterly or Westerly zonal wind regimes which characterize the development of meso-scale convective systems over the region. These results have important implications for modelling and downscaling rainfall fields over tropical land areas.

Grid scale drives the scale and long-term stability of place maps

PubMed Central

Mallory, Caitlin S; Hardcastle, Kiah; Bant, Jason S; Giocomo, Lisa M

2018-01-01

Medial entorhinal cortex (MEC) grid cells fire at regular spatial intervals and project to the hippocampus, where place cells are active in spatially restricted locations. One feature of the grid population is the increase in grid spatial scale along the dorsal-ventral MEC axis. However, the difficulty in perturbing grid scale without impacting the properties of other functionally-defined MEC cell types has obscured how grid scale influences hippocampal coding and spatial memory. Here, we use a targeted viral approach to knock out HCN1 channels selectively in MEC, causing grid scale to expand while leaving other MEC spatial and velocity signals intact. Grid scale expansion resulted in place scale expansion in fields located far from environmental boundaries, reduced long-term place field stability and impaired spatial learning. These observations, combined with simulations of a grid-to-place cell model and position decoding of place cells, illuminate how grid scale impacts place coding and spatial memory. PMID:29335607

Transferring Error Characteristics of Satellite Rainfall Data from Ground Validation (gauged) into Non-ground Validation (ungauged)

NASA Astrophysics Data System (ADS)

Tang, L.; Hossain, F.

2009-12-01

Understanding the error characteristics of satellite rainfall data at different spatial/temporal scales is critical, especially when the scheduled Global Precipitation Mission (GPM) plans to provide High Resolution Precipitation Products (HRPPs) at global scales. Satellite rainfall data contain errors which need ground validation (GV) data for characterization, while satellite rainfall data will be most useful in the regions that are lacking in GV. Therefore, a critical step is to develop a spatial interpolation scheme for transferring the error characteristics of satellite rainfall data from GV regions to Non-GV regions. As a prelude to GPM, The TRMM Multi-satellite Precipitation Analysis (TMPA) products of 3B41RT and 3B42RT (Huffman et al., 2007) over the US spanning a record of 6 years are used as a representative example of satellite rainfall data. Next Generation Radar (NEXRAD) Stage IV rainfall data are used as the reference for GV data. Initial work by the authors (Tang et al., 2009, GRL) has shown promise in transferring error from GV to Non-GV regions, based on a six-year climatologic average of satellite rainfall data assuming only 50% of GV coverage. However, this transfer of error characteristics needs to be investigated for a range of GV data coverage. In addition, it is also important to investigate if proxy-GV data from an accurate space-borne sensor, such as the TRMM PR (or the GPM DPR), can be leveraged for the transfer of error at sparsely gauged regions. The specific question we ask in this study is, “what is the minimum coverage of GV data required for error transfer scheme to be implemented at acceptable accuracy in hydrological relevant scale?” Three geostatistical interpolation methods are compared: ordinary kriging, indicator kriging and disjunctive kriging. Various error metrics are assessed for transfer such as, Probability of Detection for rain and no rain, False Alarm Ratio, Frequency Bias, Critical Success Index, RMSE etc. Understanding the proper space-time scales at which these metrics can be reasonably transferred is also explored in this study. Keyword: Satellite rainfall, error transfer, spatial interpolation, kriging methods.

Seismic clusters analysis in Northeastern Italy by the nearest-neighbor approach

NASA Astrophysics Data System (ADS)

Peresan, Antonella; Gentili, Stefania

2018-01-01

The main features of earthquake clusters in Northeastern Italy are explored, with the aim to get new insights on local scale patterns of seismicity in the area. The study is based on a systematic analysis of robustly and uniformly detected seismic clusters, which are identified by a statistical method, based on nearest-neighbor distances of events in the space-time-energy domain. The method permits us to highlight and investigate the internal structure of earthquake sequences, and to differentiate the spatial properties of seismicity according to the different topological features of the clusters structure. To analyze seismicity of Northeastern Italy, we use information from local OGS bulletins, compiled at the National Institute of Oceanography and Experimental Geophysics since 1977. A preliminary reappraisal of the earthquake bulletins is carried out and the area of sufficient completeness is outlined. Various techniques are considered to estimate the scaling parameters that characterize earthquakes occurrence in the region, namely the b-value and the fractal dimension of epicenters distribution, required for the application of the nearest-neighbor technique. Specifically, average robust estimates of the parameters of the Unified Scaling Law for Earthquakes, USLE, are assessed for the whole outlined region and are used to compute the nearest-neighbor distances. Clusters identification by the nearest-neighbor method turn out quite reliable and robust with respect to the minimum magnitude cutoff of the input catalog; the identified clusters are well consistent with those obtained from manual aftershocks identification of selected sequences. We demonstrate that the earthquake clusters have distinct preferred geographic locations, and we identify two areas that differ substantially in the examined clustering properties. Specifically, burst-like sequences are associated with the north-western part and swarm-like sequences with the south-eastern part of the study region. The territorial heterogeneity of earthquakes clustering is in good agreement with spatial variability of scaling parameters identified by the USLE. In particular, the fractal dimension is higher to the west (about 1.2-1.4), suggesting a spatially more distributed seismicity, compared to the eastern parte of the investigated territory, where fractal dimension is very low (about 0.8-1.0).

Fault Network Reconstruction using Agglomerative Clustering: Applications to South Californian Seismicity

NASA Astrophysics Data System (ADS)

Kamer, Yavor; Ouillon, Guy; Sornette, Didier; Wössner, Jochen

2014-05-01

We present applications of a new clustering method for fault network reconstruction based on the spatial distribution of seismicity. Unlike common approaches that start from the simplest large scale and gradually increase the complexity trying to explain the small scales, our method uses a bottom-up approach, by an initial sampling of the small scales and then reducing the complexity. The new approach also exploits the location uncertainty associated with each event in order to obtain a more accurate representation of the spatial probability distribution of the seismicity. For a given dataset, we first construct an agglomerative hierarchical cluster (AHC) tree based on Ward's minimum variance linkage. Such a tree starts out with one cluster and progressively branches out into an increasing number of clusters. To atomize the structure into its constitutive protoclusters, we initialize a Gaussian Mixture Modeling (GMM) at a given level of the hierarchical clustering tree. We then let the GMM converge using an Expectation Maximization (EM) algorithm. The kernels that become ill defined (less than 4 points) at the end of the EM are discarded. By incrementing the number of initialization clusters (by atomizing at increasingly populated levels of the AHC tree) and repeating the procedure above, we are able to determine the maximum number of Gaussian kernels the structure can hold. The kernels in this configuration constitute our protoclusters. In this setting, merging of any pair will lessen the likelihood (calculated over the pdf of the kernels) but in turn will reduce the model's complexity. The information loss/gain of any possible merging can thus be quantified based on the Minimum Description Length (MDL) principle. Similar to an inter-distance matrix, where the matrix element di,j gives the distance between points i and j, we can construct a MDL gain/loss matrix where mi,j gives the information gain/loss resulting from the merging of kernels i and j. Based on this matrix, merging events resulting in MDL gain are performed in descending order until no gainful merging is possible anymore. We envision that the results of this study could lead to a better understanding of the complex interactions within the Californian fault system and hopefully use the acquired insights for earthquake forecasting.

Optimal configurations of spatial scale for grid cell firing under noise and uncertainty

PubMed Central

Towse, Benjamin W.; Barry, Caswell; Bush, Daniel; Burgess, Neil

2014-01-01

We examined the accuracy with which the location of an agent moving within an environment could be decoded from the simulated firing of systems of grid cells. Grid cells were modelled with Poisson spiking dynamics and organized into multiple ‘modules’ of cells, with firing patterns of similar spatial scale within modules and a wide range of spatial scales across modules. The number of grid cells per module, the spatial scaling factor between modules and the size of the environment were varied. Errors in decoded location can take two forms: small errors of precision and larger errors resulting from ambiguity in decoding periodic firing patterns. With enough cells per module (e.g. eight modules of 100 cells each) grid systems are highly robust to ambiguity errors, even over ranges much larger than the largest grid scale (e.g. over a 500 m range when the maximum grid scale is 264 cm). Results did not depend strongly on the precise organization of scales across modules (geometric, co-prime or random). However, independent spatial noise across modules, which would occur if modules receive independent spatial inputs and might increase with spatial uncertainty, dramatically degrades the performance of the grid system. This effect of spatial uncertainty can be mitigated by uniform expansion of grid scales. Thus, in the realistic regimes simulated here, the optimal overall scale for a grid system represents a trade-off between minimizing spatial uncertainty (requiring large scales) and maximizing precision (requiring small scales). Within this view, the temporary expansion of grid scales observed in novel environments may be an optimal response to increased spatial uncertainty induced by the unfamiliarity of the available spatial cues. PMID:24366144

It's the Heat AND the Humidity -- Assessment of Extreme Heat Scenarios to Enable the Assessment of Climate Impacts on Public Health

NASA Technical Reports Server (NTRS)

Crosson, William L; Al-Hamdan, Mohammad Z.; Economou, Sigrid, A.; Estes, Maurice G.; Estes, Sue M.; Puckett, Mark; Quattrochi, Dale A

2013-01-01

In the United States, extreme heat is the most deadly weather-related hazard. In the face of a warming climate and urbanization, which contributes to local-scale urban heat islands, it is very likely that extreme heat events (EHEs) will become more common and more severe in the U.S. In a NASA-funded project supporting the National Climate Assessment, we are providing historical and future measures of extreme heat to enable assessments of the impacts of heat on public health over the coterminous U.S. We use atmospheric temperature and humidity information from meteorological reanalysis and from Global Climate Models (GCMs) to provide data on past and future heat events. The project s emphasis is on providing assessments of the magnitude, frequency and geographic distribution of extreme heat in the U.S. to facilitate public health studies. In our approach, long-term climate change is captured with GCM output, and the temporal and spatial characteristics of short-term extremes are represented by the reanalysis data. Two future time horizons, 2040 and 2090, are the focus of future assessments; these are compared to the recent past period of 1981-2000. We are characterizing regional-scale temperature and humidity conditions using GCM output for two climate change scenarios (A2 and A1B) defined in the Special Report on Emissions Scenarios (SRES). For each future period, 20 years of multi-model GCM output have been analyzed to develop a heat stress climatology based on statistics of extreme heat indicators. Differences between the two future and past periods have been used to define temperature and humidity changes on a monthly time scale and regional spatial scale. These changes, combined with hourly historical meteorological data at a spatial scale (12 km) much finer than that of GCMs, enable us to create future climate realizations, from which we compute the daily heat stress measures and related spatially-specific climatological fields. These include the mean annual number of days above certain thresholds of maximum and minimum air temperatures, heat indices and a new heat stress variable that gives an integrated measure of heat stress (and relief) over the course of a day. Comparisons are made between projected (2040 and 2090) and past (1990) heat stress statistics. All output is being provided at the 12 km spatial scale and will also be aggregated to the county level, which is a popular scale of analysis for public health researchers. County-level statistics will be made available by our collaborators at the Centers for Disease Control and Prevention (CDC) via the Wide-ranging Online Data for Epidemiologic Research (WONDER) system. CDC WONDER makes the information resources of the CDC available to public health professionals and the general public. This addition of heat stress measures to CDC WONDER will allow decision and policy makers to assess the impact of alternative approaches to optimize the public health response to EHEs. It will also allow public health researchers and policy makers to better include such heat stress measures in the context of national health data available in the CDC WONDER system. The users will be able to spatially and temporally query public health and heat-related data sets and create county-level maps and statistical charts of such data across the coterminous U.S.

Multi-temporal thermal analyses for submarine groundwater discharge (SGD) detection over large spatial scales in the Mediterranean

NASA Astrophysics Data System (ADS)

Hennig, Hanna; Mallast, Ulf; Merz, Ralf

2015-04-01

Submarine groundwater discharge (SGD) sites act as important pathways for nutrients and contaminants that deteriorate marine ecosystems. In the Mediterranean it is estimated that 75% of freshwater input is contributed from karst aquifers. Thermal remote sensing can be used for a pre-screening of potential SGD sites in order to optimize field surveys. Although different platforms (ground-, air- and spaceborne) may serve for thermal remote sensing, the most cost-effective are spaceborne platforms (satellites) that likewise cover the largest spatial scale (>100 km per image). Therefore an automatized and objective approach that uses thermal satellite images from Landsat 7 and Landsat 8 was used to localize potential SGD sites on a large spatial scale. The method using descriptive statistic parameter specially range and standard deviation by (Mallast et al., 2014) was adapted to the Mediterranean Sea. Since the method was developed for the Dead Sea were satellite images with cloud cover are rare and no sea level change occurs through tidal cycles it was essential to adapt the method to a region where tidal cycles occur and cloud cover is more frequent . These adaptations include: (1) an automatic and adaptive coastline detection (2) include and process cloud covered scenes to enlarge the data basis, (3) implement tidal data in order to analyze low tide images as SGD is enhanced during these phases and (4) test the applicability for Landsat 8 images that will provide data in the future once Landsat 7 stops working. As previously shown, the range method shows more accurate results compared to the standard deviation. However, the result exclusively depends on two scenes (minimum and maximum) and is largely influenced by outliers. Counteracting on this drawback we developed a new approach. Since it is assumed that sea surface temperature (SST) is stabilized by groundwater at SGD sites, the slope of a bootstrapped linear model fitted to sorted SST per pixel would be less steep than the slope of the surrounding area, resulting in less influence through outliers and an equal weighting of all integrated scenes. Both methods could be used to detect SGD sites in the Mediterranean regardless to the discharge characteristics (diffuse and focused) exceptions are sites with deep emergences. Better results could be shown in bays compared to more exposed sites. Since the range of the SST is mostly influenced by maximum and minimum of the scenes, the slope approach can be seen as a more representative method using all scenes. References: Mallast, U., Gloaguen, R., Friesen, J., Rödiger, T., Geyer, S., Merz, R., Siebert, C., 2014. How to identify groundwater-caused thermal anomalies in lakes based on multi-temporal satellite data in semi-arid regions. Hydrol. Earth Syst. Sci. 18 (7), 2773-2787.

Enabling heterogenous multi-scale database for emergency service functions through geoinformation technologies

NASA Astrophysics Data System (ADS)

Bhanumurthy, V.; Venugopala Rao, K.; Srinivasa Rao, S.; Ram Mohan Rao, K.; Chandra, P. Satya; Vidhyasagar, J.; Diwakar, P. G.; Dadhwal, V. K.

2014-11-01

Geographical Information Science (GIS) is now graduated from traditional desktop system to Internet system. Internet GIS is emerging as one of the most promising technologies for addressing Emergency Management. Web services with different privileges are playing an important role in dissemination of the emergency services to the decision makers. Spatial database is one of the most important components in the successful implementation of Emergency Management. It contains spatial data in the form of raster, vector, linked with non-spatial information. Comprehensive data is required to handle emergency situation in different phases. These database elements comprise core data, hazard specific data, corresponding attribute data, and live data coming from the remote locations. Core data sets are minimum required data including base, thematic, infrastructure layers to handle disasters. Disaster specific information is required to handle a particular disaster situation like flood, cyclone, forest fire, earth quake, land slide, drought. In addition to this Emergency Management require many types of data with spatial and temporal attributes that should be made available to the key players in the right format at right time. The vector database needs to be complemented with required resolution satellite imagery for visualisation and analysis in disaster management. Therefore, the database is interconnected and comprehensive to meet the requirement of an Emergency Management. This kind of integrated, comprehensive and structured database with appropriate information is required to obtain right information at right time for the right people. However, building spatial database for Emergency Management is a challenging task because of the key issues such as availability of data, sharing policies, compatible geospatial standards, data interoperability etc. Therefore, to facilitate using, sharing, and integrating the spatial data, there is a need to define standards to build emergency database systems. These include aspects such as i) data integration procedures namely standard coding scheme, schema, meta data format, spatial format ii) database organisation mechanism covering data management, catalogues, data models iii) database dissemination through a suitable environment, as a standard service for effective service dissemination. National Database for Emergency Management (NDEM) is such a comprehensive database for addressing disasters in India at the national level. This paper explains standards for integrating, organising the multi-scale and multi-source data with effective emergency response using customized user interfaces for NDEM. It presents standard procedure for building comprehensive emergency information systems for enabling emergency specific functions through geospatial technologies.

High spatial resolution mapping of folds and fractures using Unmanned Aerial Vehicle (UAV) photogrammetry

NASA Astrophysics Data System (ADS)

Cruden, A. R.; Vollgger, S.

2016-12-01

The emerging capability of UAV photogrammetry combines a simple and cost-effective method to acquire digital aerial images with advanced computer vision algorithms that compute spatial datasets from a sequence of overlapping digital photographs from various viewpoints. Depending on flight altitude and camera setup, sub-centimeter spatial resolution orthophotographs and textured dense point clouds can be achieved. Orientation data can be collected for detailed structural analysis by digitally mapping such high-resolution spatial datasets in a fraction of time and with higher fidelity compared to traditional mapping techniques. Here we describe a photogrammetric workflow applied to a structural study of folds and fractures within alternating layers of sandstone and mudstone at a coastal outcrop in SE Australia. We surveyed this location using a downward looking digital camera mounted on commercially available multi-rotor UAV that autonomously followed waypoints at a set altitude and speed to ensure sufficient image overlap, minimum motion blur and an appropriate resolution. The use of surveyed ground control points allowed us to produce a geo-referenced 3D point cloud and an orthophotograph from hundreds of digital images at a spatial resolution < 10 mm per pixel, and cm-scale location accuracy. Orientation data of brittle and ductile structures were semi-automatically extracted from these high-resolution datasets using open-source software. This resulted in an extensive and statistically relevant orientation dataset that was used to 1) interpret the progressive development of folds and faults in the region, and 2) to generate a 3D structural model that underlines the complex internal structure of the outcrop and quantifies spatial variations in fold geometries. Overall, our work highlights how UAV photogrammetry can contribute to new insights in structural analysis.

Modelling Spatial Dependence Structures Between Climate Variables by Combining Mixture Models with Copula Models

NASA Astrophysics Data System (ADS)

Khan, F.; Pilz, J.; Spöck, G.

2017-12-01

Spatio-temporal dependence structures play a pivotal role in understanding the meteorological characteristics of a basin or sub-basin. This further affects the hydrological conditions and consequently will provide misleading results if these structures are not taken into account properly. In this study we modeled the spatial dependence structure between climate variables including maximum, minimum temperature and precipitation in the Monsoon dominated region of Pakistan. For temperature, six, and for precipitation four meteorological stations have been considered. For modelling the dependence structure between temperature and precipitation at multiple sites, we utilized C-Vine, D-Vine and Student t-copula models. For temperature, multivariate mixture normal distributions and for precipitation gamma distributions have been used as marginals under the copula models. A comparison was made between C-Vine, D-Vine and Student t-copula by observational and simulated spatial dependence structure to choose an appropriate model for the climate data. The results show that all copula models performed well, however, there are subtle differences in their performances. The copula models captured the patterns of spatial dependence structures between climate variables at multiple meteorological sites, however, the t-copula showed poor performance in reproducing the dependence structure with respect to magnitude. It was observed that important statistics of observed data have been closely approximated except of maximum values for temperature and minimum values for minimum temperature. Probability density functions of simulated data closely follow the probability density functions of observational data for all variables. C and D-Vines are better tools when it comes to modelling the dependence between variables, however, Student t-copulas compete closely for precipitation. Keywords: Copula model, C-Vine, D-Vine, Spatial dependence structure, Monsoon dominated region of Pakistan, Mixture models, EM algorithm.

Source-space ICA for MEG source imaging.

PubMed

Jonmohamadi, Yaqub; Jones, Richard D

2016-02-01

One of the most widely used approaches in electroencephalography/magnetoencephalography (MEG) source imaging is application of an inverse technique (such as dipole modelling or sLORETA) on the component extracted by independent component analysis (ICA) (sensor-space ICA + inverse technique). The advantage of this approach over an inverse technique alone is that it can identify and localize multiple concurrent sources. Among inverse techniques, the minimum-variance beamformers offer a high spatial resolution. However, in order to have both high spatial resolution of beamformer and be able to take on multiple concurrent sources, sensor-space ICA + beamformer is not an ideal combination. We propose source-space ICA for MEG as a powerful alternative approach which can provide the high spatial resolution of the beamformer and handle multiple concurrent sources. The concept of source-space ICA for MEG is to apply the beamformer first and then singular value decomposition + ICA. In this paper we have compared source-space ICA with sensor-space ICA both in simulation and real MEG. The simulations included two challenging scenarios of correlated/concurrent cluster sources. Source-space ICA provided superior performance in spatial reconstruction of source maps, even though both techniques performed equally from a temporal perspective. Real MEG from two healthy subjects with visual stimuli were also used to compare performance of sensor-space ICA and source-space ICA. We have also proposed a new variant of minimum-variance beamformer called weight-normalized linearly-constrained minimum-variance with orthonormal lead-field. As sensor-space ICA-based source reconstruction is popular in EEG and MEG imaging, and given that source-space ICA has superior spatial performance, it is expected that source-space ICA will supersede its predecessor in many applications.

GIS-based niche modeling for mapping species' habitats

USGS Publications Warehouse

Rotenberry, J.T.; Preston, K.L.; Knick, S.

2006-01-01

Ecological a??niche modelinga?? using presence-only locality data and large-scale environmental variables provides a powerful tool for identifying and mapping suitable habitat for species over large spatial extents. We describe a niche modeling approach that identifies a minimum (rather than an optimum) set of basic habitat requirements for a species, based on the assumption that constant environmental relationships in a species' distribution (i.e., variables that maintain a consistent value where the species occurs) are most likely to be associated with limiting factors. Environmental variables that take on a wide range of values where a species occurs are less informative because they do not limit a species' distribution, at least over the range of variation sampled. This approach is operationalized by partitioning Mahalanobis D2 (standardized difference between values of a set of environmental variables for any point and mean values for those same variables calculated from all points at which a species was detected) into independent components. The smallest of these components represents the linear combination of variables with minimum variance; increasingly larger components represent larger variances and are increasingly less limiting. We illustrate this approach using the California Gnatcatcher (Polioptila californica Brewster) and provide SAS code to implement it.

Snowmelt hydrograph interpretation: Revealing watershed scale hydrologic characteristics of the Yellowstone volcanic plateau

USGS Publications Warehouse

Payton, Gardner W.; Susong, D.D.; Kip, Solomon D.; Heasler, H.

2010-01-01

Snowmelt hydrograph analysis and groundwater age dates of cool water springs on the Yellowstone volcanic plateau provide evidence of high volumes of groundwater circulation in watersheds comprised of quaternary Yellowstone volcanics. Ratios of maximum to minimum mean daily discharge and average recession indices are calculated for watersheds within and surrounding the Yellowstone volcanic plateau. A model for snowmelt recession is used to separate groundwater discharge from overland runoff, and compare groundwater systems. Hydrograph signal interpretation is corroborated with chlorofluorocarbon (CFC) and tritium concentrations in cool water springs on the Yellowstone volcanic plateau. Hydrograph parameters show a spatial pattern correlated with watershed geology. Watersheds comprised dominantly of quaternary Yellowstone volcanics are characterized by slow streamflow recession, low maximum to minimum flow ratios. Cool springs sampled within the Park contain CFC's and tritium and have apparent CFC age dates that range from about 50 years to modern. Watersheds comprised of quaternary Yellowstone volcanics have a large volume of active groundwater circulation. A large, advecting groundwater field would be the dominant mechanism for mass and energy transport in the shallow crust of the Yellowstone volcanic plateau, and thus control the Yellowstone hydrothermal system. ?? 2009 Elsevier B.V.

A Simplified Ab Initio Cosmic-ray Modulation Model with Simulated Time Dependence and Predictive Capability

NASA Astrophysics Data System (ADS)

Moloto, K. D.; Engelbrecht, N. E.; Burger, R. A.

2018-06-01

A simplified ab initio approach is followed to model cosmic-ray proton modulation, using a steady-state three-dimensional stochastic solver of the Parker transport equation that simulates some effects of time dependence. Standard diffusion coefficients based on Quasilinear Theory and Nonlinear Guiding Center Theory are employed. The spatial and temporal dependences of the various turbulence quantities required as inputs for the diffusion, as well as the turbulence-reduced drift coefficients, follow from parametric fits to results from a turbulence transport model as well as from spacecraft observations of these turbulence quantities. Effective values are used for the solar wind speed, magnetic field magnitude, and tilt angle in the modulation model to simulate temporal effects due to changes in the large-scale heliospheric plasma. The unusually high cosmic-ray intensities observed during the 2009 solar minimum follow naturally from the current model for most of the energies considered. This demonstrates that changes in turbulence contribute significantly to the high intensities during that solar minimum. We also discuss and illustrate how this model can be used to predict future cosmic-ray intensities, and comment on the reliability of such predictions.

Possible future changes in South East Australian frost frequency: an inter-comparison of statistical downscaling approaches

NASA Astrophysics Data System (ADS)

Crimp, Steven; Jin, Huidong; Kokic, Philip; Bakar, Shuvo; Nicholls, Neville

2018-04-01

Anthropogenic climate change has already been shown to effect the frequency, intensity, spatial extent, duration and seasonality of extreme climate events. Understanding these changes is an important step in determining exposure, vulnerability and focus for adaptation. In an attempt to support adaptation decision-making we have examined statistical modelling techniques to improve the representation of global climate model (GCM) derived projections of minimum temperature extremes (frosts) in Australia. We examine the spatial changes in minimum temperature extreme metrics (e.g. monthly and seasonal frost frequency etc.), for a region exhibiting the strongest station trends in Australia, and compare these changes with minimum temperature extreme metrics derived from 10 GCMs, from the Coupled Model Inter-comparison Project Phase 5 (CMIP 5) datasets, and via statistical downscaling. We compare the observed trends with those derived from the "raw" GCM minimum temperature data as well as examine whether quantile matching (QM) or spatio-temporal (spTimerQM) modelling with Quantile Matching can be used to improve the correlation between observed and simulated extreme minimum temperatures. We demonstrate, that the spTimerQM modelling approach provides correlations with observed daily minimum temperatures for the period August to November of 0.22. This represents an almost fourfold improvement over either the "raw" GCM or QM results. The spTimerQM modelling approach also improves correlations with observed monthly frost frequency statistics to 0.84 as opposed to 0.37 and 0.81 for the "raw" GCM and QM results respectively. We apply the spatio-temporal model to examine future extreme minimum temperature projections for the period 2016 to 2048. The spTimerQM modelling results suggest the persistence of current levels of frost risk out to 2030, with the evidence of continuing decadal variation.

Characterizing spatial heterogeneity based on the b-value and fractal analyses of the 2015 Nepal earthquake sequence

NASA Astrophysics Data System (ADS)

Nampally, Subhadra; Padhy, Simanchal; Dimri, Vijay P.

2018-01-01

The nature of spatial distribution of heterogeneities in the source area of the 2015 Nepal earthquake is characterized based on the seismic b-value and fractal analysis of its aftershocks. The earthquake size distribution of aftershocks gives a b-value of 1.11 ± 0.08, possibly representing the highly heterogeneous and low stress state of the region. The aftershocks exhibit a fractal structure characterized by a spectrum of generalized dimensions, Dq varying from D2 = 1.66 to D22 = 0.11. The existence of a fractal structure suggests that the spatial distribution of aftershocks is not a random phenomenon, but it self-organizes into a critical state, exhibiting a scale-independent structure governed by a power-law scaling, where a small perturbation in stress is sufficient enough to trigger aftershocks. In order to obtain the bias in fractal dimensions resulting from finite data size, we compared the multifractal spectrum for the real data and random simulations. On comparison, we found that the lower limit of bias in D2 is 0.44. The similarity in their multifractal spectra suggests the lack of long-range correlation in the data, with an only weakly multifractal or a monofractal with a single correlation dimension D2 characterizing the data. The minimum number of events required for a multifractal process with an acceptable error is discussed. We also tested for a possible correlation between changes in D2 and energy released during the earthquakes. The values of D2 rise during the two largest earthquakes (M > 7.0) in the sequence. The b- and D2 values are related by D2 = 1.45 b that corresponds to the intermediate to large earthquakes. Our results provide useful constraints on the spatial distribution of b- and D2-values, which are useful for seismic hazard assessment in the aftershock area of a large earthquake.

Climate limits across space and time on European forest structure

NASA Astrophysics Data System (ADS)

Moreno, A. L. S.; Neumann, M.; Hasenauer, H.

2017-12-01

The impact climate has on forests has been extensively studied. However, the large scale effect climate has on forest structures, such as average diameters, heights and basal area are understudied in a spatially explicit manner. The limits, tipping points and thresholds that climate places on forest structures dictate the services a forest may provide, the vulnerability of a forest to mortality and the potential value of the timber there within. The majority of current research either investigates climate impacts on forest pools and fluxes, on a tree physiological scale or on case studies that are used to extrapolate results and potential impacts. A spatially explicit study on how climate affects forest structure over a large region would give valuable information to stakeholders who are more concerned with ecosystem services that cannot be described by pools and fluxes but require spatially explicit information - such as biodiversity, habitat suitability, and market values. In this study, we quantified the limits that climate (maximum, minimum temperature and precipitation) places on 3 forest structures, diameter at breast height, height, and basal area throughout Europe. Our results show clear climatic zones of high and low upper limits for each forest structure variable studied. We also spatially analyzed how climate restricts the potential bio-physical upper limits and creates tipping points of each forest structure variable and which climate factors are most limiting. Further, we demonstrated how the climate change has affected 8 individual forests across Europe and then the continent as a whole. We find that diameter, height and basal area are limited by climate in different ways and that areas may have high upper limits in one structure and low upper limits in another limitted by different climate variables. We also found that even though individual forests may have increased their potential upper limit forest structure values, European forests as a whole have lost, on average, 5.0%, 1.7% and 6.5% in potential mean forest diameter, height and basal area, respectively.

An application to model traffic intensity of agricultural machinery at field scale

NASA Astrophysics Data System (ADS)

Augustin, Katja; Kuhwald, Michael; Duttmann, Rainer

2017-04-01

Several soil-pressure-models deal with the impact of agricultural machines on soils. In many cases, these models were used for single spots and consider a static machine configuration. Therefore, a statement about the spatial distribution of soil compaction risk for entire working processes is limited. The aim of the study is the development of an application for the spatial modelling of traffic lanes from agricultural vehicles including wheel load, ground pressure and wheel passages at the field scale. The application is based on Open Source software, application and data formats, using python programming language. Minimum input parameters are GPS-positions, vehicles and tires (producer and model) and the tire inflation pressure. Five working processes were distinguished: soil tillage, manuring, plant protection, sowing and harvest. Currently, two different models (Diserens 2009, Rücknagel et al. 2015) were implemented to calculate the soil pressure. The application was tested at a study site in Lower Saxony, Germany. Since 2015, field traffic were recorded by RTK-GPS and used machine set ups were noted. Using these input information the traffic lanes, wheel load and soil pressure were calculated for all working processes. For instance, the maize harvest in 2016 with a crop chopper and one transport vehicle crossed about 55 % of the total field area. At some places the machines rolled over up to 46 times. Approximately 35 % of the total area was affected by wheel loads over 7 tons and soil pressures between 163 and 193 kPa. With the information about the spatial distribution of wheel passages, wheel load and soil pressure it is possible to identify hot spots of intensive field traffic. Additionally, the use of the application enables the analysis of soil compaction risk induced by agricultural machines for long- and short-term periods.

Automating the selection of standard parallels for conic map projections

NASA Astrophysics Data System (ADS)

Šavriǒ, Bojan; Jenny, Bernhard

2016-05-01

Conic map projections are appropriate for mapping regions at medium and large scales with east-west extents at intermediate latitudes. Conic projections are appropriate for these cases because they show the mapped area with less distortion than other projections. In order to minimize the distortion of the mapped area, the two standard parallels of conic projections need to be selected carefully. Rules of thumb exist for placing the standard parallels based on the width-to-height ratio of the map. These rules of thumb are simple to apply, but do not result in maps with minimum distortion. There also exist more sophisticated methods that determine standard parallels such that distortion in the mapped area is minimized. These methods are computationally expensive and cannot be used for real-time web mapping and GIS applications where the projection is adjusted automatically to the displayed area. This article presents a polynomial model that quickly provides the standard parallels for the three most common conic map projections: the Albers equal-area, the Lambert conformal, and the equidistant conic projection. The model defines the standard parallels with polynomial expressions based on the spatial extent of the mapped area. The spatial extent is defined by the length of the mapped central meridian segment, the central latitude of the displayed area, and the width-to-height ratio of the map. The polynomial model was derived from 3825 maps-each with a different spatial extent and computationally determined standard parallels that minimize the mean scale distortion index. The resulting model is computationally simple and can be used for the automatic selection of the standard parallels of conic map projections in GIS software and web mapping applications.

Hydrological and geomorphological controls of malaria transmission

NASA Astrophysics Data System (ADS)

Smith, M. W.; Macklin, M. G.; Thomas, C. J.

2013-01-01

Malaria risk is linked inextricably to the hydrological and geomorphological processes that form vector breeding sites. Yet environmental controls of malaria transmission are often represented by temperature and rainfall amounts, ignoring hydrological and geomorphological influences altogether. Continental-scale studies incorporate hydrology implicitly through simple minimum rainfall thresholds, while community-scale coupled hydrological and entomological models do not represent the actual diversity of the mosquito vector breeding sites. The greatest range of malaria transmission responses to environmental factors is observed at the catchment scale where seemingly contradictory associations between rainfall and malaria risk can be explained by hydrological and geomorphological processes that govern surface water body formation and persistence. This paper extends recent efforts to incorporate ecological factors into malaria-risk models, proposing that the same detailed representation be afforded to hydrological and, at longer timescales relevant for predictions of climate change impacts, geomorphological processes. We review existing representations of environmental controls of malaria and identify a range of hydrologically distinct vector breeding sites from existing literature. We illustrate the potential complexity of interactions among hydrology, geomorphology and vector breeding sites by classifying a range of water bodies observed in a catchment in East Africa. Crucially, the mechanisms driving surface water body formation and destruction must be considered explicitly if we are to produce dynamic spatial models of malaria risk at catchment scales.

Satellite observations for describing fire patterns and climate-related fire drivers in the Brazilian savannas

NASA Astrophysics Data System (ADS)

Verola Mataveli, Guilherme Augusto; Siqueira Silva, Maria Elisa; Pereira, Gabriel; da Silva Cardozo, Francielle; Shinji Kawakubo, Fernando; Bertani, Gabriel; Cezar Costa, Julio; de Cássia Ramos, Raquel; Valéria da Silva, Viviane

2018-01-01

In the Brazilian savannas (Cerrado biome) fires are natural and a tool for shifting land use; therefore, temporal and spatial patterns result from the interaction of climate, vegetation condition and human activities. Moreover, orbital sensors are the most effective approach to establish patterns in the biome. We aimed to characterize fire, precipitation and vegetation condition regimes and to establish spatial patterns of fire occurrence and their correlation with precipitation and vegetation condition in the Cerrado. The Cerrado was first and second biome for the occurrence of burned areas (BA) and hotspots, respectively. Occurrences are higher during the dry season and in the savanna land use. Hotspots and BA tend to decrease, and concentrate in the north, but more intense hotspots are not necessarily located where concentration is higher. Spatial analysis showed that averaged and summed values can hide patterns, such as for precipitation, which has the lowest average in August, but minimum precipitation in August was found in 7 % of the Cerrado. Usually, there is a 2-3-month lag between minimum precipitation and maximum hotspots and BA, while minimum VCI and maximum hotspots and BA occur in the same month. Hotspots and BA are better correlated with VCI than precipitation, qualifying VCI as an indicator of the susceptibility of vegetation to ignition.

Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

NASA Astrophysics Data System (ADS)

Mishra, U.; Riley, W. J.

2015-01-01

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing heterogeneity of terrestrial hydrological and biogeochemical processes in earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a dataset with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales (s = 100, 200, 500 m, 1, 2, 5, 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions (R2 = 0.83-0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98% of variability in the variance of SOC stocks. We found moderately-accurate linear relationships between mean and higher-order moments of predicted SOC stocks (R2 ~ 0.55-0.63). Current ESMs operate at coarse spatial scales (50-100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks can improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.

Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

NASA Astrophysics Data System (ADS)

Mishra, U.; Riley, W. J.

2015-07-01

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing the heterogeneity of terrestrial hydrological and biogeochemical processes in Earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a data set with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales (s = 100, 200, and 500 m and 1, 2, 5, and 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions (R2 = 0.83-0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 m to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98 % of variability in the variance of SOC stocks. We found moderately accurate linear relationships between mean and higher-order moments of predicted SOC stocks (R2 ∼ 0.55-0.63). Current ESMs operate at coarse spatial scales (50-100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks could improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.

Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

DOE PAGES

Mishra, U.; Riley, W. J.

2015-07-02

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing the heterogeneity of terrestrial hydrological and biogeochemical processes in Earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a data setmore » with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales ( s = 100, 200, and 500 m and 1, 2, 5, and 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions ( R 2 = 0.83–0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 m to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98 % of variability in the variance of SOC stocks. We found moderately accurate linear relationships between mean and higher-order moments of predicted SOC stocks ( R 2 ∼ 0.55–0.63). Current ESMs operate at coarse spatial scales (50–100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks could improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.« less

Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

DOE PAGES

Mishra, U.; Riley, W. J.

2015-01-01

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing heterogeneity of terrestrial hydrological and biogeochemical processes in earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a dataset with reasonablemore » fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales ( s = 100, 200, 500 m, 1, 2, 5, 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions ( R 2 = 0.83–0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98% of variability in the variance of SOC stocks. We found moderately-accurate linear relationships between mean and higher-order moments of predicted SOC stocks ( R 2 ~ 0.55–0.63). Current ESMs operate at coarse spatial scales (50–100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks can improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.« less

Assessing Seasonal and Inter-Annual Variations of Lake Surface Areas in Mongolia during 2000-2011 Using Minimum Composite MODIS NDVI

PubMed Central

Kang, Sinkyu; Hong, Suk Young

2016-01-01

A minimum composite method was applied to produce a 15-day interval normalized difference vegetation index (NDVI) dataset from Moderate Resolution Imaging Spectroradiometer (MODIS) daily 250 m reflectance in the red and near-infrared bands. This dataset was applied to determine lake surface areas in Mongolia. A total of 73 lakes greater than 6.25 km2in area were selected, and 28 of these lakes were used to evaluate detection errors. The minimum composite NDVI showed a better detection performance on lake water pixels than did the official MODIS 16-day 250 m NDVI based on a maximum composite method. The overall lake area detection performance based on the 15-day minimum composite NDVI showed -2.5% error relative to the Landsat-derived lake area for the 28 evaluated lakes. The errors increased with increases in the perimeter-to-area ratio but decreased with lake size over 10 km2. The lake area decreased by -9.3% at an annual rate of -53.7 km2 yr-1 during 2000 to 2011 for the 73 lakes. However, considerable spatial variations, such as slight-to-moderate lake area reductions in semi-arid regions and rapid lake area reductions in arid regions, were also detected. This study demonstrated applicability of MODIS 250 m reflectance data for biweekly monitoring of lake area change and diagnosed considerable lake area reduction and its spatial variability in arid and semi-arid regions of Mongolia. Future studies are required for explaining reasons of lake area changes and their spatial variability. PMID:27007233

Assessing Seasonal and Inter-Annual Variations of Lake Surface Areas in Mongolia during 2000-2011 Using Minimum Composite MODIS NDVI.

PubMed

Kang, Sinkyu; Hong, Suk Young

2016-01-01

A minimum composite method was applied to produce a 15-day interval normalized difference vegetation index (NDVI) dataset from Moderate Resolution Imaging Spectroradiometer (MODIS) daily 250 m reflectance in the red and near-infrared bands. This dataset was applied to determine lake surface areas in Mongolia. A total of 73 lakes greater than 6.25 km2in area were selected, and 28 of these lakes were used to evaluate detection errors. The minimum composite NDVI showed a better detection performance on lake water pixels than did the official MODIS 16-day 250 m NDVI based on a maximum composite method. The overall lake area detection performance based on the 15-day minimum composite NDVI showed -2.5% error relative to the Landsat-derived lake area for the 28 evaluated lakes. The errors increased with increases in the perimeter-to-area ratio but decreased with lake size over 10 km(2). The lake area decreased by -9.3% at an annual rate of -53.7 km(2) yr(-1) during 2000 to 2011 for the 73 lakes. However, considerable spatial variations, such as slight-to-moderate lake area reductions in semi-arid regions and rapid lake area reductions in arid regions, were also detected. This study demonstrated applicability of MODIS 250 m reflectance data for biweekly monitoring of lake area change and diagnosed considerable lake area reduction and its spatial variability in arid and semi-arid regions of Mongolia. Future studies are required for explaining reasons of lake area changes and their spatial variability.

Scaling in two-fluid pinch-off

NASA Astrophysics Data System (ADS)

Pommer, Chris; Suryo, Ronald; Subramani, Hariprasad; Harris, Michael; Basaran, Osman

2009-11-01

Two-fluid pinch-off is encountered when drops or bubbles of one fluid are ejected from a nozzle into another fluid or when a compound jet breaks. While the breakup of a drop in a passive environment and that of a passive bubble in a liquid are well understood, the physics of pinch-off when both the inner and outer fluids are dynamically active is inadequately understood. In this talk, the breakup of a compound jet whose core and shell are both incompressible Newtonian fluids is analyzed computationally by a method of lines ALE algorithm which uses finite elements with elliptic mesh generation for spatial discretization and adaptive finite differences for time integration. Pinch-off dynamics are investigated well beyond the limit of experiments set by the wavelength of visible light and that of various algorithms used in the literature. Simulations show that the minimum neck radius r initially scales with time τ before breakup as &αcirc; where α varies over a certain range. However, depending on the values of the governing dimensionless groups, this initial scaling regime may be transitory and, closer to pinch-off, the dynamics may transition to a final asymptotic regime for which r ˜&βcirc;, where β!=α.

Assimilation of the seabird and ship drift data in the north-eastern sea of Japan into an operational ocean nowcast/forecast system

PubMed Central

Miyazawa, Yasumasa; Guo, Xinyu; Varlamov, Sergey M.; Miyama, Toru; Yoda, Ken; Sato, Katsufumi; Kano, Toshiyuki; Sato, Keiji

2015-01-01

At the present time, ocean current is being operationally monitored mainly by combined use of numerical ocean nowcast/forecast models and satellite remote sensing data. Improvement in the accuracy of the ocean current nowcast/forecast requires additional measurements with higher spatial and temporal resolution as expected from the current observation network. Here we show feasibility of assimilating high-resolution seabird and ship drift data into an operational ocean forecast system. Data assimilation of geostrophic current contained in the observed drift leads to refinement in the gyre mode events of the Tsugaru warm current in the north-eastern sea of Japan represented by the model. Fitting the observed drift to the model depends on ability of the drift representing geostrophic current compared to that representing directly wind driven components. A preferable horizontal scale of 50 km indicated for the seabird drift data assimilation implies their capability of capturing eddies with smaller horizontal scale than the minimum scale of 100 km resolved by the satellite altimetry. The present study actually demonstrates that transdisciplinary approaches combining bio-/ship- logging and numerical modeling could be effective for enhancement in monitoring the ocean current. PMID:26633309

Development of a gridded meteorological dataset over Java island, Indonesia 1985–2014

PubMed Central

Yanto; Livneh, Ben; Rajagopalan, Balaji

2017-01-01

We describe a gridded daily meteorology dataset consisting of precipitation, minimum and maximum temperature over Java Island, Indonesia at 0.125°×0.125° (~14 km) resolution spanning 30 years from 1985–2014. Importantly, this data set represents a marked improvement from existing gridded data sets over Java with higher spatial resolution, derived exclusively from ground-based observations unlike existing satellite or reanalysis-based products. Gap-infilling and gridding were performed via the Inverse Distance Weighting (IDW) interpolation method (radius, r, of 25 km and power of influence, α, of 3 as optimal parameters) restricted to only those stations including at least 3,650 days (~10 years) of valid data. We employed MSWEP and CHIRPS rainfall products in the cross-validation. It shows that the gridded rainfall presented here produces the most reasonable performance. Visual inspection reveals an increasing performance of gridded precipitation from grid, watershed to island scale. The data set, stored in a network common data form (NetCDF), is intended to support watershed-scale and island-scale studies of short-term and long-term climate, hydrology and ecology. PMID:28534871

Variation in soil carbon dioxide efflux at two spatial scales in a topographically complex boreal forest

USGS Publications Warehouse

Kelsey, Katharine C.; Wickland, Kimberly P.; Striegl, Robert G.; Neff, Jason C.

2012-01-01

Carbon dynamics of high-latitude regions are an important and highly uncertain component of global carbon budgets, and efforts to constrain estimates of soil-atmosphere carbon exchange in these regions are contingent on accurate representations of spatial and temporal variability in carbon fluxes. This study explores spatial and temporal variability in soilatmosphere carbon dynamics at both fine and coarse spatial scales in a high-elevation, permafrost-dominated boreal black spruce forest. We evaluate the importance of landscape-level investigations of soil-atmosphere carbon dynamics by characterizing seasonal trends in soil-atmosphere carbon exchange, describing soil temperature-moisture-respiration relations, and quantifying temporal and spatial variability at two spatial scales: the plot scale (0–5 m) and the landscape scale (500–1000 m). Plot-scale spatial variability (average variation on a given measurement day) in soil CO2 efflux ranged from a coefficient of variation (CV) of 0.25 to 0.69, and plot-scale temporal variability (average variation of plots across measurement days) in efflux ranged from a CV of 0.19 to 0.36. Landscape-scale spatial and temporal variability in efflux was represented by a CV of 0.40 and 0.31, respectively, indicating that plot-scale spatial variability in soil respiration is as great as landscape-scale spatial variability at this site. While soil respiration was related to soil temperature at both the plot- and landscape scale, landscape-level descriptions of soil moisture were necessary to define soil respiration-moisture relations. Soil moisture variability was also integral to explaining temporal variability in soil respiration. Our results have important implications for research efforts in high-latitude regions where remote study sites make landscape-scale field campaigns challenging.

Cost-effective sampling of (137)Cs-derived net soil redistribution: part 2 - estimating the spatial mean change over time.

PubMed

Chappell, A; Li, Y; Yu, H Q; Zhang, Y Z; Li, X Y

2015-06-01

The caesium-137 ((137)Cs) technique for estimating net, time-integrated soil redistribution by the processes of wind, water and tillage is increasingly being used with repeated sampling to form a baseline to evaluate change over small (years to decades) timeframes. This interest stems from knowledge that since the 1950s soil redistribution has responded dynamically to different phases of land use change and management. Currently, there is no standard approach to detect change in (137)Cs-derived net soil redistribution and thereby identify the driving forces responsible for change. We outline recent advances in space-time sampling in the soil monitoring literature which provide a rigorous statistical and pragmatic approach to estimating the change over time in the spatial mean of environmental properties. We apply the space-time sampling framework, estimate the minimum detectable change of net soil redistribution and consider the information content and cost implications of different sampling designs for a study area in the Chinese Loess Plateau. Three phases (1954-1996, 1954-2012 and 1996-2012) of net soil erosion were detectable and attributed to well-documented historical change in land use and management practices in the study area and across the region. We recommend that the design for space-time sampling is considered carefully alongside cost-effective use of the spatial mean to detect and correctly attribute cause of change over time particularly across spatial scales of variation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Monitoring meteorological spatial variability in viticulture using a low-cost Wireless Sensor Network

NASA Astrophysics Data System (ADS)

Matese, Alessandro; Crisci, Alfonso; Di Gennaro, Filippo; Primicerio, Jacopo; Tomasi, Diego; Guidoni, Silvia

2014-05-01

In a long-term perspective, the current global agricultural scenario will be characterize by critical issues in terms of water resource management and environmental protection. The concept of sustainable agriculture would become crucial at reducing waste, optimizing the use of pesticides and fertilizers to crops real needs. This can be achieved through a minimum-scale monitoring of the crop physiologic status and the environmental parameters that characterize the microclimate. Viticulture is often subject to high variability within the same vineyard, thus becomes important to monitor this heterogeneity to allow a site-specific management and maximize the sustainability and quality of production. Meteorological variability expressed both at vineyard scale (mesoclimate) and at single plant level (microclimate) plays an important role during the grape ripening process. The aim of this work was to compare temperature, humidity and solar radiation measurements at different spatial scales. The measurements were assessed for two seasons (2011, 2012) in two vineyards of the Veneto region (North-East Italy), planted with Pinot gris and Cabernet Sauvignon using a specially designed and developed Wireless Sensor Network (WSN). The WSN consists of various levels: the Master/Gateway level coordinates the WSN and performs data aggregation; the Farm/Server level takes care of storing data on a server, data processing and graphic rendering. Nodes level is based on a network of peripheral nodes consisting of a sensor board equipped with sensors and wireless module. The system was able to monitor the agrometeorological parameters in the vineyard: solar radiation, air temperature and air humidity. Different sources of spatial variation were studied, from meso-scale to micro-scale. A widespread investigation was conducted, building a factorial design able to evidence the role played by any factor influencing the physical environment in the vineyard, such as the surrounding climate effect, canopy management and relative position inside the vineyard. The results highlighted that the impact of agrometeorological parameters variability is predominantly determined by differences between within-field and external-field. These results may provide support for the composition of crop production and disease model simulations where data are usually taken from an agrometeorological station not representative of actual field conditions. Finally, the WSN performances, in terms of monitoring and reliability of the system, have been evaluated considering: its handiness, cost-effective, non-invasive dimensions and low power.

Predicting habitat suitability for rare plants at local spatial scales using a species distribution model.

PubMed

Gogol-Prokurat, Melanie

2011-01-01

If species distribution models (SDMs) can rank habitat suitability at a local scale, they may be a valuable conservation planning tool for rare, patchily distributed species. This study assessed the ability of Maxent, an SDM reported to be appropriate for modeling rare species, to rank habitat suitability at a local scale for four edaphic endemic rare plants of gabbroic soils in El Dorado County, California, and examined the effects of grain size, spatial extent, and fine-grain environmental predictors on local-scale model accuracy. Models were developed using species occurrence data mapped on public lands and were evaluated using an independent data set of presence and absence locations on surrounding lands, mimicking a typical conservation-planning scenario that prioritizes potential habitat on unsurveyed lands surrounding known occurrences. Maxent produced models that were successful at discriminating between suitable and unsuitable habitat at the local scale for all four species, and predicted habitat suitability values were proportional to likelihood of occurrence or population abundance for three of four species. Unfortunately, models with the best discrimination (i.e., AUC) were not always the most useful for ranking habitat suitability. The use of independent test data showed metrics that were valuable for evaluating which variables and model choices (e.g., grain, extent) to use in guiding habitat prioritization for conservation of these species. A goodness-of-fit test was used to determine whether habitat suitability values ranked habitat suitability on a continuous scale. If they did not, a minimum acceptable error predicted area criterion was used to determine the threshold for classifying habitat as suitable or unsuitable. I found a trade-off between model extent and the use of fine-grain environmental variables: goodness of fit was improved at larger extents, and fine-grain environmental variables improved local-scale accuracy, but fine-grain variables were not available at large extents. No single model met all habitat prioritization criteria, and the best models were overlaid to identify consensus areas of high suitability. Although the four species modeled here co-occur and are treated together for conservation planning, model accuracy and predicted suitable areas varied among species.

Practical implementation of Channelized Hotelling Observers: Effect of ROI size

PubMed Central

Yu, Lifeng; Leng, Shuai; McCollough, Cynthia H.

2017-01-01

Fundamental to the development and application of channelized Hotelling observer (CHO) models is the selection of the region of interest (ROI) to evaluate. For assessment of medical imaging systems, reducing the ROI size can be advantageous. Smaller ROIs enable a greater concentration of interrogable objects in a single phantom image, thereby providing more information from a set of images and reducing the overall image acquisition burden. Additionally, smaller ROIs may promote better assessment of clinical patient images as different patient anatomies present different ROI constraints. To this end, we investigated the minimum ROI size that does not compromise the performance of the CHO model. In this study, we evaluated both simulated images and phantom CT images to identify the minimum ROI size that resulted in an accurate figure of merit (FOM) of the CHO’s performance. More specifically, the minimum ROI size was evaluated as a function of the following: number of channels, spatial frequency and number of rotations of the Gabor filters, size and contrast of the object, and magnitude of the image noise. Results demonstrate that a minimum ROI size exists below which the CHO’s performance is grossly inaccurate. The minimum ROI size is shown to increase with number of channels and be dictated by truncation of lower frequency filters. We developed a model to estimate the minimum ROI size as a parameterized function of the number of orientations and spatial frequencies of the Gabor filters, providing a guide for investigators to appropriately select parameters for model observer studies. PMID:28943699

Getting the Big Picture: Development of Spatial Scaling Abilities

ERIC Educational Resources Information Center

Frick, Andrea; Newcombe, Nora S.

2012-01-01

Spatial scaling is an integral aspect of many spatial tasks that involve symbol-to-referent correspondences (e.g., map reading, drawing). In this study, we asked 3-6-year-olds and adults to locate objects in a two-dimensional spatial layout using information from a second spatial representation (map). We examined how scaling factor and reference…

Representation of vegetation by continental data sets derived from NOAA-AVHRR data

NASA Technical Reports Server (NTRS)

Justice, C. O.; Townshend, J. R. G.; Kalb, V. L.

1991-01-01

Images of the normalized difference vegetation index (NDVI) are examined with specific attention given to the effect of spatial scales on the understanding of surface phenomena. A scale variance analysis is conducted on NDVI annual and seasonal images of Africa taken from 1987 NOAA-AVHRR data at spatial scales ranging from 8-512 km. The scales at which spatial variation takes place are determined and the relative magnitude of the variations are considered. Substantial differences are demonstrated, notably an increase in spatial variation with coarsening spatial resolution. Different responses in scale variance as a function of spatial resolution are noted in an analysis of maximum value composites for February and September; the difference is most marked in areas with very seasonal vegetation. The spatial variation at different scales is attributed to different factors, and methods involving the averaging of areas of transition and surface heterogeneity can oversimplify surface conditions. The spatial characteristics and the temporal variability of areas should be considered to accurately apply satellite data to global models.

Quantitative three-dimensional dynamic imaging of structure and function of the cardiopulmonary and circulatory systems in all regions of the body

NASA Technical Reports Server (NTRS)

Sturm, R. E.; Ritman, E. L.; Wood, E. H.

1975-01-01

The background for, and design of a third generation, general purpose, all electronic spatial scanning system, the DSR is described. Its specified performance capabilities provide dynamic and stop action three dimensional spatial reconstructions of any portion of the body based on a minimum exposure time of 0.01 second for each 28 multiplanar 180 deg scanning set, a maximum scan repetition rate of sixty 28 multiplane scan sets per second, each scan set consisting of a maximum of 240 parallel cross sections of a minimum thickness of 0.9 mm, and encompassing a maximum cylindrical volume about 23 cm in length and up to 38 cm in diameter.

Dark gap solitons in exciton-polariton condensates in a periodic potential.

PubMed

Cheng, Szu-Cheng; Chen, Ting-Wei

2018-03-01

We show that dark spatial gap solitons can occur inside the band gap of an exciton-polariton condensate (EPC) in a one-dimensional periodic potential. The energy dispersions of an EPC loaded into a periodic potential show a band-gap structure. Using the effective-mass model of the complex Gross-Pitaevskii equation with pump and dissipation in an EPC in a periodic potential, dark gap solitons are demonstrated near the minimum energy points of the band center and band edge of the first and second bands, respectively. The excitation energies of dark gap solitons are below these minimum points and fall into the band gap. The spatial width of a dark gap soliton becomes smaller as the pump power is increased.

Dark gap solitons in exciton-polariton condensates in a periodic potential

NASA Astrophysics Data System (ADS)

Cheng, Szu-Cheng; Chen, Ting-Wei

2018-03-01

We show that dark spatial gap solitons can occur inside the band gap of an exciton-polariton condensate (EPC) in a one-dimensional periodic potential. The energy dispersions of an EPC loaded into a periodic potential show a band-gap structure. Using the effective-mass model of the complex Gross-Pitaevskii equation with pump and dissipation in an EPC in a periodic potential, dark gap solitons are demonstrated near the minimum energy points of the band center and band edge of the first and second bands, respectively. The excitation energies of dark gap solitons are below these minimum points and fall into the band gap. The spatial width of a dark gap soliton becomes smaller as the pump power is increased.

Communication scheme based on evolutionary spatial 2×2 games

NASA Astrophysics Data System (ADS)

Ziaukas, Pranas; Ragulskis, Tautvydas; Ragulskis, Minvydas

2014-06-01

A visual communication scheme based on evolutionary spatial 2×2 games is proposed in this paper. Self-organizing patterns induced by complex interactions between competing individuals are exploited for hiding and transmitting secret visual information. Properties of the proposed communication scheme are discussed in details. It is shown that the hiding capacity of the system (the minimum size of the detectable primitives and the minimum distance between two primitives) is sufficient for the effective transmission of digital dichotomous images. Also, it is demonstrated that the proposed communication scheme is resilient to time backwards, plain image attacks and is highly sensitive to perturbations of private and public keys. Several computational experiments are used to demonstrate the effectiveness of the proposed communication scheme.

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

Mishra, U.; Riley, W. J.

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing the heterogeneity of terrestrial hydrological and biogeochemical processes in Earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a data setmore » with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales ( s = 100, 200, and 500 m and 1, 2, 5, and 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions ( R 2 = 0.83–0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 m to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98 % of variability in the variance of SOC stocks. We found moderately accurate linear relationships between mean and higher-order moments of predicted SOC stocks ( R 2 ∼ 0.55–0.63). Current ESMs operate at coarse spatial scales (50–100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks could improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.« less

Relationship of scores on the Escapism Scale of the MMPI to escape from minimum security federal custody.

PubMed

White, R B

1979-04-01

Investigated the ability of the Escapism (Ec) scale of the MMPI to differentiate between escape and non-escape minimum security federal prisoners. At the .05 level there was no difference between the scores of the two groups on the Ec scale or on comparisons of other correctional data, age, and ethnic composition. It appears that the Ec scale alone or in combination with other data will be a poor predictor of escape. Also, the rate of escape was so low as to make accurate prediction from any criteria extremely unlikely.

The combined effects of exogenous and endogenous variability on the spatial distribution of ant communities in a forested ecosystem (Hymenoptera: Formicidae).

PubMed

Yitbarek, Senay; Vandermeer, John H; Allen, David

2011-10-01

Spatial patterns observed in ecosystems have traditionally been attributed to exogenous processes. Recently, ecologists have found that endogenous processes also have the potential to create spatial patterns. Yet, relatively few studies have attempted to examine the combined effects of exogenous and endogenous processes on the distribution of organisms across spatial and temporal scales. Here we aim to do this, by investigating whether spatial patterns of under-story tree species at a large spatial scale (18 ha) influences the spatial patterns of ground foraging ant species at a much smaller spatial scale (20 m by 20 m). At the regional scale, exogenous processes (under-story tree community) had a strong effect on the spatial patterns in the ground-foraging ant community. We found significantly more Camponotus noveboracensis, Formica subsericae, and Lasius alienus species in black cherry (Prunis serotine Ehrh.) habitats. In witch-hazel (Hamamelis virginiana L.) habitats, we similarly found significantly more Myrmica americana, Formica fusca, and Formica subsericae. At smaller spatial scales, we observed the emergence of mosaic ant patches changing rapidly in space and time. Our study reveals that spatial patterns are the result of both exogenous and endogenous forces, operating at distinct scales.

Spatial-temporal changes of maximum and minimum temperatures in the Wei River Basin, China: Changing patterns, causes and implications

NASA Astrophysics Data System (ADS)

Liu, Saiyan; Huang, Shengzhi; Xie, Yangyang; Huang, Qiang; Leng, Guoyong; Hou, Beibei; Zhang, Ying; Wei, Xiu

2018-05-01

Due to the important role of temperature in the global climate system and energy cycles, it is important to investigate the spatial-temporal change patterns, causes and implications of annual maximum (Tmax) and minimum (Tmin) temperatures. In this study, the Cloud model were adopted to fully and accurately analyze the changing patterns of annual Tmax and Tmin from 1958 to 2008 by quantifying their mean, uniformity, and stability in the Wei River Basin (WRB), a typical arid and semi-arid region in China. Additionally, the cross wavelet analysis was applied to explore the correlations among annual Tmax and Tmin and the yearly sunspots number, Arctic Oscillation, Pacific Decadal Oscillation, and soil moisture with an aim to determine possible causes of annual Tmax and Tmin variations. Furthermore, temperature-related impacts on vegetation cover and precipitation extremes were also examined. Results indicated that: (1) the WRB is characterized by increasing trends in annual Tmax and Tmin, with a more evident increasing trend in annual Tmin, which has a higher dispersion degree and is less uniform and stable than annual Tmax; (2) the asymmetric variations of Tmax and Tmin can be generally explained by the stronger effects of solar activity (primarily), large-scale atmospheric circulation patterns, and soil moisture on annual Tmin than on annual Tmax; and (3) increasing annual Tmax and Tmin have exerted strong influences on local precipitation extremes, in terms of their duration, intensity, and frequency in the WRB. This study presents new analyses of Tmax and Tmin in the WRB, and the findings may help guide regional agricultural production and water resources management.

The minimum or natural rate of flow and droplet size ejected by Taylor cone-jets: physical symmetries and scaling laws

NASA Astrophysics Data System (ADS)

Gañán-Calvo, A. M.; Rebollo-Muñoz, N.; Montanero, J. M.

2013-03-01

We aim to establish the scaling laws for both the minimum rate of flow attainable in the steady cone-jet mode of electrospray, and the size of the resulting droplets in that limit. Use is made of a small body of literature on Taylor cone-jets reporting precise measurements of the transported electric current and droplet size as a function of the liquid properties and flow rate. The projection of the data onto an appropriate non-dimensional parameter space maps a region bounded by the minimum rate of flow attainable in the steady state. To explain these experimental results, we propose a theoretical model based on the generalized concept of physical symmetry, stemming from the system time invariance (steadiness). A group of symmetries rising at the cone-to-jet geometrical transition determines the scaling for the minimum flow rate and related variables. If the flow rate is decreased below that minimum value, those symmetries break down, which leads to dripping. We find that the system exhibits two instability mechanisms depending on the nature of the forces arising against the flow: one dominated by viscosity and the other by the liquid polarity. In the former case, full charge relaxation is guaranteed down to the minimum flow rate, while in the latter the instability condition becomes equivalent to the symmetry breakdown by charge relaxation or separation. When cone-jets are formed without artificially imposing a flow rate, a microjet is issued quasi-steadily. The flow rate naturally ejected this way coincides with the minimum flow rate studied here. This natural flow rate determines the minimum droplet size that can be steadily produced by any electrohydrodynamic means for a given set of liquid properties.

Correlated patterns in hydrothermal plume distribution and apparent magmatic budget along 2500 km of the Southeast Indian Ridge

USGS Publications Warehouse

Baker, Edward; Christophe Hémond,; Anne Briais,; Marcia Maia,; Scheirer, Daniel S.; Sharon L. Walker,; Tingting Wang,; Yongshun John Chen,

2014-01-01

Multiple geological processes affect the distribution of hydrothermal venting along a mid-ocean ridge. Deciphering the role of a specific process is often frustrated by simultaneous changes in other influences. Here we take advantage of the almost constant spreading rate (65–71 mm/yr) along 2500 km of the Southeast Indian Ridge (SEIR) between 77°E and 99°E to examine the spatial density of hydrothermal venting relative to regional and segment-scale changes in the apparent magmatic budget. We use 227 vertical profiles of light backscatter and (on 41 profiles) oxidation-reduction potential along 27 first and second-order ridge segments on and adjacent to the Amsterdam-St. Paul (ASP) Plateau to map ph, the fraction of casts detecting a plume. At the regional scale, venting on the five segments crossing the magma-thickened hot spot plateau is almost entirely suppressed (ph = 0.02). Conversely, the combined ph (0.34) from all other segments follows the global trend of ph versus spreading rate. Off the ASP Plateau, multisegment trends in ph track trends in the regional axial depth, high where regional depth increases and low where it decreases. At the individual segment scale, a robust correlation between ph and cross-axis inflation for first-order segments shows that different magmatic budgets among first-order segments are expressed as different levels of hydrothermal spatial density. This correlation is absent among second-order segments. Eighty-five percent of the plumes occur in eight clusters totaling ∼350 km. We hypothesize that these clusters are a minimum estimate of the length of axial melt lenses underlying this section of the SEIR.

Correlated patterns in hydrothermal plume distribution and apparent magmatic budget along 2500 km of the Southeast Indian Ridge

NASA Astrophysics Data System (ADS)

Baker, Edward T.; Hémond, Christophe; Briais, Anne; Maia, Marcia; Scheirer, Daniel S.; Walker, Sharon L.; Wang, Tingting; Chen, Yongshun John

2014-08-01

Multiple geological processes affect the distribution of hydrothermal venting along a mid-ocean ridge. Deciphering the role of a specific process is often frustrated by simultaneous changes in other influences. Here we take advantage of the almost constant spreading rate (65-71 mm/yr) along 2500 km of the Southeast Indian Ridge (SEIR) between 77°E and 99°E to examine the spatial density of hydrothermal venting relative to regional and segment-scale changes in the apparent magmatic budget. We use 227 vertical profiles of light backscatter and (on 41 profiles) oxidation-reduction potential along 27 first and second-order ridge segments on and adjacent to the Amsterdam-St. Paul (ASP) Plateau to map ph, the fraction of casts detecting a plume. At the regional scale, venting on the five segments crossing the magma-thickened hot spot plateau is almost entirely suppressed (ph = 0.02). Conversely, the combined ph (0.34) from all other segments follows the global trend of ph versus spreading rate. Off the ASP Plateau, multisegment trends in ph track trends in the regional axial depth, high where regional depth increases and low where it decreases. At the individual segment scale, a robust correlation between ph and cross-axis inflation for first-order segments shows that different magmatic budgets among first-order segments are expressed as different levels of hydrothermal spatial density. This correlation is absent among second-order segments. Eighty-five percent of the plumes occur in eight clusters totaling ˜350 km. We hypothesize that these clusters are a minimum estimate of the length of axial melt lenses underlying this section of the SEIR.

A minimum entropy principle in the gas dynamics equations

NASA Technical Reports Server (NTRS)

Tadmor, E.

1986-01-01

Let u(x bar,t) be a weak solution of the Euler equations, governing the inviscid polytropic gas dynamics; in addition, u(x bar, t) is assumed to respect the usual entropy conditions connected with the conservative Euler equations. We show that such entropy solutions of the gas dynamics equations satisfy a minimum entropy principle, namely, that the spatial minimum of their specific entropy, (Ess inf s(u(x,t)))/x, is an increasing function of time. This principle equally applies to discrete approximations of the Euler equations such as the Godunov-type and Lax-Friedrichs schemes. Our derivation of this minimum principle makes use of the fact that there is a family of generalized entrophy functions connected with the conservative Euler equations.

An Extended Spectral-Spatial Classification Approach for Hyperspectral Data

NASA Astrophysics Data System (ADS)

Akbari, D.

2017-11-01

In this paper an extended classification approach for hyperspectral imagery based on both spectral and spatial information is proposed. The spatial information is obtained by an enhanced marker-based minimum spanning forest (MSF) algorithm. Three different methods of dimension reduction are first used to obtain the subspace of hyperspectral data: (1) unsupervised feature extraction methods including principal component analysis (PCA), independent component analysis (ICA), and minimum noise fraction (MNF); (2) supervised feature extraction including decision boundary feature extraction (DBFE), discriminate analysis feature extraction (DAFE), and nonparametric weighted feature extraction (NWFE); (3) genetic algorithm (GA). The spectral features obtained are then fed into the enhanced marker-based MSF classification algorithm. In the enhanced MSF algorithm, the markers are extracted from the classification maps obtained by both SVM and watershed segmentation algorithm. To evaluate the proposed approach, the Pavia University hyperspectral data is tested. Experimental results show that the proposed approach using GA achieves an approximately 8 % overall accuracy higher than the original MSF-based algorithm.

Turbulent Transport in a Three-dimensional Solar Wind

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

Shiota, D.; Zank, G. P.; Adhikari, L.

2017-03-01

Turbulence in the solar wind can play essential roles in the heating of coronal and solar wind plasma and the acceleration of the solar wind and energetic particles. Turbulence sources are not well understood and thought to be partly enhanced by interaction with the large-scale inhomogeneity of the solar wind and the interplanetary magnetic field and/or transported from the solar corona. To investigate the interaction with background inhomogeneity and the turbulence sources, we have developed a new 3D MHD model that includes the transport and dissipation of turbulence using the theoretical model of Zank et al. We solve for themore » temporal and spatial evolution of three moments or variables, the energy in the forward and backward fluctuating modes and the residual energy and their three corresponding correlation lengths. The transport model is coupled to our 3D model of the inhomogeneous solar wind. We present results of the coupled solar wind-turbulence model assuming a simple tilted dipole magnetic configuration that mimics solar minimum conditions, together with several comparative intermediate cases. By considering eight possible solar wind and turbulence source configurations, we show that the large-scale solar wind and IMF inhomogeneity and the strength of the turbulence sources significantly affect the distribution of turbulence in the heliosphere within 6 au. We compare the predicted turbulence distribution results from a complete solar minimum model with in situ measurements made by the Helios and Ulysses spacecraft, finding that the synthetic profiles of the turbulence intensities show reasonable agreement with observations.« less

Paleoceanographic insights on recent oxygen minimum zone expansion: lessons for modern oceanography.

PubMed

Moffitt, Sarah E; Moffitt, Russell A; Sauthoff, Wilson; Davis, Catherine V; Hewett, Kathryn; Hill, Tessa M

2015-01-01

Climate-driven Oxygen Minimum Zone (OMZ) expansions in the geologic record provide an opportunity to characterize the spatial and temporal scales of OMZ change. Here we investigate OMZ expansion through the global-scale warming event of the most recent deglaciation (18-11 ka), an event with clear relevance to understanding modern anthropogenic climate change. Deglacial marine sediment records were compiled to quantify the vertical extent, intensity, surface area and volume impingements of hypoxic waters upon continental margins. By integrating sediment records (183-2,309 meters below sea level; mbsl) containing one or more geochemical, sedimentary or microfossil oxygenation proxies integrated with analyses of eustatic sea level rise, we reconstruct the timing, depth and intensity of seafloor hypoxia. The maximum vertical OMZ extent during the deglaciation was variable by region: Subarctic Pacific (~600-2,900 mbsl), California Current (~330-1,500 mbsl), Mexico Margin (~330-830 mbsl), and the Humboldt Current and Equatorial Pacific (~110-3,100 mbsl). The timing of OMZ expansion is regionally coherent but not globally synchronous. Subarctic Pacific and California Current continental margins exhibit tight correlation to the oscillations of Northern Hemisphere deglacial events (Termination IA, Bølling-Allerød, Younger Dryas and Termination IB). Southern regions (Mexico Margin and the Equatorial Pacific and Humboldt Current) exhibit hypoxia expansion prior to Termination IA (~14.7 ka), and no regional oxygenation oscillations. Our analyses provide new evidence for the geographically and vertically extensive expansion of OMZs, and the extreme compression of upper-ocean oxygenated ecosystems during the geologically recent deglaciation.

Paleoceanographic Insights on Recent Oxygen Minimum Zone Expansion: Lessons for Modern Oceanography

PubMed Central

Moffitt, Sarah E.; Moffitt, Russell A.; Sauthoff, Wilson; Davis, Catherine V.; Hewett, Kathryn; Hill, Tessa M.

2015-01-01

Climate-driven Oxygen Minimum Zone (OMZ) expansions in the geologic record provide an opportunity to characterize the spatial and temporal scales of OMZ change. Here we investigate OMZ expansion through the global-scale warming event of the most recent deglaciation (18-11 ka), an event with clear relevance to understanding modern anthropogenic climate change. Deglacial marine sediment records were compiled to quantify the vertical extent, intensity, surface area and volume impingements of hypoxic waters upon continental margins. By integrating sediment records (183-2,309 meters below sea level; mbsl) containing one or more geochemical, sedimentary or microfossil oxygenation proxies integrated with analyses of eustatic sea level rise, we reconstruct the timing, depth and intensity of seafloor hypoxia. The maximum vertical OMZ extent during the deglaciation was variable by region: Subarctic Pacific (~600-2,900 mbsl), California Current (~330-1,500 mbsl), Mexico Margin (~330-830 mbsl), and the Humboldt Current and Equatorial Pacific (~110-3,100 mbsl). The timing of OMZ expansion is regionally coherent but not globally synchronous. Subarctic Pacific and California Current continental margins exhibit tight correlation to the oscillations of Northern Hemisphere deglacial events (Termination IA, Bølling-Allerød, Younger Dryas and Termination IB). Southern regions (Mexico Margin and the Equatorial Pacific and Humboldt Current) exhibit hypoxia expansion prior to Termination IA (~14.7 ka), and no regional oxygenation oscillations. Our analyses provide new evidence for the geographically and vertically extensive expansion of OMZs, and the extreme compression of upper-ocean oxygenated ecosystems during the geologically recent deglaciation. PMID:25629508

Perception of scale in forest management planning: Challenges and implications

Treesearch

Swee May Tang; Eric J. Gustafson

1997-01-01

Forest management practices imposed at one spatial scale may affect the patterns and processes of ecosystems at other scales. These impacts and feedbacks on the functioning of ecosystems across spatial scales are not well understood. We examined the effects of silvicultural manipulations simulated at two spatial scales of management planning on landscape pattern and...

[Estimation of the number of minimum salaries attributed to professions in function of their prestige].

PubMed

Sousa, F A; da Silva, J A

2000-04-01

The purpose of this study was to verify the relationship between professional prestige scaled through estimations and the professional prestige scaled through estimation of the number of minimum salaries attributed to professions in function of their prestige in society. Results showed: 1--the relationship between the estimation of magnitudes and the estimation of the number of minimum salaries attributed to the professions in function of their prestige is characterized by a function of potence with an exponent lower than 1,0,2--the orders of degrees of prestige of the professions resultant from different experiments involving different samples of subjects are highly concordant (W = 0.85; p < 0.001), considering the modality used as a number (estimation of magnitudes of minimum salaries).

Density dependence, spatial scale and patterning in sessile biota.

PubMed

Gascoigne, Joanna C; Beadman, Helen A; Saurel, Camille; Kaiser, Michel J

2005-09-01

Sessile biota can compete with or facilitate each other, and the interaction of facilitation and competition at different spatial scales is key to developing spatial patchiness and patterning. We examined density and scale dependence in a patterned, soft sediment mussel bed. We followed mussel growth and density at two spatial scales separated by four orders of magnitude. In summer, competition was important at both scales. In winter, there was net facilitation at the small scale with no evidence of density dependence at the large scale. The mechanism for facilitation is probably density dependent protection from wave dislodgement. Intraspecific interactions in soft sediment mussel beds thus vary both temporally and spatially. Our data support the idea that pattern formation in ecological systems arises from competition at large scales and facilitation at smaller scales, so far only shown in vegetation systems. The data, and a simple, heuristic model, also suggest that facilitative interactions in sessile biota are mediated by physical stress, and that interactions change in strength and sign along a spatial or temporal gradient of physical stress.

Quantifying spatial scaling patterns and their local and regional correlates in headwater streams: Implications for resilience

USGS Publications Warehouse

Gothe, Emma; Sandin, Leonard; Allen, Craig R.; Angeler, David G.

2014-01-01

The distribution of functional traits within and across spatiotemporal scales has been used to quantify and infer the relative resilience across ecosystems. We use explicit spatial modeling to evaluate within- and cross-scale redundancy in headwater streams, an ecosystem type with a hierarchical and dendritic network structure. We assessed the cross-scale distribution of functional feeding groups of benthic invertebrates in Swedish headwater streams during two seasons. We evaluated functional metrics, i.e., Shannon diversity, richness, and evenness, and the degree of redundancy within and across modeled spatial scales for individual feeding groups. We also estimated the correlates of environmental versus spatial factors of both functional composition and the taxonomic composition of functional groups for each spatial scale identified. Measures of functional diversity and within-scale redundancy of functions were similar during both seasons, but both within- and cross-scale redundancy were low. This apparent low redundancy was partly attributable to a few dominant taxa explaining the spatial models. However, rare taxa with stochastic spatial distributions might provide additional information and should therefore be considered explicitly for complementing future resilience assessments. Otherwise, resilience may be underestimated. Finally, both environmental and spatial factors correlated with the scale-specific functional and taxonomic composition. This finding suggests that resilience in stream networks emerges as a function of not only local conditions but also regional factors such as habitat connectivity and invertebrate dispersal.

A Spatial Framework to Map Heat Health Risks at Multiple Scales.

PubMed

Ho, Hung Chak; Knudby, Anders; Huang, Wei

2015-12-18

In the last few decades extreme heat events have led to substantial excess mortality, most dramatically in Central Europe in 2003, in Russia in 2010, and even in typically cool locations such as Vancouver, Canada, in 2009. Heat-related morbidity and mortality is expected to increase over the coming centuries as the result of climate-driven global increases in the severity and frequency of extreme heat events. Spatial information on heat exposure and population vulnerability may be combined to map the areas of highest risk and focus mitigation efforts there. However, a mismatch in spatial resolution between heat exposure and vulnerability data can cause spatial scale issues such as the Modifiable Areal Unit Problem (MAUP). We used a raster-based model to integrate heat exposure and vulnerability data in a multi-criteria decision analysis, and compared it to the traditional vector-based model. We then used the Getis-Ord G(i) index to generate spatially smoothed heat risk hotspot maps from fine to coarse spatial scales. The raster-based model allowed production of maps at spatial resolution, more description of local-scale heat risk variability, and identification of heat-risk areas not identified with the vector-based approach. Spatial smoothing with the Getis-Ord G(i) index produced heat risk hotspots from local to regional spatial scale. The approach is a framework for reducing spatial scale issues in future heat risk mapping, and for identifying heat risk hotspots at spatial scales ranging from the block-level to the municipality level.

Multiple regression and inverse moments improve the characterization of the spatial scaling behavior of daily streamflows in the Southeast United States

USGS Publications Warehouse

Farmer, William H.; Over, Thomas M.; Vogel, Richard M.

2015-01-01

Understanding the spatial structure of daily streamflow is essential for managing freshwater resources, especially in poorly-gaged regions. Spatial scaling assumptions are common in flood frequency prediction (e.g., index-flood method) and the prediction of continuous streamflow at ungaged sites (e.g. drainage-area ratio), with simple scaling by drainage area being the most common assumption. In this study, scaling analyses of daily streamflow from 173 streamgages in the southeastern US resulted in three important findings. First, the use of only positive integer moment orders, as has been done in most previous studies, captures only the probabilistic and spatial scaling behavior of flows above an exceedance probability near the median; negative moment orders (inverse moments) are needed for lower streamflows. Second, assessing scaling by using drainage area alone is shown to result in a high degree of omitted-variable bias, masking the true spatial scaling behavior. Multiple regression is shown to mitigate this bias, controlling for regional heterogeneity of basin attributes, especially those correlated with drainage area. Previous univariate scaling analyses have neglected the scaling of low-flow events and may have produced biased estimates of the spatial scaling exponent. Third, the multiple regression results show that mean flows scale with an exponent of one, low flows scale with spatial scaling exponents greater than one, and high flows scale with exponents less than one. The relationship between scaling exponents and exceedance probabilities may be a fundamental signature of regional streamflow. This signature may improve our understanding of the physical processes generating streamflow at different exceedance probabilities. 

The effect of minimum impact education on visitor spatial behavior in parks and protected areas: An experimental investigation using GPS-based tracking.

PubMed

Kidd, Abigail M; Monz, Christopher; D'Antonio, Ashley; Manning, Robert E; Reigner, Nathan; Goonan, Kelly A; Jacobi, Charles

2015-10-01

The unmanaged impacts of recreation and tourism can often result in unacceptable changes in resource conditions and quality of the visitor experience. Minimum impact visitor education programs aim to reduce the impacts of recreation by altering visitor behaviors. Specifically, education seeks to reduce impacts resulting from lack of knowledge both about the consequences of one's actions and impact-minimizing best practices. In this study, three different on-site minimum impact education strategies ("treatments") and a control condition were applied on the trails and summit area of Sargent Mountain in Acadia National Park, Maine. Treatment conditions were designed to encourage visitors to stay on marked trails and minimize off-trail travel. Treatments included a message delivered via personal contact, and both an ecological-based message and an amenity-based message posted on signs located alongside the trail. A control condition of current trail markings and directional signs was also assessed. The efficacy of the messaging was evaluated through the use of Global Positioning System (GPS) tracking of visitor spatial behavior on/off trails. Spatial analysis of GPS tracks revealed statistically significant differences among treatments, with the personal contact treatment yielding significantly less dispersion of visitors on the mountain summit. Results also indicate that the signs deployed in the study were ineffective at limiting off-trail use beyond what can be accomplished with trail markers and directional signs. These findings suggest that personal contact by a uniformed ranger or volunteer may be the most effective means of message delivery for on-site minimum impact education. Copyright © 2015 Elsevier Ltd. All rights reserved.

Using Mental Transformation Strategies for Spatial Scaling: Evidence from a Discrimination Task

ERIC Educational Resources Information Center

Möhring, Wenke; Newcombe, Nora S.; Frick, Andrea

2016-01-01

Spatial scaling, or an understanding of how distances in different-sized spaces relate to each other, is fundamental for many spatial tasks and relevant for success in numerous professions. Previous research has suggested that adults use mental transformation strategies to mentally scale spatial input, as indicated by linear increases in response…

Correlation Lengths for Estimating the Large-Scale Carbon and Heat Content of the Southern Ocean

NASA Astrophysics Data System (ADS)

Mazloff, M. R.; Cornuelle, B. D.; Gille, S. T.; Verdy, A.

2018-02-01

The spatial correlation scales of oceanic dissolved inorganic carbon, heat content, and carbon and heat exchanges with the atmosphere are estimated from a realistic numerical simulation of the Southern Ocean. Biases in the model are assessed by comparing the simulated sea surface height and temperature scales to those derived from optimally interpolated satellite measurements. While these products do not resolve all ocean scales, they are representative of the climate scale variability we aim to estimate. Results show that constraining the carbon and heat inventory between 35°S and 70°S on time-scales longer than 90 days requires approximately 100 optimally spaced measurement platforms: approximately one platform every 20° longitude by 6° latitude. Carbon flux has slightly longer zonal scales, and requires a coverage of approximately 30° by 6°. Heat flux has much longer scales, and thus a platform distribution of approximately 90° by 10° would be sufficient. Fluxes, however, have significant subseasonal variability. For all fields, and especially fluxes, sustained measurements in time are required to prevent aliasing of the eddy signals into the longer climate scale signals. Our results imply a minimum of 100 biogeochemical-Argo floats are required to monitor the Southern Ocean carbon and heat content and air-sea exchanges on time-scales longer than 90 days. However, an estimate of formal mapping error using the current Argo array implies that in practice even an array of 600 floats (a nominal float density of about 1 every 7° longitude by 3° latitude) will result in nonnegligible uncertainty in estimating climate signals.

Differential segregation in a cell-cell contact interface: the dynamics of the immunological synapse.

PubMed Central

Burroughs, Nigel John; Wülfing, Christoph

2002-01-01

Receptor-ligand couples in the cell-cell contact interface between a T cell and an antigen-presenting cell form distinct geometric patterns and undergo spatial rearrangement within the contact interface. Spatial segregation of the antigen and adhesion receptors occurs within seconds of contact, central aggregation of the antigen receptor then occurring over 1-5 min. This structure, called the immunological synapse, is becoming a paradigm for localized signaling. However, the mechanisms driving its formation, in particular spatial segregation, are currently not understood. With a reaction diffusion model incorporating thermodynamics, elasticity, and reaction kinetics, we examine the hypothesis that differing bond lengths (extracellular domain size) is the driving force behind molecular segregation. We derive two key conditions necessary for segregation: a thermodynamic criterion on the effective bond elasticity and a requirement for the seeding/nucleation of domains. Domains have a minimum length scale and will only spontaneously coalesce/aggregate if the contact area is small or the membrane relaxation distance large. Otherwise, differential attachment of receptors to the cytoskeleton is required for central aggregation. Our analysis indicates that differential bond lengths have a significant effect on synapse dynamics, i.e., there is a significant contribution to the free energy of the interaction, suggesting that segregation by differential bond length is important in cell-cell contact interfaces and the immunological synapse. PMID:12324401

The benefits of GIS to land use planning

NASA Astrophysics Data System (ADS)

Strielko, Irina; Pereira, Paulo

2014-05-01

The development of information technologies has significantly changed the approach to land use and spatial planning, management of natural resources. GIS considerably simplifies territorial planning operating analyzing necessary data concerning their spatial relationship that allows carrying out complex assessment of the situation and creates a basis for adoption of more exact and scientifically reasonable decisions in the course of land use. To assess the current land use situation and the possibility of modeling possible future changes associated with complex of adopted measures GIS allows the integration of diverse spatial data, for example, data about soils, climate, vegetation, and other and also to visualize available information in the form of maps, graphs or charts, 3D models. For the purposes of land use GIS allow using data of remote sensing, which allows to make monitoring of anthropogenic influence in a particular area and estimate scales and rates of degradation of green cover, flora and fauna. Assessment of land use can be made in complex or componentwise, indicating the test sites depending on the goals. GIS make it easy to model spatial distribution of various types of pollution of stationary and mobile sources in soil, atmosphere and the hydrological network. Based on results of the analysis made by GIS choose the optimal solutions of land use that provide the minimum impact on environment, make optimal decisions of conflict associated with land use and control of their using. One of the major advantages of using GIS is possibility of the complex analysis in concrete existential aspect. Analytical opportunities of GIS define conditionality of spatial distribution of objects and interrelation communication between them. For a variety of land management objectives analysis method is chosen based on the parameters of the problem and parameters of use of its results.

Mesoscale spatial variability of selected aquatic invertebrate community metrics from a minimally impaired stream segment

USGS Publications Warehouse

Gebler, J.B.

2004-01-01

The related topics of spatial variability of aquatic invertebrate community metrics, implications of spatial patterns of metric values to distributions of aquatic invertebrate communities, and ramifications of natural variability to the detection of human perturbations were investigated. Four metrics commonly used for stream assessment were computed for 9 stream reaches within a fairly homogeneous, minimally impaired stream segment of the San Pedro River, Arizona. Metric variability was assessed for differing sampling scenarios using simple permutation procedures. Spatial patterns of metric values suggest that aquatic invertebrate communities are patchily distributed on subsegment and segment scales, which causes metric variability. Wide ranges of metric values resulted in wide ranges of metric coefficients of variation (CVs) and minimum detectable differences (MDDs), and both CVs and MDDs often increased as sample size (number of reaches) increased, suggesting that any particular set of sampling reaches could yield misleading estimates of population parameters and effects that can be detected. Mean metric variabilities were substantial, with the result that only fairly large differences in metrics would be declared significant at ?? = 0.05 and ?? = 0.20. The number of reaches required to obtain MDDs of 10% and 20% varied with significance level and power, and differed for different metrics, but were generally large, ranging into tens and hundreds of reaches. Study results suggest that metric values from one or a small number of stream reach(es) may not be adequate to represent a stream segment, depending on effect sizes of interest, and that larger sample sizes are necessary to obtain reasonable estimates of metrics and sample statistics. For bioassessment to progress, spatial variability may need to be investigated in many systems and should be considered when designing studies and interpreting data.

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.

Multiscale Medical Image Fusion in Wavelet Domain

PubMed Central

Khare, Ashish

2013-01-01

Wavelet transforms have emerged as a powerful tool in image fusion. However, the study and analysis of medical image fusion is still a challenging area of research. Therefore, in this paper, we propose a multiscale fusion of multimodal medical images in wavelet domain. Fusion of medical images has been performed at multiple scales varying from minimum to maximum level using maximum selection rule which provides more flexibility and choice to select the relevant fused images. The experimental analysis of the proposed method has been performed with several sets of medical images. Fusion results have been evaluated subjectively and objectively with existing state-of-the-art fusion methods which include several pyramid- and wavelet-transform-based fusion methods and principal component analysis (PCA) fusion method. The comparative analysis of the fusion results has been performed with edge strength (Q), mutual information (MI), entropy (E), standard deviation (SD), blind structural similarity index metric (BSSIM), spatial frequency (SF), and average gradient (AG) metrics. The combined subjective and objective evaluations of the proposed fusion method at multiple scales showed the effectiveness and goodness of the proposed approach. PMID:24453868

Three-dimensional microarchitected materials and devices using nanoparticle assembly by pointwise spatial printing.

PubMed

Saleh, Mohammad Sadeq; Hu, Chunshan; Panat, Rahul

2017-03-01

Three-dimensional (3D) hierarchical materials are important to a wide range of emerging technological applications. We report a method to synthesize complex 3D microengineered materials, such as microlattices, with nearly fully dense truss elements with a minimum diameter of approximately 20 μm and having high aspect ratios (up to 20:1) without using any templating or supporting materials. By varying the postprocessing conditions, we have also introduced an additional control over the internal porosity of the truss elements to demonstrate a hierarchical porous structure with an overall void size and feature size control of over five orders of magnitudes in length scale. The method uses direct printing of nanoparticle dispersions using the Aerosol Jet technology in 3D space without templating or supporting materials followed by binder removal and sintering. In addition to 3D microlattices, we have also demonstrated directly printed stretchable interconnects, spirals, and pillars. This assembly method could be implemented by a variety of microdroplet generation methods for fast and large-scale fabrication of the hierarchical materials for applications in tissue engineering, ultralight or multifunctional materials, microfluidics, and micro-optoelectronics.

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

Li, Fuyu; Collins, William D.; Wehner, Michael F.

High-resolution climate models have been shown to improve the statistics of tropical storms and hurricanes compared to low-resolution models. The impact of increasing horizontal resolution in the tropical storm simulation is investigated exclusively using a series of Atmospheric Global Climate Model (AGCM) runs with idealized aquaplanet steady-state boundary conditions and a fixed operational storm-tracking algorithm. The results show that increasing horizontal resolution helps to detect more hurricanes, simulate stronger extreme rainfall, and emulate better storm structures in the models. However, increasing model resolution does not necessarily produce stronger hurricanes in terms of maximum wind speed, minimum sea level pressure, andmore » mean precipitation, as the increased number of storms simulated by high-resolution models is mainly associated with weaker storms. The spatial scale at which the analyses are conducted appears to have more important control on these meteorological statistics compared to horizontal resolution of the model grid. When the simulations are analyzed on common low-resolution grids, the statistics of the hurricanes, particularly the hurricane counts, show reduced sensitivity to the horizontal grid resolution and signs of scale invariant.« less

Three-dimensional cell to tissue assembly process

NASA Technical Reports Server (NTRS)

Wolf, David A. (Inventor); Schwarz, Ray P. (Inventor); Lewis, Marian L. (Inventor); Cross, John H. (Inventor); Huls, Mary H. (Inventor)

1992-01-01

The present invention relates a 3-dimensional cell to tissue and maintenance process, more particularly to methods of culturing cells in a culture environment, either in space or in a gravity field, with minimum fluid shear stress, freedom for 3-dimensional spatial orientation of the suspended particles and localization of particles with differing or similar sedimentation properties in a similar spatial region.

Reserve selection with minimum contiguous area restrictions: An application to open space protection planning in suburban Chicago

Treesearch

Sandor F. Toth; Robert Haight; Stephanie A. Snyder; Sonney George; James R. Miller; Mark S. Gregory; Adam M. Skibbe

2009-01-01

Conservation efforts often require site or parcel selection strategies that lead to spatially cohesive reserves. Although habitat contiguity is thought to be conducive to the persistence of many sensitive species, availability of funding and suitable land may restrict the extent to which this spatial attribute can be pursued in land management or conservation. Using...

Call sign intelligibility improvement using a spatial auditory display

NASA Technical Reports Server (NTRS)

Begault, Durand R.

1993-01-01

A spatial auditory display was used to convolve speech stimuli, consisting of 130 different call signs used in the communications protocol of NASA's John F. Kennedy Space Center, to different virtual auditory positions. An adaptive staircase method was used to determine intelligibility levels of the signal against diotic speech babble, with spatial positions at 30 deg azimuth increments. Non-individualized, minimum-phase approximations of head-related transfer functions were used. The results showed a maximal intelligibility improvement of about 6 dB when the signal was spatialized to 60 deg or 90 deg azimuth positions.

Understanding the spatial complexity of surface hoar from slope to range scale

NASA Astrophysics Data System (ADS)

Hendrikx, J.

2015-12-01

Surface hoar, once buried, is a common weak layer type in avalanche accidents in continental and intermountain snowpacks around the World. Despite this, there is still limited understanding of the spatial variability in both the formation of, and eventual burial of, surface hoar at spatial scales which are of critical importance to avalanche forecasters. While it is relatively well understood that aspect plays an important role in the spatial location of the formation, and burial of these grain forms, due to the unequal distribution of incoming radiation, this factor alone does not explain the complex and often confusing spatial pattern of these grains forms throughout the landscape at different spatial scales. In this paper we present additional data from a unique data set including over two hundred days of manual observations of surface hoar at sixteen locations on Pioneer Mountain at the Yellowstone Club in southwestern Montana. Using this wealth of observational data located on different aspects, elevations and exposures, coupled with detailed meteorological observations, and detailed slope scale observation, we examine the spatial variability of surface hoar at this scale, and examine the factors that control its spatial distribution. Our results further supports our preliminary work, which shows that small-scale slope conditions, meteorological differences, and local scale lapse rates, can greatly influence the spatial variability of surface hoar, over and above that which aspect alone can explain. These results highlight our incomplete understanding of the processes at both the slope and range scale, and are likely to have implications for both regional and local scale avalanche forecasting in environments where surface hoar cause ongoing instabilities.

Direct statistical modeling and its implications for predictive mapping in mining exploration

NASA Astrophysics Data System (ADS)

Sterligov, Boris; Gumiaux, Charles; Barbanson, Luc; Chen, Yan; Cassard, Daniel; Cherkasov, Sergey; Zolotaya, Ludmila

2010-05-01

Recent advances in geosciences make more and more multidisciplinary data available for mining exploration. This allowed developing methodologies for computing forecast ore maps from the statistical combination of such different input parameters, all based on an inverse problem theory. Numerous statistical methods (e.g. algebraic method, weight of evidence, Siris method, etc) with varying degrees of complexity in their development and implementation, have been proposed and/or adapted for ore geology purposes. In literature, such approaches are often presented through applications on natural examples and the results obtained can present specificities due to local characteristics. Moreover, though crucial for statistical computations, "minimum requirements" needed for input parameters (number of minimum data points, spatial distribution of objects, etc) are often only poorly expressed. From these, problems often arise when one has to choose between one and the other method for her/his specific question. In this study, a direct statistical modeling approach is developed in order to i) evaluate the constraints on the input parameters and ii) test the validity of different existing inversion methods. The approach particularly focused on the analysis of spatial relationships between location of points and various objects (e.g. polygons and /or polylines) which is particularly well adapted to constrain the influence of intrusive bodies - such as a granite - and faults or ductile shear-zones on spatial location of ore deposits (point objects). The method is designed in a way to insure a-dimensionality with respect to scale. In this approach, both spatial distribution and topology of objects (polygons and polylines) can be parametrized by the user (e.g. density of objects, length, surface, orientation, clustering). Then, the distance of points with respect to a given type of objects (polygons or polylines) is given using a probability distribution. The location of points is computed assuming either independency or different grades of dependency between the two probability distributions. The results show that i)polygons surface mean value, polylines length mean value, the number of objects and their clustering are critical and ii) the validity of the different tested inversion methods strongly depends on the relative importance and on the dependency between the parameters used. In addition, this combined approach of direct and inverse modeling offers an opportunity to test the robustness of the inferred distribution point laws with respect to the quality of the input data set.

Association between mild cognitive impairment and trajectory-based spatial parameters during timed up and go test using a laser range sensor.

PubMed

Nishiguchi, Shu; Yorozu, Ayanori; Adachi, Daiki; Takahashi, Masaki; Aoyama, Tomoki

2017-08-08

The Timed Up and Go (TUG) test may be a useful tool to detect not only mobility impairment but also possible cognitive impairment. In this cross-sectional study, we used the TUG test to investigate the associations between trajectory-based spatial parameters measured by laser range sensor (LRS) and cognitive impairment in community-dwelling older adults. The participants were 63 community-dwelling older adults (mean age, 73.0 ± 6.3 years). The trajectory-based spatial parameters during the TUG test were measured using an LRS. In each forward and backward phase, we calculated the minimum distance from the marker, the maximum distance from the x-axis (center line), the length of the trajectories, and the area of region surrounded by the trajectory of the center of gravity and the x-axis (center line). We measured mild cognitive impairment using the Mini-Mental State Examination score (26/27 was the cut-off score for defining mild cognitive impairment). Compared with participants with normal cognitive function, those with mild cognitive impairment exhibited the following trajectory-based spatial parameters: short minimum distance from the marker (p = 0.044), narrow area of center of gravity in the forward phase (p = 0.012), and a large forward/whole phase ratio of the area of the center of gravity (p = 0.026) during the TUG test. In multivariate logistic regression analyses, a short minimum distance from the marker (odds ratio [OR]: 0.82, 95% confidence interval [CI]: 0.69-0.98), narrow area of the center of gravity in the forward phase (OR: 0.01, 95% CI: 0.00-0.36), and large forward/whole phase ratio of the area of the center of gravity (OR: 0.94, 95% CI: 0.88-0.99) were independently associated with mild cognitive impairment. In conclusion, our results indicate that some of the trajectory-based spatial parameters measured by LRS during the TUG test were independently associated with cognitive impairment in older adults. In particular, older adults with cognitive impairment exhibit shorter minimum distances from the marker and asymmetrical trajectories during the TUG test.

Modular GIS Framework for National Scale Hydrologic and Hydraulic Modeling Support

NASA Astrophysics Data System (ADS)

Djokic, D.; Noman, N.; Kopp, S.

2015-12-01

Geographic information systems (GIS) have been extensively used for pre- and post-processing of hydrologic and hydraulic models at multiple scales. An extensible GIS-based framework was developed for characterization of drainage systems (stream networks, catchments, floodplain characteristics) and model integration. The framework is implemented as a set of free, open source, Python tools and builds on core ArcGIS functionality and uses geoprocessing capabilities to ensure extensibility. Utilization of COTS GIS core capabilities allows immediate use of model results in a variety of existing online applications and integration with other data sources and applications.The poster presents the use of this framework to downscale global hydrologic models to local hydraulic scale and post process the hydraulic modeling results and generate floodplains at any local resolution. Flow forecasts from ECMWF or WRF-Hydro are downscaled and combined with other ancillary data for input into the RAPID flood routing model. RAPID model results (stream flow along each reach) are ingested into a GIS-based scale dependent stream network database for efficient flow utilization and visualization over space and time. Once the flows are known at localized reaches, the tools can be used to derive the floodplain depth and extent for each time step in the forecast at any available local resolution. If existing rating curves are available they can be used to relate the flow to the depth of flooding, or synthetic rating curves can be derived using the tools in the toolkit and some ancillary data/assumptions. The results can be published as time-enabled spatial services to be consumed by web applications that use floodplain information as an input. Some of the existing online presentation templates can be easily combined with available online demographic and infrastructure data to present the impact of the potential floods on the local community through simple, end user products. This framework has been successfully used in both the data rich environments as well as in locales with minimum available spatial and hydrographic data.

Combining Livestock Production Information in a Process-Based Vegetation Model to Reconstruct the History of Grassland Management

NASA Technical Reports Server (NTRS)

Chang, Jinfeng; Ciais, Philippe; Herrero, Mario; Havlik, Petr; Campioli, Matteo; Zhang, Xianzhou; Bai, Yongfei; Viovy, Nicolas; Joiner, Joanna; Wang, Xuhui;

A variance-decomposition approach to investigating multiscale habitat associations

USGS Publications Warehouse

Lawler, J.J.; Edwards, T.C.

2006-01-01

The recognition of the importance of spatial scale in ecology has led many researchers to take multiscale approaches to studying habitat associations. However, few of the studies that investigate habitat associations at multiple spatial scales have considered the potential effects of cross-scale correlations in measured habitat variables. When cross-scale correlations in such studies are strong, conclusions drawn about the relative strength of habitat associations at different spatial scales may be inaccurate. Here we adapt and demonstrate an analytical technique based on variance decomposition for quantifying the influence of cross-scale correlations on multiscale habitat associations. We used the technique to quantify the variation in nest-site locations of Red-naped Sapsuckers (Sphyrapicus nuchalis) and Northern Flickers (Colaptes auratus) associated with habitat descriptors at three spatial scales. We demonstrate how the method can be used to identify components of variation that are associated only with factors at a single spatial scale as well as shared components of variation that represent cross-scale correlations. Despite the fact that no explanatory variables in our models were highly correlated (r < 0.60), we found that shared components of variation reflecting cross-scale correlations accounted for roughly half of the deviance explained by the models. These results highlight the importance of both conducting habitat analyses at multiple spatial scales and of quantifying the effects of cross-scale correlations in such analyses. Given the limits of conventional analytical techniques, we recommend alternative methods, such as the variance-decomposition technique demonstrated here, for analyzing habitat associations at multiple spatial scales. ?? The Cooper Ornithological Society 2006.

Accuracy of stream habitat interpolations across spatial scales

USGS Publications Warehouse

Sheehan, Kenneth R.; Welsh, Stuart A.

2013-01-01

Stream habitat data are often collected across spatial scales because relationships among habitat, species occurrence, and management plans are linked at multiple spatial scales. Unfortunately, scale is often a factor limiting insight gained from spatial analysis of stream habitat data. Considerable cost is often expended to collect data at several spatial scales to provide accurate evaluation of spatial relationships in streams. To address utility of single scale set of stream habitat data used at varying scales, we examined the influence that data scaling had on accuracy of natural neighbor predictions of depth, flow, and benthic substrate. To achieve this goal, we measured two streams at gridded resolution of 0.33 × 0.33 meter cell size over a combined area of 934 m2 to create a baseline for natural neighbor interpolated maps at 12 incremental scales ranging from a raster cell size of 0.11 m2 to 16 m2 . Analysis of predictive maps showed a logarithmic linear decay pattern in RMSE values in interpolation accuracy for variables as resolution of data used to interpolate study areas became coarser. Proportional accuracy of interpolated models (r2 ) decreased, but it was maintained up to 78% as interpolation scale moved from 0.11 m2 to 16 m2 . Results indicated that accuracy retention was suitable for assessment and management purposes at various scales different from the data collection scale. Our study is relevant to spatial modeling, fish habitat assessment, and stream habitat management because it highlights the potential of using a single dataset to fulfill analysis needs rather than investing considerable cost to develop several scaled datasets.

A Bayesian method for assessing multiscalespecies-habitat relationships

USGS Publications Warehouse

Stuber, Erica F.; Gruber, Lutz F.; Fontaine, Joseph J.

2017-01-01

ContextScientists face several theoretical and methodological challenges in appropriately describing fundamental wildlife-habitat relationships in models. The spatial scales of habitat relationships are often unknown, and are expected to follow a multi-scale hierarchy. Typical frequentist or information theoretic approaches often suffer under collinearity in multi-scale studies, fail to converge when models are complex or represent an intractable computational burden when candidate model sets are large.ObjectivesOur objective was to implement an automated, Bayesian method for inference on the spatial scales of habitat variables that best predict animal abundance.MethodsWe introduce Bayesian latent indicator scale selection (BLISS), a Bayesian method to select spatial scales of predictors using latent scale indicator variables that are estimated with reversible-jump Markov chain Monte Carlo sampling. BLISS does not suffer from collinearity, and substantially reduces computation time of studies. We present a simulation study to validate our method and apply our method to a case-study of land cover predictors for ring-necked pheasant (Phasianus colchicus) abundance in Nebraska, USA.ResultsOur method returns accurate descriptions of the explanatory power of multiple spatial scales, and unbiased and precise parameter estimates under commonly encountered data limitations including spatial scale autocorrelation, effect size, and sample size. BLISS outperforms commonly used model selection methods including stepwise and AIC, and reduces runtime by 90%.ConclusionsGiven the pervasiveness of scale-dependency in ecology, and the implications of mismatches between the scales of analyses and ecological processes, identifying the spatial scales over which species are integrating habitat information is an important step in understanding species-habitat relationships. BLISS is a widely applicable method for identifying important spatial scales, propagating scale uncertainty, and testing hypotheses of scaling relationships.

Acoustic and aerodynamic testing of a scale model variable pitch fan

NASA Technical Reports Server (NTRS)

Jutras, R. R.; Kazin, S. B.

1974-01-01

A fully reversible pitch scale model fan with variable pitch rotor blades was tested to determine its aerodynamic and acoustic characteristics. The single-stage fan has a design tip speed of 1160 ft/sec (353.568 m/sec) at a bypass pressure ratio of 1.5. Three operating lines were investigated. Test results show that the blade pitch for minimum noise also resulted in the highest efficiency for all three operating lines at all thrust levels. The minimum perceived noise on a 200-ft (60.96 m) sideline was obtained with the nominal nozzle. At 44% of takeoff thrust, the PNL reduction between blade pitch and minimum noise blade pitch is 1.8 PNdB for the nominal nozzle and decreases with increasing thrust. The small nozzle (6% undersized) has the highest efficiency at all part thrust conditions for the minimum noise blade pitch setting; although, the noise is about 1.0 PNdB higher for the small nozzle at the minimum noise blade pitch position.

Comparison of Spatial Correlation Parameters between Full and Model Scale Launch Vehicles

NASA Technical Reports Server (NTRS)

Kenny, Jeremy; Giacomoni, Clothilde

2016-01-01

The current vibro-acoustic analysis tools require specific spatial correlation parameters as input to define the liftoff acoustic environment experienced by the launch vehicle. Until recently these parameters have not been very well defined. A comprehensive set of spatial correlation data were obtained during a scale model acoustic test conducted in 2014. From these spatial correlation data, several parameters were calculated: the decay coefficient, the diffuse to propagating ratio, and the angle of incidence. Spatial correlation data were also collected on the EFT-1 flight of the Delta IV vehicle which launched on December 5th, 2014. A comparison of the spatial correlation parameters from full scale and model scale data will be presented.

Large scale patterns in vertical distribution and behaviour of mesopelagic scattering layers

NASA Astrophysics Data System (ADS)

Klevjer, T. A.; Irigoien, X.; Røstad, A.; Fraile-Nuez, E.; Benítez-Barrios, V. M.; Kaartvedt., S.

2016-01-01

Recent studies suggest that previous estimates of mesopelagic biomasses are severely biased, with the new, higher estimates underlining the need to unveil behaviourally mediated coupling between shallow and deep ocean habitats. We analysed vertical distribution and diel vertical migration (DVM) of mesopelagic acoustic scattering layers (SLs) recorded at 38 kHz across oceanographic regimes encountered during the circumglobal Malaspina expedition. Mesopelagic SLs were observed in all areas covered, but vertical distributions and DVM patterns varied markedly. The distribution of mesopelagic backscatter was deepest in the southern Indian Ocean (weighted mean daytime depth: WMD 590 m) and shallowest at the oxygen minimum zone in the eastern Pacific (WMD 350 m). DVM was evident in all areas covered, on average ~50% of mesopelagic backscatter made daily excursions from mesopelagic depths to shallow waters. There were marked differences in migrating proportions between the regions, ranging from ~20% in the Indian Ocean to ~90% in the Eastern Pacific. Overall the data suggest strong spatial gradients in mesopelagic DVM patterns, with implied ecological and biogeochemical consequences. Our results suggest that parts of this spatial variability can be explained by horizontal patterns in physical-chemical properties of water masses, such as oxygen, temperature and turbidity.

Large scale patterns in vertical distribution and behaviour of mesopelagic scattering layers.

PubMed

Klevjer, T A; Irigoien, X; Røstad, A; Fraile-Nuez, E; Benítez-Barrios, V M; Kaartvedt, S

2016-01-27

Recent studies suggest that previous estimates of mesopelagic biomasses are severely biased, with the new, higher estimates underlining the need to unveil behaviourally mediated coupling between shallow and deep ocean habitats. We analysed vertical distribution and diel vertical migration (DVM) of mesopelagic acoustic scattering layers (SLs) recorded at 38 kHz across oceanographic regimes encountered during the circumglobal Malaspina expedition. Mesopelagic SLs were observed in all areas covered, but vertical distributions and DVM patterns varied markedly. The distribution of mesopelagic backscatter was deepest in the southern Indian Ocean (weighted mean daytime depth: WMD 590 m) and shallowest at the oxygen minimum zone in the eastern Pacific (WMD 350 m). DVM was evident in all areas covered, on average ~50% of mesopelagic backscatter made daily excursions from mesopelagic depths to shallow waters. There were marked differences in migrating proportions between the regions, ranging from ~20% in the Indian Ocean to ~90% in the Eastern Pacific. Overall the data suggest strong spatial gradients in mesopelagic DVM patterns, with implied ecological and biogeochemical consequences. Our results suggest that parts of this spatial variability can be explained by horizontal patterns in physical-chemical properties of water masses, such as oxygen, temperature and turbidity.

Accuracy and uncertainty analysis of soil Bbf spatial distribution estimation at a coking plant-contaminated site based on normalization geostatistical technologies.

PubMed

Liu, Geng; Niu, Junjie; Zhang, Chao; Guo, Guanlin

2015-12-01

Data distribution is usually skewed severely by the presence of hot spots in contaminated sites. This causes difficulties for accurate geostatistical data transformation. Three types of typical normal distribution transformation methods termed the normal score, Johnson, and Box-Cox transformations were applied to compare the effects of spatial interpolation with normal distribution transformation data of benzo(b)fluoranthene in a large-scale coking plant-contaminated site in north China. Three normal transformation methods decreased the skewness and kurtosis of the benzo(b)fluoranthene, and all the transformed data passed the Kolmogorov-Smirnov test threshold. Cross validation showed that Johnson ordinary kriging has a minimum root-mean-square error of 1.17 and a mean error of 0.19, which was more accurate than the other two models. The area with fewer sampling points and that with high levels of contamination showed the largest prediction standard errors based on the Johnson ordinary kriging prediction map. We introduce an ideal normal transformation method prior to geostatistical estimation for severely skewed data, which enhances the reliability of risk estimation and improves the accuracy for determination of remediation boundaries.

A Clustering Algorithm for Ecological Stream Segment Identification from Spatially Extensive Digital Databases

NASA Astrophysics Data System (ADS)

Brenden, T. O.; Clark, R. D.; Wiley, M. J.; Seelbach, P. W.; Wang, L.

2005-05-01

Remote sensing and geographic information systems have made it possible to attribute variables for streams at increasingly detailed resolutions (e.g., individual river reaches). Nevertheless, management decisions still must be made at large scales because land and stream managers typically lack sufficient resources to manage on an individual reach basis. Managers thus require a method for identifying stream management units that are ecologically similar and that can be expected to respond similarly to management decisions. We have developed a spatially-constrained clustering algorithm that can merge neighboring river reaches with similar ecological characteristics into larger management units. The clustering algorithm is based on the Cluster Affinity Search Technique (CAST), which was developed for clustering gene expression data. Inputs to the clustering algorithm are the neighbor relationships of the reaches that comprise the digital river network, the ecological attributes of the reaches, and an affinity value, which identifies the minimum similarity for merging river reaches. In this presentation, we describe the clustering algorithm in greater detail and contrast its use with other methods (expert opinion, classification approach, regular clustering) for identifying management units using several Michigan watersheds as a backdrop.

Comparing the minimum spatial-frequency content for recognizing Chinese and alphabet characters

PubMed Central

Wang, Hui; Legge, Gordon E.

2018-01-01

Visual blur is a common problem that causes difficulty in pattern recognition for normally sighted people under degraded viewing conditions (e.g., near the acuity limit, when defocused, or in fog) and also for people with impaired vision. For reliable identification, the spatial frequency content of an object needs to extend up to or exceed a minimum value in units of cycles per object, referred to as the critical spatial frequency. In this study, we investigated the critical spatial frequency for alphabet and Chinese characters, and examined the effect of pattern complexity. The stimuli were divided into seven categories based on their perimetric complexity, including the lowercase and uppercase alphabet letters, and five groups of Chinese characters. We found that the critical spatial frequency significantly increased with complexity, from 1.01 cycles per character for the simplest group to 2.00 cycles per character for the most complex group of Chinese characters. A second goal of the study was to test a space-bandwidth invariance hypothesis that would represent a tradeoff between the critical spatial frequency and the number of adjacent patterns that can be recognized at one time. We tested this hypothesis by comparing the critical spatial frequencies in cycles per character from the current study and visual-span sizes in number of characters (measured by Wang, He, & Legge, 2014) for sets of characters with different complexities. For the character size (1.2°) we used in the study, we found an invariant product of approximately 10 cycles, which may represent a capacity limitation on visual pattern recognition. PMID:29297056

On the nonlinearity of spatial scales in extreme weather attribution statements

NASA Astrophysics Data System (ADS)

Angélil, Oliver; Stone, Daíthí; Perkins-Kirkpatrick, Sarah; Alexander, Lisa V.; Wehner, Michael; Shiogama, Hideo; Wolski, Piotr; Ciavarella, Andrew; Christidis, Nikolaos

2018-04-01

In the context of ongoing climate change, extreme weather events are drawing increasing attention from the public and news media. A question often asked is how the likelihood of extremes might have changed by anthropogenic greenhouse-gas emissions. Answers to the question are strongly influenced by the model used, duration, spatial extent, and geographic location of the event—some of these factors often overlooked. Using output from four global climate models, we provide attribution statements characterised by a change in probability of occurrence due to anthropogenic greenhouse-gas emissions, for rainfall and temperature extremes occurring at seven discretised spatial scales and three temporal scales. An understanding of the sensitivity of attribution statements to a range of spatial and temporal scales of extremes allows for the scaling of attribution statements, rendering them relevant to other extremes having similar but non-identical characteristics. This is a procedure simple enough to approximate timely estimates of the anthropogenic contribution to the event probability. Furthermore, since real extremes do not have well-defined physical borders, scaling can help quantify uncertainty around attribution results due to uncertainty around the event definition. Results suggest that the sensitivity of attribution statements to spatial scale is similar across models and that the sensitivity of attribution statements to the model used is often greater than the sensitivity to a doubling or halving of the spatial scale of the event. The use of a range of spatial scales allows us to identify a nonlinear relationship between the spatial scale of the event studied and the attribution statement.

On the nonlinearity of spatial scales in extreme weather attribution statements

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

Angélil, Oliver; Stone, Daíthí; Perkins-Kirkpatrick, Sarah

In the context of continuing climate change, extreme weather events are drawing increasing attention from the public and news media. A question often asked is how the likelihood of extremes might have changed by anthropogenic greenhouse-gas emissions. Answers to the question are strongly influenced by the model used, duration, spatial extent, and geographic location of the event—some of these factors often overlooked. Using output from four global climate models, we provide attribution statements characterised by a change in probability of occurrence due to anthropogenic greenhouse-gas emissions, for rainfall and temperature extremes occurring at seven discretised spatial scales and three temporalmore » scales. An understanding of the sensitivity of attribution statements to a range of spatial and temporal scales of extremes allows for the scaling of attribution statements, rendering them relevant to other extremes having similar but non-identical characteristics. This is a procedure simple enough to approximate timely estimates of the anthropogenic contribution to the event probability. Furthermore, since real extremes do not have well-defined physical borders, scaling can help quantify uncertainty around attribution results due to uncertainty around the event definition. Results suggest that the sensitivity of attribution statements to spatial scale is similar across models and that the sensitivity of attribution statements to the model used is often greater than the sensitivity to a doubling or halving of the spatial scale of the event. The use of a range of spatial scales allows us to identify a nonlinear relationship between the spatial scale of the event studied and the attribution statement.« less

On the nonlinearity of spatial scales in extreme weather attribution statements

DOE PAGES

Angélil, Oliver; Stone, Daíthí; Perkins-Kirkpatrick, Sarah; ...

2017-06-17

In the context of continuing climate change, extreme weather events are drawing increasing attention from the public and news media. A question often asked is how the likelihood of extremes might have changed by anthropogenic greenhouse-gas emissions. Answers to the question are strongly influenced by the model used, duration, spatial extent, and geographic location of the event—some of these factors often overlooked. Using output from four global climate models, we provide attribution statements characterised by a change in probability of occurrence due to anthropogenic greenhouse-gas emissions, for rainfall and temperature extremes occurring at seven discretised spatial scales and three temporalmore » scales. An understanding of the sensitivity of attribution statements to a range of spatial and temporal scales of extremes allows for the scaling of attribution statements, rendering them relevant to other extremes having similar but non-identical characteristics. This is a procedure simple enough to approximate timely estimates of the anthropogenic contribution to the event probability. Furthermore, since real extremes do not have well-defined physical borders, scaling can help quantify uncertainty around attribution results due to uncertainty around the event definition. Results suggest that the sensitivity of attribution statements to spatial scale is similar across models and that the sensitivity of attribution statements to the model used is often greater than the sensitivity to a doubling or halving of the spatial scale of the event. The use of a range of spatial scales allows us to identify a nonlinear relationship between the spatial scale of the event studied and the attribution statement.« less

Sensitivity of landscape metrics to changing scale of remote sensing data in spatial pattern analysis: effect, criticality and scaling.

NASA Astrophysics Data System (ADS)

Xu, C.; Zhao, S.; Zhao, B.

2017-12-01

Spatial heterogeneity is scale-dependent, that is, the quantification and representation of spatial pattern vary with the resolution and extent. Overwhelming practices focused on scale effect of landscape metrics, and predicable scaling relationships found among some of them are thought to be the most effective and precise way to quantify multi-scale characteristics. However, previous studies tended to consider a narrow range of scales, and few focused on the critical threshold of scaling function. Here we examine the scalograms of 38 widely-used landscape-level metrics in a more integral spectrum of grain size among 96 landscapes with various extent (i.e. from 25km2 up towards to 221 km2), which sampled randomly from NLCD product. Our goal is to explore the existence of scaling domain and whether the response of metrics to changing resolution would be influenced by spatial extent. Results clearly show the existence of scaling domain for 13 of them (Type II), while the behaviors of other 13 (Type I) exhibit simple scaling functions and the rest (Type III) demonstrate various forms like no obvious change or fluctuation across the integral spectrum of grain size. In addition, an invariant power law scaling relationship was found between critical resolution and spatial extent for metrics falling into Type II, as the critical resolution is proportional to Eρ (ρ is a constant, and E is the extent). All the scaling exponents (ρ) are positive, suggesting that the critical resolutions for these characteristics of landscape structure can be relaxed as the spatial extent expands. This agrees well with empirical perception that coarser grain size might be allowed for spatial data with larger extent. Furthermore, the parameters of scaling functions for metrics falling into Type I and Type II vary with spatial extent, and power law or logarithmic relationships could be identified between them for some metrics. Our finding support the existence of self-organized criticality for a hierarchically-structured landscape. Although the underlying mechanism driving the scaling relationship remains unclear, it could provide guidance toward general principles in spatial pattern analysis and on selecting the proper resolution to avoid the misrepresentation of spatial pattern and profound biases in further ecological progress research.

Scaling properties of the Arctic sea ice Deformation from Buoy Dispersion Analysis

NASA Astrophysics Data System (ADS)

Weiss, J.; Rampal, P.; Marsan, D.; Lindsay, R.; Stern, H.

2007-12-01

A temporal and spatial scaling analysis of Arctic sea ice deformation is performed over time scales from 3 hours to 3 months and over spatial scales from 300 m to 300 km. The deformation is derived from the dispersion of pairs of drifting buoys, using the IABP (International Arctic Buoy Program) buoy data sets. This study characterizes the deformation of a very large solid plate -the Arctic sea ice cover- stressed by heterogeneous forcing terms like winds and ocean currents. It shows that the sea ice deformation rate depends on the scales of observation following specific space and time scaling laws. These scaling properties share similarities with those observed for turbulent fluids, especially for the ocean and the atmosphere. However, in our case, the time scaling exponent depends on the spatial scale, and the spatial exponent on the temporal scale, which implies a time/space coupling. An analysis of the exponent values shows that Arctic sea ice deformation is very heterogeneous and intermittent whatever the scales, i.e. it cannot be considered as viscous-like, even at very large time and/or spatial scales. Instead, it suggests a deformation accommodated by a multi-scale fracturing/faulting processes.

Scaling properties of Arctic sea ice deformation in high-resolution viscous-plastic sea ice models and satellite observations

NASA Astrophysics Data System (ADS)

Hutter, Nils; Losch, Martin; Menemenlis, Dimitris

2017-04-01

Sea ice models with the traditional viscous-plastic (VP) rheology and very high grid resolution can resolve leads and deformation rates that are localised along Linear Kinematic Features (LKF). In a 1-km pan-Arctic sea ice-ocean simulation, the small scale sea-ice deformations in the Central Arctic are evaluated with a scaling analysis in relation to satellite observations of the Envisat Geophysical Processor System (EGPS). A new coupled scaling analysis for data on Eulerian grids determines the spatial and the temporal scaling as well as the coupling between temporal and spatial scales. The spatial scaling of the modelled sea ice deformation implies multi-fractality. The spatial scaling is also coupled to temporal scales and varies realistically by region and season. The agreement of the spatial scaling and its coupling to temporal scales with satellite observations and models with the modern elasto-brittle rheology challenges previous results with VP models at coarse resolution where no such scaling was found. The temporal scaling analysis, however, shows that the VP model does not fully resolve the intermittency of sea ice deformation that is observed in satellite data.

Multiscale spatial and small-scale temporal variation in the composition of Riverine fish communities.

PubMed

Growns, Ivor; Astles, Karen; Gehrke, Peter

2006-03-01

We studied the multiscale (sites, river reaches and rivers) and short-term temporal (monthly) variability in a freshwater fish assemblage. We found that small-scale spatial variation and short-term temporal variability significantly influenced fish community structure in the Macquarie and Namoi Rivers. However, larger scale spatial differences between rivers were the largest source of variation in the data. The interaction between temporal change and spatial variation in fish community structure, whilst statistically significant, was smaller than the variation between rivers. This suggests that although the fish communities within each river changed between sampling occasions, the underlying differences between rivers were maintained. In contrast, the strongest interaction between temporal and spatial effects occurred at the smallest spatial scale, at the level of individual sites. This means whilst the composition of the fish assemblage at a given site may fluctuate, the magnitude of these changes is unlikely to affect larger scale differences between reaches within rivers or between rivers. These results suggest that sampling at any time within a single season will be sufficient to show spatial differences that occur over large spatial scales, such as comparisons between rivers or between biogeographical regions.

Identification of the key ecological factors influencing vegetation degradation in semi-arid agro-pastoral ecotone considering spatial scales

NASA Astrophysics Data System (ADS)

Peng, Yu; Wang, Qinghui; Fan, Min

2017-11-01

When assessing re-vegetation project performance and optimizing land management, identification of the key ecological factors inducing vegetation degradation has crucial implications. Rainfall, temperature, elevation, slope, aspect, land use type, and human disturbance are ecological factors affecting the status of vegetation index. However, at different spatial scales, the key factors may vary. Using Helin County, Inner-Mongolia, China as the study site and combining remote sensing image interpretation, field surveying, and mathematical methods, this study assesses key ecological factors affecting vegetation degradation under different spatial scales in a semi-arid agro-pastoral ecotone. It indicates that the key factors are different at various spatial scales. Elevation, rainfall, and temperature are identified as crucial for all spatial extents. Elevation, rainfall and human disturbance are key factors for small-scale quadrats of 300 m × 300 m and 600 m × 600 m, temperature and land use type are key factors for a medium-scale quadrat of 1 km × 1 km, and rainfall, temperature, and land use are key factors for large-scale quadrats of 2 km × 2 km and 5 km × 5 km. For this region, human disturbance is not the key factor for vegetation degradation across spatial scales. It is necessary to consider spatial scale for the identification of key factors determining vegetation characteristics. The eco-restoration programs at various spatial scales should identify key influencing factors according their scales so as to take effective measurements. The new understanding obtained in this study may help to explore the forces which driving vegetation degradation in the degraded regions in the world.

Satellite measurements reveal strong anisotropy in spatial coherence of climate variations over the Tibet Plateau.

PubMed

Chen, Deliang; Tian, Yudong; Yao, Tandong; Ou, Tinghai

2016-08-24

This study uses high-resolution, long-term satellite observations to evaluate the spatial scales of the climate variations across the Tibet Plateau (TP). Both land surface temperature and precipitation observations of more than 10 years were analysed with a special attention to eight existing ice-core sites in the TP. The temporal correlation for the monthly or annual anomalies between any two points decreases exponentially with their spatial distance, and we used the e-folding decay constant to quantify the spatial scales. We found that the spatial scales are strongly direction-dependent, with distinctive patterns in the west-east and south-north orientations, for example. Meanwhile, in the same directions the scales are largely symmetric backward and forward. Focusing on the west-east and south-north directions, we found the spatial coherence in the first is generally stronger than in the second. The annual surface temperature had typical spatial scales of 302-480 km, while the annual precipitation showed smaller scales of 111-182 km. The majority of the eight ice-core sites exhibit scales much smaller than the typical scales over the TP as a whole. These results provide important observational basis for the selection of appropriate downscaling strategies, deployment of climate-data collection networks, and interpreting paleoclimate reconstructions.

Satellite measurements reveal strong anisotropy in spatial coherence of climate variations over the Tibet Plateau

NASA Astrophysics Data System (ADS)

Chen, Deliang; Tian, Yudong; Yao, Tandong; Ou, Tinghai

2016-08-01

This study uses high-resolution, long-term satellite observations to evaluate the spatial scales of the climate variations across the Tibet Plateau (TP). Both land surface temperature and precipitation observations of more than 10 years were analysed with a special attention to eight existing ice-core sites in the TP. The temporal correlation for the monthly or annual anomalies between any two points decreases exponentially with their spatial distance, and we used the e-folding decay constant to quantify the spatial scales. We found that the spatial scales are strongly direction-dependent, with distinctive patterns in the west-east and south-north orientations, for example. Meanwhile, in the same directions the scales are largely symmetric backward and forward. Focusing on the west-east and south-north directions, we found the spatial coherence in the first is generally stronger than in the second. The annual surface temperature had typical spatial scales of 302-480 km, while the annual precipitation showed smaller scales of 111-182 km. The majority of the eight ice-core sites exhibit scales much smaller than the typical scales over the TP as a whole. These results provide important observational basis for the selection of appropriate downscaling strategies, deployment of climate-data collection networks, and interpreting paleoclimate reconstructions.

Satellite measurements reveal strong anisotropy in spatial coherence of climate variations over the Tibet Plateau

PubMed Central

Chen, Deliang; Tian, Yudong; Yao, Tandong; Ou, Tinghai

2016-01-01

This study uses high-resolution, long-term satellite observations to evaluate the spatial scales of the climate variations across the Tibet Plateau (TP). Both land surface temperature and precipitation observations of more than 10 years were analysed with a special attention to eight existing ice-core sites in the TP. The temporal correlation for the monthly or annual anomalies between any two points decreases exponentially with their spatial distance, and we used the e-folding decay constant to quantify the spatial scales. We found that the spatial scales are strongly direction-dependent, with distinctive patterns in the west-east and south-north orientations, for example. Meanwhile, in the same directions the scales are largely symmetric backward and forward. Focusing on the west-east and south-north directions, we found the spatial coherence in the first is generally stronger than in the second. The annual surface temperature had typical spatial scales of 302–480 km, while the annual precipitation showed smaller scales of 111–182 km. The majority of the eight ice-core sites exhibit scales much smaller than the typical scales over the TP as a whole. These results provide important observational basis for the selection of appropriate downscaling strategies, deployment of climate-data collection networks, and interpreting paleoclimate reconstructions. PMID:27553388

Patterns and scaling properties of surface soil moisture in an agricultural landscape: An ecohydrological modeling study

NASA Astrophysics Data System (ADS)

Korres, W.; Reichenau, T. G.; Schneider, K.

2013-08-01

Soil moisture is a key variable in hydrology, meteorology and agriculture. Soil moisture, and surface soil moisture in particular, is highly variable in space and time. Its spatial and temporal patterns in agricultural landscapes are affected by multiple natural (precipitation, soil, topography, etc.) and agro-economic (soil management, fertilization, etc.) factors, making it difficult to identify unequivocal cause and effect relationships between soil moisture and its driving variables. The goal of this study is to characterize and analyze the spatial and temporal patterns of surface soil moisture (top 20 cm) in an intensively used agricultural landscape (1100 km2 northern part of the Rur catchment, Western Germany) and to determine the dominant factors and underlying processes controlling these patterns. A second goal is to analyze the scaling behavior of surface soil moisture patterns in order to investigate how spatial scale affects spatial patterns. To achieve these goals, a dynamically coupled, process-based and spatially distributed ecohydrological model was used to analyze the key processes as well as their interactions and feedbacks. The model was validated for two growing seasons for the three main crops in the investigation area: Winter wheat, sugar beet, and maize. This yielded RMSE values for surface soil moisture between 1.8 and 7.8 vol.% and average RMSE values for all three crops of 0.27 kg m-2 for total aboveground biomass and 0.93 for green LAI. Large deviations of measured and modeled soil moisture can be explained by a change of the infiltration properties towards the end of the growing season, especially in maize fields. The validated model was used to generate daily surface soil moisture maps, serving as a basis for an autocorrelation analysis of spatial patterns and scale. Outside of the growing season, surface soil moisture patterns at all spatial scales depend mainly upon soil properties. Within the main growing season, larger scale patterns that are induced by soil properties are superimposed by the small scale land use pattern and the resulting small scale variability of evapotranspiration. However, this influence decreases at larger spatial scales. Most precipitation events cause temporarily higher surface soil moisture autocorrelation lengths at all spatial scales for a short time even beyond the autocorrelation lengths induced by soil properties. The relation of daily spatial variance to the spatial scale of the analysis fits a power law scaling function, with negative values of the scaling exponent, indicating a decrease in spatial variability with increasing spatial resolution. High evapotranspiration rates cause an increase in the small scale soil moisture variability, thus leading to large negative values of the scaling exponent. Utilizing a multiple regression analysis, we found that 53% of the variance of the scaling exponent can be explained by a combination of an independent LAI parameter and the antecedent precipitation.

Predicting probability of occurrence and factors affecting distribution and abundance of three Ozark endemic crayfish species at multiple spatial scales

USGS Publications Warehouse

Nolen, Matthew S.; Magoulick, Daniel D.; DiStefano, Robert J.; Imhoff, Emily M.; Wagner, Brian K.

2014-01-01

We found that a range of environmental variables were important in predicting crayfish distribution and abundance at multiple spatial scales and their importance was species-, response variable- and scale dependent. We would encourage others to examine the influence of spatial scale on species distribution and abundance patterns.

Impact of scale on morphological spatial pattern of forest

Treesearch

Katarzyna Ostapowicz; Peter Vogt; Kurt H. Riitters; Jacek Kozak; Christine Estreguil

2008-01-01

Assessing and monitoring landscape pattern structure from multi-scale land-cover maps can utilize morphological spatial pattern analysis (MSPA), only if various influences of scale are known and taken into account. This paper lays part of the foundation for applying MSPA analysis in landscape monitoring by quantifying scale effects on six classes of spatial patterns...

Metacommunity versus Biogeography: A Case Study of Two Groups of Neotropical Vegetation-Dwelling Arthropods

PubMed Central

Gonçalves-Souza, Thiago; Romero, Gustavo Q.; Cottenie, Karl

2014-01-01

Biogeography and metacommunity ecology provide two different perspectives on species diversity. Both are spatial in nature but their spatial scales do not necessarily match. With recent boom of metacommunity studies, we see an increasing need for clear discrimination of spatial scales relevant for both perspectives. This discrimination is a necessary prerequisite for improved understanding of ecological phenomena across scales. Here we provide a case study to illustrate some spatial scale-dependent concepts in recent metacommunity studies and identify potential pitfalls. We presented here the diversity patterns of Neotropical lepidopterans and spiders viewed both from metacommunity and biogeographical perspectives. Specifically, we investigated how the relative importance of niche- and dispersal-based processes for community assembly change at two spatial scales: metacommunity scale, i.e. within a locality, and biogeographical scale, i.e. among localities widely scattered along a macroclimatic gradient. As expected, niche-based processes dominated the community assembly at metacommunity scale, while dispersal-based processes played a major role at biogeographical scale for both taxonomical groups. However, we also observed small but significant spatial effects at metacommunity scale and environmental effects at biogeographical scale. We also observed differences in diversity patterns between the two taxonomical groups corresponding to differences in their dispersal modes. Our results thus support the idea of continuity of processes interactively shaping diversity patterns across scales and emphasize the necessity of integration of metacommunity and biogeographical perspectives. PMID:25549332

The relationship between observational scale and explained variance in benthic communities

PubMed Central

Flood, Roger D.; Frisk, Michael G.; Garza, Corey D.; Lopez, Glenn R.; Maher, Nicole P.

2018-01-01

This study addresses the impact of spatial scale on explaining variance in benthic communities. In particular, the analysis estimated the fraction of community variation that occurred at a spatial scale smaller than the sampling interval (i.e., the geographic distance between samples). This estimate is important because it sets a limit on the amount of community variation that can be explained based on the spatial configuration of a study area and sampling design. Six benthic data sets were examined that consisted of faunal abundances, common environmental variables (water depth, grain size, and surficial percent cover), and sonar backscatter treated as a habitat proxy (categorical acoustic provinces). Redundancy analysis was coupled with spatial variograms generated by multiscale ordination to quantify the explained and residual variance at different spatial scales and within and between acoustic provinces. The amount of community variation below the sampling interval of the surveys (< 100 m) was estimated to be 36–59% of the total. Once adjusted for this small-scale variation, > 71% of the remaining variance was explained by the environmental and province variables. Furthermore, these variables effectively explained the spatial structure present in the infaunal community. Overall, no scale problems remained to compromise inferences, and unexplained infaunal community variation had no apparent spatial structure within the observational scale of the surveys (> 100 m), although small-scale gradients (< 100 m) below the observational scale may be present. PMID:29324746

Subjective well-being and minimum wages: Evidence from U.S. states.

PubMed

Kuroki, Masanori

2018-02-01

This paper investigates whether increases in minimum wages are associated with higher life satisfaction by using monthly-level state minimum wages and individual-level data from the 2005-2010 Behavioral Risk Factor Surveillance System. The magnitude I find suggests that a 10% increase in the minimum wage is associated with a 0.03-point increase in life satisfaction for workers without a high school diploma, on a 4-point scale. Contrary to popular belief that higher minimum wages hurt business owners, I find little evidence that higher minimum wages lead to the loss of well-being among self-employed people. Copyright © 2017 John Wiley & Sons, Ltd.

Void Growth and Coalescence Simulations

DTIC Science & Technology

2013-08-01

distortion and damage, minimum time step, and appropriate material model parameters. Further, a temporal and spatial convergence study was used to...estimate errors, thus, this study helps to provide guidelines for modeling of materials with voids. Finally, we use a Gurson model with Johnson-Cook...spatial convergence study was used to estimate errors, thus, this study helps to provide guidelines for modeling of materials with voids. Finally, we

Analysing and correcting the differences between multi-source and multi-scale spatial remote sensing observations.

PubMed

Dong, Yingying; Luo, Ruisen; Feng, Haikuan; Wang, Jihua; Zhao, Jinling; Zhu, Yining; Yang, Guijun

2014-01-01

Differences exist among analysis results of agriculture monitoring and crop production based on remote sensing observations, which are obtained at different spatial scales from multiple remote sensors in same time period, and processed by same algorithms, models or methods. These differences can be mainly quantitatively described from three aspects, i.e. multiple remote sensing observations, crop parameters estimation models, and spatial scale effects of surface parameters. Our research proposed a new method to analyse and correct the differences between multi-source and multi-scale spatial remote sensing surface reflectance datasets, aiming to provide references for further studies in agricultural application with multiple remotely sensed observations from different sources. The new method was constructed on the basis of physical and mathematical properties of multi-source and multi-scale reflectance datasets. Theories of statistics were involved to extract statistical characteristics of multiple surface reflectance datasets, and further quantitatively analyse spatial variations of these characteristics at multiple spatial scales. Then, taking the surface reflectance at small spatial scale as the baseline data, theories of Gaussian distribution were selected for multiple surface reflectance datasets correction based on the above obtained physical characteristics and mathematical distribution properties, and their spatial variations. This proposed method was verified by two sets of multiple satellite images, which were obtained in two experimental fields located in Inner Mongolia and Beijing, China with different degrees of homogeneity of underlying surfaces. Experimental results indicate that differences of surface reflectance datasets at multiple spatial scales could be effectively corrected over non-homogeneous underlying surfaces, which provide database for further multi-source and multi-scale crop growth monitoring and yield prediction, and their corresponding consistency analysis evaluation.

Analysing and Correcting the Differences between Multi-Source and Multi-Scale Spatial Remote Sensing Observations

PubMed Central

Dong, Yingying; Luo, Ruisen; Feng, Haikuan; Wang, Jihua; Zhao, Jinling; Zhu, Yining; Yang, Guijun

2014-01-01

Differences exist among analysis results of agriculture monitoring and crop production based on remote sensing observations, which are obtained at different spatial scales from multiple remote sensors in same time period, and processed by same algorithms, models or methods. These differences can be mainly quantitatively described from three aspects, i.e. multiple remote sensing observations, crop parameters estimation models, and spatial scale effects of surface parameters. Our research proposed a new method to analyse and correct the differences between multi-source and multi-scale spatial remote sensing surface reflectance datasets, aiming to provide references for further studies in agricultural application with multiple remotely sensed observations from different sources. The new method was constructed on the basis of physical and mathematical properties of multi-source and multi-scale reflectance datasets. Theories of statistics were involved to extract statistical characteristics of multiple surface reflectance datasets, and further quantitatively analyse spatial variations of these characteristics at multiple spatial scales. Then, taking the surface reflectance at small spatial scale as the baseline data, theories of Gaussian distribution were selected for multiple surface reflectance datasets correction based on the above obtained physical characteristics and mathematical distribution properties, and their spatial variations. This proposed method was verified by two sets of multiple satellite images, which were obtained in two experimental fields located in Inner Mongolia and Beijing, China with different degrees of homogeneity of underlying surfaces. Experimental results indicate that differences of surface reflectance datasets at multiple spatial scales could be effectively corrected over non-homogeneous underlying surfaces, which provide database for further multi-source and multi-scale crop growth monitoring and yield prediction, and their corresponding consistency analysis evaluation. PMID:25405760

Climate and weather influences on spatial temporal patterns of mountain pine beetle populations in Washington and Oregon.

PubMed

Preisler, Haiganoush K; Hicke, Jeffrey A; Ager, Alan A; Hayes, Jane L

2012-11-01

Widespread outbreaks of mountain pine beetle in North America have drawn the attention of scientists, forest managers, and the public. There is strong evidence that climate change has contributed to the extent and severity of recent outbreaks. Scientists are interested in quantifying relationships between bark beetle population dynamics and trends in climate. Process models that simulate climate suitability for mountain pine beetle outbreaks have advanced our understanding of beetle population dynamics; however, there are few studies that have assessed their accuracy across multiple outbreaks or at larger spatial scales. This study used the observed number of trees killed by mountain pine beetles per square kilometer in Oregon and Washington, USA, over the past three decades to quantify and assess the influence of climate and weather variables on beetle activity over longer time periods and larger scales than previously studied. Influences of temperature and precipitation in addition to process model output variables were assessed at annual and climatological time scales. The statistical analysis showed that new attacks are more likely to occur at locations with climatological mean August temperatures >15 degrees C. After controlling for beetle pressure, the variables with the largest effect on the odds of an outbreak exceeding a certain size were minimum winter temperature (positive relationship) and drought conditions in current and previous years. Precipitation levels in the year prior to the outbreak had a positive effect, possibly an indication of the influence of this driver on brood size. Two-year cumulative precipitation had a negative effect, a possible indication of the influence of drought on tree stress. Among the process model variables, cold tolerance was the strongest indicator of an outbreak increasing to epidemic size. A weather suitability index developed from the regression analysis indicated a 2.5x increase in the odds of outbreak at locations with highly suitable weather vs. locations with low suitability. The models were useful for estimating expected amounts of damage (total area with outbreaks) and for quantifying the contribution of climate to total damage. Overall, the results confirm the importance of climate and weather on the spatial expansion of bark beetle outbreaks over time.

Spatial analysis and temporal trends of porcine reproductive and respiratory syndrome in Denmark from 2007 to 2010 based on laboratory submission data.

PubMed

Antunes, Ana Carolina Lopes; Halasa, Tariq; Lauritsen, Klara Tølbøl; Kristensen, Charlotte Sonne; Larsen, Lars Erik; Toft, Nils

2015-12-21

Porcine reproductive and respiratory syndrome (PRRS) has been a cause for great concern to the Danish pig industry since it was first diagnosed in 1992. The causative agent of PRRS is an RNA virus which is divided into different genotypes. The clinical signs, as well as its morbidity and mortality, is highly variable between herds and regions. Two different genotypes of PRRS virus (PRRSV) are found in Denmark: type 1 and type 2. Approximately 40% of Danish swine herds are seropositive for one or both PRRSV types. The objective of this study was to describe the temporal trend and spatial distribution of PRRSV in Danish swine herds from 2007 to 2010, based on type-specific serological tests from the PRRS surveillance and control program in Denmark using the results stored in the information management system at the National Veterinary Institute, Technical University of Denmark (DTU Vet). The average monthly seroprevalence of PRRSV type 1 was 9% (minimum of 5%; maximum of 13%) in breeding herds, and 20% (minimum of 14%; maximum of 26%) in production herds; PRRSV type 2 had an average seroprevalence of 3% (minimum of 1%; maximum of 9%) in breeding herds and of 9% (minimum of 5%; maximum of 13%) within production herds. The seroconversion rate followed a similar and consistent pattern, being higher for type 1 than for type 2 for both PRRSV types. Regarding the spatiotemporal results, the relative risk distribution maps changed over time as a consequence of the changes in PRRSV seroprevalence, suggesting a general decline in the extent of areas with higher relative risk for both type 1 and 2. Local spatial analysis results demonstrated the existence of statistically significant clusters in areas where the relative risk was higher for both herds. PRRSV type 1 seroprevalence was constantly higher than for PRRSV type 2 in both herd types. Significant spatial clusters were consistently found in Denmark, suggesting that PRRSV is endemic in these areas. Furthermore, relative risk distribution maps revealed different patterns over time as a consequence of the changes in seroprevalence.

National review of ambient air toxics observations.

PubMed

Strum, Madeleine; Scheffe, Richard

2016-02-01

Ambient air observations of hazardous air pollutant (HAPs), also known as air toxics, derived from routine monitoring networks operated by states, local agencies, and tribes (SLTs), are analyzed to characterize national concentrations and risk across the nation for a representative subset of the 187 designated HAPs. Observations from the National Air Toxics Trend Sites (NATTS) network of 27 stations located in most major urban areas of the contiguous United States have provided a consistent record of HAPs that have been identified as posing the greatest risk since 2003 and have also captured similar concentration patterns of nearly 300 sites operated by SLTs. Relatively high concentration volatile organic compounds (VOCs) such as benzene, formaldehyde, and toluene exhibit the highest annual average concentration levels, typically ranging from 1 to 5 µg/m(3). Halogenated (except for methylene chloride) and semivolatile organic compounds (SVOCs) and metals exhibit concentrations typically 2-3 orders of magnitude lower. Formaldehyde is the highest national risk driver based on estimated cancer risk and, nationally, has not exhibited significant changes in concentration, likely associated with the large pool of natural isoprene and formaldehyde emissions. Benzene, toluene, ethylbenzene, and 1,3-butadiene are ubiquitous VOC HAPs with large mobile source contributions that continue to exhibit declining concentrations over the last decade. Common chlorinated organic compounds such as ethylene dichloride and methylene chloride exhibit increasing concentrations. The variety of physical and chemical attributes and measurement technologies across 187 HAPs result in a broad range of method detection limits (MDLs) and cancer risk thresholds that challenge confidence in risk results for low concentration HAPs with MDLs near or greater than risk thresholds. From a national monitoring network perspective, the ability of the HAPs observational database to characterize the multiple pollutant and spatial scale patterns influencing exposure is severely limited and positioned to benefit by leveraging a variety of emerging measurement technologies. Ambient air toxics observation networks have limited ability to characterize the broad suite of hazardous air pollutants (HAPs) that affect exposures across multiple spatial scales. While our networks are best suited to capture major urban-scale signals of ubiquitous volatile organic compound HAPs, incorporation of sensing technologies that address regional and local-scale exposures should be pursued to address major gaps in spatial resolution. Caution should be exercised in interpreting HAPs observations based on data proximity to minimum detection limit and risk thresholds.

An invariability-area relationship sheds new light on the spatial scaling of ecological stability.

PubMed

Wang, Shaopeng; Loreau, Michel; Arnoldi, Jean-Francois; Fang, Jingyun; Rahman, K Abd; Tao, Shengli; de Mazancourt, Claire

2017-05-19

The spatial scaling of stability is key to understanding ecological sustainability across scales and the sensitivity of ecosystems to habitat destruction. Here we propose the invariability-area relationship (IAR) as a novel approach to investigate the spatial scaling of stability. The shape and slope of IAR are largely determined by patterns of spatial synchrony across scales. When synchrony decays exponentially with distance, IARs exhibit three phases, characterized by steeper increases in invariability at both small and large scales. Such triphasic IARs are observed for primary productivity from plot to continental scales. When synchrony decays as a power law with distance, IARs are quasilinear on a log-log scale. Such quasilinear IARs are observed for North American bird biomass at both species and community levels. The IAR provides a quantitative tool to predict the effects of habitat loss on population and ecosystem stability and to detect regime shifts in spatial ecological systems, which are goals of relevance to conservation and policy.

Paleoceanographic insights on oxygen minimum zone expansion: Lessons from the most recent deglaciation

NASA Astrophysics Data System (ADS)

Moffitt, S. E.; Moffitt, R.; Sauthoff, W.; Davis, C. V.; Hewett, K.; Hill, T. M.

2013-12-01

The expansion of low oxygen hydrographic zones in the modern ocean, known as Oxygen Minimum Zones (OMZ), has the potential to deteriorate ecosystems, alter ocean nutrient cycling and inflict mass mortality events upon benthic and pelagic communities. During the last deglaciation (18-10 ka), large, climate-driven changes in the oxygen content of the upper ocean occurred. We propose that previous climate-driven OMZ expansions are data-rich events with which to characterize the spatial scales of OMZ hydrographic perturbation, and the temporal scales of natural OMZ variability. Here we synthesize a global compilation of marine sediment records from modern OMZ regions to investigate deglacial changes in the vertical extent, intensity, and surface area impingements of hypoxic waters upon continental margins. We surveyed sediment core records within water depths of 183-3,296 meters below sea level (mbsl) and took advantage of cores with geochemical, sedimentary or microfossil oxygenation proxies to reconstruct the timing, depth and intensity of seafloor hypoxia. OMZ maximum vertical extent during the deglaciation was variable by region: Subarctic Pacific (~600-2,900 mbsl), California Current (~330-1,500 mbsl), Baja and Mexico (~330-830 mbsl), and Equatorial Pacific and Humboldt Current (~110-3,100 mbsl). Expansion timing is regionally coherent but not globally synchronous, such that Subarctic Pacific and California Current marginal areas exhibit tight correlation and oxygenation reversals with Northern Hemisphere deglacial events (Termination 1A, Bølling-Allerød, Younger Dryas and Termination 1B). Southern regions (Baja and Mexico, and the Equatorial Pacific and Humboldt Current) exhibit hypoxia expansion prior to Termination 1A (~16 ka), and no oxygenation reversals. Our analysis provides new evidence for the geospatially coherent and temporally rapid expansion of OMZs during the last deglaciation, and reveals the extreme shallowness of the upper hypoxic boundary in coastal waters during events of global-scale warming.

Local properties and global structure of McVittie spacetimes with non-flat Friedmann-Lemaître-Robertson-Walker backgrounds

NASA Astrophysics Data System (ADS)

Nolan, Brien C.

2017-11-01

McVittie spacetimes embed the vacuum Schwarzschild(-(anti) de Sitter) spacetime in an isotropic, Friedmann-Lemaître-Robertson-Walker (FLRW) background universe. The global structure of such spacetimes is well understood when the FLRW background is spatially flat. In this paper, we study the global structure of McVittie spacetimes with spatially non-flat FLRW backgrounds. We derive some basic results on the metric, curvature and matter content of these spacetimes and provide a representation of the metric that makes the study of their global properties possible. In the closed case, we find that at each instant of time, the spacetime is confined to a region bounded by a (positive) minimum and a maximum area radius, and is bounded either to the future or to the past by a scalar curvature singularity. This allowed region only exists when the background scale factor is above a certain minimum, and so is bounded away from the Big Bang singularity, as in the flat case. In the open case, the situation is different, and we focus mainly on this case. In K<0 McVittie spacetimes, radial null geodesics originate in finite affine time in the past at a boundary formed by the union of the Big Bang singularity of the FLRW background and a hypersurface (of varying causal character) which is non-singular in the sense of scalar curvature. Furthermore, in the case of eternally expanding open universes with Λ≥slant0 , we prove that black holes are ubiquitous: ingoing radial null geodesics extend in finite affine time to a hypersurface that forms the boundary of the region from which photons can escape to future null infinity. We determine the structure of the conformal diagrams that can arise in the open case. Finally, we revisit the black hole interpretation of McVittie spacetimes in the spatially flat case, and show that this interpretation holds also in the case of a vanishing cosmological constant, contrary to a previous claim of ours.

Settling of hot particles through turbulence

NASA Astrophysics Data System (ADS)

Coletti, Filippo; Frankel, Ari; Pouransari, Hadi; Mani, Ali

2014-11-01

Particle-laden flows in which the dispersed phase is not isothermal with the continuous phase are common in a wealth of natural and industrial setting. In this study we consider the case of inertial particles heated by thermal radiation while settling through a turbulent transparent gas. Particles much smaller than the minimum flow scales are considered. The particle Stokes number (based on the Kolmogorov time scale) and the nominal settling velocity (normalized by the root-mean-square fluid velocity fluctuation) are both of order unity. In the considered dilute and optically thin regime, each particle receives the same heat flux. Numerical simulations are performed in which the two-way coupling between dispersed and continuous phase is taken into account. The momentum and energy equations are solved in a triply periodic domain, resolving all spatial and temporal scales. While falling, the heated particles shed plumes of buoyant gas, modifying the turbulence structure and enhancing velocity fluctuations in the vertical direction. The radiative forcing does not affect preferential concentration (clustering of particles in low vorticity regions), but reduces preferential sweeping (particle sampling regions of downward fluid motion). Overall, the mean settling velocity varies slightly when heating the particles, while its variance is greatly increased. We gratefully acknowledges support from DOE PSAAP II program.

The thermal impact of aquifer thermal energy storage (ATES) systems: a case study in the Netherlands, combining monitoring and modeling

NASA Astrophysics Data System (ADS)

Visser, Philip W.; Kooi, Henk; Stuyfzand, Pieter J.

2015-05-01

Results are presented of a comprehensive thermal impact study on an aquifer thermal energy storage (ATES) system in Bilthoven, the Netherlands. The study involved monitoring of the thermal impact and modeling of the three-dimensional temperature evolution of the storage aquifer and over- and underlying units. Special attention was paid to non-uniformity of the background temperature, which varies laterally and vertically in the aquifer. Two models were applied with different levels of detail regarding initial conditions and heterogeneity of hydraulic and thermal properties: a fine-scale heterogeneity model which construed the lateral and vertical temperature distribution more realistically, and a simplified model which represented the aquifer system with only a limited number of homogeneous layers. Fine-scale heterogeneity was shown to be important to accurately model the ATES-impacted vertical temperature distribution and the maximum and minimum temperatures in the storage aquifer, and the spatial extent of the thermal plumes. The fine-scale heterogeneity model resulted in larger thermally impacted areas and larger temperature anomalies than the simplified model. The models showed that scattered and scarce monitoring data of ATES-induced temperatures can be interpreted in a useful way by groundwater and heat transport modeling, resulting in a realistic assessment of the thermal impact.

Towards a More Biologically-meaningful Climate Characterization: Variability in Space and Time at Multiple Scales

NASA Astrophysics Data System (ADS)

Christianson, D. S.; Kaufman, C. G.; Kueppers, L. M.; Harte, J.

2013-12-01

Sampling limitations and current modeling capacity justify the common use of mean temperature values in summaries of historical climate and future projections. However, a monthly mean temperature representing a 1-km2 area on the landscape is often unable to capture the climate complexity driving organismal and ecological processes. Estimates of variability in addition to mean values are more biologically meaningful and have been shown to improve projections of range shifts for certain species. Historical analyses of variance and extreme events at coarse spatial scales, as well as coarse-scale projections, show increasing temporal variability in temperature with warmer means. Few studies have considered how spatial variance changes with warming, and analysis for both temporal and spatial variability across scales is lacking. It is unclear how the spatial variability of fine-scale conditions relevant to plant and animal individuals may change given warmer coarse-scale mean values. A change in spatial variability will affect the availability of suitable habitat on the landscape and thus, will influence future species ranges. By characterizing variability across both temporal and spatial scales, we can account for potential bias in species range projections that use coarse climate data and enable improvements to current models. In this study, we use temperature data at multiple spatial and temporal scales to characterize spatial and temporal variability under a warmer climate, i.e., increased mean temperatures. Observational data from the Sierra Nevada (California, USA), experimental climate manipulation data from the eastern and western slopes of the Rocky Mountains (Colorado, USA), projected CMIP5 data for California (USA) and observed PRISM data (USA) allow us to compare characteristics of a mean-variance relationship across spatial scales ranging from sub-meter2 to 10,000 km2 and across temporal scales ranging from hours to decades. Preliminary spatial analysis at fine-spatial scales (sub-meter to 10-meter) shows greater temperature variability with warmer mean temperatures. This is inconsistent with the inherent assumption made in current species distribution models that fine-scale variability is static, implying that current projections of future species ranges may be biased -- the direction and magnitude requiring further study. While we focus our findings on the cross-scaling characteristics of temporal and spatial variability, we also compare the mean-variance relationship between 1) experimental climate manipulations and observed conditions and 2) temporal versus spatial variance, i.e., variability in a time-series at one location vs. variability across a landscape at a single time. The former informs the rich debate concerning the ability to experimentally mimic a warmer future. The latter informs space-for-time study design and analyses, as well as species persistence via a combined spatiotemporal probability of suitable future habitat.

Scaling local species-habitat relations to the larger landscape with a hierarchical spatial count model

USGS Publications Warehouse

Thogmartin, W.E.; Knutson, M.G.

2007-01-01

Much of what is known about avian species-habitat relations has been derived from studies of birds at local scales. It is entirely unclear whether the relations observed at these scales translate to the larger landscape in a predictable linear fashion. We derived habitat models and mapped predicted abundances for three forest bird species of eastern North America using bird counts, environmental variables, and hierarchical models applied at three spatial scales. Our purpose was to understand habitat associations at multiple spatial scales and create predictive abundance maps for purposes of conservation planning at a landscape scale given the constraint that the variables used in this exercise were derived from local-level studies. Our models indicated a substantial influence of landscape context for all species, many of which were counter to reported associations at finer spatial extents. We found land cover composition provided the greatest contribution to the relative explained variance in counts for all three species; spatial structure was second in importance. No single spatial scale dominated any model, indicating that these species are responding to factors at multiple spatial scales. For purposes of conservation planning, areas of predicted high abundance should be investigated to evaluate the conservation potential of the landscape in their general vicinity. In addition, the models and spatial patterns of abundance among species suggest locations where conservation actions may benefit more than one species. ?? 2006 Springer Science+Business Media B.V.

Compressed sensing and the reconstruction of ultrafast 2D NMR data: Principles and biomolecular applications.

PubMed

Shrot, Yoav; Frydman, Lucio

2011-04-01

A topic of active investigation in 2D NMR relates to the minimum number of scans required for acquiring this kind of spectra, particularly when these are dictated by sampling rather than by sensitivity considerations. Reductions in this minimum number of scans have been achieved by departing from the regular sampling used to monitor the indirect domain, and relying instead on non-uniform sampling and iterative reconstruction algorithms. Alternatively, so-called "ultrafast" methods can compress the minimum number of scans involved in 2D NMR all the way to a minimum number of one, by spatially encoding the indirect domain information and subsequently recovering it via oscillating field gradients. Given ultrafast NMR's simultaneous recording of the indirect- and direct-domain data, this experiment couples the spectral constraints of these orthogonal domains - often calling for the use of strong acquisition gradients and large filter widths to fulfill the desired bandwidth and resolution demands along all spectral dimensions. This study discusses a way to alleviate these demands, and thereby enhance the method's performance and applicability, by combining spatial encoding with iterative reconstruction approaches. Examples of these new principles are given based on the compressed-sensed reconstruction of biomolecular 2D HSQC ultrafast NMR data, an approach that we show enables a decrease of the gradient strengths demanded in this type of experiments by up to 80%. Copyright © 2011 Elsevier Inc. All rights reserved.

Minimum entropy deconvolution and blind equalisation

NASA Technical Reports Server (NTRS)

Satorius, E. H.; Mulligan, J. J.

1992-01-01

Relationships between minimum entropy deconvolution, developed primarily for geophysics applications, and blind equalization are pointed out. It is seen that a large class of existing blind equalization algorithms are directly related to the scale-invariant cost functions used in minimum entropy deconvolution. Thus the extensive analyses of these cost functions can be directly applied to blind equalization, including the important asymptotic results of Donoho.

Scaling-up the minimum requirements analysis for big wilderness issues

Treesearch

David N. Cole

2007-01-01

The concept of applying a "minimum requirements" analysis to decisions about administrative actions in wilderness in the United States has been around for a long time. It comes from Section 4(c) of the Wilderness Act of 1964, which states that "except as necessary to meet minimum requirements for the administration of the area for the purposes of this...

Scaling properties of sea ice deformation from buoy dispersion analysis

NASA Astrophysics Data System (ADS)

Rampal, P.; Weiss, J.; Marsan, D.; Lindsay, R.; Stern, H.

2008-03-01

A temporal and spatial scaling analysis of Arctic sea ice deformation is performed over timescales from 3 h to 3 months and over spatial scales from 300 m to 300 km. The deformation is derived from the dispersion of pairs of drifting buoys, using the IABP (International Arctic Buoy Program) buoy data sets. This study characterizes the deformation of a very large solid plate (the Arctic sea ice cover) stressed by heterogeneous forcing terms like winds and ocean currents. It shows that the sea ice deformation rate depends on the scales of observation following specific space and time scaling laws. These scaling properties share similarities with those observed for turbulent fluids, especially for the ocean and the atmosphere. However, in our case, the time scaling exponent depends on the spatial scale, and the spatial exponent on the temporal scale, which implies a time/space coupling. An analysis of the exponent values shows that Arctic sea ice deformation is very heterogeneous and intermittent whatever the scales, i.e., it cannot be considered as viscous-like, even at very large time and/or spatial scales. Instead, it suggests a deformation accommodated by a multiscale fracturing/faulting processes.

Dissecting the multi-scale spatial relationship of earthworm assemblages with soil environmental variability.

PubMed

Jiménez, Juan J; Decaëns, Thibaud; Lavelle, Patrick; Rossi, Jean-Pierre

2014-12-05

Studying the drivers and determinants of species, population and community spatial patterns is central to ecology. The observed structure of community assemblages is the result of deterministic abiotic (environmental constraints) and biotic factors (positive and negative species interactions), as well as stochastic colonization events (historical contingency). We analyzed the role of multi-scale spatial component of soil environmental variability in structuring earthworm assemblages in a gallery forest from the Colombian "Llanos". We aimed to disentangle the spatial scales at which species assemblages are structured and determine whether these scales matched those expressed by soil environmental variables. We also tested the hypothesis of the "single tree effect" by exploring the spatial relationships between root-related variables and soil nutrient and physical variables in structuring earthworm assemblages. Multivariate ordination techniques and spatially explicit tools were used, namely cross-correlograms, Principal Coordinates of Neighbor Matrices (PCNM) and variation partitioning analyses. The relationship between the spatial organization of earthworm assemblages and soil environmental parameters revealed explicitly multi-scale responses. The soil environmental variables that explained nested population structures across the multi-spatial scale gradient differed for earthworms and assemblages at the very-fine- (<10 m) to medium-scale (10-20 m). The root traits were correlated with areas of high soil nutrient contents at a depth of 0-5 cm. Information on the scales of PCNM variables was obtained using variogram modeling. Based on the size of the plot, the PCNM variables were arbitrarily allocated to medium (>30 m), fine (10-20 m) and very fine scales (<10 m). Variation partitioning analysis revealed that the soil environmental variability explained from less than 1% to as much as 48% of the observed earthworm spatial variation. A large proportion of the spatial variation did not depend on the soil environmental variability for certain species. This finding could indicate the influence of contagious biotic interactions, stochastic factors, or unmeasured relevant soil environmental variables.

Minimum entropy density method for the time series analysis

NASA Astrophysics Data System (ADS)

Lee, Jeong Won; Park, Joongwoo Brian; Jo, Hang-Hyun; Yang, Jae-Suk; Moon, Hie-Tae

2009-01-01

The entropy density is an intuitive and powerful concept to study the complicated nonlinear processes derived from physical systems. We develop the minimum entropy density method (MEDM) to detect the structure scale of a given time series, which is defined as the scale in which the uncertainty is minimized, hence the pattern is revealed most. The MEDM is applied to the financial time series of Standard and Poor’s 500 index from February 1983 to April 2006. Then the temporal behavior of structure scale is obtained and analyzed in relation to the information delivery time and efficient market hypothesis.

Spatial and temporal variation in emergency transport during periods of extreme heat in Japan: A nationwide study.

PubMed

Onozuka, Daisuke; Hagihara, Akihito

2016-02-15

Several studies have reported the burden of climate change on extreme heat-related mortality or morbidity. However, few studies have investigated the spatial and temporal variation in emergency transport during periods of extreme heat on a national scale. Daily emergency ambulance dispatch data from 2007 to 2010 were acquired from all 47 prefectures of Japan. The temporal variability in the relationship between heat and morbidity in each prefecture was estimated using Poisson regression combined with a distributed lag non-linear model and adjusted for time trends. The spatial variability in the heat-morbidity relationships between prefectures was estimated using a multivariate meta-analysis. A total of 5,289,660 emergency transports were reported during the summer months (June through September) within the study period. The overall cumulative relative risk (RR) at the 99th percentile vs. the minimum morbidity percentile was 1.292 (95% CI: 1.251-1.333) for all causes, 1.039 (95% CI: 0.989-1.091) for cardiovascular diseases, and 1.287 (95% CI: 1.210-1.368) for respiratory diseases. Temporal variation in the estimated effects indicated a non-linear relationship, and there were differences in the temporal variations between heat and all-cause and cause-specific morbidity. Spatial variation between prefectures was observed for all causes (Cochran Q test, p<0.001; I(2)=45.8%); however, there was no significant spatial heterogeneity for cardiovascular (Cochran Q test, p=0.054; I(2)=15.1%) and respiratory (Cochran Q test, p=0.681; I(2)=1.0%) diseases. Our nationwide study demonstrated differences in the spatial and temporal variations in the relative risk for all-cause and cause-specific emergency transport during periods of extreme heat in Japan between 2007 and 2010. Our results suggest that public health strategies aimed at controlling heat-related morbidity should be tailored according to region-specific weather conditions. Copyright © 2015 Elsevier B.V. All rights reserved.

A multi-scale comparison of trait linkages to environmental and spatial variables in fish communities across a large freshwater lake.

PubMed

Strecker, Angela L; Casselman, John M; Fortin, Marie-Josée; Jackson, Donald A; Ridgway, Mark S; Abrams, Peter A; Shuter, Brian J

2011-07-01

Species present in communities are affected by the prevailing environmental conditions, and the traits that these species display may be sensitive indicators of community responses to environmental change. However, interpretation of community responses may be confounded by environmental variation at different spatial scales. Using a hierarchical approach, we assessed the spatial and temporal variation of traits in coastal fish communities in Lake Huron over a 5-year time period (2001-2005) in response to biotic and abiotic environmental factors. The association of environmental and spatial variables with trophic, life-history, and thermal traits at two spatial scales (regional basin-scale, local site-scale) was quantified using multivariate statistics and variation partitioning. We defined these two scales (regional, local) on which to measure variation and then applied this measurement framework identically in all 5 study years. With this framework, we found that there was no change in the spatial scales of fish community traits over the course of the study, although there were small inter-annual shifts in the importance of regional basin- and local site-scale variables in determining community trait composition (e.g., life-history, trophic, and thermal). The overriding effects of regional-scale variables may be related to inter-annual variation in average summer temperature. Additionally, drivers of fish community traits were highly variable among study years, with some years dominated by environmental variation and others dominated by spatially structured variation. The influence of spatial factors on trait composition was dynamic, which suggests that spatial patterns in fish communities over large landscapes are transient. Air temperature and vegetation were significant variables in most years, underscoring the importance of future climate change and shoreline development as drivers of fish community structure. Overall, a trait-based hierarchical framework may be a useful conservation tool, as it highlights the multi-scaled interactive effect of variables over a large landscape.

The Relationship between Spatial and Temporal Magnitude Estimation of Scientific Concepts at Extreme Scales

NASA Astrophysics Data System (ADS)

Price, Aaron; Lee, H.

2010-01-01

Many astronomical objects, processes, and events exist and occur at extreme scales of spatial and temporal magnitudes. Our research draws upon the psychological literature, replete with evidence of linguistic and metaphorical links between the spatial and temporal domains, to compare how students estimate spatial and temporal magnitudes associated with objects and processes typically taught in science class.. We administered spatial and temporal scale estimation tests, with many astronomical items, to 417 students enrolled in 12 undergraduate science courses. Results show that while the temporal test was more difficult, students’ overall performance patterns between the two tests were mostly similar. However, asymmetrical correlations between the two tests indicate that students think of the extreme ranges of spatial and temporal scales in different ways, which is likely influenced by their classroom experience. When making incorrect estimations, students tended to underestimate the difference between the everyday scale and the extreme scales on both tests. This suggests the use of a common logarithmic mental number line for both spatial and temporal magnitude estimation. However, there are differences between the two tests in the errors student make in the everyday range. Among the implications discussed is the use of spatio-temporal reference frames, instead of smooth bootstrapping, to help students maneuver between scales of magnitude and the use of logarithmic transformations between reference frames. Implications for astronomy range from learning about spectra to large scale galaxy structure.

Effects of spatial variability and scale on areal -average evapotranspiration

NASA Technical Reports Server (NTRS)

Famiglietti, J. S.; Wood, Eric F.

1993-01-01

This paper explores the effect of spatial variability and scale on areally-averaged evapotranspiration. A spatially-distributed water and energy balance model is employed to determine the effect of explicit patterns of model parameters and atmospheric forcing on modeled areally-averaged evapotranspiration over a range of increasing spatial scales. The analysis is performed from the local scale to the catchment scale. The study area is King's Creek catchment, an 11.7 sq km watershed located on the native tallgrass prairie of Kansas. The dominant controls on the scaling behavior of catchment-average evapotranspiration are investigated by simulation, as is the existence of a threshold scale for evapotranspiration modeling, with implications for explicit versus statistical representation of important process controls. It appears that some of our findings are fairly general, and will therefore provide a framework for understanding the scaling behavior of areally-averaged evapotranspiration at the catchment and larger scales.

Estimating the spatial scales of landscape effects on abundance

Treesearch

Richard Chandler; Jeffrey Hepinstall-Cymerman

2016-01-01

Spatial variation in abundance is influenced by local- and landscape-level environmental variables, but modeling landscape effects is challenging because the spatial scales of the relationships are unknown. Current approaches involve buffering survey locations with polygons of various sizes and using model selection to identify the best scale. The buffering...

RESPONSIVENESS OF THE ACTIVITIES OF DAILY LIVING SCALE OF THE KNEE OUTCOME SURVEY AND NUMERIC PAIN RATING SCALE IN PATIENTS WITH PATELLOFEMORAL PAIN

PubMed Central

Piva, Sara R.; Gil, Alexandra B.; Moore, Charity G.; Fitzgerald, G. Kelley

2016-01-01

Objective To assess internal and external responsiveness of the Activity of Daily Living Scale of the Knee Outcome Survey and Numeric Pain Rating Scale on patients with patellofemoral pain. Design One group pre-post design. Subjects A total of 60 individuals with patellofemoral pain (33 women; mean age 29.9 (standard deviation 9.6) years). Methods The Activity of Daily Living Scale and the Numeric Pain Rating Scale were assessed before and after 8 weeks of physical therapy program. Patients completed a global rating of change scale at the end of therapy. The standardized effect size, Guyatt responsiveness index, and the minimum clinical important difference were calculated. Results Standardized effect size of the Activity of Daily Living Scale was 0.63, Guyatt responsiveness index was 1.4, area under the curve was 0.83 (95% confidence interval: 0.72, 0.94), and the minimum clinical important difference corresponded to an increase of 7.1 percentile points. Standardized effect size of the Numeric Pain Rating Scale was 0.72, Guyatt responsiveness index was 2.2, area under the curve was 0.80 (95% confidence interval: 0.70, 0.92), and the minimum clinical important difference corresponded to a decrease of 1.16 points. Conclusion Information from this study may be helpful to therapists when evaluating the effectiveness of rehabilitation intervention on physical function and pain, and to power future clinical trials on patients with patellofemoral pain. PMID:19229444

Responsiveness of the activities of daily living scale of the knee outcome survey and numeric pain rating scale in patients with patellofemoral pain.

PubMed

Piva, Sara R; Gil, Alexandra B; Moore, Charity G; Fitzgerald, G Kelley

2009-02-01

To assess internal and external responsiveness of the Activity of Daily Living Scale of the Knee Outcome Survey and Numeric Pain Rating Scale on patients with patellofemoral pain. One group pre-post design. A total of 60 individuals with patellofemoral pain (33 women; mean age 29.9 (standard deviation 9.6) years). The Activity of Daily Living Scale and the Numeric Pain Rating Scale were assessed before and after 8 weeks of physical therapy program. Patients completed a global rating of change scale at the end of therapy. The standardized effect size, Guyatt responsiveness index, and the minimum clinical important difference were calculated. Standardized effect size of the Activity of Daily Living Scale was 0.63, Guyatt responsiveness index was 1.4, area under the curve was 0.83 (95% confidence interval: 0.72, 0.94), and the minimum clinical important difference corresponded to an increase of 7.1 percentile points. Standardized effect size of the Numeric Pain Rating Scale was 0.72, Guyatt responsiveness index was 2.2, area under the curve was 0.80 (95% confidence interval: 0.70, 0.92), and the minimum clinical important difference corresponded to a decrease of 1.16 points. Information from this study may be helpful to therapists when evaluating the effectiveness of rehabilitation intervention on physical function and pain, and to power future clinical trials on patients with patellofemoral pain.

Fast adaptive diamond search algorithm for block-matching motion estimation using spatial correlation

NASA Astrophysics Data System (ADS)

Park, Sang-Gon; Jeong, Dong-Seok

2000-12-01

In this paper, we propose a fast adaptive diamond search algorithm (FADS) for block matching motion estimation. Many fast motion estimation algorithms reduce the computational complexity by the UESA (Unimodal Error Surface Assumption) where the matching error monotonically increases as the search moves away from the global minimum point. Recently, many fast BMAs (Block Matching Algorithms) make use of the fact that global minimum points in real world video sequences are centered at the position of zero motion. But these BMAs, especially in large motion, are easily trapped into the local minima and result in poor matching accuracy. So, we propose a new motion estimation algorithm using the spatial correlation among the neighboring blocks. We move the search origin according to the motion vectors of the spatially neighboring blocks and their MAEs (Mean Absolute Errors). The computer simulation shows that the proposed algorithm has almost the same computational complexity with DS (Diamond Search), but enhances PSNR. Moreover, the proposed algorithm gives almost the same PSNR as that of FS (Full Search), even for the large motion with half the computational load.

Spatial distribution of landslides triggered from the 2007 Niigata Chuetsu–Oki Japan Earthquake

USGS Publications Warehouse

Collins, Brian D.; Kayen, Robert E.; Tanaka, Yasuo

2012-01-01

Understanding the spatial distribution of earthquake-induced landslides from specific earthquakes provides an opportunity to recognize what to expect from future events. The July 16, 2007 Mw 6.6 (MJMA 6.8) Niigata Chuetsu–Oki Japan earthquake triggered hundreds of landslides in the area surrounding the coastal city of Kashiwazaki and provides one such opportunity to evaluate the impacts of an offshore, magnitude 6 + earthquake on a steep coastal region. As part of a larger effort to document all forms of geotechnical damage from this earthquake, we performed landslide inventory mapping throughout the epicentral area and analyzed the resulting data for spatial, seismic-motion, and geologic correlations to describe the pattern of landsliding. Coupled with examination of a third-party, aerial-photo-based landslide inventory, our analyses reveal several areas of high landslide concentration that are not readily explained by either traditional epicentral and fault–plane-distance metrics or by recorded and inferred ground-motions. Whereas average landslide concentrations averaged less than 1 landslide per square kilometer (LS/km2), some areas reached up to 2 LS/km2 in the Nishiyama Hills to the northeast of Kashiwazaki and between 2 and 11 LS/km2 in coastal areas to the north and south of the city. Correlation with seismometer-based and monument overturning back-calculated ground motions suggests that a minimum peak ground acceleration (PGA) of approximately 0.2 g was necessary for landsliding throughout the region, but does not explain the subregional areas of high landslide concentration. However, analysis of topographic slope and the distribution of generally weak, dip-slope, geologic units does sufficiently explain why, on a sub-regional scale, high landslide concentrations occurred where they did. These include: (1) an inland region of steep, dip-slope, anticlinal sedimentary strata with associated fold belt compression and uplift of the anticline and (2) coastal areas with generally weaker, weathered outcrop lithology and steeper slopes resulting from active marine and terrestrial cliff processes. The results offer lessons for understanding the effects of earthquakes on both regional and subregional scales with regard to the spatial distribution of landsliding.

The underlying processes of a soil mite metacommunity on a small scale.

PubMed

Dong, Chengxu; Gao, Meixiang; Guo, Chuanwei; Lin, Lin; Wu, Donghui; Zhang, Limin

2017-01-01

Metacommunity theory provides an understanding of how ecological processes regulate local community assemblies. However, few field studies have evaluated the underlying mechanisms of a metacommunity on a small scale through revealing the relative roles of spatial and environmental filtering in structuring local community composition. Based on a spatially explicit sampling design in 2012 and 2013, this study aims to evaluate the underlying processes of a soil mite metacommunity on a small spatial scale (50 m) in a temperate deciduous forest located at the Maoershan Ecosystem Research Station, Northeast China. Moran's eigenvector maps (MEMs) were used to model independent spatial variables. The relative importance of spatial (including trend variables, i.e., geographical coordinates, and broad- and fine-scale spatial variables) and environmental factors in driving the soil mite metacommunity was determined by variation partitioning. Mantel and partial Mantel tests and a redundancy analysis (RDA) were also used to identify the relative contributions of spatial and environmental variables. The results of variation partitioning suggested that the relatively large and significant variance was a result of spatial variables (including broad- and fine-scale spatial variables and trend), indicating the importance of dispersal limitation and autocorrelation processes. The significant contribution of environmental variables was detected in 2012 based on a partial Mantel test, and soil moisture and soil organic matter were especially important for the soil mite metacommunity composition in both years. The study suggested that the soil mite metacommunity was primarily regulated by dispersal limitation due to broad-scale and neutral biotic processes at a fine-scale and that environmental filtering might be of subordinate importance. In conclusion, a combination of metacommunity perspectives between neutral and species sorting theories was suggested to be important in the observed structure of the soil mite metacommunity at the studied small scale.

The underlying processes of a soil mite metacommunity on a small scale

PubMed Central

Guo, Chuanwei; Lin, Lin; Wu, Donghui; Zhang, Limin

2017-01-01

Metacommunity theory provides an understanding of how ecological processes regulate local community assemblies. However, few field studies have evaluated the underlying mechanisms of a metacommunity on a small scale through revealing the relative roles of spatial and environmental filtering in structuring local community composition. Based on a spatially explicit sampling design in 2012 and 2013, this study aims to evaluate the underlying processes of a soil mite metacommunity on a small spatial scale (50 m) in a temperate deciduous forest located at the Maoershan Ecosystem Research Station, Northeast China. Moran’s eigenvector maps (MEMs) were used to model independent spatial variables. The relative importance of spatial (including trend variables, i.e., geographical coordinates, and broad- and fine-scale spatial variables) and environmental factors in driving the soil mite metacommunity was determined by variation partitioning. Mantel and partial Mantel tests and a redundancy analysis (RDA) were also used to identify the relative contributions of spatial and environmental variables. The results of variation partitioning suggested that the relatively large and significant variance was a result of spatial variables (including broad- and fine-scale spatial variables and trend), indicating the importance of dispersal limitation and autocorrelation processes. The significant contribution of environmental variables was detected in 2012 based on a partial Mantel test, and soil moisture and soil organic matter were especially important for the soil mite metacommunity composition in both years. The study suggested that the soil mite metacommunity was primarily regulated by dispersal limitation due to broad-scale and neutral biotic processes at a fine-scale and that environmental filtering might be of subordinate importance. In conclusion, a combination of metacommunity perspectives between neutral and species sorting theories was suggested to be important in the observed structure of the soil mite metacommunity at the studied small scale. PMID:28481906

Relationships between landscape pattern and land surface temperature and their applications to the study of West Nile Virus: As case studies in cities of Indianapolis and Chicago, United States

NASA Astrophysics Data System (ADS)

Liu, Hua

A new synthesis of remote sensing and landscape ecology approaches was developed to establish relationships between the landscape patterns and land surface temperatures (LST) in the city of Indianapolis, Indiana, United States. Land use and land cover (LULC) and LST images were derived from Terra Satellite's Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imagery. An analytical procedure using landscape metrics was developed, applying configuration analysis of landscape patterns and land surface temperature zones. Detailed landscape pattern analyses at the landscape and class scales were conducted using landscape metrics in the City of Indianapolis. The effects of spatial resolution on the identification of the relationship were examined in the same city. The best level of equalization between the LULC and LST maps was determined based on minimum distance analysis in landscape metrics space. The analyses of relationships between the landscape patterns and land surface temperatures, and scaling effects were applied to the spread of West Nile Virus (WNV) in the City of Chicago, Illinois. Results show that urban, forest, and grassland were the main landscape components in Indianapolis. They possessed relatively higher fractal dimensions but lower spatial aggregation levels in April 5, 2004, June 16, 2001, and October 3, 2000, but not in February 6, 2006. Obvious seasonal differences existed with the most distinct landscape pattern detected on February 6, 2006. Urban was the dominant LULC type in high-temperature zones, while water and vegetation mainly fell in low-temperature zones. For each individual date, the metrics of LST zones apparently corresponded to the metrics of LULC types. In the study of scaling-up effect analysis, Patch Percentage, Patch Density, and Landscape Shape index were found to be able to effectively quantify the spatial changes of LULC types and temperature zones at different scales without contradiction. Urban, forest, and grassland in each season were more easily affected by the process in Patch Density and Landscape Shape index. Ninety meters was believed to be the optimal spatial resolution to examine relationships between landscape patterns and LSTs in the City of Indianapolis. In the study of the spread of West Nile Virus in the City of Chicago, WNV was found to have been spread throughout all of Cook County since 2001. Landscape factors, like landscape aggregation index and areas of urban, grass, and water showed a strong correlation with the number of WNV infections. Socioeconomic conditions, like population above 65 years old also showed a strong relationship with the spread of WNV in Cook County. Thermal conditions of water had a lower but still significant correlation to the spread of WNV. This research offers an opportunity to explore the mechanism of interaction between urban landscape patterns and land surface temperatures at different spatial scales, and show the effects of landscape pattern and land surface temperature on the spread of West Nile Virus. This study can be useful for urban planning and environmental management practices in the studied areas. It also contributes to public health management and protection.

From broadscale patterns to fine-scale processes: habitat structure influences genetic differentiation in the pitcher plant midge across multiple spatial scales.

PubMed

Rasic, Gordana; Keyghobadi, Nusha

2012-01-01

The spatial scale at which samples are collected and analysed influences the inferences that can be drawn from landscape genetic studies. We examined genetic structure and its landscape correlates in the pitcher plant midge, Metriocnemus knabi, an inhabitant of the purple pitcher plant, Sarracenia purpurea, across several spatial scales that are naturally delimited by the midge's habitat (leaf, plant, cluster of plants, bog and system of bogs). We analysed 11 microsatellite loci in 710 M. knabi larvae from two systems of bogs in Algonquin Provincial Park (Canada) and tested the hypotheses that variables related to habitat structure are associated with genetic differentiation in this midge. Up to 54% of variation in individual-based genetic distances at several scales was explained by broadscale landscape variables of bog size, pitcher plant density within bogs and connectivity of pitcher plant clusters. Our results indicate that oviposition behaviour of females at fine scales, as inferred from the spatial locations of full-sib larvae, and spatially limited gene flow at broad scales represent the important processes underlying observed genetic patterns in M. knabi. Broadscale landscape features (bog size and plant density) appear to influence oviposition behaviour of midges, which in turn influences the patterns of genetic differentiation observed at both fine and broad scales. Thus, we inferred linkages among genetic patterns, landscape patterns and ecological processes across spatial scales in M. knabi. Our results reinforce the value of exploring such links simultaneously across multiple spatial scales and landscapes when investigating genetic diversity within a species. © 2011 Blackwell Publishing Ltd.

Land motion due to 20th century mass balance of the Greenland Ice Sheet

NASA Astrophysics Data System (ADS)

Kjeldsen, K. K.; Khan, S. A.

2017-12-01

Quantifying the contribution from ice sheets and glaciers to past sea level change is of great value for understanding sea level projections into the 21st century. However, quantifying and understanding past changes are equally important, in particular understanding the impact in the near-field where the signal is highest. We assess the impact of 20th century mass balance of the Greenland Ice Sheet on land motion using results from Kjeldsen et al, 2015. These results suggest that the ice sheet on average lost a minimum of 75 Gt/yr, but also show that the mass balance was highly spatial- and temporal variable, and moreover that on a centennial time scale changes were driven by a decreasing surface mass balance. Based on preliminary results we discuss land motion during the 20th century due to mass balance changes and the driving components surface mass balance and ice dynamics.

Preliminary analysis of remote infrared imagery of shuttle during entry: An aerothermodynamic flight experiment

NASA Technical Reports Server (NTRS)

Swenson, B. L.; Edsinger, L. E.

1977-01-01

The preliminary feasibility of remote high-resolution infrared imagery of the space shuttle orbiter lower surface during entry to obtain accurate measurements of aerodynamic heat transfer to that vehicle was examined. In general, it was determined that such such images can be taken from an existing aircraft/telescope system (the C-141 AIRO) with a minimum modification or addition of systems using available technology. These images will have a spatial resolution of about 0.3 m and a temperature resolution much better than 2.5 percent. The data from these images will be at conditions and at a scale not reproducible in ground based facilities and should aid in the reduction of the prudent factors of safety required to account for phenomenological uncertainties on the thermal protection system design. Principal phenomena to be observed include laminar heating, boundary-layer transition, turbulent heating, surface catalysis, and flow separation and reattachment.

First-passage dynamics of linear stochastic interface models: weak-noise theory and influence of boundary conditions

NASA Astrophysics Data System (ADS)

Gross, Markus

2018-03-01

We consider a one-dimensional fluctuating interfacial profile governed by the Edwards–Wilkinson or the stochastic Mullins-Herring equation for periodic, standard Dirichlet and Dirichlet no-flux boundary conditions. The minimum action path of an interfacial fluctuation conditioned to reach a given maximum height M at a finite (first-passage) time T is calculated within the weak-noise approximation. Dynamic and static scaling functions for the profile shape are obtained in the transient and the equilibrium regime, i.e. for first-passage times T smaller or larger than the characteristic relaxation time, respectively. In both regimes, the profile approaches the maximum height M with a universal algebraic time dependence characterized solely by the dynamic exponent of the model. It is shown that, in the equilibrium regime, the spatial shape of the profile depends sensitively on boundary conditions and conservation laws, but it is essentially independent of them in the transient regime.

Single-ion microwave near-field quantum sensor

NASA Astrophysics Data System (ADS)

Wahnschaffe, M.; Hahn, H.; Zarantonello, G.; Dubielzig, T.; Grondkowski, S.; Bautista-Salvador, A.; Kohnen, M.; Ospelkaus, C.

2017-01-01

We develop an intuitive model of 2D microwave near-fields in the unusual regime of centimeter waves localized to tens of microns. Close to an intensity minimum, a simple effective description emerges with five parameters that characterize the strength and spatial orientation of the zero and first order terms of the near-field, as well as the field polarization. Such a field configuration is realized in a microfabricated planar structure with an integrated microwave conductor operating near 1 GHz. We use a single 9 Be+ ion as a high-resolution quantum sensor to measure the field distribution through energy shifts in its hyperfine structure. We find agreement with simulations at the sub-micron and few-degree level. Our findings give a clear and general picture of the basic properties of oscillatory 2D near-fields with applications in quantum information processing, neutral atom trapping and manipulation, chip-scale atomic clocks, and integrated microwave circuits.

Highly Crumpled All-Carbon Transistors for Brain Activity Recording.

PubMed

Yang, Long; Zhao, Yan; Xu, Wenjing; Shi, Enzheng; Wei, Wenjing; Li, Xinming; Cao, Anyuan; Cao, Yanping; Fang, Ying

2017-01-11

Neural probes based on graphene field-effect transistors have been demonstrated. Yet, the minimum detectable signal of graphene transistor-based probes is inversely proportional to the square root of the active graphene area. This fundamentally limits the scaling of graphene transistor-based neural probes for improved spatial resolution in brain activity recording. Here, we address this challenge using highly crumpled all-carbon transistors formed by compressing down to 16% of its initial area. All-carbon transistors, chemically synthesized by seamless integration of graphene channels and hybrid graphene/carbon nanotube electrodes, maintained structural integrity and stable electronic properties under large mechanical deformation, whereas stress-induced cracking and junction failure occurred in conventional graphene/metal transistors. Flexible, highly crumpled all-carbon transistors were further verified for in vivo recording of brain activity in rats. These results highlight the importance of advanced material and device design concepts to make improvements in neuroelectronics.

The Dynamics of Eddy Fluxes and Jet-Scale Overturning Circulations and its Impact on the Mixed Layer Formation in the Indo-Western Pacific Southern Ocean

NASA Astrophysics Data System (ADS)

LI, Q.; Lee, S.

2016-12-01

The relationship between Antarctic Circumpolar Current (ACC) jets and eddy fluxes in the Indo-western Pacific Southern Ocean (90°E-145°E) is investigated using an eddy-resolving model. In this region, transient eddy momentum flux convergence occurs at the latitude of the primary jet core, whereas eddy buoyancy flux is located over a broader region that encompasses the jet and the inter-jet minimum. In a small sector (120°E-144°E) where jets are especially zonal, a spatial and temporal decomposition of the eddy fluxes further reveals that fast eddies act to accelerate the jet with the maximum eddy momentum flux convergence at the jet center, while slow eddies tend to decelerate the zonal current at the inter-jet minimum. Transformed Eulerian mean (TEM) diagnostics reveals that the eddy momentum contribution accelerates the jets at all model depths, whereas the buoyancy flux contribution decelerates the jets at depths below 600 m. In ocean sectors where the jets are relatively well defined, there exist jet-scale overturning circulations (JSOC) with sinking motion on the equatorward flank, and rising motion on the poleward flank of the jets. The location and structure of these thermally indirect circulations suggest that they are driven by the eddy momentum flux convergence, much like the Ferrel cell in the atmosphere. This study also found that the JSOC plays a significant role in the oceanic heat transport and that it also contributes to the formation of a thin band of mixed layer that exists on the equatorward flank of the Indo-western Pacific ACC jets.

Effects of spatial habitat heterogeneity on habitat selection and annual fecundity for a migratory forest songbird

USGS Publications Warehouse

Cornell, K.L.; Donovan, T.M.

2010-01-01

Understanding how spatial habitat patterns influence abundance and dynamics of animal populations is a primary goal in landscape ecology. We used an information-theoretic approach to investigate the association between habitat patterns at multiple spatial scales and demographic patterns for black-throated blue warblers (Dendroica caerulescens) at 20 study sites in west-central Vermont, USA from 2002 to 2005. Sites were characterized by: (1) territory-scale shrub density, (2) patch-scale shrub density occurring within 25 ha of territories, and (3) landscape-scale habitat patterns occurring within 5 km radius extents of territories. We considered multiple population parameters including abundance, age ratios, and annual fecundity. Territory-scale shrub density was most important for determining abundance and age ratios, but landscape-scale habitat structure strongly influenced reproductive output. Sites with higher territory-scale shrub density had higher abundance, and were more likely to be occupied by older, more experienced individuals compared to sites with lower shrub density. However, annual fecundity was higher on sites located in contiguously forested landscapes where shrub density was lower than the fragmented sites. Further, effects of habitat pattern at one spatial scale depended on habitat conditions at different scales. For example, abundance increased with increasing territory-scale shrub density, but this effect was much stronger in fragmented landscapes than in contiguously forested landscapes. These results suggest that habitat pattern at different spatial scales affect demographic parameters in different ways, and that effects of habitat patterns at one spatial scale depends on habitat conditions at other scales. ?? Springer Science+Business Media B.V. 2009.

On the subduction of oxygenated surface water in submesoscale cold filaments off Peru.

NASA Astrophysics Data System (ADS)

Thomsen, Soeren; Kanzow, Torsten; Colas, Francois; Echevin, Vincent; Krahmann, Gerd

2015-04-01

The Peruvian upwelling regime is characterized by pronounced submesoscale variability including filaments and sharp density fronts. Submesoscale frontal processes can drive large vertical velocities and enhance vertical tracer fluxes in the upper ocean. The associated high temporal and spatial variability poses a large challenge to observational approaches targeting submesoscale processes. In this study the role of submesoscale processes for both the ventilation of the near-coastal oxygen minimum zone off Peru and the physical-biogeochemical coupling at these scales is investigated. For our study we use satellite based sea surface temperature measurements in combination with multiple high-resolution glider observations of temperature, salinity, oxygen and chlorophyll fluorescence carried out in January and February 2013 off Peru near 14°S during active upwelling. Additionally, high-resolution regional ocean circulation model outputs (ROMS) are analysed. At the beginning of our observations a previously upwelled, productive and highly oxygenated body of water is found within the mixed layer. Subsequently, a cold filament forms and the waters are moved offshore. After the decay of the filament and the relaxation of the upwelling front, the oxygen enriched surface water is found within the previously less oxygenated thermocline suggesting the occurrence of frontal subduction. A numerical model simulation is used to analyse the evolution of passive tracers and Lagrangian floats within several upwelling filaments, whose vertical structure and hydrographic properties agree well with the observations. The simulated temporal evolution of the tracers and floats support our interpretation that the subduction of previously upwelled water indeed occurs within cold filaments off Peru. Filaments are common features within eastern boundary upwelling systems, which all encompass large oxygen minimum zones. However, most state of-the-art large and regional scale physical-biogeochemical ocean models do not resolve submesoscale filaments and the associated downward transport of oxygen and other solutes. Even if the observed subduction event only reaches into the still oxygenated thermocline the associated ventilation mechanism likely influences the shape and depth of the upper boundary of oxygen minimum zones, which would probably be even shallower without this process.

Design and implementation of a distributed large-scale spatial database system based on J2EE

NASA Astrophysics Data System (ADS)

Gong, Jianya; Chen, Nengcheng; Zhu, Xinyan; Zhang, Xia

2003-03-01

With the increasing maturity of distributed object technology, CORBA, .NET and EJB are universally used in traditional IT field. However, theories and practices of distributed spatial database need farther improvement in virtue of contradictions between large scale spatial data and limited network bandwidth or between transitory session and long transaction processing. Differences and trends among of CORBA, .NET and EJB are discussed in details, afterwards the concept, architecture and characteristic of distributed large-scale seamless spatial database system based on J2EE is provided, which contains GIS client application, web server, GIS application server and spatial data server. Moreover the design and implementation of components of GIS client application based on JavaBeans, the GIS engine based on servlet, the GIS Application server based on GIS enterprise JavaBeans(contains session bean and entity bean) are explained.Besides, the experiments of relation of spatial data and response time under different conditions are conducted, which proves that distributed spatial database system based on J2EE can be used to manage, distribute and share large scale spatial data on Internet. Lastly, a distributed large-scale seamless image database based on Internet is presented.

Precoded spatial multiplexing MIMO system with spatial component interleaver.

PubMed

Gao, Xiang; Wu, Zhanji

In this paper, the performance of precoded bit-interleaved coded modulation (BICM) spatial multiplexing multiple-input multiple-output (MIMO) system with spatial component interleaver is investigated. For the ideal precoded spatial multiplexing MIMO system with spatial component interleaver based on singular value decomposition (SVD) of the MIMO channel, the average pairwise error probability (PEP) of coded bits is derived. Based on the PEP analysis, the optimum spatial Q-component interleaver design criterion is provided to achieve the minimum error probability. For the limited feedback precoded proposed scheme with linear zero forcing (ZF) receiver, in order to minimize a bound on the average probability of a symbol vector error, a novel effective signal-to-noise ratio (SNR)-based precoding matrix selection criterion and a simplified criterion are proposed. Based on the average mutual information (AMI)-maximization criterion, the optimal constellation rotation angles are investigated. Simulation results indicate that the optimized spatial multiplexing MIMO system with spatial component interleaver can achieve significant performance advantages compared to the conventional spatial multiplexing MIMO system.

Two-decade reconstruction of algal blooms in China's Lake Taihu.

PubMed

Duan, Hongtao; Ma, Ronghua; Xu, Xiaofeng; Kong, Fanxiang; Zhang, Shouxuan; Kong, Weijuan; Hao, Jingyan; Shang, Linlin

2009-05-15

The algal blooming in the inland lakes has become a critically important issue for its impacts not only on local natural and social environments, but also on global human community. However, the occurrences of blooming on larger spatial scale and longer time scale have rarely been studied. As the third largest freshwater lake in China, Lake Taihu has drawn increasing attention from both public and scientific communities concerning its degradation. Using available satellite images, we reconstructed the spatial and temporal patterns of algal blooms in Lake Taihu through the pasttwo decades. The blooming characteristics over the past two decades were examined with the dynamic of initial blooming date being highlighted. The initial blooming dates were gradually becoming later and later from 1987 to 1997. Since 1998, however, the initial blooming date came earlier and earlier year by year, with approximately 11.42 days advancement per year. From 1987 to 2007, the annual duration of algal blooms lengthened year by year, in line with the substantial increases in the occurrences of algal blooms in spring and summer months. The algal blooms usually occur in northern bays and spread to center and south parts of Lake Taihu. The increases in previous winter's mean daily minimum temperature partially contributed to the earlier blooming onset. However, human activities, expressed as total gross domestic product (GDP) and population, outweighed the climatic contribution on the initial blooming date and blooming duration. This study may provide insights for the policy makers who try to curb the algal blooming and improve the water quality of inland freshwater lakes.

Catchment-Scale Conservation Units Identified for the Threatened Yarra Pygmy Perch (Nannoperca obscura) in Highly Modified River Systems

PubMed Central

Brauer, Chris J.; Unmack, Peter J.; Hammer, Michael P.; Adams, Mark; Beheregaray, Luciano B.

2013-01-01

Habitat fragmentation caused by human activities alters metapopulation dynamics and decreases biological connectivity through reduced migration and gene flow, leading to lowered levels of population genetic diversity and to local extinctions. The threatened Yarra pygmy perch, Nannoperca obscura, is a poor disperser found in small, isolated populations in wetlands and streams of southeastern Australia. Modifications to natural flow regimes in anthropogenically-impacted river systems have recently reduced the amount of habitat for this species and likely further limited its opportunity to disperse. We employed highly resolving microsatellite DNA markers to assess genetic variation, population structure and the spatial scale that dispersal takes place across the distribution of this freshwater fish and used this information to identify conservation units for management. The levels of genetic variation found for N. obscura are amongst the lowest reported for a fish species (mean heterozygosity of 0.318 and mean allelic richness of 1.92). We identified very strong population genetic structure, nil to little evidence of recent migration among demes and a minimum of 11 units for conservation management, hierarchically nested within four major genetic lineages. A combination of spatial analytical methods revealed hierarchical genetic structure corresponding with catchment boundaries and also demonstrated significant isolation by riverine distance. Our findings have implications for the national recovery plan of this species by demonstrating that N. obscura populations should be managed at a catchment level and highlighting the need to restore habitat and avoid further alteration of the natural hydrology. PMID:24349405

Snow depth spatial structure from hillslope to basin scale

NASA Astrophysics Data System (ADS)

Deems, J. S.

2017-12-01

Knowledge of spatial patterns of snow accumulation is required for understanding the hydrology, climatology, and ecology of mountain regions. Spatial structure in snow accumulation patterns changes with the scale of observation, a feature that has been characterized using fractal dimensions calculated from lidar-derived snow depth maps: fractal scaling structure at short length scales, with a `scale break' transition to more stochastic patterns at longer separation distances. Previous work has shown that this fractal structure of snow depth distributions differs between sites with different vegetation and terrain characteristics. Forested areas showed a transition to a nearly random spatial distribution at a much shorter lag distance than do unforested sites, enabling a statistical characterization. Alpine areas, however, showed strong spatial structure for a much wider scale range, and were the source of the dominant spatial pattern observable over a wider area. These spatial structure characteristics suggest that the choice of measurement or model resolution (satellite sensor, DEM, field survey point spacing, etc.) will strongly affect the estimates of snow volume or mass, as well as the magnitude of spatial variability. These prior efforts used data sets that were high resolution ( 1 m laser point spacing) but of limited extent ( 1 km2), constraining detection of scale features such as fractal dimension or scale breaks to areas of relatively similar characteristics and to lag distances of under 500 m. New datasets available from the NASA JPL Airborne Snow Observatory (ASO) provide similar resolution but over large areas, enabling assessment of snow spatial structure across an entire watershed, or in similar vegetation or physiography but in different parts of the basin. Additionally, the multi-year ASO time series allows an investigation into the temporal stability of these scale characteristics, within a single snow season and between seasons of strongly varying accumulation totals and patterns. This presentation will explore initial results from this study, using data from the Tuolumne River Basin in California, USA. Fractal scaling characteristics derived from ASO lidar snow depth measurements are examined at the basin scale, as well as in varying topographic and forest cover environments.

A dynamic-solver-consistent minimum action method: With an application to 2D Navier-Stokes equations

NASA Astrophysics Data System (ADS)

Wan, Xiaoliang; Yu, Haijun

2017-02-01

This paper discusses the necessity and strategy to unify the development of a dynamic solver and a minimum action method (MAM) for a spatially extended system when employing the large deviation principle (LDP) to study the effects of small random perturbations. A dynamic solver is used to approximate the unperturbed system, and a minimum action method is used to approximate the LDP, which corresponds to solving an Euler-Lagrange equation related to but more complicated than the unperturbed system. We will clarify possible inconsistencies induced by independent numerical approximations of the unperturbed system and the LDP, based on which we propose to define both the dynamic solver and the MAM on the same approximation space for spatial discretization. The semi-discrete LDP can then be regarded as the exact LDP of the semi-discrete unperturbed system, which is a finite-dimensional ODE system. We achieve this methodology for the two-dimensional Navier-Stokes equations using a divergence-free approximation space. The method developed can be used to study the nonlinear instability of wall-bounded parallel shear flows, and be generalized straightforwardly to three-dimensional cases. Numerical experiments are presented.

Spatial Analysis of Rice Blast in China at Three Different Scales.

PubMed

Guo, Fangfang; Chen, Xinglong; Lu, Minghong; Yang, Li; Wang, Shi Wei; Wu, Bo Ming

2018-05-22

In this study, spatial analyses were conducted at three different scales to better understand the epidemiology of rice blast, a major rice disease caused by Magnaporthe oryzae. At regional scale, across the major rice production regions in China, rice blast incidence was monitored on 101 dates at 193 stations from June 10 th to Sep. 10 th during 2009-2014, and surveyed in 143 fields in September, 2016; at county scale, 3 surveys were done covering 1-5 counties in 2015-2016; and at field scale, blast was evaluated in 6 fields in 2015-2016. Spatial cluster and hot spot analyses were conducted in GIS on the geographical pattern of the disease at regional scale, and geostatistical analysis performed at all the three scales. Cluster and hot spot analyses revealed that high-disease areas were clustered in mountainous areas in China. Geostatistical analyses detected spatial dependence of blast incidence with influence ranges of 399 to 1080 km at regional scale, and 5 to 10 m at field scale, but not at county scale. The spatial patterns at different scales might be determined by inherent properties of rice blast and environmental driving forces, and findings from this study provide helpful information to sampling and management of rice blast.

Optimization of a lensless digital holographic otoscope system for transient measurements of the human tympanic membrane

PubMed Central

Dobrev, I.; Furlong, C.; Cheng, J. T.; Rosowski, J. J.

2014-01-01

In this paper, we propose a multi-pulsed double exposure (MPDE) acquisition method to quantify in full-field-of-view the transient (i.e., >10 kHz) acoustically induced nanometer scale displacements of the human tympanic membrane (TM or eardrum). The method takes advantage of the geometrical linearity and repeatability of the TM displacements to enable high-speed measurements with a conventional camera (i.e., <20 fps). The MPDE is implemented on a previously developed digital holographic system (DHS) to enhance its measurement capabilities, at a minimum cost, while avoiding constraints imposed by the spatial resolutions and dimensions of high-speed (i.e., >50 kfps) cameras. To our knowledge, there is currently no existing system to provide such capabilities for the study of the human TM. The combination of high temporal (i.e., >50 kHz) and spatial (i.e., >500k data points) resolutions enables measurements of the temporal and frequency response of all points across the surface of the TM simultaneously. The repeatability and accuracy of the MPDE method are verified against a Laser Doppler Vibrometer (LDV) on both artificial membranes and ex-vivo human TMs that are acoustically excited with a sharp (i.e., <100 μs duration) click. The measuring capabilities of the DHS, enhanced by the MPDE acquisition method, allow for quantification of spatially dependent motion parameters of the TM, such as modal frequencies, time constants, as well as inferring local material properties. PMID:25780271

Spatial vulnerability of Australian urban populations to extreme heat events

NASA Astrophysics Data System (ADS)

Loughnan, Margaret; Tapper, Nigel; Phan, Thu; Lynch, Kellie; McInnes, Judith

2013-04-01

Extreme heat events pose a risk to the health of all individuals, especially the elderly and the chronically ill, and are associated with an increased demand for healthcare services. In order to address this problem, policy makers' need information about temperatures above which mortality and morbidity of the exposed population is likely to increase, where the vulnerable groups in the community are located, and how the risks from extreme heat events are likely to change in the future. This study identified threshold temperatures for all Australian capital cities, developed a spatial index of population vulnerability, and used climate model output to predict changes in the number of days exceeding temperature thresholds in the future, as well as changes in risk related to changes in urban density and an ageing population. The study has shown that daily maximum and minimum temperatures from the Bureau of Meteorology forecasts can be used to calculate temperature thresholds for heat alert days. The key risk factors related to adverse health outcomes were found to be areas with intense urban heat islands, areas with higher proportions of older people, and areas with ethnic communities. Maps of spatial vulnerability have been developed to provide information to assist emergency managers, healthcare professionals, and ancillary services develop heatwave preparedness plans at a local scale that target vulnerable groups and address heat-related health risks. The numbers of days exceeding current heat thresholds are predicted to increase over the next 20 to 40 years in all Australian capital cities.

Denitrification potential of riparian soils in relation to multiscale spatial environmental factors: a case study of a typical watershed, China.

PubMed

Wei, Jianbing; Feng, Hao; Cheng, Quanguo; Gao, Shiqian; Liu, Haiyan

2017-02-01

The objective of this study was to test the hypothesis that environmental regulators of riparian zone soil denitrification potential differ according to spatial scale within a watershed; consequently, a second objective was to provide spatial strategies for conserving and restoring the purification function of runoff in riparian ecosystems. The results show that soil denitrification in riparian zones was more heterogeneous at the profile scale than at the cross-section and landscape scales. At the profile scale, biogeochemical factors (including soil total organic carbon, total nitrogen, and nitrate-nitrogen) were the major direct regulators of the spatial distribution of soil denitrification enzyme activity (DEA). At the cross-section scale, factors included distance from river bank and vegetation density, while landscape-scale factors, including topographic index, elevation, and land use types, indirectly regulated the spatial distribution of DEA. At the profile scale, soil DEA was greatest in the upper soil layers. At the cross-section scale, maximum soil DEA occurred in the mid-part of the riparian zone. At the landscape scale, soil DEA showed an increasing trend towards downstream sites, except for those in urbanized areas.

Time-variant Lagrangian transport formulation reduces aggregation bias of water and solute mean travel time in heterogeneous catchments

NASA Astrophysics Data System (ADS)

Danesh-Yazdi, Mohammad; Botter, Gianluca; Foufoula-Georgiou, Efi

2017-05-01

Lack of hydro-bio-chemical data at subcatchment scales necessitates adopting an aggregated system approach for estimating water and solute transport properties, such as residence and travel time distributions, at the catchment scale. In this work, we show that within-catchment spatial heterogeneity, as expressed in spatially variable discharge-storage relationships, can be appropriately encapsulated within a lumped time-varying stochastic Lagrangian formulation of transport. This time (variability) for space (heterogeneity) substitution yields mean travel times (MTTs) that are not significantly biased to the aggregation of spatial heterogeneity. Despite the significant variability of MTT at small spatial scales, there exists a characteristic scale above which the MTT is not impacted by the aggregation of spatial heterogeneity. Extensive simulations of randomly generated river networks reveal that the ratio between the characteristic scale and the mean incremental area is on average independent of river network topology and the spatial arrangement of incremental areas.

[Spatial point patterns of Antarctic krill fishery in the northern Antarctic Peninsula].

PubMed

Yang, Xiao Ming; Li, Yi Xin; Zhu, Guo Ping

2016-12-01

As a key species in the Antarctic ecosystem, the spatial distribution of Antarctic krill (thereafter krill) often tends to present aggregation characteristics, which therefore reflects the spatial patterns of krill fishing operation. Based on the fishing data collected from Chinese krill fishing vessels, of which vessel A was professional krill fishing vessel and Vessel B was a fishing vessel which shifted between Chilean jack mackerel (Trachurus murphyi) fishing ground and krill fishing ground. In order to explore the characteristics of spatial distribution pattern and their ecological effects of two obvious different fishing fleets under a high and low nominal catch per unit effort (CPUE), from the viewpoint of spatial point pattern, the present study analyzed the spatial distribution characteristics of krill fishery in the northern Antarctic Peninsula from three aspects: (1) the two vessels' point pattern characteristics of higher CPUEs and lower CPUEs at different scales; (2) correlation of the bivariate point patterns between these points of higher CPUE and lower CPUE; and (3) correlation patterns of CPUE. Under the analysis derived from the Ripley's L function and mark correlation function, the results showed that the point patterns of the higher/lo-wer catch available were similar, both showing an aggregation distribution in this study windows at all scale levels. The aggregation intensity of krill fishing was nearly maximum at 15 km spatial scale, and kept stably higher values at the scale of 15-50 km. The aggregation intensity of krill fishery point patterns could be described in order as higher CPUE of vessel A > lower CPUE of vessel B >higher CPUE of vessel B > higher CPUE of vessel B. The relationship of the higher and lo-wer CPUEs of vessel A showed positive correlation at the spatial scale of 0-75 km, and presented stochastic relationship after 75 km scale, whereas vessel B showed positive correlation at all spatial scales. The point events of higher and lower CPUEs were synchronized, showing significant correlations at most of spatial scales because of the dynamics nature and complex of krill aggregation patterns. The distribution of vessel A's CPUEs was positively correlated at scales of 0-44 km, but negatively correlated at the scales of 44-80 km. The distribution of vessel B's CPUEs was negatively correlated at the scales of 50-70 km, but no significant correlations were found at other scales. The CPUE mark point patterns showed a negative correlation, which indicated that intraspecific competition for space and prey was significant. There were significant differences in spatial point pattern distribution between vessel A with higher fishing capacity and vessel B with lower fishing capacity. The results showed that the professional krill fishing vessel is suitable to conduct the analysis of spatial point pattern and scientific fishery survey.

Similar Processes but Different Environmental Filters for Soil Bacterial and Fungal Community Composition Turnover on a Broad Spatial Scale

PubMed Central

Chemidlin Prévost-Bouré, Nicolas; Dequiedt, Samuel; Thioulouse, Jean; Lelièvre, Mélanie; Saby, Nicolas P. A.; Jolivet, Claudy; Arrouays, Dominique; Plassart, Pierre; Lemanceau, Philippe; Ranjard, Lionel

2014-01-01

Spatial scaling of microorganisms has been demonstrated over the last decade. However, the processes and environmental filters shaping soil microbial community structure on a broad spatial scale still need to be refined and ranked. Here, we compared bacterial and fungal community composition turnovers through a biogeographical approach on the same soil sampling design at a broad spatial scale (area range: 13300 to 31000 km2): i) to examine their spatial structuring; ii) to investigate the relative importance of environmental selection and spatial autocorrelation in determining their community composition turnover; and iii) to identify and rank the relevant environmental filters and scales involved in their spatial variations. Molecular fingerprinting of soil bacterial and fungal communities was performed on 413 soils from four French regions of contrasting environmental heterogeneity (Landes

Similar processes but different environmental filters for soil bacterial and fungal community composition turnover on a broad spatial scale.

PubMed

Chemidlin Prévost-Bouré, Nicolas; Dequiedt, Samuel; Thioulouse, Jean; Lelièvre, Mélanie; Saby, Nicolas P A; Jolivet, Claudy; Arrouays, Dominique; Plassart, Pierre; Lemanceau, Philippe; Ranjard, Lionel

2014-01-01

Spatial scaling of microorganisms has been demonstrated over the last decade. However, the processes and environmental filters shaping soil microbial community structure on a broad spatial scale still need to be refined and ranked. Here, we compared bacterial and fungal community composition turnovers through a biogeographical approach on the same soil sampling design at a broad spatial scale (area range: 13300 to 31000 km2): i) to examine their spatial structuring; ii) to investigate the relative importance of environmental selection and spatial autocorrelation in determining their community composition turnover; and iii) to identify and rank the relevant environmental filters and scales involved in their spatial variations. Molecular fingerprinting of soil bacterial and fungal communities was performed on 413 soils from four French regions of contrasting environmental heterogeneity (Landes

Soil organic matter dynamics and CO2 fluxes in relation to landscape scale processes: linking process understanding to regional scale carbon mass-balances

NASA Astrophysics Data System (ADS)

Van Oost, Kristof; Nadeu, Elisabet; Wiaux, François; Wang, Zhengang; Stevens, François; Vanclooster, Marnik; Tran, Anh; Bogaert, Patrick; Doetterl, Sebastian; Lambot, Sébastien; Van wesemael, Bas

2014-05-01

In this paper, we synthesize the main outcomes of a collaborative project (2009-2014) initiated at the UCL (Belgium). The main objective of the project was to increase our understanding of soil organic matter dynamics in complex landscapes and use this to improve predictions of regional scale soil carbon balances. In a first phase, the project characterized the emergent spatial variability in soil organic matter storage and key soil properties at the regional scale. Based on the integration of remote sensing, geomorphological and soil analysis techniques, we quantified the temporal and spatial variability of soil carbon stock and pool distribution at the local and regional scales. This work showed a linkage between lateral fluxes of C in relation with sediment transport and the spatial variation in carbon storage at multiple spatial scales. In a second phase, the project focused on characterizing key controlling factors and process interactions at the catena scale. In-situ experiments of soil CO2 respiration showed that the soil carbon response at the catena scale was spatially heterogeneous and was mainly controlled by the catenary variation of soil physical attributes (soil moisture, temperature, C quality). The hillslope scale characterization relied on advanced hydrogeophysical techniques such as GPR (Ground Penetrating Radar), EMI (Electromagnetic induction), ERT (Electrical Resistivity Tomography), and geophysical inversion and data mining tools. Finally, we report on the integration of these insights into a coupled and spatially explicit model and its application. Simulations showed that C stocks and redistribution of mass and energy fluxes are closely coupled, they induce structured spatial and temporal patterns with non negligible attached uncertainties. We discuss the main outcomes of these activities in relation to sink-source behavior and relevance of erosion processes for larger-scale C budgets.

Floodplain complexity and surface metrics: influences of scale and geomorphology

USGS Publications Warehouse

Scown, Murray W.; Thoms, Martin C.; DeJager, Nathan R.

2015-01-01

Many studies of fluvial geomorphology and landscape ecology examine a single river or landscape, thus lack generality, making it difficult to develop a general understanding of the linkages between landscape patterns and larger-scale driving variables. We examined the spatial complexity of eight floodplain surfaces in widely different geographic settings and determined how patterns measured at different scales relate to different environmental drivers. Floodplain surface complexity is defined as having highly variable surface conditions that are also highly organised in space. These two components of floodplain surface complexity were measured across multiple sampling scales from LiDAR-derived DEMs. The surface character and variability of each floodplain were measured using four surface metrics; namely, standard deviation, skewness, coefficient of variation, and standard deviation of curvature from a series of moving window analyses ranging from 50 to 1000 m in radius. The spatial organisation of each floodplain surface was measured using spatial correlograms of the four surface metrics. Surface character, variability, and spatial organisation differed among the eight floodplains; and random, fragmented, highly patchy, and simple gradient spatial patterns were exhibited, depending upon the metric and window size. Differences in surface character and variability among the floodplains became statistically stronger with increasing sampling scale (window size), as did their associations with environmental variables. Sediment yield was consistently associated with differences in surface character and variability, as were flow discharge and variability at smaller sampling scales. Floodplain width was associated with differences in the spatial organization of surface conditions at smaller sampling scales, while valley slope was weakly associated with differences in spatial organisation at larger scales. A comparison of floodplain landscape patterns measured at different scales would improve our understanding of the role that different environmental variables play at different scales and in different geomorphic settings.

Determination of spatial scale of response unit for WASSI-C eco–hydrological model—a case study on the upper Zagunao River watershed of China

Treesearch

Ning Liu; Peng-Sen Sun; Shi-Rong Liu; Ge Sun

2013-01-01

Main publication is written in Chinese.Aims: Optimal spatial scale of hydrological response unit (HRU) is a precondition for eco-hydrological modeling as it is essential to improve accuracy. Our objective was to evaluate the spatial scale of HRU for application of the WASSSI-C model.Methods: We determined the best HRU scale for the eco-...

Zooming in on Spatial Scaling: Preschool Children and Adults Use Mental Transformations to Scale Spaces

ERIC Educational Resources Information Center

Möhring, Wenke; Newcombe, Nora S.; Frick, Andrea

2014-01-01

Spatial scaling is an important prerequisite for many spatial tasks and involves an understanding of how distances in different-sized spaces correspond. Previous studies have found evidence for such an understanding in preschoolers; however, the mental processes involved remain unclear. In the present study, we investigated whether children and…

FUEL3-D: A Spatially Explicit Fractal Fuel Distribution Model

Treesearch

Russell A. Parsons

2006-01-01

Efforts to quantitatively evaluate the effectiveness of fuels treatments are hampered by inconsistencies between the spatial scale at which fuel treatments are implemented and the spatial scale, and detail, with which we model fire and fuel interactions. Central to this scale inconsistency is the resolution at which variability within the fuel bed is considered. Crown...

Accuracy of Scale Conceptions in Science: Mental Maneuverings across Many Orders of Spatial Magnitude

ERIC Educational Resources Information Center

Tretter, Thomas R.; Jones, M. Gail; Minogue, James

2006-01-01

The use of unifying themes that span the various branches of science is recommended to enhance curricular coherence in science instruction. Conceptions of spatial scale are one such unifying theme. This research explored the accuracy of spatial scale conceptions of science phenomena across a spectrum of 215 participants: fifth grade, seventh…

Dynamic Positron Emission Tomography [PET] in Man Using Small Bismuth Germanate Crystals

DOE R&D Accomplishments Database

Derenzo, S. E.; Budinger, T. F.; Huesman, R. H.; Cahoon, J. L.

1982-04-01

Primary considerations for the design of positron emission tomographs for medical studies in humans are the need for high imaging sensitivity, whole organ coverage, good spatial resolution, high maximum data rates, adequate spatial sampling with minimum mechanical motion, shielding against out of plane activity, pulse height discrimination against scattered photons, and timing discrimination against accidental coincidences. We discuss the choice of detectors, sampling motion, shielding, and electronics to meet these objectives.

Species richness and biomass explain spatial turnover in ecosystem functioning across tropical and temperate ecosystems.

PubMed

Barnes, Andrew D; Weigelt, Patrick; Jochum, Malte; Ott, David; Hodapp, Dorothee; Haneda, Noor Farikhah; Brose, Ulrich

2016-05-19

Predicting ecosystem functioning at large spatial scales rests on our ability to scale up from local plots to landscapes, but this is highly contingent on our understanding of how functioning varies through space. Such an understanding has been hampered by a strong experimental focus of biodiversity-ecosystem functioning research restricted to small spatial scales. To address this limitation, we investigate the drivers of spatial variation in multitrophic energy flux-a measure of ecosystem functioning in complex communities-at the landscape scale. We use a structural equation modelling framework based on distance matrices to test how spatial and environmental distances drive variation in community energy flux via four mechanisms: species composition, species richness, niche complementarity and biomass. We found that in both a tropical and a temperate study region, geographical and environmental distance indirectly influence species richness and biomass, with clear evidence that these are the dominant mechanisms explaining variability in community energy flux over spatial and environmental gradients. Our results reveal that species composition and trait variability may become redundant in predicting ecosystem functioning at the landscape scale. Instead, we demonstrate that species richness and total biomass may best predict rates of ecosystem functioning at larger spatial scales. © 2016 The Author(s).

An Optical Flow-Based Full Reference Video Quality Assessment Algorithm.

PubMed

K, Manasa; Channappayya, Sumohana S

2016-06-01

We present a simple yet effective optical flow-based full-reference video quality assessment (FR-VQA) algorithm for assessing the perceptual quality of natural videos. Our algorithm is based on the premise that local optical flow statistics are affected by distortions and the deviation from pristine flow statistics is proportional to the amount of distortion. We characterize the local flow statistics using the mean, the standard deviation, the coefficient of variation (CV), and the minimum eigenvalue ( λ min ) of the local flow patches. Temporal distortion is estimated as the change in the CV of the distorted flow with respect to the reference flow, and the correlation between λ min of the reference and of the distorted patches. We rely on the robust multi-scale structural similarity index for spatial quality estimation. The computed temporal and spatial distortions, thus, are then pooled using a perceptually motivated heuristic to generate a spatio-temporal quality score. The proposed method is shown to be competitive with the state-of-the-art when evaluated on the LIVE SD database, the EPFL Polimi SD database, and the LIVE Mobile HD database. The distortions considered in these databases include those due to compression, packet-loss, wireless channel errors, and rate-adaptation. Our algorithm is flexible enough to allow for any robust FR spatial distortion metric for spatial distortion estimation. In addition, the proposed method is not only parameter-free but also independent of the choice of the optical flow algorithm. Finally, we show that the replacement of the optical flow vectors in our proposed method with the much coarser block motion vectors also results in an acceptable FR-VQA algorithm. Our algorithm is called the flow similarity index.

Factorial inferential grid grouping and representativeness analysis for a systematic selection of representative grids

NASA Astrophysics Data System (ADS)

Cheng, Guanhui; Huang, Guohe; Dong, Cong; Xu, Ye; Yao, Yao

2017-08-01

A factorial inferential grid grouping and representativeness analysis (FIGGRA) approach is developed to achieve a systematic selection of representative grids in large-scale climate change impact assessment and adaptation (LSCCIAA) studies and other fields of Earth and space sciences. FIGGRA is applied to representative-grid selection for temperature (Tas) and precipitation (Pr) over the Loess Plateau (LP) to verify methodological effectiveness. FIGGRA is effective at and outperforms existing grid-selection approaches (e.g., self-organizing maps) in multiple aspects such as clustering similar grids, differentiating dissimilar grids, and identifying representative grids for both Tas and Pr over LP. In comparison with Pr, the lower spatial heterogeneity and higher spatial discontinuity of Tas over LP lead to higher within-group similarity, lower between-group dissimilarity, lower grid grouping effectiveness, and higher grid representativeness; the lower interannual variability of the spatial distributions of Tas results in lower impacts of the interannual variability on the effectiveness of FIGGRA. For LP, the spatial climatic heterogeneity is the highest in January for Pr and in October for Tas; it decreases from spring, autumn, summer to winter for Tas and from summer, spring, autumn to winter for Pr. Two parameters, i.e., the statistical significance level (α) and the minimum number of grids in every climate zone (Nmin), and their joint effects are significant for the effectiveness of FIGGRA; normalization of a nonnormal climate-variable distribution is helpful for the effectiveness only for Pr. For FIGGRA-based LSCCIAA studies, a low value of Nmin is recommended for both Pr and Tas, and a high and medium value of α for Pr and Tas, respectively.

Uncertainty Assessment of the NASA Earth Exchange Global Daily Downscaled Climate Projections (NEX-GDDP) Dataset

NASA Technical Reports Server (NTRS)

Wang, Weile; Nemani, Ramakrishna R.; Michaelis, Andrew; Hashimoto, Hirofumi; Dungan, Jennifer L.; Thrasher, Bridget L.; Dixon, Keith W.

2016-01-01

The NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) dataset is comprised of downscaled climate projections that are derived from 21 General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 5 (CMIP5) and across two of the four greenhouse gas emissions scenarios (RCP4.5 and RCP8.5). Each of the climate projections includes daily maximum temperature, minimum temperature, and precipitation for the periods from 1950 through 2100 and the spatial resolution is 0.25 degrees (approximately 25 km x 25 km). The GDDP dataset has received warm welcome from the science community in conducting studies of climate change impacts at local to regional scales, but a comprehensive evaluation of its uncertainties is still missing. In this study, we apply the Perfect Model Experiment framework (Dixon et al. 2016) to quantify the key sources of uncertainties from the observational baseline dataset, the downscaling algorithm, and some intrinsic assumptions (e.g., the stationary assumption) inherent to the statistical downscaling techniques. We developed a set of metrics to evaluate downscaling errors resulted from bias-correction ("quantile-mapping"), spatial disaggregation, as well as the temporal-spatial non-stationarity of climate variability. Our results highlight the spatial disaggregation (or interpolation) errors, which dominate the overall uncertainties of the GDDP dataset, especially over heterogeneous and complex terrains (e.g., mountains and coastal area). In comparison, the temporal errors in the GDDP dataset tend to be more constrained. Our results also indicate that the downscaled daily precipitation also has relatively larger uncertainties than the temperature fields, reflecting the rather stochastic nature of precipitation in space. Therefore, our results provide insights in improving statistical downscaling algorithms and products in the future.

Spatial and temporal variation in vertical migration of dissolved 137Cs passed through the litter layer in Fukushima forests.

PubMed

Kurihara, Momo; Onda, Yuichi; Suzuki, Hiroyuki; Iwasaki, Yuichi; Yasutaka, Tetsuo

2018-05-26

We examined spatial variation in vertical 137 Cs flux from the litter layer using lysimeters combined with copper-substituted Prussian blue in two forests (deciduous broad-leaved and Japanese cedar (Cryptomeria japonica)), approximately 40 km northwest of the Fukushima Daiichi Nuclear power plant. The study ran from August 2016 to February 2017 in three periods; summer (10 Aug-4 Oct), autumn (5 Oct-30 Nov) and winter (1 Dec-27 Feb). Twenty-five and 15 lysimeters were installed in the deciduous broad-leaved and the Japanese cedar sites within 400 and 300 m 2 areas with 3-5 m intervals, respectively. The geometric means of the flux in the deciduous broad-leaved site were 0.51, 0.085 and 0.060 kBq/m 2 /month in summer, autumn and winter periods, respectively. In the Japanese cedar site, the mean fluxes were 0.45, 0.036 and 0.023 kBq/m 2 /month. The ratio of 137 Cs flux during the survey period to litter 137 Cs inventory was 6% and 1% on average in the deciduous broad-leaved and Japanese cedar sites, respectively. The 137 Cs flux in the summer period was much larger than those in other periods, resulting from higher precipitation in the summer. Our fine scale observation with 5 m interval showed very large spatial variation in the 137 Cs flux and the differences between maximum and minimum range from 8 to 104 times, but were mostly 20-25 times. The spatial variations in the 137 Cs flux were affected positively by those in the litter 137 Cs inventory and negatively by canopy openness. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Influence of the Magnitude and Spatial Distribution of Water Storage in Aquifers on the Character of Baseflow Recessions

NASA Astrophysics Data System (ADS)

Nieber, J. L.; Li, W.

2017-12-01

The instantaneous groundwater discharge (Qgw) from a watershed is related to volume of drainable water stored (Sgw) within the watershed aquifer(s). The relation is hysteretic and the magnitude of the hysteresis is completely scale-dependent. In the research reported here we apply a previously calibrated (USGS) GSFLOW model to the simulation of surface and subsurface runoff for the Sagehen Creek watershed. This 29.3 km2 watershed is located in the eastern range of the Sierra Nevada Mountains, and most of the precipitation falls in the form of snow. The GSFLOW model is composed of a surface water and shallow subsurface flow hydrology model, PRMS, and a groundwater flow component based on MODFLOW. PRMS is a semi-distributed watershed model, very similar in character to the well-known SWAT model. The PRMS model is coupled with the MODFLOW model in that deep percolation generated within the PRMS model feeds into the MODFLOW model. The simulated baseflow recessions, plotted as -dQ/dt vs Q, show a strong dependence to watershed topography and plot concave downward. These plots show a somewhat weaker dependence on the hydrologic fluxes of evapotranspiration and recharge, with the concave downward shape maintained but somewhat modified by these hydrologic fluxes. As expected the Qgw vs Sgw relation is markedly hysteretic. The cause for this hysteresis is related to the magnitude of water stored, and also the spatial distribution of water stored in the watershed, with the antecedent storage in upland areas controlling the recession flow in late time, while the valley area dominates the recession flow in the early time. Both the minimum streamflow (Qmin ; the flow at the transition between early time and late time uninterrupted recession) and the intercept (intercept of the regression line fit to the recession data on a log-log scale) show a strong relationship with antecedent streamflows. The minimum streamflow, Qmin, is found to be a valid normalizing parameter for producing a unique normalized -dQ/dt vs. Q relation from data manifesting the effects of hysteresis. It is proposed that this normalized relation can be used to improve the performance of low-dimension dynamic models of watershed hydrology that would otherwise not account for hysteresis in Qgw vs Sgw.

A Gridded Daily Min/Max Temperature Dataset With 0.1° Resolution for the Yangtze River Valley and its Error Estimation

NASA Astrophysics Data System (ADS)

Xiong, Qiufen; Hu, Jianglin

2013-05-01

The minimum/maximum (Min/Max) temperature in the Yangtze River valley is decomposed into the climatic mean and anomaly component. A spatial interpolation is developed which combines the 3D thin-plate spline scheme for climatological mean and the 2D Barnes scheme for the anomaly component to create a daily Min/Max temperature dataset. The climatic mean field is obtained by the 3D thin-plate spline scheme because the relationship between the decreases in Min/Max temperature with elevation is robust and reliable on a long time-scale. The characteristics of the anomaly field tend to be related to elevation variation weakly, and the anomaly component is adequately analyzed by the 2D Barnes procedure, which is computationally efficient and readily tunable. With this hybridized interpolation method, a daily Min/Max temperature dataset that covers the domain from 99°E to 123°E and from 24°N to 36°N with 0.1° longitudinal and latitudinal resolution is obtained by utilizing daily Min/Max temperature data from three kinds of station observations, which are national reference climatological stations, the basic meteorological observing stations and the ordinary meteorological observing stations in 15 provinces and municipalities in the Yangtze River valley from 1971 to 2005. The error estimation of the gridded dataset is assessed by examining cross-validation statistics. The results show that the statistics of daily Min/Max temperature interpolation not only have high correlation coefficient (0.99) and interpolation efficiency (0.98), but also the mean bias error is 0.00 °C. For the maximum temperature, the root mean square error is 1.1 °C and the mean absolute error is 0.85 °C. For the minimum temperature, the root mean square error is 0.89 °C and the mean absolute error is 0.67 °C. Thus, the new dataset provides the distribution of Min/Max temperature over the Yangtze River valley with realistic, successive gridded data with 0.1° × 0.1° spatial resolution and daily temporal scale. The primary factors influencing the dataset precision are elevation and terrain complexity. In general, the gridded dataset has a relatively high precision in plains and flatlands and a relatively low precision in mountainous areas.

Committed sea-level rise for the next century from Greenland ice sheet dynamics during the past decade

PubMed Central

Price, Stephen F.; Payne, Antony J.; Howat, Ian M.; Smith, Benjamin E.

2011-01-01

We use a three-dimensional, higher-order ice flow model and a realistic initial condition to simulate dynamic perturbations to the Greenland ice sheet during the last decade and to assess their contribution to sea level by 2100. Starting from our initial condition, we apply a time series of observationally constrained dynamic perturbations at the marine termini of Greenland’s three largest outlet glaciers, Jakobshavn Isbræ, Helheim Glacier, and Kangerdlugssuaq Glacier. The initial and long-term diffusive thinning within each glacier catchment is then integrated spatially and temporally to calculate a minimum sea-level contribution of approximately 1 ± 0.4 mm from these three glaciers by 2100. Based on scaling arguments, we extend our modeling to all of Greenland and estimate a minimum dynamic sea-level contribution of approximately 6 ± 2 mm by 2100. This estimate of committed sea-level rise is a minimum because it ignores mass loss due to future changes in ice sheet dynamics or surface mass balance. Importantly, > 75% of this value is from the long-term, diffusive response of the ice sheet, suggesting that the majority of sea-level rise from Greenland dynamics during the past decade is yet to come. Assuming similar and recurring forcing in future decades and a self-similar ice dynamical response, we estimate an upper bound of 45 mm of sea-level rise from Greenland dynamics by 2100. These estimates are constrained by recent observations of dynamic mass loss in Greenland and by realistic model behavior that accounts for both the long-term cumulative mass loss and its decay following episodic boundary forcing. PMID:21576500

Constraints on Water Reservoir Lifetimes From Catchment-Wide 10Be Erosion Rates—A Case Study From Western Turkey

NASA Astrophysics Data System (ADS)

Heineke, Caroline; Hetzel, Ralf; Akal, Cüneyt; Christl, Marcus

2017-11-01

The functionality and retention capacity of water reservoirs is generally impaired by upstream erosion and reservoir sedimentation, making a reliable assessment of erosion indispensable to estimate reservoir lifetimes. Widely used river gauging methods may underestimate sediment yield, because they do not record rare, high-magnitude events and may underestimate bed load transport. Hence, reservoir lifetimes calculated from short-term erosion rates should be regarded as maximum values. We propose that erosion rates from cosmogenic 10Be, which commonly integrate over hundreds to thousands of years, are useful to complement short-term sediment yield estimates and should be employed to estimate minimum reservoir lifetimes. Here we present 10Be erosion rates for the drainage basins of six water reservoirs in Western Turkey, which are located in a tectonically active region with easily erodible bedrock. Our 10Be erosion rates for these catchments are high, ranging from ˜170 to ˜1,040 t/km2/yr. When linked to reservoir volumes, they yield minimum reservoir lifetimes between 25 ± 5 and 1,650 ± 360 years until complete filling, with four reservoirs having minimum lifespans of ≤110 years. In a neighboring region with more resistant bedrock and less tectonic activity, we obtain much lower catchment-wide 10Be erosion rates of ˜33 to ˜95 t/km2/yr, illustrating that differences in lithology and tectonic boundary conditions can cause substantial variations in erosion even at a spatial scale of only ˜50 km. In conclusion, we suggest that both short-term sediment yield estimates and 10Be erosion rates should be employed to predict the lifetimes of reservoirs.

Committed sea-level rise for the next century from Greenland ice sheet dynamics during the past decade.

PubMed

Price, Stephen F; Payne, Antony J; Howat, Ian M; Smith, Benjamin E

2011-05-31

We use a three-dimensional, higher-order ice flow model and a realistic initial condition to simulate dynamic perturbations to the Greenland ice sheet during the last decade and to assess their contribution to sea level by 2100. Starting from our initial condition, we apply a time series of observationally constrained dynamic perturbations at the marine termini of Greenland's three largest outlet glaciers, Jakobshavn Isbræ, Helheim Glacier, and Kangerdlugssuaq Glacier. The initial and long-term diffusive thinning within each glacier catchment is then integrated spatially and temporally to calculate a minimum sea-level contribution of approximately 1 ± 0.4 mm from these three glaciers by 2100. Based on scaling arguments, we extend our modeling to all of Greenland and estimate a minimum dynamic sea-level contribution of approximately 6 ± 2 mm by 2100. This estimate of committed sea-level rise is a minimum because it ignores mass loss due to future changes in ice sheet dynamics or surface mass balance. Importantly, > 75% of this value is from the long-term, diffusive response of the ice sheet, suggesting that the majority of sea-level rise from Greenland dynamics during the past decade is yet to come. Assuming similar and recurring forcing in future decades and a self-similar ice dynamical response, we estimate an upper bound of 45 mm of sea-level rise from Greenland dynamics by 2100. These estimates are constrained by recent observations of dynamic mass loss in Greenland and by realistic model behavior that accounts for both the long-term cumulative mass loss and its decay following episodic boundary forcing.

The Effects of Spectral Nudging on Arctic Temperature and Precipitation Extremes as Produced by the Pan-Arctic WRF

NASA Astrophysics Data System (ADS)

Glisan, J. M.; Gutowski, W. J.; Higgins, M.; Cassano, J. J.

2011-12-01

Pan-Arctic WRF (PAW) simulations produced using the 50-km wr50a domain developed for the fully-coupled Regional Arctic Climate Model (RACM) were found to produce deep atmospheric circulation biases over the northern Pacific Ocean, manifested in pressure, geopotential height, and temperature fields. Various remedies were unsuccessfully tested to correct these large biases, such as modifying the physical domain or using different initial/boundary conditions. Spectral (interior) nudging was introduced as a way of constraining the model to be more consistent with observed behavior. However, such control over numerical model behavior raises concerns over how much nudging may affect unforced variability and extremes. Strong nudging may reduce or filter out extreme events, since the nudging pushes the model toward a relatively smooth, large-scale state. The question then becomes - what is the minimum spectral nudging needed to correct the biases occurring on the RACM domain while not limiting PAW simulation of extreme events? To determine this, case studies were devised, using a six-member PAW ensemble on the RACM grid with varying spectral nudging strength. Two simulations were run, one in the cold season (January 2007) and one in a warm season (July 2007). Precipitation and 2-m temperature fields were extracted from the output and analyzed to determine how changing spectral nudging strength impacts both temporal and spatial temperature and precipitation extremes. The maximum and minimum temperatures at each point from among the ensemble members were examined, on the 95th confidence interval. The maximum and minimums over the simulation period will also be considered. Results suggest that there is a marked lack of sensitivity to the degrees of nudging. Moreover, it appears nudging strength can be considerably smaller than the standard strength and still produce reliably good simulations.

Up, Down, and All Around: Scale-Dependent Spatial Variation in Rocky-Shore Communities of Fildes Peninsula, King George Island, Antarctica

PubMed Central

Valdivia, Nelson; Díaz, María J.; Holtheuer, Jorge; Garrido, Ignacio; Huovinen, Pirjo; Gómez, Iván

2014-01-01

Understanding the variation of biodiversity along environmental gradients and multiple spatial scales is relevant for theoretical and management purposes. Hereby, we analysed the spatial variability in diversity and structure of intertidal and subtidal macrobenthic Antarctic communities along vertical environmental stress gradients and across multiple horizontal spatial scales. Since biotic interactions and local topographic features are likely major factors for coastal assemblages, we tested the hypothesis that fine-scale processes influence the effects of the vertical environmental stress gradients on the macrobenthic diversity and structure. We used nested sampling designs in the intertidal and subtidal habitats, including horizontal spatial scales ranging from few centimetres to 1000s of metres along the rocky shore of Fildes Peninsula, King George Island. In both intertidal and subtidal habitats, univariate and multivariate analyses showed a marked vertical zonation in taxon richness and community structure. These patterns depended on the horizontal spatial scale of observation, as all analyses showed a significant interaction between height (or depth) and the finer spatial scale analysed. Variance and pseudo-variance components supported our prediction for taxon richness, community structure, and the abundance of dominant species such as the filamentous green alga Urospora penicilliformis (intertidal), the herbivore Nacella concinna (intertidal), the large kelp-like Himantothallus grandifolius (subtidal), and the red crustose red alga Lithothamnion spp. (subtidal). We suggest that in coastal ecosystems strongly governed by physical factors, fine-scale processes (e.g. biotic interactions and refugia availability) are still relevant for the structuring and maintenance of the local communities. The spatial patterns found in this study serve as a necessary benchmark to understand the dynamics and adaptation of natural assemblages in response to observed and predicted environmental changes in Antarctica. PMID:24956114

Spatial Structure of a Braided River: Metric Resolution Hydrodynamic Modeling Reveals What SWOT Might See

NASA Astrophysics Data System (ADS)

Schubert, J.; Sanders, B. F.; Andreadis, K.

2013-12-01

The Surface Water and Ocean Topography (SWOT) mission, currently under study by NASA (National Aeronautics and Space Administration) and CNES (Centre National d'Etudes Spatiales), is designed to provide global spatial measurements of surface water properties at resolutions better than 10 m and with centimetric accuracy. The data produced by SWOT will include irregularly spaced point clouds of the water surface height, with point spacings from roughly 2-50 m depending on a point's location within SWOT's swath. This could offer unprecedented insight into the spatial structure of rivers. Features that may be resolved include backwater profiles behind dams, drawdown profiles, uniform flow sections, critical flow sections, and even riffle-pool flow structures. In the event that SWOT scans a river during a major flood, it becomes possible to delineate the limits of the flood as well as the spatial structure of the water surface elevation, yielding insight into the dynamic interaction of channels and flood plains. The Platte River in Nebraska, USA, is a braided river with a width and slope of approximately 100 m and 100 cm/km, respectively. A 1 m resolution Digital Terrain Model (DTM) of the river basin, based on airborne lidar collected during low-flow conditions, was used to parameterize a two-dimensional, variable resolution, unstructured grid, hydrodynamic model that uses 3 m resolution triangles in low flow channels and 10 m resolution triangles in the floodplain. Use of a fine resolution mesh guarantees that local variability in topography is resolved, and after applying the hydrodynamic model, the effects of topographic variability are expressed as variability in the water surface height, depth-averaged velocity and flow depth. Flow is modeled over a reach length of 10 km for multi-day durations to capture both frequent (diurnal variations associated with regulated flow) and infrequent (extreme flooding) flow phenomena. Model outputs reveal a number of interesting features, including a high degree of variability in the water depth and velocity and lesser variability in the free-surface profile and river discharge. Hydraulic control sections are also revealed, and shown to depend on flow stage. Reach-averaging of model output is applied to study the macro-scale balance of forces in this system, and the scales at which such a force balance is appropriate. We find that the reach-average slope exhibits a declining reach-length dependence with increasing reach length, up to reach lengths of 1 km. Hence, 1 km appears to be the minimum appropriate length for reach-averaging, and at this scale, a diffusive-wave momentum balance is a reasonable approximation suitable for emerging models of discharge estimation that rely only on SWOT-observable river properties (width, height, slope, etc.).

Toward long-lead operational forecasts of drought: An experimental study in the Murray-Darling River Basin

NASA Astrophysics Data System (ADS)

Barros, Ana P.; Bowden, Gavin J.

2008-08-01

SummaryResiliency and effectiveness in water resources management of drought is strongly depend on advanced knowledge of drought onset, duration and severity. The motivation of this work is to extend the lead time of operational drought forecasts. The research strategy is to explore the predictability of drought severity from space-time varying indices of large-scale climate phenomena relevant to regional hydrometeorology (e.g. ENSO) by integrating linear and non-linear statistical data models, specifically self-organizing maps (SOM) and multivariate linear regression analysis. The methodology is demonstrated through the step-by-step development of a model to forecast monthly spatial patterns of the standard precipitation index (SPI) within the Murray-Darling Basin (MDB) in Australia up to 12 months in advance. First, the rationale for the physical hypothesis and the exploratory data analysis including principal components, wavelet and partial mutual information analysis to identify and select predictor variables are presented. The focus is on spatial datasets of precipitation, sea surface temperature anomaly (SSTA) patterns over the Indian and Pacific Oceans, temporal and spatial gradients of outgoing longwave radiation (OLR) in the Pacific Ocean, and the far western Pacific wind-stress anomaly. Second, the process of model construction, calibration and evaluation is described. The experimental forecasts show that there is ample opportunity to increase the lead time of drought forecasts for decision support using parsimonious data models that capture the governing climate processes at regional scale. OLR gradients proved to be dispensable predictors, whereas SPI-based predictors appear to control predictability when the SSTA in the region [87.5°N-87.5°S; 27.5°E-67.5°W] and eastward wind-stress anomalies in the region [4°N-4°S; 130°E-160°E) are small, respectively, ±1° and ±0.01 dyne/cm 2, that is when ENSO activity is weak. The areal averaged 12-month lead-time forecasts of SPI in the MDB explain up to 60% of the variance in the observations ( r > 0.7). Based on a threshold SPI of -0.5 for severe drought at the regional scale and for a nominal 12-month lead time, the forecast of the timing of onset is within 0-2 months of the actual threshold being met by the observations, thus effectively a 10-month lead time forecast at a minimum. Spatial analysis suggests that forecast errors can be attributed in part to a mismatch between the spatial heterogeneity of rainfall and raingauge density in the observational network. Forecast uncertainty on the other hand appears associated with the number of redundant predictors used in the forecast model.

Spatial outline of malaria transmission in Iran.

PubMed

Barati, Mohammad; Keshavarz-valian, Hossein; Habibi-nokhandan, Majid; Raeisi, Ahmad; Faraji, Leyla; Salahi-moghaddam, Abdoreza

2012-10-01

To conduct for modeling spatial distribution of malaria transmission in Iran. Records of all malaria cases from the period 2008-2010 in Iran were retrieved for malaria control department, MOH&ME. Metrological data including annual rainfall, maximum and minimum temperature, relative humidity, altitude, demographic, districts border shapefiles, and NDVI images received from Iranian Climatologic Research Center. Data arranged in ArcGIS. 99.65% of malaria transmission cases were focused in southeast part of Iran. These transmissions had statistically correlation with altitude (650 m), maximum (30 °C), minimum (20 °C) and average temperature (25.3 °C). Statistical correlation and overall relationship between NDVI (118.81), relative humidity (⩾45%) and rainfall in southeast area was defined and explained in this study. According to ecological condition and mentioned cut-off points, predictive map was generated using cokriging method. Copyright © 2012 Hainan Medical College. Published by Elsevier B.V. All rights reserved.

On the functional optimization of a certain class of nonstationary spatial functions

USGS Publications Warehouse

Christakos, G.; Paraskevopoulos, P.N.

1987-01-01

Procedures are developed in order to obtain optimal estimates of linear functionals for a wide class of nonstationary spatial functions. These procedures rely on well-established constrained minimum-norm criteria, and are applicable to multidimensional phenomena which are characterized by the so-called hypothesis of inherentity. The latter requires elimination of the polynomial, trend-related components of the spatial function leading to stationary quantities, and also it generates some interesting mathematics within the context of modelling and optimization in several dimensions. The arguments are illustrated using various examples, and a case study computed in detail. ?? 1987 Plenum Publishing Corporation.

Scaling Properties of Arctic Sea Ice Deformation in a High‐Resolution Viscous‐Plastic Sea Ice Model and in Satellite Observations

PubMed Central

Losch, Martin; Menemenlis, Dimitris

2018-01-01

Abstract Sea ice models with the traditional viscous‐plastic (VP) rheology and very small horizontal grid spacing can resolve leads and deformation rates localized along Linear Kinematic Features (LKF). In a 1 km pan‐Arctic sea ice‐ocean simulation, the small‐scale sea ice deformations are evaluated with a scaling analysis in relation to satellite observations of the Envisat Geophysical Processor System (EGPS) in the Central Arctic. A new coupled scaling analysis for data on Eulerian grids is used to determine the spatial and temporal scaling and the coupling between temporal and spatial scales. The spatial scaling of the modeled sea ice deformation implies multifractality. It is also coupled to temporal scales and varies realistically by region and season. The agreement of the spatial scaling with satellite observations challenges previous results with VP models at coarser resolution, which did not reproduce the observed scaling. The temporal scaling analysis shows that the VP model, as configured in this 1 km simulation, does not fully resolve the intermittency of sea ice deformation that is observed in satellite data. PMID:29576996

Scaling Properties of Arctic Sea Ice Deformation in a High-Resolution Viscous-Plastic Sea Ice Model and in Satellite Observations

NASA Astrophysics Data System (ADS)

Hutter, Nils; Losch, Martin; Menemenlis, Dimitris

2018-01-01

Sea ice models with the traditional viscous-plastic (VP) rheology and very small horizontal grid spacing can resolve leads and deformation rates localized along Linear Kinematic Features (LKF). In a 1 km pan-Arctic sea ice-ocean simulation, the small-scale sea ice deformations are evaluated with a scaling analysis in relation to satellite observations of the Envisat Geophysical Processor System (EGPS) in the Central Arctic. A new coupled scaling analysis for data on Eulerian grids is used to determine the spatial and temporal scaling and the coupling between temporal and spatial scales. The spatial scaling of the modeled sea ice deformation implies multifractality. It is also coupled to temporal scales and varies realistically by region and season. The agreement of the spatial scaling with satellite observations challenges previous results with VP models at coarser resolution, which did not reproduce the observed scaling. The temporal scaling analysis shows that the VP model, as configured in this 1 km simulation, does not fully resolve the intermittency of sea ice deformation that is observed in satellite data.

Scaling Properties of Arctic Sea Ice Deformation in a High-Resolution Viscous-Plastic Sea Ice Model and in Satellite Observations.

PubMed

Hutter, Nils; Losch, Martin; Menemenlis, Dimitris

2018-01-01

Sea ice models with the traditional viscous-plastic (VP) rheology and very small horizontal grid spacing can resolve leads and deformation rates localized along Linear Kinematic Features (LKF). In a 1 km pan-Arctic sea ice-ocean simulation, the small-scale sea ice deformations are evaluated with a scaling analysis in relation to satellite observations of the Envisat Geophysical Processor System (EGPS) in the Central Arctic. A new coupled scaling analysis for data on Eulerian grids is used to determine the spatial and temporal scaling and the coupling between temporal and spatial scales. The spatial scaling of the modeled sea ice deformation implies multifractality. It is also coupled to temporal scales and varies realistically by region and season. The agreement of the spatial scaling with satellite observations challenges previous results with VP models at coarser resolution, which did not reproduce the observed scaling. The temporal scaling analysis shows that the VP model, as configured in this 1 km simulation, does not fully resolve the intermittency of sea ice deformation that is observed in satellite data.

Genetic structuring of northern myotis (Myotis septentrionalis) at multiple spatial scales

USGS Publications Warehouse

Johnson, Joshua B.; Roberts, James H.; King, Timothy L.; Edwards, John W.; Ford, W. Mark; Ray, David A.

2014-01-01

Although groups of bats may be genetically distinguishable at large spatial scales, the effects of forest disturbances, particularly permanent land use conversions on fine-scale population structure and gene flow of summer aggregations of philopatric bat species are less clear. We genotyped and analyzed variation at 10 nuclear DNA microsatellite markers in 182 individuals of the forest-dwelling northern myotis (Myotis septentrionalis) at multiple spatial scales, from within first-order watersheds scaling up to larger regional areas in West Virginia and New York. Our results indicate that groups of northern myotis were genetically indistinguishable at any spatial scale we considered, and the collective population maintained high genetic diversity. It is likely that the ability to migrate, exploit small forest patches, and use networks of mating sites located throughout the Appalachian Mountains, Interior Highlands, and elsewhere in the hibernation range have allowed northern myotis to maintain high genetic diversity and gene flow regardless of forest disturbances at local and regional spatial scales. A consequence of maintaining high gene flow might be the potential to minimize genetic founder effects following population declines caused currently by the enzootic White-nose Syndrome.

Point sensitive NMR imaging system using a magnetic field configuration with a spatial minimum

DOEpatents

Eberhard, P.H.

A point-sensitive NMR imaging system in which a main solenoid coil produces a relatively strong and substantially uniform magnetic field and a pair of perturbing coils powered by current in the same direction superimposes a pair of relatively weak perturbing fields on the main field to produce a resultant point of minimum field strength at a desired location in a direction along the Z-axis. Two other pairs of perturbing coils superimpose relatively weak field gradients on the main field in directions along the X- and Y-axes to locate the minimum field point at a desired location in a plane normal to the Z-axes. An rf generator irradiates a tissue specimen in the field with radio frequency energy so that desired nuclei in a small volume at the point of minimum field strength will resonate.

Spatial connections in regional climate model rainfall outputs at different temporal scales: Application of network theory

NASA Astrophysics Data System (ADS)

Naufan, Ihsan; Sivakumar, Bellie; Woldemeskel, Fitsum M.; Raghavan, Srivatsan V.; Vu, Minh Tue; Liong, Shie-Yui

2018-01-01

Understanding the spatial and temporal variability of rainfall has always been a great challenge, and the impacts of climate change further complicate this issue. The present study employs the concepts of complex networks to study the spatial connections in rainfall, with emphasis on climate change and rainfall scaling. Rainfall outputs (during 1961-1990) from a regional climate model (i.e. Weather Research and Forecasting (WRF) model that downscaled the European Centre for Medium-range Weather Forecasts, ECMWF ERA-40 reanalyses) over Southeast Asia are studied, and data corresponding to eight different temporal scales (6-hr, 12-hr, daily, 2-day, 4-day, weekly, biweekly, and monthly) are analyzed. Two network-based methods are applied to examine the connections in rainfall: clustering coefficient (a measure of the network's local density) and degree distribution (a measure of the network's spread). The influence of rainfall correlation threshold (T) on spatial connections is also investigated by considering seven different threshold levels (ranging from 0.5 to 0.8). The results indicate that: (1) rainfall networks corresponding to much coarser temporal scales exhibit properties similar to that of small-world networks, regardless of the threshold; (2) rainfall networks corresponding to much finer temporal scales may be classified as either small-world networks or scale-free networks, depending upon the threshold; and (3) rainfall spatial connections exhibit a transition phase at intermediate temporal scales, especially at high thresholds. These results suggest that the most appropriate model for studying spatial connections may often be different at different temporal scales, and that a combination of small-world and scale-free network models might be more appropriate for rainfall upscaling/downscaling across all scales, in the strict sense of scale-invariance. The results also suggest that spatial connections in the studied rainfall networks in Southeast Asia are weak, especially when more stringent conditions are imposed (i.e. when T is very high), except at the monthly scale.

Impact of asymmetry in the total ozone distribution in Antarctic region to the South Ocean ecosystem

NASA Astrophysics Data System (ADS)

Kovalenok, S.; Evtushevsky, A.; Grytsai, A.; Milinevsky, G.

2009-04-01

Impact of asymmetry in the total ozone distribution in Antarctic region to South Ocean ecosystem is studied. The existence of the considerable zonal asymmetry in total ozone distribution over Antarctica observed last decades based on the satellite TOMS measurements in 1979-2005 due to existence of quasi-stationary planetary waves in a polar stratosphere. As was shown by authors earlier in the latitudinal interval of 55-75°S in Antarctic spring months (Sep-Nov) the region of zonal total ozone minimum experienced the systematic spatial drift to the east. In the same period a minimum and maximum of quasi-stationary wave in TOC distribution are located: minimum over the Antarctic Peninsula and Weddell Sea area, and maximum in the Ross Sea area. We expect that zonal asymmetry in total ozone distribution and its long-term spatial changes should impact to South Ocean ecosystem food chain, especially in primary level. The systematic eastern shift of the quasi-stationary minimum in ozone distribution over north Weddell Sea area should cause the increased UV radiation on sea surface in comparison to Ross Sea area, where the lack of UVR should exist in spring month. To study this influence the available data of phytoplankton distribution in South Ocean in 1997-2007 were analyzed. The results of analysis in connections with Antarctic Peninsula regional climate warming are discussed. The research was partly supported by project 06BF051-12 of the National Taras Shevchenko University of Kyiv.

Forest loss maps from regional satellite monitoring systematically underestimate deforestation in two rapidly changing parts of the Amazon

NASA Astrophysics Data System (ADS)

Milodowski, D. T.; Mitchard, E. T. A.; Williams, M.

2017-09-01

Accurate, consistent reporting of changing forest area, stratified by forest type, is required for all countries under their commitments to the Paris Agreement (UNFCCC 2015 Adoption of the Paris Agreement (Paris: UNFCCC)). Such change reporting may directly impact on payments through comparisons to national Reference (Emissions) Levels under the Reducing Emissions from Deforestation and forest Degradation (REDD+) framework. The emergence of global, satellite-based forest monitoring systems, including Global Forest Watch (GFW) and FORMA, have great potential in aiding this endeavour. However, the accuracy of these systems has been questioned and their uncertainties are poorly constrained, both in terms of the spatial extent of forest loss and timing of change. Here, using annual time series of 5 m optical imagery at two sites in the Brazilian Amazon, we demonstrate that GFW more accurately detects forest loss than the coarser-resolution FORMA or Brazil’s national-level PRODES product, though all underestimate the rate of loss. We conclude GFW provides robust indicators of forest loss, at least for larger-scale forest change, but under-predicts losses driven by small-scale disturbances (< 2 ha), even though these are much larger than its minimum mapping unit (0.09 ha).

Forest loss maps from regional satellite monitoring systematically underestimate deforestation in two rapidly changing parts of the Amazon

NASA Astrophysics Data System (ADS)

Milodowski, D. T.; Mitchard, E. T. A.; Williams, M.

2016-09-01

Accurate, consistent reporting of changing forest area, stratified by forest type, is required for all countries under their commitments to the Paris Agreement (UNFCCC 2015 Adoption of the Paris Agreement (Paris: UNFCCC)). Such change reporting may directly impact on payments through comparisons to national Reference (Emissions) Levels under the Reducing Emissions from Deforestation and forest Degradation (REDD+) framework. The emergence of global, satellite-based forest monitoring systems, including Global Forest Watch (GFW) and FORMA, have great potential in aiding this endeavour. However, the accuracy of these systems has been questioned and their uncertainties are poorly constrained, both in terms of the spatial extent of forest loss and timing of change. Here, using annual time series of 5 m optical imagery at two sites in the Brazilian Amazon, we demonstrate that GFW more accurately detects forest loss than the coarser-resolution FORMA or Brazil’s national-level PRODES product, though all underestimate the rate of loss. We conclude GFW provides robust indicators of forest loss, at least for larger-scale forest change, but under-predicts losses driven by small-scale disturbances (< 2 ha), even though these are much larger than its minimum mapping unit (0.09 ha).

Mapping of heavy metal pollution in river water at daily time-scale using spatio-temporal fusion of MODIS-aqua and Landsat satellite imageries.

PubMed

Swain, Ratnakar; Sahoo, Bhabagrahi

2017-05-01

For river water quality monitoring at 30m × 1-day spatio-temporal scales, a spatial and temporal adaptive reflectance fusion model (STARFM) is developed for estimating turbidity (T u ), total suspended solid (TSS), and six heavy metals (HV) of iron, zinc, copper, chromium, lead and cadmium, by blending the Moderate-Resolution Imaging Spectroradiometer (MODIS) and Landsat (L s ) spectral bands. A combination of regression analysis and genetic algorithm (GA) techniques are applied to develop spectral relationships between T u -L s , TSS-T u , and each HV-TSS. The STARFM algorithm and all the developed relationship models are evaluated satisfactorily by various performance evaluation measures to develop heavy metal pollution index-based vulnerability maps at 1-km resolution in the Brahmani River in eastern India. The Monte-Carlo simulation based analysis of the developed formulations reveals that the uncertainty in estimating Zn and Cd is the minimum (1.04%) and the maximum (5.05%), respectively. Hence, the remote sensing based approach developed herein can effectively be used in many world rivers for real-time monitoring of heavy metal pollution. Copyright © 2017 Elsevier Ltd. All rights reserved.

Transmitted light microscopy for visualizing the turbulent primary breakup of a microscale liquid jet

NASA Astrophysics Data System (ADS)

Reddemann, Manuel A.; Mathieu, Florian; Kneer, Reinhold

2013-11-01

Aiming at a maximum spatial resolution and a minimum motion blur, a new simple double-imaging transmitted light microscopy technique is developed in this work enabling a fundamental investigation of primary breakup of a microscale liquid jet. Contrary to conventional far-field visualization techniques, the working distance is minimized to increase the numerical aperture. The resulting images provide information about shapes, length scales and velocities of primary liquid structures. The method is applied to an optically dense spray leaving a 109-μm diesel nozzle at various injection pressures under atmospheric conditions. A phenomenological study on the temporal spray evolution is done with focus on droplet and ligament formation. Different breakup processes are identified and described. It is found that the jet is characterized by long ligaments parallel or angular to the inner jet region. These ligaments result from collapsing films developing at the spray edge. A significant influence of outlet velocity variation on shape and velocity of these ligaments is observed. The experimental results prove that a transmitted light microscopy technique with reduced working distance is an appropriate tool for a better understanding of primary breakup for small-scaled diesel nozzles and a valuable complement to highly complex measurement techniques.

Toward an operational framework for fine-scale urban land-cover mapping in Wallonia using submeter remote sensing and ancillary vector data

NASA Astrophysics Data System (ADS)

Beaumont, Benjamin; Grippa, Tais; Lennert, Moritz; Vanhuysse, Sabine; Stephenne, Nathalie; Wolff, Eléonore

2017-07-01

Encouraged by the EU INSPIRE directive requirements and recommendations, the Walloon authorities, similar to other EU regional or national authorities, want to develop operational land-cover (LC) and land-use (LU) mapping methods using existing geodata. Urban planners and environmental monitoring stakeholders of Wallonia have to rely on outdated, mixed, and incomplete LC and LU information. The current reference map is 10-years old. The two object-based classification methods, i.e., a rule- and a classifier-based method, for detailed regional urban LC mapping are compared. The added value of using the different existing geospatial datasets in the process is assessed. This includes the comparison between satellite and aerial optical data in terms of mapping accuracies, visual quality of the map, costs, processing, data availability, and property rights. The combination of spectral, tridimensional, and vector data provides accuracy values close to 0.90 for mapping the LC into nine categories with a minimum mapping unit of 15 m2. Such a detailed LC map offers opportunities for fine-scale environmental and spatial planning activities. Still, the regional application poses challenges regarding automation, big data handling, and processing time, which are discussed.

The observable signature of late heating of the Universe during cosmic reionization.

PubMed

Fialkov, Anastasia; Barkana, Rennan; Visbal, Eli

2014-02-13

Models and simulations of the epoch of reionization predict that spectra of the 21-centimetre transition of atomic hydrogen will show a clear fluctuation peak, at a redshift and scale, respectively, that mark the central stage of reionization and the characteristic size of ionized bubbles. This is based on the assumption that the cosmic gas was heated by stellar remnants-particularly X-ray binaries-to temperatures well above the cosmic microwave background at that time (about 30 kelvin). Here we show instead that the hard spectra (that is, spectra with more high-energy photons than low-energy photons) of X-ray binaries make such heating ineffective, resulting in a delayed and spatially uniform heating that modifies the 21-centimetre signature of reionization. Rather than looking for a simple rise and fall of the large-scale fluctuations (peaking at several millikelvin), we must expect a more complex signal also featuring a distinct minimum (at less than a millikelvin) that marks the rise of the cosmic mean gas temperature above the microwave background. Observing this signal, possibly with radio telescopes in operation today, will demonstrate the presence of a cosmic background of hard X-rays at that early time.

Polarization transformation as an algorithm for automatic generalization and quality assessment

NASA Astrophysics Data System (ADS)

Qian, Haizhong; Meng, Liqiu

2007-06-01

Since decades it has been a dream of cartographers to computationally mimic the generalization processes in human brains for the derivation of various small-scale target maps or databases from a large-scale source map or database. This paper addresses in a systematic way the polarization transformation (PT) - a new algorithm that serves both the purpose of automatic generalization of discrete features and the quality assurance. By means of PT, two dimensional point clusters or line networks in the Cartesian system can be transformed into a polar coordinate system, which then can be unfolded as a single spectrum line r = f(α), where r and a stand for the polar radius and the polar angle respectively. After the transformation, the original features will correspond to nodes on the spectrum line delimited between 0° and 360° along the horizontal axis, and between the minimum and maximum polar radius along the vertical axis. Since PT is a lossless transformation, it allows a straighforward analysis and comparison of the original and generalized distributions, thus automatic generalization and quality assurance can be down in this way. Examples illustrate that PT algorithm meets with the requirement of generalization of discrete spatial features and is more scientific.

Factors Driving Potential Ammonia Oxidation in Canadian Arctic Ecosystems: Does Spatial Scale Matter?

PubMed Central

Banerjee, Samiran

2012-01-01

Ammonia oxidation is a major process in nitrogen cycling, and it plays a key role in nitrogen limited soil ecosystems such as those in the arctic. Although mm-scale spatial dependency of ammonia oxidizers has been investigated, little is known about the field-scale spatial dependency of aerobic ammonia oxidation processes and ammonia-oxidizing archaeal and bacterial communities, particularly in arctic soils. The purpose of this study was to explore the drivers of ammonia oxidation at the field scale in cryosols (soils with permafrost within 1 m of the surface). We measured aerobic ammonia oxidation potential (both autotrophic and heterotrophic) and functional gene abundance (bacterial amoA and archaeal amoA) in 279 soil samples collected from three arctic ecosystems. The variability associated with quantifying genes was substantially less than the spatial variability observed in these soils, suggesting that molecular methods can be used reliably evaluate spatial dependency in arctic ecosystems. Ammonia-oxidizing archaeal and bacterial communities and aerobic ammonia oxidation were spatially autocorrelated. Gene abundances were spatially structured within 4 m, whereas biochemical processes were structured within 40 m. Ammonia oxidation was driven at small scales (<1m) by moisture and total organic carbon, whereas gene abundance and other edaphic factors drove ammonia oxidation at medium (1 to 10 m) and large (10 to 100 m) scales. In these arctic soils heterotrophs contributed between 29 and 47% of total ammonia oxidation potential. The spatial scale for aerobic ammonia oxidation genes differed from potential ammonia oxidation, suggesting that in arctic ecosystems edaphic, rather than genetic, factors are an important control on ammonia oxidation. PMID:22081570

Spatial synchrony of local populations has increased in association with the recent Northern Hemisphere climate trend.

PubMed

Post, Eric; Forchhammer, Mads C

2004-06-22

According to ecological theory, populations whose dynamics are entrained by environmental correlation face increased extinction risk as environmental conditions become more synchronized spatially. This prediction is highly relevant to the study of ecological consequences of climate change. Recent empirical studies have indicated, for example, that large-scale climate synchronizes trophic interactions and population dynamics over broad spatial scales in freshwater and terrestrial systems. Here, we present an analysis of century-scale, spatially replicated data on local weather and the population dynamics of caribou in Greenland. Our results indicate that spatial autocorrelation in local weather has increased with large-scale climatic warming. This increase in spatial synchrony of environmental conditions has been matched, in turn, by an increase in the spatial synchrony of local caribou populations toward the end of the 20th century. Our results indicate that spatial synchrony in environmental conditions and the populations influenced by them are highly variable through time and can increase with climatic warming. We suggest that if future warming can increase population synchrony, it may also increase extinction risk.

[Spatial point pattern analysis of main trees and flowering Fargesia qinlingensis in Abies fargesii forests in Mt Taibai of the Qinling Mountains, China].

PubMed

Li, Guo Chun; Song, Hua Dong; Li, Qi; Bu, Shu Hai

2017-11-01

In Abies fargesii forests of the giant panda's habitats in Mt. Taibai, the spatial distribution patterns and interspecific associations of main tree species and their spatial associations with the understory flowering Fargesia qinlingensis were analyzed at multiple scales by univariate and bivaria-te O-ring function in point pattern analysis. The results showed that in the A. fargesii forest, the number of A. fargesii was largest but its population structure was in decline. The population of Betula platyphylla was relatively young, with a stable population structure, while the population of B. albo-sinensis declined. The three populations showed aggregated distributions at small scales and gradually showed random distributions with increasing spatial scales. Spatial associations among tree species were mainly showed at small scales and gradually became not spatially associated with increasing scale. A. fargesii and B. platyphylla were positively associated with flowering F. qinlingensis at large and medium scales, whereas B. albo-sinensis showed negatively associated with flowering F. qinlingensis at large and medium scales. The interaction between trees and F. qinlingensis in the habitats of giant panda promoted the dynamic succession and development of forests, which changed the environment of giant panda's habitats in Qinling.

Multiscale field-aligned current analyzer

NASA Astrophysics Data System (ADS)

Bunescu, C.; Marghitu, O.; Constantinescu, D.; Narita, Y.; Vogt, J.; Blǎgǎu, A.

2015-11-01

The magnetosphere-ionosphere coupling is achieved, essentially, by a superposition of quasi-stationary and time-dependent field-aligned currents (FACs), over a broad range of spatial and temporal scales. The planarity of the FAC structures observed by satellite data and the orientation of the planar FAC sheets can be investigated by the well-established minimum variance analysis (MVA) of the magnetic perturbation. However, such investigations are often constrained to a predefined time window, i.e., to a specific scale of the FAC. The multiscale field-aligned current analyzer, introduced here, relies on performing MVA continuously and over a range of scales by varying the width of the analyzing window, appropriate for the complexity of the magnetic field signatures above the auroral oval. The proposed technique provides multiscale information on the planarity and orientation of the observed FACs. A new approach, based on the derivative of the largest eigenvalue of the magnetic variance matrix with respect to the length of the analysis window, makes possible the inference of the current structures' location (center) and scale (thickness). The capabilities of the FAC analyzer are explored analytically for the magnetic field profile of the Harris sheet and tested on synthetic FAC structures with uniform current density and infinite or finite geometry in the cross-section plane of the FAC. The method is illustrated with data observed by the Cluster spacecraft on crossing the nightside auroral region, and the results are cross checked with the optical observations from the Time History of Events and Macroscale Interactions during Substorms ground network.

Understanding relationships among ecosystem services across spatial scales and over time

NASA Astrophysics Data System (ADS)

Qiu, Jiangxiao; Carpenter, Stephen R.; Booth, Eric G.; Motew, Melissa; Zipper, Samuel C.; Kucharik, Christopher J.; Loheide, Steven P., II; Turner, Monica G.

2018-05-01

Sustaining ecosystem services (ES), mitigating their tradeoffs and avoiding unfavorable future trajectories are pressing social-environmental challenges that require enhanced understanding of their relationships across scales. Current knowledge of ES relationships is often constrained to one spatial scale or one snapshot in time. In this research, we integrated biophysical modeling with future scenarios to examine changes in relationships among eight ES indicators from 2001–2070 across three spatial scales—grid cell, subwatershed, and watershed. We focused on the Yahara Watershed (Wisconsin) in the Midwestern United States—an exemplar for many urbanizing agricultural landscapes. Relationships among ES indicators changed over time; some relationships exhibited high interannual variations (e.g. drainage vs. food production, nitrate leaching vs. net ecosystem exchange) and even reversed signs over time (e.g. perennial grass production vs. phosphorus yield). Robust patterns were detected for relationships among some regulating services (e.g. soil retention vs. water quality) across three spatial scales, but other relationships lacked simple scaling rules. This was especially true for relationships of food production vs. water quality, and drainage vs. number of days with runoff >10 mm, which differed substantially across spatial scales. Our results also showed that local tradeoffs between food production and water quality do not necessarily scale up, so reducing local tradeoffs may be insufficient to mitigate such tradeoffs at the watershed scale. We further synthesized these cross-scale patterns into a typology of factors that could drive changes in ES relationships across scales: (1) effects of biophysical connections, (2) effects of dominant drivers, (3) combined effects of biophysical linkages and dominant drivers, and (4) artificial scale effects, and concluded with management implications. Our study highlights the importance of taking a dynamic perspective and accounting for spatial scales in monitoring and management to sustain future ES.

Effect of spatial and temporal scales on habitat suitability modeling: A case study of Ommastrephes bartramii in the northwest pacific ocean

NASA Astrophysics Data System (ADS)

Gong, Caixia; Chen, Xinjun; Gao, Feng; Tian, Siquan

2014-12-01

Temporal and spatial scales play important roles in fishery ecology, and an inappropriate spatio-temporal scale may result in large errors in modeling fish distribution. The objective of this study is to evaluate the roles of spatio-temporal scales in habitat suitability modeling, with the western stock of winter-spring cohort of neon flying squid ( Ommastrephes bartramii) in the northwest Pacific Ocean as an example. In this study, the fishery-dependent data from the Chinese Mainland Squid Jigging Technical Group and sea surface temperature (SST) from remote sensing during August to October of 2003-2008 were used. We evaluated the differences in a habitat suitability index model resulting from aggregating data with 36 different spatial scales with a combination of three latitude scales (0.5°, 1° and 2°), four longitude scales (0.5°, 1°, 2° and 4°), and three temporal scales (week, fortnight, and month). The coefficients of variation (CV) of the weekly, biweekly and monthly suitability index (SI) were compared to determine which temporal and spatial scales of SI model are more precise. This study shows that the optimal temporal and spatial scales with the lowest CV are month, and 0.5° latitude and 0.5° longitude for O. bartramii in the northwest Pacific Ocean. This suitability index model developed with an optimal scale can be cost-effective in improving forecasting fishing ground and requires no excessive sampling efforts. We suggest that the uncertainty associated with spatial and temporal scales used in data aggregations needs to be considered in habitat suitability modeling.

[Spatial distribution and scale effect of species diversity of secondary forests in montane region of eastern Liaoning Province, China.

PubMed

Deng, Li Ping; Bai, Xue Jiao; Qin, Sheng Jin; Wei, Ya Wei; Zhou, Yong Bin; Li, Lu Lu; Niu, Sha Sha; Han, Mei Na

2016-07-01

With secondary forest in the montane region of eastern Liaoning Province as research object, this paper analyzed the spatial distribution and scale effect of Gleason richness index, Simpson dominance index, Shannon diversity index and Pielou evenness index in a 4 hm 2 plot. The results showed that spatial distributions of the four diversity indices showed higher spatial heterogeneity. Variance of the four diversity indices varied with increasing scale. Coefficients of variation of the four diversity indices decreased with increasing scale. The four diversity indices of the tree layer were higher than those of the shrub layer, and the variation tendency varied with increasing scale. The results indicated that sampling scale should be taken into account when studying species diversity in the montane region of eastern Liaoning Province.

Olive cultivars adaptability in Southern Italy in present and future climate

NASA Astrophysics Data System (ADS)

Riccardi, M.; Alfieri, S.; Bonfante, A.; Basile, A.; Di Tommasi, P.; Menenti, M.; De Lorenzi, F.

2012-04-01

The intra-specific biodiversity of agricultural crops is very significant and likely to provide the single major opportunity to cope with the effects of the changing climate on agricultural ecosystems. Assessment of adaptive capacity must rely on quantitative descriptions of plant responses to environmental factors (e.g. soil water availability, temperature). Moreover climate scenario needs to be downscaled to the spatial scale relevant to crop and farm management. Distributed models of crop response to environmental forcing might be used for this purpose, but severely constrained by the very scarce knowledge on variety-specific values of model parameters, thus limiting the potential exploitation of intra-specific biodiversity towards adaptation. We have developed an approach towards this objective that relies on two complementary elements: a)a distributed model of the soil plant atmosphere system to downscale climate scenarios to landscape units, where generic model parameters for each species are used; b)a data base on climatic requirements of as many varieties as feasible for each species relevant to the agricultural production system of a given region. By means of this approach, the adaptability of some olive cultivars was evaluated in a composite (hills and plains) area of Southern Italy (Valle Telesina, Campania Region, about 20.000 ha). The yearly average temperature is 22.5 °C and rainfall ranges between 600 and 900 mm. Two different climate scenarios were considered: current climate (1961-1990) and future climate (2021-2050). Future climate scenarios at low spatial resolution were generated with general circulation models (AOGCM) and down-scaled by means of a statistical model (Tomozeiu et al., 2007). The climate was represented by daily observations of minimum, maximum temperature and precipitation on a regular grid with a spatial resolution of 35 km; 50 realizations were used for future climate. The soil water regime of 45 soil units was described for the two climate scenarios by using an hydrological distributed model (SWAP). For 11 olive cultivars, the yield response function to soil water regime was determined through the re-analysis of experimental data (unpublished or derived from scientific literature). According to these responses, cultivar-specific threshold values of soil water (or evapotranspiration) deficit were defined. The soil water regime calculated by the distributed model was compared with the threshold values to identify cultivars compatible with present and expected climates. The operation is repeated for a set of realizations of each climate scenario. This analysis is performed in a distributed manner, i.e. using the time series for each model grid to assess possible variations in the extent and spatial distribution of cultivated area of olive cultivars. In the study area future climate scenarios predict an increase of monthly minimum and maximum air temperature of about 2°C during the summer (June, July and August) and a reduction of rainfall in autumn. Spatial pattern of cultivars distribution, according their threshold values and soil water regime, was determined in the present and future climate scenarios, thus assessing variations in cultivars adaptability to future climate with respect to the present. Key words: climate change, biodiversity, water availability, yield response. The work was carried out within the Italian national project AGROSCENARI funded by the Ministry for Agricultural, Food and Forest Policies (MIPAAF, D.M. 8608/7303/2008).

Environmental Controls on Multi-Scale Soil Nutrient Variability in the Tropics: the Importance of Land-Cover Change

NASA Astrophysics Data System (ADS)

Holmes, K. W.; Kyriakidis, P. C.; Chadwick, O. A.; Matricardi, E.; Soares, J. V.; Roberts, D. A.

2003-12-01

The natural controls on soil variability and the spatial scales at which correlation exists among soil and environmental variables are critical information for evaluating the effects of deforestation. We detect different spatial scales of variability in soil nutrient levels over a large region (hundreds of thousands of km2) in the Amazon, analyze correlations among soil properties at these different scales, and evaluate scale-specific relationships among soil properties and the factors potentially driving soil development. Statistical relationships among physical drivers of soil formation, namely geology, precipitation, terrain attributes, classified soil types, and land cover derived from remote sensing, were included to determine which factors are related to soil biogeochemistry at each spatial scale. Surface and subsurface soil profile data from a 3000 sample database collected in Rond“nia, Brazil, were used to investigate patterns in pH, phosphorus, nitrogen, organic carbon, effective cation exchange capacity, calcium, magnesium, potassium, aluminum, sand, and clay in this environment grading from closed canopy tropical forest to savanna. We focus on pH in this presentation for simplicity, because pH is the single most important soil characteristic for determining the chemical environment of higher plants and soil microbial activity. We determined four spatial scales which characterize integrated patterns of soil chemistry: less than 3 km; 3 to 10 km; 10 to 68 km; and from 68 to 550 km (extent of study area). Although the finest observable scale was fixed by the field sampling density, the coarser scales were determined from relationships in the data through coregionalization modeling, rather than being imposed by the researcher. Processes which affect soils over short distances, such as land cover and terrain attributes, were good predictors of fine scale spatial components of nutrients; processes which affect soils over very large distances, such as precipitation and geology, were better predictors at coarse spatial scales. However, this result may be affected by the resolution of the available predictor maps. Land-cover change exerted a strong influence on soil chemistry at fine spatial scales, and had progressively less of an effect at coarser scales. It is important to note that land cover, and interactions among land cover and the other predictors, continued to be a significant predictor of soil chemistry at every spatial scale up to hundreds of thousands of kilometers.

SU-F-I-10: Spatially Local Statistics for Adaptive Image Filtering

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

Iliopoulos, AS; Sun, X; Floros, D

Purpose: To facilitate adaptive image filtering operations, addressing spatial variations in both noise and signal. Such issues are prevalent in cone-beam projections, where physical effects such as X-ray scattering result in spatially variant noise, violating common assumptions of homogeneous noise and challenging conventional filtering approaches to signal extraction and noise suppression. Methods: We present a computational mechanism for probing into and quantifying the spatial variance of noise throughout an image. The mechanism builds a pyramid of local statistics at multiple spatial scales; local statistical information at each scale includes (weighted) mean, median, standard deviation, median absolute deviation, as well asmore » histogram or dynamic range after local mean/median shifting. Based on inter-scale differences of local statistics, the spatial scope of distinguishable noise variation is detected in a semi- or un-supervised manner. Additionally, we propose and demonstrate the incorporation of such information in globally parametrized (i.e., non-adaptive) filters, effectively transforming the latter into spatially adaptive filters. The multi-scale mechanism is materialized by efficient algorithms and implemented in parallel CPU/GPU architectures. Results: We demonstrate the impact of local statistics for adaptive image processing and analysis using cone-beam projections of a Catphan phantom, fitted within an annulus to increase X-ray scattering. The effective spatial scope of local statistics calculations is shown to vary throughout the image domain, necessitating multi-scale noise and signal structure analysis. Filtering results with and without spatial filter adaptation are compared visually, illustrating improvements in imaging signal extraction and noise suppression, and in preserving information in low-contrast regions. Conclusion: Local image statistics can be incorporated in filtering operations to equip them with spatial adaptivity to spatial signal/noise variations. An efficient multi-scale computational mechanism is developed to curtail processing latency. Spatially adaptive filtering may impact subsequent processing tasks such as reconstruction and numerical gradient computations for deformable registration. NIH Grant No. R01-184173.« less

A spatial scaling relationship for soil moisture in a semiarid landscape, using spatial scaling relationships for pedology

NASA Astrophysics Data System (ADS)

Willgoose, G. R.; Chen, M.; Cohen, S.; Saco, P. M.; Hancock, G. R.

2013-12-01

In humid areas it is generally considered that soil moisture scales spatially according to the wetness index of the landscape. This scaling arises from lateral flow downslope of ground water within the soil zone. However, in semi-arid and drier regions, this lateral flow is small and fluxes are dominated by vertical flows driven by infiltration and evapotranspiration. Thus, in the absence of runon processes, soil moisture at a location is more driven by local factors such as soil and vegetation properties at that location rather than upstream processes draining to that point. The 'apparent' spatial randomness of soil and vegetation properties generally suggests that soil moisture for semi-arid regions is spatially random. In this presentation a new analysis of neutron probe data during summer from the Tarrawarra site near Melbourne, Australia shows persistent spatial organisation of soil moisture over several years. This suggests a link between permanent features of the catchment (e.g. soil properties) and soil moisture distribution, even though the spatial pattern of soil moisture during the 4 summers monitored appears spatially random. This and other data establishes a prima facie case that soil variations drive spatial variation in soil moisture. Accordingly, we used a previously published spatial scaling relationship for soil properties derived using the mARM pedogenesis model to simulate the spatial variation of soil grading. This soil grading distribution was used in the Rosetta pedotransfer model to derive a spatial distribution of soil functional properties (e.g. saturated hydraulic conductivity, porosity). These functional properties were then input into the HYDRUS-1D soil moisture model and soil moisture simulated for 3 years at daily resolution. The HYDRUS model used had previously been calibrated to field observed soil moisture data at our SASMAS field site. The scaling behaviour of soil moisture derived from this modelling will be discussed and compared with observed data from our SASMAS field sites.

The complex roles of space and environment in structuring functional, taxonomic and phylogenetic beta diversity of frogs in the Atlantic Forest

PubMed Central

Luiz, Amom Mendes; Sawaya, Ricardo J.

2018-01-01

Ecological communities are complex entities that can be maintained and structured by niche-based processes such as environmental conditions, and spatial processes such as dispersal. Thus, diversity patterns may be shaped simultaneously at different spatial scales by very distinct processes. Herein we assess whether and how functional, taxonomic, and phylogenetic beta diversities of frog tadpoles are explained by environmental and/or spatial predictors. We implemented a distance–based redundancy analysis to explore variation in components of beta diversity explained by pure environmental and pure spatial predictors, as well as their interactions, at both fine and broad spatial scales. Our results indicated important but complex roles of spatial and environmental predictors in structuring phylogenetic, taxonomic and functional beta diversities. The pure fine-scales spatial fraction was more important in structuring all beta diversity components, especially to functional and taxonomical spatial turnover. Environmental variables such as canopy cover and vegetation structure were important predictors of all components, but especially to functional and taxonomic beta diversity. We emphasize that distinct factors related to environment and space are affecting distinct components of beta diversity in different ways. Although weaker, phylogenetic beta diversity, which is structured more on biogeographical scales, and thus can be represented by spatially structured processes, was more related to broad spatial processes than other components. However, selected fine-scale spatial predictors denoted negative autocorrelation, which may be revealing the existence of differences in unmeasured habitat variables among samples. Although overall important, local environmental-based processes explained better functional and taxonomic beta diversity, as these diversity components carry an important ecological value. We highlight the importance of assessing different components of diversity patterns at different scales by spatially explicit models in order to improve our understanding of community structure and help to unravel the complex nature of biodiversity. PMID:29672575

A reaction-diffusion within-host HIV model with cell-to-cell transmission.

PubMed

Ren, Xinzhi; Tian, Yanni; Liu, Lili; Liu, Xianning

2018-06-01

In this paper, a reaction-diffusion within-host HIV model is proposed. It incorporates cell mobility, spatial heterogeneity and cell-to-cell transmission, which depends on the diffusion ability of the infected cells. In the case of a bounded domain, the basic reproduction number [Formula: see text] is established and shown as a threshold: the virus-free steady state is globally asymptotically stable if [Formula: see text] and the virus is uniformly persistent if [Formula: see text]. The explicit formula for [Formula: see text] and the global asymptotic stability of the constant positive steady state are obtained for the case of homogeneous space. In the case of an unbounded domain and [Formula: see text], the existence of the traveling wave solutions is proved and the minimum wave speed [Formula: see text] is obtained, providing the mobility of infected cells does not exceed that of the virus. These results are obtained by using Schauder fixed point theorem, limiting argument, LaSalle's invariance principle and one-side Laplace transform. It is found that the asymptotic spreading speed may be larger than the minimum wave speed via numerical simulations. However, our simulations show that it is possible either to underestimate or overestimate the spread risk [Formula: see text] if the spatial averaged system is used rather than one that is spatially explicit. The spread risk may also be overestimated if we ignore the mobility of the cells. It turns out that the minimum wave speed could be either underestimated or overestimated as long as the mobility of infected cells is ignored.

Geo-spatial analysis of temporal trends of temperature and its extremes over India using daily gridded (1°×1°) temperature data of 1969-2005

NASA Astrophysics Data System (ADS)

Chakraborty, Abhishek; Seshasai, M. V. R.; Rao, S. V. C. Kameswara; Dadhwal, V. K.

2017-10-01

Daily gridded (1°×1°) temperature data (1969-2005) were used to detect spatial patterns of temporal trends of maximum and minimum temperature (monthly and seasonal), growing degree days (GDDs) over the crop-growing season ( kharif, rabi, and zaid) and annual frequencies of temperature extremes over India. The direction and magnitude of trends, at each grid level, were estimated using the Mann-Kendall statistics ( α = 0.05) and further assessed at the homogeneous temperature regions using a field significance test ( α=0.05). General warming trends were observed over India with considerable variations in direction and magnitude over space and time. The spatial extent and the magnitude of the increasing trends of minimum temperature (0.02-0.04 °C year-1) were found to be higher than that of maximum temperature (0.01-0.02 °C year-1) during winter and pre-monsoon seasons. Significant negative trends of minimum temperature were found over eastern India during the monsoon months. Such trends were also observed for the maximum temperature over northern and eastern parts, particularly in the winter month of January. The general warming patterns also changed the thermal environment of the crop-growing season causing significant increase in GDDs during kharif and rabi seasons across India. The warming climate has also caused significant increase in occurrences of hot extremes such as hot days and hot nights, and significant decrease in cold extremes such as cold days and cold nights.

Effects of spatial scale of sampling on food web structure

PubMed Central

Wood, Spencer A; Russell, Roly; Hanson, Dieta; Williams, Richard J; Dunne, Jennifer A

2015-01-01

This study asks whether the spatial scale of sampling alters structural properties of food webs and whether any differences are attributable to changes in species richness and connectance with scale. Understanding how different aspects of sampling effort affect ecological network structure is important for both fundamental ecological knowledge and the application of network analysis in conservation and management. Using a highly resolved food web for the marine intertidal ecosystem of the Sanak Archipelago in the Eastern Aleutian Islands, Alaska, we assess how commonly studied properties of network structure differ for 281 versions of the food web sampled at five levels of spatial scale representing six orders of magnitude in area spread across the archipelago. Species (S) and link (L) richness both increased by approximately one order of magnitude across the five spatial scales. Links per species (L/S) more than doubled, while connectance (C) decreased by approximately two-thirds. Fourteen commonly studied properties of network structure varied systematically with spatial scale of sampling, some increasing and others decreasing. While ecological network properties varied systematically with sampling extent, analyses using the niche model and a power-law scaling relationship indicate that for many properties, this apparent sensitivity is attributable to the increasing S and decreasing C of webs with increasing spatial scale. As long as effects of S and C are accounted for, areal sampling bias does not have a special impact on our understanding of many aspects of network structure. However, attention does need be paid to some properties such as the fraction of species in loops, which increases more than expected with greater spatial scales of sampling. PMID:26380704

Improving left spatial neglect through music scale playing.

PubMed

Bernardi, Nicolò Francesco; Cioffi, Maria Cristina; Ronchi, Roberta; Maravita, Angelo; Bricolo, Emanuela; Zigiotto, Luca; Perucca, Laura; Vallar, Giuseppe

2017-03-01

The study assessed whether the auditory reference provided by a music scale could improve spatial exploration of a standard musical instrument keyboard in right-brain-damaged patients with left spatial neglect. As performing music scales involves the production of predictable successive pitches, the expectation of the subsequent note may facilitate patients to explore a larger extension of space in the left affected side, during the production of music scales from right to left. Eleven right-brain-damaged stroke patients with left spatial neglect, 12 patients without neglect, and 12 age-matched healthy participants played descending scales on a music keyboard. In a counterbalanced design, the participants' exploratory performance was assessed while producing scales in three feedback conditions: With congruent sound, no-sound, or random sound feedback provided by the keyboard. The number of keys played and the timing of key press were recorded. Spatial exploration by patients with left neglect was superior with congruent sound feedback, compared to both Silence and Random sound conditions. Both the congruent and incongruent sound conditions were associated with a greater deceleration in all groups. The frame provided by the music scale improves exploration of the left side of space, contralateral to the right hemisphere, damaged in patients with left neglect. Performing a scale with congruent sounds may trigger at some extent preserved auditory and spatial multisensory representations of successive sounds, thus influencing the time course of space scanning, and ultimately resulting in a more extensive spatial exploration. These findings offer new perspectives also for the rehabilitation of the disorder. © 2015 The British Psychological Society.

Large scale patterns in vertical distribution and behaviour of mesopelagic scattering layers

PubMed Central

Klevjer, T. A.; Irigoien, X.; Røstad, A.; Fraile-Nuez, E.; Benítez-Barrios, V. M.; Kaartvedt., S.

2016-01-01

Recent studies suggest that previous estimates of mesopelagic biomasses are severely biased, with the new, higher estimates underlining the need to unveil behaviourally mediated coupling between shallow and deep ocean habitats. We analysed vertical distribution and diel vertical migration (DVM) of mesopelagic acoustic scattering layers (SLs) recorded at 38 kHz across oceanographic regimes encountered during the circumglobal Malaspina expedition. Mesopelagic SLs were observed in all areas covered, but vertical distributions and DVM patterns varied markedly. The distribution of mesopelagic backscatter was deepest in the southern Indian Ocean (weighted mean daytime depth: WMD 590 m) and shallowest at the oxygen minimum zone in the eastern Pacific (WMD 350 m). DVM was evident in all areas covered, on average ~50% of mesopelagic backscatter made daily excursions from mesopelagic depths to shallow waters. There were marked differences in migrating proportions between the regions, ranging from ~20% in the Indian Ocean to ~90% in the Eastern Pacific. Overall the data suggest strong spatial gradients in mesopelagic DVM patterns, with implied ecological and biogeochemical consequences. Our results suggest that parts of this spatial variability can be explained by horizontal patterns in physical-chemical properties of water masses, such as oxygen, temperature and turbidity. PMID:26813333

Seasonal and nonseasonal variability of satellite-derived chlorophyll and colored dissolved organic matter concentration in the California Current

NASA Astrophysics Data System (ADS)

Kahru, Mati; Mitchell, B. Greg

2001-02-01

Time series of surface chlorophyll a concentration (Chl) and colored dissolved organic matter (CDOM) derived from the Ocean Color and Temperature Sensor and Sea-Viewing Wide Field-of-View Sensor were evaluated for the California Current area using regional algorithms. Satellite data composited for 8-day periods provide the ability to describe large-scale changes in surface parameters. These changes are difficult to detect based on in situ observations alone that suffer from undersampling the large temporal and spatial variability, especially in Chl. We detected no significant bias in satellite Chl estimates compared with ship-based measurements. The variability in CDOM concentration was significantly smaller than that in Chl, both spatially and temporally. While being subject to large interannual and short-term variations, offshore waters (100-1000 km from the shore) have an annual cycle of Chl and CDOM with a maximum in winter-spring (December-March) and a minimum in late summer. For inshore waters the maximum is more likely in spring (April-May). We detect significant increase in both Chl and CDOM off central and southern California during the La Niña year of 1999. The trend of increasing Chl and CDOM from October 1996 to June 2000 is statistically significant in many areas.

Magnetoencephalography with temporal spread imaging to visualize propagation of epileptic activity.

PubMed

Shibata, Sumiya; Matsuhashi, Masao; Kunieda, Takeharu; Yamao, Yukihiro; Inano, Rika; Kikuchi, Takayuki; Imamura, Hisaji; Takaya, Shigetoshi; Matsumoto, Riki; Ikeda, Akio; Takahashi, Ryosuke; Mima, Tatsuya; Fukuyama, Hidenao; Mikuni, Nobuhiro; Miyamoto, Susumu

2017-05-01

We describe temporal spread imaging (TSI) that can identify the spatiotemporal pattern of epileptic activity using Magnetoencephalography (MEG). A three-dimensional grid of voxels covering the brain is created. The array-gain minimum-variance spatial filter is applied to an interictal spike to estimate the magnitude of the source and the time (Ta) when the magnitude exceeds a predefined threshold at each voxel. This calculation is performed through all spikes. Each voxel has the mean Ta () and spike number (N sp ), which is the number of spikes whose source exceeds the threshold. Then, a random resampling method is used to determine the cutoff value of N sp for the statistically reproducible pattern of the activity. Finally, all the voxels where the source exceeds the threshold reproducibly shown on the MRI with a color scale representing . Four patients with intractable mesial temporal lobe epilepsy (MTLE) were analyzed. In three patients, the common pattern of the overlap between the propagation and the hypometabolism shown by fluorodeoxyglucose-positron emission tomography (FDG-PET) was identified. TSI can visualize statistically reproducible patterns of the temporal and spatial spread of epileptic activity. TSI can assess the statistical significance of the spatiotemporal pattern based on its reproducibility. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Spatial scale of similarity as an indicator of metacommunity stability in exploited marine systems.

PubMed

Shackell, Nancy L; Fisher, Jonathan A D; Frank, Kenneth T; Lawton, Peter

2012-01-01

The spatial scale of similarity among fish communities is characteristically large in temperate marine systems: connectivity is enhanced by high rates of dispersal during the larval/juvenile stages and the increased mobility of large-bodied fish. A larger spatial scale of similarity (low beta diversity) is advantageous in heavily exploited systems because locally depleted populations are more likely to be "rescued" by neighboring areas. We explored whether the spatial scale of similarity changed from 1970 to 2006 due to overfishing of dominant, large-bodied groundfish across a 300 000-km2 region of the Northwest Atlantic. Annually, similarities among communities decayed slowly with increasing geographic distance in this open system, but through time the decorrelation distance declined by 33%, concomitant with widespread reductions in biomass, body size, and community evenness. The decline in connectivity stemmed from an erosion of community similarity among local subregions separated by distances as small as 100 km. Larger fish, of the same species, contribute proportionally more viable offspring, so observed body size reductions will have affected maternal output. The cumulative effect of nonlinear maternal influences on egg/larval quality may have compromised the spatial scale of effective larval dispersal, which may account for the delayed recovery of certain member species. Our study adds strong support for using the spatial scale of similarity as an indicator of metacommunity stability both to understand the spatial impacts of exploitation and to refine how spatial structure is used in management plans.

Comparison of MODIS and SWAT evapotranspiration over a complex terrain at different spatial scales

NASA Astrophysics Data System (ADS)

Abiodun, Olanrewaju O.; Guan, Huade; Post, Vincent E. A.; Batelaan, Okke

2018-05-01

In most hydrological systems, evapotranspiration (ET) and precipitation are the largest components of the water balance, which are difficult to estimate, particularly over complex terrain. In recent decades, the advent of remotely sensed data based ET algorithms and distributed hydrological models has provided improved spatially upscaled ET estimates. However, information on the performance of these methods at various spatial scales is limited. This study compares the ET from the MODIS remotely sensed ET dataset (MOD16) with the ET estimates from a SWAT hydrological model on graduated spatial scales for the complex terrain of the Sixth Creek Catchment of the Western Mount Lofty Ranges, South Australia. ET from both models was further compared with the coarser-resolution AWRA-L model at catchment scale. The SWAT model analyses are performed on daily timescales with a 6-year calibration period (2000-2005) and 7-year validation period (2007-2013). Differences in ET estimation between the SWAT and MOD16 methods of up to 31, 19, 15, 11 and 9 % were observed at respectively 1, 4, 9, 16 and 25 km2 spatial resolutions. Based on the results of the study, a spatial scale of confidence of 4 km2 for catchment-scale evapotranspiration is suggested in complex terrain. Land cover differences, HRU parameterisation in AWRA-L and catchment-scale averaging of input climate data in the SWAT semi-distributed model were identified as the principal sources of weaker correlations at higher spatial resolution.

Interactions across spatial scales among forest dieback, fire, and erosion in northern New Mexico landscapes

USGS Publications Warehouse

Allen, Craig D.

2007-01-01

Ecosystem patterns and disturbance processes at one spatial scale often interact with processes at another scale, and the result of such cross-scale interactions can be nonlinear dynamics with thresholds. Examples of cross-scale pattern-process relationships and interactions among forest dieback, fire, and erosion are illustrated from northern New Mexico (USA) landscapes, where long-term studies have recently documented all of these disturbance processes. For example, environmental stress, operating on individual trees, can cause tree death that is amplified by insect mortality agents to propagate to patch and then landscape or even regional-scale forest dieback. Severe drought and unusual warmth in the southwestern USA since the late 1990s apparently exceeded species-specific physiological thresholds for multiple tree species, resulting in substantial vegetation mortality across millions of hectares of woodlands and forests in recent years. Predictions of forest dieback across spatial scales are constrained by uncertainties associated with: limited knowledge of species-specific physiological thresholds; individual and site-specific variation in these mortality thresholds; and positive feedback loops between rapidly-responding insect herbivore populations and their stressed plant hosts, sometimes resulting in nonlinear “pest” outbreak dynamics. Fire behavior also exhibits nonlinearities across spatial scales, illustrated by changes in historic fire regimes where patch-scale grazing disturbance led to regional-scale collapse of surface fire activity and subsequent recent increases in the scale of extreme fire events in New Mexico. Vegetation dieback interacts with fire activity by modifying fuel amounts and configurations at multiple spatial scales. Runoff and erosion processes are also subject to scale-dependent threshold behaviors, exemplified by ecohydrological work in semiarid New Mexico watersheds showing how declines in ground surface cover lead to non-linear increases in bare patch connectivity and thereby accelerated runoff and erosion at hillslope and watershed scales. Vegetation dieback, grazing, and fire can change land surface properties and cross-scale hydrologic connectivities, directly altering ecohydrological patterns of runoff and erosion. The interactions among disturbance processes across spatial scales can be key drivers in ecosystem dynamics, as illustrated by these studies of recent landscape changes in northern New Mexico. To better anticipate and mitigate accelerating human impacts to the planetary ecosystem at all spatial scales, improvements are needed in our conceptual and quantitative understanding of cross-scale interactions among disturbance processes.

River eutrophication: irrigated vs. non-irrigated agriculture through different spatial scales.

PubMed

Monteagudo, Laura; Moreno, José Luis; Picazo, Félix

2012-05-15

The main objective of this study was to determine how spatial scale may affect the results when relating land use to nutrient enrichment of rivers and, secondly, to investigate which agricultural practices are more responsible for river eutrophication in the study area. Agriculture was split into three subclasses (irrigated, non-irrigated and low-impact agriculture) which were correlated to stream nutrient concentration on four spatial scales: large scale (drainage area of total subcatchment and 100 m wide subcatchment corridors) and local scale (5 and 1 km radius buffers). Nitrate, ammonium and orthophosphate concentrations and land use composition (agriculture, urban and forest) were measured at 130 river reaches in south-central Spain during the 2001-2009 period. Results suggested that different spatial scales may lead to different conclusions. Spatial autocorrelation and the inadequate representation of some land uses produced unreal results on large scales. Conversely, local scales did not show data autocorrelation and agriculture subclasses were well represented. The local scale of 1 km buffer was the most appropriate to detect river eutrophication in central Spanish rivers, with irrigated cropland as the main cause of river pollution by nitrate. As regards river management, a threshold of 50% irrigated cropland within a 1 km radius buffer has been obtained using breakpoint regression analysis. This means that no more than 50% of irrigation croplands should be allowed near river banks in order to avoid river eutrophication. Finally, a methodological approach is proposed to choose the appropriate spatial scale when studying river eutrophication caused by diffuse pollution like agriculture. Copyright © 2012 Elsevier Ltd. All rights reserved.

Anisotropic ion heating and BBELF waves within the low-altitude ion upflow region

NASA Astrophysics Data System (ADS)

Shen, Y.; Knudsen, D. J.; Burchill, J. K.; James, H. G.; Miles, D. M.

2016-12-01

Previous studies have shown that low-energy (<10 eV) ion upflow energization processes involve multiple steps. At the initial stage, contributions from transverse-to-B ion heating by wave-particle interaction (WPI) are often underestimated. The wave-generation mechanisms, the specific wave modes leading to the ion heating, and the minimum altitude where WPI takes place remain unresolved. With this in mind, we statistically investigate the relation between anisotropic ion temperature enhancements and broadband extremely low frequency (BBELF) wave emissions within the ion upflow region using data from the Suprathermal Electron imager (SEI), the Fluxgate Magnetometer (MGF), and the Radio Receiver Instrument (RRI) onboard the e-POP satellite. Initial results demonstrate that perpendicular-to-B ion temperatures can reach up to 4.3 eV in approximately 1 km wide spatial region near 410 km altitude inside an active auroral surge. Intense small-scale field-aligned currents (FACs) as well as strong BBELF wave emissions, comprising electromagnetic waves below 80 Hz and electrostatic waves above, accompany these ion heating events. The minimum altitude of potential WPI reported here is lower than as previously suggested as 520 km by Frederick-Frost et al. 2007. We measure polarization and power spectral density for specific wave modes to explore the nature of ion heating within the BBELF waves. Acknowledgement: This research is supported by an Eyes High Doctoral Recruitment Scholarship at University of Calgary.

Evidence for Tropopause Layer Moistening by Convection During CRYSTAL-FACE

NASA Technical Reports Server (NTRS)

Ackerman, A.; Fridlind, A.; Jensen, E.; Miloshevich, L.; Heymsfield, G.; McGill, M.

2003-01-01

Measurements and analysis of the impact of deep convection on tropopause layer moisture are easily confounded by difficulties making precise observations with sufficient spatial coverage before and after convective events and difficulties distinguishing between changes due to local convection versus large-scale advection. The interactions between cloud microphysics and dynamics in the convective transport of moisture into the tropopause layer also result in a sufficiently complex and poorly characterized system to allow for considerable freedom in theoretical models of stratosphere-troposphere exchange. In this work we perform detailed large-eddy simulations with an explicit cloud microphysics model to study the impact of deep convection on tropopause layer moisture profiles observed over southern Florida during CRYSTALFACE. For four days during the campaign (July 11, 16, 28, and 29) we initialize a 100-km square domain with temperature and moisture profiles measured prior to convection at the PARSL ground site, and initiate convection with a warm bubble that produces an anvil at peak elevations in agreement with lidar and radar observations on that day. Comparing the moisture field after the anvils decay with the initial state, we find that convection predominantly moistens the tropopause layer (as defined by minimum temperature and minimum potential temperature lapse rate), although some drying is also predicted in localized layers. We will also present results of sensitivity tests designed to separate the roles of cloud microphysics and dynamics.

Spatial Variability of Snowpack Properties On Small Slopes

NASA Astrophysics Data System (ADS)

Pielmeier, C.; Kronholm, K.; Schneebeli, M.; Schweizer, J.

The spatial variability of alpine snowpacks is created by a variety of parameters like deposition, wind erosion, sublimation, melting, temperature, radiation and metamor- phism of the snow. Spatial variability is thought to strongly control the avalanche initi- ation and failure propagation processes. Local snowpack measurements are currently the basis for avalanche warning services and there exist contradicting hypotheses about the spatial continuity of avalanche active snow layers and interfaces. Very little about the spatial variability of the snowpack is known so far, therefore we have devel- oped a systematic and objective method to measure the spatial variability of snowpack properties, layering and its relation to stability. For a complete coverage, the analysis of the spatial variability has to entail all scales from mm to km. In this study the small to medium scale spatial variability is investigated, i.e. the range from centimeters to tenths of meters. During the winter 2000/2001 we took systematic measurements in lines and grids on a flat snow test field with grid distances from 5 cm to 0.5 m. Fur- thermore, we measured systematic grids with grid distances between 0.5 m and 2 m in undisturbed flat fields and on small slopes above the tree line at the Choerbschhorn, in the region of Davos, Switzerland. On 13 days we measured the spatial pattern of the snowpack stratigraphy with more than 110 snow micro penetrometer measure- ments at slopes and flat fields. Within this measuring grid we placed 1 rutschblock and 12 stuffblock tests to measure the stability of the snowpack. With the large num- ber of measurements we are able to use geostatistical methods to analyse the spatial variability of the snowpack. Typical correlation lengths are calculated from semivari- ograms. Discerning the systematic trends from random spatial variability is analysed using statistical models. Scale dependencies are shown and recurring scaling patterns are outlined. The importance of the small and medium scale spatial variability for the larger (kilometer) scale spatial variability as well as for the avalanche formation are discussed. Finally, an outlook on spatial models for the snowpack variability is given.

Application of wildfire spread and behavior models to assess fire probability and severity in the Mediterranean region

NASA Astrophysics Data System (ADS)

Salis, Michele; Arca, Bachisio; Bacciu, Valentina; Spano, Donatella; Duce, Pierpaolo; Santoni, Paul; Ager, Alan; Finney, Mark

2010-05-01

Characterizing the spatial pattern of large fire occurrence and severity is an important feature of the fire management planning in the Mediterranean region. The spatial characterization of fire probabilities, fire behavior distributions and value changes are key components for quantitative risk assessment and for prioritizing fire suppression resources, fuel treatments and law enforcement. Because of the growing wildfire severity and frequency in recent years (e.g.: Portugal, 2003 and 2005; Italy and Greece, 2007 and 2009), there is an increasing demand for models and tools that can aid in wildfire prediction and prevention. Newer wildfire simulation systems offer promise in this regard, and allow for fine scale modeling of wildfire severity and probability. Several new applications has resulted from the development of a minimum travel time (MTT) fire spread algorithm (Finney, 2002), that models the fire growth searching for the minimum time for fire to travel among nodes in a 2D network. The MTT approach makes computationally feasible to simulate thousands of fires and generate burn probability and fire severity maps over large areas. The MTT algorithm is imbedded in a number of research and fire modeling applications. High performance computers are typically used for MTT simulations, although the algorithm is also implemented in the FlamMap program (www.fire.org). In this work, we described the application of the MTT algorithm to estimate spatial patterns of burn probability and to analyze wildfire severity in three fire prone areas of the Mediterranean Basin, specifically Sardinia (Italy), Sicily (Italy) and Corsica (France) islands. We assembled fuels and topographic data for the simulations in 500 x 500 m grids for the study areas. The simulations were run using 100,000 ignitions under weather conditions that replicated severe and moderate weather conditions (97th and 70th percentile, July and August weather, 1995-2007). We used both random ignition locations and ignition probability grids (1000 x 1000 m) built from historical fire data (1995-2007). The simulation outputs were then examined to understand relationships between burn probability and specific vegetation types and ignition sources. Wildfire threats to specific values of human interest were quantified to map landscape patterns of wildfire risk. The simulation outputs also allowed us to differentiate between areas of the landscape that were progenitors of fires versus "victims" of large fires. The results provided spatially explicit data on wildfire likelihood and intensity that can be used in a variety of strategic and tactical planning forums to mitigate wildfire threats to human and other values in the Mediterranean Basin.

Optimization of fixed-range trajectories for supersonic transport aircraft

NASA Astrophysics Data System (ADS)

Windhorst, Robert Dennis

1999-11-01

This thesis develops near-optimal guidance laws that generate minimum fuel, time, or direct operating cost fixed-range trajectories for supersonic transport aircraft. The approach uses singular perturbation techniques to time-scale de-couple the equations of motion into three sets of dynamics, two of which are analyzed in the main body of this thesis and one of which is analyzed in the Appendix. The two-point-boundary-value-problems obtained by application of the maximum principle to the dynamic systems are solved using the method of matched asymptotic expansions. Finally, the two solutions are combined using the matching principle and an additive composition rule to form a uniformly valid approximation of the full fixed-range trajectory. The approach is used on two different time-scale formulations. The first holds weight constant, and the second allows weight and range dynamics to propagate on the same time-scale. Solutions for the first formulation are only carried out to zero order in the small parameter, while solutions for the second formulation are carried out to first order. Calculations for a HSCT design were made to illustrate the method. Results show that the minimum fuel trajectory consists of three segments: a minimum fuel energy-climb, a cruise-climb, and a minimum drag glide. The minimum time trajectory also has three segments: a maximum dynamic pressure ascent, a constant altitude cruise, and a maximum dynamic pressure glide. The minimum direct operating cost trajectory is an optimal combination of the two. For realistic costs of fuel and flight time, the minimum direct operating cost trajectory is very similar to the minimum fuel trajectory. Moreover, the HSCT has three local optimum cruise speeds, with the globally optimum cruise point at the highest allowable speed, if range is sufficiently long. The final range of the trajectory determines which locally optimal speed is best. Ranges of 500 to 6,000 nautical miles, subsonic and supersonic mixed flight, and varying fuel efficiency cases are analyzed. Finally, the payload-range curve of the HSCT design is determined.

Spatially explicit and stochastic simulation of forest landscape fire disturbance and succession

Treesearch

Hong S. He; David J. Mladenoff

1999-01-01

Understanding disturbance and recovery of forest landscapes is a challenge because of complex interactions over a range of temporal and spatial scales. Landscape simulation models offer an approach to studying such systems at broad scales. Fire can be simulated spatially using mechanistic or stochastic approaches. We describe the fire module in a spatially explicit,...

Spatial scaling of non-native fish richness across the United States

Treesearch

Qinfeng Guo; Julian D. Olden

2014-01-01

A major goal and challenge of invasion ecology is to describe and interpret spatial and temporal patterns of species invasions. Here, we examined fish invasion patterns at four spatially structured and hierarchically nested scales across the contiguous United States (i.e., from large to small: region, basin, watershed, and sub-watershed). All spatial relationships in...

Spatial distribution of heavy metals in soil, water, and vegetables of farms in Sanandaj, Kurdistan, Iran.

PubMed

Maleki, Afshin; Amini, Hassan; Nazmara, Shahrokh; Zandi, Shiva; Mahvi, Amir Hossein

2014-01-01

Heavy metals are ubiquitous elsewhere in nature and their measurement in environment is necessary to develop health management strategies. In this study, we aimed to find out concentrations and spatial patterns of heavy metals in main farms of Sanandaj in Kurdistan, Iran. Over May to October 2012, six farms were selected to analyze concentrations and spatial patterns of several heavy metals, namely aluminum (Al), arsenic (As), cadmium (Cd), cobalt (Co), chromium (Cr), copper (Cu), nickel (Ni), lead (Pb), and zinc (Zn) in their soil, irrigation water, and edible vegetables. Overall, 36 samples of soil and water and 72 samples of vegetables including coriander (Coriandrum sativum), dill (Anethum graveolens), radish (Raphanus sativus) root and radish leaf were collected. The concentrations of metals were determined by inductively coupled plasma optical emission spectrometry. The spatial surfaces of heavy metals were created using geospatial information system. The order of metals in soil was Al > Zn > Ni > Cu > Cr > Pb > Co > As > Cd while in water it was Cr > Co > Zn > Pb > Cu > Ni > Al = As = Cd. The order of heavy metals in vegetables was Al > Zn > Cu > Cr > Ni > Pb > Co > As > Cd. Totally, the minimum concentrations of Al, Cu, Pb, and Zn were found in radish root while the maximum of Al, Co, Cr, and Ni were found in radish leaf. The minimum concentrations of Cd and Cr and maximum concentrations of Cu and Zn were also deciphered in dill. Noteworthy, coriander had the minimum concentrations of Co and Ni. The concentrations of Cr and Pb in vegetables were more than maximum allowable limits of the Food and Agriculture Organization (FAO) and the World Health Organization (WHO). In summary, albeit the concentrations of heavy metals in soil and water samples were below FAO and the WHO standards, vegetables were contaminated by chromium and lead.

Scale Dependence of Magnetic Helicity in the Solar Wind

NASA Technical Reports Server (NTRS)

Brandenburg, Axel; Subramanian, Kandaswamy; Balogh, Andre; Goldstein, Melvyn L.

2011-01-01

We determine the magnetic helicity, along with the magnetic energy, at high latitudes using data from the Ulysses mission. The data set spans the time period from 1993 to 1996. The basic assumption of the analysis is that the solar wind is homogeneous. Because the solar wind speed is high, we follow the approach first pioneered by Matthaeus et al. by which, under the assumption of spatial homogeneity, one can use Fourier transforms of the magnetic field time series to construct one-dimensional spectra of the magnetic energy and magnetic helicity under the assumption that the Taylor frozen-in-flow hypothesis is valid. That is a well-satisfied assumption for the data used in this study. The magnetic helicity derives from the skew-symmetric terms of the three-dimensional magnetic correlation tensor, while the symmetric terms of the tensor are used to determine the magnetic energy spectrum. Our results show a sign change of magnetic helicity at wavenumber k approximately equal to 2AU(sup -1) (or frequency nu approximately equal to 2 microHz) at distances below 2.8AU and at k approximately equal to 30AU(sup -1) (or nu approximately equal to 25 microHz) at larger distances. At small scales the magnetic helicity is positive at northern heliographic latitudes and negative at southern latitudes. The positive magnetic helicity at small scales is argued to be the result of turbulent diffusion reversing the sign relative to what is seen at small scales at the solar surface. Furthermore, the magnetic helicity declines toward solar minimum in 1996. The magnetic helicity flux integrated separately over one hemisphere amounts to about 10(sup 45) Mx(sup 2) cycle(sup -1) at large scales and to a three times lower value at smaller scales.

Repeated measures from FIA data facilitates analysis across spatial scales of tree growth responses to nitrogen deposition from individual trees to whole ecoregions

Treesearch

Charles H. (Hobie) Perry; Kevin J. Horn; R. Quinn Thomas; Linda H. Pardo; Erica A.H. Smithwick; Doug Baldwin; Gregory B. Lawrence; Scott W. Bailey; Sabine Braun; Christopher M. Clark; Mark Fenn; Annika Nordin; Jennifer N. Phelan; Paul G. Schaberg; Sam St. Clair; Richard Warby; Shaun Watmough; Steven S. Perakis

2015-01-01

The abundance of temporally and spatially consistent Forest Inventory and Analysis data facilitates hierarchical/multilevel analysis to investigate factors affecting tree growth, scaling from plot-level to continental scales. Herein we use FIA tree and soil inventories in conjunction with various spatial climate and soils data to estimate species-specific responses of...

Analysis of Large Scale Spatial Variability of Soil Moisture Using a Geostatistical Method

DTIC Science & Technology

2010-01-25

2010 / Accepted: 19 January 2010 / Published: 25 January 2010 Abstract: Spatial and temporal soil moisture dynamics are critically needed to...scale observed and simulated estimates of soil moisture under pre- and post-precipitation event conditions. This large scale variability is a crucial... dynamics is essential in the hydrological and meteorological modeling, improves our understanding of land surface–atmosphere interactions. Spatial and

Study of satellite retrieved aerosol optical depth spatial resolution effect on particulate matter concentration prediction

NASA Astrophysics Data System (ADS)

Strandgren, J.; Mei, L.; Vountas, M.; Burrows, J. P.; Lyapustin, A.; Wang, Y.

2014-10-01

The Aerosol Optical Depth (AOD) spatial resolution effect is investigated for the linear correlation between satellite retrieved AOD and ground level particulate matter concentrations (PM2.5). The Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for the Moderate Resolution Imaging Spectroradiometer (MODIS) for obtaining AOD with a high spatial resolution of 1 km and provides a good dataset for the study of the AOD spatial resolution effect on the particulate matter concentration prediction. 946 Environmental Protection Agency (EPA) ground monitoring stations across the contiguous US have been used to investigate the linear correlation between AOD and PM2.5 using AOD at different spatial resolutions (1, 3 and 10 km) and for different spatial scales (urban scale, meso-scale and continental scale). The main conclusions are: (1) for both urban, meso- and continental scale the correlation between PM2.5 and AOD increased significantly with increasing spatial resolution of the AOD, (2) the correlation between AOD and PM2.5 decreased significantly as the scale of study region increased for the eastern part of the US while vice versa for the western part of the US, (3) the correlation between PM2.5 and AOD is much more stable and better over the eastern part of the US compared to western part due to the surface characteristics and atmospheric conditions like the fine mode fraction.

CRKSPH: A new meshfree hydrodynamics method with applications to astrophysics

NASA Astrophysics Data System (ADS)

Owen, John Michael; Raskin, Cody; Frontiere, Nicholas

2018-01-01

The study of astrophysical phenomena such as supernovae, accretion disks, galaxy formation, and large-scale structure formation requires computational modeling of, at a minimum, hydrodynamics and gravity. Developing numerical methods appropriate for these kinds of problems requires a number of properties: shock-capturing hydrodynamics benefits from rigorous conservation of invariants such as total energy, linear momentum, and mass; lack of obvious symmetries or a simplified spatial geometry to exploit necessitate 3D methods that ideally are Galilean invariant; the dynamic range of mass and spatial scales that need to be resolved can span many orders of magnitude, requiring methods that are highly adaptable in their space and time resolution. We have developed a new Lagrangian meshfree hydrodynamics method called Conservative Reproducing Kernel Smoothed Particle Hydrodynamics, or CRKSPH, in order to meet these goals. CRKSPH is a conservative generalization of the meshfree reproducing kernel method, combining the high-order accuracy of reproducing kernels with the explicit conservation of mass, linear momentum, and energy necessary to study shock-driven hydrodynamics in compressible fluids. CRKSPH's Lagrangian, particle-like nature makes it simple to combine with well-known N-body methods for modeling gravitation, similar to the older Smoothed Particle Hydrodynamics (SPH) method. Indeed, CRKSPH can be substituted for SPH in existing SPH codes due to these similarities. In comparison to SPH, CRKSPH is able to achieve substantially higher accuracy for a given number of points due to the explicitly consistent (and higher-order) interpolation theory of reproducing kernels, while maintaining the same conservation principles (and therefore applicability) as SPH. There are currently two coded implementations of CRKSPH available: one in the open-source research code Spheral, and the other in the high-performance cosmological code HACC. Using these codes we have applied CRKSPH to a number of astrophysical scenarios, such as rotating gaseous disks, supernova remnants, and large-scale cosmological structure formation. In this poster we present an overview of CRKSPH and show examples of these astrophysical applications.

Restricted cross-scale habitat selection by American beavers.

PubMed

Francis, Robert A; Taylor, Jimmy D; Dibble, Eric; Strickland, Bronson; Petro, Vanessa M; Easterwood, Christine; Wang, Guiming

2017-12-01

Animal habitat selection, among other ecological phenomena, is spatially scale dependent. Habitat selection by American beavers Castor canadensis (hereafter, beaver) has been studied at singular spatial scales, but to date no research addresses multi-scale selection. Our objectives were to determine if beaver habitat selection was specialized to semiaquatic habitats and if variables explaining habitat selection are consistent between landscape and fine spatial scales. We built maximum entropy (MaxEnt) models to relate landscape-scale presence-only data to landscape variables, and used generalized linear mixed models to evaluate fine spatial scale habitat selection using global positioning system (GPS) relocation data. Explanatory variables between the landscape and fine spatial scale were compared for consistency. Our findings suggested that beaver habitat selection at coarse (study area) and fine (within home range) scales was congruent, and was influenced by increasing amounts of woody wetland edge density and shrub edge density, and decreasing amounts of open water edge density. Habitat suitability at the landscape scale also increased with decreasing amounts of grass frequency. As territorial, central-place foragers, beavers likely trade-off open water edge density (i.e., smaller non-forested wetlands or lodges closer to banks) for defense and shorter distances to forage and obtain construction material. Woody plants along edges and expanses of open water for predator avoidance may limit beaver fitness and subsequently determine beaver habitat selection.

Restricted cross-scale habitat selection by American beavers

PubMed Central

Taylor, Jimmy D; Dibble, Eric; Strickland, Bronson; Petro, Vanessa M; Easterwood, Christine; Wang, Guiming

2017-01-01

Abstract Animal habitat selection, among other ecological phenomena, is spatially scale dependent. Habitat selection by American beavers Castor canadensis (hereafter, beaver) has been studied at singular spatial scales, but to date no research addresses multi-scale selection. Our objectives were to determine if beaver habitat selection was specialized to semiaquatic habitats and if variables explaining habitat selection are consistent between landscape and fine spatial scales. We built maximum entropy (MaxEnt) models to relate landscape-scale presence-only data to landscape variables, and used generalized linear mixed models to evaluate fine spatial scale habitat selection using global positioning system (GPS) relocation data. Explanatory variables between the landscape and fine spatial scale were compared for consistency. Our findings suggested that beaver habitat selection at coarse (study area) and fine (within home range) scales was congruent, and was influenced by increasing amounts of woody wetland edge density and shrub edge density, and decreasing amounts of open water edge density. Habitat suitability at the landscape scale also increased with decreasing amounts of grass frequency. As territorial, central-place foragers, beavers likely trade-off open water edge density (i.e., smaller non-forested wetlands or lodges closer to banks) for defense and shorter distances to forage and obtain construction material. Woody plants along edges and expanses of open water for predator avoidance may limit beaver fitness and subsequently determine beaver habitat selection. PMID:29492032

Spatiotemporal variability of suspended sediment particle size in a mixed-land-use watershed.

PubMed

Kellner, Elliott; Hubbart, Jason A

2018-02-15

Given existing knowledge gaps, there is a need for research that quantitatively characterizes spatiotemporal variation of suspended sediment particle size distribution (PSD) in contemporary watersheds. A five-year study was conducted in a representative watershed of the central United States utilizing a nested-scale experimental watershed study design, comprising five gauging sites partitioning the catchment into five sub-watersheds. Streamwater grab samples were collected four times per week, at each gauging site, for the duration of the study period (Oct. 2009-Feb. 2014). Samples were analyzed using laser particle diffraction. Significantly different (p<0.05) suspended sediment PSDs were observed at monitoring sites throughout the course of the study. For example, results indicated greater proportions of silt at site #5 (65%), relative to other sites (41, 32, 29, and 43%, for sites #1-#4, respectively). Likewise, results showed greater proportions of sand at sites #2 and #3 (66 and 68%, respectively), relative to other sites (57, 55, and 34%, for sites #1, #4, and #5, respectively). PSD spatial variability was not fully explained by hydroclimate or sub-watershed land use/land cover characteristics. Rather, results were strengthened by consideration of surficial geology (e.g. supply-controlled spatial variation of particle size). PSD displayed consistent seasonality during the study, characterized by peaks in the proportion of sand (and aggregates) during the winter (i.e. 70-90%), and minimums during the summer (i.e. 12-38%); and peaks in the proportion of silt particles in the summer (i.e. 61-88%) and minimums in the winter (i.e. 10-23%). Likely explanations of results include seasonal streamflow differences. Results comprise distinct observations of spatiotemporal variation of PSD, thereby improving understanding of lotic suspended sediment regimes and advancing future management practices in mixed-land-use watersheds. Copyright © 2017 Elsevier B.V. All rights reserved.

Integrating expert opinion with modelling for quantitative multi-hazard risk assessment in the Eastern Italian Alps

NASA Astrophysics Data System (ADS)

Chen, Lixia; van Westen, Cees J.; Hussin, Haydar; Ciurean, Roxana L.; Turkington, Thea; Chavarro-Rincon, Diana; Shrestha, Dhruba P.

2016-11-01

Extreme rainfall events are the main triggering causes for hydro-meteorological hazards in mountainous areas, where development is often constrained by the limited space suitable for construction. In these areas, hazard and risk assessments are fundamental for risk mitigation, especially for preventive planning, risk communication and emergency preparedness. Multi-hazard risk assessment in mountainous areas at local and regional scales remain a major challenge because of lack of data related to past events and causal factors, and the interactions between different types of hazards. The lack of data leads to a high level of uncertainty in the application of quantitative methods for hazard and risk assessment. Therefore, a systematic approach is required to combine these quantitative methods with expert-based assumptions and decisions. In this study, a quantitative multi-hazard risk assessment was carried out in the Fella River valley, prone to debris flows and flood in the north-eastern Italian Alps. The main steps include data collection and development of inventory maps, definition of hazard scenarios, hazard assessment in terms of temporal and spatial probability calculation and intensity modelling, elements-at-risk mapping, estimation of asset values and the number of people, physical vulnerability assessment, the generation of risk curves and annual risk calculation. To compare the risk for each type of hazard, risk curves were generated for debris flows, river floods and flash floods. Uncertainties were expressed as minimum, average and maximum values of temporal and spatial probability, replacement costs of assets, population numbers, and physical vulnerability. These result in minimum, average and maximum risk curves. To validate this approach, a back analysis was conducted using the extreme hydro-meteorological event that occurred in August 2003 in the Fella River valley. The results show a good performance when compared to the historical damage reports.

AEGIS: a wildfire prevention and management information system

NASA Astrophysics Data System (ADS)

Kalabokidis, Kostas; Ager, Alan; Finney, Mark; Athanasis, Nikos; Palaiologou, Palaiologos; Vasilakos, Christos

2016-03-01

We describe a Web-GIS wildfire prevention and management platform (AEGIS) developed as an integrated and easy-to-use decision support tool to manage wildland fire hazards in Greece (http://aegis.aegean.gr). The AEGIS platform assists with early fire warning, fire planning, fire control and coordination of firefighting forces by providing online access to information that is essential for wildfire management. The system uses a number of spatial and non-spatial data sources to support key system functionalities. Land use/land cover maps were produced by combining field inventory data with high-resolution multispectral satellite images (RapidEye). These data support wildfire simulation tools that allow the users to examine potential fire behavior and hazard with the Minimum Travel Time fire spread algorithm. End-users provide a minimum number of inputs such as fire duration, ignition point and weather information to conduct a fire simulation. AEGIS offers three types of simulations, i.e., single-fire propagation, point-scale calculation of potential fire behavior, and burn probability analysis, similar to the FlamMap fire behavior modeling software. Artificial neural networks (ANNs) were utilized for wildfire ignition risk assessment based on various parameters, training methods, activation functions, pre-processing methods and network structures. The combination of ANNs and expected burned area maps are used to generate integrated output map of fire hazard prediction. The system also incorporates weather information obtained from remote automatic weather stations and weather forecast maps. The system and associated computation algorithms leverage parallel processing techniques (i.e., High Performance Computing and Cloud Computing) that ensure computational power required for real-time application. All AEGIS functionalities are accessible to authorized end-users through a web-based graphical user interface. An innovative smartphone application, AEGIS App, also provides mobile access to the web-based version of the system.

Optimal redistribution of an urban air quality monitoring network using atmospheric dispersion model and genetic algorithm

NASA Astrophysics Data System (ADS)

Hao, Yufang; Xie, Shaodong

2018-03-01

Air quality monitoring networks play a significant role in identifying the spatiotemporal patterns of air pollution, and they need to be deployed efficiently, with a minimum number of sites. The revision and optimal adjustment of existing monitoring networks is crucial for cities that have undergone rapid urban expansion and experience temporal variations in pollution patterns. The approach based on the Weather Research and Forecasting-California PUFF (WRF-CALPUFF) model and genetic algorithm (GA) was developed to design an optimal monitoring network. The maximization of coverage with minimum overlap and the ability to detect violations of standards were developed as the design objectives for redistributed networks. The non-dominated sorting genetic algorithm was applied to optimize the network size and site locations simultaneously for Shijiazhuang city, one of the most polluted cities in China. The assessment on the current network identified the insufficient spatial coverage of SO2 and NO2 monitoring for the expanding city. The optimization results showed that significant improvements were achieved in multiple objectives by redistributing the original network. Efficient coverage of the resulting designs improved to 60.99% and 76.06% of the urban area for SO2 and NO2, respectively. The redistributing design for multi-pollutant including 8 sites was also proposed, with the spatial representation covered 52.30% of the urban area and the overlapped areas decreased by 85.87% compared with the original network. The abilities to detect violations of standards were not improved as much as the other two objectives due to the conflicting nature between the multiple objectives. Additionally, the results demonstrated that the algorithm was slightly sensitive to the parameter settings, with the number of generations presented the most significant effect. Overall, our study presents an effective and feasible procedure for air quality network optimization at a city scale.

Scale structure: Processing Minimum Standard and Maximum Standard Scalar Adjectives

PubMed Central

Frazier, Lyn; Clifton, Charles; Stolterfoht, Britta

2008-01-01

Gradable adjectives denote a function that takes an object and returns a measure of the degree to which the object possesses some gradable property (Kennedy, 1999). Scales, ordered sets of degrees, have begun to be studied systematically in semantics (Kennedy, to appear, Kennedy & McNally, 2005, Rotstein & Winter, 2004). We report four experiments designed to investigate the processing of absolute adjectives with a maximum standard (e.g., clean) and their minimum standard antonyms (dirty). The central hypothesis is that the denotation of an absolute adjective introduces a ‘standard value’ on a scale as part of the normal comprehension of a sentence containing the adjective (the “Obligatory Scale” hypothesis). In line with the predictions of Kennedy and McNally (2005) and Rotstein and Winter (2004), maximum standard adjectives and minimum standard adjectives systematically differ from each other when they are combined with minimizing modifiers like slightly, as indicated by speeded acceptability judgments. An eye movement recording study shows that, as predicted by the Obligatory Scale hypothesis, the penalty due to combining slightly with a maximum standard adjective can be observed during the processing of the sentence; the penalty is not the result of some after-the-fact inferencing mechanism. Further, a type of ‘quantificational variability effect’ may be observed when a quantificational adverb (mostly) is combined with a minimum standard adjective in sentences like The dishes are mostly dirty, which may receive either a degree interpretation (e.g. 80% dirty) or a quantity interpretation (e.g., 80% of the dishes are dirty). The quantificational variability results provide suggestive support for the Obligatory Scale hypothesis by showing that the standard of a scalar adjective influences the preferred interpretation of other constituents in the sentence. PMID:17376422

Comparison of dislocation density tensor fields derived from discrete dislocation dynamics and crystal plasticity simulations of torsion

DOE PAGES

Jones, Reese E.; Zimmerman, Jonathan A.; Po, Giacomo; ...

2016-02-01

Accurate simulation of the plastic deformation of ductile metals is important to the design of structures and components to performance and failure criteria. Many techniques exist that address the length scales relevant to deformation processes, including dislocation dynamics (DD), which models the interaction and evolution of discrete dislocation line segments, and crystal plasticity (CP), which incorporates the crystalline nature and restricted motion of dislocations into a higher scale continuous field framework. While these two methods are conceptually related, there have been only nominal efforts focused at the global material response that use DD-generated information to enhance the fidelity of CPmore » models. To ascertain to what degree the predictions of CP are consistent with those of DD, we compare their global and microstructural response in a number of deformation modes. After using nominally homogeneous compression and shear deformation dislocation dynamics simulations to calibrate crystal plasticity ow rule parameters, we compare not only the system-level stress-strain response of prismatic wires in torsion but also the resulting geometrically necessary dislocation density fields. To establish a connection between explicit description of dislocations and the continuum assumed with crystal plasticity simulations we ascertain the minimum length-scale at which meaningful dislocation density fields appear. Furthermore, our results show that, for the case of torsion, that the two material models can produce comparable spatial dislocation density distributions.« less

Process scales in catchment science: a new synthesis

EPA Science Inventory

Concerns surrounding data resolution, choice of spatial and temporal scales in research design, and problems with extrapolation of processes across spatial and temporal scales differ greatly between scientific process-elucidation research and scenario exploration for watershed ma...

Cross-scale analysis of fire regimes

Treesearch

Donald A. Falk; Carol Miller; Donald McKenzie; Anne E. Black

2007-01-01

Cross-scale spatial and temporal perspectives are important for studying contagious landscape disturbances such as fire, which are controlled by myriad processes operating at different scales. We examine fire regimes in forests of western North America, focusing on how observed patterns of fire frequency change across spatial scales. To quantify changes in fire...

Predictor variable resolution governs modeled soil types

USDA-ARS?s Scientific Manuscript database

Soil mapping identifies different soil types by compressing a unique suite of spatial patterns and processes across multiple spatial scales. It can be quite difficult to quantify spatial patterns of soil properties with remotely sensed predictor variables. More specifically, matching the right scale...

Range-wide wetland associations of the King Rail: A multi-scale approach

USGS Publications Warehouse

Glisson, Wesley J.; Conway, Courtney J.; Nadeau, Christopher P.; Borgmann, Kathi L.; Laxson, Thomas A.

2015-01-01

King Rail populations have declined and identifying wetland features that influence King Rail occupancy can help prevent further population declines. We integrated continent-wide marsh bird survey data with spatial wetland data from the National Wetland Inventory (NWI) to examine wetland features that influenced King Rail occupancy throughout the species’ range. We analyzed wetland data at 7 spatial scales to examine the scale(s) at which 68 wetland features were most strongly related to King Rail occupancy. Occupancy was most strongly associated with estuarine features and brackish and tidal saltwater regimes. King Rail occupancy was positively associated with emergent and scrub-shrub wetlands and negatively associated with forested wetlands. The best spatial scale for assessing King Rail occupancy differed among wetland features; we could not identify one spatial scale (among all wetland features) that best explained variation in occupancy. Future research on King Rail habitat that includes multiple spatial scales is more likely to identify the suite of features that influence occupancy. Our results indicate that NWI data may be useful for predicting occupancy based on broad habitat features across the King Rail’s range, which may help inform management decisions for this and other wetland-dependent birds.

A Spatial Method to Calculate Small-Scale Fisheries Extent

NASA Astrophysics Data System (ADS)

Johnson, A. F.; Moreno-Báez, M.; Giron-Nava, A.; Corominas, J.; Erisman, B.; Ezcurra, E.; Aburto-Oropeza, O.

2016-02-01

Despite global catch per unit effort having redoubled since the 1950's, the global fishing fleet is estimated to be twice the size that the oceans can sustainably support. In order to gauge the collateral impacts of fishing intensity, we must be able to estimate the spatial extent and amount of fishing vessels in the oceans. Methods that do currently exist are built around electronic tracking and log book systems and generally focus on industrial fisheries. Spatial extent for small-scale fisheries therefore remains elusive for many small-scale fishing fleets; even though these fisheries land the same biomass for human consumption as industrial fisheries. Current methods are data-intensive and require extensive extrapolation when estimated across large spatial scales. We present an accessible, spatial method of calculating the extent of small-scale fisheries based on two simple measures that are available, or at least easily estimable, in even the most data poor fisheries: the number of boats and the local coastal human population. We demonstrate this method is fishery-type independent and can be used to quantitatively evaluate the efficacy of growth in small-scale fisheries. This method provides an important first step towards estimating the fishing extent of the small-scale fleet, globally.

Spatial Covariability of Temperature and Hydroclimate as a Function of Timescale During the Common Era

NASA Astrophysics Data System (ADS)

McKay, N.

2017-12-01

As timescale increases from years to centuries, the spatial scale of covariability in the climate system is hypothesized to increase as well. Covarying spatial scales are larger for temperature than for hydroclimate, however, both aspects of the climate system show systematic changes on large-spatial scales on orbital to tectonic timescales. The extent to which this phenomenon is evident in temperature and hydroclimate at centennial timescales is largely unknown. Recent syntheses of multidecadal to century-scale variability in hydroclimate during the past 2k in the Arctic, North America, and Australasia show little spatial covariability in hydroclimate during the Common Era. To determine 1) the evidence for systematic relationships between the spatial scale of climate covariability as a function of timescale, and 2) whether century-scale hydroclimate variability deviates from the relationship between spatial covariability and timescale, we quantify this phenomenon during the Common Era by calculating the e-folding distance in large instrumental and paleoclimate datasets. We calculate this metric of spatial covariability, at different timescales (1, 10 and 100-yr), for a large network of temperature and precipitation observations from the Global Historical Climatology Network (n=2447), from v2.0.0 of the PAGES2k temperature database (n=692), and from moisture-sensitive paleoclimate records North America, the Arctic, and the Iso2k project (n = 328). Initial results support the hypothesis that the spatial scale of covariability is larger for temperature, than for precipitation or paleoclimate hydroclimate indicators. Spatially, e-folding distances for temperature are largest at low latitudes and over the ocean. Both instrumental and proxy temperature data show clear evidence for increasing spatial extent as a function of timescale, but this phenomenon is very weak in the hydroclimate data analyzed here. In the proxy hydroclimate data, which are predominantly indicators of effective moisture, e-folding distance increases from annual to decadal timescales, but does not continue to increase to centennial timescales. Future work includes examining additional instrumental and proxy datasets of moisture variability, and extending the analysis to millennial timescales of variability.

Delineation and validation of river network spatial scales for water resources and fisheries management.

PubMed

Wang, Lizhu; Brenden, Travis; Cao, Yong; Seelbach, Paul

2012-11-01

Identifying appropriate spatial scales is critically important for assessing health, attributing data, and guiding management actions for rivers. We describe a process for identifying a three-level hierarchy of spatial scales for Michigan rivers. Additionally, we conduct a variance decomposition of fish occurrence, abundance, and assemblage metric data to evaluate how much observed variability can be explained by the three spatial scales as a gage of their utility for water resources and fisheries management. The process involved the development of geographic information system programs, statistical models, modification by experienced biologists, and simplification to meet the needs of policy makers. Altogether, 28,889 reaches, 6,198 multiple-reach segments, and 11 segment classes were identified from Michigan river networks. The segment scale explained the greatest amount of variation in fish abundance and occurrence, followed by segment class, and reach. Segment scale also explained the greatest amount of variation in 13 of the 19 analyzed fish assemblage metrics, with segment class explaining the greatest amount of variation in the other six fish metrics. Segments appear to be a useful spatial scale/unit for measuring and synthesizing information for managing rivers and streams. Additionally, segment classes provide a useful typology for summarizing the numerous segments into a few categories. Reaches are the foundation for the identification of segments and segment classes and thus are integral elements of the overall spatial scale hierarchy despite reaches not explaining significant variation in fish assemblage data.

Spatial pattern of Baccharis platypoda shrub as determined by sex and life stages

NASA Astrophysics Data System (ADS)

Fonseca, Darliana da Costa; de Oliveira, Marcio Leles Romarco; Pereira, Israel Marinho; Gonzaga, Anne Priscila Dias; de Moura, Cristiane Coelho; Machado, Evandro Luiz Mendonça

2017-11-01

Spatial patterns of dioecious species can be determined by their nutritional requirements and intraspecific competition, apart from being a response to environmental heterogeneity. The aim of the study was to evaluate the spatial pattern of populations of a dioecious shrub reporting to sex and reproductive stage patterns of individuals. Sampling was carried out in three areas located in the meridional portion of Serra do Espinhaço, where in individuals of the studied species were mapped. The spatial pattern was determined through O-ring analysis and Ripley's K-function and the distribution of individuals' frequencies was verified through x2 test. Populations in two areas showed an aggregate spatial pattern tending towards random or uniform according to the observed scale. Male and female adults presented an aggregate pattern at smaller scales, while random and uniform patterns were verified above 20 m for individuals of both sexes of the areas A2 and A3. Young individuals presented an aggregate pattern in all areas and spatial independence in relation to adult individuals, especially female plants. The interactions between individuals of both genders presented spatial independence with respect to spatial distribution. Baccharis platypoda showed characteristics in accordance with the spatial distribution of savannic and dioecious species, whereas the population was aggregated tending towards random at greater spatial scales. Young individuals showed an aggregated pattern at different scales compared to adults, without positive association between them. Female and male adult individuals presented similar characteristics, confirming that adult individuals at greater scales are randomly distributed despite their distinct preferences for environments with moisture variation.

Exponential bound in the quest for absolute zero

NASA Astrophysics Data System (ADS)

Stefanatos, Dionisis

2017-10-01

In most studies for the quantification of the third law of thermodynamics, the minimum temperature which can be achieved with a long but finite-time process scales as a negative power of the process duration. In this article, we use our recent complete solution for the optimal control problem of the quantum parametric oscillator to show that the minimum temperature which can be obtained in this system scales exponentially with the available time. The present work is expected to motivate further research in the active quest for absolute zero.

Exponential bound in the quest for absolute zero.

PubMed

Stefanatos, Dionisis

2017-10-01

In most studies for the quantification of the third law of thermodynamics, the minimum temperature which can be achieved with a long but finite-time process scales as a negative power of the process duration. In this article, we use our recent complete solution for the optimal control problem of the quantum parametric oscillator to show that the minimum temperature which can be obtained in this system scales exponentially with the available time. The present work is expected to motivate further research in the active quest for absolute zero.

Spatial Pattern of Attacks of the Invasive Woodwasp Sirex noctilio, at Landscape and Stand Scales.

PubMed

Lantschner, M Victoria; Corley, Juan C

2015-01-01

Invasive insect pests are responsible for important damage to native and plantation forests, when population outbreaks occur. Understanding the spatial pattern of attacks by forest pest populations is essential to improve our understanding of insect population dynamics and for predicting attack risk by invasives or planning pest management strategies. The woodwasp Sirex noctilio is an invasive woodwasp that has become probably the most important pest of pine plantations in the Southern Hemisphere. Our aim was to study the spatial dynamics of S. noctilio populations in Southern Argentina. Specifically we describe: (1) the spatial patterns of S. noctilio outbreaks and their relation with environmental factors at a landscape scale; and (2) characterize the spatial pattern of attacked trees at the stand scale. We surveyed the spatial distribution of S. noctilio outbreaks in three pine plantation landscapes, and we assessed potential associations with topographic variables, habitat characteristics, and distance to other outbreaks. We also looked at the spatial distribution of attacked trees in 20 stands with different levels of infestation, and assessed the relationship of attacks with stand composition and management. We found that the spatial pattern of pine stands with S. noctilio outbreaks at the landscape scale is influenced mainly by the host species present, slope aspect, and distance to other outbreaks. At a stand scale, there is strong aggregation of attacked trees in stands with intermediate infestation levels, and the degree of attacks is influenced by host species and plantation management. We conclude that the pattern of S. noctilio damage at different spatial scales is influenced by a combination of both inherent population dynamics and the underlying patterns of environmental factors. Our results have important implications for the understanding and management of invasive insect outbreaks in forest systems.

Simulation of nitrate reduction in groundwater - An upscaling approach from small catchments to the Baltic Sea basin

NASA Astrophysics Data System (ADS)

Hansen, A. L.; Donnelly, C.; Refsgaard, J. C.; Karlsson, I. B.

2018-01-01

This paper describes a modeling approach proposed to simulate the impact of local-scale, spatially targeted N-mitigation measures for the Baltic Sea Basin. Spatially targeted N-regulations aim at exploiting the considerable spatial differences in the natural N-reduction taking place in groundwater and surface water. While such measures can be simulated using local-scale physically-based catchment models, use of such detailed models for the 1.8 million km2 Baltic Sea basin is not feasible due to constraints on input data and computing power. Large-scale models that are able to simulate the Baltic Sea basin, on the other hand, do not have adequate spatial resolution to simulate some of the field-scale measures. Our methodology combines knowledge and results from two local-scale physically-based MIKE SHE catchment models, the large-scale and more conceptual E-HYPE model, and auxiliary data in order to enable E-HYPE to simulate how spatially targeted regulation of agricultural practices may affect N-loads to the Baltic Sea. We conclude that the use of E-HYPE with this upscaling methodology enables the simulation of the impact on N-loads of applying a spatially targeted regulation at the Baltic Sea basin scale to the correct order-of-magnitude. The E-HYPE model together with the upscaling methodology therefore provides a sound basis for large-scale policy analysis; however, we do not expect it to be sufficiently accurate to be useful for the detailed design of local-scale measures.

Interactive effects of nitrogen addition, warming and invasion across organizational levels in an old-field plant community.

PubMed

Gornish, Elise S

2014-10-08

Response to global change is dependent on the level of biological organization (e.g. the ecologically relevant spatial scale) in which species are embedded. For example, individual responses can affect population-level responses, which, in turn, can affect community-level responses. Although relationships are known to exist among responses to global change across levels of biological organization, formal investigations of these relationships are still uncommon. I conducted an exploratory analysis to identify how nitrogen addition and warming by open top chambers might affect plants across spatial scales by estimating treatment effect size at the leaf level, the plant level and the community level. Moreover, I investigated if the presence of Pityopsis aspera, an experimentally introduced plant species, modified the relationship between spatial scale and effect size across treatments. I found that, overall, the spatial scale significantly contributes to differences in effect size, supporting previous work which suggests that mechanisms driving biotic response to global change are scale dependent. Interestingly, the relationship between spatial scale and effect size in both the absence and presence of experimental invasion is very similar for nitrogen addition and warming treatments. The presence of invasion, however, did not affect the relationship between spatial scale and effect size, suggesting that in this system, invasion may not exacerbate or attenuate climate change effects. This exercise highlights the value of moving beyond integration and scaling to the practice of directly testing for scale effects within single experiments. Published by Oxford University Press on behalf of the Annals of Botany Company.

How large is large enough for insects? Forest fragmentation effects at three spatial scales

NASA Astrophysics Data System (ADS)

Ribas, C. R.; Sobrinho, T. G.; Schoereder, J. H.; Sperber, C. F.; Lopes-Andrade, C.; Soares, S. M.

2005-02-01

Several mechanisms may lead to species loss in fragmented habitats, such as edge and shape effects, loss of habitat and heterogeneity. Ants and crickets were sampled in 18 forest remnants in south-eastern Brazil, to test whether a group of small remnants maintains the same insect species richness as similar sized large remnants, at three spatial scales. We tested hypotheses about alpha and gamma diversity to explain the results. Groups of remnants conserve as many species of ants as a single one. Crickets, however, showed a scale-dependent pattern: at small scales there was no significant or important difference between groups of remnants and a single one, while at the larger scale the group of remnants maintained more species. Alpha diversity (local species richness) was similar in a group of remnants and in a single one, at the three spatial scales, both for ants and crickets. Gamma diversity, however, varied both with taxa (ants and crickets) and spatial scale, which may be linked to insect mobility, remnant isolation, and habitat heterogeneity. Biological characteristics of the organisms involved have to be considered when studying fragmentation effects, as well as spatial scale at which it operates. Mobility of the organisms influences fragmentation effects, and consequently conservation strategies.

Imaging spectroscopy links aspen genotype with below-ground processes at landscape scales

PubMed Central

Madritch, Michael D.; Kingdon, Clayton C.; Singh, Aditya; Mock, Karen E.; Lindroth, Richard L.; Townsend, Philip A.

2014-01-01

Fine-scale biodiversity is increasingly recognized as important to ecosystem-level processes. Remote sensing technologies have great potential to estimate both biodiversity and ecosystem function over large spatial scales. Here, we demonstrate the capacity of imaging spectroscopy to discriminate among genotypes of Populus tremuloides (trembling aspen), one of the most genetically diverse and widespread forest species in North America. We combine imaging spectroscopy (AVIRIS) data with genetic, phytochemical, microbial and biogeochemical data to determine how intraspecific plant genetic variation influences below-ground processes at landscape scales. We demonstrate that both canopy chemistry and below-ground processes vary over large spatial scales (continental) according to aspen genotype. Imaging spectrometer data distinguish aspen genotypes through variation in canopy spectral signature. In addition, foliar spectral variation correlates well with variation in canopy chemistry, especially condensed tannins. Variation in aspen canopy chemistry, in turn, is correlated with variation in below-ground processes. Variation in spectra also correlates well with variation in soil traits. These findings indicate that forest tree species can create spatial mosaics of ecosystem functioning across large spatial scales and that these patterns can be quantified via remote sensing techniques. Moreover, they demonstrate the utility of using optical properties as proxies for fine-scale measurements of biodiversity over large spatial scales. PMID:24733949

Minimum detectable gas concentration performance evaluation method for gas leak infrared imaging detection systems.

PubMed

Zhang, Xu; Jin, Weiqi; Li, Jiakun; Wang, Xia; Li, Shuo

2017-04-01

Thermal imaging technology is an effective means of detecting hazardous gas leaks. Much attention has been paid to evaluation of the performance of gas leak infrared imaging detection systems due to several potential applications. The minimum resolvable temperature difference (MRTD) and the minimum detectable temperature difference (MDTD) are commonly used as the main indicators of thermal imaging system performance. This paper establishes a minimum detectable gas concentration (MDGC) performance evaluation model based on the definition and derivation of MDTD. We proposed the direct calculation and equivalent calculation method of MDGC based on the MDTD measurement system. We build an experimental MDGC measurement system, which indicates the MDGC model can describe the detection performance of a thermal imaging system to typical gases. The direct calculation, equivalent calculation, and direct measurement results are consistent. The MDGC and the minimum resolvable gas concentration (MRGC) model can effectively describe the performance of "detection" and "spatial detail resolution" of thermal imaging systems to gas leak, respectively, and constitute the main performance indicators of gas leak detection systems.

Seeing is believing I: The use of thermal sensing from satellite imagery to predict crop yield

NASA Astrophysics Data System (ADS)

B, Potgieter A.; D, Rodriguez; B, Power; J, Mclean; P, Davis

2014-02-01

Volatility in crop production has been part of the Australian environment since cropping began with the arrival of the first European settlers. Climate variability is the main factor affecting crop production at national, state and local scales. At field level spatial patterns on yield production are also determined by spatially changing soil properties in interaction with seasonal climate conditions and weather patterns at critical stages in the crop development. Here we used a combination of field level weather records, canopy characteristics, and satellite information to determine the spatial performance of a large field of wheat. The main objective of this research is to determine the ability of remote sensing technologies to capture yield losses due to water stress at the canopy level. The yield, canopy characteristics (i.e. canopy temperature and ground cover) and seasonal conditions of a field of wheat (~1400ha) (-29.402° South and 149.508°, New South Wales, Australia) were continuously monitored during the winter of 2011. Weather and crop variables were continuously monitored by installing three automatic weather stations in a transect covering different positions and soils in the landscape. Weather variables included rainfall, minimum and maximum temperatures and relative humidity, and crop characteristics included ground cover and canopy temperature. Satellite imagery Landsat TM 5 and 7 was collected at five different stages in the crop cycle. Weather variables and crop characteristics were used to calculate a crop stress index (CSI) at point and field scale (39 fields). Field data was used to validate a spatial satellite image derived index. Spatial yield data was downloaded from the harvester at the different locations in the field. We used the thermal band (land surface temperature, LST) and enhanced vegetation index (EVI) bands from the MODIS (250 m for visible bands and 1km for thermal band) and a derived EVI from Landsat TM 7 (25 m for visible and 90m for thermal) satellite platforms. Results showed that spatial variations in crop yield were related to a satellite derived canopy stress index (CSIsat) and a moisture stress index (MSIsat). A weather station level canopy stress index (CSIws) calculated at midday was correlated to the CSIsat at late morning. In addition, a strong linear relationship was observed between EVI and LST at point scale throughout the crop growth period. Differences were smallest at anthesis when the canopy closure was highest. This suggests that LST imagery data around flowering could be used to calculate crop stress over large areas of the crop. The harvested yield was related (R2 = 0.67) to CSIsat using a fix date across all fields. This relationship improved (R2 = 0.92) using both indices from all five dates across all fields during the crop growth period. Here we successfully showed that satellite derived crop attributes (CSIsat and MSIsat) can account for most of the variability in final crop yield and that they can be used to predict crop yield at field scales. Applications of these results could enhance the ability of producers to hedge their financial on -farm crop production losses due to in-season water stress by taking crop insurance. This is likely to further improve their adaptive capacity and thus strengthening the long-term viability of the industry domestically and elsewhere.

Home range, den selection and habitat use of Carolina northern flying squirrels (Glaucomys sabrinus coloratus)

USGS Publications Warehouse

Diggins, Corinne A.; Silvis, Alexander; Kelly, Christine A.; Ford, W. Mark

2017-01-01

Context: Understanding habitat selection is important for determining conservation and management strategies for endangered species. The Carolina northern flying squirrel (CNFS; Glaucomys sabrinus coloratus) is an endangered subspecies found in the high-elevation montane forests of the southern Appalachians, USA. The primary use of nest boxes to monitor CNFS has provided biased information on habitat use for this subspecies, as nest boxes are typically placed in suitable denning habitat.Aims: We conducted a radio-telemetry study on CNFS to determine home range, den site selection and habitat use at multiple spatial scales.Methods: We radio-collared 21 CNFS in 2012 and 2014–15. We tracked squirrels to diurnal den sites and during night-time activity.Key results: The MCP (minimum convex polygon) home range at 95% for males was 5.2 ± 1.2 ha and for females was 4.0 ± 0.7. The BRB (biased random bridge) home range at 95% for males was 10.8 ± 3.8 ha and for females was 8.3 ± 2.1. Den site (n = 81) selection occurred more frequently in montane conifer dominate forests (81.4%) vs northern hardwood forests or conifer–northern hardwood forests (9.9% and 8.7%, respectively). We assessed habitat selection using Euclidean distance-based analysis at the 2nd order and 3rd order scale. We found that squirrels were non-randomly selecting for habitat at both 2nd and 3rd order scales.Conclusions: At both spatial scales, CNFS preferentially selected for montane conifer forests more than expected based on availability on the landscape. Squirrels selected neither for nor against northern hardwood forests, regardless of availability on the landscape. Additionally, CNFS denned in montane conifer forests more than other habitat types.Implications: Our results highlight the importance of montane conifer to CNFS in the southern Appalachians. Management and restoration activities that increase the quality, connectivity and extent of this naturally rare forest type may be important for long-term conservation of this subspecies, especially with the impending threat of anthropogenic climate change.

Recent Studies of the Behavior of the Sun's White-Light Corona Over Time

NASA Technical Reports Server (NTRS)

SaintCyr, O. C.; Young, D. E.; Pesnell, W. D.; Lecinski, A.; Eddy, J.

2008-01-01

Predictions of upcoming solar cycles are often related to the nature and dynamics of the Sun's polar magnetic field and its influence on the corona. For the past 30 years we have a more-or-less continuous record of the Sun's white-light corona from groundbased and spacebased coronagraphs. Over that interval, the large scale features of the corona have varied in what we now consider a 'predictable' fashion--complex, showing multiple streamers at all latitudes during solar activity maximum; and a simple dipolar shape aligned with the rotational pole during solar minimum. Over the past three decades the white-light corona appears to be a better indicator of 'true' solar minimum than sunspot number since sunspots disappear for months (even years) at solar minimum. Since almost all predictions of the timing of the next solar maximum depend on the timing of solar minimum, the white-light corona is a potentially important observational discriminator for future predictors. In this contribution we describe recent work quantifying the large-scale appearance of the Sun's corona to correlate it with the sunspot record, especially around solar minimum. These three decades can be expanded with the HAO archive of eclipse photographs which, although sparse compared to the coronagraphic coverage, extends back to 1869. A more extensive understanding of this proxy would give researchers confidence in using the white-light corona as an indicator of solar minimum conditions.

Minimum Sample Size Requirements for Mokken Scale Analysis

ERIC Educational Resources Information Center

Straat, J. Hendrik; van der Ark, L. Andries; Sijtsma, Klaas

2014-01-01

An automated item selection procedure in Mokken scale analysis partitions a set of items into one or more Mokken scales, if the data allow. Two algorithms are available that pursue the same goal of selecting Mokken scales of maximum length: Mokken's original automated item selection procedure (AISP) and a genetic algorithm (GA). Minimum…

Harnessing Big Data to Represent 30-meter Spatial Heterogeneity in Earth System Models

NASA Astrophysics Data System (ADS)

Chaney, N.; Shevliakova, E.; Malyshev, S.; Van Huijgevoort, M.; Milly, C.; Sulman, B. N.

2016-12-01

Terrestrial land surface processes play a critical role in the Earth system; they have a profound impact on the global climate, food and energy production, freshwater resources, and biodiversity. One of the most fascinating yet challenging aspects of characterizing terrestrial ecosystems is their field-scale (˜30 m) spatial heterogeneity. It has been observed repeatedly that the water, energy, and biogeochemical cycles at multiple temporal and spatial scales have deep ties to an ecosystem's spatial structure. Current Earth system models largely disregard this important relationship leading to an inadequate representation of ecosystem dynamics. In this presentation, we will show how existing global environmental datasets can be harnessed to explicitly represent field-scale spatial heterogeneity in Earth system models. For each macroscale grid cell, these environmental data are clustered according to their field-scale soil and topographic attributes to define unique sub-grid tiles. The state-of-the-art Geophysical Fluid Dynamics Laboratory (GFDL) land model is then used to simulate these tiles and their spatial interactions via the exchange of water, energy, and nutrients along explicit topographic gradients. Using historical simulations over the contiguous United States, we will show how a robust representation of field-scale spatial heterogeneity impacts modeled ecosystem dynamics including the water, energy, and biogeochemical cycles as well as vegetation composition and distribution.

Imaging the Subsurface of the Thuringian Basin (Germany) on Different Spatial Scales

NASA Astrophysics Data System (ADS)

Goepel, A.; Krause, M.; Methe, P.; Kukowski, N.

2014-12-01

Understanding the coupled dynamics of near surface and deep fluid flow patterns is essential to characterize the properties of sedimentary basins, to identify the processes of compaction, diagenesis, and transport of mass and energy. The multidisciplinary project INFLUINS (Integrated FLUid dynamics IN Sedimentary basins) aims for investigating the behavior of fluids in the Thuringian Basin, a small intra-continental sedimentary basin in Germany, at different spatial scales, ranging from the pore scale to the extent of the entire basin. As hydraulic properties often significantly vary with spatial scales, e.g. seismic data using different frequencies are required to gain information about the spatial variability of elastic and hydraulic subsurface properties. For the Thuringian Basin, we use seismic and borehole data acquired in the framework of INFLUINS. Basin-wide structural imaging data are available from 2D reflection seismic profiles as well as 2.5D and 3D seismic travel time tomography. Further, core material from a 1,179 m deep drill hole completed in 2013 is available for laboratory seismic experiments on mm- to cm-scale. The data are complemented with logging data along the entire drill hole. This campaign yielded e.g. sonic and density logs allowing the estimation of in-situ P-velocity and acoustic impedance with a spatial resolution on the cm-scale and provides improved information about petrologic and stratigraphic variability at different scales. Joint interpretation of basin scale structural and elastic properties data with laboratory scale data from ultrasound experiments using core samples enables a detailed and realistic imaging of the subsurface properties on different spatial scales. Combining seismic travel time tomography with stratigraphic interpretation provides useful information of variations in the elastic properties for certain geological units and therefore gives indications for changes in hydraulic properties.

Exploring the effect of the spatial scale of fishery management.

PubMed

Takashina, Nao; Baskett, Marissa L

2016-02-07

For any spatially explicit management, determining the appropriate spatial scale of management decisions is critical to success at achieving a given management goal. Specifically, managers must decide how much to subdivide a given managed region: from implementing a uniform approach across the region to considering a unique approach in each of one hundred patches and everything in between. Spatially explicit approaches, such as the implementation of marine spatial planning and marine reserves, are increasingly used in fishery management. Using a spatially explicit bioeconomic model, we quantify how the management scale affects optimal fishery profit, biomass, fishery effort, and the fraction of habitat in marine reserves. We find that, if habitats are randomly distributed, the fishery profit increases almost linearly with the number of segments. However, if habitats are positively autocorrelated, then the fishery profit increases with diminishing returns. Therefore, the true optimum in management scale given cost to subdivision depends on the habitat distribution pattern. Copyright © 2015 Elsevier Ltd. All rights reserved.

Multi-Timescale Analysis of the Spatial Representativeness of In Situ Soil Moisture Data within Satellite Footprints

NASA Astrophysics Data System (ADS)

Molero, B.; Leroux, D. J.; Richaume, P.; Kerr, Y. H.; Merlin, O.; Cosh, M. H.; Bindlish, R.

2018-01-01

We conduct a novel comprehensive investigation that seeks to prove the connection between spatial scales and timescales in surface soil moisture (SM) within the satellite footprint ( 50 km). Modeled and measured point series at Yanco and Little Washita in situ networks are first decomposed into anomalies at timescales ranging from 0.5 to 128 days, using wavelet transforms. Then, their degree of spatial representativeness is evaluated on a per-timescale basis by comparison to large spatial scale data sets (the in situ spatial average, SMOS, AMSR2, and ECMWF). Four methods are used for this: temporal stability analysis (TStab), triple collocation (TC), percentage of correlated areas (CArea), and a new proposed approach that uses wavelet-based correlations (WCor). We found that the mean of the spatial representativeness values tends to increase with the timescale but so does their dispersion. Locations exhibit poor spatial representativeness at scales below 4 days, while either very good or poor representativeness at seasonal scales. Regarding the methods, TStab cannot be applied to the anomaly series due to their multiple zero-crossings, and TC is suitable for week and month scales but not for other scales where data set cross-correlations are found low. In contrast, WCor and CArea give consistent results at all timescales. WCor is less sensitive to the spatial sampling density, so it is a robust method that can be applied to sparse networks (one station per footprint). These results are promising to improve the validation and downscaling of satellite SM series and the optimization of SM networks.

Fine-scale natal homing and localized movement as shaped by sex and spawning habitat in chinook salmon

USGS Publications Warehouse

Neville, Helen; Isaak, Daniel; Dunham, J.B.; Thurow, Russel; Rieman, B.

2006-01-01

Natal homing is a hallmark of the life history of salmonid fishes, but the spatial scale of homing within local, naturally reproducing salmon populations is still poorly understood. Accurate homing (paired with restricted movement) should lead to the existence of fine-scale genetic structuring due to the spatial clustering of related individuals on spawning grounds. Thus, we explored the spatial resolution of natal homing using genetic associations among individual Chinook salmon (Oncorhynchus tshawytscha) in an interconnected stream network. We also investigated the relationship between genetic patterns and two factors hypothesized to influence natal homing and localized movements at finer scales in this species, localized patterns in the distribution of spawning gravels and sex. Spatial autocorrelation analyses showed that spawning locations in both sub-basins of our study site were spatially clumped, but the upper sub-basin generally had a larger spatial extent and continuity of redd locations than the lower sub-basin, where the distribution of redds and associated habitat conditions were more patchy. Male genotypes were not autocorrelated at any spatial scale in either sub-basin. Female genotypes showed significant spatial autocorrelation and genetic patterns for females varied in the direction predicted between the two sub-basins, with much stronger autocorrelation in the sub-basin with less continuity in spawning gravels. The patterns observed here support predictions about differential constraints and breeding tactics between the two sexes and the potential for fine-scale habitat structure to influence the precision of natal homing and localized movements of individual Chinook salmon on their breeding grounds.

Scaling effects on spring phenology detections from MODIS data at multiple spatial resolutions over the contiguous United States

NASA Astrophysics Data System (ADS)

Peng, Dailiang; Zhang, Xiaoyang; Zhang, Bing; Liu, Liangyun; Liu, Xinjie; Huete, Alfredo R.; Huang, Wenjiang; Wang, Siyuan; Luo, Shezhou; Zhang, Xiao; Zhang, Helin

2017-10-01

Land surface phenology (LSP) has been widely retrieved from satellite data at multiple spatial resolutions, but the spatial scaling effects on LSP detection are poorly understood. In this study, we collected enhanced vegetation index (EVI, 250 m) from collection 6 MOD13Q1 product over the contiguous United States (CONUS) in 2007 and 2008, and generated a set of multiple spatial resolution EVI data by resampling 250 m to 2 × 250 m and 3 × 250 m, 4 × 250 m, …, 35 × 250 m. These EVI time series were then used to detect the start of spring season (SOS) at various spatial resolutions. Further the SOS variation across scales was examined at each coarse resolution grid (35 × 250 m ≈ 8 km, refer to as reference grid) and ecoregion. Finally, the SOS scaling effects were associated with landscape fragment, proportion of primary land cover type, and spatial variability of seasonal greenness variation within each reference grid. The results revealed the influences of satellite spatial resolutions on SOS retrievals and the related impact factors. Specifically, SOS significantly varied lineally or logarithmically across scales although the relationship could be either positive or negative. The overall SOS values averaged from spatial resolutions between 250 m and 35 × 250 m at large ecosystem regions were generally similar with a difference less than 5 days, while the SOS values within the reference grid could differ greatly in some local areas. Moreover, the standard deviation of SOS across scales in the reference grid was less than 5 days in more than 70% of area over the CONUS, which was smaller in northeastern than in southern and western regions. The SOS scaling effect was significantly associated with heterogeneity of vegetation properties characterized using land landscape fragment, proportion of primary land cover type, and spatial variability of seasonal greenness variation, but the latter was the most important impact factor.

Spatial cognition and science achievement: The contribution of intrinsic and extrinsic spatial skills from 7 to 11 years.

PubMed

Hodgkiss, Alex; Gilligan, Katie A; Tolmie, Andrew K; Thomas, Michael S C; Farran, Emily K

2018-01-22

Prior longitudinal and correlational research with adults and adolescents indicates that spatial ability is a predictor of science learning and achievement. However, there is little research to date with primary-school aged children that addresses this relationship. Understanding this association has the potential to inform curriculum design and support the development of early interventions. This study examined the relationship between primary-school children's spatial skills and their science achievement. Children aged 7-11 years (N = 123) completed a battery of five spatial tasks, based on a model of spatial ability in which skills fall along two dimensions: intrinsic-extrinsic; static-dynamic. Participants also completed a curriculum-based science assessment. Controlling for verbal ability and age, mental folding (intrinsic-dynamic spatial ability), and spatial scaling (extrinsic-static spatial ability) each emerged as unique predictors of overall science scores, with mental folding a stronger predictor than spatial scaling. These spatial skills combined accounted for 8% of the variance in science scores. When considered by scientific discipline, mental folding uniquely predicted both physics and biology scores, and spatial scaling accounted for additional variance in biology and variance in chemistry scores. The children's embedded figures task (intrinsic-static spatial ability) only accounted for variance in chemistry scores. The patterns of association were consistent across the age range. Spatial skills, particularly mental folding, spatial scaling, and disembedding, are predictive of 7- to 11-year-olds' science achievement. These skills make a similar contribution to performance for each age group. © 2018 The Authors. British Journal of Education Psychology published by John Wiley & Sons Ltd on behalf of British Psychological Society.

Exploring the effects of spatial autocorrelation when identifying key drivers of wildlife crop-raiding.

PubMed

Songhurst, Anna; Coulson, Tim

2014-03-01

Few universal trends in spatial patterns of wildlife crop-raiding have been found. Variations in wildlife ecology and movements, and human spatial use have been identified as causes of this apparent unpredictability. However, varying spatial patterns of spatial autocorrelation (SA) in human-wildlife conflict (HWC) data could also contribute. We explicitly explore the effects of SA on wildlife crop-raiding data in order to facilitate the design of future HWC studies. We conducted a comparative survey of raided and nonraided fields to determine key drivers of crop-raiding. Data were subsampled at different spatial scales to select independent raiding data points. The model derived from all data was fitted to subsample data sets. Model parameters from these models were compared to determine the effect of SA. Most methods used to account for SA in data attempt to correct for the change in P-values; yet, by subsampling data at broader spatial scales, we identified changes in regression estimates. We consequently advocate reporting both model parameters across a range of spatial scales to help biological interpretation. Patterns of SA vary spatially in our crop-raiding data. Spatial distribution of fields should therefore be considered when choosing the spatial scale for analyses of HWC studies. Robust key drivers of elephant crop-raiding included raiding history of a field and distance of field to a main elephant pathway. Understanding spatial patterns and determining reliable socio-ecological drivers of wildlife crop-raiding is paramount for designing mitigation and land-use planning strategies to reduce HWC. Spatial patterns of HWC are complex, determined by multiple factors acting at more than one scale; therefore, studies need to be designed with an understanding of the effects of SA. Our methods are accessible to a variety of practitioners to assess the effects of SA, thereby improving the reliability of conservation management actions.

Fine-scale structure in the far-infrared Milky-Way

NASA Technical Reports Server (NTRS)

Waller, William H.; Wall, William F.; Reach, William T.; Varosi, Frank; Ebert, Rick; Laughlin, Gaylin; Boulanger, Francois

1995-01-01

This final report summarizes the work performed and which falls into five broad categories: (1) generation of a new data product (mosaics of the far-infrared emission in the Milky Way); (2) acquisition of associated data products at other wavelengths; (3) spatial filtering of the far-infrared mosaics and resulting images of the FIR fine-scale structure; (4) evaluation of the spatially filtered data; (5) characterization of the FIR fine-scale structure in terms of its spatial statistics; and (6) identification of interstellar counterparts to the FIR fine-scale structure.

Demeter-W

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

2017-09-27

Demeter-W, an open-access software written in Python, consists of extensible module packages. It is developed with statistical downscaling algorithms, to spatially and temporally downscale water demand data into finer scale. The spatial resolution will be downscaled from region/basin scale to grid (0.5 geographic degree) scale and the temporal resolution will be downscaled from year to month. For better understanding of the driving forces and patterns for global water withdrawal, the researchers is able to utilize Demeter-W to reconstruct the data sets to examine the issues related to water withdrawals at fine spatial and temporal scales.

Characterizing multiscale variability of zero intermittency in spatial rainfall

NASA Technical Reports Server (NTRS)

Kumar, Praveen; Foufoula-Georgiou, Efi

1994-01-01

In this paper the authors study how zero intermittency in spatial rainfall, as described by the fraction of area covered by rainfall, changes with spatial scale of rainfall measurement or representation. A statistical measure of intermittency that describes the size distribution of 'voids' (nonrainy areas imbedded inside rainy areas) as a function of scale is also introduced. Morphological algorithms are proposed for reconstructing rainfall intermittency at fine scales given the intermittency at coarser scales. These algorithms are envisioned to be useful in hydroclimatological studies where the rainfall spatial variability at the subgrid scale needs to be reconstructed from the results of synoptic- or mesoscale meteorological numerical models. The developed methodologies are demsonstrated and tested using data from a severe springtime midlatitude squall line and a mild midlatitude winter storm monitored by a meteorological radar in Norman, Oklahoma.

Downscaling RCP8.5 daily temperatures and precipitation in Ontario using localized ensemble optimal interpolation (EnOI) and bias correction

NASA Astrophysics Data System (ADS)

Deng, Ziwang; Liu, Jinliang; Qiu, Xin; Zhou, Xiaolan; Zhu, Huaiping

2017-10-01

A novel method for daily temperature and precipitation downscaling is proposed in this study which combines the Ensemble Optimal Interpolation (EnOI) and bias correction techniques. For downscaling temperature, the day to day seasonal cycle of high resolution temperature of the NCEP climate forecast system reanalysis (CFSR) is used as background state. An enlarged ensemble of daily temperature anomaly relative to this seasonal cycle and information from global climate models (GCMs) are used to construct a gain matrix for each calendar day. Consequently, the relationship between large and local-scale processes represented by the gain matrix will change accordingly. The gain matrix contains information of realistic spatial correlation of temperature between different CFSR grid points, between CFSR grid points and GCM grid points, and between different GCM grid points. Therefore, this downscaling method keeps spatial consistency and reflects the interaction between local geographic and atmospheric conditions. Maximum and minimum temperatures are downscaled using the same method. For precipitation, because of the non-Gaussianity issue, a logarithmic transformation is used to daily total precipitation prior to conducting downscaling. Cross validation and independent data validation are used to evaluate this algorithm. Finally, data from a 29-member ensemble of phase 5 of the Coupled Model Intercomparison Project (CMIP5) GCMs are downscaled to CFSR grid points in Ontario for the period from 1981 to 2100. The results show that this method is capable of generating high resolution details without changing large scale characteristics. It results in much lower absolute errors in local scale details at most grid points than simple spatial downscaling methods. Biases in the downscaled data inherited from GCMs are corrected with a linear method for temperatures and distribution mapping for precipitation. The downscaled ensemble projects significant warming with amplitudes of 3.9 and 6.5 °C for 2050s and 2080s relative to 1990s in Ontario, respectively; Cooling degree days and hot days will significantly increase over southern Ontario and heating degree days and cold days will significantly decrease in northern Ontario. Annual total precipitation will increase over Ontario and heavy precipitation events will increase as well. These results are consistent with conclusions in many other studies in the literature.

Structure formation by a fifth force: N-body versus linear simulations

NASA Astrophysics Data System (ADS)

Li, Baojiu; Zhao, Hongsheng

2009-08-01

We lay out the frameworks to numerically study the structure formation in both linear and nonlinear regimes in general dark-matter-coupled scalar field models, and give an explicit example where the scalar field serves as a dynamical dark energy. Adopting parameters of the scalar field which yield a realistic cosmic microwave background (CMB) spectrum, we generate the initial conditions for our N-body simulations, which follow the spatial distributions of the dark matter and the scalar field by solving their equations of motion using the multilevel adaptive grid technique. We show that the spatial configuration of the scalar field tracks well the voids and clusters of dark matter. Indeed, the propagation of scalar degree of freedom effectively acts as a fifth force on dark matter particles, whose range and magnitude are determined by the two model parameters (μ,γ), local dark matter density as well as the background value for the scalar field. The model behaves like the ΛCDM paradigm on scales relevant to the CMB spectrum, which are well beyond the probe of the local fifth force and thus not significantly affected by the matter-scalar coupling. On scales comparable or shorter than the range of the local fifth force, the fifth force is perfectly parallel to gravity and their strengths have a fixed ratio 2γ2 determined by the matter-scalar coupling, provided that the chameleon effect is weak; if on the other hand there is a strong chameleon effect (i.e., the scalar field almost resides at its effective potential minimum everywhere in the space), the fifth force indeed has suppressed effects in high density regions and shows no obvious correlation with gravity, which means that the dark-matter-scalar-field coupling is not simply equivalent to a rescaling of the gravitational constant or the mass of the dark matter particles. We show these spatial distributions and (lack of) correlations at typical redshifts (z=0,1,5.5) in our multigrid million-particle simulations. The viable parameters for the scalar field can be inferred on intermediate or small scales at late times from, e.g., weak lensing and phase space properties, while the predicted Hubble expansion and linearly simulated CMB spectrum are virtually indistinguishable from the standard ΛCDM predictions.

High-Resolution Biogeochemical Simulation Identifies Practical Opportunities for Bioenergy Landscape Intensification Across Diverse US Agricultural Regions

NASA Astrophysics Data System (ADS)

Field, J.; Adler, P. R.; Evans, S.; Paustian, K.; Marx, E.; Easter, M.

2015-12-01

The sustainability of biofuel expansion is strongly dependent on the environmental footprint of feedstock production, including both direct impacts within feedstock-producing areas and potential leakage effects due to disruption of existing food, feed, or fiber production. Assessing and minimizing these impacts requires novel methods compared to traditional supply chain lifecycle assessment. When properly validated and applied at appropriate spatial resolutions, biogeochemical process models are useful for simulating how the productivity and soil greenhouse gas fluxes of cultivating both conventional crops and advanced feedstock crops respond across gradients of land quality and management intensity. In this work we use the DayCent model to assess the biogeochemical impacts of agricultural residue collection, establishment of perennial grasses on marginal cropland or conservation easements, and intensification of existing cropping at high spatial resolution across several real-world case study landscapes in diverse US agricultural regions. We integrate the resulting estimates of productivity, soil carbon changes, and nitrous oxide emissions with crop production budgets and lifecycle inventories, and perform a basic optimization to generate landscape cost/GHG frontiers and determine the most practical opportunities for low-impact feedstock provisioning. The optimization is constrained to assess the minimum combined impacts of residue collection, land use change, and intensification of existing agriculture necessary for the landscape to supply a commercial-scale biorefinery while maintaining exiting food, feed, and fiber production levels. These techniques can be used to assess how different feedstock provisioning strategies perform on both economic and environmental criteria, and sensitivity of performance to environmental and land use factors. The included figure shows an example feedstock cost-GHG mitigation tradeoff frontier for a commercial-scale cellulosic biofuel facility in Kansas.

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.

Observed Spatial and Temporal Variability of Subglacial Discharge-Driven Plumes in Greenland's Outlet Glacial Fjords

NASA Astrophysics Data System (ADS)

Sutherland, D.; Carroll, D.; Nash, J. D.; Shroyer, E.; Mickett, J.; Stearns, L. A.; Fried, M.; Bartholomaus, T.; Catania, G. A.

2015-12-01

Hydrographic and velocity observations in Greenland's outlet glacier fjords have revealed, unsurprisingly, a rich set of dynamics over a range of spatial and temporal scales. Through teasing apart the distinct processes that control circulation within these fjords, we are likely to better understand the impact of fjord circulation on modulating outlet glacier dynamics, and thus, changes in Greenland Ice Sheet mass balance. Here, we report on data from the summers of 2013-2015 in two neighboring fjords in the Uummannaq Bay region of west Greenland: Kangerlussuup Sermia (KS) and Rink Isbræ (RI). We find strong subglacial discharge driven plumes in both systems that evolve on synoptic and seasonal time scales, without the complicating presence of other circulation processes. The plumes both modify fjord water properties and respond to differences in ambient water properties, supporting the notion that a feedback exists between subglacial discharge plume circulation and water mass properties. This feedback between subglacial discharge and water properties potentially influences submarine melt rates at the glacier termini. Observed plume properties, including the vertical structure of velocity, and temperature and salinity anomalies, are compared favorably to model estimates. In KS, we find a near-surface intensified plume with high sediment content that slows and widens as it evolves downstream. In contrast, the plume in RI is entirely subsurface, ranging from 100-300 m depth at its core during summer, although it shows similar temperature, salinity, and optical backscatter signals to the KS plume. Importantly, the distinct vertical plume structures imprint on the overall water mass properties found in each fjord, raising the minimum temperatures by up to 1-2°C in the case of RI.

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

DEVELOPMENT OF RIPARIAN ZONE INDICATORS (INT. GRANT)

EPA Science Inventory

Landscape features (e.g., land use) influence water quality characteristics on a variety of spatial scales. For example, while land use is controlled by anthropogenic features at a local scale, geologic features are set at larger spatial, and longer temporal scales. Individual ...

Scale considerations for ecosystem management

Treesearch

Jonathan B. Haufler; Thomas R. Crow; David Wilcove

1999-01-01

One of the difficult challenges facing ecosystem management is the determination of appropriate spatial and temporal scales to use. Scale in spatial sence includes considerations of both the size area or extent of an ecosystem management activity, as well as thedegree of resolution of mapped or measured data. In the temporal sense, scale concerns the duration of both...

Conceptualizing Magnification and Scale: The Roles of Spatial Visualization and Logical Thinking

ERIC Educational Resources Information Center

Jones, M. Gail; Gardner, Grant; Taylor, Amy R.; Wiebe, Eric; Forrester, Jennifer

2011-01-01

This study explored factors that contribute to students' concepts of magnification and scale. Spatial visualization, logical thinking, and concepts of magnification and scale were measured for 46 middle school students. Scores on the "Zoom Assessment" (an assessment of knowledge of magnification and scale) were correlated with the "Test of Logical…

Experienced and Novice Teachers' Concepts of Spatial Scale

ERIC Educational Resources Information Center

Jones, M. Gail; Tretter, Thomas; Taylor, Amy; Oppewal, Tom

2008-01-01

Scale is one of the thematic threads that runs through nearly all of the sciences and is considered one of the major prevailing ideas of science. This study explored novice and experienced teachers' concepts of spatial scale with a focus on linear sizes from very small (nanoscale) to very large (cosmic scale). Novice teachers included…

Scale dependency of American marten (Martes americana) habitat relations [Chapter 12

Treesearch

Andrew J. Shirk; Tzeidle N. Wasserman; Samuel A. Cushman; Martin G. Raphael

2012-01-01

Animals select habitat resources at multiple spatial scales; therefore, explicit attention to scale-dependency when modeling habitat relations is critical to understanding how organisms select habitat in complex landscapes. Models that evaluate habitat variables calculated at a single spatial scale (e.g., patch, home range) fail to account for the effects of...

Effect of random inhomogeneities in the spatial distribution of radiation-induced defect clusters on carrier transport through the thin base of a heterojunction bipolar transistor upon neutron irradiation

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

Puzanov, A. S.; Obolenskiy, S. V., E-mail: obolensk@rf.unn.ru; Kozlov, V. A.

We analyze the electron transport through the thin base of a GaAs heterojunction bipolar transistor with regard to fluctuations in the spatial distribution of defect clusters induced by irradiation with a fissionspectrum fast neutron flux. We theoretically demonstrate that the homogeneous filling of the working region with radiation-induced defect clusters causes minimum degradation of the dc gain of the heterojunction bipolar transistor.

Polariton solitons and nonlinear localized states in a one-dimensional semiconductor microcavity

NASA Astrophysics Data System (ADS)

Chen, Ting-Wei; Cheng, Szu-Cheng

2018-01-01

This paper presents numerical studies of cavity polariton solitons (CPSs) in a resonantly pumped semiconductor microcavity with an imbedded spatial defect. In the bistable regime of the well-known homogeneous polariton condensate, with proper incident wave vector and pump strength, bright and/or dark cavity solitons can be found in the presence of a spatially confined potential. The minimum pump strength required to observe the CPSs or nonlinear localized states in this parametric pump scheme is therefore reported.

Theories of Simplification and Scaling of Spatially Distributed Processes. Chapter 12

NASA Technical Reports Server (NTRS)

Levin, Simon A.; Pacala, Stephen W.

1997-01-01

The problem of scaling is at the heart of ecological theory, the essence of understanding and of the development of a predictive capability. The description of any system depends on the spatial, temporal, and organizational perspective chosen; hence it is essential to understand not only how patterns and dynamics vary with scale, but also how patterns at one scale are manifestations of processes operating at other scales. Evolution has shaped the characteristics of species in ways that result in scale displacement: Each species experiences the environment at its own unique set of spatial and temporal scales and interfaces the biota through unique assemblages of phenotypes. In this way, coexistence becomes possible, and biodiversity is enhanced. By averaging over space, time, and biological interactions, a genotype filters variation at fine scales and selects the arena in which it will face the vicissitudes of nature. Variation at finer scales is then noise, of minor importance to the survival and dynamics of the species, and consequently of minor importance in any attempt at description. In attempting to model ecological interactions in space, contributors throughout this book have struggled with a trade-off between simplification and "realistic" complexity and detail. Although the challenge of simplification is widely recognized in ecology, less appreciated is the intertwining of scaling questions and scaling laws with the process of simplification. In the context of this chapter simplification will in general mean the use of spatial or ensemble means and low-order moments to capture more detailed interactions by integrating over given areas. In this way, one can derive descriptions of the system at different spatial scales, which provides the essentials for the extraction of scaling laws by examination of how system properties vary with scale.

Climate and climate change and infectious disease risk in Thailand: A spatial study of dengue hemorrhagic fever using GIS and remotely-sensed imagery

NASA Astrophysics Data System (ADS)

Kuzera, Kristopher

The scientific community has widely accepted that climate plays a key role in the sustainability and transmission of many infectious diseases. Global climate change can potentially trigger the spread of disease into new regions and increase the intensity of disease in regions where it is endemic. This study explores the association between monthly conditions of climate change to changes in disease risk, emphasizing the potential spread of dengue fever due to climate change in Thailand. This study also develops techniques new to GIS and remote sensing that generate surfaces of daily minimum temperature toward identifying areas at greater transmission risk. Dengue fever expansion due to global warming is a serious concern for Thailand where warming temperatures may increase the size of the habitat of the disease-spreading vector, Aedes aegypti, particularly during cooler months when transmission is limited by environmental conditions. In this study, first, the association between past dengue hemorrhagic fever (DHF) and climate in Thailand is determined. Second, evidence of recent climate change is related to changes in DHF rates. Third, daily minimum temperature is derived from remote sensing toward identifying the spatial and temporal limitations of potential transmission risk. The results indicate that minimum temperature has recently experienced a rapid increase, particularly in the winter months when transmission is low. This is associated with a recent rise in winter DHF cases. As increasing minimum temperatures in these regions are anticipated to continue, we can expect dengue transmission rates to also increase throughout the year.

Coexistence between wildlife and humans at fine spatial scales.

PubMed

Carter, Neil H; Shrestha, Binoj K; Karki, Jhamak B; Pradhan, Narendra Man Babu; Liu, Jianguo

2012-09-18

Many wildlife species face imminent extinction because of human impacts, and therefore, a prevailing belief is that some wildlife species, particularly large carnivores and ungulates, cannot coexist with people at fine spatial scales (i.e., cannot regularly use the exact same point locations). This belief provides rationale for various conservation programs, such as resettling human communities outside protected areas. However, quantitative information on the capacity and mechanisms for wildlife to coexist with humans at fine spatial scales is scarce. Such information is vital, because the world is becoming increasingly crowded. Here, we provide empirical information about the capacity and mechanisms for tigers (a globally endangered species) to coexist with humans at fine spatial scales inside and outside Nepal's Chitwan National Park, a flagship protected area for imperiled wildlife. Information obtained from field cameras in 2010 and 2011 indicated that human presence (i.e., people on foot and vehicles) was ubiquitous and abundant throughout the study site; however, tiger density was also high. Surprisingly, even at a fine spatial scale (i.e., camera locations), tigers spatially overlapped with people on foot and vehicles in both years. However, in both years, tigers offset their temporal activity patterns to be much less active during the day when human activity peaked. In addition to temporal displacement, tiger-human coexistence was likely enhanced by abundant tiger prey and low levels of tiger poaching. Incorporating fine-scale spatial and temporal activity patterns into conservation plans can help address a major global challenge-meeting human needs while sustaining wildlife.

Network analysis reveals multiscale controls on streamwater chemistry

USGS Publications Warehouse

McGuire, Kevin J.; Torgersen, Christian E.; Likens, Gene E.; Buso, Donald C.; Lowe, Winsor H.; Bailey, Scott W.

2014-01-01

By coupling synoptic data from a basin-wide assessment of streamwater chemistry with network-based geostatistical analysis, we show that spatial processes differentially affect biogeochemical condition and pattern across a headwater stream network. We analyzed a high-resolution dataset consisting of 664 water samples collected every 100 m throughout 32 tributaries in an entire fifth-order stream network. These samples were analyzed for an exhaustive suite of chemical constituents. The fine grain and broad extent of this study design allowed us to quantify spatial patterns over a range of scales by using empirical semivariograms that explicitly incorporated network topology. Here, we show that spatial structure, as determined by the characteristic shape of the semivariograms, differed both among chemical constituents and by spatial relationship (flow-connected, flow-unconnected, or Euclidean). Spatial structure was apparent at either a single scale or at multiple nested scales, suggesting separate processes operating simultaneously within the stream network and surrounding terrestrial landscape. Expected patterns of spatial dependence for flow-connected relationships (e.g., increasing homogeneity with downstream distance) occurred for some chemical constituents (e.g., dissolved organic carbon, sulfate, and aluminum) but not for others (e.g., nitrate, sodium). By comparing semivariograms for the different chemical constituents and spatial relationships, we were able to separate effects on streamwater chemistry of (i) fine-scale versus broad-scale processes and (ii) in-stream processes versus landscape controls. These findings provide insight on the hierarchical scaling of local, longitudinal, and landscape processes that drive biogeochemical patterns in stream networks.

Network analysis reveals multiscale controls on streamwater chemistry

PubMed Central

McGuire, Kevin J.; Torgersen, Christian E.; Likens, Gene E.; Buso, Donald C.; Lowe, Winsor H.; Bailey, Scott W.

2014-01-01

By coupling synoptic data from a basin-wide assessment of streamwater chemistry with network-based geostatistical analysis, we show that spatial processes differentially affect biogeochemical condition and pattern across a headwater stream network. We analyzed a high-resolution dataset consisting of 664 water samples collected every 100 m throughout 32 tributaries in an entire fifth-order stream network. These samples were analyzed for an exhaustive suite of chemical constituents. The fine grain and broad extent of this study design allowed us to quantify spatial patterns over a range of scales by using empirical semivariograms that explicitly incorporated network topology. Here, we show that spatial structure, as determined by the characteristic shape of the semivariograms, differed both among chemical constituents and by spatial relationship (flow-connected, flow-unconnected, or Euclidean). Spatial structure was apparent at either a single scale or at multiple nested scales, suggesting separate processes operating simultaneously within the stream network and surrounding terrestrial landscape. Expected patterns of spatial dependence for flow-connected relationships (e.g., increasing homogeneity with downstream distance) occurred for some chemical constituents (e.g., dissolved organic carbon, sulfate, and aluminum) but not for others (e.g., nitrate, sodium). By comparing semivariograms for the different chemical constituents and spatial relationships, we were able to separate effects on streamwater chemistry of (i) fine-scale versus broad-scale processes and (ii) in-stream processes versus landscape controls. These findings provide insight on the hierarchical scaling of local, longitudinal, and landscape processes that drive biogeochemical patterns in stream networks. PMID:24753575

Network analysis reveals multiscale controls on streamwater chemistry.

PubMed

McGuire, Kevin J; Torgersen, Christian E; Likens, Gene E; Buso, Donald C; Lowe, Winsor H; Bailey, Scott W

2014-05-13

By coupling synoptic data from a basin-wide assessment of streamwater chemistry with network-based geostatistical analysis, we show that spatial processes differentially affect biogeochemical condition and pattern across a headwater stream network. We analyzed a high-resolution dataset consisting of 664 water samples collected every 100 m throughout 32 tributaries in an entire fifth-order stream network. These samples were analyzed for an exhaustive suite of chemical constituents. The fine grain and broad extent of this study design allowed us to quantify spatial patterns over a range of scales by using empirical semivariograms that explicitly incorporated network topology. Here, we show that spatial structure, as determined by the characteristic shape of the semivariograms, differed both among chemical constituents and by spatial relationship (flow-connected, flow-unconnected, or Euclidean). Spatial structure was apparent at either a single scale or at multiple nested scales, suggesting separate processes operating simultaneously within the stream network and surrounding terrestrial landscape. Expected patterns of spatial dependence for flow-connected relationships (e.g., increasing homogeneity with downstream distance) occurred for some chemical constituents (e.g., dissolved organic carbon, sulfate, and aluminum) but not for others (e.g., nitrate, sodium). By comparing semivariograms for the different chemical constituents and spatial relationships, we were able to separate effects on streamwater chemistry of (i) fine-scale versus broad-scale processes and (ii) in-stream processes versus landscape controls. These findings provide insight on the hierarchical scaling of local, longitudinal, and landscape processes that drive biogeochemical patterns in stream networks.

The relationship between the spatial scaling of biodiversity and ecosystem stability

PubMed Central

Delsol, Robin; Loreau, Michel; Haegeman, Bart

2018-01-01

Aim Ecosystem stability and its link with biodiversity have mainly been studied at the local scale. Here we present a simple theoretical model to address the joint dependence of diversity and stability on spatial scale, from local to continental. Methods The notion of stability we use is based on the temporal variability of an ecosystem-level property, such as primary productivity. In this way, our model integrates the well-known species–area relationship (SAR) with a recent proposal to quantify the spatial scaling of stability, called the invariability–area relationship (IAR). Results We show that the link between the two relationships strongly depends on whether the temporal fluctuations of the ecosystem property of interest are more correlated within than between species. If fluctuations are correlated within species but not between them, then the IAR is strongly constrained by the SAR. If instead individual fluctuations are only correlated by spatial proximity, then the IAR is unrelated to the SAR. We apply these two correlation assumptions to explore the effects of species loss and habitat destruction on stability, and find a rich variety of multi-scale spatial dependencies, with marked differences between the two assumptions. Main conclusions The dependence of ecosystem stability on biodiversity across spatial scales is governed by the spatial decay of correlations within and between species. Our work provides a point of reference for mechanistic models and data analyses. More generally, it illustrates the relevance of macroecology for ecosystem functioning and stability. PMID:29651225

Spatial scale of land-use impacts on riverine drinking source water quality

NASA Astrophysics Data System (ADS)

Hurley, Tim; Mazumder, Asit

2013-03-01

Drinking water purveyors are increasingly relying on land conservation and management to ensure the safety of the water that they provide to consumers. To cost-effectively implement any such landscape initiatives, resources must be targeted to the appropriate spatial scale to address quality impairments of concern in a cost-effective manner. Using data gathered from 40 Canadian rivers across four ecozones, we examined the spatial scales at which land use was most closely associated with drinking source water quality metrics. Exploratory linear mixed-effects models accounting for climatic, hydrological, and physiographic variation among sites suggested that different spatial areas of land-use influence drinking source water quality depending on the parameter and season investigated. Escherichia coli spatial variability was only associated with land use at a local (5-10 km) spatial scale. Turbidity measures exhibited a complex association with land use, suggesting that the land-use areas of greatest influence can range from a 1 km subcatchment to the entire watershed depending on the season. Total organic carbon concentrations were only associated with land use characterized at the entire watershed scale. The Canadian Council of Ministers of the Environment Water Quality Index was used to calculate a composite measure of seasonal drinking source water quality but did not provide additional information beyond the analyses of individual parameters. These results suggest that entire watershed management is required to safeguard drinking water sources with more focused efforts at targeted spatial scales to reduce specific risk parameters.

Spatial distribution of enzyme driven reactions at micro-scales

NASA Astrophysics Data System (ADS)

Kandeler, Ellen; Boeddinghaus, Runa; Nassal, Dinah; Preusser, Sebastian; Marhan, Sven; Poll, Christian

2017-04-01

Studies of microbial biogeography can often provide key insights into the physiologies, environmental tolerances, and ecological strategies of soil microorganisms that dominate in natural environments. In comparison with aquatic systems, soils are particularly heterogeneous. Soil heterogeneity results from the interaction of a hierarchical series of interrelated variables that fluctuate at many different spatial and temporal scales. Whereas spatial dependence of chemical and physical soil properties is well known at scales ranging from decimetres to several hundred metres, the spatial structure of soil enzymes is less clear. Previous work has primarily focused on spatial heterogeneity at a single analytical scale using the distribution of individual cells, specific types of organisms or collective parameters such as bacterial abundance or total microbial biomass. There are fewer studies that have considered variations in community function and soil enzyme activities. This presentation will give an overview about recent studies focusing on spatial pattern of different soil enzymes in the terrestrial environment. Whereas zymography allows the visualization of enzyme pattern in the close vicinity of roots, micro-sampling strategies followed by MUF analyses clarify micro-scale pattern of enzymes associated to specific microhabitats (micro-aggregates, organo-mineral complexes, subsoil compartments).

Mapping spatial patterns of denitrifiers at large scales (Invited)

NASA Astrophysics Data System (ADS)

Philippot, L.; Ramette, A.; Saby, N.; Bru, D.; Dequiedt, S.; Ranjard, L.; Jolivet, C.; Arrouays, D.

2010-12-01

Little information is available regarding the landscape-scale distribution of microbial communities and its environmental determinants. Here we combined molecular approaches and geostatistical modeling to explore spatial patterns of the denitrifying community at large scales. The distribution of denitrifrying community was investigated over 107 sites in Burgundy, a 31 500 km2 region of France, using a 16 X 16 km sampling grid. At each sampling site, the abundances of denitrifiers and 42 soil physico-chemical properties were measured. The relative contributions of land use, spatial distance, climatic conditions, time and soil physico-chemical properties to the denitrifier spatial distribution were analyzed by canonical variation partitioning. Our results indicate that 43% to 85% of the spatial variation in community abundances could be explained by the measured environmental parameters, with soil chemical properties (mostly pH) being the main driver. We found spatial autocorrelation up to 739 km and used geostatistical modelling to generate predictive maps of the distribution of denitrifiers at the landscape scale. Studying the distribution of the denitrifiers at large scale can help closing the artificial gap between the investigation of microbial processes and microbial community ecology, therefore facilitating our understanding of the relationships between the ecology of denitrifiers and N-fluxes by denitrification.

Fractals and Spatial Methods for Mining Remote Sensing Imagery

NASA Technical Reports Server (NTRS)

Lam, Nina; Emerson, Charles; Quattrochi, Dale

2003-01-01

The rapid increase in digital remote sensing and GIS data raises a critical problem -- how can such an enormous amount of data be handled and analyzed so that useful information can be derived quickly? Efficient handling and analysis of large spatial data sets is central to environmental research, particularly in global change studies that employ time series. Advances in large-scale environmental monitoring and modeling require not only high-quality data, but also reliable tools to analyze the various types of data. A major difficulty facing geographers and environmental scientists in environmental assessment and monitoring is that spatial analytical tools are not easily accessible. Although many spatial techniques have been described recently in the literature, they are typically presented in an analytical form and are difficult to transform to a numerical algorithm. Moreover, these spatial techniques are not necessarily designed for remote sensing and GIS applications, and research must be conducted to examine their applicability and effectiveness in different types of environmental applications. This poses a chicken-and-egg problem: on one hand we need more research to examine the usability of the newer techniques and tools, yet on the other hand, this type of research is difficult to conduct if the tools to be explored are not accessible. Another problem that is fundamental to environmental research are issues related to spatial scale. The scale issue is especially acute in the context of global change studies because of the need to integrate remote-sensing and other spatial data that are collected at different scales and resolutions. Extrapolation of results across broad spatial scales remains the most difficult problem in global environmental research. There is a need for basic characterization of the effects of scale on image data, and the techniques used to measure these effects must be developed and implemented to allow for a multiple scale assessment of the data before any useful process-oriented modeling involving scale-dependent data can be conducted. Through the support of research grants from NASA, we have developed a software module called ICAMS (Image Characterization And Modeling System) to address the need to develop innovative spatial techniques and make them available to the broader scientific communities. ICAMS provides new spatial techniques, such as fractal analysis, geostatistical functions, and multiscale analysis that are not easily available in commercial GIS/image processing software. By bundling newer spatial methods in a user-friendly software module, researchers can begin to test and experiment with the new spatial analysis methods and they can gauge scale effects using a variety of remote sensing imagery. In the following, we describe briefly the development of ICAMS and present application examples.

Executive functions as endophenotypes in ADHD: evidence from the Cambridge Neuropsychological Test Battery (CANTAB).

PubMed

Gau, Susan Shur-Fen; Shang, Chi-Yung

2010-07-01

Little is known about executive functions among unaffected siblings of children with attention deficit/hyperactivity disorder (ADHD), and there is lack of such information from non-Western countries. We examined verbal and nonverbal executive functions in adolescents with ADHD, unaffected siblings and controls to test whether executive functions could be potential endophenotypes for ADHD. We assessed 279 adolescents (age range: 11-17 years) with a childhood diagnosis of DSM-IV ADHD, 136 biological siblings (108 unaffected, 79.4%), and 173 unaffected controls by using psychiatric interviews, the Wechsler Intelligence Scale for Children - 3rd edition (WISC-III), including digit spans, and the tasks involving executive functions of the Cambridge Neuropsychological Test Automated Battery (CANTAB): Intra-dimensional/Extra-dimensional Shifts (IED), Spatial Span (SSP), Spatial Working Memory (SWM), and Stockings of Cambridge (SOC). Compared with the controls, adolescents with ADHD and unaffected siblings had a significantly shorter backward digit span, more extra-dimensional shift errors in the IED, shorter spatial span length in the SSP, more total errors and poorer strategy use in the SWM, and fewer problems solved in the minimum number of moves and shorter initial thinking time in the SOC. The magnitudes of the differences in the SWM and SOC increased with increased task difficulties. In general, neither persistent ADHD nor comorbidity was associated with increased deficits in executive functions among adolescents with ADHD. The lack of much difference in executive dysfunctions between unaffected siblings and ADHD adolescents suggests that executive dysfunctions may be useful cognitive endophenotypes for ADHD genetic studies.

Spatial optimization of watershed management practices for nitrogen load reduction using a modeling-optimization framework.

PubMed

Yang, Guoxiang; Best, Elly P H

2015-09-15

Best management practices (BMPs) can be used effectively to reduce nutrient loads transported from non-point sources to receiving water bodies. However, methodologies of BMP selection and placement in a cost-effective way are needed to assist watershed management planners and stakeholders. We developed a novel modeling-optimization framework that can be used to find cost-effective solutions of BMP placement to attain nutrient load reduction targets. This was accomplished by integrating a GIS-based BMP siting method, a WQM-TMDL-N modeling approach to estimate total nitrogen (TN) loading, and a multi-objective optimization algorithm. Wetland restoration and buffer strip implementation were the two BMP categories used to explore the performance of this framework, both differing greatly in complexity of spatial analysis for site identification. Minimizing TN load and BMP cost were the two objective functions for the optimization process. The performance of this framework was demonstrated in the Tippecanoe River watershed, Indiana, USA. Optimized scenario-based load reduction indicated that the wetland subset selected by the minimum scenario had the greatest N removal efficiency. Buffer strips were more effective for load removal than wetlands. The optimized solutions provided a range of trade-offs between the two objective functions for both BMPs. This framework can be expanded conveniently to a regional scale because the NHDPlus catchment serves as its spatial computational unit. The present study demonstrated the potential of this framework to find cost-effective solutions to meet a water quality target, such as a 20% TN load reduction, under different conditions. Copyright © 2015 Elsevier Ltd. All rights reserved.

Spatial and temporal variability of precipitation in Serbia for the period 1961-2010

NASA Astrophysics Data System (ADS)

Milovanović, Boško; Schuster, Phillip; Radovanović, Milan; Vakanjac, Vesna Ristić; Schneider, Christoph

2017-10-01

Monthly, seasonal and annual sums of precipitation in Serbia were analysed in this paper for the period 1961-2010. Latitude, longitude and altitude of 421 precipitation stations and terrain features in their close environment (slope and aspect of terrain within a radius of 10 km around the station) were used to develop a regression model on which spatial distribution of precipitation was calculated. The spatial distribution of annual, June (maximum values for almost all of the stations) and February (minimum values for almost all of the stations) precipitation is presented. Annual precipitation amounts ranged from 500 to 600 mm to over 1100 mm. June precipitation ranged from 60 to 140 mm and February precipitation from 30 to 100 mm. The validation results expressed as root mean square error (RMSE) for monthly sums ranged from 3.9 mm in October (7.5% of the average precipitation for this month) to 6.2 mm in April (10.4%). For seasonal sums, RMSE ranged from 10.4 mm during autumn (6.1% of the average precipitation for this season) to 20.5 mm during winter (13.4%). On the annual scale, RMSE was 68 mm (9.5% of the average amount of precipitation). We further analysed precipitation trends using Sen's estimation, while the Mann-Kendall test was used for testing the statistical significance of the trends. For most parts of Serbia, the mean annual precipitation trends fell between -5 and +5 and +5 and +15 mm/decade. June precipitation trends were mainly between -8 and +8 mm/decade. February precipitation trends generally ranged from -3 to +3 mm/decade.

Effects of spatial resolution and landscape structure on land cover characterization

NASA Astrophysics Data System (ADS)

Yang, Wenli

This dissertation addressed problems in scaling, problems that are among the main challenges in remote sensing. The principal objective of the research was to investigate the effects of changing spatial scale on the representation of land cover. A second objective was to determine the relationship between such effects, characteristics of landscape structure and scaling procedures. Four research issues related to spatial scaling were examined. They included: (1) the upscaling of Normalized Difference Vegetation Index (NDVI); (2) the effects of spatial scale on indices of landscape structure; (3) the representation of land cover databases at different spatial scales; and (4) the relationships between landscape indices and land cover area estimations. The overall bias resulting from non-linearity of NDVI in relation to spatial resolution is generally insignificant as compared to other factors such as influences of aerosols and water vapor. The bias is, however, related to land surface characteristics. Significant errors may be introduced in heterogeneous areas where different land cover types exhibit strong spectral contrast. Spatially upscaled SPOT and TM NDVIs have information content comparable with the AVHRR-derived NDVI. Indices of landscape structure and spatial resolution are generally related, but the exact forms of the relationships are subject to changes in other factors including the basic patch unit constituting a landscape and the proportional area of foreground land cover under consideration. The extent of agreement between spatially aggregated coarse resolution land cover datasets and full resolution datasets changes with the properties of the original datasets, including the pixel size and class definition. There are close relationships between landscape structure and class areas estimated from spatially aggregated land cover databases. The relationships, however, do not permit extension from one area to another. Inversion calibration across different geographic/ecological areas is, therefore, not feasible. Different rules govern the land cover area changes across resolutions when different upscaling methods are used. Special attention should be given to comparison between land cover maps derived using different methods.

Frugivory and Spatial Patterns of Seed Deposition by Carnivorous Mammals in Anthropogenic Landscapes: A Multi-Scale Approach

PubMed Central

López-Bao, José V.; González-Varo, Juan P.

2011-01-01

Background Knowledge about how frugivory and seed deposition are spatially distributed is valuable to understand the role of dispersers on the structure and dynamics of plant populations. This may be particularly important within anthropogenic areas, where either the patchy distribution of wild plants or the presence of cultivated fleshy-fruits may influence plant-disperser interactions. Methodology/Principal Findings We investigated frugivory and spatial patterns of seed deposition by carnivorous mammals in anthropogenic landscapes considering two spatial scales: ‘landscape’ (∼10 km2) and ‘habitat type’ (∼1–2 km2). We sampled carnivore faeces and plant abundance at three contrasting habitats (chestnut woods, mosaics and scrublands), each replicated within three different landscapes. Sixty-five percent of faeces collected (n = 1077) contained seeds, among which wild and cultivated seeds appeared in similar proportions (58% and 53%) despite that cultivated fruiting plants were much less abundant. Seed deposition was spatially structured among both spatial scales being different between fruit types. Whereas the most important source of spatial variation in deposition of wild seeds was the landscape scale, it was the habitat scale for cultivated seeds. At the habitat scale, seeds of wild species were mostly deposited within mosaics while seeds of cultivated species were within chestnut woods and scrublands. Spatial concordance between seed deposition and plant abundance was found only for wild species. Conclusions/Significance Spatial patterns of seed deposition by carnivores differed between fruit types and seemed to be modulated by the fleshy-fruited plant assemblages and the behaviour of dispersers. Our results suggest that a strong preference for cultivated fruits by carnivores may influence their spatial foraging behaviour and lower their dispersal services to wild species. However, the high amount of seeds removed within and between habitats suggests that carnivores must play an important role – often overlooked – as ‘restorers’ and ‘habitat shapers’ in anthropogenic areas. PMID:21297861

Abandoned Uranium Mines (AUM) Site Screening Map Service, 2016, US EPA Region 9

EPA Pesticide Factsheets

As described in detail in the Five-Year Report, US EPA completed on-the-ground screening of 521 abandoned uranium mine areas. US EPA and the Navajo EPA are using the Comprehensive Database and Atlas to determine which mines should be cleaned up first. US EPA continues to research and identify Potentially Responsible Parties (PRPs) under Superfund to contribute to the costs of cleanup efforts.This US EPA Region 9 web service contains the following map layers:Abandoned Uranium Mines, Priority Mines, Tronox Mines, Navajo Environmental Response Trust Mines, Mines with Enforcement Actions, Superfund AUM Regions, Navajo Nation Administrative Boundaries and Chapter Houses.Mine points have a maximum scale of 1:220,000, while Mine polygons have a minimum scale of 1:220,000. Chapter houses have a minimum scale of 1:200,000. BLM Land Status has a minimum scale of 1:150,000.Full FGDC metadata records for each layer can be found by clicking the layer name at the web service endpoint and viewing the layer description. Data used to create this web service are available for download at https://edg.epa.gov/metadata/catalog/data/data.page.Security Classification: Public. Access Constraints: None. Use Constraints: None. Please check sources, scale, accuracy, currentness and other available information. Please confirm that you are using the most recent copy of both data and metadata. Acknowledgement of the EPA would be appreciated.

The Effects of Fine-scale Soil Moisture and Canopy Heterogeneities on Energy and Soil Water Fluxes in a Temperate Mixed Deciduous Forest

NASA Astrophysics Data System (ADS)

He, L.; Ivanov, V. Y.; Bohrer, G.; Maurer, K.; Vogel, C. S.; Moghaddam, M.

2011-12-01

Vegetation is heterogeneous at different scales, influencing spatially variable energy and water exchanges between land-surface and atmosphere. Current land surface parameterizations of large-scale models consider spatial variability at a scale of a few kilometers and treat vegetation cover as aggregated patches with uniform properties. However, the coupling mechanisms between fine-scale soil moisture, vegetation, and energy fluxes such as evapotranspiration are strongly nonlinear; the aggregation of surface variations may produce biased energy fluxes. This study aims to improve the understanding of the scale impact in atmosphere-biosphere-hydrosphere interactions, which affects predictive capabilities of land surface models. The study uses a high-resolution, physically-based ecohydrological model tRIBS + VEGGIE as a data integration tool to upscale the heterogeneity of canopy distribution resolved at a few meters to the watershed scale. The study was carried out for a spatially heterogeneous, temperate mixed forest environment of Northern Michigan located near the University of Michigan Biological Station (UMBS). Energy and soil water dynamics were simulated at the tree-canopy resolution in the horizontal plane for a small domain (~2 sq. km) located within a footprint of the AmeriFlux tower. A variety of observational data were used to constrain and confirm the model, including a 3-m profile continuous soil moisture dataset and energy flux data (measured at the AmeriFlux tower footprint). A scenario with a spatially uniform canopy, corresponding to the commonly used 'big-leaf' scheme in land surface parameterizations was used to infer the effects of coarse-scale averaging. To gain insights on how heterogeneous canopy and soil moisture interact and contribute to the domain-averaged transpiration, several scenarios of tree-scale leaf area and soil moisture spatial variability were designed. Specifically, for the same mean states, the scenarios of variability of canopy biomass account for the spatial distribution of photosynthesis (and thus the stomatal resistance), the aerodynamic and leaf boundary layer resistances as well as the differential radiation forcing due to tall tree exposure and lateral shading of short trees. The numerical experiments show that by transpiring spatially varying amounts of water, heterogeneous canopies adjust the spatial soil water state to the scaled inverse of the canopy biomass regardless of the initial moisture state. Such a spatial distribution can be further wiped out because of the differential water stress. The aggregation of canopy-scale atmosphere-biosphere-hydrosphere interactions demonstrates non-linear relationship between soil moisture and evapotranspiration, influencing domain-averaged energy fluxes.

Accounting for small scale heterogeneity in ecohydrologic watershed models

NASA Astrophysics Data System (ADS)

Bhaskar, A.; Fleming, B.; Hogan, D. M.

2016-12-01

Spatially distributed ecohydrologic models are inherently constrained by the spatial resolution of their smallest units, below which land and processes are assumed to be homogenous. At coarse scales, heterogeneity is often accounted for by computing store and fluxes of interest over a distribution of land cover types (or other sources of heterogeneity) within spatially explicit modeling units. However this approach ignores spatial organization and the lateral transfer of water and materials downslope. The challenge is to account both for the role of flow network topology and fine-scale heterogeneity. We present a new approach that defines two levels of spatial aggregation and that integrates spatially explicit network approach with a flexible representation of finer-scale aspatial heterogeneity. Critically, this solution does not simply increase the resolution of the smallest spatial unit, and so by comparison, results in improved computational efficiency. The approach is demonstrated by adapting Regional Hydro-Ecologic Simulation System (RHESSys), an ecohydrologic model widely used to simulate climate, land use, and land management impacts. We illustrate the utility of our approach by showing how the model can be used to better characterize forest thinning impacts on ecohydrology. Forest thinning is typically done at the scale of individual trees, and yet management responses of interest include impacts on watershed scale hydrology and on downslope riparian vegetation. Our approach allow us to characterize the variability in tree size/carbon reduction and water transfers between neighboring trees while still capturing hillslope to watershed scale effects, Our illustrative example demonstrates that accounting for these fine scale effects can substantially alter model estimates, in some cases shifting the impacts of thinning on downslope water availability from increases to decreases. We conclude by describing other use cases that may benefit from this approach including characterizing urban vegetation and storm water management features and their impact on watershed scale hydrology and biogeochemical cycling.

Accounting for small scale heterogeneity in ecohydrologic watershed models

NASA Astrophysics Data System (ADS)

Burke, W.; Tague, C.

2017-12-01

Spatially distributed ecohydrologic models are inherently constrained by the spatial resolution of their smallest units, below which land and processes are assumed to be homogenous. At coarse scales, heterogeneity is often accounted for by computing store and fluxes of interest over a distribution of land cover types (or other sources of heterogeneity) within spatially explicit modeling units. However this approach ignores spatial organization and the lateral transfer of water and materials downslope. The challenge is to account both for the role of flow network topology and fine-scale heterogeneity. We present a new approach that defines two levels of spatial aggregation and that integrates spatially explicit network approach with a flexible representation of finer-scale aspatial heterogeneity. Critically, this solution does not simply increase the resolution of the smallest spatial unit, and so by comparison, results in improved computational efficiency. The approach is demonstrated by adapting Regional Hydro-Ecologic Simulation System (RHESSys), an ecohydrologic model widely used to simulate climate, land use, and land management impacts. We illustrate the utility of our approach by showing how the model can be used to better characterize forest thinning impacts on ecohydrology. Forest thinning is typically done at the scale of individual trees, and yet management responses of interest include impacts on watershed scale hydrology and on downslope riparian vegetation. Our approach allow us to characterize the variability in tree size/carbon reduction and water transfers between neighboring trees while still capturing hillslope to watershed scale effects, Our illustrative example demonstrates that accounting for these fine scale effects can substantially alter model estimates, in some cases shifting the impacts of thinning on downslope water availability from increases to decreases. We conclude by describing other use cases that may benefit from this approach including characterizing urban vegetation and storm water management features and their impact on watershed scale hydrology and biogeochemical cycling.

Spatial Structure of Seagrass Suggests That Size-Dependent Plant Traits Have a Strong Influence on the Distribution and Maintenance of Tropical Multispecies Meadows

PubMed Central

Ooi, Jillian L. S.; Van Niel, Kimberly P.; Kendrick, Gary A.; Holmes, Karen W.

2014-01-01

Background Seagrass species in the tropics occur in multispecies meadows. How these meadows are maintained through species co-existence and what their ecological drivers may be has been an overarching question in seagrass biogeography. In this study, we quantify the spatial structure of four co-existing species and infer potential ecological processes from these structures. Methods and Results Species presence/absence data were collected using underwater towed and dropped video cameras in Pulau Tinggi, Malaysia. The geostatistical method, utilizing semivariograms, was used to describe the spatial structure of Halophila spp, Halodule uninervis, Syringodium isoetifolium and Cymodocea serrulata. Species had spatial patterns that were oriented in the along-shore and across-shore directions, nested with larger species in meadow interiors, and consisted of multiple structures that indicate the influence of 2–3 underlying processes. The Linear Model of Coregionalization (LMC) was used to estimate the amount of variance contributing to the presence of a species at specific spatial scales. These distances were <2.5 m (micro-scale), 2.5–50 m (fine-scale) and >50 m (broad-scale) in the along-shore; and <2.5 m (micro-scale), 2.5–140 m (fine-scale) and >140 m (broad-scale) in the across-shore. The LMC suggests that smaller species (Halophila spp and H. uninervis) were most influenced by broad-scale processes such as hydrodynamics and water depth whereas large, localised species (S. isoetifolium and C. serrulata) were more influenced by finer-scale processes such as sediment burial, seagrass colonization and growth, and physical disturbance. Conclusion In this study, we provide evidence that spatial structure is distinct even when species occur in well-mixed multispecies meadows, and we suggest that size-dependent plant traits have a strong influence on the distribution and maintenance of tropical marine plant communities. This study offers a contrast from previous spatial models of seagrasses which have largely focused on monospecific temperate meadows. PMID:24497978

Spatial structure of seagrass suggests that size-dependent plant traits have a strong influence on the distribution and maintenance of tropical multispecies meadows.

PubMed

Ooi, Jillian L S; Van Niel, Kimberly P; Kendrick, Gary A; Holmes, Karen W

2014-01-01

Seagrass species in the tropics occur in multispecies meadows. How these meadows are maintained through species co-existence and what their ecological drivers may be has been an overarching question in seagrass biogeography. In this study, we quantify the spatial structure of four co-existing species and infer potential ecological processes from these structures. Species presence/absence data were collected using underwater towed and dropped video cameras in Pulau Tinggi, Malaysia. The geostatistical method, utilizing semivariograms, was used to describe the spatial structure of Halophila spp, Halodule uninervis, Syringodium isoetifolium and Cymodocea serrulata. Species had spatial patterns that were oriented in the along-shore and across-shore directions, nested with larger species in meadow interiors, and consisted of multiple structures that indicate the influence of 2-3 underlying processes. The Linear Model of Coregionalization (LMC) was used to estimate the amount of variance contributing to the presence of a species at specific spatial scales. These distances were <2.5 m (micro-scale), 2.5-50 m (fine-scale) and >50 m (broad-scale) in the along-shore; and <2.5 m (micro-scale), 2.5-140 m (fine-scale) and >140 m (broad-scale) in the across-shore. The LMC suggests that smaller species (Halophila spp and H. uninervis) were most influenced by broad-scale processes such as hydrodynamics and water depth whereas large, localised species (S. isoetifolium and C. serrulata) were more influenced by finer-scale processes such as sediment burial, seagrass colonization and growth, and physical disturbance. In this study, we provide evidence that spatial structure is distinct even when species occur in well-mixed multispecies meadows, and we suggest that size-dependent plant traits have a strong influence on the distribution and maintenance of tropical marine plant communities. This study offers a contrast from previous spatial models of seagrasses which have largely focused on monospecific temperate meadows.

Spatial Distribution of Surface Soil Moisture in a Small Forested Catchment

EPA Science Inventory

Predicting the spatial distribution of soil moisture is an important hydrological question. We measured the spatial distribution of surface soil moisture (upper 6 cm) using an Amplitude Domain Reflectometry sensor at the plot scale (2 × 2 m) and small catchment scale (0.84 ha) in...

Spatial correlations of Diceroprocta apache and its host plants: Evidence for a negative impact from Tamarix invasion

USGS Publications Warehouse

Ellingson, A.R.; Andersen, D.C.

2002-01-01

1. The hypothesis that the habitat-scale spatial distribution of the, Apache cicada Diceroprocta apache Davis is unaffected by the presence of the invasive exotic saltcedar Tamarix ramosissima was tested using data from 205 1-m2 quadrats placed within the flood-plain of the Bill Williams River, Arizona, U.S.A. Spatial dependencies within and between cicada density and habitat variables were estimated using Moran's I and its bivariate analogue to discern patterns and associations at spatial scales from 1 to 30 m. 2. Apache cicadas were spatially aggregated in high-density clusters averaging 3m in diameter. A positive association between cicada density, estimated by exuvial density, and the per cent canopy cover of a native tree, Goodding's willow Salix gooddingii, was detected in a non-spatial correlation analysis. No non-spatial association between cicada density and saltcedar canopy cover was detected. 3. Tests for spatial cross-correlation using the bivariate IYZ indicated the presence of a broad-scale negative association between cicada density and saltcedar canopy cover. This result suggests that large continuous stands of saltcedar are associated with reduced cicada density. In contrast, positive associations detected at spatial scales larger than individual quadrats suggested a spill-over of high cicada density from areas featuring Goodding's willow canopy into surrounding saltcedar monoculture. 4. Taken together and considered in light of the Apache cicada's polyphagous habits, the observed spatial patterns suggest that broad-scale factors such as canopy heterogeneity affect cicada habitat use more than host plant selection. This has implications for management of lower Colorado River riparian woodlands to promote cicada presence and density through maintenance or creation of stands of native trees as well as manipulation of the characteristically dense and homogeneous saltcedar canopies.

Spatial correlations of Diceroprocta apache and its host plants: Evidence for a negative impact from Tamarix invasion

USGS Publications Warehouse

Ellingson, A.R.; Andersen, D.C.

2002-01-01

1. The hypothesis that the habitat-scale spatial distribution of the Apache cicada Diceroprocta apache Davis is unaffected by the presence of the invasive exotic saltcedar Tamarix ramosissima was tested using data from 205 1-m2 quadrats placed within the flood-plain of the Bill Williams River, Arizona, U.S.A. Spatial dependencies within and between cicada density and habitat variables were estimated using Moran's I and its bivariate analogue to discern patterns and associations at spatial scales from 1 to 30 m.2. Apache cicadas were spatially aggregated in high-density clusters averaging 3 m in diameter. A positive association between cicada density, estimated by exuvial density, and the per cent canopy cover of a native tree, Goodding's willow Salix gooddingii, was detected in a non-spatial correlation analysis. No non-spatial association between cicada density and saltcedar canopy cover was detected.3. Tests for spatial cross-correlation using the bivariate IYZ indicated the presence of a broad-scale negative association between cicada density and saltcedar canopy cover. This result suggests that large continuous stands of saltcedar are associated with reduced cicada density. In contrast, positive associations detected at spatial scales larger than individual quadrats suggested a spill-over of high cicada density from areas featuring Goodding's willow canopy into surrounding saltcedar monoculture.4. Taken together and considered in light of the Apache cicada's polyphagous habits, the observed spatial patterns suggest that broad-scale factors such as canopy heterogeneity affect cicada habitat use more than host plant selection. This has implications for management of lower Colorado River riparian woodlands to promote cicada presence and density through maintenance or creation of stands of native trees as well as manipulation of the characteristically dense and homogeneous saltcedar canopies.

Toward a RPC-based muon tomography system for cargo containers.

NASA Astrophysics Data System (ADS)

Baesso, P.; Cussans, D.; Thomay, C.; Velthuis, J.

2014-10-01

A large area scanner for cosmic muon tomography is currently being developed at University of Bristol. Thanks to their abundance and penetrating power, cosmic muons have been suggested as ideal candidates to scan large containers in search of special nuclear materials, which are characterized by high-Z and high density. The feasibility of such a scanner heavily depends on the detectors used to track the muons: for a typical container, the minimum required sensitive area is of the order of 100 2. The spatial resolution required depends on the geometrical configuration of the detectors. For practical purposes, a resolution of the order of 1 mm or better is desirable. A good time resolution can be exploited to provide momentum information: a resolution of the order of nanoseconds can be used to separate sub-GeV muons from muons with higher energies. Resistive plate chambers have a low cost per unit area and good spatial and time resolution; these features make them an excellent choice as detectors for muon tomography. In order to instrument a large area demonstrator we have produced 25 new readout boards and 30 glass RPCs. The RPCs measure 1800 mm× 600 mm and are read out using 1.68 mm pitch copper strips. The chambers were tested with a standardized procedure, i.e. without optimizing the working parameters to take into account differences in the manufacturing process, and the results show that the RPCs have an efficiency between 87% and 95%. The readout electronics show a signal to noise ratio greater than 20 for minimum ionizing particles. Spatial resolution better than 500 μm can easily be achieved using commercial read out ASICs. These results are better than the original minimum requirements to pass the tests and we are now ready to install the detectors.

Spatial Patterns in Water Temperature in Pacific Northwest Rivers: Diversity at Multiple Scales and Potential Influence of Climate Change

NASA Astrophysics Data System (ADS)

Torgersen, C. E.; Fullerton, A.; Lawler, J. J.; Ebersole, J. L.; Leibowitz, S. G.; Steel, E. A.; Beechie, T. J.; Faux, R.

2016-12-01

Understanding spatial patterns in water temperature will be essential for evaluating vulnerability of aquatic biota to future climate and for identifying and protecting diverse thermal habitats. We used high-resolution remotely sensed water temperature data for over 16,000 km of 2nd to 7th-order rivers throughout the Pacific Northwest and California to evaluate spatial patterns of summertime water temperature at multiple spatial scales. We found a diverse and geographically distributed suite of whole-river patterns. About half of rivers warmed asymptotically in a downstream direction, whereas the rest exhibited complex and unique spatial patterns. Patterns were associated with both broad-scale hydroclimatic variables as well as characteristics unique to each basin. Within-river thermal heterogeneity patterns were highly river-specific; across rivers, median size and spacing of cool patches <15 °C were around 250 m. Patches of this size are large enough for juvenile salmon rearing and for resting during migration, and the distance between patches is well within the movement capabilities of both juvenile and adult salmon. We found considerable thermal heterogeneity at fine spatial scales that may be important to fish that would be missed if data were analyzed at coarser scales. We estimated future thermal heterogeneity and concluded that climate change will cause warmer temperatures overall, but that thermal heterogeneity patterns may remain similar in the future for many rivers. We demonstrated considerable spatial complexity in both current and future water temperature, and resolved spatial patterns that could not have been perceived without spatially continuous data.

Using High Spatial Resolution Satellite Imagery to Map Forest Burn Severity Across Spatial Scales in a Pine Barrens Ecosystem

NASA Technical Reports Server (NTRS)

Meng, Ran; Wu, Jin; Schwager, Kathy L.; Zhao, Feng; Dennison, Philip E.; Cook, Bruce D.; Brewster, Kristen; Green, Timothy M.; Serbin, Shawn P.

2017-01-01

As a primary disturbance agent, fire significantly influences local processes and services of forest ecosystems. Although a variety of remote sensing based approaches have been developed and applied to Landsat mission imagery to infer burn severity at 30 m spatial resolution, forest burn severity have still been seldom assessed at fine spatial scales (less than or equal to 5 m) from very-high-resolution (VHR) data. We assessed a 432 ha forest fire that occurred in April 2012 on Long Island, New York, within the Pine Barrens region, a unique but imperiled fire-dependent ecosystem in the northeastern United States. The mapping of forest burn severity was explored here at fine spatial scales, for the first time using remotely sensed spectral indices and a set of Multiple Endmember Spectral Mixture Analysis (MESMA) fraction images from bi-temporal - pre- and post-fire event - WorldView-2 (WV-2) imagery at 2 m spatial resolution. We first evaluated our approach using 1 m by 1 m validation points at the sub-crown scale per severity class (i.e. unburned, low, moderate, and high severity) from the post-fire 0.10 m color aerial ortho-photos; then, we validated the burn severity mapping of geo-referenced dominant tree crowns (crown scale) and 15 m by 15 m fixed-area plots (inter-crown scale) with the post-fire 0.10 m aerial ortho-photos and measured crown information of twenty forest inventory plots. Our approach can accurately assess forest burn severity at the sub-crown (overall accuracy is 84% with a Kappa value of 0.77), crown (overall accuracy is 82% with a Kappa value of 0.76), and inter-crown scales (89% of the variation in estimated burn severity ratings (i.e. Geo-Composite Burn Index (CBI)). This work highlights that forest burn severity mapping from VHR data can capture heterogeneous fire patterns at fine spatial scales over the large spatial extents. This is important since most ecological processes associated with fire effects vary at the less than 30 m scale and VHR approaches could significantly advance our ability to characterize fire effects on forest ecosystems.

Using high spatial resolution satellite imagery to map forest burn severity across spatial scales in a Pine Barrens ecosystem

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

Meng, Ran; Wu, Jin; Schwager, Kathy L.

As a primary disturbance agent, fire significantly influences local processes and services of forest ecosystems. Although a variety of remote sensing based approaches have been developed and applied to Landsat mission imagery to infer burn severity at 30 m spatial resolution, forest burn severity have still been seldom assessed at fine spatial scales (≤ 5 m) from very-high-resolution (VHR) data. Here we assessed a 432 ha forest fire that occurred in April 2012 on Long Island, New York, within the Pine Barrens region, a unique but imperiled fire-dependent ecosystem in the northeastern United States. The mapping of forest burn severitymore » was explored here at fine spatial scales, for the first time using remotely sensed spectral indices and a set of Multiple Endmember Spectral Mixture Analysis (MESMA) fraction images from bi-temporal — pre- and post-fire event — WorldView-2 (WV-2) imagery at 2 m spatial resolution. We first evaluated our approach using 1 m by 1 m validation points at the sub-crown scale per severity class (i.e. unburned, low, moderate, and high severity) from the post-fire 0.10 m color aerial ortho-photos; then, we validated the burn severity mapping of geo-referenced dominant tree crowns (crown scale) and 15 m by 15 m fixed-area plots (inter-crown scale) with the post-fire 0.10 m aerial ortho-photos and measured crown information of twenty forest inventory plots. Our approach can accurately assess forest burn severity at the sub-crown (overall accuracy is 84% with a Kappa value of 0.77), crown (overall accuracy is 82% with a Kappa value of 0.76), and inter-crown scales (89% of the variation in estimated burn severity ratings (i.e. Geo-Composite Burn Index (CBI)). Lastly, this work highlights that forest burn severity mapping from VHR data can capture heterogeneous fire patterns at fine spatial scales over the large spatial extents. This is important since most ecological processes associated with fire effects vary at the < 30 m scale and VHR approaches could significantly advance our ability to characterize fire effects on forest ecosystems.« less

Using high spatial resolution satellite imagery to map forest burn severity across spatial scales in a Pine Barrens ecosystem

DOE PAGES

Meng, Ran; Wu, Jin; Schwager, Kathy L.; ...

2017-01-21

As a primary disturbance agent, fire significantly influences local processes and services of forest ecosystems. Although a variety of remote sensing based approaches have been developed and applied to Landsat mission imagery to infer burn severity at 30 m spatial resolution, forest burn severity have still been seldom assessed at fine spatial scales (≤ 5 m) from very-high-resolution (VHR) data. Here we assessed a 432 ha forest fire that occurred in April 2012 on Long Island, New York, within the Pine Barrens region, a unique but imperiled fire-dependent ecosystem in the northeastern United States. The mapping of forest burn severitymore » was explored here at fine spatial scales, for the first time using remotely sensed spectral indices and a set of Multiple Endmember Spectral Mixture Analysis (MESMA) fraction images from bi-temporal — pre- and post-fire event — WorldView-2 (WV-2) imagery at 2 m spatial resolution. We first evaluated our approach using 1 m by 1 m validation points at the sub-crown scale per severity class (i.e. unburned, low, moderate, and high severity) from the post-fire 0.10 m color aerial ortho-photos; then, we validated the burn severity mapping of geo-referenced dominant tree crowns (crown scale) and 15 m by 15 m fixed-area plots (inter-crown scale) with the post-fire 0.10 m aerial ortho-photos and measured crown information of twenty forest inventory plots. Our approach can accurately assess forest burn severity at the sub-crown (overall accuracy is 84% with a Kappa value of 0.77), crown (overall accuracy is 82% with a Kappa value of 0.76), and inter-crown scales (89% of the variation in estimated burn severity ratings (i.e. Geo-Composite Burn Index (CBI)). Lastly, this work highlights that forest burn severity mapping from VHR data can capture heterogeneous fire patterns at fine spatial scales over the large spatial extents. This is important since most ecological processes associated with fire effects vary at the < 30 m scale and VHR approaches could significantly advance our ability to characterize fire effects on forest ecosystems.« less

Beta diversity at different spatial scales: plant communities in organic and conventional agriculture.

PubMed

Gabriel, Doreen; Roschewitz, Indra; Tscharntke, Teja; Thies, Carsten

2006-10-01

Biodiversity studies that guide agricultural subsidy policy have generally compared farming systems at a single spatial scale: the field. However, diversity patterns vary across spatial scales. Here, we examined the effects of farming system (organic vs. conventional) and position in the field (edge vs. center) on plant species richness in wheat fields at three spatial scales. We quantified alpha-, beta-, and gamma-diversity at the microscale in 800 plots, at the mesoscale in 40 fields, and at the macroscale in three regions using the additive partitioning approach, and evaluated the relative contribution of beta-diversity at each spatial scale to total observed species richness. We found that alpha-, beta-, and gamma-diversity were higher in organic than conventional fields and higher at the field edge than in the field center at all spatial scales. In both farming systems, beta-diversity at the meso- and macroscale explained most of the overall species richness (up to 37% and 25%, respectively), indicating considerable differences in community composition among fields and regions due to environmental heterogeneity. The spatial scale at which beta-diversity contributed the most to overall species richness differed between rare and common species. Total richness of rare species (present in < or = 5% of total samples) was mainly explained by differences in community composition at the meso- and macroscale (up to 27% and 48%, respectively), but only in organic fields. Total richness of common species (present in > or = 25% of total samples) was explained by differences in community composition at the micro- and mesoscale (up to 29% and 47%, respectively), i.e., among plots and fields, independent of farming system. Our results show that organic farming made the greatest contribution to total species richness at the meso (among fields) and macro (among regions) scale due to environmental heterogeneity. Hence, agri-environment schemes should exploit this large-scale contribution of beta-diversity by tailoring schemes at regional scales to maximize dissimilarity between conservation areas using geographic information systems rather than focusing entirely at the classical local-field scale, which is the current practice.

Model simulations and proxy-based reconstructions for the European region in the past millennium (Invited)

NASA Astrophysics Data System (ADS)

Zorita, E.

2009-12-01

One of the objectives when comparing simulations of past climates to proxy-based climate reconstructions is to asses the skill of climate models to simulate climate change. This comparison may accomplished at large spatial scales, for instance the evolution of simulated and reconstructed Northern Hemisphere annual temperature, or at regional or point scales. In both approaches a 'fair' comparison has to take into account different aspects that affect the inevitable uncertainties and biases in the simulations and in the reconstructions. These efforts face a trade-off: climate models are believed to be more skillful at large hemispheric scales, but climate reconstructions are these scales are burdened by the spatial distribution of available proxies and by methodological issues surrounding the statistical method used to translate the proxy information into large-spatial averages. Furthermore, the internal climatic noise at large hemispheric scales is low, so that the sampling uncertainty tends to be also low. On the other hand, the skill of climate models at regional scales is limited by the coarse spatial resolution, which hinders a faithful representation of aspects important for the regional climate. At small spatial scales, the reconstruction of past climate probably faces less methodological problems if information from different proxies is available. The internal climatic variability at regional scales is, however, high. In this contribution some examples of the different issues faced when comparing simulation and reconstructions at small spatial scales in the past millennium are discussed. These examples comprise reconstructions from dendrochronological data and from historical documentary data in Europe and climate simulations with global and regional models. These examples indicate that the centennial climate variations can offer a reasonable target to assess the skill of global climate models and of proxy-based reconstructions, even at small spatial scales. However, as the focus shifts towards higher frequency variability, decadal or multidecadal, the need for larger simulation ensembles becomes more evident. Nevertheless,the comparison at these time scales may expose some lines of research on the origin of multidecadal regional climate variability.

Scaling biodiversity responses to hydrological regimes.

PubMed

Rolls, Robert J; Heino, Jani; Ryder, Darren S; Chessman, Bruce C; Growns, Ivor O; Thompson, Ross M; Gido, Keith B

2018-05-01

Of all ecosystems, freshwaters support the most dynamic and highly concentrated biodiversity on Earth. These attributes of freshwater biodiversity along with increasing demand for water mean that these systems serve as significant models to understand drivers of global biodiversity change. Freshwater biodiversity changes are often attributed to hydrological alteration by water-resource development and climate change owing to the role of the hydrological regime of rivers, wetlands and floodplains affecting patterns of biodiversity. However, a major gap remains in conceptualising how the hydrological regime determines patterns in biodiversity's multiple spatial components and facets (taxonomic, functional and phylogenetic). We synthesised primary evidence of freshwater biodiversity responses to natural hydrological regimes to determine how distinct ecohydrological mechanisms affect freshwater biodiversity at local, landscape and regional spatial scales. Hydrological connectivity influences local and landscape biodiversity, yet responses vary depending on spatial scale. Biodiversity at local scales is generally positively associated with increasing connectivity whereas landscape-scale biodiversity is greater with increasing fragmentation among locations. The effects of hydrological disturbance on freshwater biodiversity are variable at separate spatial scales and depend on disturbance frequency and history and organism characteristics. The role of hydrology in determining habitat for freshwater biodiversity also depends on spatial scaling. At local scales, persistence, stability and size of habitat each contribute to patterns of freshwater biodiversity yet the responses are variable across the organism groups that constitute overall freshwater biodiversity. We present a conceptual model to unite the effects of different ecohydrological mechanisms on freshwater biodiversity across spatial scales, and develop four principles for applying a multi-scaled understanding of freshwater biodiversity responses to hydrological regimes. The protection and restoration of freshwater biodiversity is both a fundamental justification and a central goal of environmental water allocation worldwide. Clearer integration of concepts of spatial scaling in the context of understanding impacts of hydrological regimes on biodiversity will increase uptake of evidence into environmental flow implementation, identify suitable biodiversity targets responsive to hydrological change or restoration, and identify and manage risks of environmental flows contributing to biodiversity decline. © 2017 Cambridge Philosophical Society.

A rank-based approach for correcting systematic biases in spatial disaggregation of coarse-scale climate simulations

NASA Astrophysics Data System (ADS)

Nahar, Jannatun; Johnson, Fiona; Sharma, Ashish

2017-07-01

Use of General Circulation Model (GCM) precipitation and evapotranspiration sequences for hydrologic modelling can result in unrealistic simulations due to the coarse scales at which GCMs operate and the systematic biases they contain. The Bias Correction Spatial Disaggregation (BCSD) method is a popular statistical downscaling and bias correction method developed to address this issue. The advantage of BCSD is its ability to reduce biases in the distribution of precipitation totals at the GCM scale and then introduce more realistic variability at finer scales than simpler spatial interpolation schemes. Although BCSD corrects biases at the GCM scale before disaggregation; at finer spatial scales biases are re-introduced by the assumptions made in the spatial disaggregation process. Our study focuses on this limitation of BCSD and proposes a rank-based approach that aims to reduce the spatial disaggregation bias especially for both low and high precipitation extremes. BCSD requires the specification of a multiplicative bias correction anomaly field that represents the ratio of the fine scale precipitation to the disaggregated precipitation. It is shown that there is significant temporal variation in the anomalies, which is masked when a mean anomaly field is used. This can be improved by modelling the anomalies in rank-space. Results from the application of the rank-BCSD procedure improve the match between the distributions of observed and downscaled precipitation at the fine scale compared to the original BCSD approach. Further improvements in the distribution are identified when a scaling correction to preserve mass in the disaggregation process is implemented. An assessment of the approach using a single GCM over Australia shows clear advantages especially in the simulation of particularly low and high downscaled precipitation amounts.

Measuring floodplain spatial patterns using continuous surface metrics at multiple scales

USGS Publications Warehouse

Scown, Murray W.; Thoms, Martin C.; DeJager, Nathan R.

2015-01-01

Interactions between fluvial processes and floodplain ecosystems occur upon a floodplain surface that is often physically complex. Spatial patterns in floodplain topography have only recently been quantified over multiple scales, and discrepancies exist in how floodplain surfaces are perceived to be spatially organised. We measured spatial patterns in floodplain topography for pool 9 of the Upper Mississippi River, USA, using moving window analyses of eight surface metrics applied to a 1 × 1 m2 DEM over multiple scales. The metrics used were Range, SD, Skewness, Kurtosis, CV, SDCURV,Rugosity, and Vol:Area, and window sizes ranged from 10 to 1000 m in radius. Surface metric values were highly variable across the floodplain and revealed a high degree of spatial organisation in floodplain topography. Moran's I correlograms fit to the landscape of each metric at each window size revealed that patchiness existed at nearly all window sizes, but the strength and scale of patchiness changed within window size, suggesting that multiple scales of patchiness and patch structure exist in the topography of this floodplain. Scale thresholds in the spatial patterns were observed, particularly between the 50 and 100 m window sizes for all surface metrics and between the 500 and 750 m window sizes for most metrics. These threshold scales are ~ 15–20% and 150% of the main channel width (1–2% and 10–15% of the floodplain width), respectively. These thresholds may be related to structuring processes operating across distinct scale ranges. By coupling surface metrics, multi-scale analyses, and correlograms, quantifying floodplain topographic complexity is possible in ways that should assist in clarifying how floodplain ecosystems are structured.

Multi-scale variation in spatial heterogeneity for microbial community structure in an eastern Virginia agricultural field

NASA Technical Reports Server (NTRS)

Franklin, Rima B.; Mills, Aaron L.

2003-01-01

To better understand the distribution of soil microbial communities at multiple spatial scales, a survey was conducted to examine the spatial organization of community structure in a wheat field in eastern Virginia (USA). Nearly 200 soil samples were collected at a variety of separation distances ranging from 2.5 cm to 11 m. Whole-community DNA was extracted from each sample, and community structure was compared using amplified fragment length polymorphism (AFLP) DNA fingerprinting. Relative similarity was calculated between each pair of samples and compared using geostatistical variogram analysis to study autocorrelation as a function of separation distance. Spatial autocorrelation was found at scales ranging from 30 cm to more than 6 m, depending on the sampling extent considered. In some locations, up to four different correlation length scales were detected. The presence of nested scales of variability suggests that the environmental factors regulating the development of the communities in this soil may operate at different scales. Kriging was used to generate maps of the spatial organization of communities across the plot, and the results demonstrated that bacterial distributions can be highly structured, even within a habitat that appears relatively homogeneous at the plot and field scale. Different subsets of the microbial community were distributed differently across the plot, and this is thought to be due to the variable response of individual populations to spatial heterogeneity associated with soil properties. c2003 Federation of European Microbiological Societies. Published by Elsevier Science B.V. All rights reserved.

Uniform functional structure across spatial scales in an intertidal benthic assemblage.

PubMed

Barnes, R S K; Hamylton, Sarah

2015-05-01

To investigate the causes of the remarkable similarity of emergent assemblage properties that has been demonstrated across disparate intertidal seagrass sites and assemblages, this study examined whether their emergent functional-group metrics are scale related by testing the null hypothesis that functional diversity and the suite of dominant functional groups in seagrass-associated macrofauna are robust structural features of such assemblages and do not vary spatially across nested scales within a 0.4 ha area. This was carried out via a lattice of 64 spatially referenced stations. Although densities of individual components were patchily dispersed across the locality, rank orders of importance of the 14 functional groups present, their overall functional diversity and evenness, and the proportions of the total individuals contained within each showed, in contrast, statistically significant spatial uniformity, even at areal scales <2 m(2). Analysis of the proportional importance of the functional groups in their geospatial context also revealed weaker than expected levels of spatial autocorrelation, and then only at the smaller scales and amongst the most dominant groups, and only a small number of negative correlations occurred between the proportional importances of the individual groups. In effect, such patterning was a surface veneer overlying remarkable stability of assemblage functional composition across all spatial scales. Although assemblage species composition is known to be homogeneous in some soft-sediment marine systems over equivalent scales, this combination of patchy individual components yet basically constant functional-group structure seems as yet unreported. Copyright © 2015 Elsevier Ltd. All rights reserved.

Selecting habitat to survive: the impact of road density on survival in a large carnivore.

PubMed

Basille, Mathieu; Van Moorter, Bram; Herfindal, Ivar; Martin, Jodie; Linnell, John D C; Odden, John; Andersen, Reidar; Gaillard, Jean-Michel

2013-01-01

Habitat selection studies generally assume that animals select habitat and food resources at multiple scales to maximise their fitness. However, animals sometimes prefer habitats of apparently low quality, especially when considering the costs associated with spatially heterogeneous human disturbance. We used spatial variation in human disturbance, and its consequences on lynx survival, a direct fitness component, to test the Hierarchical Habitat Selection hypothesis from a population of Eurasian lynx Lynx lynx in southern Norway. Data from 46 lynx monitored with telemetry indicated that a high proportion of forest strongly reduced the risk of mortality from legal hunting at the home range scale, while increasing road density strongly increased such risk at the finer scale within the home range. We found hierarchical effects of the impact of human disturbance, with a higher road density at a large scale reinforcing its negative impact at a fine scale. Conversely, we demonstrated that lynx shifted their habitat selection to avoid areas with the highest road densities within their home ranges, thus supporting a compensatory mechanism at fine scale enabling lynx to mitigate the impact of large-scale disturbance. Human impact, positively associated with high road accessibility, was thus a stronger driver of lynx space use at a finer scale, with home range characteristics nevertheless constraining habitat selection. Our study demonstrates the truly hierarchical nature of habitat selection, which aims at maximising fitness by selecting against limiting factors at multiple spatial scales, and indicates that scale-specific heterogeneity of the environment is driving individual spatial behaviour, by means of trade-offs across spatial scales.

Spatial downscaling of soil prediction models based on weighted generalized additive models in smallholder farm settings.

PubMed

Xu, Yiming; Smith, Scot E; Grunwald, Sabine; Abd-Elrahman, Amr; Wani, Suhas P; Nair, Vimala D

2017-09-11

Digital soil mapping (DSM) is gaining momentum as a technique to help smallholder farmers secure soil security and food security in developing regions. However, communications of the digital soil mapping information between diverse audiences become problematic due to the inconsistent scale of DSM information. Spatial downscaling can make use of accessible soil information at relatively coarse spatial resolution to provide valuable soil information at relatively fine spatial resolution. The objective of this research was to disaggregate the coarse spatial resolution soil exchangeable potassium (K ex ) and soil total nitrogen (TN) base map into fine spatial resolution soil downscaled map using weighted generalized additive models (GAMs) in two smallholder villages in South India. By incorporating fine spatial resolution spectral indices in the downscaling process, the soil downscaled maps not only conserve the spatial information of coarse spatial resolution soil maps but also depict the spatial details of soil properties at fine spatial resolution. The results of this study demonstrated difference between the fine spatial resolution downscaled maps and fine spatial resolution base maps is smaller than the difference between coarse spatial resolution base maps and fine spatial resolution base maps. The appropriate and economical strategy to promote the DSM technique in smallholder farms is to develop the relatively coarse spatial resolution soil prediction maps or utilize available coarse spatial resolution soil maps at the regional scale and to disaggregate these maps to the fine spatial resolution downscaled soil maps at farm scale.