Deciphering the adjustment between environment and life history in annuals: lessons from a geographically-explicit approach in Arabidopsis thaliana.

PubMed

Manzano-Piedras, Esperanza; Marcer, Arnald; Alonso-Blanco, Carlos; Picó, F Xavier

2014-01-01

The role that different life-history traits may have in the process of adaptation caused by divergent selection can be assessed by using extensive collections of geographically-explicit populations. This is because adaptive phenotypic variation shifts gradually across space as a result of the geographic patterns of variation in environmental selective pressures. Hence, large-scale experiments are needed to identify relevant adaptive life-history traits as well as their relationships with putative selective agents. We conducted a field experiment with 279 geo-referenced accessions of the annual plant Arabidopsis thaliana collected across a native region of its distribution range, the Iberian Peninsula. We quantified variation in life-history traits throughout the entire life cycle. We built a geographic information system to generate an environmental data set encompassing climate, vegetation and soil data. We analysed the spatial autocorrelation patterns of environmental variables and life-history traits, as well as the relationship between environmental and phenotypic data. Almost all environmental variables were significantly spatially autocorrelated. By contrast, only two life-history traits, seed weight and flowering time, exhibited significant spatial autocorrelation. Flowering time, and to a lower extent seed weight, were the life-history traits with the highest significant correlation coefficients with environmental factors, in particular with annual mean temperature. In general, individual fitness was higher for accessions with more vigorous seed germination, higher recruitment and later flowering times. Variation in flowering time mediated by temperature appears to be the main life-history trait by which A. thaliana adjusts its life history to the varying Iberian environmental conditions. The use of extensive geographically-explicit data sets obtained from field experiments represents a powerful approach to unravel adaptive patterns of variation. In a context of current global warming, geographically-explicit approaches, evaluating the match between organisms and the environments where they live, may contribute to better assess and predict the consequences of global warming.

Spatial modeling in ecology: the flexibility of eigenfunction spatial analyses.

PubMed

Griffith, Daniel A; Peres-Neto, Pedro R

2006-10-01

Recently, analytical approaches based on the eigenfunctions of spatial configuration matrices have been proposed in order to consider explicitly spatial predictors. The present study demonstrates the usefulness of eigenfunctions in spatial modeling applied to ecological problems and shows equivalencies of and differences between the two current implementations of this methodology. The two approaches in this category are the distance-based (DB) eigenvector maps proposed by P. Legendre and his colleagues, and spatial filtering based upon geographic connectivity matrices (i.e., topology-based; CB) developed by D. A. Griffith and his colleagues. In both cases, the goal is to create spatial predictors that can be easily incorporated into conventional regression models. One important advantage of these two approaches over any other spatial approach is that they provide a flexible tool that allows the full range of general and generalized linear modeling theory to be applied to ecological and geographical problems in the presence of nonzero spatial autocorrelation.

Direct and indirect effects of biological factors on extinction risk in fossil bivalves

PubMed Central

Harnik, Paul G.

2011-01-01

Biological factors, such as abundance and body size, may contribute directly to extinction risk and indirectly through their influence on other biological characteristics, such as geographic range size. Paleontological data can be used to explicitly test many of these hypothesized relationships, and general patterns revealed through analysis of the fossil record can help refine predictive models of extinction risk developed for extant species. Here, I use structural equation modeling to tease apart the contributions of three canonical predictors of extinction—abundance, body size, and geographic range size—to the duration of bivalve species in the early Cenozoic marine fossil record of the eastern United States. I find that geographic range size has a strong direct effect on extinction risk and that an apparent direct effect of abundance can be explained entirely by its covariation with geographic range. The influence of geographic range on extinction risk is manifest across three ecologically disparate bivalve clades. Body size also has strong direct effects on extinction risk but operates in opposing directions in different clades, and thus, it seems to be decoupled from extinction risk in bivalves as a whole. Although abundance does not directly predict extinction risk, I reveal weak indirect effects of both abundance and body size through their positive influence on geographic range size. Multivariate models that account for the pervasive covariation between biological factors and extinction are necessary for assessing causality in evolutionary processes and making informed predictions in applied conservation efforts. PMID:21808004

Direct and indirect effects of biological factors on extinction risk in fossil bivalves.

PubMed

Harnik, Paul G

2011-08-16

Biological factors, such as abundance and body size, may contribute directly to extinction risk and indirectly through their influence on other biological characteristics, such as geographic range size. Paleontological data can be used to explicitly test many of these hypothesized relationships, and general patterns revealed through analysis of the fossil record can help refine predictive models of extinction risk developed for extant species. Here, I use structural equation modeling to tease apart the contributions of three canonical predictors of extinction--abundance, body size, and geographic range size--to the duration of bivalve species in the early Cenozoic marine fossil record of the eastern United States. I find that geographic range size has a strong direct effect on extinction risk and that an apparent direct effect of abundance can be explained entirely by its covariation with geographic range. The influence of geographic range on extinction risk is manifest across three ecologically disparate bivalve clades. Body size also has strong direct effects on extinction risk but operates in opposing directions in different clades, and thus, it seems to be decoupled from extinction risk in bivalves as a whole. Although abundance does not directly predict extinction risk, I reveal weak indirect effects of both abundance and body size through their positive influence on geographic range size. Multivariate models that account for the pervasive covariation between biological factors and extinction are necessary for assessing causality in evolutionary processes and making informed predictions in applied conservation efforts.

Locally adaptive, spatially explicit projection of US population for 2030 and 2050.

PubMed

McKee, Jacob J; Rose, Amy N; Bright, Edward A; Huynh, Timmy; Bhaduri, Budhendra L

2015-02-03

Localized adverse events, including natural hazards, epidemiological events, and human conflict, underscore the criticality of quantifying and mapping current population. Building on the spatial interpolation technique previously developed for high-resolution population distribution data (LandScan Global and LandScan USA), we have constructed an empirically informed spatial distribution of projected population of the contiguous United States for 2030 and 2050, depicting one of many possible population futures. Whereas most current large-scale, spatially explicit population projections typically rely on a population gravity model to determine areas of future growth, our projection model departs from these by accounting for multiple components that affect population distribution. Modeled variables, which included land cover, slope, distances to larger cities, and a moving average of current population, were locally adaptive and geographically varying. The resulting weighted surface was used to determine which areas had the greatest likelihood for future population change. Population projections of county level numbers were developed using a modified version of the US Census's projection methodology, with the US Census's official projection as the benchmark. Applications of our model include incorporating multiple various scenario-driven events to produce a range of spatially explicit population futures for suitability modeling, service area planning for governmental agencies, consequence assessment, mitigation planning and implementation, and assessment of spatially vulnerable populations.

Causal relations among events and states in dynamic geographical phenomena

NASA Astrophysics Data System (ADS)

Huang, Zhaoqiang; Feng, Xuezhi; Xuan, Wenling; Chen, Xiuwan

2007-06-01

There is only a static state of the real world to be recorded in conventional geographical information systems. However, there is not only static information but also dynamic information in geographical phenomena. So that how to record the dynamic information and reveal the relations among dynamic information is an important issue in a spatio-temporal information system. From an ontological perspective, we can initially divide the spatio-temporal entities in the world into continuants and occurrents. Continuant entities endure through some extended (although possibly very short) interval of time (e.g., houses, roads, cities, and real-estate). Occurrent entities happen and are then gone (e.g., a house repair job, road construction project, urban expansion, real-estate transition). From an information system perspective, continuants and occurrents that have a unique identity in the system are referred to as objects and events, respectively. And the change is represented implicitly by static snapshots in current spatial temporal information systems. In the previous models, the objects can be considered as the fundamental components of the system, and the change is modeled by considering time-varying attributes of these objects. In the spatio-temporal database, the temporal information that is either interval or instant is involved and the underlying data structures and indexes for temporal are considerable investigated. However, there is the absence of explicit ways of considering events, which affect the attributes of objects or the state. So the research issue of this paper focuses on how to model events in conceptual models of dynamic geographical phenomena and how to represent the causal relations among events and the objects or states. Firstly, the paper reviews the conceptual modeling in a temporal GIS by researchers. Secondly, this paper discusses the spatio-temporal entities: objects and events. Thirdly, this paper investigates the causal relations amongst events and states. The qualitative spatiotemporal change is an important issue in the dynamic geographic-scale phenomena. In real estate transition, the events and states are needed to be represented explicitly. In our modeling the evolution of a dynamic system, it can not avoid fetching in the view of causality. The object's transition is represented by the state of object. Event causes the state of objects changing and causes other events happen. Events connect with objects closely. The basic causal relations are the state-event and event-state relationships. Lastly, the paper concludes with the overview about the causal relations amongst events and states. And this future work is pointed.

Linking river management to species conservation using dynamic landscape scale models

USGS Publications Warehouse

Freeman, Mary C.; Buell, Gary R.; Hay, Lauren E.; Hughes, W. Brian; Jacobson, Robert B.; Jones, John W.; Jones, S.A.; LaFontaine, Jacob H.; Odom, Kenneth R.; Peterson, James T.; Riley, Jeffrey W.; Schindler, J. Stephen; Shea, C.; Weaver, J.D.

2013-01-01

Efforts to conserve stream and river biota could benefit from tools that allow managers to evaluate landscape-scale changes in species distributions in response to water management decisions. We present a framework and methods for integrating hydrology, geographic context and metapopulation processes to simulate effects of changes in streamflow on fish occupancy dynamics across a landscape of interconnected stream segments. We illustrate this approach using a 482 km2 catchment in the southeastern US supporting 50 or more stream fish species. A spatially distributed, deterministic and physically based hydrologic model is used to simulate daily streamflow for sub-basins composing the catchment. We use geographic data to characterize stream segments with respect to channel size, confinement, position and connectedness within the stream network. Simulated streamflow dynamics are then applied to model fish metapopulation dynamics in stream segments, using hypothesized effects of streamflow magnitude and variability on population processes, conditioned by channel characteristics. The resulting time series simulate spatially explicit, annual changes in species occurrences or assemblage metrics (e.g. species richness) across the catchment as outcomes of management scenarios. Sensitivity analyses using alternative, plausible links between streamflow components and metapopulation processes, or allowing for alternative modes of fish dispersal, demonstrate large effects of ecological uncertainty on model outcomes and highlight needed research and monitoring. Nonetheless, with uncertainties explicitly acknowledged, dynamic, landscape-scale simulations may prove useful for quantitatively comparing river management alternatives with respect to species conservation.

A Development of Nonstationary Regional Frequency Analysis Model with Large-scale Climate Information: Its Application to Korean Watershed

NASA Astrophysics Data System (ADS)

Kim, Jin-Young; Kwon, Hyun-Han; Kim, Hung-Soo

2015-04-01

The existing regional frequency analysis has disadvantages in that it is difficult to consider geographical characteristics in estimating areal rainfall. In this regard, this study aims to develop a hierarchical Bayesian model based nonstationary regional frequency analysis in that spatial patterns of the design rainfall with geographical information (e.g. latitude, longitude and altitude) are explicitly incorporated. This study assumes that the parameters of Gumbel (or GEV distribution) are a function of geographical characteristics within a general linear regression framework. Posterior distribution of the regression parameters are estimated by Bayesian Markov Chain Monte Carlo (MCMC) method, and the identified functional relationship is used to spatially interpolate the parameters of the distributions by using digital elevation models (DEM) as inputs. The proposed model is applied to derive design rainfalls over the entire Han-river watershed. It was found that the proposed Bayesian regional frequency analysis model showed similar results compared to L-moment based regional frequency analysis. In addition, the model showed an advantage in terms of quantifying uncertainty of the design rainfall and estimating the area rainfall considering geographical information. Finally, comprehensive discussion on design rainfall in the context of nonstationary will be presented. KEYWORDS: Regional frequency analysis, Nonstationary, Spatial information, Bayesian Acknowledgement This research was supported by a grant (14AWMP-B082564-01) from Advanced Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

Moving forward socio-economically focused models of deforestation.

PubMed

Dezécache, Camille; Salles, Jean-Michel; Vieilledent, Ghislain; Hérault, Bruno

2017-09-01

Whilst high-resolution spatial variables contribute to a good fit of spatially explicit deforestation models, socio-economic processes are often beyond the scope of these models. Such a low level of interest in the socio-economic dimension of deforestation limits the relevancy of these models for decision-making and may be the cause of their failure to accurately predict observed deforestation trends in the medium term. This study aims to propose a flexible methodology for taking into account multiple drivers of deforestation in tropical forested areas, where the intensity of deforestation is explicitly predicted based on socio-economic variables. By coupling a model of deforestation location based on spatial environmental variables with several sub-models of deforestation intensity based on socio-economic variables, we were able to create a map of predicted deforestation over the period 2001-2014 in French Guiana. This map was compared to a reference map for accuracy assessment, not only at the pixel scale but also over cells ranging from 1 to approximately 600 sq. km. Highly significant relationships were explicitly established between deforestation intensity and several socio-economic variables: population growth, the amount of agricultural subsidies, gold and wood production. Such a precise characterization of socio-economic processes allows to avoid overestimation biases in high deforestation areas, suggesting a better integration of socio-economic processes in the models. Whilst considering deforestation as a purely geographical process contributes to the creation of conservative models unable to effectively assess changes in the socio-economic and political contexts influencing deforestation trends, this explicit characterization of the socio-economic dimension of deforestation is critical for the creation of deforestation scenarios in REDD+ projects. © 2017 John Wiley & Sons Ltd.

The shape and temporal dynamics of phylogenetic trees arising from geographic speciation.

PubMed

Pigot, Alex L; Phillimore, Albert B; Owens, Ian P F; Orme, C David L

2010-12-01

Phylogenetic trees often depart from the expectations of stochastic models, exhibiting imbalance in diversification among lineages and slowdowns in the rate of lineage accumulation through time. Such departures have led to a widespread perception that ecological differences among species or adaptation and subsequent niche filling are required to explain patterns of diversification. However, a key element missing from models of diversification is the geographical context of speciation and extinction. In this study, we develop a spatially explicit model of geographic range evolution and cladogenesis, where speciation arises via vicariance or peripatry, and explore the effects of these processes on patterns of diversification. We compare the results with those observed in 41 reconstructed avian trees. Our model shows that nonconstant rates of speciation and extinction are emergent properties of the apportioning of geographic ranges that accompanies speciation. The dynamics of diversification exhibit wide variation, depending on the mode of speciation, tendency for range expansion, and rate of range evolution. By varying these parameters, the model is able to capture many, but not all, of the features exhibited by birth-death trees and extant bird clades. Under scenarios with relatively stable geographic ranges, strong slowdowns in diversification rates are produced, with faster rates of range dynamics leading to constant or accelerating rates of apparent diversification. A peripatric model of speciation with stable ranges also generates highly unbalanced trees typical of bird phylogenies but fails to produce realistic range size distributions among the extant species. Results most similar to those of a birth-death process are reached under a peripatric speciation scenario with highly volatile range dynamics. Taken together, our results demonstrate that considering the geographical context of speciation and extinction provides a more conservative null model of diversification and offers a very different perspective on the phylogenetic patterns expected in the absence of ecology.

The accuracy of climate models' simulated season lengths and the effectiveness of grid scale correction factors

DOE PAGES

Winterhalter, Wade E.

2011-09-01

Global climate change is expected to impact biological populations through a variety of mechanisms including increases in the length of their growing season. Climate models are useful tools for predicting how season length might change in the future. However, the accuracy of these models tends to be rather low at regional geographic scales. Here, I determined the ability of several atmosphere and ocean general circulating models (AOGCMs) to accurately simulate historical season lengths for a temperate ectotherm across the continental United States. I also evaluated the effectiveness of regional-scale correction factors to improve the accuracy of these models. I foundmore » that both the accuracy of simulated season lengths and the effectiveness of the correction factors to improve the model's accuracy varied geographically and across models. These results suggest that regional specific correction factors do not always adequately remove potential discrepancies between simulated and historically observed environmental parameters. As such, an explicit evaluation of the correction factors' effectiveness should be included in future studies of global climate change's impact on biological populations.« less

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

PubMed

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

2018-01-01

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

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

PubMed Central

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

2018-01-01

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

The spatial pattern of suicide in the US in relation to deprivation, fragmentation and rurality.

PubMed

Congdon, Peter

2011-01-01

Analysis of geographical patterns of suicide and psychiatric morbidity has demonstrated the impact of latent ecological variables (such as deprivation, rurality). Such latent variables may be derived by conventional multivariate techniques from sets of observed indices (for example, by principal components), by composite variable methods or by methods which explicitly consider the spatial framework of areas and, in particular, the spatial clustering of latent risks and outcomes. This article considers a latent random variable approach to explaining geographical contrasts in suicide in the US; and it develops a spatial structural equation model incorporating deprivation, social fragmentation and rurality. The approach allows for such latent spatial constructs to be correlated both within and between areas. Potential effects of area ethnic mix are also included. The model is applied to male and female suicide deaths over 2002–06 in 3142 US counties.

Barrier displacement on a neutral landscape: Towards a theory of continental biogeography

USGS Publications Warehouse

Albert, James S.; Schoolmaster, Donald; Tagliacollo, Victor; Duke-Sylvester, Scott M.

2017-01-01

Here we present SEAMLESS (Spatially-Explicit Area Model of Landscape Evolution by SimulationS) that generates clade diversification by moving geographic barriers on a continuous, neutral landscape. SEAMLESS is a neutral Landscape Evolution Model (LEM) that treats species and barriers as functionally equivalent with respect to model parameters. SEAMLESS differs from other model-based biogeographic methods (e.g. Lagrange, GeoSSE, BayArea, BioGeoBEARS) by modeling properties of dispersal barriers rather than areas, and by modeling the evolution of species lineages on a continuous landscape, rather than the evolution of geographic ranges along branches of a phylogeny. SEAMLESS shows how dispersal is required to maintain species richness and avoid clade-wide extinction, demonstrates that ancestral range size does not predict species richness, and provides a unified explanation for the suite of commonly observed biogeographic and phylogenetic patterns listed above. SEAMLESS explains how a simple barrier-displacement mechanism affects lineage diversification under neutral conditions, and is advanced here towards the formulation of a general theory of continental biogeography.                   

Enhancing robustness and immunization in geographical networks

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

Huang Liang; Department of Physics, Lanzhou University, Lanzhou 730000; Yang Kongqing

2007-03-15

We find that different geographical structures of networks lead to varied percolation thresholds, although these networks may have similar abstract topological structures. Thus, strategies for enhancing robustness and immunization of a geographical network are proposed. Using the generating function formalism, we obtain an explicit form of the percolation threshold q{sub c} for networks containing arbitrary order cycles. For three-cycles, the dependence of q{sub c} on the clustering coefficients is ascertained. The analysis substantiates the validity of the strategies with analytical evidence.

Evaluating Bayesian spatial methods for modelling species distributions with clumped and restricted occurrence data.

PubMed

Redding, David W; Lucas, Tim C D; Blackburn, Tim M; Jones, Kate E

2017-01-01

Statistical approaches for inferring the spatial distribution of taxa (Species Distribution Models, SDMs) commonly rely on available occurrence data, which is often clumped and geographically restricted. Although available SDM methods address some of these factors, they could be more directly and accurately modelled using a spatially-explicit approach. Software to fit models with spatial autocorrelation parameters in SDMs are now widely available, but whether such approaches for inferring SDMs aid predictions compared to other methodologies is unknown. Here, within a simulated environment using 1000 generated species' ranges, we compared the performance of two commonly used non-spatial SDM methods (Maximum Entropy Modelling, MAXENT and boosted regression trees, BRT), to a spatial Bayesian SDM method (fitted using R-INLA), when the underlying data exhibit varying combinations of clumping and geographic restriction. Finally, we tested how any recommended methodological settings designed to account for spatially non-random patterns in the data impact inference. Spatial Bayesian SDM method was the most consistently accurate method, being in the top 2 most accurate methods in 7 out of 8 data sampling scenarios. Within high-coverage sample datasets, all methods performed fairly similarly. When sampling points were randomly spread, BRT had a 1-3% greater accuracy over the other methods and when samples were clumped, the spatial Bayesian SDM method had a 4%-8% better AUC score. Alternatively, when sampling points were restricted to a small section of the true range all methods were on average 10-12% less accurate, with greater variation among the methods. Model inference under the recommended settings to account for autocorrelation was not impacted by clumping or restriction of data, except for the complexity of the spatial regression term in the spatial Bayesian model. Methods, such as those made available by R-INLA, can be successfully used to account for spatial autocorrelation in an SDM context and, by taking account of random effects, produce outputs that can better elucidate the role of covariates in predicting species occurrence. Given that it is often unclear what the drivers are behind data clumping in an empirical occurrence dataset, or indeed how geographically restricted these data are, spatially-explicit Bayesian SDMs may be the better choice when modelling the spatial distribution of target species.

Predicting the genetic consequences of future climate change: The power of coupling spatial demography, the coalescent, and historical landscape changes.

PubMed

Brown, Jason L; Weber, Jennifer J; Alvarado-Serrano, Diego F; Hickerson, Michael J; Franks, Steven J; Carnaval, Ana C

2016-01-01

Climate change is a widely accepted threat to biodiversity. Species distribution models (SDMs) are used to forecast whether and how species distributions may track these changes. Yet, SDMs generally fail to account for genetic and demographic processes, limiting population-level inferences. We still do not understand how predicted environmental shifts will impact the spatial distribution of genetic diversity within taxa. We propose a novel method that predicts spatially explicit genetic and demographic landscapes of populations under future climatic conditions. We use carefully parameterized SDMs as estimates of the spatial distribution of suitable habitats and landscape dispersal permeability under present-day, past, and future conditions. We use empirical genetic data and approximate Bayesian computation to estimate unknown demographic parameters. Finally, we employ these parameters to simulate realistic and complex models of responses to future environmental shifts. We contrast parameterized models under current and future landscapes to quantify the expected magnitude of change. We implement this framework on neutral genetic data available from Penstemon deustus. Our results predict that future climate change will result in geographically widespread declines in genetic diversity in this species. The extent of reduction will heavily depend on the continuity of population networks and deme sizes. To our knowledge, this is the first study to provide spatially explicit predictions of within-species genetic diversity using climatic, demographic, and genetic data. Our approach accounts for climatic, geographic, and biological complexity. This framework is promising for understanding evolutionary consequences of climate change, and guiding conservation planning. © 2016 Botanical Society of America.

Microphysics, Radiation and Surface Processes in the Goddard Cumulus Ensemble (GCE) Model

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Simpson, J.; Baker, D.; Braun, S.; Chou, M.-D.; Ferrier, B.; Johnson, D.; Khain, A.; Lang, S.; Lynn, B.

2001-01-01

The response of cloud systems to their environment is an important link in a chain of processes responsible for monsoons, frontal depression, El Nino Southern Oscillation (ENSO) episodes and other climate variations (e.g., 30-60 day intra-seasonal oscillations). Numerical models of cloud properties provide essential insights into the interactions of clouds with each other, with their surroundings, and with land and ocean surfaces. Significant advances are currently being made in the modeling of rainfall and rain-related cloud processes, ranging in scales from the very small up to the simulation of an extensive population of raining cumulus clouds in a tropical- or midlatitude-storm environment. The Goddard Cumulus Ensemble (GCE) model is a multi-dimensional nonhydrostatic dynamic/microphysical cloud resolving model. It has been used to simulate many different mesoscale convective systems that occurred in various geographic locations. In this paper, recent GCE model improvements (microphysics, radiation and surface processes) will be described as well as their impact on the development of precipitation events from various geographic locations. The performance of these new physical processes will be examined by comparing the model results with observations. In addition, the explicit interactive processes between cloud, radiation and surface processes will be discussed.

Spatially-explicit modeling of multi-scale drivers of aboveground forest biomass and water yield in watersheds of the Southeastern United States.

PubMed

Ajaz Ahmed, Mukhtar Ahmed; Abd-Elrahman, Amr; Escobedo, Francisco J; Cropper, Wendell P; Martin, Timothy A; Timilsina, Nilesh

2017-09-01

Understanding ecosystem processes and the influence of regional scale drivers can provide useful information for managing forest ecosystems. Examining more local scale drivers of forest biomass and water yield can also provide insights for identifying and better understanding the effects of climate change and management on forests. We used diverse multi-scale datasets, functional models and Geographically Weighted Regression (GWR) to model ecosystem processes at the watershed scale and to interpret the influence of ecological drivers across the Southeastern United States (SE US). Aboveground forest biomass (AGB) was determined from available geospatial datasets and water yield was estimated using the Water Supply and Stress Index (WaSSI) model at the watershed level. Our geostatistical model examined the spatial variation in these relationships between ecosystem processes, climate, biophysical, and forest management variables at the watershed level across the SE US. Ecological and management drivers at the watershed level were analyzed locally to identify whether drivers contribute positively or negatively to aboveground forest biomass and water yield ecosystem processes and thus identifying potential synergies and tradeoffs across the SE US region. Although AGB and water yield drivers varied geographically across the study area, they were generally significantly influenced by climate (rainfall and temperature), land-cover factor1 (Water and barren), land-cover factor2 (wetland and forest), organic matter content high, rock depth, available water content, stand age, elevation, and LAI drivers. These drivers were positively or negatively associated with biomass or water yield which significantly contributes to ecosystem interactions or tradeoff/synergies. Our study introduced a spatially-explicit modelling framework to analyze the effect of ecosystem drivers on forest ecosystem structure, function and provision of services. This integrated model approach facilitates multi-scale analyses of drivers and interactions at the local to regional scale. Copyright © 2017 Elsevier Ltd. All rights reserved.

Comparing approaches to spatially explicit ecosystem service modeling: a case study from the San Pedro River, Arizona

USGS Publications Warehouse

Bagstad, Kenneth J.; Semmens, Darius J.; Winthrop, Robert

2013-01-01

Although the number of ecosystem service modeling tools has grown in recent years, quantitative comparative studies of these tools have been lacking. In this study, we applied two leading open-source, spatially explicit ecosystem services modeling tools – Artificial Intelligence for Ecosystem Services (ARIES) and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) – to the San Pedro River watershed in southeast Arizona, USA, and northern Sonora, Mexico. We modeled locally important services that both modeling systems could address – carbon, water, and scenic viewsheds. We then applied managerially relevant scenarios for urban growth and mesquite management to quantify ecosystem service changes. InVEST and ARIES use different modeling approaches and ecosystem services metrics; for carbon, metrics were more similar and results were more easily comparable than for viewsheds or water. However, findings demonstrate similar gains and losses of ecosystem services and conclusions when comparing effects across our scenarios. Results were more closely aligned for landscape-scale urban-growth scenarios and more divergent for a site-scale mesquite-management scenario. Follow-up studies, including testing in different geographic contexts, can improve our understanding of the strengths and weaknesses of these and other ecosystem services modeling tools as they move closer to readiness for supporting day-to-day resource management.

Comparison of NGA-West2 directivity models

USGS Publications Warehouse

Spudich, Paul A.; Rowshandel, Badie; Shahi, Shrey; Baker, Jack W.; Chiou, Brian S-J

2014-01-01

Five directivity models have been developed based on data from the NGA-West2 database and based on numerical simulations of large strike-slip and reverse-slip earthquakes. All models avoid the use of normalized rupture dimension, enabling them to scale up to the largest earthquakes in a physically reasonable way. Four of the five models are explicitly “narrow-band” (in which the effect of directivity is maximum at a specific period that is a function of earthquake magnitude). Several strategies for determining the zero-level for directivity have been developed. We show comparisons of maps of the directivity amplification. This comparison suggests that the predicted geographic distributions of directivity amplification are dominated by effects of the models' assumptions, and more than one model should be used for ruptures dipping less than about 65 degrees.

General practitioner (family physician) workforce in Australia: comparing geographic data from surveys, a mailing list and medicare

PubMed Central

2013-01-01

Background Good quality spatial data on Family Physicians or General Practitioners (GPs) are key to accurately measuring geographic access to primary health care. The validity of computed associations between health outcomes and measures of GP access such as GP density is contingent on geographical data quality. This is especially true in rural and remote areas, where GPs are often small in number and geographically dispersed. However, there has been limited effort in assessing the quality of nationally comprehensive, geographically explicit, GP datasets in Australia or elsewhere. Our objective is to assess the extent of association or agreement between different spatially explicit nationwide GP workforce datasets in Australia. This is important since disagreement would imply differential relationships with primary healthcare relevant outcomes with different datasets. We also seek to enumerate these associations across categories of rurality or remoteness. Method We compute correlations of GP headcounts and workload contributions between four different datasets at two different geographical scales, across varying levels of rurality and remoteness. Results The datasets are in general agreement with each other at two different scales. Small numbers of absolute headcounts, with relatively larger fractions of locum GPs in rural areas cause unstable statistical estimates and divergences between datasets. Conclusion In the Australian context, many of the available geographic GP workforce datasets may be used for evaluating valid associations with health outcomes. However, caution must be exercised in interpreting associations between GP headcounts or workloads and outcomes in rural and remote areas. The methods used in these analyses may be replicated in other locales with multiple GP or physician datasets. PMID:24005003

A Behavioral Model of Landscape Change in the Amazon Basin: The Colonist Case

NASA Technical Reports Server (NTRS)

Walker, R. A.; Drzyzga, S. A.; Li, Y. L.; Wi, J. G.; Caldas, M.; Arima, E.; Vergara, D.

2004-01-01

This paper presents the prototype of a predictive model capable of describing both magnitudes of deforestation and its spatial articulation into patterns of forest fragmentation. In a departure from other landscape models, it establishes an explicit behavioral foundation for algorithm development, predicated on notions of the peasant economy and on household production theory. It takes a 'bottom-up' approach, generating the process of land-cover change occurring at lot level together with the geography of a transportation system to describe regional landscape change. In other words, it translates the decentralized decisions of individual households into a collective, spatial impact. In so doing, the model unites the richness of survey research on farm households with the analytical rigor of spatial analysis enabled by geographic information systems (GIs). The paper describes earlier efforts at spatial modeling, provides a critique of the so-called spatially explicit model, and elaborates a behavioral foundation by considering farm practices of colonists in the Amazon basin. It then uses, insight from the behavioral statement to motivate a GIs-based model architecture. The model is implemented for a long-standing colonization frontier in the eastern sector of the basin, along the Trans-Amazon Highway in the State of Para, Brazil. Results are subjected to both sensitivity analysis and error assessment, and suggestions are made about how the model could be improved.

An agent-based approach for modeling dynamics of contagious disease spread

PubMed Central

Perez, Liliana; Dragicevic, Suzana

2009-01-01

Background The propagation of communicable diseases through a population is an inherent spatial and temporal process of great importance for modern society. For this reason a spatially explicit epidemiologic model of infectious disease is proposed for a greater understanding of the disease's spatial diffusion through a network of human contacts. Objective The objective of this study is to develop an agent-based modelling approach the integrates geographic information systems (GIS) to simulate the spread of a communicable disease in an urban environment, as a result of individuals' interactions in a geospatial context. Methods The methodology for simulating spatiotemporal dynamics of communicable disease propagation is presented and the model is implemented using measles outbreak in an urban environment as a case study. Individuals in a closed population are explicitly represented by agents associated to places where they interact with other agents. They are endowed with mobility, through a transportation network allowing them to move between places within the urban environment, in order to represent the spatial heterogeneity and the complexity involved in infectious diseases diffusion. The model is implemented on georeferenced land use dataset from Metro Vancouver and makes use of census data sets from Statistics Canada for the municipality of Burnaby, BC, Canada study site. Results The results provide insights into the application of the model to calculate ratios of susceptible/infected in specific time frames and urban environments, due to its ability to depict the disease progression based on individuals' interactions. It is demonstrated that the dynamic spatial interactions within the population lead to high numbers of exposed individuals who perform stationary activities in areas after they have finished commuting. As a result, the sick individuals are concentrated in geographical locations like schools and universities. Conclusion The GIS-agent based model designed for this study can be easily customized to study the disease spread dynamics of any other communicable disease by simply adjusting the modeled disease timeline and/or the infection model and modifying the transmission process. This type of simulations can help to improve comprehension of disease spread dynamics and to take better steps towards the prevention and control of an epidemic outbreak. PMID:19656403

SEARCH: Spatially Explicit Animal Response to Composition of Habitat.

PubMed

Pauli, Benjamin P; McCann, Nicholas P; Zollner, Patrick A; Cummings, Robert; Gilbert, Jonathan H; Gustafson, Eric J

2013-01-01

Complex decisions dramatically affect animal dispersal and space use. Dispersing individuals respond to a combination of fine-scale environmental stimuli and internal attributes. Individual-based modeling offers a valuable approach for the investigation of such interactions because it combines the heterogeneity of animal behaviors with spatial detail. Most individual-based models (IBMs), however, vastly oversimplify animal behavior and such behavioral minimalism diminishes the value of these models. We present program SEARCH (Spatially Explicit Animal Response to Composition of Habitat), a spatially explicit, individual-based, population model of animal dispersal through realistic landscapes. SEARCH uses values in Geographic Information System (GIS) maps to apply rules that animals follow during dispersal, thus allowing virtual animals to respond to fine-scale features of the landscape and maintain a detailed memory of areas sensed during movement. SEARCH also incorporates temporally dynamic landscapes so that the environment to which virtual animals respond can change during the course of a simulation. Animals in SEARCH are behaviorally dynamic and able to respond to stimuli based upon their individual experiences. Therefore, SEARCH is able to model behavioral traits of dispersing animals at fine scales and with many dynamic aspects. Such added complexity allows investigation of unique ecological questions. To illustrate SEARCH's capabilities, we simulated case studies using three mammals. We examined the impact of seasonally variable food resources on the weight distribution of dispersing raccoons (Procyon lotor), the effect of temporally dynamic mortality pressure in combination with various levels of behavioral responsiveness in eastern chipmunks (Tamias striatus), and the impact of behavioral plasticity and home range selection on disperser mortality and weight change in virtual American martens (Martes americana). These simulations highlight the relevance of SEARCH for a variety of applications and illustrate benefits it can provide for conservation planning.

Explanatory models concerning the effects of small-area characteristics on individual health.

PubMed

Voigtländer, Sven; Vogt, Verena; Mielck, Andreas; Razum, Oliver

2014-06-01

Material and social living conditions at the small-area level are assumed to have an effect on individual health. We review existing explanatory models concerning the effects of small-area characteristics on health and describe the gaps future research should try to fill. Systematic literature search for, and analysis of, studies that propose an explanatory model of the relationship between small-area characteristics and health. Fourteen studies met our inclusion criteria. Using various theoretical approaches, almost all of the models are based on a three-tier structure linking social inequalities (posited at the macro-level), small-area characteristics (posited at the meso-level) and individual health (micro-level). No study explicitly defines the geographical borders of the small-area context. The health impact of the small-area characteristics is explained by specific pathways involving mediating factors (psychological, behavioural, biological). These pathways tend to be seen as uni-directional; often, causality is implied. They may be modified by individual factors. A number of issues need more attention in research on explanatory models concerning small-area effects on health. Among them are the (geographical) definition of the small-area context; the systematic description of pathways comprising small-area contextual as well as compositional factors; questions of direction of association and causality; and the integration of a time dimension.

Utilization of geoinformation tools for the development of forest fire hazard mapping system: example of Pekan fire, Malaysia

NASA Astrophysics Data System (ADS)

Mahmud, Ahmad Rodzi; Setiawan, Iwan; Mansor, Shattri; Shariff, Abdul Rashid Mohamed; Pradhan, Biswajeet; Nuruddin, Ahmed

2009-12-01

A study in modeling fire hazard assessment will be essential in establishing an effective forest fire management system especially in controlling and preventing peat fire. In this paper, we have used geographic information system (GIS), in combination with other geoinformation technologies such as remote sensing and computer modeling, for all aspects of wild land fire management. Identifying areas that have a high probability of burning is an important component of fire management planning. The development of spatially explicit GIS models has greatly facilitated this process by allowing managers to map and analyze variables contributing to fire occurrence across large, unique geographic units. Using the model and its associated software engine, the fire hazard map was produced. Extensive avenue programming scripts were written to provide additional capabilities in the development of these interfaces to meet the full complement of operational software considering various users requirements. The system developed not only possesses user friendly step by step operations to deliver the fire vulnerability mapping but also allows authorized users to edit, add or modify parameters whenever necessary. Results from the model can support fire hazard mapping in the forest and enhance alert system function by simulating and visualizing forest fire and helps for contingency planning.

Investigating population continuity with ancient DNA under a spatially explicit simulation framework.

PubMed

Silva, Nuno Miguel; Rio, Jeremy; Currat, Mathias

2017-12-15

Recent advances in sequencing technologies have allowed for the retrieval of ancient DNA data (aDNA) from skeletal remains, providing direct genetic snapshots from diverse periods of human prehistory. Comparing samples taken in the same region but at different times, hereafter called "serial samples", may indicate whether there is continuity in the peopling history of that area or whether an immigration of a genetically different population has occurred between the two sampling times. However, the exploration of genetic relationships between serial samples generally ignores their geographical locations and the spatiotemporal dynamics of populations. Here, we present a new coalescent-based, spatially explicit modelling approach to investigate population continuity using aDNA, which includes two fundamental elements neglected in previous methods: population structure and migration. The approach also considers the extensive temporal and geographical variance that is commonly found in aDNA population samples. We first showed that our spatially explicit approach is more conservative than the previous (panmictic) approach and should be preferred to test for population continuity, especially when small and isolated populations are considered. We then applied our method to two mitochondrial datasets from Germany and France, both including modern and ancient lineages dating from the early Neolithic. The results clearly reject population continuity for the maternal line over the last 7500 years for the German dataset but not for the French dataset, suggesting regional heterogeneity in post-Neolithic migratory processes. Here, we demonstrate the benefits of using a spatially explicit method when investigating population continuity with aDNA. It constitutes an improvement over panmictic methods by considering the spatiotemporal dynamics of genetic lineages and the precise location of ancient samples. The method can be used to investigate population continuity between any pair of serial samples (ancient-ancient or ancient-modern) and to investigate more complex evolutionary scenarios. Although we based our study on mitochondrial DNA sequences, diploid molecular markers of different types (DNA, SNP, STR) can also be simulated with our approach. It thus constitutes a promising tool for the analysis of the numerous aDNA datasets being produced, including genome wide data, in humans but also in many other species.

Interdependence of geomorphic and ecologic resilience properties in a geographic context

NASA Astrophysics Data System (ADS)

Anthony Stallins, J.; Corenblit, Dov

2018-03-01

Ecology and geomorphology recognize the dynamic aspects of resistance and resilience. However, formal resilience theory in ecology has tended to deemphasize the geomorphic habitat template. Conversely, landscape sensitivity and state-and-transition models in geomorphology downweight mechanisms of biotic adaptation operative in fluctuating, spatially explicit environments. Adding to the interdisciplinary challenge of understanding complex biogeomorphic systems is that environmental heterogeneity and overlapping gradients of disturbance complicate inference of the geographic patterns of resistance and resilience. We develop a conceptual model for comparing the resilience properties among barrier dunes. The model illustrates how adaptive cycles and panarchies, the formal building blocks of resilience recognized in ecology, can be expressed as a set of hierarchically nested geomorphic and ecological metrics. The variance structure of these data is proposed as a means to delineate different kinds and levels of resilience. Specifically, it is the dimensionality of these data and how geomorphic and ecological variables load on the first and succeeding axes that facilitates the delineation of resistance and resilience. The construction of dune topographic state space from observations among different barrier islands is proposed as a way to measure the interdependence of geomorphic and ecological resilience properties.

The consequences of landscape change on ecological resources: An assessment of the United States mid-Atlantic region, 1973-1993

USGS Publications Warehouse

Jones, K.B.; Neale, A.C.; Wade, T.G.; Wickham, J.D.; Cross, C.L.; Edmonds, C.M.; Loveland, Thomas R.; Nash, M.S.; Riitters, K.H.; Smith, E.R.

2001-01-01

Spatially explicit identification of changes in ecological conditions over large areas is key to targeting and prioritizing areas for environmental protection and restoration by managers at watershed, basin, and regional scales. A critical limitation to this point has been the development of methods to conduct such broad-scale assessments. Field-based methods have proven to be too costly and too inconsistent in their application to make estimates of ecological conditions over large areas. New spatial data derived from satellite imagery and other sources, the development of statistical models relating landscape composition and pattern to ecological endpoints, and geographic information systems (GIS) make it possible to evaluate ecological conditions at multiple scales over broad geographic regions. In this study, we demonstrate the application of spatially distributed models for bird habitat quality and nitrogen yield to streams to assess the consequences of landcover change across the mid-Atlantic region between the 1970s and 1990s. Moreover, we present a way to evaluate spatial concordance between models related to different environmental endpoints. Results of this study should help environmental managers in the mid-Atlantic region target those areas in need of conservation and protection.

Participatory, Multi-Criteria Evaluation Methods as a Means to Increase the Legitimacy and Sustainability of Land Use Planning Processes. The Case of the Chaco Region in Salta, Argentina.

PubMed

Seghezzo, Lucas; Venencia, Cristian; Buliubasich, E Catalina; Iribarnegaray, Martín A; Volante, José N

2017-02-01

Conflicts over land use and ownership are common in South America and generate frequent confrontations among indigenous peoples, small-scale farmers, and large-scale agricultural producers. We argue in this paper that an accurate identification of these conflicts, together with a participatory evaluation of their importance, will increase the social legitimacy of land use planning processes, rendering decision-making more sustainable in the long term. We describe here a participatory, multi-criteria conflict assessment model developed to identify, locate, and categorize land tenure and use conflicts. The model was applied to the case of the "Chaco" region of the province of Salta, in northwestern Argentina. Basic geographic, cadastral, and social information needed to apply the model was made spatially explicit on a Geographic Information System. Results illustrate the contrasting perceptions of different stakeholders (government officials, social and environmental non-governmental organizations, large-scale agricultural producers, and scholars) on the intensity of land use conflicts in the study area. These results can help better understand and address land tenure conflicts in areas with different cultures and conflicting social and enviornmental interests.

Participatory, Multi-Criteria Evaluation Methods as a Means to Increase the Legitimacy and Sustainability of Land Use Planning Processes. The Case of the Chaco Region in Salta, Argentina

NASA Astrophysics Data System (ADS)

Seghezzo, Lucas; Venencia, Cristian; Buliubasich, E. Catalina; Iribarnegaray, Martín A.; Volante, José N.

2017-02-01

Conflicts over land use and ownership are common in South America and generate frequent confrontations among indigenous peoples, small-scale farmers, and large-scale agricultural producers. We argue in this paper that an accurate identification of these conflicts, together with a participatory evaluation of their importance, will increase the social legitimacy of land use planning processes, rendering decision-making more sustainable in the long term. We describe here a participatory, multi-criteria conflict assessment model developed to identify, locate, and categorize land tenure and use conflicts. The model was applied to the case of the "Chaco" region of the province of Salta, in northwestern Argentina. Basic geographic, cadastral, and social information needed to apply the model was made spatially explicit on a Geographic Information System. Results illustrate the contrasting perceptions of different stakeholders (government officials, social and environmental non-governmental organizations, large-scale agricultural producers, and scholars) on the intensity of land use conflicts in the study area. These results can help better understand and address land tenure conflicts in areas with different cultures and conflicting social and enviornmental interests.

Spatially Explicit Modeling Reveals Cephalopod Distributions Match Contrasting Trophic Pathways in the Western Mediterranean Sea

PubMed Central

Puerta, Patricia; Hunsicker, Mary E.; Quetglas, Antoni; Álvarez-Berastegui, Diego; Esteban, Antonio; González, María; Hidalgo, Manuel

2015-01-01

Populations of the same species can experience different responses to the environment throughout their distributional range as a result of spatial and temporal heterogeneity in habitat conditions. This highlights the importance of understanding the processes governing species distribution at local scales. However, research on species distribution often averages environmental covariates across large geographic areas, missing variability in population-environment interactions within geographically distinct regions. We used spatially explicit models to identify interactions between species and environmental, including chlorophyll a (Chla) and sea surface temperature (SST), and trophic (prey density) conditions, along with processes governing the distribution of two cephalopods with contrasting life-histories (octopus and squid) across the western Mediterranean Sea. This approach is relevant for cephalopods, since their population dynamics are especially sensitive to variations in habitat conditions and rarely stable in abundance and location. The regional distributions of the two cephalopod species matched two different trophic pathways present in the western Mediterranean Sea, associated with the Gulf of Lion upwelling and the Ebro river discharges respectively. The effects of the studied environmental and trophic conditions were spatially variant in both species, with usually stronger effects along their distributional boundaries. We identify areas where prey availability limited the abundance of cephalopod populations as well as contrasting effects of temperature in the warmest regions. Despite distributional patterns matching productive areas, a general negative effect of Chla on cephalopod densities suggests that competition pressure is common in the study area. Additionally, results highlight the importance of trophic interactions, beyond other common environmental factors, in shaping the distribution of cephalopod populations. Our study presents a valuable approach for understanding the spatially variant ecology of cephalopod populations, which is important for fisheries and ecosystem management. PMID:26201075

Effect of ancient population structure on the degree of polymorphism shared between modern human populations and ancient hominins.

PubMed

Eriksson, Anders; Manica, Andrea

2012-08-28

Recent comparisons between anatomically modern humans and ancient genomes of other hominins have raised the tantalizing, and hotly debated, possibility of hybridization. Although several tests of hybridization have been devised, they all rely on the degree to which different modern populations share genetic polymorphisms with the ancient genomes of other hominins. However, spatial population structure is expected to generate genetic patterns similar to those that might be attributed to hybridization. To investigate this problem, we take Neanderthals as a case study, and build a spatially explicit model of the shared history of anatomically modern humans and this hominin. We show that the excess polymorphism shared between Eurasians and Neanderthals is compatible with scenarios in which no hybridization occurred, and is strongly linked to the strength of population structure in ancient populations. Thus, we recommend caution in inferring admixture from geographic patterns of shared polymorphisms, and argue that future attempts to investigate ancient hybridization between humans and other hominins should explicitly account for population structure.

Component 1: Current and Future Methods for Representing and Interacting with Qualitative Geographic Information

DTIC Science & Technology

2011-10-26

the user in a graphical fashion. Despite the fact that tag clouds are now ubiquitous (Cidell 2010 , Lee et al . 2010 , Viégas, Wattenberg and Feinberg...this work (e.g. Compus) focused on exploration of document structure explicitly (Figure 3), other research (Krstajic et al . 2010 ) has focused on...geographic visualization tool called HealthGeoJunction focused on foraging PubMed articles about avian influenza (MacEachren et al . 2010 ). 5 | P a g e

Modeling acute respiratory illness during the 2007 San Diego wildland fires using a coupled emissions-transport system and generalized additive modeling.

PubMed

Thelen, Brian; French, Nancy H F; Koziol, Benjamin W; Billmire, Michael; Owen, Robert Chris; Johnson, Jeffrey; Ginsberg, Michele; Loboda, Tatiana; Wu, Shiliang

2013-11-05

A study of the impacts on respiratory health of the 2007 wildland fires in and around San Diego County, California is presented. This study helps to address the impact of fire emissions on human health by modeling the exposure potential of proximate populations to atmospheric particulate matter (PM) from vegetation fires. Currently, there is no standard methodology to model and forecast the potential respiratory health effects of PM plumes from wildland fires, and in part this is due to a lack of methodology for rigorously relating the two. The contribution in this research specifically targets that absence by modeling explicitly the emission, transmission, and distribution of PM following a wildland fire in both space and time. Coupled empirical and deterministic models describing particulate matter (PM) emissions and atmospheric dispersion were linked to spatially explicit syndromic surveillance health data records collected through the San Diego Aberration Detection and Incident Characterization (SDADIC) system using a Generalized Additive Modeling (GAM) statistical approach. Two levels of geographic aggregation were modeled, a county-wide regional level and division of the county into six sub regions. Selected health syndromes within SDADIC from 16 emergency departments within San Diego County relevant for respiratory health were identified for inclusion in the model. The model captured the variability in emergency department visits due to several factors by including nine ancillary variables in addition to wildfire PM concentration. The model coefficients and nonlinear function plots indicate that at peak fire PM concentrations the odds of a person seeking emergency care is increased by approximately 50% compared to non-fire conditions (40% for the regional case, 70% for a geographically specific case). The sub-regional analyses show that demographic variables also influence respiratory health outcomes from smoke. The model developed in this study allows a quantitative assessment and prediction of respiratory health outcomes as it relates to the location and timing of wildland fire emissions relevant for application to future wildfire scenarios. An important aspect of the resulting model is its generality thus allowing its ready use for geospatial assessments of respiratory health impacts under possible future wildfire conditions in the San Diego region. The coupled statistical and process-based modeling demonstrates an end-to-end methodology for generating reasonable estimates of wildland fire PM concentrations and health effects at resolutions compatible with syndromic surveillance data.

Towards a new paleotemperature proxy from reef coral occurrences.

PubMed

Lauchstedt, Andreas; Pandolfi, John M; Kiessling, Wolfgang

2017-09-05

Global mean temperature is thought to have exceeded that of today during the last interglacial episode (LIG, ~ 125,000 yrs b.p.) but robust paleoclimate data are still rare in low latitudes. Occurrence data of tropical reef corals may provide new proxies of low latitude sea-surface temperatures. Using modern reef coral distributions we developed a geographically explicit model of sea surface temperatures. Applying this model to coral occurrence data of the LIG provides a latitudinal U-shaped pattern of temperature anomalies with cooler than modern temperatures around the equator and warmer subtropical climes. Our results agree with previously published estimates of LIG temperatures and suggest a poleward broadening of the habitable zone for reef corals during the LIG.

Extending Primitive Spatial Data Models to Include Semantics

NASA Astrophysics Data System (ADS)

Reitsma, F.; Batcheller, J.

2009-04-01

Our traditional geospatial data model involves associating some measurable quality, such as temperature, or observable feature, such as a tree, with a point or region in space and time. When capturing data we implicitly subscribe to some kind of conceptualisation. If we can make this explicit in an ontology and associate it with the captured data, we can leverage formal semantics to reason with the concepts represented in our spatial data sets. To do so, we extend our fundamental representation of geospatial data in a data model by including a URI in our basic data model that links it to our ontology defining our conceptualisation, We thus extend Goodchild et al's geo-atom [1] with the addition of a URI: (x, Z, z(x), URI) . This provides us with pixel or feature level knowledge and the ability to create layers of data from a set of pixels or features that might be drawn from a database based on their semantics. Using open source tools, we present a prototype that involves simple reasoning as a proof of concept. References [1] M.F. Goodchild, M. Yuan, and T.J. Cova. Towards a general theory of geographic representation in gis. International Journal of Geographical Information Science, 21(3):239-260, 2007.

Predicting the geographical distribution of two invasive termite species from occurrence data.

PubMed

Tonini, Francesco; Divino, Fabio; Lasinio, Giovanna Jona; Hochmair, Hartwig H; Scheffrahn, Rudolf H

2014-10-01

Predicting the potential habitat of species under both current and future climate change scenarios is crucial for monitoring invasive species and understanding a species' response to different environmental conditions. Frequently, the only data available on a species is the location of its occurrence (presence-only data). Using occurrence records only, two models were used to predict the geographical distribution of two destructive invasive termite species, Coptotermes gestroi (Wasmann) and Coptotermes formosanus Shiraki. The first model uses a Bayesian linear logistic regression approach adjusted for presence-only data while the second one is the widely used maximum entropy approach (Maxent). Results show that the predicted distributions of both C. gestroi and C. formosanus are strongly linked to urban development. The impact of future scenarios such as climate warming and population growth on the biotic distribution of both termite species was also assessed. Future climate warming seems to affect their projected probability of presence to a lesser extent than population growth. The Bayesian logistic approach outperformed Maxent consistently in all models according to evaluation criteria such as model sensitivity and ecological realism. The importance of further studies for an explicit treatment of residual spatial autocorrelation and a more comprehensive comparison between both statistical approaches is suggested.

Reconciling paleodistribution models and comparative phylogeography in the Wet Tropics rainforest land snail Gnarosophia bellendenkerensis (Brazier 1875).

PubMed

Hugall, Andrew; Moritz, Craig; Moussalli, Adnan; Stanisic, John

2002-04-30

Comparative phylogeography has proved useful for investigating biological responses to past climate change and is strongest when combined with extrinsic hypotheses derived from the fossil record or geology. However, the rarity of species with sufficient, spatially explicit fossil evidence restricts the application of this method. Here, we develop an alternative approach in which spatial models of predicted species distributions under serial paleoclimates are compared with a molecular phylogeography, in this case for a snail endemic to the rainforests of North Queensland, Australia. We also compare the phylogeography of the snail to those from several endemic vertebrates and use consilience across all of these approaches to enhance biogeographical inference for this rainforest fauna. The snail mtDNA phylogeography is consistent with predictions from paleoclimate modeling in relation to the location and size of climatic refugia through the late Pleistocene-Holocene and broad patterns of extinction and recolonization. There is general agreement between quantitative estimates of population expansion from sequence data (using likelihood and coalescent methods) vs. distributional modeling. The snail phylogeography represents a composite of both common and idiosyncratic patterns seen among vertebrates, reflecting the geographically finer scale of persistence and subdivision in the snail. In general, this multifaceted approach, combining spatially explicit paleoclimatological models and comparative phylogeography, provides a powerful approach to locating historical refugia and understanding species' responses to them.

Reconciling paleodistribution models and comparative phylogeography in the Wet Tropics rainforest land snail Gnarosophia bellendenkerensis (Brazier 1875)

PubMed Central

Hugall, Andrew; Moritz, Craig; Moussalli, Adnan; Stanisic, John

2002-01-01

Comparative phylogeography has proved useful for investigating biological responses to past climate change and is strongest when combined with extrinsic hypotheses derived from the fossil record or geology. However, the rarity of species with sufficient, spatially explicit fossil evidence restricts the application of this method. Here, we develop an alternative approach in which spatial models of predicted species distributions under serial paleoclimates are compared with a molecular phylogeography, in this case for a snail endemic to the rainforests of North Queensland, Australia. We also compare the phylogeography of the snail to those from several endemic vertebrates and use consilience across all of these approaches to enhance biogeographical inference for this rainforest fauna. The snail mtDNA phylogeography is consistent with predictions from paleoclimate modeling in relation to the location and size of climatic refugia through the late Pleistocene-Holocene and broad patterns of extinction and recolonization. There is general agreement between quantitative estimates of population expansion from sequence data (using likelihood and coalescent methods) vs. distributional modeling. The snail phylogeography represents a composite of both common and idiosyncratic patterns seen among vertebrates, reflecting the geographically finer scale of persistence and subdivision in the snail. In general, this multifaceted approach, combining spatially explicit paleoclimatological models and comparative phylogeography, provides a powerful approach to locating historical refugia and understanding species' responses to them. PMID:11972064

ENVISIONING ALTERNATIVES: USING CITIZEN GUIDANCE TO MAP FUTURE LAND AND WATER USE

EPA Science Inventory

Spatially explicit landscape analyses are a central activity in research on the relationships between people and changes in natural systems. Using geographical information systems and related tools, the Pacific Northwest Ecosystem Research Consortium depicted historical (pre-Eur...

Mapping malaria risk and vulnerability in the United Republic of Tanzania: a spatial explicit model.

PubMed

Hagenlocher, Michael; Castro, Marcia C

2015-01-01

Outbreaks of vector-borne diseases (VBDs) impose a heavy burden on vulnerable populations. Despite recent progress in eradication and control, malaria remains the most prevalent VBD. Integrative approaches that take into account environmental, socioeconomic, demographic, biological, cultural, and political factors contributing to malaria risk and vulnerability are needed to effectively reduce malaria burden. Although the focus on malaria risk has increasingly gained ground, little emphasis has been given to develop quantitative methods for assessing malaria risk including malaria vulnerability in a spatial explicit manner. Building on a conceptual risk and vulnerability framework, we propose a spatial explicit approach for modeling relative levels of malaria risk - as a function of hazard, exposure, and vulnerability - in the United Republic of Tanzania. A logistic regression model was employed to identify a final set of risk factors and their contribution to malaria endemicity based on multidisciplinary geospatial information. We utilized a Geographic Information System for the construction and visualization of a malaria vulnerability index and its integration into a spatially explicit malaria risk map. The spatial pattern of malaria risk was very heterogeneous across the country. Malaria risk was higher in Mainland areas than in Zanzibar, which is a result of differences in both malaria entomological inoculation rate and prevailing vulnerabilities. Areas of high malaria risk were identified in the southeastern part of the country, as well as in two distinct "hotspots" in the northwestern part of the country bordering Lake Victoria, while concentrations of high malaria vulnerability seem to occur in the northwestern, western, and southeastern parts of the mainland. Results were visualized using both 10×10 km(2) grids and subnational administrative units. The presented approach makes an important contribution toward a decision support tool. By decomposing malaria risk into its components, the approach offers evidence on which factors could be targeted for reducing malaria risk and vulnerability to the disease. Ultimately, results offer relevant information for place-based intervention planning and more effective spatial allocation of resources.

Generalized reproduction numbers and the prediction of patterns in waterborne disease

PubMed Central

Gatto, Marino; Mari, Lorenzo; Bertuzzo, Enrico; Casagrandi, Renato; Righetto, Lorenzo; Rodriguez-Iturbe, Ignacio; Rinaldo, Andrea

2012-01-01

Understanding, predicting, and controlling outbreaks of waterborne diseases are crucial goals of public health policies, but pose challenging problems because infection patterns are influenced by spatial structure and temporal asynchrony. Although explicit spatial modeling is made possible by widespread data mapping of hydrology, transportation infrastructure, population distribution, and sanitation, the precise condition under which a waterborne disease epidemic can start in a spatially explicit setting is still lacking. Here we show that the requirement that all the local reproduction numbers be larger than unity is neither necessary nor sufficient for outbreaks to occur when local settlements are connected by networks of primary and secondary infection mechanisms. To determine onset conditions, we derive general analytical expressions for a reproduction matrix , explicitly accounting for spatial distributions of human settlements and pathogen transmission via hydrological and human mobility networks. At disease onset, a generalized reproduction number (the dominant eigenvalue of ) must be larger than unity. We also show that geographical outbreak patterns in complex environments are linked to the dominant eigenvector and to spectral properties of . Tests against data and computations for the 2010 Haiti and 2000 KwaZulu-Natal cholera outbreaks, as well as against computations for metapopulation networks, demonstrate that eigenvectors of provide a synthetic and effective tool for predicting the disease course in space and time. Networked connectivity models, describing the interplay between hydrology, epidemiology, and social behavior sustaining human mobility, thus prove to be key tools for emergency management of waterborne infections. PMID:23150538

Speciation in the Derrida-Higgs model with finite genomes and spatial populations

NASA Astrophysics Data System (ADS)

de Aguiar, Marcus A. M.

2017-02-01

The speciation model proposed by Derrida and Higgs demonstrated that a sexually reproducing population can split into different species in the absence of natural selection or any type of geographic isolation, provided that mating is assortative and the number of genes involved in the process is infinite. Here we revisit this model and simulate it for finite genomes, focusing on the question of how many genes it actually takes to trigger neutral sympatric speciation. We find that, for typical parameters used in the original model, it takes the order of 105 genes. We compare the results with a similar spatially explicit model where about 100 genes suffice for speciation. We show that when the number of genes is small the species that emerge are strongly segregated in space. For a larger number of genes, on the other hand, the spatial structure of the population is less important and the species distribution overlap considerably.

A model-based approach to determine the long-term effects of multiple interacting stressors on coral reefs.

PubMed

Blackwood, Julie C; Hastings, Alan; Mumby, Peter J

2011-10-01

The interaction between multiple stressors on Caribbean coral reefs, namely, fishing effort and hurricane impacts, is a key element in the future sustainability of reefs. We develop an analytic model of coral-algal interactions and explicitly consider grazing by herbivorous reef fish. Further, we consider changes in structural complexity, or rugosity, in addition to the direct impacts of hurricanes, which are implemented as stochastic jump processes. The model simulations consider various levels of fishing effort corresponding to' several hurricane frequencies and impact levels dependent on geographic location. We focus on relatively short time scales so we do not explicitly include changes in ocean temperature, chemistry, or sea level rise. The general features of our approach would, however, apply to these other stressors and to the management of other systems in the face of multiple stressors. It is determined that the appropriate management policy, either local reef restoration or fisheries management, greatly depends on hurricane frequency and impact level. For sufficiently low hurricane impact and macroalgal growth rate, our results indicate that regions with lower-frequency hurricanes require stricter fishing regulations, whereas management in regions with higher-frequency hurricanes might be less concerned with enhancing grazing and instead consider whether local-scale restorative activities to increase vertical structure are cost-effective.

Water balance model for mean annual hydrogen and oxygen isotope distributions in surface waters of the contiguous United States

NASA Astrophysics Data System (ADS)

Bowen, Gabriel J.; Kennedy, Casey D.; Liu, Zhongfang; Stalker, Jeremy

2011-12-01

The stable H and O isotope composition of river and stream water records information on runoff sources and land-atmosphere water fluxes within the catchment and is a potentially powerful tool for network-based monitoring of ecohydrological systems. Process-based hydrological models, however, have thus far shown limited power to replicate observed large-scale variation in U.S. surface water isotope ratios. Here we develop a geographic information system-based model to predict long-term annual average surface water isotope ratios across the contiguous United States. We use elevation-explicit, gridded precipitation isotope maps as model input and data from a U.S. Geological Survey monitoring program for validation. We find that models incorporating monthly variation in precipitation-evapotranspiration (P-E) amounts account for the majority (>89%) of isotopic variation and have reduced regional bias relative to models that do not consider intra-annual P-E effects on catchment water balance. Residuals from the water balance model exhibit strong spatial patterning and correlations that suggest model residuals isolate additional hydrological signal. We use interpolated model residuals to generate optimized prediction maps for U.S. surface water δ2H and δ18O values. We show that the modeled surface water values represent a relatively accurate and unbiased proxy for drinking water isotope ratios across the United States, making these data products useful in ecological and criminal forensics applications that require estimates of the local environmental water isotope variation across large geographic regions.

A Spatial Framework for Understanding Population Structure and Admixture.

PubMed

Bradburd, Gideon S; Ralph, Peter L; Coop, Graham M

2016-01-01

Geographic patterns of genetic variation within modern populations, produced by complex histories of migration, can be difficult to infer and visually summarize. A general consequence of geographically limited dispersal is that samples from nearby locations tend to be more closely related than samples from distant locations, and so genetic covariance often recapitulates geographic proximity. We use genome-wide polymorphism data to build "geogenetic maps," which, when applied to stationary populations, produces a map of the geographic positions of the populations, but with distances distorted to reflect historical rates of gene flow. In the underlying model, allele frequency covariance is a decreasing function of geogenetic distance, and nonlocal gene flow such as admixture can be identified as anomalously strong covariance over long distances. This admixture is explicitly co-estimated and depicted as arrows, from the source of admixture to the recipient, on the geogenetic map. We demonstrate the utility of this method on a circum-Tibetan sampling of the greenish warbler (Phylloscopus trochiloides), in which we find evidence for gene flow between the adjacent, terminal populations of the ring species. We also analyze a global sampling of human populations, for which we largely recover the geography of the sampling, with support for significant histories of admixture in many samples. This new tool for understanding and visualizing patterns of population structure is implemented in a Bayesian framework in the program SpaceMix.

A Spatial Framework for Understanding Population Structure and Admixture

PubMed Central

Bradburd, Gideon S.; Ralph, Peter L.; Coop, Graham M.

2016-01-01

Geographic patterns of genetic variation within modern populations, produced by complex histories of migration, can be difficult to infer and visually summarize. A general consequence of geographically limited dispersal is that samples from nearby locations tend to be more closely related than samples from distant locations, and so genetic covariance often recapitulates geographic proximity. We use genome-wide polymorphism data to build “geogenetic maps,” which, when applied to stationary populations, produces a map of the geographic positions of the populations, but with distances distorted to reflect historical rates of gene flow. In the underlying model, allele frequency covariance is a decreasing function of geogenetic distance, and nonlocal gene flow such as admixture can be identified as anomalously strong covariance over long distances. This admixture is explicitly co-estimated and depicted as arrows, from the source of admixture to the recipient, on the geogenetic map. We demonstrate the utility of this method on a circum-Tibetan sampling of the greenish warbler (Phylloscopus trochiloides), in which we find evidence for gene flow between the adjacent, terminal populations of the ring species. We also analyze a global sampling of human populations, for which we largely recover the geography of the sampling, with support for significant histories of admixture in many samples. This new tool for understanding and visualizing patterns of population structure is implemented in a Bayesian framework in the program SpaceMix. PMID:26771578

Phylogenetic conservatism of thermal traits explains dispersal limitation and genomic differentiation of Streptomyces sister-taxa.

PubMed

Choudoir, Mallory J; Buckley, Daniel H

2018-06-07

The latitudinal diversity gradient is a pattern of biogeography observed broadly in plants and animals but largely undocumented in terrestrial microbial systems. Although patterns of microbial biogeography across broad taxonomic scales have been described in a range of contexts, the mechanisms that generate biogeographic patterns between closely related taxa remain incompletely characterized. Adaptive processes are a major driver of microbial biogeography, but there is less understanding of how microbial biogeography and diversification are shaped by dispersal limitation and drift. We recently described a latitudinal diversity gradient of species richness and intraspecific genetic diversity in Streptomyces by using a geographically explicit culture collection. Within this geographically explicit culture collection, we have identified Streptomyces sister-taxa whose geographic distribution is delimited by latitude. These sister-taxa differ in geographic distribution, genomic diversity, and ecological traits despite having nearly identical SSU rRNA gene sequences. Comparative genomic analysis reveals genomic differentiation of these sister-taxa consistent with restricted gene flow across latitude. Furthermore, we show phylogenetic conservatism of thermal traits between the sister-taxa suggesting that thermal trait adaptation limits dispersal and gene flow across climate regimes as defined by latitude. Such phylogenetic conservatism of thermal traits is commonly associated with latitudinal diversity gradients for plants and animals. These data provide further support for the hypothesis that the Streptomyces latitudinal diversity gradient was formed as a result of historical demographic processes defined by dispersal limitation and driven by paleoclimate dynamics.

Locally-Adaptive, Spatially-Explicit Projection of U.S. Population for 2030 and 2050

DOE PAGES

McKee, Jacob J.; Rose, Amy N.; Bright, Eddie A.; ...

2015-02-03

Localized adverse events, including natural hazards, epidemiological events, and human conflict, underscore the criticality of quantifying and mapping current population. Moreover, knowing the spatial distribution of future population allows for increased preparation in the event of an emergency. Building on the spatial interpolation technique previously developed for high resolution population distribution data (LandScan Global and LandScan USA), we have constructed an empirically-informed spatial distribution of the projected population of the contiguous U.S. for 2030 and 2050. Whereas most current large-scale, spatially explicit population projections typically rely on a population gravity model to determine areas of future growth, our projection modelmore » departs from these by accounting for multiple components that affect population distribution. Modelled variables, which included land cover, slope, distances to larger cities, and a moving average of current population, were locally adaptive and geographically varying. The resulting weighted surface was used to determine which areas had the greatest likelihood for future population change. Population projections of county level numbers were developed using a modified version of the U.S. Census s projection methodology with the U.S. Census s official projection as the benchmark. Applications of our model include, but are not limited to, suitability modelling, service area planning for governmental agencies, consequence assessment, mitigation planning and implementation, and assessment of spatially vulnerable populations.« less

Locally-Adaptive, Spatially-Explicit Projection of U.S. Population for 2030 and 2050

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

McKee, Jacob J.; Rose, Amy N.; Bright, Eddie A.

Localized adverse events, including natural hazards, epidemiological events, and human conflict, underscore the criticality of quantifying and mapping current population. Moreover, knowing the spatial distribution of future population allows for increased preparation in the event of an emergency. Building on the spatial interpolation technique previously developed for high resolution population distribution data (LandScan Global and LandScan USA), we have constructed an empirically-informed spatial distribution of the projected population of the contiguous U.S. for 2030 and 2050. Whereas most current large-scale, spatially explicit population projections typically rely on a population gravity model to determine areas of future growth, our projection modelmore » departs from these by accounting for multiple components that affect population distribution. Modelled variables, which included land cover, slope, distances to larger cities, and a moving average of current population, were locally adaptive and geographically varying. The resulting weighted surface was used to determine which areas had the greatest likelihood for future population change. Population projections of county level numbers were developed using a modified version of the U.S. Census s projection methodology with the U.S. Census s official projection as the benchmark. Applications of our model include, but are not limited to, suitability modelling, service area planning for governmental agencies, consequence assessment, mitigation planning and implementation, and assessment of spatially vulnerable populations.« less

Regional Extinctions and Quaternary Shifts in the Geographic Range of Lestodelphys halli, the Southernmost Living Marsupial: Clues for Its Conservation.

PubMed

Formoso, Anahí E; Martin, Gabriel M; Teta, Pablo; Carbajo, Aníbal E; Sauthier, Daniel E Udrizar; Pardiñas, Ulyses F J

2015-01-01

The Patagonian opossum (Lestodelphys halli), the southernmost living marsupial, inhabits dry and open environments, mainly in the Patagonian steppe (between ~32 °S and ~49 °S). Its rich fossil record shows its occurrence further north in Central Argentina during the Quaternary. The paleoenvironmental meaning of the past distribution of L. halli has been mostly addressed in a subjective framework without an explicit connection with the climatic "space" currently occupied by this animal. Here, we assessed the potential distribution of this species and the changes occurred in its geographic range during late Pleistocene-Holocene times and linked the results obtained with conservation issues. To this end, we generated three potential distribution models with fossil records and three with current ones, using MaxEnt software. These models showed a decrease in the suitable habitat conditions for the species, highlighting a range shift from Central-Eastern to South-Western Argentina. Our results support that the presence of L. halli in the Pampean region during the Pleistocene-Holocene can be related to precipitation and temperature variables and that its current presence in Patagonia is more related to temperature and dominant soils. The models obtained suggest that the species has been experiencing a reduction in its geographic range since the middle Holocene, a process that is in accordance with a general increase in moisture and temperature in Central Argentina. Considering the findings of our work and the future scenario of global warming projected for Patagonia, we might expect a harsh impact on the distribution range of this opossum in the near future.

Modelling the dispersal of the two main hosts of the raccoon rabies variant in heterogeneous environments with landscape genetics.

PubMed

Rioux Paquette, Sébastien; Talbot, Benoit; Garant, Dany; Mainguy, Julien; Pelletier, Fanie

2014-08-01

Predicting the geographic spread of wildlife epidemics requires knowledge about the movement patterns of disease hosts or vectors. The field of landscape genetics provides valuable approaches to study dispersal indirectly, which in turn may be used to understand patterns of disease spread. Here, we applied landscape genetic analyses and spatially explicit models to identify the potential path of raccoon rabies spread in a mesocarnivore community. We used relatedness estimates derived from microsatellite genotypes of raccoons and striped skunks to investigate their dispersal patterns in a heterogeneous landscape composed predominantly of agricultural, forested and residential areas. Samples were collected in an area covering 22 000 km(2) in southern Québec, where the raccoon rabies variant (RRV) was first detected in 2006. Multiple regressions on distance matrices revealed that genetic distance among male raccoons was strictly a function of geographic distance, while dispersal in female raccoons was significantly reduced by the presence of agricultural fields. In skunks, our results suggested that dispersal is increased in edge habitats between fields and forest fragments in both males and females. Resistance modelling allowed us to identify likely dispersal corridors used by these two rabies hosts, which may prove especially helpful for surveillance and control (e.g. oral vaccination) activities.

Barrier Displacement on a Neutral Landscape: Toward a Theory of Continental Biogeography.

PubMed

Albert, James S; Schoolmaster, Donald R; Tagliacollo, Victor; Duke-Sylvester, Scott M

2017-03-01

Macroevolutionary theory posits three processes leading to lineage diversification and the formation of regional biotas: dispersal (species geographic range expansion), speciation (species lineage splitting), and extinction (species lineage termination). The Theory of Island Biogeography (TIB) predicts species richness values using just two of these processes; dispersal and extinction. Yet most species on Earth live on continents or continental shelves, and the dynamics of evolutionary diversification at regional and continental scales are qualitatively different from those that govern the formation of species richness on biogeographic islands. Certain geomorphological processes operating perennially on continental platforms displace barriers to gene flow and organismal dispersal, and affect all three terms of macroevolutionary diversification. For example, uplift of a dissected landscape and river capture both merge and separate portions of adjacent areas, allowing dispersal and larger geographic ranges, vicariant speciation and smaller geographic ranges, and extinction when range sizes are subdivided below a minimum persistence threshold. The TIB also does not predict many biogeographic and phylogenetic patterns widely observed in continentally distributed taxa, including: (i) power function-like species-area relationships; (ii) log-normal distribution of species geographic range sizes, in which most species have restricted ranges (are endemic) and few species have broad ranges (are cosmopolitan); (iii) mid-domain effects with more species toward the geographic center, and more early-branching, species-poor clades toward the geographic periphery; (iv) exponential rates of net diversification with log-linear accumulation of lineages through geological time; and (v) power function-like relationships between species-richness and clade diversity, in which most clades are species-poor and few clades are species-rich. Current theory does not provide a robust mechanistic framework to connect these seemingly disparate patterns. Here we present SEAMLESS (Spatially Explicit Area Model of Landscape Evolution by SimulationS) that generates clade diversification by moving geographic barriers on a continuous, neutral landscape. SEAMLESS is a neutral Landscape Evolution Model (LEM) that treats species and barriers as functionally equivalent with respect to model parameters. SEAMLESS differs from other model-based biogeographic methods (e.g., Lagrange, GeoSSE, BayArea, and BioGeoBEARS) by modeling properties of dispersal barriers rather than areas, and by modeling the evolution of species lineages on a continuous landscape, rather than the evolution of geographic ranges along branches of a phylogeny. SEAMLESS shows how dispersal is required to maintain species richness and avoid clade-wide extinction, demonstrates that ancestral range size does not predict species richness, and provides a unified explanation for the suite of commonly observed biogeographic and phylogenetic patterns listed above. SEAMLESS explains how a simple barrier-displacement mechanism affects lineage diversification under neutral conditions, and is advanced here toward the formulation of a general theory of continental biogeography. [Diversification, extinction, geodispersal, macroevolution, river capture, vicariance.]. Published by Oxford University Press on behalf of Society of Systematic Biologists 2016. This work is written by a US Government employee and is in the public domain in the US.

Phylogeography Takes a Relaxed Random Walk in Continuous Space and Time

PubMed Central

Lemey, Philippe; Rambaut, Andrew; Welch, John J.; Suchard, Marc A.

2010-01-01

Research aimed at understanding the geographic context of evolutionary histories is burgeoning across biological disciplines. Recent endeavors attempt to interpret contemporaneous genetic variation in the light of increasingly detailed geographical and environmental observations. Such interest has promoted the development of phylogeographic inference techniques that explicitly aim to integrate such heterogeneous data. One promising development involves reconstructing phylogeographic history on a continuous landscape. Here, we present a Bayesian statistical approach to infer continuous phylogeographic diffusion using random walk models while simultaneously reconstructing the evolutionary history in time from molecular sequence data. Moreover, by accommodating branch-specific variation in dispersal rates, we relax the most restrictive assumption of the standard Brownian diffusion process and demonstrate increased statistical efficiency in spatial reconstructions of overdispersed random walks by analyzing both simulated and real viral genetic data. We further illustrate how drawing inference about summary statistics from a fully specified stochastic process over both sequence evolution and spatial movement reveals important characteristics of a rabies epidemic. Together with recent advances in discrete phylogeographic inference, the continuous model developments furnish a flexible statistical framework for biogeographical reconstructions that is easily expanded upon to accommodate various landscape genetic features. PMID:20203288

Do more hospital beds lead to higher hospitalization rates? a spatial examination of Roemer's Law.

PubMed

Delamater, Paul L; Messina, Joseph P; Grady, Sue C; WinklerPrins, Vince; Shortridge, Ashton M

2013-01-01

Roemer's Law, a widely cited principle in health care policy, states that hospital beds that are built tend to be used. This simple but powerful expression has been invoked to justify Certificate of Need regulation of hospital beds in an effort to contain health care costs. Despite its influence, a surprisingly small body of empirical evidence supports its content. Furthermore, known geographic factors influencing health services use and the spatial structure of the relationship between hospital bed availability and hospitalization rates have not been sufficiently explored in past examinations of Roemer's Law. We pose the question, "Accounting for space in health care access and use, is there an observable association between the availability of hospital beds and hospital utilization?" We employ an ecological research design based upon the Anderson behavioral model of health care utilization. This conceptual model is implemented in an explicitly spatial context. The effect of hospital bed availability on the utilization of hospital services is evaluated, accounting for spatial structure and controlling for other known determinants of hospital utilization. The stability of this relationship is explored by testing across numerous geographic scales of analysis. The case study comprises an entire state system of hospitals and population, evaluating over one million inpatient admissions. We find compelling evidence that a positive, statistically significant relationship exists between hospital bed availability and inpatient hospitalization rates. Additionally, the observed relationship is invariant with changes in the geographic scale of analysis. This study provides evidence for the effects of Roemer's Law, thus suggesting that variations in hospitalization rates have origins in the availability of hospital beds. This relationship is found to be robust across geographic scales of analysis. These findings suggest continued regulation of hospital bed supply to assist in controlling hospital utilization is justified.

Using a 'value-added' approach for contextual design of geographic information.

PubMed

May, Andrew J

2013-11-01

The aim of this article is to demonstrate how a 'value-added' approach can be used for user-centred design of geographic information. An information science perspective was used, with value being the difference in outcomes arising from alternative information sets. Sixteen drivers navigated a complex, unfamiliar urban route, using visual and verbal instructions representing the distance-to-turn and junction layout information presented by typical satellite navigation systems. Data measuring driving errors, navigation errors and driver confidence were collected throughout the trial. The results show how driver performance varied considerably according to the geographic context at specific locations, and that there are specific opportunities to add value with enhanced geographical information. The conclusions are that a value-added approach facilitates a more explicit focus on 'desired' (and feasible) levels of end user performance with different information sets, and is a potentially effective approach to user-centred design of geographic information. Copyright © 2012 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Unravelling the structure of species extinction risk for predictive conservation science.

PubMed

Lee, Tien Ming; Jetz, Walter

2011-05-07

Extinction risk varies across species and space owing to the combined and interactive effects of ecology/life history and geography. For predictive conservation science to be effective, large datasets and integrative models that quantify the relative importance of potential factors and separate rapidly changing from relatively static threat drivers are urgently required. Here, we integrate and map in space the relative and joint effects of key correlates of The International Union for Conservation of Nature-assessed extinction risk for 8700 living birds. Extinction risk varies significantly with species' broad-scale environmental niche, geographical range size, and life-history and ecological traits such as body size, developmental mode, primary diet and foraging height. Even at this broad scale, simple quantifications of past human encroachment across species' ranges emerge as key in predicting extinction risk, supporting the use of land-cover change projections for estimating future threat in an integrative setting. A final joint model explains much of the interspecific variation in extinction risk and provides a remarkably strong prediction of its observed global geography. Our approach unravels the species-level structure underlying geographical gradients in extinction risk and offers a means of disentangling static from changing components of current and future threat. This reconciliation of intrinsic and extrinsic, and of past and future extinction risk factors may offer a critical step towards a more continuous, forward-looking assessment of species' threat status based on geographically explicit environmental change projections, potentially advancing global predictive conservation science.

Conceptualizing violence for health and medical geography.

PubMed

DeVerteuil, Geoffrey

2015-05-01

Despite the fact that violence is a major threat to public health, the term itself is rarely considered as a phenomenon unto itself, and rarely figures explicitly in work by health and medical geographers. In response, I propose a definitionally and conceptually more robust approach to violence using a tripartite frame (interpersonal violence, structural violence, mass intentional violence) and suggest critical interventions through which to apply this more explicit and conceptually more robust approach: violence and embodiment via substance abuse in health geography, and structural violence via mental illness in medical geography. Copyright © 2015 Elsevier Ltd. All rights reserved.

Assessment of economically optimal water management and geospatial potential for large-scale water storage

NASA Astrophysics Data System (ADS)

Weerasinghe, Harshi; Schneider, Uwe A.

2010-05-01

Assessment of economically optimal water management and geospatial potential for large-scale water storage Weerasinghe, Harshi; Schneider, Uwe A Water is an essential but limited and vulnerable resource for all socio-economic development and for maintaining healthy ecosystems. Water scarcity accelerated due to population expansion, improved living standards, and rapid growth in economic activities, has profound environmental and social implications. These include severe environmental degradation, declining groundwater levels, and increasing problems of water conflicts. Water scarcity is predicted to be one of the key factors limiting development in the 21st century. Climate scientists have projected spatial and temporal changes in precipitation and changes in the probability of intense floods and droughts in the future. As scarcity of accessible and usable water increases, demand for efficient water management and adaptation strategies increases as well. Addressing water scarcity requires an intersectoral and multidisciplinary approach in managing water resources. This would in return safeguard the social welfare and the economical benefit to be at their optimal balance without compromising the sustainability of ecosystems. This paper presents a geographically explicit method to assess the potential for water storage with reservoirs and a dynamic model that identifies the dimensions and material requirements under an economically optimal water management plan. The methodology is applied to the Elbe and Nile river basins. Input data for geospatial analysis at watershed level are taken from global data repositories and include data on elevation, rainfall, soil texture, soil depth, drainage, land use and land cover; which are then downscaled to 1km spatial resolution. Runoff potential for different combinations of land use and hydraulic soil groups and for mean annual precipitation levels are derived by the SCS-CN method. Using the overlay and decision tree algorithms in GIS, potential water storage sites are identified for constructing regional reservoirs. Subsequently, sites are prioritized based on runoff generation potential (m3 per unit area), and geographical suitability for constructing storage structures. The results from the spatial analysis are used as input for the optimization model. Allocation of resources and appropriate dimension for dams and associated structures are identified using the optimization model. The model evaluates the capability of alternative reservoirs for cost-efficient water management. The Geographic Information System is used to store, analyze, and integrate spatially explicit and non-spatial attribute information whereas the algebraic modeling platform is used to develop the dynamic optimization model. The results of this methodology are validated over space against satellite remote sensing data and existing data on reservoir capacities and runoff. The method is suitable for application of on-farm water storage structures, water distribution networks, and moisture conservation structures in a global context.

A decision support system for forest harvest planning in North Carolina

Treesearch

D.G. Jones

2010-01-01

Forest preharvest planning (FPP) can enhance recognition of environmentally-sensitive areas in advance of forest harvesting, including soil and water resources. While preharvest planning is often a standard component of many forest harvesting operations, either explicitly with paper-based checklists or implicitly with best professional judgment, Geographic Information...

Spatial allocation of forest recreation value

Treesearch

Kenneth A. Baerenklau; Armando Gonzalez-Caban; Catrina Paez; Edgard Chavez

2009-01-01

Non-market valuation methods and geographic information systems are useful planning and management tools for public land managers. Recent attention has been given to investigation and demonstration of methods for combining these tools to provide spatially-explicit representations of non-market value. Most of these efforts have focused on spatial allocation of...

CONFRONTING THE MODIFIABLE AREAL UNIT PROBLEM FOR INFERENCE ON NITRATE IN REGIONAL SHALLOW GROUND WATER

EPA Science Inventory

This work addresses a potentially serious problem in synthesis of
spatially explicit data on ground water quality from wells, known to
geographers as the modifiable areal unit problem (MAUP). Investigators
are faced with choosing a level of aggregation appropriate to
...

Generalized reproduction numbers and the prediction of patterns in waterborne disease.

PubMed

Gatto, Marino; Mari, Lorenzo; Bertuzzo, Enrico; Casagrandi, Renato; Righetto, Lorenzo; Rodriguez-Iturbe, Ignacio; Rinaldo, Andrea

2012-11-27

Understanding, predicting, and controlling outbreaks of waterborne diseases are crucial goals of public health policies, but pose challenging problems because infection patterns are influenced by spatial structure and temporal asynchrony. Although explicit spatial modeling is made possible by widespread data mapping of hydrology, transportation infrastructure, population distribution, and sanitation, the precise condition under which a waterborne disease epidemic can start in a spatially explicit setting is still lacking. Here we show that the requirement that all the local reproduction numbers R0 be larger than unity is neither necessary nor sufficient for outbreaks to occur when local settlements are connected by networks of primary and secondary infection mechanisms. To determine onset conditions, we derive general analytical expressions for a reproduction matrix G0, explicitly accounting for spatial distributions of human settlements and pathogen transmission via hydrological and human mobility networks. At disease onset, a generalized reproduction number Λ0 (the dominant eigenvalue of G0) must be larger than unity. We also show that geographical outbreak patterns in complex environments are linked to the dominant eigenvector and to spectral properties of G0. Tests against data and computations for the 2010 Haiti and 2000 KwaZulu-Natal cholera outbreaks, as well as against computations for metapopulation networks, demonstrate that eigenvectors of G0 provide a synthetic and effective tool for predicting the disease course in space and time. Networked connectivity models, describing the interplay between hydrology, epidemiology, and social behavior sustaining human mobility, thus prove to be key tools for emergency management of waterborne infections.

Evaluating mechanisms of diversification in a Guineo-Congolian tropical forest frog using demographic model selection.

PubMed

Portik, Daniel M; Leaché, Adam D; Rivera, Danielle; Barej, Michael F; Burger, Marius; Hirschfeld, Mareike; Rödel, Mark-Oliver; Blackburn, David C; Fujita, Matthew K

2017-10-01

The accumulation of biodiversity in tropical forests can occur through multiple allopatric and parapatric models of diversification, including forest refugia, riverine barriers and ecological gradients. Considerable debate surrounds the major diversification process, particularly in the West African Lower Guinea forests, which contain a complex geographic arrangement of topographic features and historical refugia. We used genomic data to investigate alternative mechanisms of diversification in the Gaboon forest frog, Scotobleps gabonicus, by first identifying population structure and then performing demographic model selection and spatially explicit analyses. We found that a majority of population divergences are best explained by allopatric models consistent with the forest refugia hypothesis and involve divergence in isolation with subsequent expansion and gene flow. These population divergences occurred simultaneously and conform to predictions based on climatically stable regions inferred through ecological niche modelling. Although forest refugia played a prominent role in the intraspecific diversification of S. gabonicus, we also find evidence for potential interactions between landscape features and historical refugia, including major rivers and elevational barriers such as the Cameroonian Volcanic Line. We outline the advantages of using genomewide variation in a model-testing framework to distinguish between alternative allopatric hypotheses, and the pitfalls of limited geographic and molecular sampling. Although phylogeographic patterns are often species-specific and related to life-history traits, additional comparative studies incorporating genomic data are necessary for separating shared historical processes from idiosyncratic responses to environmental, climatic and geological influences on diversification. © 2017 John Wiley & Sons Ltd.

Spatially Explicit Models to Investigate Geographic Patterns in the Distribution of Forensic STRs: Application to the North-Eastern Mediterranean.

PubMed

Messina, Francesco; Finocchio, Andrea; Akar, Nejat; Loutradis, Aphrodite; Michalodimitrakis, Emmanuel I; Brdicka, Radim; Jodice, Carla; Novelletto, Andrea

2016-01-01

Human forensic STRs used for individual identification have been reported to have little power for inter-population analyses. Several methods have been developed which incorporate information on the spatial distribution of individuals to arrive at a description of the arrangement of diversity. We genotyped at 16 forensic STRs a large population sample obtained from many locations in Italy, Greece and Turkey, i.e. three countries crucial to the understanding of discontinuities at the European/Asian junction and the genetic legacy of ancient migrations, but seldom represented together in previous studies. Using spatial PCA on the full dataset, we detected patterns of population affinities in the area. Additionally, we devised objective criteria to reduce the overall complexity into reduced datasets. Independent spatially explicit methods applied to these latter datasets converged in showing that the extraction of information on long- to medium-range geographical trends and structuring from the overall diversity is possible. All analyses returned the picture of a background clinal variation, with regional discontinuities captured by each of the reduced datasets. Several aspects of our results are confirmed on external STR datasets and replicate those of genome-wide SNP typings. High levels of gene flow were inferred within the main continental areas by coalescent simulations. These results are promising from a microevolutionary perspective, in view of the fast pace at which forensic data are being accumulated for many locales. It is foreseeable that this will allow the exploitation of an invaluable genotypic resource, assembled for other (forensic) purposes, to clarify important aspects in the formation of local gene pools.

Natural Human Mobility Patterns and Spatial Spread of Infectious Diseases

NASA Astrophysics Data System (ADS)

Belik, Vitaly; Geisel, Theo; Brockmann, Dirk

2011-08-01

We investigate a model for spatial epidemics explicitly taking into account bidirectional movements between base and destination locations on individual mobility networks. We provide a systematic analysis of generic dynamical features of the model on regular and complex metapopulation network topologies and show that significant dynamical differences exist to ordinary reaction-diffusion and effective force of infection models. On a lattice we calculate an expression for the velocity of the propagating epidemic front and find that, in contrast to the diffusive systems, our model predicts a saturation of the velocity with an increasing traveling rate. Furthermore, we show that a fully stochastic system exhibits a novel threshold for the attack ratio of an outbreak that is absent in diffusion and force of infection models. These insights not only capture natural features of human mobility relevant for the geographical epidemic spread, they may serve as a starting point for modeling important dynamical processes in human and animal epidemiology, population ecology, biology, and evolution.

Genetic patterns of habitat fragmentation and past climate-change effects in the Mediterranean high-mountain plant Armeria caespitosa (Plumbaginaceae).

PubMed

García-Fernández, Alfredo; Iriondo, Jose M; Escudero, Adrián; Aguilar, Javier Fuertes; Feliner, Gonzalo Nieto

2013-08-01

Mountain plants are among the species most vulnerable to global warming, because of their isolation, narrow geographic distribution, and limited geographic range shifts. Stochastic and selective processes can act on the genome, modulating genetic structure and diversity. Fragmentation and historical processes also have a great influence on current genetic patterns, but the spatial and temporal contexts of these processes are poorly known. We aimed to evaluate the microevolutionary processes that may have taken place in Mediterranean high-mountain plants in response to changing historical environmental conditions. Genetic structure, diversity, and loci under selection were analyzed using AFLP markers in 17 populations distributed over the whole geographic range of Armeria caespitosa, an endemic plant that inhabits isolated mountains (Sierra de Guadarrama, Spain). Differences in altitude, geographic location, and climate conditions were considered in the analyses, because they may play an important role in selective and stochastic processes. Bayesian clustering approaches identified nine genetic groups, although some discrepancies in assignment were found between alternative analyses. Spatially explicit analyses showed a weak relationship between genetic parameters and spatial or environmental distances. However, a large proportion of outlier loci were detected, and some outliers were related to environmental variables. A. caespitosa populations exhibit spatial patterns of genetic structure that cannot be explained by the isolation-by-distance model. Shifts along the altitude gradient in response to Pleistocene climatic oscillations and environmentally mediated selective forces might explain the resulting structure and genetic diversity values found.

Spatially explicit measures of production of young alewives in Lake Michigan: Linkage between essential fish habitat and recruitment

USGS Publications Warehouse

Hook, Tomas O.; Rutherford, Edward S.; Brines, Shannon J.; Mason, Doran M.; Schwab, David J.; McCormick, Michael; Desorcie, Timothy J.

2003-01-01

The identification and protection of essential habitats for early life stages of fishes are necessary to sustain fish stocks. Essential fish habitat for early life stages may be defined as areas where fish densities, growth, survival, or production rates are relatively high. To identify critical habitats for young-of-year (YOY) alewives (Alosa pseud oharengus) in Lake Michigan, we integrated bioenergetics models with GIS (Geographic Information Systems) to generate spatially explicit estimates of potential population production (an index of habitat quality). These estimates were based upon YOY alewife bioenergetic growth rate potential and their salmonine predators’ consumptive demand. We compared estimates of potential population production to YOY alewife yield (an index of habitat importance). Our analysis suggested that during 1994–1995, YOY alewife habitat quality and yield varied widely throughout Lake Michigan. Spatial patterns of alewife yield were not significantly correlated to habitat quality. Various mechanisms (e.g., predator migrations, lake circulation patterns, alternative strategies) may preclude YOY alewives from concentrating in areas of high habitat quality in Lake Michigan.

Do People Use the Shortest Path? An Empirical Test of Wardrop’s First Principle

PubMed Central

Zhu, Shanjiang; Levinson, David

2015-01-01

Most recent route choice models, following either the random utility maximization or rule-based paradigm, require explicit enumeration of feasible routes. The quality of model estimation and prediction is sensitive to the appropriateness of the consideration set. However, few empirical studies of revealed route characteristics have been reported in the literature. This study evaluates the widely applied shortest path assumption by evaluating routes followed by residents of the Minneapolis—St. Paul metropolitan area. Accurate Global Positioning System (GPS) and Geographic Information System (GIS) data were employed to reveal routes people used over an eight to thirteen week period. Most people did not choose the shortest path. Using three weeks of that data, we find that current route choice set generation algorithms do not reveal the majority of paths that individuals took. Findings from this study may guide future efforts in building better route choice models. PMID:26267756

Using landscape limnology to classify freshwater ecosystems for multi-ecosystem management and conservation

USGS Publications Warehouse

Soranno, Patricia A.; Cheruvelil, Kendra Spence; Webster, Katherine E.; Bremigan, Mary T.; Wagner, Tyler; Stow, Craig A.

2010-01-01

Governmental entities are responsible for managing and conserving large numbers of lake, river, and wetland ecosystems that can be addressed only rarely on a case-by-case basis. We present a system for predictive classification modeling, grounded in the theoretical foundation of landscape limnology, that creates a tractable number of ecosystem classes to which management actions may be tailored. We demonstrate our system by applying two types of predictive classification modeling approaches to develop nutrient criteria for eutrophication management in 1998 north temperate lakes. Our predictive classification system promotes the effective management of multiple ecosystems across broad geographic scales by explicitly connecting management and conservation goals to the classification modeling approach, considering multiple spatial scales as drivers of ecosystem dynamics, and acknowledging the hierarchical structure of freshwater ecosystems. Such a system is critical for adaptive management of complex mosaics of freshwater ecosystems and for balancing competing needs for ecosystem services in a changing world.

Modeling acute respiratory illness during the 2007 San Diego wildland fires using a coupled emissions-transport system and generalized additive modeling

PubMed Central

2013-01-01

Background A study of the impacts on respiratory health of the 2007 wildland fires in and around San Diego County, California is presented. This study helps to address the impact of fire emissions on human health by modeling the exposure potential of proximate populations to atmospheric particulate matter (PM) from vegetation fires. Currently, there is no standard methodology to model and forecast the potential respiratory health effects of PM plumes from wildland fires, and in part this is due to a lack of methodology for rigorously relating the two. The contribution in this research specifically targets that absence by modeling explicitly the emission, transmission, and distribution of PM following a wildland fire in both space and time. Methods Coupled empirical and deterministic models describing particulate matter (PM) emissions and atmospheric dispersion were linked to spatially explicit syndromic surveillance health data records collected through the San Diego Aberration Detection and Incident Characterization (SDADIC) system using a Generalized Additive Modeling (GAM) statistical approach. Two levels of geographic aggregation were modeled, a county-wide regional level and division of the county into six sub regions. Selected health syndromes within SDADIC from 16 emergency departments within San Diego County relevant for respiratory health were identified for inclusion in the model. Results The model captured the variability in emergency department visits due to several factors by including nine ancillary variables in addition to wildfire PM concentration. The model coefficients and nonlinear function plots indicate that at peak fire PM concentrations the odds of a person seeking emergency care is increased by approximately 50% compared to non-fire conditions (40% for the regional case, 70% for a geographically specific case). The sub-regional analyses show that demographic variables also influence respiratory health outcomes from smoke. Conclusions The model developed in this study allows a quantitative assessment and prediction of respiratory health outcomes as it relates to the location and timing of wildland fire emissions relevant for application to future wildfire scenarios. An important aspect of the resulting model is its generality thus allowing its ready use for geospatial assessments of respiratory health impacts under possible future wildfire conditions in the San Diego region. The coupled statistical and process-based modeling demonstrates an end-to-end methodology for generating reasonable estimates of wildland fire PM concentrations and health effects at resolutions compatible with syndromic surveillance data. PMID:24192051

A Comparison Between Gravity Wave Momentum Fluxes in Observations and Climate Models

NASA Technical Reports Server (NTRS)

Geller, Marvin A.; Alexadner, M. Joan; Love, Peter T.; Bacmeister, Julio; Ern, Manfred; Hertzog, Albert; Manzini, Elisa; Preusse, Peter; Sato, Kaoru; Scaife, Adam A.;

Geographical thinking in nursing inquiry, part one: locations, contents, meanings.

PubMed

Andrews, Gavin J

2016-10-01

Spatial thought is undergoing somewhat of a renaissance in nursing. Building on a long disciplinary tradition of conceptualizing and studying 'nursing environment', the past twenty years has witnessing the establishment and refinement of explicitly geographical nursing research. This article - part one in a series of two - reviews the perspectives taken to date, ranging from historical precedent in classical nursing theory through to positivistic spatial science, political economy, and social constructivism in contemporary inquiry. This discussion sets up part two, which considers the potential of non-representational theory for framing future studies. © 2016 John Wiley & Sons Ltd.

Camera traps and mark-resight models: The value of ancillary data for evaluating assumptions

USGS Publications Warehouse

Parsons, Arielle W.; Simons, Theodore R.; Pollock, Kenneth H.; Stoskopf, Michael K.; Stocking, Jessica J.; O'Connell, Allan F.

2015-01-01

Unbiased estimators of abundance and density are fundamental to the study of animal ecology and critical for making sound management decisions. Capture–recapture models are generally considered the most robust approach for estimating these parameters but rely on a number of assumptions that are often violated but rarely validated. Mark-resight models, a form of capture–recapture, are well suited for use with noninvasive sampling methods and allow for a number of assumptions to be relaxed. We used ancillary data from continuous video and radio telemetry to evaluate the assumptions of mark-resight models for abundance estimation on a barrier island raccoon (Procyon lotor) population using camera traps. Our island study site was geographically closed, allowing us to estimate real survival and in situ recruitment in addition to population size. We found several sources of bias due to heterogeneity of capture probabilities in our study, including camera placement, animal movement, island physiography, and animal behavior. Almost all sources of heterogeneity could be accounted for using the sophisticated mark-resight models developed by McClintock et al. (2009b) and this model generated estimates similar to a spatially explicit mark-resight model previously developed for this population during our study. Spatially explicit capture–recapture models have become an important tool in ecology and confer a number of advantages; however, non-spatial models that account for inherent individual heterogeneity may perform nearly as well, especially where immigration and emigration are limited. Non-spatial models are computationally less demanding, do not make implicit assumptions related to the isotropy of home ranges, and can provide insights with respect to the biological traits of the local population.

A hidden Markov model for reconstructing animal paths from solar geolocation loggers using templates for light intensity.

PubMed

Rakhimberdiev, Eldar; Winkler, David W; Bridge, Eli; Seavy, Nathaniel E; Sheldon, Daniel; Piersma, Theunis; Saveliev, Anatoly

2015-01-01

Solar archival tags (henceforth called geolocators) are tracking devices deployed on animals to reconstruct their long-distance movements on the basis of locations inferred post hoc with reference to the geographical and seasonal variations in the timing and speeds of sunrise and sunset. The increased use of geolocators has created a need for analytical tools to produce accurate and objective estimates of migration routes that are explicit in their uncertainty about the position estimates. We developed a hidden Markov chain model for the analysis of geolocator data. This model estimates tracks for animals with complex migratory behaviour by combining: (1) a shading-insensitive, template-fit physical model, (2) an uncorrelated random walk movement model that includes migratory and sedentary behavioural states, and (3) spatially explicit behavioural masks. The model is implemented in a specially developed open source R package FLightR. We used the particle filter (PF) algorithm to provide relatively fast model posterior computation. We illustrate our modelling approach with analysis of simulated data for stationary tags and of real tracks of both a tree swallow Tachycineta bicolor migrating along the east and a golden-crowned sparrow Zonotrichia atricapilla migrating along the west coast of North America. We provide a model that increases accuracy in analyses of noisy data and movements of animals with complicated migration behaviour. It provides posterior distributions for the positions of animals, their behavioural states (e.g., migrating or sedentary), and distance and direction of movement. Our approach allows biologists to estimate locations of animals with complex migratory behaviour based on raw light data. This model advances the current methods for estimating migration tracks from solar geolocation, and will benefit a fast-growing number of tracking studies with this technology.

Regional Extinctions and Quaternary Shifts in the Geographic Range of Lestodelphys halli, the Southernmost Living Marsupial: Clues for Its Conservation

PubMed Central

Formoso, Anahí E.; Martin, Gabriel M.; Teta, Pablo; Carbajo, Aníbal E.; Sauthier, Daniel E. Udrizar; Pardiñas, Ulyses F. J.

2015-01-01

The Patagonian opossum (Lestodelphys halli), the southernmost living marsupial, inhabits dry and open environments, mainly in the Patagonian steppe (between ~32°S and ~49°S). Its rich fossil record shows its occurrence further north in Central Argentina during the Quaternary. The paleoenvironmental meaning of the past distribution of L. halli has been mostly addressed in a subjective framework without an explicit connection with the climatic “space” currently occupied by this animal. Here, we assessed the potential distribution of this species and the changes occurred in its geographic range during late Pleistocene-Holocene times and linked the results obtained with conservation issues. To this end, we generated three potential distribution models with fossil records and three with current ones, using MaxEnt software. These models showed a decrease in the suitable habitat conditions for the species, highlighting a range shift from Central-Eastern to South-Western Argentina. Our results support that the presence of L. halli in the Pampean region during the Pleistocene-Holocene can be related to precipitation and temperature variables and that its current presence in Patagonia is more related to temperature and dominant soils. The models obtained suggest that the species has been experiencing a reduction in its geographic range since the middle Holocene, a process that is in accordance with a general increase in moisture and temperature in Central Argentina. Considering the findings of our work and the future scenario of global warming projected for Patagonia, we might expect a harsh impact on the distribution range of this opossum in the near future. PMID:26203650

Accounting for spatial effects in land use regression for urban air pollution modeling.

PubMed

Bertazzon, Stefania; Johnson, Markey; Eccles, Kristin; Kaplan, Gilaad G

2015-01-01

In order to accurately assess air pollution risks, health studies require spatially resolved pollution concentrations. Land-use regression (LUR) models estimate ambient concentrations at a fine spatial scale. However, spatial effects such as spatial non-stationarity and spatial autocorrelation can reduce the accuracy of LUR estimates by increasing regression errors and uncertainty; and statistical methods for resolving these effects--e.g., spatially autoregressive (SAR) and geographically weighted regression (GWR) models--may be difficult to apply simultaneously. We used an alternate approach to address spatial non-stationarity and spatial autocorrelation in LUR models for nitrogen dioxide. Traditional models were re-specified to include a variable capturing wind speed and direction, and re-fit as GWR models. Mean R(2) values for the resulting GWR-wind models (summer: 0.86, winter: 0.73) showed a 10-20% improvement over traditional LUR models. GWR-wind models effectively addressed both spatial effects and produced meaningful predictive models. These results suggest a useful method for improving spatially explicit models. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Does Interdisciplinarity Exist behind the Facade of Traditional Disciplines? A Study of Natural Resource Management Teaching

ERIC Educational Resources Information Center

Pharo, Emma; Bridle, Kerry

2012-01-01

We investigated the hypothesis that interdisciplinarity is being explicitly taught behind the facade of traditional disciplines. We interviewed 14 academics (seven geographers and seven agricultural scientists) about their teaching in the inherently interdisciplinary field of natural resource management. Our teachers were generally well informed…

An Analysis of the Cape Verdean Status Quo: Outgrowths of a Critical Environment.

ERIC Educational Resources Information Center

Brown, Christopher

Utilizing an anthropological approach, this paper provides an intense and unified description of the dominant geographic, economic, political, historic, and social trends prevalent in Cape Verde. It serves as a quasi-explicit and exceptionally objective emphasis of the island's background, and the outgrowths evident in the status quo. The…

A BAYES LIKELIHOOD INFORMATION THEORETIC APPROACH FOR THE EXOGENOUS AGGREGATION OF REGIONAL GROUND WATER QUALITY DATA

EPA Science Inventory

This work addresses a potentially serious problem in analysis or synthesis of spatially explicit data on ground water quality from wells, known to geographers as the modifiable areal unit problem (MAUP). It results from the fact that in regional aggregation of spatial data, inves...

Spatially-explicit estimation of geographical representation in large-scale species distribution datasets.

PubMed

Kalwij, Jesse M; Robertson, Mark P; Ronk, Argo; Zobel, Martin; Pärtel, Meelis

2014-01-01

Much ecological research relies on existing multispecies distribution datasets. Such datasets, however, can vary considerably in quality, extent, resolution or taxonomic coverage. We provide a framework for a spatially-explicit evaluation of geographical representation within large-scale species distribution datasets, using the comparison of an occurrence atlas with a range atlas dataset as a working example. Specifically, we compared occurrence maps for 3773 taxa from the widely-used Atlas Florae Europaeae (AFE) with digitised range maps for 2049 taxa of the lesser-known Atlas of North European Vascular Plants. We calculated the level of agreement at a 50-km spatial resolution using average latitudinal and longitudinal species range, and area of occupancy. Agreement in species distribution was calculated and mapped using Jaccard similarity index and a reduced major axis (RMA) regression analysis of species richness between the entire atlases (5221 taxa in total) and between co-occurring species (601 taxa). We found no difference in distribution ranges or in the area of occupancy frequency distribution, indicating that atlases were sufficiently overlapping for a valid comparison. The similarity index map showed high levels of agreement for central, western, and northern Europe. The RMA regression confirmed that geographical representation of AFE was low in areas with a sparse data recording history (e.g., Russia, Belarus and the Ukraine). For co-occurring species in south-eastern Europe, however, the Atlas of North European Vascular Plants showed remarkably higher richness estimations. Geographical representation of atlas data can be much more heterogeneous than often assumed. Level of agreement between datasets can be used to evaluate geographical representation within datasets. Merging atlases into a single dataset is worthwhile in spite of methodological differences, and helps to fill gaps in our knowledge of species distribution ranges. Species distribution dataset mergers, such as the one exemplified here, can serve as a baseline towards comprehensive species distribution datasets.

Phenological plasticity will not help all species adapt to climate change.

PubMed

Duputié, Anne; Rutschmann, Alexis; Ronce, Ophélie; Chuine, Isabelle

2015-08-01

Concerns are rising about the capacity of species to adapt quickly enough to climate change. In long-lived organisms such as trees, genetic adaptation is slow, and how much phenotypic plasticity can help them cope with climate change remains largely unknown. Here, we assess whether, where and when phenological plasticity is and will be adaptive in three major European tree species. We use a process-based species distribution model, parameterized with extensive ecological data, and manipulate plasticity to suppress phenological variations due to interannual, geographical and trend climate variability, under current and projected climatic conditions. We show that phenological plasticity is not always adaptive and mostly affects fitness at the margins of the species' distribution and climatic niche. Under current climatic conditions, phenological plasticity constrains the northern range limit of oak and beech and the southern range limit of pine. Under future climatic conditions, phenological plasticity becomes strongly adaptive towards the trailing edges of beech and oak, but severely constrains the range and niche of pine. Our results call for caution when interpreting geographical variation in trait means as adaptive, and strongly point towards species distribution models explicitly taking phenotypic plasticity into account when forecasting species distribution under climate change scenarios. © 2015 John Wiley & Sons Ltd.

Dynamic assessment of urban economy-environment-energy system using system dynamics model: A case study in Beijing.

PubMed

Wu, Desheng; Ning, Shuang

2018-07-01

Economic development, accompanying with environmental damage and energy depletion, becomes essential nowadays. There is a complicated and comprehensive interaction between economics, environment and energy. Understanding the operating mechanism of Energy-Environment-Economy model (3E) and its key factors is the inherent part in dealing with the issue. In this paper, we combine System Dynamics model and Geographic Information System to analyze the energy-environment-economy (3E) system both temporally and spatially, which explicitly explore the interaction of economics, energy, and environment and effects of the key influencing factors. Beijing is selected as a case study to verify our SD-GIS model. Alternative scenarios, e.g., current, technology, energy and environment scenarios are explored and compared. Simulation results shows that, current scenario is not sustainable; technology scenario is applicable to economic growth; environment scenario maintains a balanced path of development for long term stability. Policy-making insights are given based on our results and analysis. Copyright © 2018 Elsevier Inc. All rights reserved.

a Model Study of Small-Scale World Map Generalization

NASA Astrophysics Data System (ADS)

Cheng, Y.; Yin, Y.; Li, C. M.; Wu, W.; Guo, P. P.; Ma, X. L.; Hu, F. M.

2018-04-01

With the globalization and rapid development every filed is taking an increasing interest in physical geography and human economics. There is a surging demand for small scale world map in large formats all over the world. Further study of automated mapping technology, especially the realization of small scale production on a large scale global map, is the key of the cartographic field need to solve. In light of this, this paper adopts the improved model (with the map and data separated) in the field of the mapmaking generalization, which can separate geographic data from mapping data from maps, mainly including cross-platform symbols and automatic map-making knowledge engine. With respect to the cross-platform symbol library, the symbol and the physical symbol in the geographic information are configured at all scale levels. With respect to automatic map-making knowledge engine consists 97 types, 1086 subtypes, 21845 basic algorithm and over 2500 relevant functional modules.In order to evaluate the accuracy and visual effect of our model towards topographic maps and thematic maps, we take the world map generalization in small scale as an example. After mapping generalization process, combining and simplifying the scattered islands make the map more explicit at 1 : 2.1 billion scale, and the map features more complete and accurate. Not only it enhance the map generalization of various scales significantly, but achieve the integration among map-makings of various scales, suggesting that this model provide a reference in cartographic generalization for various scales.

Linked Forests: Semantic similarity of geographical concepts "forest"

NASA Astrophysics Data System (ADS)

Čerba, Otakar; Jedlička, Karel

2016-01-01

Linked Data represents the new trend in geoinformatics and geomatics. It produces a structure of objects (in a form of concepts or terms) interconnected by object relations expressing a type of semantic relationships of various concepts. The research published in this article studies, if objects connected by above mentioned relations are more similar than objects representing the same phenomenon, but standing alone. The phenomenon "forest" and relevant geographical concepts were chosen as the domain of the research. The concepts similarity (Tanimoto coefficient as a specification of Tversky index) was computed on the basis of explicit information provided by thesauri containing particular concepts. Overall in the seven thesauri (AGROVOC, EuroVoc, GEMET, LusTRE/EARTh, NAL, OECD and STW) there was tested if the "forest" concept interconnected by the relation skos:exactMatch are more similar than other, not interlinked concepts. The results of the research are important for the sharing and combining of geographical data, information and knowledge. The proposed methodology can be reused to a comparison of other geographical concepts.

Land-use change, deforestation, and peasant farm systems: A case study of Mexico's Southern Yucatan Peninsular Region

NASA Astrophysics Data System (ADS)

Vance, Colin James

This dissertation develops spatially explicit econometric models by linking Thematic Mapper (TM) satellite imagery with household survey data to test behavioral propositions of semi-subsistence farmers in the Southern Yucatan Peninsular Region (SYPR) of Mexico. Covering 22,000 km2, this agricultural frontier contains one of the largest and oldest expanses of tropical forests in the Americas outside of Amazonia. Over the past 30 years, the SYPR has undergone significant land-use change largely owing to the construction of a highway through the region's center in 1967. These landscape dynamics are modeled by exploiting a spatial database linking a time series of TM imagery with socio-economic and geo-referenced land-use data collected from a random sample of 188 farm households. The dissertation moves beyond the existing literature on deforestation in three principal respects. Theoretically, the study develops a non-separable model of land-use that relaxes the assumption of profit maximization almost exclusively invoked in studies of the deforestation issue. The model is derived from a utility-maximizing framework that explicitly incorporates the interdependency of the household's production and consumption choices as these affect the allocation of resources. Methodologically, the study assembles a spatial database that couples satellite imagery with household-level socio-economic data. The field survey protocol recorded geo-referenced land-use data through the use of a geographic positioning system and the creation of sketch maps detailing the location of different uses observed within individual plots. Empirically, the study estimates spatially explicit econometric models of land-use change using switching regressions and duration analysis. A distinguishing feature of these models is that they link the dependent and independent variables at the level of the decision unit, the land manager, thereby capturing spatial and temporal heterogeneity that is otherwise obscured in studies using data aggregated to higher scales of analysis. The empirical findings suggest the potential of various policy initiatives to impede or otherwise alter the pattern of land-cover conversions. In this regard, the study reveals that consideration of missing or thin markets is critical to understanding how farmers in the SYPR reach subsistence and commercial cropping decisions.

Spatially Explicit Models to Investigate Geographic Patterns in the Distribution of Forensic STRs: Application to the North-Eastern Mediterranean

PubMed Central

Messina, Francesco; Finocchio, Andrea; Akar, Nejat; Loutradis, Aphrodite; Michalodimitrakis, Emmanuel I.; Brdicka, Radim; Jodice, Carla

2016-01-01

Human forensic STRs used for individual identification have been reported to have little power for inter-population analyses. Several methods have been developed which incorporate information on the spatial distribution of individuals to arrive at a description of the arrangement of diversity. We genotyped at 16 forensic STRs a large population sample obtained from many locations in Italy, Greece and Turkey, i.e. three countries crucial to the understanding of discontinuities at the European/Asian junction and the genetic legacy of ancient migrations, but seldom represented together in previous studies. Using spatial PCA on the full dataset, we detected patterns of population affinities in the area. Additionally, we devised objective criteria to reduce the overall complexity into reduced datasets. Independent spatially explicit methods applied to these latter datasets converged in showing that the extraction of information on long- to medium-range geographical trends and structuring from the overall diversity is possible. All analyses returned the picture of a background clinal variation, with regional discontinuities captured by each of the reduced datasets. Several aspects of our results are confirmed on external STR datasets and replicate those of genome-wide SNP typings. High levels of gene flow were inferred within the main continental areas by coalescent simulations. These results are promising from a microevolutionary perspective, in view of the fast pace at which forensic data are being accumulated for many locales. It is foreseeable that this will allow the exploitation of an invaluable genotypic resource, assembled for other (forensic) purposes, to clarify important aspects in the formation of local gene pools. PMID:27898725

Regional data to support biodiversity assessments: terrestrial vertebrate and butterfly data from the Southwest

Treesearch

Darren J. Bender; Curtis H. Flather; Kenneth R. Wilson; Gordon C. Reese

2005-01-01

Spatially explicit data on the location of species across broad geographic areas greatly facilitate effective conservation planning on lands managed for multiple uses. The importance of these data notwithstanding, our knowledge about the geography of biodiversity is remarkably incomplete. An important factor contributing to our ignorance is that much of the...

Deciphering the Origin of Dogs: From Fossils to Genomes.

PubMed

Freedman, Adam H; Wayne, Robert K

2017-02-08

Understanding the timing and geographic context of dog origins is a crucial component for understanding human history, as well as the evolutionary context in which the morphological and behavioral divergence of dogs from wolves occurred. A substantial challenge to understanding domestication is that dogs have experienced a complicated demographic history. An initial severe bottleneck was associated with domestication followed by postdivergence gene flow between dogs and wolves, as well as population expansions, contractions, and replacements. In addition, because the domestication of dogs occurred in the relatively recent past, much of the observed polymorphism may be shared between dogs and wolves, limiting the power to distinguish between alternative models of dog history. Greater insight into the domestication process will require explicit tests of alternative models of domestication through the joint analysis of whole genomes from modern lineages and ancient wolves and dogs from across Eurasia.

Do More Hospital Beds Lead to Higher Hospitalization Rates? A Spatial Examination of Roemer’s Law

PubMed Central

Delamater, Paul L.; Messina, Joseph P.; Grady, Sue C.; WinklerPrins, Vince; Shortridge, Ashton M.

2013-01-01

Background Roemer’s Law, a widely cited principle in health care policy, states that hospital beds that are built tend to be used. This simple but powerful expression has been invoked to justify Certificate of Need regulation of hospital beds in an effort to contain health care costs. Despite its influence, a surprisingly small body of empirical evidence supports its content. Furthermore, known geographic factors influencing health services use and the spatial structure of the relationship between hospital bed availability and hospitalization rates have not been sufficiently explored in past examinations of Roemer’s Law. We pose the question, “Accounting for space in health care access and use, is there an observable association between the availability of hospital beds and hospital utilization?” Methods We employ an ecological research design based upon the Anderson behavioral model of health care utilization. This conceptual model is implemented in an explicitly spatial context. The effect of hospital bed availability on the utilization of hospital services is evaluated, accounting for spatial structure and controlling for other known determinants of hospital utilization. The stability of this relationship is explored by testing across numerous geographic scales of analysis. The case study comprises an entire state system of hospitals and population, evaluating over one million inpatient admissions. Results We find compelling evidence that a positive, statistically significant relationship exists between hospital bed availability and inpatient hospitalization rates. Additionally, the observed relationship is invariant with changes in the geographic scale of analysis. Conclusions This study provides evidence for the effects of Roemer’s Law, thus suggesting that variations in hospitalization rates have origins in the availability of hospital beds. This relationship is found to be robust across geographic scales of analysis. These findings suggest continued regulation of hospital bed supply to assist in controlling hospital utilization is justified. PMID:23418432

A Theoretical Analysis of the Geography of Schistosomiasis in Burkina Faso Highlights the Roles of Human Mobility and Water Resources Development in Disease Transmission

PubMed Central

Perez-Saez, Javier; Mari, Lorenzo; Bertuzzo, Enrico; Casagrandi, Renato; Sokolow, Susanne H.; De Leo, Giulio A.; Mande, Theophile; Ceperley, Natalie; Froehlich, Jean-Marc; Sou, Mariam; Karambiri, Harouna; Yacouba, Hamma; Maiga, Amadou; Gatto, Marino; Rinaldo, Andrea

2015-01-01

We study the geography of schistosomiasis across Burkina Faso by means of a spatially explicit model of water-based disease dynamics. The model quantitatively addresses the geographic stratification of disease burden in a novel framework by explicitly accounting for drivers and controls of the disease, including spatial information on the distributions of population and infrastructure, jointly with a general description of human mobility and climatic/ecological drivers. Spatial patterns of disease are analysed by the extraction and the mapping of suitable eigenvectors of the Jacobian matrix subsuming the stability of the disease-free equilibrium. The relevance of the work lies in the novel mapping of disease burden, a byproduct of the parametrization induced by regional upscaling, by model-guided field validations and in the predictive scenarios allowed by exploiting the range of possible parameters and processes. Human mobility is found to be a primary control at regional scales both for pathogen invasion success and the overall distribution of disease burden. The effects of water resources development highlighted by systematic reviews are accounted for by the average distances of human settlements from water bodies that are habitats for the parasite’s intermediate host. Our results confirm the empirical findings about the role of water resources development on disease spread into regions previously nearly disease-free also by inspection of empirical prevalence patterns. We conclude that while the model still needs refinements based on field and epidemiological evidence, the proposed framework provides a powerful tool for large-scale public health planning and schistosomiasis management. PMID:26513655

Ring distributions leading to species formation: a global topographic analysis of geographic barriers associated with ring species

PubMed Central

2012-01-01

Background In the mid 20th century, Ernst Mayr and Theodosius Dobzhansky championed the significance of circular overlaps or ring species as the perfect demonstration of speciation, yet in the over 50 years since, only a handful of such taxa are known. We developed a topographic model to evaluate whether the geographic barriers that favor processes leading to ring species are common or rare, and to predict where other candidate ring barriers might be found. Results Of the 952,147 geographic barriers identified on the planet, only about 1% are topographically similar to barriers associated with known ring taxa, with most of the likely candidates occurring in under-studied parts of the world (for example, marine environments, tropical latitudes). Predicted barriers separate into two distinct categories: (i) single cohesive barriers (< 50,000 km2), associated with taxa that differentiate at smaller spatial scales (salamander: Ensatina eschscholtzii; tree: Acacia karroo); and (ii) composite barriers - formed by groups of barriers (each 184,000 to 1.7 million km2) in close geographic proximity (totaling 1.9 to 2.3 million km2) - associated with taxa that differentiate at larger spatial scales (birds: Phylloscopus trochiloides and Larus (sp. argentatus and fuscus)). When evaluated globally, we find a large number of cohesive barriers that are topographically similar to those associated with known ring taxa. Yet, compared to cohesive barriers, an order of magnitude fewer composite barriers are similar to those that favor ring divergence in species with higher dispersal. Conclusions While these findings confirm that the topographic conditions that favor evolutionary processes leading to ring speciation are, in fact, rare, they also suggest that many understudied natural systems could provide valuable demonstrations of continuous divergence towards the formation of new species. Distinct advantages of the model are that it (i) requires no a priori information on the relative importance of features that define barriers, (ii) can be replicated using any kind of continuously distributed environmental variable, and (iii) generates spatially explicit hypotheses of geographic species formation. The methods developed here - combined with study of the geographical ecology and genetics of taxa in their environments - should enable recognition of ring species phenomena throughout the world. PMID:22410314

Two memories for geographical slant: separation and interdependence of action and awareness

NASA Technical Reports Server (NTRS)

Creem, S. H.; Proffitt, D. R.; Kaiser, M. K. (Principal Investigator)

1998-01-01

The present study extended previous findings of geographical slant perception, in which verbal judgments of the incline of hills were greatly overestimated but motoric (haptic) adjustments were much more accurate. In judging slant from memory following a brief or extended time delay, subjects' verbal judgments were greater than those given when viewing hills. Motoric estimates differed depending on the length of the delay and place of response. With a short delay, motoric adjustments made in the proximity of the hill did not differ from those evoked during perception. When given a longer delay or when taken away from the hill, subjects' motoric responses increased along with the increase in verbal reports. These results suggest two different memorial influences on action. With a short delay at the hill, memory for visual guidance is separate from the explicit memory informing the conscious response. With short or long delays away from the hill, short-term visual guidance memory no longer persists, and both motor and verbal responses are driven by an explicit representation. These results support recent research involving visual guidance from memory, where actions become influenced by conscious awareness, and provide evidence for communication between the "what" and "how" visual processing systems.

Microcomputer-based classification of environmental data in municipal areas

NASA Astrophysics Data System (ADS)

Thiergärtner, H.

1995-10-01

Multivariate data-processing methods used in mineral resource identification can be used to classify urban regions. Using elements of expert systems, geographical information systems, as well as known classification and prognosis systems, it is possible to outline a single model that consists of resistant and of temporary parts of a knowledge base including graphical input and output treatment and of resistant and temporary elements of a bank of methods and algorithms. Whereas decision rules created by experts will be stored in expert systems directly, powerful classification rules in form of resistant but latent (implicit) decision algorithms may be implemented in the suggested model. The latent functions will be transformed into temporary explicit decision rules by learning processes depending on the actual task(s), parameter set(s), pixels selection(s), and expert control(s). This takes place both at supervised and nonsupervised classification of multivariately described pixel sets representing municipal subareas. The model is outlined briefly and illustrated by results obtained in a target area covering a part of the city of Berlin (Germany).

Enhancing community based health programs in Iran: a multi-objective location-allocation model.

PubMed

Khodaparasti, S; Maleki, H R; Jahedi, S; Bruni, M E; Beraldi, P

2017-12-01

Community Based Organizations (CBOs) are important health system stakeholders with the mission of addressing the social and economic needs of individuals and groups in a defined geographic area, usually no larger than a county. The access and success efforts of CBOs vary, depending on the integration between health care providers and CBOs but also in relation to the community participation level. To achieve widespread results, it is important to carefully design an efficient network which can serve as a bridge between the community and the health care system. This study addresses this challenge through a location-allocation model that deals with the hierarchical nature of the system explicitly. To reflect social welfare concerns of equity, local accessibility, and efficiency, we develop the model in a multi-objective framework, capturing the ambiguity in the decision makers' aspiration levels through a fuzzy goal programming approach. This study reports the findings for the real case of Shiraz city, Fars province, Iran, obtained by a thorough analysis of the results.

A new solution method for wheel/rail rolling contact.

PubMed

Yang, Jian; Song, Hua; Fu, Lihua; Wang, Meng; Li, Wei

2016-01-01

To solve the problem of wheel/rail rolling contact of nonlinear steady-state curving, a three-dimensional transient finite element (FE) model is developed by the explicit software ANSYS/LS-DYNA. To improve the solving speed and efficiency, an explicit-explicit order solution method is put forward based on analysis of the features of implicit and explicit algorithm. The solution method was first applied to calculate the pre-loading of wheel/rail rolling contact with explicit algorithm, and then the results became the initial conditions in solving the dynamic process of wheel/rail rolling contact with explicit algorithm as well. Simultaneously, the common implicit-explicit order solution method is used to solve the FE model. Results show that the explicit-explicit order solution method has faster operation speed and higher efficiency than the implicit-explicit order solution method while the solution accuracy is almost the same. Hence, the explicit-explicit order solution method is more suitable for the wheel/rail rolling contact model with large scale and high nonlinearity.

Explicit area-based accuracy assessment for mangrove tree crown delineation using Geographic Object-Based Image Analysis (GEOBIA)

NASA Astrophysics Data System (ADS)

Kamal, Muhammad; Johansen, Kasper

2017-10-01

Effective mangrove management requires spatially explicit information of mangrove tree crown map as a basis for ecosystem diversity study and health assessment. Accuracy assessment is an integral part of any mapping activities to measure the effectiveness of the classification approach. In geographic object-based image analysis (GEOBIA) the assessment of the geometric accuracy (shape, symmetry and location) of the created image objects from image segmentation is required. In this study we used an explicit area-based accuracy assessment to measure the degree of similarity between the results of the classification and reference data from different aspects, including overall quality (OQ), user's accuracy (UA), producer's accuracy (PA) and overall accuracy (OA). We developed a rule set to delineate the mangrove tree crown using WorldView-2 pan-sharpened image. The reference map was obtained by visual delineation of the mangrove tree crowns boundaries form a very high-spatial resolution aerial photograph (7.5cm pixel size). Ten random points with a 10 m radius circular buffer were created to calculate the area-based accuracy assessment. The resulting circular polygons were used to clip both the classified image objects and reference map for area comparisons. In this case, the area-based accuracy assessment resulted 64% and 68% for the OQ and OA, respectively. The overall quality of the calculation results shows the class-related area accuracy; which is the area of correctly classified as tree crowns was 64% out of the total area of tree crowns. On the other hand, the overall accuracy of 68% was calculated as the percentage of all correctly classified classes (tree crowns and canopy gaps) in comparison to the total class area (an entire image). Overall, the area-based accuracy assessment was simple to implement and easy to interpret. It also shows explicitly the omission and commission error variations of object boundary delineation with colour coded polygons.

Ancient trade routes shaped the genetic structure of horses in eastern Eurasia.

PubMed

Warmuth, Vera M; Campana, Michael G; Eriksson, Anders; Bower, Mim; Barker, Graeme; Manica, Andrea

2013-11-01

Animal exchange networks have been shown to play an important role in determining gene flow among domestic animal populations. The Silk Road is one of the oldest continuous exchange networks in human history, yet its effectiveness in facilitating animal exchange across large geographical distances and topographically challenging landscapes has never been explicitly studied. Horses are known to have been traded along the Silk Roads; however, extensive movement of horses in connection with other human activities may have obscured the genetic signature of the Silk Roads. To investigate the role of the Silk Roads in shaping the genetic structure of horses in eastern Eurasia, we analysed microsatellite genotyping data from 455 village horses sampled from 17 locations. Using least-cost path methods, we compared the performance of models containing the Silk Roads as corridors for gene flow with models containing single landscape features. We also determined whether the recent isolation of former Soviet Union countries from the rest of Eurasia has affected the genetic structure of our samples. The overall level of genetic differentiation was low, consistent with historically high levels of gene flow across the study region. The spatial genetic structure was characterized by a significant, albeit weak, pattern of isolation by distance across the continent with no evidence for the presence of distinct genetic clusters. Incorporating landscape features considerably improved the fit of the data; however, when we controlled for geographical distance, only the correlation between genetic differentiation and the Silk Roads remained significant, supporting the effectiveness of this ancient trade network in facilitating gene flow across large geographical distances in a topographically complex landscape. © 2013 John Wiley & Sons Ltd.

Mapping the Gulf of Maine with side-scan sonar: A new bottom-type classification for complex seafloors

USGS Publications Warehouse

Barnhardt, W.A.; Kelley, J.T.; Dickson, S.M.; Belknap, D.F.

1998-01-01

The bedrock-framed seafloor in the northwestern Gulf of Maine is characterized by extreme changes in bathymetric relief and covered with a wide variety of surficial materials. Traditional methods of mapping cannot accurately represent the great heterogeneity of such a glaciated region. A new mapping scheme for complex seafloors, based primarily on the interpretation of side-scan sonar imagery, utilizes four easily recognized units: rock, gravel, sand and mud. In many places, however, the seafloor exhibits a complicated mixture or extremely 'patchy' distribution of the four basic units, which are too small to map individually. Twelve composite units, each a two-component mixture of the basic units, were established to represent this patchiness at a small scale (1:100,000). Using a geographic information system, these and all other available data (seismic profiles, grab samples, submersible dives and cores) were referenced to a common geographic base, superimposed on bathymetric contours and then integrated into surficial geologic maps of the regional inner continental shelf. This digital representation of the seafloor comprises a multidimensional, interactive model complete with explicit attributes (depth, bottom type) that allow for detailed analysis of marine environments.

Spatially explicit models, generalized reproduction numbers and the prediction of patterns of waterborne disease

NASA Astrophysics Data System (ADS)

Rinaldo, A.; Gatto, M.; Mari, L.; Casagrandi, R.; Righetto, L.; Bertuzzo, E.; Rodriguez-Iturbe, I.

2012-12-01

Metacommunity and individual-based theoretical models are studied in the context of the spreading of infections of water-borne diseases along the ecological corridors defined by river basins and networks of human mobility. The overarching claim is that mathematical models can indeed provide predictive insight into the course of an ongoing epidemic, potentially aiding real-time emergency management in allocating health care resources and by anticipating the impact of alternative interventions. To support the claim, we examine the ex-post reliability of published predictions of the 2010-2011 Haiti cholera outbreak from four independent modeling studies that appeared almost simultaneously during the unfolding epidemic. For each modeled epidemic trajectory, it is assessed how well predictions reproduced the observed spatial and temporal features of the outbreak to date. The impact of different approaches is considered to the modeling of the spatial spread of V. cholera, the mechanics of cholera transmission and in accounting for the dynamics of susceptible and infected individuals within different local human communities. A generalized model for Haitian epidemic cholera and the related uncertainty is thus constructed and applied to the year-long dataset of reported cases now available. Specific emphasis will be dedicated to models of human mobility, a fundamental infection mechanism. Lessons learned and open issues are discussed and placed in perspective, supporting the conclusion that, despite differences in methods that can be tested through model-guided field validation, mathematical modeling of large-scale outbreaks emerges as an essential component of future cholera epidemic control. Although explicit spatial modeling is made routinely possible by widespread data mapping of hydrology, transportation infrastructure, population distribution, and sanitation, the precise condition under which a waterborne disease epidemic can start in a spatially explicit setting is still lacking. Here, we show that the requirement that all the local reproduction numbers R0 be larger than unity is neither necessary nor sufficient for outbreaks to occur when local settlements are connected by networks of primary and secondary infection mechanisms. To determine onset conditions, we derive general analytical expressions for a reproduction matrix G0 explicitly accounting for spatial distributions of human settlements and pathogen transmission via hydrological and human mobility networks. At disease onset, a generalized reproduction number Λ0 (the dominant eigenvalue of G0) must be larger than unity. We also show that geographical outbreak patterns in complex environments are linked to the dominant eigenvector and to spectral properties of G0. Tests against data and computations for the 2010 Haiti and 2000 KwaZulu-Natal cholera outbreaks, as well as against computations for metapopulation networks, demonstrate that eigenvectors of G0 provide a synthetic and effective tool for predicting the disease course in space and time. Networked connectivity models, describing the interplay between hydrology, epidemiology and social behavior sustaining human mobility, thus prove to be key tools for emergency management of waterborne infections.

The review of some chosen approaches to foresee the development of urban areas. (Polish Title: Przeglad wybranych podejsc w zakresie prognozowania rozwoju obszarow miast)

NASA Astrophysics Data System (ADS)

Radło-Kulisiewicz, M.

2015-12-01

The practical importance of Geographical Information Systems in urban planning and managing of urban areas is becoming much more explicit. Managing small cities usually needs simple GIS spatial analysis tools to support planners' decisions. Otherwise, the urban dynamic is bigger and factors affecting changes in city are combined. These analyses are not sufficient and then a need for more advanced and sophisticated solutions can appear. The aim of this article is to introduce popular techniques for urban modelling and underlying importance of GIS as an environment for creating simple models, which let t easy decisions in creating vision of a city be taken. The Article touches on the following issues related to the planning and management of urban space; from the applicable standards concerning materials planning in Poland, through the possibilities that give us network solutions useful at the municipal and country level, to existing techniques in modelling cities in the world. The background for these questions are the Geographical Information Systems (their role in this respect), that naturally fit into this theme. The ability to analyze multi-source data at different levels of detail, in different variants and ranges, predispose the GIS to environmental urban management. While also taking into account social - economic factors, integrated with GIS predictive modeling techniques, allows us to understand dependencies that navigate complex urban phenomena. City management in an integrated and thoughtful manner and will reduce the costs associated with the expansion of the urban fabric and avoid the chaos of urban development.

Phylogeographic analysis and environmental niche modeling of the plain-bellied watersnake (Nerodia erythrogaster) reveals low levels of genetic and ecological differentiation

PubMed Central

Makowsky, Robert; Marshall, John C.; McVay, John; Chippindale, Paul T.; Rissler, Leslie J.

2012-01-01

Species that exhibit geographically defined phenotypic variation traditionally have been divided into subspecies. Subspecies based on phenotypic features may not comprise monophyletic groups due to selection, gene flow, and/or convergent evolution. In many taxonomic groups the number of species once designated as widespread is dwindling rapidly, and many workers reject the concept of subspecies altogether. We tested whether currently recognized subspecies in the plain-bellied watersnake Nerodia erythrogaster are concordant with relationships based on mitochondrial markers, and whether it represents a single widespread species. The range of this taxon spans multiple potential biogeographic barriers (especially the Mississippi and Apalachicola Rivers) that correspond with lineage breaks in many species, including other snakes. We sequenced three mitochondrialgenes (NADH-II, Cyt-b, Cox-I) from 156 geo-referenced specimens and developed ecological niche models using Maxent and spatially-explicit climate data to examine historical and ecological factors affecting variation in N. erythrogaster across its range. Overall, we found little support for the recognized subspecies as either independent evolutionary lineages or geographically circumscribed units and conclude that although some genetic and niche differentiation has occurred, most populations assigned to N. erythrogaster appear to represent a single, widespread species. However, additional sampling and application of nuclear markers are necessary to clarify the status of the easternmost populations. PMID:20302955

Including Fossils in Phylogenetic Climate Reconstructions: A Deep Time Perspective on the Climatic Niche Evolution and Diversification of Spiny Lizards (Sceloporus).

PubMed

Lawing, A Michelle; Polly, P David; Hews, Diana K; Martins, Emília P

2016-08-01

Fossils and other paleontological information can improve phylogenetic comparative method estimates of phenotypic evolution and generate hypotheses related to species diversification. Here, we use fossil information to calibrate ancestral reconstructions of suitable climate for Sceloporus lizards in North America. Integrating data from the fossil record, general circulation models of paleoclimate during the Miocene, climate envelope modeling, and phylogenetic comparative methods provides a geographically and temporally explicit species distribution model of Sceloporus-suitable habitat through time. We provide evidence to support the historic biogeographic hypothesis of Sceloporus diversification in warm North American deserts and suggest a relatively recent Sceloporus invasion into Mexico around 6 Ma. We use a physiological model to map extinction risk. We suggest that the number of hours of restriction to a thermal refuge limited Sceloporus from inhabiting Mexico until the climate cooled enough to provide suitable habitat at approximately 6 Ma. If the future climate returns to the hotter climates of the past, Mexico, the place of highest modern Sceloporus richness, will no longer provide suitable habitats for Sceloporus to survive and reproduce.

Anticipating the unintended consequences of security dynamics.

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

Backus, George A.; Overfelt, James Robert; Malczynski, Leonard A.

2010-01-01

In a globalized world, dramatic changes within any one nation causes ripple or even tsunamic effects within neighbor nations and nations geographically far removed. Multinational interventions to prevent or mitigate detrimental changes can easily cause secondary unintended consequences more detrimental and enduring than the feared change instigating the intervention. This LDRD research developed the foundations for a flexible geopolitical and socioeconomic simulation capability that focuses on the dynamic national security implications of natural and man-made trauma for a nation-state and the states linked to it through trade or treaty. The model developed contains a database for simulating all 229 recognizedmore » nation-states and sovereignties with the detail of 30 economic sectors including consumers and natural resources. The model explicitly simulates the interactions among the countries and their governments. Decisions among governments and populations is based on expectation formation. In the simulation model, failed expectations are used as a key metric for tension across states, among ethnic groups, and between population factions. This document provides the foundational documentation for the model.« less

Quantifying inter- and intra-population niche variability using hierarchical bayesian stable isotope mixing models.

PubMed

Semmens, Brice X; Ward, Eric J; Moore, Jonathan W; Darimont, Chris T

2009-07-09

Variability in resource use defines the width of a trophic niche occupied by a population. Intra-population variability in resource use may occur across hierarchical levels of population structure from individuals to subpopulations. Understanding how levels of population organization contribute to population niche width is critical to ecology and evolution. Here we describe a hierarchical stable isotope mixing model that can simultaneously estimate both the prey composition of a consumer diet and the diet variability among individuals and across levels of population organization. By explicitly estimating variance components for multiple scales, the model can deconstruct the niche width of a consumer population into relevant levels of population structure. We apply this new approach to stable isotope data from a population of gray wolves from coastal British Columbia, and show support for extensive intra-population niche variability among individuals, social groups, and geographically isolated subpopulations. The analytic method we describe improves mixing models by accounting for diet variability, and improves isotope niche width analysis by quantitatively assessing the contribution of levels of organization to the niche width of a population.

Modeling aesthetics to support an ecosystem services approach for natural resource management decision making.

PubMed

Booth, Pieter N; Law, Sheryl A; Ma, Jane; Buonagurio, John; Boyd, James; Turnley, Jessica

2017-09-01

This paper reviews literature on aesthetics and describes the development of vista and landscape aesthetics models. Spatially explicit variables were chosen to represent physical characteristics of natural landscapes that are important to aesthetic preferences. A vista aesthetics model evaluates the aesthetics of natural landscapes viewed from distances of more than 1000 m, and a landscape aesthetics model evaluates the aesthetic value of wetlands and forests within 1000 m from the viewer. Each of the model variables is quantified using spatially explicit metrics on a pixel-specific basis within EcoAIM™, a geographic information system (GIS)-based ecosystem services (ES) decision analysis support tool. Pixel values are "binned" into ranked categories, and weights are assigned to select variables to represent stakeholder preferences. The final aesthetic score is the weighted sum of all variables and is assigned ranked values from 1 to 10. Ranked aesthetic values are displayed on maps by patch type and integrated within EcoAIM. The response of the aesthetic scoring in the models was tested by comparing current conditions in a discrete area of the facility with a Development scenario in the same area. The Development scenario consisted of two 6-story buildings and a trail replacing natural areas. The results of the vista aesthetic model indicate that the viewshed area variable had the greatest effect on the aesthetics overall score. Results from the landscape aesthetics model indicate a 10% increase in overall aesthetics value, attributed to the increase in landscape diversity. The models are sensitive to the weights assigned to certain variables by the user, and these weights should be set to reflect regional landscape characteristics as well as stakeholder preferences. This demonstration project shows that natural landscape aesthetics can be evaluated as part of a nonmonetary assessment of ES, and a scenario-building exercise provides end users with a tradeoff analysis in support of natural resource management decisions. Integr Environ Assess Manag 2017;13:926-938. © 2017 SETAC. © 2017 SETAC.

Habitat evaluation using GIS a case study applied to the San Joaquin Kit Fox

USGS Publications Warehouse

Gerrard, R.; Stine, P.; Church, R.; Gilpin, M.

2001-01-01

Concern over the fate of plant and animal species throughout the world has accelerated over recent decades. Habitat loss is considered the main culprit in reducing many species' abundance and range, leading to numerous efforts to plan and manage habitat preservation. Our work uses Geographic Information Systems (GIS) data and modeling to define a spatially explicit analysis of habitat value, using the San Joaquin Kit Fox (Vulpes macrotis mutica) of California (USA) as an example. Over the last 30 years, many field studies and surveys have enhanced our knowledge of the life history, behavior, and needs of the kit fox, which has been proposed as an umbrella or indicator species for grassland habitat in the San Joaquin Valley of California. There has yet been no attempt to convert much of this field knowledge into a model of spatial habitat value useful for planning purposes. This is a significant omission given the importance and visibility of the imperiled kit fox and increasing trends toward spatially explicit modeling and planning. In this paper we apply data from northern California to derive a small-cell GIS raster of habitat value for the kit fox that incorporates both intrinsic habitat quality and neighborhood context, as well the effects of barriers such as roads. Such a product is a useful basis for assessing the presence and amounts of good (and poor) quality habitat and for eventually constructing GIS representations of viable animal territories that could be included in future reserves. ?? 2001 Elsevier Science B.V.

Effects of explicit convection on global land-atmosphere coupling in the superparameterized CAM

DOE PAGES

Sun, Jian; Pritchard, Michael S.

2016-07-25

Here, conventional global climate models are prone to producing unrealistic land-atmosphere coupling signals. Cumulus and convection parameterizations are natural culprits but the effect of bypassing them with explicitly resolved convection on global land-atmosphere coupling dynamics has not been explored systematically. We apply a suite of modern land-atmosphere coupling diagnostics to isolate the effect of cloud Superparameterization in the Community Atmosphere Model (SPCAM) v3.5, focusing on both the terrestrial segment (i.e., soil moisture and surface turbulent fluxes interaction) and atmospheric segment (i.e., surface turbulent fluxes and precipitation interaction) in the water pathway of the landatmosphere feedback loop. At daily timescales, SPCAMmore » produces stronger uncoupled terrestrial signals (negative sign) over tropical rainforests in wet seasons, reduces the terrestrial coupling strength in the Central Great Plain in American, and reverses the coupling sign (from negative to positive) over India in the boreal summer season—all favorable improvements relative to reanalysis-forced land modeling. Analysis of the triggering feedback strength (TFS) and amplification feedback strength (AFS) shows that SPCAM favorably reproduces the observed geographic patterns of these indices over North America, with the probability of afternoon precipitation enhanced by high evaporative fraction along the eastern United States and Mexico, while conventional CAM does not capture this signal. We introduce a new diagnostic called the Planetary Boundary Layer (PBL) Feedback Strength (PFS), which reveals that SPCAM exhibits a tight connection between the responses of the lifting condensation level, the PBL height, and the rainfall triggering to surface turbulent fluxes; a triggering disconnect is found in CAM.« less

Effects of explicit convection on global land-atmosphere coupling in the superparameterized CAM

NASA Astrophysics Data System (ADS)

Sun, Jian; Pritchard, Michael S.

2016-09-01

Conventional global climate models are prone to producing unrealistic land-atmosphere coupling signals. Cumulus and convection parameterizations are natural culprits but the effect of bypassing them with explicitly resolved convection on global land-atmosphere coupling dynamics has not been explored systematically. We apply a suite of modern land-atmosphere coupling diagnostics to isolate the effect of cloud Superparameterization in the Community Atmosphere Model (SPCAM) v3.5, focusing on both the terrestrial segment (i.e., soil moisture and surface turbulent fluxes interaction) and atmospheric segment (i.e., surface turbulent fluxes and precipitation interaction) in the water pathway of the land-atmosphere feedback loop. At daily timescales, SPCAM produces stronger uncoupled terrestrial signals (negative sign) over tropical rainforests in wet seasons, reduces the terrestrial coupling strength in the Central Great Plain in American, and reverses the coupling sign (from negative to positive) over India in the boreal summer season—all favorable improvements relative to reanalysis-forced land modeling. Analysis of the triggering feedback strength (TFS) and amplification feedback strength (AFS) shows that SPCAM favorably reproduces the observed geographic patterns of these indices over North America, with the probability of afternoon precipitation enhanced by high evaporative fraction along the eastern United States and Mexico, while conventional CAM does not capture this signal. We introduce a new diagnostic called the Planetary Boundary Layer (PBL) Feedback Strength (PFS), which reveals that SPCAM exhibits a tight connection between the responses of the lifting condensation level, the PBL height, and the rainfall triggering to surface turbulent fluxes; a triggering disconnect is found in CAM.

Effects of explicit convection on global land-atmosphere coupling in the superparameterized CAM

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

Sun, Jian; Pritchard, Michael S.

Here, conventional global climate models are prone to producing unrealistic land-atmosphere coupling signals. Cumulus and convection parameterizations are natural culprits but the effect of bypassing them with explicitly resolved convection on global land-atmosphere coupling dynamics has not been explored systematically. We apply a suite of modern land-atmosphere coupling diagnostics to isolate the effect of cloud Superparameterization in the Community Atmosphere Model (SPCAM) v3.5, focusing on both the terrestrial segment (i.e., soil moisture and surface turbulent fluxes interaction) and atmospheric segment (i.e., surface turbulent fluxes and precipitation interaction) in the water pathway of the landatmosphere feedback loop. At daily timescales, SPCAMmore » produces stronger uncoupled terrestrial signals (negative sign) over tropical rainforests in wet seasons, reduces the terrestrial coupling strength in the Central Great Plain in American, and reverses the coupling sign (from negative to positive) over India in the boreal summer season—all favorable improvements relative to reanalysis-forced land modeling. Analysis of the triggering feedback strength (TFS) and amplification feedback strength (AFS) shows that SPCAM favorably reproduces the observed geographic patterns of these indices over North America, with the probability of afternoon precipitation enhanced by high evaporative fraction along the eastern United States and Mexico, while conventional CAM does not capture this signal. We introduce a new diagnostic called the Planetary Boundary Layer (PBL) Feedback Strength (PFS), which reveals that SPCAM exhibits a tight connection between the responses of the lifting condensation level, the PBL height, and the rainfall triggering to surface turbulent fluxes; a triggering disconnect is found in CAM.« less

Spatiotemporal variability of urban growth factors: A global and local perspective on the megacity of Mumbai

NASA Astrophysics Data System (ADS)

Shafizadeh-Moghadam, Hossein; Helbich, Marco

2015-03-01

The rapid growth of megacities requires special attention among urban planners worldwide, and particularly in Mumbai, India, where growth is very pronounced. To cope with the planning challenges this will bring, developing a retrospective understanding of urban land-use dynamics and the underlying driving-forces behind urban growth is a key prerequisite. This research uses regression-based land-use change models - and in particular non-spatial logistic regression models (LR) and auto-logistic regression models (ALR) - for the Mumbai region over the period 1973-2010, in order to determine the drivers behind spatiotemporal urban expansion. Both global models are complemented by a local, spatial model, the so-called geographically weighted logistic regression (GWLR) model, one that explicitly permits variations in driving-forces across space. The study comes to two main conclusions. First, both global models suggest similar driving-forces behind urban growth over time, revealing that LRs and ALRs result in estimated coefficients with comparable magnitudes. Second, all the local coefficients show distinctive temporal and spatial variations. It is therefore concluded that GWLR aids our understanding of urban growth processes, and so can assist context-related planning and policymaking activities when seeking to secure a sustainable urban future.

Role of animal movement and indirect contact among farms in transmission of porcine epidemic diarrhea virus.

PubMed

VanderWaal, Kimberly; Perez, Andres; Torremorrell, Montse; Morrison, Robert M; Craft, Meggan

2018-04-12

Epidemiological models of the spread of pathogens in livestock populations primarily focus on direct contact between farms based on animal movement data, and in some cases, local spatial spread based on proximity between premises. The roles of other types of indirect contact among farms is rarely accounted for. In addition, data on animal movements is seldom available in the United States. However, the spread of porcine epidemic diarrhea virus (PEDv) in U.S. swine represents one of the best documented emergences of a highly infectious pathogen in the U.S. livestock industry, providing an opportunity to parameterize models of pathogen spread via direct and indirect transmission mechanisms in swine. Using observed data on pig movements during the initial phase of the PEDv epidemic, we developed a network-based and spatially explicit epidemiological model that simulates the spread of PEDv via both indirect and direct movement-related contact in order to answer unresolved questions concerning factors facilitating between-farm transmission. By modifying the likelihood of each transmission mechanism and fitting this model to observed epidemiological dynamics, our results suggest that between-farm transmission was primarily driven by direct mechanisms related to animal movement and indirect mechanisms related to local spatial spread based on geographic proximity. However, other forms of indirect transmission among farms, including contact via contaminated vehicles and feed, were responsible for high consequence transmission events resulting in the introduction of the virus into new geographic areas. This research is among the first reports of farm-level animal movements in the U.S. swine industry and, to our knowledge, represents the first epidemiological model of commercial U.S. swine using actual data on farm-level animal movement. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Novel probabilistic models of spatial genetic ancestry with applications to stratification correction in genome-wide association studies.

PubMed

Bhaskar, Anand; Javanmard, Adel; Courtade, Thomas A; Tse, David

2017-03-15

Genetic variation in human populations is influenced by geographic ancestry due to spatial locality in historical mating and migration patterns. Spatial population structure in genetic datasets has been traditionally analyzed using either model-free algorithms, such as principal components analysis (PCA) and multidimensional scaling, or using explicit spatial probabilistic models of allele frequency evolution. We develop a general probabilistic model and an associated inference algorithm that unify the model-based and data-driven approaches to visualizing and inferring population structure. Our spatial inference algorithm can also be effectively applied to the problem of population stratification in genome-wide association studies (GWAS), where hidden population structure can create fictitious associations when population ancestry is correlated with both the genotype and the trait. Our algorithm Geographic Ancestry Positioning (GAP) relates local genetic distances between samples to their spatial distances, and can be used for visually discerning population structure as well as accurately inferring the spatial origin of individuals on a two-dimensional continuum. On both simulated and several real datasets from diverse human populations, GAP exhibits substantially lower error in reconstructing spatial ancestry coordinates compared to PCA. We also develop an association test that uses the ancestry coordinates inferred by GAP to accurately account for ancestry-induced correlations in GWAS. Based on simulations and analysis of a dataset of 10 metabolic traits measured in a Northern Finland cohort, which is known to exhibit significant population structure, we find that our method has superior power to current approaches. Our software is available at https://github.com/anand-bhaskar/gap . abhaskar@stanford.edu or ajavanma@usc.edu. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Geographical Inequalities in Use of Improved Drinking Water Supply and Sanitation across Sub-Saharan Africa: Mapping and Spatial Analysis of Cross-sectional Survey Data

PubMed Central

Pullan, Rachel L.; Freeman, Matthew C.; Gething, Peter W.; Brooker, Simon J.

2014-01-01

Background Understanding geographic inequalities in coverage of drinking-water supply and sanitation (WSS) will help track progress towards universal coverage of water and sanitation by identifying marginalized populations, thus helping to control a large number of infectious diseases. This paper uses household survey data to develop comprehensive maps of WSS coverage at high spatial resolution for sub-Saharan Africa (SSA). Analysis is extended to investigate geographic heterogeneity and relative geographic inequality within countries. Methods and Findings Cluster-level data on household reported use of improved drinking-water supply, sanitation, and open defecation were abstracted from 138 national surveys undertaken from 1991–2012 in 41 countries. Spatially explicit logistic regression models were developed and fitted within a Bayesian framework, and used to predict coverage at the second administrative level (admin2, e.g., district) across SSA for 2012. Results reveal substantial geographical inequalities in predicted use of water and sanitation that exceed urban-rural disparities. The average range in coverage seen between admin2 within countries was 55% for improved drinking water, 54% for use of improved sanitation, and 59% for dependence upon open defecation. There was also some evidence that countries with higher levels of inequality relative to coverage in use of an improved drinking-water source also experienced higher levels of inequality in use of improved sanitation (rural populations r = 0.47, p = 0.002; urban populations r = 0.39, p = 0.01). Results are limited by the quantity of WSS data available, which varies considerably by country, and by the reliability and utility of available indicators. Conclusions This study identifies important geographic inequalities in use of WSS previously hidden within national statistics, confirming the necessity for targeted policies and metrics that reach the most marginalized populations. The presented maps and analysis approach can provide a mechanism for monitoring future reductions in inequality within countries, reflecting priorities of the post-2015 development agenda. Please see later in the article for the Editors' Summary PMID:24714528

Geographical inequalities in use of improved drinking water supply and sanitation across Sub-Saharan Africa: mapping and spatial analysis of cross-sectional survey data.

PubMed

Pullan, Rachel L; Freeman, Matthew C; Gething, Peter W; Brooker, Simon J

2014-04-01

Understanding geographic inequalities in coverage of drinking-water supply and sanitation (WSS) will help track progress towards universal coverage of water and sanitation by identifying marginalized populations, thus helping to control a large number of infectious diseases. This paper uses household survey data to develop comprehensive maps of WSS coverage at high spatial resolution for sub-Saharan Africa (SSA). Analysis is extended to investigate geographic heterogeneity and relative geographic inequality within countries. Cluster-level data on household reported use of improved drinking-water supply, sanitation, and open defecation were abstracted from 138 national surveys undertaken from 1991-2012 in 41 countries. Spatially explicit logistic regression models were developed and fitted within a Bayesian framework, and used to predict coverage at the second administrative level (admin2, e.g., district) across SSA for 2012. Results reveal substantial geographical inequalities in predicted use of water and sanitation that exceed urban-rural disparities. The average range in coverage seen between admin2 within countries was 55% for improved drinking water, 54% for use of improved sanitation, and 59% for dependence upon open defecation. There was also some evidence that countries with higher levels of inequality relative to coverage in use of an improved drinking-water source also experienced higher levels of inequality in use of improved sanitation (rural populations r = 0.47, p = 0.002; urban populations r = 0.39, p = 0.01). Results are limited by the quantity of WSS data available, which varies considerably by country, and by the reliability and utility of available indicators. This study identifies important geographic inequalities in use of WSS previously hidden within national statistics, confirming the necessity for targeted policies and metrics that reach the most marginalized populations. The presented maps and analysis approach can provide a mechanism for monitoring future reductions in inequality within countries, reflecting priorities of the post-2015 development agenda. Please see later in the article for the Editors' Summary.

Hydroclimatology of Dual-Peak Annual Cholera Incidence: Insights from a Spatially Explicit Model

NASA Astrophysics Data System (ADS)

Bertuzzo, E.; Mari, L.; Righetto, L.; Gatto, M.; Casagrandi, R.; Rodriguez-Iturbe, I.; Rinaldo, A.

2012-12-01

Cholera incidence in some regions of the Indian subcontinent may exhibit two annual peaks although the main environmental drivers that have been linked to the disease (e.g. sea surface temperature, zooplankton abundance, river discharge) peak once per year during the summer. An empirical hydroclimatological explanation relating cholera transmission to river flows and to the disease spatial spreading has been recently proposed. We specifically support and substantiate mechanistically such hypothesis by means of a spatially explicit model of cholera transmission. Our framework directly accounts for the role of the river network in transporting and redistributing cholera bacteria among human communities as well as for spatial and temporal annual fluctuations of precipitation and river flows. To single out the single out the hydroclimatologic controls on the prevalence patterns in a non-specific geographical context, we first apply the model to Optimal Channel Networks as a general model of hydrological networks. Moreover, we impose a uniform distribution of population. The model is forced by seasonal environmental drivers, namely precipitation, temperature and chlorophyll concentration in the coastal environment, a proxy for Vibrio cholerae concentration. Our results show that these drivers may suffice to generate dual-peak cholera prevalence patterns for proper combinations of timescales involved in pathogen transport, hydrologic variability and disease unfolding. The model explains the possible occurrence of spatial patterns of cholera incidence characterized by a spring peak confined to coastal areas and a fall peak involving inland regions. We then proceed applying the model to the specific settings of Bay of Bengal accounting for the actual river networks (derived from digital terrain map manipulations), the proper distribution of population (estimated from downscaling of census data based on remotely sensed features) and precipitation patterns. Overall our modeling framework suggests insights on how environmental drivers concert the generation of complex spatiotemporal infections and proposes an explanation for the different cholera patterns (dual or single annual peaks) exhibited by regions that share similar hydroclimatological forcings.

An evaluation of the performance of a WRF multi-physics ensemble for heatwave events over the city of Melbourne in southeast Australia

NASA Astrophysics Data System (ADS)

Imran, H. M.; Kala, J.; Ng, A. W. M.; Muthukumaran, S.

2018-04-01

Appropriate choice of physics options among many physics parameterizations is important when using the Weather Research and Forecasting (WRF) model. The responses of different physics parameterizations of the WRF model may vary due to geographical locations, the application of interest, and the temporal and spatial scales being investigated. Several studies have evaluated the performance of the WRF model in simulating the mean climate and extreme rainfall events for various regions in Australia. However, no study has explicitly evaluated the sensitivity of the WRF model in simulating heatwaves. Therefore, this study evaluates the performance of a WRF multi-physics ensemble that comprises 27 model configurations for a series of heatwave events in Melbourne, Australia. Unlike most previous studies, we not only evaluate temperature, but also wind speed and relative humidity, which are key factors influencing heatwave dynamics. No specific ensemble member for all events explicitly showed the best performance, for all the variables, considering all evaluation metrics. This study also found that the choice of planetary boundary layer (PBL) scheme had largest influence, the radiation scheme had moderate influence, and the microphysics scheme had the least influence on temperature simulations. The PBL and microphysics schemes were found to be more sensitive than the radiation scheme for wind speed and relative humidity. Additionally, the study tested the role of Urban Canopy Model (UCM) and three Land Surface Models (LSMs). Although the UCM did not play significant role, the Noah-LSM showed better performance than the CLM4 and NOAH-MP LSMs in simulating the heatwave events. The study finally identifies an optimal configuration of WRF that will be a useful modelling tool for further investigations of heatwaves in Melbourne. Although our results are invariably region-specific, our results will be useful to WRF users investigating heatwave dynamics elsewhere.

Proximal Association of Land Management Preferences: Evidence from Family Forest Owners

PubMed Central

Aguilar, Francisco X.; Cai, Zhen; Butler, Brett

2017-01-01

Individual behavior is influenced by factors intrinsic to the decision-maker but also associated with other individuals and their ownerships with such relationship intensified by geographic proximity. The land management literature is scarce in the spatially integrated analysis of biophysical and socio-economic data. Localized land management decisions are likely driven by spatially-explicit but often unobserved resource conditions, influenced by an individual’s own characteristics, proximal lands and fellow owners. This study examined stated choices over the management of family-owned forests as an example of a resource that captures strong pecuniary and non-pecuniary values with identifiable decision makers. An autoregressive model controlled for spatially autocorrelated willingness-to-harvest (WTH) responses using a sample of residential and absentee family forest owners from the U.S. State of Missouri. WTH responses were largely explained by affective, cognitive and experience variables including timber production objectives and past harvest experience. Demographic variables, including income and age, were associated with WTH and helped define socially-proximal groups. The group of closest identity was comprised of resident males over 55 years of age with annual income of at least $50,000. Spatially-explicit models showed that indirect impacts, capturing spillover associations, on average accounted for 14% of total marginal impacts among statistically significant explanatory variables. We argue that not all proximal family forest owners are equal and owners-in-absentia have discernible differences in WTH preferences with important implications for public policy and future research. PMID:28060960

A coupled modeling framework for sustainable watershed management in transboundary river basins

NASA Astrophysics Data System (ADS)

Furqan Khan, Hassaan; Yang, Y. C. Ethan; Xie, Hua; Ringler, Claudia

2017-12-01

There is a growing recognition among water resource managers that sustainable watershed management needs to not only account for the diverse ways humans benefit from the environment, but also incorporate the impact of human actions on the natural system. Coupled natural-human system modeling through explicit modeling of both natural and human behavior can help reveal the reciprocal interactions and co-evolution of the natural and human systems. This study develops a spatially scalable, generalized agent-based modeling (ABM) framework consisting of a process-based semi-distributed hydrologic model (SWAT) and a decentralized water system model to simulate the impacts of water resource management decisions that affect the food-water-energy-environment (FWEE) nexus at a watershed scale. Agents within a river basin are geographically delineated based on both political and watershed boundaries and represent key stakeholders of ecosystem services. Agents decide about the priority across three primary water uses: food production, hydropower generation and ecosystem health within their geographical domains. Agents interact with the environment (streamflow) through the SWAT model and interact with other agents through a parameter representing willingness to cooperate. The innovative two-way coupling between the water system model and SWAT enables this framework to fully explore the feedback of human decisions on the environmental dynamics and vice versa. To support non-technical stakeholder interactions, a web-based user interface has been developed that allows for role-play and participatory modeling. The generalized ABM framework is also tested in two key transboundary river basins, the Mekong River basin in Southeast Asia and the Niger River basin in West Africa, where water uses for ecosystem health compete with growing human demands on food and energy resources. We present modeling results for crop production, energy generation and violation of eco-hydrological indicators at both the agent and basin-wide levels to shed light on holistic FWEE management policies in these two basins.

Utility assessment of a map-based online geo-collaboration tool.

PubMed

Sidlar, Christopher L; Rinner, Claus

2009-05-01

Spatial group decision-making processes often include both informal and analytical components. Discussions among stakeholders or planning experts are an example of an informal component. When participants discuss spatial planning projects they typically express concerns and comments by pointing to places on a map. The Argumentation Map model provides a conceptual basis for collaborative tools that enable explicit linkages of arguments to the places to which they refer. These tools allow for the input of explicitly geo-referenced arguments as well as the visual access to arguments through a map interface. In this paper, we will review previous utility studies in geo-collaboration and evaluate a case study of a Web-based Argumentation Map application. The case study was conducted in the summer of 2005 when student participants discussed planning issues on the University of Toronto St. George campus. During a one-week unmoderated discussion phase, 11 participants wrote 60 comments on issues such as safety, facilities, parking, and building aesthetics. By measuring the participants' use of geographic references, we draw conclusions on how well the software tool supported the potential of the underlying concept. This research aims to contribute to a scientific approach to geo-collaboration in which the engineering of novel spatial decision support methods is complemented by a critical assessment of their utility in controlled, realistic experiments.

Process-Based Species Pools Reveal the Hidden Signature of Biotic Interactions Amid the Influence of Temperature Filtering.

PubMed

Lessard, Jean-Philippe; Weinstein, Ben G; Borregaard, Michael K; Marske, Katharine A; Martin, Danny R; McGuire, Jimmy A; Parra, Juan L; Rahbek, Carsten; Graham, Catherine H

2016-01-01

A persistent challenge in ecology is to tease apart the influence of multiple processes acting simultaneously and interacting in complex ways to shape the structure of species assemblages. We implement a heuristic approach that relies on explicitly defining species pools and permits assessment of the relative influence of the main processes thought to shape assemblage structure: environmental filtering, dispersal limitations, and biotic interactions. We illustrate our approach using data on the assemblage composition and geographic distribution of hummingbirds, a comprehensive phylogeny and morphological traits. The implementation of several process-based species pool definitions in null models suggests that temperature-but not precipitation or dispersal limitation-acts as the main regional filter of assemblage structure. Incorporating this environmental filter directly into the definition of assemblage-specific species pools revealed an otherwise hidden pattern of phylogenetic evenness, indicating that biotic interactions might further influence hummingbird assemblage structure. Such hidden patterns of assemblage structure call for a reexamination of a multitude of phylogenetic- and trait-based studies that did not explicitly consider potentially important processes in their definition of the species pool. Our heuristic approach provides a transparent way to explore patterns and refine interpretations of the underlying causes of assemblage structure.

Facing uncertainty in ecosystem services-based resource management.

PubMed

Grêt-Regamey, Adrienne; Brunner, Sibyl H; Altwegg, Jürg; Bebi, Peter

2013-09-01

The concept of ecosystem services is increasingly used as a support for natural resource management decisions. While the science for assessing ecosystem services is improving, appropriate methods to address uncertainties in a quantitative manner are missing. Ignoring parameter uncertainties, modeling uncertainties and uncertainties related to human-environment interactions can modify decisions and lead to overlooking important management possibilities. In this contribution, we present a new approach for mapping the uncertainties in the assessment of multiple ecosystem services. The spatially explicit risk approach links Bayesian networks to a Geographic Information System for forecasting the value of a bundle of ecosystem services and quantifies the uncertainties related to the outcomes in a spatially explicit manner. We demonstrate that mapping uncertainties in ecosystem services assessments provides key information for decision-makers seeking critical areas in the delivery of ecosystem services in a case study in the Swiss Alps. The results suggest that not only the total value of the bundle of ecosystem services is highly dependent on uncertainties, but the spatial pattern of the ecosystem services values changes substantially when considering uncertainties. This is particularly important for the long-term management of mountain forest ecosystems, which have long rotation stands and are highly sensitive to pressing climate and socio-economic changes. Copyright © 2012 Elsevier Ltd. All rights reserved.

The uncertain role of diversity dependence in species diversification and the need to incorporate time-varying carrying capacities

PubMed Central

Marshall, Charles R.; Quental, Tiago B.

2016-01-01

There is no agreement among palaeobiologists or biologists as to whether, or to what extent, there are limits on diversification and species numbers. Here, we posit that part of the disagreement stems from: (i) the lack of explicit criteria for defining the relevant species pools, which may be defined phylogenetically, ecologically or geographically; (ii) assumptions that must be made when extrapolating from population-level logistic growth to macro-evolutionary diversification; and (iii) too much emphasis being placed on fixed carrying capacities, rather than taking into account the opportunities for increased species richness on evolutionary timescales, for example, owing to increased biologically available energy, increased habitat complexity and the ability of many clades to better extract resources from the environment, or to broaden their resource base. Thus, we argue that a more effective way of assessing the evidence for and against the ideas of bound versus unbound diversification is through appropriate definition of the relevant species pools, and through explicit modelling of diversity-dependent diversification with time-varying carrying capacities. Here, we show that time-varying carrying capacities, either increases or decreases, can be accommodated through changing intrinsic diversification rates (diversity-independent effects), or changing the effects of crowding (diversity-dependent effects). PMID:26977059

Explicitly represented polygon wall boundary model for the explicit MPS method

NASA Astrophysics Data System (ADS)

Mitsume, Naoto; Yoshimura, Shinobu; Murotani, Kohei; Yamada, Tomonori

2015-05-01

This study presents an accurate and robust boundary model, the explicitly represented polygon (ERP) wall boundary model, to treat arbitrarily shaped wall boundaries in the explicit moving particle simulation (E-MPS) method, which is a mesh-free particle method for strong form partial differential equations. The ERP model expresses wall boundaries as polygons, which are explicitly represented without using the distance function. These are derived so that for viscous fluids, and with less computational cost, they satisfy the Neumann boundary condition for the pressure and the slip/no-slip condition on the wall surface. The proposed model is verified and validated by comparing computed results with the theoretical solution, results obtained by other models, and experimental results. Two simulations with complex boundary movements are conducted to demonstrate the applicability of the E-MPS method to the ERP model.

Transfers to the old, government debt and demographic change.

PubMed

Verbon, H A

1990-01-01

"In this paper we take the view that policy makers...take the relationship between (explicit) intergenerational transfer systems (including public pension schemes) and government deficits into account. It is assumed that policy makers are behaving altruistically towards past and future generations. Given the behavioral model, an analysis is made of the effects of demographic changes (such as the 'baby-boom' of the 1940s and 1950s and the decline of birth rates in the 1970s) on the decisions to be taken with respect to the tax rate of the public pension system and the size of government debt. From the analysis it appears that, with the assumption of altruistic decision-makers, periods of increasing or decreasing debt can occur alternately in periods of demographic change." The geographical focus is on developed countries. excerpt

Forest dynamics to precipitation and temperature in the Gulf of Mexico coastal region.

PubMed

Li, Tianyu; Meng, Qingmin

2017-05-01

The forest is one of the most significant components of the Gulf of Mexico (GOM) coast. It provides livelihood to inhabitant and is known to be sensitive to climatic fluctuations. This study focuses on examining the impacts of temperature and precipitation variations on coastal forest. Two different regression methods, ordinary least squares (OLS) and geographically weighted regression (GWR), were employed to reveal the relationship between meteorological variables and forest dynamics. OLS regression analysis shows that changes in precipitation and temperature, over a span of 12 months, are responsible for 56% of NDVI variation. The forest, which is not particularly affected by the average monthly precipitation in most months, is observed to be affected by cumulative seasonal and annual precipitation explicitly. Temperature and precipitation almost equally impact on NDVI changes; about 50% of the NDVI variations is explained in OLS modeling, and about 74% of the NDVI variations is explained in GWR modeling. GWR analysis indicated that both precipitation and temperature characterize the spatial heterogeneity patterns of forest dynamics.

The impact of strain-specific immunity on Lyme disease incidence is spatially heterogeneous.

PubMed

Khatchikian, Camilo E; Nadelman, Robert B; Nowakowski, John; Schwartz, Ira; Wormser, Gary P; Brisson, Dustin

2017-12-01

Lyme disease, caused by the bacterium Borrelia burgdorferi, is the most common tick-borne infection in the US. Recent studies have demonstrated that the incidence of human Lyme disease would have been even greater were it not for the presence of strain-specific immunity, which protects previously infected patients against subsequent infections by the same B. burgdorferi strain. Here, spatial heterogeneity is incorporated into epidemiological models to accurately estimate the impact of strain-specific immunity on human Lyme disease incidence. The estimated reduction in the number of Lyme disease cases is greater in epidemiologic models that explicitly include the spatial distribution of Lyme disease cases reported at the county level than those that utilize nationwide data. strain-specific immunity has the greatest epidemiologic impact in geographic areas with the highest Lyme disease incidence due to the greater proportion of people that have been previously infected and have developed strain-specific immunity. Copyright © 2017 Elsevier Inc. All rights reserved.

Forest dynamics to precipitation and temperature in the Gulf of Mexico coastal region

NASA Astrophysics Data System (ADS)

Li, Tianyu; Meng, Qingmin

2017-05-01

The forest is one of the most significant components of the Gulf of Mexico (GOM) coast. It provides livelihood to inhabitant and is known to be sensitive to climatic fluctuations. This study focuses on examining the impacts of temperature and precipitation variations on coastal forest. Two different regression methods, ordinary least squares (OLS) and geographically weighted regression (GWR), were employed to reveal the relationship between meteorological variables and forest dynamics. OLS regression analysis shows that changes in precipitation and temperature, over a span of 12 months, are responsible for 56% of NDVI variation. The forest, which is not particularly affected by the average monthly precipitation in most months, is observed to be affected by cumulative seasonal and annual precipitation explicitly. Temperature and precipitation almost equally impact on NDVI changes; about 50% of the NDVI variations is explained in OLS modeling, and about 74% of the NDVI variations is explained in GWR modeling. GWR analysis indicated that both precipitation and temperature characterize the spatial heterogeneity patterns of forest dynamics.

Contrasting benefits of different artemisinin combination therapies as first-line malaria treatments using model-based cost-effectiveness analysis

PubMed Central

Okell, Lucy C.; Cairns, Matthew; Griffin, Jamie T.; Ferguson, Neil M.; Tarning, Joel; Jagoe, George; Hugo, Pierre; Baker, Mark; D’Alessandro, Umberto; Bousema, Teun; Ubben, David; Ghani, Azra C.

2014-01-01

There are currently several recommended drug regimens for uncomplicated falciparum malaria in Africa. Each has different properties that determine its impact on disease burden. Two major antimalarial policy options are artemether–lumefantrine (AL) and dihydroartemisinin–piperaquine (DHA–PQP). Clinical trial data show that DHA–PQP provides longer protection against reinfection, while AL is better at reducing patient infectiousness. Here we incorporate pharmacokinetic-pharmacodynamic factors, transmission-reducing effects and cost into a mathematical model and simulate malaria transmission and treatment in Africa, using geographically explicit data on transmission intensity and seasonality, population density, treatment access and outpatient costs. DHA–PQP has a modestly higher estimated impact than AL in 64% of the population at risk. Given current higher cost estimates for DHA–PQP, there is a slightly greater cost per case averted, except in areas with high, seasonally varying transmission where the impact is particularly large. We find that a locally optimized treatment policy can be highly cost effective for reducing clinical malaria burden. PMID:25425081

Understanding African Swine Fever infection dynamics in Sardinia using a spatially explicit transmission model in domestic pig farms.

PubMed

Mur, L; Sánchez-Vizcaíno, J M; Fernández-Carrión, E; Jurado, C; Rolesu, S; Feliziani, F; Laddomada, A; Martínez-López, B

2018-02-01

African swine fever virus (ASFV) has been endemic in Sardinia since 1978, resulting in severe losses for local pig producers and creating important problems for the island's veterinary authorities. This study used a spatially explicit stochastic transmission model followed by two regression models to investigate the dynamics of ASFV spread amongst domestic pig farms, to identify geographic areas at highest risk and determine the role of different susceptible pig populations (registered domestic pigs, non-registered domestic pigs [brado] and wild boar) in ASF occurrence. We simulated transmission within and between farms using an adapted version of the previously described model known as Be-FAST. Results from the model revealed a generally low diffusion of ASF in Sardinia, with only 24% of the simulations resulting in disease spread, and for each simulated outbreak on average only four farms and 66 pigs were affected. Overall, local spread (indirect transmission between farms within a 2 km radius through fomites) was the most common route of transmission, being responsible for 98.6% of secondary cases. The risk of ASF occurrence for each domestic pig farm was estimated from the spread model results and integrated in two regression models together with available data for brado and wild boar populations. There was a significant association between the density of all three populations (domestic pigs, brado, and wild boar) and ASF occurrence in Sardinia. The most significant risk factors were the high densities of brado (OR = 2.2) and wild boar (OR = 2.1). The results of both analyses demonstrated that ASF epidemiology and infection dynamics in Sardinia create a complex and multifactorial disease situation, where all susceptible populations play an important role. To stop ASF transmission in Sardinia, three main factors (improving biosecurity on domestic pig farms, eliminating brado practices and better management of wild boars) need to be addressed. © 2017 Blackwell Verlag GmbH.

Geographers of Mars: cartographic inscription and exploration narrative in late Victorian representations of the red planet.

PubMed

Lane, K Maria D

2005-12-01

Over two decades spanning the turn of the twentieth century, astronomers' claims about the landscape and climate of Mars spurred widespread scientific and popular interest in the possibility that the red planet might be inhabited. This essay offers a new explanation for the power with which the notion of an inhabited Mars gripped noted scholars and everyday citizens on both sides of the Atlantic. Rather than pointing to a rekindling of age-old philosophical interest in the plurality of worlds, it argues that turn-of-the-century scientific narratives about Mars derived much of their power and popularity from ties with the newly established discipline of geography. From mapmaking to travelogue-style writing, astronomers borrowed powerful representational strategies from the discipline of geography to legitimize their claims about the red planet. In making the link between geographical and astronomical science more explicit, the essay further suggests that turn-of-the-century representations of Mars could be productively recontextualized alongside geographical works produced in the same period.

Identifying geographic hot spots of reassortment in a multipartite plant virus

PubMed Central

Savory, Fiona R; Varma, Varun; Ramakrishnan, Uma

2014-01-01

Reassortment between different species or strains plays a key role in the evolution of multipartite plant viruses and can have important epidemiological implications. Identifying geographic locations where reassortant lineages are most likely to emerge could be a valuable strategy for informing disease management and surveillance efforts. We developed a predictive framework to identify potential geographic hot spots of reassortment based upon spatially explicit analyses of genome constellation diversity. To demonstrate the utility of this approach, we examined spatial variation in the potential for reassortment among Cardamom bushy dwarf virus (CBDV; Nanoviridae, Babuvirus) isolates in Northeast India. Using sequence data corresponding to six discrete genome components for 163 CBDV isolates, a quantitative measure of genome constellation diversity was obtained for locations across the sampling region. Two key areas were identified where viruses with highly distinct genome constellations cocirculate, and these locations were designated as possible geographic hot spots of reassortment, where novel reassortant lineages could emerge. Our study demonstrates that the potential for reassortment can be spatially dependent in multipartite plant viruses and highlights the use of evolutionary analyses to identify locations which could be actively managed to facilitate the prevention of outbreaks involving novel reassortant strains. PMID:24944570

Mapping the potential distribution of the invasive Red Shiner, Cyprinella lutrensis (Teleostei: Cyprinidae) across waterways of the conterminous United States

USGS Publications Warehouse

Poulos, Helen M.; Chernoff, Barry; Fuller, Pam L.; Butman, David

2012-01-01

Predicting the future spread of non-native aquatic species continues to be a high priority for natural resource managers striving to maintain biodiversity and ecosystem function. Modeling the potential distributions of alien aquatic species through spatially explicit mapping is an increasingly important tool for risk assessment and prediction. Habitat modeling also facilitates the identification of key environmental variables influencing species distributions. We modeled the potential distribution of an aggressive invasive minnow, the red shiner (Cyprinella lutrensis), in waterways of the conterminous United States using maximum entropy (Maxent). We used inventory records from the USGS Nonindigenous Aquatic Species Database, native records for C. lutrensis from museum collections, and a geographic information system of 20 raster climatic and environmental variables to produce a map of potential red shiner habitat. Summer climatic variables were the most important environmental predictors of C. lutrensis distribution, which was consistent with the high temperature tolerance of this species. Results from this study provide insights into the locations and environmental conditions in the US that are susceptible to red shiner invasion.

Ontology patterns for complex topographic feature yypes

USGS Publications Warehouse

Varanka, Dalia E.

2011-01-01

Complex feature types are defined as integrated relations between basic features for a shared meaning or concept. The shared semantic concept is difficult to define in commonly used geographic information systems (GIS) and remote sensing technologies. The role of spatial relations between complex feature parts was recognized in early GIS literature, but had limited representation in the feature or coverage data models of GIS. Spatial relations are more explicitly specified in semantic technology. In this paper, semantics for topographic feature ontology design patterns (ODP) are developed as data models for the representation of complex features. In the context of topographic processes, component assemblages are supported by resource systems and are found on local landscapes. The topographic ontology is organized across six thematic modules that can account for basic feature types, resource systems, and landscape types. Types of complex feature attributes include location, generative processes and physical description. Node/edge networks model standard spatial relations and relations specific to topographic science to represent complex features. To demonstrate these concepts, data from The National Map of the U. S. Geological Survey was converted and assembled into ODP.

Spatializing 6,000 years of global urbanization from 3700 BC to AD 2000

NASA Astrophysics Data System (ADS)

Reba, Meredith; Reitsma, Femke; Seto, Karen C.

2016-06-01

How were cities distributed globally in the past? How many people lived in these cities? How did cities influence their local and regional environments? In order to understand the current era of urbanization, we must understand long-term historical urbanization trends and patterns. However, to date there is no comprehensive record of spatially explicit, historic, city-level population data at the global scale. Here, we developed the first spatially explicit dataset of urban settlements from 3700 BC to AD 2000, by digitizing, transcribing, and geocoding historical, archaeological, and census-based urban population data previously published in tabular form by Chandler and Modelski. The dataset creation process also required data cleaning and harmonization procedures to make the data internally consistent. Additionally, we created a reliability ranking for each geocoded location to assess the geographic uncertainty of each data point. The dataset provides the first spatially explicit archive of the location and size of urban populations over the last 6,000 years and can contribute to an improved understanding of contemporary and historical urbanization trends.

Spatializing 6,000 years of global urbanization from 3700 BC to AD 2000

PubMed Central

Reba, Meredith; Reitsma, Femke; Seto, Karen C.

2016-01-01

How were cities distributed globally in the past? How many people lived in these cities? How did cities influence their local and regional environments? In order to understand the current era of urbanization, we must understand long-term historical urbanization trends and patterns. However, to date there is no comprehensive record of spatially explicit, historic, city-level population data at the global scale. Here, we developed the first spatially explicit dataset of urban settlements from 3700 BC to AD 2000, by digitizing, transcribing, and geocoding historical, archaeological, and census-based urban population data previously published in tabular form by Chandler and Modelski. The dataset creation process also required data cleaning and harmonization procedures to make the data internally consistent. Additionally, we created a reliability ranking for each geocoded location to assess the geographic uncertainty of each data point. The dataset provides the first spatially explicit archive of the location and size of urban populations over the last 6,000 years and can contribute to an improved understanding of contemporary and historical urbanization trends. PMID:27271481

Modelling social vulnerability in sub-Saharan West Africa using a geographical information system

PubMed Central

Arokoyu, Samuel B.

2015-01-01

In recent times, disasters and risk management have gained significant attention, especially with increasing awareness of the risks and increasing impact of natural and other hazards especially in the developing world. Vulnerability, the potential for loss of life or property from disaster, has biophysical or social dimensions. Social vulnerability relates to societal attributes which has negative impacts on disaster outcomes. This study sought to develop a spatially explicit index of social vulnerability, thus addressing the dearth of research in this area in sub-Saharan Africa. Nineteen variables were identified covering various aspects. Descriptive analysis of these variables revealed high heterogeneity across the South West region of Nigeria for both the state and the local government areas (LGAs). Feature identification using correlation analysis identified six important variables. Factor analysis identified two dimensions, namely accessibility and socioeconomic conditions, from this subset. A social vulnerability index (SoVI) showed that Ondo and Ekiti have more vulnerable LGAs than other states in the region. About 50% of the LGAs in Osun and Ogun have a relatively low social vulnerability. Distribution of the SoVI shows that there are great differences within states as well as across regions. Scores of population density, disability and poverty have a high margin of error in relation to mean state scores. The study showed that with a geographical information system there are opportunities to model social vulnerability and monitor its evolution and dynamics across the continent.

CDPOP: A spatially explicit cost distance population genetics program

Treesearch

Erin L. Landguth; S. A. Cushman

2010-01-01

Spatially explicit simulation of gene flow in complex landscapes is essential to explain observed population responses and provide a foundation for landscape genetics. To address this need, we wrote a spatially explicit, individual-based population genetics model (CDPOP). The model implements individual-based population modelling with Mendelian inheritance and k-allele...

Performance metrics and variance partitioning reveal sources of uncertainty in species distribution models

USGS Publications Warehouse

Watling, James I.; Brandt, Laura A.; Bucklin, David N.; Fujisaki, Ikuko; Mazzotti, Frank J.; Romañach, Stephanie; Speroterra, Carolina

2015-01-01

Species distribution models (SDMs) are widely used in basic and applied ecology, making it important to understand sources and magnitudes of uncertainty in SDM performance and predictions. We analyzed SDM performance and partitioned variance among prediction maps for 15 rare vertebrate species in the southeastern USA using all possible combinations of seven potential sources of uncertainty in SDMs: algorithms, climate datasets, model domain, species presences, variable collinearity, CO2 emissions scenarios, and general circulation models. The choice of modeling algorithm was the greatest source of uncertainty in SDM performance and prediction maps, with some additional variation in performance associated with the comprehensiveness of the species presences used for modeling. Other sources of uncertainty that have received attention in the SDM literature such as variable collinearity and model domain contributed little to differences in SDM performance or predictions in this study. Predictions from different algorithms tended to be more variable at northern range margins for species with more northern distributions, which may complicate conservation planning at the leading edge of species' geographic ranges. The clear message emerging from this work is that researchers should use multiple algorithms for modeling rather than relying on predictions from a single algorithm, invest resources in compiling a comprehensive set of species presences, and explicitly evaluate uncertainty in SDM predictions at leading range margins.

COPEWELL: A Conceptual Framework and System Dynamics Model for Predicting Community Functioning and Resilience After Disasters.

PubMed

Links, Jonathan M; Schwartz, Brian S; Lin, Sen; Kanarek, Norma; Mitrani-Reiser, Judith; Sell, Tara Kirk; Watson, Crystal R; Ward, Doug; Slemp, Cathy; Burhans, Robert; Gill, Kimberly; Igusa, Tak; Zhao, Xilei; Aguirre, Benigno; Trainor, Joseph; Nigg, Joanne; Inglesby, Thomas; Carbone, Eric; Kendra, James M

2018-02-01

Policy-makers and practitioners have a need to assess community resilience in disasters. Prior efforts conflated resilience with community functioning, combined resistance and recovery (the components of resilience), and relied on a static model for what is inherently a dynamic process. We sought to develop linked conceptual and computational models of community functioning and resilience after a disaster. We developed a system dynamics computational model that predicts community functioning after a disaster. The computational model outputted the time course of community functioning before, during, and after a disaster, which was used to calculate resistance, recovery, and resilience for all US counties. The conceptual model explicitly separated resilience from community functioning and identified all key components for each, which were translated into a system dynamics computational model with connections and feedbacks. The components were represented by publicly available measures at the county level. Baseline community functioning, resistance, recovery, and resilience evidenced a range of values and geographic clustering, consistent with hypotheses based on the disaster literature. The work is transparent, motivates ongoing refinements, and identifies areas for improved measurements. After validation, such a model can be used to identify effective investments to enhance community resilience. (Disaster Med Public Health Preparedness. 2018;12:127-137).

The spatial structure of chronic morbidity: evidence from UK census returns.

PubMed

Dutey-Magni, Peter F; Moon, Graham

2016-08-24

Disease prevalence models have been widely used to estimate health, lifestyle and disability characteristics for small geographical units when other data are not available. Yet, knowledge is often lacking about how to make informed decisions around the specification of such models, especially regarding spatial assumptions placed on their covariance structure. This paper is concerned with understanding processes of spatial dependency in unexplained variation in chronic morbidity. 2011 UK census data on limiting long-term illness (LLTI) is used to look at the spatial structure in chronic morbidity across England and Wales. The variance and spatial clustering of the odds of LLTI across local authority districts (LADs) and middle layer super output areas are measured across 40 demographic cross-classifications. A series of adjacency matrices based on distance, contiguity and migration flows are tested to examine the spatial structure in LLTI. Odds are then modelled using a logistic mixed model to examine the association with district-level covariates and their predictive power. The odds of chronic illness are more dispersed than local age characteristics, mortality, hospitalisation rates and chance alone would suggest. Of all adjacency matrices, the three-nearest neighbour method is identified as the best fitting. Migration flows can also be used to construct spatial weights matrices which uncover non-negligible autocorrelation. Once the most important characteristics observable at the LAD-level are taken into account, substantial spatial autocorrelation remains which can be modelled explicitly to improve disease prevalence predictions. Systematic investigation of spatial structures and dependency is important to develop model-based estimation tools in chronic disease mapping. Spatial structures reflecting migration interactions are easy to develop and capture autocorrelation in LLTI. Patterns of spatial dependency in the geographical distribution of LLTI are not comparable across ethnic groups. Ethnic stratification of local health information is needed and there is potential to further address complexity in prevalence models by improving access to disaggregated data.

Predicting rare plant occurrence in Great Smoky Mountains National Park, USA

USGS Publications Warehouse

Boetsch, J.R.; van Manen, Frank T.; Clark, Joseph D.

2003-01-01

We investigated the applicability of biometric habitat modeling to rare plant inventory and conservation by developing and field testing a geographically explicit model for Cardamine clematitis Shuttleworth ex A. Gray (mountain bittercress), an endemic plant of the southern Blue Ridge Mountains, USA. For each of 187 confirmed coordinates for C. clematitis in Great Smoky Mountains National Park, 13 habitat variables were measured with a geographic information system. These data were used to calculate Mahalanobis distances for each 30-m x 30-m pixel within the study area; small values of Mahalanobis distance represented site conditions similar to those of known locations of C. clematitis, whereas larger distance values represented dissimilar conditions. Following model development, we tested model performance by sampling 120 randomly distributed plots for C. clematitis presence. Logistic regression showed that Mahalanobis distance values were strongly related to C. clematitis occurrence (P = 0.039). Overall, 75% of all known occurrences of C. clematitis had associated Mahalanobis distance values below 17.7, and 95% of all occurrences were below 33.8; the median Mahalanobis distance value for the study area as a whole was 40.0. A habitat suitability cutoff value was defined which identified roughly 23,640 ha (19.5% of the study area) as suitable habitat. Although the model successfully predicted species absence in test plots with high Mahalanobis distance values, many sites with low values did not contain C. clematitis. Only 16.2% of test plots below the habitat suitability cutoff contained C. clematitis. The absence of C. clematitis from sites with low Mahalanobis distance values (low specificity) is not necessarily indicative of a poor model; metapopulation processes (e.g., recolonizations, local extinctions) have been shown to play a major role in presence or absence of many plant species. That may be partially the case with our model as evidenced by a relationship between C. clematitis presence and habitat patch size.

A seawater desalination scheme for global hydrological models

NASA Astrophysics Data System (ADS)

Hanasaki, Naota; Yoshikawa, Sayaka; Kakinuma, Kaoru; Kanae, Shinjiro

2016-10-01

Seawater desalination is a practical technology for providing fresh water to coastal arid regions. Indeed, the use of desalination is rapidly increasing due to growing water demand in these areas and decreases in production costs due to technological advances. In this study, we developed a model to estimate the areas where seawater desalination is likely to be used as a major water source and the likely volume of production. The model was designed to be incorporated into global hydrological models (GHMs) that explicitly include human water usage. The model requires spatially detailed information on climate, income levels, and industrial and municipal water use, which represent standard input/output data in GHMs. The model was applied to a specific historical year (2005) and showed fairly good reproduction of the present geographical distribution and national production of desalinated water in the world. The model was applied globally to two periods in the future (2011-2040 and 2041-2070) under three distinct socioeconomic conditions, i.e., SSP (shared socioeconomic pathway) 1, SSP2, and SSP3. The results indicate that the usage of seawater desalination will have expanded considerably in geographical extent, and that production will have increased by 1.4-2.1-fold in 2011-2040 compared to the present (from 2.8 × 109 m3 yr-1 in 2005 to 4.0-6.0 × 109 m3 yr-1), and 6.7-17.3-fold in 2041-2070 (from 18.7 to 48.6 × 109 m3 yr-1). The estimated global costs for production for each period are USD 1.1-10.6 × 109 (0.002-0.019 % of the total global GDP), USD 1.6-22.8 × 109 (0.001-0.020 %), and USD 7.5-183.9 × 109 (0.002-0.100 %), respectively. The large spreads in these projections are primarily attributable to variations within the socioeconomic scenarios.

Ecological niche modeling of rabies in the changing Arctic of Alaska.

PubMed

Huettmann, Falk; Magnuson, Emily Elizabeth; Hueffer, Karsten

2017-03-20

Rabies is a disease of global significance including in the circumpolar Arctic. In Alaska enzootic rabies persist in northern and western coastal areas. Only sporadic cases have occurred in areas outside of the regions considered enzootic for the virus, such as the interior of the state and urbanized regions. Here we examine the distribution of diagnosed rabies cases in Alaska, explicit in space and time. We use a geographic information system (GIS), 20 environmental data layers and provide a quantitative non-parsimonious estimate of the predicted ecological niche, based on data mining, machine learning and open access data. We identify ecological correlates and possible drivers that determine the ecological niche of rabies virus in Alaska. More specifically, our models show that rabies cases are closely associated with human infrastructure, and reveal an ecological niche in remote northern wilderness areas. Furthermore a model utilizing climate modeling suggests a reduction of the current ecological niche for detection of rabies virus in Alaska, a state that is disproportionately affected by a changing climate. Our results may help to better inform public health decisions in the future and guide further studies on individual drivers of rabies distribution in the Arctic.

Mapping and monitoring Mt. Graham Red Squirrel habitat with GIS and thematic mapper imagery

USGS Publications Warehouse

Hatten, James R.; Koprowski, John L.; Sanderson, H. Reed; Koprowski, John L.

2009-01-01

To estimate the Mt. Graham red squirrel (MGRS) population, personnel visit a proportion of middens each year to determine their occupancy (Snow in this vol.). The method results in very tight confidence intervals (high precision), but the accuracy of the population estimate is dependent upon knowing where all the middens are located. I hypothesized that there might be areas outside the survey boundary that contained Mt. Graham red squirrel middens, but the ruggedness of the Pinaleno Mountains made mountain-wide surveys difficult. Therefore, I started exploring development of a spatially explicit (geographic information system [GIS]-based) habitat model in 1998 that could identify MGRS habitat remotely with satellite imagery and a GIS. A GIS-based model would also allow us to assess changes in MGRS habitat between two time periods because Landsat passes over the same location every 16 days, imaging the earth in 185 km swaths (Aronoff 1989). Specifically, the objectives of this analysis were to (1) develop a pattern recognition model for MGRS habitat, (2) map potential (predicted/modeled) MGRS habitat, (3) identify changes in potential MGRS habitat between 1993 and 2003, and (4) evaluate the current location of the MGRS survey boundary.

Age-Friendly Rural Communities: Conceptualizing 'Best-Fit'.

PubMed

Keating, Norah; Eales, Jacquie; Phillips, Judith E

2013-12-01

The literature on age-friendly communities is predominantly focused on a model of urban aging, thereby failing to reflect the diversity of rural communities. In this article, we address that gap by focusing on the concept of community in a rural context and asking what makes a good fi t between older people and their environment. We do this through (a) autobiographical and biographical accounts of two very different geographical living environments: bucolic and bypassed communities; and through (b) analysis of the different needs and resources of two groups of people: marginalized and community-active older adults, who live in those two different rural communities. We argue that the original 2007 Health Organization definition of age friendly should be reconceptualized to explicitly accommodate different community needs and resources, to be more inclusive as well as more interactive and dynamic, incorporating changes that have occurred over time in people and place.

Statistical Tools for Designing Initial and Post-Removal UXO Characterization Surveys

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

Pulsipher, Brent A.; Gilbert, Richard O.; Wilson, John E.

2002-09-06

The Department of Defense (DoD) is in the process of assessing and remediating closed, transferred, and transferring ranges. It is estimated that over 20 million acres of land in the United States potentially contain UXO. The release of DoD sites for public use will require high confidence that UXO is not present. This high confidence may be achieved solely from an extensive knowledge of historical site operations as documented in the conceptual site model or in combination with geophysical sensor surveys designed to have a sufficiently high probability of finding UXO contaminated zones. Many of these sites involve very largemore » geographical areas such that it is often impractical and/or cost prohibitive to perform 100% surveys of the entire site of interest. In that case, it is necessary to be explicit about the performance required of a survey that covers less than 100% of the site.« less

Spatial patterns of phylogenetic diversity.

PubMed

Morlon, Hélène; Schwilk, Dylan W; Bryant, Jessica A; Marquet, Pablo A; Rebelo, Anthony G; Tauss, Catherine; Bohannan, Brendan J M; Green, Jessica L

2011-02-01

Ecologists and conservation biologists have historically used species-area and distance-decay relationships as tools to predict the spatial distribution of biodiversity and the impact of habitat loss on biodiversity. These tools treat each species as evolutionarily equivalent, yet the importance of species' evolutionary history in their ecology and conservation is becoming increasingly evident. Here, we provide theoretical predictions for phylogenetic analogues of the species-area and distance-decay relationships. We use a random model of community assembly and a spatially explicit flora dataset collected in four Mediterranean-type regions to provide theoretical predictions for the increase in phylogenetic diversity - the total phylogenetic branch-length separating a set of species - with increasing area and the decay in phylogenetic similarity with geographic separation. These developments may ultimately provide insights into the evolution and assembly of biological communities, and guide the selection of protected areas. © 2010 Blackwell Publishing Ltd/CNRS.

Mapping, Bayesian Geostatistical Analysis and Spatial Prediction of Lymphatic Filariasis Prevalence in Africa

PubMed Central

Slater, Hannah; Michael, Edwin

2013-01-01

There is increasing interest to control or eradicate the major neglected tropical diseases. Accurate modelling of the geographic distributions of parasitic infections will be crucial to this endeavour. We used 664 community level infection prevalence data collated from the published literature in conjunction with eight environmental variables, altitude and population density, and a multivariate Bayesian generalized linear spatial model that allows explicit accounting for spatial autocorrelation and incorporation of uncertainty in input data and model parameters, to construct the first spatially-explicit map describing LF prevalence distribution in Africa. We also ran the best-fit model against predictions made by the HADCM3 and CCCMA climate models for 2050 to predict the likely distributions of LF under future climate and population changes. We show that LF prevalence is strongly influenced by spatial autocorrelation between locations but is only weakly associated with environmental covariates. Infection prevalence, however, is found to be related to variations in population density. All associations with key environmental/demographic variables appear to be complex and non-linear. LF prevalence is predicted to be highly heterogenous across Africa, with high prevalences (>20%) estimated to occur primarily along coastal West and East Africa, and lowest prevalences predicted for the central part of the continent. Error maps, however, indicate a need for further surveys to overcome problems with data scarcity in the latter and other regions. Analysis of future changes in prevalence indicates that population growth rather than climate change per se will represent the dominant factor in the predicted increase/decrease and spread of LF on the continent. We indicate that these results could play an important role in aiding the development of strategies that are best able to achieve the goals of parasite elimination locally and globally in a manner that may also account for the effects of future climate change on parasitic infection. PMID:23951194

A Multi-Temporal Remote Sensing Approach to Freshwater Turtle Conservation

NASA Astrophysics Data System (ADS)

Mui, Amy B.

Freshwater turtles are a globally declining taxa, and estimates of population status are not available for many species. Primary causes of decline stem from widespread habitat loss and degradation, and obtaining spatially-explicit information on remaining habitat across a relevant spatial scale has proven challenging. The discipline of remote sensing science has been employed widely in studies of biodiversity conservation, but it has not been utilized as frequently for cryptic, and less vagile species such as turtles, despite their vulnerable status. The work presented in this thesis investigates how multi-temporal remote sensing imagery can contribute key information for building spatially-explicit and temporally dynamic models of habitat and connectivity for the threatened, Blanding's turtle (Emydoidea blandingii) in southern Ontario, Canada. I began with outlining a methodological approach for delineating freshwater wetlands from high spatial resolution remote sensing imagery, using a geographic object-based image analysis (GEOBIA) approach. This method was applied to three different landscapes in southern Ontario, and across two biologically relevant seasons during the active (non-hibernating) period of Blanding's turtles. Next, relevant environmental variables associated with turtle presence were extracted from remote sensing imagery, and a boosted regression tree model was developed to predict the probability of occurrence of this species. Finally, I analysed the movement potential for Blanding's turtles in a disturbed landscape using a combination of approaches. Results indicate that (1) a parsimonious GEOBIA approach to land cover mapping, incorporating texture, spectral indices, and topographic information can map heterogeneous land cover with high accuracy, (2) remote-sensing derived environmental variables can be used to build habitat models with strong predictive power, and (3) connectivity potential is best estimated using a variety of approaches, though accurate estimates across human-altered landscapes is challenging. Overall, this body of work supports the use of remote sensing imagery in species distribution models to strengthen the precision, and power of predictive models, and also draws attention to the need to consider a multi-temporal examination of species habitat requirements.

42 CFR § 512.105 - Geographic areas.

Code of Federal Regulations, 2010 CFR

2017-10-01

... (CONTINUED) HEALTH CARE INFRASTRUCTURE AND MODEL PROGRAMS EPISODE PAYMENT MODEL Episode Payment Model Participants § 512.105 Geographic areas. (a) The SHFFT model must be implemented in the same geographic areas as the CJR model as described under § 510.105 of the chapter. (b) The geographic areas for inclusion...

Effects of Explicit Instructions, Metacognition, and Motivation on Creative Performance

ERIC Educational Resources Information Center

Hong, Eunsook; O'Neil, Harold F.; Peng, Yun

2016-01-01

Effects of explicit instructions, metacognition, and intrinsic motivation on creative homework performance were examined in 303 Chinese 10th-grade students. Models that represent hypothesized relations among these constructs and trait covariates were tested using structural equation modelling. Explicit instructions geared to originality were…

Midpoint attractors and species richness: Modelling the interaction between environmental drivers and geometric constraints.

PubMed

Colwell, Robert K; Gotelli, Nicholas J; Ashton, Louise A; Beck, Jan; Brehm, Gunnar; Fayle, Tom M; Fiedler, Konrad; Forister, Matthew L; Kessler, Michael; Kitching, Roger L; Klimes, Petr; Kluge, Jürgen; Longino, John T; Maunsell, Sarah C; McCain, Christy M; Moses, Jimmy; Noben, Sarah; Sam, Katerina; Sam, Legi; Shapiro, Arthur M; Wang, Xiangping; Novotny, Vojtech

2016-09-01

We introduce a novel framework for conceptualising, quantifying and unifying discordant patterns of species richness along geographical gradients. While not itself explicitly mechanistic, this approach offers a path towards understanding mechanisms. In this study, we focused on the diverse patterns of species richness on mountainsides. We conjectured that elevational range midpoints of species may be drawn towards a single midpoint attractor - a unimodal gradient of environmental favourability. The midpoint attractor interacts with geometric constraints imposed by sea level and the mountaintop to produce taxon-specific patterns of species richness. We developed a Bayesian simulation model to estimate the location and strength of the midpoint attractor from species occurrence data sampled along mountainsides. We also constructed midpoint predictor models to test whether environmental variables could directly account for the observed patterns of species range midpoints. We challenged these models with 16 elevational data sets, comprising 4500 species of insects, vertebrates and plants. The midpoint predictor models generally failed to predict the pattern of species midpoints. In contrast, the midpoint attractor model closely reproduced empirical spatial patterns of species richness and range midpoints. Gradients of environmental favourability, subject to geometric constraints, may parsimoniously account for elevational and other patterns of species richness. © 2016 John Wiley & Sons Ltd/CNRS.

EVALUATING HYDROLOGICAL RESPONSE TO ...

EPA Pesticide Factsheets

Studies of future management and policy options based on different assumptions provide a mechanism to examine possible outcomes and especially their likely benefits or consequences. Planning and assessment in land and water resource management are evolving toward complex, spatially explicit regional assessments. These problems have to be addressed with distributed models that can compute runoff and erosion at different spatial and temporal scales. The extensive data requirements and the difficult task of building input parameter files, however, have long been an obstacle to the timely and cost-effective use of such complex models by resource managers. The U.S. EPA Landscape Ecology Branch in collaboration with the USDA-ARS Southwest Watershed Research Center has developed a geographic information system (GIS) tool to facilitate this process. A GIS provides the framework within which spatially distributed data are collected and used to prepare model input files, and model results are evaluated. The Automated Geospatial Watershed Assessment (AGWA) tool uses widely available standardized spatial datasets that can be obtained via the internet at no cost to the user. The data are used to develop input parameter files for KINEROS2 and SWAT, two watershed runoff and erosion simulation models that operate at different spatial and temporal scales. AGWA automates the process of transforming digital data into simulation model results and provides a visualization tool

Within-Site Variation in Feather Stable Hydrogen Isotope (δ2Hf) Values of Boreal Songbirds: Implications for Assignment to Molt Origin.

PubMed

Nordell, Cameron J; Haché, Samuel; Bayne, Erin M; Sólymos, Péter; Foster, Kenneth R; Godwin, Christine M; Krikun, Richard; Pyle, Peter; Hobson, Keith A

2016-01-01

Understanding bird migration and dispersal is important to inform full life-cycle conservation planning. Stable hydrogen isotope ratios from feathers (δ2Hf) can be linked to amount-weighted long-term, growing season precipitation δ2H (δ2Hp) surfaces to create δ2Hf isoscapes for assignment to molt origin. However, transfer functions linking δ2Hp with δ2Hf are influenced by physiological and environmental processes. A better understanding of the causes and consequences of variation in δ2Hf values among individuals and species will improve the predictive ability of geographic assignment tests. We tested for effects of species, land cover, forage substrate, nest substrate, diet composition, body mass, sex, and phylogenetic relatedness on δ2Hf from individuals at least two years old of 21 songbird species captured during the same breeding season at a site in northeastern Alberta, Canada. For four species, we also tested for a year × species interaction effect on δ2Hf. A model including species as single predictor received the most support (AIC weight = 0.74) in explaining variation in δ2Hf. A species-specific variance parameter was part of all best-ranked models, suggesting variation in δ2Hf was not consistent among species. The second best-ranked model included a forage substrate × diet interaction term (AIC weight = 0.16). There was a significant year × species interaction effect on δ2Hf suggesting that interspecific differences in δ2Hf can differ among years. Our results suggest that within- and among-year interspecific variation in δ2Hf is the most important source of variance typically not being explicitly quantified in geographic assignment tests using non-specific transfer functions to convert δ2Hp into δ2Hf. However, this source of variation is consistent with the range of variation from the transfer functions most commonly being propagated in assignment tests of geographic origins for passerines breeding in North America.

Improvement, Verification, and Refinement of Spatially-Explicit Exposure Models in Risk Assessment - FishRand Spatially-Explicit Bioaccumulation Model Demonstration

DTIC Science & Technology

2015-08-01

21  Figure 4. Data-based proportion of DDD , DDE and DDT in total DDx in fish and sediment by... DDD dichlorodiphenyldichloroethane DDE dichlorodiphenyldichloroethylene DDT dichlorodiphenyltrichloroethane DoD Department of Defense ERM... DDD ) at the other site. The spatially-explicit model consistently predicts tissue concentrations that closely match both the average and the

Using volunteered geographic information to visualize ...

EPA Pesticide Factsheets

Volunteered geographic information (VGI), specifically geotagged photographs available from social media platforms, is a promising technology that can be utilized to identify public values for ecosystem goods and services in a defined geographic area. VGI can help researchers indirectly survey and report on the values and preferences of communities involved in restoration and revitalization projects. We are using geotagged images from three social media platforms: Flickr, Instagram, and Panaramio. Images are obtained for the neighborhoods to the St. Louis River in the Duluth, MN and analyzed along several dimensions including the spatial distribution of images from each platform and the types and frequencies of social values and ecosystem service depicted. This study will demonstrate a method for translating the values of ecosystem goods and services as captured in social media into spatially-explicit data. Study outcomes are the incorporation of social media-derived indicators of ecosystems services into City of Duluth’s Comprehensive Planning and community revitalization efforts, habitat restoration in a Great Lakes Area of Concern, and the USEPA’s Office of Research and Development Sustainable and Healthy Community research. Not applicable

Beyond the Census Tract: Patterns and Determinants of Racial Segregation at Multiple Geographic Scales*

PubMed Central

Lee, Barrett A.; Reardon, Sean F.; Firebaugh, Glenn; Farrell, Chad R.; Matthews, Stephen A.; O'Sullivan, David

2014-01-01

The census tract-based residential segregation literature rests on problematic assumptions about geographic scale and proximity. We pursue a new tract-free approach that combines explicitly spatial concepts and methods to examine racial segregation across egocentric local environments of varying size. Using 2000 census data for the 100 largest U.S. metropolitan areas, we compute a spatially modified version of the information theory index H to describe patterns of black-white, Hispanic-white, Asian-white, and multi-group segregation at different scales. The metropolitan structural characteristics that best distinguish micro-segregation from macro-segregation for each group combination are identified, and their effects are decomposed into portions due to racial variation occurring over short and long distances. A comparison of our results to those from tract-based analyses confirms the value of the new approach. PMID:25324575

Prediction of Complex Aerodynamic Flows with Explicit Algebraic Stress Models

NASA Technical Reports Server (NTRS)

Abid, Ridha; Morrison, Joseph H.; Gatski, Thomas B.; Speziale, Charles G.

1996-01-01

An explicit algebraic stress equation, developed by Gatski and Speziale, is used in the framework of K-epsilon formulation to predict complex aerodynamic turbulent flows. The nonequilibrium effects are modeled through coefficients that depend nonlinearly on both rotational and irrotational strains. The proposed model was implemented in the ISAAC Navier-Stokes code. Comparisons with the experimental data are presented which clearly demonstrate that explicit algebraic stress models can predict the correct response to nonequilibrium flow.

Program SPACECAP: software for estimating animal density using spatially explicit capture-recapture models

USGS Publications Warehouse

Gopalaswamy, Arjun M.; Royle, J. Andrew; Hines, James E.; Singh, Pallavi; Jathanna, Devcharan; Kumar, N. Samba; Karanth, K. Ullas

2012-01-01

1. The advent of spatially explicit capture-recapture models is changing the way ecologists analyse capture-recapture data. However, the advantages offered by these new models are not fully exploited because they can be difficult to implement. 2. To address this need, we developed a user-friendly software package, created within the R programming environment, called SPACECAP. This package implements Bayesian spatially explicit hierarchical models to analyse spatial capture-recapture data. 3. Given that a large number of field biologists prefer software with graphical user interfaces for analysing their data, SPACECAP is particularly useful as a tool to increase the adoption of Bayesian spatially explicit capture-recapture methods in practice.

Geo-referenced multimedia environmental fate model (G-CIEMS): model formulation and comparison to the generic model and monitoring approaches.

PubMed

Suzuki, Noriyuki; Murasawa, Kaori; Sakurai, Takeo; Nansai, Keisuke; Matsuhashi, Keisuke; Moriguchi, Yuichi; Tanabe, Kiyoshi; Nakasugi, Osami; Morita, Masatoshi

2004-11-01

A spatially resolved and geo-referenced dynamic multimedia environmental fate model, G-CIEMS (Grid-Catchment Integrated Environmental Modeling System) was developed on a geographical information system (GIS). The case study for Japan based on the air grid cells of 5 x 5 km resolution and catchments with an average area of 9.3 km2, which corresponds to about 40,000 air grid cells and 38,000 river segments/catchment polygons, were performed for dioxins, benzene, 1,3-butadiene, and di-(2-ethyhexyl)phthalate. The averaged concentration of the model and monitoring output were within a factor of 2-3 for all the media. Outputs from G-CIEMS and the generic model were essentially comparable when identical parameters were employed, whereas the G-CIEMS model gave explicit information of distribution of chemicals in the environment. Exposure-weighted averaged concentrations (EWAC) in air were calculated to estimate the exposure ofthe population, based on the results of generic, G-CIEMS, and monitoring approaches. The G-CIEMS approach showed significantly better agreement with the monitoring-derived EWAC than the generic model approach. Implication for the use of a geo-referenced modeling approach in the risk assessment scheme is discussed as a generic-spatial approach, which can be used to provide more accurate exposure estimation with distribution information, using generally available data sources for a wide range of chemicals.

Connecting Free Energy Surfaces in Implicit and Explicit Solvent: an Efficient Method to Compute Conformational and Solvation Free Energies

PubMed Central

Deng, Nanjie; Zhang, Bin W.; Levy, Ronald M.

2015-01-01

The ability to accurately model solvent effects on free energy surfaces is important for understanding many biophysical processes including protein folding and misfolding, allosteric transitions and protein-ligand binding. Although all-atom simulations in explicit solvent can provide an accurate model for biomolecules in solution, explicit solvent simulations are hampered by the slow equilibration on rugged landscapes containing multiple basins separated by barriers. In many cases, implicit solvent models can be used to significantly speed up the conformational sampling; however, implicit solvent simulations do not fully capture the effects of a molecular solvent, and this can lead to loss of accuracy in the estimated free energies. Here we introduce a new approach to compute free energy changes in which the molecular details of explicit solvent simulations are retained while also taking advantage of the speed of the implicit solvent simulations. In this approach, the slow equilibration in explicit solvent, due to the long waiting times before barrier crossing, is avoided by using a thermodynamic cycle which connects the free energy basins in implicit solvent and explicit solvent using a localized decoupling scheme. We test this method by computing conformational free energy differences and solvation free energies of the model system alanine dipeptide in water. The free energy changes between basins in explicit solvent calculated using fully explicit solvent paths agree with the corresponding free energy differences obtained using the implicit/explicit thermodynamic cycle to within 0.3 kcal/mol out of ~3 kcal/mol at only ~8 % of the computational cost. We note that WHAM methods can be used to further improve the efficiency and accuracy of the explicit/implicit thermodynamic cycle. PMID:26236174

Connecting free energy surfaces in implicit and explicit solvent: an efficient method to compute conformational and solvation free energies.

PubMed

Deng, Nanjie; Zhang, Bin W; Levy, Ronald M

2015-06-09

The ability to accurately model solvent effects on free energy surfaces is important for understanding many biophysical processes including protein folding and misfolding, allosteric transitions, and protein–ligand binding. Although all-atom simulations in explicit solvent can provide an accurate model for biomolecules in solution, explicit solvent simulations are hampered by the slow equilibration on rugged landscapes containing multiple basins separated by barriers. In many cases, implicit solvent models can be used to significantly speed up the conformational sampling; however, implicit solvent simulations do not fully capture the effects of a molecular solvent, and this can lead to loss of accuracy in the estimated free energies. Here we introduce a new approach to compute free energy changes in which the molecular details of explicit solvent simulations are retained while also taking advantage of the speed of the implicit solvent simulations. In this approach, the slow equilibration in explicit solvent, due to the long waiting times before barrier crossing, is avoided by using a thermodynamic cycle which connects the free energy basins in implicit solvent and explicit solvent using a localized decoupling scheme. We test this method by computing conformational free energy differences and solvation free energies of the model system alanine dipeptide in water. The free energy changes between basins in explicit solvent calculated using fully explicit solvent paths agree with the corresponding free energy differences obtained using the implicit/explicit thermodynamic cycle to within 0.3 kcal/mol out of ∼3 kcal/mol at only ∼8% of the computational cost. We note that WHAM methods can be used to further improve the efficiency and accuracy of the implicit/explicit thermodynamic cycle.

Assessment of Biases Against Latinos and African Americans Among Primary Care Providers and Community Members

PubMed Central

Havranek, Edward P.; Price, David W.; Hanratty, Rebecca; Fairclough, Diane L.; Farley, Tillman; Hirsh, Holen K.; Steiner, John F.

2013-01-01

Objectives. We assessed implicit and explicit bias against both Latinos and African Americans among experienced primary care providers (PCPs) and community members (CMs) in the same geographic area. Methods. Two hundred ten PCPs and 190 CMs from 3 health care organizations in the Denver, Colorado, metropolitan area completed Implicit Association Tests and self-report measures of implicit and explicit bias, respectively. Results. With a 60% participation rate, the PCPs demonstrated substantial implicit bias against both Latinos and African Americans, but this was no different from CMs. Explicit bias was largely absent in both groups. Adjustment for background characteristics showed the PCPs had slightly weaker ethnic/racial bias than CMs. Conclusions. This research provided the first evidence of implicit bias against Latinos in health care, as well as confirming previous findings of implicit bias against African Americans. Lack of substantive differences in bias between the experienced PCPs and CMs suggested a wider societal problem. At the same time, the wide range of implicit bias suggested that bias in health care is neither uniform nor inevitable, and important lessons might be learned from providers who do not exhibit bias. PMID:23153155

Landscape modeling for Everglades ecosystem restoration

USGS Publications Warehouse

DeAngelis, D.L.; Gross, L.J.; Huston, M.A.; Wolff, W.F.; Fleming, D.M.; Comiskey, E.J.; Sylvester, S.M.

1998-01-01

A major environmental restoration effort is under way that will affect the Everglades and its neighboring ecosystems in southern Florida. Ecosystem and population-level modeling is being used to help in the planning and evaluation of this restoration. The specific objective of one of these modeling approaches, the Across Trophic Level System Simulation (ATLSS), is to predict the responses of a suite of higher trophic level species to several proposed alterations in Everglades hydrology. These include several species of wading birds, the snail kite, Cape Sable seaside sparrow, Florida panther, white-tailed deer, American alligator, and American crocodile. ATLSS is an ecosystem landscape-modeling approach and uses Geographic Information System (GIS) vegetation data and existing hydrology models for South Florida to provide the basic landscape for these species. A method of pseudotopography provides estimates of water depths through time at 28 ?? 28-m resolution across the landscape of southern Florida. Hydrologic model output drives models of habitat and prey availability for the higher trophic level species. Spatially explicit, individual-based computer models simulate these species. ATLSS simulations can compare the landscape dynamic spatial pattern of the species resulting from different proposed water management strategies. Here we compare the predicted effects of one possible change in water management in South Florida with the base case of no change. Preliminary model results predict substantial differences between these alternatives in some biotic spatial patterns. ?? 1998 Springer-Verlag.

Past and future perspectives on mathematical models of tick-borne pathogens.

PubMed

Norman, R A; Worton, A J; Gilbert, L

2016-06-01

Ticks are vectors of pathogens which are important both with respect to human health and economically. They have a complex life cycle requiring several blood meals throughout their life. These blood meals take place on different individual hosts and potentially on different host species. Their life cycle is also dependent on environmental conditions such as the temperature and habitat type. Mathematical models have been used for the more than 30 years to help us understand how tick dynamics are dependent on these environmental factors and host availability. In this paper, we review models of tick dynamics and summarize the main results. This summary is split into two parts, one which looks at tick dynamics and one which looks at tick-borne pathogens. In general, the models of tick dynamics are used to determine when the peak in tick densities is likely to occur in the year and how that changes with environmental conditions. The models of tick-borne pathogens focus more on the conditions under which the pathogen can persist and how host population densities might be manipulated to control these pathogens. In the final section of the paper, we identify gaps in the current knowledge and future modelling approaches. These include spatial models linked to environmental information and Geographic Information System maps, and development of new modelling techniques which model tick densities per host more explicitly.

Computational Model of D-Region Ion Production Caused by Energetic Electron Precipitations Based on General Monte Carlo Transport Calculations

NASA Astrophysics Data System (ADS)

Kouznetsov, A.; Cully, C. M.

2017-12-01

During enhanced magnetic activities, large ejections of energetic electrons from radiation belts are deposited in the upper polar atmosphere where they play important roles in its physical and chemical processes, including VLF signals subionospheric propagation. Electron deposition can affect D-Region ionization, which are estimated based on ionization rates derived from energy depositions. We present a model of D-region ion production caused by an arbitrary (in energy and pitch angle) distribution of fast (10 keV - 1 MeV) electrons. The model relies on a set of pre-calculated results obtained using a general Monte Carlo approach with the latest version of the MCNP6 (Monte Carlo N-Particle) code for the explicit electron tracking in magnetic fields. By expressing those results using the ionization yield functions, the pre-calculated results are extended to cover arbitrary magnetic field inclinations and atmospheric density profiles, allowing ionization rate altitude profile computations in the range of 20 and 200 km at any geographic point of interest and date/time by adopting results from an external atmospheric density model (e.g. NRLMSISE-00). The pre-calculated MCNP6 results are stored in a CDF (Common Data Format) file, and IDL routines library is written to provide an end-user interface to the model.

Parasite biodiversity faces extinction and redistribution in a changing climate.

PubMed

Carlson, Colin J; Burgio, Kevin R; Dougherty, Eric R; Phillips, Anna J; Bueno, Veronica M; Clements, Christopher F; Castaldo, Giovanni; Dallas, Tad A; Cizauskas, Carrie A; Cumming, Graeme S; Doña, Jorge; Harris, Nyeema C; Jovani, Roger; Mironov, Sergey; Muellerklein, Oliver C; Proctor, Heather C; Getz, Wayne M

2017-09-01

Climate change is a well-documented driver of both wildlife extinction and disease emergence, but the negative impacts of climate change on parasite diversity are undocumented. We compiled the most comprehensive spatially explicit data set available for parasites, projected range shifts in a changing climate, and estimated extinction rates for eight major parasite clades. On the basis of 53,133 occurrences capturing the geographic ranges of 457 parasite species, conservative model projections suggest that 5 to 10% of these species are committed to extinction by 2070 from climate-driven habitat loss alone. We find no evidence that parasites with zoonotic potential have a significantly higher potential to gain range in a changing climate, but we do find that ectoparasites (especially ticks) fare disproportionately worse than endoparasites. Accounting for host-driven coextinctions, models predict that up to 30% of parasitic worms are committed to extinction, driven by a combination of direct and indirect pressures. Despite high local extinction rates, parasite richness could still increase by an order of magnitude in some places, because species successfully tracking climate change invade temperate ecosystems and replace native species with unpredictable ecological consequences.

Conceptual Design of Optimized Fossil Energy Systems with Capture and Sequestration of Carbon Dioxide

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

Nils Johnson; Joan Ogden

2010-12-31

In this final report, we describe research results from Phase 2 of a technical/economic study of fossil hydrogen energy systems with carbon dioxide (CO{sub 2}) capture and storage (CCS). CO{sub 2} capture and storage, or alternatively, CO{sub 2} capture and sequestration, involves capturing CO{sub 2} from large point sources and then injecting it into deep underground reservoirs for long-term storage. By preventing CO{sub 2} emissions into the atmosphere, this technology has significant potential to reduce greenhouse gas (GHG) emissions from fossil-based facilities in the power and industrial sectors. Furthermore, the application of CCS to power plants and hydrogen production facilitiesmore » can reduce CO{sub 2} emissions associated with electric vehicles (EVs) and hydrogen fuel cell vehicles (HFCVs) and, thus, can also improve GHG emissions in the transportation sector. This research specifically examines strategies for transitioning to large-scale coal-derived energy systems with CCS for both hydrogen fuel production and electricity generation. A particular emphasis is on the development of spatially-explicit modeling tools for examining how these energy systems might develop in real geographic regions. We employ an integrated modeling approach that addresses all infrastructure components involved in the transition to these energy systems. The overall objective is to better understand the system design issues and economics associated with the widespread deployment of hydrogen and CCS infrastructure in real regions. Specific objectives of this research are to: Develop improved techno-economic models for all components required for the deployment of both hydrogen and CCS infrastructure, Develop novel modeling methods that combine detailed spatial data with optimization tools to explore spatially-explicit transition strategies, Conduct regional case studies to explore how these energy systems might develop in different regions of the United States, and Examine how the design and cost of coal-based H{sub 2} and CCS infrastructure depend on geography and location.« less

Implicit and explicit self-esteem and their reciprocal relationship with symptoms of depression and social anxiety: a longitudinal study in adolescents.

PubMed

van Tuijl, Lonneke A; de Jong, Peter J; Sportel, B Esther; de Hullu, Eva; Nauta, Maaike H

2014-03-01

A negative self-view is a prominent factor in most cognitive vulnerability models of depression and anxiety. Recently, there has been increased attention to differentiate between the implicit (automatic) and the explicit (reflective) processing of self-related evaluations. This longitudinal study aimed to test the association between implicit and explicit self-esteem and symptoms of adolescent depression and social anxiety disorder. Two complementary models were tested: the vulnerability model and the scarring effect model. Participants were 1641 first and second year pupils of secondary schools in the Netherlands. The Rosenberg Self-Esteem Scale, self-esteem Implicit Association Test and Revised Child Anxiety and Depression Scale were completed to measure explicit self-esteem, implicit self-esteem and symptoms of social anxiety disorder (SAD) and major depressive disorder (MDD), respectively, at baseline and two-year follow-up. Explicit self-esteem at baseline was associated with symptoms of MDD and SAD at follow-up. Symptomatology at baseline was not associated with explicit self-esteem at follow-up. Implicit self-esteem was not associated with symptoms of MDD or SAD in either direction. We relied on self-report measures of MDD and SAD symptomatology. Also, findings are based on a non-clinical sample. Our findings support the vulnerability model, and not the scarring effect model. The implications of these findings suggest support of an explicit self-esteem intervention to prevent increases in MDD and SAD symptomatology in non-clinical adolescents. Copyright © 2013 Elsevier Ltd. All rights reserved.

Are mixed explicit/implicit solvation models reliable for studying phosphate hydrolysis? A comparative study of continuum, explicit and mixed solvation models.

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

Kamerlin, Shina C. L.; Haranczyk, Maciej; Warshel, Arieh

2009-05-01

Phosphate hydrolysis is ubiquitous in biology. However, despite intensive research on this class of reactions, the precise nature of the reaction mechanism remains controversial. In this work, we have examined the hydrolysis of three homologous phosphate diesters. The solvation free energy was simulated by means of either an implicit solvation model (COSMO), hybrid quantum mechanical / molecular mechanical free energy perturbation (QM/MM-FEP) or a mixed solvation model in which N water molecules were explicitly included in the ab initio description of the reacting system (where N=1-3), with the remainder of the solvent being implicitly modelled as a continuum. Here, bothmore » COSMO and QM/MM-FEP reproduce Delta Gobs within an error of about 2kcal/mol. However, we demonstrate that in order to obtain any form of reliable results from a mixed model, it is essential to carefully select the explicit water molecules from short QM/MM runs that act as a model for the true infinite system. Additionally, the mixed models tend to be increasingly inaccurate the more explicit water molecules are placed into the system. Thus, our analysis indicates that this approach provides an unreliable way for modelling phosphate hydrolysis in solution.« less

[A spatially explicit analysis of traffic accidents involving pedestrians and cyclists in Berlin].

PubMed

Lakes, Tobia

2017-12-01

In many German cities and counties, sustainable mobility concepts that strengthen pedestrian and cyclist traffic are promoted. From the perspectives of urban development, traffic planning and public healthcare, a spatially differentiated analysis of traffic accident data is decisive. 1) The identification of spatial and temporal patterns of the distribution of accidents involving cyclists and pedestrians, 2) the identification of hotspots and exploration of possible underlying causes and 3) the critical discussion of benefits and challenges of the results and the derivation of conclusions. Spatio-temporal distributions of data from accident statistics in Berlin involving pedestrians and cyclists from 2011 to 2015 were analysed with geographic information systems (GIS). While the total number of accidents remains relatively stable for pedestrian and cyclist accidents, the spatial distribution analysis shows, however, that there are significant spatial clusters (hotspots) of traffic accidents with a strong concentration in the inner city area. In a critical discussion, the benefits of geographic concepts are identified, such as spatially explicit health data (in this case traffic accident data), the importance of the integration of other data sources for the evaluation of the health impact of areas (traffic accident statistics of the police), and the possibilities and limitations of spatial-temporal data analysis (spatial point-density analyses) for the derivation of decision-supported recommendations and for the evaluation of policy measures of health prevention and of health-relevant urban development.

Explicit filtering in large eddy simulation using a discontinuous Galerkin method

NASA Astrophysics Data System (ADS)

Brazell, Matthew J.

The discontinuous Galerkin (DG) method is a formulation of the finite element method (FEM). DG provides the ability for a high order of accuracy in complex geometries, and allows for highly efficient parallelization algorithms. These attributes make the DG method attractive for solving the Navier-Stokes equations for large eddy simulation (LES). The main goal of this work is to investigate the feasibility of adopting an explicit filter in the numerical solution of the Navier-Stokes equations with DG. Explicit filtering has been shown to increase the numerical stability of under-resolved simulations and is needed for LES with dynamic sub-grid scale (SGS) models. The explicit filter takes advantage of DG's framework where the solution is approximated using a polyno- mial basis where the higher modes of the solution correspond to a higher order polynomial basis. By removing high order modes, the filtered solution contains low order frequency content much like an explicit low pass filter. The explicit filter implementation is tested on a simple 1-D solver with an initial condi- tion that has some similarity to turbulent flows. The explicit filter does restrict the resolution as well as remove accumulated energy in the higher modes from aliasing. However, the ex- plicit filter is unable to remove numerical errors causing numerical dissipation. A second test case solves the 3-D Navier-Stokes equations of the Taylor-Green vortex flow (TGV). The TGV is useful for SGS model testing because it is initially laminar and transitions into a fully turbulent flow. The SGS models investigated include the constant coefficient Smagorinsky model, dynamic Smagorinsky model, and dynamic Heinz model. The constant coefficient Smagorinsky model is over dissipative, this is generally not desirable however it does add stability. The dynamic Smagorinsky model generally performs better, especially during the laminar-turbulent transition region as expected. The dynamic Heinz model which is based on an improved model, handles the laminar-turbulent transition region well while also showing additional robustness.

Embedded-explicit emergent literacy intervention I: Background and description of approach.

PubMed

Justice, Laura M; Kaderavek, Joan N

2004-07-01

This article, the first of a two-part series, provides background information and a general description of an emergent literacy intervention model for at-risk preschoolers and kindergartners. The embedded-explicit intervention model emphasizes the dual importance of providing young children with socially embedded opportunities for meaningful, naturalistic literacy experiences throughout the day, in addition to regular structured therapeutic interactions that explicitly target critical emergent literacy goals. The role of the speech-language pathologist (SLP) in the embedded-explicit model encompasses both indirect and direct service delivery: The SLP consults and collaborates with teachers and parents to ensure the highest quality and quantity of socially embedded literacy-focused experiences and serves as a direct provider of explicit interventions using structured curricula and/or lesson plans. The goal of this integrated model is to provide comprehensive emergent literacy interventions across a spectrum of early literacy skills to ensure the successful transition of at-risk children from prereaders to readers.

Developing Spatially Explicit Habitat Models for Grassland Bird Conservation Planning in the Prairie Pothole Region of North Dakota

Treesearch

Neal D. Niemuth; Michael E. Estey; Charles R. Loesch

2005-01-01

Conservation planning for birds is increasingly focused on landscapes. However, little spatially explicit information is available to guide landscape-level conservation planning for many species of birds. We used georeferenced 1995 Breeding Bird Survey (BBS) data in conjunction with land-cover information to develop a spatially explicit habitat model predicting the...

Explicit robust schemes for implementation of general principal value-based constitutive models

NASA Technical Reports Server (NTRS)

Arnold, S. M.; Saleeb, A. F.; Tan, H. Q.; Zhang, Y.

1993-01-01

The issue of developing effective and robust schemes to implement general hyperelastic constitutive models is addressed. To this end, special purpose functions are used to symbolically derive, evaluate, and automatically generate the associated FORTRAN code for the explicit forms of the corresponding stress function and material tangent stiffness tensors. These explicit forms are valid for the entire deformation range. The analytical form of these explicit expressions is given here for the case in which the strain-energy potential is taken as a nonseparable polynomial function of the principle stretches.

Implementation of UML Schema to RDBM

NASA Astrophysics Data System (ADS)

Nagni, M.; Ventouras, S.; Parton, G.

2012-04-01

Multiple disciplines - especially those within the earth and physical sciences, and increasingly those within social science and medical fields - require Geographic Information (GI) i.e. information concerning phenomena implicitly or explicitly associated with a location relative to the Earth [1]. Therefore geographic datasets are increasingly being shared, exchanged and frequently used for purposes other than those for which they were originally intended. The ISO Technical Committee 211 (ISO/TC 211) together with Open Geospatial Consortium (OGC) provide a series of standards and guidelines for developing application schemas which should: a) capture relevant conceptual aspects of the data involved; and b) be sufficient to satisfy previously defined use-cases of a specific or cross-domain concerns. In addition, the Hollow World technology offers an accessible and industry-standardised methodology for creating and editing Application Schema UML models which conform to international standards for interoperable GI [2]. We present a technology which seamlessly transforms an Application Schema UML model to a relational database model (RDBM). This technology, using the same UML information model, complements the XML transformation of an information model produced by the FullMoon tool [2]. In preparation for the generation of a RDBM the UML model is first mapped to a collection of OO classes and relationships. Any external dependencies that exist are then resolved through the same mechanism. However, a RDBM does not support a hierarchical (relational) data structure - a function that may be required by UML models. Previous approaches have addressed this problem through use of nested sets or an adjacent list to represent such structure. Our unique strategy addresses the hierarchical data structure issue, whether singular or multiple inheritance, by hiding a delegation pattern within an OO class. This permits the object-relational mapping (ORM) software used to generate the RDBM to easily map the class into the RDBM. In other words the particular structure of the resulting OO class may expose a "composition-like aspect" to the ORM whilst maintaining an "inherited-like aspect" for use within an OO program. This methodology has been used to implement a software application to manages the new CEDA metadata model which is based on MOLES 3.4, Python, Django and SQLAlchemy.

Uncertainty in spatially explicit animal dispersal models

USGS Publications Warehouse

Mooij, Wolf M.; DeAngelis, Donald L.

2003-01-01

Uncertainty in estimates of survival of dispersing animals is a vexing difficulty in conservation biology. The current notion is that this uncertainty decreases the usefulness of spatially explicit population models in particular. We examined this problem by comparing dispersal models of three levels of complexity: (1) an event-based binomial model that considers only the occurrence of mortality or arrival, (2) a temporally explicit exponential model that employs mortality and arrival rates, and (3) a spatially explicit grid-walk model that simulates the movement of animals through an artificial landscape. Each model was fitted to the same set of field data. A first objective of the paper is to illustrate how the maximum-likelihood method can be used in all three cases to estimate the means and confidence limits for the relevant model parameters, given a particular set of data on dispersal survival. Using this framework we show that the structure of the uncertainty for all three models is strikingly similar. In fact, the results of our unified approach imply that spatially explicit dispersal models, which take advantage of information on landscape details, suffer less from uncertainly than do simpler models. Moreover, we show that the proposed strategy of model development safeguards one from error propagation in these more complex models. Finally, our approach shows that all models related to animal dispersal, ranging from simple to complex, can be related in a hierarchical fashion, so that the various approaches to modeling such dispersal can be viewed from a unified perspective.

A multilevel model for cardiovascular disease prevalence in the US and its application to micro area prevalence estimates.

PubMed

Congdon, Peter

2009-01-30

Estimates of disease prevalence for small areas are increasingly required for the allocation of health funds according to local need. Both individual level and geographic risk factors are likely to be relevant to explaining prevalence variations, and in turn relevant to the procedure for small area prevalence estimation. Prevalence estimates are of particular importance for major chronic illnesses such as cardiovascular disease. A multilevel prevalence model for cardiovascular outcomes is proposed that incorporates both survey information on patient risk factors and the effects of geographic location. The model is applied to derive micro area prevalence estimates, specifically estimates of cardiovascular disease for Zip Code Tabulation Areas in the USA. The model incorporates prevalence differentials by age, sex, ethnicity and educational attainment from the 2005 Behavioral Risk Factor Surveillance System survey. Influences of geographic context are modelled at both county and state level, with the county effects relating to poverty and urbanity. State level influences are modelled using a random effects approach that allows both for spatial correlation and spatial isolates. To assess the importance of geographic variables, three types of model are compared: a model with person level variables only; a model with geographic effects that do not interact with person attributes; and a full model, allowing for state level random effects that differ by ethnicity. There is clear evidence that geographic effects improve statistical fit. Geographic variations in disease prevalence partly reflect the demographic composition of area populations. However, prevalence variations may also show distinct geographic 'contextual' effects. The present study demonstrates by formal modelling methods that improved explanation is obtained by allowing for distinct geographic effects (for counties and states) and for interaction between geographic and person variables. Thus an appropriate methodology to estimate prevalence at small area level should include geographic effects as well as person level demographic variables.

A multilevel model for cardiovascular disease prevalence in the US and its application to micro area prevalence estimates

PubMed Central

Congdon, Peter

2009-01-01

Background Estimates of disease prevalence for small areas are increasingly required for the allocation of health funds according to local need. Both individual level and geographic risk factors are likely to be relevant to explaining prevalence variations, and in turn relevant to the procedure for small area prevalence estimation. Prevalence estimates are of particular importance for major chronic illnesses such as cardiovascular disease. Methods A multilevel prevalence model for cardiovascular outcomes is proposed that incorporates both survey information on patient risk factors and the effects of geographic location. The model is applied to derive micro area prevalence estimates, specifically estimates of cardiovascular disease for Zip Code Tabulation Areas in the USA. The model incorporates prevalence differentials by age, sex, ethnicity and educational attainment from the 2005 Behavioral Risk Factor Surveillance System survey. Influences of geographic context are modelled at both county and state level, with the county effects relating to poverty and urbanity. State level influences are modelled using a random effects approach that allows both for spatial correlation and spatial isolates. Results To assess the importance of geographic variables, three types of model are compared: a model with person level variables only; a model with geographic effects that do not interact with person attributes; and a full model, allowing for state level random effects that differ by ethnicity. There is clear evidence that geographic effects improve statistical fit. Conclusion Geographic variations in disease prevalence partly reflect the demographic composition of area populations. However, prevalence variations may also show distinct geographic 'contextual' effects. The present study demonstrates by formal modelling methods that improved explanation is obtained by allowing for distinct geographic effects (for counties and states) and for interaction between geographic and person variables. Thus an appropriate methodology to estimate prevalence at small area level should include geographic effects as well as person level demographic variables. PMID:19183458

Effective Reading and Writing Instruction: A Focus on Modeling

ERIC Educational Resources Information Center

Regan, Kelley; Berkeley, Sheri

2012-01-01

When providing effective reading and writing instruction, teachers need to provide explicit modeling. Modeling is particularly important when teaching students to use cognitive learning strategies. Examples of how teachers can provide specific, explicit, and flexible instructional modeling is presented in the context of two evidence-based…

Cumulative biological impacts framework for solar energy projects in the California Desert

USGS Publications Warehouse

Davis, Frank W.; Kreitler, Jason R.; Soong, Oliver; Stoms, David M.; Dashiell, Stephanie; Hannah, Lee; Wilkinson, Whitney; Dingman, John

2013-01-01

This project developed analytical approaches, tools and geospatial data to support conservation planning for renewable energy development in the California deserts. Research focused on geographical analysis to avoid, minimize and mitigate the cumulative biological effects of utility-scale solar energy development. A hierarchical logic model was created to map the compatibility of new solar energy projects with current biological conservation values. The research indicated that the extent of compatible areas is much greater than the estimated land area required to achieve 2040 greenhouse gas reduction goals. Species distribution models were produced for 65 animal and plant species that were of potential conservation significance to the Desert Renewable Energy Conservation Plan process. These models mapped historical and projected future habitat suitability using 270 meter resolution climate grids. The results were integrated into analytical frameworks to locate potential sites for offsetting project impacts and evaluating the cumulative effects of multiple solar energy projects. Examples applying these frameworks in the Western Mojave Desert ecoregion show the potential of these publicly-available tools to assist regional planning efforts. Results also highlight the necessity to explicitly consider projected land use change and climate change when prioritizing areas for conservation and mitigation offsets. Project data, software and model results are all available online.

Estimates of vital rates for a declining loggerhead turtle (Caretta caretta) subpopulation: implications for management

USGS Publications Warehouse

Lamont, Margaret M.; Fujisaki, Ikuko; Carthy, Raymond R.

2014-01-01

Because subpopulations can differ geographically, genetically and/or phenotypically, using data from one subpopulation to derive vital rates for another, while often unavoidable, is not optimal. We used a two-state open robust design model to analyze a 14-year dataset (1998–2011) from the St. Joseph Peninsula, Florida (USA; 29.748°, −85.400°) which is the densest loggerhead (Caretta caretta) nesting beach in the Northern Gulf of Mexico subpopulation. For these analyses, 433 individuals were marked of which only 7.2 % were observed re-nesting in the study area in subsequent years during the study period. Survival was estimated at 0.86 and is among the highest estimates for all subpopulations in the Northwest Atlantic population. The robust model estimated a nesting assemblage size that ranged from 32 to 230 individuals each year with an annual average of 110. The model estimates indicated an overall population decline of 17 %. The results presented here for this nesting group represent the first estimates for this subpopulation. These data provide managers with information specific to this subpopulation that can be used to develop recovery plans and conduct subpopulation-specific modeling exercises explicit to the challenges faced by turtles nesting in this region.

Estimating carbon and showing impacts of drought using satellite data in regression-tree models

USGS Publications Warehouse

Boyte, Stephen; Wylie, Bruce K.; Howard, Danny; Dahal, Devendra; Gilmanov, Tagir G.

2018-01-01

Integrating spatially explicit biogeophysical and remotely sensed data into regression-tree models enables the spatial extrapolation of training data over large geographic spaces, allowing a better understanding of broad-scale ecosystem processes. The current study presents annual gross primary production (GPP) and annual ecosystem respiration (RE) for 2000–2013 in several short-statured vegetation types using carbon flux data from towers that are located strategically across the conterminous United States (CONUS). We calculate carbon fluxes (annual net ecosystem production [NEP]) for each year in our study period, which includes 2012 when drought and higher-than-normal temperatures influence vegetation productivity in large parts of the study area. We present and analyse carbon flux dynamics in the CONUS to better understand how drought affects GPP, RE, and NEP. Model accuracy metrics show strong correlation coefficients (r) (r ≥ 94%) between training and estimated data for both GPP and RE. Overall, average annual GPP, RE, and NEP are relatively constant throughout the study period except during 2012 when almost 60% less carbon is sequestered than normal. These results allow us to conclude that this modelling method effectively estimates carbon dynamics through time and allows the exploration of impacts of meteorological anomalies and vegetation types on carbon dynamics.

Modeling Forest Biomass and Growth: Coupling Long-Term Inventory and Lidar Data

NASA Technical Reports Server (NTRS)

Babcock, Chad; Finley, Andrew O.; Cook, Bruce D.; Weiskittel, Andrew; Woodall, Christopher W.

2016-01-01

Combining spatially-explicit long-term forest inventory and remotely sensed information from Light Detection and Ranging (LiDAR) datasets through statistical models can be a powerful tool for predicting and mapping above-ground biomass (AGB) at a range of geographic scales. We present and examine a novel modeling approach to improve prediction of AGB and estimate AGB growth using LiDAR data. The proposed model accommodates temporal misalignment between field measurements and remotely sensed data-a problem pervasive in such settings-by including multiple time-indexed measurements at plot locations to estimate AGB growth. We pursue a Bayesian modeling framework that allows for appropriately complex parameter associations and uncertainty propagation through to prediction. Specifically, we identify a space-varying coefficients model to predict and map AGB and its associated growth simultaneously. The proposed model is assessed using LiDAR data acquired from NASA Goddard's LiDAR, Hyper-spectral & Thermal imager and field inventory data from the Penobscot Experimental Forest in Bradley, Maine. The proposed model outperformed the time-invariant counterpart models in predictive performance as indicated by a substantial reduction in root mean squared error. The proposed model adequately accounts for temporal misalignment through the estimation of forest AGB growth and accommodates residual spatial dependence. Results from this analysis suggest that future AGB models informed using remotely sensed data, such as LiDAR, may be improved by adapting traditional modeling frameworks to account for temporal misalignment and spatial dependence using random effects.

Estimating nitrogen oxides emissions at city scale in China with a nightlight remote sensing model.

PubMed

Jiang, Jianhui; Zhang, Jianying; Zhang, Yangwei; Zhang, Chunlong; Tian, Guangming

2016-02-15

Increasing nitrogen oxides (NOx) emissions over the fast developing regions have been of great concern due to their critical associations with the aggravated haze and climate change. However, little geographically specific data exists for estimating spatio-temporal trends of NOx emissions. In order to quantify the spatial and temporal variations of NOx emissions, a spatially explicit approach based on the continuous satellite observations of artificial nighttime stable lights (NSLs) from the Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) was developed to estimate NOx emissions from the largest emission source of fossil fuel combustion. The NSL based model was established with three types of data including satellite data of nighttime stable lights, geographical data of administrative boundaries, and provincial energy consumptions in China, where a significant growth of NOx emission has experienced during three policy stages corresponding to the 9th-11th)Five-Year Plan (FYP, 1995-2010). The estimated national NOx emissions increased by 8.2% per year during the study period, and the total annual NOx emissions in China estimated by the NSL-based model were approximately 4.1%-13.8% higher than the previous estimates. The spatio-temporal variations of NOx emissions at city scale were then evaluated by the Moran's I indices. The global Moran's I indices for measuring spatial agglomerations of China's NOx emission increased by 50.7% during 1995-2010. Although the inland cities have shown larger contribution to the emission growth than the more developed coastal cities since 2005, the High-High clusters of NOx emission located in Beijing-Tianjin-Hebei regions, the Yangtze River Delta, and the Pearl River Delta should still be the major focus of NOx mitigation. Our results indicate that the readily available DMSP/OLS nighttime stable lights based model could be an easily accessible and effective tool for achieving strategic decision making toward NOx reduction. Copyright © 2015 Elsevier B.V. All rights reserved.

Social values for ecosystem services (SolVES): Documentation and user manual, version 2.0

USGS Publications Warehouse

Sherrouse, Benson C.; Semmens, Darius J.

2012-01-01

In response to the need for incorporating quantified and spatially explicit measures of social values into ecosystem services assessments, the Rocky Mountain Geographic Science Center (RMGSC), in collaboration with Colorado State University, developed a geographic information system (GIS) application, Social Values for Ecosystem Services (SolVES). With version 2.0 (SolVES 2.0), RMGSC has improved and extended the functionality of SolVES, which was designed to assess, map, and quantify the perceived social values of ecosystem services. Social values such as aesthetics, biodiversity, and recreation can be evaluated for various stakeholder groups as distinguished by their attitudes and preferences regarding public uses, such as motorized recreation and logging. As with the previous version, SolVES 2.0 derives a quantitative, 10-point, social-values metric, the Value Index, from a combination of spatial and nonspatial responses to public attitude and preference surveys and calculates metrics characterizing the underlying environment, such as average distance to water and dominant landcover. Additionally, SolVES 2.0 integrates Maxent maximum entropy modeling software to generate more complete social value maps and to produce robust statistical models describing the relationship between the social values maps and explanatory environmental variables. The performance of these models can be evaluated for a primary study area, as well as for similar areas where primary survey data are not available but where social value mapping could potentially be completed using value-transfer methodology. SolVES 2.0 also introduces the flexibility for users to define their own social values and public uses, model any number and type of environmental variable, and modify the spatial resolution of analysis. With these enhancements, SolVES 2.0 provides an improved public domain tool for decisionmakers and researchers to evaluate the social values of ecosystem services and to facilitate discussions among diverse stakeholders regarding the tradeoffs among different ecosystem services in a variety of physical and social contexts ranging from forest and rangeland to coastal and marine.

Spatially explicit modeling of animal tuberculosis at the wildlife-livestock interface in Ciudad Real province, Spain.

PubMed

LaHue, Nathaniel P; Baños, Joaquín Vicente; Acevedo, Pelayo; Gortázar, Christian; Martínez-López, Beatriz

2016-06-01

Eurasian wild boar (Sus scrofa) and red deer (Cervus elaphus) are the most important wildlife reservoirs for animal tuberculosis (TB) caused by the Mycobacterium tuberculosis complex (MTC), in Mediterranean Spain. These species are considered to play an important role in the transmission and persistence of MTC in cattle in some regions; however the factors contributing to the risk of transmission at the wildlife-livestock interface and the areas at highest risk for such transmission are largely unknown. This study sought to identify geographic areas where wildlife-livestock interactions are most likely to occur and to characterize the environmental and management factors at this interface contributing to persistence, incidence, and occurrence of TB on cattle farms, in one of the provinces with higher TB prevalence in Spain, Ciudad Real. We used spatially explicit, ecological niche models to evaluate the importance of factors such as wildlife demographics and hunting management, land use, climatic, and environmental variables as well as TB status in wildlife for TB breakdown (model 1), persistence (model 2) and new infection (model 3) on cattle farms and to generate high resolution maps of predicted TB occurrence to guide risk-based interventions. Models revealed that land use, particularly open area and woodland, high wild boar TB prevalence, and close proximity to fenced hunting estates were the most important factors associated with TB infection on cattle farms. This is the first time that local TB prevalence in wild boar for individual hunting estates has been significantly associated with TB occurrence on cattle farms at a local scale. Prediction maps identified two areas with high likelihood of TB occurrence in the southwest and northwest of the province where wildlife-livestock interactions and TB occurrence are highly likely and where TB preventative and mitigation strategies (e.g. targeted vaccination, increased biosecurity, etc.) should be prioritized. Methods and results of this study were aimed to inform the implementation of risk-based interventions to better prevent and control TB at the wildlife-livestock interface, a necessary step for the successful eradication of TB in cattle in Spain. Copyright © 2016 Elsevier B.V. All rights reserved.

Explicit continuous charge-based compact model for long channel heavily doped surrounding-gate MOSFETs incorporating interface traps and quantum effects

NASA Astrophysics Data System (ADS)

Hamzah, Afiq; Hamid, Fatimah A.; Ismail, Razali

2016-12-01

An explicit solution for long-channel surrounding-gate (SRG) MOSFETs is presented from intrinsic to heavily doped body including the effects of interface traps and fixed oxide charges. The solution is based on the core SRGMOSFETs model of the Unified Charge Control Model (UCCM) for heavily doped conditions. The UCCM model of highly doped SRGMOSFETs is derived to obtain the exact equivalent expression as in the undoped case. Taking advantage of the undoped explicit charge-based expression, the asymptotic limits for below threshold and above threshold have been redefined to include the effect of trap states for heavily doped cases. After solving the asymptotic limits, an explicit mobile charge expression is obtained which includes the trap state effects. The explicit mobile charge model shows very good agreement with respect to numerical simulation over practical terminal voltages, doping concentration, geometry effects, and trap state effects due to the fixed oxide charges and interface traps. Then, the drain current is obtained using the Pao-Sah's dual integral, which is expressed as a function of inversion charge densities at the source/drain ends. The drain current agreed well with the implicit solution and numerical simulation for all regions of operation without employing any empirical parameters. A comparison with previous explicit models has been conducted to verify the competency of the proposed model with the doping concentration of 1× {10}19 {{cm}}-3, as the proposed model has better advantages in terms of its simplicity and accuracy at a higher doping concentration.

From Cycle Rooted Spanning Forests to the Critical Ising Model: an Explicit Construction

NASA Astrophysics Data System (ADS)

de Tilière, Béatrice

2013-04-01

Fisher established an explicit correspondence between the 2-dimensional Ising model defined on a graph G and the dimer model defined on a decorated version {{G}} of this graph (Fisher in J Math Phys 7:1776-1781, 1966). In this paper we explicitly relate the dimer model associated to the critical Ising model and critical cycle rooted spanning forests (CRSFs). This relation is established through characteristic polynomials, whose definition only depends on the respective fundamental domains, and which encode the combinatorics of the model. We first show a matrix-tree type theorem establishing that the dimer characteristic polynomial counts CRSFs of the decorated fundamental domain {{G}_1}. Our main result consists in explicitly constructing CRSFs of {{G}_1} counted by the dimer characteristic polynomial, from CRSFs of G 1, where edges are assigned Kenyon's critical weight function (Kenyon in Invent Math 150(2):409-439, 2002); thus proving a relation on the level of configurations between two well known 2-dimensional critical models.

Geographic variations of ecosystem service intensity in Fuzhou City, China.

PubMed

Hu, Xisheng; Hong, Wei; Qiu, Rongzu; Hong, Tao; Chen, Can; Wu, Chengzhen

2015-04-15

Ecosystem services are strongly influenced by the landscape configuration of natural and human systems. So they are heterogeneous across landscapes. However lack of the knowledge of spatial variations of ecosystem services constrains the effective management and conservation of ecosystems. We presented a spatially explicit and quantitative assessment of the geographic variations in ecosystem services for the Fuzhou City in 2009 using exploratory spatial data analysis (ESDA) and semivariance analysis. Results confirmed a significant and positive spatial autocorrelation, and revealed several hot-spots and cold-spots for the spatial distribution of ecosystem service intensity (ESI) in the study area. Also the trend surface analysis indicated that the level of ESI tended to be reduced gradually from north to south and from west to east, with a trough in the urban central area, which was quite in accordance with land-use structure. A more precise cluster map was then developed using the range of lag distance, deriving from semivariance analysis, as neighborhood size instead of default value in the software of ESRI ArcGIS 10.0, and geographical clusters where population growth and land-use pressure varied significantly and positively with ESI across the city were also created by geographically weighted regression (GWR). This study has good policy implications applicable to prioritize areas for conservation or construction, and design ecological corridor to improve ecosystem service delivery to benefiting areas. Copyright © 2015 Elsevier B.V. All rights reserved.

An explicit microphysics thunderstorm model.

Treesearch

R. Solomon; C.M. Medaglia; C. Adamo; S. Dietrick; A. Mugnai; U. Biader Ceipidor

2005-01-01

The authors present a brief description of a 1.5-dimensional thunderstorm model with a lightning parameterization that utilizes an explicit microphysical scheme to model lightning-producing clouds. The main intent of this work is to describe the basic microphysical and electrical properties of the model, with a small illustrative section to show how the model may be...

Graph-based analysis of connectivity in spatially-explicit population models: HexSim and the Connectivity Analysis Toolkit

EPA Science Inventory

Background / Question / Methods Planning for the recovery of threatened species is increasingly informed by spatially-explicit population models. However, using simulation model results to guide land management decisions can be difficult due to the volume and complexity of model...

CONSTRUCTING, PERTURBATION ANALYSIIS AND TESTING OF A MULTI-HABITAT PERIODIC MATRIX POPULATION MODEL

EPA Science Inventory

We present a matrix model that explicitly incorporates spatial habitat structure and seasonality and discuss preliminary results from a landscape level experimental test. Ecological risk to populations is often modeled without explicit treatment of spatially or temporally distri...

Green-Ampt approximations: A comprehensive analysis

NASA Astrophysics Data System (ADS)

Ali, Shakir; Islam, Adlul; Mishra, P. K.; Sikka, Alok K.

2016-04-01

Green-Ampt (GA) model and its modifications are widely used for simulating infiltration process. Several explicit approximate solutions to the implicit GA model have been developed with varying degree of accuracy. In this study, performance of nine explicit approximations to the GA model is compared with the implicit GA model using the published data for broad range of soil classes and infiltration time. The explicit GA models considered are Li et al. (1976) (LI), Stone et al. (1994) (ST), Salvucci and Entekhabi (1994) (SE), Parlange et al. (2002) (PA), Barry et al. (2005) (BA), Swamee et al. (2012) (SW), Ali et al. (2013) (AL), Almedeij and Esen (2014) (AE), and Vatankhah (2015) (VA). Six statistical indicators (e.g., percent relative error, maximum absolute percent relative error, average absolute percent relative errors, percent bias, index of agreement, and Nash-Sutcliffe efficiency) and relative computer computation time are used for assessing the model performance. Models are ranked based on the overall performance index (OPI). The BA model is found to be the most accurate followed by the PA and VA models for variety of soil classes and infiltration periods. The AE, SW, SE, and LI model also performed comparatively better. Based on the overall performance index, the explicit models are ranked as BA > PA > VA > LI > AE > SE > SW > ST > AL. Results of this study will be helpful in selection of accurate and simple explicit approximate GA models for solving variety of hydrological problems.

Facilitating CCS Business Planning by Extending the Functionality of the SimCCS Integrated System Model

DOE PAGES

Ellett, Kevin M.; Middleton, Richard S.; Stauffer, Philip H.; ...

2017-08-18

The application of integrated system models for evaluating carbon capture and storage technology has expanded steadily over the past few years. To date, such models have focused largely on hypothetical scenarios of complex source-sink matching involving numerous large-scale CO 2 emitters, and high-volume, continuous reservoirs such as deep saline formations to function as geologic sinks for carbon storage. Though these models have provided unique insight on the potential costs and feasibility of deploying complex networks of integrated infrastructure, there remains a pressing need to translate such insight to the business community if this technology is to ever achieve a trulymore » meaningful impact in greenhouse gas mitigation. Here, we present a new integrated system modelling tool termed SimCCUS aimed at providing crucial decision support for businesses by extending the functionality of a previously developed model called SimCCS. The primary innovation of the SimCCUS tool development is the incorporation of stacked geological reservoir systems with explicit consideration of processes and costs associated with the operation of multiple CO 2 utilization and storage targets from a single geographic location. In such locations provide significant efficiencies through economies of scale, effectively minimizing CO 2 storage costs while simultaneously maximizing revenue streams via the utilization of CO 2 as a commodity for enhanced hydrocarbon recovery.« less

Finite Element Analysis of Saferooms Subjected to Tornado Impact Loads

NASA Astrophysics Data System (ADS)

Parfilko, Y.; Amaral de Arruda, F.; Varela, B.

2017-10-01

A Tornado is one of the most dreadful and unpredictable events in nature. Unfortunately, weather and geographic conditions make a large portion of the United States prone to this phenomenon. Tornado saferooms are monolithic reinforced concrete protective structures engineered to guard against these natural disasters. Saferooms must withstand impacts and wind loads from EF-5 tornadoes - where the wind speed reaches up to 150 m/s (300 mph) and airborne projectiles can reach up to 50 m/s (100 mph). The objective of this work is to evaluate the performance of a saferoom under impact from tornado-generated debris and tornado-dragged vehicles. Numerical simulations were performed to model the impact problem using explicit dynamics and energy methods. Finite element models of the saferoom, windborne debris, and vehicle models were studied using the LS-DYNA software. RHT concrete material was used to model the saferoom and vehicle models from NCAC were used to characterize damage from impacts at various speeds. Simulation results indicate good performance of the saferoom structure at vehicle impact speeds up to 25 meters per second. Damage is more significant and increases nonlinearly starting at impact velocities of 35 m/s (78 mph). Results of this study give valuable insight into the dynamic response of saferooms subjected to projectile impacts, and provide design considerations for civilian protective structures. Further work is being done to validate the models with experimental measurements.

Facilitating CCS Business Planning by Extending the Functionality of the SimCCS Integrated System Model

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

Ellett, Kevin M.; Middleton, Richard S.; Stauffer, Philip H.

The application of integrated system models for evaluating carbon capture and storage technology has expanded steadily over the past few years. To date, such models have focused largely on hypothetical scenarios of complex source-sink matching involving numerous large-scale CO 2 emitters, and high-volume, continuous reservoirs such as deep saline formations to function as geologic sinks for carbon storage. Though these models have provided unique insight on the potential costs and feasibility of deploying complex networks of integrated infrastructure, there remains a pressing need to translate such insight to the business community if this technology is to ever achieve a trulymore » meaningful impact in greenhouse gas mitigation. Here, we present a new integrated system modelling tool termed SimCCUS aimed at providing crucial decision support for businesses by extending the functionality of a previously developed model called SimCCS. The primary innovation of the SimCCUS tool development is the incorporation of stacked geological reservoir systems with explicit consideration of processes and costs associated with the operation of multiple CO 2 utilization and storage targets from a single geographic location. In such locations provide significant efficiencies through economies of scale, effectively minimizing CO 2 storage costs while simultaneously maximizing revenue streams via the utilization of CO 2 as a commodity for enhanced hydrocarbon recovery.« less

Ensemble forecasting of potential habitat for three invasive fishes

USGS Publications Warehouse

Poulos, Helen M.; Chernoff, Barry; Fuller, Pam L.; Butman, David

2012-01-01

Aquatic invasive species pose major ecological and economic threats to aquatic ecosystems worldwide via displacement, predation, or hybridization with native species and the alteration of aquatic habitats and hydrologic cycles. Modeling the habitat suitability of alien aquatic species through spatially explicit mapping is an increasingly important risk assessment tool. Habitat modeling also facilitates identification of key environmental variables influencing invasive species distributions. We compared four modeling methods to predict the potential continental United States distributions of northern snakehead Channa argus (Cantor, 1842), round goby Neogobius melanostomus (Pallas, 1814), and silver carp Hypophthalmichthys molitrix (Valenciennes, 1844) using maximum entropy (Maxent), the genetic algorithm for rule set production (GARP), DOMAIN, and support vector machines (SVM). We used inventory records from the USGS Nonindigenous Aquatic Species Database and a geographic information system of 20 climatic and environmental variables to generate individual and ensemble distribution maps for each species. The ensemble maps from our study performed as well as or better than all of the individual models except Maxent. The ensemble and Maxent models produced significantly higher accuracy individual maps than GARP, one-class SVMs, or DOMAIN. The key environmental predictor variables in the individual models were consistent with the tolerances of each species. Results from this study provide insights into which locations and environmental conditions may promote the future spread of invasive fish in the US.

Application of the NASA A-Train to Evaluate Clouds Simulated by the Weather Research and Forecast Model

NASA Technical Reports Server (NTRS)

Molthan, Andrew L.; Jedlovec, Gary J.; Lapenta, William M.

2008-01-01

The CloudSat Mission, part of the NASA A-Train, is providing the first global survey of cloud profiles and cloud physical properties, observing seasonal and geographical variations that are pertinent to evaluating the way clouds are parameterized in weather and climate forecast models. CloudSat measures the vertical structure of clouds and precipitation from space through the Cloud Profiling Radar (CPR), a 94 GHz nadir-looking radar measuring the power backscattered by clouds as a function of distance from the radar. One of the goals of the CloudSat mission is to evaluate the representation of clouds in forecast models, thereby contributing to improved predictions of weather, climate and the cloud-climate feedback problem. This paper highlights potential limitations in cloud microphysical schemes currently employed in the Weather Research and Forecast (WRF) modeling system. The horizontal and vertical structure of explicitly simulated cloud fields produced by the WRF model at 4-km resolution are being evaluated using CloudSat observations in concert with products derived from MODIS and AIRS. A radiative transfer model is used to produce simulated profiles of radar reflectivity given WRF input profiles of hydrometeor mixing ratios and ambient atmospheric conditions. The preliminary results presented in the paper will compare simulated and observed reflectivity fields corresponding to horizontal and vertical cloud structures associated with midlatitude cyclone events.

RIPGIS-NET: a GIS tool for riparian groundwater evapotranspiration in MODFLOW.

PubMed

Ajami, Hoori; Maddock, Thomas; Meixner, Thomas; Hogan, James F; Guertin, D Phillip

2012-01-01

RIPGIS-NET, an Environmental System Research Institute (ESRI's) ArcGIS 9.2/9.3 custom application, was developed to derive parameters and visualize results of spatially explicit riparian groundwater evapotranspiration (ETg), evapotranspiration from saturated zone, in groundwater flow models for ecohydrology, riparian ecosystem management, and stream restoration. Specifically RIPGIS-NET works with riparian evapotranspiration (RIP-ET), a modeling package that works with the MODFLOW groundwater flow model. RIP-ET improves ETg simulations by using a set of eco-physiologically based ETg curves for plant functional subgroups (PFSGs), and separates ground evaporation and plant transpiration processes from the water table. The RIPGIS-NET program was developed in Visual Basic 2005, .NET framework 2.0, and runs in ArcMap 9.2 and 9.3 applications. RIPGIS-NET, a pre- and post-processor for RIP-ET, incorporates spatial variability of riparian vegetation and land surface elevation into ETg estimation in MODFLOW groundwater models. RIPGIS-NET derives RIP-ET input parameters including PFSG evapotranspiration curve parameters, fractional coverage areas of each PFSG in a MODFLOW cell, and average surface elevation per riparian vegetation polygon using a digital elevation model. RIPGIS-NET also provides visualization tools for modelers to create head maps, depth to water table (DTWT) maps, and plot DTWT for a PFSG in a polygon in the Geographic Information System based on MODFLOW simulation results. © 2011, The Author(s). Ground Water © 2011, National Ground Water Association.

Direct versus Indirect Explicit Methods of Enhancing EFL Students' English Grammatical Competence: A Concept Checking-Based Consciousness-Raising Tasks Model

ERIC Educational Resources Information Center

Dang, Trang Thi Doan; Nguyen, Huong Thu

2013-01-01

Two approaches to grammar instruction are often discussed in the ESL literature: direct explicit grammar instruction (DEGI) (deduction) and indirect explicit grammar instruction (IEGI) (induction). This study aims to explore the effects of indirect explicit grammar instruction on EFL learners' mastery of English tenses. Ninety-four…

Genome-wide SNPs reveal the drivers of gene flow in an urban population of the Asian Tiger Mosquito, Aedes albopictus.

PubMed

Schmidt, Thomas L; Rašić, Gordana; Zhang, Dongjing; Zheng, Xiaoying; Xi, Zhiyong; Hoffmann, Ary A

2017-10-01

Aedes albopictus is a highly invasive disease vector with an expanding worldwide distribution. Genetic assays using low to medium resolution markers have found little evidence of spatial genetic structure even at broad geographic scales, suggesting frequent passive movement along human transportation networks. Here we analysed genetic structure of Aedes albopictus collected from 12 sample sites in Guangzhou, China, using thousands of genome-wide single nucleotide polymorphisms (SNPs). We found evidence for passive gene flow, with distance from shipping terminals being the strongest predictor of genetic distance among mosquitoes. As further evidence of passive dispersal, we found multiple pairs of full-siblings distributed between two sample sites 3.7 km apart. After accounting for geographical variability, we also found evidence for isolation by distance, previously undetectable in Ae. albopictus. These findings demonstrate how large SNP datasets and spatially-explicit hypothesis testing can be used to decipher processes at finer geographic scales than formerly possible. Our approach can be used to help predict new invasion pathways of Ae. albopictus and to refine strategies for vector control that involve the transformation or suppression of mosquito populations.

Spatiotemporal variation in local adaptation of a specialist insect herbivore to its long-lived host plant.

PubMed

Kalske, Aino; Leimu, Roosa; Scheepens, J F; Mutikainen, Pia

2016-09-01

Local adaptation of interacting species to one another indicates geographically variable reciprocal selection. This process of adaptation is central in the organization and maintenance of genetic variation across populations. Given that the strength of selection and responses to it often vary in time and space, the strength of local adaptation should in theory vary between generations and among populations. However, such spatiotemporal variation has rarely been explicitly demonstrated in nature and local adaptation is commonly considered to be relatively static. We report persistent local adaptation of the short-lived herbivore Abrostola asclepiadis to its long-lived host plant Vincetoxicum hirundinaria over three successive generations in two studied populations and considerable temporal variation in local adaptation in six populations supporting the geographic mosaic theory. The observed variation in local adaptation among populations was best explained by geographic distance and population isolation, suggesting that gene flow reduces local adaptation. Changes in herbivore population size did not conclusively explain temporal variation in local adaptation. Our results also imply that short-term studies are likely to capture only a part of the existing variation in local adaptation. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

Global Health, Geographical Contingency, and Contingent Geographies

PubMed Central

Herrick, Clare

2016-01-01

Health geography has emerged from under the “shadow of the medical” to become one of the most vibrant of all the subdisciplines. Yet, this success has also meant that health research has become increasingly siloed within this subdisciplinary domain. As this article explores, this represents a potential lost opportunity with regard to the study of global health, which has instead come to be dominated by anthropology and political science. Chief among the former's concerns are exploring the gap between the programmatic intentions of global health and the unintended or unanticipated consequences of their deployment. This article asserts that recent work on contingency within geography offers significant conceptual potential for examining this gap. It therefore uses the example of alcohol taxation in Botswana, an emergent global health target and tool, to explore how geographical contingency and the emergent, contingent geographies that result might help counter the prevailing tendency for geography to be side-stepped within critical studies of global health. At the very least, then, this intervention aims to encourage reflection by geographers on how to make explicit the all-too-often implicit links between their research and global health debates located outside the discipline. PMID:27611662

DEFINING RECOVERY GOALS AND STRATEGIES FOR ENDANGERED SPECIES USING SPATIALLY-EXPLICIT POPULATION MODELS

EPA Science Inventory

We used a spatially explicit population model of wolves (Canis lupus) to propose a framework for defining rangewide recovery priorities and finer-scale strategies for regional reintroductions. The model predicts that Yellowstone and central Idaho, where wolves have recently been ...

Behavioral mechanisms in HIV epidemiology and prevention: past, present, and future roles.

PubMed

Bingenheimer, Jeffrey B; Geronimus, Arline T

2009-09-01

In the 1980s, behavioral variations across geographically and socially defined populations were the central focus of AIDS research, and behavior change was seen as the primary means of controlling HIV epidemics. Today, biological mechanisms--especially other sexually transmitted infections, antiretroviral therapy, and male circumcision--predominate in HIV epidemiology and prevention. We describe several reasons for this shift in emphasis. Although the shift is understandable, we argue for a sustained focus on behavioral mechanisms in HIV research in order to realize the theoretical promise of interventions targeting the biological aspects of HIV risk. We also provide evidence to suggest that large reductions in HIV prevalence may be accomplished by small changes in behavior. Moreover, we contend that behavioral mechanisms will find their proper place in HIV epidemiology and prevention only when investigators adopt a conceptual model that treats prevalence as a determinant as well as an outcome of behavior and that explicitly recognizes the dynamic interdependence between behavior and other epidemiological and demographic parameters.

The ecology of primate material culture.

PubMed

Koops, Kathelijne; Visalberghi, Elisabetta; van Schaik, Carel P

2014-11-01

Tool use in extant primates may inform our understanding of the conditions that favoured the expansion of hominin technology and material culture. The 'method of exclusion' has, arguably, confirmed the presence of culture in wild animal populations by excluding ecological and genetic explanations for geographical variation in behaviour. However, this method neglects ecological influences on culture, which, ironically, may be critical for understanding technology and thus material culture. We review all the current evidence for the role of ecology in shaping material culture in three habitual tool-using non-human primates: chimpanzees, orangutans and capuchin monkeys. We show that environmental opportunity, rather than necessity, is the main driver. We argue that a better understanding of primate technology requires explicit investigation of the role of ecological conditions. We propose a model in which three sets of factors, namely environment, sociality and cognition, influence invention, transmission and retention of material culture. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Addressing the determinants of child mental health: intersectionality as a guide to primary health care renewal.

PubMed

McPherson, Charmaine M; McGibbon, Elizabeth A

2010-09-01

Primary health care (PHC) renewal was designed explicitly to attend to the multidimensional factors impacting on health, including the social determinants of health. These determinants are central considerations in the development of integrated, cross-sectoral, and multi-jurisdictional policies such as those that inform models of shared mental health care for children. However, there are complex theoretical challenges in translating these multidimensional issues into policy. One of these is the rarely discussed interrelationships among the social determinants of health and identities such as race, gender, age, sexuality, and social class within the added confluence of geographic contexts. An intersectionality lens is used to examine the complex interrelationships among the factors affecting child mental health and the associated policy challenges surrounding PHC renewal. The authors argue that an understanding of the intersections of social determinants of health, identity, and geography is pivotal in guiding policy-makers as they address child mental health inequities using a PHC renewal agenda.

Human Appropriation of Net Primary Production - Can Earth Keep Up?

NASA Technical Reports Server (NTRS)

Imhoff, Marc L.

2006-01-01

The amount of Earth's vegetation or net primary production required to support human activities is powerful measure of aggregate human impacts on the biosphere. Biophysical models applied to consumption statistics were used to estimate the annual amount of net primary production in the form of elemental carbon required for food, fibre, and fuel-wood by the global population. The calculations were then compared to satellite-based estimates of Earth's average net primary production to produce a geographically explicit balance sheet of net primary production "supply" and "demand". Humans consume 20% of Earth's net primary production (11.5 petagrams carbon) annually and this percentage varies regionally from 6% (South America) to over 70% (Europe and Asia), and locally from near 0% (central Australia) to over 30,000% (New York City, USA). The uneven footprint of human consumption and related environmental impacts, indicate the degree to which human populations are vulnerable to climate change and suggest policy options for slowing future growth of NPP demand.

Place-based social contact and mixing: a typology of generic meeting places of relevance for infectious disease transmission.

PubMed

Strömgren, M; Holm, E; Dahlström, Ö; Ekberg, J; Eriksson, H; Spreco, A; Timpka, T

2017-09-01

This study aims to develop a typology of generic meeting places based on social contact and mixing of relevance for infectious disease transmission. Data were collected by means of a contact diary survey conducted on a representative sample of the Swedish population. The typology is derived from a cluster analysis accounting for four dimensions associated with transmission risk: visit propensity and its characteristics in terms of duration, number of other persons present and likelihood of physical contact. In the analysis, we also study demographic, socio-economic and geographical differences in the propensity of visiting meeting places. The typology identifies the family venue, the fixed activity site, the family vehicle, the trading plaza and the social network hub as generic meeting places. The meeting place typology represents a spatially explicit account of social contact and mixing relevant to infectious disease modelling, where the social context of the outbreak can be highlighted in light of the actual infectious disease.

Consequences of environmental and biological variances for range margins: a spatially explicit theoretical model

NASA Astrophysics Data System (ADS)

Malanson, G. P.; DeRose, R. J.; Bekker, M. F.

2016-12-01

The consequences of increasing climatic variance while including variability among individuals and populations are explored for range margins of species with a spatially explicit simulation. The model has a single environmental gradient and a single species then extended to two species. Species response to the environment is a Gaussian function with a peak of 1.0 at their peak fitness on the gradient. The variance in the environment is taken from the total variance in the tree ring series of 399 individuals of Pinus edulis in FIA plots in the western USA. The variability is increased by a multiplier of the standard deviation for various doubling times. The variance of individuals in the simulation is drawn from these same series. Inheritance of individual variability is based on the geographic locations of the individuals. The variance for P. edulis is recomputed as time-dependent conditional standard deviations using the GARCH procedure. Establishment and mortality are simulated in a Monte Carlo process with individual variance. Variance for P. edulis does not show a consistent pattern of heteroscedasticity. An obvious result is that increasing variance has deleterious effects on species persistence because extreme events that result in extinctions cannot be balanced by positive anomalies, but even less extreme negative events cannot be balanced by positive anomalies because of biological and spatial constraints. In the two species model the superior competitor is more affected by increasing climatic variance because its response function is steeper at the point of intersection with the other species and so the uncompensated effects of negative anomalies are greater for it. These theoretical results can guide the anticipated need to mitigate the effects of increasing climatic variability on P. edulis range margins. The trailing edge, here subject to increasing drought stress with increasing temperatures, will be more affected by negative anomalies.

Comparison of the spatial patterns of schistosomiasis in Zimbabwe at two points in time, spaced twenty-nine years apart: is climate variability of importance?

PubMed

Pedersen, Ulrik B; Karagiannis-Voules, Dimitrios-Alexios; Midzi, Nicholas; Mduluza, Tkafira; Mukaratirwa, Samson; Fensholt, Rasmus; Vennervald, Birgitte J; Kristensen, Thomas K; Vounatsou, Penelope; Stensgaard, Anna-Sofie

2017-05-08

Temperature, precipitation and humidity are known to be important factors for the development of schistosome parasites as well as their intermediate snail hosts. Climate therefore plays an important role in determining the geographical distribution of schistosomiasis and it is expected that climate change will alter distribution and transmission patterns. Reliable predictions of distribution changes and likely transmission scenarios are key to efficient schistosomiasis intervention-planning. However, it is often difficult to assess the direction and magnitude of the impact on schistosomiasis induced by climate change, as well as the temporal transferability and predictive accuracy of the models, as prevalence data is often only available from one point in time. We evaluated potential climate-induced changes on the geographical distribution of schistosomiasis in Zimbabwe using prevalence data from two points in time, 29 years apart; to our knowledge, this is the first study investigating this over such a long time period. We applied historical weather data and matched prevalence data of two schistosome species (Schistosoma haematobium and S. mansoni). For each time period studied, a Bayesian geostatistical model was fitted to a range of climatic, environmental and other potential risk factors to identify significant predictors that could help us to obtain spatially explicit schistosomiasis risk estimates for Zimbabwe. The observed general downward trend in schistosomiasis prevalence for Zimbabwe from 1981 and the period preceding a survey and control campaign in 2010 parallels a shift towards a drier and warmer climate. However, a statistically significant relationship between climate change and the change in prevalence could not be established.

On Spatially Explicit Models of Cholera Epidemics: Hydrologic controls, environmental drivers, human-mediated transmissions (Invited)

NASA Astrophysics Data System (ADS)

Rinaldo, A.; Bertuzzo, E.; Mari, L.; Righetto, L.; Gatto, M.; Casagrandi, R.; Rodriguez-Iturbe, I.

2010-12-01

A recently proposed model for cholera epidemics is examined. The model accounts for local communities of susceptibles and infectives in a spatially explicit arrangement of nodes linked by networks having different topologies. The vehicle of infection (Vibrio cholerae) is transported through the network links which are thought of as hydrological connections among susceptible communities. The mathematical tools used are borrowed from general schemes of reactive transport on river networks acting as the environmental matrix for the circulation and mixing of water-borne pathogens. The results of a large-scale application to the Kwa Zulu (Natal) epidemics of 2001-2002 will be discussed. Useful theoretical results derived in the spatially-explicit context will also be reviewed (like e.g. the exact derivation of the speed of propagation for traveling fronts of epidemics on regular lattices endowed with uniform population density). Network effects will be discussed. The analysis of the limit case of uniformly distributed population density proves instrumental in establishing the overall conditions for the relevance of spatially explicit models. To that extent, it is shown that the ratio between spreading and disease outbreak timescales proves the crucial parameter. The relevance of our results lies in the major differences potentially arising between the predictions of spatially explicit models and traditional compartmental models of the SIR-like type. Our results suggest that in many cases of real-life epidemiological interest timescales of disease dynamics may trigger outbreaks that significantly depart from the predictions of compartmental models. Finally, a view on further developments includes: hydrologically improved aquatic reservoir models for pathogens; human mobility patterns affecting disease propagation; double-peak emergence and seasonality in the spatially explicit epidemic context.

The Use of a Predictive Habitat Model and a Fuzzy Logic Approach for Marine Management and Planning

PubMed Central

Hattab, Tarek; Ben Rais Lasram, Frida; Albouy, Camille; Sammari, Chérif; Romdhane, Mohamed Salah; Cury, Philippe; Leprieur, Fabien; Le Loc’h, François

2013-01-01

Bottom trawl survey data are commonly used as a sampling technique to assess the spatial distribution of commercial species. However, this sampling technique does not always correctly detect a species even when it is present, and this can create significant limitations when fitting species distribution models. In this study, we aim to test the relevance of a mixed methodological approach that combines presence-only and presence-absence distribution models. We illustrate this approach using bottom trawl survey data to model the spatial distributions of 27 commercially targeted marine species. We use an environmentally- and geographically-weighted method to simulate pseudo-absence data. The species distributions are modelled using regression kriging, a technique that explicitly incorporates spatial dependence into predictions. Model outputs are then used to identify areas that met the conservation targets for the deployment of artificial anti-trawling reefs. To achieve this, we propose the use of a fuzzy logic framework that accounts for the uncertainty associated with different model predictions. For each species, the predictive accuracy of the model is classified as ‘high’. A better result is observed when a large number of occurrences are used to develop the model. The map resulting from the fuzzy overlay shows that three main areas have a high level of agreement with the conservation criteria. These results align with expert opinion, confirming the relevance of the proposed methodology in this study. PMID:24146867

From descriptive to predictive distribution models: a working example with Iberian amphibians and reptiles.

PubMed

Arntzen, J W

2006-05-04

Aim of the study was to identify the conditions under which spatial-environmental models can be used for the improved understanding of species distributions, under the explicit criterion of model predictive performance. I constructed distribution models for 17 amphibian and 21 reptile species in Portugal from atlas data and 13 selected ecological variables with stepwise logistic regression and a geographic information system. Models constructed for Portugal were extrapolated over Spain and tested against range maps and atlas data. Descriptive model precision ranged from 'fair' to 'very good' for 12 species showing a range border inside Portugal ('edge species', kappa (k) 0.35-0.89, average 0.57) and was at best 'moderate' for 26 species with a countrywide Portuguese distribution ('non-edge species', k = 0.03-0.54, average 0.29). The accuracy of the prediction for Spain was significantly related to the precision of the descriptive model for the group of edge species and not for the countrywide species. In the latter group data were consistently better captured with the single variable search-effort than by the panel of environmental data. Atlas data in presence-absence format are often inadequate to model the distribution of species if the considered area does not include part of the range border. Conversely, distribution models for edge-species, especially those displaying high precision, may help in the correct identification of parameters underlying the species range and assist with the informed choice of conservation measures.

Spatially explicit watershed modeling: tracking water, mercury and nitrogen in multiple systems under diverse conditions

EPA Science Inventory

Environmental decision-making and the influences of various stressors, such as landscape and climate changes on water quantity and quality, requires the application of environmental modeling. Spatially explicit environmental and watershed-scale models using GIS as a base framewor...

HexSim - A general purpose framework for spatially-explicit, individual-based modeling

EPA Science Inventory

HexSim is a framework for constructing spatially-explicit, individual-based computer models designed for simulating terrestrial wildlife population dynamics and interactions. HexSim is useful for a broad set of modeling applications. This talk will focus on a subset of those ap...

Studies of implicit and explicit solution techniques in transient thermal analysis of structures

NASA Technical Reports Server (NTRS)

Adelman, H. M.; Haftka, R. T.; Robinson, J. C.

1982-01-01

Studies aimed at an increase in the efficiency of calculating transient temperature fields in complex aerospace vehicle structures are reported. The advantages and disadvantages of explicit and implicit algorithms are discussed and a promising set of implicit algorithms with variable time steps, known as GEARIB, is described. Test problems, used for evaluating and comparing various algorithms, are discussed and finite element models of the configurations are described. These problems include a coarse model of the Space Shuttle wing, an insulated frame tst article, a metallic panel for a thermal protection system, and detailed models of sections of the Space Shuttle wing. Results generally indicate a preference for implicit over explicit algorithms for transient structural heat transfer problems when the governing equations are stiff (typical of many practical problems such as insulated metal structures). The effects on algorithm performance of different models of an insulated cylinder are demonstrated. The stiffness of the problem is highly sensitive to modeling details and careful modeling can reduce the stiffness of the equations to the extent that explicit methods may become the best choice. Preliminary applications of a mixed implicit-explicit algorithm and operator splitting techniques for speeding up the solution of the algebraic equations are also described.

Studies of implicit and explicit solution techniques in transient thermal analysis of structures

NASA Astrophysics Data System (ADS)

Adelman, H. M.; Haftka, R. T.; Robinson, J. C.

1982-08-01

Studies aimed at an increase in the efficiency of calculating transient temperature fields in complex aerospace vehicle structures are reported. The advantages and disadvantages of explicit and implicit algorithms are discussed and a promising set of implicit algorithms with variable time steps, known as GEARIB, is described. Test problems, used for evaluating and comparing various algorithms, are discussed and finite element models of the configurations are described. These problems include a coarse model of the Space Shuttle wing, an insulated frame tst article, a metallic panel for a thermal protection system, and detailed models of sections of the Space Shuttle wing. Results generally indicate a preference for implicit over explicit algorithms for transient structural heat transfer problems when the governing equations are stiff (typical of many practical problems such as insulated metal structures). The effects on algorithm performance of different models of an insulated cylinder are demonstrated. The stiffness of the problem is highly sensitive to modeling details and careful modeling can reduce the stiffness of the equations to the extent that explicit methods may become the best choice. Preliminary applications of a mixed implicit-explicit algorithm and operator splitting techniques for speeding up the solution of the algebraic equations are also described.

Unravelling the genetic differentiation among varieties of the Neotropical savanna tree Hancornia speciosa Gomes.

PubMed

Collevatti, Rosane G; Rodrigues, Eduardo E; Vitorino, Luciana C; Lima-Ribeiro, Matheus S; Chaves, Lázaro J; Telles, Mariana P C

2018-04-20

Spatial distribution of species genetic diversity is often driven by geographical distance (isolation by distance) or environmental conditions (isolation by environment), especially under climate change scenarios such as Quaternary glaciations. Here, we used coalescent analyses coupled with ecological niche modelling (ENM), spatially explicit quantile regression analyses and the multiple matrix regression with randomization (MMRR) approach to unravel the patterns of genetic differentiation in the widely distributed Neotropical savanna tree, Hancornia speciosa (Apocynaceae). Due to its high morphological differentiation, the species was originally classified into six botanical varieties by Monachino, and has recently been recognized as only two varieties by Flora do Brasil 2020. Thus, H. speciosa is a good biological model for learning about evolution of phenotypic plasticity under genetic and ecological effects, and predicting their responses to changing environmental conditions. We sampled 28 populations (777 individuals) of Monachino's four varieties of H. speciosa and used seven microsatellite loci to genotype them. Bayesian clustering showed five distinct genetic groups (K = 5) with high admixture among Monachino's varieties, mainly among populations in the central area of the species geographical range. Genetic differentiation among Monachino's varieties was lower than the genetic differentiation among populations within varieties, with higher within-population inbreeding. A high historical connectivity among populations of the central Cerrado shown by coalescent analyses may explain the high admixture among varieties. In addition, areas of higher climatic suitability also presented higher genetic diversity in such a way that the wide historical refugium across central Brazil might have promoted the long-term connectivity among populations. Yet, FST was significantly related to geographic distances, but not to environmental distances, and coalescent analyses and ENM predicted a demographical scenario of quasi-stability through time. Our findings show that demographical history and isolation by distance, but not isolation by environment, drove genetic differentiation of populations. Finally, the genetic clusters do not support the two recently recognized botanical varieties of H. speciosa, but partially support Monachino's classification at least for the four sampled varieties, similar to morphological variation.

On explicit algebraic stress models for complex turbulent flows

NASA Technical Reports Server (NTRS)

Gatski, T. B.; Speziale, C. G.

1992-01-01

Explicit algebraic stress models that are valid for three-dimensional turbulent flows in noninertial frames are systematically derived from a hierarchy of second-order closure models. This represents a generalization of the model derived by Pope who based his analysis on the Launder, Reece, and Rodi model restricted to two-dimensional turbulent flows in an inertial frame. The relationship between the new models and traditional algebraic stress models -- as well as anistropic eddy visosity models -- is theoretically established. The need for regularization is demonstrated in an effort to explain why traditional algebraic stress models have failed in complex flows. It is also shown that these explicit algebraic stress models can shed new light on what second-order closure models predict for the equilibrium states of homogeneous turbulent flows and can serve as a useful alternative in practical computations.

Assessing ecohydrological controls on catchment water storage, flux and age dynamics using tracers in a physically-based, spatially distributed model

NASA Astrophysics Data System (ADS)

Kuppel, S.; Tetzlaff, D.; Maneta, M. P.; Soulsby, C.

2017-12-01

Stable water isotope tracing has been extensively used in a wide range of geographical environments as a means to understand the sources, flow paths and ages of water stored and exiting a landscape via evapotranspiration, surface runoff and/or stream flow. Comparisons of isotopic signatures of precipitation and water in streams, soils, groundwater and plant xylem facilitates the assessment of how plant water use may affect preferential hydrologic pathways, storage dynamics and transit times in the critical zone. While tracers are also invaluable for testing model structure and accuracy, in most cases the measured isotopic signatures have been used to guide the calibration of conceptual runoff models with simplified vegetation and energy balance representation, which lacks sufficient detail to constrain key ecohydrological controls on flow paths and water ages. Here, we use a physically-based, distributed ecohydrological model (EcH2O) which we have extended to track 2H and 18O (including fractionation processes), and water age. This work is part of the "VeWa" project which aims at understanding ecohydrological couplings across climatic gradients in the wider North, where the hydrological implications of projected environmental change are essentially unknown though expected to be high. EcH2O combines a hydrologic scheme with an explicit representation of plant growth and phenology while resolving the energy balance across the soil-vegetation-atmosphere continuum. We focus on a montane catchment in Scotland, where unique long-term, high resolution hydrometric, ecohydrological and isotopic data allows for extensive model testing and projections. Results show the importance of incorporating soil fractionation processes to explain stream isotope dynamics, particularly seasonal enrichment in this humid, energy-limited catchment. This generic process-based approach facilitates analysis of dynamics in isotopes, storage and ages for the different hydrological compartments (canopy to groundwater) and, in particular, the explicit partitioning between soil evaporation and plant transpiration. Our study clearly advances our understanding of dynamics in water storage, flux and age in northern ecosystems, integrating ecohydrology, unsaturated zone, surface water, and groundwater hydrology.

Emissions from ships in the northwestern United States.

PubMed

Corbett, James J

2002-03-15

Recent inventory efforts have focused on developing nonroad inventories for emissions modeling and policy insights. Characterizing these inventories geographically and explicitly treating the uncertaintiesthat result from limited emissions testing, incomplete activity and usage data, and other important input parameters currently pose the largest methodological challenges. This paper presents a commercial marine vessel (CMV) emissions inventory for Washington and Oregon using detailed statistics regarding fuel consumption, vessel movements, and cargo volumes for the Columbia and Snake River systems. The inventory estimates emissions for oxides of nitrogen (NOx), particulate matter (PM), and oxides of sulfur (SOx). This analysis estimates that annual NOx emissions from marine transportation in the Columbia and Snake River systems in Washington and Oregon equal 6900 t of NOx (as NO2) per year, 2.6 times greater than previous NO, inventories for this region. Statewide CMV NO, emissions are estimated to be 9,800 t of NOx per year. By relying on a "bottom-up" fuel consumption model that includes vessel characteristics and transit information, the river system inventory may be more accurate than previous estimates. This inventory provides modelers with bounded parametric inputs for sensitivity analysis in pollution modeling. The ability to parametrically model the uncertainty in commercial marine vessel inventories also will help policy-makers determine whether better policy decisions can be enabled through further vessel testing and improved inventory resolution.

Explicit least squares system parameter identification for exact differential input/output models

NASA Technical Reports Server (NTRS)

Pearson, A. E.

1993-01-01

The equation error for a class of systems modeled by input/output differential operator equations has the potential to be integrated exactly, given the input/output data on a finite time interval, thereby opening up the possibility of using an explicit least squares estimation technique for system parameter identification. The paper delineates the class of models for which this is possible and shows how the explicit least squares cost function can be obtained in a way that obviates dealing with unknown initial and boundary conditions. The approach is illustrated by two examples: a second order chemical kinetics model and a third order system of Lorenz equations.

Key Technology Research on Open Architecture for The Sharing of Heterogeneous Geographic Analysis Models

NASA Astrophysics Data System (ADS)

Yue, S. S.; Wen, Y. N.; Lv, G. N.; Hu, D.

2013-10-01

In recent years, the increasing development of cloud computing technologies laid critical foundation for efficiently solving complicated geographic issues. However, it is still difficult to realize the cooperative operation of massive heterogeneous geographical models. Traditional cloud architecture is apt to provide centralized solution to end users, while all the required resources are often offered by large enterprises or special agencies. Thus, it's a closed framework from the perspective of resource utilization. Solving comprehensive geographic issues requires integrating multifarious heterogeneous geographical models and data. In this case, an open computing platform is in need, with which the model owners can package and deploy their models into cloud conveniently, while model users can search, access and utilize those models with cloud facility. Based on this concept, the open cloud service strategies for the sharing of heterogeneous geographic analysis models is studied in this article. The key technology: unified cloud interface strategy, sharing platform based on cloud service, and computing platform based on cloud service are discussed in detail, and related experiments are conducted for further verification.

A geostatistical approach to the change-of-support problem and variable-support data fusion in spatial analysis

NASA Astrophysics Data System (ADS)

Wang, Jun; Wang, Yang; Zeng, Hui

2016-01-01

A key issue to address in synthesizing spatial data with variable-support in spatial analysis and modeling is the change-of-support problem. We present an approach for solving the change-of-support and variable-support data fusion problems. This approach is based on geostatistical inverse modeling that explicitly accounts for differences in spatial support. The inverse model is applied here to produce both the best predictions of a target support and prediction uncertainties, based on one or more measurements, while honoring measurements. Spatial data covering large geographic areas often exhibit spatial nonstationarity and can lead to computational challenge due to the large data size. We developed a local-window geostatistical inverse modeling approach to accommodate these issues of spatial nonstationarity and alleviate computational burden. We conducted experiments using synthetic and real-world raster data. Synthetic data were generated and aggregated to multiple supports and downscaled back to the original support to analyze the accuracy of spatial predictions and the correctness of prediction uncertainties. Similar experiments were conducted for real-world raster data. Real-world data with variable-support were statistically fused to produce single-support predictions and associated uncertainties. The modeling results demonstrate that geostatistical inverse modeling can produce accurate predictions and associated prediction uncertainties. It is shown that the local-window geostatistical inverse modeling approach suggested offers a practical way to solve the well-known change-of-support problem and variable-support data fusion problem in spatial analysis and modeling.

Geographical Topics Learning of Geo-Tagged Social Images.

PubMed

Zhang, Xiaoming; Ji, Shufan; Wang, Senzhang; Li, Zhoujun; Lv, Xueqiang

2016-03-01

With the availability of cheap location sensors, geotagging of images in online social media is very popular. With a large amount of geo-tagged social images, it is interesting to study how these images are shared across geographical regions and how the geographical language characteristics and vision patterns are distributed across different regions. Unlike textual document, geo-tagged social image contains multiple types of content, i.e., textual description, visual content, and geographical information. Existing approaches usually mine geographical characteristics using a subset of multiple types of image contents or combining those contents linearly, which ignore correlations between different types of contents, and their geographical distributions. Therefore, in this paper, we propose a novel method to discover geographical characteristics of geo-tagged social images using a geographical topic model called geographical topic model of social images (GTMSIs). GTMSI integrates multiple types of social image contents as well as the geographical distributions, in which image topics are modeled based on both vocabulary and visual features. In GTMSI, each region of the image would have its own topic distribution, and hence have its own language model and vision pattern. Experimental results show that our GTMSI could identify interesting topics and vision patterns, as well as provide location prediction and image tagging.

Climate effects on the distribution of wetland habitats and connectivity in networks of migratory waterbirds

NASA Astrophysics Data System (ADS)

Bellisario, Bruno; Cerfolli, Fulvio; Nascetti, Giuseppe

2014-07-01

The establishment and maintenance of conservation areas are among the most common measures to mitigate the loss of biodiversity. However, recent advances in conservation biology have challenged the reliability of such areas to cope with variation in climate conditions. Climate change can reshuffle the geographic distribution of species, but in many cases suitable habitats become scarce or unavailable, limiting the ability to migrate or adapt in response to modified environments. In this respect, the extent to which existing protected areas are able to compensate changes in habitat conditions to ensure the persistence of species still remains unclear. We used a spatially explicit model to measure the effects of climate change on the potential distribution of wetland habitats and connectivity of Natura 2000 sites in Italy. The effects of climate change were measured on the potential for water accumulation in a given site, as a surrogate measure for the persistence of aquatic ecosystems and their associated migratory waterbirds. Climate impacts followed a geographic trend, changing the distribution of suitable habitats for migrants and highlighting a latitudinal threshold beyond which the connectivity reaches a sudden collapse. Our findings show the relative poor reliability of most sites in dealing with changing habitat conditions and ensure the long-term connectivity, with possible consequences for the persistence of species. Although alterations of climate suitability and habitat destruction could impact critical areas for migratory waterbirds, more research is needed to evaluate all possible long-term effects on the connectivity of migratory networks.

Flexible explicit but rigid implicit learning in a visuomotor adaptation task

PubMed Central

Bond, Krista M.

2015-01-01

There is mounting evidence for the idea that performance in a visuomotor rotation task can be supported by both implicit and explicit forms of learning. The implicit component of learning has been well characterized in previous experiments and is thought to arise from the adaptation of an internal model driven by sensorimotor prediction errors. However, the role of explicit learning is less clear, and previous investigations aimed at characterizing the explicit component have relied on indirect measures such as dual-task manipulations, posttests, and descriptive computational models. To address this problem, we developed a new method for directly assaying explicit learning by having participants verbally report their intended aiming direction on each trial. While our previous research employing this method has demonstrated the possibility of measuring explicit learning over the course of training, it was only tested over a limited scope of manipulations common to visuomotor rotation tasks. In the present study, we sought to better characterize explicit and implicit learning over a wider range of task conditions. We tested how explicit and implicit learning change as a function of the specific visual landmarks used to probe explicit learning, the number of training targets, and the size of the rotation. We found that explicit learning was remarkably flexible, responding appropriately to task demands. In contrast, implicit learning was strikingly rigid, with each task condition producing a similar degree of implicit learning. These results suggest that explicit learning is a fundamental component of motor learning and has been overlooked or conflated in previous visuomotor tasks. PMID:25855690

Drivers of Non-Native Aquatic Species Invasions across the ...

EPA Pesticide Factsheets

Background/Question/Methods Mapping the geographic distribution of non-native aquatic species is a critically important precursor to understanding the anthropogenic and environmental factors that drive freshwater biological invasions. Such efforts are often limited to local scales and/or to a single taxa, missing the opportunity to observe and understand the drivers of macroscale invasion patterns at sub-continental or continental scales. Here we map the distribution of exotic freshwater species richness across the continental United States using publicly accessible species occurrence data (e.g GBIF) and investigate the role of human activity in driving macroscale patterns of aquatic invasion. Using a dasymetric model of human population density and a spatially explicit model of recreational freshwater fishing demand, we analyzed the effect of these metrics of human influence on non-native aquatic species richness at the watershed scale, while controlling for spatial and sampling bias. We also assessed the effects that a temporal mismatch between occurrence data (collected since 1815) and cross-sectional predictors (developed using 2010 data) may have on model fit. Results/Conclusions Our results indicated that non-native aquatic species richness exhibits a highly patchy distribution, with hotspots in the Northeast, Great Lakes, Florida, and human population centers on the Pacific coast. These richness patterns are correlated with population density, but are m

Long-term Global Morphology of Gravity Wave Activity Using UARS Data

NASA Technical Reports Server (NTRS)

Eckermann, Stephen D.; Jackman, C. (Technical Monitor)

2000-01-01

This quarter was largely devoted to a detailed study of temperature data acquired by the Cryogenic Limb Array Etalon Spectrometer (CLAES) on UARS. Our analysis used the same sequence of methods that have been developed, tested and refined on a more limited subset of temperature data acquired by the CRISTA instrument. We focused on a limited subset of our reasoning that geographical and vertical trends in the small-scale temperature variability could be compared with similar trends observed in November 1994 by the CRISTA-SPAS satellite. Results, backed up with hindcasts from the Mountain Wave Forecast Model (MWFM), reveal strong evidence of mountain waves, most persuasively in the Himalayas on 16-17 November, 1992. These CLAES results are coherent over the 30-50 km range and compare well with MWFM hindcasts for the same period. This constitutes, we believe, the first clear evidence that CLAES explicitly resolved long wavelength gravity waves in its CO2 temperature channel. A series of other tasks, related to mesoscale modeling of mountain waves in CRISTA data and fitting of ground-based and HRDI data on global scales, were seen through to publication stage in peer-reviewed journals.

Parasite biodiversity faces extinction and redistribution in a changing climate

PubMed Central

Carlson, Colin J.; Burgio, Kevin R.; Dougherty, Eric R.; Phillips, Anna J.; Bueno, Veronica M.; Clements, Christopher F.; Castaldo, Giovanni; Dallas, Tad A.; Cizauskas, Carrie A.; Cumming, Graeme S.; Doña, Jorge; Harris, Nyeema C.; Jovani, Roger; Mironov, Sergey; Muellerklein, Oliver C.; Proctor, Heather C.; Getz, Wayne M.

2017-01-01

Climate change is a well-documented driver of both wildlife extinction and disease emergence, but the negative impacts of climate change on parasite diversity are undocumented. We compiled the most comprehensive spatially explicit data set available for parasites, projected range shifts in a changing climate, and estimated extinction rates for eight major parasite clades. On the basis of 53,133 occurrences capturing the geographic ranges of 457 parasite species, conservative model projections suggest that 5 to 10% of these species are committed to extinction by 2070 from climate-driven habitat loss alone. We find no evidence that parasites with zoonotic potential have a significantly higher potential to gain range in a changing climate, but we do find that ectoparasites (especially ticks) fare disproportionately worse than endoparasites. Accounting for host-driven coextinctions, models predict that up to 30% of parasitic worms are committed to extinction, driven by a combination of direct and indirect pressures. Despite high local extinction rates, parasite richness could still increase by an order of magnitude in some places, because species successfully tracking climate change invade temperate ecosystems and replace native species with unpredictable ecological consequences. PMID:28913417

Distance from sub-Saharan Africa predicts mutational load in diverse human genomes.

PubMed

Henn, Brenna M; Botigué, Laura R; Peischl, Stephan; Dupanloup, Isabelle; Lipatov, Mikhail; Maples, Brian K; Martin, Alicia R; Musharoff, Shaila; Cann, Howard; Snyder, Michael P; Excoffier, Laurent; Kidd, Jeffrey M; Bustamante, Carlos D

2016-01-26

The Out-of-Africa (OOA) dispersal ∼ 50,000 y ago is characterized by a series of founder events as modern humans expanded into multiple continents. Population genetics theory predicts an increase of mutational load in populations undergoing serial founder effects during range expansions. To test this hypothesis, we have sequenced full genomes and high-coverage exomes from seven geographically divergent human populations from Namibia, Congo, Algeria, Pakistan, Cambodia, Siberia, and Mexico. We find that individual genomes vary modestly in the overall number of predicted deleterious alleles. We show via spatially explicit simulations that the observed distribution of deleterious allele frequencies is consistent with the OOA dispersal, particularly under a model where deleterious mutations are recessive. We conclude that there is a strong signal of purifying selection at conserved genomic positions within Africa, but that many predicted deleterious mutations have evolved as if they were neutral during the expansion out of Africa. Under a model where selection is inversely related to dominance, we show that OOA populations are likely to have a higher mutation load due to increased allele frequencies of nearly neutral variants that are recessive or partially recessive.

Hydrological modelling of snail dispersal patterns in Msambweni, Kenya and potential resurgence of Schistosoma haematobium transmission.

PubMed

Clennon, J A; King, C H; Muchiri, E M; Kitron, U

2007-05-01

Urinary schistosomiasis is an important source of human morbidity in Msambweni, Kenya, where the intermediate host snail, Bulinus nasutus is found in ponds and water pools. In the past, aquatic habitats in the area have been studied separately; however, recent collections of B. nasutus snails and shells indicated that many of these ponds are in fact connected during and following sufficient rains. Satellite imagery and a geographical information system (GIS) were used to survey the main water courses and potential drainage routes, to locate potential source populations of snails and to determine probable snail dispersal routes. The 2 water bodies implicated as being the most important Schistosoma haematobium transmission foci in the area were found to differ in their degree of connectivity to other B. nasutus source habitats. One pond becomes connected even after normal rains, while the other pond requires prolonged rains or flooding to become connected with source habitats. Consequently, the transmission foci differ in their susceptibility to snail population control measures. Spatially explicit dispersal models that consider the spatial and temporal patterns of connectivity between aquatic habitats will contribute to improved snail surveillance and more focused control for urinary schistosomiasis at a local level.

Coevolution of Cooperation and Partner Rewiring Range in Spatial Social Networks

NASA Astrophysics Data System (ADS)

Khoo, Tommy; Fu, Feng; Pauls, Scott

2016-11-01

In recent years, there has been growing interest in the study of coevolutionary games on networks. Despite much progress, little attention has been paid to spatially embedded networks, where the underlying geographic distance, rather than the graph distance, is an important and relevant aspect of the partner rewiring process. It thus remains largely unclear how individual partner rewiring range preference, local vs. global, emerges and affects cooperation. Here we explicitly address this issue using a coevolutionary model of cooperation and partner rewiring range preference in spatially embedded social networks. In contrast to local rewiring, global rewiring has no distance restriction but incurs a one-time cost upon establishing any long range link. We find that under a wide range of model parameters, global partner switching preference can coevolve with cooperation. Moreover, the resulting partner network is highly degree-heterogeneous with small average shortest path length while maintaining high clustering, thereby possessing small-world properties. We also discover an optimum availability of reputation information for the emergence of global cooperators, who form distant partnerships at a cost to themselves. From the coevolutionary perspective, our work may help explain the ubiquity of small-world topologies arising alongside cooperation in the real world.

Composing Models of Geographic Physical Processes

NASA Astrophysics Data System (ADS)

Hofer, Barbara; Frank, Andrew U.

Processes are central for geographic information science; yet geographic information systems (GIS) lack capabilities to represent process related information. A prerequisite to including processes in GIS software is a general method to describe geographic processes independently of application disciplines. This paper presents such a method, namely a process description language. The vocabulary of the process description language is derived formally from mathematical models. Physical processes in geography can be described in two equivalent languages: partial differential equations or partial difference equations, where the latter can be shown graphically and used as a method for application specialists to enter their process models. The vocabulary of the process description language comprises components for describing the general behavior of prototypical geographic physical processes. These process components can be composed by basic models of geographic physical processes, which is shown by means of an example.

Solvent Reaction Field Potential inside an Uncharged Globular Protein: A Bridge between Implicit and Explicit Solvent Models?

PubMed Central

Baker, Nathan A.; McCammon, J. Andrew

2008-01-01

The solvent reaction field potential of an uncharged protein immersed in Simple Point Charge/Extended (SPC/E) explicit solvent was computed over a series of molecular dynamics trajectories, intotal 1560 ns of simulation time. A finite, positive potential of 13 to 24 kbTec−1 (where T = 300K), dependent on the geometry of the solvent-accessible surface, was observed inside the biomolecule. The primary contribution to this potential arose from a layer of positive charge density 1.0 Å from the solute surface, on average 0.008 ec/Å3, which we found to be the product of a highly ordered first solvation shell. Significant second solvation shell effects, including additional layers of charge density and a slight decrease in the short-range solvent-solvent interaction strength, were also observed. The impact of these findings on implicit solvent models was assessed by running similar explicit-solvent simulations on the fully charged protein system. When the energy due to the solvent reaction field in the uncharged system is accounted for, correlation between per-atom electrostatic energies for the explicit solvent model and a simple implicit (Poisson) calculation is 0.97, and correlation between per-atom energies for the explicit solvent model and a previously published, optimized Poisson model is 0.99. PMID:17949217

Solvent reaction field potential inside an uncharged globular protein: A bridge between implicit and explicit solvent models?

NASA Astrophysics Data System (ADS)

Cerutti, David S.; Baker, Nathan A.; McCammon, J. Andrew

2007-10-01

The solvent reaction field potential of an uncharged protein immersed in simple point charge/extended explicit solvent was computed over a series of molecular dynamics trajectories, in total 1560ns of simulation time. A finite, positive potential of 13-24 kbTec-1 (where T =300K), dependent on the geometry of the solvent-accessible surface, was observed inside the biomolecule. The primary contribution to this potential arose from a layer of positive charge density 1.0Å from the solute surface, on average 0.008ec/Å3, which we found to be the product of a highly ordered first solvation shell. Significant second solvation shell effects, including additional layers of charge density and a slight decrease in the short-range solvent-solvent interaction strength, were also observed. The impact of these findings on implicit solvent models was assessed by running similar explicit solvent simulations on the fully charged protein system. When the energy due to the solvent reaction field in the uncharged system is accounted for, correlation between per-atom electrostatic energies for the explicit solvent model and a simple implicit (Poisson) calculation is 0.97, and correlation between per-atom energies for the explicit solvent model and a previously published, optimized Poisson model is 0.99.

Ancient numerical daemons of conceptual hydrological modeling: 1. Fidelity and efficiency of time stepping schemes

NASA Astrophysics Data System (ADS)

Clark, Martyn P.; Kavetski, Dmitri

2010-10-01

A major neglected weakness of many current hydrological models is the numerical method used to solve the governing model equations. This paper thoroughly evaluates several classes of time stepping schemes in terms of numerical reliability and computational efficiency in the context of conceptual hydrological modeling. Numerical experiments are carried out using 8 distinct time stepping algorithms and 6 different conceptual rainfall-runoff models, applied in a densely gauged experimental catchment, as well as in 12 basins with diverse physical and hydroclimatic characteristics. Results show that, over vast regions of the parameter space, the numerical errors of fixed-step explicit schemes commonly used in hydrology routinely dwarf the structural errors of the model conceptualization. This substantially degrades model predictions, but also, disturbingly, generates fortuitously adequate performance for parameter sets where numerical errors compensate for model structural errors. Simply running fixed-step explicit schemes with shorter time steps provides a poor balance between accuracy and efficiency: in some cases daily-step adaptive explicit schemes with moderate error tolerances achieved comparable or higher accuracy than 15 min fixed-step explicit approximations but were nearly 10 times more efficient. From the range of simple time stepping schemes investigated in this work, the fixed-step implicit Euler method and the adaptive explicit Heun method emerge as good practical choices for the majority of simulation scenarios. In combination with the companion paper, where impacts on model analysis, interpretation, and prediction are assessed, this two-part study vividly highlights the impact of numerical errors on critical performance aspects of conceptual hydrological models and provides practical guidelines for robust numerical implementation.

Empirical methods for modeling landscape change, ecosystem services, and biodiversity

Treesearch

David Lewis; Ralph Alig

2009-01-01

The purpose of this paper is to synthesize recent economics research aimed at integrating discrete-choice econometric models of land-use change with spatially-explicit landscape simulations and quantitative ecology. This research explicitly models changes in the spatial pattern of landscapes in two steps: 1) econometric estimation of parcel-scale transition...

SPATIALLY EXPLICIT MICRO-LEVEL MODELLING OF LAND USE CHANGE AT THE RURAL-URBAN INTERFACE. (R828012)

EPA Science Inventory

This paper describes micro-economic models of land use change applicable to the rural–urban interface in the US. Use of a spatially explicit micro-level modelling approach permits the analysis of regional patterns of land use as the aggregate outcomes of many, disparate...

Quality Inspection and Analysis of Three-Dimensional Geographic Information Model Based on Oblique Photogrammetry

NASA Astrophysics Data System (ADS)

Dong, S.; Yan, Q.; Xu, Y.; Bai, J.

2018-04-01

In order to promote the construction of digital geo-spatial framework in China and accelerate the construction of informatization mapping system, three-dimensional geographic information model emerged. The three-dimensional geographic information model based on oblique photogrammetry technology has higher accuracy, shorter period and lower cost than traditional methods, and can more directly reflect the elevation, position and appearance of the features. At this stage, the technology of producing three-dimensional geographic information models based on oblique photogrammetry technology is rapidly developing. The market demand and model results have been emerged in a large amount, and the related quality inspection needs are also getting larger and larger. Through the study of relevant literature, it is found that there are a lot of researches on the basic principles and technical characteristics of this technology, and relatively few studies on quality inspection and analysis. On the basis of summarizing the basic principle and technical characteristics of oblique photogrammetry technology, this paper introduces the inspection contents and inspection methods of three-dimensional geographic information model based on oblique photogrammetry technology. Combined with the actual inspection work, this paper summarizes the quality problems of three-dimensional geographic information model based on oblique photogrammetry technology, analyzes the causes of the problems and puts forward the quality control measures. It provides technical guidance for the quality inspection of three-dimensional geographic information model data products based on oblique photogrammetry technology in China and provides technical support for the vigorous development of three-dimensional geographic information model based on oblique photogrammetry technology.

A Galilean Invariant Explicit Algebraic Reynolds Stress Model for Curved Flows

NASA Technical Reports Server (NTRS)

Girimaji, Sharath

1996-01-01

A Galilean invariant weak-equilbrium hypothesis that is sensitive to streamline curvature is proposed. The hypothesis leads to an algebraic Reynolds stress model for curved flows that is fully explicit and self-consistent. The model is tested in curved homogeneous shear flow: the agreement is excellent with Reynolds stress closure model and adequate with available experimental data.

A functional-dynamic reflection on participatory processes in modeling projects.

PubMed

Seidl, Roman

2015-12-01

The participation of nonscientists in modeling projects/studies is increasingly employed to fulfill different functions. However, it is not well investigated if and how explicitly these functions and the dynamics of a participatory process are reflected by modeling projects in particular. In this review study, I explore participatory modeling projects from a functional-dynamic process perspective. The main differences among projects relate to the functions of participation-most often, more than one per project can be identified, along with the degree of explicit reflection (i.e., awareness and anticipation) on the dynamic process perspective. Moreover, two main approaches are revealed: participatory modeling covering diverse approaches and companion modeling. It becomes apparent that the degree of reflection on the participatory process itself is not always explicit and perfectly visible in the descriptions of the modeling projects. Thus, the use of common protocols or templates is discussed to facilitate project planning, as well as the publication of project results. A generic template may help, not in providing details of a project or model development, but in explicitly reflecting on the participatory process. It can serve to systematize the particular project's approach to stakeholder collaboration, and thus quality management.

Climate change, humans, and the extinction of the woolly mammoth.

PubMed

Nogués-Bravo, David; Rodríguez, Jesús; Hortal, Joaquín; Batra, Persaram; Araújo, Miguel B

2008-04-01

Woolly mammoths inhabited Eurasia and North America from late Middle Pleistocene (300 ky BP [300,000 years before present]), surviving through different climatic cycles until they vanished in the Holocene (3.6 ky BP). The debate about why the Late Quaternary extinctions occurred has centred upon environmental and human-induced effects, or a combination of both. However, testing these two hypotheses-climatic and anthropogenic-has been hampered by the difficulty of generating quantitative estimates of the relationship between the contraction of the mammoth's geographical range and each of the two hypotheses. We combined climate envelope models and a population model with explicit treatment of woolly mammoth-human interactions to measure the extent to which a combination of climate changes and increased human pressures might have led to the extinction of the species in Eurasia. Climate conditions for woolly mammoths were measured across different time periods: 126 ky BP, 42 ky BP, 30 ky BP, 21 ky BP, and 6 ky BP. We show that suitable climate conditions for the mammoth reduced drastically between the Late Pleistocene and the Holocene, and 90% of its geographical range disappeared between 42 ky BP and 6 ky BP, with the remaining suitable areas in the mid-Holocene being mainly restricted to Arctic Siberia, which is where the latest records of woolly mammoths in continental Asia have been found. Results of the population models also show that the collapse of the climatic niche of the mammoth caused a significant drop in their population size, making woolly mammoths more vulnerable to the increasing hunting pressure from human populations. The coincidence of the disappearance of climatically suitable areas for woolly mammoths and the increase in anthropogenic impacts in the Holocene, the coup de grâce, likely set the place and time for the extinction of the woolly mammoth.

High Performance Programming Using Explicit Shared Memory Model on Cray T3D1

NASA Technical Reports Server (NTRS)

Simon, Horst D.; Saini, Subhash; Grassi, Charles

1994-01-01

The Cray T3D system is the first-phase system in Cray Research, Inc.'s (CRI) three-phase massively parallel processing (MPP) program. This system features a heterogeneous architecture that closely couples DEC's Alpha microprocessors and CRI's parallel-vector technology, i.e., the Cray Y-MP and Cray C90. An overview of the Cray T3D hardware and available programming models is presented. Under Cray Research adaptive Fortran (CRAFT) model four programming methods (data parallel, work sharing, message-passing using PVM, and explicit shared memory model) are available to the users. However, at this time data parallel and work sharing programming models are not available to the user community. The differences between standard PVM and CRI's PVM are highlighted with performance measurements such as latencies and communication bandwidths. We have found that the performance of neither standard PVM nor CRI s PVM exploits the hardware capabilities of the T3D. The reasons for the bad performance of PVM as a native message-passing library are presented. This is illustrated by the performance of NAS Parallel Benchmarks (NPB) programmed in explicit shared memory model on Cray T3D. In general, the performance of standard PVM is about 4 to 5 times less than obtained by using explicit shared memory model. This degradation in performance is also seen on CM-5 where the performance of applications using native message-passing library CMMD on CM-5 is also about 4 to 5 times less than using data parallel methods. The issues involved (such as barriers, synchronization, invalidating data cache, aligning data cache etc.) while programming in explicit shared memory model are discussed. Comparative performance of NPB using explicit shared memory programming model on the Cray T3D and other highly parallel systems such as the TMC CM-5, Intel Paragon, Cray C90, IBM-SP1, etc. is presented.

A Novel Petri Nets-Based Modeling Method for the Interaction between the Sensor and the Geographic Environment in Emerging Sensor Networks

PubMed Central

Zhang, Feng; Xu, Yuetong; Chou, Jarong

2016-01-01

The service of sensor device in Emerging Sensor Networks (ESNs) is the extension of traditional Web services. Through the sensor network, the service of sensor device can communicate directly with the entity in the geographic environment, and even impact the geographic entity directly. The interaction between the sensor device in ESNs and geographic environment is very complex, and the interaction modeling is a challenging problem. This paper proposed a novel Petri Nets-based modeling method for the interaction between the sensor device and the geographic environment. The feature of the sensor device service in ESNs is more easily affected by the geographic environment than the traditional Web service. Therefore, the response time, the fault-tolerant ability and the resource consumption become important factors in the performance of the whole sensor application system. Thus, this paper classified IoT services as Sensing services and Controlling services according to the interaction between IoT service and geographic entity, and classified GIS services as data services and processing services. Then, this paper designed and analyzed service algebra and Colored Petri Nets model to modeling the geo-feature, IoT service, GIS service and the interaction process between the sensor and the geographic enviroment. At last, the modeling process is discussed by examples. PMID:27681730

Simulating ectomycorrhiza in boreal forests: implementing ectomycorrhizal fungi model MYCOFON in CoupModel (v5)

NASA Astrophysics Data System (ADS)

He, Hongxing; Meyer, Astrid; Jansson, Per-Erik; Svensson, Magnus; Rütting, Tobias; Klemedtsson, Leif

2018-02-01

The symbiosis between plants and Ectomycorrhizal fungi (ECM) is shown to considerably influence the carbon (C) and nitrogen (N) fluxes between the soil, rhizosphere, and plants in boreal forest ecosystems. However, ECM are either neglected or presented as an implicit, undynamic term in most ecosystem models, which can potentially reduce the predictive power of models.

In order to investigate the necessity of an explicit consideration of ECM in ecosystem models, we implement the previously developed MYCOFON model into a detailed process-based, soil-plant-atmosphere model, Coup-MYCOFON, which explicitly describes the C and N fluxes between ECM and roots. This new Coup-MYCOFON model approach (ECM explicit) is compared with two simpler model approaches: one containing ECM implicitly as a dynamic uptake of organic N considering the plant roots to represent the ECM (ECM implicit), and the other a static N approach in which plant growth is limited to a fixed N level (nonlim). Parameter uncertainties are quantified using Bayesian calibration in which the model outputs are constrained to current forest growth and soil C / N ratio for four forest sites along a climate and N deposition gradient in Sweden and simulated over a 100-year period.

The nonlim approach could not describe the soil C / N ratio due to large overestimation of soil N sequestration but simulate the forest growth reasonably well. The ECM implicit and explicit approaches both describe the soil C / N ratio well but slightly underestimate the forest growth. The implicit approach simulated lower litter production and soil respiration than the explicit approach. The ECM explicit Coup-MYCOFON model provides a more detailed description of internal ecosystem fluxes and feedbacks of C and N between plants, soil, and ECM. Our modeling highlights the need to incorporate ECM and organic N uptake into ecosystem models, and the nonlim approach is not recommended for future long-term soil C and N predictions. We also provide a key set of posterior fungal parameters that can be further investigated and evaluated in future ECM studies.

The importance of explicitly mapping instructional analogies in science education

NASA Astrophysics Data System (ADS)

Asay, Loretta Johnson

Analogies are ubiquitous during instruction in science classrooms, yet research about the effectiveness of using analogies has produced mixed results. An aspect seldom studied is a model of instruction when using analogies. The few existing models for instruction with analogies have not often been examined quantitatively. The Teaching With Analogies (TWA) model (Glynn, 1991) is one of the models frequently cited in the variety of research about analogies. The TWA model outlines steps for instruction, including the step of explicitly mapping the features of the source to the target. An experimental study was conducted to examine the effects of explicitly mapping the features of the source and target in an analogy during computer-based instruction about electrical circuits. Explicit mapping was compared to no mapping and to a control with no analogy. Participants were ninth- and tenth-grade biology students who were each randomly assigned to one of three conditions (no analogy module, analogy module, or explicitly mapped analogy module) for computer-based instruction. Subjects took a pre-test before the instruction, which was used to assign them to a level of previous knowledge about electrical circuits for analysis of any differential effects. After the instruction modules, students took a post-test about electrical circuits. Two weeks later, they took a delayed post-test. No advantage was found for explicitly mapping the analogy. Learning patterns were the same, regardless of the type of instruction. Those who knew the least about electrical circuits, based on the pre-test, made the most gains. After the two-week delay, this group maintained the largest amount of their gain. Implications exist for science education classrooms, as analogy use should be based on research about effective practices. Further studies are suggested to foster the building of research-based models for classroom instruction with analogies.

Combining Model-driven and Schema-based Program Synthesis

NASA Technical Reports Server (NTRS)

Denney, Ewen; Whittle, John

2004-01-01

We describe ongoing work which aims to extend the schema-based program synthesis paradigm with explicit models. In this context, schemas can be considered as model-to-model transformations. The combination of schemas with explicit models offers a number of advantages, namely, that building synthesis systems becomes much easier since the models can be used in verification and in adaptation of the synthesis systems. We illustrate our approach using an example from signal processing.

Cohen's Kappa and classification table metrics 2.0: An ArcView 3.x extension for accuracy assessment of spatially explicit models

Treesearch

Jeff Jenness; J. Judson Wynne

2005-01-01

In the field of spatially explicit modeling, well-developed accuracy assessment methodologies are often poorly applied. Deriving model accuracy metrics have been possible for decades, but these calculations were made by hand or with the use of a spreadsheet application. Accuracy assessments may be useful for: (1) ascertaining the quality of a model; (2) improving model...

Mapping fires and American Red Cross aid using demographic indicators of vulnerability.

PubMed

Lue, Evan; Wilson, John P

2017-04-01

Social vulnerability indicators can assist with informing disaster relief preparation. Certain demographic segments of a population may suffer disproportionately during disaster events, and a geographical understanding of them can help to determine where to place strategically logistical assets and to target disaster-awareness outreach endeavours. Records of house fire events and American Red Cross aid provision over a five-year period were mapped for the County of Los Angeles, California, United States, to examine the congruence between actual events and expectations of risk based on vulnerability theory. The geographical context provided by the data was compared with spatially-explicit indicators of vulnerability, such as age, race, and wealth. Fire events were found to occur more frequently in more vulnerable areas, and Red Cross aid was found to have an even stronger relationship to those places. The findings suggest that these indicators speak beyond vulnerability and relate to patterns of fire risk. © 2017 The Author(s). Disasters © Overseas Development Institute, 2017.

Moderators of the Relationship between Implicit and Explicit Evaluation

PubMed Central

Nosek, Brian A.

2005-01-01

Automatic and controlled modes of evaluation sometimes provide conflicting reports of the quality of social objects. This paper presents evidence for four moderators of the relationship between automatic (implicit) and controlled (explicit) evaluations. Implicit and explicit preferences were measured for a variety of object pairs using a large sample. The average correlation was r = .36, and 52 of the 57 object pairs showed a significant positive correlation. Results of multilevel modeling analyses suggested that: (a) implicit and explicit preferences are related, (b) the relationship varies as a function of the objects assessed, and (c) at least four variables moderate the relationship – self-presentation, evaluative strength, dimensionality, and distinctiveness. The variables moderated implicit-explicit correspondence across individuals and accounted for much of the observed variation across content domains. The resulting model of the relationship between automatic and controlled evaluative processes is grounded in personal experience with the targets of evaluation. PMID:16316292

Geographers in the Post-Industrial Age: A Conceptual Curriculum Model for Geography.

ERIC Educational Resources Information Center

Verduin-Muller, Henriette

The document describes a conceptual curriculum model for designing original geographical curriculum materials. The model emanated from a series of research projects at the Geographical Institute's Department of Geography for Education at the Rijksuniversiteit of Utrecht, the Netherlands. The objective of the research was to gain insight into the…

Bayesian analysis of biogeography when the number of areas is large.

PubMed

Landis, Michael J; Matzke, Nicholas J; Moore, Brian R; Huelsenbeck, John P

2013-11-01

Historical biogeography is increasingly studied from an explicitly statistical perspective, using stochastic models to describe the evolution of species range as a continuous-time Markov process of dispersal between and extinction within a set of discrete geographic areas. The main constraint of these methods is the computational limit on the number of areas that can be specified. We propose a Bayesian approach for inferring biogeographic history that extends the application of biogeographic models to the analysis of more realistic problems that involve a large number of areas. Our solution is based on a "data-augmentation" approach, in which we first populate the tree with a history of biogeographic events that is consistent with the observed species ranges at the tips of the tree. We then calculate the likelihood of a given history by adopting a mechanistic interpretation of the instantaneous-rate matrix, which specifies both the exponential waiting times between biogeographic events and the relative probabilities of each biogeographic change. We develop this approach in a Bayesian framework, marginalizing over all possible biogeographic histories using Markov chain Monte Carlo (MCMC). Besides dramatically increasing the number of areas that can be accommodated in a biogeographic analysis, our method allows the parameters of a given biogeographic model to be estimated and different biogeographic models to be objectively compared. Our approach is implemented in the program, BayArea.

Bayesian inference for the spatio-temporal invasion of alien species.

PubMed

Cook, Alex; Marion, Glenn; Butler, Adam; Gibson, Gavin

2007-08-01

In this paper we develop a Bayesian approach to parameter estimation in a stochastic spatio-temporal model of the spread of invasive species across a landscape. To date, statistical techniques, such as logistic and autologistic regression, have outstripped stochastic spatio-temporal models in their ability to handle large numbers of covariates. Here we seek to address this problem by making use of a range of covariates describing the bio-geographical features of the landscape. Relative to regression techniques, stochastic spatio-temporal models are more transparent in their representation of biological processes. They also explicitly model temporal change, and therefore do not require the assumption that the species' distribution (or other spatial pattern) has already reached equilibrium as is often the case with standard statistical approaches. In order to illustrate the use of such techniques we apply them to the analysis of data detailing the spread of an invasive plant, Heracleum mantegazzianum, across Britain in the 20th Century using geo-referenced covariate information describing local temperature, elevation and habitat type. The use of Markov chain Monte Carlo sampling within a Bayesian framework facilitates statistical assessments of differences in the suitability of different habitat classes for H. mantegazzianum, and enables predictions of future spread to account for parametric uncertainty and system variability. Our results show that ignoring such covariate information may lead to biased estimates of key processes and implausible predictions of future distributions.

Latin hypercube sampling and geostatistical modeling of spatial uncertainty in a spatially explicit forest landscape model simulation

Treesearch

Chonggang Xu; Hong S. He; Yuanman Hu; Yu Chang; Xiuzhen Li; Rencang Bu

2005-01-01

Geostatistical stochastic simulation is always combined with Monte Carlo method to quantify the uncertainty in spatial model simulations. However, due to the relatively long running time of spatially explicit forest models as a result of their complexity, it is always infeasible to generate hundreds or thousands of Monte Carlo simulations. Thus, it is of great...

Increasing prominence of implantology research: a chronological trend analysis of 100 top-cited articles in periodontal journals.

PubMed

Chiang, Ho-Sheng; Huang, Ren-Yeong; Weng, Pei-Wei; Mau, Lian-Ping; Su, Chi-Chun; Tsai, Yi-Wen Cathy; Wu, Yu-Chiao; Chung, Chi-Hsiang; Shieh, Yi-Shing; Cheng, Wan-Chien

To identify 100 top-cited articles published in periodontal journals and analyse the research trends by using citation analysis. 100 top-cited articles published in periodontal journals were retrieved by searching the database of the ISI Web of Science and Journal Citation reports. For each article, the following principal bibliometric parameters: authorship, geographic and institute origin, manuscript type, study design, scope of study, and citation count of each time period were analysed from 1965 to 2015. The identified 100 top-cited articles were retrieved from five periodontal journals and citation counts were recorded between 262 and 1,693 times. For the institute of origin, the most productive institute, in terms of the number of 100 top-cited articles published, was the University of Gothenburg (Sweden) (n = 19), followed by the Forsyth Dental Center (USA) (n = 15). Most manuscripts were original research (n = 74), and the inflammatory periodontal disease (n = 59) was the most frequent topic studied. Interestingly, the trend of increase average citation reached significance for implantology (β = 26.75, P = 0.003) and systemic interactions (β = 29.83, P = 0.005), but not for inflammatory disease (β = -10.30, P = 0.248) and tissue regeneration (β = 9.04, P = 0.081). By using multivariable linear regression in a generalised linear model, suitable published journal (Journal of Clinical Periodontology), geographic regions (Europe), more intense international collaboration, adequate manuscript type (review article) and study design (systematic review) could be attributed to escalating average citation counts in implantology (all P < 0.05). However, for systemic interactions, only geographic region and study design were significantly associated with the increasing citation trend. These principal bibliometric characteristics revealed escalated trends in average citation count in implantology throughout time. Conflict-of-interest statement The authors have stated explicitly that there are no conflicts of interest in connection with this article. The study was self-funded by the authors and their institution.

A geographic analysis of population density thresholds in the influenza pandemic of 1918-19.

PubMed

Chandra, Siddharth; Kassens-Noor, Eva; Kuljanin, Goran; Vertalka, Joshua

2013-02-20

Geographic variables play an important role in the study of epidemics. The role of one such variable, population density, in the spread of influenza is controversial. Prior studies have tested for such a role using arbitrary thresholds for population density above or below which places are hypothesized to have higher or lower mortality. The results of such studies are mixed. The objective of this study is to estimate, rather than assume, a threshold level of population density that separates low-density regions from high-density regions on the basis of population loss during an influenza pandemic. We study the case of the influenza pandemic of 1918-19 in India, where over 15 million people died in the short span of less than one year. Using data from six censuses for 199 districts of India (n=1194), the country with the largest number of deaths from the influenza of 1918-19, we use a sample-splitting method embedded within a population growth model that explicitly quantifies population loss from the pandemic to estimate a threshold level of population density that separates low-density districts from high-density districts. The results demonstrate a threshold level of population density of 175 people per square mile. A concurrent finding is that districts on the low side of the threshold experienced rates of population loss (3.72%) that were lower than districts on the high side of the threshold (4.69%). This paper introduces a useful analytic tool to the health geographic literature. It illustrates an application of the tool to demonstrate that it can be useful for pandemic awareness and preparedness efforts. Specifically, it estimates a level of population density above which policies to socially distance, redistribute or quarantine populations are likely to be more effective than they are for areas with population densities that lie below the threshold.

A geographic analysis of population density thresholds in the influenza pandemic of 1918–19

PubMed Central

2013-01-01

Background Geographic variables play an important role in the study of epidemics. The role of one such variable, population density, in the spread of influenza is controversial. Prior studies have tested for such a role using arbitrary thresholds for population density above or below which places are hypothesized to have higher or lower mortality. The results of such studies are mixed. The objective of this study is to estimate, rather than assume, a threshold level of population density that separates low-density regions from high-density regions on the basis of population loss during an influenza pandemic. We study the case of the influenza pandemic of 1918–19 in India, where over 15 million people died in the short span of less than one year. Methods Using data from six censuses for 199 districts of India (n=1194), the country with the largest number of deaths from the influenza of 1918–19, we use a sample-splitting method embedded within a population growth model that explicitly quantifies population loss from the pandemic to estimate a threshold level of population density that separates low-density districts from high-density districts. Results The results demonstrate a threshold level of population density of 175 people per square mile. A concurrent finding is that districts on the low side of the threshold experienced rates of population loss (3.72%) that were lower than districts on the high side of the threshold (4.69%). Conclusions This paper introduces a useful analytic tool to the health geographic literature. It illustrates an application of the tool to demonstrate that it can be useful for pandemic awareness and preparedness efforts. Specifically, it estimates a level of population density above which policies to socially distance, redistribute or quarantine populations are likely to be more effective than they are for areas with population densities that lie below the threshold. PMID:23425498

Source apportionment of airborne particulates through receptor modeling: Indian scenario

NASA Astrophysics Data System (ADS)

Banerjee, Tirthankar; Murari, Vishnu; Kumar, Manish; Raju, M. P.

2015-10-01

Airborne particulate chemistry mostly governed by associated sources and apportionment of specific sources is extremely essential to delineate explicit control strategies. The present submission initially deals with the publications (1980s-2010s) of Indian origin which report regional heterogeneities of particulate concentrations with reference to associated species. Such meta-analyses clearly indicate the presence of reservoir of both primary and secondary aerosols in different geographical regions. Further, identification of specific signatory molecules for individual source category was also evaluated in terms of their scientific merit and repeatability. Source signatures mostly resemble international profile while, in selected cases lack appropriateness. In India, source apportionment (SA) of airborne particulates was initiated way back in 1985 through factor analysis, however, principal component analysis (PCA) shares a major proportion of applications (34%) followed by enrichment factor (EF, 27%), chemical mass balance (CMB, 15%) and positive matrix factorization (PMF, 9%). Mainstream SA analyses identify earth crust and road dust resuspensions (traced by Al, Ca, Fe, Na and Mg) as a principal source (6-73%) followed by vehicular emissions (traced by Fe, Cu, Pb, Cr, Ni, Mn, Ba and Zn; 5-65%), industrial emissions (traced by Co, Cr, Zn, V, Ni, Mn, Cd; 0-60%), fuel combustion (traced by K, NH4+, SO4-, As, Te, S, Mn; 4-42%), marine aerosols (traced by Na, Mg, K; 0-15%) and biomass/refuse burning (traced by Cd, V, K, Cr, As, TC, Na, K, NH4+, NO3-, OC; 1-42%). In most of the cases, temporal variations of individual source contribution for a specific geographic region exhibit radical heterogeneity possibly due to unscientific orientation of individual tracers for specific source and well exaggerated by methodological weakness, inappropriate sample size, implications of secondary aerosols and inadequate emission inventories. Conclusively, a number of challenging issues and specific recommendations have been included which need to be considered for a scientific apportionment of particulate sources in different geographical regions of India.

A Method for Analyzing Volunteered Geographic Information ...

EPA Pesticide Factsheets

Volunteered geographic information (VGI) can be used to identify public valuation of ecosystem services in a defined geographic area using photos as a representation of lived experiences. This method can help researchers better survey and report on the values and preferences of stakeholders involved in rehabilitation and revitalization projects. Current research utilizes VGI in the form of geotagged social media photos from three platforms: Flickr, Instagram, and Panaramio. Social media photos have been obtained for the neighborhoods next to the St. Louis River in Duluth, Minnesota, and are being analyzed along several dimensions. These dimensions include the spatial distribution of each platform, the characteristics of the physical environment portrayed in the photos, and finally, the ecosystem service depicted. In this poster, we focus on the photos from the Irving and Fairmount neighborhoods of Duluth, MN to demonstrate the method at the neighborhood scale. This study demonstrates a method for translating the values expressed in social media photos into ecosystem services and spatially-explicit data to be used in multiple settings, including the City of Duluth’s Comprehensive Planning and community revitalization efforts, habitat restoration in a Great Lakes Area of Concern, and the USEPA’s Office of Research and Development. This poster will demonstrate a method for translating values expressed in social media photos into ecosystem services and spatially

Latitude delineates patterns of biogeography in terrestrial Streptomyces.

PubMed

Choudoir, Mallory J; Doroghazi, James R; Buckley, Daniel H

2016-12-01

The biogeography of Streptomyces was examined at regional spatial scales to identify factors that govern patterns of microbial diversity. Streptomyces are spore forming filamentous bacteria which are widespread in soil. Streptomyces strains were isolated from perennial grass habitats sampled across a spatial scale of more than 6000 km. Previous analysis of this geographically explicit culture collection provided evidence for a latitudinal diversity gradient in Streptomyces species. Here the hypothesis that this latitudinal diversity gradient is a result of evolutionary dynamics associated with historical demographic processes was evaluated. Historical demographic phenomena have genetic consequences that can be evaluated through analysis of population genetics. Population genetic approaches were applied to analyze population structure in six of the most numerically abundant and geographically widespread Streptomyces phylogroups from our culture collection. Streptomyces population structure varied at regional spatial scales, and allelic diversity correlated with geographic distance. In addition, allelic diversity and gene flow are partitioned by latitude. Finally, it was found that nucleotide diversity within phylogroups was negatively correlated with latitude. These results indicate that phylogroup diversification is constrained by dispersal limitation at regional spatial scales, and they are consistent with the hypothesis that historical demographic processes have influenced the contemporary biogeography of Streptomyces. © 2016 Society for Applied Microbiology and John Wiley & Sons Ltd.

Beyond the climate envelope: using trait filtering models to predict biome boundaries from plant physiology.

NASA Astrophysics Data System (ADS)

Fisher, R.; Hoffmann, W. A.; Muszala, S.

2014-12-01

The introduction of second-generation dynamic vegetation models - which simulate the distribution of light resources between plant types along the vertical canopy profile, and therefore facilitate the representation of plant competition explicitly - is a large increase in the complexity and fidelity with which the terrestrial biosphere is abstracted into Earth System Models. In this new class of model, biome boundaries are predicted as the emergent properties of plant physiology, and are therefore sensitive to the high-dimensional parameterizations of plant functional traits. These new approaches offer the facility to quantitatively test ecophysiological hypotheses of plant distribution at large scales, a field which remains surprisingly under-developed. Here we describe experiments conducted with the Community Land Model Ecosystem Demography component, CLM(ED), in which we reduce the complexity of the problem by testing how individual plant functional trait changes to control the location of biome boundaries between functional types. Specifically, we investigate which physiological trade-offs determine the boundary between frequently burned savanna and forest biomes, and attempt to distinguish how each strategic life-history trade-off (carbon storage, bark investment, re-sprouting strategy) contributes towards the maintenance of sharp geographical gradients between fire adapted and typically inflammable closed canopy ecosystems. This study forms part of the planning for a model-inspired fire manipulation experiment at the cerrado-forest boundary in South-Eastern Brazil, and the results will be used to guide future data-collection and analysis strategies.

Entangling mobility and interactions in social media.

PubMed

Grabowicz, Przemyslaw A; Ramasco, José J; Gonçalves, Bruno; Eguíluz, Víctor M

2014-01-01

Daily interactions naturally define social circles. Individuals tend to be friends with the people they spend time with and they choose to spend time with their friends, inextricably entangling physical location and social relationships. As a result, it is possible to predict not only someone's location from their friends' locations but also friendship from spatial and temporal co-occurrence. While several models have been developed to separately describe mobility and the evolution of social networks, there is a lack of studies coupling social interactions and mobility. In this work, we introduce a model that bridges this gap by explicitly considering the feedback of mobility on the formation of social ties. Data coming from three online social networks (Twitter, Gowalla and Brightkite) is used for validation. Our model reproduces various topological and physical properties of the networks not captured by models uncoupling mobility and social interactions such as: i) the total size of the connected components, ii) the distance distribution between connected users, iii) the dependence of the reciprocity on the distance, iv) the variation of the social overlap and the clustering with the distance. Besides numerical simulations, a mean-field approach is also used to study analytically the main statistical features of the networks generated by a simplified version of our model. The robustness of the results to changes in the model parameters is explored, finding that a balance between friend visits and long-range random connections is essential to reproduce the geographical features of the empirical networks.

Implicit and explicit ethnocentrism: revisiting the ideologies of prejudice.

PubMed

Cunningham, William A; Nezlek, John B; Banaji, Mahzarin R

2004-10-01

Two studies investigated relationships among individual differences in implicit and explicit prejudice, right-wing ideology, and rigidity in thinking. The first study examined these relationships focusing on White Americans' prejudice toward Black Americans. The second study provided the first test of implicit ethnocentrism and its relationship to explicit ethnocentrism by studying the relationship between attitudes toward five social groups. Factor analyses found support for both implicit and explicit ethnocentrism. In both studies, mean explicit attitudes toward out groups were positive, whereas implicit attitudes were negative, suggesting that implicit and explicit prejudices are distinct; however, in both studies, implicit and explicit attitudes were related (r = .37, .47). Latent variable modeling indicates a simple structure within this ethnocentric system, with variables organized in order of specificity. These results lead to the conclusion that (a) implicit ethnocentrism exists and (b) it is related to and distinct from explicit ethnocentrism.

Pre-Service Teachers' Implicit and Explicit Attitudes toward Obesity Influence Their Judgments of Students

ERIC Educational Resources Information Center

Glock, Sabine; Beverborg, Arnoud Oude Groote; Müller, Barbara C. N.

2016-01-01

Obese children experience disadvantages in school and discrimination from their teachers. Teachers' implicit and explicit attitudes have been identified as contributing to these disadvantages. Drawing on dual process models, we investigated the nature of pre-service teachers' implicit and explicit attitudes, their motivation to respond without…

Explicit and Implicit Stigma of Mental Illness as Predictors of the Recovery Attitudes of Assertive Community Treatment Practitioners.

PubMed

Stull, Laura G; McConnell, Haley; McGrew, John; Salyers, Michelle P

2017-01-01

While explicit negative stereotypes of mental illness are well established as barriers to recovery, implicit attitudes also may negatively impact outcomes. The current study is unique in its focus on both explicit and implicit stigma as predictors of recovery attitudes of mental health practitioners. Assertive Community Treatment practitioners (n = 154) from 55 teams completed online measures of stigma, recovery attitudes, and an Implicit Association Test (IAT). Three of four explicit stigma variables (perceptions of blameworthiness, helplessness, and dangerousness) and all three implicit stigma variables were associated with lower recovery attitudes. In a multivariate, hierarchical model, however, implicit stigma did not explain additional variance in recovery attitudes. In the overall model, perceptions of dangerousness and implicitly associating mental illness with "bad" were significant individual predictors of lower recovery attitudes. The current study demonstrates a need for interventions to lower explicit stigma, particularly perceptions of dangerousness, to increase mental health providers' expectations for recovery. The extent to which implicit and explicit stigma differentially predict outcomes, including recovery attitudes, needs further research.

Human-environment interactions and sustainable urban development: Spatial modeling and landscape prediction the case of Nang Rong town, Thailand

NASA Astrophysics Data System (ADS)

Varnakovida, Pariwate

It is now well-recognized that, at local, regional, and global scales, land use changes are significantly altering land cover, perhaps at an accelerating pace. Further, the world's scientific community is increasingly recognizing what, in retrospect, should have been obvious, that human behavior and agency is a critical driver of Land Cover and Land Use Change. In this research, using recently developed computer modeling procedures and a rich case study, I develop spatially-explicit model-based simulations of LULCC scenarios within the rubric of sustainability science for Nang Rong town, Thailand. The research draws heavily on recent work in geography and complexity theory. A series of scenarios were built to explore different development trajectories based upon empirically observed relationships. The development models incorporate a) history and spatial pattern of village settlement; b) road development and changing geographic accessibility; c) population; d) biophysical characteristics and e) social drivers. This research uses multi-temporal and spatially-explicit data, analytic results, and dynamic modeling approaches combined with to describe, explain, and explore LULCC as the consequences of different production theories for rural, small town urbanization in the South East Asian context. Two Agent Based models were built: 1) Settlement model and 2) Land-use model. The Settlement model suggests that new development will emerge along the existing road network especially along the major highway and in close proximity to the urban center. If the population doubles in 2021, the settlement process may inhibit development along some corridors creating low density sprawl. The Land-use model under the urban expansion scenario suggests that new settlements will occur in close proximity to the town center and roads; even though, the area is suitable for rice farming or located on a flood plain. The Land-use model under the cash-crop expansion scenario captures that new agriculture will occur on the flood plain and other areas suitable for rice farming. The Land-use model under the King's Theory scenario suggests that agriculture agents occupied more disperse lands than the cash-crops scenario. In addition, the King's Theory scenario provided more access to water surface than other scenarios and was the most sustainable development plan. These products offer a better understanding of the urban growth and LULCC at a regional scale and will potentially guide more systematic and effective resource management and policy decisions. Although this research focuses on a specific site, the methods employed are applicable to other rural regions with similar characteristics.

Structure and application of an interface program between a geographic-information system and a ground-water flow model

USGS Publications Warehouse

Van Metre, P.C.

1990-01-01

A computer-program interface between a geographic-information system and a groundwater flow model links two unrelated software systems for use in developing the flow models. The interface program allows the modeler to compile and manage geographic components of a groundwater model within the geographic information system. A significant savings of time and effort is realized in developing, calibrating, and displaying the groundwater flow model. Four major guidelines were followed in developing the interface program: (1) no changes to the groundwater flow model code were to be made; (2) a data structure was to be designed within the geographic information system that follows the same basic data structure as the groundwater flow model; (3) the interface program was to be flexible enough to support all basic data options available within the model; and (4) the interface program was to be as efficient as possible in terms of computer time used and online-storage space needed. Because some programs in the interface are written in control-program language, the interface will run only on a computer with the PRIMOS operating system. (USGS)

Regulatory T cell effects in antitumor laser immunotherapy: a mathematical model and analysis

NASA Astrophysics Data System (ADS)

Dawkins, Bryan A.; Laverty, Sean M.

2016-03-01

Regulatory T cells (Tregs) have tremendous influence on treatment outcomes in patients receiving immunotherapy for cancerous tumors. We present a mathematical model incorporating the primary cellular and molecular components of antitumor laser immunotherapy. We explicitly model developmental classes of dendritic cells (DCs), cytotoxic T cells (CTLs), primary and metastatic tumor cells, and tumor antigen. Regulatory T cells have been shown to kill antigen presenting cells, to influence dendritic cell maturation and migration, to kill activated killer CTLs in the tumor microenvironment, and to influence CTL proliferation. Since Tregs affect explicitly modeled cells, but we do not explicitly model dynamics of Treg themselves, we use model parameters to analyze effects of Treg immunosuppressive activity. We will outline a systematic method for assigning clinical outcomes to model simulations and use this condition to associate simulated patient treatment outcome with Treg activity.

A Unified Framework for Monetary Theory and Policy Analysis.

ERIC Educational Resources Information Center

Lagos, Ricardo; Wright, Randall

2005-01-01

Search-theoretic models of monetary exchange are based on explicit descriptions of the frictions that make money essential. However, tractable versions of these models typically make strong assumptions that render them ill suited for monetary policy analysis. We propose a new framework, based on explicit micro foundations, within which macro…

A Naturalistic Inquiry into Praxis When Education Instructors Use Explicit Metacognitive Modeling

ERIC Educational Resources Information Center

Shannon, Nancy Gayle

2014-01-01

This naturalistic inquiry brought together six education instructors in one small teacher preparation program to explore what happens to educational instructors' praxis when the education instructors use explicit metacognitive modeling to reveal their thinking behind their pedagogical decision-making. The participants, while teaching an…

Can a continuum solvent model reproduce the free energy landscape of a -hairpin folding in water?

NASA Astrophysics Data System (ADS)

Zhou, Ruhong; Berne, Bruce J.

2002-10-01

The folding free energy landscape of the C-terminal -hairpin of protein G is explored using the surface-generalized Born (SGB) implicit solvent model, and the results are compared with the landscape from an earlier study with explicit solvent model. The OPLSAA force field is used for the -hairpin in both implicit and explicit solvent simulations, and the conformational space sampling is carried out with a highly parallel replica-exchange method. Surprisingly, we find from exhaustive conformation space sampling that the free energy landscape from the implicit solvent model is quite different from that of the explicit solvent model. In the implicit solvent model some nonnative states are heavily overweighted, and more importantly, the lowest free energy state is no longer the native -strand structure. An overly strong salt-bridge effect between charged residues (E42, D46, D47, E56, and K50) is found to be responsible for this behavior in the implicit solvent model. Despite this, we find that the OPLSAA/SGB energies of all the nonnative structures are higher than that of the native structure; thus the OPLSAA/SGB energy is still a good scoring function for structure prediction for this -hairpin. Furthermore, the -hairpin population at 282 K is found to be less than 40% from the implicit solvent model, which is much smaller than the 72% from the explicit solvent model and 80% from experiment. On the other hand, both implicit and explicit solvent simulations with the OPLSAA force field exhibit no meaningful helical content during the folding process, which is in contrast to some very recent studies using other force fields.

Can a continuum solvent model reproduce the free energy landscape of a β-hairpin folding in water?

PubMed Central

Zhou, Ruhong; Berne, Bruce J.

2002-01-01

The folding free energy landscape of the C-terminal β-hairpin of protein G is explored using the surface-generalized Born (SGB) implicit solvent model, and the results are compared with the landscape from an earlier study with explicit solvent model. The OPLSAA force field is used for the β-hairpin in both implicit and explicit solvent simulations, and the conformational space sampling is carried out with a highly parallel replica-exchange method. Surprisingly, we find from exhaustive conformation space sampling that the free energy landscape from the implicit solvent model is quite different from that of the explicit solvent model. In the implicit solvent model some nonnative states are heavily overweighted, and more importantly, the lowest free energy state is no longer the native β-strand structure. An overly strong salt-bridge effect between charged residues (E42, D46, D47, E56, and K50) is found to be responsible for this behavior in the implicit solvent model. Despite this, we find that the OPLSAA/SGB energies of all the nonnative structures are higher than that of the native structure; thus the OPLSAA/SGB energy is still a good scoring function for structure prediction for this β-hairpin. Furthermore, the β-hairpin population at 282 K is found to be less than 40% from the implicit solvent model, which is much smaller than the 72% from the explicit solvent model and ≈80% from experiment. On the other hand, both implicit and explicit solvent simulations with the OPLSAA force field exhibit no meaningful helical content during the folding process, which is in contrast to some very recent studies using other force fields. PMID:12242327

Can a continuum solvent model reproduce the free energy landscape of a beta -hairpin folding in water?

PubMed

Zhou, Ruhong; Berne, Bruce J

2002-10-01

The folding free energy landscape of the C-terminal beta-hairpin of protein G is explored using the surface-generalized Born (SGB) implicit solvent model, and the results are compared with the landscape from an earlier study with explicit solvent model. The OPLSAA force field is used for the beta-hairpin in both implicit and explicit solvent simulations, and the conformational space sampling is carried out with a highly parallel replica-exchange method. Surprisingly, we find from exhaustive conformation space sampling that the free energy landscape from the implicit solvent model is quite different from that of the explicit solvent model. In the implicit solvent model some nonnative states are heavily overweighted, and more importantly, the lowest free energy state is no longer the native beta-strand structure. An overly strong salt-bridge effect between charged residues (E42, D46, D47, E56, and K50) is found to be responsible for this behavior in the implicit solvent model. Despite this, we find that the OPLSAA/SGB energies of all the nonnative structures are higher than that of the native structure; thus the OPLSAA/SGB energy is still a good scoring function for structure prediction for this beta-hairpin. Furthermore, the beta-hairpin population at 282 K is found to be less than 40% from the implicit solvent model, which is much smaller than the 72% from the explicit solvent model and approximately equal 80% from experiment. On the other hand, both implicit and explicit solvent simulations with the OPLSAA force field exhibit no meaningful helical content during the folding process, which is in contrast to some very recent studies using other force fields.

Support from the relationship of genetic and geographic distance in human populations for a serial founder effect originating in Africa

PubMed Central

Ramachandran, Sohini; Deshpande, Omkar; Roseman, Charles C.; Rosenberg, Noah A.; Feldman, Marcus W.; Cavalli-Sforza, L. Luca

2005-01-01

Equilibrium models of isolation by distance predict an increase in genetic differentiation with geographic distance. Here we find a linear relationship between genetic and geographic distance in a worldwide sample of human populations, with major deviations from the fitted line explicable by admixture or extreme isolation. A close relationship is shown to exist between the correlation of geographic distance and genetic differentiation (as measured by FST) and the geographic pattern of heterozygosity across populations. Considering a worldwide set of geographic locations as possible sources of the human expansion, we find that heterozygosities in the globally distributed populations of the data set are best explained by an expansion originating in Africa and that no geographic origin outside of Africa accounts as well for the observed patterns of genetic diversity. Although the relationship between FST and geographic distance has been interpreted in the past as the result of an equilibrium model of drift and dispersal, simulation shows that the geographic pattern of heterozygosities in this data set is consistent with a model of a serial founder effect starting at a single origin. Given this serial-founder scenario, the relationship between genetic and geographic distance allows us to derive bounds for the effects of drift and natural selection on human genetic variation. PMID:16243969

Design and Establishment of Quality Model of Fundamental Geographic Information Database

NASA Astrophysics Data System (ADS)

Ma, W.; Zhang, J.; Zhao, Y.; Zhang, P.; Dang, Y.; Zhao, T.

2018-04-01

In order to make the quality evaluation for the Fundamental Geographic Information Databases(FGIDB) more comprehensive, objective and accurate, this paper studies and establishes a quality model of FGIDB, which formed by the standardization of database construction and quality control, the conformity of data set quality and the functionality of database management system, and also designs the overall principles, contents and methods of the quality evaluation for FGIDB, providing the basis and reference for carry out quality control and quality evaluation for FGIDB. This paper designs the quality elements, evaluation items and properties of the Fundamental Geographic Information Database gradually based on the quality model framework. Connected organically, these quality elements and evaluation items constitute the quality model of the Fundamental Geographic Information Database. This model is the foundation for the quality demand stipulation and quality evaluation of the Fundamental Geographic Information Database, and is of great significance on the quality assurance in the design and development stage, the demand formulation in the testing evaluation stage, and the standard system construction for quality evaluation technology of the Fundamental Geographic Information Database.

Improvement of the F-Perceptory Approach Through Management of Fuzzy Complex Geographic Objects

NASA Astrophysics Data System (ADS)

Khalfi, B.; de Runz, C.; Faiz, S.; Akdag, H.

2015-08-01

In the real world, data is imperfect and in various ways such as imprecision, vagueness, uncertainty, ambiguity and inconsistency. For geographic data, the fuzzy aspect is mainly manifested in time, space and the function of objects and is due to a lack of precision. Therefore, the researchers in the domain emphasize the importance of modeling data structures in GIS but also their lack of adaptation to fuzzy data. The F-Perceptory approachh manages the modeling of imperfect geographic information with UML. This management is essential to maintain faithfulness to reality and to better guide the user in his decision-making. However, this approach does not manage fuzzy complex geographic objects. The latter presents a multiple object with similar or different geographic shapes. So, in this paper, we propose to improve the F-Perceptory approach by proposing to handle fuzzy complex geographic objects modeling. In a second step, we propose its transformation to the UML modeling.

Modeling Task Switching without Switching Tasks: A Short-Term Priming Account of Explicitly Cued Performance

ERIC Educational Resources Information Center

Schneider, Darryl W.; Logan, Gordon D.

2005-01-01

Switch costs in task switching are commonly attributed to an executive control process of task-set reconfiguration, particularly in studies involving the explicit task-cuing procedure. The authors propose an alternative account of explicitly cued performance that is based on 2 mechanisms: priming of cue encoding from residual activation of cues in…

The Things You Do: Internal Models of Others’ Expected Behaviour Guide Action Observation

PubMed Central

Schenke, Kimberley C.; Wyer, Natalie A.; Bach, Patric

2016-01-01

Predictions allow humans to manage uncertainties within social interactions. Here, we investigate how explicit and implicit person models–how different people behave in different situations–shape these predictions. In a novel action identification task, participants judged whether actors interacted with or withdrew from objects. In two experiments, we manipulated, unbeknownst to participants, the two actors action likelihoods across situations, such that one actor typically interacted with one object and withdrew from the other, while the other actor showed the opposite behaviour. In Experiment 2, participants additionally received explicit information about the two individuals that either matched or mismatched their actual behaviours. The data revealed direct but dissociable effects of both kinds of person information on action identification. Implicit action likelihoods affected response times, speeding up the identification of typical relative to atypical actions, irrespective of the explicit knowledge about the individual’s behaviour. Explicit person knowledge, in contrast, affected error rates, causing participants to respond according to expectations instead of observed behaviour, even when they were aware that the explicit information might not be valid. Together, the data show that internal models of others’ behaviour are routinely re-activated during action observation. They provide first evidence of a person-specific social anticipation system, which predicts forthcoming actions from both explicit information and an individuals’ prior behaviour in a situation. These data link action observation to recent models of predictive coding in the non-social domain where similar dissociations between implicit effects on stimulus identification and explicit behavioural wagers have been reported. PMID:27434265

Alcohol-Approach Inclinations and Drinking Identity as Predictors of Behavioral Economic Demand for Alcohol

PubMed Central

Ramirez, Jason J.; Dennhardt, Ashley A.; Baldwin, Scott A.; Murphy, James G.; Lindgren, Kristen P.

2016-01-01

Behavioral economic demand curve indices of alcohol consumption reflect decisions to consume alcohol at varying costs. Although these indices predict alcohol-related problems beyond established predictors, little is known about the determinants of elevated demand. Two cognitive constructs that may underlie alcohol demand are alcohol-approach inclinations and drinking identity. The aim of this study was to evaluate implicit and explicit measures of these constructs as predictors of alcohol demand curve indices. College student drinkers (N = 223, 59% female) completed implicit and explicit measures of drinking identity and alcohol-approach inclinations at three timepoints separated by three-month intervals, and completed the Alcohol Purchase Task to assess demand at Time 3. Given no change in our alcohol-approach inclinations and drinking identity measures over time, random intercept-only models were used to predict two demand indices: Amplitude, which represents maximum hypothetical alcohol consumption and expenditures, and Persistence, which represents sensitivity to increasing prices. When modeled separately, implicit and explicit measures of drinking identity and alcohol-approach inclinations positively predicted demand indices. When implicit and explicit measures were included in the same model, both measures of drinking identity predicted Amplitude, but only explicit drinking identity predicted Persistence. In contrast, explicit measures of alcohol-approach inclinations, but not implicit measures, predicted both demand indices. Therefore, there was more support for explicit, versus implicit, measures as unique predictors of alcohol demand. Overall, drinking identity and alcohol-approach inclinations both exhibit positive associations with alcohol demand and represent potentially modifiable cognitive constructs that may underlie elevated demand in college student drinkers. PMID:27379444

Predictive models and spatial variations of vital capacity in healthy people from 6 to 84 years old in China based on geographical factors.

PubMed

He, Jinwei; Ge, Miao; Wang, Congxia; Jiang, Naigui; Zhang, Mingxin; Yun, Pujun

2014-07-01

The aim of this study was to provide a scientific basic for a unified standard of the reference value of vital capacity (VC) of healthy subjects from 6 and 84 years old in China. The normal reference value of VC was correlated to seven geographical factors, including altitude (X1), annual duration of sunshine (X2), annual mean air temperature (X3), annual mean relative humidity (X4), annual precipitation amount (X5), annual air temperature range (X6) and annual mean wind speed (X7). Predictive models were established by five different linear and nonlinear methods. The best models were selected by t-test. The geographical distribution map of VC in different age groups can be interpolated by Kriging's method using ArcGIS software. It was found that the correlation of VC and geographical factors in China was quite significant, especially for both males and females aged from 6 to 45. The best models were built for different age groups. The geographical distribution map shows the spatial variations of VC in China precisely. The VC of healthy subjects can be simulated by the best model or acquired from the geographical distribution map provided the geographical factors for that city or county of China are known.

Investigating Surface Bias Errors in the Weather Research and Forecasting (WRF) Model using a Geographic Information System (GIS)

DTIC Science & Technology

2015-02-01

WRF ) Model using a Geographic Information System (GIS) by Jeffrey A Smith, Theresa A Foley, John W Raby, and Brian Reen...ARL-TR-7212 ● FEB 2015 US Army Research Laboratory Investigating Surface Bias Errors in the Weather Research and Forecasting ( WRF ) Model...SUBTITLE Investigating surface bias errors in the Weather Research and Forecasting ( WRF ) Model using a Geographic Information System (GIS) 5a

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

Doherty, K.E.; Naugle, D.E.; Walker, B.L.

Recent energy development has resulted in rapid and large-scale changes to western shrub-steppe ecosystems without a complete understanding of its potential impacts on wildlife populations. We modeled winter habitat use by female greater sage-grouse (Centrocercus urophasianus) in the Powder River Basin (PRB) of Wyoming and Montana, USA, to 1) identify landscape features that influenced sage-grouse habitat selection, 2) assess the scale at which selection occurred, 3) spatially depict winter habitat quality in a Geographic Information System, and 4) assess the effect of coal-bed natural gas (CBNG) development on winter habitat selection. We developed a model of winter habitat selection basedmore » on 435 aerial relocations of 200 radiomarked female sage-grouse obtained during the winters of 2005 and 2006. Percent sagebrush (Artemisia spp.) cover on the landscape was an important predictor of use by sage-grouse in winter. Sage-grouse were 1.3 times more likely to occupy sagebrush habitats that lacked CBNG wells within a 4-km{sup 2} area, compared to those that had the maximum density of 12.3 wells per 4 km{sup 2} allowed on federal lands. We validated the model with 74 locations from 74 radiomarked individuals obtained during the winters of 2004 and 2007. This winter habitat model based on vegetation, topography, and CBNG avoidance was highly predictive (validation R{sup 2} = 0.984). Our spatially explicit model can be used to identify areas that provide the best remaining habitat for wintering sage-grouse in the PRB to mitigate impacts of energy development.« less

An integrated multi-criteria scenario evaluation web tool for participatory land-use planning in urbanized areas: The Ecosystem Portfolio Model

USGS Publications Warehouse

Labiosa, Bill; Forney, William M.; Hearn,, Paul P.; Hogan, Dianna M.; Strong, David R.; Swain, Eric D.; Esnard, Ann-Margaret; Mitsova-Boneva, D.; Bernknopf, R.; Pearlstine, Leonard; Gladwin, Hugh

2013-01-01

Land-use land-cover change is one of the most important and direct drivers of changes in ecosystem functions and services. Given the complexity of the decision-making, there is a need for Internet-based decision support systems with scenario evaluation capabilities to help planners, resource managers and communities visualize, compare and consider trade-offs among the many values at stake in land use planning. This article presents details on an Ecosystem Portfolio Model (EPM) prototype that integrates ecological, socio-economic information and associated values of relevance to decision-makers and stakeholders. The EPM uses a multi-criteria scenario evaluation framework, Geographic Information Systems (GIS) analysis and spatially-explicit land-use/land-cover change-sensitive models to characterize changes in important land-cover related ecosystem values related to ecosystem services and functions, land parcel prices, and community quality-of-life (QoL) metrics. Parameters in the underlying models can be modified through the interface, allowing users in a facilitated group setting to explore simultaneously issues of scientific uncertainty and divergence in the preferences of stakeholders. One application of the South Florida EPM prototype reported in this article shows the modeled changes (which are significant) in aggregate ecological value, landscape patterns and fragmentation, biodiversity potential and ecological restoration potential for current land uses compared to the 2050 land-use scenario. Ongoing refinements to EPM, and future work especially in regard to modifiable sea level rise scenarios are also discussed.

A Three-Stage Model of Housing Search,

DTIC Science & Technology

1980-05-01

Hanushek and Quigley, 1978) that recognize housing search as a transaction cost but rarely - .. examine search behavior; and descriptive studies of search...explicit mobility models that have recently appeared in the liter- ature (Speare et al., 1975; Hanushek and Quigley, 1978; Brummell, 1979). Although...1978; Hanushek and Quigley, 1978; Cronin, 1978). By explicitly assigning dollar values, the economic models attempt to obtain an objective measure of

DoD Product Line Practice Workshop Report

DTIC Science & Technology

1998-05-01

capability. The essential enterprise management practices include ensuring sound business goals providing an appropriate funding model performing...business. This way requires vision and explicit support at the organizational level. There must be an explicit funding model to support the development...the same group seems to work best in smaller organizations. A funding model for core asset development also needs to be developed because the core

Global Dynamic Exposure and the OpenBuildingMap

NASA Astrophysics Data System (ADS)

Schorlemmer, D.; Beutin, T.; Hirata, N.; Hao, K. X.; Wyss, M.; Cotton, F.; Prehn, K.

2015-12-01

Detailed understanding of local risk factors regarding natural catastrophes requires in-depth characterization of the local exposure. Current exposure capture techniques have to find the balance between resolution and coverage. We aim at bridging this gap by employing a crowd-sourced approach to exposure capturing focusing on risk related to earthquake hazard. OpenStreetMap (OSM), the rich and constantly growing geographical database, is an ideal foundation for us. More than 2.5 billion geographical nodes, more than 150 million building footprints (growing by ~100'000 per day), and a plethora of information about school, hospital, and other critical facility locations allow us to exploit this dataset for risk-related computations. We will harvest this dataset by collecting exposure and vulnerability indicators from explicitly provided data (e.g. hospital locations), implicitly provided data (e.g. building shapes and positions), and semantically derived data, i.e. interpretation applying expert knowledge. With this approach, we can increase the resolution of existing exposure models from fragility classes distribution via block-by-block specifications to building-by-building vulnerability. To increase coverage, we will provide a framework for collecting building data by any person or community. We will implement a double crowd-sourced approach to bring together the interest and enthusiasm of communities with the knowledge of earthquake and engineering experts. The first crowd-sourced approach aims at collecting building properties in a community by local people and activists. This will be supported by tailored building capture tools for mobile devices for simple and fast building property capturing. The second crowd-sourced approach involves local experts in estimating building vulnerability that will provide building classification rules that translate building properties into vulnerability and exposure indicators as defined in the Building Taxonomy 2.0 developed by the Global Earthquake Model (GEM). These indicators will then be combined with a hazard model using the GEM OpenQuake engine to compute a risk model. The free/open framework we will provide can be used on commodity hardware for local to regional exposure capturing and for communities to understand their earthquake risk.

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

Wieder, William R.; Allison, Steven D.; Davidson, Eric A.

Microbes influence soil organic matter (SOM) decomposition and the long-term stabilization of carbon (C) in soils. We contend that by revising the representation of microbial processes and their interactions with the physicochemical soil environment, Earth system models (ESMs) may make more realistic global C cycle projections. Explicit representation of microbial processes presents considerable challenges due to the scale at which these processes occur. Thus, applying microbial theory in ESMs requires a framework to link micro-scale process-level understanding and measurements to macro-scale models used to make decadal- to century-long projections. Here, we review the diversity, advantages, and pitfalls of simulating soilmore » biogeochemical cycles using microbial-explicit modeling approaches. We present a roadmap for how to begin building, applying, and evaluating reliable microbial-explicit model formulations that can be applied in ESMs. Drawing from experience with traditional decomposition models we suggest: (1) guidelines for common model parameters and output that can facilitate future model intercomparisons; (2) development of benchmarking and model-data integration frameworks that can be used to effectively guide, inform, and evaluate model parameterizations with data from well-curated repositories; and (3) the application of scaling methods to integrate microbial-explicit soil biogeochemistry modules within ESMs. With contributions across scientific disciplines, we feel this roadmap can advance our fundamental understanding of soil biogeochemical dynamics and more realistically project likely soil C response to environmental change at global scales.« less

Self-Love or Other-Love? Explicit Other-Preference but Implicit Self-Preference

PubMed Central

Gebauer, Jochen E.; Göritz, Anja S.; Hofmann, Wilhelm; Sedikides, Constantine

2012-01-01

Do humans prefer the self even over their favorite other person? This question has pervaded philosophy and social-behavioral sciences. Psychology’s distinction between explicit and implicit preferences calls for a two-tiered solution. Our evolutionarily-based Dissociative Self-Preference Model offers two hypotheses. Other-preferences prevail at an explicit level, because they convey caring for others, which strengthens interpersonal bonds–a major evolutionary advantage. Self-preferences, however, prevail at an implicit level, because they facilitate self-serving automatic behavior, which favors the self in life-or-die situations–also a major evolutionary advantage. We examined the data of 1,519 participants, who completed an explicit measure and one of five implicit measures of preferences for self versus favorite other. The results were consistent with the Dissociative Self-Preference Model. Explicitly, participants preferred their favorite other over the self. Implicitly, however, they preferred the self over their favorite other (be it their child, romantic partner, or best friend). Results are discussed in relation to evolutionary theorizing on self-deception. PMID:22848605

A Metacognitive Approach to "Implicit" and "Explicit" Evaluations: Comment on Gawronski and Bodenhausen (2006)

ERIC Educational Resources Information Center

Petty, Richard E.; Brinol, Pablo

2006-01-01

Comments on the article by B. Gawronski and G. V. Bodenhausen (see record 2006-10465-003). A metacognitive model (MCM) is presented to describe how automatic (implicit) and deliberative (explicit) measures of attitudes respond to change attempts. The model assumes that contemporary implicit measures tap quick evaluative associations, whereas…

A Watershed-based spatially-explicit demonstration of an Integrated Environmental Modeling Framework for Ecosystem Services in the Coal River Basin (WV, USA)

EPA Science Inventory

We demonstrate a spatially-explicit regional assessment of current condition of aquatic ecoservices in the Coal River Basin (CRB), with limited sensitivity analysis for the atmospheric contaminant mercury. The integrated modeling framework (IMF) forecasts water quality and quant...

USING THE ECLPSS SOFTWARE ENVIRONMENT TO BUILD A SPATIALLY EXPLICIT COMPONENT-BASED MODEL OF OZONE EFFECTS ON FOREST ECOSYSTEMS. (R827958)

EPA Science Inventory

We have developed a modeling framework to support grid-based simulation of ecosystems at multiple spatial scales, the Ecological Component Library for Parallel Spatial Simulation (ECLPSS). ECLPSS helps ecologists to build robust spatially explicit simulations of ...

A masked negative self-esteem? Implicit and explicit self-esteem in patients with Narcissistic Personality Disorder.

PubMed

Marissen, Marlies A E; Brouwer, Marlies E; Hiemstra, Annemarie M F; Deen, Mathijs L; Franken, Ingmar H A

2016-08-30

The mask model of narcissism states that the narcissistic traits of patients with NPD are the result of a compensatory reaction to underlying ego fragility. This model assumes that high explicit self-esteem masks low implicit self-esteem. However, research on narcissism has predominantly focused on non-clinical participants and data derived from patients diagnosed with Narcissistic Personality Disorder (NPD) remain scarce. Therefore, the goal of the present study was to test the mask model hypothesis of narcissism among patients with NPD. Male patients with NPD were compared to patients with other PD's and healthy participants on implicit and explicit self-esteem. NPD patients did not differ in levels of explicit and implicit self-esteem compared to both the psychiatric and the healthy control group. Overall, the current study found no evidence in support of the mask model of narcissism among a clinical group. This implicates that it might not be relevant for clinicians to focus treatment of NPD on an underlying negative self-esteem. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

The Planetary Data System Information Model for Geometry Metadata

NASA Astrophysics Data System (ADS)

Guinness, E. A.; Gordon, M. K.

2014-12-01

The NASA Planetary Data System (PDS) has recently developed a new set of archiving standards based on a rigorously defined information model. An important part of the new PDS information model is the model for geometry metadata, which includes, for example, attributes of the lighting and viewing angles of observations, position and velocity vectors of a spacecraft relative to Sun and observing body at the time of observation and the location and orientation of an observation on the target. The PDS geometry model is based on requirements gathered from the planetary research community, data producers, and software engineers who build search tools. A key requirement for the model is that it fully supports the breadth of PDS archives that include a wide range of data types from missions and instruments observing many types of solar system bodies such as planets, ring systems, and smaller bodies (moons, comets, and asteroids). Thus, important design aspects of the geometry model are that it standardizes the definition of the geometry attributes and provides consistency of geometry metadata across planetary science disciplines. The model specification also includes parameters so that the context of values can be unambiguously interpreted. For example, the reference frame used for specifying geographic locations on a planetary body is explicitly included with the other geometry metadata parameters. The structure and content of the new PDS geometry model is designed to enable both science analysis and efficient development of search tools. The geometry model is implemented in XML, as is the main PDS information model, and uses XML schema for validation. The initial version of the geometry model is focused on geometry for remote sensing observations conducted by flyby and orbiting spacecraft. Future releases of the PDS geometry model will be expanded to include metadata for landed and rover spacecraft.

Large-area mapping of biodiversity

USGS Publications Warehouse

Scott, J.M.; Jennings, M.D.

1998-01-01

The age of discovery, description, and classification of biodiversity is entering a new phase. In responding to the conservation imperative, we can now supplement the essential work of systematics with spatially explicit information on species and assemblages of species. This is possible because of recent conceptual, technical, and organizational progress in generating synoptic views of the earth's surface and a great deal of its biological content, at multiple scales of thematic as well as geographic resolution. The development of extensive spatial data on species distributions and vegetation types provides us with a framework for: (a) assessing what we know and where we know it at meso-scales, and (b) stratifying the biological universe so that higher-resolution surveys can be more efficiently implemented, coveting, for example, geographic adequacy of specimen collections, population abundance, reproductive success, and genetic dynamics. The land areas involved are very large, and the questions, such as resolution, scale, classification, and accuracy, are complex. In this paper, we provide examples from the United States Gap Analysis Program on the advantages and limitations of mapping the occurrence of terrestrial vertebrate species and dominant land-cover types over large areas as joint ventures and in multi-organizational partnerships, and how these cooperative efforts can be designed to implement results from data development and analyses as on-the-ground actions. Clearly, new frameworks for thinking about biogeographic information as well as organizational cooperation are needed if we are to have any hope of documenting the full range of species occurrences and ecological processes in ways meaningful to their management. The Gap Analysis experience provides one model for achieving these new frameworks.

Spatial autocorrelation among automated geocoding errors and its effects on testing for disease clustering

PubMed Central

Li, Jie; Fang, Xiangming

2010-01-01

Automated geocoding of patient addresses is an important data assimilation component of many spatial epidemiologic studies. Inevitably, the geocoding process results in positional errors. Positional errors incurred by automated geocoding tend to reduce the power of tests for disease clustering and otherwise affect spatial analytic methods. However, there are reasons to believe that the errors may often be positively spatially correlated and that this may mitigate their deleterious effects on spatial analyses. In this article, we demonstrate explicitly that the positional errors associated with automated geocoding of a dataset of more than 6000 addresses in Carroll County, Iowa are spatially autocorrelated. Furthermore, through two simulation studies of disease processes, including one in which the disease process is overlain upon the Carroll County addresses, we show that spatial autocorrelation among geocoding errors maintains the power of two tests for disease clustering at a level higher than that which would occur if the errors were independent. Implications of these results for cluster detection, privacy protection, and measurement-error modeling of geographic health data are discussed. PMID:20087879

Mobile, Collaborative Situated Knowledge Creation for Urban Planning

PubMed Central

Zurita, Gustavo; Baloian, Nelson

2012-01-01

Geo-collaboration is an emerging research area in computer sciences studying the way spatial, geographically referenced information and communication technologies can support collaborative activities. Scenarios in which information associated to its physical location are of paramount importance are often referred as Situated Knowledge Creation scenarios. To date there are few computer systems supporting knowledge creation that explicitly incorporate physical context as part of the knowledge being managed in mobile face-to-face scenarios. This work presents a collaborative software application supporting visually-geo-referenced knowledge creation in mobile working scenarios while the users are interacting face-to-face. The system allows to manage data information associated to specific physical locations for knowledge creation processes in the field, such as urban planning, identifying specific physical locations, territorial management, etc.; using Tablet-PCs and GPS in order to geo-reference data and information. It presents a model for developing mobile applications supporting situated knowledge creation in the field, introducing the requirements for such an application and the functionalities it should have in order to fulfill them. The paper also presents the results of utility and usability evaluations. PMID:22778639

Mobile, collaborative situated knowledge creation for urban planning.

PubMed

Zurita, Gustavo; Baloian, Nelson

2012-01-01

Geo-collaboration is an emerging research area in computer sciences studying the way spatial, geographically referenced information and communication technologies can support collaborative activities. Scenarios in which information associated to its physical location are of paramount importance are often referred as Situated Knowledge Creation scenarios. To date there are few computer systems supporting knowledge creation that explicitly incorporate physical context as part of the knowledge being managed in mobile face-to-face scenarios. This work presents a collaborative software application supporting visually-geo-referenced knowledge creation in mobile working scenarios while the users are interacting face-to-face. The system allows to manage data information associated to specific physical locations for knowledge creation processes in the field, such as urban planning, identifying specific physical locations, territorial management, etc.; using Tablet-PCs and GPS in order to geo-reference data and information. It presents a model for developing mobile applications supporting situated knowledge creation in the field, introducing the requirements for such an application and the functionalities it should have in order to fulfill them. The paper also presents the results of utility and usability evaluations.

The role of E-mentorship in a virtual world for youth transplant recipients.

PubMed

Cantrell, Kathryn; Fischer, Amy; Bouzaher, Alisha; Bers, Marina

2010-01-01

Because of geographic distances, many youth transplant recipients do not have the opportunity to meet and form relationships with peers who have undergone similar experiences. This article explores the role of E-mentorship in virtual environments. Most specifically, by analyzing data from a study conducted with the Zora virtual world with pediatric transplant recipients, suggestions and recommendations are given for conceiving the role of virtual mentors and allocating the needed resources. Zora is a graphical virtual world designed to create a community that offers psychoeducational support and the possibility of participating in virtual activities following a curriculum explicitly designed to address issues of school transition and medical adherence. Activities are designed to foster relationships, teach technological skills, and facilitate the formation of a support network of peers and mentors.This article addresses the research question, "What makes a successful E-mentorship model in virtual worlds for children with serious illnesses?" by looking at E-mentoring patterns such as time spent online, chat analysis, initiation of conversation, initiation of activities, and out-of-world contact.

The Effects of Explicit Teaching of Strategies, Second-Order Concepts, and Epistemological Underpinnings on Students' Ability to Reason Causally in History

ERIC Educational Resources Information Center

Stoel, Gerhard L.; van Drie, Jannet P.; van Boxtel, Carla A. M.

2017-01-01

This article reports an experimental study on the effects of explicit teaching on 11th grade students' ability to reason causally in history. Underpinned by the model of domain learning, explicit teaching is conceptualized as multidimensional, focusing on strategies and second-order concepts to generate and verbalize causal explanations and…

Investigating the predictive validity of implicit and explicit measures of motivation on condom use, physical activity and healthy eating.

PubMed

Keatley, David; Clarke, David D; Hagger, Martin S

2012-01-01

The literature on health-related behaviours and motivation is replete with research involving explicit processes and their relations with intentions and behaviour. Recently, interest has been focused on the impact of implicit processes and measures on health-related behaviours. Dual-systems models have been proposed to provide a framework for understanding the effects of explicit or deliberative and implicit or impulsive processes on health behaviours. Informed by a dual-systems approach and self-determination theory, the aim of this study was to test the effects of implicit and explicit motivation on three health-related behaviours in a sample of undergraduate students (N = 162). Implicit motives were hypothesised to predict behaviour independent of intentions while explicit motives would be mediated by intentions. Regression analyses indicated that implicit motivation predicted physical activity behaviour only. Across all behaviours, intention mediated the effects of explicit motivational variables from self-determination theory. This study provides limited support for dual-systems models and the role of implicit motivation in the prediction of health-related behaviour. Suggestions for future research into the role of implicit processes in motivation are outlined.

The feasibility of using explicit method for linear correction of the particle size variation using NIR Spectroscopy combined with PLS2regression method

NASA Astrophysics Data System (ADS)

Yulia, M.; Suhandy, D.

2018-03-01

NIR spectra obtained from spectral data acquisition system contains both chemical information of samples as well as physical information of the samples, such as particle size and bulk density. Several methods have been established for developing calibration models that can compensate for sample physical information variations. One common approach is to include physical information variation in the calibration model both explicitly and implicitly. The objective of this study was to evaluate the feasibility of using explicit method to compensate the influence of different particle size of coffee powder in NIR calibration model performance. A number of 220 coffee powder samples with two different types of coffee (civet and non-civet) and two different particle sizes (212 and 500 µm) were prepared. Spectral data was acquired using NIR spectrometer equipped with an integrating sphere for diffuse reflectance measurement. A discrimination method based on PLS-DA was conducted and the influence of different particle size on the performance of PLS-DA was investigated. In explicit method, we add directly the particle size as predicted variable results in an X block containing only the NIR spectra and a Y block containing the particle size and type of coffee. The explicit inclusion of the particle size into the calibration model is expected to improve the accuracy of type of coffee determination. The result shows that using explicit method the quality of the developed calibration model for type of coffee determination is a little bit superior with coefficient of determination (R2) = 0.99 and root mean square error of cross-validation (RMSECV) = 0.041. The performance of the PLS2 calibration model for type of coffee determination with particle size compensation was quite good and able to predict the type of coffee in two different particle sizes with relatively high R2 pred values. The prediction also resulted in low bias and RMSEP values.

An explicit asymptotic model for the surface wave in a viscoelastic half-space based on applying Rabotnov's fractional exponential integral operators

NASA Astrophysics Data System (ADS)

Wilde, M. V.; Sergeeva, N. V.

2018-05-01

An explicit asymptotic model extracting the contribution of a surface wave to the dynamic response of a viscoelastic half-space is derived. Fractional exponential Rabotnov's integral operators are used for describing of material properties. The model is derived by extracting the principal part of the poles corresponding to the surface waves after applying Laplace and Fourier transforms. The simplified equations for the originals are written by using power series expansions. Padè approximation is constructed to unite short-time and long-time models. The form of this approximation allows to formulate the explicit model using a fractional exponential Rabotnov's integral operator with parameters depending on the properties of surface wave. The applicability of derived models is studied by comparing with the exact solutions of a model problem. It is revealed that the model based on Padè approximation is highly effective for all the possible time domains.

Age effects on explicit and implicit memory

PubMed Central

Ward, Emma V.; Berry, Christopher J.; Shanks, David R.

2013-01-01

It is well-documented that explicit memory (e.g., recognition) declines with age. In contrast, many argue that implicit memory (e.g., priming) is preserved in healthy aging. For example, priming on tasks such as perceptual identification is often not statistically different in groups of young and older adults. Such observations are commonly taken as evidence for distinct explicit and implicit learning/memory systems. In this article we discuss several lines of evidence that challenge this view. We describe how patterns of differential age-related decline may arise from differences in the ways in which the two forms of memory are commonly measured, and review recent research suggesting that under improved measurement methods, implicit memory is not age-invariant. Formal computational models are of considerable utility in revealing the nature of underlying systems. We report the results of applying single and multiple-systems models to data on age effects in implicit and explicit memory. Model comparison clearly favors the single-system view. Implications for the memory systems debate are discussed. PMID:24065942

High-Order/Low-Order methods for ocean modeling

DOE PAGES

Newman, Christopher; Womeldorff, Geoff; Chacón, Luis; ...

2015-06-01

In this study, we examine a High Order/Low Order (HOLO) approach for a z-level ocean model and show that the traditional semi-implicit and split-explicit methods, as well as a recent preconditioning strategy, can easily be cast in the framework of HOLO methods. The HOLO formulation admits an implicit-explicit method that is algorithmically scalable and second-order accurate, allowing timesteps much larger than the barotropic time scale. We show how HOLO approaches, in particular the implicit-explicit method, can provide a solid route for ocean simulation to heterogeneous computing and exascale environments.

Explicit robust schemes for implementation of a class of principal value-based constitutive models: Symbolic and numeric implementation

NASA Technical Reports Server (NTRS)

Arnold, S. M.; Saleeb, A. F.; Tan, H. Q.; Zhang, Y.

1993-01-01

The issue of developing effective and robust schemes to implement a class of the Ogden-type hyperelastic constitutive models is addressed. To this end, special purpose functions (running under MACSYMA) are developed for the symbolic derivation, evaluation, and automatic FORTRAN code generation of explicit expressions for the corresponding stress function and material tangent stiffness tensors. These explicit forms are valid over the entire deformation range, since the singularities resulting from repeated principal-stretch values have been theoretically removed. The required computational algorithms are outlined, and the resulting FORTRAN computer code is presented.

Modelling the ecological vulnerability to forest fires in mediterranean ecosystems using geographic information technologies.

PubMed

Duguy, Beatriz; Alloza, José Antonio; Baeza, M Jaime; De la Riva, Juan; Echeverría, Maite; Ibarra, Paloma; Llovet, Juan; Cabello, Fernando Pérez; Rovira, Pere; Vallejo, Ramon V

2012-12-01

Forest fires represent a major driver of change at the ecosystem and landscape levels in the Mediterranean region. Environmental features and vegetation are key factors to estimate the ecological vulnerability to fire; defined as the degree to which an ecosystem is susceptible to, and unable to cope with, adverse effects of fire (provided a fire occurs). Given the predicted climatic changes for the region, it is urgent to validate spatially explicit tools for assessing this vulnerability in order to support the design of new fire prevention and restoration strategies. This work presents an innovative GIS-based modelling approach to evaluate the ecological vulnerability to fire of an ecosystem, considering its main components (soil and vegetation) and different time scales. The evaluation was structured in three stages: short-term (focussed on soil degradation risk), medium-term (focussed on changes in vegetation), and coupling of the short- and medium-term vulnerabilities. The model was implemented in two regions: Aragón (inland North-eastern Spain) and Valencia (eastern Spain). Maps of the ecological vulnerability to fire were produced at a regional scale. We partially validated the model in a study site combining two complementary approaches that focused on testing the adequacy of model's predictions in three ecosystems, all very common in fire-prone landscapes of eastern Spain: two shrublands and a pine forest. Both approaches were based on the comparison of model's predictions with values of NDVI (Normalized Difference Vegetation Index), which is considered a good proxy for green biomass. Both methods showed that the model's performance is satisfactory when applied to the three selected vegetation types.

Class of self-limiting growth models in the presence of nonlinear diffusion

NASA Astrophysics Data System (ADS)

Kar, Sandip; Banik, Suman Kumar; Ray, Deb Shankar

2002-06-01

The source term in a reaction-diffusion system, in general, does not involve explicit time dependence. A class of self-limiting growth models dealing with animal and tumor growth and bacterial population in a culture, on the other hand, are described by kinetics with explicit functions of time. We analyze a reaction-diffusion system to study the propagation of spatial front for these models.

Magnetic navigation behavior and the oceanic ecology of young loggerhead sea turtles.

PubMed

Putman, Nathan F; Verley, Philippe; Endres, Courtney S; Lohmann, Kenneth J

2015-04-01

During long-distance migrations, animals navigate using a variety of sensory cues, mechanisms and strategies. Although guidance mechanisms are usually studied under controlled laboratory conditions, such methods seldom allow for navigation behavior to be examined in an environmental context. Similarly, although realistic environmental models are often used to investigate the ecological implications of animal movement, explicit consideration of navigation mechanisms in such models is rare. Here, we used an interdisciplinary approach in which we first conducted lab-based experiments to determine how hatchling loggerhead sea turtles (Caretta caretta) respond to magnetic fields that exist at five widely separated locations along their migratory route, and then studied the consequences of the observed behavior by simulating it within an ocean circulation model. Magnetic fields associated with two geographic regions that pose risks to young turtles (due to cold wintertime temperatures or potential displacement from the migratory route) elicited oriented swimming, whereas fields from three locations where surface currents and temperature pose no such risk did not. Additionally, at locations with fields that elicited oriented swimming, simulations indicate that the observed behavior greatly increases the likelihood of turtles advancing along the migratory pathway. Our findings suggest that the magnetic navigation behavior of sea turtles is intimately tied to their oceanic ecology and is shaped by a complex interplay between ocean circulation and geomagnetic dynamics. © 2015. Published by The Company of Biologists Ltd.

Optimal policy for mitigating emissions in the European transport sector

NASA Astrophysics Data System (ADS)

Leduc, Sylvain; Piera, Patrizio; Sennai, Mesfun; Igor, Staritsky; Berien, Elbersen; Tijs, Lammens; Florian, Kraxner

2017-04-01

A geographic explicit techno-economic model, BeWhere (www.iiasa.ac.at/bewhere), has been developed at the European scale (Europe 28, the Balkans countries, Turkey, Moldavia and Ukraine) at a 40km grid size, to assess the potential of bioenergy from non-food feedstock. Based on the minimization of the supply chain from feedstock collection to the final energy product distribution, the model identifies the optimal bioenergy production plants in terms of spatial location, technology and capacity. The feedstock of interests are woody biomass (divided into eight types from conifers and non-conifers) and five different crop residuals. For each type of feedstock, one or multiple technologies can be applied for either heat, electricity or biofuel production. The model is run for different policy tools such as carbon cost, biofuel support, or subsidies, and the optimal mix of technologies and biomass needed is optimized to reach a production cost competitive against the actual reference system which is fossil fuel based. From this approach, the optimal mix of policy tools that can be applied country wide in Europe will be identified. The preliminary results show that high carbon tax and biofuel support contribute to the development of large scale biofuel production based on woody biomass plants mainly located in the northern part of Europe. Finally the highest emission reduction is reached with low biofuel support and high carbon tax evenly distributed in Europe.

Geographical distance and local environmental conditions drive the genetic population structure of a freshwater microalga (Bathycoccaceae; Chlorophyta) in Patagonian lakes.

PubMed

Fernández, Leonardo D; Hernández, Cristián E; Schiaffino, M Romina; Izaguirre, Irina; Lara, Enrique

2017-10-01

The patterns and mechanisms underlying the genetic structure of microbial populations remain unresolved. Herein we investigated the role played by two non-mutually exclusive models (i.e. isolation by distance and isolation by environment) in shaping the genetic structure of lacustrine populations of a microalga (a freshwater Bathycoccaceae) in the Argentinean Patagonia. To our knowledge, this was the first study to investigate the genetic population structure in a South American microorganism. Population-level analyses based on ITS1-5.8S-ITS2 sequences revealed high levels of nucleotide and haplotype diversity within and among populations. Fixation index and a spatially explicit Bayesian analysis confirmed the occurrence of genetically distinct microalga populations in Patagonia. Isolation by distance and isolation by environment accounted for 38.5% and 17.7% of the genetic structure observed, respectively, whereas together these models accounted for 41% of the genetic differentiation. While our results highlighted isolation by distance and isolation by environment as important mechanisms in driving the genetic population structure of the microalga studied, none of these models (either alone or together) could explain the entire genetic differentiation observed. The unexplained variation in the genetic differentiation observed could be the result of founder events combined with rapid local adaptations, as proposed by the monopolisation hypothesis. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Agent-Based Simulations of Malaria Transmissions with Applications to a Study Site in Thailand

NASA Technical Reports Server (NTRS)

Kiang, Richard K.; Adimi, Farida; Zollner, Gabriela E.; Coleman, Russell E.

2006-01-01

The dynamics of malaria transmission are driven by environmental, biotic and socioeconomic factors. Because of the geographic dependency of these factors and the complex interactions among them, it is difficult to generalize the key factors that perpetuate or intensify malaria transmission. Methods: Discrete event simulations were used for modeling the detailed interactions among the vector life cycle, sporogonic cycle and human infection cycle, under the explicit influences of selected extrinsic and intrinsic factors. Meteorological and environmental parameters may be derived from satellite data. The output of the model includes the individual infection status and the quantities normally observed in field studies, such as mosquito biting rates, sporozoite infection rates, gametocyte prevalence and incidence. Results were compared with mosquito vector and human malaria data acquired over 4.5 years (June 1999 - January 2004) in Kong Mong Tha, a remote village in Kanchanaburi Province, western Thailand. Results: Three years of transmissions of vivax and falciparum malaria were simulated for a hypothetical hamlet with approximately 1/7 of the study site population. The model generated results for a number of scenarios, including applications of larvicide and insecticide, asymptomatic cases receiving or not receiving treatment, blocking malaria transmission in mosquito vectors, and increasing the density of farm (host) animals in the hamlet. Transmission characteristics and trends in the simulated results are comparable to actual data collected at the study site.

Validation of prediction models: examining temporal and geographic stability of baseline risk and estimated covariate effects

PubMed Central

Austin, Peter C.; van Klaveren, David; Vergouwe, Yvonne; Nieboer, Daan; Lee, Douglas S.; Steyerberg, Ewout W.

2018-01-01

Background Stability in baseline risk and estimated predictor effects both geographically and temporally is a desirable property of clinical prediction models. However, this issue has received little attention in the methodological literature. Our objective was to examine methods for assessing temporal and geographic heterogeneity in baseline risk and predictor effects in prediction models. Methods We studied 14,857 patients hospitalized with heart failure at 90 hospitals in Ontario, Canada, in two time periods. We focussed on geographic and temporal variation in baseline risk (intercept) and predictor effects (regression coefficients) of the EFFECT-HF mortality model for predicting 1-year mortality in patients hospitalized for heart failure. We used random effects logistic regression models for the 14,857 patients. Results The baseline risk of mortality displayed moderate geographic variation, with the hospital-specific probability of 1-year mortality for a reference patient lying between 0.168 and 0.290 for 95% of hospitals. Furthermore, the odds of death were 11% lower in the second period than in the first period. However, we found minimal geographic or temporal variation in predictor effects. Among 11 tests of differences in time for predictor variables, only one had a modestly significant P value (0.03). Conclusions This study illustrates how temporal and geographic heterogeneity of prediction models can be assessed in settings with a large sample of patients from a large number of centers at different time periods. PMID:29350215

Geographic Video 3d Data Model And Retrieval

NASA Astrophysics Data System (ADS)

Han, Z.; Cui, C.; Kong, Y.; Wu, H.

2014-04-01

Geographic video includes both spatial and temporal geographic features acquired through ground-based or non-ground-based cameras. With the popularity of video capture devices such as smartphones, the volume of user-generated geographic video clips has grown significantly and the trend of this growth is quickly accelerating. Such a massive and increasing volume poses a major challenge to efficient video management and query. Most of the today's video management and query techniques are based on signal level content extraction. They are not able to fully utilize the geographic information of the videos. This paper aimed to introduce a geographic video 3D data model based on spatial information. The main idea of the model is to utilize the location, trajectory and azimuth information acquired by sensors such as GPS receivers and 3D electronic compasses in conjunction with video contents. The raw spatial information is synthesized to point, line, polygon and solid according to the camcorder parameters such as focal length and angle of view. With the video segment and video frame, we defined the three categories geometry object using the geometry model of OGC Simple Features Specification for SQL. We can query video through computing the spatial relation between query objects and three categories geometry object such as VFLocation, VSTrajectory, VSFOView and VFFovCone etc. We designed the query methods using the structured query language (SQL) in detail. The experiment indicate that the model is a multiple objective, integration, loosely coupled, flexible and extensible data model for the management of geographic stereo video.

Innovations in individual feature history management - The significance of feature-based temporal model

USGS Publications Warehouse

Choi, J.; Seong, J.C.; Kim, B.; Usery, E.L.

2008-01-01

A feature relies on three dimensions (space, theme, and time) for its representation. Even though spatiotemporal models have been proposed, they have principally focused on the spatial changes of a feature. In this paper, a feature-based temporal model is proposed to represent the changes of both space and theme independently. The proposed model modifies the ISO's temporal schema and adds new explicit temporal relationship structure that stores temporal topological relationship with the ISO's temporal primitives of a feature in order to keep track feature history. The explicit temporal relationship can enhance query performance on feature history by removing topological comparison during query process. Further, a prototype system has been developed to test a proposed feature-based temporal model by querying land parcel history in Athens, Georgia. The result of temporal query on individual feature history shows the efficiency of the explicit temporal relationship structure. ?? Springer Science+Business Media, LLC 2007.

Tiled vector data model for the geographical features of symbolized maps.

PubMed

Li, Lin; Hu, Wei; Zhu, Haihong; Li, You; Zhang, Hang

2017-01-01

Electronic maps (E-maps) provide people with convenience in real-world space. Although web map services can display maps on screens, a more important function is their ability to access geographical features. An E-map that is based on raster tiles is inferior to vector tiles in terms of interactive ability because vector maps provide a convenient and effective method to access and manipulate web map features. However, the critical issue regarding rendering tiled vector maps is that geographical features that are rendered in the form of map symbols via vector tiles may cause visual discontinuities, such as graphic conflicts and losses of data around the borders of tiles, which likely represent the main obstacles to exploring vector map tiles on the web. This paper proposes a tiled vector data model for geographical features in symbolized maps that considers the relationships among geographical features, symbol representations and map renderings. This model presents a method to tailor geographical features in terms of map symbols and 'addition' (join) operations on the following two levels: geographical features and map features. Thus, these maps can resolve the visual discontinuity problem based on the proposed model without weakening the interactivity of vector maps. The proposed model is validated by two map data sets, and the results demonstrate that the rendered (symbolized) web maps present smooth visual continuity.

Evaluating the Significance of Paleophylogeographic Species Distribution Models in Reconstructing Quaternary Range-Shifts of Nearctic Chelonians

PubMed Central

Flecks, Morris; Ahmadzadeh, Faraham; Dambach, Johannes; Engler, Jan O.; Habel, Jan Christian; Hartmann, Timo; Hörnes, David; Ihlow, Flora; Schidelko, Kathrin; Stiels, Darius; Polly, P. David

2013-01-01

The climatic cycles of the Quaternary, during which global mean annual temperatures have regularly changed by 5–10°C, provide a special opportunity for studying the rate, magnitude, and effects of geographic responses to changing climates. During the Quaternary, high- and mid-latitude species were extirpated from regions that were covered by ice or otherwise became unsuitable, persisting in refugial retreats where the environment was compatible with their tolerances. In this study we combine modern geographic range data, phylogeny, Pleistocene paleoclimatic models, and isotopic records of changes in global mean annual temperature, to produce a temporally continuous model of geographic changes in potential habitat for 59 species of North American turtles over the past 320 Ka (three full glacial-interglacial cycles). These paleophylogeographic models indicate the areas where past climates were compatible with the modern ranges of the species and serve as hypotheses for how their geographic ranges would have changed in response to Quaternary climate cycles. We test these hypotheses against physiological, genetic, taxonomic and fossil evidence, and we then use them to measure the effects of Quaternary climate cycles on species distributions. Patterns of range expansion, contraction, and fragmentation in the models are strongly congruent with (i) phylogeographic differentiation; (ii) morphological variation; (iii) physiological tolerances; and (iv) intraspecific genetic variability. Modern species with significant interspecific differentiation have geographic ranges that strongly fluctuated and repeatedly fragmented throughout the Quaternary. Modern species with low genetic diversity have geographic distributions that were highly variable and at times exceedingly small in the past. Our results reveal the potential for paleophylogeographic models to (i) reconstruct past geographic range modifications, (ii) identify geographic processes that result in genetic bottlenecks; and (iii) predict threats due to anthropogenic climate change in the future. PMID:24130664

Geographic information system/watershed model interface

USGS Publications Warehouse

Fisher, Gary T.

1989-01-01

Geographic information systems allow for the interactive analysis of spatial data related to water-resources investigations. A conceptual design for an interface between a geographic information system and a watershed model includes functions for the estimation of model parameter values. Design criteria include ease of use, minimal equipment requirements, a generic data-base management system, and use of a macro language. An application is demonstrated for a 90.1-square-kilometer subbasin of the Patuxent River near Unity, Maryland, that performs automated derivation of watershed parameters for hydrologic modeling.

Labeling and Knowing: A Reconciliation of Implicit Theory and Explicit Theory among Students with Exceptionalities

ERIC Educational Resources Information Center

lo, C. Owen

2014-01-01

Using a realist grounded theory method, this study resulted in a theoretical model and 4 propositions. As displayed in the LINK model, the labeling practice is situated in and endorsed by a social context that carries explicit theory about and educational policies regarding the labels. Taking a developmental perspective, the labeling practice…

Spatial variation of natural radiation and childhood leukaemia incidence in Great Britain.

PubMed

Richardson, S; Monfort, C; Green, M; Draper, G; Muirhead, C

This paper describes an analysis of the geographical variation of childhood leukaemia incidence in Great Britain over a 15 year period in relation to natural radiation (gamma and radon). Data at the level of the 459 district level local authorities in England, Wales and regional districts in Scotland are analysed in two complementary ways: first, by Poisson regressions with the inclusion of environmental covariates and a smooth spatial structure; secondly, by a hierarchical Bayesian model in which extra-Poisson variability is modelled explicitly in terms of spatial and non-spatial components. From this analysis, we deduce a strong indication that a main part of the variability is accounted for by a local neighbourhood 'clustering' structure. This structure is furthermore relatively stable over the 15 year period for the lymphocytic leukaemias which make up the majority of observed cases. We found no evidence of a positive association of childhood leukaemia incidence with outdoor or indoor gamma radiation levels. There is no consistent evidence of any association with radon levels. Indeed, in the Poisson regressions, a significant positive association was only observed for one 5-year period, a result which is not compatible with a stable environmental effect. Moreover, this positive association became clearly non-significant when over-dispersion relative to the Poisson distribution was taken into account.

Healthcare quality improvement -- policy implications and practicalities.

PubMed

Esain, Ann Elizabeth; Williams, Sharon J; Gakhal, Sandeep; Caley, Lynne; Cooke, Matthew W

2012-01-01

This article aims to explore quality improvement (QI) at individual, group and organisational level. It also aims to identify restraining forces using formative evaluation and discuss implications for current UK policy, particularly quality, innovation, productivity and prevention. Learning events combined with work-based projects, focusing on individual and group responses are evaluated. A total of 11 multi-disciplinary groups drawn from NHS England healthcare Trusts (self-governing operational groups) were sampled. These Trusts have different geographic locations and participants were drawn from primary, secondary and commissioning arms. Mixed methods: questionnaires, observations and reflective accounts were used. The paper finds that solution versus problem identification causes confusion and influences success. Time for problem solving to achieve QI was absent. Feedback and learning structures are often not in place or inflexible. Limited focus on patient-centred services may be related to past assumptions regarding organisational design, hence assumptions and models need to be understood and challenged. The authors revise the Plan, Do, Study; Act (PDSA) model by adding an explicit problem identification step and hence avoiding solution-focused habits; demonstrating the need for more formative evaluations to inform managers and policy makers about healthcare QI processes. - Although UK-centric, the quality agenda is a USA and European theme, findings may help those embarking on this journey or those struggling with QI.

Assessing Contamination Potential of Nitrate-N in Groundwater of Lanyang Plain

NASA Astrophysics Data System (ADS)

Liang, Ching-Ping; Tu, Yu-Lin; Lin, Chien-Wen; Jang, Cheng-Shin

2013-04-01

Nitrate-N pollution is often relevant to agricultural activities such as the fertilization of crops. Significant increases in the nitrate-N pollution of groundwater are found in natural recharging zones of Taiwan. The increasing nitrate-N contamination seriously threatens public drinking water supply and human health. Constructing a correct map of aquifer contamination potential is an effective and feasible way to protect groundwater for quality assessment and management. Therefore, in this study, we use DRASTIC model with the help of geographic information system (GIS) to assess and predict the contamination potential of nitrate-N in the aquifer of Lanyang Plain, Taiwan. Seven factors of hydrogeology and hydrology, which includes seven parameters - Depth to groundwater, net Recharge, Aquifer media, Soil media, Topography, Impact of vadose zone, and hydraulic Conductivity, are considered to carry out this assessment. The validity of the presented model is established by comparing the results with the measured nitrate concentration in wells within the study area. Adjusting factor weightings via the discriminant analysis is performed to improve the assessment and prediction. The analyzed results can provide residents with suggestive strategies against nitrate-N pollution in agricultural regions and government administrators with explicit information of Nitrate-N pollution extents when plans of water resources are considered.

Time and place in the prehistory of the Aslian languages.

PubMed

Dunn, Michael; Kruspe, Nicole; Burenhult, Niclas

2013-01-01

The Aslian language family, located in the Malay Peninsula and southern Thai Isthmus, consists of four distinct branches comprising some 18 languages. These languages predate the now dominant Malay and Thai. The speakers of Aslian languages exhibit some of the highest degree of phylogenetic and societal diversity present in Mainland Southeast Asia today, among them a foraging tradition particularly associated with locally ancient, Pleistocene genetic lineages. Little advance has been made in our understanding of the linguistic prehistory of this region or how such complexity arose. In this article we present a Bayesian phylogeographic analysis of a large sample of Aslian languages. An explicit geographic model of diffusion is combined with a cognate birth-word death model of lexical evolution to infer the location of the major events of Aslian cladogenesis. The resultant phylogenetic trees are calibrated against dates in the historical and archaeological record to infer a detailed picture of Aslian language history, addressing a number of outstanding questions, including (1) whether the root ancestor of Aslian was spoken in the Malay Peninsula, or whether the family had already divided before entry, and (2) the dynamics of the movement of Aslian languages across the peninsula, with a particular focus on its spread to the indigenous foragers. Copyright © 2013 Wayne State University Press, Detroit, Michigan 48201-1309.

Assessment of the GECKO-A Modeling Tool and Simplified 3D Model Parameterizations for SOA Formation

NASA Astrophysics Data System (ADS)

Aumont, B.; Hodzic, A.; La, S.; Camredon, M.; Lannuque, V.; Lee-Taylor, J. M.; Madronich, S.

2014-12-01

Explicit chemical mechanisms aim to embody the current knowledge of the transformations occurring in the atmosphere during the oxidation of organic matter. These explicit mechanisms are therefore useful tools to explore the fate of organic matter during its tropospheric oxidation and examine how these chemical processes shape the composition and properties of the gaseous and the condensed phases. Furthermore, explicit mechanisms provide powerful benchmarks to design and assess simplified parameterizations to be included 3D model. Nevertheless, the explicit mechanism describing the oxidation of hydrocarbons with backbones larger than few carbon atoms involves millions of secondary organic compounds, far exceeding the size of chemical mechanisms that can be written manually. Data processing tools can however be designed to overcome these difficulties and automatically generate consistent and comprehensive chemical mechanisms on a systematic basis. The Generator for Explicit Chemistry and Kinetics of Organics in the Atmosphere (GECKO-A) has been developed for the automatic writing of explicit chemical schemes of organic species and their partitioning between the gas and condensed phases. GECKO-A can be viewed as an expert system that mimics the steps by which chemists might develop chemical schemes. GECKO-A generates chemical schemes according to a prescribed protocol assigning reaction pathways and kinetics data on the basis of experimental data and structure-activity relationships. In its current version, GECKO-A can generate the full atmospheric oxidation scheme for most linear, branched and cyclic precursors, including alkanes and alkenes up to C25. Assessments of the GECKO-A modeling tool based on chamber SOA observations will be presented. GECKO-A was recently used to design a parameterization for SOA formation based on a Volatility Basis Set (VBS) approach. First results will be presented.

The mixed impact of medical school on medical students' implicit and explicit weight bias.

PubMed

Phelan, Sean M; Puhl, Rebecca M; Burke, Sara E; Hardeman, Rachel; Dovidio, John F; Nelson, David B; Przedworski, Julia; Burgess, Diana J; Perry, Sylvia; Yeazel, Mark W; van Ryn, Michelle

2015-10-01

Health care trainees demonstrate implicit (automatic, unconscious) and explicit (conscious) bias against people from stigmatised and marginalised social groups, which can negatively influence communication and decision making. Medical schools are well positioned to intervene and reduce bias in new physicians. This study was designed to assess medical school factors that influence change in implicit and explicit bias against individuals from one stigmatised group: people with obesity. This was a prospective cohort study of medical students enrolled at 49 US medical schools randomly selected from all US medical schools within the strata of public and private schools and region. Participants were 1795 medical students surveyed at the beginning of their first year and end of their fourth year. Web-based surveys included measures of weight bias, and medical school experiences and climate. Bias change was compared with changes in bias in the general public over the same period. Linear mixed models were used to assess the impact of curriculum, contact with people with obesity, and faculty role modelling on weight bias change. Increased implicit and explicit biases were associated with less positive contact with patients with obesity and more exposure to faculty role modelling of discriminatory behaviour or negative comments about patients with obesity. Increased implicit bias was associated with training in how to deal with difficult patients. On average, implicit weight bias decreased and explicit bias increased during medical school, over a period of time in which implicit weight bias in the general public increased and explicit bias remained stable. Medical schools may reduce students' weight biases by increasing positive contact between students and patients with obesity, eliminating unprofessional role modelling by faculty members and residents, and altering curricula focused on treating difficult patients. © 2015 John Wiley & Sons Ltd.

Explicit and implicit learning: The case of computer programming

NASA Astrophysics Data System (ADS)

Mancy, Rebecca

The central question of this thesis concerns the role of explicit and implicit learning in the acquisition of a complex skill, namely computer programming. This issue is explored with reference to information processing models of memory drawn from cognitive science. These models indicate that conscious information processing occurs in working memory where information is stored and manipulated online, but that this mode of processing shows serious limitations in terms of capacity or resources. Some information processing models also indicate information processing in the absence of conscious awareness through automation and implicit learning. It was hypothesised that students would demonstrate implicit and explicit knowledge and that both would contribute to their performance in programming. This hypothesis was investigated via two empirical studies. The first concentrated on temporary storage and online processing in working memory and the second on implicit and explicit knowledge. Storage and processing were tested using two tools: temporary storage capacity was measured using a digit span test; processing was investigated with a disembedding test. The results were used to calculate correlation coefficients with performance on programming examinations. Individual differences in temporary storage had only a small role in predicting programming performance and this factor was not a major determinant of success. Individual differences in disembedding were more strongly related to programming achievement. The second study used interviews to investigate the use of implicit and explicit knowledge. Data were analysed according to a grounded theory paradigm. The results indicated that students possessed implicit and explicit knowledge, but that the balance between the two varied between students and that the most successful students did not necessarily possess greater explicit knowledge. The ways in which students described their knowledge led to the development of a framework which extends beyond the implicit-explicit dichotomy to four descriptive categories of knowledge along this dimension. Overall, the results demonstrated that explicit and implicit knowledge both contribute to the acquisition ofprogramming skills. Suggestions are made for further research, and the results are discussed in the context of their implications for education.

Explicit tests of palaeodrainage connections of southeastern North America and the historical biogeography of Orangethroat Darters (Percidae: Etheostoma: Ceasia).

PubMed

Bossu, Christen M; Beaulieu, Jeremy M; Ceas, Patrick A; Near, Thomas J

2013-11-01

The alteration in palaeodrainage river connections has shaped patterns of speciation, genetic diversity and the geographical distribution of the species-rich freshwater fauna of North America. The integration of ancestral range reconstruction methods and divergence time estimates provides an opportunity to infer palaeodrainage connectivity and test alternative palaeodrainage hypotheses. Members of the Orangethroat Darter clade, Ceasia, are endemic to southeastern North America and occur north and south of the Pleistocene glacial front, a distributional pattern that makes this clade of closely related species an ideal system to investigate the number and location of glacial refugia and compare alternative hypotheses regarding the proposed evolution of the Teays-Mahomet palaeodrainage. This study utilized time-calibrated mitochondrial and nuclear gene phylogenies and present-day geographical distributions to investigate hypothesized Teays-Mahomet River connections through time using a dispersal-extinction-cladogenesis (DEC) framework. Results of DEC ancestral area reconstructions indicate that the Teays-Mahomet River was a key dispersal route between disjunct highland regions connecting the Mississippi River tributaries to the Old-Ohio Drainage minimally at two separate occasions during the Pleistocene. There was a dynamic interplay between palaeodrainage connections through time and postglacial range expansion from three glacial refugia that shaped the current genetic structure and geographical distributions of the species that comprise Ceasia. © 2013 John Wiley & Sons Ltd.

Geographical genetics of Pseudoplatystoma punctifer (Castelnau, 1855) (Siluriformes, Pimelodidae) in the Amazon Basin.

PubMed

Telles, M P C; Collevatti, R G; Braga, R S; Guedes, L B S; Castro, T G; Costa, M C; Silva-Júnior, N J; Barthem, R B; Diniz-Filho, J A F

2014-05-09

Geographical genetics allows the evaluation of evolutionary processes underlying genetic variation within and among local populations and forms the basis for establishing more effective strategies for biodiversity conservation at the population level. In this study, we used explicit spatial analyses to investigate molecular genetic variation (estimated using 7 microsatellite markers) of Pseudoplatystoma punctifer, by using samples obtained from 15 localities along the Madeira River and Solimões, Amazon Basin. A high genetic diversity was observed associated with a relatively low FST (0.057; P < 0.001), but pairwise FST values ranged from zero up to 0.21 when some pairs of populations were compared. These FST values have a relatively low correlation with geographic distances (r = 0.343; P = 0.074 by Mantel test), but a Mantel correlogram revealed that close populations (up to 80 km) tended to be more similar than expected by chance (r = 0.360; P = 0.015). The correlogram also showed a exponential-like decrease of genetic similarity with distance, with a patch-size of around 200 km, compatible with isolation-by-distance and analogous processes related to local constraints of dispersal and spatially structured levels of gene flow. The pattern revealed herein has important implications for establishing strategies to maintain genetic diversity in the species, especially considering the threats due to human impacts caused by building large dams in this river system.

Cloud Modeling

NASA Technical Reports Server (NTRS)

Tao, Wei-Kuo; Moncrieff, Mitchell; Einaud, Franco (Technical Monitor)

2001-01-01

Numerical cloud models have been developed and applied extensively to study cloud-scale and mesoscale processes during the past four decades. The distinctive aspect of these cloud models is their ability to treat explicitly (or resolve) cloud-scale dynamics. This requires the cloud models to be formulated from the non-hydrostatic equations of motion that explicitly include the vertical acceleration terms since the vertical and horizontal scales of convection are similar. Such models are also necessary in order to allow gravity waves, such as those triggered by clouds, to be resolved explicitly. In contrast, the hydrostatic approximation, usually applied in global or regional models, does allow the presence of gravity waves. In addition, the availability of exponentially increasing computer capabilities has resulted in time integrations increasing from hours to days, domain grids boxes (points) increasing from less than 2000 to more than 2,500,000 grid points with 500 to 1000 m resolution, and 3-D models becoming increasingly prevalent. The cloud resolving model is now at a stage where it can provide reasonably accurate statistical information of the sub-grid, cloud-resolving processes poorly parameterized in climate models and numerical prediction models.

Local Difference Measures between Complex Networks for Dynamical System Model Evaluation

PubMed Central

Lange, Stefan; Donges, Jonathan F.; Volkholz, Jan; Kurths, Jürgen

2015-01-01

A faithful modeling of real-world dynamical systems necessitates model evaluation. A recent promising methodological approach to this problem has been based on complex networks, which in turn have proven useful for the characterization of dynamical systems. In this context, we introduce three local network difference measures and demonstrate their capabilities in the field of climate modeling, where these measures facilitate a spatially explicit model evaluation. Building on a recent study by Feldhoff et al. [1] we comparatively analyze statistical and dynamical regional climate simulations of the South American monsoon system. Three types of climate networks representing different aspects of rainfall dynamics are constructed from the modeled precipitation space-time series. Specifically, we define simple graphs based on positive as well as negative rank correlations between rainfall anomaly time series at different locations, and such based on spatial synchronizations of extreme rain events. An evaluation against respective networks built from daily satellite data provided by the Tropical Rainfall Measuring Mission 3B42 V7 reveals far greater differences in model performance between network types for a fixed but arbitrary climate model than between climate models for a fixed but arbitrary network type. We identify two sources of uncertainty in this respect. Firstly, climate variability limits fidelity, particularly in the case of the extreme event network; and secondly, larger geographical link lengths render link misplacements more likely, most notably in the case of the anticorrelation network; both contributions are quantified using suitable ensembles of surrogate networks. Our model evaluation approach is applicable to any multidimensional dynamical system and especially our simple graph difference measures are highly versatile as the graphs to be compared may be constructed in whatever way required. Generalizations to directed as well as edge- and node-weighted graphs are discussed. PMID:25856374

Local difference measures between complex networks for dynamical system model evaluation.

PubMed

Lange, Stefan; Donges, Jonathan F; Volkholz, Jan; Kurths, Jürgen

2015-01-01

A faithful modeling of real-world dynamical systems necessitates model evaluation. A recent promising methodological approach to this problem has been based on complex networks, which in turn have proven useful for the characterization of dynamical systems. In this context, we introduce three local network difference measures and demonstrate their capabilities in the field of climate modeling, where these measures facilitate a spatially explicit model evaluation.Building on a recent study by Feldhoff et al. [8] we comparatively analyze statistical and dynamical regional climate simulations of the South American monsoon system [corrected]. types of climate networks representing different aspects of rainfall dynamics are constructed from the modeled precipitation space-time series. Specifically, we define simple graphs based on positive as well as negative rank correlations between rainfall anomaly time series at different locations, and such based on spatial synchronizations of extreme rain events. An evaluation against respective networks built from daily satellite data provided by the Tropical Rainfall Measuring Mission 3B42 V7 reveals far greater differences in model performance between network types for a fixed but arbitrary climate model than between climate models for a fixed but arbitrary network type. We identify two sources of uncertainty in this respect. Firstly, climate variability limits fidelity, particularly in the case of the extreme event network; and secondly, larger geographical link lengths render link misplacements more likely, most notably in the case of the anticorrelation network; both contributions are quantified using suitable ensembles of surrogate networks. Our model evaluation approach is applicable to any multidimensional dynamical system and especially our simple graph difference measures are highly versatile as the graphs to be compared may be constructed in whatever way required. Generalizations to directed as well as edge- and node-weighted graphs are discussed.

Testing the cognitive catalyst model of rumination with explicit and implicit cognitive content.

PubMed

Sova, Christopher C; Roberts, John E

2018-06-01

The cognitive catalyst model posits that rumination and negative cognitive content, such as negative schema, interact to predict depressive affect. Past research has found support for this model using explicit measures of negative cognitive content such as self-report measures of trait self-esteem and dysfunctional attitudes. The present study tested whether these findings would extend to implicit measures of negative cognitive content such as implicit self-esteem, and whether effects would depend on initial mood state and history of depression. Sixty-one undergraduate students selected on the basis of depression history (27 previously depressed; 34 never depressed) completed explicit and implicit measures of negative cognitive content prior to random assignment to a rumination induction followed by a distraction induction or vice versa. Dysphoric affect was measured both before and after these inductions. Analyses revealed that explicit measures, but not implicit measures, interacted with rumination to predict change in dysphoric affect, and these interactions were further moderated by baseline levels of dysphoria. Limitations include the small nonclinical sample and use of a self-report measure of depression history. These findings suggest that rumination amplifies the association between explicit negative cognitive content and depressive affect primarily among people who are already experiencing sad mood. Copyright © 2018 Elsevier Ltd. All rights reserved.

Effect of explicit dimension instruction on speech category learning

PubMed Central

Chandrasekaran, Bharath; Yi, Han-Gyol; Smayda, Kirsten E.; Maddox, W. Todd

2015-01-01

Learning non-native speech categories is often considered a challenging task in adulthood. This difficulty is driven by cross-language differences in weighting critical auditory dimensions that differentiate speech categories. For example, previous studies have shown that differentiating Mandarin tonal categories requires attending to dimensions related to pitch height and direction. Relative to native speakers of Mandarin, the pitch direction dimension is under-weighted by native English speakers. In the current study, we examined the effect of explicit instructions (dimension instruction) on native English speakers' Mandarin tone category learning within the framework of a dual-learning systems (DLS) model. This model predicts that successful speech category learning is initially mediated by an explicit, reflective learning system that frequently utilizes unidimensional rules, with an eventual switch to a more implicit, reflexive learning system that utilizes multidimensional rules. Participants were explicitly instructed to focus and/or ignore the pitch height dimension, the pitch direction dimension, or were given no explicit prime. Our results show that instruction instructing participants to focus on pitch direction, and instruction diverting attention away from pitch height resulted in enhanced tone categorization. Computational modeling of participant responses suggested that instruction related to pitch direction led to faster and more frequent use of multidimensional reflexive strategies, and enhanced perceptual selectivity along the previously underweighted pitch direction dimension. PMID:26542400

The explicit and implicit dance in psychoanalytic change.

PubMed

Fosshage, James L

2004-02-01

How the implicit/non-declarative and explicit/declarative cognitive domains interact is centrally important in the consideration of effecting change within the psychoanalytic arena. Stern et al. (1998) declare that long-lasting change occurs in the domain of implicit relational knowledge. In the view of this author, the implicit and explicit domains are intricately intertwined in an interactive dance within a psychoanalytic process. The author views that a spirit of inquiry (Lichtenberg, Lachmann & Fosshage 2002) serves as the foundation of the psychoanalytic process. Analyst and patient strive to explore, understand and communicate and, thereby, create a 'spirit' of interaction that contributes, through gradual incremental learning, to new implicit relational knowledge. This spirit, as part of the implicit relational interaction, is a cornerstone of the analytic relationship. The 'inquiry' more directly brings explicit/declarative processing to the foreground in the joint attempt to explore and understand. The spirit of inquiry in the psychoanalytic arena highlights both the autobiographical scenarios of the explicit memory system and the mental models of the implicit memory system as each contributes to a sense of self, other, and self with other. This process facilitates the extrication and suspension of the old models, so that new models based on current relational experience can be gradually integrated into both memory systems for lasting change.

Integrating remote sensing and spatially explicit epidemiological modeling

NASA Astrophysics Data System (ADS)

Finger, Flavio; Knox, Allyn; Bertuzzo, Enrico; Mari, Lorenzo; Bompangue, Didier; Gatto, Marino; Rinaldo, Andrea

2015-04-01

Spatially explicit epidemiological models are a crucial tool for the prediction of epidemiological patterns in time and space as well as for the allocation of health care resources. In addition they can provide valuable information about epidemiological processes and allow for the identification of environmental drivers of the disease spread. Most epidemiological models rely on environmental data as inputs. They can either be measured in the field by the means of conventional instruments or using remote sensing techniques to measure suitable proxies of the variables of interest. The later benefit from several advantages over conventional methods, including data availability, which can be an issue especially in developing, and spatial as well as temporal resolution of the data, which is particularly crucial for spatially explicit models. Here we present the case study of a spatially explicit, semi-mechanistic model applied to recurring cholera outbreaks in the Lake Kivu area (Democratic Republic of the Congo). The model describes the cholera incidence in eight health zones on the shore of the lake. Remotely sensed datasets of chlorophyll a concentration in the lake, precipitation and indices of global climate anomalies are used as environmental drivers. Human mobility and its effect on the disease spread is also taken into account. Several model configurations are tested on a data set of reported cases. The best models, accounting for different environmental drivers, and selected using the Akaike information criterion, are formally compared via cross validation. The best performing model accounts for seasonality, El Niño Southern Oscillation, precipitation and human mobility.

Modeling the Explicit Chemistry of Anthropogenic and Biogenic Organic Aerosols

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

Madronich, Sasha

2015-12-09

The atmospheric burden of Secondary Organic Aerosols (SOA) remains one of the most important yet uncertain aspects of the radiative forcing of climate. This grant focused on improving our quantitative understanding of SOA formation and evolution, by developing, applying, and improving a highly detailed model of atmospheric organic chemistry, the Generation of Explicit Chemistry and Kinetics of Organics in the Atmosphere (GECKO-A) model. Eleven (11) publications have resulted from this grant.

Anticipating Forest and Range Land Development in Central Oregon (USA) for Landscape Analysis, with an Example Application Involving Mule Deer

NASA Astrophysics Data System (ADS)

Kline, Jeffrey D.; Moses, Alissa; Burcsu, Theresa

2010-05-01

Forest policymakers, public lands managers, and scientists in the Pacific Northwest (USA) seek ways to evaluate the landscape-level effects of policies and management through the multidisciplinary development and application of spatially explicit methods and models. The Interagency Mapping and Analysis Project (IMAP) is an ongoing effort to generate landscape-wide vegetation data and models to evaluate the integrated effects of disturbances and management activities on natural resource conditions in Oregon and Washington (USA). In this initial analysis, we characterized the spatial distribution of forest and range land development in a four-county pilot study region in central Oregon. The empirical model describes the spatial distribution of buildings and new building construction as a function of population growth, existing development, topography, land-use zoning, and other factors. We used the model to create geographic information system maps of likely future development based on human population projections to inform complementary landscape analyses underway involving vegetation, habitat, and wildfire interactions. In an example application, we use the model and resulting maps to show the potential impacts of future forest and range land development on mule deer ( Odocoileus hemionus) winter range. Results indicate significant development encroachment and habitat loss already in 2000 with development located along key migration routes and increasing through the projection period to 2040. The example application illustrates a simple way for policymakers and public lands managers to combine existing data and preliminary model outputs to begin to consider the potential effects of development on future landscape conditions.

GIS Modeling of Air Toxics Releases from TRI-Reporting and Non-TRI-Reporting Facilities: Impacts for Environmental Justice

PubMed Central

Dolinoy, Dana C.; Miranda, Marie Lynn

2004-01-01

The Toxics Release Inventory (TRI) requires facilities with 10 or more full-time employees that process > 25,000 pounds in aggregate or use > 10,000 pounds of any one TRI chemical to report releases annually. However, little is known about releases from non-TRI-reporting facilities, nor has attention been given to the very localized equity impacts associated with air toxics releases. Using geographic information systems and industrial source complex dispersion modeling, we developed methods for characterizing air releases from TRI-reporting as well as non-TRI-reporting facilities at four levels of geographic resolution. We characterized the spatial distribution and concentration of air releases from one representative industry in Durham County, North Carolina (USA). Inclusive modeling of all facilities rather than modeling of TRI sites alone significantly alters the magnitude and spatial distribution of modeled air concentrations. Modeling exposure receptors at more refined levels of geographic resolution reveals localized, neighborhood-level exposure hot spots that are not apparent at coarser geographic scales. Multivariate analysis indicates that inclusive facility modeling at fine levels of geographic resolution reveals exposure disparities by income and race. These new methods significantly enhance the ability to model air toxics, perform equity analysis, and clarify conflicts in the literature regarding environmental justice findings. This work has substantial implications for how to structure TRI reporting requirements, as well as methods and types of analysis that will successfully elucidate the spatial distribution of exposure potentials across geographic, income, and racial lines. PMID:15579419

Bayesian Analysis of Biogeography when the Number of Areas is Large

PubMed Central

Landis, Michael J.; Matzke, Nicholas J.; Moore, Brian R.; Huelsenbeck, John P.

2013-01-01

Historical biogeography is increasingly studied from an explicitly statistical perspective, using stochastic models to describe the evolution of species range as a continuous-time Markov process of dispersal between and extinction within a set of discrete geographic areas. The main constraint of these methods is the computational limit on the number of areas that can be specified. We propose a Bayesian approach for inferring biogeographic history that extends the application of biogeographic models to the analysis of more realistic problems that involve a large number of areas. Our solution is based on a “data-augmentation” approach, in which we first populate the tree with a history of biogeographic events that is consistent with the observed species ranges at the tips of the tree. We then calculate the likelihood of a given history by adopting a mechanistic interpretation of the instantaneous-rate matrix, which specifies both the exponential waiting times between biogeographic events and the relative probabilities of each biogeographic change. We develop this approach in a Bayesian framework, marginalizing over all possible biogeographic histories using Markov chain Monte Carlo (MCMC). Besides dramatically increasing the number of areas that can be accommodated in a biogeographic analysis, our method allows the parameters of a given biogeographic model to be estimated and different biogeographic models to be objectively compared. Our approach is implemented in the program, BayArea. [ancestral area analysis; Bayesian biogeographic inference; data augmentation; historical biogeography; Markov chain Monte Carlo.] PMID:23736102

Classification and prediction of river network ephemerality and its relevance for waterborne disease epidemiology

NASA Astrophysics Data System (ADS)

Perez-Saez, Javier; Mande, Theophile; Larsen, Joshua; Ceperley, Natalie; Rinaldo, Andrea

2017-12-01

The transmission of waterborne diseases hinges on the interactions between hydrology and ecology of hosts, vectors and parasites, with the long-term absence of water constituting a strict lower bound. However, the link between spatio-temporal patterns of hydrological ephemerality and waterborne disease transmission is poorly understood and difficult to account for. The use of limited biophysical and hydroclimate information from otherwise data scarce regions is therefore needed to characterize, classify, and predict river network ephemerality in a spatially explicit framework. Here, we develop a novel large-scale ephemerality classification and prediction methodology based on monthly discharge data, water and energy availability, and remote-sensing measures of vegetation, that is relevant to epidemiology, and maintains a mechanistic link to catchment hydrologic processes. Specifically, with reference to the context of Burkina Faso in sub-Saharan Africa, we extract a relevant set of catchment covariates that include the aridity index, annual runoff estimation using the Budyko framework, and hysteretical relations between precipitation and vegetation. Five ephemerality classes, from permanent to strongly ephemeral, are defined from the duration of 0-flow periods that also accounts for the sensitivity of river discharge to the long-lasting drought of the 70's-80's in West Africa. Using such classes, a gradient-boosted tree-based prediction yielded three distinct geographic regions of ephemerality. Importantly, we observe a strong epidemiological association between our predictions of hydrologic ephemerality and the known spatial patterns of schistosomiasis, an endemic parasitic waterborne disease in which infection occurs with human-water contact, and requires aquatic snails as an intermediate host. The general nature of our approach and its relevance for predicting the hydrologic controls on schistosomiasis occurrence provides a pathway for the explicit inclusion of hydrologic drivers within epidemiological models of waterborne disease transmission.

Remote Sensing in Geography in the New Millennium: Prospects, Challenges and Opportunities

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Walsh, Stephen J.; Jensen, John R.; Ridd, Merrill K.; Arnold, James E. (Technical Monitor)

2002-01-01

As noted in the first edition of Geography in America, the term remote sensing was coined in the early 1960's by geographers to describe the process of obtaining data by use of both photographic and nonphotographic instruments. Although this is still a working definition today, a more explicit and updated definition as it relates to geography can be phrased as: "remote sensing is the science, art, and technology of identifying, characterizing, measuring, and mapping of Earth surface, and near earth surface, phenomena from some position above using photographic or nonphotographic instruments." Both patterns and processes may be the object of investigation using remote sensing data. The science dimension of geographic remote sensing is rooted in the fact that: a) it is dealing with primary data, wherein the investigator must have an understanding of the environmental phenomena under scrutiny, and b) the investigator must understand something of the physics of the energy involved in the sensing instrument and the atmospheric pathway through which the energy passes from the energy source, to the Earth object to the sensor.

Including resonances in the multiperipheral model

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

Pinsky, S.S.; Snider, D.R.; Thomas, G.H.

1973-10-01

A simple generalization of the multiperipheral model (MPM) and the Mueller--Regge Model (MRM) is given which has improved phenomenological capabilities by explicitly incorporating resonance phenomena, and still is simple enough to be an important theoretical laboratory. The model is discussed both with and without charge. In addition, the one channel, two channel, three channel and N channel cases are explicitly treated. Particular attention is paid to the constraints of charge conservation and positivity in the MRM. The recently proven equivalence between the MRM and MPM is extended to this model, and is used extensively. (auth)

Explicit Pore Pressure Material Model in Carbon-Cloth Phenolic

NASA Technical Reports Server (NTRS)

Gutierrez-Lemini, Danton; Ehle, Curt

2003-01-01

An explicit material model that uses predicted pressure in the pores of a carbon-cloth phenolic (CCP) composite has been developed. This model is intended to be used within a finite-element model to predict phenomena specific to CCP components of solid-fuel-rocket nozzles subjected to high operating temperatures and to mechanical stresses that can be great enough to cause structural failures. Phenomena that can be predicted with the help of this model include failures of specimens in restrained-thermal-growth (RTG) tests, pocketing erosion, and ply lifting

Assessing the Application of a Geographic Presence-Only Model for Land Suitability Mapping

PubMed Central

Heumann, Benjamin W.; Walsh, Stephen J.; McDaniel, Phillip M.

2011-01-01

Recent advances in ecological modeling have focused on novel methods for characterizing the environment that use presence-only data and machine-learning algorithms to predict the likelihood of species occurrence. These novel methods may have great potential for land suitability applications in the developing world where detailed land cover information is often unavailable or incomplete. This paper assesses the adaptation and application of the presence-only geographic species distribution model, MaxEnt, for agricultural crop suitability mapping in a rural Thailand where lowland paddy rice and upland field crops predominant. To assess this modeling approach, three independent crop presence datasets were used including a social-demographic survey of farm households, a remote sensing classification of land use/land cover, and ground control points, used for geodetic and thematic reference that vary in their geographic distribution and sample size. Disparate environmental data were integrated to characterize environmental settings across Nang Rong District, a region of approximately 1,300 sq. km in size. Results indicate that the MaxEnt model is capable of modeling crop suitability for upland and lowland crops, including rice varieties, although model results varied between datasets due to the high sensitivity of the model to the distribution of observed crop locations in geographic and environmental space. Accuracy assessments indicate that model outcomes were influenced by the sample size and the distribution of sample points in geographic and environmental space. The need for further research into accuracy assessments of presence-only models lacking true absence data is discussed. We conclude that the Maxent model can provide good estimates of crop suitability, but many areas need to be carefully scrutinized including geographic distribution of input data and assessment methods to ensure realistic modeling results. PMID:21860606

Effects of prompting and reinforcement of one response pattern upon imitation of a different modeled pattern

PubMed Central

Bondy, Andrew S.

1982-01-01

Twelve preschool children participated in a study of the effects of explicit training on the imitation of modeled behavior. The responses trained involved a marble-dropping pattern that differed from the modeled pattern. Training consisted of physical prompts and verbal praise during a single session. No prompts or praise were used during test periods. After operant levels of the experimental responses were measured, training either preceded or was interposed within a series of exposures to modeled behavior that differed from the trained behavior. Children who were initially exposed to a modeling session immediately imitated, whereas those children who were initially trained immediately performed the appropriate response. Children initially trained on one pattern generally continued to exhibit that pattern even after many modeling sessions. Children who first viewed the modeled response and then were exposed to explicit training of a different response reversed their response pattern from the trained response to the modeled response within a few sessions. The results suggest that under certain conditions explicit training will exert greater control over responding than immediate modeling stimuli. PMID:16812260

Transient modeling/analysis of hyperbolic heat conduction problems employing mixed implicit-explicit alpha method

NASA Technical Reports Server (NTRS)

Tamma, Kumar K.; D'Costa, Joseph F.

1991-01-01

This paper describes the evaluation of mixed implicit-explicit finite element formulations for hyperbolic heat conduction problems involving non-Fourier effects. In particular, mixed implicit-explicit formulations employing the alpha method proposed by Hughes et al. (1987, 1990) are described for the numerical simulation of hyperbolic heat conduction models, which involves time-dependent relaxation effects. Existing analytical approaches for modeling/analysis of such models involve complex mathematical formulations for obtaining closed-form solutions, while in certain numerical formulations the difficulties include severe oscillatory solution behavior (which often disguises the true response) in the vicinity of the thermal disturbances, which propagate with finite velocities. In view of these factors, the alpha method is evaluated to assess the control of the amount of numerical dissipation for predicting the transient propagating thermal disturbances. Numerical test models are presented, and pertinent conclusions are drawn for the mixed-time integration simulation of hyperbolic heat conduction models involving non-Fourier effects.

Uncertainties in SOA Formation from the Photooxidation of α-pinene

NASA Astrophysics Data System (ADS)

McVay, R.; Zhang, X.; Aumont, B.; Valorso, R.; Camredon, M.; La, S.; Seinfeld, J.

2015-12-01

Explicit chemical models such as GECKO-A (the Generator for Explicit Chemistry and Kinetics of Organics in the Atmosphere) enable detailed modeling of gas-phase photooxidation and secondary organic aerosol (SOA) formation. Comparison between these explicit models and chamber experiments can provide insight into processes that are missing or unknown in these models. GECKO-A is used to model seven SOA formation experiments from α-pinene photooxidation conducted at varying seed particle concentrations with varying oxidation rates. We investigate various physical and chemical processes to evaluate the extent of agreement between the experiments and the model predictions. We examine the effect of vapor wall loss on SOA formation and how the importance of this effect changes at different oxidation rates. Proposed gas-phase autoxidation mechanisms are shown to significantly affect SOA predictions. The potential effects of particle-phase dimerization and condensed-phase photolysis are investigated. We demonstrate the extent to which SOA predictions in the α-pinene photooxidation system depend on uncertainties in the chemical mechanism.

Testing the Use of Implicit Solvent in the Molecular Dynamics Modelling of DNA Flexibility

NASA Astrophysics Data System (ADS)

Mitchell, J.; Harris, S.

DNA flexibility controls packaging, looping and in some cases sequence specific protein binding. Molecular dynamics simulations carried out with a computationally efficient implicit solvent model are potentially a powerful tool for studying larger DNA molecules than can be currently simulated when water and counterions are represented explicitly. In this work we compare DNA flexibility at the base pair step level modelled using an implicit solvent model to that previously determined from explicit solvent simulations and database analysis. Although much of the sequence dependent behaviour is preserved in implicit solvent, the DNA is considerably more flexible when the approximate model is used. In addition we test the ability of the implicit solvent to model stress induced DNA disruptions by simulating a series of DNA minicircle topoisomers which vary in size and superhelical density. When compared with previously run explicit solvent simulations, we find that while the levels of DNA denaturation are similar using both computational methodologies, the specific structural form of the disruptions is different.

Spatially explicit modelling of cholera epidemics

NASA Astrophysics Data System (ADS)

Finger, F.; Bertuzzo, E.; Mari, L.; Knox, A. C.; Gatto, M.; Rinaldo, A.

2013-12-01

Epidemiological models can provide crucial understanding about the dynamics of infectious diseases. Possible applications range from real-time forecasting and allocation of health care resources to testing alternative intervention mechanisms such as vaccines, antibiotics or the improvement of sanitary conditions. We apply a spatially explicit model to the cholera epidemic that struck Haiti in October 2010 and is still ongoing. The dynamics of susceptibles as well as symptomatic and asymptomatic infectives are modelled at the scale of local human communities. Dissemination of Vibrio cholerae through hydrological transport and human mobility along the road network is explicitly taken into account, as well as the effect of rainfall as a driver of increasing disease incidence. The model is calibrated using a dataset of reported cholera cases. We further model the long term impact of several types of interventions on the disease dynamics by varying parameters appropriately. Key epidemiological mechanisms and parameters which affect the efficiency of treatments such as antibiotics are identified. Our results lead to conclusions about the influence of different intervention strategies on the overall epidemiological dynamics.

Assessing implicit models for nonpolar mean solvation forces: The importance of dispersion and volume terms

PubMed Central

Wagoner, Jason A.; Baker, Nathan A.

2006-01-01

Continuum solvation models provide appealing alternatives to explicit solvent methods because of their ability to reproduce solvation effects while alleviating the need for expensive sampling. Our previous work has demonstrated that Poisson-Boltzmann methods are capable of faithfully reproducing polar explicit solvent forces for dilute protein systems; however, the popular solvent-accessible surface area model was shown to be incapable of accurately describing nonpolar solvation forces at atomic-length scales. Therefore, alternate continuum methods are needed to reproduce nonpolar interactions at the atomic scale. In the present work, we address this issue by supplementing the solvent-accessible surface area model with additional volume and dispersion integral terms suggested by scaled particle models and Weeks–Chandler–Andersen theory, respectively. This more complete nonpolar implicit solvent model shows very good agreement with explicit solvent results and suggests that, although often overlooked, the inclusion of appropriate dispersion and volume terms are essential for an accurate implicit solvent description of atomic-scale nonpolar forces. PMID:16709675

Development and assessment of 30-meter pine density maps for landscape-level modeling of mountain pine beetle dynamics

Treesearch

Benjamin A. Crabb; James A. Powell; Barbara J. Bentz

2012-01-01

Forecasting spatial patterns of mountain pine beetle (MPB) population success requires spatially explicit information on host pine distribution. We developed a means of producing spatially explicit datasets of pine density at 30-m resolution using existing geospatial datasets of vegetation composition and structure. Because our ultimate goal is to model MPB population...

Emergence of a coherent and cohesive swarm based on mutual anticipation

PubMed Central

Murakami, Hisashi; Niizato, Takayuki; Gunji, Yukio-Pegio

2017-01-01

Collective behavior emerging out of self-organization is one of the most striking properties of an animal group. Typically, it is hypothesized that each individual in an animal group tends to align its direction of motion with those of its neighbors. Most previous models for collective behavior assume an explicit alignment rule, by which an agent matches its velocity with that of neighbors in a certain neighborhood, to reproduce a collective order pattern by simple interactions. Recent empirical studies, however, suggest that there is no evidence for explicit matching of velocity, and that collective polarization arises from interactions other than those that follow the explicit alignment rule. We here propose a new lattice-based computational model that does not incorporate the explicit alignment rule but is based instead on mutual anticipation and asynchronous updating. Moreover, we show that this model can realize densely collective motion with high polarity. Furthermore, we focus on the behavior of a pair of individuals, and find that the turning response is drastically changed depending on the distance between two individuals rather than the relative heading, and is consistent with the empirical observations. Therefore, the present results suggest that our approach provides an alternative model for collective behavior. PMID:28406173

Flory-type theories of polymer chains under different external stimuli

NASA Astrophysics Data System (ADS)

Budkov, Yu A.; Kiselev, M. G.

2018-01-01

In this Review, we present a critical analysis of various applications of the Flory-type theories to a theoretical description of the conformational behavior of single polymer chains in dilute polymer solutions under a few external stimuli. Different theoretical models of flexible polymer chains in the supercritical fluid are discussed and analysed. Different points of view on the conformational behavior of the polymer chain near the liquid-gas transition critical point of the solvent are presented. A theoretical description of the co-solvent-induced coil-globule transitions within the implicit-solvent-explicit-co-solvent models is discussed. Several explicit-solvent-explicit-co-solvent theoretical models of the coil-to-globule-to-coil transition of the polymer chain in a mixture of good solvents (co-nonsolvency) are analysed and compared with each other. Finally, a new theoretical model of the conformational behavior of the dielectric polymer chain under the external constant electric field in the dilute polymer solution with an explicit account for the many-body dipole correlations is discussed. The polymer chain collapse induced by many-body dipole correlations of monomers in the context of statistical thermodynamics of dielectric polymers is analysed.

Implicit-Explicit Time Integration Methods for Non-hydrostatic Atmospheric Models

NASA Astrophysics Data System (ADS)

Gardner, D. J.; Guerra, J. E.; Hamon, F. P.; Reynolds, D. R.; Ullrich, P. A.; Woodward, C. S.

2016-12-01

The Accelerated Climate Modeling for Energy (ACME) project is developing a non-hydrostatic atmospheric dynamical core for high-resolution coupled climate simulations on Department of Energy leadership class supercomputers. An important factor in computational efficiency is avoiding the overly restrictive time step size limitations of fully explicit time integration methods due to the stiffest modes present in the model (acoustic waves). In this work we compare the accuracy and performance of different Implicit-Explicit (IMEX) splittings of the non-hydrostatic equations and various Additive Runge-Kutta (ARK) time integration methods. Results utilizing the Tempest non-hydrostatic atmospheric model and the ARKode package show that the choice of IMEX splitting and ARK scheme has a significant impact on the maximum stable time step size as well as solution quality. Horizontally Explicit Vertically Implicit (HEVI) approaches paired with certain ARK methods lead to greatly improved runtimes. With effective preconditioning IMEX splittings that incorporate some implicit horizontal dynamics can be competitive with HEVI results. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-ABS-699187

Spatial modeling of agricultural land use change at global scale

NASA Astrophysics Data System (ADS)

Meiyappan, P.; Dalton, M.; O'Neill, B. C.; Jain, A. K.

2014-11-01

Long-term modeling of agricultural land use is central in global scale assessments of climate change, food security, biodiversity, and climate adaptation and mitigation policies. We present a global-scale dynamic land use allocation model and show that it can reproduce the broad spatial features of the past 100 years of evolution of cropland and pastureland patterns. The modeling approach integrates economic theory, observed land use history, and data on both socioeconomic and biophysical determinants of land use change, and estimates relationships using long-term historical data, thereby making it suitable for long-term projections. The underlying economic motivation is maximization of expected profits by hypothesized landowners within each grid cell. The model predicts fractional land use for cropland and pastureland within each grid cell based on socioeconomic and biophysical driving factors that change with time. The model explicitly incorporates the following key features: (1) land use competition, (2) spatial heterogeneity in the nature of driving factors across geographic regions, (3) spatial heterogeneity in the relative importance of driving factors and previous land use patterns in determining land use allocation, and (4) spatial and temporal autocorrelation in land use patterns. We show that land use allocation approaches based solely on previous land use history (but disregarding the impact of driving factors), or those accounting for both land use history and driving factors by mechanistically fitting models for the spatial processes of land use change do not reproduce well long-term historical land use patterns. With an example application to the terrestrial carbon cycle, we show that such inaccuracies in land use allocation can translate into significant implications for global environmental assessments. The modeling approach and its evaluation provide an example that can be useful to the land use, Integrated Assessment, and the Earth system modeling communities.

The Construction of Visual-spatial Situation Models in Children's Reading and Their Relation to Reading Comprehension

PubMed Central

Barnes, Marcia A.; Raghubar, Kimberly P.; Faulkner, Heather; Denton, Carolyn A.

2014-01-01

Readers construct mental models of situations described by text to comprehend what they read, updating these situation models based on explicitly described and inferred information about causal, temporal, and spatial relations. Fluent adult readers update their situation models while reading narrative text based in part on spatial location information that is consistent with the perspective of the protagonist. The current study investigates whether children update spatial situation models in a similar way, whether there are age-related changes in children's formation of spatial situation models during reading, and whether measures of the ability to construct and update spatial situation models are predictive of reading comprehension. Typically-developing children from ages 9 through 16 years (n=81) were familiarized with a physical model of a marketplace. Then the model was covered, and children read stories that described the movement of a protagonist through the marketplace and were administered items requiring memory for both explicitly stated and inferred information about the character's movements. Accuracy of responses and response times were evaluated. Results indicated that: (a) location and object information during reading appeared to be activated and updated not simply from explicit text-based information but from a mental model of the real world situation described by the text; (b) this pattern showed no age-related differences; and (c) the ability to update the situation model of the text based on inferred information, but not explicitly stated information, was uniquely predictive of reading comprehension after accounting for word decoding. PMID:24315376

Extreme deconstruction supports niche conservatism driving New World bird diversity

NASA Astrophysics Data System (ADS)

Diniz-Filho, José Alexandre Felizola; Rangel, Thiago Fernando; dos Santos, Mariana Rocha

2012-08-01

It is expected that if environment fully establishes the borders of species geographic distribution, then richness patterns will arise simple by changing parameters on how environment affect each of the species. However, if other mechanisms (i.e., non-equilibrium of species' distributions with climate and historical contingency, shifts in adaptive peaks or biotic interactions) are driving species geographic distribution, models for species distribution and richness will not entirely match. Here we used the extreme deconstruction principle to test how niche conservatism keeping species geographic distributions in certain parts of environmental space drives richness patterns in New World birds, under tropical niche conservatism. Eight environmental variables were used to model the geographic distribution of 2790 species within 28 bird families using a GLM. Spatial patterns in richness for each of these families were also modeled as a function of these same variables using a standard OLS regression. Fit of these two types of models (mean MacFadden's ρ2 for GLM and R2 of OLS) across families and the match between GLM and OLS standardized slopes within and among bird families were then compared. We found a positive and significant correlation between GLM and OLS model fit (r = 0.601; P < 0.01), indicating that when environment strongly determine richness of a family, it also explains its species geographic distributions. The match between GLM and OLS slopes is significantly correlated with families' phylogenetic root distance (r = -0.467; P = 0.012), so that more basal families tend to have a better match between environmental drivers of richness and geographic distribution models. This is expected under tropical niche conservatism model and provides an integrated explanation on how processes at a lower hierarchical level (species' geographic distribution) drive diversity patterns.

Rapid Response Tools and Datasets for Post-fire Erosion Modeling: Lessons Learned from the Rock House and High Park Fires

NASA Astrophysics Data System (ADS)

Miller, Mary Ellen; Elliot, William E.; MacDonald, Lee H.

2013-04-01

Once the danger posed by an active wildfire has passed, land managers must rapidly assess the threat from post-fire runoff and erosion due to the loss of surface cover and fire-induced changes in soil properties. Increased runoff and sediment delivery are of great concern to both the pubic and resource managers. Post-fire assessments and proposals to mitigate these threats are typically undertaken by interdisciplinary Burned Area Emergency Response (BAER) teams. These teams are under very tight deadlines, so they often begin their analysis while the fire is still burning and typically must complete their plans within a couple of weeks. Many modeling tools and datasets have been developed over the years to assist BAER teams, but process-based, spatially explicit models are currently under-utilized relative to simpler, lumped models because they are more difficult to set up and require the preparation of spatially-explicit data layers such as digital elevation models, soils, and land cover. The difficulty of acquiring and utilizing these data layers in spatially-explicit models increases with increasing fire size. Spatially-explicit post-fire erosion modeling was attempted for a small watershed in the 1270 km2 Rock House fire in Texas, but the erosion modeling work could not be completed in time. The biggest limitation was the time required to extract the spatially explicit soils data needed to run the preferred post-fire erosion model (GeoWEPP with Disturbed WEPP parameters). The solution is to have the spatial soil, land cover, and DEM data layers prepared ahead of time, and to have a clear methodology for the BAER teams to incorporate these layers in spatially-explicit modeling interfaces like GeoWEPP. After a fire occurs the data layers can quickly be clipped to the fire perimeter. The soil and land cover parameters can then be adjusted according to the burn severity map, which is one of the first products generated for the BAER teams. Under a previous project for the U.S. Environmental Protection Agency this preparatory work was done for much of Colorado, and in June 2012 the High Park wildfire in north central Colorado burned over 340 km2. The data layers for the entire burn area were quickly assembled and the spatially explicit runoff and erosion modeling was completed in less than three days. The resulting predictions were then used by the BAER team to quantify downstream risks and delineate priority areas for different post-fire treatments. These two contrasting case studies demonstrate the feasibility and the value of preparing datasets and modeling tools ahead of time. In recognition of this, the U.S. National Aeronautic and Space Administration has agreed to fund a pilot project to demonstrate the utility of acquiring and preparing the necessary data layers for fire-prone wildlands across the western U.S. A similar modeling and data acquisition approach could be followed

Explicit and implicit cognition: a preliminary test of a dual-process theory of cognitive vulnerability to depression.

PubMed

Haeffel, Gerald J; Abramson, Lyn Y; Brazy, Paige C; Shah, James Y; Teachman, Bethany A; Nosek, Brian A

2007-06-01

Two studies were conducted to test a dual-process theory of cognitive vulnerability to depression. According to this theory, implicit and explicit cognitive processes have differential effects on depressive reactions to stressful life events. Implicit processes are hypothesized to be critical in determining an individual's immediate affective reaction to stress whereas explicit cognitions are thought to be more involved in long-term depressive reactions. Consistent with hypotheses, the results of study 1 (cross-sectional; N=237) showed that implicit, but not explicit, cognitions predicted immediate affective reactions to a lab stressor. Study 2 (longitudinal; N=251) also supported the dual-process model of cognitive vulnerability to depression. Results showed that both the implicit and explicit measures interacted with life stress to predict prospective changes in depressive symptoms, respectively. However, when both implicit and explicit predictors were entered into a regression equation simultaneously, only the explicit measure interacted with stress to remain a unique predictor of depressive symptoms over the five-week prospective interval.

Comparison of Damage Path Predictions for Composite Laminates by Explicit and Standard Finite Element Analysis Tools

NASA Technical Reports Server (NTRS)

Bogert, Philip B.; Satyanarayana, Arunkumar; Chunchu, Prasad B.

2006-01-01

Splitting, ultimate failure load and the damage path in center notched composite specimens subjected to in-plane tension loading are predicted using progressive failure analysis methodology. A 2-D Hashin-Rotem failure criterion is used in determining intra-laminar fiber and matrix failures. This progressive failure methodology has been implemented in the Abaqus/Explicit and Abaqus/Standard finite element codes through user written subroutines "VUMAT" and "USDFLD" respectively. A 2-D finite element model is used for predicting the intra-laminar damages. Analysis results obtained from the Abaqus/Explicit and Abaqus/Standard code show good agreement with experimental results. The importance of modeling delamination in progressive failure analysis methodology is recognized for future studies. The use of an explicit integration dynamics code for simple specimen geometry and static loading establishes a foundation for future analyses where complex loading and nonlinear dynamic interactions of damage and structure will necessitate it.

Group-based differences in anti-aging bias among medical students.

PubMed

Ruiz, Jorge G; Andrade, Allen D; Anam, Ramanakumar; Taldone, Sabrina; Karanam, Chandana; Hogue, Christie; Mintzer, Michael J

2015-01-01

Medical students (MS) may develop ageist attitudes early in their training that may predict their future avoidance of caring for the elderly. This study sought to determine MS' patterns of explicit and implicit anti-aging bias, intent to practice with older people and using the quad model, the role of gender, race, and motivation-based differences. One hundred and three MS completed an online survey that included explicit and implicit measures. Explicit measures revealed a moderately positive perception of older people. Female medical students and those high in internal motivation showed lower anti-aging bias, and both were more likely to intend to practice with older people. Although the implicit measure revealed more negativity toward the elderly than the explicit measures, there were no group differences. However, using the quad model the authors identified gender, race, and motivation-based differences in controlled and automatic processes involved in anti-aging bias.

A VGI data integration framework based on linked data model

NASA Astrophysics Data System (ADS)

Wan, Lin; Ren, Rongrong

2015-12-01

This paper aims at the geographic data integration and sharing method for multiple online VGI data sets. We propose a semantic-enabled framework for online VGI sources cooperative application environment to solve a target class of geospatial problems. Based on linked data technologies - which is one of core components of semantic web, we can construct the relationship link among geographic features distributed in diverse VGI platform by using linked data modeling methods, then deploy these semantic-enabled entities on the web, and eventually form an interconnected geographic data network to support geospatial information cooperative application across multiple VGI data sources. The mapping and transformation from VGI sources to RDF linked data model is presented to guarantee the unique data represent model among different online social geographic data sources. We propose a mixed strategy which combined spatial distance similarity and feature name attribute similarity as the measure standard to compare and match different geographic features in various VGI data sets. And our work focuses on how to apply Markov logic networks to achieve interlinks of the same linked data in different VGI-based linked data sets. In our method, the automatic generating method of co-reference object identification model according to geographic linked data is discussed in more detail. It finally built a huge geographic linked data network across loosely-coupled VGI web sites. The results of the experiment built on our framework and the evaluation of our method shows the framework is reasonable and practicable.

A different time and place test of ArcHSI: A spatially explicit habitat model for elk in the Black Hills

Treesearch

Mark A. Rumble; Lakhdar Benkobi; R. Scott Gamo

2007-01-01

We tested predictions of the spatially explicit ArcHSI habitat model for elk. The distribution of elk relative to proximity of forage and cover differed from that predicted. Elk used areas near primary roads similar to that predicted by the model, but elk were farther from secondary roads. Elk used areas categorized as good (> 0.7), fair (> 0.42 to 0.7), and poor...

Pulsar distances and the galactic distribution of free electrons

NASA Technical Reports Server (NTRS)

Taylor, J. H.; Cordes, J. M.

1993-01-01

The present quantitative model for Galactic free electron distribution abandons the assumption of axisymmetry and explicitly incorporates spiral arms; their shapes and locations are derived from existing radio and optical observations of H II regions. The Gum Nebula's dispersion-measure contributions are also explicitly modeled. Adjustable quantities are calibrated by reference to three different types of data. The new model is estimated to furnish distance estimates to known pulsars that are accurate to about 25 percent.

Developing landscape habitat models for rare amphibians with small geographic ranges: a case study of Siskiyou Mountains salamanders in the western USA

Treesearch

Nobuya Suzuki; Deanna H. Olson; Edward C. Reilly

2007-01-01

To advance the development of conservation planning for rare species with small geographic ranges, we determined habitat associations of Siskiyou Mountains salamanders (Plethodon stormi) and developed habitat suitability models at fine (10 ha), medium (40 ha), and broad (202 ha) spatial scales using available geographic information systems data and...

Continuum Fatigue Damage Modeling for Use in Life Extending Control

NASA Technical Reports Server (NTRS)

Lorenzo, Carl F.

1994-01-01

This paper develops a simplified continuum (continuous wrp to time, stress, etc.) fatigue damage model for use in Life Extending Controls (LEC) studies. The work is based on zero mean stress local strain cyclic damage modeling. New nonlinear explicit equation forms of cyclic damage in terms of stress amplitude are derived to facilitate the continuum modeling. Stress based continuum models are derived. Extension to plastic strain-strain rate models are also presented. Application of these models to LEC applications is considered. Progress toward a nonzero mean stress based continuum model is presented. Also, new nonlinear explicit equation forms in terms of stress amplitude are also derived for this case.

Importance of spatial autocorrelation in modeling bird distributions at a continental scale

USGS Publications Warehouse

Bahn, V.; O'Connor, R.J.; Krohn, W.B.

2006-01-01

Spatial autocorrelation in species' distributions has been recognized as inflating the probability of a type I error in hypotheses tests, causing biases in variable selection, and violating the assumption of independence of error terms in models such as correlation or regression. However, it remains unclear whether these problems occur at all spatial resolutions and extents, and under which conditions spatially explicit modeling techniques are superior. Our goal was to determine whether spatial models were superior at large extents and across many different species. In addition, we investigated the importance of purely spatial effects in distribution patterns relative to the variation that could be explained through environmental conditions. We studied distribution patterns of 108 bird species in the conterminous United States using ten years of data from the Breeding Bird Survey. We compared the performance of spatially explicit regression models with non-spatial regression models using Akaike's information criterion. In addition, we partitioned the variance in species distributions into an environmental, a pure spatial and a shared component. The spatially-explicit conditional autoregressive regression models strongly outperformed the ordinary least squares regression models. In addition, partialling out the spatial component underlying the species' distributions showed that an average of 17% of the explained variation could be attributed to purely spatial effects independent of the spatial autocorrelation induced by the underlying environmental variables. We concluded that location in the range and neighborhood play an important role in the distribution of species. Spatially explicit models are expected to yield better predictions especially for mobile species such as birds, even in coarse-grained models with a large extent. ?? Ecography.

LES with and without explicit filtering: comparison and assessment of various models

NASA Astrophysics Data System (ADS)

Winckelmans, Gregoire S.; Jeanmart, Herve; Wray, Alan A.; Carati, Daniele

2000-11-01

The proper mathematical formalism for large eddy simulation (LES) of turbulent flows assumes that a regular ``explicit" filter (i.e., a filter with a well-defined second moment, such as the gaussian, the top hat, etc.) is applied to the equations of fluid motion. This filter is then responsible for a ``filtered-scale" stress. Because of the discretization of the filtered equations, using the LES grid, there is also a ``subgrid-scale" stress. The global effective stress is found to be the discretization of a filtered-scale stress plus a subgrid-scale stress. The former can be partially reconstructed from an exact, infinite, series, the first term of which is the ``tensor-diffusivity" model of Leonard and is found, in practice, to be sufficient for modeling. Alternatively, sufficient reconstruction can also be achieved using the ``scale-similarity" model of Bardina. The latter corresponds to loss of information: it cannot be reconstructed; its effect (essentially dissipation) must be modeled using ad hoc modeling strategies (such as the dynamic version of the ``effective viscosity" model of Smagorinsky). Practitionners also often assume LES without explicit filtering: the effective stress is then only a subgrid-scale stress. We here compare the performance of various LES models for both approaches (with and without explicit filtering), and for cases without solid boundaries: (1) decay of isotropic turbulence; (2) decay of aircraft wake vortices in a turbulent atmosphere. One main conclusion is that better subgrid-scale models are still needed, the effective viscosity models being too active at the large scales.

Epidemiology of Dengue Virus in Iquitos, Peru 1999 to 2005: Interepidemic and Epidemic Patterns of Transmission

PubMed Central

Morrison, Amy C.; Minnick, Sharon L.; Rocha, Claudio; Forshey, Brett M.; Stoddard, Steven T.; Getis, Arthur; Focks, Dana A.; Russell, Kevin L.; Olson, James G.; Blair, Patrick J.; Watts, Douglas M.; Sihuincha, Moises; Scott, Thomas W.; Kochel, Tadeusz J.

2010-01-01

Background Comprehensive, longitudinal field studies that monitor both disease and vector populations for dengue viruses are urgently needed as a pre-requisite for developing locally adaptable prevention programs or to appropriately test and license new vaccines. Methodology and Principal Findings We report the results from such a study spanning 5 years in the Amazonian city of Iquitos, Peru where DENV infection was monitored serologically among ∼2,400 members of a neighborhood-based cohort and through school-based absenteeism surveillance for active febrile illness among a subset of this cohort. At baseline, 80% of the study population had DENV antibodies, seroprevalence increased with age, and significant geographic variation was observed, with neighborhood-specific age-adjusted rates ranging from 67.1 to 89.9%. During the first 15 months, when DENV-1 and DENV-2 were co-circulating, population-based incidence rates ranged from 2–3 infections/100 person-years (p-years). The introduction of DENV-3 during the last half of 2001 was characterized by 3 distinct periods: amplification over at least 5–6 months, replacement of previously circulating serotypes, and epidemic transmission when incidence peaked at 89 infections/100 p-years. Conclusions/Significance Neighborhood-specific baseline seroprevalence rates were not predictive of geographic incidence patterns prior to the DENV-3 introduction, but were closely mirrored during the invasion of this serotype. Transmission varied geographically, with peak incidence occurring at different times among the 8 geographic zones in ∼16 km2 of the city. The lag from novel serotype introduction to epidemic transmission and knowledge of spatially explicit areas of elevated risk should be considered for more effective application of limited resources for dengue prevention. PMID:20454609

On the performance of explicit and implicit algorithms for transient thermal analysis

NASA Astrophysics Data System (ADS)

Adelman, H. M.; Haftka, R. T.

1980-09-01

The status of an effort to increase the efficiency of calculating transient temperature fields in complex aerospace vehicle structures is described. The advantages and disadvantages of explicit and implicit algorithms are discussed. A promising set of implicit algorithms, known as the GEAR package is described. Four test problems, used for evaluating and comparing various algorithms, have been selected and finite element models of the configurations are discribed. These problems include a space shuttle frame component, an insulated cylinder, a metallic panel for a thermal protection system and a model of the space shuttle orbiter wing. Calculations were carried out using the SPAR finite element program, the MITAS lumped parameter program and a special purpose finite element program incorporating the GEAR algorithms. Results generally indicate a preference for implicit over explicit algorithms for solution of transient structural heat transfer problems when the governing equations are stiff. Careful attention to modeling detail such as avoiding thin or short high-conducting elements can sometimes reduce the stiffness to the extent that explicit methods become advantageous.

The Importance of Explicitly Representing Soil Carbon with Depth over the Permafrost Region in Earth System Models: Implications for Atmospheric Carbon Dynamics at Multiple Temporal Scales between 1960 and 2300.

NASA Astrophysics Data System (ADS)

McGuire, A. D.

2014-12-01

We conducted an assessment of changes in permafrost area and carbon storage simulated by process-based models between 1960 and 2300. The models participating in this comparison were those that had joined the model integration team of the Vulnerability of Permafrost Carbon Research Coordination Network (see http://www.biology.ufl.edu/permafrostcarbon/). Each of the models in this comparison conducted simulations over the permafrost land region in the Northern Hemisphere driven by CCSM4-simulated climate for RCP 4.5 and 8.5 scenarios. Among the models, the area of permafrost (defined as the area for which active layer thickness was less than 3 m) ranged between 13.2 and 20.0 million km2. Between 1960 and 2300, models indicated the loss of permafrost area between 5.1 to 6.0 million km2 for RCP 4.5 and between 7.1 and 15.2 million km2 for RCP 8.5. Among the models, the density of soil carbon storage in 1960 ranged between 13 and 42 thousand g C m-2; models that explicitly represented carbon with depth had estimates greater than 27 thousand g C m-2. For the RCP 4.5 scenario, changes in soil carbon between 1960 and 2300 ranged between losses of 32 Pg C to gains of 58 Pg C, in which models that explicitly represent soil carbon with depth simulated losses or lower gains of soil carbon in comparison with those that did not. For the RCP 8.5 scenario, changes in soil carbon between 1960 and 2300 ranged between losses of 642 Pg C to gains of 66 Pg C, in which those models that represent soil carbon explicitly with depth all simulated losses, while those that do not all simulated gains. These results indicate that there are substantial differences in responses of carbon dynamics between model that do and do not explicitly represent soil carbon with depth in the permafrost region. We present analyses of the implications of the differences for atmospheric carbon dynamics at multiple temporal scales between 1960 and 2300.

Predicting geographically distributed adult dental decay in the greater Auckland region of New Zealand.

PubMed

Rocha, C M; Kruger, E; Whyman, R; Tennant, M

2014-06-01

To model the geographic distribution of current (and treated) dental decay on a high-resolution geographic basis for the Auckland region of New Zealand. The application of matrix-based mathematics to modelling adult dental disease-based on known population risk profiles to provide a detailed map of the dental caries distribution for the greater Auckland region. Of the 29 million teeth in adults in the region some 1.2 million (4%) are suffering decay whilst 7.2 million (25%) have previously suffered decay and are now restored. The model provides a high-resolution picture of where the disease burden lies geographically and presents to health planners a method for developing future service plans.

Application of models to conservation planning for terrestrial birds in North America

USGS Publications Warehouse

Fitzgerald, Jane A.; Thogmartin, Wayne E.; Dettmers, Randy; Jones, Tim; Rustay, Christopher; Ruth, Janet M.; Thompson, Frank R.; Will, Tom; Millspaugh, Joshua J.; Thompson, Frank R.

2009-01-01

Partners in Flight (PIF), a public–private coalition for the conservation of land birds, has developed one of four international bird conservation plans recognized under the auspices of the North American Bird Conservation Initiative (NABCI). Partners in Flight prioritized species most in need of conservation attention and set range-wide population goals for 448 species of terrestrial birds. Partnerships are now tasked with developing spatially explicit estimates of the distribution, and abundance of priority species across large ecoregions and identifying habitat acreages needed to support populations at prescribed levels. The PIF Five Elements process of conservation design identifies five steps needed to implement all bird conservation at the ecoregional scale. Habitat assessment and landscape characterization describe the current amounts of different habitat types and summarize patch characteristics, and landscape configurations that define the ability of a landscape to sustain healthy bird populations and are a valuable first step to describing the planning area before pursuing more complex species-specific models. Spatially linked database models, landscape-scale habitat suitability models, and statistical models are viable alternatives for predicting habitat suitability or bird abundance across large planning areas to help assess conservation opportunities, design landscapes to meet population objectives, and monitor change in habitat suitability or bird numbers over time.Bird conservation in the United States is a good example of the use of models in large-scale wildlife conservation planning because of its geographic extent, focus on multiple species, involvement of multiple partners, and use of simple to complex models. We provide some background on the recent development of bird conservation initiatives in the United States and the approaches used for regional conservation assessment and planning. We focus on approaches being used for landscape characterization and assessment, and bird population response modeling.

A Dual-Process Approach to the Role of Mother's Implicit and Explicit Attitudes toward Their Child in Parenting Models

ERIC Educational Resources Information Center

Sturge-Apple, Melissa L.; Rogge, Ronald D.; Skibo, Michael A.; Peltz, Jack S.; Suor, Jennifer H.

2015-01-01

Extending dual process frameworks of cognition to a novel domain, the present study examined how mothers' explicit and implicit attitudes about her child may operate in models of parenting. To assess implicit attitudes, two separate studies were conducted using the same child-focused Go/No-go Association Task (GNAT-Child). In Study 1, model…

Calabi-Yau structures on categories of matrix factorizations

NASA Astrophysics Data System (ADS)

Shklyarov, Dmytro

2017-09-01

Using tools of complex geometry, we construct explicit proper Calabi-Yau structures, that is, non-degenerate cyclic cocycles on differential graded categories of matrix factorizations of regular functions with isolated critical points. The formulas involve the Kapustin-Li trace and its higher corrections. From the physics perspective, our result yields explicit 'off-shell' models for categories of topological D-branes in B-twisted Landau-Ginzburg models.

Does Teaching Students How to Explicitly Model the Causal Structure of Systems Improve Their Understanding of These Systems?

ERIC Educational Resources Information Center

Jensen, Eva

2014-01-01

If students really understand the systems they study, they would be able to tell how changes in the system would affect a result. This demands that the students understand the mechanisms that drive its behaviour. The study investigates potential merits of learning how to explicitly model the causal structure of systems. The approach and…

An Explicit Algorithm for the Simulation of Fluid Flow through Porous Media

NASA Astrophysics Data System (ADS)

Trapeznikova, Marina; Churbanova, Natalia; Lyupa, Anastasiya

2018-02-01

The work deals with the development of an original mathematical model of porous medium flow constructed by analogy with the quasigasdynamic system of equations and allowing implementation via explicit numerical methods. The model is generalized to the case of multiphase multicomponent fluid and takes into account possible heat sources. The proposed approach is verified by a number of test predictions.

Development and Validation of Spatially Explicit Habitat Models for Cavity-nesting Birds in Fishlake National Forest, Utah

Treesearch

Randall A., Jr. Schultz; Thomas C., Jr. Edwards; Gretchen G. Moisen; Tracey S. Frescino

2005-01-01

The ability of USDA Forest Service Forest Inventory and Analysis (FIA) generated spatial products to increase the predictive accuracy of spatially explicit, macroscale habitat models was examined for nest-site selection by cavity-nesting birds in Fishlake National Forest, Utah. One FIA-derived variable (percent basal area of aspen trees) was significant in the habitat...

Integrating spatial modeling, climate change scenarios, invasive species risk, and public perceptions to inform sustainable management in mixed hemlock-hardwood forests in Maine

NASA Astrophysics Data System (ADS)

Dunckel, Kathleen Lois

Introduced invasive pests and climate change are perhaps the most important and persistent catalyst for changes in forest composition. Infestation and outbreak of the hemlock woolly adelgid (HWA, Adelges tsugae) along the eastern coast of the USA, has led to widespread loss of hemlock (Tsuga canadensis (L.) Carr.), and a shift in tree species composition towards hardwood stands. Maine's forest dominated landscape and position at the leading edge of the HWA invasion provides an excellent opportunity to inform sustainable forest management (SFM) practices by using spatially explicit models to predict current tree species distribution, future range shifts, and solicit broad based feedback from Maine residents about forest management goals and preferences. This paper describes an interdisciplinary study of the ecological and social implications of changes in mixed northern hardwood forests due to disturbance. A two stage mapping approach was used where presence/absence of eastern hemlock is predicted with an overall accuracy of 85% and the continuous distribution (% basal area) was predicted with an accuracy of 83%. Given the importance of climate variables in predicting eastern hemlock, forecasts of future range shifts are possible using data generated through climate scenarios. The NASA Earth Exchange (NEX) Downscaled Climate Projections (NEX-DCP30) dataset was used to model future shifts in the geographic range of eastern hemlock throughout the state of Maine. The results clearly describe a significant shift in eastern hemlock range with gains in total geographic area that is suitable habitat. Sustaining forest systems across the landscape requires not only ecological knowledge, but also the integration of multiple socio-economic criteria as well, including data obtained through broad-based public participation approaches. Here, 3000 Maine residents were surveyed and asked how they: (1) value local forests; (2) view forest management goals and threats to forest ecosystems; and (3) evaluate alternative treatment options for the control of invasive species - in this case, HWA. Results suggest that despite Maine's historic dependence on forest products, resident values regarding forests are complex and display agreement with both psycho-spiritual and anthropocentric motivations.

Combining Distributed and Shared Memory Models: Approach and Evolution of the Global Arrays Toolkit

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

Nieplocha, Jarek; Harrison, Robert J.; Kumar, Mukul

2002-07-29

Both shared memory and distributed memory models have advantages and shortcomings. Shared memory model is much easier to use but it ignores data locality/placement. Given the hierarchical nature of the memory subsystems in the modern computers this characteristic might have a negative impact on performance and scalability. Various techniques, such as code restructuring to increase data reuse and introducing blocking in data accesses, can address the problem and yield performance competitive with message passing[Singh], however at the cost of compromising the ease of use feature. Distributed memory models such as message passing or one-sided communication offer performance and scalability butmore » they compromise the ease-of-use. In this context, the message-passing model is sometimes referred to as?assembly programming for the scientific computing?. The Global Arrays toolkit[GA1, GA2] attempts to offer the best features of both models. It implements a shared-memory programming model in which data locality is managed explicitly by the programmer. This management is achieved by explicit calls to functions that transfer data between a global address space (a distributed array) and local storage. In this respect, the GA model has similarities to the distributed shared-memory models that provide an explicit acquire/release protocol. However, the GA model acknowledges that remote data is slower to access than local data and allows data locality to be explicitly specified and hence managed. The GA model exposes to the programmer the hierarchical memory of modern high-performance computer systems, and by recognizing the communication overhead for remote data transfer, it promotes data reuse and locality of reference. This paper describes the characteristics of the Global Arrays programming model, capabilities of the toolkit, and discusses its evolution.« less

Projecting the Local Impacts of Climate Change on a Central American Montane Avian Community

NASA Technical Reports Server (NTRS)

Gasner, Matthew R.; Jankowski, Jill E.; Ciecka, Anna L.; Kyle, Keiller O.; Rabenold, Kerry N.

2010-01-01

Significant changes in the climates of Central America are expected over the next century. Lowland rainforests harbor high alpha diversity on local scales (<1 km2), yet montane landscapes often support higher beta diversity on 10-100 km2 scales. Climate change will likely disrupt the altitudinal zonation of montane communities that produces such landscape diversity. Projections of biotic response to climate change have often used broad-scale modelling of geographical ranges, but understanding likely impacts on population viability is also necessary for anticipating local and global extinctions. We model species abundances and estimate range shifts for birds in the Tilaran Mountains of Costa Rica, asking whether projected changes in temperature and rainfall could be sufficient to imperil high-elevation endemics and whether these variables will likely impact communities similarly. We find that nearly half of 77 forest bird species can be expected to decline in the next century. Almost half of species projected to decline are endemic to Central America, and seven of eight species projected to become locally extinct are endemic to the highlands of Costa Rica and Panam . Logistic-regression modelling of distributions and similarity in projections produced by temperature and rainfall models suggest that changes in both variables will be important. Although these projections are probably conservative because they do not explicitly incorporate biological or climate variable interactions, they provide a starting point for incorporating more realistic biological complexity into community-change models. Prudent conservation planning for tropical mountains should focus on regions with room for altitudinal reorganization of communities comprised of ecological specialists.

An approach to hydrogeological modeling of a large system of groundwater-fed lakes and wetlands in the Nebraska Sand Hills, USA

NASA Astrophysics Data System (ADS)

Rossman, Nathan R.; Zlotnik, Vitaly A.; Rowe, Clinton M.

2018-05-01

The feasibility of a hydrogeological modeling approach to simulate several thousand shallow groundwater-fed lakes and wetlands without explicitly considering their connection with groundwater is investigated at the regional scale ( 40,000 km2) through an application in the semi-arid Nebraska Sand Hills (NSH), USA. Hydraulic heads are compared to local land-surface elevations from a digital elevation model (DEM) within a geographic information system to assess locations of lakes and wetlands. The water bodies are inferred where hydraulic heads exceed, or are above a certain depth below, the land surface. Numbers of lakes and/or wetlands are determined via image cluster analysis applied to the same 30-m grid as the DEM after interpolating both simulated and estimated heads. The regional water-table map was used for groundwater model calibration, considering MODIS-based net groundwater recharge data. Resulting values of simulated total baseflow to interior streams are within 1% of observed values. Locations, areas, and numbers of simulated lakes and wetlands are compared with Landsat 2005 survey data and with areas of lakes from a 1979-1980 Landsat survey and the National Hydrography Dataset. This simplified process-based modeling approach avoids the need for field-based morphology or water-budget data from individual lakes or wetlands, or determination of lake-groundwater exchanges, yet it reproduces observed lake-wetland characteristics at regional groundwater management scales. A better understanding of the NSH hydrogeology is attained, and the approach shows promise for use in simulations of groundwater-fed lake and wetland characteristics in other large groundwater systems.

Parameter and uncertainty estimation for mechanistic, spatially explicit epidemiological models

NASA Astrophysics Data System (ADS)

Finger, Flavio; Schaefli, Bettina; Bertuzzo, Enrico; Mari, Lorenzo; Rinaldo, Andrea

2014-05-01

Epidemiological models can be a crucially important tool for decision-making during disease outbreaks. The range of possible applications spans from real-time forecasting and allocation of health-care resources to testing alternative intervention mechanisms such as vaccines, antibiotics or the improvement of sanitary conditions. Our spatially explicit, mechanistic models for cholera epidemics have been successfully applied to several epidemics including, the one that struck Haiti in late 2010 and is still ongoing. Calibration and parameter estimation of such models represents a major challenge because of properties unusual in traditional geoscientific domains such as hydrology. Firstly, the epidemiological data available might be subject to high uncertainties due to error-prone diagnosis as well as manual (and possibly incomplete) data collection. Secondly, long-term time-series of epidemiological data are often unavailable. Finally, the spatially explicit character of the models requires the comparison of several time-series of model outputs with their real-world counterparts, which calls for an appropriate weighting scheme. It follows that the usual assumption of a homoscedastic Gaussian error distribution, used in combination with classical calibration techniques based on Markov chain Monte Carlo algorithms, is likely to be violated, whereas the construction of an appropriate formal likelihood function seems close to impossible. Alternative calibration methods, which allow for accurate estimation of total model uncertainty, particularly regarding the envisaged use of the models for decision-making, are thus needed. Here we present the most recent developments regarding methods for parameter and uncertainty estimation to be used with our mechanistic, spatially explicit models for cholera epidemics, based on informal measures of goodness of fit.

The Impacts of Information-Sharing Mechanisms on Spatial Market Formation Based on Agent-Based Modeling

PubMed Central

Li, Qianqian; Yang, Tao; Zhao, Erbo; Xia, Xing’ang; Han, Zhangang

2013-01-01

There has been an increasing interest in the geographic aspects of economic development, exemplified by P. Krugman’s logical analysis. We show in this paper that the geographic aspects of economic development can be modeled using multi-agent systems that incorporate multiple underlying factors. The extent of information sharing is assumed to be a driving force that leads to economic geographic heterogeneity across locations without geographic advantages or disadvantages. We propose an agent-based market model that considers a spectrum of different information-sharing mechanisms: no information sharing, information sharing among friends and pheromone-like information sharing. Finally, we build a unified model that accommodates all three of these information-sharing mechanisms based on the number of friends who can share information. We find that the no information-sharing model does not yield large economic zones, and more information sharing can give rise to a power-law distribution of market size that corresponds to the stylized fact of city size and firm size distributions. The simulations show that this model is robust. This paper provides an alternative approach to studying economic geographic development, and this model could be used as a test bed to validate the detailed assumptions that regulate real economic agglomeration. PMID:23484007

Anthropogenic habitat disturbance and the dynamics of hantavirus using remote sensing, GIS, and a spatially explicit agent-based model

NASA Astrophysics Data System (ADS)

Cao, Lina

Sin Nombre virus (SNV), a strain of hantavirus, causes hantavirus pulmonary syndrome (HPS) in humans, a deadly disease with high mortality rate (>50%). The primary virus host is deer mice, and greater deer mice abundance has been shown to increase the human risk of HPS. There is a great need in understanding the nature of the virus host, its temporal and spatial dynamics, and its relation to the human population with the purpose of predicting human risk of the disease. This research studies SNV dynamics in deer mice in the Great Basin Desert of central Utah, USA using multiyear field data and integrated geospatial approaches including remote sensing, Geographic Information System (GIS), and a spatially explicit agent-based model. The goal is to advance our understanding of the important ecological and demographic factors that affect the dynamics of deer mouse population and SNV prevalence. The primary research question is how climate, habitat disturbance, and deer mouse demographics affect deer mouse population density, its movement, and SNV prevalence in the sagebrush habitat. The results show that the normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI) can be good predictors of deer mouse density and the number of infected deer mice with a time lag of 1.0 to 1.3 years. This information can be very useful in predicting mouse abundance and SNV risk. The results also showed that climate, mouse density, sex, mass, and SNV infection had significant effects on deer mouse movement. The effect of habitat disturbance on mouse movement varies according to climate conditions with positive relationship in predrought condition and negative association in postdrought condition. The heavier infected deer mice moved the most. Season and disturbance alone had no significant effects. The spatial agent-based model (SABM) simulation results show that prevalence was negatively related to the disturbance levels and the sensitivity analysis showed that population density was one of the most important parameters affecting the SNV dynamics. The results also indicated that habitat disturbance could increase hantavirus transmission likely by increasing the movement and consequently contact rates. However, the model suggested that habitat disturbance had a much stronger effect on prevalence by decreasing population density than by increasing mice movement. Therefore, overall habitat disturbance reduces SNV prevalence.

Methods used to parameterize the spatially-explicit components of a state-and-transition simulation model

USGS Publications Warehouse

Sleeter, Rachel; Acevedo, William; Soulard, Christopher E.; Sleeter, Benjamin M.

2015-01-01

Spatially-explicit state-and-transition simulation models of land use and land cover (LULC) increase our ability to assess regional landscape characteristics and associated carbon dynamics across multiple scenarios. By characterizing appropriate spatial attributes such as forest age and land-use distribution, a state-and-transition model can more effectively simulate the pattern and spread of LULC changes. This manuscript describes the methods and input parameters of the Land Use and Carbon Scenario Simulator (LUCAS), a customized state-and-transition simulation model utilized to assess the relative impacts of LULC on carbon stocks for the conterminous U.S. The methods and input parameters are spatially explicit and describe initial conditions (strata, state classes and forest age), spatial multipliers, and carbon stock density. Initial conditions were derived from harmonization of multi-temporal data characterizing changes in land use as well as land cover. Harmonization combines numerous national-level datasets through a cell-based data fusion process to generate maps of primary LULC categories. Forest age was parameterized using data from the North American Carbon Program and spatially-explicit maps showing the locations of past disturbances (i.e. wildfire and harvest). Spatial multipliers were developed to spatially constrain the location of future LULC transitions. Based on distance-decay theory, maps were generated to guide the placement of changes related to forest harvest, agricultural intensification/extensification, and urbanization. We analyze the spatially-explicit input parameters with a sensitivity analysis, by showing how LUCAS responds to variations in the model input. This manuscript uses Mediterranean California as a regional subset to highlight local to regional aspects of land change, which demonstrates the utility of LUCAS at many scales and applications.

Corruption of accuracy and efficiency of Markov chain Monte Carlo simulation by inaccurate numerical implementation of conceptual hydrologic models

NASA Astrophysics Data System (ADS)

Schoups, G.; Vrugt, J. A.; Fenicia, F.; van de Giesen, N. C.

2010-10-01

Conceptual rainfall-runoff models have traditionally been applied without paying much attention to numerical errors induced by temporal integration of water balance dynamics. Reliance on first-order, explicit, fixed-step integration methods leads to computationally cheap simulation models that are easy to implement. Computational speed is especially desirable for estimating parameter and predictive uncertainty using Markov chain Monte Carlo (MCMC) methods. Confirming earlier work of Kavetski et al. (2003), we show here that the computational speed of first-order, explicit, fixed-step integration methods comes at a cost: for a case study with a spatially lumped conceptual rainfall-runoff model, it introduces artificial bimodality in the marginal posterior parameter distributions, which is not present in numerically accurate implementations of the same model. The resulting effects on MCMC simulation include (1) inconsistent estimates of posterior parameter and predictive distributions, (2) poor performance and slow convergence of the MCMC algorithm, and (3) unreliable convergence diagnosis using the Gelman-Rubin statistic. We studied several alternative numerical implementations to remedy these problems, including various adaptive-step finite difference schemes and an operator splitting method. Our results show that adaptive-step, second-order methods, based on either explicit finite differencing or operator splitting with analytical integration, provide the best alternative for accurate and efficient MCMC simulation. Fixed-step or adaptive-step implicit methods may also be used for increased accuracy, but they cannot match the efficiency of adaptive-step explicit finite differencing or operator splitting. Of the latter two, explicit finite differencing is more generally applicable and is preferred if the individual hydrologic flux laws cannot be integrated analytically, as the splitting method then loses its advantage.

Explicit Instruction Elements in Core Reading Programs

ERIC Educational Resources Information Center

Child, Angela R.

2012-01-01

Classroom teachers are provided instructional recommendations for teaching reading from their adopted core reading programs (CRPs). Explicit instruction elements or what is also called instructional moves, including direct explanation, modeling, guided practice, independent practice, discussion, feedback, and monitoring, were examined within CRP…

Source identification of western Oregon Douglas-fir wood cores using mass spectrometry and random forest classification.

PubMed

Finch, Kristen; Espinoza, Edgard; Jones, F Andrew; Cronn, Richard

2017-05-01

We investigated whether wood metabolite profiles from direct analysis in real time (time-of-flight) mass spectrometry (DART-TOFMS) could be used to determine the geographic origin of Douglas-fir wood cores originating from two regions in western Oregon, USA. Three annual ring mass spectra were obtained from 188 adult Douglas-fir trees, and these were analyzed using random forest models to determine whether samples could be classified to geographic origin, growth year, or growth year and geographic origin. Specific wood molecules that contributed to geographic discrimination were identified. Douglas-fir mass spectra could be differentiated into two geographic classes with an accuracy between 70% and 76%. Classification models could not accurately classify sample mass spectra based on growth year. Thirty-two molecules were identified as key for classifying western Oregon Douglas-fir wood cores to geographic origin. DART-TOFMS is capable of detecting minute but regionally informative differences in wood molecules over a small geographic scale, and these differences made it possible to predict the geographic origin of Douglas-fir wood with moderate accuracy. Studies involving DART-TOFMS, alone and in combination with other technologies, will be relevant for identifying the geographic origin of illegally harvested wood.

Late positive potential to explicit sexual images associated with the number of sexual intercourse partners

PubMed Central

Steele, Vaughn R.; Staley, Cameron; Sabatinelli, Dean

2015-01-01

Risky sexual behaviors typically occur when a person is sexually motivated by potent, sexual reward cues. Yet, individual differences in sensitivity to sexual cues have not been examined with respect to sexual risk behaviors. A greater responsiveness to sexual cues might provide greater motivation for a person to act sexually; a lower responsiveness to sexual cues might lead a person to seek more intense, novel, possibly risky, sexual acts. In this study, event-related potentials were recorded in 64 men and women while they viewed a series of emotional, including explicit sexual, photographs. The motivational salience of the sexual cues was varied by including more and less explicit sexual images. Indeed, the more explicit sexual stimuli resulted in enhanced late positive potentials (LPP) relative to the less explicit sexual images. Participants with fewer sexual intercourse partners in the last year had reduced LPP amplitude to the less explicit sexual images than the more explicit sexual images, whereas participants with more partners responded similarly to the more and less explicit sexual images. This pattern of results is consistent with a greater responsivity model. Those who engage in more sexual behaviors consistent with risk are also more responsive to less explicit sexual cues. PMID:24526189

Spatiotemporal database of US congressional elections, 1896–2014

PubMed Central

Wolf, Levi John

2017-01-01

High-quality historical data about US Congressional elections has long provided common ground for electoral studies. However, advances in geographic information science have recently made it efficient to compile, distribute, and analyze large spatio-temporal data sets on the structure of US Congressional districts. A single spatio-temporal data set that relates US Congressional election results to the spatial extent of the constituencies has not yet been developed. To address this, existing high-quality data sets of elections returns were combined with a spatiotemporal data set on Congressional district boundaries to generate a new spatio-temporal database of US Congressional election results that are explicitly linked to the geospatial data about the districts themselves. PMID:28809849

Assessment of implicit health attitudes: a multitrait-multimethod approach and a comparison between patients with hypochondriasis and patients with anxiety disorders.

PubMed

Weck, Florian; Höfling, Volkmar

2015-01-01

Two adaptations of the Implicit Association Task were used to assess implicit anxiety (IAT-Anxiety) and implicit health attitudes (IAT-Hypochondriasis) in patients with hypochondriasis (n = 58) and anxiety patients (n = 71). Explicit anxieties and health attitudes were assessed using questionnaires. The analysis of several multitrait-multimethod models indicated that the low correlation between explicit and implicit measures of health attitudes is due to the substantial methodological differences between the IAT and the self-report questionnaire. Patients with hypochondriasis displayed significantly more dysfunctional explicit and implicit health attitudes than anxiety patients, but no differences were found regarding explicit and implicit anxieties. The study demonstrates the specificity of explicit and implicit dysfunctional health attitudes among patients with hypochondriasis.

Free energy landscape of protein folding in water: explicit vs. implicit solvent.

PubMed

Zhou, Ruhong

2003-11-01

The Generalized Born (GB) continuum solvent model is arguably the most widely used implicit solvent model in protein folding and protein structure prediction simulations; however, it still remains an open question on how well the model behaves in these large-scale simulations. The current study uses the beta-hairpin from C-terminus of protein G as an example to explore the folding free energy landscape with various GB models, and the results are compared to the explicit solvent simulations and experiments. All free energy landscapes are obtained from extensive conformation space sampling with a highly parallel replica exchange method. Because solvation model parameters are strongly coupled with force fields, five different force field/solvation model combinations are examined and compared in this study, namely the explicit solvent model: OPLSAA/SPC model, and the implicit solvent models: OPLSAA/SGB (Surface GB), AMBER94/GBSA (GB with Solvent Accessible Surface Area), AMBER96/GBSA, and AMBER99/GBSA. Surprisingly, we find that the free energy landscapes from implicit solvent models are quite different from that of the explicit solvent model. Except for AMBER96/GBSA, all other implicit solvent models find the lowest free energy state not the native state. All implicit solvent models show erroneous salt-bridge effects between charged residues, particularly in OPLSAA/SGB model, where the overly strong salt-bridge effect results in an overweighting of a non-native structure with one hydrophobic residue F52 expelled from the hydrophobic core in order to make better salt bridges. On the other hand, both AMBER94/GBSA and AMBER99/GBSA models turn the beta-hairpin in to an alpha-helix, and the alpha-helical content is much higher than the previously reported alpha-helices in an explicit solvent simulation with AMBER94 (AMBER94/TIP3P). Only AMBER96/GBSA shows a reasonable free energy landscape with the lowest free energy structure the native one despite an erroneous salt-bridge between D47 and K50. Detailed results on free energy contour maps, lowest free energy structures, distribution of native contacts, alpha-helical content during the folding process, NOE comparison with NMR, and temperature dependences are reported and discussed for all five models. Copyright 2003 Wiley-Liss, Inc.

Global Climate Forcing from Albedo Change Caused by Large-scale Deforestation and Reforestation: Quantification and Attribution of Geographic Variation

NASA Technical Reports Server (NTRS)

Gao, Feng; Ghimire, Bardan; Jiao, Tong; Williams, Christopher A.; Masek, Jeffrey; Schaaf, Crystal

2017-01-01

Large-scale deforestation and reforestation have contributed substantially to historical and contemporary global climate change in part through albedo-induced radiative forcing, with meaningful implications for forest management aiming to mitigate climate change. Associated warming or cooling varies widely across the globe due to a range of factors including forest type, snow cover, and insolation, but resulting geographic variation remain spoorly described and has been largely based on model assessments. This study provides an observation-based approach to quantify local and global radiative forcings from large-scale deforestation and reforestation and further examines mechanisms that result in the spatial heterogeneity of radiative forcing. We incorporate a new spatially and temporally explicit land cover-specific albedo product derived from Moderate Resolution Imaging Spectroradiometer with a historical land use data set (Land Use Harmonization product). Spatial variation in radiative forcing was attributed to four mechanisms, including the change in snow-covered albedo, change in snow-free albedo, snow cover fraction, and incoming solar radiation. We find an albedo-only radiative forcing (RF) of -0.819 W m(exp -2) if year 2000 forests were completely deforested and converted to croplands. Albedo RF from global reforestation of present-day croplands to recover year 1700 forests is estimated to be 0.161 W m)exp -2). Snow-cover fraction is identified as the primary factor in determining the spatial variation of radiative forcing in winter, while the magnitude of the change in snow-free albedo is the primary factor determining variations in summertime RF. Findings reinforce the notion that, for conifers at the snowier high latitudes, albedo RF diminishes the warming from forest loss and the cooling from forest gain more so than for other forest types, latitudes, and climate settings.

Global wheat production potentials and management flexibility under the representative concentration pathways

NASA Astrophysics Data System (ADS)

Balkovič, Juraj; van der Velde, Marijn; Skalský, Rastislav; Xiong, Wei; Folberth, Christian; Khabarov, Nikolay; Smirnov, Alexey; Mueller, Nathaniel D.; Obersteiner, Michael

2014-11-01

Wheat is the third largest crop globally and an essential source of calories in human diets. Maintaining and increasing global wheat production is therefore strongly linked to food security. A large geographic variation in wheat yields across similar climates points to sizeable yield gaps in many nations, and indicates a regionally variable flexibility to increase wheat production. Wheat is particularly sensitive to a changing climate thus limiting management opportunities to enable (sustainable) intensification with potentially significant implications for future wheat production. We present a comprehensive global evaluation of future wheat yields and production under distinct Representative Concentration Pathways (RCPs) using the Environmental Policy Integrated Climate (EPIC) agro-ecosystem model. We project, in a geographically explicit manner, future wheat production pathways for rainfed and irrigated wheat systems. We explore agricultural management flexibility by quantifying the development of wheat yield potentials under current, rainfed, exploitable (given current irrigation infrastructure), and irrigated intensification levels. Globally, because of climate change, wheat production under conventional management (around the year 2000) would decrease across all RCPs by 37 to 52 and 54 to 103 Mt in the 2050s and 2090s, respectively. However, the exploitable and potential production gap will stay above 350 and 580 Mt, respectively, for all RCPs and time horizons, indicating that negative impacts of climate change can globally be offset by adequate intensification using currently existing irrigation infrastructure and nutrient additions. Future world wheat production on cropland already under cultivation can be increased by ~ 35% through intensified fertilization and ~ 50% through increased fertilization and extended irrigation, if sufficient water would be available. Significant potential can still be exploited, especially in rainfed wheat systems in Russia, Eastern Europe and North America.

Limitation of Biofuel Production in Europe from the Forest Market

NASA Astrophysics Data System (ADS)

Leduc, Sylvain; Wetterlund, Elisabeth; Dotzauer, Erik; Kindermann, Georg

2013-04-01

The European Union has set a 10% target for the share of biofuel in the transportation sector to be met by 2020. To reach this target, second generation biofuel is expected to replace 3 to 5% of the transport fossil fuel consumption. But the competition on the feedstock is an issue and makes the planning for the second generation biofuel plant a challenge. Moreover, no commercial second generation biofuel production plant is under operation, but if reaching commercial status, this type of production plants are expected to become very large. In order to minimize the tranportation costs and to takle the competetion for the feedstock against the existing woody based industries, the geographical location of biofuel production plants becomes an issue. This study investigates the potential of second generation biofuel economically feasible in Europe by 2020 in regards with the competition for the feedsstock with the existing woody biomass based industries (CHP, pulp and paper mills, sawmills...). To assess the biofuel potential in Europe, a techno-economic, geographically explicit model, BeWhere, is used. It determines the optimal locations of bio-energy production plants by minimizing the costs and CO2 emissions of the entire supply chain. The existing woody based industries have to first meet their wood demand, and if the amount of wood that remains is suficiant, new bio-energy production plants if any can be set up. Preliminary results show that CHP plants are preferably chosen over biofuel production plants. Strong biofuel policy support is needed in order to consequently increase the biofuel production in Europe. The carbon tax influences the emission reduction to a higher degree than the biofuel support. And the potential of second generation biofuel would at most reach 3% of the European transport fuel if the wood demand does not increase from 2010.

Propagule pressure and stream characteristics influence introgression: Cutthroat and rainbow trout in British Columbia

USGS Publications Warehouse

Bennett, S.N.; Olson, J.R.; Kershner, J.L.; Corbett, P.

2010-01-01

Hybridization and introgression between introduced and native salmonids threaten the continued persistence of many inland cutthroat trout species. Environmental models have been developed to predict the spread of introgression, but few studies have assessed the role of propagule pressure. We used an extensive set of fish stocking records and geographic information system (GIS) data to produce a spatially explicit index of potential propagule pressure exerted by introduced rainbow trout in the Upper Kootenay River, British Columbia, Canada. We then used logistic regression and the information-theoretic approach to test the ability of a set of environmental and spatial variables to predict the level of introgression between native westslope cutthroat trout and introduced rainbow trout. Introgression was assessed using between four and seven co-dominant, diagnostic nuclear markers at 45 sites in 31 different streams. The best model for predicting introgression included our GIS propagule pressure index and an environmental variable that accounted for the biogeoclimatic zone of the site (r2 = 0.62). This model was 1.4 times more likely to explain introgression than the next-best model, which consisted of only the propagule pressure index variable. We created a composite model based on the model-averaged results of the seven top models that included environmental, spatial, and propagule pressure variables. The propagule pressure index had the highest importance weight (0.995) of all variables tested and was negatively related to sites with no introgression. This study used an index of propagule pressure and demonstrated that propagule pressure had the greatest influence on the level of introgression between a native and introduced trout in a human-induced hybrid zone. ?? 2010 by the Ecological Society of America.

Land Use Change on Household Farms in the Ecuadorian Amazon: Design and Implementation of an Agent-Based Model.

PubMed

Mena, Carlos F; Walsh, Stephen J; Frizzelle, Brian G; Xiaozheng, Yao; Malanson, George P

2011-01-01

This paper describes the design and implementation of an Agent-Based Model (ABM) used to simulate land use change on household farms in the Northern Ecuadorian Amazon (NEA). The ABM simulates decision-making processes at the household level that is examined through a longitudinal, socio-economic and demographic survey that was conducted in 1990 and 1999. Geographic Information Systems (GIS) are used to establish spatial relationships between farms and their environment, while classified Landsat Thematic Mapper (TM) imagery is used to set initial land use/land cover conditions for the spatial simulation, assess from-to land use/land cover change patterns, and describe trajectories of land use change at the farm and landscape levels. Results from prior studies in the NEA provide insights into the key social and ecological variables, describe human behavioral functions, and examine population-environment interactions that are linked to deforestation and agricultural extensification, population migration, and demographic change. Within the architecture of the model, agents are classified as active or passive. The model comprises four modules, i.e., initialization, demography, agriculture, and migration that operate individually, but are linked through key household processes. The main outputs of the model include a spatially-explicit representation of the land use/land cover on survey and non-survey farms and at the landscape level for each annual time-step, as well as simulated socio-economic and demographic characteristics of households and communities. The work describes the design and implementation of the model and how population-environment interactions can be addressed in a frontier setting. The paper contributes to land change science by examining important pattern-process relations, advocating a spatial modeling approach that is capable of synthesizing fundamental relationships at the farm level, and links people and environment in complex ways.

Modeling effects of climate change on Yakima River salmonid habitats

USGS Publications Warehouse

Hatten, James R.; Batt, Thomas R.; Connolly, Patrick J.; Maule, Alec G.

2014-01-01

We evaluated the potential effects of two climate change scenarios on salmonid habitats in the Yakima River by linking the outputs from a watershed model, a river operations model, a two-dimensional (2D) hydrodynamic model, and a geographic information system (GIS). The watershed model produced a discharge time series (hydrograph) in two study reaches under three climate scenarios: a baseline (1981–2005), a 1-°C increase in mean air temperature (plus one scenario), and a 2-°C increase (plus two scenario). A river operations model modified the discharge time series with Yakima River operational rules, a 2D model provided spatially explicit depth and velocity grids for two floodplain reaches, while an expert panel provided habitat criteria for four life stages of coho and fall Chinook salmon. We generated discharge-habitat functions for each salmonid life stage (e.g., spawning, rearing) in main stem and side channels, and habitat time series for baseline, plus one (P1) and plus two (P2) scenarios. The spatial and temporal patterns in salmonid habitats differed by reach, life stage, and climate scenario. Seventy-five percent of the 28 discharge-habitat responses exhibited a decrease in habitat quantity, with the P2 scenario producing the largest changes, followed by P1. Fry and spring/summer rearing habitats were the most sensitive to warming and flow modification for both species. Side channels generally produced more habitat than main stem and were more responsive to flow changes, demonstrating the importance of lateral connectivity in the floodplain. A discharge-habitat sensitivity analysis revealed that proactive management of regulated surface waters (i.e., increasing or decreasing flows) might lessen the impacts of climate change on salmonid habitats.

Evolution of microgastropods (Ellobioidea, Carychiidae): integrating taxonomic, phylogenetic and evolutionary hypotheses

PubMed Central

2013-01-01

Background Current biodiversity patterns are considered largely the result of past climatic and tectonic changes. In an integrative approach, we combine taxonomic and phylogenetic hypotheses to analyze temporal and geographic diversification of epigean (Carychium) and subterranean (Zospeum) evolutionary lineages in Carychiidae (Eupulmonata, Ellobioidea). We explicitly test three hypotheses: 1) morphospecies encompass unrecognized evolutionary lineages, 2) limited dispersal results in a close genetic relationship of geographical proximally distributed taxa and 3) major climatic and tectonic events had an impact on lineage diversification within Carychiidae. Results Initial morphospecies assignments were investigated by different molecular delimitation approaches (threshold, ABGD, GMYC and SP). Despite a conservative delimitation strategy, carychiid morphospecies comprise a great number of unrecognized evolutionary lineages. We attribute this phenomenon to historic underestimation of morphological stasis and phenotypic variability amongst lineages. The first molecular phylogenetic hypothesis for the Carychiidae (based on COI, 16S and H3) reveals Carychium and Zospeum to be reciprocally monophyletic. Geographical proximally distributed lineages are often closely related. The temporal diversification of Carychiidae is best described by a constant rate model of diversification. The evolution of Carychiidae is characterized by relatively few (long distance) colonization events. We find support for an Asian origin of Carychium. Zospeum may have arrived in Europe before extant members of Carychium. Distantly related Carychium clades inhabit a wide spectrum of the available bioclimatic niche and demonstrate considerable niche overlap. Conclusions Carychiid taxonomy is in dire need of revision. An inferred wide distribution and variable phenotype suggest underestimated diversity in Zospeum. Several Carychium morphospecies are results of past taxonomic lumping. By collecting populations at their type locality, molecular investigations are able to link historic morphospecies assignments to their respective evolutionary lineage. We propose that rare founder populations initially colonized a continent or cave system. Subsequent passive dispersal into adjacent areas led to in situ pan-continental or mountain range diversifications. Major environmental changes did not influence carychiid diversification. However, certain molecular delimitation methods indicated a recent decrease in diversification rate. We attribute this decrease to protracted speciation. PMID:23343473

Explicit and implicit springback simulation in sheet metal forming using fully coupled ductile damage and distortional hardening model

NASA Astrophysics Data System (ADS)

Yetna n'jock, M.; Houssem, B.; Labergere, C.; Saanouni, K.; Zhenming, Y.

2018-05-01

The springback is an important phenomenon which accompanies the forming of metallic sheets especially for high strength materials. A quantitative prediction of springback becomes very important for newly developed material with high mechanical characteristics. In this work, a numerical methodology is developed to quantify this undesirable phenomenon. This methodoly is based on the use of both explicit and implicit finite element solvers of Abaqus®. The most important ingredient of this methodology consists on the use of highly predictive mechanical model. A thermodynamically-consistent, non-associative and fully anisotropic elastoplastic constitutive model strongly coupled with isotropic ductile damage and accounting for distortional hardening is then used. An algorithm for local integration of the complete set of the constitutive equations is developed. This algorithm considers the rotated frame formulation (RFF) to ensure the incremental objectivity of the model in the framework of finite strains. This algorithm is implemented in both explicit (Abaqus/Explicit®) and implicit (Abaqus/Standard®) solvers of Abaqus® through the users routine VUMAT and UMAT respectively. The implicit solver of Abaqus® has been used to study spingback as it is generally a quasi-static unloading. In order to compare the methods `efficiency, the explicit method (Dynamic Relaxation Method) proposed by Rayleigh has been also used for springback prediction. The results obtained within U draw/bending benchmark are studied, discussed and compared with experimental results as reference. Finally, the purpose of this work is to evaluate the reliability of different methods predict efficiently springback in sheet metal forming.

Free energy landscapes of small peptides in an implicit solvent model determined by force-biased multicanonical molecular dynamics simulation

NASA Astrophysics Data System (ADS)

Watanabe, Yukihisa S.; Kim, Jae Gil; Fukunishi, Yoshifumi; Nakamura, Haruki

2004-12-01

In order to investigate whether the implicit solvent (GB/SA) model could reproduce the free energy landscapes of peptides, the potential of mean forces (PMFs) of eight tripeptides was examined and compared with the PMFs of the explicit water model. The force-biased multicanonical molecular dynamics method was used for the enhanced conformational sampling. Consequently, the GB/SA model reproduced almost all the global and local minima in the PMFs observed with the explicit water model. However, the GB/SA model overestimated frequencies of the structures that are stabilized by intra-peptide hydrogen bonds.

A Goddard Multi-Scale Modeling System with Unified Physics

NASA Technical Reports Server (NTRS)

Tao, W.K.; Anderson, D.; Atlas, R.; Chern, J.; Houser, P.; Hou, A.; Lang, S.; Lau, W.; Peters-Lidard, C.; Kakar, R.;

A neurocomputational theory of how explicit learning bootstraps early procedural learning.

PubMed

Paul, Erick J; Ashby, F Gregory

2013-01-01

It is widely accepted that human learning and memory is mediated by multiple memory systems that are each best suited to different requirements and demands. Within the domain of categorization, at least two systems are thought to facilitate learning: an explicit (declarative) system depending largely on the prefrontal cortex, and a procedural (non-declarative) system depending on the basal ganglia. Substantial evidence suggests that each system is optimally suited to learn particular categorization tasks. However, it remains unknown precisely how these systems interact to produce optimal learning and behavior. In order to investigate this issue, the present research evaluated the progression of learning through simulation of categorization tasks using COVIS, a well-known model of human category learning that includes both explicit and procedural learning systems. Specifically, the model's parameter space was thoroughly explored in procedurally learned categorization tasks across a variety of conditions and architectures to identify plausible interaction architectures. The simulation results support the hypothesis that one-way interaction between the systems occurs such that the explicit system "bootstraps" learning early on in the procedural system. Thus, the procedural system initially learns a suboptimal strategy employed by the explicit system and later refines its strategy. This bootstrapping could be from cortical-striatal projections that originate in premotor or motor regions of cortex, or possibly by the explicit system's control of motor responses through basal ganglia-mediated loops.

Random-growth urban model with geographical fitness

NASA Astrophysics Data System (ADS)

Kii, Masanobu; Akimoto, Keigo; Doi, Kenji

2012-12-01

This paper formulates a random-growth urban model with a notion of geographical fitness. Using techniques of complex-network theory, we study our system as a type of preferential-attachment model with fitness, and we analyze its macro behavior to clarify the properties of the city-size distributions it predicts. First, restricting the geographical fitness to take positive values and using a continuum approach, we show that the city-size distributions predicted by our model asymptotically approach Pareto distributions with coefficients greater than unity. Then, allowing the geographical fitness to take negative values, we perform local coefficient analysis to show that the predicted city-size distributions can deviate from Pareto distributions, as is often observed in actual city-size distributions. As a result, the model we propose can generate a generic class of city-size distributions, including but not limited to Pareto distributions. For applications to city-population projections, our simple model requires randomness only when new cities are created, not during their subsequent growth. This property leads to smooth trajectories of city population growth, in contrast to other models using Gibrat’s law. In addition, a discrete form of our dynamical equations can be used to estimate past city populations based on present-day data; this fact allows quantitative assessment of the performance of our model. Further study is needed to determine appropriate formulas for the geographical fitness.

A watershed-based spatially-explicit demonstration of an integrated environmental modeling framework for ecosystem services in the Coal River Basin (WV, USA)

Treesearch

John M. Johnston; Mahion C. Barber; Kurt Wolfe; Mike Galvin; Mike Cyterski; Rajbir Parmar; Luis Suarez

2016-01-01

We demonstrate a spatially-explicit regional assessment of current condition of aquatic ecoservices in the Coal River Basin (CRB), with limited sensitivity analysis for the atmospheric contaminant mercury. The integrated modeling framework (IMF) forecasts water quality and quantity, habitat suitability for aquatic biota, fish biomasses, population densities, ...

Finite Element Modeling of Coupled Flexible Multibody Dynamics and Liquid Sloshing

DTIC Science & Technology

2006-09-01

tanks is presented. The semi-discrete combined solid and fluid equations of motions are integrated using a time- accurate parallel explicit solver...Incompressible fluid flow in a moving/deforming container including accurate modeling of the free-surface, turbulence, and viscous effects ...paper, a single computational code which uses a time- accurate explicit solution procedure is used to solve both the solid and fluid equations of

Incorporating geographical factors with artificial neural networks to predict reference values of erythrocyte sedimentation rate

PubMed Central

2013-01-01

Background The measurement of the Erythrocyte Sedimentation Rate (ESR) value is a standard procedure performed during a typical blood test. In order to formulate a unified standard of establishing reference ESR values, this paper presents a novel prediction model in which local normal ESR values and corresponding geographical factors are used to predict reference ESR values using multi-layer feed-forward artificial neural networks (ANN). Methods and findings Local normal ESR values were obtained from hospital data, while geographical factors that include altitude, sunshine hours, relative humidity, temperature and precipitation were obtained from the National Geographical Data Information Centre in China. The results show that predicted values are statistically in agreement with measured values. Model results exhibit significant agreement between training data and test data. Consequently, the model is used to predict the unseen local reference ESR values. Conclusions Reference ESR values can be established with geographical factors by using artificial intelligence techniques. ANN is an effective method for simulating and predicting reference ESR values because of its ability to model nonlinear and complex relationships. PMID:23497145

Incorporating geographical factors with artificial neural networks to predict reference values of erythrocyte sedimentation rate.

PubMed

Yang, Qingsheng; Mwenda, Kevin M; Ge, Miao

2013-03-12

The measurement of the Erythrocyte Sedimentation Rate (ESR) value is a standard procedure performed during a typical blood test. In order to formulate a unified standard of establishing reference ESR values, this paper presents a novel prediction model in which local normal ESR values and corresponding geographical factors are used to predict reference ESR values using multi-layer feed-forward artificial neural networks (ANN). Local normal ESR values were obtained from hospital data, while geographical factors that include altitude, sunshine hours, relative humidity, temperature and precipitation were obtained from the National Geographical Data Information Centre in China.The results show that predicted values are statistically in agreement with measured values. Model results exhibit significant agreement between training data and test data. Consequently, the model is used to predict the unseen local reference ESR values. Reference ESR values can be established with geographical factors by using artificial intelligence techniques. ANN is an effective method for simulating and predicting reference ESR values because of its ability to model nonlinear and complex relationships.

Statistical detection of geographic clusters of resistant Escherichia coli in a regional network with WHONET and SaTScan.

PubMed

Park, Rachel; O'Brien, Thomas F; Huang, Susan S; Baker, Meghan A; Yokoe, Deborah S; Kulldorff, Martin; Barrett, Craig; Swift, Jamie; Stelling, John

2016-11-01

While antimicrobial resistance threatens the prevention, treatment, and control of infectious diseases, systematic analysis of routine microbiology laboratory test results worldwide can alert new threats and promote timely response. This study explores statistical algorithms for recognizing geographic clustering of multi-resistant microbes within a healthcare network and monitoring the dissemination of new strains over time. Escherichia coli antimicrobial susceptibility data from a three-year period stored in WHONET were analyzed across ten facilities in a healthcare network utilizing SaTScan's spatial multinomial model with two models for defining geographic proximity. We explored geographic clustering of multi-resistance phenotypes within the network and changes in clustering over time. Geographic clustering identified from both latitude/longitude and non-parametric facility groupings geographic models were similar, while the latter was offers greater flexibility and generalizability. Iterative application of the clustering algorithms suggested the possible recognition of the initial appearance of invasive E. coli ST131 in the clinical database of a single hospital and subsequent dissemination to others. Systematic analysis of routine antimicrobial resistance susceptibility test results supports the recognition of geographic clustering of microbial phenotypic subpopulations with WHONET and SaTScan, and iterative application of these algorithms can detect the initial appearance in and dissemination across a region prompting early investigation, response, and containment measures.

A spatially explicit hydro-ecological modeling framework (BEPS-TerrainLab V2.0): Model description and test in a boreal ecosystem in Eastern North America

NASA Astrophysics Data System (ADS)

Govind, Ajit; Chen, Jing Ming; Margolis, Hank; Ju, Weimin; Sonnentag, Oliver; Giasson, Marc-André

2009-04-01

SummaryA spatially explicit, process-based hydro-ecological model, BEPS-TerrainLab V2.0, was developed to improve the representation of ecophysiological, hydro-ecological and biogeochemical processes of boreal ecosystems in a tightly coupled manner. Several processes unique to boreal ecosystems were implemented including the sub-surface lateral water fluxes, stratification of vegetation into distinct layers for explicit ecophysiological representation, inclusion of novel spatial upscaling strategies and biogeochemical processes. To account for preferential water fluxes common in humid boreal ecosystems, a novel scheme was introduced based on laboratory analyses. Leaf-scale ecophysiological processes were upscaled to canopy-scale by explicitly considering leaf physiological conditions as affected by light and water stress. The modified model was tested with 2 years of continuous measurements taken at the Eastern Old Black Spruce Site of the Fluxnet-Canada Research Network located in a humid boreal watershed in eastern Canada. Comparison of the simulated and measured ET, water-table depth (WTD), volumetric soil water content (VSWC) and gross primary productivity (GPP) revealed that BEPS-TerrainLab V2.0 simulates hydro-ecological processes with reasonable accuracy. The model was able to explain 83% of the ET, 92% of the GPP variability and 72% of the WTD dynamics. The model suggests that in humid ecosystems such as eastern North American boreal watersheds, topographically driven sub-surface baseflow is the main mechanism of soil water partitioning which significantly affects the local-scale hydrological conditions.

Understanding the effects of different social data on selecting priority conservation areas.

PubMed

Karimi, Azadeh; Tulloch, Ayesha I T; Brown, Greg; Hockings, Marc

2017-12-01

Conservation success is contingent on assessing social and environmental factors so that cost-effective implementation of strategies and actions can be placed in a broad social-ecological context. Until now, the focus has been on how to include spatially explicit social data in conservation planning, whereas the value of different kinds of social data has received limited attention. In a regional systematic conservation planning case study in Australia, we examined the spatial concurrence of a range of spatially explicit social values and land-use preferences collected using a public participation geographic information system and biological data. We used Zonation to integrate the social data with the biological data in a series of spatial-prioritization scenarios to determine the effect of the different types of social data on spatial prioritization compared with biological data alone. The type of social data (i.e., conservation opportunities or constraints) significantly affected spatial prioritization outcomes. The integration of social values and land-use preferences under different scenarios was highly variable and generated spatial prioritizations 1.2-51% different from those based on biological data alone. The inclusion of conservation-compatible values and preferences added relatively few new areas to conservation priorities, whereas including noncompatible economic values and development preferences as costs significantly changed conservation priority areas (48.2% and 47.4%, respectively). Based on our results, a multifaceted conservation prioritization approach that combines spatially explicit social data with biological data can help conservation planners identify the type of social data to collect for more effective and feasible conservation actions. © 2017 Society for Conservation Biology.

Applying metapopulation theory to conservation of migratory birds

USGS Publications Warehouse

Esler, Daniel N.

2000-01-01

Metapopulation theory has proven useful for understanding the population structure and dynamics of many species of conservation concern. The metapopulation concept has been applied almost exclusively to nonmigratory species, however, for which subpopulation demographic independence—a requirement for a classically defined metapopulation - is explicitly related to geographic distribution and dispersal probabilities. Defining the degree of demographic independence among subpopulations of migratory animals, and thus the applicability of metapopulation theory as a conceptual framework for understanding population dynamics, is much more difficult. Unlike nonmigratory species, subpopulations of migratory animals cannot be defined as synonymous with geographic areas. Groups of migratory birds that are geographically separate at one part of the annual cycle may occur together at others, but co-occurrence in time and space does not preclude the demographic independence of subpopulations. I suggest that metapopulation theory can be applied to migratory species but that understanding the degree of subpopulation independence may require information about both spatial distribution throughout the annual cycle and behavioral mechanisms that may lead to subpopulation demographic independence. The key for applying metapopulation theory to migratory animals lies in identifying demographically independent subpopulations, even as they move during the annual cycle and potentially co-occur with other subpopulations. Using examples of migratory bird species, I demonstrate that spatial and temporal modes of subpopulation independence can interact with behavioral mechanisms to create demographically independent subpopulations, including cases in which subpopulations are not spatially distinct in some parts of the annual cycle.

Analytical validation of an explicit finite element model of a rolling element bearing with a localised line spall

NASA Astrophysics Data System (ADS)

Singh, Sarabjeet; Howard, Carl Q.; Hansen, Colin H.; Köpke, Uwe G.

2018-03-01

In this paper, numerically modelled vibration response of a rolling element bearing with a localised outer raceway line spall is presented. The results were obtained from a finite element (FE) model of the defective bearing solved using an explicit dynamics FE software package, LS-DYNA. Time domain vibration signals of the bearing obtained directly from the FE modelling were processed further to estimate time-frequency and frequency domain results, such as spectrogram and power spectrum, using standard signal processing techniques pertinent to the vibration-based monitoring of rolling element bearings. A logical approach to analyses of the numerically modelled results was developed with an aim to presenting the analytical validation of the modelled results. While the time and frequency domain analyses of the results show that the FE model generates accurate bearing kinematics and defect frequencies, the time-frequency analysis highlights the simulation of distinct low- and high-frequency characteristic vibration signals associated with the unloading and reloading of the rolling elements as they move in and out of the defect, respectively. Favourable agreement of the numerical and analytical results demonstrates the validation of the results from the explicit FE modelling of the bearing.

The influence of habitats on female mobility in Central and Western Africa inferred from human mitochondrial variation

PubMed Central

2013-01-01

Background When studying the genetic structure of human populations, the role of cultural factors may be difficult to ascertain due to a lack of formal models. Linguistic diversity is a typical example of such a situation. Patrilocality, on the other hand, can be integrated into a biological framework, allowing the formulation of explicit working hypotheses. The present study is based on the assumption that patrilocal traditions make the hypervariable region I of the mtDNA a valuable tool for the exploration of migratory dynamics, offering the opportunity to explore the relationships between genetic and linguistic diversity. We studied 85 Niger-Congo-speaking patrilocal populations that cover regions from Senegal to Central African Republic. A total of 4175 individuals were included in the study. Results By combining a multivariate analysis aimed at investigating the population genetic structure, with a Bayesian approach used to test models and extent of migration, we were able to detect a stepping-stone migration model as the best descriptor of gene flow across the region, with the main discontinuities corresponding to forested areas. Conclusions Our analyses highlight an aspect of the influence of habitat variation on human genetic diversity that has yet to be understood. Rather than depending simply on geographic linear distances, patterns of female genetic variation vary substantially between savannah and rainforest environments. Our findings may be explained by the effects of recent gene flow constrained by environmental factors, which superimposes on a background shaped by pre-agricultural peopling. PMID:23360301

Echinoids of the Kerguelen Plateau - occurrence data and environmental setting for past, present, and future species distribution modelling.

PubMed

Guillaumot, Charlène; Martin, Alexis; Fabri-Ruiz, Salomé; Eléaume, Marc; Saucède, Thomas

2016-01-01

The present dataset provides a case study for species distribution modelling (SDM) and for model testing in a poorly documented marine region. The dataset includes spatially-explicit data for echinoid (Echinodermata: Echinoidea) distribution. Echinoids were collected during oceanographic campaigns led around the Kerguelen Plateau (+63°/+81°E; -46°/-56°S) since 1872. In addition to the identification of collection specimens from historical cruises, original data from the recent campaigns POKER II (2010) and PROTEKER 2 to 4 (2013-2015) are also provided. In total, five families, ten genera, and 12 echinoid species are recorded in the region of the Kerguelen Plateau. The dataset is complemented with environmental descriptors available and relevant for echinoid ecology and SDM. The environmental data was compiled from different sources and was modified to suit the geographic extent of the Kerguelen Plateau, using scripts developed with the R language (R Core Team 2015). Spatial resolution was set at a common 0.1° pixel resolution. Mean seafloor and sea surface temperatures, salinity and their amplitudes, all derived from the World Ocean Database (Boyer et al. 2013) are made available for the six following decades: 1955-1964, 1965-1974, 1975-1984, 1985-1994, 1995-2004, 2005-2012. Future projections are provided for several parameters: they were modified from the Bio-ORACLE database (Tyberghein et al. 2012). They are based on three IPCC scenarii (B1, AIB, A2) for years 2100 and 2200 (IPCC, 4 th report).

Modeling habitat dynamics accounting for possible misclassification

USGS Publications Warehouse

Veran, Sophie; Kleiner, Kevin J.; Choquet, Remi; Collazo, Jaime; Nichols, James D.

2012-01-01

Land cover data are widely used in ecology as land cover change is a major component of changes affecting ecological systems. Landscape change estimates are characterized by classification errors. Researchers have used error matrices to adjust estimates of areal extent, but estimation of land cover change is more difficult and more challenging, with error in classification being confused with change. We modeled land cover dynamics for a discrete set of habitat states. The approach accounts for state uncertainty to produce unbiased estimates of habitat transition probabilities using ground information to inform error rates. We consider the case when true and observed habitat states are available for the same geographic unit (pixel) and when true and observed states are obtained at one level of resolution, but transition probabilities estimated at a different level of resolution (aggregations of pixels). Simulation results showed a strong bias when estimating transition probabilities if misclassification was not accounted for. Scaling-up does not necessarily decrease the bias and can even increase it. Analyses of land cover data in the Southeast region of the USA showed that land change patterns appeared distorted if misclassification was not accounted for: rate of habitat turnover was artificially increased and habitat composition appeared more homogeneous. Not properly accounting for land cover misclassification can produce misleading inferences about habitat state and dynamics and also misleading predictions about species distributions based on habitat. Our models that explicitly account for state uncertainty should be useful in obtaining more accurate inferences about change from data that include errors.

Increasing the sampling efficiency of protein conformational transition using velocity-scaling optimized hybrid explicit/implicit solvent REMD simulation

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

Yu, Yuqi; Wang, Jinan; Shao, Qiang, E-mail: qshao@mail.shcnc.ac.cn, E-mail: Jiye.Shi@ucb.com, E-mail: wlzhu@mail.shcnc.ac.cn

2015-03-28

The application of temperature replica exchange molecular dynamics (REMD) simulation on protein motion is limited by its huge requirement of computational resource, particularly when explicit solvent model is implemented. In the previous study, we developed a velocity-scaling optimized hybrid explicit/implicit solvent REMD method with the hope to reduce the temperature (replica) number on the premise of maintaining high sampling efficiency. In this study, we utilized this method to characterize and energetically identify the conformational transition pathway of a protein model, the N-terminal domain of calmodulin. In comparison to the standard explicit solvent REMD simulation, the hybrid REMD is much lessmore » computationally expensive but, meanwhile, gives accurate evaluation of the structural and thermodynamic properties of the conformational transition which are in well agreement with the standard REMD simulation. Therefore, the hybrid REMD could highly increase the computational efficiency and thus expand the application of REMD simulation to larger-size protein systems.« less

Precipitation areal-reduction factor estimation using an annual-maxima centered approach

USGS Publications Warehouse

Asquith, W.H.; Famiglietti, J.S.

2000-01-01

The adjustment of precipitation depth of a point storm to an effective (mean) depth over a watershed is important for characterizing rainfall-runoff relations and for cost-effective designs of hydraulic structures when design storms are considered. A design storm is the precipitation point depth having a specified duration and frequency (recurrence interval). Effective depths are often computed by multiplying point depths by areal-reduction factors (ARF). ARF range from 0 to 1, vary according to storm characteristics, such as recurrence interval; and are a function of watershed characteristics, such as watershed size, shape, and geographic location. This paper presents a new approach for estimating ARF and includes applications for the 1-day design storm in Austin, Dallas, and Houston, Texas. The approach, termed 'annual-maxima centered,' specifically considers the distribution of concurrent precipitation surrounding an annual-precipitation maxima, which is a feature not seen in other approaches. The approach does not require the prior spatial averaging of precipitation, explicit determination of spatial correlation coefficients, nor explicit definition of a representative area of a particular storm in the analysis. The annual-maxima centered approach was designed to exploit the wide availability of dense precipitation gauge data in many regions of the world. The approach produces ARF that decrease more rapidly than those from TP-29. Furthermore, the ARF from the approach decay rapidly with increasing recurrence interval of the annual-precipitation maxima. (C) 2000 Elsevier Science B.V.The adjustment of precipitation depth of a point storm to an effective (mean) depth over a watershed is important for characterizing rainfall-runoff relations and for cost-effective designs of hydraulic structures when design storms are considered. A design storm is the precipitation point depth having a specified duration and frequency (recurrence interval). Effective depths are often computed by multiplying point depths by areal-reduction factors (ARF). ARF range from 0 to 1, vary according to storm characteristics, such as recurrence interval; and are a function of watershed characteristics, such as watershed size, shape, and geographic location. This paper presents a new approach for estimating ARF and includes applications for the 1-day design storm in Austin, Dallas, and Houston, Texas. The approach, termed 'annual-maxima centered,' specifically considers the distribution of concurrent precipitation surrounding an annual-precipitation maxima, which is a feature not seen in other approaches. The approach does not require the prior spatial averaging of precipitation, explicit determination of spatial correlation coefficients, nor explicit definition of a representative area of a particular storm in the analysis. The annual-maxima centered approach was designed to exploit the wide availability of dense precipitation gauge data in many regions of the world. The approach produces ARF that decrease more rapidly than those from TP-29. Furthermore, the ARF from the approach decay rapidly with increasing recurrence interval of the annual-precipitation maxima.

Predictive Validity of Explicit and Implicit Threat Overestimation in Contamination Fear

PubMed Central

Green, Jennifer S.; Teachman, Bethany A.

2012-01-01

We examined the predictive validity of explicit and implicit measures of threat overestimation in relation to contamination-fear outcomes using structural equation modeling. Undergraduate students high in contamination fear (N = 56) completed explicit measures of contamination threat likelihood and severity, as well as looming vulnerability cognitions, in addition to an implicit measure of danger associations with potential contaminants. Participants also completed measures of contamination-fear symptoms, as well as subjective distress and avoidance during a behavioral avoidance task, and state looming vulnerability cognitions during an exposure task. The latent explicit (but not implicit) threat overestimation variable was a significant and unique predictor of contamination fear symptoms and self-reported affective and cognitive facets of contamination fear. On the contrary, the implicit (but not explicit) latent measure predicted behavioral avoidance (at the level of a trend). Results are discussed in terms of differential predictive validity of implicit versus explicit markers of threat processing and multiple fear response systems. PMID:24073390

Explicit and Implicit Processes Constitute the Fast and Slow Processes of Sensorimotor Learning.

PubMed

McDougle, Samuel D; Bond, Krista M; Taylor, Jordan A

2015-07-01

A popular model of human sensorimotor learning suggests that a fast process and a slow process work in parallel to produce the canonical learning curve (Smith et al., 2006). Recent evidence supports the subdivision of sensorimotor learning into explicit and implicit processes that simultaneously subserve task performance (Taylor et al., 2014). We set out to test whether these two accounts of learning processes are homologous. Using a recently developed method to assay explicit and implicit learning directly in a sensorimotor task, along with a computational modeling analysis, we show that the fast process closely resembles explicit learning and the slow process approximates implicit learning. In addition, we provide evidence for a subdivision of the slow/implicit process into distinct manifestations of motor memory. We conclude that the two-state model of motor learning is a close approximation of sensorimotor learning, but it is unable to describe adequately the various implicit learning operations that forge the learning curve. Our results suggest that a wider net be cast in the search for the putative psychological mechanisms and neural substrates underlying the multiplicity of processes involved in motor learning. Copyright © 2015 the authors 0270-6474/15/359568-12$15.00/0.

Investigating the predictive validity of implicit and explicit measures of motivation in problem-solving behavioural tasks.

PubMed

Keatley, David; Clarke, David D; Hagger, Martin S

2013-09-01

Research into the effects of individuals'autonomous motivation on behaviour has traditionally adopted explicit measures and self-reported outcome assessment. Recently, there has been increased interest in the effects of implicit motivational processes underlying behaviour from a self-determination theory (SDT) perspective. The aim of the present research was to provide support for the predictive validity of an implicit measure of autonomous motivation on behavioural persistence on two objectively measurable tasks. SDT and a dual-systems model were adopted as frameworks to explain the unique effects offered by explicit and implicit autonomous motivational constructs on behavioural persistence. In both studies, implicit autonomous motivation significantly predicted unique variance in time spent on each task. Several explicit measures of autonomous motivation also significantly predicted persistence. Results provide support for the proposed model and the inclusion of implicit measures in research on motivated behaviour. In addition, implicit measures of autonomous motivation appear to be better suited to explaining variance in behaviours that are more spontaneous or unplanned. Future implications for research examining implicit motivation from dual-systems models and SDT approaches are outlined. © 2012 The British Psychological Society.

Modeling Active Aging and Explicit Memory: An Empirical Study.

PubMed

Ponce de León, Laura Ponce; Lévy, Jean Pierre; Fernández, Tomás; Ballesteros, Soledad

2015-08-01

The rapid growth of the population of older adults and their concomitant psychological status and health needs have captured the attention of researchers and health professionals. To help fill the void of literature available to social workers interested in mental health promotion and aging, the authors provide a model for active aging that uses psychosocial variables. Structural equation modeling was used to examine the relationships among the latent variables of the state of explicit memory, the perception of social resources, depression, and the perception of quality of life in a sample of 184 older adults. The results suggest that explicit memory is not a direct indicator of the perception of quality of life, but it could be considered an indirect indicator as it is positively correlated with perception of social resources and negatively correlated with depression. These last two variables influenced the perception of quality of life directly, the former positively and the latter negatively. The main outcome suggests that the perception of social support improves explicit memory and quality of life and reduces depression in active older adults. The findings also suggest that gerontological professionals should design memory training programs, improve available social resources, and offer environments with opportunities to exercise memory.

Explicit and Implicit Processes Constitute the Fast and Slow Processes of Sensorimotor Learning

PubMed Central

Bond, Krista M.; Taylor, Jordan A.

2015-01-01

A popular model of human sensorimotor learning suggests that a fast process and a slow process work in parallel to produce the canonical learning curve (Smith et al., 2006). Recent evidence supports the subdivision of sensorimotor learning into explicit and implicit processes that simultaneously subserve task performance (Taylor et al., 2014). We set out to test whether these two accounts of learning processes are homologous. Using a recently developed method to assay explicit and implicit learning directly in a sensorimotor task, along with a computational modeling analysis, we show that the fast process closely resembles explicit learning and the slow process approximates implicit learning. In addition, we provide evidence for a subdivision of the slow/implicit process into distinct manifestations of motor memory. We conclude that the two-state model of motor learning is a close approximation of sensorimotor learning, but it is unable to describe adequately the various implicit learning operations that forge the learning curve. Our results suggest that a wider net be cast in the search for the putative psychological mechanisms and neural substrates underlying the multiplicity of processes involved in motor learning. PMID:26134640

Independence polynomial and matching polynomial of the Koch network

NASA Astrophysics Data System (ADS)

Liao, Yunhua; Xie, Xiaoliang

2015-11-01

The lattice gas model and the monomer-dimer model are two classical models in statistical mechanics. It is well known that the partition functions of these two models are associated with the independence polynomial and the matching polynomial in graph theory, respectively. Both polynomials have been shown to belong to the “#P-complete” class, which indicate the problems are computationally “intractable”. We consider these two polynomials of the Koch networks which are scale-free with small-world effects. Explicit recurrences are derived, and explicit formulae are presented for the number of independent sets of a certain type.

A geographically explicit ecological momentary assessment (GEMA) mixed method for understanding substance use.

PubMed

McQuoid, Julia; Thrul, Johannes; Ling, Pamela

2018-04-01

Tobacco use is increasingly concentrated within marginalized groups, including LGBTQ+ young adults. Developing tailored interventions to reduce tobacco-related health disparities requires understanding the mechanisms linking individual and contextual factors associated with tobacco use to behavior. This paper presents an in-depth exploration of three cases from a novel mixed method study designed to identify the situational factors and place-based practices of substance use among high-risk individuals. We combined geographically explicit ecological momentary assessment (GEMA) with an adapted travel diary-interview method. Participants (young adult bisexual smokers, ages 18-26) reported on non-smoking and smoking situations for 30 days with a smartphone app. GEMA surveys captured internal and external situational factors (e.g., craving intensity, location type, seeing others smoking). Continuous locational data was collected via smartphone GPS. Subsequently, participants completed in-depth interviews reviewing maps of their own GEMA data. GEMA data and transcripts were analyzed separately and integrated at the case level in a matrix. Using GEMA maps to guide the interview grounded discussion in participants' everyday smoking situations and routines. Interviews clarified participant interpretation of GEMA measures and revealed experiences and meanings of smoking locations and practices. The GEMA method identified the most frequent smoking locations/times for each participant (e.g., afternoons at university). Interviews provided description of associated situational factors and perceptions of smoking contexts (e.g., peer rejection of bisexual identity) and the roles of smoking therein (e.g., physically escape uncomfortable environments). In conclusion, this mixed method contributes to advancing qualitative GIS and other hypothesis-generating approaches working to reveal the richness of individuals' experiences of the everyday contexts of health behavior, while also providing reliable measures of situational predictors of behaviors of interest, such as substance use. Limitations of and future directions for the method are discussed. Copyright © 2018 Elsevier Ltd. All rights reserved.

Assessment of an Explicit Algebraic Reynolds Stress Model

NASA Technical Reports Server (NTRS)

Carlson, Jan-Renee

2005-01-01

This study assesses an explicit algebraic Reynolds stress turbulence model in the in the three-dimensional Reynolds averaged Navier-Stokes (RANS) solver, ISAAC (Integrated Solution Algorithm for Arbitrary Con gurations). Additionally, it compares solutions for two select configurations between ISAAC and the RANS solver PAB3D. This study compares with either direct numerical simulation data, experimental data, or empirical models for several different geometries with compressible, separated, and high Reynolds number flows. In general, the turbulence model matched data or followed experimental trends well, and for the selected configurations, the computational results of ISAAC closely matched those of PAB3D using the same turbulence model.

Source identification of western Oregon Douglas-fir wood cores using mass spectrometry and random forest classification1

PubMed Central

Finch, Kristen; Espinoza, Edgard; Jones, F. Andrew; Cronn, Richard

2017-01-01

Premise of the study: We investigated whether wood metabolite profiles from direct analysis in real time (time-of-flight) mass spectrometry (DART-TOFMS) could be used to determine the geographic origin of Douglas-fir wood cores originating from two regions in western Oregon, USA. Methods: Three annual ring mass spectra were obtained from 188 adult Douglas-fir trees, and these were analyzed using random forest models to determine whether samples could be classified to geographic origin, growth year, or growth year and geographic origin. Specific wood molecules that contributed to geographic discrimination were identified. Results: Douglas-fir mass spectra could be differentiated into two geographic classes with an accuracy between 70% and 76%. Classification models could not accurately classify sample mass spectra based on growth year. Thirty-two molecules were identified as key for classifying western Oregon Douglas-fir wood cores to geographic origin. Discussion: DART-TOFMS is capable of detecting minute but regionally informative differences in wood molecules over a small geographic scale, and these differences made it possible to predict the geographic origin of Douglas-fir wood with moderate accuracy. Studies involving DART-TOFMS, alone and in combination with other technologies, will be relevant for identifying the geographic origin of illegally harvested wood. PMID:28529831

A multilevel model for comorbid outcomes: obesity and diabetes in the US.

PubMed

Congdon, Peter

2010-02-01

Multilevel models are overwhelmingly applied to single health outcomes, but when two or more health conditions are closely related, it is important that contextual variation in their joint prevalence (e.g., variations over different geographic settings) is considered. A multinomial multilevel logit regression approach for analysing joint prevalence is proposed here that includes subject level risk factors (e.g., age, race, education) while also taking account of geographic context. Data from a US population health survey (the 2007 Behavioral Risk Factor Surveillance System or BRFSS) are used to illustrate the method, with a six category multinomial outcome defined by diabetic status and weight category (obese, overweight, normal). The influence of geographic context is partly represented by known geographic variables (e.g., county poverty), and partly by a model for latent area influences. In particular, a shared latent variable (common factor) approach is proposed to measure the impact of unobserved area influences on joint weight and diabetes status, with the latent variable being spatially structured to reflect geographic clustering in risk.

Logistic Mixed Models to Investigate Implicit and Explicit Belief Tracking.

PubMed

Lages, Martin; Scheel, Anne

2016-01-01

We investigated the proposition of a two-systems Theory of Mind in adults' belief tracking. A sample of N = 45 participants predicted the choice of one of two opponent players after observing several rounds in an animated card game. Three matches of this card game were played and initial gaze direction on target and subsequent choice predictions were recorded for each belief task and participant. We conducted logistic regressions with mixed effects on the binary data and developed Bayesian logistic mixed models to infer implicit and explicit mentalizing in true belief and false belief tasks. Although logistic regressions with mixed effects predicted the data well a Bayesian logistic mixed model with latent task- and subject-specific parameters gave a better account of the data. As expected explicit choice predictions suggested a clear understanding of true and false beliefs (TB/FB). Surprisingly, however, model parameters for initial gaze direction also indicated belief tracking. We discuss why task-specific parameters for initial gaze directions are different from choice predictions yet reflect second-order perspective taking.

Characterizing Aeroelastic Systems Using Eigenanalysis, Explicitly Retaining The Aerodynamic Degrees of Freedom

NASA Technical Reports Server (NTRS)

Heeg, Jennifer; Dowell, Earl H.

2001-01-01

Discrete time aeroelastic models with explicitly retained aerodynamic modes have been generated employing a time marching vortex lattice aerodynamic model. This paper presents analytical results from eigenanalysis of these models. The potential of these models to calculate the behavior of modes that represent damped system motion (noncritical modes) in addition to the simple harmonic modes is explored. A typical section with only structural freedom in pitch is examined. The eigenvalues are examined and compared to experimental data. Issues regarding the convergence of the solution with regard to refining the aerodynamic discretization are investigated. Eigenvector behavior is examined; the eigenvector associated with a particular eigenvalue can be viewed as the set of modal participation factors for that particular mode. For the present formulation of the equations of motion, the vorticity for each aerodynamic element appears explicitly as an element of each eigenvector in addition to the structural dynamic generalized coordinates. Thus, modal participation of the aerodynamic degrees of freedom can be assessed in M addition to participation of structural degrees of freedom.

Quantum mechanical force field for hydrogen fluoride with explicit electronic polarization.

PubMed

Mazack, Michael J M; Gao, Jiali

2014-05-28

The explicit polarization (X-Pol) theory is a fragment-based quantum chemical method that explicitly models the internal electronic polarization and intermolecular interactions of a chemical system. X-Pol theory provides a framework to construct a quantum mechanical force field, which we have extended to liquid hydrogen fluoride (HF) in this work. The parameterization, called XPHF, is built upon the same formalism introduced for the XP3P model of liquid water, which is based on the polarized molecular orbital (PMO) semiempirical quantum chemistry method and the dipole-preserving polarization consistent point charge model. We introduce a fluorine parameter set for PMO, and find good agreement for various gas-phase results of small HF clusters compared to experiments and ab initio calculations at the M06-2X/MG3S level of theory. In addition, the XPHF model shows reasonable agreement with experiments for a variety of structural and thermodynamic properties in the liquid state, including radial distribution functions, interaction energies, diffusion coefficients, and densities at various state points.

A modeling framework for the establishment and spread of invasive species in heterogeneous environments.

PubMed

Lustig, Audrey; Worner, Susan P; Pitt, Joel P W; Doscher, Crile; Stouffer, Daniel B; Senay, Senait D

2017-10-01

Natural and human-induced events are continuously altering the structure of our landscapes and as a result impacting the spatial relationships between individual landscape elements and the species living in the area. Yet, only recently has the influence of the surrounding landscape on invasive species spread started to be considered. The scientific community increasingly recognizes the need for broader modeling framework that focuses on cross-study comparisons at different spatiotemporal scales. Using two illustrative examples, we introduce a general modeling framework that allows for a systematic investigation of the effect of habitat change on invasive species establishment and spread. The essential parts of the framework are (i) a mechanistic spatially explicit model (a modular dispersal framework-MDIG) that allows population dynamics and dispersal to be modeled in a geographical information system (GIS), (ii) a landscape generator that allows replicated landscape patterns with partially controllable spatial properties to be generated, and (iii) landscape metrics that depict the essential aspects of landscape with which dispersal and demographic processes interact. The modeling framework provides functionality for a wide variety of applications ranging from predictions of the spatiotemporal spread of real species and comparison of potential management strategies, to theoretical investigation of the effect of habitat change on population dynamics. Such a framework allows to quantify how small-grain landscape characteristics, such as habitat size and habitat connectivity, interact with life-history traits to determine the dynamics of invasive species spread in fragmented landscape. As such, it will give deeper insights into species traits and landscape features that lead to establishment and spread success and may be key to preventing new incursions and the development of efficient monitoring, surveillance, control or eradication programs.

Implications of movement for species distribution models - Rethinking environmental data tools.

PubMed

Bruneel, Stijn; Gobeyn, Sacha; Verhelst, Pieterjan; Reubens, Jan; Moens, Tom; Goethals, Peter

2018-07-01

Movement is considered an essential process in shaping the distributions of species. Nevertheless, most species distribution models (SDMs) still focus solely on environment-species relationships to predict the occurrence of species. Furthermore, the currently used indirect estimates of movement allow to assess habitat accessibility, but do not provide an accurate description of movement. Better proxies of movement are needed to assess the dispersal potential of individual species and to gain a more practical insight in the interconnectivity of communities. Telemetry techniques are rapidly evolving and highly capable to provide explicit descriptions of movement, but their usefulness for SDMs will mainly depend on the ability of these models to deal with hitherto unconsidered ecological processes. More specifically, the integration of movement is likely to affect the environmental data requirements as the connection between environmental and biological data is crucial to provide reliable results. Mobility implies the occupancy of a continuum of space, hence an adequate representation of both geographical and environmental space is paramount to study mobile species distributions. In this context, environmental models, remote sensing techniques and animal-borne environmental sensors are discussed as potential techniques to obtain suitable environmental data. In order to provide an in-depth review of the aforementioned methods, we have chosen to use the modelling of fish distributions as a case study. The high mobility of fish and the often highly variable nature of the aquatic environment generally complicate model development, making it an adequate subject for research. Furthermore, insight into the distribution of fish is of great interest for fish stock assessments and water management worldwide, underlining its practical relevance. Copyright © 2018 Elsevier B.V. All rights reserved.

Towards integrated modelling of soil organic carbon cycling at landscape scale

NASA Astrophysics Data System (ADS)

Viaud, V.

2009-04-01

Soil organic carbon (SOC) is recognized as a key factor of the chemical, biological and physical quality of soil. Numerous models of soil organic matter turnover have been developed since the 1930ies, most of them dedicated to plot scale applications. More recently, they have been applied to national scales to establish the inventories of carbon stocks directed by the Kyoto protocol. However, only few studies consider the intermediate landscape scale, where the spatio-temporal pattern of land management practices, its interactions with the physical environment and its impacts on SOC dynamics can be investigated to provide guidelines for sustainable management of soils in agricultural areas. Modelling SOC cycling at this scale requires accessing accurate spatially explicit input data on soils (SOC content, bulk density, depth, texture) and land use (land cover, farm practices), and combining both data in a relevant integrated landscape representation. The purpose of this paper is to present a first approach to modelling SOC evolution in a small catchment. The impact of the way landscape is represented on SOC stocks in the catchment was more specifically addressed. This study was based on the field map, the soil survey, the crop rotations and land management practices of an actual 10-km² agricultural catchment located in Brittany (France). RothC model was used to drive soil organic matter dynamics. Landscape representation in the form of a systematic regular grid, where driving properties vary continuously in space, was compared to a representation where landscape is subdivided into a set of homogeneous geographical units. This preliminary work enabled to identify future needs to improve integrated soil-landscape modelling in agricultural areas.

Blast and the Consequences on Traumatic Brain Injury-Multiscale Mechanical Modeling of Brain

DTIC Science & Technology

2011-02-17

blast simulation. LS-DYNA as an explicit FE code has been employed to simulate this multi- material fluid –structure interaction problem. The 3-D head...formulation is implemented to model the air-blast simulation. LS-DYNA as an explicit FE code has been employed to simulate this multi-material fluid ...Biomechanics Study of Influencing Parameters for brain under Impact ............................... 12 5.1 The Impact of Cerebrospinal Fluid

Traveling waves in a spring-block chain sliding down a slope

NASA Astrophysics Data System (ADS)

Morales, J. E.; James, G.; Tonnelier, A.

2017-07-01

Traveling waves are studied in a spring slider-block model. We explicitly construct front waves (kinks) for a piecewise-linear spinodal friction force. Pulse waves are obtained as the matching of two traveling fronts with identical speeds. Explicit formulas are obtained for the wavespeed and the wave form in the anticontinuum limit. The link with localized waves in a Burridge-Knopoff model of an earthquake fault is briefly discussed.

Biomass and fire dynamics in a temperate forest-grassland mosaic: Integrating multi-species herbivory, climate, and fire with the FireBGCv2/GrazeBGC system

Treesearch

Robert A. Riggs; Robert E. Keane; Norm Cimon; Rachel Cook; Lisa Holsinger; John Cook; Timothy DelCurto; L.Scott Baggett; Donald Justice; David Powell; Martin Vavra; Bridgett Naylor

2015-01-01

Landscape fire succession models (LFSMs) predict spatially-explicit interactions between vegetation succession and disturbance, but these models have yet to fully integrate ungulate herbivory as a driver of their processes. We modified a complex LFSM, FireBGCv2, to include a multi-species herbivory module, GrazeBGC. The system is novel in that it explicitly...

Traveling waves in a spring-block chain sliding down a slope.

PubMed

Morales, J E; James, G; Tonnelier, A

2017-07-01

Traveling waves are studied in a spring slider-block model. We explicitly construct front waves (kinks) for a piecewise-linear spinodal friction force. Pulse waves are obtained as the matching of two traveling fronts with identical speeds. Explicit formulas are obtained for the wavespeed and the wave form in the anticontinuum limit. The link with localized waves in a Burridge-Knopoff model of an earthquake fault is briefly discussed.

Declining physical activity and the socio-cultural context of the geography of industrial restructuring: a novel conceptual framework.

PubMed

Rind, Esther; Jones, Andy

2014-05-01

At the population level, the prevalence of physical activity has declined considerably in many developed countries in recent decades. There is some evidence that areas exhibiting the lowest activity levels are those which have undergone a particularly strong transition away from employment in physically demanding occupations. We propose that processes of deindustrialization may be causally linked to unexplained geographical disparities in levels of physical activity. While the sociocultural correlates of physical activity have been well studied, and prior conceptual frameworks have been developed to explain more general patterns of activity, none have explicitly attempted to identify the components of industrial change that may impact physical activity. In this work we review the current literature on sociocultural correlates of health behaviors before using a case study centered on the United Kingdom to present a novel framework that links industrial change to declining levels of physical activity. We developed a comprehensive model linking sociocultural correlates of physical activity to processes associated with industrial restructuring and discuss implication for policy and practice. A better understanding of sociocultural processes may help to ameliorate adverse health consequences of employment decline in communities that have experienced substantial losses of manual employment.

Impact of human mobility on the emergence of dengue epidemics in Pakistan

PubMed Central

Wesolowski, Amy; Qureshi, Taimur; Boni, Maciej F.; Sundsøy, Pål Roe; Johansson, Michael A.; Rasheed, Syed Basit; Engø-Monsen, Kenth; Buckee, Caroline O.

2015-01-01

The recent emergence of dengue viruses into new susceptible human populations throughout Asia and the Middle East, driven in part by human travel on both local and global scales, represents a significant global health risk, particularly in areas with changing climatic suitability for the mosquito vector. In Pakistan, dengue has been endemic for decades in the southern port city of Karachi, but large epidemics in the northeast have emerged only since 2011. Pakistan is therefore representative of many countries on the verge of countrywide endemic dengue transmission, where prevention, surveillance, and preparedness are key priorities in previously dengue-free regions. We analyze spatially explicit dengue case data from a large outbreak in Pakistan in 2013 and compare the dynamics of the epidemic to an epidemiological model of dengue virus transmission based on climate and mobility data from ∼40 million mobile phone subscribers. We find that mobile phone-based mobility estimates predict the geographic spread and timing of epidemics in both recently epidemic and emerging locations. We combine transmission suitability maps with estimates of seasonal dengue virus importation to generate fine-scale dynamic risk maps with direct application to dengue containment and epidemic preparedness. PMID:26351662

Historical contingency and ecological determinism interact to prime speciation in sticklebacks, Gasterosteus.

PubMed Central

Taylor, E B; McPhail, J D

2000-01-01

Historical contingency and determinism are often cast as opposing paradigms under which evolutionary diversification operates. It may be, however, that both factors act together to promote evolutionary divergence, although there are few examples of such interaction in nature. We tested phylogenetic predictions of an explicit historical model of divergence (double invasions of freshwater by marine ancestors) in sympatric species of three-spined sticklebacks (Gasterosteus aculeatus) where determinism has been implicated as an important factor driving evolutionary novelty. Microsatellite DNA variation at six loci revealed relatively low genetic variation in freshwater populations, supporting the hypothesis that they were derived by colonization of freshwater by more diverse marine ancestors. Phylogenetic and genetic distance analyses suggested that pairs of sympatric species have evolved multiple times, further implicating determinism as a factor in speciation. Our data also supported predictions based on the hypothesis that the evolution of sympatric species was contingent upon 'double invasions' of postglacial lakes by ancestral marine sticklebacks. Sympatric sticklebacks, therefore, provide an example of adaptive radiation by determinism contingent upon historical conditions promoting unique ecological interactions, and illustrate how contingency and determinism may interact to generate geographical variation in species diversity PMID:11133026

Environmental Impacts of Future Urban Deployment of Electric Vehicles: Assessment Framework and Case Study of Copenhagen for 2016-2030.

PubMed

Bohnes, Florence A; Gregg, Jay S; Laurent, Alexis

2017-12-05

To move toward environmentally sustainable transport systems, electric vehicles (EVs) are increasingly seen as viable alternatives to internal combustion vehicles (ICVs). To ensure effectiveness of such deployment, holistic assessments of environmental impacts can help decision-makers determine optimized urban strategies in a long-term perspective. However, explicit guidance and conduct of such assessments are currently missing. Here, we therefore propose a framework using life cycle assessment that enables the quantification of environmental impacts of a transport system at full urban scale from a fleet-based, foresight perspective. The analysis of the passenger car fleet development in the city of Copenhagen for the years 2016-2030 is used as a proof-of-concept. We modeled and compared five powertrain technologies, and we assessed four fleet-based scenarios for the entire city. Our results showed relative environmental benefits from range-extended and fuel-cell EVs over ICVs and standard EVs. These results were found to be sensitive to local settings, like electricity grid mix, which could alter the relative environmental performances across EV technologies. The comprehensive framework developed here can be applied to other geographic areas and contexts to assess the environmental sustainability of transport systems.

Developing collaborative classifiers using an expert-based model

USGS Publications Warehouse

Mountrakis, G.; Watts, R.; Luo, L.; Wang, Jingyuan

2009-01-01

This paper presents a hierarchical, multi-stage adaptive strategy for image classification. We iteratively apply various classification methods (e.g., decision trees, neural networks), identify regions of parametric and geographic space where accuracy is low, and in these regions, test and apply alternate methods repeating the process until the entire image is classified. Currently, classifiers are evaluated through human input using an expert-based system; therefore, this paper acts as the proof of concept for collaborative classifiers. Because we decompose the problem into smaller, more manageable sub-tasks, our classification exhibits increased flexibility compared to existing methods since classification methods are tailored to the idiosyncrasies of specific regions. A major benefit of our approach is its scalability and collaborative support since selected low-accuracy classifiers can be easily replaced with others without affecting classification accuracy in high accuracy areas. At each stage, we develop spatially explicit accuracy metrics that provide straightforward assessment of results by non-experts and point to areas that need algorithmic improvement or ancillary data. Our approach is demonstrated in the task of detecting impervious surface areas, an important indicator for human-induced alterations to the environment, using a 2001 Landsat scene from Las Vegas, Nevada. ?? 2009 American Society for Photogrammetry and Remote Sensing.

Chromosome inversions and ecological plasticity in the main African malaria mosquitoes

PubMed Central

Ayala, Diego; Acevedo, Pelayo; Pombi, Marco; Dia, Ibrahima; Boccolini, Daniela; Costantini, Carlo; Simard, Frédéric; Fontenille, Didier

2017-01-01

Chromosome inversions have fascinated the scientific community, mainly because of their role in the rapid adaption of different taxa to changing environments. However, the ecological traits linked to chromosome inversions have been poorly studied. Here, we investigated the roles played by 23 chromosome inversions in the adaptation of the four major African malaria mosquitoes to local environments in Africa. We studied their distribution patterns by using spatially explicit modeling and characterized the ecogeographical determinants of each inversion range. We then performed hierarchical clustering and constrained ordination analyses to assess the spatial and ecological similarities among inversions. Our results show that most inversions are environmentally structured, suggesting that they are actively involved in processes of local adaptation. Some inversions exhibited similar geographical patterns and ecological requirements among the four mosquito species, providing evidence for parallel evolution. Conversely, common inversion polymorphisms between sibling species displayed divergent ecological patterns, suggesting that they might have a different adaptive role in each species. These results are in agreement with the finding that chromosomal inversions play a role in Anopheles ecotypic adaptation. This study establishes a strong ecological basis for future genome-based analyses to elucidate the genetic mechanisms of local adaptation in these four mosquitoes. PMID:28071788

Spin-orbit splitted excited states using explicitly-correlated equation-of-motion coupled-cluster singles and doubles eigenvectors

NASA Astrophysics Data System (ADS)

Bokhan, Denis; Trubnikov, Dmitrii N.; Perera, Ajith; Bartlett, Rodney J.

2018-04-01

An explicitly-correlated method of calculation of excited states with spin-orbit couplings, has been formulated and implemented. Developed approach utilizes left and right eigenvectors of equation-of-motion coupled-cluster model, which is based on the linearly approximated explicitly correlated coupled-cluster singles and doubles [CCSD(F12)] method. The spin-orbit interactions are introduced by using the spin-orbit mean field (SOMF) approximation of the Breit-Pauli Hamiltonian. Numerical tests for several atoms and molecules show good agreement between explicitly-correlated results and the corresponding values, calculated in complete basis set limit (CBS); the highly-accurate excitation energies can be obtained already at triple- ζ level.

Genetic GIScience: Toward a Place-Based Synthesis of the Genome, Exposome, and Behavome

PubMed Central

Jacquez, Geoffrey M.; Sabel, Clive E.; Shi, Chen

2015-01-01

The exposome, defined as the totality of an individual’s exposures over the life course, is a seminal concept in the environmental health sciences. Although inherently geographic, the exposome as yet is unfamiliar to many geographers. This article proposes a place-based synthesis, genetic geographic information science (Genetic GISc) that is founded on the exposome, genome+ and behavome. It provides an improved understanding of human health in relation to biology (the genome+), environmental exposures (the exposome), and their social, societal and behavioral determinants (the behavome). Genetic GISc poses three key needs: First, a mathematical foundation for emergent theory; Second, process-based models that bridge biological and geographic scales; Third, biologically plausible estimates of space-time disease lags. Compartmental models are a possible solution; this article develops two models using pancreatic cancer as an exemplar. The first models carcinogenesis based on the cascade of mutations and cellular changes that lead to metastatic cancer. The second models cancer stages by diagnostic criteria. These provide empirical estimates of the distribution of latencies in cellular states and disease stages, and maps of the burden of yet to be diagnosed disease. This approach links our emerging knowledge of genomics to cancer progression at the cellular level, to individuals and their cancer stage at diagnosis, to geographic distributions of cancer in extant populations. These methodological developments and exemplar provide the basis for a new synthesis in health geography: genetic geographic information science. PMID:26339073

Heavy-light mesons in chiral AdS/QCD

NASA Astrophysics Data System (ADS)

Liu, Yizhuang; Zahed, Ismail

2017-06-01

We discuss a minimal holographic model for the description of heavy-light and light mesons with chiral symmetry, defined in a slab of AdS space. The model consists of a pair of chiral Yang-Mills and tachyon fields with specific boundary conditions that break spontaneously chiral symmetry in the infrared. The heavy-light spectrum and decay constants are evaluated explicitly. In the heavy mass limit the model exhibits both heavy-quark and chiral symmetry and allows for the explicit derivation of the one-pion axial couplings to the heavy-light mesons.

Nonminimally coupled massive scalar field in a 2D black hole: Exactly solvable model

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

Frolov, V.; Zelnikov, A.

2001-06-15

We study a nonminimal massive scalar field in the background of a two-dimensional black hole spacetime. We consider the black hole which is the solution of the 2D dilaton gravity derived from string-theoretical models. We find an explicit solution in a closed form for all modes and the Green function of the scalar field with an arbitrary mass and a nonminimal coupling to the curvature. Greybody factors, the Hawking radiation, and 2>{sup ren} are calculated explicitly for this exactly solvable model.

Test-Case Generation using an Explicit State Model Checker Final Report

NASA Technical Reports Server (NTRS)

Heimdahl, Mats P. E.; Gao, Jimin

2003-01-01

In the project 'Test-Case Generation using an Explicit State Model Checker' we have extended an existing tools infrastructure for formal modeling to export Java code so that we can use the NASA Ames tool Java Pathfinder (JPF) for test case generation. We have completed a translator from our source language RSML(exp -e) to Java and conducted initial studies of how JPF can be used as a testing tool. In this final report, we provide a detailed description of the translation approach as implemented in our tools.

Optimal weighted combinatorial forecasting model of QT dispersion of ECGs in Chinese adults.

PubMed

Wen, Zhang; Miao, Ge; Xinlei, Liu; Minyi, Cen

2016-07-01

This study aims to provide a scientific basis for unifying the reference value standard of QT dispersion of ECGs in Chinese adults. Three predictive models including regression model, principal component model, and artificial neural network model are combined to establish the optimal weighted combination model. The optimal weighted combination model and single model are verified and compared. Optimal weighted combinatorial model can reduce predicting risk of single model and improve the predicting precision. The reference value of geographical distribution of Chinese adults' QT dispersion was precisely made by using kriging methods. When geographical factors of a particular area are obtained, the reference value of QT dispersion of Chinese adults in this area can be estimated by using optimal weighted combinatorial model and reference value of the QT dispersion of Chinese adults anywhere in China can be obtained by using geographical distribution figure as well.

Population-Based Analysis and Projections of Liver Supply Under Redistricting.

PubMed

Parikh, Neehar D; Marrero, Wesley J; Sonnenday, Christopher J; Lok, Anna S; Hutton, David W; Lavieri, Mariel S

2017-09-01

To reduce the geographic heterogeneity in liver transplant allocation, the United Network of Organ Sharing has proposed redistricting, which is impacted by both donor supply and liver transplantation demand. We aimed to determine the impact of demographic changes on the redistricting proposal and characterize causes behind geographic heterogeneity in donor supply. We analyzed adult donors from 2002 to 2014 from the United Network of Organ Sharing database and calculated regional liver donation and utilization stratified by age, race, and body mass index. We used US population data to make regional projections of available donors from 2016 to 2025, incorporating the proposed 8-region redistricting plan. We used donors/100 000 population age 18 to 84 years (D/100K) as a measure of equity. We calculated a coefficient of variation (standard deviation/mean) for each regional model. We performed an exploratory analysis where we used national rates of donation, utilization and both for each regional model. The overall projected D/100K will decrease from 2.53 to 2.49 from 2016 to 2025. The coefficient of variation in 2016 is expected to be 20.3% in the 11-region model and 13.2% in the 8-region model. We found that standardizing regional donation and utilization rates would reduce geographic heterogeneity to 4.9% in the 8-region model and 4.6% in the 11-region model. The 8-region allocation model will reduce geographic variation in donor supply to a significant extent; however, we project that geographic disparity will marginally increase over time. Though challenging, interventions to better standardize donation and utilization rates would be impactful in reducing geographic heterogeneity in organ supply.

An evaluation of the relations between flow regime components, stream characteristics, species traits and meta-demographic rates of warmwater stream fishes: Implications for aquatic resource management

USGS Publications Warehouse

Peterson, James T.; Shea, C.P.

2015-01-01

Fishery biologists are increasingly recognizing the importance of considering the dynamic nature of streams when developing streamflow policies. Such approaches require information on how flow regimes influence the physical environment and how those factors, in turn, affect species-specific demographic rates. A more cost-effective alternative could be the use of dynamic occupancy models to predict how species are likely to respond to changes in flow. To appraise the efficacy of this approach, we evaluated relative support for hypothesized effects of seasonal streamflow components, stream channel characteristics, and fish species traits on local extinction, colonization, and recruitment (meta-demographic rates) of stream fishes. We used 4 years of seasonal fish collection data from 23 streams to fit multistate, multiseason occupancy models for 42 fish species in the lower Flint River Basin, Georgia. Modelling results suggested that meta-demographic rates were influenced by streamflows, particularly short-term (10-day) flows. Flow effects on meta-demographic rates also varied with stream size, channel morphology, and fish species traits. Small-bodied species with generalized life-history characteristics were more resilient to flow variability than large-bodied species with specialized life-history characteristics. Using this approach, we simplified the modelling framework, thereby facilitating the development of dynamic, spatially explicit evaluations of the ecological consequences of water resource development activities over broad geographic areas. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.

Mapping Regional Impervious Surface Distribution from Night Time Light: The Variability across Global Cities

NASA Astrophysics Data System (ADS)

Lin, M.; Yang, Z.; Park, H.; Qian, S.; Chen, J.; Fan, P.

2017-12-01

Impervious surface area (ISA) has become an important indicator for studying urban environments, but mapping ISA at the regional or global scale is still challenging due to the complexity of impervious surface features. The Defense Meteorological Satellite Program's Operational Linescan System (DMSP-OLS) nighttime light data is (NTL) and Resolution Imaging Spectroradiometer (MODIS) are the major remote sensing data source for regional ISA mapping. A single regression relationship between fractional ISA and NTL or various index derived based on NTL and MODIS vegetation index (NDVI) data was established in many previous studies for regional ISA mapping. However, due to the varying geographical, climatic, and socio-economic characteristics of different cities, the same regression relationship may vary significantly across different cities in the same region in terms of both fitting performance (i.e. R2) and the rate of change (Slope). In this study, we examined the regression relationship between fractional ISA and Vegetation Adjusted Nighttime light Urban Index (VANUI) for 120 randomly selected cities around the world with a multilevel regression model. We found that indeed there is substantial variability of both the R2 (0.68±0.29) and slopes (0.64±0.40) among individual regressions, which suggests that multilevel/hierarchical models are needed for accuracy improvement of future regional ISA mapping .Further analysis also let us find the this substantial variability are affected by climate conditions, socio-economic status, and urban spatial structures. However, all these effects are nonlinear rather than linear, thus could not modeled explicitly in multilevel linear regression models.

Drivers and hotspots of extinction risk in marine mammals.

PubMed

Davidson, Ana D; Boyer, Alison G; Kim, Hwahwan; Pompa-Mansilla, Sandra; Hamilton, Marcus J; Costa, Daniel P; Ceballos, Gerardo; Brown, James H

2012-02-28

The world's oceans are undergoing profound changes as a result of human activities. However, the consequences of escalating human impacts on marine mammal biodiversity remain poorly understood. The International Union for the Conservation of Nature (IUCN) identifies 25% of marine mammals as at risk of extinction, but the conservation status of nearly 40% of marine mammals remains unknown due to insufficient data. Predictive models of extinction risk are crucial to informing present and future conservation needs, yet such models have not been developed for marine mammals. In this paper, we: (i) used powerful machine-learning and spatial-modeling approaches to understand the intrinsic and extrinsic drivers of marine mammal extinction risk; (ii) used this information to predict risk across all marine mammals, including IUCN "Data Deficient" species; and (iii) conducted a spatially explicit assessment of these results to understand how risk is distributed across the world's oceans. Rate of offspring production was the most important predictor of risk. Additional predictors included taxonomic group, small geographic range area, and small social group size. Although the interaction of both intrinsic and extrinsic variables was important in predicting risk, overall, intrinsic traits were more important than extrinsic variables. In addition to the 32 species already on the IUCN Red List, our model identified 15 more species, suggesting that 37% of all marine mammals are at risk of extinction. Most at-risk species occur in coastal areas and in productive regions of the high seas. We identify 13 global hotspots of risk and show how they overlap with human impacts and Marine Protected Areas.

Thriving in the Cold: Glacial Expansion and Post-Glacial Contraction of a Temperate Terrestrial Salamander (Plethodon serratus)

PubMed Central

Newman, Catherine E.; Austin, Christopher C.

2015-01-01

The dynamic geologic history of the southeastern United States has played a major role in shaping the geographic distributions of amphibians in the region. In the phylogeographic literature, the predominant pattern of distribution shifts through time of temperate species is one of contraction during glacial maxima and persistence in refugia. However, the diverse biology and ecology of amphibian species suggest that a “one-size-fits-all” model may be inappropriate. Nearly 10% of amphibian species in the region have a current distribution comprised of multiple disjunct, restricted areas that resemble the shape of Pleistocene refugia identified for other temperate taxa in the literature. Here, we apply genetics and spatially explicit climate analyses to test the hypothesis that the disjunct regions of these species ranges are climatic refugia for species that were more broadly distributed during glacial maxima. We use the salamander Plethodon serratus as a model, as its range consists of four disjunct regions in the Southeast. Phylogenetic results show that P. serratus is comprised of multiple genetic lineages, and the four regions are not reciprocally monophyletic. The Appalachian salamanders form a clade sister to all other P. serratus. Niche and paleodistribution modeling results suggest that P. serratus expanded from the Appalachians during the cooler Last Glacial Maximum and has since been restricted to its current disjunct distribution by a warming climate. These data reject the universal applicability of the glacial contraction model to temperate taxa and reiterate the importance of considering the natural history of individual species. PMID:26132077

Pathogen-Host Associations and Predicted Range Shifts of Human Monkeypox in Response to Climate Change in Central Africa

PubMed Central

Thomassen, Henri A.; Fuller, Trevon; Asefi-Najafabady, Salvi; Shiplacoff, Julia A. G.; Mulembakani, Prime M.; Blumberg, Seth; Johnston, Sara C.; Kisalu, Neville K.; Kinkela, Timothée L.; Fair, Joseph N.; Wolfe, Nathan D.; Shongo, Robert L.; LeBreton, Matthew; Meyer, Hermann; Wright, Linda L.; Muyembe, Jean-Jacques; Buermann, Wolfgang; Okitolonda, Emile; Hensley, Lisa E.; Lloyd-Smith, James O.; Smith, Thomas B.; Rimoin, Anne W.

2013-01-01

Climate change is predicted to result in changes in the geographic ranges and local prevalence of infectious diseases, either through direct effects on the pathogen, or indirectly through range shifts in vector and reservoir species. To better understand the occurrence of monkeypox virus (MPXV), an emerging Orthopoxvirus in humans, under contemporary and future climate conditions, we used ecological niche modeling techniques in conjunction with climate and remote-sensing variables. We first created spatially explicit probability distributions of its candidate reservoir species in Africa's Congo Basin. Reservoir species distributions were subsequently used to model current and projected future distributions of human monkeypox (MPX). Results indicate that forest clearing and climate are significant driving factors of the transmission of MPX from wildlife to humans under current climate conditions. Models under contemporary climate conditions performed well, as indicated by high values for the area under the receiver operator curve (AUC), and tests on spatially randomly and non-randomly omitted test data. Future projections were made on IPCC 4th Assessment climate change scenarios for 2050 and 2080, ranging from more conservative to more aggressive, and representing the potential variation within which range shifts can be expected to occur. Future projections showed range shifts into regions where MPX has not been recorded previously. Increased suitability for MPX was predicted in eastern Democratic Republic of Congo. Models developed here are useful for identifying areas where environmental conditions may become more suitable for human MPX; targeting candidate reservoir species for future screening efforts; and prioritizing regions for future MPX surveillance efforts. PMID:23935820

Population dynamics can be more important than physiological limits for determining range shifts under climate change.

PubMed

Fordham, Damien A; Mellin, Camille; Russell, Bayden D; Akçakaya, Reşit H; Bradshaw, Corey J A; Aiello-Lammens, Matthew E; Caley, Julian M; Connell, Sean D; Mayfield, Stephen; Shepherd, Scoresby A; Brook, Barry W

2013-10-01

Evidence is accumulating that species' responses to climate changes are best predicted by modelling the interaction of physiological limits, biotic processes and the effects of dispersal-limitation. Using commercially harvested blacklip (Haliotis rubra) and greenlip abalone (Haliotis laevigata) as case studies, we determine the relative importance of accounting for interactions among physiology, metapopulation dynamics and exploitation in predictions of range (geographical occupancy) and abundance (spatially explicit density) under various climate change scenarios. Traditional correlative ecological niche models (ENM) predict that climate change will benefit the commercial exploitation of abalone by promoting increased abundances without any reduction in range size. However, models that account simultaneously for demographic processes and physiological responses to climate-related factors result in future (and present) estimates of area of occupancy (AOO) and abundance that differ from those generated by ENMs alone. Range expansion and population growth are unlikely for blacklip abalone because of important interactions between climate-dependent mortality and metapopulation processes; in contrast, greenlip abalone should increase in abundance despite a contraction in AOO. The strongly non-linear relationship between abalone population size and AOO has important ramifications for the use of ENM predictions that rely on metrics describing change in habitat area as proxies for extinction risk. These results show that predicting species' responses to climate change often require physiological information to understand climatic range determinants, and a metapopulation model that can make full use of this data to more realistically account for processes such as local extirpation, demographic rescue, source-sink dynamics and dispersal-limitation. © 2013 John Wiley & Sons Ltd.

Active dispersal in loggerhead sea turtles (Caretta caretta) during the ‘lost years’

PubMed Central

Briscoe, D. K.; Parker, D. M.; Balazs, G. H.; Kurita, M.; Saito, T.; Okamoto, H.; Rice, M.; Polovina, J. J.; Crowder, L. B.

2016-01-01

Highly migratory marine species can travel long distances and across entire ocean basins to reach foraging and breeding grounds, yet gaps persist in our knowledge of oceanic dispersal and habitat use. This is especially true for sea turtles, whose complex life history and lengthy pelagic stage present unique conservation challenges. Few studies have explored how these young at-sea turtles navigate their environment, but advancements in satellite technology and numerical models have shown that active and passive movements are used in relation to open ocean features. Here, we provide the first study, to the best of our knowledge, to simultaneously combine a high-resolution physical forcing ocean circulation model with long-term multi-year tracking data of young, trans-oceanic North Pacific loggerhead sea turtles during their ‘lost years’ at sea. From 2010 to 2014, we compare simulated trajectories of passive transport with empirical data of 1–3 year old turtles released off Japan (29.7–37.5 straight carapace length cm). After several years, the at-sea distribution of simulated current-driven trajectories significantly differed from that of the observed turtle tracks. These results underscore current theories on active dispersal by young oceanic-stage sea turtles and give further weight to hypotheses of juvenile foraging strategies for this species. Such information can also provide critical geographical information for spatially explicit conservation approaches to this endangered population. PMID:27252021

An overview assessment of the effectiveness and global popularity of some methods used in measuring riverbank filtration

NASA Astrophysics Data System (ADS)

Umar, Da'u. Abba; Ramli, Mohammad Firuz; Aris, Ahmad Zaharin; Sulaiman, Wan Nor Azmin; Kura, Nura Umar; Tukur, Abubakar Ibrahim

2017-07-01

This paper presents an overview assessment of the effectiveness and popularity of some methods adopted in measuring river bank filtration (RBF). The review is aim at understanding some of the appropriate methods used in measuring riverbank filtration, their frequencies of use, and their spatial applications worldwide. The most commonly used methods and techniques in riverbank filtration studies are: Geographical Information System (GIS) (site suitability/surface characterization), Geophysical, Pumping Test and borehole logging (sub-surface), Hydrochemical, Geochemical, and Statistical techniques (hydrochemistry of water), Numerical modelling, Tracer techniques and Stable Isotope Approaches (degradation and contaminants attenuation processes). From the summary in Table 1, hydrochemical, numerical modelling and pumping test are the frequently used and popular methods, while geophysical, GIS and statistical techniques are the less attractive. However, many researchers prefer integrated approach especially that riverbank filtration studies involve diverse and interrelated components. In term of spatial popularity and successful implementation of riverbank filtration, it is explicitly clear that the popularity and success of the technology is more pronounced in developed countries like U.S. and most European countries. However, it is gradually gaining ground in Asia and Africa, although it is not far from its infancy state in Africa, where the technology could be more important considering the economic status of the region and its peculiarity when it comes to water resources predicaments.

The evolution of antibiotic resistance in a structured host population.

PubMed

Blanquart, François; Lehtinen, Sonja; Lipsitch, Marc; Fraser, Christophe

2018-06-01

The evolution of antibiotic resistance in opportunistic pathogens such as Streptococcus pneumoniae , Escherichia coli or Staphylococcus aureus is a major public health problem, as infection with resistant strains leads to prolonged hospital stay and increased risk of death. Here, we develop a new model of the evolution of antibiotic resistance in a commensal bacterial population adapting to a heterogeneous host population composed of untreated and treated hosts, and structured in different host classes with different antibiotic use. Examples of host classes include age groups and geographic locations. Explicitly modelling the antibiotic treatment reveals that the emergence of a resistant strain is favoured by more frequent but shorter antibiotic courses, and by higher transmission rates. In addition, in a structured host population, localized transmission in host classes promotes both local adaptation of the bacterial population and the global maintenance of coexistence between sensitive and resistant strains. When transmission rates are heterogeneous across host classes, resistant strains evolve more readily in core groups of transmission. These findings have implications for the better management of antibiotic resistance: reducing the rate at which individuals receive antibiotics is more effective to reduce resistance than reducing the duration of treatment. Reducing the rate of treatment in a targeted class of the host population allows greater reduction in resistance, but determining which class to target is difficult in practice. © 2018 The Authors.

Active dispersal in loggerhead sea turtles (Caretta caretta) during the 'lost years'.

PubMed

Briscoe, D K; Parker, D M; Balazs, G H; Kurita, M; Saito, T; Okamoto, H; Rice, M; Polovina, J J; Crowder, L B

2016-06-15

Highly migratory marine species can travel long distances and across entire ocean basins to reach foraging and breeding grounds, yet gaps persist in our knowledge of oceanic dispersal and habitat use. This is especially true for sea turtles, whose complex life history and lengthy pelagic stage present unique conservation challenges. Few studies have explored how these young at-sea turtles navigate their environment, but advancements in satellite technology and numerical models have shown that active and passive movements are used in relation to open ocean features. Here, we provide the first study, to the best of our knowledge, to simultaneously combine a high-resolution physical forcing ocean circulation model with long-term multi-year tracking data of young, trans-oceanic North Pacific loggerhead sea turtles during their 'lost years' at sea. From 2010 to 2014, we compare simulated trajectories of passive transport with empirical data of 1-3 year old turtles released off Japan (29.7-37.5 straight carapace length cm). After several years, the at-sea distribution of simulated current-driven trajectories significantly differed from that of the observed turtle tracks. These results underscore current theories on active dispersal by young oceanic-stage sea turtles and give further weight to hypotheses of juvenile foraging strategies for this species. Such information can also provide critical geographical information for spatially explicit conservation approaches to this endangered population. © 2016 The Author(s).

Habitat capacity for cougar recolonization in the Upper Great Lakes region.

PubMed

O Neil, Shawn T; Rahn, Kasey C; Bump, Joseph K

2014-01-01

Recent findings indicate that cougars (Puma concolor) are expanding their range into the midwestern United States. Confirmed reports of cougar in Michigan, Minnesota, and Wisconsin have increased dramatically in frequency during the last five years, leading to speculation that cougars may re-establish in the Upper Great Lakes (UGL) region, USA. Recent work showed favorable cougar habitat in northeastern Minnesota, suggesting that the northern forested regions of Michigan and Wisconsin may have similar potential. Recolonization of cougars in the UGL states would have important ecological, social, and political impacts that will require effective management. Using Geographic Information Systems (GIS), we extended a cougar habitat model to Michigan and Wisconsin and incorporated primary prey densities to estimate the capacity of the region to support cougars. Results suggest that approximately 39% (>58,000 km2) of the study area could support cougars, and that there is potential for a population of approximately 500 or more animals. An exploratory validation of this habitat model revealed strong association with 58 verified cougar locations occurring in the study area between 2008 and 2013. Spatially explicit information derived from this study could potentially lead to estimation of a viable population, delineation of possible cougar-human conflict areas, and the targeting of site locations for current monitoring. Understanding predator-prey interactions, interspecific competition, and human-wildlife relationships is becoming increasingly critical as top carnivores continue to recolonize the UGL region.

Spatial Relation Predicates in Topographic Feature Semantics

USGS Publications Warehouse

Varanka, Dalia E.; Caro, Holly K.

2013-01-01

Topographic data are designed and widely used for base maps of diverse applications, yet the power of these information sources largely relies on the interpretive skills of map readers and relational database expert users once the data are in map or geographic information system (GIS) form. Advances in geospatial semantic technology offer data model alternatives for explicating concepts and articulating complex data queries and statements. To understand and enrich the vocabulary of topographic feature properties for semantic technology, English language spatial relation predicates were analyzed in three standard topographic feature glossaries. The analytical approach drew from disciplinary concepts in geography, linguistics, and information science. Five major classes of spatial relation predicates were identified from the analysis; representations for most of these are not widely available. The classes are: part-whole (which are commonly modeled throughout semantic and linked-data networks), geometric, processes, human intention, and spatial prepositions. These are commonly found in the ‘real world’ and support the environmental science basis for digital topographical mapping. The spatial relation concepts are based on sets of relation terms presented in this chapter, though these lists are not prescriptive or exhaustive. The results of this study make explicit the concepts forming a broad set of spatial relation expressions, which in turn form the basis for expanding the range of possible queries for topographical data analysis and mapping.

Implicit and explicit weight bias in a national sample of 4,732 medical students: the medical student CHANGES study.

PubMed

Phelan, Sean M; Dovidio, John F; Puhl, Rebecca M; Burgess, Diana J; Nelson, David B; Yeazel, Mark W; Hardeman, Rachel; Perry, Sylvia; van Ryn, Michelle

2014-04-01

To examine the magnitude of explicit and implicit weight biases compared to biases against other groups; and identify student factors predicting bias in a large national sample of medical students. A web-based survey was completed by 4,732 1st year medical students from 49 medical schools as part of a longitudinal study of medical education. The survey included a validated measure of implicit weight bias, the implicit association test, and 2 measures of explicit bias: a feeling thermometer and the anti-fat attitudes test. A majority of students exhibited implicit (74%) and explicit (67%) weight bias. Implicit weight bias scores were comparable to reported bias against racial minorities. Explicit attitudes were more negative toward obese people than toward racial minorities, gays, lesbians, and poor people. In multivariate regression models, implicit and explicit weight bias was predicted by lower BMI, male sex, and non-Black race. Either implicit or explicit bias was also predicted by age, SES, country of birth, and specialty choice. Implicit and explicit weight bias is common among 1st year medical students, and varies across student factors. Future research should assess implications of biases and test interventions to reduce their impact. Copyright © 2013 The Obesity Society.

Different Mechanisms of Soil Microbial Response to Global Change Result in Different Outcomes in the MIMICS-CN Model

NASA Astrophysics Data System (ADS)

Kyker-Snowman, E.; Wieder, W. R.; Grandy, S.

2017-12-01

Microbial-explicit models of soil carbon (C) and nitrogen (N) cycling have improved upon simulations of C and N stocks and flows at site-to-global scales relative to traditional first-order linear models. However, the response of microbial-explicit soil models to global change factors depends upon which parameters and processes in a model are altered by those factors. We used the MIcrobial-MIneral Carbon Stabilization Model with coupled N cycling (MIMICS-CN) to compare modeled responses to changes in temperature and plant inputs at two previously-modeled sites (Harvard Forest and Kellogg Biological Station). We spun the model up to equilibrium, applied each perturbation, and evaluated 15 years of post-perturbation C and N pools and fluxes. To model the effect of increasing temperatures, we independently examined the impact of decreasing microbial C use efficiency (CUE), increasing the rate of microbial turnover, and increasing Michaelis-Menten kinetic rates of litter decomposition, plus several combinations of the three. For plant inputs, we ran simulations with stepwise increases in metabolic litter, structural litter, whole litter (structural and metabolic), or labile soil C. The cumulative change in soil C or N varied in both sign and magnitude across simulations. For example, increasing kinetic rates of litter decomposition resulted in net releases of both C and N from soil pools, while decreasing CUE produced short-term increases in respiration but long-term accumulation of C in litter pools and shifts in soil C:N as microbial demand for C increased and biomass declined. Given that soil N cycling constrains the response of plant productivity to global change and that soils generate a large amount of uncertainty in current earth system models, microbial-explicit models are a critical opportunity to advance the modeled representation of soils. However, microbial-explicit models must be improved by experiments to isolate the physiological and stoichiometric parameters of soil microbes that shift under global change.

Modelling explicit fracture of nuclear fuel pellets using peridynamics

NASA Astrophysics Data System (ADS)

Mella, R.; Wenman, M. R.

2015-12-01

Three dimensional models of explicit cracking of nuclear fuel pellets for a variety of power ratings have been explored with peridynamics, a non-local, mesh free, fracture mechanics method. These models were implemented in the explicitly integrated molecular dynamics code LAMMPS, which was modified to include thermal strains in solid bodies. The models of fuel fracture, during initial power transients, are shown to correlate with the mean number of cracks observed on the inner and outer edges of the pellet, by experimental post irradiation examination of fuel, for power ratings of 10 and 15 W g-1 UO2. The models of the pellet show the ability to predict expected features such as the mid-height pellet crack, the correct number of radial cracks and initiation and coalescence of radial cracks. This work presents a modelling alternative to empirical fracture data found in many fuel performance codes and requires just one parameter of fracture strain. Weibull distributions of crack numbers were fitted to both numerical and experimental data using maximum likelihood estimation so that statistical comparison could be made. The findings show P-values of less than 0.5% suggesting an excellent agreement between model and experimental distributions.

Aerosol-cloud interactions in a multi-scale modeling framework

NASA Astrophysics Data System (ADS)

Lin, G.; Ghan, S. J.

2017-12-01

Atmospheric aerosols play an important role in changing the Earth's climate through scattering/absorbing solar and terrestrial radiation and interacting with clouds. However, quantification of the aerosol effects remains one of the most uncertain aspects of current and future climate projection. Much of the uncertainty results from the multi-scale nature of aerosol-cloud interactions, which is very challenging to represent in traditional global climate models (GCMs). In contrast, the multi-scale modeling framework (MMF) provides a viable solution, which explicitly resolves the cloud/precipitation in the cloud resolved model (CRM) embedded in the GCM grid column. In the MMF version of community atmospheric model version 5 (CAM5), aerosol processes are treated with a parameterization, called the Explicit Clouds Parameterized Pollutants (ECPP). It uses the cloud/precipitation statistics derived from the CRM to treat the cloud processing of aerosols on the GCM grid. However, this treatment treats clouds on the CRM grid but aerosols on the GCM grid, which is inconsistent with the reality that cloud-aerosol interactions occur on the cloud scale. To overcome the limitation, here, we propose a new aerosol treatment in the MMF: Explicit Clouds Explicit Aerosols (ECEP), in which we resolve both clouds and aerosols explicitly on the CRM grid. We first applied the MMF with ECPP to the Accelerated Climate Modeling for Energy (ACME) model to have an MMF version of ACME. Further, we also developed an alternative version of ACME-MMF with ECEP. Based on these two models, we have conducted two simulations: one with the ECPP and the other with ECEP. Preliminary results showed that the ECEP simulations tend to predict higher aerosol concentrations than ECPP simulations, because of the more efficient vertical transport from the surface to the higher atmosphere but the less efficient wet removal. We also found that the cloud droplet number concentrations are also different between the two simulations due to the difference in the cloud droplet lifetime. Next, we will explore how the ECEP treatment affects the anthropogenic aerosol forcing, particularly the aerosol indirect forcing, by comparing present-day and pre-industrial simulations.

Benchmarking carbon-nitrogen interactions in Earth System Models to observations: An inter-comparison of nitrogen limitation in global land surface models with carbon and nitrogen cycles (CLM-CN and O-CN)

NASA Astrophysics Data System (ADS)

Thomas, R. Q.; Zaehle, S.; Templer, P. H.; Goodale, C. L.

2011-12-01

Predictions of climate change depend on accurately modeling the feedbacks among the carbon cycle, nitrogen cycle, and climate system. Several global land surface models have shown that nitrogen limitation determines how land carbon fluxes respond to rising CO2, nitrogen deposition, and climate change, thereby influencing predictions of climate change. However, the magnitude of the carbon-nitrogen-climate feedbacks varies considerably by model, leading to critical and timely questions of why they differ and how they compare to field observations. To address these questions, we initiated a model inter-comparison of spatial patterns and drivers of nitrogen limitation. The experiment assessed the regional consequences of sustained nitrogen additions in a set of 25-year global nitrogen fertilization simulations. The model experiments were designed to cover effects from small changes in nitrogen inputs associated with plausible increases in nitrogen deposition to large changes associated with field-based nitrogen fertilization experiments. The analyses of model simulations included assessing the geographically varying degree of nitrogen limitation on plant and soil carbon cycling and the mechanisms underlying model differences. Here, we present results from two global land-surface models (CLM-CN and O-CN) with differing approaches to modeling carbon-nitrogen interactions. The predictions from each model were compared to a set of globally distributed observational data that includes nitrogen fertilization experiments, 15N tracer studies, small catchment nitrogen input-output studies, and syntheses across nitrogen deposition gradients. Together these datasets test many aspects of carbon-nitrogen coupling and are able to differentiate between the two models. Overall, this study is the first to explicitly benchmark carbon and nitrogen interactions in Earth System Models using a range of observations and is a foundation for future inter-comparisons.

ORILAM, a three-moment lognormal aerosol scheme for mesoscale atmospheric model: Online coupling into the Meso-NH-C model and validation on the Escompte campaign

NASA Astrophysics Data System (ADS)

Tulet, Pierre; Crassier, Vincent; Cousin, Frederic; Suhre, Karsten; Rosset, Robert

2005-09-01

Classical aerosol schemes use either a sectional (bin) or lognormal approach. Both approaches have particular capabilities and interests: the sectional approach is able to describe every kind of distribution, whereas the lognormal one makes assumption of the distribution form with a fewer number of explicit variables. For this last reason we developed a three-moment lognormal aerosol scheme named ORILAM to be coupled in three-dimensional mesoscale or CTM models. This paper presents the concept and hypothesis of a range of aerosol processes such as nucleation, coagulation, condensation, sedimentation, and dry deposition. One particular interest of ORILAM is to keep explicit the aerosol composition and distribution (mass of each constituent, mean radius, and standard deviation of the distribution are explicit) using the prediction of three-moment (m0, m3, and m6). The new model was evaluated by comparing simulations to measurements from the Escompte campaign and to a previously published aerosol model. The numerical cost of the lognormal mode is lower than two bins of the sectional one.

Determinants of Dentists' Geographic Distribution.

ERIC Educational Resources Information Center

Beazoglou, Tryfon J.; And Others

1992-01-01

A model for explaining the geographic distribution of dentists' practice locations is presented and applied to particular market areas in Connecticut. Results show geographic distribution is significantly related to a few key variables, including demography, disposable income, and housing prices. Implications for helping students make practice…

A spatiotemporal data model for incorporating time in geographic information systems (GEN-STGIS)

NASA Astrophysics Data System (ADS)

Narciso, Flor Eugenia

Temporal Geographic Information Systems (TGIS) is a new technology, which is being developed to work with Geographic Information Systems (GIS) that deal with geographic phenomena that change over time. The capabilities of TGIS depend on the underlying data model. However, a literature review of current spatiotemporal GIS data models has shown that they are not adequate for managing time when representing temporal data. In addition, the majority of these data models have been designed to support the requirements of specific-purpose applications. In an effort to resolve this problem, the related literature has been explored. A comparative investigation of the current spatiotemporal GIS data models has been made to identify their characteristics, advantages and disadvantages, similarities and differences, and to determine why they do not work adequately. A new object-oriented General-purpose Spatiotemporal GIS (GEN-STGIS) data model is proposed here. This model provides better representation, storage and management of data related to geographic phenomena that change over time and overcomes some of the problems detected in the reviewed data models. The proposed data model has four key benefits. First, it provides the capabilities of a standard vector-based GIS embedded in the 2-D Euclidean space. Second, it includes the two temporal dimensions, valid time and transaction time, supported by temporal databases. Third, it inherits, from the object oriented approach, the flexibility, modularity and ability to handle the complexities introduced by spatial and temporal dimensions. Fourth, it improves the geographic query capabilities of current TGIS with the introduction of the concept of bounding box while providing temporal and spatiotemporal query capabilities. The data model is then evaluated in order to assess its strengths and weaknesses as a spatiotemporal GIS data model, and to determine how well the model satisfies the requirements imposed by TGIS applications. The practicality of the data model is demonstrated by the creation of a TGIS example and the partial implementation of the model using the POET Java software for developing the object-oriented database. the object-oriented database.

Cancer risks near nuclear facilities: the importance of research design and explicit study hypotheses.

PubMed

Wing, Steve; Richardson, David B; Hoffmann, Wolfgang

2011-04-01

In April 2010, the U.S. Nuclear Regulatory Commission asked the National Academy of Sciences to update a 1990 study of cancer risks near nuclear facilities. Prior research on this topic has suffered from problems in hypothesis formulation and research design. We review epidemiologic principles used in studies of generic exposure-response associations and in studies of specific sources of exposure. We then describe logical problems with assumptions, formation of testable hypotheses, and interpretation of evidence in previous research on cancer risks near nuclear facilities. Advancement of knowledge about cancer risks near nuclear facilities depends on testing specific hypotheses grounded in physical and biological mechanisms of exposure and susceptibility while considering sample size and ability to adequately quantify exposure, ascertain cancer cases, and evaluate plausible confounders. Next steps in advancing knowledge about cancer risks near nuclear facilities require studies of childhood cancer incidence, focus on in utero and early childhood exposures, use of specific geographic information, and consideration of pathways for transport and uptake of radionuclides. Studies of cancer mortality among adults, cancers with long latencies, large geographic zones, and populations that reside at large distances from nuclear facilities are better suited for public relations than for scientific purposes.

Spatial and temporal drivers of phenotypic diversity in polymorphic snakes.

PubMed

Cox, Christian L; Davis Rabosky, Alison R

2013-08-01

Color polymorphism in natural populations presents an ideal opportunity to study the evolutionary drivers of phenotypic diversity. Systems with striking spatial, temporal, and qualitative variation in color can be leveraged to study the mechanisms promoting the distribution of different types of variation in nature. We used the highly polymorphic ground snake (Sonora semiannulata), a putative coral snake mimic with both cryptic and conspicuous morphs, to compare patterns of neutral genetic variation and variation over space and time in color polymorphism to investigate the mechanistic drivers of phenotypic variation across scales. We found that strong selection promotes color polymorphism across spatial and temporal scales, with morph frequencies differing markedly between juvenile and adult age classes within a single population, oscillating over time within multiple populations, and varying drastically over the landscape despite minimal population genetic structure. However, we found no evidence that conspicuousness of morphs was related to which color pattern was favored by selection or to any geographic factors, including sympatry with coral snakes. We suggest that complex patterns of phenotypic variation in polymorphic systems may be a fundamental outcome of the conspicuousness of morphs and that explicit tests of temporal and geographic variation are critical to the interpretation of conspicuousness and mimicry.