Spatial working memory interferes with explicit, but not probabilistic cuing of spatial attention.

PubMed

Won, Bo-Yeong; Jiang, Yuhong V

2015-05-01

Recent empirical and theoretical work has depicted a close relationship between visual attention and visual working memory. For example, rehearsal in spatial working memory depends on spatial attention, whereas adding a secondary spatial working memory task impairs attentional deployment in visual search. These findings have led to the proposal that working memory is attention directed toward internal representations. Here, we show that the close relationship between these 2 constructs is limited to some but not all forms of spatial attention. In 5 experiments, participants held color arrays, dot locations, or a sequence of dots in working memory. During the memory retention interval, they performed a T-among-L visual search task. Crucially, the probable target location was cued either implicitly through location probability learning or explicitly with a central arrow or verbal instruction. Our results showed that whereas imposing a visual working memory load diminished the effectiveness of explicit cuing, it did not interfere with probability cuing. We conclude that spatial working memory shares similar mechanisms with explicit, goal-driven attention but is dissociated from implicitly learned attention. (c) 2015 APA, all rights reserved).

Spatial working memory interferes with explicit, but not probabilistic cuing of spatial attention

PubMed Central

Won, Bo-Yeong; Jiang, Yuhong V.

2014-01-01

Recent empirical and theoretical work has depicted a close relationship between visual attention and visual working memory. For example, rehearsal in spatial working memory depends on spatial attention, whereas adding a secondary spatial working memory task impairs attentional deployment in visual search. These findings have led to the proposal that working memory is attention directed toward internal representations. Here we show that the close relationship between these two constructs is limited to some but not all forms of spatial attention. In five experiments, participants held color arrays, dot locations, or a sequence of dots in working memory. During the memory retention interval they performed a T-among-L visual search task. Crucially, the probable target location was cued either implicitly through location probability learning, or explicitly with a central arrow or verbal instruction. Our results showed that whereas imposing a visual working memory load diminished the effectiveness of explicit cuing, it did not interfere with probability cuing. We conclude that spatial working memory shares similar mechanisms with explicit, goal-driven attention but is dissociated from implicitly learned attention. PMID:25401460

Spatial modeling of cell signaling networks.

PubMed

Cowan, Ann E; Moraru, Ion I; Schaff, James C; Slepchenko, Boris M; Loew, Leslie M

2012-01-01

The shape of a cell, the sizes of subcellular compartments, and the spatial distribution of molecules within the cytoplasm can all control how molecules interact to produce a cellular behavior. This chapter describes how these spatial features can be included in mechanistic mathematical models of cell signaling. The Virtual Cell computational modeling and simulation software is used to illustrate the considerations required to build a spatial model. An explanation of how to appropriately choose between physical formulations that implicitly or explicitly account for cell geometry and between deterministic versus stochastic formulations for molecular dynamics is provided, along with a discussion of their respective strengths and weaknesses. As a first step toward constructing a spatial model, the geometry needs to be specified and associated with the molecules, reactions, and membrane flux processes of the network. Initial conditions, diffusion coefficients, velocities, and boundary conditions complete the specifications required to define the mathematics of the model. The numerical methods used to solve reaction-diffusion problems both deterministically and stochastically are then described and some guidance is provided in how to set up and run simulations. A study of cAMP signaling in neurons ends the chapter, providing an example of the insights that can be gained in interpreting experimental results through the application of spatial modeling. Copyright © 2012 Elsevier Inc. All rights reserved.

3D Printing Variable Stiffness Foams Using Viscous Thread Instability

NASA Astrophysics Data System (ADS)

Lipton, Jeffrey I.; Lipson, Hod

2016-08-01

Additive manufacturing of cellular structures has numerous applications ranging from fabrication of biological scaffolds and medical implants, to mechanical weight reduction and control over mechanical properties. Various additive manufacturing processes have been used to produce open regular cellular structures limited only by the resolution of the printer. These efforts have focused on printing explicitly designed cells or explicitly planning offsets between strands. Here we describe a technique for producing cellular structures implicitly by inducing viscous thread instability when extruding material. This process allows us to produce complex cellular structures at a scale that is finer than the native resolution of the printer. We demonstrate tunable effective elastic modulus and density that span two orders of magnitude. Fine grained cellular structures allow for fabrication of foams for use in a wide range of fields ranging from bioengineering, to robotics to food printing.

Modeling trends from North American Breeding Bird Survey data: a spatially explicit approach

USGS Publications Warehouse

Bled, Florent; Sauer, John R.; Pardieck, Keith L.; Doherty, Paul; Royle, J. Andy

2013-01-01

Population trends, defined as interval-specific proportional changes in population size, are often used to help identify species of conservation interest. Efficient modeling of such trends depends on the consideration of the correlation of population changes with key spatial and environmental covariates. This can provide insights into causal mechanisms and allow spatially explicit summaries at scales that are of interest to management agencies. We expand the hierarchical modeling framework used in the North American Breeding Bird Survey (BBS) by developing a spatially explicit model of temporal trend using a conditional autoregressive (CAR) model. By adopting a formal spatial model for abundance, we produce spatially explicit abundance and trend estimates. Analyses based on large-scale geographic strata such as Bird Conservation Regions (BCR) can suffer from basic imbalances in spatial sampling. Our approach addresses this issue by providing an explicit weighting based on the fundamental sample allocation unit of the BBS. We applied the spatial model to three species from the BBS. Species have been chosen based upon their well-known population change patterns, which allows us to evaluate the quality of our model and the biological meaning of our estimates. We also compare our results with the ones obtained for BCRs using a nonspatial hierarchical model (Sauer and Link 2011). Globally, estimates for mean trends are consistent between the two approaches but spatial estimates provide much more precise trend estimates in regions on the edges of species ranges that were poorly estimated in non-spatial analyses. Incorporating a spatial component in the analysis not only allows us to obtain relevant and biologically meaningful estimates for population trends, but also enables us to provide a flexible framework in order to obtain trend estimates for any area.

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...

3D Printing Variable Stiffness Foams Using Viscous Thread Instability

PubMed Central

Lipton, Jeffrey I.; Lipson, Hod

2016-01-01

Additive manufacturing of cellular structures has numerous applications ranging from fabrication of biological scaffolds and medical implants, to mechanical weight reduction and control over mechanical properties. Various additive manufacturing processes have been used to produce open regular cellular structures limited only by the resolution of the printer. These efforts have focused on printing explicitly designed cells or explicitly planning offsets between strands. Here we describe a technique for producing cellular structures implicitly by inducing viscous thread instability when extruding material. This process allows us to produce complex cellular structures at a scale that is finer than the native resolution of the printer. We demonstrate tunable effective elastic modulus and density that span two orders of magnitude. Fine grained cellular structures allow for fabrication of foams for use in a wide range of fields ranging from bioengineering, to robotics to food printing. PMID:27503148

Deciphering the roles of acyl-CoA-binding proteins in plant cells.

PubMed

Lung, Shiu-Cheung; Chye, Mee-Len

2016-09-01

Lipid trafficking is vital for metabolite exchange and signal communications between organelles and endomembranes. Acyl-CoA-binding proteins (ACBPs) are involved in the intracellular transport, protection, and pool formation of acyl-CoA esters, which are important intermediates and regulators in lipid metabolism and cellular signaling. In this review, we highlight recent advances in our understanding of plant ACBP families from a cellular and developmental perspective. Plant ACBPs have been extensively studied in Arabidopsis thaliana (a dicot) and to a lesser extent in Oryza sativa (a monocot). Thus far, they have been detected in the plasma membrane, vesicles, endoplasmic reticulum, Golgi apparatus, apoplast, cytosol, nuclear periphery, and peroxisomes. In combination with biochemical and molecular genetic tools, the widespread subcellular distribution of respective ACBP members has been explicitly linked to their functions in lipid metabolism during development and in response to stresses. At the cellular level, strong expression of specific ACBP homologs in specialized cells, such as embryos, stem epidermis, guard cells, male gametophytes, and phloem sap, is of relevance to their corresponding distinct roles in organ development and stress responses. Other interesting patterns in their subcellular localization and spatial expression that prompt new directions in future investigations are discussed.

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.

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.

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...

The organisation of spatial and temporal relations in memory.

PubMed

Rondina, Renante; Curtiss, Kaitlin; Meltzer, Jed A; Barense, Morgan D; Ryan, Jennifer D

2017-04-01

Episodic memories are comprised of details of "where" and "when"; spatial and temporal relations, respectively. However, evidence from behavioural, neuropsychological, and neuroimaging studies has provided mixed interpretations about how memories for spatial and temporal relations are organised-they may be hierarchical, fully interactive, or independent. In the current study, we examined the interaction of memory for spatial and temporal relations. Using explicit reports and eye-tracking, we assessed younger and older adults' memory for spatial and temporal relations of objects that were presented singly across time in unique spatial locations. Explicit change detection of spatial relations was affected by a change in temporal relations, but explicit change detection of temporal relations was not affected by a change in spatial relations. Younger and older adults showed eye movement evidence of incidental memory for temporal relations, but only younger adults showed eye movement evidence of incidental memory for spatial relations. Together, these findings point towards a hierarchical organisation of relational memory. The implications of these findings are discussed in the context of the neural mechanisms that may support such a hierarchical organisation of memory.

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...

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.

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 ...

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...

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...

From water use to water scarcity footprinting in environmentally extended input-output analysis.

PubMed

Ridoutt, Bradley George; Hadjikakou, Michalis; Nolan, Martin; Bryan, Brett A

2018-05-18

Environmentally extended input-output analysis (EEIOA) supports environmental policy by quantifying how demand for goods and services leads to resource use and emissions across the economy. However, some types of resource use and emissions require spatially-explicit impact assessment for meaningful interpretation, which is not possible in conventional EEIOA. For example, water use in locations of scarcity and abundance is not environmentally equivalent. Opportunities for spatially-explicit impact assessment in conventional EEIOA are limited because official input-output tables tend to be produced at the scale of political units which are not usually well aligned with environmentally relevant spatial units. In this study, spatially-explicit water scarcity factors and a spatially disaggregated Australian water use account were used to develop water scarcity extensions that were coupled with a multi-regional input-output model (MRIO). The results link demand for agricultural commodities to the problem of water scarcity in Australia and globally. Important differences were observed between the water use and water scarcity footprint results, as well as the relative importance of direct and indirect water use, with significant implications for sustainable production and consumption-related policies. The approach presented here is suggested as a feasible general approach for incorporating spatially-explicit impact assessment in EEIOA.

Exploring the effect of the spatial scale of fishery management.

PubMed

Takashina, Nao; Baskett, Marissa L

2016-02-07

For any spatially explicit management, determining the appropriate spatial scale of management decisions is critical to success at achieving a given management goal. Specifically, managers must decide how much to subdivide a given managed region: from implementing a uniform approach across the region to considering a unique approach in each of one hundred patches and everything in between. Spatially explicit approaches, such as the implementation of marine spatial planning and marine reserves, are increasingly used in fishery management. Using a spatially explicit bioeconomic model, we quantify how the management scale affects optimal fishery profit, biomass, fishery effort, and the fraction of habitat in marine reserves. We find that, if habitats are randomly distributed, the fishery profit increases almost linearly with the number of segments. However, if habitats are positively autocorrelated, then the fishery profit increases with diminishing returns. Therefore, the true optimum in management scale given cost to subdivision depends on the habitat distribution pattern. Copyright © 2015 Elsevier Ltd. All rights reserved.

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...

On the topological sensitivity of cellular automata

NASA Astrophysics Data System (ADS)

Baetens, Jan M.; De Baets, Bernard

2011-06-01

Ever since the conceptualization of cellular automata (CA), much attention has been paid to the dynamical properties of these discrete dynamical systems, and, more in particular, to their sensitivity to the initial condition from which they are evolved. Yet, the sensitivity of CA to the topology upon which they are based has received only minor attention, such that a clear insight in this dependence is still lacking and, furthermore, a quantification of this so-called topological sensitivity has not yet been proposed. The lack of attention for this issue is rather surprising since CA are spatially explicit, which means that their dynamics is directly affected by their topology. To overcome these shortcomings, we propose topological Lyapunov exponents that measure the divergence of two close trajectories in phase space originating from a topological perturbation, and we relate them to a measure grasping the sensitivity of CA to their topology that relies on the concept of topological derivatives, which is introduced in this paper. The validity of the proposed methodology is illustrated for the 256 elementary CA and for a family of two-state irregular totalistic CA.

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...

Spatially explicit shallow landslide susceptibility mapping over large areas

Treesearch

Dino Bellugi; William E. Dietrich; Jonathan Stock; Jim McKean; Brian Kazian; Paul Hargrove

2011-01-01

Recent advances in downscaling climate model precipitation predictions now yield spatially explicit patterns of rainfall that could be used to estimate shallow landslide susceptibility over large areas. In California, the United States Geological Survey is exploring community emergency response to the possible effects of a very large simulated storm event and to do so...

Evaluating spatially explicit burn probabilities for strategic fire management planning

Treesearch

C. Miller; M.-A. Parisien; A. A. Ager; M. A. Finney

2008-01-01

Spatially explicit information on the probability of burning is necessary for virtually all strategic fire and fuels management planning activities, including conducting wildland fire risk assessments, optimizing fuel treatments, and prevention planning. Predictive models providing a reliable estimate of the annual likelihood of fire at each point on the landscape have...

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...

Multi-scale approaches for high-speed imaging and analysis of large neural populations

PubMed Central

Ahrens, Misha B.; Yuste, Rafael; Peterka, Darcy S.; Paninski, Liam

2017-01-01

Progress in modern neuroscience critically depends on our ability to observe the activity of large neuronal populations with cellular spatial and high temporal resolution. However, two bottlenecks constrain efforts towards fast imaging of large populations. First, the resulting large video data is challenging to analyze. Second, there is an explicit tradeoff between imaging speed, signal-to-noise, and field of view: with current recording technology we cannot image very large neuronal populations with simultaneously high spatial and temporal resolution. Here we describe multi-scale approaches for alleviating both of these bottlenecks. First, we show that spatial and temporal decimation techniques based on simple local averaging provide order-of-magnitude speedups in spatiotemporally demixing calcium video data into estimates of single-cell neural activity. Second, once the shapes of individual neurons have been identified at fine scale (e.g., after an initial phase of conventional imaging with standard temporal and spatial resolution), we find that the spatial/temporal resolution tradeoff shifts dramatically: after demixing we can accurately recover denoised fluorescence traces and deconvolved neural activity of each individual neuron from coarse scale data that has been spatially decimated by an order of magnitude. This offers a cheap method for compressing this large video data, and also implies that it is possible to either speed up imaging significantly, or to “zoom out” by a corresponding factor to image order-of-magnitude larger neuronal populations with minimal loss in accuracy or temporal resolution. PMID:28771570

Predicting spatio-temporal failure in large scale observational and micro scale experimental systems

NASA Astrophysics Data System (ADS)

de las Heras, Alejandro; Hu, Yong

2006-10-01

Forecasting has become an essential part of modern thought, but the practical limitations still are manifold. We addressed future rates of change by comparing models that take into account time, and models that focus more on space. Cox regression confirmed that linear change can be safely assumed in the short-term. Spatially explicit Poisson regression, provided a ceiling value for the number of deforestation spots. With several observed and estimated rates, it was decided to forecast using the more robust assumptions. A Markov-chain cellular automaton thus projected 5-year deforestation in the Amazonian Arc of Deforestation, showing that even a stable rate of change would largely deplete the forest area. More generally, resolution and implementation of the existing models could explain many of the modelling difficulties still affecting forecasting.

The assessment of mangrove biomass and carbon in West Africa: a spatially explicit analytical framework

Treesearch

Wenwu Tang; Wenpeng Feng; Meijuan Jia; Jiyang Shi; Huifang Zuo; Carl C. Trettin

2015-01-01

Mangrove forests are highly productive and have large carbon sinks while also providing numerous goods and ecosystem services. However, effective management and conservation of the mangrove forests are often dependent on spatially explicit assessments of the resource. Given the remote and highly dispersed nature of mangroves, estimation of biomass and carbon...

Implicit and Explicit Gender Beliefs in Spatial Ability: Stronger Stereotyping in Boys than Girls.

PubMed

Vander Heyden, Karin M; van Atteveldt, Nienke M; Huizinga, Mariette; Jolles, Jelle

2016-01-01

Sex differences in spatial ability are a seriously debated topic, given the importance of spatial ability for success in the fields of science, technology, engineering, and mathematics (STEM) and girls' underrepresentation in these domains. In the current study we investigated the presence of stereotypic gender beliefs on spatial ability (i.e., "spatial ability is for boys") in 10- and 12-year-old children. We used both an explicit measure (i.e., a self-report questionnaire) and an implicit measure (i.e., a child IAT). Results of the explicit measure showed that both sexes associated spatial ability with boys, with boys holding more male stereotyped attitudes than girls. On the implicit measure, boys associated spatial ability with boys, while girls were gender-neutral. In addition, we examined the effects of gender beliefs on spatial performance, by experimentally activating gender beliefs within a pretest-instruction-posttest design. We compared three types of instruction: boys are better, girls are better, and no sex differences. No effects of these gender belief instructions were found on children's spatial test performance (i.e., mental rotation and paper folding). The finding that children of this age already have stereotypic beliefs about the spatial capacities of their own sex is important, as these beliefs may influence children's choices for spatial leisure activities and educational tracks in the STEM domain.

Implicit and Explicit Gender Beliefs in Spatial Ability: Stronger Stereotyping in Boys than Girls

PubMed Central

Vander Heyden, Karin M.; van Atteveldt, Nienke M.; Huizinga, Mariette; Jolles, Jelle

2016-01-01

Sex differences in spatial ability are a seriously debated topic, given the importance of spatial ability for success in the fields of science, technology, engineering, and mathematics (STEM) and girls' underrepresentation in these domains. In the current study we investigated the presence of stereotypic gender beliefs on spatial ability (i.e., “spatial ability is for boys”) in 10- and 12-year-old children. We used both an explicit measure (i.e., a self-report questionnaire) and an implicit measure (i.e., a child IAT). Results of the explicit measure showed that both sexes associated spatial ability with boys, with boys holding more male stereotyped attitudes than girls. On the implicit measure, boys associated spatial ability with boys, while girls were gender-neutral. In addition, we examined the effects of gender beliefs on spatial performance, by experimentally activating gender beliefs within a pretest—instruction—posttest design. We compared three types of instruction: boys are better, girls are better, and no sex differences. No effects of these gender belief instructions were found on children's spatial test performance (i.e., mental rotation and paper folding). The finding that children of this age already have stereotypic beliefs about the spatial capacities of their own sex is important, as these beliefs may influence children's choices for spatial leisure activities and educational tracks in the STEM domain. PMID:27507956

Physiological considerations acting on triplet oxygen for explicit dosimetry in photodynamic therapy.

PubMed

Sánchez, Víctor; Romero, María Paulina; Pratavieira, Sebastião; Costa, César

2017-09-01

The aims of this study were to determine the spatial and temporal theoretical distribution of the concentrations of Protoporphyrin IX, 3 O 2 and doses of 1 O 2 . The type II mechanism and explicit dosimetry in photodynamic therapy were used. Furthermore, the mechanism of respiration and cellular metabolism acting on 3 O 2 were taken into account. The dermis was considered as an absorbing and a scattering medium. An analytical solution was used for light diffusion in the skin. The photophysical, photochemical and biological effects caused by PDT with the initial irradiances of 20, 60 and 150mW/cm 2 were studied for a time of exposure of 20min and a maximum depth of 0.5cm. We found that the initial irradiance triples its value in 0.02cm and that almost 100% of PpIX is part of the dynamics of reactions in photodynamic therapy. Additionally, with about 40μMof 3 O 2 there is a balance between the consumed and supplied oxygen. Finally, we determined that with 60mW/cm 2 , the highest dose of 1 O 2 is obtained. Copyright © 2017 Elsevier B.V. All rights reserved.

Spatial reconstruction of single-cell gene expression

PubMed Central

Satija, Rahul; Farrell, Jeffrey A.; Gennert, David; Schier, Alexander F.; Regev, Aviv

2015-01-01

Spatial localization is a key determinant of cellular fate and behavior, but spatial RNA assays traditionally rely on staining for a limited number of RNA species. In contrast, single-cell RNA-seq allows for deep profiling of cellular gene expression, but established methods separate cells from their native spatial context. Here we present Seurat, a computational strategy to infer cellular localization by integrating single-cell RNA-seq data with in situ RNA patterns. We applied Seurat to spatially map 851 single cells from dissociated zebrafish (Danio rerio) embryos, inferring a transcriptome-wide map of spatial patterning. We confirmed Seurat’s accuracy using several experimental approaches, and used it to identify a set of archetypal expression patterns and spatial markers. Additionally, Seurat correctly localizes rare subpopulations, accurately mapping both spatially restricted and scattered groups. Seurat will be applicable to mapping cellular localization within complex patterned tissues in diverse systems. PMID:25867923

Reversible elementary cellular automaton with rule number 150 and periodic boundary conditions over 𝔽p

NASA Astrophysics Data System (ADS)

Martín Del Rey, A.; Rodríguez Sánchez, G.

2015-03-01

The study of the reversibility of elementary cellular automata with rule number 150 over the finite state set 𝔽p and endowed with periodic boundary conditions is done. The dynamic of such discrete dynamical systems is characterized by means of characteristic circulant matrices, and their analysis allows us to state that the reversibility depends on the number of cells of the cellular space and to explicitly compute the corresponding inverse cellular automata.

Collaborative development of land use change scenarios for analysing hydro-meteorological risk

NASA Astrophysics Data System (ADS)

Malek, Žiga; Glade, Thomas

2015-04-01

Simulating future land use changes remains a difficult task, due to uncontrollable and uncertain driving forces of change. Scenario development emerged as a tool to address these limitations. Scenarios offer the exploration of possible futures and environmental consequences, and enable the analysis of possible decisions. Therefore, there is increasing interest of both decision makers and researchers to apply scenarios when studying future land use changes and their consequences. The uncertainties related to generating land use change scenarios are among others defined by the accuracy of data, identification and quantification of driving forces, and the relation between expected future changes and the corresponding spatial pattern. To address the issue of data and intangible driving forces, several studies have applied collaborative, participatory techniques when developing future scenarios. The involvement of stakeholders can lead to incorporating a broader spectrum of professional values and experience. Moreover, stakeholders can help to provide missing data, improve detail, uncover mistakes, and offer alternatives. Thus, collaborative scenarios can be considered as more reliable and relevant. Collaborative scenario development has been applied to study a variety of issues in environmental sciences on different spatial and temporal scales. Still, these participatory approaches are rarely spatially explicit, making them difficult to apply when analysing changes to hydro-meteorological risk on a local scale. Spatial explicitness is needed to identify potentially critical areas of land use change, leading to locations where the risk might increase. In order to allocate collaboratively developed scenarios of land change, we combined participatory modeling with geosimulation in a multi-step scenario generation framework. We propose a framework able to develop scenarios that are plausible, can overcome data inaccessibility, address intangible and external driving forces of land change, and is transferable to other case study areas with different land use change processes and consequences. The framework starts with the involvement of stakeholders where driving forces of land use change are being studied by performing interviews and group discussions. In order to bridge the gap between qualitative methods and conventional geospatial techniques, we applied cognitive mapping and the Drivers-Pressures-State-Impact and Response framework (DPSIR) to develop a conceptual land use change model. This was later transformed into a spatially explicit land use change model based on remote sensing data, GIS and cellular automata spatial allocation. The methodology was developed and applied in a study area in the eastern Italian Alps, where the uncertainties regarding future urban expansion are high. Later, we transferred it to a study area in the Romanian Carpathians, where the identified prevailing process of land use change is deforestation. Both areas are subject to hydro-meteorological risk, posing a need for the analysis of the possible future spatial pattern and locations of land use change. The resulting scenarios enabled us, to point at identifying hot-spots of land use change, serving as a possible input for a risk assessment.

Cellular Automata and the Humanities.

ERIC Educational Resources Information Center

Gallo, Ernest

1994-01-01

The use of cellular automata to analyze several pre-Socratic hypotheses about the evolution of the physical world is discussed. These hypotheses combine characteristics of both rigorous and metaphoric language. Since the computer demands explicit instructions for each step in the evolution of the automaton, such models can reveal conceptual…

Spatial Differentiation of Arable Land and Permanent Grasslands to Improve a Regional Land Management Model for Nutrient Balancing

NASA Astrophysics Data System (ADS)

Gómez Giménez, M.; Della Peruta, R.; de Jong, R.; Keller, A.; Schaepman, M. E.

2015-12-01

Agroecosystems play an important role providing economic and ecosystem services, which directly impact society. Inappropriate land use and unsustainable agricultural management with associated nutrient cycles can jeopardize important soil functions such as food production, livestock feeding and conservation of biodiversity. The objective of this study was to integrate remotely sensed land cover information into a regional Land Management Model (LMM) to improve the assessment of spatial explicit nutrient balances for agroecosystems. Remotely sensed data as well as an optimized parameter set contributed to feed the LMM providing a better spatial allocation of agricultural data aggregated at farm level. The integration of land use information in the land allocation process relied predominantly on three factors: i) spatial resolution, ii) classification accuracy and iii) parcels definition. The best-input parameter combination resulted in two different land cover classifications with overall accuracies of 98%, improving the LMM performance by 16% as compared to using non-spatially explicit input. Firstly, the use of spatial explicit information improved the spatial allocation output resulting in a pattern that better followed parcel boundaries (Figure 1). Second, the high classification accuracies ensured consistency between the datasets used. Third, the use of a suitable spatial unit to define the parcels boundaries influenced the model in terms of computational time and the amount of farmland allocated. We conclude that the combined use of remote sensing (RS) data with the LMM has the potential to provide highly accurate information of spatial explicit nutrient balances that are crucial for policy options concerning sustainable management of agricultural soils. Figure 1. Details of the spatial pattern obtained: a) Using only the farm census data, b) using also land use information. Framed in black in the left image (a), examples of artifacts that disappeared when using land use information (right image, b). Colors represent different ownership.

Implicit representations of space after bilateral parietal lobe damage.

PubMed

Kim, M S; Robertson, L C

2001-11-15

There is substantial evidence that the primate cortex is grossly divided into two functional streams, an occipital-parietal-frontal pathway that processes "where" and an occipital-temporal-frontal pathway that processes "what" (Ungerleider and Mishkin, 1982). In humans, bilateral occipital-parietal damage results in severe spatial deficits and a neuropsychological disorder known as Balint's syndrome in which a single object can be perceived (simultanagnosia) but its location is unknown (Balint, 1995). The data reported here demonstrate that spatial information for visual features that cannot be explicitly located is represented normally below the level of spatial awareness even with large occipital-parietal lesions. They also demonstrate that parietal damage does not affect preattentive spatial coding of feature locations or complex spatial relationships between parts of a stimulus despite explicit spatial deficits and simultanagnosia.

Competitive intransitivity promotes species coexistence.

PubMed

Laird, Robert A; Schamp, Brandon S

2006-08-01

Using a spatially explicit cellular automaton model with local competition, we investigate the potential for varied levels of competitive intransitivity (i.e., nonhierarchical competition) to promote species coexistence. As predicted, on average, increased levels of intransitivity result in more sustained coexistence within simulated communities, although the outcome of competition also becomes increasingly unpredictable. Interestingly, even a moderate degree of intransitivity within a community can promote coexistence, in terms of both the length of time until the first competitive exclusion and the number of species remaining in the community after 500 simulated generations. These results suggest that modest levels of intransitivity in nature, such as those that are thought to be characteristic of plant communities, can contribute to coexistence and, therefore, community-scale biodiversity. We explore a potential connection between competitive intransitivity and neutral theory, whereby competitive intransitivity may represent an important mechanism for "ecological equivalence."

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.

Estimating and interpreting migration of Amazonian forests using spatially implicit and semi-explicit neutral models.

PubMed

Pos, Edwin; Guevara Andino, Juan Ernesto; Sabatier, Daniel; Molino, Jean-François; Pitman, Nigel; Mogollón, Hugo; Neill, David; Cerón, Carlos; Rivas-Torres, Gonzalo; Di Fiore, Anthony; Thomas, Raquel; Tirado, Milton; Young, Kenneth R; Wang, Ophelia; Sierra, Rodrigo; García-Villacorta, Roosevelt; Zagt, Roderick; Palacios Cuenca, Walter; Aulestia, Milton; Ter Steege, Hans

2017-06-01

With many sophisticated methods available for estimating migration, ecologists face the difficult decision of choosing for their specific line of work. Here we test and compare several methods, performing sanity and robustness tests, applying to large-scale data and discussing the results and interpretation. Five methods were selected to compare for their ability to estimate migration from spatially implicit and semi-explicit simulations based on three large-scale field datasets from South America (Guyana, Suriname, French Guiana and Ecuador). Space was incorporated semi-explicitly by a discrete probability mass function for local recruitment, migration from adjacent plots or from a metacommunity. Most methods were able to accurately estimate migration from spatially implicit simulations. For spatially semi-explicit simulations, estimation was shown to be the additive effect of migration from adjacent plots and the metacommunity. It was only accurate when migration from the metacommunity outweighed that of adjacent plots, discrimination, however, proved to be impossible. We show that migration should be considered more an approximation of the resemblance between communities and the summed regional species pool. Application of migration estimates to simulate field datasets did show reasonably good fits and indicated consistent differences between sets in comparison with earlier studies. We conclude that estimates of migration using these methods are more an approximation of the homogenization among local communities over time rather than a direct measurement of migration and hence have a direct relationship with beta diversity. As betadiversity is the result of many (non)-neutral processes, we have to admit that migration as estimated in a spatial explicit world encompasses not only direct migration but is an ecological aggregate of these processes. The parameter m of neutral models then appears more as an emerging property revealed by neutral theory instead of being an effective mechanistic parameter and spatially implicit models should be rejected as an approximation of forest dynamics.

Follow your nose: Implicit spatial processing within the chemosensory systems.

PubMed

Wudarczyk, Olga A; Habel, Ute; Turetsky, Bruce I; Gur, Raquel E; Kellermann, Thilo; Schneider, Frank; Moessnang, Carolin

2016-11-01

Although most studies agree that humans cannot smell in stereo, it was recently suggested that olfactory localization is possible when assessed implicitly. In a spatial cueing paradigm, lateralized olfactory cues impaired the detection of congruently presented visual targets, an effect contrary to the typical facilitation observed in other sensory domains. Here, we examined the specificity and the robustness of this finding by studying implicit localization abilities in another chemosensory system and by accounting for possible confounds in a modified paradigm. Sixty participants completed a spatial cueing task along with an explicit localization task, using trigeminal (Experiment 1) and olfactory (Experiment 2) stimuli. A control task was implemented to control for residual somatosensory stimulation (Experiment 3). In the trigeminal experiment, stimuli were localized with high accuracy on the explicit level, while the cueing effect in form of facilitation was limited to response accuracy. In the olfactory experiment, responses were slowed by congruent cues on the implicit level, while no explicit localization was observed. Our results point to the robustness of the olfactory interference effect, corroborating the implicit-explicit dissociation of olfactory localization, and challenging the view that humans lost the ability to extract spatial information from smell. The absence of a similar interference for trigeminal cues suggests distinct implicit spatial processing mechanisms within the chemosensory systems. Moreover, the lack of a typical facilitation effect in the trigeminal domain points to important differences from spatial information processing in other, nonchemosensory domains. The possible mechanisms driving the effects are discussed. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

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

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, ...

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...

Preserved memory-based orienting of attention with impaired explicit memory in healthy ageing

PubMed Central

Salvato, Gerardo; Patai, Eva Z.; Nobre, Anna C.

2016-01-01

It is increasingly recognised that spatial contextual long-term memory (LTM) prepares neural activity for guiding visuo-spatial attention in a proactive manner. In the current study, we investigated whether the decline in explicit memory observed in healthy ageing would compromise this mechanism. We compared the behavioural performance of younger and older participants on learning new contextual memories, on orienting visual attention based on these learnt contextual associations, and on explicit recall of contextual memories. We found a striking dissociation between older versus younger participants in the relationship between the ability to retrieve contextual memories versus the ability to use these to guide attention to enhance performance on a target-detection task. Older participants showed significant deficits in the explicit retrieval task, but their behavioural benefits from memory-based orienting of attention were equivalent to those in young participants. Furthermore, memory-based orienting correlated significantly with explicit contextual LTM in younger adults but not in older adults. These results suggest that explicit memory deficits in ageing might not compromise initial perception and encoding of events. Importantly, the results also shed light on the mechanisms of memory-guided attention, suggesting that explicit contextual memories are not necessary. PMID:26649914

Spatial Patterns in Alternative States and Thresholds: A Missing Link for Management of Landscapes?

USDA-ARS?s Scientific Manuscript database

The detection of threshold dynamics (and other dynamics of interest) would benefit from explicit representations of spatial patterns of disturbance, spatial dependence in responses to disturbance, and the spatial structure of feedbacks in the design of monitoring and management strategies. Spatially...

On the Nexus of the Spatial Dynamics of Global Urbanization and the Age of the City

PubMed Central

Scheuer, Sebastian; Haase, Dagmar; Volk, Martin

2016-01-01

A number of concepts exist regarding how urbanization can be described as a process. Understanding this process that affects billions of people and its future development in a spatial manner is imperative to address related issues such as human quality of life. In the focus of spatially explicit studies on urbanization is typically a city, a particular urban region, an agglomeration. However, gaps remain in spatially explicit global models. This paper addresses that issue by examining the spatial dynamics of urban areas over time, for a full coverage of the world. The presented model identifies past, present and potential future hotspots of urbanization as a function of an urban area's spatial variation and age, whose relation could be depicted both as a proxy and as a path of urban development. PMID:27490199

On the Nexus of the Spatial Dynamics of Global Urbanization and the Age of the City.

PubMed

Scheuer, Sebastian; Haase, Dagmar; Volk, Martin

2016-01-01

A number of concepts exist regarding how urbanization can be described as a process. Understanding this process that affects billions of people and its future development in a spatial manner is imperative to address related issues such as human quality of life. In the focus of spatially explicit studies on urbanization is typically a city, a particular urban region, an agglomeration. However, gaps remain in spatially explicit global models. This paper addresses that issue by examining the spatial dynamics of urban areas over time, for a full coverage of the world. The presented model identifies past, present and potential future hotspots of urbanization as a function of an urban area's spatial variation and age, whose relation could be depicted both as a proxy and as a path of urban development.

Radar orthogonality and radar length in Finsler and metric spacetime geometry

NASA Astrophysics Data System (ADS)

Pfeifer, Christian

2014-09-01

The radar experiment connects the geometry of spacetime with an observers measurement of spatial length. We investigate the radar experiment on Finsler spacetimes which leads to a general definition of radar orthogonality and radar length. The directions radar orthogonal to an observer form the spatial equal time surface an observer experiences and the radar length is the physical length the observer associates to spatial objects. We demonstrate these concepts on a forth order polynomial Finsler spacetime geometry which may emerge from area metric or premetric linear electrodynamics or in quantum gravity phenomenology. In an explicit generalization of Minkowski spacetime geometry we derive the deviation from the Euclidean spatial length measure in an observers rest frame explicitly.

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.

Improving carbon monitoring and reporting in forests using spatially-explicit information.

PubMed

Boisvenue, Céline; Smiley, Byron P; White, Joanne C; Kurz, Werner A; Wulder, Michael A

2016-12-01

Understanding and quantifying carbon (C) exchanges between the biosphere and the atmosphere-specifically the process of C removal from the atmosphere, and how this process is changing-is the basis for developing appropriate adaptation and mitigation strategies for climate change. Monitoring forest systems and reporting on greenhouse gas (GHG) emissions and removals are now required components of international efforts aimed at mitigating rising atmospheric GHG. Spatially-explicit information about forests can improve the estimates of GHG emissions and removals. However, at present, remotely-sensed information on forest change is not commonly integrated into GHG reporting systems. New, detailed (30-m spatial resolution) forest change products derived from satellite time series informing on location, magnitude, and type of change, at an annual time step, have recently become available. Here we estimate the forest GHG balance using these new Landsat-based change data, a spatial forest inventory, and develop yield curves as inputs to the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) to estimate GHG emissions and removals at a 30 m resolution for a 13 Mha pilot area in Saskatchewan, Canada. Our results depict the forests as cumulative C sink (17.98 Tg C or 0.64 Tg C year -1 ) between 1984 and 2012 with an average C density of 206.5 (±0.6) Mg C ha -1 . Comparisons between our estimates and estimates from Canada's National Forest Carbon Monitoring, Accounting and Reporting System (NFCMARS) were possible only on a subset of our study area. In our simulations the area was a C sink, while the official reporting simulations, it was a C source. Forest area and overall C stock estimates also differ between the two simulated estimates. Both estimates have similar uncertainties, but the spatially-explicit results we present here better quantify the potential improvement brought on by spatially-explicit modelling. We discuss the source of the differences between these estimates. This study represents an important first step towards the integration of spatially-explicit information into Canada's NFCMARS.

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.

Habitat fragmentation resulting in overgrazing by herbivores.

PubMed

Kondoh, Michio

2003-12-21

Habitat fragmentation sometimes results in outbreaks of herbivorous insect and causes an enormous loss of primary production. It is hypothesized that the driving force behind such herbivore outbreaks is disruption of natural enemy attack that releases herbivores from top-down control. To test this hypothesis I studied how trophic community structure changes along a gradient of habitat fragmentation level using spatially implicit and explicit models of a tri-trophic (plant, herbivore and natural enemy) food chain. While in spatially implicit model number of trophic levels gradually decreases with increasing fragmentation, in spatially explicit model a relatively low level of habitat fragmentation leads to overgrazing by herbivore to result in extinction of the plant population followed by a total system collapse. This provides a theoretical support to the hypothesis that habitat fragmentation can lead to overgrazing by herbivores and suggests a central role of spatial structure in the influence of habitat fragmentation on trophic communities. Further, the spatially explicit model shows (i) that the total system collapse by the overgrazing can occur only if herbivore colonization rate is high; (ii) that with increasing natural enemy colonization rate, the fragmentation level that leads to the system collapse becomes higher, and the frequency of the collapse is lowered.

Exploring spatial change and gravity center movement for ecosystem services value using a spatially explicit ecosystem services value index and gravity model.

PubMed

He, Yingbin; Chen, Youqi; Tang, Huajun; Yao, Yanmin; Yang, Peng; Chen, Zhongxin

2011-04-01

Spatially explicit ecosystem services valuation and change is a newly developing area of research in the field of ecology. Using the Beijing region as a study area, the authors have developed a spatially explicit ecosystem services value index and implemented this to quantify and spatially differentiate ecosystem services value at 1-km grid resolution. A gravity model was developed to trace spatial change in the total ecosystem services value of the Beijing study area from a holistic point of view. Study results show that the total value of ecosystem services for the study area decreased by 19.75% during the period 1996-2006 (3,226.2739 US$×10(6) in 1996, 2,589.0321 US$×10(6) in 2006). However, 27.63% of the total area of the Beijing study area increased in ecosystem services value. Spatial differences in ecosystem services values for both 1996 and 2006 are very clear. The center of gravity of total ecosystem services value for the study area moved 32.28 km northwestward over the 10 years due to intensive human intervention taking place in southeast Beijing. The authors suggest that policy-makers should pay greater attention to ecological protection under conditions of rapid socio-economic development and increase the area of green belt in the southeastern part of Beijing.

Template Directed Replication Supports the Maintenance of the Metabolically Coupled Replicator System

NASA Astrophysics Data System (ADS)

Könnyű, Balázs; Czárán, Tamás

2015-06-01

The RNA World scenario of prebiotic chemical evolution is among the most plausible conceptual framework available today for modelling the origin of life. RNA offers genetic and catalytic (metabolic) functionality embodied in a single chemical entity, and a metabolically cooperating community of RNA molecules would constitute a viable infrabiological subsystem with a potential to evolve into proto-cellular life. Our Metabolically Coupled Replicator System (MCRS) model is a spatially explicit computer simulation implementation of the RNA-World scenario, in which replicable ribozymes cooperate in supplying each other with monomers for their own replication. MCRS has been repeatedly demonstrated to be viable and evolvable, with different versions of the model improved in depth (chemical detail of metabolism) or in extension (additional functions of RNA molecules). One of the dynamically relevant extensions of the MCRS approach to prebiotic RNA evolution is the explicit inclusion of template replication into its assumptions, which we have studied in the present version. We found that this modification has not changed the behaviour of the system in the qualitative sense, just the range of the parameter space which is optimal for the coexistence of metabolically cooperating replicators has shifted in terms of metabolite mobility. The system also remains resistant and tolerant to parasitic replicators.

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

Cellular Factors Shape 3D Genome Landscape

Cancer.gov

Researchers, using novel large-scale imaging technology, have mapped the spatial location of individual genes in the nucleus of human cells and identified 50 cellular factors required for the proper 3D positioning of genes. These spatial locations play important roles in gene expression, DNA repair, genome stability, and other cellular activities.

A methodological approach for deriving regional crop rotations as basis for the assessment of the impact of agricultural strategies using soil erosion as example.

PubMed

Lorenz, Marco; Fürst, Christine; Thiel, Enrico

2013-09-01

Regarding increasing pressures by global societal and climate change, the assessment of the impact of land use and land management practices on land degradation and the related decrease in sustainable provision of ecosystem services gains increasing interest. Existing approaches to assess agricultural practices focus on the assessment of single crops or statistical data because spatially explicit information on practically applied crop rotations is mostly not available. This provokes considerable uncertainties in crop production models as regional specifics have to be neglected or cannot be considered in an appropriate way. In a case study in Saxony, we developed an approach to (i) derive representative regional crop rotations by combining different data sources and expert knowledge. This includes the integration of innovative crop sequences related to bio-energy production or organic farming and different soil tillage, soil management and soil protection techniques. Furthermore, (ii) we developed a regionalization approach for transferring crop rotations and related soil management strategies on the basis of statistical data and spatially explicit data taken from so called field blocks. These field blocks are the smallest spatial entity for which agricultural practices must be reported to apply for agricultural funding within the frame of the European Agricultural Fund for Rural Development (EAFRD) program. The information was finally integrated into the spatial decision support tool GISCAME to assess and visualize in spatially explicit manner the impact of alternative agricultural land use strategies on soil erosion risk and ecosystem services provision. Objective of this paper is to present the approach how to create spatially explicit information on agricultural management practices for a study area around Dresden, the capital of the German Federal State Saxony. Copyright © 2013 Elsevier Ltd. All rights reserved.

Spatially explicit multi-criteria decision analysis for managing vector-borne diseases

PubMed Central

2011-01-01

The complex epidemiology of vector-borne diseases creates significant challenges in the design and delivery of prevention and control strategies, especially in light of rapid social and environmental changes. Spatial models for predicting disease risk based on environmental factors such as climate and landscape have been developed for a number of important vector-borne diseases. The resulting risk maps have proven value for highlighting areas for targeting public health programs. However, these methods generally only offer technical information on the spatial distribution of disease risk itself, which may be incomplete for making decisions in a complex situation. In prioritizing surveillance and intervention strategies, decision-makers often also need to consider spatially explicit information on other important dimensions, such as the regional specificity of public acceptance, population vulnerability, resource availability, intervention effectiveness, and land use. There is a need for a unified strategy for supporting public health decision making that integrates available data for assessing spatially explicit disease risk, with other criteria, to implement effective prevention and control strategies. Multi-criteria decision analysis (MCDA) is a decision support tool that allows for the consideration of diverse quantitative and qualitative criteria using both data-driven and qualitative indicators for evaluating alternative strategies with transparency and stakeholder participation. Here we propose a MCDA-based approach to the development of geospatial models and spatially explicit decision support tools for the management of vector-borne diseases. We describe the conceptual framework that MCDA offers as well as technical considerations, approaches to implementation and expected outcomes. We conclude that MCDA is a powerful tool that offers tremendous potential for use in public health decision-making in general and vector-borne disease management in particular. PMID:22206355

Analysis of Spatial Concepts, Spatial Skills and Spatial Representations in New York State Regents Earth Science Examinations

ERIC Educational Resources Information Center

Kastens, Kim A.; Pistolesi, Linda; Passow, Michael J.

2014-01-01

Research has shown that spatial thinking is important in science in general, and in Earth Science in particular, and that performance on spatially demanding tasks can be fostered through instruction. Because spatial thinking is rarely taught explicitly in the U.S. education system, improving spatial thinking may be "low-hanging fruit" as…

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

Plant growth and architectural modelling and its applications

PubMed Central

Guo, Yan; Fourcaud, Thierry; Jaeger, Marc; Zhang, Xiaopeng; Li, Baoguo

2011-01-01

Over the last decade, a growing number of scientists around the world have invested in research on plant growth and architectural modelling and applications (often abbreviated to plant modelling and applications, PMA). By combining physical and biological processes, spatially explicit models have shown their ability to help in understanding plant–environment interactions. This Special Issue on plant growth modelling presents new information within this topic, which are summarized in this preface. Research results for a variety of plant species growing in the field, in greenhouses and in natural environments are presented. Various models and simulation platforms are developed in this field of research, opening new features to a wider community of researchers and end users. New modelling technologies relating to the structure and function of plant shoots and root systems are explored from the cellular to the whole-plant and plant-community levels. PMID:21638797

Modelling the collective response of heterogeneous cell populations to stationary gradients and chemical signal relay

NASA Astrophysics Data System (ADS)

Pineda, M.; Eftimie, R.

2017-12-01

The directed motion of cell aggregates toward a chemical source occurs in many relevant biological processes. Understanding the mechanisms that control this complex behavior is of great relevance for our understanding of developmental biological processes and many diseases. In this paper, we consider a self-propelled particle model for the movement of heterogeneous subpopulations of chemically interacting cells towards an imposed stable chemical gradient. Our simulations show explicitly how self-organisation of cell populations (which could lead to engulfment or complete cell segregation) can arise from the heterogeneity of chemotactic responses alone. This new result complements current theoretical and experimental studies that emphasise the role of differential cell-cell adhesion on self-organisation and spatial structure of cellular aggregates. We also investigate how the speed of individual cell aggregations increases with the chemotactic sensitivity of the cells, and decreases with the number of cells inside the aggregates

Spatial Working Memory Interferes with Explicit, but Not Probabilistic Cuing of Spatial Attention

ERIC Educational Resources Information Center

Won, Bo-Yeong; Jiang, Yuhong V.

2015-01-01

Recent empirical and theoretical work has depicted a close relationship between visual attention and visual working memory. For example, rehearsal in spatial working memory depends on spatial attention, whereas adding a secondary spatial working memory task impairs attentional deployment in visual search. These findings have led to the proposal…

Spatial reconstruction of single-cell gene expression data.

PubMed

Satija, Rahul; Farrell, Jeffrey A; Gennert, David; Schier, Alexander F; Regev, Aviv

2015-05-01

Spatial localization is a key determinant of cellular fate and behavior, but methods for spatially resolved, transcriptome-wide gene expression profiling across complex tissues are lacking. RNA staining methods assay only a small number of transcripts, whereas single-cell RNA-seq, which measures global gene expression, separates cells from their native spatial context. Here we present Seurat, a computational strategy to infer cellular localization by integrating single-cell RNA-seq data with in situ RNA patterns. We applied Seurat to spatially map 851 single cells from dissociated zebrafish (Danio rerio) embryos and generated a transcriptome-wide map of spatial patterning. We confirmed Seurat's accuracy using several experimental approaches, then used the strategy to identify a set of archetypal expression patterns and spatial markers. Seurat correctly localizes rare subpopulations, accurately mapping both spatially restricted and scattered groups. Seurat will be applicable to mapping cellular localization within complex patterned tissues in diverse systems.

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...

Preserved memory-based orienting of attention with impaired explicit memory in healthy ageing.

PubMed

Salvato, Gerardo; Patai, Eva Z; Nobre, Anna C

2016-01-01

It is increasingly recognised that spatial contextual long-term memory (LTM) prepares neural activity for guiding visuo-spatial attention in a proactive manner. In the current study, we investigated whether the decline in explicit memory observed in healthy ageing would compromise this mechanism. We compared the behavioural performance of younger and older participants on learning new contextual memories, on orienting visual attention based on these learnt contextual associations, and on explicit recall of contextual memories. We found a striking dissociation between older versus younger participants in the relationship between the ability to retrieve contextual memories versus the ability to use these to guide attention to enhance performance on a target-detection task. Older participants showed significant deficits in the explicit retrieval task, but their behavioural benefits from memory-based orienting of attention were equivalent to those in young participants. Furthermore, memory-based orienting correlated significantly with explicit contextual LTM in younger adults but not in older adults. These results suggest that explicit memory deficits in ageing might not compromise initial perception and encoding of events. Importantly, the results also shed light on the mechanisms of memory-guided attention, suggesting that explicit contextual memories are not necessary. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

Using a spatially explicit analysis model to evaluate spatial variation of corn yield

USDA-ARS?s Scientific Manuscript database

Spatial irrigation of agricultural crops using site-specific variable-rate irrigation (VRI) systems is beginning to have wide-spread acceptance. However, optimizing the management of these VRI systems to conserve natural resources and increase profitability requires an understanding of the spatial ...

Spatially explicit global population scenarios consistent with the Shared Socioeconomic Pathways

DOE PAGES

Jones, B.; O’Neill, B. C.

2016-07-29

Here we report that the projected size and spatial distribution of the future population are important drivers of global change and key determinants of exposure and vulnerability to hazards. Spatial demographic projections are widely used as inputs to spatial projections of land use, energy use, and emissions, as well as to assessments of the impacts of extreme events, sea level rise, and other climate-related outcomes. To date, however, there are very few global-scale, spatially explicit population projections, and those that do exist are often based on simple scaling or trend extrapolation. Here we present a new set of global, spatiallymore » explicit population scenarios that are consistent with the new Shared Socioeconomic Pathways (SSPs) developed to facilitate global change research. We use a parameterized gravity-based downscaling model to produce projections of spatial population change that are quantitatively consistent with national population and urbanization projections for the SSPs and qualitatively consistent with assumptions in the SSP narratives regarding spatial development patterns. We show that the five SSPs lead to substantially different spatial population outcomes at the continental, national, and sub-national scale. In general, grid cell-level outcomes are most influenced by national-level population change, second by urbanization rate, and third by assumptions about the spatial style of development. However, the relative importance of these factors is a function of the magnitude of the projected change in total population and urbanization for each country and across SSPs. We also demonstrate variation in outcomes considering the example of population existing in a low-elevation coastal zone under alternative scenarios.« less

Spatially explicit global population scenarios consistent with the Shared Socioeconomic Pathways

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

Jones, B.; O’Neill, B. C.

Here we report that the projected size and spatial distribution of the future population are important drivers of global change and key determinants of exposure and vulnerability to hazards. Spatial demographic projections are widely used as inputs to spatial projections of land use, energy use, and emissions, as well as to assessments of the impacts of extreme events, sea level rise, and other climate-related outcomes. To date, however, there are very few global-scale, spatially explicit population projections, and those that do exist are often based on simple scaling or trend extrapolation. Here we present a new set of global, spatiallymore » explicit population scenarios that are consistent with the new Shared Socioeconomic Pathways (SSPs) developed to facilitate global change research. We use a parameterized gravity-based downscaling model to produce projections of spatial population change that are quantitatively consistent with national population and urbanization projections for the SSPs and qualitatively consistent with assumptions in the SSP narratives regarding spatial development patterns. We show that the five SSPs lead to substantially different spatial population outcomes at the continental, national, and sub-national scale. In general, grid cell-level outcomes are most influenced by national-level population change, second by urbanization rate, and third by assumptions about the spatial style of development. However, the relative importance of these factors is a function of the magnitude of the projected change in total population and urbanization for each country and across SSPs. We also demonstrate variation in outcomes considering the example of population existing in a low-elevation coastal zone under alternative scenarios.« less

Research on reconstructing spatial distribution of historical cropland over 300 years in traditional cultivated regions of China

NASA Astrophysics Data System (ADS)

Yang, Xuhong; Jin, Xiaobin; Guo, Beibei; Long, Ying; Zhou, Yinkang

2015-05-01

Constructing a spatially explicit time series of historical cultivated land is of upmost importance for climatic and ecological studies that make use of Land Use and Cover Change (LUCC) data. Some scholars have made efforts to simulate and reconstruct the quantitative information on historical land use at the global or regional level based on "top-down" decision-making behaviors to match overall cropland area to land parcels using land arability and universal parameters. Considering the concentrated distribution of cultivated land and various factors influencing cropland distribution, including environmental and human factors, this study developed a "bottom-up" model of historical cropland based on constrained Cellular Automaton (CA). Our model takes a historical cropland area as an external variable and the cropland distribution in 1980 as the maximum potential scope of historical cropland. We selected elevation, slope, water availability, average annual precipitation, and distance to the nearest rural settlement as the main influencing factors of land use suitability. Then, an available labor force index is used as a proxy for the amount of cropland to inspect and calibrate these spatial patterns. This paper applies the model to a traditional cultivated region in China and reconstructs its spatial distribution of cropland during 6 periods. The results are shown as follows: (1) a constrained CA is well suited for simulating and reconstructing the spatial distribution of cropland in China's traditional cultivated region. (2) Taking the different factors affecting spatial pattern of cropland into consideration, the partitioning of the research area effectively reflected the spatial differences in cropland evolution rules and rates. (3) Compared with "HYDE datasets", this research has formed higher-resolution Boolean spatial distribution datasets of historical cropland with a more definitive concept of spatial pattern in terms of fractional format. We conclude that our reconstruction is closer to the actual change pattern of the traditional cultivated region in China.

Exploring component-based approaches in forest landscape modeling

Treesearch

H. S. He; D. R. Larsen; D. J. Mladenoff

2002-01-01

Forest management issues are increasingly required to be addressed in a spatial context, which has led to the development of spatially explicit forest landscape models. The numerous processes, complex spatial interactions, and diverse applications in spatial modeling make the development of forest landscape models difficult for any single research group. New...

Spatially explicit spectral analysis of point clouds and geospatial data

USGS Publications Warehouse

Buscombe, Daniel D.

2015-01-01

The increasing use of spatially explicit analyses of high-resolution spatially distributed data (imagery and point clouds) for the purposes of characterising spatial heterogeneity in geophysical phenomena necessitates the development of custom analytical and computational tools. In recent years, such analyses have become the basis of, for example, automated texture characterisation and segmentation, roughness and grain size calculation, and feature detection and classification, from a variety of data types. In this work, much use has been made of statistical descriptors of localised spatial variations in amplitude variance (roughness), however the horizontal scale (wavelength) and spacing of roughness elements is rarely considered. This is despite the fact that the ratio of characteristic vertical to horizontal scales is not constant and can yield important information about physical scaling relationships. Spectral analysis is a hitherto under-utilised but powerful means to acquire statistical information about relevant amplitude and wavelength scales, simultaneously and with computational efficiency. Further, quantifying spatially distributed data in the frequency domain lends itself to the development of stochastic models for probing the underlying mechanisms which govern the spatial distribution of geological and geophysical phenomena. The software packagePySESA (Python program for Spatially Explicit Spectral Analysis) has been developed for generic analyses of spatially distributed data in both the spatial and frequency domains. Developed predominantly in Python, it accesses libraries written in Cython and C++ for efficiency. It is open source and modular, therefore readily incorporated into, and combined with, other data analysis tools and frameworks with particular utility for supporting research in the fields of geomorphology, geophysics, hydrography, photogrammetry and remote sensing. The analytical and computational structure of the toolbox is described, and its functionality illustrated with an example of a high-resolution bathymetric point cloud data collected with multibeam echosounder.

Implicit and Explicit Number-Space Associations Differentially Relate to Interference Control in Young Adults With ADHD

PubMed Central

Georges, Carrie; Hoffmann, Danielle; Schiltz, Christine

2018-01-01

Behavioral evidence for the link between numerical and spatial representations comes from the spatial-numerical association of response codes (SNARC) effect, consisting in faster reaction times to small/large numbers with the left/right hand respectively. The SNARC effect is, however, characterized by considerable intra- and inter-individual variability. It depends not only on the explicit or implicit nature of the numerical task, but also relates to interference control. To determine whether the prevalence of the latter relation in the elderly could be ascribed to younger individuals’ ceiling performances on executive control tasks, we determined whether the SNARC effect related to Stroop and/or Flanker effects in 26 young adults with ADHD. We observed a divergent pattern of correlation depending on the type of numerical task used to assess the SNARC effect and the type of interference control measure involved in number-space associations. Namely, stronger number-space associations during parity judgments involving implicit magnitude processing related to weaker interference control in the Stroop but not Flanker task. Conversely, stronger number-space associations during explicit magnitude classifications tended to be associated with better interference control in the Flanker but not Stroop paradigm. The association of stronger parity and magnitude SNARC effects with weaker and better interference control respectively indicates that different mechanisms underlie these relations. Activation of the magnitude-associated spatial code is irrelevant and potentially interferes with parity judgments, but in contrast assists explicit magnitude classifications. Altogether, the present study confirms the contribution of interference control to number-space associations also in young adults. It suggests that magnitude-associated spatial codes in implicit and explicit tasks are monitored by different interference control mechanisms, thereby explaining task-related intra-individual differences in number-space associations. PMID:29881363

Coupling Cellular Automata Land Use Change with Distributed Hydrologic Models

NASA Astrophysics Data System (ADS)

Shu, L.; Duffy, C.

2017-12-01

There has been extensive research on LUC modeling with broad applications to simulating urban growth and changing demographic patterns across multiple scales. The importance of land conversion is a critical issue in watershed scale studies and is generally not treated in most watershed modeling approaches. In this study we apply spatially explicit hydrologic and landuse change models and the Conestoga Watershed in Lancaster County, Pennsylvania. The Penn State Integrated Hydrologic Model (PIHM) partitions the water balance in space and time over the urban catchment, the coupled Cellular Automata Land Use Change model (CALUC) dynamically simulates the evolution of land use classes based on physical measures associated with population change and land use demand factors. The CALUC model is based on iteratively applying discrete rules to each individual spatial cell. The essence the CA modeling involves calculation of the Transition Potential (TP) for conversion of a grid cell from one land use class to another. This potential includes five factors: random perturbation, suitability, accessibility, neighborhood effect, inertia effects and zonal factors. In spite of simplicity, this CALUC model has been shown to be very effective for simulating LUC leading to the emergence of complex spatial patterns. The components of TP are derived from present land use data for landuse reanalysis and for realistic future land use scenarios. For the CALUC we use early-settlement (circa 1790) initial land class values and final or present-day (2010) land classes to calibrate the model. CALUC- PIHM dynamically simulates the hydrologic response of conversion from pre-settlement to present landuse. The simulations highlight the capability and value of dynamic coupling of catchment hydrology with land use change over long time periods. Analysis of the simulation uses various metrics such as the distributed water balance, flow duration curves, etc. to show how deforestation, urbanization and agricultural land development interact for the period 1790- present.

Quantitative Imaging in Cancer Evolution and Ecology

PubMed Central

Grove, Olya; Gillies, Robert J.

2013-01-01

Cancer therapy, even when highly targeted, typically fails because of the remarkable capacity of malignant cells to evolve effective adaptations. These evolutionary dynamics are both a cause and a consequence of cancer system heterogeneity at many scales, ranging from genetic properties of individual cells to large-scale imaging features. Tumors of the same organ and cell type can have remarkably diverse appearances in different patients. Furthermore, even within a single tumor, marked variations in imaging features, such as necrosis or contrast enhancement, are common. Similar spatial variations recently have been reported in genetic profiles. Radiologic heterogeneity within tumors is usually governed by variations in blood flow, whereas genetic heterogeneity is typically ascribed to random mutations. However, evolution within tumors, as in all living systems, is subject to Darwinian principles; thus, it is governed by predictable and reproducible interactions between environmental selection forces and cell phenotype (not genotype). This link between regional variations in environmental properties and cellular adaptive strategies may permit clinical imaging to be used to assess and monitor intratumoral evolution in individual patients. This approach is enabled by new methods that extract, report, and analyze quantitative, reproducible, and mineable clinical imaging data. However, most current quantitative metrics lack spatialness, expressing quantitative radiologic features as a single value for a region of interest encompassing the whole tumor. In contrast, spatially explicit image analysis recognizes that tumors are heterogeneous but not well mixed and defines regionally distinct habitats, some of which appear to harbor tumor populations that are more aggressive and less treatable than others. By identifying regional variations in key environmental selection forces and evidence of cellular adaptation, clinical imaging can enable us to define intratumoral Darwinian dynamics before and during therapy. Advances in image analysis will place clinical imaging in an increasingly central role in the development of evolution-based patient-specific cancer therapy. © RSNA, 2013 PMID:24062559

Confidentiality and spatially explicit data: Concerns and challenges

PubMed Central

VanWey, Leah K.; Rindfuss, Ronald R.; Gutmann, Myron P.; Entwisle, Barbara; Balk, Deborah L.

2005-01-01

Recent theoretical, methodological, and technological advances in the spatial sciences create an opportunity for social scientists to address questions about the reciprocal relationship between context (spatial organization, environment, etc.) and individual behavior. This emerging research community has yet to adequately address the new threats to the confidentiality of respondent data in spatially explicit social survey or census data files, however. This paper presents four sometimes conflicting principles for the conduct of ethical and high-quality science using such data: protection of confidentiality, the social–spatial linkage, data sharing, and data preservation. The conflict among these four principles is particularly evident in the display of spatially explicit data through maps combined with the sharing of tabular data files. This paper reviews these two research activities and shows how current practices favor one of the principles over the others and do not satisfactorily resolve the conflict among them. Maps are indispensable for the display of results but also reveal information on the location of respondents and sampling clusters that can then be used in combination with shared data files to identify respondents. The current practice of sharing modified or incomplete data sets or using data enclaves is not ideal for either the advancement of science or the protection of confidentiality. Further basic research and open debate are needed to advance both understanding of and solutions to this dilemma. PMID:16230608

CDFISH: an individual-based, spatially-explicit, landscape genetics simulator for aquatic species in complex riverscapes

USGS Publications Warehouse

Erin L. Landguth,; Muhlfeld, Clint C.; Luikart, Gordon

2012-01-01

We introduce Cost Distance FISHeries (CDFISH), a simulator of population genetics and connectivity in complex riverscapes for a wide range of environmental scenarios of aquatic organisms. The spatially-explicit program implements individual-based genetic modeling with Mendelian inheritance and k-allele mutation on a riverscape with resistance to movement. The program simulates individuals in subpopulations through time employing user-defined functions of individual migration, reproduction, mortality, and dispersal through straying on a continuous resistance surface.

Counting Cats: Spatially Explicit Population Estimates of Cheetah (Acinonyx jubatus) Using Unstructured Sampling Data

PubMed Central

Broekhuis, Femke; Gopalaswamy, Arjun M.

2016-01-01

Many ecological theories and species conservation programmes rely on accurate estimates of population density. Accurate density estimation, especially for species facing rapid declines, requires the application of rigorous field and analytical methods. However, obtaining accurate density estimates of carnivores can be challenging as carnivores naturally exist at relatively low densities and are often elusive and wide-ranging. In this study, we employ an unstructured spatial sampling field design along with a Bayesian sex-specific spatially explicit capture-recapture (SECR) analysis, to provide the first rigorous population density estimates of cheetahs (Acinonyx jubatus) in the Maasai Mara, Kenya. We estimate adult cheetah density to be between 1.28 ± 0.315 and 1.34 ± 0.337 individuals/100km2 across four candidate models specified in our analysis. Our spatially explicit approach revealed ‘hotspots’ of cheetah density, highlighting that cheetah are distributed heterogeneously across the landscape. The SECR models incorporated a movement range parameter which indicated that male cheetah moved four times as much as females, possibly because female movement was restricted by their reproductive status and/or the spatial distribution of prey. We show that SECR can be used for spatially unstructured data to successfully characterise the spatial distribution of a low density species and also estimate population density when sample size is small. Our sampling and modelling framework will help determine spatial and temporal variation in cheetah densities, providing a foundation for their conservation and management. Based on our results we encourage other researchers to adopt a similar approach in estimating densities of individually recognisable species. PMID:27135614

Counting Cats: Spatially Explicit Population Estimates of Cheetah (Acinonyx jubatus) Using Unstructured Sampling Data.

PubMed

Broekhuis, Femke; Gopalaswamy, Arjun M

2016-01-01

Many ecological theories and species conservation programmes rely on accurate estimates of population density. Accurate density estimation, especially for species facing rapid declines, requires the application of rigorous field and analytical methods. However, obtaining accurate density estimates of carnivores can be challenging as carnivores naturally exist at relatively low densities and are often elusive and wide-ranging. In this study, we employ an unstructured spatial sampling field design along with a Bayesian sex-specific spatially explicit capture-recapture (SECR) analysis, to provide the first rigorous population density estimates of cheetahs (Acinonyx jubatus) in the Maasai Mara, Kenya. We estimate adult cheetah density to be between 1.28 ± 0.315 and 1.34 ± 0.337 individuals/100km2 across four candidate models specified in our analysis. Our spatially explicit approach revealed 'hotspots' of cheetah density, highlighting that cheetah are distributed heterogeneously across the landscape. The SECR models incorporated a movement range parameter which indicated that male cheetah moved four times as much as females, possibly because female movement was restricted by their reproductive status and/or the spatial distribution of prey. We show that SECR can be used for spatially unstructured data to successfully characterise the spatial distribution of a low density species and also estimate population density when sample size is small. Our sampling and modelling framework will help determine spatial and temporal variation in cheetah densities, providing a foundation for their conservation and management. Based on our results we encourage other researchers to adopt a similar approach in estimating densities of individually recognisable species.

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.

Heteroskedasticity as a leading indicator of desertification in spatially explicit data.

PubMed

Seekell, David A; Dakos, Vasilis

2015-06-01

Regime shifts are abrupt transitions between alternate ecosystem states including desertification in arid regions due to drought or overgrazing. Regime shifts may be preceded by statistical anomalies such as increased autocorrelation, indicating declining resilience and warning of an impending shift. Tests for conditional heteroskedasticity, a type of clustered variance, have proven powerful leading indicators for regime shifts in time series data, but an analogous indicator for spatial data has not been evaluated. A spatial analog for conditional heteroskedasticity might be especially useful in arid environments where spatial interactions are critical in structuring ecosystem pattern and process. We tested the efficacy of a test for spatial heteroskedasticity as a leading indicator of regime shifts with simulated data from spatially extended vegetation models with regular and scale-free patterning. These models simulate shifts from extensive vegetative cover to bare, desert-like conditions. The magnitude of spatial heteroskedasticity increased consistently as the modeled systems approached a regime shift from vegetated to desert state. Relative spatial autocorrelation, spatial heteroskedasticity increased earlier and more consistently. We conclude that tests for spatial heteroskedasticity can contribute to the growing toolbox of early warning indicators for regime shifts analyzed with spatially explicit data.

Configuration of the thermal landscape determines thermoregulatory performance of ectotherms

PubMed Central

Sears, Michael W.; Angilletta, Michael J.; Schuler, Matthew S.; Borchert, Jason; Dilliplane, Katherine F.; Stegman, Monica; Rusch, Travis W.; Mitchell, William A.

2016-01-01

Although most organisms thermoregulate behaviorally, biologists still cannot easily predict whether mobile animals will thermoregulate in natural environments. Current models fail because they ignore how the spatial distribution of thermal resources constrains thermoregulatory performance over space and time. To overcome this limitation, we modeled the spatially explicit movements of animals constrained by access to thermal resources. Our models predict that ectotherms thermoregulate more accurately when thermal resources are dispersed throughout space than when these resources are clumped. This prediction was supported by thermoregulatory behaviors of lizards in outdoor arenas with known distributions of environmental temperatures. Further, simulations showed how the spatial structure of the landscape qualitatively affects responses of animals to climate. Biologists will need spatially explicit models to predict impacts of climate change on local scales. PMID:27601639

A new spatial multiple discrete-continuous modeling approach to land use change analysis.

DOT National Transportation Integrated Search

2013-09-01

This report formulates a multiple discrete-continuous probit (MDCP) land-use model within a : spatially explicit economic structural framework for land-use change decisions. The spatial : MDCP model is capable of predicting both the type and intensit...

How does spatial variability of climate affect catchment streamflow predictions?

EPA Science Inventory

Spatial variability of climate can negatively affect catchment streamflow predictions if it is not explicitly accounted for in hydrologic models. In this paper, we examine the changes in streamflow predictability when a hydrologic model is run with spatially variable (distribute...

Using IBMs to Investigate Spatially-dependent Processes in Landscape Genetics Theory

EPA Science Inventory

Much of landscape and conservation genetics theory has been derived using non-spatialmathematical models. Here, we use a mechanistic, spatially-explicit, eco-evolutionary IBM to examine the utility of this theoretical framework in landscapes with spatial structure. Our analysis...

Biased figure-ground assignment affects conscious object recognition in spatial neglect.

PubMed

Eramudugolla, Ranmalee; Driver, Jon; Mattingley, Jason B

2010-09-01

Unilateral spatial neglect is a disorder of attention and spatial representation, in which early visual processes such as figure-ground segmentation have been assumed to be largely intact. There is evidence, however, that the spatial attention bias underlying neglect can bias the segmentation of a figural region from its background. Relatively few studies have explicitly examined the effect of spatial neglect on processing the figures that result from such scene segmentation. Here, we show that a neglect patient's bias in figure-ground segmentation directly influences his conscious recognition of these figures. By varying the relative salience of figural and background regions in static, two-dimensional displays, we show that competition between elements in such displays can modulate a neglect patient's ability to recognise parsed figures in a scene. The findings provide insight into the interaction between scene segmentation, explicit object recognition, and attention.

Latent spatial models and sampling design for landscape genetics

Treesearch

Ephraim M. Hanks; Melvin B. Hooten; Steven T. Knick; Sara J. Oyler-McCance; Jennifer A. Fike; Todd B. Cross; Michael K. Schwartz

2016-01-01

We propose a spatially-explicit approach for modeling genetic variation across space and illustrate how this approach can be used to optimize spatial prediction and sampling design for landscape genetic data. We propose a multinomial data model for categorical microsatellite allele data commonly used in landscape genetic studies, and introduce a latent spatial...

Cytoskeletal Network Morphology Regulates Intracellular Transport Dynamics

PubMed Central

Ando, David; Korabel, Nickolay; Huang, Kerwyn Casey; Gopinathan, Ajay

2015-01-01

Intracellular transport is essential for maintaining proper cellular function in most eukaryotic cells, with perturbations in active transport resulting in several types of disease. Efficient delivery of critical cargos to specific locations is accomplished through a combination of passive diffusion and active transport by molecular motors that ballistically move along a network of cytoskeletal filaments. Although motor-based transport is known to be necessary to overcome cytoplasmic crowding and the limited range of diffusion within reasonable timescales, the topological features of the cytoskeletal network that regulate transport efficiency and robustness have not been established. Using a continuum diffusion model, we observed that the time required for cellular transport was minimized when the network was localized near the nucleus. In simulations that explicitly incorporated network spatial architectures, total filament mass was the primary driver of network transit times. However, filament traps that redirect cargo back to the nucleus caused large variations in network transport. Filament polarity was more important than filament orientation in reducing average transit times, and transport properties were optimized in networks with intermediate motor on and off rates. Our results provide important insights into the functional constraints on intracellular transport under which cells have evolved cytoskeletal structures, and have potential applications for enhancing reactions in biomimetic systems through rational transport network design. PMID:26488648

USE OF HABITAT-CONTAMINATION SPATIAL CORRELATION TO DETERMINE WHEN TO PERFORM A SPATIALLY EXPLICIT ECOLOGICAL RISK ASSESSMENT

EPA Science Inventory

Anthropogenic contamination is typically distributed heterogeneously through space. This spatial structure can have different effects on the cumulative doses of individuals exposed to contamination within the environment. These effects are accentuated when individuals pursue di...

Kinetic attractor phase diagrams of active nematic suspensions: the dilute regime.

PubMed

Forest, M Gregory; Wang, Qi; Zhou, Ruhai

2015-08-28

Large-scale simulations by the authors of the kinetic-hydrodynamic equations for active polar nematics revealed a variety of spatio-temporal attractors, including steady and unsteady, banded (1d) and cellular (2d) spatial patterns. These particle scale activation-induced attractors arise at dilute nanorod volume fractions where the passive equilibrium phase is isotropic, whereas all previous model simulations have focused on the semi-dilute, nematic equilibrium regime and mostly on low-moment orientation tensor and polarity vector models. Here we extend our previous results to complete attractor phase diagrams for active nematics, with and without an explicit polar potential, to map out novel spatial and dynamic transitions, and to identify some new attractors, over the parameter space of dilute nanorod volume fraction and nanorod activation strength. The particle-scale activation parameter corresponds experimentally to a tunable force dipole strength (so-called pushers with propulsion from the rod tail) generated by active rod macromolecules, e.g., catalysis with the solvent phase, ATP-induced propulsion, or light-activated propulsion. The simulations allow 2d spatial variations in all flow and orientational variables and full spherical orientational degrees of freedom; the attractors correspond to numerical integration of a coupled system of 125 nonlinear PDEs in 2d plus time. The phase diagrams with and without the polar interaction potential are remarkably similar, implying that polar interactions among the rodlike particles are not essential to long-range spatial and temporal correlations in flow, polarity, and nematic order. As a general rule, above a threshold, low volume fractions induce 1d banded patterns, whereas higher yet still dilute volume fractions yield 2d patterns. Again as a general rule, varying activation strength at fixed volume fraction induces novel dynamic transitions. First, stationary patterns saturate the instability of the isotropic state, consisting of discrete 1d banded or 2d cellular patterns depending on nanorod volume fraction. Increasing activation strength further induces a sequence of attractor bifurcations, including oscillations superimposed on the 1d and 2d stationary patterns, a uniform translational motion of 1d and 2d oscillating patterns, and periodic switching between 1d and 2d patterns. These results imply that active macromolecular suspensions are capable of long-range spatial and dynamic organization at isotropic equilibrium concentrations, provided particle-scale activation is sufficiently strong.

Tumor Heterogenity Research Interactive Visualization Environment (THRIVE) | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

A platform for quantitative evaluation of intratumoral spatial heterogeneity in multiplexed immunofluorescence images, via characterization of the spatial interactions between different cellular phenotypes and non-cellular constituents in the tumor microenvironment.

The need for spatially explicit quantification of benefits in invasive-species management.

PubMed

Januchowski-Hartley, Stephanie R; Adams, Vanessa M; Hermoso, Virgilio

2018-04-01

Worldwide, invasive species are a leading driver of environmental change across terrestrial, marine, and freshwater environments and cost billions of dollars annually in ecological damages and economic losses. Resources limit invasive-species control, and planning processes are needed to identify cost-effective solutions. Thus, studies are increasingly considering spatially variable natural and socioeconomic assets (e.g., species persistence, recreational fishing) when planning the allocation of actions for invasive-species management. There is a need to improve understanding of how such assets are considered in invasive-species management. We reviewed over 1600 studies focused on management of invasive species, including flora and fauna. Eighty-four of these studies were included in our final analysis because they focused on the prioritization of actions for invasive species management. Forty-five percent (n = 38) of these studies were based on spatial optimization methods, and 35% (n = 13) accounted for spatially variable assets. Across all 84 optimization studies considered, 27% (n = 23) explicitly accounted for spatially variable assets. Based on our findings, we further explored the potential costs and benefits to invasive species management when spatially variable assets are explicitly considered or not. To include spatially variable assets in decision-making processes that guide invasive-species management there is a need to quantify environmental responses to invasive species and to enhance understanding of potential impacts of invasive species on different natural or socioeconomic assets. We suggest these gaps could be filled by systematic reviews, quantifying invasive species impacts on native species at different periods, and broadening sources and enhancing sharing of knowledge. © 2017 Society for Conservation Biology.

Shared Spatial Representations for Numbers and Space: The Reversal of the SNARC and the Simon Effects

ERIC Educational Resources Information Center

Notebaert, Wim; Gevers, Wim; Verguts, Tom; Fias, Wim

2006-01-01

In 4 experiments, the authors investigated the reversal of spatial congruency effects when participants concurrently practiced incompatible mapping rules (J. G. Marble & R. W. Proctor, 2000). The authors observed an effect of an explicit spatially incompatible mapping rule on the way numerical information was associated with spatial responses. The…

Open space preservation, property value, and optimal spatial configuration

Treesearch

Yong Jiang; Stephen K. Swallow

2007-01-01

The public has increasingly demonstrated a strong support for open space preservation. How to finance the socially efficient level of open space with the optimal spatial structure is of high policy relevance to local governments. In this study, we developed a spatially explicit open space model to help identify the socially optimal amount and optimal spatial...

Promotion of Spatial Skills in Chemistry and Biochemistry Education at the College Level

ERIC Educational Resources Information Center

Oliver-Hoyo, Maria; Babilonia-Rosa, Melissa A.

2017-01-01

Decades of research have demonstrated the correlation of spatial abilities to chemistry achievement and career selection. Nonetheless, reviews have highlighted the need and scarcity of explicit spatial instruction to promote spatial skills. Therefore, the goal of this literature review is to summarize what has been done during the past decade in…

How Far Is "Near"? Inferring Distance from Spatial Descriptions

ERIC Educational Resources Information Center

Carlson, Laura A.; Covey, Eric S.

2005-01-01

A word may mean different things in different contexts. The current study explored the changing denotations of spatial terms, focusing on how the distance inferred from a spatial description varied as a function of the size of the objects being spatially related. We examined both terms that explicitly convey distance (i.e., topological terms such…

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.

On Spatially Explicit Models of Epidemic and Endemic Cholera: The Haiti and Lake Kivu Case Studies.

NASA Astrophysics Data System (ADS)

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

2014-12-01

The first part of the Lecture deals with the predictive ability of mechanistic models for the Haitian cholera epidemic. Predictive models of epidemic cholera need to resolve at suitable aggregation levels spatial data pertaining to local communities, epidemiological records, hydrologic drivers, waterways, patterns of human mobility and proxies of exposure rates. A formal model comparison framework provides a quantitative assessment of the explanatory and predictive abilities of various model settings with different spatial aggregation levels. Intensive computations and objective model comparisons show that parsimonious spatially explicit models accounting for spatial connections have superior explanatory power than spatially disconnected ones for short-to intermediate calibration windows. In general, spatially connected models show better predictive ability than disconnected ones. We suggest limits and validity of the various approaches and discuss the pathway towards the development of case-specific predictive tools in the context of emergency management. The second part deals with approaches suitable to describe patterns of endemic cholera. Cholera outbreaks have been reported in the Democratic Republic of the Congo since the 1970s. Here we employ a spatially explicit, inhomogeneous Markov chain model to describe cholera incidence in eight health zones on the shore of lake Kivu. Remotely sensed datasets of chlorophyll a concentration in the lake, precipitation and indices of global climate anomalies are used as environmental drivers in addition to baseline seasonality. The effect of human mobility is also modelled mechanistically. We test several models on a multi-year dataset of reported cholera cases. Fourteen models, accounting for different environmental drivers, are selected in calibration. Among these, the one accounting for seasonality, El Nino Southern Oscillation, precipitation and human mobility outperforms the others in cross-validation.

Multicellular regulation of entropy, spatial order, and information

NASA Astrophysics Data System (ADS)

Youk, Hyun

Many multicellular systems such as tissues and microbial biofilms consist of cells that secrete and sense signalling molecules. Understanding how collective behaviours of secrete-and-sense cells is an important challenge. We combined experimental and theoretical approaches to understand multicellular coordination of gene expression and spatial pattern formation among secrete-and-sense cells. We engineered secrete-and-sense yeast cells to show that cells can collectively and permanently remember a past event by reminding each other with their secreted signalling molecule. If one cell ``forgets'' then another cell can remind it. Cell-cell communication ensures a long-term (permanent) memory by overcoming common limitations of intracellular memory. We also established a new theoretical framework inspired by statistical mechanics to understand how fields of secrete-and-sense cells form spatial patterns. We introduce new metrics - cellular entropy, cellular Hamiltonian, and spatial order index - for dynamics of cellular automata that form spatial patterns. Our theory predicts how fast any spatial patterns form, how ordered they are, and establishes cellular Hamiltonian that, like energy for non-living systems, monotonically decreases towards a minimum over time. ERC Starting Grant (MultiCellSysBio), NWO VIDI, NWO NanoFront.

Modeling spatial variation in avian survival and residency probabilities

USGS Publications Warehouse

Saracco, James F.; Royle, J. Andrew; DeSante, David F.; Gardner, Beth

2010-01-01

The importance of understanding spatial variation in processes driving animal population dynamics is widely recognized. Yet little attention has been paid to spatial modeling of vital rates. Here we describe a hierarchical spatial autoregressive model to provide spatially explicit year-specific estimates of apparent survival (phi) and residency (pi) probabilities from capture-recapture data. We apply the model to data collected on a declining bird species, Wood Thrush (Hylocichla mustelina), as part of a broad-scale bird-banding network, the Monitoring Avian Productivity and Survivorship (MAPS) program. The Wood Thrush analysis showed variability in both phi and pi among years and across space. Spatial heterogeneity in residency probability was particularly striking, suggesting the importance of understanding the role of transients in local populations. We found broad-scale spatial patterning in Wood Thrush phi and pi that lend insight into population trends and can direct conservation and research. The spatial model developed here represents a significant advance over approaches to investigating spatial pattern in vital rates that aggregate data at coarse spatial scales and do not explicitly incorporate spatial information in the model. Further development and application of hierarchical capture-recapture models offers the opportunity to more fully investigate spatiotemporal variation in the processes that drive population changes.

Spatial Contiguity and Incidental Learning in Multimedia Environments

ERIC Educational Resources Information Center

Paek, Seungoh; Hoffman, Daniel L.; Saravanos, Antonios

2017-01-01

Drawing on dual-process theories of cognitive function, the degree to which spatial contiguity influences incidental learning outcomes was examined. It was hypothesized that spatial contiguity would mediate what was learned even in the absence of an explicit learning goal. To test this hypothesis, 149 adults completed a multimedia-related task…

Utility of computer simulations in landscape genetics

Treesearch

Bryan K. Epperson; Brad H. McRae; Kim Scribner; Samuel A. Cushman; Michael S. Rosenberg; Marie-Josee Fortin; Patrick M. A. James; Melanie Murphy; Stephanie Manel; Pierre Legendre; Mark R. T. Dale

2010-01-01

Population genetics theory is primarily based on mathematical models in which spatial complexity and temporal variability are largely ignored. In contrast, the field of landscape genetics expressly focuses on how population genetic processes are affected by complex spatial and temporal environmental heterogeneity. It is spatially explicit and relates patterns to...

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...

A cellular automata approach for modeling surface water runoff

NASA Astrophysics Data System (ADS)

Jozefik, Zoltan; Nanu Frechen, Tobias; Hinz, Christoph; Schmidt, Heiko

2015-04-01

This abstract reports the development and application of a two-dimensional cellular automata based model, which couples the dynamics of overland flow, infiltration processes and surface evolution through sediment transport. The natural hill slopes are represented by their topographic elevation and spatially varying soil properties infiltration rates and surface roughness coefficients. This model allows modeling of Hortonian overland flow and infiltration during complex rainfall events. An advantage of the cellular automata approach over the kinematic wave equations is that wet/dry interfaces that often appear with rainfall overland flows can be accurately captured and are not a source of numerical instabilities. An adaptive explicit time stepping scheme allows for rainfall events to be adequately resolved in time, while large time steps are taken during dry periods to provide for simulation run time efficiency. The time step is constrained by the CFL condition and mass conservation considerations. The spatial discretization is shown to be first-order accurate. For validation purposes, hydrographs for non-infiltrating and infiltrating plates are compared to the kinematic wave analytic solutions and data taken from literature [1,2]. Results show that our cellular automata model quantitatively accurately reproduces hydrograph patterns. However, recent works have showed that even through the hydrograph is satisfyingly reproduced, the flow field within the plot might be inaccurate [3]. For a more stringent validation, we compare steady state velocity, water flux, and water depth fields to rainfall simulation experiments conducted in Thies, Senegal [3]. Comparisons show that our model is able to accurately capture these flow properties. Currently, a sediment transport and deposition module is being implemented and tested. [1] M. Rousseau, O. Cerdan, O. Delestre, F. Dupros, F. James, S. Cordier. Overland flow modeling with the Shallow Water Equation using a well balanced numerical scheme: Adding efficiency or sum more complexity?. 2012. [2] Fritz R. Fiedler, J. A. Ramirez. A numerical method for simulating discontinuous shallow flow over an infiltrating surface. In. J. Numer. Mech. Fluids 200: 32: 219-240. [3] C. Mügler, O. Planchon, J. Patin, S. Weill, N. Silvera, P. Richard, E. Mouche. Comparison of Roughness models to simulate overland flow and tracer transport experiments under simulated rainfall at plot scale. Journal of Hydrology. 402 (2011) 25-40.

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.

Modeling the spatial and temporal variability in climate and primary productivity across the Luquillo Mountains, Puerto Rico.

Treesearch

Hongqing Wanga; Charles A.S. Halla; Frederick N. Scatenab; Ned Fetcherc; Wei Wua

2003-01-01

There are few studies that have examined the spatial variability of forest productivity over an entire tropical forested landscape. In this study, we used a spatially-explicit forest productivity model, TOPOPROD, which is based on the FORESTBGC model, to simulate spatial patterns of gross primary productivity (GPP), net primary productivity (NPP), and respiration over...

High-Order Space-Time Methods for Conservation Laws

NASA Technical Reports Server (NTRS)

Huynh, H. T.

2013-01-01

Current high-order methods such as discontinuous Galerkin and/or flux reconstruction can provide effective discretization for the spatial derivatives. Together with a time discretization, such methods result in either too small a time step size in the case of an explicit scheme or a very large system in the case of an implicit one. To tackle these problems, two new high-order space-time schemes for conservation laws are introduced: the first is explicit and the second, implicit. The explicit method here, also called the moment scheme, achieves a Courant-Friedrichs-Lewy (CFL) condition of 1 for the case of one-spatial dimension regardless of the degree of the polynomial approximation. (For standard explicit methods, if the spatial approximation is of degree p, then the time step sizes are typically proportional to 1/p(exp 2)). Fourier analyses for the one and two-dimensional cases are carried out. The property of super accuracy (or super convergence) is discussed. The implicit method is a simplified but optimal version of the discontinuous Galerkin scheme applied to time. It reduces to a collocation implicit Runge-Kutta (RK) method for ordinary differential equations (ODE) called Radau IIA. The explicit and implicit schemes are closely related since they employ the same intermediate time levels, and the former can serve as a key building block in an iterative procedure for the latter. A limiting technique for the piecewise linear scheme is also discussed. The technique can suppress oscillations near a discontinuity while preserving accuracy near extrema. Preliminary numerical results are shown

Towards a minimal stochastic model for a large class of diffusion-reactions on biological membranes.

PubMed

Chevalier, Michael W; El-Samad, Hana

2012-08-28

Diffusion of biological molecules on 2D biological membranes can play an important role in the behavior of stochastic biochemical reaction systems. Yet, we still lack a fundamental understanding of circumstances where explicit accounting of the diffusion and spatial coordinates of molecules is necessary. In this work, we illustrate how time-dependent, non-exponential reaction probabilities naturally arise when explicitly accounting for the diffusion of molecules. We use the analytical expression of these probabilities to derive a novel algorithm which, while ignoring the exact position of the molecules, can still accurately capture diffusion effects. We investigate the regions of validity of the algorithm and show that for most parameter regimes, it constitutes an accurate framework for studying these systems. We also document scenarios where large spatial fluctuation effects mandate explicit consideration of all the molecules and their positions. Taken together, our results derive a fundamental understanding of the role of diffusion and spatial fluctuations in these systems. Simultaneously, they provide a general computational methodology for analyzing a broad class of biological networks whose behavior is influenced by diffusion on membranes.

Spatially explicit decision support for selecting translocation areas for Mojave desert tortoises

USGS Publications Warehouse

Heaton, Jill S.; Nussear, Kenneth E.; Esque, Todd C.; Inman, Richard D.; Davenport, Frank; Leuteritz, Thomas E.; Medica, Philip A.; Strout, Nathan W.; Burgess, Paul A.; Benvenuti, Lisa

2008-01-01

Spatially explicit decision support systems are assuming an increasing role in natural resource and conservation management. In order for these systems to be successful, however, they must address real-world management problems with input from both the scientific and management communities. The National Training Center at Fort Irwin, California, has expanded its training area, encroaching U.S. Fish and Wildlife Service critical habitat set aside for the Mojave desert tortoise (Gopherus agassizii), a federally threatened species. Of all the mitigation measures proposed to offset expansion, the most challenging to implement was the selection of areas most feasible for tortoise translocation. We developed an objective, open, scientifically defensible spatially explicit decision support system to evaluate translocation potential within the Western Mojave Recovery Unit for tortoise populations under imminent threat from military expansion. Using up to a total of 10 biological, anthropogenic, and/or logistical criteria, seven alternative translocation scenarios were developed. The final translocation model was a consensus model between the seven scenarios. Within the final model, six potential translocation areas were identified.

Using spatially explicit surveillance models to provide confidence in the eradication of an invasive ant

PubMed Central

Ward, Darren F.; Anderson, Dean P.; Barron, Mandy C.

2016-01-01

Effective detection plays an important role in the surveillance and management of invasive species. Invasive ants are very difficult to eradicate and are prone to imperfect detection because of their small size and cryptic nature. Here we demonstrate the use of spatially explicit surveillance models to estimate the probability that Argentine ants (Linepithema humile) have been eradicated from an offshore island site, given their absence across four surveys and three surveillance methods, conducted since ant control was applied. The probability of eradication increased sharply as each survey was conducted. Using all surveys and surveillance methods combined, the overall median probability of eradication of Argentine ants was 0.96. There was a high level of confidence in this result, with a high Credible Interval Value of 0.87. Our results demonstrate the value of spatially explicit surveillance models for the likelihood of eradication of Argentine ants. We argue that such models are vital to give confidence in eradication programs, especially from highly valued conservation areas such as offshore islands. PMID:27721491

Systems Modeling at Multiple Levels of Regulation: Linking Systems and Genetic Networks to Spatially Explicit Plant Populations

PubMed Central

Kitchen, James L.; Allaby, Robin G.

2013-01-01

Selection and adaptation of individuals to their underlying environments are highly dynamical processes, encompassing interactions between the individual and its seasonally changing environment, synergistic or antagonistic interactions between individuals and interactions amongst the regulatory genes within the individual. Plants are useful organisms to study within systems modeling because their sedentary nature simplifies interactions between individuals and the environment, and many important plant processes such as germination or flowering are dependent on annual cycles which can be disrupted by climate behavior. Sedentism makes plants relevant candidates for spatially explicit modeling that is tied in with dynamical environments. We propose that in order to fully understand the complexities behind plant adaptation, a system that couples aspects from systems biology with population and landscape genetics is required. A suitable system could be represented by spatially explicit individual-based models where the virtual individuals are located within time-variable heterogeneous environments and contain mutable regulatory gene networks. These networks could directly interact with the environment, and should provide a useful approach to studying plant adaptation. PMID:27137364

Multilayer networks reveal the spatial structure of seed-dispersal interactions across the Great Rift landscapes.

PubMed

Timóteo, Sérgio; Correia, Marta; Rodríguez-Echeverría, Susana; Freitas, Helena; Heleno, Ruben

2018-01-10

Species interaction networks are traditionally explored as discrete entities with well-defined spatial borders, an oversimplification likely impairing their applicability. Using a multilayer network approach, explicitly accounting for inter-habitat connectivity, we investigate the spatial structure of seed-dispersal networks across the Gorongosa National Park, Mozambique. We show that the overall seed-dispersal network is composed by spatially explicit communities of dispersers spanning across habitats, functionally linking the landscape mosaic. Inter-habitat connectivity determines spatial structure, which cannot be accurately described with standard monolayer approaches either splitting or merging habitats. Multilayer modularity cannot be predicted by null models randomizing either interactions within each habitat or those linking habitats; however, as habitat connectivity increases, random processes become more important for overall structure. The importance of dispersers for the overall network structure is captured by multilayer versatility but not by standard metrics. Highly versatile species disperse many plant species across multiple habitats, being critical to landscape functional cohesion.

The Stabilizing Effect of Spacetime Expansion on Relativistic Fluids With Sharp Results for the Radiation Equation of State

NASA Astrophysics Data System (ADS)

Speck, Jared

2013-07-01

In this article, we study the 1 + 3-dimensional relativistic Euler equations on a pre-specified conformally flat expanding spacetime background with spatial slices that are diffeomorphic to {R}^3. We assume that the fluid verifies the equation of state {p = c2s ρ,} where {0 ≤ cs ≤ √{1/3}} is the speed of sound. We also assume that the reciprocal of the scale factor associated with the expanding spacetime metric verifies a c s -dependent time-integrability condition. Under these assumptions, we use the vector field energy method to prove that an explicit family of physically motivated, spatially homogeneous, and spatially isotropic fluid solutions are globally future-stable under small perturbations of their initial conditions. The explicit solutions corresponding to each scale factor are analogs of the well-known spatially flat Friedmann-Lemaître-Robertson-Walker family. Our nonlinear analysis, which exploits dissipative terms generated by the expansion, shows that the perturbed solutions exist for all future times and remain close to the explicit solutions. This work is an extension of previous results, which showed that an analogous stability result holds when the spacetime is exponentially expanding. In the case of the radiation equation of state p = (1/3)ρ, we also show that if the time-integrability condition for the reciprocal of the scale factor fails to hold, then the explicit fluid solutions are unstable. More precisely, we show the existence of an open family of initial data such that (i) it contains arbitrarily small smooth perturbations of the explicit solutions' data and (ii) the corresponding perturbed solutions necessarily form shocks in finite time. The shock formation proof is based on the conformal invariance of the relativistic Euler equations when {c2s = 1/3,} which allows for a reduction to a well-known result of Christodoulou.

Effects of spatial variability and scale on areal -average evapotranspiration

NASA Technical Reports Server (NTRS)

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

1993-01-01

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

Unique spatial and cellular expression patterns of Hoxa5, Hoxb4 and Hoxb6 proteins in normal developing murine lung are modified in pulmonary hypoplasia

PubMed Central

Volpe, MaryAnn Vitoria; Wang, Karen Ting Wai; Nielsen, Heber Carl; Chinoy, Mala Romeshchandra

2009-01-01

Background Hox transcription factors modulate signaling pathways controlling organ morphogenesis and maintain cell fate and differentiation in adults. Retinoid signaling, key in regulating Hox expression, is altered in pulmonary hypoplasia. Information on pattern-specific expression of Hox proteins in normal lung development and in pulmonary hypoplasia is minimal. Our objective was to determine how pulmonary hypoplasia alters temporal, spatial and cellular expression of Hoxa5, Hoxb4 and Hoxb6 proteins compared to normal lung development. Methods Temporal, spatial and cellular Hoxa5, Hoxb4 and Hoxb6 expression was studied in normal (untreated) and nitrofen-induced hypoplastic (NT-PH) lungs from gestational day 13.5, 16, 19 fetuses and neonates using western blot and immunohistochemistry. Results Modification of protein levels and spatial and cellular Hox expression patterns in NT-PH lungs was consistent with delayed lung development. Distinct protein isoforms were detected for each Hox protein. Expression levels of the Hoxa5 and Hoxb6 isoforms changed with development and further in NT-PH lungs. Compared to normal lungs, Gd19 and neonatal NT-PH lungs had decreased Hoxb6 and increased Hoxa5 and Hoxb4. Hoxa5 cellular localization changed from mesenchyme to epithelia earlier in normal lungs. Hoxb4 was expressed in mesenchyme and epithelial cells throughout development. Hoxb6 remained mainly in mesenchymal cells around distal airways. Conclusions Unique spatial and cellular expression of Hoxa5, Hoxb4 and Hoxb6 participates in branching morphogenesis and terminal sac formation. Altered Hox protein temporal and cellular balance of expression either contributes to pulmonary hypoplasia or functions as a compensatory mechanism attempting to correct abnormal lung development and maturation in this condition. PMID:18553509

Climate change and plant dispersal along corridors in fragmented landscapes of Mesoamerica

PubMed Central

Imbach, Pablo A; Locatelli, Bruno; Molina, Luis G; Ciais, Philippe; Leadley, Paul W

2013-01-01

Climate change is a threat to biodiversity, and adaptation measures should be considered in biodiversity conservation planning. Protected areas (PA) are expected to be impacted by climate change and improving their connectivity with biological corridors (BC) has been proposed as a potential adaptation measure, although assessing its effectiveness remains a challenge. In Mesoamerica, efforts to preserve the biodiversity have led to the creation of a regional network of PA and, more recently, BC. This study evaluates the role of BC for facilitating plant dispersal between PA under climate change in Mesoamerica. A spatially explicit dynamic model (cellular automaton) was developed to simulate species dispersal under different climate and conservation policy scenarios. Plant functional types (PFT) were defined based on a range of dispersal rates and vegetation types to represent the diversity of species in the region. The impacts of climate change on PA and the role of BC for dispersal were assessed spatially. Results show that most impacted PA are those with low altitudinal range in hot, dry, or high latitude areas. PA with low altitudinal range in high cool areas benefit the most from corridors. The most important corridors cover larger areas and have high altitude gradients. Only the fastest PFT can keep up with the expected change in climate and benefit from corridors for dispersal. We conclude that the spatial assessment of the vulnerability of PA and the role of corridors in facilitating dispersal can help conservation planning under a changing climate. PMID:24101983

Characterizing forest fragments in boreal, temperate, and tropical ecosystems

Treesearch

Arjan J. H. Meddens; Andrew T. Hudak; Jeffrey S. Evans; William A. Gould; Grizelle Gonzalez

2008-01-01

An increased ability to analyze landscapes in a spatial manner through the use of remote sensing leads to improved capabilities for quantifying human-induced forest fragmentation. Developments of spatially explicit methods in landscape analyses are emerging. In this paper, the image delineation software program eCognition and the spatial pattern analysis program...

Spatiality and the Place of the Material in Schools

ERIC Educational Resources Information Center

McGregor, Jane

2004-01-01

Drawing on a research study into the spatiality of teachers' workplaces, this article explores the "concrete realities" of the artefact-filled world with which teachers, support staff and students interact, and considers the way in which networks of people and things order the spaces of the school. Spatiality is examined explicitly in…

Attending to space within and between objects: Implications from a patient with Balint’s syndrome

PubMed Central

Robertson, Lynn C.; Treisman, Anne

2007-01-01

Neuropsychological conditions such as Balint’s syndrome have shown that perceptual organization of parts into a perceptual unit can be dissociated from the ability to localize objects relative to each other. Neural mechanisms that code the spatial structure within individual objects or words may seem to be intact, while between-object structure is compromised. Here we investigate the nature of within-object spatial processing in a patient with Balint’s syndrome (RM). We suggest that within-object spatial structure can be determined (a) directly by explicit spatial processing of between-part relations, mediated by the same dorsal pathway as between-object spatial relations; or (b) indirectly by the discrimination of object identities, which may involve implicit processing of between-part relations and which is probably mediated by the ventral system. When this route is ruled out, by testing discrimination of differences in part location that do not change the identity of the object, we find no evidence of explicit within-object spatial coding in a patient without functioning parietal lobes. PMID:21049339

Rotational wind indicator enhances control of rotated displays

NASA Technical Reports Server (NTRS)

Cunningham, H. A.; Pavel, Misha

1991-01-01

Rotation by 108 deg of the spatial mapping between a visual display and a manual input device produces large spatial errors in a discrete aiming task. These errors are not easily corrected by voluntary mental effort, but the central nervous system does adapt gradually to the new mapping. Bernotat (1970) showed that adding true hand position to a 90 deg rotated display improved performance of a compensatory tracking task, but tracking error rose again upon removal of the explicit cue. This suggests that the explicit error signal did not induce changes in the neural mapping, but rather allowed the operator to reduce tracking error using a higher mental strategy. In this report, we describe an explicit visual display enhancement applied to a 108 deg rotated discrete aiming task. A 'wind indicator' corresponding to the effect of the mapping rotation is displayed on the operator-controlled cursor. The human operator is instructed to oppose the virtual force represented by the indicator, as one would do if flying an airplane in a crosswind. This enhancement reduces spatial aiming error in the first 10 minutes of practice by an average of 70 percent when compared to a no enhancement control condition. Moreover, it produces adaptation aftereffect, which is evidence of learning by neural adaptation rather than by mental strategy. Finally, aiming error does not rise upon removal of the explicit cue.

Empirical evaluation of spatial and non-spatial European-scale multimedia fate models: results and implications for chemical risk assessment.

PubMed

Armitage, James M; Cousins, Ian T; Hauck, Mara; Harbers, Jasper V; Huijbregts, Mark A J

2007-06-01

Multimedia environmental fate models are commonly-applied tools for assessing the fate and distribution of contaminants in the environment. Owing to the large number of chemicals in use and the paucity of monitoring data, such models are often adopted as part of decision-support systems for chemical risk assessment. The purpose of this study was to evaluate the performance of three multimedia environmental fate models (spatially- and non-spatially-explicit) at a European scale. The assessment was conducted for four polycyclic aromatic hydrocarbons (PAHs) and hexachlorobenzene (HCB) and compared predicted and median observed concentrations using monitoring data collected for air, water, sediments and soils. Model performance in the air compartment was reasonable for all models included in the evaluation exercise as predicted concentrations were typically within a factor of 3 of the median observed concentrations. Furthermore, there was good correspondence between predictions and observations in regions that had elevated median observed concentrations for both spatially-explicit models. On the other hand, all three models consistently underestimated median observed concentrations in sediment and soil by 1-3 orders of magnitude. Although regions with elevated median observed concentrations in these environmental media were broadly identified by the spatially-explicit models, the magnitude of the discrepancy between predicted and median observed concentrations is of concern in the context of chemical risk assessment. These results were discussed in terms of factors influencing model performance such as the steady-state assumption, inaccuracies in emission estimates and the representativeness of monitoring data.

Modelling the effect of urbanization on the transmission of an infectious disease.

PubMed

Zhang, Ping; Atkinson, Peter M

2008-01-01

This paper models the impact of urbanization on infectious disease transmission by integrating a CA land use development model, population projection matrix model and CA epidemic model in S-Plus. The innovative feature of this model lies in both its explicit treatment of spatial land use development, demographic changes, infectious disease transmission and their combination in a dynamic, stochastic model. Heuristically-defined transition rules in cellular automata (CA) were used to capture the processes of both land use development with urban sprawl and infectious disease transmission. A population surface model and dwelling distribution surface were used to bridge the gap between urbanization and infectious disease transmission. A case study is presented involving modelling influenza transmission in Southampton, a dynamically evolving city in the UK. The simulation results for Southampton over a 30-year period show that the pattern of the average number of infection cases per day can depend on land use and demographic changes. The modelling framework presents a useful tool that may be of use in planning applications.

Beyond input-output computings: error-driven emergence with parallel non-distributed slime mold computer.

PubMed

Aono, Masashi; Gunji, Yukio-Pegio

2003-10-01

The emergence derived from errors is the key importance for both novel computing and novel usage of the computer. In this paper, we propose an implementable experimental plan for the biological computing so as to elicit the emergent property of complex systems. An individual plasmodium of the true slime mold Physarum polycephalum acts in the slime mold computer. Modifying the Elementary Cellular Automaton as it entails the global synchronization problem upon the parallel computing provides the NP-complete problem solved by the slime mold computer. The possibility to solve the problem by giving neither all possible results nor explicit prescription of solution-seeking is discussed. In slime mold computing, the distributivity in the local computing logic can change dynamically, and its parallel non-distributed computing cannot be reduced into the spatial addition of multiple serial computings. The computing system based on exhaustive absence of the super-system may produce, something more than filling the vacancy.

REVIEW OF SIMULATION METHODS FOR SPATIALLY-EXPLICIT POPULATION-LEVEL RISK ASSESSMENT

EPA Science Inventory

Factors that significantly impact population dynamics, such as resource availability and exposure to stressors, frequently vary over space and thereby determine the heterogeneous spatial distributions of organisms. Considering this fact, the US Environmental Protection Agency's ...

Rapid Response Tools and Datasets for Post-fire Hydrological Modeling

NASA Astrophysics Data System (ADS)

Miller, Mary Ellen; MacDonald, Lee H.; Billmire, Michael; Elliot, William J.; Robichaud, Pete R.

2016-04-01

Rapid response is critical following natural disasters. Flooding, erosion, and debris flows are a major threat to life, property and municipal water supplies after moderate and high severity wildfires. The problem is that mitigation measures must be rapidly implemented if they are to be effective, but they are expensive and cannot be applied everywhere. Fires, runoff, and erosion risks also are highly heterogeneous in space, so there is an urgent need for a rapid, spatially-explicit assessment. Past post-fire modeling efforts have usually relied on lumped, conceptual models because of the lack of readily available, spatially-explicit data layers on the key controls of topography, vegetation type, climate, and soil characteristics. The purpose of this project is to develop a set of spatially-explicit data layers for use in process-based models such as WEPP, and to make these data layers freely available. The resulting interactive online modeling database (http://geodjango.mtri.org/geowepp/) is now operational and publically available for 17 western states in the USA. After a fire, users only need to upload a soil burn severity map, and this is combined with the pre-existing data layers to generate the model inputs needed for spatially explicit models such as GeoWEPP (Renschler, 2003). The development of this online database has allowed us to predict post-fire erosion and various remediation scenarios in just 1-7 days for six fires ranging in size from 4-540 km2. These initial successes have stimulated efforts to further improve the spatial extent and amount of data, and add functionality to support the USGS debris flow model, batch processing for Disturbed WEPP (Elliot et al., 2004) and ERMiT (Robichaud et al., 2007), and to support erosion modeling for other land uses, such as agriculture or mining. The design and techniques used to create the database and the modeling interface are readily repeatable for any area or country that has the necessary topography, climate, soil, and land cover datasets.

The influence of uncertainty and location-specific conditions on the environmental prioritisation of human pharmaceuticals in Europe.

PubMed

Oldenkamp, Rik; Huijbregts, Mark A J; Ragas, Ad M J

2016-05-01

The selection of priority APIs (Active Pharmaceutical Ingredients) can benefit from a spatially explicit approach, since an API might exceed the threshold of environmental concern in one location, while staying below that same threshold in another. However, such a spatially explicit approach is relatively data intensive and subject to parameter uncertainty due to limited data. This raises the question to what extent a spatially explicit approach for the environmental prioritisation of APIs remains worthwhile when accounting for uncertainty in parameter settings. We show here that the inclusion of spatially explicit information enables a more efficient environmental prioritisation of APIs in Europe, compared with a non-spatial EU-wide approach, also under uncertain conditions. In a case study with nine antibiotics, uncertainty distributions of the PAF (Potentially Affected Fraction) of aquatic species were calculated in 100∗100km(2) environmental grid cells throughout Europe, and used for the selection of priority APIs. Two APIs have median PAF values that exceed a threshold PAF of 1% in at least one environmental grid cell in Europe, i.e., oxytetracycline and erythromycin. At a tenfold lower threshold PAF (i.e., 0.1%), two additional APIs would be selected, i.e., cefuroxime and ciprofloxacin. However, in 94% of the environmental grid cells in Europe, no APIs exceed either of the thresholds. This illustrates the advantage of following a location-specific approach in the prioritisation of APIs. This added value remains when accounting for uncertainty in parameter settings, i.e., if the 95th percentile of the PAF instead of its median value is compared with the threshold. In 96% of the environmental grid cells, the location-specific approach still enables a reduction of the selection of priority APIs of at least 50%, compared with a EU-wide prioritisation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Spatially explicit modeling of 1992-2100 land cover and forest stand age for the conterminous United States

USGS Publications Warehouse

Sohl, Terry L.; Sayler, Kristi L.; Bouchard, Michelle; Reker, Ryan R.; Friesz, Aaron M.; Bennett, Stacie L.; Sleeter, Benjamin M.; Sleeter, Rachel R.; Wilson, Tamara; Soulard, Christopher E.; Knuppe, Michelle; Van Hofwegen, Travis

2014-01-01

Information on future land-use and land-cover (LULC) change is needed to analyze the impact of LULC change on ecological processes. The U.S. Geological Survey has produced spatially explicit, thematically detailed LULC projections for the conterminous United States. Four qualitative and quantitative scenarios of LULC change were developed, with characteristics consistent with the Intergovernmental Panel on Climate Change (IPCC) Special Report on 5 Emission Scenarios (SRES). The four quantified scenarios (A1B, A2, B1, and B2) served as input to the Forecasting Scenarios of Land-use Change (FORE-SCE) model. Four spatially explicit datasets consistent with scenario storylines were produced for the conterminous United States, with annual LULC maps from 1992 through 2100. The future projections are characterized by a loss of natural land covers in most scenarios, with corresponding expansion of 10 anthropogenic land uses. Along with the loss of natural land covers, remaining natural land covers experience increased fragmentation under most scenarios, with only the B2 scenario remaining relatively stable in both proportion of remaining natural land covers and basic fragmentation measures. Forest stand age was also modeled. By 2100, scenarios and ecoregions with heavy forest cutting have relatively lower mean stand ages compared to those with less 15 forest cutting. Stand ages differ substantially between unprotected and protected forest lands, as well as between different forest classes. The modeled data were compared to the National Land Cover Database (NLCD) and other data sources to assess model characteristics. The consistent, spatially explicit, and thematically detailed LULC projections and the associated forest stand age data layers have been used to analyze LULC impacts on carbon and greenhouse gas fluxes, 20 biodiversity, climate and weather variability, hydrologic change, and other ecological processes.

On the spatial heterogeneity of net ecosystem productivity in complex landscapes

Treesearch

Ryan E. Emanuel; Diego A. Riveros-Iregui; Brian L. McGlynn; Howard E. Epstein

2011-01-01

Micrometeorological flux towers provide spatially integrated estimates of net ecosystem production (NEP) of carbon over areas ranging from several hectares to several square kilometers, but they do so at the expense of spatially explicit information within the footprint of the tower. This finer-scale information is crucial for understanding how physical and biological...

Spatial abstraction for autonomous robot navigation.

PubMed

Epstein, Susan L; Aroor, Anoop; Evanusa, Matthew; Sklar, Elizabeth I; Parsons, Simon

2015-09-01

Optimal navigation for a simulated robot relies on a detailed map and explicit path planning, an approach problematic for real-world robots that are subject to noise and error. This paper reports on autonomous robots that rely on local spatial perception, learning, and commonsense rationales instead. Despite realistic actuator error, learned spatial abstractions form a model that supports effective travel.

FUEL3-D: A Spatially Explicit Fractal Fuel Distribution Model

Treesearch

Russell A. Parsons

2006-01-01

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

A spatial stochastic programming model for timber and core area management under risk of stand-replacing fire

Treesearch

Dung Tuan Nguyen

2012-01-01

Forest harvest scheduling has been modeled using deterministic and stochastic programming models. Past models seldom address explicit spatial forest management concerns under the influence of natural disturbances. In this research study, we employ multistage full recourse stochastic programming models to explore the challenges and advantages of building spatial...

A spatial stochastic programming model for timber and core area management under risk of fires

Treesearch

Yu Wei; Michael Bevers; Dung Nguyen; Erin Belval

2014-01-01

Previous stochastic models in harvest scheduling seldom address explicit spatial management concerns under the influence of natural disturbances. We employ multistage stochastic programming models to explore the challenges and advantages of building spatial optimization models that account for the influences of random stand-replacing fires. Our exploratory test models...

High-resolution infrared thermography for capturing wildland fire behaviour - RxCADRE 2012

Treesearch

Joseph J. O’Brien; E. Louise Loudermilk; Benjamin Hornsby; Andrew T. Hudak; Benjamin C. Bright; Matthew B. Dickinson; J. Kevin Hiers; Casey Teske; Roger D. Ottmar

2016-01-01

Wildland fire radiant energy emission is one of the only measurements of combustion that can be made at wide spatial extents and high temporal and spatial resolutions. Furthermore, spatially and temporally explicit measurements are critical for making inferences about fire effects and useful for examining patterns of fire spread. In this study we describe our...

Using the van Hiele K-12 Geometry Learning Theory to Modify Engineering Mechanics Instruction

ERIC Educational Resources Information Center

Sharp, Janet M.; Zachary, Loren W.

2004-01-01

Engineering students use spatial thinking when examining diagrams or models to study structure design. It is expected that most engineering students have solidified spatial thinking skills during K-12 schooling. However, according to what we know about geometry learning and teaching, spatial thinking probably needs to be explicitly taught within…

Cytoskeletal Network Morphology Regulates Intracellular Transport Dynamics.

PubMed

Ando, David; Korabel, Nickolay; Huang, Kerwyn Casey; Gopinathan, Ajay

2015-10-20

Intracellular transport is essential for maintaining proper cellular function in most eukaryotic cells, with perturbations in active transport resulting in several types of disease. Efficient delivery of critical cargos to specific locations is accomplished through a combination of passive diffusion and active transport by molecular motors that ballistically move along a network of cytoskeletal filaments. Although motor-based transport is known to be necessary to overcome cytoplasmic crowding and the limited range of diffusion within reasonable timescales, the topological features of the cytoskeletal network that regulate transport efficiency and robustness have not been established. Using a continuum diffusion model, we observed that the time required for cellular transport was minimized when the network was localized near the nucleus. In simulations that explicitly incorporated network spatial architectures, total filament mass was the primary driver of network transit times. However, filament traps that redirect cargo back to the nucleus caused large variations in network transport. Filament polarity was more important than filament orientation in reducing average transit times, and transport properties were optimized in networks with intermediate motor on and off rates. Our results provide important insights into the functional constraints on intracellular transport under which cells have evolved cytoskeletal structures, and have potential applications for enhancing reactions in biomimetic systems through rational transport network design. Copyright © 2015 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Spatial-explicit modeling of social vulnerability to malaria in East Africa

PubMed Central

2014-01-01

Background Despite efforts in eradication and control, malaria remains a global challenge, particularly affecting vulnerable groups. Despite the recession in malaria cases, previously malaria free areas are increasingly confronted with epidemics as a result of changing environmental and socioeconomic conditions. Next to modeling transmission intensities and probabilities, integrated spatial methods targeting the complex interplay of factors that contribute to social vulnerability are required to effectively reduce malaria burden. We propose an integrative method for mapping relative levels of social vulnerability in a spatially explicit manner to support the identification of intervention measures. Methods Based on a literature review, a holistic risk and vulnerability framework has been developed to guide the assessment of social vulnerability to water-related vector-borne diseases (VBDs) in the context of changing environmental and societal conditions. Building on the framework, this paper applies spatially explicit modeling for delineating homogeneous regions of social vulnerability to malaria in eastern Africa, while taking into account expert knowledge for weighting the single vulnerability indicators. To assess the influence of the selected indicators on the final index a local sensitivity analysis is carried out. Results Results indicate that high levels of malaria vulnerability are concentrated in the highlands, where immunity within the population is currently low. Additionally, regions with a lack of access to education and health services aggravate vulnerability. Lower values can be found in regions with relatively low poverty, low population pressure, low conflict density and reduced contributions from the biological susceptibility domain. Overall, the factors characterizing vulnerability vary spatially in the region. The vulnerability index reveals a high level of robustness in regard to the final choice of input datasets, with the exception of the immunity indicator which has a marked impact on the composite vulnerability index. Conclusions We introduce a conceptual framework for modeling risk and vulnerability to VBDs. Drawing on the framework we modeled social vulnerability to malaria in the context of global change using a spatially explicit approach. The results provide decision makers with place-specific options for targeting interventions that aim at reducing the burden of the disease amongst the different vulnerable population groups. PMID:25127688

ML-Space: Hybrid Spatial Gillespie and Particle Simulation of Multi-Level Rule-Based Models in Cell Biology.

PubMed

Bittig, Arne T; Uhrmacher, Adelinde M

2017-01-01

Spatio-temporal dynamics of cellular processes can be simulated at different levels of detail, from (deterministic) partial differential equations via the spatial Stochastic Simulation algorithm to tracking Brownian trajectories of individual particles. We present a spatial simulation approach for multi-level rule-based models, which includes dynamically hierarchically nested cellular compartments and entities. Our approach ML-Space combines discrete compartmental dynamics, stochastic spatial approaches in discrete space, and particles moving in continuous space. The rule-based specification language of ML-Space supports concise and compact descriptions of models and to adapt the spatial resolution of models easily.

Modeling Spatial Dependencies and Semantic Concepts in Data Mining

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

Vatsavai, Raju

Data mining is the process of discovering new patterns and relationships in large datasets. However, several studies have shown that general data mining techniques often fail to extract meaningful patterns and relationships from the spatial data owing to the violation of fundamental geospatial principles. In this tutorial, we introduce basic principles behind explicit modeling of spatial and semantic concepts in data mining. In particular, we focus on modeling these concepts in the widely used classification, clustering, and prediction algorithms. Classification is the process of learning a structure or model (from user given inputs) and applying the known model to themore » new data. Clustering is the process of discovering groups and structures in the data that are ``similar,'' without applying any known structures in the data. Prediction is the process of finding a function that models (explains) the data with least error. One common assumption among all these methods is that the data is independent and identically distributed. Such assumptions do not hold well in spatial data, where spatial dependency and spatial heterogeneity are a norm. In addition, spatial semantics are often ignored by the data mining algorithms. In this tutorial we cover recent advances in explicitly modeling of spatial dependencies and semantic concepts in data mining.« less

AUTOMATED GEOSPATIAL WATERSHED ASSESSMENT: A GIS-BASED HYDROLOGIC MODELING TOOL

EPA Science Inventory

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 extens...

SPATIAL EXPLICIT POPULATION MODELS FOR RISK ASSESSMENT: COMMON LOONS AND MERCURY AS A CASE STUDY

EPA Science Inventory

Factors that significantly impact population dynamics, such as resource availability and exposure to stressors, frequently vary over space and thereby determine the heterogeneous spatial distributions of organisms. Considering this fact, the US Environmental Protection Agency's ...

Delineating resource sheds in aquatic ecosystems (presentation)

EPA Science Inventory

Analysis of spatially-explicit ecological phenomena in aquatic ecosystems is impeded by a lack of knowledge of, and tools to delimit, spatial patterns of material supply to point locations. Here we apply the concept of "resource sheds" to coasts and watersheds. Resource sheds ar...

The Tacit-Explicit Dimension of the Learning of Mathematics: An Investigation Report

ERIC Educational Resources Information Center

Frade, Cristina; Borges, Oto

2006-01-01

This paper reports on study that investigated the tacit-explicit dimension of the learning of mathematics. The study was carried out in a secondary school and consisted of an episode analysis related to a class discussion about the difference between plane figures and spatial figures. The data analysis was based on integration between some aspects…

The role of perspective taking in how children connect reference frames when explaining astronomical phenomena

NASA Astrophysics Data System (ADS)

Plummer, Julia D.; Bower, Corinne A.; Liben, Lynn S.

2016-02-01

This study investigates the role of perspective-taking skills in how children explain spatially complex astronomical phenomena. Explaining many astronomical phenomena, especially those studied in elementary and middle school, requires shifting between an Earth-based description of the phenomena and a space-based reference frame. We studied 7- to 9-year-old children (N = 15) to (a) develop a method for capturing how children make connections between reference frames and to (b) explore connections between perspective-taking skill and the nature of children's explanations. Children's explanations for the apparent motion of the Sun and stars and for seasonal changes in constellations were coded for accuracy of explanation, connection between frames of reference, and use of gesture. Children with higher spatial perspective-taking skills made more explicit connections between reference frames and used certain gesture-types more frequently, although this pattern was evident for only some phenomena. Findings suggest that children - particularly those with lower perspective-taking skills - may need additional support in learning to explicitly connect reference frames in astronomy. Understanding spatial thinking among children who successfully made explicit connections between reference frames in their explanations could be a starting point for future instruction in this domain.

Quantifying the correlation between spatially defined oxygen gradients and cell fate in an engineered three-dimensional culture model.

PubMed

Ardakani, Amir G; Cheema, Umber; Brown, Robert A; Shipley, Rebecca J

2014-09-06

A challenge in three-dimensional tissue culture remains the lack of quantitative information linking nutrient delivery and cellular distribution. Both in vivo and in vitro, oxygen is delivered by diffusion from its source (blood vessel or the construct margins). The oxygen level at a defined distance from its source depends critically on the balance of diffusion and cellular metabolism. Cells may respond to this oxygen environment through proliferation, death and chemotaxis, resulting in spatially resolved gradients in cellular density. This study extracts novel spatially resolved and simultaneous data on tissue oxygenation, cellular proliferation, viability and chemotaxis in three-dimensional spiralled, cellular collagen constructs. Oxygen concentration gradients drove preferential cellular proliferation rates and viability in the higher oxygen zones and induced chemotaxis along the spiral of the collagen construct; an oxygen gradient of 1.03 mmHg mm(-1) in the spiral direction induced a mean migratory speed of 1015 μm day(-1). Although this movement was modest, it was effective in balancing the system to a stable cell density distribution, and provided insights into the natural cell mechanism for adapting cell number and activity to a prevailing oxygen regime.

Spatial taxation effects on regional coal economic activities

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

Yang, C.W.; Labys, W.C.

1982-01-01

Taxation effects on resource production, consumption and prices are seldom evaluated especially in the field of spatial commodity modeling. The most commonly employed linear programming model has fixed-point estimated demands and capacity constraints; hence it makes taxation effects difficult to be modeled. The second type of resource allocation model, the interregional input-output models does not include a direct and explicit price mechanism. Therefore, it is not suitable for analyzing taxation effects. The third type or spatial commodity model has been econometric in nature. While such an approach has a good deal of flexibility in modeling political and non-economic variables, itmore » treats taxation (or tariff) effects loosely using only dummy variables, and, in many cases, must sacrifice the consistency criterion important for spatial commodity modeling. This leaves model builders only one legitimate choice for analyzing taxation effects: the quadratic programming model which explicitly allows the interplay of regional demand and supply relations via a continuous spatial price constructed by the authors related to the regional demand for and supply of coal from Appalachian markets.« less

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.

Place mapping and the role of spatial scale in understanding landowner views of fire and fuels management

Treesearch

Michael A. Cacciapaglia; Laurie Yung; Michael E. Patterson

2011-01-01

Place mapping is emerging as a way to understand the spatial components of people's relationships with particular locations and how these relate to support for management proposals. But despite the spatial focus of place mapping, scale is rarely explicitly examined in such exercises. This is particularly problematic since scalar definitions and configurations have...

IN-STREAM AND WATERSHED PREDICTORS OF GENETIC DIVERSITY, EFFECTIVE POPULATION SIZE AND IMMIGRATION ACROSS RIVER-STREAM NETWORKS

EPA Science Inventory

The influence of spatial processes on population dynamics within river-stream networks is poorly understood. Utilizing spatially explicit analyses of temporal genetic variance, we examined whether persistence of Central Stonerollers (Campostoma anomalum) reflects differences in h...

Spatially explicit rangeland erosion monitoring using high-resolution digital aerial imagery

USDA-ARS?s Scientific Manuscript database

Nearly all of the ecosystem services supported by rangelands, including production of livestock forage, carbon sequestration, and provisioning of clean water, are negatively impacted by soil erosion. Accordingly, monitoring the severity, spatial extent, and rate of soil erosion is essential for long...

A SPATIALLY EXPLICIT HIERARCHICAL APPROACH TO MODELING COMPLEX ECOLOGICAL SYSTEMS: THEORY AND APPLICATIONS. (R827676)

EPA Science Inventory

Ecological systems are generally considered among the most complex because they are characterized by a large number of diverse components, nonlinear interactions, scale multiplicity, and spatial heterogeneity. Hierarchy theory, as well as empirical evidence, suggests that comp...

GIS-BASED HYDROLOGIC MODELING: THE AUTOMATED GEOSPATIAL WATERSHED ASSESSMENT TOOL

EPA Science Inventory

Planning and assessment in land and water resource management are evolving from simple, local scale problems toward complex, spatially explicit regional ones. Such problems have to be
addressed with distributed models that can compute runoff and erosion at different spatial a...

Spatially explicit assessment of estuarine fish after Deepwater Horizon oil spill: trade-off in complexity and parsimony

EPA Science Inventory

Evaluating long- term contaminant effects on wildlife populations depends on spatial information about habitat quality, heterogeneity in contaminant exposure, and sensitivities and distributions of species integrated into a systems modeling approach. Rarely is this information re...

Modeling the Spatial Dynamics of Regional Land Use: The CLUE-S Model

NASA Astrophysics Data System (ADS)

Verburg, Peter H.; Soepboer, Welmoed; Veldkamp, A.; Limpiada, Ramil; Espaldon, Victoria; Mastura, Sharifah S. A.

2002-09-01

Land-use change models are important tools for integrated environmental management. Through scenario analysis they can help to identify near-future critical locations in the face of environmental change. A dynamic, spatially explicit, land-use change model is presented for the regional scale: CLUE-S. The model is specifically developed for the analysis of land use in small regions (e.g., a watershed or province) at a fine spatial resolution. The model structure is based on systems theory to allow the integrated analysis of land-use change in relation to socio-economic and biophysical driving factors. The model explicitly addresses the hierarchical organization of land use systems, spatial connectivity between locations and stability. Stability is incorporated by a set of variables that define the relative elasticity of the actual land-use type to conversion. The user can specify these settings based on expert knowledge or survey data. Two applications of the model in the Philippines and Malaysia are used to illustrate the functioning of the model and its validation.

Modeling the spatial dynamics of regional land use: the CLUE-S model.

PubMed

Verburg, Peter H; Soepboer, Welmoed; Veldkamp, A; Limpiada, Ramil; Espaldon, Victoria; Mastura, Sharifah S A

2002-09-01

Land-use change models are important tools for integrated environmental management. Through scenario analysis they can help to identify near-future critical locations in the face of environmental change. A dynamic, spatially explicit, land-use change model is presented for the regional scale: CLUE-S. The model is specifically developed for the analysis of land use in small regions (e.g., a watershed or province) at a fine spatial resolution. The model structure is based on systems theory to allow the integrated analysis of land-use change in relation to socio-economic and biophysical driving factors. The model explicitly addresses the hierarchical organization of land use systems, spatial connectivity between locations and stability. Stability is incorporated by a set of variables that define the relative elasticity of the actual land-use type to conversion. The user can specify these settings based on expert knowledge or survey data. Two applications of the model in the Philippines and Malaysia are used to illustrate the functioning of the model and its validation.

Spatial effects, sampling errors, and task specialization in the honey bee.

PubMed

Johnson, B R

2010-05-01

Task allocation patterns should depend on the spatial distribution of work within the nest, variation in task demand, and the movement patterns of workers, however, relatively little research has focused on these topics. This study uses a spatially explicit agent based model to determine whether such factors alone can generate biases in task performance at the individual level in the honey bees, Apis mellifera. Specialization (bias in task performance) is shown to result from strong sampling error due to localized task demand, relatively slow moving workers relative to nest size, and strong spatial variation in task demand. To date, specialization has been primarily interpreted with the response threshold concept, which is focused on intrinsic (typically genotypic) differences between workers. Response threshold variation and sampling error due to spatial effects are not mutually exclusive, however, and this study suggests that both contribute to patterns of task bias at the individual level. While spatial effects are strong enough to explain some documented cases of specialization; they are relatively short term and not explanatory for long term cases of specialization. In general, this study suggests that the spatial layout of tasks and fluctuations in their demand must be explicitly controlled for in studies focused on identifying genotypic specialists.

Harnessing Big Data to Represent 30-meter Spatial Heterogeneity in Earth System Models

NASA Astrophysics Data System (ADS)

Chaney, N.; Shevliakova, E.; Malyshev, S.; Van Huijgevoort, M.; Milly, C.; Sulman, B. N.

2016-12-01

Terrestrial land surface processes play a critical role in the Earth system; they have a profound impact on the global climate, food and energy production, freshwater resources, and biodiversity. One of the most fascinating yet challenging aspects of characterizing terrestrial ecosystems is their field-scale (˜30 m) spatial heterogeneity. It has been observed repeatedly that the water, energy, and biogeochemical cycles at multiple temporal and spatial scales have deep ties to an ecosystem's spatial structure. Current Earth system models largely disregard this important relationship leading to an inadequate representation of ecosystem dynamics. In this presentation, we will show how existing global environmental datasets can be harnessed to explicitly represent field-scale spatial heterogeneity in Earth system models. For each macroscale grid cell, these environmental data are clustered according to their field-scale soil and topographic attributes to define unique sub-grid tiles. The state-of-the-art Geophysical Fluid Dynamics Laboratory (GFDL) land model is then used to simulate these tiles and their spatial interactions via the exchange of water, energy, and nutrients along explicit topographic gradients. Using historical simulations over the contiguous United States, we will show how a robust representation of field-scale spatial heterogeneity impacts modeled ecosystem dynamics including the water, energy, and biogeochemical cycles as well as vegetation composition and distribution.

Towards a hierarchical optimization framework for spatially targeting incentive policies to promote green infrastructure amidst multiple objectives and uncertainty

EPA Science Inventory

We introduce a hierarchical optimization framework for spatially targeting green infrastructure (GI) incentive policies in order to meet objectives related to cost and environmental effectiveness. The framework explicitly simulates the interaction between multiple levels of polic...

Mapping the Climate of Puerto Rico, Vieques and Culebra.

Treesearch

CHRISTOPHER DALY; E. H. HELMER; MAYA QUINONES

2003-01-01

Spatially explicit climate data contribute to watershed resource management, mapping vegetation type with satellite imagery, mapping present and hypothetical future ecological zones, and predicting species distributions. The regression based Parameter-elevation Regressions on Independent Slopes Model (PRISM) uses spatial data sets, a knowledge base and expert...

Building the Foundation for International Conservation Planning for Breeding Ducks across the U.S. and Canadian Border

PubMed Central

Doherty, Kevin E.; Evans, Jeffrey S.; Walker, Johann; Devries, James H.; Howerter, David W.

2015-01-01

We used publically available data on duck breeding distribution and recently compiled geospatial data on upland habitat and environmental conditions to develop a spatially explicit model of breeding duck populations across the entire Prairie Pothole Region (PPR). Our spatial population models were able to identify key areas for duck conservation across the PPR and predict between 62.1 – 79.1% (68.4% avg.) of the variation in duck counts by year from 2002 – 2010. The median difference in observed vs. predicted duck counts at a transect segment level was 4.6 ducks. Our models are the first seamless spatially explicit models of waterfowl abundance across the entire PPR and represent an initial step toward joint conservation planning between Prairie Pothole and Prairie Habitat Joint Ventures. Our work demonstrates that when spatial and temporal variation for highly mobile birds is incorporated into conservation planning it will likely increase the habitat area required to support defined population goals. A major goal of the current North American Waterfowl Management Plan and subsequent action plan is the linking of harvest and habitat management. We contend incorporation of spatial aspects will increase the likelihood of coherent joint harvest and habitat management decisions. Our results show at a minimum, it is possible to produce spatially explicit waterfowl abundance models that when summed across survey strata will produce similar strata level population estimates as the design-based Waterfowl Breeding Pair and Habitat Survey (r2 = 0.977). This is important because these design-based population estimates are currently used to set duck harvest regulations and to set duck population and habitat goals for the North American Waterfowl Management Plan. We hope this effort generates discussion on the important linkages between spatial and temporal variation in population size, and distribution relative to habitat quantity and quality when linking habitat and population goals across this important region. PMID:25714747

Exploring complex dynamics in multi agent-based intelligent systems: Theoretical and experimental approaches using the Multi Agent-based Behavioral Economic Landscape (MABEL) model

NASA Astrophysics Data System (ADS)

Alexandridis, Konstantinos T.

This dissertation adopts a holistic and detailed approach to modeling spatially explicit agent-based artificial intelligent systems, using the Multi Agent-based Behavioral Economic Landscape (MABEL) model. The research questions that addresses stem from the need to understand and analyze the real-world patterns and dynamics of land use change from a coupled human-environmental systems perspective. Describes the systemic, mathematical, statistical, socio-economic and spatial dynamics of the MABEL modeling framework, and provides a wide array of cross-disciplinary modeling applications within the research, decision-making and policy domains. Establishes the symbolic properties of the MABEL model as a Markov decision process, analyzes the decision-theoretic utility and optimization attributes of agents towards comprising statistically and spatially optimal policies and actions, and explores the probabilogic character of the agents' decision-making and inference mechanisms via the use of Bayesian belief and decision networks. Develops and describes a Monte Carlo methodology for experimental replications of agent's decisions regarding complex spatial parcel acquisition and learning. Recognizes the gap on spatially-explicit accuracy assessment techniques for complex spatial models, and proposes an ensemble of statistical tools designed to address this problem. Advanced information assessment techniques such as the Receiver-Operator Characteristic curve, the impurity entropy and Gini functions, and the Bayesian classification functions are proposed. The theoretical foundation for modular Bayesian inference in spatially-explicit multi-agent artificial intelligent systems, and the ensembles of cognitive and scenario assessment modular tools build for the MABEL model are provided. Emphasizes the modularity and robustness as valuable qualitative modeling attributes, and examines the role of robust intelligent modeling as a tool for improving policy-decisions related to land use change. Finally, the major contributions to the science are presented along with valuable directions for future research.

Five challenges for spatial epidemic models

PubMed Central

Riley, Steven; Eames, Ken; Isham, Valerie; Mollison, Denis; Trapman, Pieter

2015-01-01

Infectious disease incidence data are increasingly available at the level of the individual and include high-resolution spatial components. Therefore, we are now better able to challenge models that explicitly represent space. Here, we consider five topics within spatial disease dynamics: the construction of network models; characterising threshold behaviour; modelling long-distance interactions; the appropriate scale for interventions; and the representation of population heterogeneity. PMID:25843387

Effects of sample size, number of markers, and allelic richness on the detection of spatial genetic pattern

Treesearch

Erin L. Landguth; Bradley C. Fedy; Sara J. Oyler-McCance; Andrew L. Garey; Sarah L. Emel; Matthew Mumma; Helene H. Wagner; Marie-Josee Fortin; Samuel A. Cushman

2012-01-01

The influence of study design on the ability to detect the effects of landscape pattern on gene flow is one of the most pressing methodological gaps in landscape genetic research. To investigate the effect of study design on landscape genetics inference, we used a spatially-explicit, individual-based program to simulate gene flow in a spatially continuous population...

Development of input data layers for the FARSITE fire growth model for the Selway-Bitterroot Wilderness Complex, USA

Treesearch

Robert E. Keane; Janice L. Garner; Kirsten M. Schmidt; Donald G. Long; James P. Menakis; Mark A. Finney

1998-01-01

Fuel and vegetation spatial data layers required by the spatially explicit fire growth model FARSITE were developed for all lands in and around the Selway-Bitterroot Wilderness Area in Idaho and Montana. Satellite imagery and terrain modeling were used to create the three base vegetation spatial data layers of potential vegetation, cover type, and structural stage....

Hierarchical analysis of spatial pattern and processes of Douglas-fir forests. Ph.D. Thesis, 10 Sep. 1991 Abstract Only

NASA Technical Reports Server (NTRS)

Bradshaw, G. A.

1995-01-01

There has been an increased interest in the quantification of pattern in ecological systems over the past years. This interest is motivated by the desire to construct valid models which extend across many scales. Spatial methods must quantify pattern, discriminate types of pattern, and relate hierarchical phenomena across scales. Wavelet analysis is introduced as a method to identify spatial structure in ecological transect data. The main advantage of the wavelet transform over other methods is its ability to preserve and display hierarchical information while allowing for pattern decomposition. Two applications of wavelet analysis are illustrated, as a means to: (1) quantify known spatial patterns in Douglas-fir forests at several scales, and (2) construct spatially-explicit hypotheses regarding pattern generating mechanisms. Application of the wavelet variance, derived from the wavelet transform, is developed for forest ecosystem analysis to obtain additional insight into spatially-explicit data. Specifically, the resolution capabilities of the wavelet variance are compared to the semi-variogram and Fourier power spectra for the description of spatial data using a set of one-dimensional stationary and non-stationary processes. The wavelet cross-covariance function is derived from the wavelet transform and introduced as a alternative method for the analysis of multivariate spatial data of understory vegetation and canopy in Douglas-fir forests of the western Cascades of Oregon.

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

USGS Publications Warehouse

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

2014-01-01

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

Local accumulation times for spatial difference in morphogen concentration

NASA Astrophysics Data System (ADS)

Wen, Xiaoqing; Yin, Hongwei

During development of multicellular organisms, spatial patterns of cells and tissue organizations rely on the action of morphogens, which are signaling molecules and act as dose-dependent regulators of gene expression and cellular differentiation. Since some experimental evidences have indicated that the spatial difference in morphogen concentration regulates cellular proliferation rather than this concentration profile in developing tissues, we propose spatially discrete models to describe this difference for a synthesis-diffusion-degradation process of morphogen in infinite and finite development fields, respectively. For both of models, we respectively derive analytical expressions of local accumulation times, which are required to form the steady state of the spatial difference in morphogen concentration. Our results show that the local accumulation times for the spatial difference in morphogen concentrations are different from the ones for morphogen concentration profiles.

Computing Pathways for Urban Decarbonization.

NASA Astrophysics Data System (ADS)

Cremades, R.; Sommer, P.

2016-12-01

Urban areas emit roughly three quarters of global carbon emissions. Cities are crucial elements for a decarbonized society. Urban expansion and related transportation needs lead to increased energy use, and to carbon-intensive lock-ins that create barriers for climate change mitigation globally. The authors present the Integrated Urban Complexity (IUC) model, based on self-organizing Cellular Automata (CA), and use it to produce a new kind of spatially explicit Transformation Pathways for Urban Decarbonization (TPUD). IUC is based on statistical evidence relating the energy needed for transportation with the spatial distribution of population, specifically IUC incorporates variables from complexity science related to urban form, like the slope of the rank-size rule or spatial entropy, which brings IUC a step beyond existing models. The CA starts its evolution with real-world urban land use and population distribution data from the Global Human Settlement Layer. Thus, the IUC model runs over existing urban settlements, transforming the spatial distribution of population so the energy consumption for transportation is minimized. The statistical evidence that governs the evolution of the CA departs from the database of the International Association of Public Transport. A selected case is presented using Stuttgart (Germany) as an example. The results show how IUC varies urban density in those places where it improves the performance of crucial parameters related to urban form, producing a TPUD that shows where the spatial distribution of population should be modified with a degree of detail of 250 meters of cell size. The TPUD shows how the urban complex system evolves over time to minimize energy consumption for transportation. The resulting dynamics or urban decarbonization show decreased energy per capita, although total energy increases for increasing population. The results provide innovative insights: by checking current urban planning against a TPUD, urban planners could understand where existing plans contradict the Agenda 2030, primarily the Sustainable Development Goals (SDGs) Climate Action (SDG 13), and Sustainable Cities and Communities (SDG 11). For the first time, evidence-based transformation pathways are produced to decarbonize cities.

Sleep Enhances Knowledge of Routes and Regions in Spatial Environments

ERIC Educational Resources Information Center

Noack, Hannes; Schick, Wiebke; Mallot, Hanspeter; Born, Jan

2017-01-01

Sleep is thought to preferentially consolidate hippocampus-dependent memory, and as such, spatial navigation. Here, we investigated the effects of sleep on route knowledge and explicit and implicit semantic regions in a virtual environment. Sleep, compared with wakefulness, improved route knowledge and also enhanced awareness of the semantic…

Factors influencing export of dissolved inorganic nitrogen by major rivers: A new seasonal, spatially explicit, global model - 2012

EPA Science Inventory

Background/Question/Methods Substantial effort has focused on understanding spatial variation in dissolved inorganic nitrogen (DIN) export to the coastal zone and specific basins have been studied in some depth. Much less is known, however, about seasonal patterns and zone and ...

Factors influencing export of dissolved inorganic nitrogen by major rivers: a new seasonal, spatially explicit, global model

EPA Science Inventory

Background/Question/Methods Substantial effort has focused on understanding spatial variation in dissolved inorganic nitrogen (DIN) export to the coastal zone and specific basins have been studied in some depth. Much less is known, however, about seasonal patterns and controls ...

Spatially explicit animal response to composition of habitat

Treesearch

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

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-...

SPATIAL PATTERN OF FUTURE VULNERABILITY OF STREAM EUTROPHICATION IN THE MID-ATLANTIC REGION OF THE UNITED STATES

EPA Science Inventory

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 d...

Spatial vegetation patterns and neighborhood competition among woody plants in an East African savanna

USDA-ARS?s Scientific Manuscript database

The majority of research on savanna vegetation dynamics has focused on the coexistence of woody and herbaceous vegetation; interactions among woody plants in savannas are relatively poorly understood. We present data from a 10-year longitudinal study of spatially explicit growth patterns of woody ve...

Spatially Explicit West Nile Virus Risk Modeling in Santa Clara County, CA

USDA-ARS?s Scientific Manuscript database

A geographic information systems model designed to identify regions of West Nile virus (WNV) transmission risk was tested and calibrated with data collected in Santa Clara County, California. American Crows that died from WNV infection in 2005, provided spatial and temporal ground truth. When the mo...

Spatially explicit West Nile virus risk modeling in Santa Clara County, California

USDA-ARS?s Scientific Manuscript database

A previously created Geographic Information Systems model designed to identify regions of West Nile virus (WNV) transmission risk is tested and calibrated in Santa Clara County, California. American Crows that died from WNV infection in 2005 provide the spatial and temporal ground truth. Model param...

Factors influencing export of dissolved inorganic nitrogen by major rivers: A new, seasonal, spatially explicit, global model

EPA Science Inventory

Substantial effort has focused on understanding spatial variation in dissolved inorganic nitrogen (DIN) export to the coastal zone and specific basins have been studied in depth. Much less is known, however, about seasonal patterns and controls of coastal DIN delivery across larg...

Nitrogen, ecosystem services and environmental justice: How can a spatial valuation approach inform responsible nutrient management?

EPA Science Inventory

Spatially-explicit ecosystem service valuation (ESV) allows for the identification of the location and magnitude of services provided by natural ecosystems along with an economic measure of their value based upon benefit transfer. While this provides an important function in term...

A cellular automaton implementation of a quantum battle of the sexes game with imperfect information

NASA Astrophysics Data System (ADS)

Alonso-Sanz, Ramón

2015-10-01

The dynamics of a spatial quantum formulation of the iterated battle of the sexes game with imperfect information is studied in this work. The game is played with variable entangling in a cellular automata manner, i.e. with local and synchronous interaction. The effect of spatial structure is assessed in fair and unfair scenarios.

Fire in the Brazilian Amazon: A Spatially Explicit Model for Policy Impact Analysis

NASA Technical Reports Server (NTRS)

Arima, Eugenio Y.; Simmons, Cynthia S.; Walker, Robert T.; Cochrane, Mark A.

2007-01-01

This article implements a spatially explicit model to estimate the probability of forest and agricultural fires in the Brazilian Amazon. We innovate by using variables that reflect farmgate prices of beef and soy, and also provide a conceptual model of managed and unmanaged fires in order to simulate the impact of road paving, cattle exports, and conservation area designation on the occurrence of fire. Our analysis shows that fire is positively correlated with the price of beef and soy, and that the creation of new conservation units may offset the negative environmental impacts caused by the increasing number of fire events associated with early stages of frontier development.

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.

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

Breast cancer mitosis detection in histopathological images with spatial feature extraction

NASA Astrophysics Data System (ADS)

Albayrak, Abdülkadir; Bilgin, Gökhan

2013-12-01

In this work, cellular mitosis detection in histopathological images has been investigated. Mitosis detection is very expensive and time consuming process. Development of digital imaging in pathology has enabled reasonable and effective solution to this problem. Segmentation of digital images provides easier analysis of cell structures in histopathological data. To differentiate normal and mitotic cells in histopathological images, feature extraction step is very crucial step for the system accuracy. A mitotic cell has more distinctive textural dissimilarities than the other normal cells. Hence, it is important to incorporate spatial information in feature extraction or in post-processing steps. As a main part of this study, Haralick texture descriptor has been proposed with different spatial window sizes in RGB and La*b* color spaces. So, spatial dependencies of normal and mitotic cellular pixels can be evaluated within different pixel neighborhoods. Extracted features are compared with various sample sizes by Support Vector Machines using k-fold cross validation method. According to the represented results, it has been shown that separation accuracy on mitotic and non-mitotic cellular pixels gets better with the increasing size of spatial window.

[Application of spatially explicit landscape model in soil loss study in Huzhong area].

PubMed

Xu, Chonggang; Hu, Yuanman; Chang, Yu; Li, Xiuzhen; Bu, Renchang; He, Hongshi; Leng, Wenfang

2004-10-01

Universal Soil Loss Equation (USLE) has been widely used to estimate the average annual soil loss. In most of the previous work on soil loss evaluation on forestland, cover management factor was calculated from the static forest landscape. The advent of spatially explicit forest landscape model in the last decade, which explicitly simulates the forest succession dynamics under natural and anthropogenic disturbances (fire, wind, harvest and so on) on heterogeneous landscape, makes it possible to take into consideration the change of forest cover, and to dynamically simulate the soil loss in different year (e.g. 10 years and 20 years after current year). In this study, we linked a spatially explicit landscape model (LANDIS) with USLE to simulate the soil loss dynamics under two scenarios: fire and no harvest, fire and harvest. We also simulated the soil loss with no fire and no harvest as a control. The results showed that soil loss varied periodically with simulation year, and the amplitude of change was the lowest under the control scenario and the highest under the fire and no harvest scenario. The effect of harvest on soil loss could not be easily identified on the map; however, the cumulative effect of harvest on soil loss was larger than that of fire. Decreasing the harvest area and the percent of bare soil increased by harvest could significantly reduce soil loss, but had no significant effects on the dynamic of soil loss. Although harvest increased the annual soil loss, it tended to decrease the variability of soil loss between different simulation years.

Stressless Schwarzschild

NASA Astrophysics Data System (ADS)

Deser, S.

2014-01-01

This self-contained pedagogical simple explicit 6-step derivation of the Schwarzschild solution, in "" formulation and conformal spatial gauge, (almost) avoids all affinity, curvature and index gymnastics.

Integrative multicellular biological modeling: a case study of 3D epidermal development using GPU algorithms

PubMed Central

2010-01-01

Background Simulation of sophisticated biological models requires considerable computational power. These models typically integrate together numerous biological phenomena such as spatially-explicit heterogeneous cells, cell-cell interactions, cell-environment interactions and intracellular gene networks. The recent advent of programming for graphical processing units (GPU) opens up the possibility of developing more integrative, detailed and predictive biological models while at the same time decreasing the computational cost to simulate those models. Results We construct a 3D model of epidermal development and provide a set of GPU algorithms that executes significantly faster than sequential central processing unit (CPU) code. We provide a parallel implementation of the subcellular element method for individual cells residing in a lattice-free spatial environment. Each cell in our epidermal model includes an internal gene network, which integrates cellular interaction of Notch signaling together with environmental interaction of basement membrane adhesion, to specify cellular state and behaviors such as growth and division. We take a pedagogical approach to describing how modeling methods are efficiently implemented on the GPU including memory layout of data structures and functional decomposition. We discuss various programmatic issues and provide a set of design guidelines for GPU programming that are instructive to avoid common pitfalls as well as to extract performance from the GPU architecture. Conclusions We demonstrate that GPU algorithms represent a significant technological advance for the simulation of complex biological models. We further demonstrate with our epidermal model that the integration of multiple complex modeling methods for heterogeneous multicellular biological processes is both feasible and computationally tractable using this new technology. We hope that the provided algorithms and source code will be a starting point for modelers to develop their own GPU implementations, and encourage others to implement their modeling methods on the GPU and to make that code available to the wider community. PMID:20696053

Environmental risk of leptospirosis infections in the Netherlands: Spatial modelling of environmental risk factors of leptospirosis in the Netherlands.

PubMed

Rood, Ente J J; Goris, Marga G A; Pijnacker, Roan; Bakker, Mirjam I; Hartskeerl, Rudy A

2017-01-01

Leptospirosis is a globally emerging zoonotic disease, associated with various climatic, biotic and abiotic factors. Mapping and quantifying geographical variations in the occurrence of leptospirosis and the surrounding environment offer innovative methods to study disease transmission and to identify associations between the disease and the environment. This study aims to investigate geographic variations in leptospirosis incidence in the Netherlands and to identify associations with environmental factors driving the emergence of the disease. Individual case data derived over the period 1995-2012 in the Netherlands were geocoded and aggregated by municipality. Environmental covariate data were extracted for each municipality and stored in a spatial database. Spatial clusters were identified using kernel density estimations and quantified using local autocorrelation statistics. Associations between the incidence of leptospirosis and the local environment were determined using Simultaneous Autoregressive Models (SAR) explicitly modelling spatial dependence of the model residuals. Leptospirosis incidence rates were found to be spatially clustered, showing a marked spatial pattern. Fitting a spatial autoregressive model significantly improved model fit and revealed significant association between leptospirosis and the coverage of arable land, built up area, grassland and sabulous clay soils. The incidence of leptospirosis in the Netherlands could effectively be modelled using a combination of soil and land-use variables accounting for spatial dependence of incidence rates per municipality. The resulting spatially explicit risk predictions provide an important source of information which will benefit clinical awareness on potential leptospirosis infections in endemic areas.

Environmental risk of leptospirosis infections in the Netherlands: Spatial modelling of environmental risk factors of leptospirosis in the Netherlands

PubMed Central

Goris, Marga G. A.; Pijnacker, Roan; Bakker, Mirjam I.; Hartskeerl, Rudy A.

2017-01-01

Leptospirosis is a globally emerging zoonotic disease, associated with various climatic, biotic and abiotic factors. Mapping and quantifying geographical variations in the occurrence of leptospirosis and the surrounding environment offer innovative methods to study disease transmission and to identify associations between the disease and the environment. This study aims to investigate geographic variations in leptospirosis incidence in the Netherlands and to identify associations with environmental factors driving the emergence of the disease. Individual case data derived over the period 1995–2012 in the Netherlands were geocoded and aggregated by municipality. Environmental covariate data were extracted for each municipality and stored in a spatial database. Spatial clusters were identified using kernel density estimations and quantified using local autocorrelation statistics. Associations between the incidence of leptospirosis and the local environment were determined using Simultaneous Autoregressive Models (SAR) explicitly modelling spatial dependence of the model residuals. Leptospirosis incidence rates were found to be spatially clustered, showing a marked spatial pattern. Fitting a spatial autoregressive model significantly improved model fit and revealed significant association between leptospirosis and the coverage of arable land, built up area, grassland and sabulous clay soils. The incidence of leptospirosis in the Netherlands could effectively be modelled using a combination of soil and land-use variables accounting for spatial dependence of incidence rates per municipality. The resulting spatially explicit risk predictions provide an important source of information which will benefit clinical awareness on potential leptospirosis infections in endemic areas. PMID:29065186

Spatially Explicit Landscape-Level Ecological Risks Induced by Land Use and Land Cover Change in a National Ecologically Representative Region in China.

PubMed

Gong, Jian; Yang, Jianxin; Tang, Wenwu

2015-11-09

Land use and land cover change is driven by multiple influential factors from environmental and social dimensions in a land system. Land use practices of human decision-makers modify the landscape of the land system, possibly leading to landscape fragmentation, biodiversity loss, or environmental pollution-severe environmental or ecological impacts. While landscape-level ecological risk assessment supports the evaluation of these impacts, investigations on how these ecological risks induced by land use practices change over space and time in response to alternative policy intervention remain inadequate. In this article, we conducted spatially explicit landscape ecological risk analysis in Ezhou City, China. Our study area is a national ecologically representative region experiencing drastic land use and land cover change, and is regulated by multiple policies represented by farmland protection, ecological conservation, and urban development. We employed landscape metrics to consider the influence of potential landscape-level disturbance for the evaluation of landscape ecological risks. Using spatiotemporal simulation, we designed scenarios to examine spatiotemporal patterns in landscape ecological risks in response to policy intervention. Our study demonstrated that spatially explicit landscape ecological risk analysis combined with simulation-driven scenario analysis is of particular importance for guiding the sustainable development of ecologically vulnerable land systems.

Analyzing Variability in Landscape Nutrient Loading Using Spatially-Explicit Maps in the Great Lakes Basin

NASA Astrophysics Data System (ADS)

Hamlin, Q. F.; Kendall, A. D.; Martin, S. L.; Whitenack, H. D.; Roush, J. A.; Hannah, B. A.; Hyndman, D. W.

2017-12-01

Excessive loading of nitrogen and phosphorous to the landscape has caused biologically and economically damaging eutrophication and harmful algal blooms in the Great Lakes Basin (GLB) and across the world. We mapped source-specific loads of nitrogen and phosphorous to the landscape using broadly available data across the GLB. SENSMap (Spatially Explicit Nutrient Source Map) is a 30m resolution snapshot of nutrient loads ca. 2010. We use these maps to study variable nutrient loading and provide this information to watershed managers through NOAA's GLB Tipping Points Planner. SENSMap individually maps nutrient point sources and six non-point sources: 1) atmospheric deposition, 2) septic tanks, 3) non-agricultural chemical fertilizer, 4) agricultural chemical fertilizer, 5) manure, and 6) nitrogen fixation from legumes. To model source-specific loads at high resolution, SENSMap synthesizes a wide range of remotely sensed, surveyed, and tabular data. Using these spatially explicit nutrient loading maps, we can better calibrate local land use-based water quality models and provide insight to watershed managers on how to focus nutrient reduction strategies. Here we examine differences in dominant nutrient sources across the GLB, and how those sources vary by land use. SENSMap's high resolution, source-specific approach offers a different lens to understand nutrient loading than traditional semi-distributed or land use based models.

Remote sensing of ecosystem health: opportunities, challenges, and future perspectives.

PubMed

Li, Zhaoqin; Xu, Dandan; Guo, Xulin

2014-11-07

Maintaining a healthy ecosystem is essential for maximizing sustainable ecological services of the best quality to human beings. Ecological and conservation research has provided a strong scientific background on identifying ecological health indicators and correspondingly making effective conservation plans. At the same time, ecologists have asserted a strong need for spatially explicit and temporally effective ecosystem health assessments based on remote sensing data. Currently, remote sensing of ecosystem health is only based on one ecosystem attribute: vigor, organization, or resilience. However, an effective ecosystem health assessment should be a comprehensive and dynamic measurement of the three attributes. This paper reviews opportunities of remote sensing, including optical, radar, and LiDAR, for directly estimating indicators of the three ecosystem attributes, discusses the main challenges to develop a remote sensing-based spatially-explicit comprehensive ecosystem health system, and provides some future perspectives. The main challenges to develop a remote sensing-based spatially-explicit comprehensive ecosystem health system are: (1) scale issue; (2) transportability issue; (3) data availability; and (4) uncertainties in health indicators estimated from remote sensing data. However, the Radarsat-2 constellation, upcoming new optical sensors on Worldview-3 and Sentinel-2 satellites, and improved technologies for the acquisition and processing of hyperspectral, multi-angle optical, radar, and LiDAR data and multi-sensoral data fusion may partly address the current challenges.

Spatially Explicit Landscape-Level Ecological Risks Induced by Land Use and Land Cover Change in a National Ecologically Representative Region in China

PubMed Central

Gong, Jian; Yang, Jianxin; Tang, Wenwu

2015-01-01

Land use and land cover change is driven by multiple influential factors from environmental and social dimensions in a land system. Land use practices of human decision-makers modify the landscape of the land system, possibly leading to landscape fragmentation, biodiversity loss, or environmental pollution—severe environmental or ecological impacts. While landscape-level ecological risk assessment supports the evaluation of these impacts, investigations on how these ecological risks induced by land use practices change over space and time in response to alternative policy intervention remain inadequate. In this article, we conducted spatially explicit landscape ecological risk analysis in Ezhou City, China. Our study area is a national ecologically representative region experiencing drastic land use and land cover change, and is regulated by multiple policies represented by farmland protection, ecological conservation, and urban development. We employed landscape metrics to consider the influence of potential landscape-level disturbance for the evaluation of landscape ecological risks. Using spatiotemporal simulation, we designed scenarios to examine spatiotemporal patterns in landscape ecological risks in response to policy intervention. Our study demonstrated that spatially explicit landscape ecological risk analysis combined with simulation-driven scenario analysis is of particular importance for guiding the sustainable development of ecologically vulnerable land systems. PMID:26569270

PHYLOGEOrec: A QGIS plugin for spatial phylogeographic reconstruction from phylogenetic tree and geographical information data

NASA Astrophysics Data System (ADS)

Nashrulloh, Maulana Malik; Kurniawan, Nia; Rahardi, Brian

2017-11-01

The increasing availability of genetic sequence data associated with explicit geographic and environment (including biotic and abiotic components) information offers new opportunities to study the processes that shape biodiversity and its patterns. Developing phylogeography reconstruction, by integrating phylogenetic and biogeographic knowledge, provides richer and deeper visualization and information on diversification events than ever before. Geographical information systems such as QGIS provide an environment for spatial modeling, analysis, and dissemination by which phylogenetic models can be explicitly linked with their associated spatial data, and subsequently, they will be integrated with other related georeferenced datasets describing the biotic and abiotic environment. We are introducing PHYLOGEOrec, a QGIS plugin for building spatial phylogeographic reconstructions constructed from phylogenetic tree and geographical information data based on QGIS2threejs. By using PHYLOGEOrec, researchers can integrate existing phylogeny and geographical information data, resulting in three-dimensional geographic visualizations of phylogenetic trees in the Keyhole Markup Language (KML) format. Such formats can be overlaid on a map using QGIS and finally, spatially viewed in QGIS by means of a QGIS2threejs engine for further analysis. KML can also be viewed in reputable geobrowsers with KML-support (i.e., Google Earth).

Effect of assessment scale on spatial and temporal variations in CH4, C02, and N20 fluxes in a forested wetland

Treesearch

Zhaohua Dai; Carl Trettin; Changsheng Li; Harbin Li; Ge Sun; Devendra Amatya

2011-01-01

Emissions of methane (CH4), carbon dioxide (CO2), and nitrous oxide (N2O) from a forested watershed (160 ha) in South Carolina, USA, were estimated with a spatially explicit watershed-scale modeling framework that utilizes the spatial variations in physical and biogeochemical characteristics across watersheds. The target watershed (WS80) consisting of wetland (23%) and...

Collective synchronization of self/non-self discrimination in T cell activation, across multiple spatio-temporal scales

NASA Astrophysics Data System (ADS)

Altan-Bonnet, Gregoire

The immune system is a collection of cells whose function is to eradicate pathogenic infections and malignant tumors while protecting healthy tissues. Recent work has delineated key molecular and cellular mechanisms associated with the ability to discriminate self from non-self agents. For example, structural studies have quantified the biophysical characteristics of antigenic molecules (those prone to trigger lymphocyte activation and a subsequent immune response). However, such molecular mechanisms were found to be highly unreliable at the individual cellular level. We will present recent efforts to build experimentally validated computational models of the immune responses at the collective cell level. Such models have become critical to delineate how higher-level integration through nonlinear amplification in signal transduction, dynamic feedback in lymphocyte differentiation and cell-to-cell communication allows the immune system to enforce reliable self/non-self discrimination at the organism level. In particular, we will present recent results demonstrating how T cells tune their antigen discrimination according to cytokine cues, and how competition for cytokine within polyclonal populations of cells shape the repertoire of responding clones. Additionally, we will present recent theoretical and experimental results demonstrating how competition between diffusion and consumption of cytokines determine the range of cell-cell communications within lymphoid organs. Finally, we will discuss how biochemically explicit models, combined with quantitative experimental validation, unravel the relevance of new feedbacks for immune regulations across multiple spatial and temporal scales.

Influence of spatial temperature estimation method in ecohydrologic modeling in the western Oregon Cascades

Treesearch

E. Garcia; C.L. Tague; J. Choate

2013-01-01

Most spatially explicit hydrologic models require estimates of air temperature patterns. For these models, empirical relationships between elevation and air temperature are frequently used to upscale point measurements or downscale regional and global climate model estimates of air temperature. Mountainous environments are particularly sensitive to air temperature...

Linking climate change and fish conservation efforts using spatially explicit decision support tools

Treesearch

Douglas P. Peterson; Seth J. Wenger; Bruce E. Rieman; Daniel J. Isaak

2013-01-01

Fisheries professionals are increasingly tasked with incorporating climate change projections into their decisions. Here we demonstrate how a structured decision framework, coupled with analytical tools and spatial data sets, can help integrate climate and biological information to evaluate management alternatives. We present examples that link downscaled climate...

Landscape ecology: Past, present, and future [Chapter 4

Treesearch

Samuel A. Cushman; Jeffrey S. Evans; Kevin McGarigal

2010-01-01

In the preceding chapters we discussed the central role that spatial and temporal variability play in ecological systems, the importance of addressing these explicitly within ecological analyses and the resulting need to carefully consider spatial and temporal scale and scaling. Landscape ecology is the science of linking patterns and processes across scale in both...

QUALITY ASSURANCE AND QUALITY CONTROL IN THE DEVELOPMENT AND APPLICATION OF THE AUTOMATED GEOSPATIAL WATERSHED ASSESSMENT (AGWA) TOOL

EPA Science Inventory

Planning and assessment in land and water resource management are evolving from simple, local-scale problems toward complex, spatially explicit regional ones. Such problems have to be addressed with distributed models that can compute runoff and erosion at different spatial and t...

REMOTE SENSING AND SPATIALLY EXPLICIT LANDSCAPE-BASED NITROGEN MODELING METHODS DEVELOPMENT IN THE NEUSE RIVER BASIN, NC

EPA Science Inventory

The objective of this research was to model and map the spatial patterns of excess nitrogen (N) sources across the landscape within the Neuse River Basin (NRB) of North
Carolina. The process included an initial land cover characterization effort to map landscape "patches" at ...

Simulating spatial and temporal context of forest management using hypothetical landscapes

Treesearch

Eric J. Gustafson; Thomas R. Crow

1998-01-01

Spatially explicit models that combine remote sensing with geographic information systems (GIS) offer great promise to land managers because they consider the arrangement of landscape elements in time and space. Their visual and geographic nature facilitate the comparison of alternative landscape designs. Among various activities associated with forest management,...

Hierarchical spatial models for predicting tree species assemblages across large domains

Treesearch

Andrew O. Finley; Sudipto Banerjee; Ronald E. McRoberts

2009-01-01

Spatially explicit data layers of tree species assemblages, referred to as forest types or forest type groups, are a key component in large-scale assessments of forest sustainability, biodiversity, timber biomass, carbon sinks and forest health monitoring. This paper explores the utility of coupling georeferenced national forest inventory (NFI) data with readily...

Scale dependency of American marten (Martes americana) habitat relations [Chapter 12

Treesearch

Andrew J. Shirk; Tzeidle N. Wasserman; Samuel A. Cushman; Martin G. Raphael

2012-01-01

Animals select habitat resources at multiple spatial scales; therefore, explicit attention to scale-dependency when modeling habitat relations is critical to understanding how organisms select habitat in complex landscapes. Models that evaluate habitat variables calculated at a single spatial scale (e.g., patch, home range) fail to account for the effects of...

Quantifying the lag time to detect barriers in landscape genetics

Treesearch

E. L. Landguth; S. A Cushman; M. K. Schwartz; K. S. McKelvey; M. Murphy; G. Luikart

2010-01-01

Understanding how spatial genetic patterns respond to landscape change is crucial for advancing the emerging field of landscape genetics. We quantified the number of generations for new landscape barrier signatures to become detectable and for old signatures to disappear after barrier removal. We used spatially explicit, individualbased simulations to examine the...

Landsat's role in ecological applications of remote sensing.

Treesearch

Warren B. Cohen; Samuel N. Goward

2004-01-01

Remote sensing, geographic information systems, and modeling have combined to produce a virtual explosion of growth in ecological investigations and applications that are explicitly spatial and temporal. Of all remotely sensed data, those acquired by landsat sensors have played the most pivotal role in spatial and temporal scaling. Modern terrestrial ecology relies on...

Integrating Spatial Components into FIA Models of Forest Resources: Some Technical Aspects

Treesearch

Pat Terletzky; Tracey Frescino

2005-01-01

We examined two software packages to determine their feasibility of implementing spatially explicit, forest resource models that integrate Forest Inventory and Analysis data (FIA). ARCINFO and Interactive Data Language (IDL) were examined for their input requirements, speed of processing, storage requirements, and flexibility of implementing. Implementations of two...

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...

A Review of High-Order and Optimized Finite-Difference Methods for Simulating Linear Wave Phenomena

NASA Technical Reports Server (NTRS)

Zingg, David W.

1996-01-01

This paper presents a review of high-order and optimized finite-difference methods for numerically simulating the propagation and scattering of linear waves, such as electromagnetic, acoustic, or elastic waves. The spatial operators reviewed include compact schemes, non-compact schemes, schemes on staggered grids, and schemes which are optimized to produce specific characteristics. The time-marching methods discussed include Runge-Kutta methods, Adams-Bashforth methods, and the leapfrog method. In addition, the following fourth-order fully-discrete finite-difference methods are considered: a one-step implicit scheme with a three-point spatial stencil, a one-step explicit scheme with a five-point spatial stencil, and a two-step explicit scheme with a five-point spatial stencil. For each method studied, the number of grid points per wavelength required for accurate simulation of wave propagation over large distances is presented. Recommendations are made with respect to the suitability of the methods for specific problems and practical aspects of their use, such as appropriate Courant numbers and grid densities. Avenues for future research are suggested.

Spatial occupancy models for large data sets

USGS Publications Warehouse

Johnson, Devin S.; Conn, Paul B.; Hooten, Mevin B.; Ray, Justina C.; Pond, Bruce A.

2013-01-01

Since its development, occupancy modeling has become a popular and useful tool for ecologists wishing to learn about the dynamics of species occurrence over time and space. Such models require presence–absence data to be collected at spatially indexed survey units. However, only recently have researchers recognized the need to correct for spatially induced overdisperison by explicitly accounting for spatial autocorrelation in occupancy probability. Previous efforts to incorporate such autocorrelation have largely focused on logit-normal formulations for occupancy, with spatial autocorrelation induced by a random effect within a hierarchical modeling framework. Although useful, computational time generally limits such an approach to relatively small data sets, and there are often problems with algorithm instability, yielding unsatisfactory results. Further, recent research has revealed a hidden form of multicollinearity in such applications, which may lead to parameter bias if not explicitly addressed. Combining several techniques, we present a unifying hierarchical spatial occupancy model specification that is particularly effective over large spatial extents. This approach employs a probit mixture framework for occupancy and can easily accommodate a reduced-dimensional spatial process to resolve issues with multicollinearity and spatial confounding while improving algorithm convergence. Using open-source software, we demonstrate this new model specification using a case study involving occupancy of caribou (Rangifer tarandus) over a set of 1080 survey units spanning a large contiguous region (108 000 km2) in northern Ontario, Canada. Overall, the combination of a more efficient specification and open-source software allows for a facile and stable implementation of spatial occupancy models for large data sets.

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.

Theory of Epithelial Cell Shape Transitions Induced by Mechanoactive Chemical Gradients.

PubMed

Dasbiswas, Kinjal; Hannezo, Edouard; Gov, Nir S

2018-02-27

Cell shape is determined by a balance of intrinsic properties of the cell as well as its mechanochemical environment. Inhomogeneous shape changes underlie many morphogenetic events and involve spatial gradients in active cellular forces induced by complex chemical signaling. Here, we introduce a mechanochemical model based on the notion that cell shape changes may be induced by external diffusible biomolecules that influence cellular contractility (or equivalently, adhesions) in a concentration-dependent manner-and whose spatial profile in turn is affected by cell shape. We map out theoretically the possible interplay between chemical concentration and cellular structure. Besides providing a direct route to spatial gradients in cell shape profiles in tissues, we show that the dependence on cell shape helps create robust mechanochemical gradients. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Latent spatial models and sampling design for landscape genetics

USGS Publications Warehouse

Hanks, Ephraim M.; Hooten, Mevin B.; Knick, Steven T.; Oyler-McCance, Sara J.; Fike, Jennifer A.; Cross, Todd B.; Schwartz, Michael K.

2016-01-01

We propose a spatially-explicit approach for modeling genetic variation across space and illustrate how this approach can be used to optimize spatial prediction and sampling design for landscape genetic data. We propose a multinomial data model for categorical microsatellite allele data commonly used in landscape genetic studies, and introduce a latent spatial random effect to allow for spatial correlation between genetic observations. We illustrate how modern dimension reduction approaches to spatial statistics can allow for efficient computation in landscape genetic statistical models covering large spatial domains. We apply our approach to propose a retrospective spatial sampling design for greater sage-grouse (Centrocercus urophasianus) population genetics in the western United States.

[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.

Time-dependent density functional theory (TD-DFT) coupled with reference interaction site model self-consistent field explicitly including spatial electron density distribution (RISM-SCF-SEDD)

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

Yokogawa, D., E-mail: d.yokogawa@chem.nagoya-u.ac.jp; Institute of Transformative Bio-Molecules

2016-09-07

Theoretical approach to design bright bio-imaging molecules is one of the most progressing ones. However, because of the system size and computational accuracy, the number of theoretical studies is limited to our knowledge. To overcome the difficulties, we developed a new method based on reference interaction site model self-consistent field explicitly including spatial electron density distribution and time-dependent density functional theory. We applied it to the calculation of indole and 5-cyanoindole at ground and excited states in gas and solution phases. The changes in the optimized geometries were clearly explained with resonance structures and the Stokes shift was correctly reproduced.

Five challenges for spatial epidemic models.

PubMed

Riley, Steven; Eames, Ken; Isham, Valerie; Mollison, Denis; Trapman, Pieter

2015-03-01

Infectious disease incidence data are increasingly available at the level of the individual and include high-resolution spatial components. Therefore, we are now better able to challenge models that explicitly represent space. Here, we consider five topics within spatial disease dynamics: the construction of network models; characterising threshold behaviour; modelling long-distance interactions; the appropriate scale for interventions; and the representation of population heterogeneity. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

On the representation of cells in bone marrow pathology by a scalar field: propagation through serial sections, co-localization and spatial interaction analysis.

PubMed

Weis, Cleo-Aron; Grießmann, Benedict Walter; Scharff, Christoph; Detzner, Caecilia; Pfister, Eva; Marx, Alexander; Zoellner, Frank Gerrit

2015-09-02

Immunohistochemical analysis of cellular interactions in the bone marrow in situ is demanding, due to its heterogeneous cellular composition, the poor delineation and overlap of functional compartments and highly complex immunophenotypes of several cell populations (e.g. regulatory T-cells) that require immunohistochemical marker sets for unambiguous characterization. To overcome these difficulties, we herein present an approach to describe objects (e.g. cells, bone trabeculae) by a scalar field that can be propagated through registered images of serial histological sections. The transformation of objects within images (e.g. cells) to a scalar field was performed by convolution of the object's centroids with differently formed radial basis function (e.g. for direct or indirect spatial interaction). On the basis of such a scalar field, a summation field described distributed objects within an image. After image registration i) colocalization analysis could be performed on basis scalar field, which is propagated through registered images, and - due to the shape of the field - were barely prone to matching errors and morphological changes by different cutting levels; ii) furthermore, depending on the field shape the colocalization measurements could also quantify spatial interaction (e.g. direct or paracrine cellular contact); ii) the field-overlap, which represents the spatial distance, of different objects (e.g. two cells) could be calculated by the histogram intersection. The description of objects (e.g. cells, cell clusters, bone trabeculae etc.) as a field offers several possibilities: First, co-localization of different markers (e.g. by immunohistochemical staining) in serial sections can be performed in an automatic, objective and quantifiable way. In contrast to multicolour staining (e.g. 10-colour immunofluorescence) the financial and technical requirements are fairly minor. Second, the approach allows searching for different types of spatial interactions (e.g. direct and indirect cellular interaction) between objects by taking field shape into account (e.g. thin vs. broad). Third, by describing spatially distributed groups of objects as summation field, it gives cluster definition that relies rather on the bare object distance than on the modelled spatial cellular interaction.

Spatial transcriptomic analysis of cryosectioned tissue samples with Geo-seq.

PubMed

Chen, Jun; Suo, Shengbao; Tam, Patrick Pl; Han, Jing-Dong J; Peng, Guangdun; Jing, Naihe

2017-03-01

Conventional gene expression studies analyze multiple cells simultaneously or single cells, for which the exact in vivo or in situ position is unknown. Although cellular heterogeneity can be discerned when analyzing single cells, any spatially defined attributes that underpin the heterogeneous nature of the cells cannot be identified. Here, we describe how to use Geo-seq, a method that combines laser capture microdissection (LCM) and single-cell RNA-seq technology. The combination of these two methods enables the elucidation of cellular heterogeneity and spatial variance simultaneously. The Geo-seq protocol allows the profiling of transcriptome information from only a small number cells and retains their native spatial information. This protocol has wide potential applications to address biological and pathological questions of cellular properties such as prospective cell fates, biological function and the gene regulatory network. Geo-seq has been applied to investigate the spatial transcriptome of mouse early embryo, mouse brain, and pathological liver and sperm tissues. The entire protocol from tissue collection and microdissection to sequencing requires ∼5 d, Data analysis takes another 1 or 2 weeks, depending on the amount of data and the speed of the processor.

High resolution tree-ring based spatial reconstructions of snow avalanche activity in Glacier National Park, Montana, USA

USGS Publications Warehouse

Pederson, Gregory T.; Reardon, Blase; Caruso, C.J.; Fagre, Daniel B.

2006-01-01

Effective design of avalanche hazard mitigation measures requires long-term records of natural avalanche frequency and extent. Such records are also vital for determining whether natural avalanche frequency and extent vary over time due to climatic or biophysical changes. Where historic records are lacking, an accepted substitute is a chronology developed from tree-ring responses to avalanche-induced damage. This study evaluates a method for using tree-ring chronologies to provide spatially explicit differentiations of avalanche frequency and temporally explicit records of avalanche extent that are often lacking. The study area - part of John F. Stevens Canyon on the southern border of Glacier National Park – is within a heavily used railroad and highway corridor with two dozen active avalanche paths. Using a spatially geo-referenced network of avalanche-damaged trees (n=109) from a single path, we reconstructed a 96-year tree-ring based chronology of avalanche extent and frequency. Comparison of the chronology with historic records revealed that trees recorded all known events as well as the same number of previously unidentified events. Kriging methods provided spatially explicit estimates of avalanche return periods. Estimated return periods for the entire avalanche path averaged 3.2 years. Within this path, return intervals ranged from ~2.3 yrs in the lower track, to ~9-11 yrs and ~12 to >25 yrs in the runout zone, where the railroad and highway are located. For avalanche professionals, engineers, and transportation managers this technique proves a powerful tool in landscape risk assessment and decision making.

Informing Species Conservation at Multiple Scales Using Data Collected for Marine Mammal Stock Assessments

PubMed Central

Grech, Alana; Sheppard, James; Marsh, Helene

2011-01-01

Background Conservation planning and the design of marine protected areas (MPAs) requires spatially explicit information on the distribution of ecological features. Most species of marine mammals range over large areas and across multiple planning regions. The spatial distributions of marine mammals are difficult to predict using habitat modelling at ecological scales because of insufficient understanding of their habitat needs, however, relevant information may be available from surveys conducted to inform mandatory stock assessments. Methodology and Results We use a 20-year time series of systematic aerial surveys of dugong (Dugong dugong) abundance to create spatially-explicit models of dugong distribution and relative density at the scale of the coastal waters of northeast Australia (∼136,000 km2). We interpolated the corrected data at the scale of 2 km * 2 km planning units using geostatistics. Planning units were classified as low, medium, high and very high dugong density on the basis of the relative density of dugongs estimated from the models and a frequency analysis. Torres Strait was identified as the most significant dugong habitat in northeast Australia and the most globally significant habitat known for any member of the Order Sirenia. The models are used by local, State and Federal agencies to inform management decisions related to the Indigenous harvest of dugongs, gill-net fisheries and Australia's National Representative System of Marine Protected Areas. Conclusion/Significance In this paper we demonstrate that spatially-explicit population models add value to data collected for stock assessments, provide a robust alternative to predictive habitat distribution models, and inform species conservation at multiple scales. PMID:21464933

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.

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.

Assessing implicit odor localization in humans using a cross-modal spatial cueing paradigm.

PubMed

Moessnang, Carolin; Finkelmeyer, Andreas; Vossen, Alexandra; Schneider, Frank; Habel, Ute

2011-01-01

Navigation based on chemosensory information is one of the most important skills in the animal kingdom. Studies on odor localization suggest that humans have lost this ability. However, the experimental approaches used so far were limited to explicit judgements, which might ignore a residual ability for directional smelling on an implicit level without conscious appraisal. A novel cueing paradigm was developed in order to determine whether an implicit ability for directional smelling exists. Participants performed a visual two-alternative forced choice task in which the target was preceded either by a side-congruent or a side-incongruent olfactory spatial cue. An explicit odor localization task was implemented in a second experiment. No effect of cue congruency on mean reaction times could be found. However, a time by condition interaction emerged, with significantly slower responses to congruently compared to incongruently cued targets at the beginning of the experiment. This cueing effect gradually disappeared throughout the course of the experiment. In addition, participants performed at chance level in the explicit odor localization task, thus confirming the results of previous research. The implicit cueing task suggests the existence of spatial information processing in the olfactory system. Response slowing after a side-congruent olfactory cue is interpreted as a cross-modal attentional interference effect. In addition, habituation might have led to a gradual disappearance of the cueing effect. It is concluded that under immobile conditions with passive monorhinal stimulation, humans are unable to explicitly determine the location of a pure odorant. Implicitly, however, odor localization seems to exert an influence on human behaviour. To our knowledge, these data are the first to show implicit effects of odor localization on overt human behaviour and thus support the hypothesis of residual directional smelling in humans. © 2011 Moessnang et al.

Estimating temporal trend in the presence of spatial complexity: A Bayesian hierarchical model for a wetland plant population undergoing restoration

USGS Publications Warehouse

Rodhouse, T.J.; Irvine, K.M.; Vierling, K.T.; Vierling, L.A.

2011-01-01

Monitoring programs that evaluate restoration and inform adaptive management are important for addressing environmental degradation. These efforts may be well served by spatially explicit hierarchical approaches to modeling because of unavoidable spatial structure inherited from past land use patterns and other factors. We developed Bayesian hierarchical models to estimate trends from annual density counts observed in a spatially structured wetland forb (Camassia quamash [camas]) population following the cessation of grazing and mowing on the study area, and in a separate reference population of camas. The restoration site was bisected by roads and drainage ditches, resulting in distinct subpopulations ("zones") with different land use histories. We modeled this spatial structure by fitting zone-specific intercepts and slopes. We allowed spatial covariance parameters in the model to vary by zone, as in stratified kriging, accommodating anisotropy and improving computation and biological interpretation. Trend estimates provided evidence of a positive effect of passive restoration, and the strength of evidence was influenced by the amount of spatial structure in the model. Allowing trends to vary among zones and accounting for topographic heterogeneity increased precision of trend estimates. Accounting for spatial autocorrelation shifted parameter coefficients in ways that varied among zones depending on strength of statistical shrinkage, autocorrelation and topographic heterogeneity-a phenomenon not widely described. Spatially explicit estimates of trend from hierarchical models will generally be more useful to land managers than pooled regional estimates and provide more realistic assessments of uncertainty. The ability to grapple with historical contingency is an appealing benefit of this approach.

A polygon-based modeling approach to assess exposure of resources and assets to wildfire

Treesearch

Matthew P. Thompson; Joe Scott; Jeffrey D. Kaiden; Julie W. Gilbertson-Day

2013-01-01

Spatially explicit burn probability modeling is increasingly applied to assess wildfire risk and inform mitigation strategy development. Burn probabilities are typically expressed on a per-pixel basis, calculated as the number of times a pixel burns divided by the number of simulation iterations. Spatial intersection of highly valued resources and assets (HVRAs) with...

Priming Facial Gender and Emotional Valence: The Influence of Spatial Frequency on Face Perception in ASD

ERIC Educational Resources Information Center

Vanmarcke, Steven; Wagemans, Johan

2017-01-01

Adolescents with and without autism spectrum disorder (ASD) performed two priming experiments in which they implicitly processed a prime stimulus, containing high and/or low spatial frequency information, and then explicitly categorized a target face either as male/female (gender task) or as positive/negative (Valence task). Adolescents with ASD…

Spatially explicit forecasts of large wildland fire probability and suppression costs for California

Treesearch

Haiganoush Preisler; Anthony L. Westerling; Krista M. Gebert; Francisco Munoz-Arriola; Thomas P. Holmes

2011-01-01

In the last decade, increases in fire activity and suppression expenditures have caused budgetary problems for federal land management agencies. Spatial forecasts of upcoming fire activity and costs have the potential to help reduce expenditures, and increase the efficiency of suppression efforts, by enabling them to focus resources where they have the greatest effect...

Integrating ecosystem sampling, gradient modeling, remote sensing, and ecosystem simulation to create spatially explicit landscape inventories

Treesearch

Robert E. Keane; Matthew G. Rollins; Cecilia H. McNicoll; Russell A. Parsons

2002-01-01

Presented is a prototype of the Landscape Ecosystem Inventory System (LEIS), a system for creating maps of important landscape characteristics for natural resource planning. This system uses gradient-based field inventories coupled with gradient modeling remote sensing, ecosystem simulation, and statistical analyses to derive spatial data layers required for ecosystem...

Phenology and trend indicators derived from spatially dynamic bi-weekly satellite imagery to support ecosystem monitoring

Treesearch

Barron J. Orr; Grant M. Casady; Daniel G. Tuttle; Willem J. D. van Leeuwen; Laura E. Baker; Colleen I. McDonald; Stuart E. Marsh

2005-01-01

Ground-based ecosystem monitoring presents some practical challenges to natural resource managers and ecologists tasked with assessing vegetation dynamics across large areas through time. RangeView (http://rangeview.arizona.edu) provides online access to spatially and temporally explicit biweekly vegetation indices derived from satellite data. It also permits side-by-...

Into the environment of mosquito-borne disease: A spatial analysis of vector distribution using traditional and remotely sensed methods

NASA Astrophysics Data System (ADS)

Brown, Heidi E.

Spatially explicit information is increasingly available for infectious disease modeling. However, such information is reluctantly or inappropriately incorporated. My dissertation research uses spatially explicit data to assess relationships between landscape and mosquito species distribution and discusses challenges regarding accurate predictive risk modeling. The goal of my research is to use remotely sensed environmental information and spatial statistical methods to better understand mosquito-borne disease epidemiology for improvement of public health responses. In addition to reviewing the progress of spatial infectious disease modeling, I present four research projects. I begin by evaluating the biases in surveillance data and build up to predictive modeling of mosquito species presence. In the first study I explore how mosquito surveillance trap types influence estimations of mosquito populations. Then. I use county-based human surveillance data and landscape variables to identify risk factors for West Nile virus disease. The third study uses satellite-based vegetation indices to identify spatial variation among West Nile virus vectors in an urban area and relates the variability to virus transmission dynamics. Finally, I explore how information from three satellite sensors of differing spatial and spectral resolution can be used to identify and distinguish mosquito habitat across central Connecticut wetlands. Analyses presented here constitute improvements to the prediction of mosquito distribution and therefore identification of disease risk factors. Current methods for mosquito surveillance data collection are labor intensive and provide an extremely limited, incomplete picture of the species composition and abundance. Human surveillance data offers additional challenges with respect to reporting bias and resolution, but is nonetheless informative in identifying environmental risk factors and disease transmission dynamics. Remotely sensed imagery supports mosquito and human disease surveillance data by providing spatially explicit, line resolution information about environmental factors relevant to vector-borne disease processes. Together, surveillance and remotely sensed environmental data facilitate improved description and modeling of disease transmission. Remote sensing can be used to develop predictive maps of mosquito distribution in relation to disease risk. This has implications for increased accuracy of mosquito control efforts. The projects presented in this dissertation enhance current public health capacities by examining the applications of spatial modeling with respect to mosquito-borne disease.

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...

Measuring spatial and temporal Ca2+ signals in Arabidopsis plants.

PubMed

Zhu, Xiaohong; Taylor, Aaron; Zhang, Shenyu; Zhang, Dayong; Feng, Ying; Liang, Gaimei; Zhu, Jian-Kang

2014-09-02

Developmental and environmental cues induce Ca(2+) fluctuations in plant cells. Stimulus-specific spatial-temporal Ca(2+) patterns are sensed by cellular Ca(2+) binding proteins that initiate Ca(2+) signaling cascades. However, we still know little about how stimulus specific Ca(2+) signals are generated. The specificity of a Ca(2+) signal may be attributed to the sophisticated regulation of the activities of Ca(2+) channels and/or transporters in response to a given stimulus. To identify these cellular components and understand their functions, it is crucial to use systems that allow a sensitive and robust recording of Ca(2+) signals at both the tissue and cellular levels. Genetically encoded Ca(2+) indicators that are targeted to different cellular compartments have provided a platform for live cell confocal imaging of cellular Ca(2+) signals. Here we describe instructions for the use of two Ca(2+) detection systems: aequorin based FAS (film adhesive seedlings) luminescence Ca(2+) imaging and case12 based live cell confocal fluorescence Ca(2+) imaging. Luminescence imaging using the FAS system provides a simple, robust and sensitive detection of spatial and temporal Ca(2+) signals at the tissue level, while live cell confocal imaging using Case12 provides simultaneous detection of cytosolic and nuclear Ca(2+) signals at a high resolution.

Nuclear Cytoplasmic Trafficking of Proteins is a Major Response of Human Fibroblasts to Oxidative Stress

PubMed Central

Baqader, Noor O.; Radulovic, Marko; Crawford, Mark; Stoeber, Kai; Godovac-Zimmermann, Jasminka

2014-01-01

We have used a subcellular spatial razor approach based on LC–MS/MS-based proteomics with SILAC isotope labeling to determine changes in protein abundances in the nuclear and cytoplasmic compartments of human IMR90 fibroblasts subjected to mild oxidative stress. We show that response to mild tert-butyl hydrogen peroxide treatment includes redistribution between the nucleus and cytoplasm of numerous proteins not previously associated with oxidative stress. The 121 proteins with the most significant changes encompass proteins with known functions in a wide variety of subcellular locations and of cellular functional processes (transcription, signal transduction, autophagy, iron metabolism, TCA cycle, ATP synthesis) and are consistent with functional networks that are spatially dispersed across the cell. Both nuclear respiratory factor 2 and the proline regulatory axis appear to contribute to the cellular metabolic response. Proteins involved in iron metabolism or with iron/heme as a cofactor as well as mitochondrial proteins are prominent in the response. Evidence suggesting that nuclear import/export and vesicle-mediated protein transport contribute to the cellular response was obtained. We suggest that measurements of global changes in total cellular protein abundances need to be complemented with measurements of the dynamic subcellular spatial redistribution of proteins to obtain comprehensive pictures of cellular function. PMID:25133973

On the spatial dynamics and oscillatory behavior of a predator-prey model based on cellular automata and local particle swarm optimization.

PubMed

Molina, Mario Martínez; Moreno-Armendáriz, Marco A; Carlos Seck Tuoh Mora, Juan

2013-11-07

A two-dimensional lattice model based on Cellular Automata theory and swarm intelligence is used to study the spatial and population dynamics of a theoretical ecosystem. It is found that the social interactions among predators provoke the formation of clusters, and that by increasing the mobility of predators the model enters into an oscillatory behavior. © 2013 Elsevier Ltd. All rights reserved.

Spatially-explicit models of global tree density.

PubMed

Glick, Henry B; Bettigole, Charlie; Maynard, Daniel S; Covey, Kristofer R; Smith, Jeffrey R; Crowther, Thomas W

2016-08-16

Remote sensing and geographic analysis of woody vegetation provide means of evaluating the distribution of natural resources, patterns of biodiversity and ecosystem structure, and socio-economic drivers of resource utilization. While these methods bring geographic datasets with global coverage into our day-to-day analytic spheres, many of the studies that rely on these strategies do not capitalize on the extensive collection of existing field data. We present the methods and maps associated with the first spatially-explicit models of global tree density, which relied on over 420,000 forest inventory field plots from around the world. This research is the result of a collaborative effort engaging over 20 scientists and institutions, and capitalizes on an array of analytical strategies. Our spatial data products offer precise estimates of the number of trees at global and biome scales, but should not be used for local-level estimation. At larger scales, these datasets can contribute valuable insight into resource management, ecological modelling efforts, and the quantification of ecosystem services.

Modeled historical land use and land cover for the conterminous United States

USGS Publications Warehouse

Sohl, Terry L.; Reker, Ryan R.; Bouchard, Michelle A.; Sayler, Kristi L.; Dornbierer, Jordan; Wika, Steve; Quenzer, Robert; Friesz, Aaron M.

2016-01-01

The landscape of the conterminous United States has changed dramatically over the last 200 years, with agricultural land use, urban expansion, forestry, and other anthropogenic activities altering land cover across vast swaths of the country. While land use and land cover (LULC) models have been developed to model potential future LULC change, few efforts have focused on recreating historical landscapes. Researchers at the US Geological Survey have used a wide range of historical data sources and a spatially explicit modeling framework to model spatially explicit historical LULC change in the conterminous United States from 1992 back to 1938. Annual LULC maps were produced at 250-m resolution, with 14 LULC classes. Assessment of model results showed good agreement with trends and spatial patterns in historical data sources such as the Census of Agriculture and historical housing density data, although comparison with historical data is complicated by definitional and methodological differences. The completion of this dataset allows researchers to assess historical LULC impacts on a range of ecological processes.

Independent operation of implicit working memory under cognitive load.

PubMed

Ji, Eunhee; Lee, Kyung Min; Kim, Min-Shik

2017-10-01

Implicit working memory (WM) has been known to operate non-consciously and unintentionally. The current study investigated whether implicit WM is a discrete mechanism from explicit WM in terms of cognitive resource. To induce cognitive resource competition, we used a conjunction search task (Experiment 1) and imposed spatial WM load (Experiment 2a and 2b). Each trial was composed of a set of five consecutive search displays. The location of the first four displays appeared as per pre-determined patterns, but the fifth display could follow the same pattern or not. If implicit WM can extract the moving pattern of stimuli, response times for the fifth target would be faster when it followed the pattern compared to when it did not. Our results showed implicit WM can operate when participants are searching for the conjunction target and even while maintaining spatial WM information. These results suggest that implicit WM is independent from explicit spatial WM. Copyright © 2017. Published by Elsevier Inc.

The CFL condition for spectral approximations to hyperbolic initial-boundary value problems

NASA Technical Reports Server (NTRS)

Gottlieb, David; Tadmor, Eitan

1991-01-01

The stability of spectral approximations to scalar hyperbolic initial-boundary value problems with variable coefficients are studied. Time is discretized by explicit multi-level or Runge-Kutta methods of order less than or equal to 3 (forward Euler time differencing is included), and spatial discretizations are studied by spectral and pseudospectral approximations associated with the general family of Jacobi polynomials. It is proved that these fully explicit spectral approximations are stable provided their time-step, delta t, is restricted by the CFL-like condition, delta t less than Const. N(exp-2), where N equals the spatial number of degrees of freedom. We give two independent proofs of this result, depending on two different choices of approximate L(exp 2)-weighted norms. In both approaches, the proofs hinge on a certain inverse inequality interesting for its own sake. The result confirms the commonly held belief that the above CFL stability restriction, which is extensively used in practical implementations, guarantees the stability (and hence the convergence) of fully-explicit spectral approximations in the nonperiodic case.

The CFL condition for spectral approximations to hyperbolic initial-boundary value problems

NASA Technical Reports Server (NTRS)

Gottlieb, David; Tadmor, Eitan

1990-01-01

The stability of spectral approximations to scalar hyperbolic initial-boundary value problems with variable coefficients are studied. Time is discretized by explicit multi-level or Runge-Kutta methods of order less than or equal to 3 (forward Euler time differencing is included), and spatial discretizations are studied by spectral and pseudospectral approximations associated with the general family of Jacobi polynomials. It is proved that these fully explicit spectral approximations are stable provided their time-step, delta t, is restricted by the CFL-like condition, delta t less than Const. N(exp-2), where N equals the spatial number of degrees of freedom. We give two independent proofs of this result, depending on two different choices of approximate L(exp 2)-weighted norms. In both approaches, the proofs hinge on a certain inverse inequality interesting for its own sake. The result confirms the commonly held belief that the above CFL stability restriction, which is extensively used in practical implementations, guarantees the stability (and hence the convergence) of fully-explicit spectral approximations in the nonperiodic case.

Solutions of the Taylor-Green Vortex Problem Using High-Resolution Explicit Finite Difference Methods

NASA Technical Reports Server (NTRS)

DeBonis, James R.

2013-01-01

A computational fluid dynamics code that solves the compressible Navier-Stokes equations was applied to the Taylor-Green vortex problem to examine the code s ability to accurately simulate the vortex decay and subsequent turbulence. The code, WRLES (Wave Resolving Large-Eddy Simulation), uses explicit central-differencing to compute the spatial derivatives and explicit Low Dispersion Runge-Kutta methods for the temporal discretization. The flow was first studied and characterized using Bogey & Bailley s 13-point dispersion relation preserving (DRP) scheme. The kinetic energy dissipation rate, computed both directly and from the enstrophy field, vorticity contours, and the energy spectra are examined. Results are in excellent agreement with a reference solution obtained using a spectral method and provide insight into computations of turbulent flows. In addition the following studies were performed: a comparison of 4th-, 8th-, 12th- and DRP spatial differencing schemes, the effect of the solution filtering on the results, the effect of large-eddy simulation sub-grid scale models, and the effect of high-order discretization of the viscous terms.

Interaction between scene-based and array-based contextual cueing.

PubMed

Rosenbaum, Gail M; Jiang, Yuhong V

2013-07-01

Contextual cueing refers to the cueing of spatial attention by repeated spatial context. Previous studies have demonstrated distinctive properties of contextual cueing by background scenes and by an array of search items. Whereas scene-based contextual cueing reflects explicit learning of the scene-target association, array-based contextual cueing is supported primarily by implicit learning. In this study, we investigated the interaction between scene-based and array-based contextual cueing. Participants searched for a target that was predicted by both the background scene and the locations of distractor items. We tested three possible patterns of interaction: (1) The scene and the array could be learned independently, in which case cueing should be expressed even when only one cue was preserved; (2) the scene and array could be learned jointly, in which case cueing should occur only when both cues were preserved; (3) overshadowing might occur, in which case learning of the stronger cue should preclude learning of the weaker cue. In several experiments, we manipulated the nature of the contextual cues present during training and testing. We also tested explicit awareness of scenes, scene-target associations, and arrays. The results supported the overshadowing account: Specifically, scene-based contextual cueing precluded array-based contextual cueing when both were predictive of the location of a search target. We suggest that explicit, endogenous cues dominate over implicit cues in guiding spatial attention.

Conservation Action Based on Threatened Species Capture Taxonomic and Phylogenetic Richness in Breeding and Wintering Populations of Central Asian Birds

PubMed Central

Schweizer, Manuel; Ayé, Raffael; Kashkarov, Roman; Roth, Tobias

2014-01-01

Although phylogenetic diversity has been suggested to be relevant from a conservation point of view, its role is still limited in applied nature conservation. Recently, the practice of investing conservation resources based on threatened species was identified as a reason for the slow integration of phylogenetic diversity in nature conservation planning. One of the main arguments is based on the observation that threatened species are not evenly distributed over the phylogenetic tree. However this argument seems to dismiss the fact that conservation action is a spatially explicit process, and even if threatened species are not evenly distributed over the phylogenetic tree, the occurrence of threatened species could still indicate areas with above average phylogenetic diversity and consequently could protect phylogenetic diversity. Here we aim to study the selection of important bird areas in Central Asia, which were nominated largely based on the presence of threatened bird species. We show that although threatened species occurring in Central Asia do not capture phylogenetically more distinct species than expected by chance, the current spatially explicit conservation approach of selecting important bird areas covers above average taxonomic and phylogenetic diversity of breeding and wintering birds. We conclude that the spatially explicit processes of conservation actions need to be considered in the current discussion of whether new prioritization methods are needed to complement conservation action based on threatened species. PMID:25337861

Remote Sensing of Ecosystem Health: Opportunities, Challenges, and Future Perspectives

PubMed Central

Li, Zhaoqin; Xu, Dandan; Guo, Xulin

2014-01-01

Maintaining a healthy ecosystem is essential for maximizing sustainable ecological services of the best quality to human beings. Ecological and conservation research has provided a strong scientific background on identifying ecological health indicators and correspondingly making effective conservation plans. At the same time, ecologists have asserted a strong need for spatially explicit and temporally effective ecosystem health assessments based on remote sensing data. Currently, remote sensing of ecosystem health is only based on one ecosystem attribute: vigor, organization, or resilience. However, an effective ecosystem health assessment should be a comprehensive and dynamic measurement of the three attributes. This paper reviews opportunities of remote sensing, including optical, radar, and LiDAR, for directly estimating indicators of the three ecosystem attributes, discusses the main challenges to develop a remote sensing-based spatially-explicit comprehensive ecosystem health system, and provides some future perspectives. The main challenges to develop a remote sensing-based spatially-explicit comprehensive ecosystem health system are: (1) scale issue; (2) transportability issue; (3) data availability; and (4) uncertainties in health indicators estimated from remote sensing data. However, the Radarsat-2 constellation, upcoming new optical sensors on Worldview-3 and Sentinel-2 satellites, and improved technologies for the acquisition and processing of hyperspectral, multi-angle optical, radar, and LiDAR data and multi-sensoral data fusion may partly address the current challenges. PMID:25386759

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

Route learning in Korsakoff's syndrome: Residual acquisition of spatial memory despite profound amnesia.

PubMed

Oudman, Erik; Van der Stigchel, Stefan; Nijboer, Tanja C W; Wijnia, Jan W; Seekles, Maaike L; Postma, Albert

2016-03-01

Korsakoff's syndrome (KS) is characterized by explicit amnesia, but relatively spared implicit memory. The aim of this study was to assess to what extent KS patients can acquire spatial information while performing a spatial navigation task. Furthermore, we examined whether residual spatial acquisition in KS was based on automatic or effortful coding processes. Therefore, 20 KS patients and 20 matched healthy controls performed six tasks on spatial navigation after they navigated through a residential area. Ten participants per group were instructed to pay close attention (intentional condition), while 10 received mock instructions (incidental condition). KS patients showed hampered performance on a majority of tasks, yet their performance was superior to chance level on a route time and distance estimation tasks, a map drawing task and a route walking task. Performance was relatively spared on the route distance estimation task, but there were large variations between participants. Acquisition in KS was automatic rather than effortful, since no significant differences were obtained between the intentional and incidental condition on any task, whereas for the healthy controls, the intention to learn was beneficial for the map drawing task and the route walking task. The results of this study suggest that KS patients are still able to acquire spatial information during navigation on multiple domains despite the presence of the explicit amnesia. Residual acquisition is most likely based on automatic coding processes. © 2014 The British Psychological Society.

Integrating biological and social values when prioritizing places for biodiversity conservation.

PubMed

Whitehead, Amy L; Kujala, Heini; Ives, Christopher D; Gordon, Ascelin; Lentini, Pia E; Wintle, Brendan A; Nicholson, Emily; Raymond, Christopher M

2014-08-01

The consideration of information on social values in conjunction with biological data is critical for achieving both socially acceptable and scientifically defensible conservation planning outcomes. However, the influence of social values on spatial conservation priorities has received limited attention and is poorly understood. We present an approach that incorporates quantitative data on social values for conservation and social preferences for development into spatial conservation planning. We undertook a public participation GIS survey to spatially represent social values and development preferences and used species distribution models for 7 threatened fauna species to represent biological values. These spatially explicit data were simultaneously included in the conservation planning software Zonation to examine how conservation priorities changed with the inclusion of social data. Integrating spatially explicit information about social values and development preferences with biological data produced prioritizations that differed spatially from the solution based on only biological data. However, the integrated solutions protected a similar proportion of the species' distributions, indicating that Zonation effectively combined the biological and social data to produce socially feasible conservation solutions of approximately equivalent biological value. We were able to identify areas of the landscape where synergies and conflicts between different value sets are likely to occur. Identification of these synergies and conflicts will allow decision makers to target communication strategies to specific areas and ensure effective community engagement and positive conservation outcomes. © 2014 Society for Conservation Biology.

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

Spatially explicit inference for open populations: estimating demographic parameters from camera-trap studies

USGS Publications Warehouse

Gardner, Beth; Reppucci, Juan; Lucherini, Mauro; Royle, J. Andrew

2010-01-01

We develop a hierarchical capture–recapture model for demographically open populations when auxiliary spatial information about location of capture is obtained. Such spatial capture–recapture data arise from studies based on camera trapping, DNA sampling, and other situations in which a spatial array of devices records encounters of unique individuals. We integrate an individual-based formulation of a Jolly-Seber type model with recently developed spatially explicit capture–recapture models to estimate density and demographic parameters for survival and recruitment. We adopt a Bayesian framework for inference under this model using the method of data augmentation which is implemented in the software program WinBUGS. The model was motivated by a camera trapping study of Pampas cats Leopardus colocolo from Argentina, which we present as an illustration of the model in this paper. We provide estimates of density and the first quantitative assessment of vital rates for the Pampas cat in the High Andes. The precision of these estimates is poor due likely to the sparse data set. Unlike conventional inference methods which usually rely on asymptotic arguments, Bayesian inferences are valid in arbitrary sample sizes, and thus the method is ideal for the study of rare or endangered species for which small data sets are typical.

Landscape genomics of Sphaeralcea ambigua in the Mojave Desert: a multivariate, spatially-explicit approach to guide ecological restoration

USGS Publications Warehouse

Shryock, Daniel F.; Havrilla, Caroline A.; DeFalco, Lesley; Esque, Todd C.; Custer, Nathan; Wood, Troy E.

2015-01-01

Local adaptation influences plant species’ responses to climate change and their performance in ecological restoration. Fine-scale physiological or phenological adaptations that direct demographic processes may drive intraspecific variability when baseline environmental conditions change. Landscape genomics characterize adaptive differentiation by identifying environmental drivers of adaptive genetic variability and mapping the associated landscape patterns. We applied such an approach to Sphaeralcea ambigua, an important restoration plant in the arid southwestern United States, by analyzing variation at 153 amplified fragment length polymorphism loci in the context of environmental gradients separating 47 Mojave Desert populations. We identified 37 potentially adaptive loci through a combination of genome scan approaches. We then used a generalized dissimilarity model (GDM) to relate variability in potentially adaptive loci with spatial gradients in temperature, precipitation, and topography. We identified non-linear thresholds in loci frequencies driven by summer maximum temperature and water stress, along with continuous variation corresponding to temperature seasonality. Two GDM-based approaches for mapping predicted patterns of local adaptation are compared. Additionally, we assess uncertainty in spatial interpolations through a novel spatial bootstrapping approach. Our study presents robust, accessible methods for deriving spatially-explicit models of adaptive genetic variability in non-model species that will inform climate change modelling and ecological restoration.

Assessment of flood susceptible areas using spatially explicit, probabilistic multi-criteria decision analysis

NASA Astrophysics Data System (ADS)

Tang, Zhongqian; Zhang, Hua; Yi, Shanzhen; Xiao, Yangfan

2018-03-01

GIS-based multi-criteria decision analysis (MCDA) is increasingly used to support flood risk assessment. However, conventional GIS-MCDA methods fail to adequately represent spatial variability and are accompanied with considerable uncertainty. It is, thus, important to incorporate spatial variability and uncertainty into GIS-based decision analysis procedures. This research develops a spatially explicit, probabilistic GIS-MCDA approach for the delineation of potentially flood susceptible areas. The approach integrates the probabilistic and the local ordered weighted averaging (OWA) methods via Monte Carlo simulation, to take into account the uncertainty related to criteria weights, spatial heterogeneity of preferences and the risk attitude of the analyst. The approach is applied to a pilot study for the Gucheng County, central China, heavily affected by the hazardous 2012 flood. A GIS database of six geomorphological and hydrometeorological factors for the evaluation of susceptibility was created. Moreover, uncertainty and sensitivity analysis were performed to investigate the robustness of the model. The results indicate that the ensemble method improves the robustness of the model outcomes with respect to variation in criteria weights and identifies which criteria weights are most responsible for the variability of model outcomes. Therefore, the proposed approach is an improvement over the conventional deterministic method and can provides a more rational, objective and unbiased tool for flood susceptibility evaluation.

Spatially explicit inference for open populations: estimating demographic parameters from camera-trap studies.

PubMed

Gardner, Beth; Reppucci, Juan; Lucherini, Mauro; Royle, J Andrew

2010-11-01

We develop a hierarchical capture-recapture model for demographically open populations when auxiliary spatial information about location of capture is obtained. Such spatial capture-recapture data arise from studies based on camera trapping, DNA sampling, and other situations in which a spatial array of devices records encounters of unique individuals. We integrate an individual-based formulation of a Jolly-Seber type model with recently developed spatially explicit capture-recapture models to estimate density and demographic parameters for survival and recruitment. We adopt a Bayesian framework for inference under this model using the method of data augmentation which is implemented in the software program WinBUGS. The model was motivated by a camera trapping study of Pampas cats Leopardus colocolo from Argentina, which we present as an illustration of the model in this paper. We provide estimates of density and the first quantitative assessment of vital rates for the Pampas cat in the High Andes. The precision of these estimates is poor due likely to the sparse data set. Unlike conventional inference methods which usually rely on asymptotic arguments, Bayesian inferences are valid in arbitrary sample sizes, and thus the method is ideal for the study of rare or endangered species for which small data sets are typical.

Geomorphology Drives Amphibian Beta Diversity in Atlantic Forest Lowlands of Southeastern Brazil

PubMed Central

Luiz, Amom Mendes; Leão-Pires, Thiago Augusto; Sawaya, Ricardo J.

2016-01-01

Beta diversity patterns are the outcome of multiple processes operating at different scales. Amphibian assemblages seem to be affected by contemporary climate and dispersal-based processes. However, historical processes involved in present patterns of beta diversity remain poorly understood. We assess and disentangle geomorphological, climatic and spatial drivers of amphibian beta diversity in coastal lowlands of the Atlantic Forest, southeastern Brazil. We tested the hypothesis that geomorphological factors are more important in structuring anuran beta diversity than climatic and spatial factors. We obtained species composition via field survey (N = 766 individuals), museum specimens (N = 9,730) and literature records (N = 4,763). Sampling area was divided in four spatially explicit geomorphological units, representing historical predictors. Climatic descriptors were represented by the first two axis of a Principal Component Analysis. Spatial predictors in different spatial scales were described by Moran Eigenvector Maps. Redundancy Analysis was implemented to partition the explained variation of species composition by geomorphological, climatic and spatial predictors. Moreover, spatial autocorrelation analyses were used to test neutral theory predictions. Beta diversity was spatially structured in broader scales. Shared fraction between climatic and geomorphological variables was an important predictor of species composition (13%), as well as broad scale spatial predictors (13%). However, geomorphological variables alone were the most important predictor of beta diversity (42%). Historical factors related to geomorphology must have played a crucial role in structuring amphibian beta diversity. The complex relationships between geomorphological history and climatic gradients generated by the Serra do Mar Precambrian basements were also important. We highlight the importance of combining spatially explicit historical and contemporary predictors for understanding and disentangling major drivers of beta diversity patterns. PMID:27171522

Geomorphology Drives Amphibian Beta Diversity in Atlantic Forest Lowlands of Southeastern Brazil.

PubMed

Luiz, Amom Mendes; Leão-Pires, Thiago Augusto; Sawaya, Ricardo J

2016-01-01

Beta diversity patterns are the outcome of multiple processes operating at different scales. Amphibian assemblages seem to be affected by contemporary climate and dispersal-based processes. However, historical processes involved in present patterns of beta diversity remain poorly understood. We assess and disentangle geomorphological, climatic and spatial drivers of amphibian beta diversity in coastal lowlands of the Atlantic Forest, southeastern Brazil. We tested the hypothesis that geomorphological factors are more important in structuring anuran beta diversity than climatic and spatial factors. We obtained species composition via field survey (N = 766 individuals), museum specimens (N = 9,730) and literature records (N = 4,763). Sampling area was divided in four spatially explicit geomorphological units, representing historical predictors. Climatic descriptors were represented by the first two axis of a Principal Component Analysis. Spatial predictors in different spatial scales were described by Moran Eigenvector Maps. Redundancy Analysis was implemented to partition the explained variation of species composition by geomorphological, climatic and spatial predictors. Moreover, spatial autocorrelation analyses were used to test neutral theory predictions. Beta diversity was spatially structured in broader scales. Shared fraction between climatic and geomorphological variables was an important predictor of species composition (13%), as well as broad scale spatial predictors (13%). However, geomorphological variables alone were the most important predictor of beta diversity (42%). Historical factors related to geomorphology must have played a crucial role in structuring amphibian beta diversity. The complex relationships between geomorphological history and climatic gradients generated by the Serra do Mar Precambrian basements were also important. We highlight the importance of combining spatially explicit historical and contemporary predictors for understanding and disentangling major drivers of beta diversity patterns.

Analysis of Extreme Snow Water Equivalent Data in Central New Hampshire

NASA Astrophysics Data System (ADS)

Vuyovich, C.; Skahill, B. E.; Kanney, J. F.; Carr, M.

2017-12-01

Heavy snowfall and snowmelt-related events have been linked to widespread flooding and damages in many regions of the U.S. Design of critical infrastructure in these regions requires spatial estimates of extreme snow water equivalent (SWE). In this study, we develop station specific and spatially explicit estimates of extreme SWE using data from fifteen snow sampling stations maintained by the New Hampshire Department of Environmental Services. The stations are located in the Mascoma, Pemigewasset, Winnipesaukee, Ossipee, Salmon Falls, Lamprey, Sugar, and Isinglass basins in New Hampshire. The average record length for the fifteen stations is approximately fifty-nine years. The spatial analysis of extreme SWE involves application of two Bayesian Hierarchical Modeling methods, one that assumes conditional independence, and another which uses the Smith max-stable process model to account for spatial dependence. We also apply additional max-stable process models, albeit not in a Bayesian framework, that better model the observed dependence among the extreme SWE data. The spatial process modeling leverages readily available and relevant spatially explicit covariate data. The noted additional max-stable process models also used the nonstationary winter North Atlantic Oscillation index, which has been observed to influence snowy weather along the east coast of the United States. We find that, for this data set, SWE return level estimates are consistently higher when derived using methods which account for the observed spatial dependence among the extreme data. This is particularly significant for design scenarios of relevance for critical infrastructure evaluation.

Evolving binary classifiers through parallel computation of multiple fitness cases.

PubMed

Cagnoni, Stefano; Bergenti, Federico; Mordonini, Monica; Adorni, Giovanni

2005-06-01

This paper describes two versions of a novel approach to developing binary classifiers, based on two evolutionary computation paradigms: cellular programming and genetic programming. Such an approach achieves high computation efficiency both during evolution and at runtime. Evolution speed is optimized by allowing multiple solutions to be computed in parallel. Runtime performance is optimized explicitly using parallel computation in the case of cellular programming or implicitly taking advantage of the intrinsic parallelism of bitwise operators on standard sequential architectures in the case of genetic programming. The approach was tested on a digit recognition problem and compared with a reference classifier.

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.

EdgeMaps: visualizing explicit and implicit relations

NASA Astrophysics Data System (ADS)

Dörk, Marian; Carpendale, Sheelagh; Williamson, Carey

2011-01-01

In this work, we introduce EdgeMaps as a new method for integrating the visualization of explicit and implicit data relations. Explicit relations are specific connections between entities already present in a given dataset, while implicit relations are derived from multidimensional data based on shared properties and similarity measures. Many datasets include both types of relations, which are often difficult to represent together in information visualizations. Node-link diagrams typically focus on explicit data connections, while not incorporating implicit similarities between entities. Multi-dimensional scaling considers similarities between items, however, explicit links between nodes are not displayed. In contrast, EdgeMaps visualize both implicit and explicit relations by combining and complementing spatialization and graph drawing techniques. As a case study for this approach we chose a dataset of philosophers, their interests, influences, and birthdates. By introducing the limitation of activating only one node at a time, interesting visual patterns emerge that resemble the aesthetics of fireworks and waves. We argue that the interactive exploration of these patterns may allow the viewer to grasp the structure of a graph better than complex node-link visualizations.

Gap-filling a spatially explicit plant trait database: comparing imputation methods and different levels of environmental information

NASA Astrophysics Data System (ADS)

Poyatos, Rafael; Sus, Oliver; Badiella, Llorenç; Mencuccini, Maurizio; Martínez-Vilalta, Jordi

2018-05-01

The ubiquity of missing data in plant trait databases may hinder trait-based analyses of ecological patterns and processes. Spatially explicit datasets with information on intraspecific trait variability are rare but offer great promise in improving our understanding of functional biogeography. At the same time, they offer specific challenges in terms of data imputation. Here we compare statistical imputation approaches, using varying levels of environmental information, for five plant traits (leaf biomass to sapwood area ratio, leaf nitrogen content, maximum tree height, leaf mass per area and wood density) in a spatially explicit plant trait dataset of temperate and Mediterranean tree species (Ecological and Forest Inventory of Catalonia, IEFC, dataset for Catalonia, north-east Iberian Peninsula, 31 900 km2). We simulated gaps at different missingness levels (10-80 %) in a complete trait matrix, and we used overall trait means, species means, k nearest neighbours (kNN), ordinary and regression kriging, and multivariate imputation using chained equations (MICE) to impute missing trait values. We assessed these methods in terms of their accuracy and of their ability to preserve trait distributions, multi-trait correlation structure and bivariate trait relationships. The relatively good performance of mean and species mean imputations in terms of accuracy masked a poor representation of trait distributions and multivariate trait structure. Species identity improved MICE imputations for all traits, whereas forest structure and topography improved imputations for some traits. No method performed best consistently for the five studied traits, but, considering all traits and performance metrics, MICE informed by relevant ecological variables gave the best results. However, at higher missingness (> 30 %), species mean imputations and regression kriging tended to outperform MICE for some traits. MICE informed by relevant ecological variables allowed us to fill the gaps in the IEFC incomplete dataset (5495 plots) and quantify imputation uncertainty. Resulting spatial patterns of the studied traits in Catalan forests were broadly similar when using species means, regression kriging or the best-performing MICE application, but some important discrepancies were observed at the local level. Our results highlight the need to assess imputation quality beyond just imputation accuracy and show that including environmental information in statistical imputation approaches yields more plausible imputations in spatially explicit plant trait datasets.

Spatially-Explicit Simulation Modeling of Ecological Response to Climate Change: Methodological Considerations in Predicting Shifting Population Dynamics of Infectious Disease Vectors.

PubMed

Dhingra, Radhika; Jimenez, Violeta; Chang, Howard H; Gambhir, Manoj; Fu, Joshua S; Liu, Yang; Remais, Justin V

2013-09-01

Poikilothermic disease vectors can respond to altered climates through spatial changes in both population size and phenology. Quantitative descriptors to characterize, analyze and visualize these dynamic responses are lacking, particularly across large spatial domains. In order to demonstrate the value of a spatially explicit, dynamic modeling approach, we assessed spatial changes in the population dynamics of Ixodes scapularis , the Lyme disease vector, using a temperature-forced population model simulated across a grid of 4 × 4 km cells covering the eastern United States, using both modeled (Weather Research and Forecasting (WRF) 3.2.1) baseline/current (2001-2004) and projected (Representative Concentration Pathway (RCP) 4.5 and RCP 8.5; 2057-2059) climate data. Ten dynamic population features (DPFs) were derived from simulated populations and analyzed spatially to characterize the regional population response to current and future climate across the domain. Each DPF under the current climate was assessed for its ability to discriminate observed Lyme disease risk and known vector presence/absence, using data from the US Centers for Disease Control and Prevention. Peak vector population and month of peak vector population were the DPFs that performed best as predictors of current Lyme disease risk. When examined under baseline and projected climate scenarios, the spatial and temporal distributions of DPFs shift and the seasonal cycle of key questing life stages is compressed under some scenarios. Our results demonstrate the utility of spatial characterization, analysis and visualization of dynamic population responses-including altered phenology-of disease vectors to altered climate.

Spatially-Explicit Simulation Modeling of Ecological Response to Climate Change: Methodological Considerations in Predicting Shifting Population Dynamics of Infectious Disease Vectors

PubMed Central

Dhingra, Radhika; Jimenez, Violeta; Chang, Howard H.; Gambhir, Manoj; Fu, Joshua S.; Liu, Yang; Remais, Justin V.

2014-01-01

Poikilothermic disease vectors can respond to altered climates through spatial changes in both population size and phenology. Quantitative descriptors to characterize, analyze and visualize these dynamic responses are lacking, particularly across large spatial domains. In order to demonstrate the value of a spatially explicit, dynamic modeling approach, we assessed spatial changes in the population dynamics of Ixodes scapularis, the Lyme disease vector, using a temperature-forced population model simulated across a grid of 4 × 4 km cells covering the eastern United States, using both modeled (Weather Research and Forecasting (WRF) 3.2.1) baseline/current (2001–2004) and projected (Representative Concentration Pathway (RCP) 4.5 and RCP 8.5; 2057–2059) climate data. Ten dynamic population features (DPFs) were derived from simulated populations and analyzed spatially to characterize the regional population response to current and future climate across the domain. Each DPF under the current climate was assessed for its ability to discriminate observed Lyme disease risk and known vector presence/absence, using data from the US Centers for Disease Control and Prevention. Peak vector population and month of peak vector population were the DPFs that performed best as predictors of current Lyme disease risk. When examined under baseline and projected climate scenarios, the spatial and temporal distributions of DPFs shift and the seasonal cycle of key questing life stages is compressed under some scenarios. Our results demonstrate the utility of spatial characterization, analysis and visualization of dynamic population responses—including altered phenology—of disease vectors to altered climate. PMID:24772388

A Heat Vulnerability Index: Spatial Patterns of Exposure, Sensitivity and Adaptive Capacity for Santiago de Chile.

PubMed

Inostroza, Luis; Palme, Massimo; de la Barrera, Francisco

2016-01-01

Climate change will worsen the high levels of urban vulnerability in Latin American cities due to specific environmental stressors. Some impacts of climate change, such as high temperatures in urban environments, have not yet been addressed through adaptation strategies, which are based on poorly supported data. These impacts remain outside the scope of urban planning. New spatially explicit approaches that identify highly vulnerable urban areas and include specific adaptation requirements are needed in current urban planning practices to cope with heat hazards. In this paper, a heat vulnerability index is proposed for Santiago, Chile. The index was created using a GIS-based spatial information system and was constructed from spatially explicit indexes for exposure, sensitivity and adaptive capacity levels derived from remote sensing data and socio-economic information assessed via principal component analysis (PCA). The objective of this study is to determine the levels of heat vulnerability at local scales by providing insights into these indexes at the intra city scale. The results reveal a spatial pattern of heat vulnerability with strong variations among individual spatial indexes. While exposure and adaptive capacities depict a clear spatial pattern, sensitivity follows a complex spatial distribution. These conditions change when examining PCA results, showing that sensitivity is more robust than exposure and adaptive capacity. These indexes can be used both for urban planning purposes and for proposing specific policies and measures that can help minimize heat hazards in highly dynamic urban areas. The proposed methodology can be applied to other Latin American cities to support policy making.

A Heat Vulnerability Index: Spatial Patterns of Exposure, Sensitivity and Adaptive Capacity for Santiago de Chile

PubMed Central

Palme, Massimo; de la Barrera, Francisco

2016-01-01

Climate change will worsen the high levels of urban vulnerability in Latin American cities due to specific environmental stressors. Some impacts of climate change, such as high temperatures in urban environments, have not yet been addressed through adaptation strategies, which are based on poorly supported data. These impacts remain outside the scope of urban planning. New spatially explicit approaches that identify highly vulnerable urban areas and include specific adaptation requirements are needed in current urban planning practices to cope with heat hazards. In this paper, a heat vulnerability index is proposed for Santiago, Chile. The index was created using a GIS-based spatial information system and was constructed from spatially explicit indexes for exposure, sensitivity and adaptive capacity levels derived from remote sensing data and socio-economic information assessed via principal component analysis (PCA). The objective of this study is to determine the levels of heat vulnerability at local scales by providing insights into these indexes at the intra city scale. The results reveal a spatial pattern of heat vulnerability with strong variations among individual spatial indexes. While exposure and adaptive capacities depict a clear spatial pattern, sensitivity follows a complex spatial distribution. These conditions change when examining PCA results, showing that sensitivity is more robust than exposure and adaptive capacity. These indexes can be used both for urban planning purposes and for proposing specific policies and measures that can help minimize heat hazards in highly dynamic urban areas. The proposed methodology can be applied to other Latin American cities to support policy making. PMID:27606592

Multi-Scale Modeling in Morphogenesis: A Critical Analysis of the Cellular Potts Model

PubMed Central

Voss-Böhme, Anja

2012-01-01

Cellular Potts models (CPMs) are used as a modeling framework to elucidate mechanisms of biological development. They allow a spatial resolution below the cellular scale and are applied particularly when problems are studied where multiple spatial and temporal scales are involved. Despite the increasing usage of CPMs in theoretical biology, this model class has received little attention from mathematical theory. To narrow this gap, the CPMs are subjected to a theoretical study here. It is asked to which extent the updating rules establish an appropriate dynamical model of intercellular interactions and what the principal behavior at different time scales characterizes. It is shown that the longtime behavior of a CPM is degenerate in the sense that the cells consecutively die out, independent of the specific interdependence structure that characterizes the model. While CPMs are naturally defined on finite, spatially bounded lattices, possible extensions to spatially unbounded systems are explored to assess to which extent spatio-temporal limit procedures can be applied to describe the emergent behavior at the tissue scale. To elucidate the mechanistic structure of CPMs, the model class is integrated into a general multiscale framework. It is shown that the central role of the surface fluctuations, which subsume several cellular and intercellular factors, entails substantial limitations for a CPM's exploitation both as a mechanistic and as a phenomenological model. PMID:22984409

Learning from Heterogeneous Data Sources: An Application in Spatial Proteomics

PubMed Central

Breckels, Lisa M.; Holden, Sean B.; Wojnar, David; Mulvey, Claire M.; Christoforou, Andy; Groen, Arnoud; Trotter, Matthew W. B.; Kohlbacher, Oliver; Lilley, Kathryn S.; Gatto, Laurent

2016-01-01

Sub-cellular localisation of proteins is an essential post-translational regulatory mechanism that can be assayed using high-throughput mass spectrometry (MS). These MS-based spatial proteomics experiments enable us to pinpoint the sub-cellular distribution of thousands of proteins in a specific system under controlled conditions. Recent advances in high-throughput MS methods have yielded a plethora of experimental spatial proteomics data for the cell biology community. Yet, there are many third-party data sources, such as immunofluorescence microscopy or protein annotations and sequences, which represent a rich and vast source of complementary information. We present a unique transfer learning classification framework that utilises a nearest-neighbour or support vector machine system, to integrate heterogeneous data sources to considerably improve on the quantity and quality of sub-cellular protein assignment. We demonstrate the utility of our algorithms through evaluation of five experimental datasets, from four different species in conjunction with four different auxiliary data sources to classify proteins to tens of sub-cellular compartments with high generalisation accuracy. We further apply the method to an experiment on pluripotent mouse embryonic stem cells to classify a set of previously unknown proteins, and validate our findings against a recent high resolution map of the mouse stem cell proteome. The methodology is distributed as part of the open-source Bioconductor pRoloc suite for spatial proteomics data analysis. PMID:27175778

Spatially explicit measurements of forest structure and fire behavior following restoration treatments in dry forests

Treesearch

Justin Paul Ziegler; Chad Hoffman; Michael Battaglia; William Mell

2017-01-01

Restoration treatments in dry forests of the western US often attempt silvicultural practices to restore the historical characteristics of forest structure and fire behavior. However, it is suggested that a reliance on non-spatial metrics of forest stand structure, along with the use of wildland fire behavior models that lack the ability to handle complex structures,...

PREDICTING RELATIVE RISK OF INVASION BY SALTCEDAR AND MUD SNAILS IN RIVER NETWORKS UNDER DIFFERENT SCENARIOS OF CLIMATE CHANGE AND DAM OPERATIONS IN THE WESTERN UNITED STATES

EPA Science Inventory

This synthetic, multi-scale approach will generate a sequence of spatially explicit maps that will provide science guidance to support strategic decision-making regarding the spatially-distributed risk of, and possible adaptation to, the spread of invasive species at local to ...

Predicted effects of gypsy moth defoliation and climate change on forest carbon dynamics in the New Jersey Pine Barrens

Treesearch

Alec M. Kretchun; Robert M. Scheller; Melissa S. Lucash; Kenneth L. Clark; John Hom; Steve Van Tuyl; Michael L. Fine

2014-01-01

Disturbance regimes within temperate forests can significantly impact carbon cycling. Additionally, projected climate change in combination with multiple, interacting disturbance effects may disrupt the capacity of forests to act as carbon sinks at large spatial and temporal scales. We used a spatially explicit forest succession and disturbance model, LANDIS-II, to...

Application of spatial models to the stopover ecology of trans-Gulf migrants

Treesearch

Theodore R. Simons; Scott M. Pearson; Frank R. Moore

2000-01-01

Studies at migratory stopover sites along the northern coast of the Gulf of Mexico are providing an understanding of how weather, habitat, and energetic factors combine to shape the stopover ecology of trans-Gulf migrants. We are coupling this understanding with analyses of landscape-level patterns of habitat availability by using spatially explicit models to simulate...

LANDIS 4.0 users guide. LANDIS: a spatially explicit model of forest landscape disturbance, management, and succession

Treesearch

Hong S. He; Wei Li; Brian R. Sturtevant; Jian Yang; Bo Z. Shang; Eric J. Gustafson; David J. Mladenoff

2005-01-01

LANDIS 4.0 is new-generation software that simulates forest landscape change over large spatial and temporal scales. It is used to explore how disturbances, succession, and management interact to determine forest composition and pattern. Also describes software architecture, model assumptions and provides detailed instructions on the use of the model.

Consistency of forest presence and biomass predictions modeled across overlapping spatial and temporal extents

Treesearch

Mark D. Nelson; Sean Healey; W. Keith Moser; J.G. Masek; Warren Cohen

2011-01-01

We assessed the consistency across space and time of spatially explicit models of forest presence and biomass in southern Missouri, USA, for adjacent, partially overlapping satellite image Path/Rows, and for coincident satellite images from the same Path/Row acquired in different years. Such consistency in satellite image-based classification and estimation is critical...

Solitons in two attractive semiconductor nanowires

NASA Astrophysics Data System (ADS)

Vroumsia, David; Mibaile, Justin; Gambo, Betchewe; Doka, Yamigno Serge; Kofane, Timoleon Crepin

2018-02-01

In this paper, by using two semiconductor nanowires attracted to each other by means of Lorentz force, we construct through similarity transformations, explicit solutions to the coupled nonlinear Schrodinger equations (CNSE) with potentials as a function of time and spatial coordinates. We find explicit solutions of electrons and holes such as periodic, bright and dark solitons. We also study the instability of the modulation (MI) of (CNSE) and note that the velocity of the electrons influences the gain MI spectrum.

Modeling Land Use/Cover Changes in an African Rural Landscape

NASA Astrophysics Data System (ADS)

Kamusoko, C.; Aniya, M.

2006-12-01

Land use/cover changes are analyzed in the Bindura district of Zimbabwe, Africa through the integration of data from a time series of Landsat imagery (1973, 1989 and 2000), a household survey and GIS coverages. We employed a hybrid supervised/unsupervised classification approach to generate land use/cover maps from which landscape metrics were calculated. Population and other household variables were derived from a sample of surveyed villages, while road accessibility and slope were obtained from topographic maps and digital elevation model, respectively. Markov-cellular automata modeling approach that incorporates Markov chain analysis, cellular automata and multi-criteria evaluation (MCE) / multi-objective allocation (MOLA) procedures was used to simulate land use/cover changes. A GIS-based MCE technique computed transition potential maps, whereas transition areas were derived from the 1973-2000 land use/cover maps using the Markov chain analysis. A 5 x 5 cellular automata filter was used to develop a spatially explicit contiguity- weighting factor to change the cells based on its previous state and those of its neighbors, while MOLA resolved land use/cover class allocation conflicts. The kappa index of agreement was used for model validation. Observed trends in land use/cover changes indicate that deforestation and the encroachment of cultivation in woodland areas is a continuous trend in the study area. This suggests that economic activities driven by agricultural expansion were the main causes of landscape fragmentation, leading to landscape degradation. Rigorous calibration of transition potential maps done by a MCE algorithm and Markovian transition probabilities produced accurate inputs for the simulation of land use/cover changes. Overall standard kappa index of agreement ranged from 0.73 to 0.83, which is sufficient for simulating land use/cover changes in the study area. Land use/cover simulations under the 1989 and 2000 scenario indicated further landscape degradation in the rural areas of the Bindura district. Keywords: Zimbabwe, land use/cover changes, landscape fragmentation, GIS, land use/cover change modeling, multi-criteria evaluation/multi-objective allocation procedures, Markov-cellular automata

Implicit transfer of spatial structure in visuomotor sequence learning.

PubMed

Tanaka, Kanji; Watanabe, Katsumi

2014-11-01

Implicit learning and transfer in sequence learning are essential in daily life. Here, we investigated the implicit transfer of visuomotor sequences following a spatial transformation. In the two experiments, participants used trial and error to learn a sequence consisting of several button presses, known as the m×n task (Hikosaka et al., 1995). After this learning session, participants learned another sequence in which the button configuration was spatially transformed in one of the following ways: mirrored, rotated, and random arrangement. Our results showed that even when participants were unaware of the transformation rules, accuracy of transfer session in the mirrored and rotated groups was higher than that in the random group (i.e., implicit transfer occurred). Both those who noticed the transformation rules and those who did not (i.e., explicit and implicit transfer instances, respectively) showed faster performance in the mirrored sequences than in the rotated sequences. Taken together, the present results suggest that people can use their implicit visuomotor knowledge to spatially transform sequences and that implicit transfers are modulated by a transformation cost, similar to that in explicit transfer. Copyright © 2014 Elsevier B.V. All rights reserved.

A spatially explicit risk assessment approach: Cetaceans and marine traffic in the Pelagos Sanctuary (Mediterranean Sea)

PubMed Central

Arcangeli, Antonella; Prado Fonseca, Vinícius; Campana, Ilaria; Pierce, Graham J.; Rotta, Andrea; Bellido, Jose Maria

2017-01-01

Spatially explicit risk assessment is an essential component of Marine Spatial Planning (MSP), which provides a comprehensive framework for managing multiple uses of the marine environment, minimizing environmental impacts and conflicts among users. In this study, we assessed the risk of the exposure to high intensity vessel traffic areas for the three most abundant cetacean species (Stenella coeruleoalba, Tursiops truncatus and Balaenoptera physalus) in the southern area of the Pelagos Sanctuary, which is the only pelagic Marine Protected Area (MPA) for marine mammals in the Mediterranean Sea. In particular, we modeled the occurrence of the three cetacean species as a function of habitat variables in June by using hierarchical Bayesian spatial-temporal models. Similarly, we modelled the marine traffic intensity in order to find high risk areas and estimated the potential conflict due to the overlap with the cetacean home ranges. Results identified two main hot-spots of high intensity marine traffic in the area, which partially overlap with the area of presence of the studied species. Our findings emphasize the need for nationally relevant and transboundary planning and management measures for these marine species. PMID:28644882

A spatially explicit risk assessment approach: Cetaceans and marine traffic in the Pelagos Sanctuary (Mediterranean Sea).

PubMed

Pennino, Maria Grazia; Arcangeli, Antonella; Prado Fonseca, Vinícius; Campana, Ilaria; Pierce, Graham J; Rotta, Andrea; Bellido, Jose Maria

2017-01-01

Spatially explicit risk assessment is an essential component of Marine Spatial Planning (MSP), which provides a comprehensive framework for managing multiple uses of the marine environment, minimizing environmental impacts and conflicts among users. In this study, we assessed the risk of the exposure to high intensity vessel traffic areas for the three most abundant cetacean species (Stenella coeruleoalba, Tursiops truncatus and Balaenoptera physalus) in the southern area of the Pelagos Sanctuary, which is the only pelagic Marine Protected Area (MPA) for marine mammals in the Mediterranean Sea. In particular, we modeled the occurrence of the three cetacean species as a function of habitat variables in June by using hierarchical Bayesian spatial-temporal models. Similarly, we modelled the marine traffic intensity in order to find high risk areas and estimated the potential conflict due to the overlap with the cetacean home ranges. Results identified two main hot-spots of high intensity marine traffic in the area, which partially overlap with the area of presence of the studied species. Our findings emphasize the need for nationally relevant and transboundary planning and management measures for these marine species.

Integrating spatially explicit representations of landscape perceptions into land change research

USGS Publications Warehouse

Dorning, Monica; Van Berkel, Derek B.; Semmens, Darius J.

2017-01-01

Purpose of ReviewHuman perceptions of the landscape can influence land-use and land-management decisions. Recognizing the diversity of landscape perceptions across space and time is essential to understanding land change processes and emergent landscape patterns. We summarize the role of landscape perceptions in the land change process, demonstrate advances in quantifying and mapping landscape perceptions, and describe how these spatially explicit techniques have and may benefit land change research.Recent FindingsMapping landscape perceptions is becoming increasingly common, particularly in research focused on quantifying ecosystem services provision. Spatial representations of landscape perceptions, often measured in terms of landscape values and functions, provide an avenue for matching social and environmental data in land change studies. Integrating these data can provide new insights into land change processes, contribute to landscape planning strategies, and guide the design and implementation of land change models.SummaryChallenges remain in creating spatial representations of human perceptions. Maps must be accompanied by descriptions of whose perceptions are being represented and the validity and uncertainty of those representations across space. With these considerations, rapid advancements in mapping landscape perceptions hold great promise for improving representation of human dimensions in landscape ecology and land change research.

Virtual Embryo: Cell-Agent Based Modeling of Developmental Processes and Toxicities (CSS BOSC)

EPA Science Inventory

Spatial regulation of cellular dynamics is fundamental to morphological development. As such, chemical disruption of spatial dynamics is a determinant of developmental toxicity. Incorporating spatial dynamics into AOPs for developmental toxicity is desired but constrained by the ...

Download Trim.Fate

EPA Pesticide Factsheets

TRIM.FaTE is a spatially explicit, compartmental mass balance model that describes the movement and transformation of pollutants over time, through a user-defined, bounded system that includes both biotic and abiotic compartments.

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.

Need for speed: An optimized gridding approach for spatially explicit disease simulations.

PubMed

Sellman, Stefan; Tsao, Kimberly; Tildesley, Michael J; Brommesson, Peter; Webb, Colleen T; Wennergren, Uno; Keeling, Matt J; Lindström, Tom

2018-04-01

Numerical models for simulating outbreaks of infectious diseases are powerful tools for informing surveillance and control strategy decisions. However, large-scale spatially explicit models can be limited by the amount of computational resources they require, which poses a problem when multiple scenarios need to be explored to provide policy recommendations. We introduce an easily implemented method that can reduce computation time in a standard Susceptible-Exposed-Infectious-Removed (SEIR) model without introducing any further approximations or truncations. It is based on a hierarchical infection process that operates on entire groups of spatially related nodes (cells in a grid) in order to efficiently filter out large volumes of susceptible nodes that would otherwise have required expensive calculations. After the filtering of the cells, only a subset of the nodes that were originally at risk are then evaluated for actual infection. The increase in efficiency is sensitive to the exact configuration of the grid, and we describe a simple method to find an estimate of the optimal configuration of a given landscape as well as a method to partition the landscape into a grid configuration. To investigate its efficiency, we compare the introduced methods to other algorithms and evaluate computation time, focusing on simulated outbreaks of foot-and-mouth disease (FMD) on the farm population of the USA, the UK and Sweden, as well as on three randomly generated populations with varying degree of clustering. The introduced method provided up to 500 times faster calculations than pairwise computation, and consistently performed as well or better than other available methods. This enables large scale, spatially explicit simulations such as for the entire continental USA without sacrificing realism or predictive power.

Need for speed: An optimized gridding approach for spatially explicit disease simulations

PubMed Central

Tildesley, Michael J.; Brommesson, Peter; Webb, Colleen T.; Wennergren, Uno; Lindström, Tom

2018-01-01

Numerical models for simulating outbreaks of infectious diseases are powerful tools for informing surveillance and control strategy decisions. However, large-scale spatially explicit models can be limited by the amount of computational resources they require, which poses a problem when multiple scenarios need to be explored to provide policy recommendations. We introduce an easily implemented method that can reduce computation time in a standard Susceptible-Exposed-Infectious-Removed (SEIR) model without introducing any further approximations or truncations. It is based on a hierarchical infection process that operates on entire groups of spatially related nodes (cells in a grid) in order to efficiently filter out large volumes of susceptible nodes that would otherwise have required expensive calculations. After the filtering of the cells, only a subset of the nodes that were originally at risk are then evaluated for actual infection. The increase in efficiency is sensitive to the exact configuration of the grid, and we describe a simple method to find an estimate of the optimal configuration of a given landscape as well as a method to partition the landscape into a grid configuration. To investigate its efficiency, we compare the introduced methods to other algorithms and evaluate computation time, focusing on simulated outbreaks of foot-and-mouth disease (FMD) on the farm population of the USA, the UK and Sweden, as well as on three randomly generated populations with varying degree of clustering. The introduced method provided up to 500 times faster calculations than pairwise computation, and consistently performed as well or better than other available methods. This enables large scale, spatially explicit simulations such as for the entire continental USA without sacrificing realism or predictive power. PMID:29624574

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.

Identifying and Prioritizing Greater Sage-Grouse Nesting and Brood-Rearing Habitat for Conservation in Human-Modified Landscapes

PubMed Central

Dzialak, Matthew R.; Olson, Chad V.; Harju, Seth M.; Webb, Stephen L.; Mudd, James P.; Winstead, Jeffrey B.; Hayden-Wing, L.D.

2011-01-01

Background Balancing animal conservation and human use of the landscape is an ongoing scientific and practical challenge throughout the world. We investigated reproductive success in female greater sage-grouse (Centrocercus urophasianus) relative to seasonal patterns of resource selection, with the larger goal of developing a spatially-explicit framework for managing human activity and sage-grouse conservation at the landscape level. Methodology/Principal Findings We integrated field-observation, Global Positioning Systems telemetry, and statistical modeling to quantify the spatial pattern of occurrence and risk during nesting and brood-rearing. We linked occurrence and risk models to provide spatially-explicit indices of habitat-performance relationships. As part of the analysis, we offer novel biological information on resource selection during egg-laying, incubation, and night. The spatial pattern of occurrence during all reproductive phases was driven largely by selection or avoidance of terrain features and vegetation, with little variation explained by anthropogenic features. Specifically, sage-grouse consistently avoided rough terrain, selected for moderate shrub cover at the patch level (within 90 m2), and selected for mesic habitat in mid and late brood-rearing phases. In contrast, risk of nest and brood failure was structured by proximity to anthropogenic features including natural gas wells and human-created mesic areas, as well as vegetation features such as shrub cover. Conclusions/Significance Risk in this and perhaps other human-modified landscapes is a top-down (i.e., human-mediated) process that would most effectively be minimized by developing a better understanding of specific mechanisms (e.g., predator subsidization) driving observed patterns, and using habitat-performance indices such as those developed herein for spatially-explicit guidance of conservation intervention. Working under the hypothesis that industrial activity structures risk by enhancing predator abundance or effectiveness, we offer specific recommendations for maintaining high-performance habitat and reducing low-performance habitat, particularly relative to the nesting phase, by managing key high-risk anthropogenic features such as industrial infrastructure and water developments. PMID:22022587

Shifts in frog size and phenology: Testing predictions of climate change on a widespread anuran using data from prior to rapid climate warming.

PubMed

Sheridan, Jennifer A; Caruso, Nicholas M; Apodaca, Joseph J; Rissler, Leslie J

2018-01-01

Changes in body size and breeding phenology have been identified as two major ecological consequences of climate change, yet it remains unclear whether climate acts directly or indirectly on these variables. To better understand the relationship between climate and ecological changes, it is necessary to determine environmental predictors of both size and phenology using data from prior to the onset of rapid climate warming, and then to examine spatially explicit changes in climate, size, and phenology, not just general spatial and temporal trends. We used 100 years of natural history collection data for the wood frog, Lithobates sylvaticus with a range >9 million km 2 , and spatially explicit environmental data to determine the best predictors of size and phenology prior to rapid climate warming (1901-1960). We then tested how closely size and phenology changes predicted by those environmental variables reflected actual changes from 1961 to 2000. Size, phenology, and climate all changed as expected (smaller, earlier, and warmer, respectively) at broad spatial scales across the entire study range. However, while spatially explicit changes in climate variables accurately predicted changes in phenology, they did not accurately predict size changes during recent climate change (1961-2000), contrary to expectations from numerous recent studies. Our results suggest that changes in climate are directly linked to observed phenological shifts. However, the mechanisms driving observed body size changes are yet to be determined, given the less straightforward relationship between size and climate factors examined in this study. We recommend that caution be used in "space-for-time" studies where measures of a species' traits at lower latitudes or elevations are considered representative of those under future projected climate conditions. Future studies should aim to determine mechanisms driving trends in phenology and body size, as well as the impact of climate on population density, which may influence body size.

Point process models for localization and interdependence of punctate cellular structures.

PubMed

Li, Ying; Majarian, Timothy D; Naik, Armaghan W; Johnson, Gregory R; Murphy, Robert F

2016-07-01

Accurate representations of cellular organization for multiple eukaryotic cell types are required for creating predictive models of dynamic cellular function. To this end, we have previously developed the CellOrganizer platform, an open source system for generative modeling of cellular components from microscopy images. CellOrganizer models capture the inherent heterogeneity in the spatial distribution, size, and quantity of different components among a cell population. Furthermore, CellOrganizer can generate quantitatively realistic synthetic images that reflect the underlying cell population. A current focus of the project is to model the complex, interdependent nature of organelle localization. We built upon previous work on developing multiple non-parametric models of organelles or structures that show punctate patterns. The previous models described the relationships between the subcellular localization of puncta and the positions of cell and nuclear membranes and microtubules. We extend these models to consider the relationship to the endoplasmic reticulum (ER), and to consider the relationship between the positions of different puncta of the same type. Our results do not suggest that the punctate patterns we examined are dependent on ER position or inter- and intra-class proximity. With these results, we built classifiers to update previous assignments of proteins to one of 11 patterns in three distinct cell lines. Our generative models demonstrate the ability to construct statistically accurate representations of puncta localization from simple cellular markers in distinct cell types, capturing the complex phenomena of cellular structure interaction with little human input. This protocol represents a novel approach to vesicular protein annotation, a field that is often neglected in high-throughput microscopy. These results suggest that spatial point process models provide useful insight with respect to the spatial dependence between cellular structures. © 2016 International Society for Advancement of Cytometry. © 2016 International Society for Advancement of Cytometry.

A quantum relativistic battle of the sexes cellular automaton

NASA Astrophysics Data System (ADS)

Alonso-Sanz, Ramón; Situ, Haozhen

2017-02-01

The effect of variable entangling on the dynamics of a spatial quantum relativistic formulation of the iterated battle of the sexes game is studied in this work. The game is played in the cellular automata manner, i.e., with local and synchronous interaction. The game is assessed in fair and unfair contests. Despite the full range of quantum parameters initially accessible, they promptly converge into fairly stable configurations, that often show rich spatial structures in simulations with no negligible entanglement.

Multicellular Computing Using Conjugation for Wiring

PubMed Central

Goñi-Moreno, Angel; Amos, Martyn; de la Cruz, Fernando

2013-01-01

Recent efforts in synthetic biology have focussed on the implementation of logical functions within living cells. One aim is to facilitate both internal “re-programming” and external control of cells, with potential applications in a wide range of domains. However, fundamental limitations on the degree to which single cells may be re-engineered have led to a growth of interest in multicellular systems, in which a “computation” is distributed over a number of different cell types, in a manner analogous to modern computer networks. Within this model, individual cell type perform specific sub-tasks, the results of which are then communicated to other cell types for further processing. The manner in which outputs are communicated is therefore of great significance to the overall success of such a scheme. Previous experiments in distributed cellular computation have used global communication schemes, such as quorum sensing (QS), to implement the “wiring” between cell types. While useful, this method lacks specificity, and limits the amount of information that may be transferred at any one time. We propose an alternative scheme, based on specific cell-cell conjugation. This mechanism allows for the direct transfer of genetic information between bacteria, via circular DNA strands known as plasmids. We design a multi-cellular population that is able to compute, in a distributed fashion, a Boolean XOR function. Through this, we describe a general scheme for distributed logic that works by mixing different strains in a single population; this constitutes an important advantage of our novel approach. Importantly, the amount of genetic information exchanged through conjugation is significantly higher than the amount possible through QS-based communication. We provide full computational modelling and simulation results, using deterministic, stochastic and spatially-explicit methods. These simulations explore the behaviour of one possible conjugation-wired cellular computing system under different conditions, and provide baseline information for future laboratory implementations. PMID:23840385

Protein subcellular location pattern classification in cellular images using latent discriminative models.

PubMed

Li, Jieyue; Xiong, Liang; Schneider, Jeff; Murphy, Robert F

2012-06-15

Knowledge of the subcellular location of a protein is crucial for understanding its functions. The subcellular pattern of a protein is typically represented as the set of cellular components in which it is located, and an important task is to determine this set from microscope images. In this article, we address this classification problem using confocal immunofluorescence images from the Human Protein Atlas (HPA) project. The HPA contains images of cells stained for many proteins; each is also stained for three reference components, but there are many other components that are invisible. Given one such cell, the task is to classify the pattern type of the stained protein. We first randomly select local image regions within the cells, and then extract various carefully designed features from these regions. This region-based approach enables us to explicitly study the relationship between proteins and different cell components, as well as the interactions between these components. To achieve these two goals, we propose two discriminative models that extend logistic regression with structured latent variables. The first model allows the same protein pattern class to be expressed differently according to the underlying components in different regions. The second model further captures the spatial dependencies between the components within the same cell so that we can better infer these components. To learn these models, we propose a fast approximate algorithm for inference, and then use gradient-based methods to maximize the data likelihood. In the experiments, we show that the proposed models help improve the classification accuracies on synthetic data and real cellular images. The best overall accuracy we report in this article for classifying 942 proteins into 13 classes of patterns is about 84.6%, which to our knowledge is the best so far. In addition, the dependencies learned are consistent with prior knowledge of cell organization. http://murphylab.web.cmu.edu/software/.

Spatial processes decouple management from objectives in a heterogeneous landscape: predator control as a case study.

PubMed

Mahoney, Peter J; Young, Julie K; Hersey, Kent R; Larsen, Randy T; McMillan, Brock R; Stoner, David C

2018-04-01

Predator control is often implemented with the intent of disrupting top-down regulation in sensitive prey populations. However, ambiguity surrounding the efficacy of predator management, as well as the strength of top-down effects of predators in general, is often exacerbated by the spatially implicit analytical approaches used in assessing data with explicit spatial structure. Here, we highlight the importance of considering spatial context in the case of a predator control study in south-central Utah. We assessed the spatial match between aerial removal risk in coyotes (Canis latrans) and mule deer (Odocoileus hemionus) resource selection during parturition using a spatially explicit, multi-level Bayesian model. With our model, we were able to evaluate spatial congruence between management action (i.e., coyote removal) and objective (i.e., parturient deer site selection) at two distinct scales: the level of the management unit and the individual coyote removal. In the case of the former, our results indicated substantial spatial heterogeneity in expected congruence between removal risk and parturient deer site selection across large areas, and is a reflection of logistical constraints acting on the management strategy and differences in space use between the two species. At the level of the individual removal, we demonstrated that the potential management benefits of a removed coyote were highly variable across all individuals removed and in many cases, spatially distinct from parturient deer resource selection. Our methods and results provide a means of evaluating where we might anticipate an impact of predator control, while emphasizing the need to weight individual removals based on spatial proximity to management objectives in any assessment of large-scale predator control. Although we highlight the importance of spatial context in assessments of predator control strategy, we believe our methods are readily generalizable in any management or large-scale experimental framework where spatial context is likely an important driver of outcomes. © 2018 by the Ecological Society of America.

Oak decline in the Boston Mountains, Arkansas, USA: Spatial and temporal patterns under two fire regimes

Treesearch

Martin A. Spetich; Hong S. He

2008-01-01

A spatially explicit forest succession and disturbance model is used to delineate the extent and dispersion of oak decline under two fire regimes over a 150-year period. The objectives of this study are to delineate potential current and future oak decline areas using species composition and age structure data in combination with ecological land types, and to...

Spatial and seasonal dynamics of surface soil carbon in the Luquillo Experimental Forest, Puerto Rico.

Treesearch

Hongqing Wang; Joseph D. Cornell; Charles A.S. Hall; David P. Marley

2002-01-01

We developed a spatially-explicit version of the CENTURY soil model to characterize the storage and flux of soil organic carbon (SOC, 0–30 cm depth) in the Luquillo Experimental Forest (LEF), Puerto Rico as a function of climate, vegetation, and soils. The model was driven by monthly estimates of average air temperature, precipitation, and potential evapotranspiration...

Predictive mapping of forest composition and structure with direct gradient analysis and nearest neighbor imputation in coastal Oregon, U.S.A.

Treesearch

Janet L. Ohmann; Matthew J. Gregory

2002-01-01

Spatially explicit information on the species composition and structure of forest vegetation is needed at broad spatial scales for natural resource policy analysis and ecological research. We present a method for predictive vegetation mapping that applies direct gradient analysis and nearest-neighbor imputation to ascribe detailed ground attributes of vegetation to...

TRIM.FaTE Public Reference Library Documentation

EPA Pesticide Factsheets

TRIM.FaTE is a spatially explicit, compartmental mass balance model that describes the movement and transformation of pollutants over time, through a user-defined, bounded system that includes both biotic and abiotic compartments.

The importance of spatial fishing behavior for coral reef resilience

NASA Astrophysics Data System (ADS)

Rassweiler, A.; Lauer, M.; Holbrook, S. J.

2016-02-01

Coral reefs are dynamic systems in which disturbances periodically reduce coral cover but are normally followed by recovery of the coral community. However, human activity may have reduced this resilience to disturbance in many coral reef systems, as an increasing number of reefs have undergone persistent transitions from coral-dominated to macroalgal-dominated community states. Fishing on herbivores may be one cause of reduced reef resilience, as lower herbivory can make it easier for macroalgae to become established after a disturbance. Despite the acknowledged importance of fishing, relatively little attention has been paid to the potential for feedbacks between ecosystem state and fisher behavior. Here we couple methods from environmental anthropology and ecology to explore these feedbacks between small-scale fisheries and coral reefs in Moorea, French Polynesia. We document how aspects of ecological state such as the abundance of macroalgae affect people's preference for fishing in particular lagoon habitats. We then incorporate biases towards fishing in certain ecological states into a spatially explicit bio-economic model of ecological dynamics and fishing in Moorea's lagoons. We find that feedbacks between spatial fishing behavior and ecological state can have critical effects on coral reefs. Presence of these spatial behaviors consistently leads to more coherence across the reef-scape. However, whether this coherence manifests as increased resilience or increased fragility depends on the spatial scales of fisher movement and the magnitudes of disturbance. These results emphasize the potential importance of spatially-explicit fishing behavior for reef resilience, but also the complexity of the feedbacks involved.

Global agriculture and carbon trade-offs

PubMed Central

Johnson, Justin Andrew; Runge, Carlisle Ford; Senauer, Benjamin; Foley, Jonathan; Polasky, Stephen

2014-01-01

Feeding a growing and increasingly affluent world will require expanded agricultural production, which may require converting grasslands and forests into cropland. Such conversions can reduce carbon storage, habitat provision, and other ecosystem services, presenting difficult societal trade-offs. In this paper, we use spatially explicit data on agricultural productivity and carbon storage in a global analysis to find where agricultural extensification should occur to meet growing demand while minimizing carbon emissions from land use change. Selective extensification saves ∼6 billion metric tons of carbon compared with a business-as-usual approach, with a value of approximately $1 trillion (2012 US dollars) using recent estimates of the social cost of carbon. This type of spatially explicit geospatial analysis can be expanded to include other ecosystem services and other industries to analyze how to minimize conflicts between economic development and environmental sustainability. PMID:25114254

The Be-WetSpa-Pest modeling approach to simulate human and environmental exposure from pesticide application

NASA Astrophysics Data System (ADS)

Binder, Claudia; Garcia-Santos, Glenda; Andreoli, Romano; Diaz, Jaime; Feola, Giuseppe; Wittensoeldner, Moritz; Yang, Jing

2016-04-01

This study presents an integrative and spatially explicit modeling approach for analyzing human and environmental exposure from pesticide application of smallholders in the potato producing Andean region in Colombia. The modeling approach fulfills the following criteria: (i) it includes environmental and human compartments; (ii) it contains a behavioral decision-making model for estimating the effect of policies on pesticide flows to humans and the environment; (iii) it is spatially explicit; and (iv) it is modular and easily expandable to include additional modules, crops or technologies. The model was calibrated and validated for the Vereda La Hoya and was used to explore the effect of different policy measures in the region. The model has moderate data requirements and can be adapted relatively easy to other regions in developing countries with similar conditions.

Global agriculture and carbon trade-offs.

PubMed

Johnson, Justin Andrew; Runge, Carlisle Ford; Senauer, Benjamin; Foley, Jonathan; Polasky, Stephen

2014-08-26

Feeding a growing and increasingly affluent world will require expanded agricultural production, which may require converting grasslands and forests into cropland. Such conversions can reduce carbon storage, habitat provision, and other ecosystem services, presenting difficult societal trade-offs. In this paper, we use spatially explicit data on agricultural productivity and carbon storage in a global analysis to find where agricultural extensification should occur to meet growing demand while minimizing carbon emissions from land use change. Selective extensification saves ∼ 6 billion metric tons of carbon compared with a business-as-usual approach, with a value of approximately $1 trillion (2012 US dollars) using recent estimates of the social cost of carbon. This type of spatially explicit geospatial analysis can be expanded to include other ecosystem services and other industries to analyze how to minimize conflicts between economic development and environmental sustainability.

An Electrophysiological Signature of Unconscious Recognition Memory

PubMed Central

Voss, Joel L.; Paller, Ken A.

2009-01-01

Contradicting the common assumption that accurate recognition reflects explicit-memory processing, we describe evidence for recognition lacking two hallmark explicit-memory features: awareness of memory retrieval and facilitation by attentive encoding. Kaleidoscope images were encoded in conjunction with an attentional diversion and subsequently recognized more accurately than those encoded without diversion. Confidence in recognition was superior following attentive encoding, though recognition was remarkably accurate when people claimed to be unaware of memory retrieval. This “implicit recognition” was associated with frontal-occipital negative brain potentials at 200-400 ms post-stimulus-onset, which were spatially and temporally distinct from positive brain potentials corresponding to explicit recollection and familiarity. This dissociation between behavioral and electrophysiological characteristics of “implicit recognition” versus explicit recognition indicates that a neurocognitive mechanism with properties similar to those that produce implicit memory can be operative in standard recognition tests. People can accurately discriminate repeat stimuli from new stimuli without necessarily knowing it. PMID:19198606

Phenomapping of rangelands in South Africa using time series of RapidEye data

NASA Astrophysics Data System (ADS)

Parplies, André; Dubovyk, Olena; Tewes, Andreas; Mund, Jan-Peter; Schellberg, Jürgen

2016-12-01

Phenomapping is an approach which allows the derivation of spatial patterns of vegetation phenology and rangeland productivity based on time series of vegetation indices. In our study, we propose a new spatial mapping approach which combines phenometrics derived from high resolution (HR) satellite time series with spatial logistic regression modeling to discriminate land management systems in rangelands. From the RapidEye time series for selected rangelands in South Africa, we calculated bi-weekly noise reduced Normalized Difference Vegetation Index (NDVI) images. For the growing season of 2011⿿2012, we further derived principal phenology metrics such as start, end and length of growing season and related phenological variables such as amplitude, left derivative and small integral of the NDVI curve. We then mapped these phenometrics across two different tenure systems, communal and commercial, at the very detailed spatial resolution of 5 m. The result of a binary logistic regression (BLR) has shown that the amplitude and the left derivative of the NDVI curve were statistically significant. These indicators are useful to discriminate commercial from communal rangeland systems. We conclude that phenomapping combined with spatial modeling is a powerful tool that allows efficient aggregation of phenology and productivity metrics for spatially explicit analysis of the relationships of crop phenology with site conditions and management. This approach has particular potential for disaggregated and patchy environments such as in farming systems in semi-arid South Africa, where phenology varies considerably among and within years. Further, we see a strong perspective for phenomapping to support spatially explicit modelling of vegetation.

Sub-cellular mRNA localization modulates the regulation of gene expression by small RNAs in bacteria

NASA Astrophysics Data System (ADS)

Teimouri, Hamid; Korkmazhan, Elgin; Stavans, Joel; Levine, Erel

2017-10-01

Small non-coding RNAs can exert significant regulatory activity on gene expression in bacteria. In recent years, substantial progress has been made in understanding bacterial gene expression by sRNAs. However, recent findings that demonstrate that families of mRNAs show non-trivial sub-cellular distributions raise the question of how localization may affect the regulatory activity of sRNAs. Here we address this question within a simple mathematical model. We show that the non-uniform spatial distributions of mRNA can alter the threshold-linear response that characterizes sRNAs that act stoichiometrically, and modulate the hierarchy among targets co-regulated by the same sRNA. We also identify conditions where the sub-cellular organization of cofactors in the sRNA pathway can induce spatial heterogeneity on sRNA targets. Our results suggest that under certain conditions, interpretation and modeling of natural and synthetic gene regulatory circuits need to take into account the spatial organization of the transcripts of participating genes.

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.

Spatial part-set cuing facilitation.

PubMed

Kelley, Matthew R; Parasiuk, Yuri; Salgado-Benz, Jennifer; Crocco, Megan

2016-07-01

Cole, Reysen, and Kelley [2013. Part-set cuing facilitation for spatial information. Journal of Experimental Psychology: Learning, Memory, & Cognition, 39, 1615-1620] reported robust part-set cuing facilitation for spatial information using snap circuits (a colour-coded electronics kit designed for children to create rudimentary circuit boards). In contrast, Drinkwater, Dagnall, and Parker [2006. Effects of part-set cuing on experienced and novice chess players' reconstruction of a typical chess midgame position. Perceptual and Motor Skills, 102(3), 645-653] and Watkins, Schwartz, and Lane [1984. Does part-set cuing test for memory organization? Evidence from reconstructions of chess positions. Canadian Journal of Psychology/Revue Canadienne de Psychologie, 38(3), 498-503] showed no influence of part-set cuing for spatial information when using chess boards. One key difference between the two procedures was that the snap circuit stimuli were explicitly connected to one another, whereas chess pieces were not. Two experiments examined the effects of connection type (connected vs. unconnected) and cue type (cued vs. uncued) on memory for spatial information. Using chess boards (Experiment 1) and snap circuits (Experiment 2), part-set cuing facilitation only occurred when the stimuli were explicitly connected; there was no influence of cuing with unconnected stimuli. These results are potentially consistent with the retrieval strategy disruption hypothesis, as well as the two- and three-mechanism accounts of part-set cuing.

Hierarchical spatial models for predicting pygmy rabbit distribution and relative abundance

USGS Publications Warehouse

Wilson, T.L.; Odei, J.B.; Hooten, M.B.; Edwards, T.C.

2010-01-01

Conservationists routinely use species distribution models to plan conservation, restoration and development actions, while ecologists use them to infer process from pattern. These models tend to work well for common or easily observable species, but are of limited utility for rare and cryptic species. This may be because honest accounting of known observation bias and spatial autocorrelation are rarely included, thereby limiting statistical inference of resulting distribution maps. We specified and implemented a spatially explicit Bayesian hierarchical model for a cryptic mammal species (pygmy rabbit Brachylagus idahoensis). Our approach used two levels of indirect sign that are naturally hierarchical (burrows and faecal pellets) to build a model that allows for inference on regression coefficients as well as spatially explicit model parameters. We also produced maps of rabbit distribution (occupied burrows) and relative abundance (number of burrows expected to be occupied by pygmy rabbits). The model demonstrated statistically rigorous spatial prediction by including spatial autocorrelation and measurement uncertainty. We demonstrated flexibility of our modelling framework by depicting probabilistic distribution predictions using different assumptions of pygmy rabbit habitat requirements. Spatial representations of the variance of posterior predictive distributions were obtained to evaluate heterogeneity in model fit across the spatial domain. Leave-one-out cross-validation was conducted to evaluate the overall model fit. Synthesis and applications. Our method draws on the strengths of previous work, thereby bridging and extending two active areas of ecological research: species distribution models and multi-state occupancy modelling. Our framework can be extended to encompass both larger extents and other species for which direct estimation of abundance is difficult. ?? 2010 The Authors. Journal compilation ?? 2010 British Ecological Society.

A Quantitative Three-Dimensional Image Analysis Tool for Maximal Acquisition of Spatial Heterogeneity Data.

PubMed

Allenby, Mark C; Misener, Ruth; Panoskaltsis, Nicki; Mantalaris, Athanasios

2017-02-01

Three-dimensional (3D) imaging techniques provide spatial insight into environmental and cellular interactions and are implemented in various fields, including tissue engineering, but have been restricted by limited quantification tools that misrepresent or underutilize the cellular phenomena captured. This study develops image postprocessing algorithms pairing complex Euclidean metrics with Monte Carlo simulations to quantitatively assess cell and microenvironment spatial distributions while utilizing, for the first time, the entire 3D image captured. Although current methods only analyze a central fraction of presented confocal microscopy images, the proposed algorithms can utilize 210% more cells to calculate 3D spatial distributions that can span a 23-fold longer distance. These algorithms seek to leverage the high sample cost of 3D tissue imaging techniques by extracting maximal quantitative data throughout the captured image.

Reconstruction of explicit structural properties at the nanoscale via spectroscopic microscopy

NASA Astrophysics Data System (ADS)

Cherkezyan, Lusik; Zhang, Di; Subramanian, Hariharan; Taflove, Allen; Backman, Vadim

2016-02-01

The spectrum registered by a reflected-light bright-field spectroscopic microscope (SM) can quantify the microscopically indiscernible, deeply subdiffractional length scales within samples such as biological cells and tissues. Nevertheless, quantification of biological specimens via any optical measures most often reveals ambiguous information about the specific structural properties within the studied samples. Thus, optical quantification remains nonintuitive to users from the diverse fields of technique application. In this work, we demonstrate that the SM signal can be analyzed to reconstruct explicit physical measures of internal structure within label-free, weakly scattering samples: characteristic length scale and the amplitude of spatial refractive-index (RI) fluctuations. We present and validate the reconstruction algorithm via finite-difference time-domain solutions of Maxwell's equations on an example of exponential spatial correlation of RI. We apply the validated algorithm to experimentally measure structural properties within isolated cells from two genetic variants of HT29 colon cancer cell line as well as within a prostate tissue biopsy section. The presented methodology can lead to the development of novel biophotonics techniques that create two-dimensional maps of explicit structural properties within biomaterials: the characteristic size of macromolecular complexes and the variance of local mass density.

Modeling the Land Use/Cover Change in an Arid Region Oasis City Constrained by Water Resource and Environmental Policy Change using Cellular Automata Model

NASA Astrophysics Data System (ADS)

Hu, X.; Li, X.; Lu, L.

2017-12-01

Land use/cover change (LUCC) is an important subject in the research of global environmental change and sustainable development, while spatial simulation on land use/cover change is one of the key content of LUCC and is also difficult due to the complexity of the system. The cellular automata (CA) model had an irreplaceable role in simulating of land use/cover change process due to the powerful spatial computing power. However, the majority of current CA land use/cover models were binary-state model that could not provide more general information about the overall spatial pattern of land use/cover change. Here, a multi-state logistic-regression-based Markov cellular automata (MLRMCA) model and a multi-state artificial-neural-network-based Markov cellular automata (MANNMCA) model were developed and were used to simulate complex land use/cover evolutionary process in an arid region oasis city constrained by water resource and environmental policy change, the Zhangye city during the period of 1990-2010. The results indicated that the MANNMCA model was superior to MLRMCA model in simulated accuracy. These indicated that by combining the artificial neural network with CA could more effectively capture the complex relationships between the land use/cover change and a set of spatial variables. Although the MLRMCA model were also some advantages, the MANNMCA model was more appropriate for simulating complex land use/cover dynamics. The two proposed models were effective and reliable, and could reflect the spatial evolution of regional land use/cover changes. These have also potential implications for the impact assessment of water resources, ecological restoration, and the sustainable urban development in arid areas.

Integrating GIS, cellular automata, and genetic algorithm in urban spatial optimization: a case study of Lanzhou

NASA Astrophysics Data System (ADS)

Xu, Xibao; Zhang, Jianming; Zhou, Xiaojian

2006-10-01

This paper presents a model integrating GIS, cellular automata (CA) and genetic algorithm (GA) in urban spatial optimization. The model involves three objectives of the maximization of land-use efficiency, the maximization of urban spatial harmony and appropriate proportion of each land-use type. CA submodel is designed with standard Moore neighbor and three transition rules to maximize the land-use efficiency and urban spatial harmony, according to the land-use suitability and spatial harmony index. GA submodel is designed with four constraints and seven steps for the maximization of urban spatial harmony and appropriate proportion of each land-use type, including encoding, initializing, calculating fitness, selection, crossover, mutation and elitism. GIS is used to prepare for the input data sets for the model and perform spatial analysis on the results, while CA and GA are integrated to optimize urban spatial structure, programmed with Matlab 7 and coupled with GIS loosely. Lanzhou, a typical valley-basin city with fast urban development, is chosen as the case study. At the end, a detail analysis and evaluation of the spatial optimization with the model are made, and it proves to be a powerful tool in optimizing urban spatial structure and make supplement for urban planning and policy-makers.

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.

The effect of area size and predation on the time to extinction of prairie vole populations. simulation studies via SERDYCA: a Spatially-Explicit Individual-Based Model of Rodent Dynamics

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

Kostova, T; Carlsen, T

2003-11-21

We present a spatially-explicit individual-based computational model of rodent dynamics, customized for the prairie vole species, M. Ochrogaster. The model is based on trophic relationships and represents important features such as territorial competition, mating behavior, density-dependent predation and dispersal out of the modeled spatial region. Vegetation growth and vole fecundity are dependent on climatic components. The results of simulations show that the model correctly predicts the overall temporal dynamics of the population density. Time-series analysis shows a very good match between the periods corresponding to the peak population density frequencies predicted by the model and the ones reported in themore » literature. The model is used to study the relation between persistence, landscape area and predation. We introduce the notions of average time to extinction (ATE) and persistence frequency to quantify persistence. While the ATE decreases with decrease of area, it is a bell-shaped function of the predation level: increasing for 'small' and decreasing for 'large' predation levels.« less

Spatial separation and entanglement of identical particles

NASA Astrophysics Data System (ADS)

Cunden, Fabio Deelan; di Martino, Sara; Facchi, Paolo; Florio, Giuseppe

2014-04-01

We reconsider the effect of indistinguishability on the reduced density operator of the internal degrees of freedom (tracing out the spatial degrees of freedom) for a quantum system composed of identical particles located in different spatial regions. We explicitly show that if the spin measurements are performed in disjoint spatial regions then there are no constraints on the structure of the reduced state of the system. This implies that the statistics of identical particles has no role from the point of view of separability and entanglement when the measurements are spatially separated. We extend the treatment to the case of n particles and show the connection with some recent criteria for separability based on subalgebras of observables.

Benefit transfer and spatial heterogeneity of preferences for water quality improvements.

PubMed

Martin-Ortega, J; Brouwer, R; Ojea, E; Berbel, J

2012-09-15

The improvement in the water quality resulting from the implementation of the EU Water Framework Directive is expected to generate substantial non-market benefits. A wide spread estimation of these benefits across Europe will require the application of benefit transfer. We use a spatially explicit valuation design to account for the spatial heterogeneity of preferences to help generate lower transfer errors. A map-based choice experiment is applied in the Guadalquivir River Basin (Spain), accounting simultaneously for the spatial distribution of water quality improvements and beneficiaries. Our results show that accounting for the spatial heterogeneity of preferences generally produces lower transfer errors. Copyright © 2012 Elsevier Ltd. All rights reserved.

Using titanium complexes to defeat cancer: the view from the shoulders of titans.

PubMed

Cini, Melchior; Bradshaw, Tracey D; Woodward, Simon

2017-02-20

When the first titanium complex with anticancer activity was identified in the 1970s, it was attractive, based on the presence of the dichloride unit in TiCl 2 Cp 2 (Cp = η-C 5 H 5 ) 2 , to assume its mode of biological action was closely aligned with cisplatin [cis-PtCl 2 (NH 3 ) 2 ]. Over the intervening 40 years however a far more complicated picture has arisen indicating multiple cellular mechanisms of cellular action can be triggered by titanium anti-cancer agents. This tutorial review aims to unpick the historical data and provide new researchers, without an explicit cancer biology background, a contemporary interpretation of both older and newer literature and to review the best techniques for attaining the identities of the biologically active titanium species and how these interact with the cancer cellular machinery.

Total Risk Integrated Methodology (TRIM) - TRIM.FaTE

EPA Pesticide Factsheets

TRIM.FaTE is a spatially explicit, compartmental mass balance model that describes the movement and transformation of pollutants over time, through a user-defined, bounded system that includes both biotic and abiotic compartments.

Tempo-spatially resolved cellular dynamics of human immunodeficiency virus transacting activator of transcription (Tat) peptide-modified nanocargos in living cells

NASA Astrophysics Data System (ADS)

Wei, Lin; Yang, Qiaoyu; Xiao, Lehui

2014-08-01

Understanding the cellular uptake mechanism and intracellular fate of nanocarriers in living cells is of great importance for the rational design of efficient drug delivery cargos as well as the development of robust biomedical diagnostic probes. In present study, with a dual wavelength view darkfield microscope (DWVD), the tempo-spatially resolved dynamics of Tat peptide-functionalized gold nanoparticles (TGNPs, with size similar to viruses) in living HeLa cells were extensively explored. It was found that energy-dependent endocytosis (both clathrin- and caveolae-mediated processes were involved) was the prevailing pathway for the cellular uptake of TGNPs. The time-correlated dynamic spatial distribution information revealed that TGNPs could not actively target the cell nuclei, which is contrary to previous observations based on fixed cell results. More importantly, the inheritance of TGNPs to the daughter cells through mitosis was found to be the major route to metabolize TGNPs by HeLa cells. These understandings on the cellular uptake mechanism and intracellular fate of nanocargos in living cells would provide deep insight on how to improve and controllably manipulate their translocation efficiency for targeted drug delivery.Understanding the cellular uptake mechanism and intracellular fate of nanocarriers in living cells is of great importance for the rational design of efficient drug delivery cargos as well as the development of robust biomedical diagnostic probes. In present study, with a dual wavelength view darkfield microscope (DWVD), the tempo-spatially resolved dynamics of Tat peptide-functionalized gold nanoparticles (TGNPs, with size similar to viruses) in living HeLa cells were extensively explored. It was found that energy-dependent endocytosis (both clathrin- and caveolae-mediated processes were involved) was the prevailing pathway for the cellular uptake of TGNPs. The time-correlated dynamic spatial distribution information revealed that TGNPs could not actively target the cell nuclei, which is contrary to previous observations based on fixed cell results. More importantly, the inheritance of TGNPs to the daughter cells through mitosis was found to be the major route to metabolize TGNPs by HeLa cells. These understandings on the cellular uptake mechanism and intracellular fate of nanocargos in living cells would provide deep insight on how to improve and controllably manipulate their translocation efficiency for targeted drug delivery. Electronic supplementary information (ESI) available: Experimental section and additional supporting results as noted in the text. See DOI: 10.1039/c4nr02732a

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.

Quantifying the impact of human mobility on malaria

PubMed Central

Wesolowski, Amy; Eagle, Nathan; Tatem, Andrew J.; Smith, David L.; Noor, Abdisalan M.; Snow, Robert W.; Buckee, Caroline O.

2013-01-01

Human movements contribute to the transmission of malaria on spatial scales that exceed the limits of mosquito dispersal. Identifying the sources and sinks of imported infections due to human travel and locating high-risk sites of parasite importation could greatly improve malaria control programs. Here we use spatially explicit mobile phone data and malaria prevalence information from Kenya to identify the dynamics of human carriers that drive parasite importation between regions. Our analysis identifies specific importation routes that contribute to malaria epidemiology on regional spatial scales. PMID:23066082

Mapping vegetation and fuels for fire management on the Gila National Forest Complex, New Mexico

Treesearch

Robert E. Keane; Scott A. Mincemoyer; Kirsten M. Schmidt; Donald G. Long; Janice L. Garner

2000-01-01

(Please note: This PDF is part of a CD-ROM package only and was not printed on paper.) Fuels and vegetation spatial data layers required by the spatially explicit fire growth model FARSITE were developed for all lands in and around the Gila National Forest in New Mexico. Satellite imagery, terrain modeling, and biophysical simulation were used to create the three...

Accumulation of Experience in a Vast Number of Cases: Enactivism as a Fit Framework for the Study of Spatial Reasoning in Mathematics Education

ERIC Educational Resources Information Center

Khan, Steven; Francis, Krista; Davis, Brent

2015-01-01

As we witness a push toward studying spatial reasoning as a principal component of mathematical competency and instruction in the twenty first century, we argue that enactivism, with its strong and explicit foci on the coupling of organism and environment, action as cognition, and sensory motor coordination provides an inclusive, expansive, apt,…

Reducing fertilizer-nitrogen losses from rowcrop landscapes: Insights and implications from a spatially explicit watershed model

USGS Publications Warehouse

McLellan, Eileen; Schilling, Keith; Robertson, Dale M.

2015-01-01

We present conceptual and quantitative models that predict changes in fertilizer-derived nitrogen delivery from rowcrop landscapes caused by agricultural conservation efforts implemented to reduce nutrient inputs and transport and increase nutrient retention in the landscape. To evaluate the relative importance of changes in the sources, transport, and sinks of fertilizer-derived nitrogen across a region, we use the spatially explicit SPAtially Referenced Regression On Watershed attributes watershed model to map the distribution, at the small watershed scale within the Upper Mississippi-Ohio River Basin (UMORB), of: (1) fertilizer inputs; (2) nutrient attenuation during delivery of those inputs to the UMORB outlet; and (3) nitrogen export from the UMORB outlet. Comparing these spatial distributions suggests that the amount of fertilizer input and degree of nutrient attenuation are both important in determining the extent of nitrogen export. From a management perspective, this means that agricultural conservation efforts to reduce nitrogen export would benefit by: (1) expanding their focus to include activities that restore and enhance nutrient processing in these highly altered landscapes; and (2) targeting specific types of best management practices to watersheds where they will be most valuable. Doing so successfully may result in a shift in current approaches to conservation planning, outreach, and funding.

Evaluating effects of Everglades restoration on American crocodile populations in south Florida using a spatially-explicit, stage-based population model

USGS Publications Warehouse

Green, Timothy W.; Slone, Daniel H.; Swain, Eric D.; Cherkiss, Michael S.; Lohmann, Melinda; Mazzotti, Frank J.; Rice, Kenneth G.

2014-01-01

The distribution and abundance of the American crocodile (Crocodylus acutus) in the Florida Everglades is dependent on the timing, amount, and location of freshwater flow. One of the goals of the Comprehensive Everglades Restoration Plan (CERP) is to restore historic freshwater flows to American crocodile habitat throughout the Everglades. To predict the impacts on the crocodile population from planned restoration activities, we created a stage-based spatially explicit crocodile population model that incorporated regional hydrology models and American crocodile research and monitoring data. Growth and survival were influenced by salinity, water depth, and density-dependent interactions. A stage-structured spatial model was used with discrete spatial convolution to direct crocodiles toward attractive sources where conditions were favorable. The model predicted that CERP would have both positive and negative impacts on American crocodile growth, survival, and distribution. Overall, crocodile populations across south Florida were predicted to decrease approximately 3 % with the implementation of CERP compared to future conditions without restoration, but local increases up to 30 % occurred in the Joe Bay area near Taylor Slough, and local decreases up to 30 % occurred in the vicinity of Buttonwood Canal due to changes in salinity and freshwater flows.

FAST TRACK COMMUNICATION Solving the ultradiscrete KdV equation

NASA Astrophysics Data System (ADS)

Willox, Ralph; Nakata, Yoichi; Satsuma, Junkichi; Ramani, Alfred; Grammaticos, Basile

2010-12-01

We show that a generalized cellular automaton, exhibiting solitonic interactions, can be explicitly solved by means of techniques first introduced in the context of the scattering problem for the KdV equation. We apply this method to calculate the phase-shifts caused by interactions between the solitonic and non-solitonic parts into which arbitrary initial states separate in time.

Multiscale modeling of porous ceramics using movable cellular automaton method

NASA Astrophysics Data System (ADS)

Smolin, Alexey Yu.; Smolin, Igor Yu.; Smolina, Irina Yu.

2017-10-01

The paper presents a multiscale model for porous ceramics based on movable cellular automaton method, which is a particle method in novel computational mechanics of solid. The initial scale of the proposed approach corresponds to the characteristic size of the smallest pores in the ceramics. At this scale, we model uniaxial compression of several representative samples with an explicit account of pores of the same size but with the unique position in space. As a result, we get the average values of Young's modulus and strength, as well as the parameters of the Weibull distribution of these properties at the current scale level. These data allow us to describe the material behavior at the next scale level were only the larger pores are considered explicitly, while the influence of small pores is included via effective properties determined earliar. If the pore size distribution function of the material has N maxima we need to perform computations for N-1 levels in order to get the properties step by step from the lowest scale up to the macroscale. The proposed approach was applied to modeling zirconia ceramics with bimodal pore size distribution. The obtained results show correct behavior of the model sample at the macroscale.

Heterogeneity of renal cortical oxygenation: seeing is believing.

PubMed

Evans, Roger G; Ow, Connie P C

2018-06-01

The limited spatial and temporal resolution of available methods for quantifying renal tissue oxygen tension is a major impediment to identification of the roles of renal hypoxia in kidney diseases. Intravital phosphorescence lifetime imaging microscopy allows cellular oxygen tension in the renal cortex of live animals to be resolved to the level of individual tubular cross-sections. This paves the way for future investigations of the spatial relationships between cellular hypoxia and pathophysiological events in kidney disease. Copyright © 2018 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.

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.

Supporting the operational use of process based hydrological models and NASA Earth Observations for use in land management and post-fire remediation through a Rapid Response Erosion Database (RRED).

NASA Astrophysics Data System (ADS)

Miller, M. E.; Elliot, W.; Billmire, M.; Robichaud, P. R.; Banach, D. M.

2017-12-01

We have built a Rapid Response Erosion Database (RRED, http://rred.mtri.org/rred/) for the continental United States to allow land managers to access properly formatted spatial model inputs for the Water Erosion Prediction Project (WEPP). Spatially-explicit process-based models like WEPP require spatial inputs that include digital elevation models (DEMs), soil, climate and land cover. The online database delivers either a 10m or 30m USGS DEM, land cover derived from the Landfire project, and soil data derived from SSURGO and STATSGO datasets. The spatial layers are projected into UTM coordinates and pre-registered for modeling. WEPP soil parameter files are also created along with linkage files to match both spatial land cover and soils data with the appropriate WEPP parameter files. Our goal is to make process-based models more accessible by preparing spatial inputs ahead of time allowing modelers to focus on addressing scenarios of concern. The database provides comprehensive support for post-fire hydrological modeling by allowing users to upload spatial soil burn severity maps, and within moments returns spatial model inputs. Rapid response is critical following natural disasters. After moderate and high severity wildfires, flooding, erosion, and debris flows are a major threat to life, property and municipal water supplies. Mitigation measures must be rapidly implemented if they are to be effective, but they are expensive and cannot be applied everywhere. Fire, runoff, and erosion risks also are highly heterogeneous in space, creating an urgent need for rapid, spatially-explicit assessment. The database has been used to help assess and plan remediation on over a dozen wildfires in the Western US. Future plans include expanding spatial coverage, improving model input data and supporting additional models. Our goal is to facilitate the use of the best possible datasets and models to support the conservation of soil and water.

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

PubMed

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

2014-12-05

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

Towards more accurate isoscapes encouraging results from wine, water and marijuana data/model and model/model comparisons.

NASA Astrophysics Data System (ADS)

West, J. B.; Ehleringer, J. R.; Cerling, T.

2006-12-01

Understanding how the biosphere responds to change it at the heart of biogeochemistry, ecology, and other Earth sciences. The dramatic increase in human population and technological capacity over the past 200 years or so has resulted in numerous, simultaneous changes to biosphere structure and function. This, then, has lead to increased urgency in the scientific community to try to understand how systems have already responded to these changes, and how they might do so in the future. Since all biospheric processes exhibit some patchiness or patterns over space, as well as time, we believe that understanding the dynamic interactions between natural systems and human technological manipulations can be improved if these systems are studied in an explicitly spatial context. We present here results of some of our efforts to model the spatial variation in the stable isotope ratios (δ2H and δ18O) of plants over large spatial extents, and how these spatial model predictions compare to spatially explicit data. Stable isotopes trace and record ecological processes and as such, if modeled correctly over Earth's surface allow us insights into changes in biosphere states and processes across spatial scales. The data-model comparisons show good agreement, in spite of the remaining uncertainties (e.g., plant source water isotopic composition). For example, inter-annual changes in climate are recorded in wine stable isotope ratios. Also, a much simpler model of leaf water enrichment driven with spatially continuous global rasters of precipitation and climate normals largely agrees with complex GCM modeling that includes leaf water δ18O. Our results suggest that modeling plant stable isotope ratios across large spatial extents may be done with reasonable accuracy, including over time. These spatial maps, or isoscapes, can now be utilized to help understand spatially distributed data, as well as to help guide future studies designed to understand ecological change across landscapes.

Spatially explicit modeling of greater sage-grouse (Centrocercus urophasianus) habitat in Nevada and northeastern California: a decision-support tool for management

USGS Publications Warehouse

Coates, Peter S.; Casazza, Michael L.; Brussee, Brianne E.; Ricca, Mark A.; Gustafson, K. Benjamin; Overton, Cory T.; Sanchez-Chopitea, Erika; Kroger, Travis; Mauch, Kimberly; Niell, Lara; Howe, Kristy; Gardner, Scott; Espinosa, Shawn; Delehanty, David J.

2014-01-01

Greater sage-grouse (Centrocercus urophasianus, hereafter referred to as “sage-grouse”) populations are declining throughout the sagebrush (Artemisia spp.) ecosystem, including millions of acres of potential habitat across the West. Habitat maps derived from empirical data are needed given impending listing decisions that will affect both sage-grouse population dynamics and human land-use restrictions. This report presents the process for developing spatially explicit maps describing relative habitat suitability for sage-grouse in Nevada and northeastern California. Maps depicting habitat suitability indices (HSI) values were generated based on model-averaged resource selection functions informed by more than 31,000 independent telemetry locations from more than 1,500 radio-marked sage-grouse across 12 project areas in Nevada and northeastern California collected during a 15-year period (1998–2013). Modeled habitat covariates included land cover composition, water resources, habitat configuration, elevation, and topography, each at multiple spatial scales that were relevant to empirically observed sage-grouse movement patterns. We then present an example of how the HSI can be delineated into categories. Specifically, we demonstrate that the deviation from the mean can be used to classify habitat suitability into three categories of habitat quality (high, moderate, and low) and one non-habitat category. The classification resulted in an agreement of 93–97 percent for habitat versus non-habitat across a suite of independent validation datasets. Lastly, we provide an example of how space use models can be integrated with habitat models to help inform conservation planning. In this example, we combined probabilistic breeding density with a non-linear probability of occurrence relative to distance to nearest lek (traditional breeding ground) using count data to calculate a composite space use index (SUI). The SUI was then classified into two categories of use (high and low-to-no) and intersected with the HSI categories to create potential management prioritization scenarios based oninformation about sage-grouse occupancy coupled with habitat suitability. This provided an example of a conservation planning application that uses the intersection of the spatially-explicit HSI and empirically-based SUI to identify potential spatially explicit strategies for sage-grouse management. Importantly, the reported categories for the HSI and SUI can be reclassified relatively easily to employ alternative conservation thresholds that may be identified through decision-making processes with stake-holders, managers, and biologists. Moreover, the HSI/SUI interface map can be updated readily as new data become available.

Spatial Dynamics of Multilayer Cellular Neural Networks

NASA Astrophysics Data System (ADS)

Wu, Shi-Liang; Hsu, Cheng-Hsiung

2018-02-01

The purpose of this work is to study the spatial dynamics of one-dimensional multilayer cellular neural networks. We first establish the existence of rightward and leftward spreading speeds of the model. Then we show that the spreading speeds coincide with the minimum wave speeds of the traveling wave fronts in the right and left directions. Moreover, we obtain the asymptotic behavior of the traveling wave fronts when the wave speeds are positive and greater than the spreading speeds. According to the asymptotic behavior and using various kinds of comparison theorems, some front-like entire solutions are constructed by combining the rightward and leftward traveling wave fronts with different speeds and a spatially homogeneous solution of the model. Finally, various qualitative features of such entire solutions are investigated.

Modeling wildlife populations with HexSim

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 including population viability analysis for on...

Contingency blindness: location-identity binding mismatches obscure awareness of spatial contingencies and produce profound interference in visual working memory.

PubMed

Fiacconi, Chris M; Milliken, Bruce

2012-08-01

The purpose of the present study was to highlight the role of location-identity binding mismatches in obscuring explicit awareness of a strong contingency. In a spatial-priming procedure, we introduced a high likelihood of location-repeat trials. Experiments 1, 2a, and 2b demonstrated that participants' explicit awareness of this contingency was heavily influenced by the local match in location-identity bindings. In Experiment 3, we sought to determine why location-identity binding mismatches produce such low levels of contingency awareness. Our results suggest that binding mismatches can interfere substantially with visual-memory performance. We attribute the low levels of contingency awareness to participants' inability to remember the critical location-identity binding in the prime on a trial-to-trial basis. These results imply a close interplay between object files and visual working memory.

The spatial representation of power in children.

PubMed

Lu, Lifeng; Schubert, Thomas W; Zhu, Lei

2017-11-01

Previous evidence demonstrates that power is mentally represented as vertical space by adults. However, little is known about how power is mentally represented in children. The current research examines such representations. The influence of vertical information (motor cues) was tested in both an explicit power evaluation task (judge whether labels refer to powerless or powerful groups) and an incidental task (judge whether labels refer to people or animals). The results showed that when power was explicitly evaluated, vertical motor responses interfered with responding in children and adults, i.e., they responded to words representing powerful groups faster with the up than the down cursor key (and vice versa for powerless groups). However, this interference effect disappeared in the incidental task in children. The findings suggest that children have developed a spatial representation of power before they have been taught power-space associations formally, but that they do not judge power spontaneously.

Global distribution and sources of dissolved inorganic nitrogen export to the coastal zone: Results from a spatially explicit, global model

NASA Astrophysics Data System (ADS)

Dumont, E.; Harrison, J. A.; Kroeze, C.; Bakker, E. J.; Seitzinger, S. P.

2005-12-01

Here we describe, test, and apply a spatially explicit, global model for predicting dissolved inorganic nitrogen (DIN) export by rivers to coastal waters (NEWS-DIN). NEWS-DIN was developed as part of an internally consistent suite of global nutrient export models. Modeled and measured DIN export values agree well (calibration R2 = 0.79), and NEWS-DIN is relatively free of bias. NEWS-DIN predicts: DIN yields ranging from 0.0004 to 5217 kg N km-2 yr-1 with the highest DIN yields occurring in Europe and South East Asia; global DIN export to coastal waters of 25 Tg N yr-1, with 16 Tg N yr-1 from anthropogenic sources; biological N2 fixation is the dominant source of exported DIN; and globally, and on every continent except Africa, N fertilizer is the largest anthropogenic source of DIN export to coastal waters.

From puddles to planet: modeling approaches to vector-borne diseases at varying resolution and scale.

PubMed

Eckhoff, Philip A; Bever, Caitlin A; Gerardin, Jaline; Wenger, Edward A; Smith, David L

2015-08-01

Since the original Ross-Macdonald formulations of vector-borne disease transmission, there has been a broad proliferation of mathematical models of vector-borne disease, but many of these models retain most to all of the simplifying assumptions of the original formulations. Recently, there has been a new expansion of mathematical frameworks that contain explicit representations of the vector life cycle including aquatic stages, multiple vector species, host heterogeneity in biting rate, realistic vector feeding behavior, and spatial heterogeneity. In particular, there are now multiple frameworks for spatially explicit dynamics with movements of vector, host, or both. These frameworks are flexible and powerful, but require additional data to take advantage of these features. For a given question posed, utilizing a range of models with varying complexity and assumptions can provide a deeper understanding of the answers derived from models. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

How effective are biodiversity conservation payments in Mexico?

PubMed

Costedoat, Sébastien; Corbera, Esteve; Ezzine-de-Blas, Driss; Honey-Rosés, Jordi; Baylis, Kathy; Castillo-Santiago, Miguel Angel

2015-01-01

We assess the additional forest cover protected by 13 rural communities located in the southern state of Chiapas, Mexico, as a result of the economic incentives received through the country's national program of payments for biodiversity conservation. We use spatially explicit data at the intra-community level to define a credible counterfactual of conservation outcomes. We use covariate-matching specifications associated with spatially explicit variables and difference-in-difference estimators to determine the treatment effect. We estimate that the additional conservation represents between 12 and 14.7 percent of forest area enrolled in the program in comparison to control areas. Despite this high degree of additionality, we also observe lack of compliance in some plots participating in the PES program. This lack of compliance casts doubt on the ability of payments alone to guarantee long-term additionality in context of high deforestation rates, even with an augmented program budget or extension of participation to communities not yet enrolled.

Ecosystem accounts define explicit and spatial trade-offs for managing natural resources.

PubMed

Keith, Heather; Vardon, Michael; Stein, John A; Stein, Janet L; Lindenmayer, David

2017-11-01

Decisions about natural resource management are frequently complex and vexed, often leading to public policy compromises. Discord between environmental and economic metrics creates problems in assessing trade-offs between different current or potential resource uses. Ecosystem accounts, which quantify ecosystems and their benefits for human well-being consistent with national economic accounts, provide exciting opportunities to contribute significantly to the policy process. We advanced the application of ecosystem accounts in a regional case study by explicitly and spatially linking impacts of human and natural activities on ecosystem assets and services to their associated industries. This demonstrated contributions of ecosystems beyond the traditional national accounts. Our results revealed that native forests would provide greater benefits from their ecosystem services of carbon sequestration, water yield, habitat provisioning and recreational amenity if harvesting for timber production ceased, thus allowing forests to continue growing to older ages.

Cellular and multicellular form and function.

PubMed

Liu, Wendy F; Chen, Christopher S

2007-11-10

Engineering artificial tissue constructs requires the appropriate spatial arrangement of cells within scaffolds. The introduction of microengineering tools to the biological community has provided a valuable set of techniques to manipulate the cellular environment, and to examine how cell structure affects cellular function. Using micropatterning techniques, investigators have found that the geometric presentation of cell-matrix adhesions are important regulators of various cell behaviors including cell growth, proliferation, differentiation, polarity and migration. Furthermore, the presence of neighboring cells in multicellular aggregates has a significant impact on the proliferative and differentiated state of cells. Using microengineering tools, it will now be possible to manipulate the various environmental factors for practical applications such as engineering tissue constructs with greater control over the physical structure and spatial arrangement of cells within their surrounding microenvironment.

Conflict resolved: On the role of spatial attention in reading and color naming tasks.

PubMed

Robidoux, Serje; Besner, Derek

2015-12-01

The debate about whether or not visual word recognition requires spatial attention has been marked by a conflict: the results from different tasks yield different conclusions. Experiments in which the primary task is reading based show no evidence that unattended words are processed, whereas when the primary task is color identification, supposedly unattended words do affect processing. However, the color stimuli used to date does not appear to demand as much spatial attention as explicit word reading tasks. We first identify a color stimulus that requires as much spatial attention to identify as does a word. We then demonstrate that when spatial attention is appropriately captured, distractor words in unattended locations do not affect color identification. We conclude that there is no word identification without spatial attention.

Spatially explicit modeling in ecology: A review

USGS Publications Warehouse

DeAngelis, Donald L.; Yurek, Simeon

2017-01-01

The use of spatially explicit models (SEMs) in ecology has grown enormously in the past two decades. One major advancement has been that fine-scale details of landscapes, and of spatially dependent biological processes, such as dispersal and invasion, can now be simulated with great precision, due to improvements in computer technology. Many areas of modeling have shifted toward a focus on capturing these fine-scale details, to improve mechanistic understanding of ecosystems. However, spatially implicit models (SIMs) have played a dominant role in ecology, and arguments have been made that SIMs, which account for the effects of space without specifying spatial positions, have an advantage of being simpler and more broadly applicable, perhaps contributing more to understanding. We address this debate by comparing SEMs and SIMs in examples from the past few decades of modeling research. We argue that, although SIMs have been the dominant approach in the incorporation of space in theoretical ecology, SEMs have unique advantages for addressing pragmatic questions concerning species populations or communities in specific places, because local conditions, such as spatial heterogeneities, organism behaviors, and other contingencies, produce dynamics and patterns that usually cannot be incorporated into simpler SIMs. SEMs are also able to describe mechanisms at the local scale that can create amplifying positive feedbacks at that scale, creating emergent patterns at larger scales, and therefore are important to basic ecological theory. We review the use of SEMs at the level of populations, interacting populations, food webs, and ecosystems and argue that SEMs are not only essential in pragmatic issues, but must play a role in the understanding of causal relationships on landscapes.

Developing and testing a global-scale regression model to quantify mean annual streamflow

NASA Astrophysics Data System (ADS)

Barbarossa, Valerio; Huijbregts, Mark A. J.; Hendriks, A. Jan; Beusen, Arthur H. W.; Clavreul, Julie; King, Henry; Schipper, Aafke M.

2017-01-01

Quantifying mean annual flow of rivers (MAF) at ungauged sites is essential for assessments of global water supply, ecosystem integrity and water footprints. MAF can be quantified with spatially explicit process-based models, which might be overly time-consuming and data-intensive for this purpose, or with empirical regression models that predict MAF based on climate and catchment characteristics. Yet, regression models have mostly been developed at a regional scale and the extent to which they can be extrapolated to other regions is not known. In this study, we developed a global-scale regression model for MAF based on a dataset unprecedented in size, using observations of discharge and catchment characteristics from 1885 catchments worldwide, measuring between 2 and 106 km2. In addition, we compared the performance of the regression model with the predictive ability of the spatially explicit global hydrological model PCR-GLOBWB by comparing results from both models to independent measurements. We obtained a regression model explaining 89% of the variance in MAF based on catchment area and catchment averaged mean annual precipitation and air temperature, slope and elevation. The regression model performed better than PCR-GLOBWB for the prediction of MAF, as root-mean-square error (RMSE) values were lower (0.29-0.38 compared to 0.49-0.57) and the modified index of agreement (d) was higher (0.80-0.83 compared to 0.72-0.75). Our regression model can be applied globally to estimate MAF at any point of the river network, thus providing a feasible alternative to spatially explicit process-based global hydrological models.

Ecohydrologic role of solar radiation on landscape evolution

NASA Astrophysics Data System (ADS)

Yetemen, Omer; Istanbulluoglu, Erkan; Flores-Cervantes, J. Homero; Vivoni, Enrique R.; Bras, Rafael L.

2015-02-01

Solar radiation has a clear signature on the spatial organization of ecohydrologic fluxes, vegetation patterns and dynamics, and landscape morphology in semiarid ecosystems. Existing landscape evolution models (LEMs) do not explicitly consider spatially explicit solar radiation as model forcing. Here, we improve an existing LEM to represent coupled processes of energy, water, and sediment balance for semiarid fluvial catchments. To ground model predictions, a study site is selected in central New Mexico where hillslope aspect has a marked influence on vegetation patterns and landscape morphology. Model predictions are corroborated using limited field observations in central NM and other locations with similar conditions. We design a set of comparative LEM simulations to investigate the role of spatially explicit solar radiation on landscape ecohydro-geomorphic development under different uplift scenarios. Aspect-control and network-control are identified as the two main drivers of soil moisture and vegetation organization on the landscape. Landscape-scale and long-term implications of these short-term ecohdrologic patterns emerged in modeled landscapes. As north facing slopes (NFS) get steeper by continuing uplift they support erosion-resistant denser vegetation cover which leads to further slope steepening until erosion and uplift attains a dynamic equilibrium. Conversely, on south facing slopes (SFS), as slopes grow with uplift, increased solar radiation exposure with slope supports sparser biomass and shallower slopes. At the landscape scale, these differential erosion processes lead to asymmetric development of catchment forms, consistent with regional observations. Understanding of ecohydrogeomorphic evolution will improve to assess the impacts of past and future climates on landscape response and morphology.

Spatially explicit shallow landslide susceptibility mapping over large areas

USGS Publications Warehouse

Bellugi, Dino; Dietrich, William E.; Stock, Jonathan D.; McKean, Jim; Kazian, Brian; Hargrove, Paul

2011-01-01

Recent advances in downscaling climate model precipitation predictions now yield spatially explicit patterns of rainfall that could be used to estimate shallow landslide susceptibility over large areas. In California, the United States Geological Survey is exploring community emergency response to the possible effects of a very large simulated storm event and to do so it has generated downscaled precipitation maps for the storm. To predict the corresponding pattern of shallow landslide susceptibility across the state, we have used the model Shalstab (a coupled steady state runoff and infinite slope stability model) which susceptibility spatially explicit estimates of relative potential instability. Such slope stability models that include the effects of subsurface runoff on potentially destabilizing pore pressure evolution require water routing and hence the definition of upslope drainage area to each potential cell. To calculate drainage area efficiently over a large area we developed a parallel framework to scale-up Shalstab and specifically introduce a new efficient parallel drainage area algorithm which produces seamless results. The single seamless shallow landslide susceptibility map for all of California was accomplished in a short run time, and indicates that much larger areas can be efficiently modelled. As landslide maps generally over predict the extent of instability for any given storm. Local empirical data on the fraction of predicted unstable cells that failed for observed rainfall intensity can be used to specify the likely extent of hazard for a given storm. This suggests that campaigns to collect local precipitation data and detailed shallow landslide location maps after major storms could be used to calibrate models and improve their use in hazard assessment for individual storms.

Reconciling nature conservation and traditional farming practices: a spatially explicit framework to assess the extent of High Nature Value farmlands in the European countryside

PubMed Central

Lomba, Angela; Alves, Paulo; Jongman, Rob H G; McCracken, David I

2015-01-01

Agriculture constitutes a dominant land cover worldwide, and rural landscapes under extensive farming practices acknowledged due to high biodiversity levels. The High Nature Value farmland (HNVf) concept has been highlighted in the EU environmental and rural policies due to their inherent potential to help characterize and direct financial support to European landscapes where high nature and/or conservation value is dependent on the continuation of specific low-intensity farming systems. Assessing the extent of HNV farmland by necessity relies on the availability of both ecological and farming systems' data, and difficulties associated with making such assessments have been widely described across Europe. A spatially explicit framework of data collection, building out from local administrative units, has recently been suggested as a means of addressing such difficulties. This manuscript tests the relevance of the proposed approach, describes the spatially explicit framework in a case study area in northern Portugal, and discusses the potential of the approach to help better inform the implementation of conservation and rural development policies. Synthesis and applications: The potential of a novel approach (combining land use/cover, farming and environmental data) to provide more accurate and efficient mapping and monitoring of HNV farmlands is tested at the local level in northern Portugal. The approach is considered to constitute a step forward toward a more precise targeting of landscapes for agri-environment schemes, as it allowed a more accurate discrimination of areas within the case study landscape that have a higher value for nature conservation. PMID:25798221

Reconstructing satellite images to quantify spatially explicit land surface change caused by fires and succession: A demonstration in the Yukon River Basin of interior Alaska

USGS Publications Warehouse

Huang, Shengli; Jin, Suming; Dahal, Devendra; Chen, Xuexia; Young, Claudia; Liu, Heping; Liu, Shuguang

2013-01-01

Land surface change caused by fires and succession is confounded by many site-specific factors and requires further study. The objective of this study was to reveal the spatially explicit land surface change by minimizing the confounding factors of weather variability, seasonal offset, topography, land cover, and drainage. In a pilot study of the Yukon River Basin of interior Alaska, we retrieved Normalized Difference Vegetation Index (NDVI), albedo, and land surface temperature (LST) from a postfire Landsat image acquired on August 5th, 2004. With a Landsat reference image acquired on June 26th, 1986, we reconstructed NDVI, albedo, and LST of 1987–2004 fire scars for August 5th, 2004, assuming that these fires had not occurred. The difference between actual postfire and assuming-no-fire scenarios depicted the fires and succession impact. Our results demonstrated the following: (1) NDVI showed an immediate decrease after burning but gradually recovered to prefire levels in the following years, in which burn severity might play an important role during this process; (2) Albedo showed an immediate decrease after burning but then recovered and became higher than prefire levels; and (3) Most fires caused surface warming, but cooler surfaces did exist; time-since-fire affected the prefire and postfire LST difference but no absolute trend could be found. Our approach provided spatially explicit land surface change rather than average condition, enabling a better understanding of fires and succession impact on ecological consequences at the pixel level.

Future Forest Cover Change Scenarios with Implications for Landslide Risk: An Example from Buzau Subcarpathians, Romania

NASA Astrophysics Data System (ADS)

Malek, Žiga; Boerboom, Luc; Glade, Thomas

2015-11-01

This study focuses on future forest cover change in Buzau Subcarpathians, a landslide prone region in Romania. Past and current trends suggest that the area might expect a future increase in deforestation. We developed spatially explicit scenarios until 2040 to analyze the spatial pattern of future forest cover change and potential changes to landslide risk. First, we generated transition probability maps using the weights of evidence method, followed by a cellular automata allocation model. We performed expert interviews, to develop two future forest management scenarios. The Alternative scenario (ALT) was defined by 67 % more deforestation than the Business as Usual scenario (BAU). We integrated the simulated scenarios with a landslide susceptibility map. In both scenarios, most of deforestation was projected in areas where landslides are less likely to occur. Still, 483 (ALT) and 276 (BAU) ha of deforestation were projected on areas with a high-landslide occurrence likelihood. Thus, deforestation could lead to a local-scale increase in landslide risk, in particular near or adjacent to forestry roads. The parallel process of near 10 % forest expansion until 2040 was projected to occur mostly on areas with high-landslide susceptibility. On a regional scale, forest expansion could so result in improved slope stability. We modeled two additional scenarios with an implemented landslide risk policy, excluding high-risk zones. The reduction of deforestation on high-risk areas was achieved without a drastic decrease in the accessibility of the areas. Together with forest expansion, it could therefore be used as a risk reduction strategy.

Future Forest Cover Change Scenarios with Implications for Landslide Risk: An Example from Buzau Subcarpathians, Romania.

PubMed

Malek, Žiga; Boerboom, Luc; Glade, Thomas

2015-11-01

This study focuses on future forest cover change in Buzau Subcarpathians, a landslide prone region in Romania. Past and current trends suggest that the area might expect a future increase in deforestation. We developed spatially explicit scenarios until 2040 to analyze the spatial pattern of future forest cover change and potential changes to landslide risk. First, we generated transition probability maps using the weights of evidence method, followed by a cellular automata allocation model. We performed expert interviews, to develop two future forest management scenarios. The Alternative scenario (ALT) was defined by 67% more deforestation than the Business as Usual scenario (BAU). We integrated the simulated scenarios with a landslide susceptibility map. In both scenarios, most of deforestation was projected in areas where landslides are less likely to occur. Still, 483 (ALT) and 276 (BAU) ha of deforestation were projected on areas with a high-landslide occurrence likelihood. Thus, deforestation could lead to a local-scale increase in landslide risk, in particular near or adjacent to forestry roads. The parallel process of near 10% forest expansion until 2040 was projected to occur mostly on areas with high-landslide susceptibility. On a regional scale, forest expansion could so result in improved slope stability. We modeled two additional scenarios with an implemented landslide risk policy, excluding high-risk zones. The reduction of deforestation on high-risk areas was achieved without a drastic decrease in the accessibility of the areas. Together with forest expansion, it could therefore be used as a risk reduction strategy.

Motivation and Organizational Principles for Anatomical Knowledge Representation

PubMed Central

Rosse, Cornelius; Mejino, José L.; Modayur, Bharath R.; Jakobovits, Rex; Hinshaw, Kevin P.; Brinkley, James F.

1998-01-01

Abstract Objective: Conceptualization of the physical objects and spaces that constitute the human body at the macroscopic level of organization, specified as a machine-parseable ontology that, in its human-readable form, is comprehensible to both expert and novice users of anatomical information. Design: Conceived as an anatomical enhancement of the UMLS Semantic Network and Metathesaurus, the anatomical ontology was formulated by specifying defining attributes and differentia for classes and subclasses of physical anatomical entities based on their partitive and spatial relationships. The validity of the classification was assessed by instantiating the ontology for the thorax. Several transitive relationships were used for symbolically modeling aspects of the physical organization of the thorax. Results: By declaring Organ as the macroscopic organizational unit of the body, and defining the entities that constitute organs and higher level entities constituted by organs, all anatomical entities could be assigned to one of three top level classes (Anatomical structure, Anatomical spatial entity and Body substance). The ontology accommodates both the systemic and regional (topographical) views of anatomy, as well as diverse clinical naming conventions of anatomical entities. Conclusions: The ontology formulated for the thorax is extendible to microscopic and cellular levels, as well as to other body parts, in that its classes subsume essentially all anatomical entities that constitute the body. Explicit definitions of these entities and their relationships provide the first requirement for standards in anatomical concept representation. Conceived from an anatomical viewpoint, the ontology can be generalized and mapped to other biomedical domains and problem solving tasks that require anatomical knowledge. PMID:9452983

An enhanced two-step floating catchment area (E2SFCA) method for measuring spatial accessibility to primary care physicians.

PubMed

Luo, Wei; Qi, Yi

2009-12-01

This paper presents an enhancement of the two-step floating catchment area (2SFCA) method for measuring spatial accessibility, addressing the problem of uniform access within the catchment by applying weights to different travel time zones to account for distance decay. The enhancement is proved to be another special case of the gravity model. When applying this enhanced 2SFCA (E2SFCA) to measure the spatial access to primary care physicians in a study area in northern Illinois, we find that it reveals spatial accessibility pattern that is more consistent with intuition and delineates more spatially explicit health professional shortage areas. It is easy to implement in GIS and straightforward to interpret.

The role of spatial selective attention in working memory for locations: evidence from event-related potentials.

PubMed

Awh, E; Anllo-Vento, L; Hillyard, S A

2000-09-01

We investigated the hypothesis that the covert focusing of spatial attention mediates the on-line maintenance of location information in spatial working memory. During the delay period of a spatial working-memory task, behaviorally irrelevant probe stimuli were flashed at both memorized and nonmemorized locations. Multichannel recordings of event-related potentials (ERPs) were used to assess visual processing of the probes at the different locations. Consistent with the hypothesis of attention-based rehearsal, early ERP components were enlarged in response to probes that appeared at memorized locations. These visual modulations were similar in latency and topography to those observed after explicit manipulations of spatial selective attention in a parallel experimental condition that employed an identical stimulus display.

Accounting for substitution and spatial heterogeneity in a labelled choice experiment.

PubMed

Lizin, S; Brouwer, R; Liekens, I; Broeckx, S

2016-10-01

Many environmental valuation studies using stated preferences techniques are single-site studies that ignore essential spatial aspects, including possible substitution effects. In this paper substitution effects are captured explicitly in the design of a labelled choice experiment and the inclusion of different distance variables in the choice model specification. We test the effect of spatial heterogeneity on welfare estimates and transfer errors for minor and major river restoration works, and the transferability of river specific utility functions, accounting for key variables such as site visitation, spatial clustering and income. River specific utility functions appear to be transferable, resulting in low transfer errors. However, ignoring spatial heterogeneity increases transfer errors. Copyright © 2016 Elsevier Ltd. All rights reserved.

Canopy-derived fuels drive patterns of in-fire energy release and understory plant mortality in a longleaf pine ( Pinus palustris ) sandhill in northwest Florida, USA

Treesearch

Joseph J. O' Brien; E. Louise Loudermilk; J. Kevin Hiers; Scott Pokswinski; Benjamin Hornsby; Andrew Hudak; Dexter Strother; Eric Rowell; Benjamin C. Bright

2016-01-01

Wildland fire radiant energy emission is one of the only measurements of combustion that can be made at high temporal and spatial resolutions. Furthermore, spatially and temporally explicit measurements are critical for making inferences about ecological fire effects. Although the correlation between fire frequency and plant biological diversity in frequently burned ...

A Rapid and Specific Microplate Assay for the Determination of Intra- and Extracellular Ascorbate in Cultured Cells

PubMed Central

Lane, Darius J. R.; Lawen, Alfons

2014-01-01

Vitamin C (ascorbate) plays numerous important roles in cellular metabolism, many of which have only come to light in recent years. For instance, within the brain, ascorbate acts in a neuroprotective and neuromodulatory manner that involves ascorbate cycling between neurons and vicinal astrocytes - a relationship that appears to be crucial for brain ascorbate homeostasis. Additionally, emerging evidence strongly suggests that ascorbate has a greatly expanded role in regulating cellular and systemic iron metabolism than is classically recognized. The increasing recognition of the integral role of ascorbate in normal and deregulated cellular and organismal physiology demands a range of medium-throughput and high-sensitivity analytic techniques that can be executed without the need for highly expensive specialist equipment. Here we provide explicit instructions for a medium-throughput, specific and relatively inexpensive microplate assay for the determination of both intra- and extracellular ascorbate in cell culture. PMID:24747535

Two-dimensional fluid-filled closed-cell cellular solid as an acoustic metamaterial with negative index

NASA Astrophysics Data System (ADS)

Dorodnitsyn, V.; Van Damme, B.

2016-04-01

A concept for acoustic metamaterials consisting of a cellular medium with fluid-filled cells is fabricated and studied experimentally. In such a system, the fluid and solid structure explicitly interact, and elastic wave propagation is coupled to both phases. Focusing here on shear wave behavior, we confirm previous numerical studies in three steps. We first measure the material deformations pertaining to three qualitatively different shear wave modes in the frequency range below 3.5 kHz. We then measure the group velocity and demonstrate that, within a certain frequency interval, the group and phase velocity have opposite signs. This shows that the system acts as a negative-index metamaterial. Finally, we confirm the presence of band gaps due to the locally resonant behavior of the cell walls. The demonstrated concept of a closed, fluid-filled cellular material as an acoustic metamaterial opens a wide space for applications.

EXTINCTION DEBT OF PROTECTED AREAS IN DEVELOPING LANDSCAPES

EPA Science Inventory

To conserve biological diversity, protected-area networks must be based not only upon current species distributions but also the landscape's long-term capacity to support populations. We used spatially-explicit population models requiring detailed habitat and demographic data to ...

Quantifying spatially and temporally explicit CO 2 fertilization effects on global terrestrial ecosystem carbon dynamics

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

Liu, Shaoqing; Zhuang, Qianlai; Chen, Min

Current terrestrial ecosystem models are usually driven with global average annual atmospheric carbon dioxide (CO 2) concentration data at the global scale. However, high-precision CO 2 measurement from eddy flux towers showed that seasonal, spatial surface atmospheric CO 2 concentration differences were as large as 35 ppmv and the site-level tests indicated that the CO 2 variation exhibited different effects on plant photosynthesis. Here we used a process-based ecosystem model driven with two spatially and temporally explicit CO 2 data sets to analyze the atmospheric CO 2 fertilization effects on the global carbon dynamics of terrestrial ecosystems from 2003 tomore » 2010. Our results demonstrated that CO 2 seasonal variation had a negative effect on plant carbon assimilation, while CO2 spatial variation exhibited a positive impact. When both CO 2 seasonal and spatial effects were considered, global gross primary production and net ecosystem production were 1.7 Pg C•yr –1 and 0.08 Pg C•yr –1 higher than the simulation using uniformly distributed CO 2 data set and the difference was significant in tropical and temperate evergreen broadleaf forest regions. Moreover, this study suggests that the CO 2 observation network should be expanded so that the realistic CO 2 variation can be incorporated into the land surface models to adequately account for CO 2 fertilization effects on global terrestrial ecosystem carbon dynamics.« less

Modeling the Impact of Spatial Structure on Growth Dynamics of Invasive Plant Species

NASA Astrophysics Data System (ADS)

Murphy, James T.; Johnson, Mark P.; Walshe, Ray

2013-07-01

Invasive nonindigenous plant species can have potentially serious detrimental effects on local ecosystems and, as a result, costly control efforts often have to be put in place to protect habitats. An example of an invasive problem on a global scale involves the salt marsh grass species from the genus Spartina. The spread of Spartina anglica in Europe and Asia has drawn much concern due to its ability to convert coastal habitats into cord-grass monocultures and to alter the native food webs. However, the patterns of invasion of Spartina species are amenable to spatially-explicit modeling strategies that take into account both temporal and spatio-temporal processes. In this study, an agent-based model of Spartina growth on a simulated mud flat environment was developed in order to study the effects of spatial pattern and initial seedling placement on the invasion dynamics of the population. The spatial pattern of an invasion plays a key role in the rate of spread of the species and understanding this can lead to significant cost savings when designing efficient control strategies. We present here a model framework that can be used to explicitly represent complex spatial and temporal patterns of invasion in order to be able to predict quantitatively the impact of these factors on invasion dynamics. This would be a useful tool for assessing eradication strategies and choosing optimal control solutions in order to be able to minimize future control costs.

Spatial patterns of agricultural expansion determine impacts on biodiversity and carbon storage.

PubMed

Chaplin-Kramer, Rebecca; Sharp, Richard P; Mandle, Lisa; Sim, Sarah; Johnson, Justin; Butnar, Isabela; Milà I Canals, Llorenç; Eichelberger, Bradley A; Ramler, Ivan; Mueller, Carina; McLachlan, Nikolaus; Yousefi, Anahita; King, Henry; Kareiva, Peter M

2015-06-16

The agricultural expansion and intensification required to meet growing food and agri-based product demand present important challenges to future levels and management of biodiversity and ecosystem services. Influential actors such as corporations, governments, and multilateral organizations have made commitments to meeting future agricultural demand sustainably and preserving critical ecosystems. Current approaches to predicting the impacts of agricultural expansion involve calculation of total land conversion and assessment of the impacts on biodiversity or ecosystem services on a per-area basis, generally assuming a linear relationship between impact and land area. However, the impacts of continuing land development are often not linear and can vary considerably with spatial configuration. We demonstrate what could be gained by spatially explicit analysis of agricultural expansion at a large scale compared with the simple measure of total area converted, with a focus on the impacts on biodiversity and carbon storage. Using simple modeling approaches for two regions of Brazil, we find that for the same amount of land conversion, the declines in biodiversity and carbon storage can vary two- to fourfold depending on the spatial pattern of conversion. Impacts increase most rapidly in the earliest stages of agricultural expansion and are more pronounced in scenarios where conversion occurs in forest interiors compared with expansion into forests from their edges. This study reveals the importance of spatially explicit information in the assessment of land-use change impacts and for future land management and conservation.

Spatial capture-recapture models allowing Markovian transience or dispersal

USGS Publications Warehouse

Royle, J. Andrew; Fuller, Angela K.; Sutherland, Chris

2016-01-01

Spatial capture–recapture (SCR) models are a relatively recent development in quantitative ecology, and they are becoming widely used to model density in studies of animal populations using camera traps, DNA sampling and other methods which produce spatially explicit individual encounter information. One of the core assumptions of SCR models is that individuals possess home ranges that are spatially stationary during the sampling period. For many species, this assumption is unlikely to be met and, even for species that are typically territorial, individuals may disperse or exhibit transience at some life stages. In this paper we first conduct a simulation study to evaluate the robustness of estimators of density under ordinary SCR models when dispersal or transience is present in the population. Then, using both simulated and real data, we demonstrate that such models can easily be described in the BUGS language providing a practical framework for their analysis, which allows us to evaluate movement dynamics of species using capture–recapture data. We find that while estimators of density are extremely robust, even to pathological levels of movement (e.g., complete transience), the estimator of the spatial scale parameter of the encounter probability model is confounded with the dispersal/transience scale parameter. Thus, use of ordinary SCR models to make inferences about density is feasible, but interpretation of SCR model parameters in relation to movement should be avoided. Instead, when movement dynamics are of interest, such dynamics should be parameterized explicitly in the model.

Spatial patterns of agricultural expansion determine impacts on biodiversity and carbon storage

PubMed Central

Chaplin-Kramer, Rebecca; Sharp, Richard P.; Mandle, Lisa; Sim, Sarah; Johnson, Justin; Butnar, Isabela; Milà i Canals, Llorenç; Eichelberger, Bradley A.; Ramler, Ivan; Mueller, Carina; McLachlan, Nikolaus; Yousefi, Anahita; King, Henry; Kareiva, Peter M.

2015-01-01

The agricultural expansion and intensification required to meet growing food and agri-based product demand present important challenges to future levels and management of biodiversity and ecosystem services. Influential actors such as corporations, governments, and multilateral organizations have made commitments to meeting future agricultural demand sustainably and preserving critical ecosystems. Current approaches to predicting the impacts of agricultural expansion involve calculation of total land conversion and assessment of the impacts on biodiversity or ecosystem services on a per-area basis, generally assuming a linear relationship between impact and land area. However, the impacts of continuing land development are often not linear and can vary considerably with spatial configuration. We demonstrate what could be gained by spatially explicit analysis of agricultural expansion at a large scale compared with the simple measure of total area converted, with a focus on the impacts on biodiversity and carbon storage. Using simple modeling approaches for two regions of Brazil, we find that for the same amount of land conversion, the declines in biodiversity and carbon storage can vary two- to fourfold depending on the spatial pattern of conversion. Impacts increase most rapidly in the earliest stages of agricultural expansion and are more pronounced in scenarios where conversion occurs in forest interiors compared with expansion into forests from their edges. This study reveals the importance of spatially explicit information in the assessment of land-use change impacts and for future land management and conservation. PMID:26082547

A framework for spatial risk assessments: Potential impacts of nonindigenous invasive species on native species

USGS Publications Warehouse

Allen, Craig R.; Johnson, A.R.; Parris, L.

2006-01-01

Many populations of wild animals and plants are declining and face increasing threats from habitat fragmentation and loss as well as exposure to stressors ranging from toxicants to diseases to invasive nonindigenous species. We describe and demonstrate a spatially explicit ecological risk assessment that allows for the incorporation of a broad array of information that may influence the distribution of an invasive species, toxicants, or other stressors, and the incorporation of landscape variables that may influence the spread of a species or substances. The first step in our analyses is to develop species models and quantify spatial overlap between stressor and target organisms. Risk is assessed as the product of spatial overlap and a hazard index based on target species vulnerabilities to the stressor of interest. We illustrate our methods with an example in which the stressor is the ecologically destructive nonindigenous ant, Solenopsis invicta, and the targets are two declining vertebrate species in the state of South Carolina, USA. A risk approach that focuses on landscapes and that is explicitly spatial is of particular relevance as remaining undeveloped lands become increasingly uncommon and isolated and more important in the management and recovery of species and ecological systems. Effective ecosystem management includes the control of multiple stressors, including invasive species with large impacts, understanding where those impacts may be the most severe, and implementing management strategies to reduce impacts. Copyright ?? 2006 by the author(s).

Quantifying spatially and temporally explicit CO 2 fertilization effects on global terrestrial ecosystem carbon dynamics

DOE PAGES

Liu, Shaoqing; Zhuang, Qianlai; Chen, Min; ...

2016-07-25

Current terrestrial ecosystem models are usually driven with global average annual atmospheric carbon dioxide (CO 2) concentration data at the global scale. However, high-precision CO 2 measurement from eddy flux towers showed that seasonal, spatial surface atmospheric CO 2 concentration differences were as large as 35 ppmv and the site-level tests indicated that the CO 2 variation exhibited different effects on plant photosynthesis. Here we used a process-based ecosystem model driven with two spatially and temporally explicit CO 2 data sets to analyze the atmospheric CO 2 fertilization effects on the global carbon dynamics of terrestrial ecosystems from 2003 tomore » 2010. Our results demonstrated that CO 2 seasonal variation had a negative effect on plant carbon assimilation, while CO2 spatial variation exhibited a positive impact. When both CO 2 seasonal and spatial effects were considered, global gross primary production and net ecosystem production were 1.7 Pg C•yr –1 and 0.08 Pg C•yr –1 higher than the simulation using uniformly distributed CO 2 data set and the difference was significant in tropical and temperate evergreen broadleaf forest regions. Moreover, this study suggests that the CO 2 observation network should be expanded so that the realistic CO 2 variation can be incorporated into the land surface models to adequately account for CO 2 fertilization effects on global terrestrial ecosystem carbon dynamics.« less

Oscillatory cellular patterns in three-dimensional directional solidification

NASA Astrophysics Data System (ADS)

Tourret, D.; Debierre, J.-M.; Song, Y.; Mota, F. L.; Bergeon, N.; Guérin, R.; Trivedi, R.; Billia, B.; Karma, A.

2015-10-01

We present a phase-field study of oscillatory breathing modes observed during the solidification of three-dimensional cellular arrays in microgravity. Directional solidification experiments conducted onboard the International Space Station have allowed us to observe spatially extended homogeneous arrays of cells and dendrites while minimizing the amount of gravity-induced convection in the liquid. In situ observations of transparent alloys have revealed the existence, over a narrow range of control parameters, of oscillations in cellular arrays with a period ranging from about 25 to 125 min. Cellular patterns are spatially disordered, and the oscillations of individual cells are spatiotemporally uncorrelated at long distance. However, in regions displaying short-range spatial ordering, groups of cells can synchronize into oscillatory breathing modes. Quantitative phase-field simulations show that the oscillatory behavior of cells in this regime is linked to a stability limit of the spacing in hexagonal cellular array structures. For relatively high cellular front undercooling (i.e., low growth velocity or high thermal gradient), a gap appears in the otherwise continuous range of stable array spacings. Close to this gap, a sustained oscillatory regime appears with a period that compares quantitatively well with experiment. For control parameters where this gap exists, oscillations typically occur for spacings at the edge of the gap. However, after a change of growth conditions, oscillations can also occur for nearby values of control parameters where this gap just closes and a continuous range of spacings exists. In addition, sustained oscillations at to the opening of this stable gap exhibit a slow periodic modulation of the phase-shift among cells with a slower period of several hours. While long-range coherence of breathing modes can be achieved in simulations for a perfect spatial arrangement of cells as initial condition, global disorder is observed in both three-dimensional experiments and simulations from realistic noisy initial conditions. In the latter case, erratic tip-splitting events promoted by large-amplitude oscillations contribute to maintaining the long-range array disorder, unlike in thin-sample experiments where long-range coherence of oscillations is experimentally observable.

Oscillatory cellular patterns in three-dimensional directional solidification

DOE PAGES

Tourret, D.; Debierre, J. -M.; Song, Y.; ...

2015-09-11

We present a phase-field study of oscillatory breathing modes observed during the solidification of three-dimensional cellular arrays in micro-gravity. Directional solidification experiments conducted onboard the International Space Station have allowed for the first time to observe spatially extended homogeneous arrays of cells and dendrites while minimizing the amount of gravity-induced convection in the liquid. In situ observations of transparent alloys have revealed the existence, over a narrow range of control parameters, of oscillations in cellular arrays with a period ranging from about 25 to 125 minutes. Cellular patterns are spatially disordered, and the oscillations of individual cells are spatiotemporally uncorrelatedmore » at long distance. However, in regions displaying short-range spatial ordering, groups of cells can synchronize into oscillatory breathing modes. Quantitative phase-field simulations show that the oscillatory behavior of cells in this regime is linked to a stability limit of the spacing in hexagonal cellular array structures. For relatively high cellular front undercooling (\\ie low growth velocity or high thermal gradient), a gap appears in the otherwise continuous range of stable array spacings. Close to this gap, a sustained oscillatory regime appears with a period that compares quantitatively well with experiment. For control parameters where this gap exist, oscillations typically occur for spacings at the edge of the gap. However, after a change of growth conditions, oscillations can also occur for nearby values of control parameters where this gap just closes and a continuous range of spacings exists. In addition, sustained oscillations at to the opening of this stable gap exhibit a slow periodic modulation of the phase-shift among cells with a slower period of several hours. While long-range coherence of breathing modes can be achieved in simulations for a perfect spatial arrangement of cells as initial condition, global disorder is observed in both three-dimensional experiments and simulations from realistic noisy initial conditions. The, erratic tip splitting events promoted by large amplitude oscillations contribute to maintaining the long-range array disorder, unlike in thin sample experiments where long-range coherence of oscillations is experimentally observable.« less

Oscillatory cellular patterns in three-dimensional directional solidification

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

Tourret, D.; Debierre, J. -M.; Song, Y.

We present a phase-field study of oscillatory breathing modes observed during the solidification of three-dimensional cellular arrays in micro-gravity. Directional solidification experiments conducted onboard the International Space Station have allowed for the first time to observe spatially extended homogeneous arrays of cells and dendrites while minimizing the amount of gravity-induced convection in the liquid. In situ observations of transparent alloys have revealed the existence, over a narrow range of control parameters, of oscillations in cellular arrays with a period ranging from about 25 to 125 minutes. Cellular patterns are spatially disordered, and the oscillations of individual cells are spatiotemporally uncorrelatedmore » at long distance. However, in regions displaying short-range spatial ordering, groups of cells can synchronize into oscillatory breathing modes. Quantitative phase-field simulations show that the oscillatory behavior of cells in this regime is linked to a stability limit of the spacing in hexagonal cellular array structures. For relatively high cellular front undercooling (\\ie low growth velocity or high thermal gradient), a gap appears in the otherwise continuous range of stable array spacings. Close to this gap, a sustained oscillatory regime appears with a period that compares quantitatively well with experiment. For control parameters where this gap exist, oscillations typically occur for spacings at the edge of the gap. However, after a change of growth conditions, oscillations can also occur for nearby values of control parameters where this gap just closes and a continuous range of spacings exists. In addition, sustained oscillations at to the opening of this stable gap exhibit a slow periodic modulation of the phase-shift among cells with a slower period of several hours. While long-range coherence of breathing modes can be achieved in simulations for a perfect spatial arrangement of cells as initial condition, global disorder is observed in both three-dimensional experiments and simulations from realistic noisy initial conditions. The, erratic tip splitting events promoted by large amplitude oscillations contribute to maintaining the long-range array disorder, unlike in thin sample experiments where long-range coherence of oscillations is experimentally observable.« less

Spatially explicit models for inference about density in unmarked or partially marked populations

USGS Publications Warehouse

Chandler, Richard B.; Royle, J. Andrew

2013-01-01

Recently developed spatial capture–recapture (SCR) models represent a major advance over traditional capture–recapture (CR) models because they yield explicit estimates of animal density instead of population size within an unknown area. Furthermore, unlike nonspatial CR methods, SCR models account for heterogeneity in capture probability arising from the juxtaposition of animal activity centers and sample locations. Although the utility of SCR methods is gaining recognition, the requirement that all individuals can be uniquely identified excludes their use in many contexts. In this paper, we develop models for situations in which individual recognition is not possible, thereby allowing SCR concepts to be applied in studies of unmarked or partially marked populations. The data required for our model are spatially referenced counts made on one or more sample occasions at a collection of closely spaced sample units such that individuals can be encountered at multiple locations. Our approach includes a spatial point process for the animal activity centers and uses the spatial correlation in counts as information about the number and location of the activity centers. Camera-traps, hair snares, track plates, sound recordings, and even point counts can yield spatially correlated count data, and thus our model is widely applicable. A simulation study demonstrated that while the posterior mean exhibits frequentist bias on the order of 5–10% in small samples, the posterior mode is an accurate point estimator as long as adequate spatial correlation is present. Marking a subset of the population substantially increases posterior precision and is recommended whenever possible. We applied our model to avian point count data collected on an unmarked population of the northern parula (Parula americana) and obtained a density estimate (posterior mode) of 0.38 (95% CI: 0.19–1.64) birds/ha. Our paper challenges sampling and analytical conventions in ecology by demonstrating that neither spatial independence nor individual recognition is needed to estimate population density—rather, spatial dependence can be informative about individual distribution and density.

Fluid and Electrolyte Balance model (FEB)

NASA Technical Reports Server (NTRS)

Fitzjerrell, D. G.

1973-01-01

The effects of various oral input water loads on solute and water distribution throughout the body are presented in the form of a model. The model was a three compartment model; the three compartments being plasma, interstitial fluid and cellular fluid. Sodium, potassium, chloride and urea were the only major solutes considered explicitly. The control of body water and electrolyte distribution was affected via drinking and hormone levels.

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.

Flood risk in a changing world - a coupled transdisciplinary modelling framework for flood risk assessment in an Alpine study area

NASA Astrophysics Data System (ADS)

Huttenlau, Matthias; Schneeberger, Klaus; Winter, Benjamin; Pazur, Robert; Förster, Kristian; Achleitner, Stefan; Bolliger, Janine

2017-04-01

Devastating flood events have caused substantial economic damage across Europe during past decades. Flood risk management has therefore become a topic of crucial interest across state agencies, research communities and the public sector including insurances. There is consensus that mitigating flood risk relies on impact assessments which quantitatively account for a broad range of aspects in a (changing) environment. Flood risk assessments which take into account the interaction between the drivers climate change, land-use change and socio-economic change might bring new insights to the understanding of the magnitude and spatial characteristic of flood risks. Furthermore, the comparative assessment of different adaptation measures can give valuable information for decision-making. With this contribution we present an inter- and transdisciplinary research project aiming at developing and applying such an impact assessment relying on a coupled modelling framework for the Province of Vorarlberg in Austria. Stakeholder engagement ensures that the final outcomes of our study are accepted and successfully implemented in flood management practice. The study addresses three key questions: (i) What are scenarios of land- use and climate change for the study area? (ii) How will the magnitude and spatial characteristic of future flood risk change as a result of changes in climate and land use? (iii) Are there spatial planning and building-protection measures which effectively reduce future flood risk? The modelling framework has a modular structure comprising modules (i) climate change, (ii) land-use change, (iii) hydrologic modelling, (iv) flood risk analysis, and (v) adaptation measures. Meteorological time series are coupled with spatially explicit scenarios of land-use change to model runoff time series. The runoff time series are combined with impact indicators such as building damages and results are statistically assessed to analyse flood risk scenarios. Thus, the regional flood risk can be expressed in terms of expected annual damage and damages associated with a low probability of occurrence. We consider building protection measures explicitly as part of the consequence analysis of flood risk whereas spatial planning measures are already considered as explicit scenarios in the course of land-use change modelling.

On ultrasound-induced microbubble oscillation in a capillary blood vessel and its implications for the blood-brain barrier

NASA Astrophysics Data System (ADS)

Wiedemair, W.; Tuković, Ž.; Jasak, H.; Poulikakos, D.; Kurtcuoglu, V.

2012-02-01

The complex interaction between an ultrasound-driven microbubble and an enclosing capillary microvessel is investigated by means of a coupled, multi-domain numerical model using the finite volume formulation. This system is of interest in the study of transient blood-brain barrier disruption (BBBD) for drug delivery applications. The compliant vessel structure is incorporated explicitly as a distinct domain described by a dedicated physical model. Red blood cells (RBCs) are taken into account as elastic solids in the blood plasma. We report the temporal and spatial development of transmural pressure (Ptm) and wall shear stress (WSS) at the luminal endothelial interface, both of which are candidates for the yet unknown mediator of BBBD. The explicit introduction of RBCs shapes the Ptm and WSS distributions and their derivatives markedly. While the peak values of these mechanical wall parameters are not affected considerably by the presence of RBCs, a pronounced increase in their spatial gradients is observed compared to a configuration with blood plasma alone. The novelty of our work lies in the explicit treatment of the vessel wall, and in the modelling of blood as a composite fluid, which we show to be relevant for the mechanical processes at the endothelium.

Biasing spatial attention with semantic information: an event coding approach.

PubMed

Amer, Tarek; Gozli, Davood G; Pratt, Jay

2017-04-21

We investigated the influence of conceptual processing on visual attention from the standpoint of Theory of Event Coding (TEC). The theory makes two predictions: first, an important factor in determining the influence of event 1 on processing event 2 is whether features of event 1 are bound into a unified representation (i.e., selection or retrieval of event 1). Second, whether processing the two events facilitates or interferes with each other should depend on the extent to which their constituent features overlap. In two experiments, participants performed a visual-attention cueing task, in which the visual target (event 2) was preceded by a relevant or irrelevant explicit (e.g., "UP") or implicit (e.g., "HAPPY") spatial-conceptual cue (event 1). Consistent with TEC, we found relevant explicit cues (which featurally overlap to a greater extent with the target) and implicit cues (which featurally overlap to a lesser extent), respectively, facilitated and interfered with target processing at compatible locations. Irrelevant explicit and implicit cues, on the other hand, both facilitated target processing, presumably because they were less likely selected or retrieved as an integrated and unified event file. We argue that such effects, often described as "attentional cueing", are better accounted for within the event coding framework.

Robust Kriged Kalman Filtering

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

Baingana, Brian; Dall'Anese, Emiliano; Mateos, Gonzalo

2015-11-11

Although the kriged Kalman filter (KKF) has well-documented merits for prediction of spatial-temporal processes, its performance degrades in the presence of outliers due to anomalous events, or measurement equipment failures. This paper proposes a robust KKF model that explicitly accounts for presence of measurement outliers. Exploiting outlier sparsity, a novel l1-regularized estimator that jointly predicts the spatial-temporal process at unmonitored locations, while identifying measurement outliers is put forth. Numerical tests are conducted on a synthetic Internet protocol (IP) network, and real transformer load data. Test results corroborate the effectiveness of the novel estimator in joint spatial prediction and outlier identification.

On the effects of scale for ecosystem services mapping

USGS Publications Warehouse

Grêt-Regamey, Adrienne; Weibel, Bettina; Bagstad, Kenneth J.; Ferrari, Marika; Geneletti, Davide; Klug, Hermann; Schirpke, Uta; Tappeiner, Ulrike

2014-01-01

Ecosystems provide life-sustaining services upon which human civilization depends, but their degradation largely continues unabated. Spatially explicit information on ecosystem services (ES) provision is required to better guide decision making, particularly for mountain systems, which are characterized by vertical gradients and isolation with high topographic complexity, making them particularly sensitive to global change. But while spatially explicit ES quantification and valuation allows the identification of areas of abundant or limited supply of and demand for ES, the accuracy and usefulness of the information varies considerably depending on the scale and methods used. Using four case studies from mountainous regions in Europe and the U.S., we quantify information gains and losses when mapping five ES - carbon sequestration, flood regulation, agricultural production, timber harvest, and scenic beauty - at coarse and fine resolution (250 m vs. 25 m in Europe and 300 m vs. 30 m in the U.S.). We analyze the effects of scale on ES estimates and their spatial pattern and show how these effects are related to different ES, terrain structure and model properties. ES estimates differ substantially between the fine and coarse resolution analyses in all case studies and across all services. This scale effect is not equally strong for all ES. We show that spatially explicit information about non-clustered, isolated ES tends to be lost at coarse resolution and against expectation, mainly in less rugged terrain, which calls for finer resolution assessments in such contexts. The effect of terrain ruggedness is also related to model properties such as dependency on land use-land cover data. We close with recommendations for mapping ES to make the resulting maps more comparable, and suggest a four-step approach to address the issue of scale when mapping ES that can deliver information to support ES-based decision making with greater accuracy and reliability.

On the Effects of Scale for Ecosystem Services Mapping

PubMed Central

Grêt-Regamey, Adrienne; Weibel, Bettina; Bagstad, Kenneth J.; Ferrari, Marika; Geneletti, Davide; Klug, Hermann; Schirpke, Uta; Tappeiner, Ulrike

2014-01-01

Ecosystems provide life-sustaining services upon which human civilization depends, but their degradation largely continues unabated. Spatially explicit information on ecosystem services (ES) provision is required to better guide decision making, particularly for mountain systems, which are characterized by vertical gradients and isolation with high topographic complexity, making them particularly sensitive to global change. But while spatially explicit ES quantification and valuation allows the identification of areas of abundant or limited supply of and demand for ES, the accuracy and usefulness of the information varies considerably depending on the scale and methods used. Using four case studies from mountainous regions in Europe and the U.S., we quantify information gains and losses when mapping five ES - carbon sequestration, flood regulation, agricultural production, timber harvest, and scenic beauty - at coarse and fine resolution (250 m vs. 25 m in Europe and 300 m vs. 30 m in the U.S.). We analyze the effects of scale on ES estimates and their spatial pattern and show how these effects are related to different ES, terrain structure and model properties. ES estimates differ substantially between the fine and coarse resolution analyses in all case studies and across all services. This scale effect is not equally strong for all ES. We show that spatially explicit information about non-clustered, isolated ES tends to be lost at coarse resolution and against expectation, mainly in less rugged terrain, which calls for finer resolution assessments in such contexts. The effect of terrain ruggedness is also related to model properties such as dependency on land use-land cover data. We close with recommendations for mapping ES to make the resulting maps more comparable, and suggest a four-step approach to address the issue of scale when mapping ES that can deliver information to support ES-based decision making with greater accuracy and reliability. PMID:25549256

Climate limits across space and time on European forest structure

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

On the effects of scale for ecosystem services mapping.

PubMed

Grêt-Regamey, Adrienne; Weibel, Bettina; Bagstad, Kenneth J; Ferrari, Marika; Geneletti, Davide; Klug, Hermann; Schirpke, Uta; Tappeiner, Ulrike

2014-01-01

Ecosystems provide life-sustaining services upon which human civilization depends, but their degradation largely continues unabated. Spatially explicit information on ecosystem services (ES) provision is required to better guide decision making, particularly for mountain systems, which are characterized by vertical gradients and isolation with high topographic complexity, making them particularly sensitive to global change. But while spatially explicit ES quantification and valuation allows the identification of areas of abundant or limited supply of and demand for ES, the accuracy and usefulness of the information varies considerably depending on the scale and methods used. Using four case studies from mountainous regions in Europe and the U.S., we quantify information gains and losses when mapping five ES - carbon sequestration, flood regulation, agricultural production, timber harvest, and scenic beauty - at coarse and fine resolution (250 m vs. 25 m in Europe and 300 m vs. 30 m in the U.S.). We analyze the effects of scale on ES estimates and their spatial pattern and show how these effects are related to different ES, terrain structure and model properties. ES estimates differ substantially between the fine and coarse resolution analyses in all case studies and across all services. This scale effect is not equally strong for all ES. We show that spatially explicit information about non-clustered, isolated ES tends to be lost at coarse resolution and against expectation, mainly in less rugged terrain, which calls for finer resolution assessments in such contexts. The effect of terrain ruggedness is also related to model properties such as dependency on land use-land cover data. We close with recommendations for mapping ES to make the resulting maps more comparable, and suggest a four-step approach to address the issue of scale when mapping ES that can deliver information to support ES-based decision making with greater accuracy and reliability.

Rolled-up Functionalized Nanomembranes as Three-Dimensional Cavities for Single Cell Studies

PubMed Central

2014-01-01

We use micropatterning and strain engineering to encapsulate single living mammalian cells into transparent tubular architectures consisting of three-dimensional (3D) rolled-up nanomembranes. By using optical microscopy, we demonstrate that these structures are suitable for the scrutiny of cellular dynamics within confined 3D-microenvironments. We show that spatial confinement of mitotic mammalian cells inside tubular architectures can perturb metaphase plate formation, delay mitotic progression, and cause chromosomal instability in both a transformed and nontransformed human cell line. These findings could provide important clues into how spatial constraints dictate cellular behavior and function. PMID:24598026

2D spatially controlled polymer micro patterning for cellular behavior studies

NASA Astrophysics Data System (ADS)

Dinca, V.; Palla-Papavlu, A.; Paraico, I.; Lippert, T.; Wokaun, A.; Dinescu, M.

2011-04-01

A simple and effective method to functionalize glass surfaces that enable polymer micropatterning and subsequent spatially controlled adhesion of cells is reported in this paper. The method involves the application of laser induced forward transfer (LIFT) to achieve polymer patterning in a single step onto cell repellent substrates (i.e. polyethyleneglycol (PEG)). This approach was used to produce micron-size polyethyleneimine (PEI)-patterns alternating with cell-repellent areas. The focus of this work is the ability of SH-SY5Y human neuroblastoma cells to orient, migrate, and produce organized cellular arrangements on laser generated PEI patterns.

Characterizing virus-induced gene silencing at the cellular level with in situ multimodal imaging

DOE PAGES

Burkhow, Sadie J.; Stephens, Nicole M.; Mei, Yu; ...

2018-05-25

Reverse genetic strategies, such as virus-induced gene silencing, are powerful techniques to study gene function. Currently, there are few tools to study the spatial dependence of the consequences of gene silencing at the cellular level. Here, we report the use of multimodal Raman and mass spectrometry imaging to study the cellular-level biochemical changes that occur from silencing the phytoene desaturase ( pds) gene using a Foxtail mosaic virus (FoMV) vector in maize leaves. The multimodal imaging method allows the localized carotenoid distribution to be measured and reveals differences lost in the spatial average when analyzing a carotenoid extraction of themore » whole leaf. The nature of the Raman and mass spectrometry signals are complementary: silencing pds reduces the downstream carotenoid Raman signal and increases the phytoene mass spectrometry signal.« less

Time-spatial model on the dynamics of the proliferation of Aedes aegypti

NASA Astrophysics Data System (ADS)

Gouvêa, Maury Meirelles, Jr.

2017-03-01

Some complex physical systems, such as cellular regulation, ecosystems, and societies, can be represented by local interactions between agents. Then, complex behaviors may emerge. A cellular automaton is a discrete dynamic system with these features. Among the several complex systems, epidemic diseases are given special attention by researchers with respect to their dynamics. Understanding the behavior of an epidemic may well benefit a society. For instance, different proliferation scenarios may be produced and a prevention policy set. This paper presents a new simulation method of the time-spatial spread of the Dengue mosquito with a cellular automaton. Thus, it will be possible to create different dissemination scenarios and preventive policies for these in several regions. Simulations were performed with different initial conditions and parameters as a result of which the behavior of the proposed method was characterized.

Characterizing virus-induced gene silencing at the cellular level with in situ multimodal imaging

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

Burkhow, Sadie J.; Stephens, Nicole M.; Mei, Yu

Reverse genetic strategies, such as virus-induced gene silencing, are powerful techniques to study gene function. Currently, there are few tools to study the spatial dependence of the consequences of gene silencing at the cellular level. Here, we report the use of multimodal Raman and mass spectrometry imaging to study the cellular-level biochemical changes that occur from silencing the phytoene desaturase ( pds) gene using a Foxtail mosaic virus (FoMV) vector in maize leaves. The multimodal imaging method allows the localized carotenoid distribution to be measured and reveals differences lost in the spatial average when analyzing a carotenoid extraction of themore » whole leaf. The nature of the Raman and mass spectrometry signals are complementary: silencing pds reduces the downstream carotenoid Raman signal and increases the phytoene mass spectrometry signal.« less

Climate Change Impacts on Freshwater Recreational Fishing in the United States

EPA Science Inventory

Using a geographic information system, a spatially explicit modeling framework was developed consisting grid cells organized into 2,099 eight-digit hydrologic unit code (HUC-8) polygons for the coterminous United States. Projected temperature and precipitation changes associated...

Changes in soil respiration across a chronosequence of tallgrass prairie reconstructions

Treesearch

Ryan M. Maher; Heidi Asbjornsen; Randall K. Kolka; Cynthia A. Cambardella; James W. Raich

2010-01-01

Close relationships among climatic factors and soil respiration (Rs) are commonly reported. However, variation in Rs across the landscape is compounded by site-specific differences that impede the development of spatially explicit models. Among factors that influence R

Predicted range expansion of Chinese tallow tree (Triadica sebifera) in forestlands of the southern United States

Treesearch

Hsiao-Hsuan Wang; William Grant; Todd Swannack; Jianbang Gan; William Rogers; Tomasz Koralewski; James Miller; John W. Taylor Jr.

2011-01-01

We present an integrated approach for predicting future range expansion of an invasive species (Chinese tallow tree) that incorporates statistical forecasting and analytical techniques within a spatially explicit, agent-based, simulation framework.

HexSim: a modeling environment for ecology and conservation.

EPA Science Inventory

HexSim is a powerful and flexible new spatially-explicit, individual based modeling environment intended for use in ecology, conservation, genetics, epidemiology, toxicology, and other disciplines. We describe HexSim, illustrate past applications that contributed to our >10 year ...

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...

INVASIVE SPECIES: PREDICTING GEOGRAPHIC DISTRIBUTIONS USING ECOLOGICAL NICHE MODELING

EPA Science Inventory

Present approaches to species invasions are reactive in nature. This scenario results in management that perpetually lags behind the most recent invasion and makes control much more difficult. In contrast, spatially explicit ecological niche modeling provides an effective solut...

AN INDIVIDUAL-BASED MODEL OF COTTUS POPULATION DYNAMICS

EPA Science Inventory

We explored population dynamics of a southern Appalachian population of Cottus bairdi using a spatially-explicit, individual-based model. The model follows daily growth, mortality, and spawning of individuals as a function of flow and temperature. We modeled movement of juveniles...

Development of resource shed delineation in aquatic ecosystems

EPA Science Inventory

Environmental issues in aquatic ecosystems of high management priority involve spatially explicit phenomena that occur over vast areas. A "landscape" perspective is thus necessary, including an understanding of how ecological phenomena at a local scale are affected by physical fo...

Bet-hedging as a complex interaction among developmental instability, environmental heterogeneity, dispersal, and life-history strategy.

PubMed

Scheiner, Samuel M

2014-02-01

One potential evolutionary response to environmental heterogeneity is the production of randomly variable offspring through developmental instability, a type of bet-hedging. I used an individual-based, genetically explicit model to examine the evolution of developmental instability. The model considered both temporal and spatial heterogeneity alone and in combination, the effect of migration pattern (stepping stone vs. island), and life-history strategy. I confirmed that temporal heterogeneity alone requires a threshold amount of variation to select for a substantial amount of developmental instability. For spatial heterogeneity only, the response to selection on developmental instability depended on the life-history strategy and the form and pattern of dispersal with the greatest response for island migration when selection occurred before dispersal. Both spatial and temporal variation alone select for similar amounts of instability, but in combination resulted in substantially more instability than either alone. Local adaptation traded off against bet-hedging, but not in a simple linear fashion. I found higher-order interactions between life-history patterns, dispersal rates, dispersal patterns, and environmental heterogeneity that are not explainable by simple intuition. We need additional modeling efforts to understand these interactions and empirical tests that explicitly account for all of these factors.

Spatial two-photon coherence of the entangled field produced by down-conversion using a partially spatially coherent pump beam

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

Jha, Anand Kumar; Boyd, Robert W.

2010-01-15

We study the spatial coherence properties of the entangled two-photon field produced by parametric down-conversion (PDC) when the pump field is, spatially, a partially coherent beam. By explicitly treating the case of a pump beam of the Gaussian Schell-model type, we show that in PDC the spatial coherence properties of the pump field get entirely transferred to the spatial coherence properties of the down-converted two-photon field. As one important consequence of this study, we find that, for two-qubit states based on the position correlations of the two-photon field, the maximum achievable entanglement, as quantified by concurrence, is bounded by themore » degree of spatial coherence of the pump field. These results could be important by providing a means of controlling the entanglement of down-converted photons by tailoring the degree of coherence of the pump field.« less

sGD: software for estimating spatially explicit indices of genetic diversity.

PubMed

Shirk, A J; Cushman, S A

2011-09-01

Anthropogenic landscape changes have greatly reduced the population size, range and migration rates of many terrestrial species. The small local effective population size of remnant populations favours loss of genetic diversity leading to reduced fitness and adaptive potential, and thus ultimately greater extinction risk. Accurately quantifying genetic diversity is therefore crucial to assessing the viability of small populations. Diversity indices are typically calculated from the multilocus genotypes of all individuals sampled within discretely defined habitat patches or larger regional extents. Importantly, discrete population approaches do not capture the clinal nature of populations genetically isolated by distance or landscape resistance. Here, we introduce spatial Genetic Diversity (sGD), a new spatially explicit tool to estimate genetic diversity based on grouping individuals into potentially overlapping genetic neighbourhoods that match the population structure, whether discrete or clinal. We compared the estimates and patterns of genetic diversity using patch or regional sampling and sGD on both simulated and empirical populations. When the population did not meet the assumptions of an island model, we found that patch and regional sampling generally overestimated local heterozygosity, inbreeding and allelic diversity. Moreover, sGD revealed fine-scale spatial heterogeneity in genetic diversity that was not evident with patch or regional sampling. These advantages should provide a more robust means to evaluate the potential for genetic factors to influence the viability of clinal populations and guide appropriate conservation plans. © 2011 Blackwell Publishing Ltd.

Spatial Bayesian belief networks as a planning decision tool for mapping ecosystem services trade-offs on forested landscapes.

PubMed

Gonzalez-Redin, Julen; Luque, Sandra; Poggio, Laura; Smith, Ron; Gimona, Alessandro

2016-01-01

An integrated methodology, based on linking Bayesian belief networks (BBN) with GIS, is proposed for combining available evidence to help forest managers evaluate implications and trade-offs between forest production and conservation measures to preserve biodiversity in forested habitats. A Bayesian belief network is a probabilistic graphical model that represents variables and their dependencies through specifying probabilistic relationships. In spatially explicit decision problems where it is difficult to choose appropriate combinations of interventions, the proposed integration of a BBN with GIS helped to facilitate shared understanding of the human-landscape relationships, while fostering collective management that can be incorporated into landscape planning processes. Trades-offs become more and more relevant in these landscape contexts where the participation of many and varied stakeholder groups is indispensable. With these challenges in mind, our integrated approach incorporates GIS-based data with expert knowledge to consider two different land use interests - biodiversity value for conservation and timber production potential - with the focus on a complex mountain landscape in the French Alps. The spatial models produced provided different alternatives of suitable sites that can be used by policy makers in order to support conservation priorities while addressing management options. The approach provided provide a common reasoning language among different experts from different backgrounds while helped to identify spatially explicit conflictive areas. Copyright © 2015 Elsevier Inc. All rights reserved.

An analysis of the relationship between drought events and mangrove changes along the northern coasts of the Pe rsian Gulf and Oman Sea

NASA Astrophysics Data System (ADS)

Mafi-Gholami, Davood; Mahmoudi, Beytollah; Zenner, Eric K.

2017-12-01

Relating the changes of mangrove forests to spatially explicit reductions in rainfall amounts and increases in drought occurrences is a prerequisite for improving the effectiveness and success of mangrove forest conservation programs. To this end, we investigated the relationship between drought events (quantified using the Standardized Precipitation Index [SPI]) and changes in area and canopy cover of mangrove forests on the northern coast of the Persian Gulf and the Oman Sea using satellite imagery and long-term annual rainfall data over a period of 30 years (1986-2016). Statistical analyses revealed 1998 as the year marking the most significant change-point in the mean annual rainfall values in the catchments and mangroves, after which average SPI values consistently remained at lower levels. In the period of 1998-2016, decreases in the mean annual rainfall and increases in the severity of droughts differed spatially and were greater in the catchments and mangroves on the coasts of the Oman Sea than the coasts of the Persian Gulf. These spatially explicit results were closely mirrored by the mangrove response, with differential in reductions in mangrove areas and canopy cover that corresponded closely with the spatial distribution of drought intensities in the different parts of the coasts, with correlation coefficients ≥0.89 for the different coastal regions.

Spatial Object Recognition Enables Endogenous LTD that Curtails LTP in the Mouse Hippocampus

PubMed Central

Goh, Jinzhong Jeremy

2013-01-01

Although synaptic plasticity is believed to comprise the cellular substrate for learning and memory, limited direct evidence exists that hippocampus-dependent learning actually triggers synaptic plasticity. It is likely, however, that long-term potentiation (LTP) works in concert with its counterpart, long-term depression (LTD) in the creation of spatial memory. It has been reported in rats that weak synaptic plasticity is facilitated into persistent plasticity if afferent stimulation is coupled with a novel spatial learning event. It is not known if this phenomenon also occurs in other species. We recorded from the hippocampal CA1 of freely behaving mice and observed that novel spatial learning triggers endogenous LTD. Specifically, we observed that LTD is enabled when test-pulse afferent stimulation is given during the learning of object constellations or during a spatial object recognition task. Intriguingly, LTP is significantly impaired by the same tasks, suggesting that LTD is the main cellular substrate for this type of learning. These data indicate that learning-facilitated plasticity is not exclusive to rats and that spatial learning leads to endogenous LTD in the hippocampus, suggesting an important role for this type of synaptic plasticity in the creation of hippocampus-dependent memory. PMID:22510536

Spatially modulated ephrinA1:EphA2 signaling increases local contractility and global focal adhesion dynamics to promote cell motility.

PubMed

Chen, Zhongwen; Oh, Dongmyung; Biswas, Kabir H; Yu, Cheng-Han; Zaidel-Bar, Ronen; Groves, Jay T

2018-06-19

Recent studies have revealed pronounced effects of the spatial distribution of EphA2 receptors on cellular response to receptor activation. However, little is known about molecular mechanisms underlying this spatial sensitivity, in part due to lack of experimental systems. Here, we introduce a hybrid live-cell patterned supported lipid bilayer experimental platform in which the sites of EphA2 activation and integrin adhesion are spatially controlled. Using a series of live-cell imaging and single-molecule tracking experiments, we map the transmission of signals from ephrinA1:EphA2 complexes. Results show that ligand-dependent EphA2 activation induces localized myosin-dependent contractions while simultaneously increasing focal adhesion dynamics throughout the cell. Mechanistically, Src kinase is activated at sites of ephrinA1:EphA2 clustering and subsequently diffuses on the membrane to focal adhesions, where it up-regulates FAK and paxillin tyrosine phosphorylation. EphrinA1:EphA2 signaling triggers multiple cellular responses with differing spatial dependencies to enable a directed migratory response to spatially resolved contact with ephrinA1 ligands.

Spatial distribution of filament elasticity determines the migratory behaviors of a cell

PubMed Central

Harn, Hans I-Chen; Hsu, Chao-Kai; Wang, Yang-Kao; Huang, Yi-Wei; Chiu, Wen-Tai; Lin, Hsi-Hui; Cheng, Chao-Min; Tang, Ming-Jer

2016-01-01

ABSTRACT Any cellular response leading to morphological changes is highly tuned to balance the force generated from structural reorganization, provided by actin cytoskeleton. Actin filaments serve as the backbone of intracellular force, and transduce external mechanical signal via focal adhesion complex into the cell. During migration, cells not only undergo molecular changes but also rapid mechanical modulation. Here we focus on determining, the role of spatial distribution of mechanical changes of actin filaments in epithelial, mesenchymal, fibrotic and cancer cells with non-migration, directional migration, and non-directional migration behaviors using the atomic force microscopy. We found 1) non-migratory cells only generated one type of filament elasticity, 2) cells generating spatially distributed two types of filament elasticity showed directional migration, and 3) pathologic cells that autonomously generated two types of filament elasticity without spatial distribution were actively migrating non-directionally. The demonstration of spatial regulation of filament elasticity of different cell types at the nano-scale highlights the coupling of cytoskeletal function with physical characters at the sub-cellular level, and provides new research directions for migration related disease. PMID:26919488

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.

IMPORTANCE OF MOVEMENT VARIES IN STATIC AND DYNAMIC LANDSCAPES

EPA Science Inventory

The relative sensitivity of spatially explicit population models (SEPMs) to movement parameters is a topic of ongoing debate among theoretical ecologists. In this study, we add additional realism to this debate by examining a SEPM's sensitivity to dispersal ability in static vs....

Management considerations

Treesearch

Steven T. Knick; Steven E. Hanser; Matthias Leu; Cameron L. Aldridge; Scott E. Neilsen; Mary M. Rowland; Sean P. Finn; Michael J. Wisdom

2011-01-01

We conducted an ecoregional assessment of sagebrush (Artemisia spp.) ecosystems in the Wyoming Basins and surrounding regions (WBEA) to determine broad-scale species-environmental relationships. Our goal was to assess the potential influence from threats to the sagebrush ecosystem on associated wildlife through the use of spatially explicit...

The development of a spatially-explicit, individual-based, disease model for frogs and the chytrid fungus

EPA Science Inventory

Background / Question / Methods The fungal pathogen, Batrachochytrium dendrobatidis (BD), has been associated with amphibian population declines and even extinctions worldwide. Transmission of the fungus between amphibian hosts occurs via motile zoospores, which are produced on...

A spatially explicit model for estimating risks of pesticide exposure on bird populations

EPA Science Inventory

Product Description (FY17 Key Product): Current ecological risk assessment for pesticides under FIFRA relies on risk quotients (RQs), which suffer from significant methodological shortcomings. For example, RQs do not integrate adverse effects arising from multiple demographic pr...

New Interoperable Tools to Facilitate Decision-Making to Support Community Sustainability

EPA Science Inventory

Communities, regional planning authorities, regulatory agencies, and other decision-making bodies do not currently have adequate access to spatially explicit information crucial to making decisions that allow them to consider a full accounting of the costs, benefits, and trade-of...

Spec2Harv: Converting Spectrum output to HARVEST input

Treesearch

Eric J. Gustafson; Luke V. Rasmussen; Larry A. Leefers

2003-01-01

Spec2Harv was developed to automate the conversion of harvest schedules generated by the Spectrum model into script files that can be used by the HARVEST simulation model to simulate the implementation of the Spectrum schedules in a spatially explicit way.

A DYNAMIC MODEL OF AN ESTUARINE INVASION BY A NON-NATIVE SEAGRASS

EPA Science Inventory

Mathematical and simulation models provide an excellent tool for examining and predicting biological invasions in time and space; however, traditional models do not incorporate dynamic rates of population growth, which limits their realism. We developed a spatially explicit simul...

Social and spatial effects on genetic variation between foraging flocks in a wild bird population.

PubMed

Radersma, Reinder; Garroway, Colin J; Santure, Anna W; de Cauwer, Isabelle; Farine, Damien R; Slate, Jon; Sheldon, Ben C

2017-10-01

Social interactions are rarely random. In some instances, animals exhibit homophily or heterophily, the tendency to interact with similar or dissimilar conspecifics, respectively. Genetic homophily and heterophily influence the evolutionary dynamics of populations, because they potentially affect sexual and social selection. Here, we investigate the link between social interactions and allele frequencies in foraging flocks of great tits (Parus major) over three consecutive years. We constructed co-occurrence networks which explicitly described the splitting and merging of 85,602 flocks through time (fission-fusion dynamics), at 60 feeding sites. Of the 1,711 birds in those flocks, we genotyped 962 individuals at 4,701 autosomal single nucleotide polymorphisms (SNPs). By combining genomewide genotyping with repeated field observations of the same individuals, we were able to investigate links between social structure and allele frequencies at a much finer scale than was previously possible. We explicitly accounted for potential spatial effects underlying genetic structure at the population level. We modelled social structure and spatial configuration of great tit fission-fusion dynamics with eigenvector maps. Variance partitioning revealed that allele frequencies were strongly affected by group fidelity (explaining 27%-45% of variance) as individuals tended to maintain associations with the same conspecifics. These conspecifics were genetically more dissimilar than expected, shown by genomewide heterophily for pure social (i.e., space-independent) grouping preferences. Genomewide homophily was linked to spatial configuration, indicating spatial segregation of genotypes. We did not find evidence for homophily or heterophily for putative socially relevant candidate genes or any other SNP markers. Together, these results demonstrate the importance of distinguishing social and spatial processes in determining population structure. © 2017 John Wiley & Sons Ltd.

A three dimensional multigrid multiblock multistage time stepping scheme for the Navier-Stokes equations

NASA Technical Reports Server (NTRS)

Elmiligui, Alaa; Cannizzaro, Frank; Melson, N. D.

1991-01-01

A general multiblock method for the solution of the three-dimensional, unsteady, compressible, thin-layer Navier-Stokes equations has been developed. The convective and pressure terms are spatially discretized using Roe's flux differencing technique while the viscous terms are centrally differenced. An explicit Runge-Kutta method is used to advance the solution in time. Local time stepping, adaptive implicit residual smoothing, and the Full Approximation Storage (FAS) multigrid scheme are added to the explicit time stepping scheme to accelerate convergence to steady state. Results for three-dimensional test cases are presented and discussed.

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.

A simple model of fluid flow and electrolyte balance in the body

NASA Technical Reports Server (NTRS)

White, R. J.; Neal, L.

1973-01-01

The model is basically a three-compartment model, the three compartments being the plasma, interstitial fluid and cellular fluid. Sodium, potassium, chloride and urea are the only major solutes considered explicitly. The control of body water and electrolyte distribution is affected via drinking and hormone levels. Basically, the model follows the effect of various oral input water loads on solute and water distribution throughout the body.

Multiscale Simulation of Porous Ceramics Based on Movable Cellular Automaton Method

NASA Astrophysics Data System (ADS)

Smolin, A.; Smolin, I.; Eremina, G.; Smolina, I.

2017-10-01

The paper presents a model for simulating mechanical behaviour of multiscale porous ceramics based on movable cellular automaton method, which is a novel particle method in computational mechanics of solid. The initial scale of the proposed approach corresponds to the characteristic size of the smallest pores in the ceramics. At this scale, we model uniaxial compression of several representative samples with an explicit account of pores of the same size but with the random unique position in space. As a result, we get the average values of Young’s modulus and strength, as well as the parameters of the Weibull distribution of these properties at the current scale level. These data allow us to describe the material behaviour at the next scale level were only the larger pores are considered explicitly, while the influence of small pores is included via the effective properties determined at the previous scale level. If the pore size distribution function of the material has N maxima we need to perform computations for N - 1 levels in order to get the properties from the lowest scale up to the macroscale step by step. The proposed approach was applied to modelling zirconia ceramics with bimodal pore size distribution. The obtained results show correct behaviour of the model sample at the macroscale.

Spatially explicit population estimates for black bears based on cluster sampling

USGS Publications Warehouse

Humm, J.; McCown, J. Walter; Scheick, B.K.; Clark, Joseph D.

2017-01-01

We estimated abundance and density of the 5 major black bear (Ursus americanus) subpopulations (i.e., Eglin, Apalachicola, Osceola, Ocala-St. Johns, Big Cypress) in Florida, USA with spatially explicit capture-mark-recapture (SCR) by extracting DNA from hair samples collected at barbed-wire hair sampling sites. We employed a clustered sampling configuration with sampling sites arranged in 3 × 3 clusters spaced 2 km apart within each cluster and cluster centers spaced 16 km apart (center to center). We surveyed all 5 subpopulations encompassing 38,960 km2 during 2014 and 2015. Several landscape variables, most associated with forest cover, helped refine density estimates for the 5 subpopulations we sampled. Detection probabilities were affected by site-specific behavioral responses coupled with individual capture heterogeneity associated with sex. Model-averaged bear population estimates ranged from 120 (95% CI = 59–276) bears or a mean 0.025 bears/km2 (95% CI = 0.011–0.44) for the Eglin subpopulation to 1,198 bears (95% CI = 949–1,537) or 0.127 bears/km2 (95% CI = 0.101–0.163) for the Ocala-St. Johns subpopulation. The total population estimate for our 5 study areas was 3,916 bears (95% CI = 2,914–5,451). The clustered sampling method coupled with information on land cover was efficient and allowed us to estimate abundance across extensive areas that would not have been possible otherwise. Clustered sampling combined with spatially explicit capture-recapture methods has the potential to provide rigorous population estimates for a wide array of species that are extensive and heterogeneous in their distribution.

Analyzing key constraints to biogas production from crop residues and manure in the EU—A spatially explicit model

PubMed Central

Persson, U. Martin

2017-01-01

This paper presents a spatially explicit method for making regional estimates of the potential for biogas production from crop residues and manure, accounting for key technical, biochemical, environmental and economic constraints. Methods for making such estimates are important as biofuels from agricultural residues are receiving increasing policy support from the EU and major biogas producers, such as Germany and Italy, in response to concerns over unintended negative environmental and social impacts of conventional biofuels. This analysis comprises a spatially explicit estimate of crop residue and manure production for the EU at 250 m resolution, and a biogas production model accounting for local constraints such as the sustainable removal of residues, transportation of substrates, and the substrates’ biochemical suitability for anaerobic digestion. In our base scenario, the EU biogas production potential from crop residues and manure is about 0.7 EJ/year, nearly double the current EU production of biogas from agricultural substrates, most of which does not come from residues or manure. An extensive sensitivity analysis of the model shows that the potential could easily be 50% higher or lower, depending on the stringency of economic, technical and biochemical constraints. We find that the potential is particularly sensitive to constraints on the substrate mixtures’ carbon-to-nitrogen ratio and dry matter concentration. Hence, the potential to produce biogas from crop residues and manure in the EU depends to large extent on the possibility to overcome the challenges associated with these substrates, either by complementing them with suitable co-substrates (e.g. household waste and energy crops), or through further development of biogas technology (e.g. pretreatment of substrates and recirculation of effluent). PMID:28141827

Interactions between spatially explicit conservation and management measures: implications for the governance of marine protected areas.

PubMed

Cárcamo, P Francisco; Gaymer, Carlos F

2013-12-01

Marine protected areas are not established in an institutional and governance vacuum and managers should pay attention to the wider social-ecological system in which they are immersed. This article examines Islas Choros-Damas Marine Reserve, a small marine protected area located in a highly productive and biologically diverse coastal marine ecosystem in northern Chile, and the interactions between human, institutional, and ecological dimensions beyond those existing within its boundaries. Through documents analysis, surveys, and interviews, we described marine reserve implementation (governing system) and the social and natural ecosystem-to-be-governed. We analyzed the interactions and the connections between the marine reserve and other spatially explicit conservation and/or management measures existing in the area and influencing management outcomes and governance. A top-down approach with poor stakeholder involvement characterized the implementation process. The marine reserve is highly connected with other spatially explicit measures and with a wider social-ecological system through various ecological processes and socio-economic interactions. Current institutional interactions with positive effects on the management and governance are scarce, although several potential interactions may be developed. For the study area, any management action must recognize interferences from outside conditions and consider some of them (e.g., ecotourism management) as cross-cutting actions for the entire social-ecological system. We consider that institutional interactions and the development of social networks are opportunities to any collective effort aiming to improve governance of Islas Choros-Damas marine reserve. Communication of connections and interactions between marine protected areas and the wider social-ecological system (as described in this study) is proposed as a strategy to improve stakeholder participation in Chilean marine protected areas.

Spatially explicit simulation of hydrologically controlled carbon and nitrogen cycles and associated feedback mechanisms in a boreal ecosystem

NASA Astrophysics Data System (ADS)

Govind, Ajit; Chen, Jing Ming; Ju, Weimin

2009-06-01

Ecosystem models that simulate biogeochemical processes usually ignore hydrological controls that govern them. It is quite possible that topographically driven water fluxes significantly influence the spatial distribution of C sources and sinks because of their large contribution to the local water balance. To investigate this, we simulated biogeochemical processes along with the associated feedback mechanisms in a boreal ecosystem using a spatially explicit hydroecological model, boreal ecosystem productivity simulator (BEPS)-TerrainLab V2.0, that has a tight coupling of ecophysiological, hydrological, and biogeochemical processes. First, the simulated dynamics of snowpack, soil temperature, net ecosystem productivity (NEP), and total ecosystem respiration (TER) were validated with high-frequency measurements for 2 years. The model was able to explain 80% of the variability in NEP and 84% of the variability in TER. Further, we investigated the influence of topographically driven subsurface base flow on soil C and N cycling and on the spatiotemporal patterns of C sources and sinks using three hydrological modeling scenarios that differed in hydrological conceptualizations. In general, the scenarios that had nonexplicit hydrological representation overestimated NEP, as opposed to the scenario that had an explicit (realistic) representation. The key processes controlling the NEP differences were attributed to the combined effects of variations in photosynthesis (due to changes in stomatal conductance and nitrogen (N) availability), heterotrophic respiration, and autotrophic respiration, all of which occur simultaneously affecting NEP. Feedback relationships were also found to exacerbate the differences. We identified six types of NEP differences (biases), of which the most commonly found was due to an underestimation of the existing C sources, highlighting the vulnerability of regional-scale ecosystem models that ignore hydrological processes.

Analyzing key constraints to biogas production from crop residues and manure in the EU-A spatially explicit model.

PubMed

Einarsson, Rasmus; Persson, U Martin

2017-01-01

This paper presents a spatially explicit method for making regional estimates of the potential for biogas production from crop residues and manure, accounting for key technical, biochemical, environmental and economic constraints. Methods for making such estimates are important as biofuels from agricultural residues are receiving increasing policy support from the EU and major biogas producers, such as Germany and Italy, in response to concerns over unintended negative environmental and social impacts of conventional biofuels. This analysis comprises a spatially explicit estimate of crop residue and manure production for the EU at 250 m resolution, and a biogas production model accounting for local constraints such as the sustainable removal of residues, transportation of substrates, and the substrates' biochemical suitability for anaerobic digestion. In our base scenario, the EU biogas production potential from crop residues and manure is about 0.7 EJ/year, nearly double the current EU production of biogas from agricultural substrates, most of which does not come from residues or manure. An extensive sensitivity analysis of the model shows that the potential could easily be 50% higher or lower, depending on the stringency of economic, technical and biochemical constraints. We find that the potential is particularly sensitive to constraints on the substrate mixtures' carbon-to-nitrogen ratio and dry matter concentration. Hence, the potential to produce biogas from crop residues and manure in the EU depends to large extent on the possibility to overcome the challenges associated with these substrates, either by complementing them with suitable co-substrates (e.g. household waste and energy crops), or through further development of biogas technology (e.g. pretreatment of substrates and recirculation of effluent).

Interactions Between Spatially Explicit Conservation and Management Measures: Implications for the Governance of Marine Protected Areas

NASA Astrophysics Data System (ADS)

Cárcamo, P. Francisco; Gaymer, Carlos F.

2013-12-01

Marine protected areas are not established in an institutional and governance vacuum and managers should pay attention to the wider social-ecological system in which they are immersed. This article examines Islas Choros-Damas Marine Reserve, a small marine protected area located in a highly productive and biologically diverse coastal marine ecosystem in northern Chile, and the interactions between human, institutional, and ecological dimensions beyond those existing within its boundaries. Through documents analysis, surveys, and interviews, we described marine reserve implementation (governing system) and the social and natural ecosystem-to-be-governed. We analyzed the interactions and the connections between the marine reserve and other spatially explicit conservation and/or management measures existing in the area and influencing management outcomes and governance. A top-down approach with poor stakeholder involvement characterized the implementation process. The marine reserve is highly connected with other spatially explicit measures and with a wider social-ecological system through various ecological processes and socio-economic interactions. Current institutional interactions with positive effects on the management and governance are scarce, although several potential interactions may be developed. For the study area, any management action must recognize interferences from outside conditions and consider some of them (e.g., ecotourism management) as cross-cutting actions for the entire social-ecological system. We consider that institutional interactions and the development of social networks are opportunities to any collective effort aiming to improve governance of Islas Choros-Damas marine reserve. Communication of connections and interactions between marine protected areas and the wider social-ecological system (as described in this study) is proposed as a strategy to improve stakeholder participation in Chilean marine protected areas.

Impact of jamming on collective cell migration

NASA Astrophysics Data System (ADS)

Nnetu, Kenechukwu David; Knorr, Melanie; Pawlizak, Steve; Fuhs, Thomas; Zink, Mareike; KäS, Josef A.

2012-02-01

Multi-cellular migration plays an important role in physiological processes such as embryogenesis, cancer metastasis and tissue repair. During migration, single cells undergo cycles of extension, adhesion and retraction resulting in morphological changes. In a confluent monolayer, there are inter-cellular interactions and crowding, however, the impact of these interactions on the dynamics and elasticity of the monolayer at the multi-cellular and single cell level is not well understood. Here we study the dynamics of a confluent epithelial monolayer by simultaneously measuring cell motion at the multi-cellular and single cell level for various cell densities and tensile elasticity. At the multi-cellular level, the system exhibited spatial kinetic transitions from isotropic to anisotropic migration on long times and the velocity of the monolayer decreased with increasing cell density. Moreover, the dynamics was spatially and temporally heterogeneous. Interestingly, the dynamics was also heterogeneous in wound-healing assays and the correlation length was fitted by compressed exponential. On the single cell scale, we observed transient caging effects with increasing cage rearrangement times as the system age due to an increase in density. Also, the density dependent elastic modulus of the monolayer scaled as a weak power law. Together, these findings suggest that caging effects at the single cell level initiates a slow and heterogeneous dynamics at the multi-cellular level which is similar to the glassy dynamics of deformable colloidal systems.

The Airborne Measurements of Methane Fluxes (AIRMETH) Arctic Campaign (Invited)

NASA Astrophysics Data System (ADS)

Serafimovich, A.; Metzger, S.; Hartmann, J.; Kohnert, K.; Sachs, T.

2013-12-01

One of the most pressing questions with regard to climate feedback processes in a warming Arctic is the regional-scale methane release from Arctic permafrost areas. The Airborne Measurements of Methane Fluxes (AIRMETH) campaign is designed to quantitatively and spatially explicitly address this question. Ground-based eddy covariance (EC) measurements provide continuous in-situ observations of the surface-atmosphere exchange of methane. However, these observations are rare in the Arctic permafrost zone and site selection is bound by logistical constraints among others. Consequently, these observations cover only small areas that are not necessarily representative of the region of interest. Airborne measurements can overcome this limitation by covering distances of hundreds of kilometers over time periods of a few hours. Here, we present the potential of environmental response functions (ERFs) for quantitatively linking methane flux observations in the atmospheric surface layer to meteorological and biophysical drivers in the flux footprints. For this purpose thousands of kilometers of AIRMETH data across the Alaskan North Slope are utilized, with the aim to extrapolate the airborne EC methane flux observations to the entire North Slope. The data were collected aboard the research aircraft POLAR 5, using its turbulence nose boom and fast response methane and meteorological sensors. After thorough data pre-processing, Reynolds averaging is used to derive spatially integrated fluxes. To increase spatial resolution and to derive ERFs, we then use wavelet transforms of the original high-frequency data. This enables much improved spatial discretization of the flux observations, and the quantification of continuous and biophysically relevant land cover properties in the flux footprint of each observation. A machine learning technique is then employed to extract and quantify the functional relationships between the methane flux observations and the meteorological and biophysical drivers in the flux footprints. Lastly, the resulting ERFs are used to extrapolate the methane release over spatio-temporally explicit grids of the Alaskan North Slope. Metzger et al. (2013) have demonstrated the efficacy of this technique for regionalizing airborne EC heat flux observations to within an accuracy of ≤18% and a precision of ≤5%. Here, we show for the first time results from applying the ERF procedure to airborne methane EC measurements, and report its potential for spatio-temporally explicit inventories of the regional-scale methane exchange. References: Metzger, S., Junkermann, W., Mauder, M., Butterbach-Bahl, K., Trancón y Widemann, B., Neidl, F., Schäfer, K., Wieneke, S., Zheng, X. H., Schmid, H. P., and Foken, T.: Spatially explicit regionalization of airborne flux measurements using environmental response functions, Biogeosciences, 10, 2193-2217, doi:10.5194/bg-10-2193-2013, 2013.

Plant-Pathogen Effectors: Cellular Probes Interfering with Plant Defenses in Spatial and Temporal Manners

PubMed Central

Toruño, Tania Y.; Stergiopoulos, Ioannis; Coaker, Gitta

2017-01-01

Plants possess large arsenals of immune receptors capable of recognizing all pathogen classes. To cause disease, pathogenic organisms must be able to overcome physical barriers, suppress or evade immune perception, and derive nutrients from host tissues. Consequently, to facilitate some of these processes, pathogens secrete effector proteins that promote colonization. This review covers recent advances in the field of effector biology, focusing on conserved cellular processes targeted by effectors from diverse pathogens. The ability of effectors to facilitate pathogen entry into the host interior, suppress plant immune perception, and alter host physiology for pathogen benefit is discussed. Pathogens also deploy effectors in a spatial and temporal manner, depending on infection stage. Recent advances have also enhanced our understanding of effectors acting in specific plant organs and tissues. Effectors are excellent cellular probes that facilitate insight into biological processes as well as key points of vulnerability in plant immune signaling networks. PMID:27359369

Predicting Fish Growth Potential and Identifying Water Quality Constraints: A Spatially-Explicit Bioenergetics Approach

NASA Astrophysics Data System (ADS)

Budy, Phaedra; Baker, Matthew; Dahle, Samuel K.

2011-10-01

Anthropogenic impairment of water bodies represents a global environmental concern, yet few attempts have successfully linked fish performance to thermal habitat suitability and fewer have distinguished co-varying water quality constraints. We interfaced fish bioenergetics, field measurements, and Thermal Remote Imaging to generate a spatially-explicit, high-resolution surface of fish growth potential, and next employed a structured hypothesis to detect relationships among measures of fish performance and co-varying water quality constraints. Our thermal surface of fish performance captured the amount and spatial-temporal arrangement of thermally-suitable habitat for three focal species in an extremely heterogeneous reservoir, but interpretation of this pattern was initially confounded by seasonal covariation of water residence time and water quality. Subsequent path analysis revealed that in terms of seasonal patterns in growth potential, catfish and walleye responded to temperature, positively and negatively, respectively; crappie and walleye responded to eutrophy (negatively). At the high eutrophy levels observed in this system, some desired fishes appear to suffer from excessive cultural eutrophication within the context of elevated temperatures whereas others appear to be largely unaffected or even enhanced. Our overall findings do not lead to the conclusion that this system is degraded by pollution; however, they do highlight the need to use a sensitive focal species in the process of determining allowable nutrient loading and as integrators of habitat suitability across multiple spatial and temporal scales. We provide an integrated approach useful for quantifying fish growth potential and identifying water quality constraints on fish performance at spatial scales appropriate for whole-system management.

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.

Research on the decision-making model of land-use spatial optimization

NASA Astrophysics Data System (ADS)

He, Jianhua; Yu, Yan; Liu, Yanfang; Liang, Fei; Cai, Yuqiu

2009-10-01

Using the optimization result of landscape pattern and land use structure optimization as constraints of CA simulation results, a decision-making model of land use spatial optimization is established coupled the landscape pattern model with cellular automata to realize the land use quantitative and spatial optimization simultaneously. And Huangpi district is taken as a case study to verify the rationality of the model.

Multi-scale and multi-physics simulations using the multi-fluid plasma model

DTIC Science & Technology

2017-04-25

small The simulation uses 512 second-order elements Bz = 1.0, Te = Ti = 0.01, ui = ue = 0 ne = ni = 1.0 + e−10(x−6) 2 Baboolal, Math . and Comp. Sim. 55...DISTRIBUTION Clearance No. 17211 23 / 31 SUMMARY The blended finite element method (BFEM) is presented DG spatial discretization with explicit Runge...Kutta (i+, n) CG spatial discretization with implicit Crank-Nicolson (e−, fileds) DG captures shocks and discontinuities CG is efficient and robust for

A spatially explicit model for estimating risks of pesticide exposure to bird populations

EPA Science Inventory

Pesticides are used widely in US agriculture and may affect non-target organisms, including birds. Some pesticide classes (e.g., acetylcholinesterase inhibitors) are known or suspected to cause direct mortality to birds, while others (e.g., synthetic pyrethroids, neonicotinoids) ...

Urban watershed modeling in Seattle, Washington using VELMA – a spatially explicit ecohydrological watershed model

EPA Science Inventory

Urban watersheds are notoriously difficult to model due to their complex, small-scale combinations of landscape and land use characteristics including impervious surfaces that ultimately affect the hydrologic system. We utilized EPA’s Visualizing Ecosystem Land Management A...

MODELING THE EFFECT OF STREAM NETWORK CHARACTERISTICS AND JUVENILE MOVEMENT ON COHO SALMON

EPA Science Inventory

Simulation modeling can be a valuable tool for improving our scientific understanding of the mechanisms that affect fish abundance and sustainability. Spatially explicit models, in particular, can be used to study interactions between fish biology and spatiotemporal habitat patt...

Global and time-resolved monitoring of crop photosynthesis with chlorophyll fluorescence

USDA-ARS?s Scientific Manuscript database

Global monitoring of agricultural productivity is critical in a world under a continuous increase of food demand. Here we have used new spaceborne retrievals of chlorophyll fluorescence, an emission quantity intrinsically linked to photosynthesis, to derive spatially explicit photosynthetic uptake r...

Evaluation of NASA satellite- and assimilation model-derived long-term daily temperature date over the continental US

USDA-ARS?s Scientific Manuscript database

Agricultural research increasingly is expected to provide precise, quantitative information with an explicit geographic coverage. Limited availability of continuous daily meteorological records often constrains efforts to provide such information through integrated use of simulation models, spatial ...

Landuse and agricultural management practice web-service (LAMPS) for agroecosystem modeling and conservation planning

USDA-ARS?s Scientific Manuscript database

Agroecosystem models and conservation planning tools require spatially and temporally explicit input data about agricultural management operations. The USDA Natural Resources Conservation Service is developing a Land Management and Operation Database (LMOD) which contains potential model input, howe...

Modular and Spatially Explicit: A Novel Approach to System Dynamics

EPA Science Inventory

The Open Modeling Environment (OME) is an open-source System Dynamics (SD) simulation engine which has been created as a joint project between Oregon State University and the US Environmental Protection Agency. It is designed around a modular implementation, and provides a standa...

Simulating natural selection in landscape genetics

Treesearch

E. L. Landguth; S. A. Cushman; N. Johnson

2012-01-01

Linking landscape effects to key evolutionary processes through individual organism movement and natural selection is essential to provide a foundation for evolutionary landscape genetics. Of particular importance is determining how spatially- explicit, individual-based models differ from classic population genetics and evolutionary ecology models based on ideal...

Spatially Explicit Life Cycle Assessment of Biofuel Feedstock Production

EPA Science Inventory

Biofuels derived from renewable resources have gained increased research and development priority due to increasing energy demand and national security concerns. In the US, the Energy Independence and Security Act (EISA) of 2007 mandated the annual production of 56.8 billion L of...

Skyshine study for next generation of fusion devices

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

Gohar, Y.; Yang, S.

1987-02-01

A shielding analysis for next generation of fusion devices (ETR/INTOR) was performed to study the dose equivalent outside the reactor building during operation including the contribution from neutrons and photons scattered back by collisions with air nuclei (skyshine component). Two different three-dimensional geometrical models for a tokamak fusion reactor based on INTOR design parameters were developed for this study. In the first geometrical model, the reactor geometry and the spatial distribution of the deuterium-tritium neutron source were simplified for a parametric survey. The second geometrical model employed an explicit representation of the toroidal geometry of the reactor chamber and themore » spatial distribution of the neutron source. The MCNP general Monte Carlo code for neutron and photon transport was used to perform all the calculations. The energy distribution of the neutron source was used explicitly in the calculations with ENDF/B-V data. The dose equivalent results were analyzed as a function of the concrete roof thickness of the reactor building and the location outside the reactor building.« less

MOAB: a spatially explicit, individual-based expert system for creating animal foraging models

USGS Publications Warehouse

Carter, J.; Finn, John T.

1999-01-01

We describe the development, structure, and corroboration process of a simulation model of animal behavior (MOAB). MOAB can create spatially explicit, individual-based animal foraging models. Users can create or replicate heterogeneous landscape patterns, and place resources and individual animals of a goven species on that landscape to simultaneously simulate the foraging behavior of multiple species. The heuristic rules for animal behavior are maintained in a user-modifiable expert system. MOAB can be used to explore hypotheses concerning the influence of landscape patttern on animal movement and foraging behavior. A red fox (Vulpes vulpes L.) foraging and nest predation model was created to test MOAB's capabilities. Foxes were simulated for 30-day periods using both expert system and random movement rules. Home range size, territory formation and other available simulation studies. A striped skunk (Mephitis mephitis L.) model also was developed. The expert system model proved superior to stochastic in respect to territory formation, general movement patterns and home range size.

A spatially explicit model for an Allee effect: why wolves recolonize so slowly in Greater Yellowstone.

PubMed

Hurford, Amy; Hebblewhite, Mark; Lewis, Mark A

2006-11-01

A reduced probability of finding mates at low densities is a frequently hypothesized mechanism for a component Allee effect. At low densities dispersers are less likely to find mates and establish new breeding units. However, many mathematical models for an Allee effect do not make a distinction between breeding group establishment and subsequent population growth. Our objective is to derive a spatially explicit mathematical model, where dispersers have a reduced probability of finding mates at low densities, and parameterize the model for wolf recolonization in the Greater Yellowstone Ecosystem (GYE). In this model, only the probability of establishing new breeding units is influenced by the reduced probability of finding mates at low densities. We analytically and numerically solve the model to determine the effect of a decreased probability in finding mates at low densities on population spread rate and density. Our results suggest that a reduced probability of finding mates at low densities may slow recolonization rate.

Damping efficiency of the Tchamwa-Wielgosz explicit dissipative scheme under instantaneous loading conditions

NASA Astrophysics Data System (ADS)

Mahéo, Laurent; Grolleau, Vincent; Rio, Gérard

2009-11-01

To deal with dynamic and wave propagation problems, dissipative methods are often used to reduce the effects of the spurious oscillations induced by the spatial and time discretization procedures. Among the many dissipative methods available, the Tchamwa-Wielgosz (TW) explicit scheme is particularly useful because it damps out the spurious oscillations occurring in the highest frequency domain. The theoretical study performed here shows that the TW scheme is decentered to the right, and that the damping can be attributed to a nodal displacement perturbation. The FEM study carried out using instantaneous 1-D and 3-D compression loads shows that it is useful to display the damping versus the number of time steps in order to obtain a constant damping efficiency whatever the size of element used for the regular meshing. A study on the responses obtained with irregular meshes shows that the TW scheme is only slightly sensitive to the spatial discretization procedure used. To cite this article: L. Mahéo et al., C. R. Mecanique 337 (2009).

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.

How Effective Are Biodiversity Conservation Payments in Mexico?

PubMed Central

Costedoat, Sébastien; Corbera, Esteve; Ezzine-de-Blas, Driss; Honey-Rosés, Jordi; Baylis, Kathy; Castillo-Santiago, Miguel Angel

2015-01-01

We assess the additional forest cover protected by 13 rural communities located in the southern state of Chiapas, Mexico, as a result of the economic incentives received through the country's national program of payments for biodiversity conservation. We use spatially explicit data at the intra-community level to define a credible counterfactual of conservation outcomes. We use covariate-matching specifications associated with spatially explicit variables and difference-in-difference estimators to determine the treatment effect. We estimate that the additional conservation represents between 12 and 14.7 percent of forest area enrolled in the program in comparison to control areas. Despite this high degree of additionality, we also observe lack of compliance in some plots participating in the PES program. This lack of compliance casts doubt on the ability of payments alone to guarantee long-term additionality in context of high deforestation rates, even with an augmented program budget or extension of participation to communities not yet enrolled. PMID:25807118

Tracing global supply chains to air pollution hotspots

NASA Astrophysics Data System (ADS)

Moran, Daniel; Kanemoto, Keiichiro

2016-09-01

While high-income countries have made significant strides since the 1970s in improving air quality, air pollution continues to rise in many developing countries and the world as a whole. A significant share of the pollution burden in developing countries can be attributed to production for export to consumers in high-income nations. However, it remains a challenge to quantify individual actors’ share of responsibility for pollution, and to involve parties other than primary emitters in cleanup efforts. Here we present a new spatially explicit modeling approach to link SO2, NO x , and PM10 severe emissions hotspots to final consumers via global supply chains. These maps show developed countries reducing their emissions domestically but driving new pollution hotspots in developing countries. This is also the first time a spatially explicit footprint inventory has been established. Linking consumers and supply chains to emissions hotspots creates opportunities for other parties to participate alongside primary emitters and local regulators in pollution abatement efforts.

On the role of attention in generating explicit awareness of contingent relations: evidence from spatial priming.

PubMed

Fiacconi, Chris M; Milliken, Bruce

2011-12-01

In a series of four experiments, we examine the hypothesis that selective attention is crucial for the generation of conscious knowledge of contingency information. We investigated this question using a spatial priming task in which participants were required to localize a target letter in a probe display. In Experiment 1, participants kept track of the frequency with which the predictive letter in the prime appeared in various locations. This manipulation had a negligible impact on contingency awareness. Subsequent experiments requiring participants to attend to features (color, location) of the predictive letter increased contingency awareness somewhat, but there remained a large proportion of individuals who remained unaware of the strong contingency. Together the results of our experiments suggest that the construct of attention does not fully capture the processes that lead to contingency awareness, and suggest a critical role for bottom-up feature integration in explicit contingency learning. Copyright © 2011 Elsevier Inc. All rights reserved.

Excellent approach to modeling urban expansion by fuzzy cellular automata: agent base model

NASA Astrophysics Data System (ADS)

Khajavigodellou, Yousef; Alesheikh, Ali A.; Mohammed, Abdulrazak A. S.; Chapi, Kamran

2014-09-01

Recently, the interaction between humans and their environment is the one of important challenges in the world. Landuse/ cover change (LUCC) is a complex process that includes actors and factors at different social and spatial levels. The complexity and dynamics of urban systems make the applicable practice of urban modeling very difficult. With the increased computational power and the greater availability of spatial data, micro-simulation such as the agent based and cellular automata simulation methods, has been developed by geographers, planners, and scholars, and it has shown great potential for representing and simulating the complexity of the dynamic processes involved in urban growth and land use change. This paper presents Fuzzy Cellular Automata in Geospatial Information System and remote Sensing to simulated and predicted urban expansion pattern. These FCA-based dynamic spatial urban models provide an improved ability to forecast and assess future urban growth and to create planning scenarios, allowing us to explore the potential impacts of simulations that correspond to urban planning and management policies. A fuzzy inference guided cellular automata approach. Semantic or linguistic knowledge on Land use change is expressed as fuzzy rules, based on which fuzzy inference is applied to determine the urban development potential for each pixel. The model integrates an ABM (agent-based model) and FCA (Fuzzy Cellular Automata) to investigate a complex decision-making process and future urban dynamic processes. Based on this model rapid development and green land protection under the influences of the behaviors and decision modes of regional authority agents, real estate developer agents, resident agents and non- resident agents and their interactions have been applied to predict the future development patterns of the Erbil metropolitan region.

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.

Extended Maptree: a Representation of Fine-Grained Topology and Spatial Hierarchy of Bim

NASA Astrophysics Data System (ADS)

Wu, Y.; Shang, J.; Hu, X.; Zhou, Z.

2017-09-01

Spatial queries play significant roles in exchanging Building Information Modeling (BIM) data and integrating BIM with indoor spatial information. However, topological operators implemented for BIM spatial queries are limited to qualitative relations (e.g. touching, intersecting). To overcome this limitation, we propose an extended maptree model to represent the fine-grained topology and spatial hierarchy of indoor spaces. The model is based on a maptree which consists of combinatorial maps and an adjacency tree. Topological relations (e.g., adjacency, incidence, and covering) derived from BIM are represented explicitly and formally by extended maptrees, which can facilitate the spatial queries of BIM. To construct an extended maptree, we first use a solid model represented by vertical extrusion and boundary representation to generate the isolated 3-cells of combinatorial maps. Then, the spatial relationships defined in IFC are used to sew them together. Furthermore, the incremental edges of extended maptrees are labeled as removed 2-cells. Based on this, we can merge adjacent 3-cells according to the spatial hierarchy of IFC.

A coupled vegetation/sediment transport model for dryland environments

NASA Astrophysics Data System (ADS)

Mayaud, Jerome R.; Bailey, Richard M.; Wiggs, Giles F. S.

2017-04-01

Dryland regions are characterized by patchy vegetation, erodible surfaces, and erosive aeolian processes. Understanding how these constituent factors interact and shape landscape evolution is critical for managing potential environmental and anthropogenic impacts in drylands. However, modeling wind erosion on partially vegetated surfaces is a complex problem that has remained challenging for researchers. We present the new, coupled cellular automaton Vegetation and Sediment TrAnsport (ViSTA) model, which is designed to address fundamental questions about the development of arid and semiarid landscapes in a spatially explicit way. The technical aspects of the ViSTA model are described, including a new method for directly imposing oblique wind and transport directions onto a cell-based domain. Verification tests for the model are reported, including stable state solutions, the impact of drought and fire stress, wake flow dynamics, temporal scaling issues, and the impact of feedbacks between sediment movement and vegetation growth on landscape morphology. The model is then used to simulate an equilibrium nebkha dune field, and the resultant bed forms are shown to have very similar size and spacing characteristics to nebkhas observed in the Skeleton Coast, Namibia. The ViSTA model is a versatile geomorphological tool that could be used to predict threshold-related transitions in a range of dryland ecogeomorphic systems.

Learning STEM Through Integrative Visual Representations

NASA Astrophysics Data System (ADS)

Virk, Satyugjit Singh

Previous cognitive models of memory have not comprehensively taken into account the internal cognitive load of chunking isolated information and have emphasized the external cognitive load of visual presentation only. Under the Virk Long Term Working Memory Multimedia Model of cognitive load, drawing from the Cowan model, students presented with integrated animations of the key neural signal transmission subcomponents where the interrelationships between subcomponents are visually and verbally explicit, were hypothesized to perform significantly better on free response and diagram labeling questions, than students presented with isolated animations of these subcomponents. This is because the internal attentional cognitive load of chunking these concepts is greatly reduced and hence the overall cognitive load is less for the integrated visuals group than the isolated group, despite the higher external load for the integrated group of having the interrelationships between subcomponents presented explicitly. Experiment 1 demonstrated that integrating the subcomponents of the neuron significantly enhanced comprehension of the interconnections between cellular subcomponents and approached significance for enhancing comprehension of the layered molecular correlates of the cellular structures and their interconnections. Experiment 2 corrected time on task confounds from Experiment 1 and focused on the cellular subcomponents of the neuron only. Results from the free response essay subcomponent subscores did demonstrate significant differences in favor of the integrated group as well as some evidence from the diagram labeling section. Results from free response, short answer and What-If (problem solving), and diagram labeling detailed interrelationship subscores demonstrated the integrated group did indeed learn the extra material they were presented with. This data demonstrating the integrated group learned the extra material they were presented with provides some initial support for the assertion that chunking mediated the greater gains in learning for the neural subcomponent concepts over the control.

Auditory Spatial Attention Representations in the Human Cerebral Cortex

PubMed Central

Kong, Lingqiang; Michalka, Samantha W.; Rosen, Maya L.; Sheremata, Summer L.; Swisher, Jascha D.; Shinn-Cunningham, Barbara G.; Somers, David C.

2014-01-01

Auditory spatial attention serves important functions in auditory source separation and selection. Although auditory spatial attention mechanisms have been generally investigated, the neural substrates encoding spatial information acted on by attention have not been identified in the human neocortex. We performed functional magnetic resonance imaging experiments to identify cortical regions that support auditory spatial attention and to test 2 hypotheses regarding the coding of auditory spatial attention: 1) auditory spatial attention might recruit the visuospatial maps of the intraparietal sulcus (IPS) to create multimodal spatial attention maps; 2) auditory spatial information might be encoded without explicit cortical maps. We mapped visuotopic IPS regions in individual subjects and measured auditory spatial attention effects within these regions of interest. Contrary to the multimodal map hypothesis, we observed that auditory spatial attentional modulations spared the visuotopic maps of IPS; the parietal regions activated by auditory attention lacked map structure. However, multivoxel pattern analysis revealed that the superior temporal gyrus and the supramarginal gyrus contained significant information about the direction of spatial attention. These findings support the hypothesis that auditory spatial information is coded without a cortical map representation. Our findings suggest that audiospatial and visuospatial attention utilize distinctly different spatial coding schemes. PMID:23180753

Modeling animal movements using stochastic differential equations

Treesearch

Haiganoush K. Preisler; Alan A. Ager; Bruce K. Johnson; John G. Kie

2004-01-01

We describe the use of bivariate stochastic differential equations (SDE) for modeling movements of 216 radiocollared female Rocky Mountain elk at the Starkey Experimental Forest and Range in northeastern Oregon. Spatially and temporally explicit vector fields were estimated using approximating difference equations and nonparametric regression techniques. Estimated...

COMPARING ECOLOGICALLY SCALED LANDSCAPE INDICES WITH A SPATIALLY EXPLICIT POPULATION MODEL

EPA Science Inventory

Vos et al. (2001) proposed a class of landscape indices they called ecologically scaled. By this they meant that the indices incorporate species-specific characteristics that are assumed to be important for population viability. I used their two ideas of species carrying capaci...

PATTERNS AND CONTROLS OF DISSOLVED ORGANIC MATTER EXPORT BY MAJOR RIVERS: A NEW SEASONAL, SPATIALLY EXPLICIT, GLOBAL MODEL

EPA Science Inventory

River-derived dissolved organic matter (DOM) influences metabolism, light attenuation, and bioavailability of metals and nutrients in coastal ecosystems. Recent work suggests that DOM concentrations in surface waters vary seasonally because different organic matter pools are mobi...

Spatially-explicit modelling model for assessing wild dog control strategies in Western Australia

EPA Science Inventory

Large predators can significantly impact livestock industries. In Australia, wild dogs (Canis lupus familiaris, Canis lupus dingo, and hybrids) cause economic losses of more than AUD $40M annually. Landscape-scale exclusion fencing coupled with lethal techniques is a widely pract...

A Spatially-Explicit Technique for Evaluation of Alternative Scenarios in the Context of Ecosystem Goods and Services

EPA Science Inventory

Ecosystems contribute to maintaining human well-being directly through provision of goods and indirectly through provision of services that support clean water, clean air, flood protection and atmospheric stability. Transparently accounting for biophysical attributes from which h...

Estimating uncertainty in map intersections

Treesearch

Ronald E. McRoberts; Mark A. Hatfield; Susan J. Crocker

2009-01-01

Traditionally, natural resource managers have asked the question "How much?" and have received sample-based estimates of resource totals or means. Increasingly, however, the same managers are now asking the additional question "Where?" and are expecting spatially explicit answers in the form of maps. Recent development of natural resource databases...

How environmental justice patterns are shaped by place: terrain and tree canopy in Cincinnati, Ohio, USA

EPA Science Inventory

Understanding the spatial distribution of environmental amenities requires consideration of social and biogeophysical factors, and how they interact to produce patterns of environmental justice or injustice. In this study, we explicitly account for terrain, a key local environmen...

EVALUATING HABITAT AS A SURROGATE FOR POPULATION VIABILITY USING A SPATIALLY EXPLICIT POPULATION MODEL

EPA Science Inventory

Because data for conservation planning are always limited, surrogates are often substituted for intractable measurements such as species richness or population viability. We examined the ability of habitat quality to act as a surrogate for population performance for both Red-sho...

The National Atlas of Ecosystem Services: Spatially Explicit Characterization of Ecosystem Services

EPA Science Inventory

The US EPA’s Ecosystem Services Research Program (ESRP) is conducting transdisciplinary research to develop tools to enable decision-makers at all levels of governance to proactively conserve ecosystem services. One of these tools is a National Atlas of Ecosystem Services which ...

EnviroAtlas: Exploring Ecosystem Services and Biodiversity Data for the Nation.

EPA Science Inventory

EnviroAtlas is an online collection of interactive tools and spatially explicit data allowing users to explore the many benefits people receive from nature. The purpose of EnviroAtlas is to provide better access to consistently derived ecosystems and socio-economic data to facil...

A spatially and temporally explicit, individual-based, life-history and productivity modeling approach for aquatic species

EPA Science Inventory

Realized life history expression and productivity in aquatic species, and salmonid fishes in particular, is the result of multiple interacting factors including genetics, habitat, growth potential and condition, and the thermal regime individuals experience, both at critical stag...

Assessing Sustainability of Coral Reef Ecosystem Services using a Spatially-Explicit Decision Support Tool

EPA Science Inventory

Forecasting and communicating the potential outcomes of decision options requires support tools that aid in evaluating alternative scenarios in a user-friendly context and that highlight variables relevant to the decision options and valuable stakeholders. Envision is a GIS-base...

A quantum Samaritan’s dilemma cellular automaton

PubMed Central

Situ, Haozhen

2017-01-01

The dynamics of a spatial quantum formulation of the iterated Samaritan’s dilemma game with variable entangling is studied in this work. The game is played in the cellular automata manner, i.e. with local and synchronous interaction. The game is assessed in fair and unfair contests, in noiseless scenarios and with disrupting quantum noise. PMID:28680654

A cellular automaton model of wildfire propagation and extinction

Treesearch

Keith C. Clarke; James A. Brass; Phillip J. Riggan

1994-01-01

We propose a new model to predict the spatial and temporal behavior of wildfires. Fire spread and intensity were simulated using a cellular automaton model. Monte Carlo techniques were used to provide fire risk probabilities for areas where fuel loadings and topography are known. The model assumes predetermined or measurable environmental variables such as wind...

SMART: A Spatially Explicit Bio-Economic Model for Assessing and Managing Demersal Fisheries, with an Application to Italian Trawlers in the Strait of Sicily

PubMed Central

Russo, Tommaso; Parisi, Antonio; Garofalo, Germana; Gristina, Michele; Cataudella, Stefano; Fiorentino, Fabio

2014-01-01

Management of catches, effort and exploitation pattern are considered the most effective measures to control fishing mortality and ultimately ensure productivity and sustainability of fisheries. Despite the growing concerns about the spatial dimension of fisheries, the distribution of resources and fishing effort in space is seldom considered in assessment and management processes. Here we propose SMART (Spatial MAnagement of demersal Resources for Trawl fisheries), a tool for assessing bio-economic feedback in different management scenarios. SMART combines information from different tasks gathered within the European Data Collection Framework on fisheries and is composed of: 1) spatial models of fishing effort, environmental characteristics and distribution of demersal resources; 2) an Artificial Neural Network which captures the relationships among these aspects in a spatially explicit way and uses them to predict resources abundances; 3) a deterministic module which analyzes the size structure of catches and the associated revenues, according to different spatially-based management scenarios. SMART is applied to demersal fishery in the Strait of Sicily, one of the most productive fisheries of the Mediterranean Sea. Three of the main target species are used as proxies for the whole range exploited by trawlers. After training, SMART is used to evaluate different management scenarios, including spatial closures, using a simulation approach that mimics the recent exploitation patterns. Results evidence good model performance, with a noteworthy coherence and reliability of outputs for the different components. Among others, the main finding is that a partial improvement in resource conditions can be achieved by means of nursery closures, even if the overall fishing effort in the area remains stable. Accordingly, a series of strategically designed areas of trawling closures could significantly improve the resource conditions of demersal fisheries in the Strait of Sicily, also supporting sustainable economic returns for fishermen if not applied simultaneously for different species. PMID:24465971

Accounting for small scale heterogeneity in ecohydrologic watershed models

NASA Astrophysics Data System (ADS)

Bhaskar, A.; Fleming, B.; Hogan, D. M.

2016-12-01

Spatially distributed ecohydrologic models are inherently constrained by the spatial resolution of their smallest units, below which land and processes are assumed to be homogenous. At coarse scales, heterogeneity is often accounted for by computing store and fluxes of interest over a distribution of land cover types (or other sources of heterogeneity) within spatially explicit modeling units. However this approach ignores spatial organization and the lateral transfer of water and materials downslope. The challenge is to account both for the role of flow network topology and fine-scale heterogeneity. We present a new approach that defines two levels of spatial aggregation and that integrates spatially explicit network approach with a flexible representation of finer-scale aspatial heterogeneity. Critically, this solution does not simply increase the resolution of the smallest spatial unit, and so by comparison, results in improved computational efficiency. The approach is demonstrated by adapting Regional Hydro-Ecologic Simulation System (RHESSys), an ecohydrologic model widely used to simulate climate, land use, and land management impacts. We illustrate the utility of our approach by showing how the model can be used to better characterize forest thinning impacts on ecohydrology. Forest thinning is typically done at the scale of individual trees, and yet management responses of interest include impacts on watershed scale hydrology and on downslope riparian vegetation. Our approach allow us to characterize the variability in tree size/carbon reduction and water transfers between neighboring trees while still capturing hillslope to watershed scale effects, Our illustrative example demonstrates that accounting for these fine scale effects can substantially alter model estimates, in some cases shifting the impacts of thinning on downslope water availability from increases to decreases. We conclude by describing other use cases that may benefit from this approach including characterizing urban vegetation and storm water management features and their impact on watershed scale hydrology and biogeochemical cycling.

Accounting for small scale heterogeneity in ecohydrologic watershed models

NASA Astrophysics Data System (ADS)

Burke, W.; Tague, C.

2017-12-01

Spatially distributed ecohydrologic models are inherently constrained by the spatial resolution of their smallest units, below which land and processes are assumed to be homogenous. At coarse scales, heterogeneity is often accounted for by computing store and fluxes of interest over a distribution of land cover types (or other sources of heterogeneity) within spatially explicit modeling units. However this approach ignores spatial organization and the lateral transfer of water and materials downslope. The challenge is to account both for the role of flow network topology and fine-scale heterogeneity. We present a new approach that defines two levels of spatial aggregation and that integrates spatially explicit network approach with a flexible representation of finer-scale aspatial heterogeneity. Critically, this solution does not simply increase the resolution of the smallest spatial unit, and so by comparison, results in improved computational efficiency. The approach is demonstrated by adapting Regional Hydro-Ecologic Simulation System (RHESSys), an ecohydrologic model widely used to simulate climate, land use, and land management impacts. We illustrate the utility of our approach by showing how the model can be used to better characterize forest thinning impacts on ecohydrology. Forest thinning is typically done at the scale of individual trees, and yet management responses of interest include impacts on watershed scale hydrology and on downslope riparian vegetation. Our approach allow us to characterize the variability in tree size/carbon reduction and water transfers between neighboring trees while still capturing hillslope to watershed scale effects, Our illustrative example demonstrates that accounting for these fine scale effects can substantially alter model estimates, in some cases shifting the impacts of thinning on downslope water availability from increases to decreases. We conclude by describing other use cases that may benefit from this approach including characterizing urban vegetation and storm water management features and their impact on watershed scale hydrology and biogeochemical cycling.

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.

Do walleye pollock exhibit flexibility in where or when they spawn based on variability in water temperature?

NASA Astrophysics Data System (ADS)

Bacheler, Nathan M.; Ciannelli, Lorenzo; Bailey, Kevin M.; Bartolino, Valerio

2012-06-01

Environmental variability is increasingly recognized as a primary determinant of year-class strength of marine fishes by directly or indirectly influencing egg and larval development, growth, and survival. Here we examined the role of annual water temperature variability in determining when and where walleye pollock (Theragra chalcogramma) spawn in the eastern Bering Sea. Walleye pollock spawning was examined using both long-term ichthyoplankton data (N=19 years), as well as with historical spatially explicit, foreign-reported, commercial catch data occurring during the primary walleye pollock spawning season (February-May) each year (N=22 years in total). We constructed variable-coefficient generalized additive models (GAMs) to relate the spatially explicit egg or adult catch-per-unit-effort (CPUE) to predictor variables including spawning stock biomass, season, position, and water temperature. The adjusted R2 value was 63.1% for the egg CPUE model and 35.5% for the adult CPUE model. Both egg and adult GAMs suggest that spawning progresses seasonally from Bogoslof Island in February and March to Outer Domain waters between the Pribilof and Unimak Islands by May. Most importantly, walleye pollock egg and adult CPUE was predicted to generally increase throughout the study area as mean annual water temperature increased. These results suggest low interannual variability in the spatial and temporal dynamics of walleye pollock spawning regardless of changes in environmental conditions, at least at the spatial scale examined in this study and within the time frame of decades.

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

Modeled and monitored variation in space and time of PCB-153 concentrations in air, sediment, soil and aquatic biota on a European scale.

PubMed

Hauck, Mara; Huijbregts, Mark A J; Hollander, Anne; Hendriks, A Jan; van de Meent, Dik

2010-08-15

We evaluated various modeling options for estimating concentrations of PCB-153 in the environment and in biota across Europe, using a nested multimedia fate model coupled with a bioaccumulation model. The most detailed model set up estimates concentrations in air, soil, fresh water sediment and fresh water biota with spatially explicit environmental characteristics and spatially explicit emissions to air and water in the period 1930-2005. Model performance was evaluated with the root mean square error (RMSE(log)), based on the difference between estimated and measured concentrations. The RMSE(log) was 5.4 for air, 5.6-6.3 for sediment and biota, and 5.5 for soil in the most detailed model scenario. Generally, model estimations tended to underestimate observed values for all compartments, except air. The decline in observed concentrations was also slightly underestimated by the model for the period where measurements were available (1989-2002). Applying a generic model setup with averaged emissions and averaged environmental characteristics, the RMSE(log) increased to 21 for air and 49 for sediment. For soil the RMSE(log) decreased to 3.5. We found that including spatial variation in emissions was most relevant for all compartments, except soil, while including spatial variation in environmental characteristics was less influential. For improving predictions of concentrations in sediment and aquatic biota, including emissions to water was found to be relevant as well. Copyright 2009 Elsevier B.V. All rights reserved.

Factors influencing reporting and harvest probabilities in North American geese

USGS Publications Warehouse

Zimmerman, G.S.; Moser, T.J.; Kendall, W.L.; Doherty, P.F.; White, Gary C.; Caswell, D.F.

2009-01-01

We assessed variation in reporting probabilities of standard bands among species, populations, harvest locations, and size classes of North American geese to enable estimation of unbiased harvest probabilities. We included reward (US10,20,30,50, or100) and control (0) banded geese from 16 recognized goose populations of 4 species: Canada (Branta canadensis), cackling (B. hutchinsii), Ross's (Chen rossii), and snow geese (C. caerulescens). We incorporated spatially explicit direct recoveries and live recaptures into a multinomial model to estimate reporting, harvest, and band-retention probabilities. We compared various models for estimating harvest probabilities at country (United States vs. Canada), flyway (5 administrative regions), and harvest area (i.e., flyways divided into northern and southern sections) scales. Mean reporting probability of standard bands was 0.73 (95 CI 0.690.77). Point estimates of reporting probabilities for goose populations or spatial units varied from 0.52 to 0.93, but confidence intervals for individual estimates overlapped and model selection indicated that models with species, population, or spatial effects were less parsimonious than those without these effects. Our estimates were similar to recently reported estimates for mallards (Anas platyrhynchos). We provide current harvest probability estimates for these populations using our direct measures of reporting probability, improving the accuracy of previous estimates obtained from recovery probabilities alone. Goose managers and researchers throughout North America can use our reporting probabilities to correct recovery probabilities estimated from standard banding operations for deriving spatially explicit harvest probabilities.

A spatial model of white sturgeon rearing habitat in the lower Columbia River, USA

USGS Publications Warehouse

Hatten, J.R.; Parsley, M.J.

2009-01-01

Concerns over the potential effects of in-water placement of dredged materials prompted us to develop a GIS-based model that characterizes in a spatially explicit manner white sturgeon Acipenser transmontanus rearing habitat in the lower Columbia River, USA. The spatial model was developed using water depth, riverbed slope and roughness, fish positions collected in 2002, and Mahalanobis distance (D2). We created a habitat suitability map by identifying a Mahalanobis distance under which >50% of white sturgeon locations occurred in 2002 (i.e., high-probability habitat). White sturgeon preferred relatively moderate to high water depths, and low to moderate riverbed slope and roughness values. The eigenvectors indicated that riverbed slope and roughness were slightly more important than water depth, but all three variables were important. We estimated the impacts that fill might have on sturgeon habitat by simulating the addition of fill to the thalweg, in 3-m increments, and recomputing Mahalanobis distances. Channel filling simulations revealed that up to 9 m of fill would have little impact on high-probability habitat, but 12 and 15 m of fill resulted in habitat declines of ???12% and ???45%, respectively. This is the first spatially explicit predictive model of white sturgeon rearing habitat in the lower Columbia River, and the first to quantitatively predict the impacts of dredging operations on sturgeon habitat. Future research should consider whether water velocity improves the accuracy and specificity of the model, and to assess its applicability to other areas in the Columbia River.

Accounting for system dynamics in reserve design.

PubMed

Leroux, Shawn J; Schmiegelow, Fiona K A; Cumming, Steve G; Lessard, Robert B; Nagy, John

2007-10-01

Systematic conservation plans have only recently considered the dynamic nature of ecosystems. Methods have been developed to incorporate climate change, population dynamics, and uncertainty in reserve design, but few studies have examined how to account for natural disturbance. Considering natural disturbance in reserve design may be especially important for the world's remaining intact areas, which still experience active natural disturbance regimes. We developed a spatially explicit, dynamic simulation model, CONSERV, which simulates patch dynamics and fire, and used it to evaluate the efficacy of hypothetical reserve networks in northern Canada. We designed six networks based on conventional reserve design methods, with different conservation targets for woodland caribou habitat, high-quality wetlands, vegetation, water bodies, and relative connectedness. We input the six reserve networks into CONSERV and tracked the ability of each to maintain initial conservation targets through time under an active natural disturbance regime. None of the reserve networks maintained all initial targets, and some over-represented certain features, suggesting that both effectiveness and efficiency of reserve design could be improved through use of spatially explicit dynamic simulation during the planning process. Spatial simulation models of landscape dynamics are commonly used in natural resource management, but we provide the first illustration of their potential use for reserve design. Spatial simulation models could be used iteratively to evaluate competing reserve designs and select targets that have a higher likelihood of being maintained through time. Such models could be combined with dynamic planning techniques to develop a general theory for reserve design in an uncertain world.

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.

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.

Deep Neural Network for Structural Prediction and Lane Detection in Traffic Scene.

PubMed

Li, Jun; Mei, Xue; Prokhorov, Danil; Tao, Dacheng

2017-03-01

Hierarchical neural networks have been shown to be effective in learning representative image features and recognizing object classes. However, most existing networks combine the low/middle level cues for classification without accounting for any spatial structures. For applications such as understanding a scene, how the visual cues are spatially distributed in an image becomes essential for successful analysis. This paper extends the framework of deep neural networks by accounting for the structural cues in the visual signals. In particular, two kinds of neural networks have been proposed. First, we develop a multitask deep convolutional network, which simultaneously detects the presence of the target and the geometric attributes (location and orientation) of the target with respect to the region of interest. Second, a recurrent neuron layer is adopted for structured visual detection. The recurrent neurons can deal with the spatial distribution of visible cues belonging to an object whose shape or structure is difficult to explicitly define. Both the networks are demonstrated by the practical task of detecting lane boundaries in traffic scenes. The multitask convolutional neural network provides auxiliary geometric information to help the subsequent modeling of the given lane structures. The recurrent neural network automatically detects lane boundaries, including those areas containing no marks, without any explicit prior knowledge or secondary modeling.

Exploring behavior of an unusual megaherbivore: A spatially explicit foraging model of the hippopotamus

USGS Publications Warehouse

Lewison, R.L.; Carter, J.

2004-01-01

Herbivore foraging theories have been developed for and tested on herbivores across a range of sizes. Due to logistical constraints, however, little research has focused on foraging behavior of megaherbivores. Here we present a research approach that explores megaherbivore foraging behavior, and assesses the applicability of foraging theories developed on smaller herbivores to megafauna. With simulation models as reference points for the analysis of empirical data, we investigate foraging strategies of the common hippopotamus (Hippopotamus amphibius). Using a spatially explicit individual based foraging model, we apply traditional herbivore foraging strategies to a model hippopotamus, compare model output, and then relate these results to field data from wild hippopotami. Hippopotami appear to employ foraging strategies that respond to vegetation characteristics, such as vegetation quality, as well as spatial reference information, namely distance to a water source. Model predictions, field observations, and comparisons of the two support that hippopotami generally conform to the central place foraging construct. These analyses point to the applicability of general herbivore foraging concepts to megaherbivores, but also point to important differences between hippopotami and other herbivores. Our synergistic approach of models as reference points for empirical data highlights a useful method of behavioral analysis for hard-to-study megafauna. ?? 2003 Elsevier B.V. All rights reserved.

Analyzing historical land use changes using a Historical Land Use Reconstruction Model: a case study in Zhenlai County, northeastern China

PubMed Central

Yang, Yuanyuan; Zhang, Shuwen; Liu, Yansui; Xing, Xiaoshi; de Sherbinin, Alex

2017-01-01

Historical land use information is essential to understanding the impact of anthropogenic modification of land use/cover on the temporal dynamics of environmental and ecological issues. However, due to a lack of spatial explicitness, complete thematic details and the conversion types for historical land use changes, the majority of historical land use reconstructions do not sufficiently meet the requirements for an adequate model. Considering these shortcomings, we explored the possibility of constructing a spatially-explicit modeling framework (HLURM: Historical Land Use Reconstruction Model). Then a three-map comparison method was adopted to validate the projected reconstruction map. The reconstruction suggested that the HLURM model performed well in the spatial reconstruction of various land-use categories, and had a higher figure of merit (48.19%) than models used in other case studies. The largest land use/cover type in the study area was determined to be grassland, followed by arable land and wetland. Using the three-map comparison, we noticed that the major discrepancies in land use changes among the three maps were as a result of inconsistencies in the classification of land-use categories during the study period, rather than as a result of the simulation model. PMID:28134342

Validating spatiotemporal predictions of an important pest of small grains.

PubMed

Merrill, Scott C; Holtzer, Thomas O; Peairs, Frank B; Lester, Philip J

2015-01-01

Arthropod pests are typically managed using tactics applied uniformly to the whole field. Precision pest management applies tactics under the assumption that within-field pest pressure differences exist. This approach allows for more precise and judicious use of scouting resources and management tactics. For example, a portion of a field delineated as attractive to pests may be selected to receive extra monitoring attention. Likely because of the high variability in pest dynamics, little attention has been given to developing precision pest prediction models. Here, multimodel synthesis was used to develop a spatiotemporal model predicting the density of a key pest of wheat, the Russian wheat aphid, Diuraphis noxia (Kurdjumov). Spatially implicit and spatially explicit models were synthesized to generate spatiotemporal pest pressure predictions. Cross-validation and field validation were used to confirm model efficacy. A strong within-field signal depicting aphid density was confirmed with low prediction errors. Results show that the within-field model predictions will provide higher-quality information than would be provided by traditional field scouting. With improvements to the broad-scale model component, the model synthesis approach and resulting tool could improve pest management strategy and provide a template for the development of spatially explicit pest pressure models. © 2014 Society of Chemical Industry.

Integrating population dynamics into mapping human exposure to seismic hazard

NASA Astrophysics Data System (ADS)

Freire, S.; Aubrecht, C.

2012-11-01

Disaster risk is not fully characterized without taking into account vulnerability and population exposure. Assessment of earthquake risk in urban areas would benefit from considering the variation of population distribution at more detailed spatial and temporal scales, and from a more explicit integration of this improved demographic data with existing seismic hazard maps. In the present work, "intelligent" dasymetric mapping is used to model population dynamics at high spatial resolution in order to benefit the analysis of spatio-temporal exposure to earthquake hazard in a metropolitan area. These night- and daytime-specific population densities are then classified and combined with seismic intensity levels to derive new spatially-explicit four-class-composite maps of human exposure. The presented approach enables a more thorough assessment of population exposure to earthquake hazard. Results show that there are significantly more people potentially at risk in the daytime period, demonstrating the shifting nature of population exposure in the daily cycle and the need to move beyond conventional residence-based demographic data sources to improve risk analyses. The proposed fine-scale maps of human exposure to seismic intensity are mainly aimed at benefiting visualization and communication of earthquake risk, but can be valuable in all phases of the disaster management process where knowledge of population densities is relevant for decision-making.

Graph theory as a proxy for spatially explicit population models in conservation planning.

PubMed

Minor, Emily S; Urban, Dean L

2007-09-01

Spatially explicit population models (SEPMs) are often considered the best way to predict and manage species distributions in spatially heterogeneous landscapes. However, they are computationally intensive and require extensive knowledge of species' biology and behavior, limiting their application in many cases. An alternative to SEPMs is graph theory, which has minimal data requirements and efficient algorithms. Although only recently introduced to landscape ecology, graph theory is well suited to ecological applications concerned with connectivity or movement. This paper compares the performance of graph theory to a SEPM in selecting important habitat patches for Wood Thrush (Hylocichla mustelina) conservation. We use both models to identify habitat patches that act as population sources and persistent patches and also use graph theory to identify patches that act as stepping stones for dispersal. Correlations of patch rankings were very high between the two models. In addition, graph theory offers the ability to identify patches that are very important to habitat connectivity and thus long-term population persistence across the landscape. We show that graph theory makes very similar predictions in most cases and in other cases offers insight not available from the SEPM, and we conclude that graph theory is a suitable and possibly preferable alternative to SEPMs for species conservation in heterogeneous landscapes.

Genetic Algorithm Calibration of Probabilistic Cellular Automata for Modeling Mining Permit Activity

USGS Publications Warehouse

Louis, S.J.; Raines, G.L.

2003-01-01

We use a genetic algorithm to calibrate a spatially and temporally resolved cellular automata to model mining activity on public land in Idaho and western Montana. The genetic algorithm searches through a space of transition rule parameters of a two dimensional cellular automata model to find rule parameters that fit observed mining activity data. Previous work by one of the authors in calibrating the cellular automaton took weeks - the genetic algorithm takes a day and produces rules leading to about the same (or better) fit to observed data. These preliminary results indicate that genetic algorithms are a viable tool in calibrating cellular automata for this application. Experience gained during the calibration of this cellular automata suggests that mineral resource information is a critical factor in the quality of the results. With automated calibration, further refinements of how the mineral-resource information is provided to the cellular automaton will probably improve our model.