Community shifts under climate change: mechanisms at multiple scales.

PubMed

Gornish, Elise S; Tylianakis, Jason M

2013-07-01

Processes that drive ecological dynamics differ across spatial scales. Therefore, the pathways through which plant communities and plant-insect relationships respond to changing environmental conditions are also expected to be scale-dependent. Furthermore, the processes that affect individual species or interactions at single sites may differ from those affecting communities across multiple sites. We reviewed and synthesized peer-reviewed literature to identify patterns in biotic or abiotic pathways underpinning changes in the composition and diversity of plant communities under three components of climate change (increasing temperature, CO2, and changes in precipitation) and how these differ across spatial scales. We also explored how these changes to plants affect plant-insect interactions. The relative frequency of biotic vs. abiotic pathways of climate effects at larger spatial scales often differ from those at smaller scales. Local-scale studies show variable responses to climate drivers, often driven by biotic factors. However, larger scale studies identify changes to species composition and/or reduced diversity as a result of abiotic factors. Differing pathways of climate effects can result from different responses of multiple species, habitat effects, and differing effects of invasions at local vs. regional to global scales. Plant community changes can affect higher trophic levels as a result of spatial or phenological mismatch, foliar quality changes, and plant abundance changes, though studies on plant-insect interactions at larger scales are rare. Climate-induced changes to plant communities will have considerable effects on community-scale trophic exchanges, which may differ from the responses of individual species or pairwise interactions.

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

NASA Astrophysics Data System (ADS)

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

2002-12-01

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

CROSS-SCALE CORRELATIONS AND THE DESIGN AND ANALYSIS OF AVIAN HABITAT SELECTION STUDIES

EPA Science Inventory

It has long been suggested that birds select habitat hierarchically, progressing from coarser to finer spatial scales. This hypothesis, in conjunction with the realization that many organisms likely respond to environmental patterns at multiple spatial scales, has led to a large ...

Quantifying drivers of wild pig movement across multiple spatial and temporal scales.

PubMed

Kay, Shannon L; Fischer, Justin W; Monaghan, Andrew J; Beasley, James C; Boughton, Raoul; Campbell, Tyler A; Cooper, Susan M; Ditchkoff, Stephen S; Hartley, Steve B; Kilgo, John C; Wisely, Samantha M; Wyckoff, A Christy; VerCauteren, Kurt C; Pepin, Kim M

2017-01-01

The movement behavior of an animal is determined by extrinsic and intrinsic factors that operate at multiple spatio-temporal scales, yet much of our knowledge of animal movement comes from studies that examine only one or two scales concurrently. Understanding the drivers of animal movement across multiple scales is crucial for understanding the fundamentals of movement ecology, predicting changes in distribution, describing disease dynamics, and identifying efficient methods of wildlife conservation and management. We obtained over 400,000 GPS locations of wild pigs from 13 different studies spanning six states in southern U.S.A., and quantified movement rates and home range size within a single analytical framework. We used a generalized additive mixed model framework to quantify the effects of five broad predictor categories on movement: individual-level attributes, geographic factors, landscape attributes, meteorological conditions, and temporal variables. We examined effects of predictors across three temporal scales: daily, monthly, and using all data during the study period. We considered both local environmental factors such as daily weather data and distance to various resources on the landscape, as well as factors acting at a broader spatial scale such as ecoregion and season. We found meteorological variables (temperature and pressure), landscape features (distance to water sources), a broad-scale geographic factor (ecoregion), and individual-level characteristics (sex-age class), drove wild pig movement across all scales, but both the magnitude and shape of covariate relationships to movement differed across temporal scales. The analytical framework we present can be used to assess movement patterns arising from multiple data sources for a range of species while accounting for spatio-temporal correlations. Our analyses show the magnitude by which reaction norms can change based on the temporal scale of response data, illustrating the importance of appropriately defining temporal scales of both the movement response and covariates depending on the intended implications of research (e.g., predicting effects of movement due to climate change versus planning local-scale management). We argue that consideration of multiple spatial scales within the same framework (rather than comparing across separate studies post-hoc ) gives a more accurate quantification of cross-scale spatial effects by appropriately accounting for error correlation.

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

PubMed

Rasic, Gordana; Keyghobadi, Nusha

2012-01-01

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

Grains of connectivity: analysis at multiple spatial scales in landscape genetics.

PubMed

Galpern, Paul; Manseau, Micheline; Wilson, Paul

2012-08-01

Landscape genetic analyses are typically conducted at one spatial scale. Considering multiple scales may be essential for identifying landscape features influencing gene flow. We examined landscape connectivity for woodland caribou (Rangifer tarandus caribou) at multiple spatial scales using a new approach based on landscape graphs that creates a Voronoi tessellation of the landscape. To illustrate the potential of the method, we generated five resistance surfaces to explain how landscape pattern may influence gene flow across the range of this population. We tested each resistance surface using a raster at the spatial grain of available landscape data (200 m grid squares). We then used our method to produce up to 127 additional grains for each resistance surface. We applied a causal modelling framework with partial Mantel tests, where evidence of landscape resistance is tested against an alternative hypothesis of isolation-by-distance, and found statistically significant support for landscape resistance to gene flow in 89 of the 507 spatial grains examined. We found evidence that major roads as well as the cumulative effects of natural and anthropogenic disturbance may be contributing to the genetic structure. Using only the original grid surface yielded no evidence for landscape resistance to gene flow. Our results show that using multiple spatial grains can reveal landscape influences on genetic structure that may be overlooked with a single grain, and suggest that coarsening the grain of landcover data may be appropriate for highly mobile species. We discuss how grains of connectivity and related analyses have potential landscape genetic applications in a broad range of systems. © 2012 Blackwell Publishing Ltd.

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

USGS Publications Warehouse

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

2010-01-01

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

Disturbance patterns in a socio-ecological system at multiple scales

Treesearch

G. Zurlini; Kurt H. Riitters; N. Zaccarelli; I. Petrosillo; K.B. Jones; L. Rossi

2006-01-01

Ecological systems with hierarchical organization and non-equilibrium dynamics require multiple-scale analyses to comprehend how a system is structured and to formulate hypotheses about regulatory mechanisms. Characteristic scales in real landscapes are determined by, or at least reflect, the spatial patterns and scales of constraining human interactions with the...

Assessing wildfire risks at multiple spatial scales

Treesearch

Justin Fitch

2008-01-01

In continuation of the efforts to advance wildfire science and develop tools for wildland fire managers, a spatial wildfire risk assessment was carried out using Classification and Regression Tree analysis (CART) and Geographic Information Systems (GIS). The analysis was performed at two scales. The small-scale assessment covered the entire state of New Mexico, while...

Spatial and Temporal Scaling of Thermal Infrared Remote Sensing Data

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Goel, Narendra S.

1995-01-01

Although remote sensing has a central role to play in the acquisition of synoptic data obtained at multiple spatial and temporal scales to facilitate our understanding of local and regional processes as they influence the global climate, the use of thermal infrared (TIR) remote sensing data in this capacity has received only minimal attention. This results from some fundamental challenges that are associated with employing TIR data collected at different space and time scales, either with the same or different sensing systems, and also from other problems that arise in applying a multiple scaled approach to the measurement of surface temperatures. In this paper, we describe some of the more important problems associated with using TIR remote sensing data obtained at different spatial and temporal scales, examine why these problems appear as impediments to using multiple scaled TIR data, and provide some suggestions for future research activities that may address these problems. We elucidate the fundamental concept of scale as it relates to remote sensing and explore how space and time relationships affect TIR data from a problem-dependency perspective. We also describe how linearity and non-linearity observation versus parameter relationships affect the quantitative analysis of TIR data. Some insight is given on how the atmosphere between target and sensor influences the accurate measurement of surface temperatures and how these effects will be compounded in analyzing multiple scaled TIR data. Last, we describe some of the challenges in modeling TIR data obtained at different space and time scales and discuss how multiple scaled TIR data can be used to provide new and important information for measuring and modeling land-atmosphere energy balance processes.

Up, Down, and All Around: Scale-Dependent Spatial Variation in Rocky-Shore Communities of Fildes Peninsula, King George Island, Antarctica

PubMed Central

Valdivia, Nelson; Díaz, María J.; Holtheuer, Jorge; Garrido, Ignacio; Huovinen, Pirjo; Gómez, Iván

2014-01-01

Understanding the variation of biodiversity along environmental gradients and multiple spatial scales is relevant for theoretical and management purposes. Hereby, we analysed the spatial variability in diversity and structure of intertidal and subtidal macrobenthic Antarctic communities along vertical environmental stress gradients and across multiple horizontal spatial scales. Since biotic interactions and local topographic features are likely major factors for coastal assemblages, we tested the hypothesis that fine-scale processes influence the effects of the vertical environmental stress gradients on the macrobenthic diversity and structure. We used nested sampling designs in the intertidal and subtidal habitats, including horizontal spatial scales ranging from few centimetres to 1000s of metres along the rocky shore of Fildes Peninsula, King George Island. In both intertidal and subtidal habitats, univariate and multivariate analyses showed a marked vertical zonation in taxon richness and community structure. These patterns depended on the horizontal spatial scale of observation, as all analyses showed a significant interaction between height (or depth) and the finer spatial scale analysed. Variance and pseudo-variance components supported our prediction for taxon richness, community structure, and the abundance of dominant species such as the filamentous green alga Urospora penicilliformis (intertidal), the herbivore Nacella concinna (intertidal), the large kelp-like Himantothallus grandifolius (subtidal), and the red crustose red alga Lithothamnion spp. (subtidal). We suggest that in coastal ecosystems strongly governed by physical factors, fine-scale processes (e.g. biotic interactions and refugia availability) are still relevant for the structuring and maintenance of the local communities. The spatial patterns found in this study serve as a necessary benchmark to understand the dynamics and adaptation of natural assemblages in response to observed and predicted environmental changes in Antarctica. PMID:24956114

Scaling in cognitive performance reflects multiplicative multifractal cascade dynamics

PubMed Central

Stephen, Damian G.; Anastas, Jason R.; Dixon, James A.

2012-01-01

Self-organized criticality purports to build multi-scaled structures out of local interactions. Evidence of scaling in various domains of biology may be more generally understood to reflect multiplicative interactions weaving together many disparate scales. The self-similarity of power-law scaling entails homogeneity: fluctuations distribute themselves similarly across many spatial and temporal scales. However, this apparent homogeneity can be misleading, especially as it spans more scales. Reducing biological processes to one power-law relationship neglects rich cascade dynamics. We review recent research into multifractality in executive-function cognitive tasks and propose that scaling reflects not criticality but instead interactions across multiple scales and among fluctuations of multiple sizes. PMID:22529819

The relative influence of habitat amount and configuration on genetic structure across multiple spatial scales

PubMed Central

Millette, Katie L; Keyghobadi, Nusha

2015-01-01

Despite strong interest in understanding how habitat spatial structure shapes the genetics of populations, the relative importance of habitat amount and configuration for patterns of genetic differentiation remains largely unexplored in empirical systems. In this study, we evaluate the relative influence of, and interactions among, the amount of habitat and aspects of its spatial configuration on genetic differentiation in the pitcher plant midge, Metriocnemus knabi. Larvae of this species are found exclusively within the water-filled leaves of pitcher plants (Sarracenia purpurea) in a system that is naturally patchy at multiple spatial scales (i.e., leaf, plant, cluster, peatland). Using generalized linear mixed models and multimodel inference, we estimated effects of the amount of habitat, patch size, interpatch distance, and patch isolation, measured at different spatial scales, on genetic differentiation (FST) among larval samples from leaves within plants, plants within clusters, and clusters within peatlands. Among leaves and plants, genetic differentiation appears to be driven by female oviposition behaviors and is influenced by habitat isolation at a broad (peatland) scale. Among clusters, gene flow is spatially restricted and aspects of both the amount of habitat and configuration at the focal scale are important, as is their interaction. Our results suggest that both habitat amount and configuration can be important determinants of genetic structure and that their relative influence is scale dependent. PMID:25628865

The relative influence of habitat amount and configuration on genetic structure across multiple spatial scales.

PubMed

Millette, Katie L; Keyghobadi, Nusha

2015-01-01

Despite strong interest in understanding how habitat spatial structure shapes the genetics of populations, the relative importance of habitat amount and configuration for patterns of genetic differentiation remains largely unexplored in empirical systems. In this study, we evaluate the relative influence of, and interactions among, the amount of habitat and aspects of its spatial configuration on genetic differentiation in the pitcher plant midge, Metriocnemus knabi. Larvae of this species are found exclusively within the water-filled leaves of pitcher plants (Sarracenia purpurea) in a system that is naturally patchy at multiple spatial scales (i.e., leaf, plant, cluster, peatland). Using generalized linear mixed models and multimodel inference, we estimated effects of the amount of habitat, patch size, interpatch distance, and patch isolation, measured at different spatial scales, on genetic differentiation (F ST) among larval samples from leaves within plants, plants within clusters, and clusters within peatlands. Among leaves and plants, genetic differentiation appears to be driven by female oviposition behaviors and is influenced by habitat isolation at a broad (peatland) scale. Among clusters, gene flow is spatially restricted and aspects of both the amount of habitat and configuration at the focal scale are important, as is their interaction. Our results suggest that both habitat amount and configuration can be important determinants of genetic structure and that their relative influence is scale dependent.

Patterns of disturbance at multiple scales in real and simulated landscapes

Treesearch

Giovanni Zurlini; Kurt H. Riitters; Nicola Zaccarelli; Irene Petrosoillo

2007-01-01

We describe a framework to characterize and interpret the spatial patterns of disturbances at multiple scales in socio-ecological systems. Domains of scale are defined in pattern metric space and mapped in geographic space, which can help to understand how anthropogenic disturbances might impact biodiversity through habitat modification. The approach identifies typical...

Vegetation responsees to landscape structure at multiple scales across a Northern Wisconsin, USA, pine barrens landscape

Treesearch

K.D. Brosofske; J. Chen; Thomas R. Crow; S.C. Saunders

1999-01-01

Increasing awareness of the importance of scale and landscape structure to landscape processes and concern about loss of biodiversity has resulted in efforts to understand patterns of biodiversity across multiple scales. We examined plant species distributions and their relationships to landscape structure at varying spatial scales across a pine barrens landscape in...

Executive Order 12898 and Social, Economic, and Sociopolitical Factors Influencing Toxic Release Inventory Facility Location in EPA Region 6: A Multi-Scale Spatial Assessment of Environmental Justice

ERIC Educational Resources Information Center

Moore, Andrea Lisa

2013-01-01

Toxic Release Inventory facilities are among the many environmental hazards shown to create environmental inequities in the United States. This project examined four factors associated with Toxic Release Inventory, specifically, manufacturing facility location at multiple spatial scales using spatial analysis techniques (i.e., O-ring statistic and…

Perspectives of Spatial Scale in a Wildland Forest Epidemic

Treesearch

W.W. Dillon; S.E. Haas; D.M. Rizzo; R.K. Meentemeyer

2014-01-01

The challenge of observing interactions between plant pathogens, their hosts, and environmental heterogeneity across multiple spatial scales commonly limits our ability to understand and manage wildland forest epidemics. Using the forest pathogen Phytophthora ramorum as a case study, we established 20 multiscale field sites to analyze how host-...

Density and nest survival of golden-cheeked warblers: Spatial scale matters

Treesearch

Jennifer L. Reidy; Frank R., III Thompson; Lisa O' Donnell

2017-01-01

Conservation and management plans often rely on indicators such as species occupancy or density to define habitat quality, ignoring factors that influence reproductive success, and potentially limiting conservation achievements. We examined relationships between predicted density and nest survival with environmental features at multiple spatial scales for the golden-...

Spatial Patterns in Water Temperature in Pacific Northwest Rivers: Diversity at Multiple Scales and Potential Influence of Climate Change

NASA Astrophysics Data System (ADS)

Torgersen, C. E.; Fullerton, A.; Lawler, J. J.; Ebersole, J. L.; Leibowitz, S. G.; Steel, E. A.; Beechie, T. J.; Faux, R.

2016-12-01

Understanding spatial patterns in water temperature will be essential for evaluating vulnerability of aquatic biota to future climate and for identifying and protecting diverse thermal habitats. We used high-resolution remotely sensed water temperature data for over 16,000 km of 2nd to 7th-order rivers throughout the Pacific Northwest and California to evaluate spatial patterns of summertime water temperature at multiple spatial scales. We found a diverse and geographically distributed suite of whole-river patterns. About half of rivers warmed asymptotically in a downstream direction, whereas the rest exhibited complex and unique spatial patterns. Patterns were associated with both broad-scale hydroclimatic variables as well as characteristics unique to each basin. Within-river thermal heterogeneity patterns were highly river-specific; across rivers, median size and spacing of cool patches <15 °C were around 250 m. Patches of this size are large enough for juvenile salmon rearing and for resting during migration, and the distance between patches is well within the movement capabilities of both juvenile and adult salmon. We found considerable thermal heterogeneity at fine spatial scales that may be important to fish that would be missed if data were analyzed at coarser scales. We estimated future thermal heterogeneity and concluded that climate change will cause warmer temperatures overall, but that thermal heterogeneity patterns may remain similar in the future for many rivers. We demonstrated considerable spatial complexity in both current and future water temperature, and resolved spatial patterns that could not have been perceived without spatially continuous data.

Imaging multi-scale dynamics in vivo with spiral volumetric optoacoustic tomography

NASA Astrophysics Data System (ADS)

Deán-Ben, X. Luís.; Fehm, Thomas F.; Ford, Steven J.; Gottschalk, Sven; Razansky, Daniel

2017-03-01

Imaging dynamics in living organisms is essential for the understanding of biological complexity. While multiple imaging modalities are often required to cover both microscopic and macroscopic spatial scales, dynamic phenomena may also extend over different temporal scales, necessitating the use of different imaging technologies based on the trade-off between temporal resolution and effective field of view. Optoacoustic (photoacoustic) imaging has been shown to offer the exclusive capability to link multiple spatial scales ranging from organelles to entire organs of small animals. Yet, efficient visualization of multi-scale dynamics remained difficult with state-of-the-art systems due to inefficient trade-offs between image acquisition and effective field of view. Herein, we introduce a spiral volumetric optoacoustic tomography (SVOT) technique that provides spectrally-enriched high-resolution optical absorption contrast across multiple spatio-temporal scales. We demonstrate that SVOT can be used to monitor various in vivo dynamics, from video-rate volumetric visualization of cardiac-associated motion in whole organs to high-resolution imaging of pharmacokinetics in larger regions. The multi-scale dynamic imaging capability thus emerges as a powerful and unique feature of the optoacoustic technology that adds to the multiple advantages of this technology for structural, functional and molecular imaging.

Selecting habitat to survive: the impact of road density on survival in a large carnivore.

PubMed

Basille, Mathieu; Van Moorter, Bram; Herfindal, Ivar; Martin, Jodie; Linnell, John D C; Odden, John; Andersen, Reidar; Gaillard, Jean-Michel

2013-01-01

Habitat selection studies generally assume that animals select habitat and food resources at multiple scales to maximise their fitness. However, animals sometimes prefer habitats of apparently low quality, especially when considering the costs associated with spatially heterogeneous human disturbance. We used spatial variation in human disturbance, and its consequences on lynx survival, a direct fitness component, to test the Hierarchical Habitat Selection hypothesis from a population of Eurasian lynx Lynx lynx in southern Norway. Data from 46 lynx monitored with telemetry indicated that a high proportion of forest strongly reduced the risk of mortality from legal hunting at the home range scale, while increasing road density strongly increased such risk at the finer scale within the home range. We found hierarchical effects of the impact of human disturbance, with a higher road density at a large scale reinforcing its negative impact at a fine scale. Conversely, we demonstrated that lynx shifted their habitat selection to avoid areas with the highest road densities within their home ranges, thus supporting a compensatory mechanism at fine scale enabling lynx to mitigate the impact of large-scale disturbance. Human impact, positively associated with high road accessibility, was thus a stronger driver of lynx space use at a finer scale, with home range characteristics nevertheless constraining habitat selection. Our study demonstrates the truly hierarchical nature of habitat selection, which aims at maximising fitness by selecting against limiting factors at multiple spatial scales, and indicates that scale-specific heterogeneity of the environment is driving individual spatial behaviour, by means of trade-offs across spatial scales.

Spatial connectivity, scaling, and temporal trajectories as emergent urban stormwater impacts

NASA Astrophysics Data System (ADS)

Jovanovic, T.; Gironas, J. A.; Hale, R. L.; Mejia, A.

2016-12-01

Urban watersheds are structurally complex systems comprised of multiple components (e.g., streets, pipes, ponds, vegetated swales, wetlands, riparian corridors, etc.). These multiple engineered components interact in unanticipated and nontrivial ways with topographic conditions, climate variability, land use/land cover changes, and the underlying eco-hydrogeomorphic dynamics. Such interactions can result in emergent urban stormwater impacts with cascading effects that can negatively influence the overall functioning of the urban watershed. For example, the interaction among many detention ponds has been shown, in some situations, to synchronize flow volumes and ultimately lead to downstream flow amplifications and increased pollutant mobilization. Additionally, interactions occur at multiple temporal and spatial scales requiring that urban stormwater dynamics be represented at the long-term temporal (decadal) and across spatial scales (from the single lot to the watershed scale). In this study, we develop and implement an event-based, high-resolution, network hydro-engineering model (NHEM), and demonstrate an approach to reconstruct the long-term regional infrastructure and land use/land cover conditions of an urban watershed. As the study area, we select an urban watershed in the metropolitan area of Scottsdale, Arizona. Using the reconstructed landscapes to drive the NHEM, we find that distinct surficial, hydrologic connectivity patterns result from the intersection of hydrologic processes, infrastructure, and land use/land cover arrangements. These spatial patters, in turn, exhibit scaling characteristics. For example, the scaling of urban watershed dispersion mechanisms shows altered scaling exponents with respect to pre-urban conditions. For example, the scaling exponent associated with geomorphic dispersion tends to increase for urban conditions, reflecting increased surficial path heterogeneity. Both the connectivity and scaling results can be used to delineate impact trajectories (i.e. the evolution of spatially referenced impacts over time). We find that the impact trajectories provide insight about the urban stormwater sustainability of watersheds as well as clues about the potential imprint of socio-environmental feedbacks in the evolutionary dynamics.

The landscape context of cereal aphid–parasitoid interactions

PubMed Central

Thies, Carsten; Roschewitz, Indra; Tscharntke, Teja

2005-01-01

Analyses at multiple spatial scales may show how important ecosystem services such as biological control are determined by processes acting on the landscape scale. We examined cereal aphid–parasitoid interactions in wheat fields in agricultural landscapes differing in structural complexity (32–100% arable land). Complex landscapes were associated with increased aphid mortality resulting from parasitism, but also with higher aphid colonization, thereby counterbalancing possible biological control by parasitoids and lastly resulting in similar aphid densities across landscapes. Thus, undisturbed perennial habitats appeared to enhance both pests and natural enemies. Analyses at multiple spatial scales (landscape sectors of 0.5–6 km diameter) showed that correlations between parasitism and percentage of arable land were significant at scales of 0.5–2 km, whereas aphid densities responded to percentage of arable land at scales of 1–6 km diameter. Hence, the higher trophic level populations appeared to be determined by smaller landscape sectors owing to dispersal limitation, showing the ‘functional spatial scale’ for species-specific landscape management. PMID:15695212

Multi-scale Homogenization of Caddisfly Metacomminities in Human-modified Landscapes

NASA Astrophysics Data System (ADS)

Simião-Ferreira, Juliana; Nogueira, Denis Silva; Santos, Anna Claudia; De Marco, Paulo; Angelini, Ronaldo

2018-04-01

The multiple scale of stream networks spatial organization reflects the hierarchical arrangement of streams habitats with increasingly levels of complexity from sub-catchments until entire hydrographic basins. Through these multiple spatial scales, local stream habitats form nested subsets of increasingly landscape scale and habitat size with varying contributions of both alpha and beta diversity for the regional diversity. Here, we aimed to test the relative importance of multiple nested hierarchical levels of spatial scales while determining alpha and beta diversity of caddisflies in regions with different levels of landscape degradation in a core Cerrado area in Brazil. We used quantitative environmental variables to test the hypothesis that landscape homogenization affects the contribution of alpha and beta diversity of caddisflies to regional diversity. We found that the contribution of alpha and beta diversity for gamma diversity varied according to landscape degradation. Sub-catchments with more intense agriculture had lower diversity at multiple levels, markedly alpha and beta diversities. We have also found that environmental predictors mainly associated with water quality, channel size, and habitat integrity (lower scores indicate stream degradation) were related to community dissimilarity at the catchment scale. For an effective management of the headwater biodiversity of caddisfly, towards the conservation of these catchments, heterogeneous streams with more pristine riparian vegetation found within the river basin need to be preserved in protected areas. Additionally, in the most degraded areas the restoration of riparian vegetation and size increase of protected areas will be needed to accomplish such effort.

Spatial and temporal variation in evapotranspiration

USDA-ARS?s Scientific Manuscript database

Spatial and temporal variation in evapotranspiration occurs at multiple scales as the result of several different spatial and temporal patterns in precipitation, soil water holding capacity, cloudiness (available energy), types of crops, and residue and tillage management practices. We have often as...

Non-native salmonids affect amphibian occupancy at multiple spatial scales

Treesearch

David S. Pilliod; Blake R. Hossack; Peter F. Bahls; Evelyn L. Bull; Paul Stephen Corn; Grant Hokit; Bryce A. Maxell; James C. Munger; Aimee Wyrick

2010-01-01

The introduction of non-native species into aquatic environments has been linked with local extinctions and altered distributions of native species. We investigated the effect of non-native salmonids on the occupancy of two native amphibians, the long-toed salamander (Ambystoma macrodactylum) and Columbia spotted frog (Rana luteiventris), across three spatial scales:...

Assessing applicability of SWAT calibrated at multiple spatial scales from field to stream

USDA-ARS?s Scientific Manuscript database

The capability of SWAT for simulating long-term hydrology and water quality was evaluated using data collected in subwatershed K of the Little River Experimental watershed located in South Atlantic Coastal Plain of the USA. The SWAT model was calibrated to measurements made at various spatial scales...

Evaluation of an index of biotic integrity approach to assess fish assemblage condition in Western USA streams and rivers at varying spatial scales

EPA Science Inventory

Consistent assessments of biological condition are needed across multiple ecoregions to provide a greater understanding of the spatial extent of environmental degradation. However, consistent assessments at large geographic scales are often hampered by lack of uniformity in data ...

Taking the pulse of a continent: Expanding site-based research infrastructure for regional- to continental-scale ecology

USDA-ARS?s Scientific Manuscript database

Many of the most dramatic and surprising effects of global change on ecological systems will occur across large spatial extents, from regions to continents. Multiple ecosystem types will be impacted across a range of interacting spatial and temporal scales. The ability of ecologists to understand an...

MONITORING COASTAL RESOURCES AT MULTIPLE SPATIAL AND TEMPORAL SCALES: LESSONS FROM EMAP 2001 EMAP SYMPOSIUM, APRIL 24-27, PENSACOLA BEACH, FL

EPA Science Inventory

In 1990, EMAP's Coastal Monitoring Program conducted its first regional sampling program in the Virginian Province. This first effort focused only at large spatial scales (regional) with some stratification to examine estuarine types. In the ensuing decade, EMAP-Coastal has condu...

Habitat selection by Forster's Terns (Sterna forsteri) at multiple spatial scales in an urbanized estuary: The importance of salt ponds

USGS Publications Warehouse

Bluso-Demers, Jill; Ackerman, Joshua T.; Takekawa, John Y.; Peterson, Sarah

2016-01-01

The highly urbanized San Francisco Bay Estuary, California, USA, is currently undergoing large-scale habitat restoration, and several thousand hectares of former salt evaporation ponds are being converted to tidal marsh. To identify potential effects of this habitat restoration on breeding waterbirds, habitat selection of radiotagged Forster's Terns (Sterna forsteri) was examined at multiple spatial scales during the pre-breeding and breeding seasons of 2005 and 2006. At each spatial scale, habitat selection ratios were calculated by season, year, and sex. Forster's Terns selected salt pond habitats at most spatial scales and demonstrated the importance of salt ponds for foraging and roosting. Salinity influenced the types of salt pond habitats that were selected. Specifically, Forster's Terns strongly selected lower salinity salt ponds (0.5–30 g/L) and generally avoided higher salinity salt ponds (≥31 g/L). Forster's Terns typically used tidal marsh and managed marsh habitats in proportion to their availability, avoided upland and tidal flat habitats, and strongly avoided open bay habitats. Salt ponds provide important habitat for breeding waterbirds, and restoration efforts to convert former salt ponds to tidal marsh may reduce the availability of preferred breeding and foraging areas.

SamuROI, a Python-Based Software Tool for Visualization and Analysis of Dynamic Time Series Imaging at Multiple Spatial Scales.

PubMed

Rueckl, Martin; Lenzi, Stephen C; Moreno-Velasquez, Laura; Parthier, Daniel; Schmitz, Dietmar; Ruediger, Sten; Johenning, Friedrich W

2017-01-01

The measurement of activity in vivo and in vitro has shifted from electrical to optical methods. While the indicators for imaging activity have improved significantly over the last decade, tools for analysing optical data have not kept pace. Most available analysis tools are limited in their flexibility and applicability to datasets obtained at different spatial scales. Here, we present SamuROI (Structured analysis of multiple user-defined ROIs), an open source Python-based analysis environment for imaging data. SamuROI simplifies exploratory analysis and visualization of image series of fluorescence changes in complex structures over time and is readily applicable at different spatial scales. In this paper, we show the utility of SamuROI in Ca 2+ -imaging based applications at three spatial scales: the micro-scale (i.e., sub-cellular compartments including cell bodies, dendrites and spines); the meso-scale, (i.e., whole cell and population imaging with single-cell resolution); and the macro-scale (i.e., imaging of changes in bulk fluorescence in large brain areas, without cellular resolution). The software described here provides a graphical user interface for intuitive data exploration and region of interest (ROI) management that can be used interactively within Jupyter Notebook: a publicly available interactive Python platform that allows simple integration of our software with existing tools for automated ROI generation and post-processing, as well as custom analysis pipelines. SamuROI software, source code and installation instructions are publicly available on GitHub and documentation is available online. SamuROI reduces the energy barrier for manual exploration and semi-automated analysis of spatially complex Ca 2+ imaging datasets, particularly when these have been acquired at different spatial scales.

SamuROI, a Python-Based Software Tool for Visualization and Analysis of Dynamic Time Series Imaging at Multiple Spatial Scales

PubMed Central

Rueckl, Martin; Lenzi, Stephen C.; Moreno-Velasquez, Laura; Parthier, Daniel; Schmitz, Dietmar; Ruediger, Sten; Johenning, Friedrich W.

2017-01-01

The measurement of activity in vivo and in vitro has shifted from electrical to optical methods. While the indicators for imaging activity have improved significantly over the last decade, tools for analysing optical data have not kept pace. Most available analysis tools are limited in their flexibility and applicability to datasets obtained at different spatial scales. Here, we present SamuROI (Structured analysis of multiple user-defined ROIs), an open source Python-based analysis environment for imaging data. SamuROI simplifies exploratory analysis and visualization of image series of fluorescence changes in complex structures over time and is readily applicable at different spatial scales. In this paper, we show the utility of SamuROI in Ca2+-imaging based applications at three spatial scales: the micro-scale (i.e., sub-cellular compartments including cell bodies, dendrites and spines); the meso-scale, (i.e., whole cell and population imaging with single-cell resolution); and the macro-scale (i.e., imaging of changes in bulk fluorescence in large brain areas, without cellular resolution). The software described here provides a graphical user interface for intuitive data exploration and region of interest (ROI) management that can be used interactively within Jupyter Notebook: a publicly available interactive Python platform that allows simple integration of our software with existing tools for automated ROI generation and post-processing, as well as custom analysis pipelines. SamuROI software, source code and installation instructions are publicly available on GitHub and documentation is available online. SamuROI reduces the energy barrier for manual exploration and semi-automated analysis of spatially complex Ca2+ imaging datasets, particularly when these have been acquired at different spatial scales. PMID:28706482

Regional Management Units for Marine Turtles: A Novel Framework for Prioritizing Conservation and Research across Multiple Scales

PubMed Central

Wallace, Bryan P.; DiMatteo, Andrew D.; Hurley, Brendan J.; Finkbeiner, Elena M.; Bolten, Alan B.; Chaloupka, Milani Y.; Hutchinson, Brian J.; Abreu-Grobois, F. Alberto; Amorocho, Diego; Bjorndal, Karen A.; Bourjea, Jerome; Bowen, Brian W.; Dueñas, Raquel Briseño; Casale, Paolo; Choudhury, B. C.; Costa, Alice; Dutton, Peter H.; Fallabrino, Alejandro; Girard, Alexandre; Girondot, Marc; Godfrey, Matthew H.; Hamann, Mark; López-Mendilaharsu, Milagros; Marcovaldi, Maria Angela; Mortimer, Jeanne A.; Musick, John A.; Nel, Ronel; Pilcher, Nicolas J.; Seminoff, Jeffrey A.; Troëng, Sebastian; Witherington, Blair; Mast, Roderic B.

2010-01-01

Background Resolving threats to widely distributed marine megafauna requires definition of the geographic distributions of both the threats as well as the population unit(s) of interest. In turn, because individual threats can operate on varying spatial scales, their impacts can affect different segments of a population of the same species. Therefore, integration of multiple tools and techniques — including site-based monitoring, genetic analyses, mark-recapture studies and telemetry — can facilitate robust definitions of population segments at multiple biological and spatial scales to address different management and research challenges. Methodology/Principal Findings To address these issues for marine turtles, we collated all available studies on marine turtle biogeography, including nesting sites, population abundances and trends, population genetics, and satellite telemetry. We georeferenced this information to generate separate layers for nesting sites, genetic stocks, and core distributions of population segments of all marine turtle species. We then spatially integrated this information from fine- to coarse-spatial scales to develop nested envelope models, or Regional Management Units (RMUs), for marine turtles globally. Conclusions/Significance The RMU framework is a solution to the challenge of how to organize marine turtles into units of protection above the level of nesting populations, but below the level of species, within regional entities that might be on independent evolutionary trajectories. Among many potential applications, RMUs provide a framework for identifying data gaps, assessing high diversity areas for multiple species and genetic stocks, and evaluating conservation status of marine turtles. Furthermore, RMUs allow for identification of geographic barriers to gene flow, and can provide valuable guidance to marine spatial planning initiatives that integrate spatial distributions of protected species and human activities. In addition, the RMU framework — including maps and supporting metadata — will be an iterative, user-driven tool made publicly available in an online application for comments, improvements, download and analysis. PMID:21253007

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

EPA Science Inventory

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

Evaluating single-pass catch as a tool for identifying spatial pattern in fish distribution

USGS Publications Warehouse

Bateman, Douglas S.; Gresswell, Robert E.; Torgersen, Christian E.

2005-01-01

We evaluate the efficacy of single-pass electrofishing without blocknets as a tool for collecting spatially continuous fish distribution data in headwater streams. We compare spatial patterns in abundance, sampling effort, and length-frequency distributions from single-pass sampling of coastal cutthroat trout (Oncorhynchus clarki clarki) to data obtained from a more precise multiple-pass removal electrofishing method in two mid-sized (500–1000 ha) forested watersheds in western Oregon. Abundance estimates from single- and multiple-pass removal electrofishing were positively correlated in both watersheds, r = 0.99 and 0.86. There were no significant trends in capture probabilities at the watershed scale (P > 0.05). Moreover, among-sample variation in fish abundance was higher than within-sample error in both streams indicating that increased precision of unit-scale abundance estimates would provide less information on patterns of abundance than increasing the fraction of habitat units sampled. In the two watersheds, respectively, single-pass electrofishing captured 78 and 74% of the estimated population of cutthroat trout with 7 and 10% of the effort. At the scale of intermediate-sized watersheds, single-pass electrofishing exhibited a sufficient level of precision to be effective in detecting spatial patterns of cutthroat trout abundance and may be a useful tool for providing the context for investigating fish-habitat relationships at multiple scales.

Comparing riparian and catchment influences on stream habitat in a forested, montane landscape.

Treesearch

K.M. Burnett; G.H. Reeves

2006-01-01

The goal of this study was to understand relationships between salmon habitat and landscape characteristics, summarized at multiple spatial scales, in a montane basin where forestry is the dominant land use. Specific study objectives were to (1) examine differences among spatial scales for landscape characteristics described with relatively coarse-resolution data, (2)...

Multiple Views of Space: Continuous Visual Flow Enhances Small-Scale Spatial Learning

ERIC Educational Resources Information Center

Holmes, Corinne A.; Marchette, Steven A.; Newcombe, Nora S.

2017-01-01

In the real word, we perceive our environment as a series of static and dynamic views, with viewpoint transitions providing a natural link from one static view to the next. The current research examined if experiencing such transitions is fundamental to learning the spatial layout of small-scale displays. In Experiment 1, participants viewed a…

Monitoring survival rates of Swainson's Thrush Catharus ustulatus at multiple spatial scales

USGS Publications Warehouse

Rosenberg, D.K.; DeSante, D.F.; McKelvey, K.S.; Hines, J.E.

1999-01-01

We estimated survival rates of Swainson's Thrush, a common, neotropical, migratory landbird, at multiple spatial scales, using data collected in the western USA from the Monitoring Avian Productivity and Survivorship Programme. We evaluated statistical power to detect spatially heterogeneous survival rates and exponentially declining survival rates among spatial scales with simulated populations parameterized from results of the Swainson's Thrush analyses. Models describing survival rates as constant across large spatial scales did not fit the data. The model we chose as most appropriate to describe survival rates of Swainson's Thrush allowed survival rates to vary among Physiographic Provinces, included a separate parameter for the probability that a newly captured bird is a resident individual in the study population, and constrained capture probability to be constant across all stations. Estimated annual survival rates under this model varied from 0.42 to 0.75 among Provinces. The coefficient of variation of survival estimates ranged from 5.8 to 20% among Physiographic Provinces. Statistical power to detect exponentially declining trends was fairly low for small spatial scales, although large annual declines (3% of previous year's rate) were likely to be detected when monitoring was conducted for long periods of time (e.g. 20 years). Although our simulations and field results are based on only four years of data from a limited number and distribution of stations, it is likely that they illustrate genuine difficulties inherent to broadscale efforts to monitor survival rates of territorial landbirds. In particular, our results suggest that more attention needs to be paid to sampling schemes of monitoring programmes, particularly regarding the trade-off between precision and potential bias of parameter estimates at varying spatial scales.

Monitoring survival rates of Swainson's Thrush Catharus ustulatus at multiple spatial scales

USGS Publications Warehouse

Rosenberg, D.K.; DeSante, D.F.; McKelvey, K.S.; Hines, J.E.

1999-01-01

We estimated survival rates of Swainson's Thrush, a common, neotropical, migratory landbird, at multiple spatial scales, using data collected in the western USA from the Monitoring Avian Productivity and Survivorship Programme. We evaluated statistical power to detect spatially heterogeneous survival rates and exponentially declining survival rates among spatial scales with simulated populations parameterized from results of the Swainson's Thrush analyses. Models describing survival rates as constant across large spatial scales did not fit the data. The model we chose as most appropriate to describe survival rates of Swainson's Thrush allowed survival rates to vary among Physiographic Provinces, included a separate parameter for the probability that a newly captured bird is a resident individual in the study population, and constrained capture probability to be constant across all stations. Estimated annual survival rates under this model varied from 0.42 to 0.75 among Provinces. The coefficient of variation of survival estimates ranged from 5.8 to 20% among Physiographic Provinces. Statistical power to detect exponentially declining trends was fairly low for small spatial scales, although large annual declines (3% of previous year's rate) were likely to be detected when monitoring was conducted for long periods of time (e.g. 20 years). Although our simulations and field results are based on only four years of date from a limited number and distribution of stations, it is likely that they illustrate genuine difficulties inherent to broadscale efforts to monitor survival rates of territorial landbirds. In particular, our results suggest that more attention needs to be paid to sampling schemes of monitoring programmes particularly regarding the trade-off between precison and potential bias o parameter estimates at varying spatial scales.

Multiple Scales of Control on the Structure and Spatial Distribution of Woody Vegetation in African Savanna Watersheds

PubMed Central

Vaughn, Nicholas R.; Asner, Gregory P.; Smit, Izak P. J.; Riddel, Edward S.

2015-01-01

Factors controlling savanna woody vegetation structure vary at multiple spatial and temporal scales, and as a consequence, unraveling their combined effects has proven to be a classic challenge in savanna ecology. We used airborne LiDAR (light detection and ranging) to map three-dimensional woody vegetation structure throughout four savanna watersheds, each contrasting in geologic substrate and climate, in Kruger National Park, South Africa. By comparison of the four watersheds, we found that geologic substrate had a stronger effect than climate in determining watershed-scale differences in vegetation structural properties, including cover, height and crown density. Generalized Linear Models were used to assess the spatial distribution of woody vegetation structural properties, including cover, height and crown density, in relation to mapped hydrologic, topographic and fire history traits. For each substrate and climate combination, models incorporating topography, hydrology and fire history explained up to 30% of the remaining variation in woody canopy structure, but inclusion of a spatial autocovariate term further improved model performance. Both crown density and the cover of shorter woody canopies were determined more by unknown factors likely to be changing on smaller spatial scales, such as soil texture, herbivore abundance or fire behavior, than by our mapped regional-scale changes in topography and hydrology. We also detected patterns in spatial covariance at distances up to 50–450 m, depending on watershed and structural metric. Our results suggest that large-scale environmental factors play a smaller role than is often attributed to them in determining woody vegetation structure in southern African savannas. This highlights the need for more spatially-explicit, wide-area analyses using high resolution remote sensing techniques. PMID:26660502

Multiple Scales of Control on the Structure and Spatial Distribution of Woody Vegetation in African Savanna Watersheds.

PubMed

Vaughn, Nicholas R; Asner, Gregory P; Smit, Izak P J; Riddel, Edward S

2015-01-01

Factors controlling savanna woody vegetation structure vary at multiple spatial and temporal scales, and as a consequence, unraveling their combined effects has proven to be a classic challenge in savanna ecology. We used airborne LiDAR (light detection and ranging) to map three-dimensional woody vegetation structure throughout four savanna watersheds, each contrasting in geologic substrate and climate, in Kruger National Park, South Africa. By comparison of the four watersheds, we found that geologic substrate had a stronger effect than climate in determining watershed-scale differences in vegetation structural properties, including cover, height and crown density. Generalized Linear Models were used to assess the spatial distribution of woody vegetation structural properties, including cover, height and crown density, in relation to mapped hydrologic, topographic and fire history traits. For each substrate and climate combination, models incorporating topography, hydrology and fire history explained up to 30% of the remaining variation in woody canopy structure, but inclusion of a spatial autocovariate term further improved model performance. Both crown density and the cover of shorter woody canopies were determined more by unknown factors likely to be changing on smaller spatial scales, such as soil texture, herbivore abundance or fire behavior, than by our mapped regional-scale changes in topography and hydrology. We also detected patterns in spatial covariance at distances up to 50-450 m, depending on watershed and structural metric. Our results suggest that large-scale environmental factors play a smaller role than is often attributed to them in determining woody vegetation structure in southern African savannas. This highlights the need for more spatially-explicit, wide-area analyses using high resolution remote sensing techniques.

Foothill yellow-legged frog (Rana boylii) oviposition site choice at multiple spatial scales

Treesearch

Amy J. Lind; Hartwell H. Welsh; Clara A. Wheeler

2016-01-01

Studies of resource selection at multiple scales are critical to understanding ecological and evolutionary attributes of a species. We analyzed relative abundance, habitat use, and oviposition site selection of Foothill Yellow-Legged Frogs (Rana boylii) at 11 localities across two geographic regions in California (northern Coast Range and Sierra...

Evolution of natural history information in the 21st century – developing an integrated framework for biological and geographical data

USGS Publications Warehouse

Reusser, Deborah A.; Lee, Henry

2011-01-01

Threats to marine and estuarine species operate over many spatial scales, from nutrient enrichment at the watershed/estuarine scale to invasive species and climate change at regional and global scales. To help address research questions across these scales, we provide here a standardized framework for a biogeographical information system containing queriable biological data that allows extraction of information on multiple species, across a variety of spatial scales based on species distributions, natural history attributes and habitat requirements. As scientists shift from research on localized impacts on individual species to regional and global scale threats, macroecological approaches of studying multiple species over broad geographical areas are becoming increasingly important. The standardized framework described here for capturing and integrating biological and geographical data is a critical first step towards addressing these macroecological questions and we urge organizations capturing biogeoinformatics data to consider adopting this framework.

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Multi-scale habitat selection modeling: A review and outlook

Treesearch

Kevin McGarigal; Ho Yi Wan; Kathy A. Zeller; Brad C. Timm; Samuel A. Cushman

2016-01-01

Scale is the lens that focuses ecological relationships. Organisms select habitat at multiple hierarchical levels and at different spatial and/or temporal scales within each level. Failure to properly address scale dependence can result in incorrect inferences in multi-scale habitat selection modeling studies.

False Discovery Control in Large-Scale Spatial Multiple Testing

PubMed Central

Sun, Wenguang; Reich, Brian J.; Cai, T. Tony; Guindani, Michele; Schwartzman, Armin

2014-01-01

Summary This article develops a unified theoretical and computational framework for false discovery control in multiple testing of spatial signals. We consider both point-wise and cluster-wise spatial analyses, and derive oracle procedures which optimally control the false discovery rate, false discovery exceedance and false cluster rate, respectively. A data-driven finite approximation strategy is developed to mimic the oracle procedures on a continuous spatial domain. Our multiple testing procedures are asymptotically valid and can be effectively implemented using Bayesian computational algorithms for analysis of large spatial data sets. Numerical results show that the proposed procedures lead to more accurate error control and better power performance than conventional methods. We demonstrate our methods for analyzing the time trends in tropospheric ozone in eastern US. PMID:25642138

Interactions across spatial scales among forest dieback, fire, and erosion in northern New Mexico landscapes

USGS Publications Warehouse

Allen, Craig D.

2007-01-01

Ecosystem patterns and disturbance processes at one spatial scale often interact with processes at another scale, and the result of such cross-scale interactions can be nonlinear dynamics with thresholds. Examples of cross-scale pattern-process relationships and interactions among forest dieback, fire, and erosion are illustrated from northern New Mexico (USA) landscapes, where long-term studies have recently documented all of these disturbance processes. For example, environmental stress, operating on individual trees, can cause tree death that is amplified by insect mortality agents to propagate to patch and then landscape or even regional-scale forest dieback. Severe drought and unusual warmth in the southwestern USA since the late 1990s apparently exceeded species-specific physiological thresholds for multiple tree species, resulting in substantial vegetation mortality across millions of hectares of woodlands and forests in recent years. Predictions of forest dieback across spatial scales are constrained by uncertainties associated with: limited knowledge of species-specific physiological thresholds; individual and site-specific variation in these mortality thresholds; and positive feedback loops between rapidly-responding insect herbivore populations and their stressed plant hosts, sometimes resulting in nonlinear “pest” outbreak dynamics. Fire behavior also exhibits nonlinearities across spatial scales, illustrated by changes in historic fire regimes where patch-scale grazing disturbance led to regional-scale collapse of surface fire activity and subsequent recent increases in the scale of extreme fire events in New Mexico. Vegetation dieback interacts with fire activity by modifying fuel amounts and configurations at multiple spatial scales. Runoff and erosion processes are also subject to scale-dependent threshold behaviors, exemplified by ecohydrological work in semiarid New Mexico watersheds showing how declines in ground surface cover lead to non-linear increases in bare patch connectivity and thereby accelerated runoff and erosion at hillslope and watershed scales. Vegetation dieback, grazing, and fire can change land surface properties and cross-scale hydrologic connectivities, directly altering ecohydrological patterns of runoff and erosion. The interactions among disturbance processes across spatial scales can be key drivers in ecosystem dynamics, as illustrated by these studies of recent landscape changes in northern New Mexico. To better anticipate and mitigate accelerating human impacts to the planetary ecosystem at all spatial scales, improvements are needed in our conceptual and quantitative understanding of cross-scale interactions among disturbance processes.

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

NASA Astrophysics Data System (ADS)

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

2013-08-01

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

Coordinated learning of grid cell and place cell spatial and temporal properties: multiple scales, attention and oscillations.

PubMed

Grossberg, Stephen; Pilly, Praveen K

2014-02-05

A neural model proposes how entorhinal grid cells and hippocampal place cells may develop as spatial categories in a hierarchy of self-organizing maps (SOMs). The model responds to realistic rat navigational trajectories by learning both grid cells with hexagonal grid firing fields of multiple spatial scales, and place cells with one or more firing fields, that match neurophysiological data about their development in juvenile rats. Both grid and place cells can develop by detecting, learning and remembering the most frequent and energetic co-occurrences of their inputs. The model's parsimonious properties include: similar ring attractor mechanisms process linear and angular path integration inputs that drive map learning; the same SOM mechanisms can learn grid cell and place cell receptive fields; and the learning of the dorsoventral organization of multiple spatial scale modules through medial entorhinal cortex to hippocampus (HC) may use mechanisms homologous to those for temporal learning through lateral entorhinal cortex to HC ('neural relativity'). The model clarifies how top-down HC-to-entorhinal attentional mechanisms may stabilize map learning, simulates how hippocampal inactivation may disrupt grid cells, and explains data about theta, beta and gamma oscillations. The article also compares the three main types of grid cell models in the light of recent data.

Mercury and methylmercury stream concentrations in a Coastal Plain watershed: A multi-scale simulation analysis

USGS Publications Warehouse

Knightes, Christopher D.; Golden, Heather E.; Journey, Celeste A.; Davis, Gary M.; Conrads, Paul; Marvin-DiPasquale, Mark; Brigham, Mark E.; Bradley, Paul M.

2014-01-01

Mercury is a ubiquitous global environmental toxicant responsible for most US fish advisories. Processes governing mercury concentrations in rivers and streams are not well understood, particularly at multiple spatial scales. We investigate how insights gained from reach-scale mercury data and model simulations can be applied at broader watershed scales using a spatially and temporally explicit watershed hydrology and biogeochemical cycling model, VELMA. We simulate fate and transport using reach-scale (0.1 km2) study data and evaluate applications to multiple watershed scales. Reach-scale VELMA parameterization was applied to two nested sub-watersheds (28 km2 and 25 km2) and the encompassing watershed (79 km2). Results demonstrate that simulated flow and total mercury concentrations compare reasonably to observations at different scales, but simulated methylmercury concentrations are out-of-phase with observations. These findings suggest that intricacies of methylmercury biogeochemical cycling and transport are under-represented in VELMA and underscore the complexity of simulating mercury fate and transport.

Selection of day-roosts by Keen's myotis (Myotis keenii) at multiple spatial scales

Treesearch

Julia L. Boland; John P. Hayes; Winston P. Smith; Manuela M. Huso

2009-01-01

Keen's myotis (Myotis keenii) has one of the most limited geographic distributions of any species of bat in North America. Because there is little knowledge of its roosting ecology, we examined selection of day-roosts in trees by male and female Keen's myotis at three spatial scales (tree, tree plot, and landscape) on Prince of Wales Island...

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

PubMed Central

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

2014-01-01

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

Concepts of scale and scaling

Treesearch

Jianguo Wu; Harbin Li

2006-01-01

The relationship between pattern and process is of great interest in all natural and social sciences, and scale is an integral part of this relationship. It is now well documented that biophysical and socioeconomic patterns and processes operate on a wide range of spatial and temporal scales. In particular, the scale multiplicity and scale dependence of pattern,...

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

A U.S. Human Well-being Index (HWBI) for Multiple Scales: Linking Services Provisioning to Human Well-being Endpoints (2000-2010)

EPA Science Inventory

objective of this report is to characterize well-being at multiple scales in order to evaluate the relationship of service flows in terms of sustainable well-being. The HWBI results presented represent snapshot assessments for the 2000-2010 time period. Based on the spatial and t...

Downscaling remotely sensed imagery using area-to-point cokriging and multiple-point geostatistical simulation

NASA Astrophysics Data System (ADS)

Tang, Yunwei; Atkinson, Peter M.; Zhang, Jingxiong

2015-03-01

A cross-scale data integration method was developed and tested based on the theory of geostatistics and multiple-point geostatistics (MPG). The goal was to downscale remotely sensed images while retaining spatial structure by integrating images at different spatial resolutions. During the process of downscaling, a rich spatial correlation model in the form of a training image was incorporated to facilitate reproduction of similar local patterns in the simulated images. Area-to-point cokriging (ATPCK) was used as locally varying mean (LVM) (i.e., soft data) to deal with the change of support problem (COSP) for cross-scale integration, which MPG cannot achieve alone. Several pairs of spectral bands of remotely sensed images were tested for integration within different cross-scale case studies. The experiment shows that MPG can restore the spatial structure of the image at a fine spatial resolution given the training image and conditioning data. The super-resolution image can be predicted using the proposed method, which cannot be realised using most data integration methods. The results show that ATPCK-MPG approach can achieve greater accuracy than methods which do not account for the change of support issue.

Grid cell hexagonal patterns formed by fast self-organized learning within entorhinal cortex.

PubMed

Mhatre, Himanshu; Gorchetchnikov, Anatoli; Grossberg, Stephen

2012-02-01

Grid cells in the dorsal segment of the medial entorhinal cortex (dMEC) show remarkable hexagonal activity patterns, at multiple spatial scales, during spatial navigation. It has previously been shown how a self-organizing map can convert firing patterns across entorhinal grid cells into hippocampal place cells that are capable of representing much larger spatial scales. Can grid cell firing fields also arise during navigation through learning within a self-organizing map? This article describes a simple and general mathematical property of the trigonometry of spatial navigation which favors hexagonal patterns. The article also develops a neural model that can learn to exploit this trigonometric relationship. This GRIDSmap self-organizing map model converts path integration signals into hexagonal grid cell patterns of multiple scales. GRIDSmap creates only grid cell firing patterns with the observed hexagonal structure, predicts how these hexagonal patterns can be learned from experience, and can process biologically plausible neural input and output signals during navigation. These results support an emerging unified computational framework based on a hierarchy of self-organizing maps for explaining how entorhinal-hippocampal interactions support spatial navigation. Copyright © 2010 Wiley Periodicals, Inc.

Coupling fine-scale root and canopy structure using ground-based remote sensing

DOE PAGES

Hardiman, Brady S.; Gough, Christopher M.; Butnor, John R.; ...

2017-02-21

Ecosystem physical structure, defined by the quantity and spatial distribution of biomass, influences a range of ecosystem functions. Remote sensing tools permit the non-destructive characterization of canopy and root features, potentially providing opportunities to link above- and belowground structure at fine spatial resolution in functionally meaningful ways. To test this possibility, we employed ground-based portable canopy LiDAR (PCL) and ground penetrating radar (GPR) along co-located transects in forested sites spanning multiple stages of ecosystem development and, consequently, of structural complexity. We examined canopy and root structural data for coherence (i.e., correlation in the frequency of spatial variation) at multiple spatialmore » scales 10 m within each site using wavelet analysis. Forest sites varied substantially in vertical canopy and root structure, with leaf area index and root mass more becoming even vertically as forests aged. In all sites, above- and belowground structure, characterized as mean maximum canopy height and root mass, exhibited significant coherence at a scale of 3.5–4 m, and results suggest that the scale of coherence may increase with stand age. Our findings demonstrate that canopy and root structure are linked at characteristic spatial scales, which provides the basis to optimize scales of observation. Lastly, our study highlights the potential, and limitations, for fusing LiDAR and radar technologies to quantitatively couple above- and belowground ecosystem structure.« less

Coupling fine-scale root and canopy structure using ground-based remote sensing

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

Hardiman, Brady S.; Gough, Christopher M.; Butnor, John R.

Ecosystem physical structure, defined by the quantity and spatial distribution of biomass, influences a range of ecosystem functions. Remote sensing tools permit the non-destructive characterization of canopy and root features, potentially providing opportunities to link above- and belowground structure at fine spatial resolution in functionally meaningful ways. To test this possibility, we employed ground-based portable canopy LiDAR (PCL) and ground penetrating radar (GPR) along co-located transects in forested sites spanning multiple stages of ecosystem development and, consequently, of structural complexity. We examined canopy and root structural data for coherence (i.e., correlation in the frequency of spatial variation) at multiple spatialmore » scales 10 m within each site using wavelet analysis. Forest sites varied substantially in vertical canopy and root structure, with leaf area index and root mass more becoming even vertically as forests aged. In all sites, above- and belowground structure, characterized as mean maximum canopy height and root mass, exhibited significant coherence at a scale of 3.5–4 m, and results suggest that the scale of coherence may increase with stand age. Our findings demonstrate that canopy and root structure are linked at characteristic spatial scales, which provides the basis to optimize scales of observation. Lastly, our study highlights the potential, and limitations, for fusing LiDAR and radar technologies to quantitatively couple above- and belowground ecosystem structure.« less

Deprivation Indices, Population Health and Geography: An Evaluation of the Spatial Effectiveness of Indices at Multiple Scales

PubMed Central

Bell, Nathaniel; Dunn, James R.; Oliver, Lisa

2007-01-01

Area-based deprivation indices (ABDIs) have become a common tool with which to investigate the patterns and magnitude of socioeconomic inequalities in health. ABDIs are also used as a proxy for individual socioeconomic status. Despite their widespread use, comparably less attention has been focused on their geographic variability and practical concerns surrounding the Modifiable Area Unit Problem (MAUP) than on the individual attributes that make up the indices. Although scale is increasingly recognized as an important factor in interpreting mapped results among population health researchers, less attention has been paid specifically to ABDI and scale. In this paper, we highlight the effect of scale on indices by mapping ABDIs at multiple census scales in an urban area. In addition, we compare self-rated health data from the Canadian Community Health Survey with ABDIs at two census scales. The results of our analysis confirm the influence of spatial extent and scale on mapping population health—with potential implications for health policy implementation and resource distribution. PMID:17447145

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

PubMed

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

2015-12-18

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

Influences of land use on leaf breakdown in Southern Appalachian headwater streams: a multiple-scale analysis

Treesearch

R.A. Sponseller; E.F. Benfield

2001-01-01

Stream ecosystems can be strongly influenced by land use within watersheds. The extent of this influence may depend on the spatial distribution of developed land and the scale at which it is evaluated. Effects of land-cover patterns on leaf breakdown were studied in 8 Southern Appalachian headwater streams. Using a GIS, land cover was evaluated at several spatial...

Resource selection by elk at two spatial scales in the Black Hills, South Dakota

Treesearch

Mark A. Rumble; R. Scott Gamo

2011-01-01

Understanding resource selection by elk (Cervus elaphus) at multiple spatial scales may provide information that will help resolve the increasing number of resource conflicts involving elk. We quantified vegetation at 412 sites where the precise location of elk was known by direct observation and 509 random sites in the Black Hills of South Dakota during 1998-2001. We...

Hierarchical drivers of reef-fish metacommunity structure.

PubMed

MacNeil, M Aaron; Graham, Nicholas A J; Polunin, Nicholas V C; Kulbicki, Michel; Galzin, René; Harmelin-Vivien, Mireille; Rushton, Steven P

2009-01-01

Coral reefs are highly complex ecological systems, where multiple processes interact across scales in space and time to create assemblages of exceptionally high biodiversity. Despite the increasing frequency of hierarchically structured sampling programs used in coral-reef science, little progress has been made in quantifying the relative importance of processes operating across multiple scales. The vast majority of reef studies are conducted, or at least analyzed, at a single spatial scale, ignoring the implicitly hierarchical structure of the overall system in favor of small-scale experiments or large-scale observations. Here we demonstrate how alpha (mean local number of species), beta diversity (degree of species dissimilarity among local sites), and gamma diversity (overall species richness) vary with spatial scale, and using a hierarchical, information-theoretic approach, we evaluate the relative importance of site-, reef-, and atoll-level processes driving the fish metacommunity structure among 10 atolls in French Polynesia. Process-based models, representing well-established hypotheses about drivers of reef-fish community structure, were assembled into a candidate set of 12 hierarchical linear models. Variation in fish abundance, biomass, and species richness were unevenly distributed among transect, reef, and atoll levels, establishing the relative contribution of variation at these spatial scales to the structure of the metacommunity. Reef-fish biomass, species richness, and the abundance of most functional-groups corresponded primarily with transect-level habitat diversity and atoll-lagoon size, whereas detritivore and grazer abundances were largely correlated with potential covariates of larval dispersal. Our findings show that (1) within-transect and among-atoll factors primarily drive the relationship between alpha and gamma diversity in this reef-fish metacommunity; (2) habitat is the primary correlate with reef-fish metacommunity structure at multiple spatial scales; and (3) inter-atoll connectedness was poorly correlated with the nonrandom clustering of reef-fish species. These results demonstrate the importance of modeling hierarchical data and processes in understanding reef-fish metacommunity structure.

Are bark beetle outbreaks less synchronous than forest Lepidoptera outbreaks?

Treesearch

Bjorn Okland; Andrew M. Liebhold; Ottar N. Bjornstad; Nadir Erbilgin; Paal Krokene; Paal Krokene

2005-01-01

Comparisons of intraspecific spatial synchrony across multiple epidemic insect species can be useful for generating hypotheses about major determinants of population patterns at larger scales. The present study compares patterns of spatial synchrony in outbreaks of six epidemic bark beetle species in North America and Europe. Spatial synchrony among populations of the...

Classification of Farmland Landscape Structure in Multiple Scales

NASA Astrophysics Data System (ADS)

Jiang, P.; Cheng, Q.; Li, M.

2017-12-01

Farmland is one of the basic terrestrial resources that support the development and survival of human beings and thus plays a crucial role in the national security of every country. Pattern change is the intuitively spatial representation of the scale and quality variation of farmland. Through the characteristic development of spatial shapes as well as through changes in system structures, functions and so on, farmland landscape patterns may indicate the landscape health level. Currently, it is still difficult to perform positioning analyses of landscape pattern changes that reflect the landscape structure variations of farmland with an index model. Depending on a number of spatial properties such as locations and adjacency relations, distance decay, fringe effect, and on the model of patch-corridor-matrix that is applied, this study defines a type system of farmland landscape structure on the national, provincial, and city levels. According to such a definition, the classification model of farmland landscape-structure type at the pixel scale is developed and validated based on mathematical-morphology concepts and on spatial-analysis methods. Then, the laws that govern farmland landscape-pattern change in multiple scales are analyzed from the perspectives of spatial heterogeneity, spatio-temporal evolution, and function transformation. The result shows that the classification model of farmland landscape-structure type can reflect farmland landscape-pattern change and its effects on farmland production function. Moreover, farmland landscape change in different scales displayed significant disparity in zonality, both within specific regions and in urban-rural areas.

Accuracy improvement in laser stripe extraction for large-scale triangulation scanning measurement system

NASA Astrophysics Data System (ADS)

Zhang, Yang; Liu, Wei; Li, Xiaodong; Yang, Fan; Gao, Peng; Jia, Zhenyuan

2015-10-01

Large-scale triangulation scanning measurement systems are widely used to measure the three-dimensional profile of large-scale components and parts. The accuracy and speed of the laser stripe center extraction are essential for guaranteeing the accuracy and efficiency of the measuring system. However, in the process of large-scale measurement, multiple factors can cause deviation of the laser stripe center, including the spatial light intensity distribution, material reflectivity characteristics, and spatial transmission characteristics. A center extraction method is proposed for improving the accuracy of the laser stripe center extraction based on image evaluation of Gaussian fitting structural similarity and analysis of the multiple source factors. First, according to the features of the gray distribution of the laser stripe, evaluation of the Gaussian fitting structural similarity is estimated to provide a threshold value for center compensation. Then using the relationships between the gray distribution of the laser stripe and the multiple source factors, a compensation method of center extraction is presented. Finally, measurement experiments for a large-scale aviation composite component are carried out. The experimental results for this specific implementation verify the feasibility of the proposed center extraction method and the improved accuracy for large-scale triangulation scanning measurements.

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

USGS Publications Warehouse

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

2010-01-01

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

Environmental monitoring of Galway Bay: fusing data from remote and in-situ sources

NASA Astrophysics Data System (ADS)

O'Connor, Edel; Hayes, Jer; Smeaton, Alan F.; O'Connor, Noel E.; Diamond, Dermot

2009-09-01

Changes in sea surface temperature can be used as an indicator of water quality. In-situ sensors are being used for continuous autonomous monitoring. However these sensors have limited spatial resolution as they are in effect single point sensors. Satellite remote sensing can be used to provide better spatial coverage at good temporal scales. However in-situ sensors have a richer temporal scale for a particular point of interest. Work carried out in Galway Bay has combined data from multiple satellite sources and in-situ sensors and investigated the benefits and drawbacks of using multiple sensing modalities for monitoring a marine location.

Spatial attention improves the quality of population codes in human visual cortex.

PubMed

Saproo, Sameer; Serences, John T

2010-08-01

Selective attention enables sensory input from behaviorally relevant stimuli to be processed in greater detail, so that these stimuli can more accurately influence thoughts, actions, and future goals. Attention has been shown to modulate the spiking activity of single feature-selective neurons that encode basic stimulus properties (color, orientation, etc.). However, the combined output from many such neurons is required to form stable representations of relevant objects and little empirical work has formally investigated the relationship between attentional modulations on population responses and improvements in encoding precision. Here, we used functional MRI and voxel-based feature tuning functions to show that spatial attention induces a multiplicative scaling in orientation-selective population response profiles in early visual cortex. In turn, this multiplicative scaling correlates with an improvement in encoding precision, as evidenced by a concurrent increase in the mutual information between population responses and the orientation of attended stimuli. These data therefore demonstrate how multiplicative scaling of neural responses provides at least one mechanism by which spatial attention may improve the encoding precision of population codes. Increased encoding precision in early visual areas may then enhance the speed and accuracy of perceptual decisions computed by higher-order neural mechanisms.

Predictions for an invaded world: A strategy to predict the distribution of native and non-indigenous species at multiple scales

USGS Publications Warehouse

Reusser, D.A.; Lee, H.

2008-01-01

Habitat models can be used to predict the distributions of marine and estuarine non-indigenous species (NIS) over several spatial scales. At an estuary scale, our goal is to predict the estuaries most likely to be invaded, but at a habitat scale, the goal is to predict the specific locations within an estuary that are most vulnerable to invasion. As an initial step in evaluating several habitat models, model performance for a suite of benthic species with reasonably well-known distributions on the Pacific coast of the US needs to be compared. We discuss the utility of non-parametric multiplicative regression (NPMR) for predicting habitat- and estuary-scale distributions of native and NIS. NPMR incorporates interactions among variables, allows qualitative and categorical variables, and utilizes data on absence as well as presence. Preliminary results indicate that NPMR generally performs well at both spatial scales and that distributions of NIS are predicted as well as those of native species. For most species, latitude was the single best predictor, although similar model performance could be obtained at both spatial scales with combinations of other habitat variables. Errors of commission were more frequent at a habitat scale, with omission and commission errors approximately equal at an estuary scale. ?? 2008 International Council for the Exploration of the Sea. Published by Oxford Journals. All rights reserved.

The value of remote sensing techniques in supporting effective extrapolation across multiple marine spatial scales.

PubMed

Strong, James Asa; Elliott, Michael

2017-03-15

The reporting of ecological phenomena and environmental status routinely required point observations, collected with traditional sampling approaches to be extrapolated to larger reporting scales. This process encompasses difficulties that can quickly entrain significant errors. Remote sensing techniques offer insights and exceptional spatial coverage for observing the marine environment. This review provides guidance on (i) the structures and discontinuities inherent within the extrapolative process, (ii) how to extrapolate effectively across multiple spatial scales, and (iii) remote sensing techniques and data sets that can facilitate this process. This evaluation illustrates that remote sensing techniques are a critical component in extrapolation and likely to underpin the production of high-quality assessments of ecological phenomena and the regional reporting of environmental status. Ultimately, is it hoped that this guidance will aid the production of robust and consistent extrapolations that also make full use of the techniques and data sets that expedite this process. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Resilience of Coral Reefs Across a Hierarchy of Spatial and Temporal scales

NASA Astrophysics Data System (ADS)

Mumby, P. J.

2016-02-01

Resilience is a dynamical property of ecosystems that integrates processes of recovery, disturbance and internal dynamics, including reinforcing feedbacks. As such, resilience is a useful framework to consider how ecosystems respond to multiple drivers occurring over multiple scales. Many insights have emerged recently including the way in which stressors can combine synergistically to deplete resilience. However, while recent advances have mapped resilience across seascapes, most studies have not captured emergent spatial dependencies and dynamics across the seascape (e.g., independent box models are run across the seascape in isolation). Here, we explore the dynamics that emerge when the seascape is `wired up' using data on larval dispersal, thereby giving a fully spatially-realistic model. We then consider how dynamics change across even larger, biogeographic scales, posing the question, `are there robust and global "rules of thumb" for the resilience of a single ecosystem?'. Answers to this question will help managers tailor their interventions and research needs for their own jurisdiction.

Distribution patterns of the crab Ucides cordatus (Brachyura, Ucididae) at different spatial scales in subtropical mangroves of Paranaguá Bay (southern Brazil)

NASA Astrophysics Data System (ADS)

Sandrini-Neto, L.; Lana, P. C.

2012-06-01

Heterogeneity in the distribution of organisms occurs at a range of spatial scales, which may vary from few centimeters to hundreds of kilometers. The exclusion of small-scale variability from routine sampling designs may confound comparisons at larger scales and lead to inconsistent interpretation of data. Despite its ecological and social-economic importance, little is known about the spatial structure of the mangrove crab Ucides cordatus in the southwest Atlantic. Previous studies have commonly compared densities at relatively broad scales, relying on alleged distribution patterns (e.g., mangroves of distinct composition and structure). We have assessed variability patterns of U. cordatus in mangroves of Paranaguá Bay at four levels of spatial hierarchy (10 s km, km, 10 s m and m) using a nested ANOVA and variance components measures. The potential role of sediment parameters, pneumatophore density, and organic matter content in regulating observed patterns was assessed by multiple regression models. Densities of total and non-commercial size crabs varied mostly at 10 s m to km scales. Densities of commercial size crabs differed at the scales of 10 s m and 10 s km. Variance components indicated that small-scale variation was the most important, contributing up to 70% of the crab density variability. Multiple regression models could not explain the observed variations. Processes driving differences in crab abundance were not related to the measured variables. Small-scale patchy distribution has direct implications to current management practices of U. cordatus. Future studies should consider processes operating at smaller scales, which are responsible for a complex mosaic of patches within previously described patterns.

Space and time scales in human-landscape systems.

PubMed

Kondolf, G Mathias; Podolak, Kristen

2014-01-01

Exploring spatial and temporal scales provides a way to understand human alteration of landscape processes and human responses to these processes. We address three topics relevant to human-landscape systems: (1) scales of human impacts on geomorphic processes, (2) spatial and temporal scales in river restoration, and (3) time scales of natural disasters and behavioral and institutional responses. Studies showing dramatic recent change in sediment yields from uplands to the ocean via rivers illustrate the increasingly vast spatial extent and quick rate of human landscape change in the last two millennia, but especially in the second half of the twentieth century. Recent river restoration efforts are typically small in spatial and temporal scale compared to the historical human changes to ecosystem processes, but the cumulative effectiveness of multiple small restoration projects in achieving large ecosystem goals has yet to be demonstrated. The mismatch between infrequent natural disasters and individual risk perception, media coverage, and institutional response to natural disasters results in un-preparedness and unsustainable land use and building practices.

Multi scale habitat relationships of Martes americana in northern Idaho, U.S.A.

Treesearch

Tzeidle N. Wasserman; Samuel A. Cushman; David O. Wallin; Jim Hayden

2012-01-01

We used bivariate scaling and logistic regression to investigate multiple-scale habitat selection by American marten (Martes americana). Bivariate scaling reveals dramatic differences in the apparent nature and strength of relationships between marten occupancy and a number of habitat variables across a range of spatial scales. These differences include reversals in...

Multi-scale temporal and spatial variation in genotypic composition of Cladophora-borne Escherichia coli populations in Lake Michigan.

PubMed

Badgley, Brian D; Ferguson, John; Vanden Heuvel, Amy; Kleinheinz, Gregory T; McDermott, Colleen M; Sandrin, Todd R; Kinzelman, Julie; Junion, Emily A; Byappanahalli, Muruleedhara N; Whitman, Richard L; Sadowsky, Michael J

2011-01-01

High concentrations of Escherichia coli in mats of Cladophora in the Great Lakes have raised concern over the continued use of this bacterium as an indicator of microbial water quality. Determining the impacts of these environmentally abundant E. coli, however, necessitates a better understanding of their ecology. In this study, the population structure of 4285 Cladophora-borne E. coli isolates, obtained over multiple three day periods from Lake Michigan Cladophora mats in 2007-2009, was examined by using DNA fingerprint analyses. In contrast to previous studies that have been done using isolates from attached Cladophora obtained over large time scales and distances, the extensive sampling done here on free-floating mats over successive days at multiple sites provided a large dataset that allowed for a detailed examination of changes in population structure over a wide range of spatial and temporal scales. While Cladophora-borne E. coli populations were highly diverse and consisted of many unique isolates, multiple clonal groups were also present and accounted for approximately 33% of all isolates examined. Patterns in population structure were also evident. At the broadest scales, E. coli populations showed some temporal clustering when examined by year, but did not show good spatial distinction among sites. E. coli population structure also showed significant patterns at much finer temporal scales. Populations were distinct on an individual mat basis at a given site, and on individual days within a single mat. Results of these studies indicate that Cladophora-borne E. coli populations consist of a mixture of stable, and possibly naturalized, strains that persist during the life of the mat, and more unique, transient strains that can change over rapid time scales. It is clear that further study of microbial processes at fine spatial and temporal scales is needed, and that caution must be taken when interpolating short term microbial dynamics from results obtained from weekly or monthly samples. Copyright © 2010 Elsevier Ltd. All rights reserved.

Multi-scale temporal and spatial variation in genotypic composition of Cladophora-borne Escherichia coli populations in Lake Michigan

USGS Publications Warehouse

Badgley, B.D.; Ferguson, J.; Heuvel, A.V.; Kleinheinz, G.T.; McDermott, C.M.; Sandrin, T.R.; Kinzelman, J.; Junion, E.A.; Byappanahalli, M.N.; Whitman, R.L.; Sadowsky, M.J.

2011-01-01

High concentrations of Escherichia coli in mats of Cladophora in the Great Lakes have raised concern over the continued use of this bacterium as an indicator of microbial water quality. Determining the impacts of these environmentally abundant E. coli, however, necessitates a better understanding of their ecology. In this study, the population structure of 4285 Cladophora-borne E. coli isolates, obtained over multiple three day periods from Lake Michigan Cladophora mats in 2007-2009, was examined by using DNA fingerprint analyses. In contrast to previous studies that have been done using isolates from attached Cladophora obtained over large time scales and distances, the extensive sampling done here on free-floating mats over successive days at multiple sites provided a large dataset that allowed for a detailed examination of changes in population structure over a wide range of spatial and temporal scales. While Cladophora-borne E. coli populations were highly diverse and consisted of many unique isolates, multiple clonal groups were also present and accounted for approximately 33% of all isolates examined. Patterns in population structure were also evident. At the broadest scales, E. coli populations showed some temporal clustering when examined by year, but did not show good spatial distinction among sites. E. coli population structure also showed significant patterns at much finer temporal scales. Populations were distinct on an individual mat basis at a given site, and on individual days within a single mat. Results of these studies indicate that Cladophora-borne E. coli populations consist of a mixture of stable, and possibly naturalized, strains that persist during the life of the mat, and more unique, transient strains that can change over rapid time scales. It is clear that further study of microbial processes at fine spatial and temporal scales is needed, and that caution must be taken when interpolating short term microbial dynamics from results obtained from weekly or monthly samples.

Accuracy of stream habitat interpolations across spatial scales

USGS Publications Warehouse

Sheehan, Kenneth R.; Welsh, Stuart A.

2013-01-01

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

Mercury and methylmercury stream concentrations in a Coastal Plain watershed: a multi-scale simulation analysis.

PubMed

Knightes, C D; Golden, H E; Journey, C A; Davis, G M; Conrads, P A; Marvin-DiPasquale, M; Brigham, M E; Bradley, P M

2014-04-01

Mercury is a ubiquitous global environmental toxicant responsible for most US fish advisories. Processes governing mercury concentrations in rivers and streams are not well understood, particularly at multiple spatial scales. We investigate how insights gained from reach-scale mercury data and model simulations can be applied at broader watershed scales using a spatially and temporally explicit watershed hydrology and biogeochemical cycling model, VELMA. We simulate fate and transport using reach-scale (0.1 km(2)) study data and evaluate applications to multiple watershed scales. Reach-scale VELMA parameterization was applied to two nested sub-watersheds (28 km(2) and 25 km(2)) and the encompassing watershed (79 km(2)). Results demonstrate that simulated flow and total mercury concentrations compare reasonably to observations at different scales, but simulated methylmercury concentrations are out-of-phase with observations. These findings suggest that intricacies of methylmercury biogeochemical cycling and transport are under-represented in VELMA and underscore the complexity of simulating mercury fate and transport. Published by Elsevier Ltd.

Mercury and methylmercury stream concentrations in a Coastal Plain watershed: A multi-scale simulation analysis

EPA Science Inventory

Mercury is a ubiquitous global environmental toxicant responsible for most US fish advisories. Processes governing mercury concentrations in rivers and streams are not well understood, particularly at multiple spatial scales. We investigate how insights gained from reach-scale me...

Multivariate analysis of scale-dependent associations between bats and landscape structure

USGS Publications Warehouse

Gorresen, P.M.; Willig, M.R.; Strauss, R.E.

2005-01-01

The assessment of biotic responses to habitat disturbance and fragmentation generally has been limited to analyses at a single spatial scale. Furthermore, methods to compare responses between scales have lacked the ability to discriminate among patterns related to the identity, strength, or direction of associations of biotic variables with landscape attributes. We present an examination of the relationship of population- and community-level characteristics of phyllostomid bats with habitat features that were measured at multiple spatial scales in Atlantic rain forest of eastern Paraguay. We used a matrix of partial correlations between each biotic response variable (i.e., species abundance, species richness, and evenness) and a suite of landscape characteristics to represent the multifaceted associations of bats with spatial structure. Correlation matrices can correspond based on either the strength (i.e., magnitude) or direction (i.e., sign) of association. Therefore, a simulation model independently evaluated correspondence in the magnitude and sign of correlations among scales, and results were combined via a meta-analysis to provide an overall test of significance. Our approach detected both species-specific differences in response to landscape structure and scale dependence in those responses. This matrix-simulation approach has broad applicability to ecological situations in which multiple intercorrelated factors contribute to patterns in space or time. ?? 2005 by the Ecological Society of America.

Spatial and Temporal Dynamics of Pacific Oyster Hemolymph Microbiota across Multiple Scales

PubMed Central

Lokmer, Ana; Goedknegt, M. Anouk; Thieltges, David W.; Fiorentino, Dario; Kuenzel, Sven; Baines, John F.; Wegner, K. Mathias

2016-01-01

Unveiling the factors and processes that shape the dynamics of host associated microbial communities (microbiota) under natural conditions is an important part of understanding and predicting an organism's response to a changing environment. The microbiota is shaped by host (i.e., genetic) factors as well as by the biotic and abiotic environment. Studying natural variation of microbial community composition in multiple host genetic backgrounds across spatial as well as temporal scales represents a means to untangle this complex interplay. Here, we combined a spatially-stratified with a longitudinal sampling scheme within differentiated host genetic backgrounds by reciprocally transplanting Pacific oysters between two sites in the Wadden Sea (Sylt and Texel). To further differentiate contingent site from host genetic effects, we repeatedly sampled the same individuals over a summer season to examine structure, diversity and dynamics of individual hemolymph microbiota following experimental removal of resident microbiota by antibiotic treatment. While a large proportion of microbiome variation could be attributed to immediate environmental conditions, we observed persistent effects of antibiotic treatment and translocation suggesting that hemolymph microbial community dynamics is subject to within-microbiome interactions and host population specific factors. In addition, the analysis of spatial variation revealed that the within-site microenvironmental heterogeneity resulted in high small-scale variability, as opposed to large-scale (between-site) stability. Similarly, considerable within-individual temporal variability was in contrast with the overall temporal stability at the site level. Overall, our longitudinal, spatially-stratified sampling design revealed that variation in hemolymph microbiota is strongly influenced by site and immediate environmental conditions, whereas internal microbiome dynamics and oyster-related factors add to their long-term stability. The combination of small and large scale resolution of spatial and temporal observations therefore represents a crucial but underused tool to study host-associated microbiome dynamics. PMID:27630625

Indicators of burn severity at extended temporal scales: a decade of ecosystem response in mixed-conifer forests of western Montana

Treesearch

Sarah A. Lewis; Andrew T. Hudak; Peter R. Robichaud; Penelope Morgan; Kevin L. Satterberg; Eva K. Strand; Alistair M. S. Smith; Joseph A. Zamudio; Leigh B. Lentile

2017-01-01

We collected field and remotely sensed data spanning 10 years after three 2003 Montana wildfires to monitor ecological change across multiple temporal and spatial scales. Multiple endmember spectral mixture analysis was used to create post-fire maps of: char, soil, green (GV) and non-photosynthetic (NPV) vegetation from high-resolution 2003 hyperspectral (HS) and 2007...

Algorithmic Foundation of Spectral Rarefaction for Measuring Satellite Imagery Heterogeneity at Multiple Spatial Scales

PubMed Central

Rocchini, Duccio

2009-01-01

Measuring heterogeneity in satellite imagery is an important task to deal with. Most measures of spectral diversity have been based on Shannon Information theory. However, this approach does not inherently address different scales, ranging from local (hereafter referred to alpha diversity) to global scales (gamma diversity). The aim of this paper is to propose a method for measuring spectral heterogeneity at multiple scales based on rarefaction curves. An algorithmic solution of rarefaction applied to image pixel values (Digital Numbers, DNs) is provided and discussed. PMID:22389600

Testing for shared biogeographic history in the lower Central American freshwater fish assemblage using comparative phylogeography: concerted, independent, or multiple evolutionary responses?

PubMed Central

Bagley, Justin C; Johnson, Jerald B

2014-01-01

A central goal of comparative phylogeography is determining whether codistributed species experienced (1) concerted evolutionary responses to past geological and climatic events, indicated by congruent spatial and temporal patterns (“concerted-response hypothesis”); (2) independent responses, indicated by spatial incongruence (“independent-response hypothesis”); or (3) multiple responses (“multiple-response hypothesis”), indicated by spatial congruence but temporal incongruence (“pseudocongruence”) or spatial and temporal incongruence (“pseudoincongruence”). We tested these competing hypotheses using DNA sequence data from three livebearing fish species codistributed in the Nicaraguan depression of Central America (Alfaro cultratus, Poecilia gillii, and Xenophallus umbratilis) that we predicted might display congruent responses due to co-occurrence in identical freshwater drainages. Spatial analyses recovered different subdivisions of genetic structure for each species, despite shared finer-scale breaks in northwestern Costa Rica (also supported by phylogenetic results). Isolation-with-migration models estimated incongruent timelines of among-region divergences, with A. cultratus and Xenophallus populations diverging over Miocene–mid-Pleistocene while P. gillii populations diverged over mid-late Pleistocene. Approximate Bayesian computation also lent substantial support to multiple discrete divergences over a model of simultaneous divergence across shared spatial breaks (e.g., Bayes factor [B10] = 4.303 for Ψ [no. of divergences] > 1 vs. Ψ = 1). Thus, the data support phylogeographic pseudoincongruence consistent with the multiple-response hypothesis. Model comparisons also indicated incongruence in historical demography, for example, support for intraspecific late Pleistocene population growth was unique to P. gillii, despite evidence for finer-scale population expansions in the other taxa. Empirical tests for phylogeographic congruence indicate that multiple evolutionary responses to historical events have shaped the population structure of freshwater species codistributed within the complex landscapes in/around the Nicaraguan depression. Recent community assembly through different routes (i.e., different past distributions or colonization routes), and intrinsic ecological differences among species, has likely contributed to the unique phylogeographical patterns displayed by these Neotropical fishes. PMID:24967085

Assessment of the spatial scaling behaviour of floods in the United Kingdom

NASA Astrophysics Data System (ADS)

Formetta, Giuseppe; Stewart, Elizabeth; Bell, Victoria

2017-04-01

Floods are among the most dangerous natural hazards, causing loss of life and significant damage to private and public property. Regional flood-frequency analysis (FFA) methods are essential tools to assess the flood hazard and plan interventions for its mitigation. FFA methods are often based on the well-known index flood method that assumes the invariance of the coefficient of variation of floods with drainage area. This assumption is equivalent to the simple scaling or self-similarity assumption for peak floods, i.e. their spatial structure remains similar in a particular, relatively simple, way to itself over a range of scales. Spatial scaling of floods has been evaluated at national scale for different countries such as Canada, USA, and Australia. According our knowledge. Such a study has not been conducted for the United Kingdom even though the standard FFA method there is based on the index flood assumption. In this work we present an integrated approach to assess of the spatial scaling behaviour of floods in the United Kingdom using three different methods: product moments (PM), probability weighted moments (PWM), and quantile analysis (QA). We analyse both instantaneous and daily annual observed maximum floods and performed our analysis both across the entire country and in its sub-climatic regions as defined in the Flood Studies Report (NERC, 1975). To evaluate the relationship between the k-th moments or quantiles and the drainage area we used both regression with area alone and multiple regression considering other explanatory variables to account for the geomorphology, amount of rainfall, and soil type of the catchments. The latter multiple regression approach was only recently demonstrated being more robust than the traditional regression with area alone that can lead to biased estimates of scaling exponents and misinterpretation of spatial scaling behaviour. We tested our framework on almost 600 rural catchments in UK considered as entire region and split in 11 sub-regions with 50 catchments per region on average. Preliminary results from the three different spatial scaling methods are generally in agreement and indicate that: i) only some of the peak flow variability is explained by area alone (approximately 50% for the entire country and ranging between the 40% and 70% for the sub-regions); ii) this percentage increases to 90% for the entire country and ranges between 80% and 95% for the sub-regions when the multiple regression is used; iii) the simple scaling hypothesis holds in all sub-regions with the exception of weak multi-scaling found in the regions 2 (North), and 5 and 6 (South East). We hypothesize that these deviations can be explained by heterogeneity in large scale precipitation and by the influence of the soil type (predominantly chalk) on the flood formation process in regions 5 and 6.

[Spatial point pattern analysis of main trees and flowering Fargesia qinlingensis in Abies fargesii forests in Mt Taibai of the Qinling Mountains, China].

PubMed

Li, Guo Chun; Song, Hua Dong; Li, Qi; Bu, Shu Hai

2017-11-01

In Abies fargesii forests of the giant panda's habitats in Mt. Taibai, the spatial distribution patterns and interspecific associations of main tree species and their spatial associations with the understory flowering Fargesia qinlingensis were analyzed at multiple scales by univariate and bivaria-te O-ring function in point pattern analysis. The results showed that in the A. fargesii forest, the number of A. fargesii was largest but its population structure was in decline. The population of Betula platyphylla was relatively young, with a stable population structure, while the population of B. albo-sinensis declined. The three populations showed aggregated distributions at small scales and gradually showed random distributions with increasing spatial scales. Spatial associations among tree species were mainly showed at small scales and gradually became not spatially associated with increasing scale. A. fargesii and B. platyphylla were positively associated with flowering F. qinlingensis at large and medium scales, whereas B. albo-sinensis showed negatively associated with flowering F. qinlingensis at large and medium scales. The interaction between trees and F. qinlingensis in the habitats of giant panda promoted the dynamic succession and development of forests, which changed the environment of giant panda's habitats in Qinling.

Range-wide wetland associations of the King Rail: A multi-scale approach

USGS Publications Warehouse

Glisson, Wesley J.; Conway, Courtney J.; Nadeau, Christopher P.; Borgmann, Kathi L.; Laxson, Thomas A.

2015-01-01

King Rail populations have declined and identifying wetland features that influence King Rail occupancy can help prevent further population declines. We integrated continent-wide marsh bird survey data with spatial wetland data from the National Wetland Inventory (NWI) to examine wetland features that influenced King Rail occupancy throughout the species’ range. We analyzed wetland data at 7 spatial scales to examine the scale(s) at which 68 wetland features were most strongly related to King Rail occupancy. Occupancy was most strongly associated with estuarine features and brackish and tidal saltwater regimes. King Rail occupancy was positively associated with emergent and scrub-shrub wetlands and negatively associated with forested wetlands. The best spatial scale for assessing King Rail occupancy differed among wetland features; we could not identify one spatial scale (among all wetland features) that best explained variation in occupancy. Future research on King Rail habitat that includes multiple spatial scales is more likely to identify the suite of features that influence occupancy. Our results indicate that NWI data may be useful for predicting occupancy based on broad habitat features across the King Rail’s range, which may help inform management decisions for this and other wetland-dependent birds.

A 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...

Identifying spatially integrated floodplains/riparian areas and wetlands

EPA Science Inventory

Floodplain delineation may play an important role in managing wetlands and riparian areas at multiple scales - local, state, and federal. This poster demonstrates multiple GIS-based approaches to delimiting floodplains and contrasts these with observed flooding events from a majo...

A Bayesian method for assessing multiscalespecies-habitat relationships

USGS Publications Warehouse

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

2017-01-01

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

Wild salmon response to natural disturbance processes

Treesearch

Russ Thurow; John M. Buffington

2016-01-01

Dynamic landscapes are shaped by a variety of natural processes and disturbances operating across multiple temporal and spatial scales. Persistence of species in these dynamic environments is also a matter of scale: how do species dispersal and reproductive rates merge with the scales of disturbance?

Space-time modeling of soil moisture

NASA Astrophysics Data System (ADS)

Chen, Zijuan; Mohanty, Binayak P.; Rodriguez-Iturbe, Ignacio

2017-11-01

A physically derived space-time mathematical representation of the soil moisture field is carried out via the soil moisture balance equation driven by stochastic rainfall forcing. The model incorporates spatial diffusion and in its original version, it is shown to be unable to reproduce the relative fast decay in the spatial correlation functions observed in empirical data. This decay resulting from variations in local topography as well as in local soil and vegetation conditions is well reproduced via a jitter process acting multiplicatively over the space-time soil moisture field. The jitter is a multiplicative noise acting on the soil moisture dynamics with the objective to deflate its correlation structure at small spatial scales which are not embedded in the probabilistic structure of the rainfall process that drives the dynamics. These scales of order of several meters to several hundred meters are of great importance in ecohydrologic dynamics. Properties of space-time correlation functions and spectral densities of the model with jitter are explored analytically, and the influence of the jitter parameters, reflecting variabilities of soil moisture at different spatial and temporal scales, is investigated. A case study fitting the derived model to a soil moisture dataset is presented in detail.

Evaluating habitat associations of a fish assemblage at multiple spatial scales in a minimally disturbed stream using low-cost remote sensing

USGS Publications Warehouse

Cheek, Brandon D.; Grabowski, Timothy B.; Bean, Preston T.; Groeschel, Jillian R.; Magnelia, Stephan J.

2016-01-01

Habitat heterogeneity at multiple scales is a major factor affecting fish assemblage structure. However, assessments that examine these relationships at multiple scales concurrently are lacking. The lack of assessments at these scales is a critical gap in understanding as conservation and restoration efforts typically work at these levels.A combination of low-cost side-scan sonar surveys, aerial imagery using an unmanned aerial vehicle, and fish collections were used to evaluate the relationship between physicochemical and landscape variables at various spatial scales (e.g. micro-mesohabitat, mesohabitat, channel unit, stream reach) and stream–fish assemblage structure and habitat associations in the South Llano River, a spring-fed second-order stream on the Edwards Plateau in central Texas during 2012–2013.Low-cost side-scan sonar surveys have not typically been used to generate data for riverscape assessments of assemblage structure, thus the secondary objective was to assess the efficacy of this approach.The finest spatial scale (micro-mesohabitat) and the intermediate scale (channel unit) had the greatest explanatory power for variation in fish assemblage structure.Many of the fish endemic to the Edwards Plateau showed similar associations with physicochemical and landscape variables suggesting that conservation and restoration actions targeting a single endemic species may provide benefits to a large proportion of the endemic species in this system.Low-cost side-scan sonar proved to be a cost-effective means of acquiring information on the habitat availability of the entire river length and allowed the assessment of how a full suite of riverscape-level variables influenced local fish assemblage structure.

Multi-scale interactions between local hydrography, seabed topography, and community assembly on cold-water coral reefs

NASA Astrophysics Data System (ADS)

Henry, L.-A.; Moreno Navas, J.; Roberts, J. M.

2013-04-01

We investigated how interactions between hydrography, topography and species ecology influence the assembly of species and functional traits across multiple spatial scales of a cold-water coral reef seascape. In a novel approach for these ecosystems, we used a spatially resolved complex three-dimensional flow model of hydrography to help explain assembly patterns. Forward-selection of distance-based Moran's eigenvector mapping (dbMEM) variables identified two submodels of spatial scales at which communities change: broad-scale (across reef) and fine-scale (within reef). Variance partitioning identified bathymetric and hydrographic gradients important in creating broad-scale assembly of species and traits. In contrast, fine-scale assembly was related more to processes that created spatially autocorrelated patches of fauna, such as philopatric recruitment in sessile fauna, and social interactions and food supply in scavenging detritivores and mobile predators. Our study shows how habitat modification of reef connectivity and hydrography by bottom fishing and renewable energy installations could alter the structure and function of an entire cold-water coral reef seascape.

Hybrid Modeling Approach to Estimate Exposures of Hazardous Air Pollutants (HAPs) for the National Air Toxics Assessment (NATA).

PubMed

Scheffe, Richard D; Strum, Madeleine; Phillips, Sharon B; Thurman, James; Eyth, Alison; Fudge, Steve; Morris, Mark; Palma, Ted; Cook, Richard

2016-11-15

A hybrid air quality model has been developed and applied to estimate annual concentrations of 40 hazardous air pollutants (HAPs) across the continental United States (CONUS) to support the 2011 calendar year National Air Toxics Assessment (NATA). By combining a chemical transport model (CTM) with a Gaussian dispersion model, both reactive and nonreactive HAPs are accommodated across local to regional spatial scales, through a multiplicative technique designed to improve mass conservation relative to previous additive methods. The broad scope of multiple pollutants capturing regional to local spatial scale patterns across a vast spatial domain is precedent setting within the air toxics community. The hybrid design exhibits improved performance relative to the stand alone CTM and dispersion model. However, model performance varies widely across pollutant categories and quantifiably definitive performance assessments are hampered by a limited observation base and challenged by the multiple physical and chemical attributes of HAPs. Formaldehyde and acetaldehyde are the dominant HAP concentration and cancer risk drivers, characterized by strong regional signals associated with naturally emitted carbonyl precursors enhanced in urban transport corridors with strong mobile source sector emissions. The multiple pollutant emission characteristics of combustion dominated source sectors creates largely similar concentration patterns across the majority of HAPs. However, reactive carbonyls exhibit significantly less spatial variability relative to nonreactive HAPs across the CONUS.

A COMPARISON OF INTERCELL METRICS ON DISCRETE GLOBAL GRID SYSTEMS

EPA Science Inventory

A discrete global grid system (DGGS) is a spatial data model that aids in global research by serving as a framework for environmental modeling, monitoring and sampling across the earth at multiple spatial scales. Topological and geometric criteria have been proposed to evaluate a...

ASSESSING THE ACCURACY OF NATIONAL LAND COVER DATASET AREA ESTIMATES AT MULTIPLE SPATIAL EXTENTS

EPA Science Inventory

Site specific accuracy assessments provide fine-scale evaluation of the thematic accuracy of land use/land cover (LULC) datasets; however, they provide little insight into LULC accuracy across varying spatial extents. Additionally, LULC data are typically used to describe lands...

Genetic analysis across differential spatial scales reveals multiple dispersal mechanisms for the invasive hydrozoan Cordylophora in the Great Lakes

EPA Science Inventory

Understanding patterns of post-establishment spread by invasive species is critically important for the design of effective management strategies and the development of appropriate theoretical models predicting spatial expansion of introduced populations. Here we explore genetic ...

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...

Insights and challenges to Intergrating data from diverse ecological networks

USDA-ARS?s Scientific Manuscript database

Many of the most dramatic and surprising effects of global change occur across large spatial extents, from regions to continents, that impact multiple ecosystem types across a range of interacting spatial and temporal scales. The ability of ecologists and interdisciplinary scientists to understand a...

Exploring seascape genetics and kinship in the reef sponge Stylissa carteri in the Red Sea

PubMed Central

Giles, Emily C; Saenz-Agudelo, Pablo; Hussey, Nigel E; Ravasi, Timothy; Berumen, Michael L

2015-01-01

A main goal of population geneticists is to study patterns of gene flow to gain a better understanding of the population structure in a given organism. To date most efforts have been focused on studying gene flow at either broad scales to identify barriers to gene flow and isolation by distance or at fine spatial scales in order to gain inferences regarding reproduction and local dispersal. Few studies have measured connectivity at multiple spatial scales and have utilized novel tools to test the influence of both environment and geography on shaping gene flow in an organism. Here a seascape genetics approach was used to gain insight regarding geographic and ecological barriers to gene flow of a common reef sponge, Stylissa carteri in the Red Sea. Furthermore, a small-scale (<1 km) analysis was also conducted to infer reproductive potential in this organism. At the broad scale, we found that sponge connectivity is not structured by geography alone, but rather, genetic isolation in the southern Red Sea correlates strongly with environmental heterogeneity. At the scale of a 50-m transect, spatial autocorrelation analyses and estimates of full-siblings revealed that there is no deviation from random mating. However, at slightly larger scales (100–200 m) encompassing multiple transects at a given site, a greater proportion of full-siblings was found within sites versus among sites in a given location suggesting that mating and/or dispersal are constrained to some extent at this spatial scale. This study adds to the growing body of literature suggesting that environmental and ecological variables play a major role in the genetic structure of marine invertebrate populations. PMID:26257865

Spatial-pattern-induced evolution of a self-replicating loop network.

PubMed

Suzuki, Keisuke; Ikegami, Takashi

2006-01-01

We study a system of self-replicating loops in which interaction rules between individuals allow competition that leads to the formation of a hypercycle-like network. The main feature of the model is the multiple layers of interaction between loops, which lead to both global spatial patterns and local replication. The network of loops manifests itself as a spiral structure from which new kinds of self-replicating loops emerge at the boundaries between different species. In these regions, larger and more complex self-replicating loops live for longer periods of time, managing to self-replicate in spite of their slower replication. Of particular interest is how micro-scale interactions between replicators lead to macro-scale spatial pattern formation, and how these macro-scale patterns in turn perturb the micro-scale replication dynamics.

Genetic analysis across different spatial scales reveals multiple dispersal mechanisms for the invasive hydrozoan Cordylophora in the Great Lakes.

PubMed

Darling, John A; Folino-Rorem, Nadine C

2009-12-01

Discerning patterns of post-establishment spread by invasive species is critically important for the design of effective management strategies and the development of appropriate theoretical models predicting spatial expansion of introduced populations. The globally invasive colonial hydrozoan Cordylophora produces propagules both sexually and vegetatively and is associated with multiple potential dispersal mechanisms, making it a promising system to investigate complex patterns of population structure generated throughout the course of rapid range expansion. Here, we explore genetic patterns associated with the spread of this taxon within the North American Great Lakes basin. We collected intensively from eight harbours in the Chicago area in order to conduct detailed investigation of local population expansion. In addition, we collected from Lakes Michigan, Erie, and Ontario, as well as Lake Cayuga in the Finger Lakes of upstate New York in order to assess genetic structure on a regional scale. Based on data from eight highly polymorphic microsatellite loci we examined the spatial extent of clonal genotypes, assessed levels of neutral genetic diversity, and explored patterns of migration and dispersal at multiple spatial scales through assessment of population level genetic differentiation (pairwise F(ST) and factorial correspondence analysis), Bayesian inference of population structure, and assignment tests on individual genotypes. Results of these analyses indicate that Cordylophora populations in this region spread predominantly through sexually produced propagules, and that while limited natural larval dispersal can drive expansion locally, regional expansion likely relies on anthropogenic dispersal vectors.

Multi-scale occupancy estimation and modelling using multiple detection methods

USGS Publications Warehouse

Nichols, James D.; Bailey, Larissa L.; O'Connell, Allan F.; Talancy, Neil W.; Grant, Evan H. Campbell; Gilbert, Andrew T.; Annand, Elizabeth M.; Husband, Thomas P.; Hines, James E.

2008-01-01

Occupancy estimation and modelling based on detection–nondetection data provide an effective way of exploring change in a species’ distribution across time and space in cases where the species is not always detected with certainty. Today, many monitoring programmes target multiple species, or life stages within a species, requiring the use of multiple detection methods. When multiple methods or devices are used at the same sample sites, animals can be detected by more than one method.We develop occupancy models for multiple detection methods that permit simultaneous use of data from all methods for inference about method-specific detection probabilities. Moreover, the approach permits estimation of occupancy at two spatial scales: the larger scale corresponds to species’ use of a sample unit, whereas the smaller scale corresponds to presence of the species at the local sample station or site.We apply the models to data collected on two different vertebrate species: striped skunks Mephitis mephitis and red salamanders Pseudotriton ruber. For striped skunks, large-scale occupancy estimates were consistent between two sampling seasons. Small-scale occupancy probabilities were slightly lower in the late winter/spring when skunks tend to conserve energy, and movements are limited to males in search of females for breeding. There was strong evidence of method-specific detection probabilities for skunks. As anticipated, large- and small-scale occupancy areas completely overlapped for red salamanders. The analyses provided weak evidence of method-specific detection probabilities for this species.Synthesis and applications. Increasingly, many studies are utilizing multiple detection methods at sampling locations. The modelling approach presented here makes efficient use of detections from multiple methods to estimate occupancy probabilities at two spatial scales and to compare detection probabilities associated with different detection methods. The models can be viewed as another variation of Pollock's robust design and may be applicable to a wide variety of scenarios where species occur in an area but are not always near the sampled locations. The estimation approach is likely to be especially useful in multispecies conservation programmes by providing efficient estimates using multiple detection devices and by providing device-specific detection probability estimates for use in survey design.

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.

Spatially extended hybrid methods: a review

PubMed Central

2018-01-01

Many biological and physical systems exhibit behaviour at multiple spatial, temporal or population scales. Multiscale processes provide challenges when they are to be simulated using numerical techniques. While coarser methods such as partial differential equations are typically fast to simulate, they lack the individual-level detail that may be required in regions of low concentration or small spatial scale. However, to simulate at such an individual level throughout a domain and in regions where concentrations are high can be computationally expensive. Spatially coupled hybrid methods provide a bridge, allowing for multiple representations of the same species in one spatial domain by partitioning space into distinct modelling subdomains. Over the past 20 years, such hybrid methods have risen to prominence, leading to what is now a very active research area across multiple disciplines including chemistry, physics and mathematics. There are three main motivations for undertaking this review. Firstly, we have collated a large number of spatially extended hybrid methods and presented them in a single coherent document, while comparing and contrasting them, so that anyone who requires a multiscale hybrid method will be able to find the most appropriate one for their need. Secondly, we have provided canonical examples with algorithms and accompanying code, serving to demonstrate how these types of methods work in practice. Finally, we have presented papers that employ these methods on real biological and physical problems, demonstrating their utility. We also consider some open research questions in the area of hybrid method development and the future directions for the field. PMID:29491179

Toward daily monitoring of vegetation conditions at field scale through fusing data from multiple sensors

USDA-ARS?s Scientific Manuscript database

Vegetation monitoring requires remote sensing data at fine spatial and temporal resolution. While imagery from coarse resolution sensors such as MODIS/VIIRS can provide daily observations, they lack spatial detail to capture surface features for crop and rangeland monitoring. The Landsat satellite s...

LAND USE AND LOTIC DIATOM ASSEMBLAGES: A MULTI-SPATIAL AND TEMPORAL ASSESSMENT

EPA Science Inventory

We assessed the effects of land-use at multiple spatial scales (e.g., catchment, stream network, and stream reach) on periphyton from 25 wadeable streams along a land-use gradient in the Willamette River Basin, Oregon, in a dry season. Additional water chemistry samples were col...

Multiple drivers, scales, and interactions influence southern Appalachian stream salamander occupancy

Treesearch

Kristen K. Cecala; John C. Maerz; Brian J. Halstead; John R. Frisch; Ted L. Gragson; Jeffrey Hepinstall-Cymerman; David S. Leigh; C. Rhett Jackson; James T. Peterson; Catherine M. Pringle

2018-01-01

Understanding how factors that vary in spatial scale relate to population abundance is vital to forecasting species responses to environmental change. Stream and river ecosystems are inherently hierarchical, potentially resulting in organismal responses to fine‐scale changes in patch characteristics that are conditional on the watershed context. Here, we...

Competition between stink bug and heliothine caterpillar pests on cotton at within-plant spatial scales

USDA-ARS?s Scientific Manuscript database

We investigated competition between Heliothine larvae and the secondary pests, southern green and brown stink bugs at the single boll and multiple boll scales; if competition does not occur with this very close association, it might be unlikely at larger scales with less close association. In both ...

Interpreting multiscale domains of tree cover disturbance patterns in North America

Treesearch

Kurt Riitters; Jennifer K. Costanza; Brian Buma

2017-01-01

Spatial patterns at multiple observation scales provide a framework to improve understanding of pattern-related phenomena. However, the metrics that are most sensitive to local patterns are least likely to exhibit consistent scaling relations with increasing extent (observation scale). A conceptual framework based on multiscale domains (i.e., geographic locations...

Influence of landscape structure on reef fish assemblages

USGS Publications Warehouse

Grober-Dunsmore, R.; Frazer, T.K.; Beets, J.P.; Lindberg, W.J.; Zwick, P.; Funicelli, N.A.

2008-01-01

Management of tropical marine environments calls for interdisciplinary studies and innovative methodologies that consider processes occurring over broad spatial scales. We investigated relationships between landscape structure and reef fish assemblage structure in the US Virgin Islands. Measures of landscape structure were transformed into a reduced set of composite indices using principal component analyses (PCA) to synthesize data on the spatial patterning of the landscape structure of the study reefs. However, composite indices (e.g., habitat diversity) were not particularly informative for predicting reef fish assemblage structure. Rather, relationships were interpreted more easily when functional groups of fishes were related to individual habitat features. In particular, multiple reef fish parameters were strongly associated with reef context. Fishes responded to benthic habitat structure at multiple spatial scales, with various groups of fishes each correlated to a unique suite of variables. Accordingly, future experiments should be designed to test functional relationships based on the ecology of the organisms of interest. Our study demonstrates that landscape-scale habitat features influence reef fish communities, illustrating promise in applying a landscape ecology approach to better understand factors that structure coral reef ecosystems. Furthermore, our findings may prove useful in design of spatially-based conservation approaches such as marine protected areas (MPAs), because landscape-scale metrics may serve as proxies for areas with high species diversity and abundance within the coral reef landscape. ?? 2007 Springer Science+Business Media B.V.

Attention Modulates Spatial Precision in Multiple-Object Tracking.

PubMed

Srivastava, Nisheeth; Vul, Ed

2016-01-01

We present a computational model of multiple-object tracking that makes trial-level predictions about the allocation of visual attention and the effect of this allocation on observers' ability to track multiple objects simultaneously. This model follows the intuition that increased attention to a location increases the spatial resolution of its internal representation. Using a combination of empirical and computational experiments, we demonstrate the existence of a tight coupling between cognitive and perceptual resources in this task: Low-level tracking of objects generates bottom-up predictions of error likelihood, and high-level attention allocation selectively reduces error probabilities in attended locations while increasing it at non-attended locations. Whereas earlier models of multiple-object tracking have predicted the big picture relationship between stimulus complexity and response accuracy, our approach makes accurate predictions of both the macro-scale effect of target number and velocity on tracking difficulty and micro-scale variations in difficulty across individual trials and targets arising from the idiosyncratic within-trial interactions of targets and distractors. Copyright © 2016 Cognitive Science Society, Inc.

DETECTING INTERACTIONS BETWEEN ELLIPTIO WACCAMAWENSIS AND LEPTODEA OCHRACEA: THE INFLUENCE OF EXPERIMENTAL SCALE.

EPA Science Inventory

Manipulative field experiments are used in ecology to study biotic interactions in populations and communities. In benthic suspension-feeding organisms, these interactions can occur over multiple spatial scales, but this has rarely received experimental attention. A field experim...

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Spatial Statistical and Modeling Strategy for Inventorying and Monitoring Ecosystem Resources at Multiple Scales and Resolution Levels

Treesearch

Robin M. Reich; C. Aguirre-Bravo; M.S. Williams

2006-01-01

A statistical strategy for spatial estimation and modeling of natural and environmental resource variables and indicators is presented. This strategy is part of an inventory and monitoring pilot study that is being carried out in the Mexican states of Jalisco and Colima. Fine spatial resolution estimates of key variables and indicators are outputs that will allow the...

Scale dependence in habitat selection: The case of the endangered brown bear (Ursus arctos) in the Cantabrian Range (NW Spain)

Treesearch

Maria C. Mateo Sanchez; Samuel A. Cushman; Santiago Saura

2013-01-01

Animals select habitat resources at multiple spatial scales. Thus, explicit attention to scale dependency in species-habitat relationships is critical to understand the habitat suitability patterns as perceived by organisms in complex landscapes. Identification of the scales at which particular environmental variables influence habitat selection may be as important as...

Seed harvesting by a generalist consumer is context-dependent: Interactive effects across multiple spatial scales

USGS Publications Warehouse

Ostoja, Steven M.; Schupp, Eugene W.; Klinger, Rob

2013-01-01

Granivore foraging decisions affect consumer success and determine the quantity and spatial pattern of seed survival. These decisions are influenced by environmental variation at spatial scales ranging from landscapes to local foraging patches. In a field experiment, the effects of seed patch variation across three spatial scales on seed removal by western harvester ants Pogonomyrmex occidentalis were evaluated. At the largest scale we assessed harvesting in different plant communities, at the intermediate scale we assessed harvesting at different distances from ant mounds, and at the smallest scale we assessed the effects of interactions among seed species in local seed neighborhoods on seed harvesting (i.e. resource–consumer interface). Selected seed species were presented alone (monospecific treatment) and in mixture with Bromus tectorum (cheatgrass; mixture treatment) at four distances from P. occidentalis mounds in adjacent intact sagebrush and non-native cheatgrass-dominated communities in the Great Basin, Utah, USA. Seed species differed in harvest, with B. tectorum being least preferred. Large and intermediate scale variation influenced harvest. More seeds were harvested in sagebrush than in cheatgrass-dominated communities (largest scale), and the quantity of seed harvested varied with distance from mounds (intermediate-scale), although the form of the distance effect differed between plant communities. At the smallest scale, seed neighborhood affected harvest, but the patterns differed among seed species considered. Ants harvested fewer seeds from mixed-seed neighborhoods than from monospecific neighborhoods, suggesting context dependence and potential associational resistance. Further, the effects of plant community and distance from mound on seed harvest in mixtures differed from their effects in monospecific treatments. Beyond the local seed neighborhood, selection of seed resources is better understood by simultaneously evaluating removal at multiple scales. Associational effects provide a useful theoretical basis for better understanding harvester ant foraging decisions. These results demonstrate the importance of ecological context for seed removal, which has implications for seed pools, plant populations and communities.

Multi-scale geophysical study to model the distribution and development of fractures in relation to the knickpoint in the Luquillo Critical Zone Observatory (Puerto Rico)

NASA Astrophysics Data System (ADS)

Comas, X.; Wright, W. J.; Hynek, S. A.; Ntarlagiannis, D.; Terry, N.; Job, M. J.; Fletcher, R. C.; Brantley, S.

2017-12-01

Previous studies in the Rio Icacos watershed in the Luquillo Mountains (Puerto Rico) have shown that regolith materials are rapidly developed from the alteration of quartz diorite bedrock, and create a blanket on top of the bedrock with a thickness that decreases with proximity to the knickpoint. The watershed is also characterized by a system of heterogeneous fractures that likely drive bedrock weathering and the formation of corestones and associated spheroidal fracturing and rindlets. Previous efforts to characterize the spatial distribution of fractures were based on aerial images that did not account for the architecture of the critical zone below the subsurface. In this study we use an array of near-surface geophysical methods at multiple scales to better understand how the spatial distribution and density of fractures varies with topography and proximity to the knickpoint. Large km-scale surveys using ground penetrating radar (GPR), terrain conductivity, and capacitively coupled resistivity, were combined with smaller scale surveys (10-100 m) using electrical resistivity imaging (ERI), and shallow seismics, and were directly constrained with boreholes from previous studies. Geophysical results were compared to theoretical models of compressive stress as due to gravity and regional compression, and showed consistency at describing increased dilation of fractures with proximity to the knickpoint. This study shows the potential of multidisciplinary approaches to model critical zone processes at multiple scales of measurement and high spatial resolution. The approach can be particularly efficient at large km-scales when applying geophysical methods that allow for rapid data acquisition (i.e. walking pace) at high spatial resolution (i.e. cm scales).

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Mushroom biomass and diversity are driven by different spatio-temporal scales along Mediterranean elevation gradients

NASA Astrophysics Data System (ADS)

Alday, Josu G.; Martínez de Aragón, Juan; de-Miguel, Sergio; Bonet, José Antonio

2017-04-01

Mushrooms are important non-wood-forest-products in many Mediterranean ecosystems, being highly vulnerable to climate change. However, the ecological scales of variation of mushroom productivity and diversity, and climate dependence has been usually overlooked due to a lack of available data. We determined the spatio-temporal variability of epigeous sporocarps and the climatic factors driving their fruiting to plan future sustainable management of wild mushrooms production. We collected fruiting bodies in Pinus sylvestris stands along an elevation gradient for 8 consecutive years. Overall, sporocarp biomass was mainly dependent on inter-annual variations, whereas richness was more spatial-scale dependent. Elevation was not significant, but there were clear elevational differences in biomass and richness patterns between ectomycorrhizal and saprotrophic guilds. The main driver of variation was late-summer-early-autumn precipitation. Thus, different scale processes (inter-annual vs. spatial-scale) drive sporocarp biomass and diversity patterns; temporal effects for biomass and ectomycorrhizal fungi vs. spatial scale for diversity and saprotrophic fungi. The significant role of precipitation across fungal guilds and spatio-temporal scales indicates that it is a limiting resource controlling sporocarp production and diversity in Mediterranean regions. The high spatial and temporal variability of mushrooms emphasize the need for long-term datasets of multiple spatial points to effectively characterize fungal fruiting patterns.

Multiple scales in metapopulations of public goods producers

NASA Astrophysics Data System (ADS)

Bauer, Marianne; Frey, Erwin

2018-04-01

Multiple scales in metapopulations can give rise to paradoxical behavior: in a conceptual model for a public goods game, the species associated with a fitness cost due to the public good production can be stabilized in the well-mixed limit due to the mere existence of these scales. The scales in this model involve a length scale corresponding to separate patches, coupled by mobility, and separate time scales for reproduction and interaction with a local environment. Contrary to the well-mixed high mobility limit, we find that for low mobilities, the interaction rate progressively stabilizes this species due to stochastic effects, and that the formation of spatial patterns is not crucial for this stabilization.

Predicting and quantifying soil processes using “geomorphon” landform Classification

USDA-ARS?s Scientific Manuscript database

Soil development and behavior vary spatially at multiple observation scales. Predicting and quantifying soil properties and processes via a catena integrates predictable landscape scale variation relevant to both management decisions and soil survey. Soil maps generally convey variation as a set of ...

TEMPORAL CHANGE IN FOREST FRAGMENTATION AT MULTIPLE SCALES

EPA Science Inventory

Previous studies of temporal changes in fragmentation have focused almost exclusively on patch and edge statistics, which might not detect changes in the spatial scale at which forest occurs in or dominates the landscape. We used temporal land-cover data for the Chesapeake Bay r...

Transboundary fisheries science: Meeting the challenges of inland fisheries management in the 21st century

USGS Publications Warehouse

Midway, Stephen R.; Wagner, Tyler; Zydlewski, Joseph D.; Irwin, Brian J.; Paukert, Craig P.

2016-01-01

Managing inland fisheries in the 21st century presents several obstacles, including the need to view fisheries from multiple spatial and temporal scales, which usually involves populations and resources spanning sociopolitical boundaries. Though collaboration is not new to fisheries science, inland aquatic systems have historically been managed at local scales and present different challenges than in marine or large freshwater systems like the Laurentian Great Lakes. Therefore, we outline a flexible strategy that highlights organization, cooperation, analytics, and implementation as building blocks toward effectively addressing transboundary fisheries issues. Additionally, we discuss the use of Bayesian hierarchical models (within the analytical stage), due to their flexibility in dealing with the variability present in data from multiple scales. With growing recognition of both ecological drivers that span spatial and temporal scales and the subsequent need for collaboration to effectively manage heterogeneous resources, we expect implementation of transboundary approaches to become increasingly critical for effective inland fisheries management.

Stochastic Downscaling of Digital Elevation Models

NASA Astrophysics Data System (ADS)

Rasera, Luiz Gustavo; Mariethoz, Gregoire; Lane, Stuart N.

2016-04-01

High-resolution digital elevation models (HR-DEMs) are extremely important for the understanding of small-scale geomorphic processes in Alpine environments. In the last decade, remote sensing techniques have experienced a major technological evolution, enabling fast and precise acquisition of HR-DEMs. However, sensors designed to measure elevation data still feature different spatial resolution and coverage capabilities. Terrestrial altimetry allows the acquisition of HR-DEMs with centimeter to millimeter-level precision, but only within small spatial extents and often with dead ground problems. Conversely, satellite radiometric sensors are able to gather elevation measurements over large areas but with limited spatial resolution. In the present study, we propose an algorithm to downscale low-resolution satellite-based DEMs using topographic patterns extracted from HR-DEMs derived for example from ground-based and airborne altimetry. The method consists of a multiple-point geostatistical simulation technique able to generate high-resolution elevation data from low-resolution digital elevation models (LR-DEMs). Initially, two collocated DEMs with different spatial resolutions serve as an input to construct a database of topographic patterns, which is also used to infer the statistical relationships between the two scales. High-resolution elevation patterns are then retrieved from the database to downscale a LR-DEM through a stochastic simulation process. The output of the simulations are multiple equally probable DEMs with higher spatial resolution that also depict the large-scale geomorphic structures present in the original LR-DEM. As these multiple models reflect the uncertainty related to the downscaling, they can be employed to quantify the uncertainty of phenomena that are dependent on fine topography, such as catchment hydrological processes. The proposed methodology is illustrated for a case study in the Swiss Alps. A swissALTI3D HR-DEM (with 5 m resolution) and a SRTM-derived LR-DEM from the Western Alps are used to downscale a SRTM-based LR-DEM from the eastern part of the Alps. The results show that the method is capable of generating multiple high-resolution synthetic DEMs that reproduce the spatial structure and statistics of the original DEM.

Control factors and scale analysis of annual river water, sediments and carbon transport in China.

PubMed

Song, Chunlin; Wang, Genxu; Sun, Xiangyang; Chang, Ruiying; Mao, Tianxu

2016-05-11

Under the context of dramatic human disturbances on river system, the processes that control the transport of water, sediment, and carbon from river basins to coastal seas are not completely understood. Here we performed a quantitative synthesis for 121 sites across China to find control factors of annual river exports (Rc: runoff coefficient; TSSC: total suspended sediment concentration; TSSL: total suspended sediment loads; TOCL: total organic carbon loads) at different spatial scales. The results indicated that human activities such as dam construction and vegetation restoration might have a greater influence than climate on the transport of river sediment and carbon, although climate was a major driver of Rc. Multiple spatial scale analyses indicated that Rc increased from the small to medium scale by 20% and then decreased at the sizable scale by 20%. TSSC decreased from the small to sizeable scale but increase from the sizeable to large scales; however, TSSL significantly decreased from small (768 g·m(-2)·a(-1)) to medium spatial scale basins (258 g·m(-2)·a(-1)), and TOCL decreased from the medium to large scale. Our results will improve the understanding of water, sediment and carbon transport processes and contribute better water and land resources management strategies from different spatial scales.

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Floodplain complexity and surface metrics: influences of scale and geomorphology

USGS Publications Warehouse

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

2015-01-01

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

Hiding in Plain Sight: A Case for Cryptic Metapopulations in Brook Trout (Salvelinus fontinalis)

PubMed Central

Kazyak, David C.; Hilderbrand, Robert H.; King, Tim L.; Keller, Stephen R.; Chhatre, Vikram E.

2016-01-01

A fundamental issue in the management and conservation of biodiversity is how to define a population. Spatially contiguous fish occupying a stream network have often been considered to represent a single, homogenous population. However, they may also represent multiple discrete populations, a single population with genetic isolation-by-distance, or a metapopulation. We used microsatellite DNA and a large-scale mark-recapture study to assess population structure in a spatially contiguous sample of Brook Trout (Salvelinus fontinalis), a species of conservation concern. We found evidence for limited genetic exchange across small spatial scales and in the absence of barriers to physical movement. Mark-recapture and stationary passive integrated transponder antenna records demonstrated that fish from two tributaries very seldom moved into the opposite tributary, but movements between the tributaries and mainstem were more common. Using Bayesian genetic clustering, we identified two genetic groups that exhibited significantly different growth rates over three years of study, yet survival rates were very similar. Our study highlights the importance of considering the possibility of multiple genetically distinct populations occurring within spatially contiguous habitats, and suggests the existence of a cryptic metapopulation: a spatially continuous distribution of organisms exhibiting metapopulation-like behaviors. PMID:26730588

Hiding in Plain Sight: A Case for Cryptic Metapopulations in Brook Trout (Salvelinus fontinalis).

PubMed

Kazyak, David C; Hilderbrand, Robert H; King, Tim L; Keller, Stephen R; Chhatre, Vikram E

2016-01-01

A fundamental issue in the management and conservation of biodiversity is how to define a population. Spatially contiguous fish occupying a stream network have often been considered to represent a single, homogenous population. However, they may also represent multiple discrete populations, a single population with genetic isolation-by-distance, or a metapopulation. We used microsatellite DNA and a large-scale mark-recapture study to assess population structure in a spatially contiguous sample of Brook Trout (Salvelinus fontinalis), a species of conservation concern. We found evidence for limited genetic exchange across small spatial scales and in the absence of barriers to physical movement. Mark-recapture and stationary passive integrated transponder antenna records demonstrated that fish from two tributaries very seldom moved into the opposite tributary, but movements between the tributaries and mainstem were more common. Using Bayesian genetic clustering, we identified two genetic groups that exhibited significantly different growth rates over three years of study, yet survival rates were very similar. Our study highlights the importance of considering the possibility of multiple genetically distinct populations occurring within spatially contiguous habitats, and suggests the existence of a cryptic metapopulation: a spatially continuous distribution of organisms exhibiting metapopulation-like behaviors.

Delineation and validation of river network spatial scales for water resources and fisheries management.

PubMed

Wang, Lizhu; Brenden, Travis; Cao, Yong; Seelbach, Paul

2012-11-01

Identifying appropriate spatial scales is critically important for assessing health, attributing data, and guiding management actions for rivers. We describe a process for identifying a three-level hierarchy of spatial scales for Michigan rivers. Additionally, we conduct a variance decomposition of fish occurrence, abundance, and assemblage metric data to evaluate how much observed variability can be explained by the three spatial scales as a gage of their utility for water resources and fisheries management. The process involved the development of geographic information system programs, statistical models, modification by experienced biologists, and simplification to meet the needs of policy makers. Altogether, 28,889 reaches, 6,198 multiple-reach segments, and 11 segment classes were identified from Michigan river networks. The segment scale explained the greatest amount of variation in fish abundance and occurrence, followed by segment class, and reach. Segment scale also explained the greatest amount of variation in 13 of the 19 analyzed fish assemblage metrics, with segment class explaining the greatest amount of variation in the other six fish metrics. Segments appear to be a useful spatial scale/unit for measuring and synthesizing information for managing rivers and streams. Additionally, segment classes provide a useful typology for summarizing the numerous segments into a few categories. Reaches are the foundation for the identification of segments and segment classes and thus are integral elements of the overall spatial scale hierarchy despite reaches not explaining significant variation in fish assemblage data.

HIS Design: Big Data that Supports Hydrologic Modeling from Continental to Hillslope Scales

NASA Astrophysics Data System (ADS)

Rasmussen, T. C.; Deemy, J. B.; Younger, S. E.; Kirk, S. E.; Brockman, L. E.

2016-12-01

Analogous to Google Maps, hydrologic data, information, and knowledge resolve differently depending upon the spatial and temporal scales of interest. We show how a multi-scale hydrologic information system (HIS) can be designed and populated for a broad range of spatial (e.g., hillslope, local, regional, continental) and temporal (e.g., current, recent, historic, geologic) scales. Surface and subsurface hydrologic and transport processes are assumed to be scale-dependent, requiring unique governing equations and parameters at each scale. This robust and flexible framework is designed to meet the inventory, monitoring, and management needs of multiple federal agencies (i.e., Forest Service, National Park Service, Fish and Wildlife Service, National Wildlife Reserves). Multi-scale HIS examples are provided using Geographic Information Systems (GIS) for the Southeastern US.

The patch mosaic and ecological decomposition across spatial scales in a managed landscape of northern Wisconsin, USA

Treesearch

Sari C. ​Saunders; Jiquan Chen; Thomas D. Drummer; Thomas R. Crow; Kimberley D. Brosofske; Eric J. Gustafson

2002-01-01

Understanding landscape organization across scales is vital for determining the impacts of management and retaining structurally and functionally diverse ecosystems. We studied the relationships of a functional variable, decomposition, to microclimatic, vegetative and structural features at multiple scales in two distinct landscapes of northern Wisconsin, USA. We hoped...

Multiple Point Statistics algorithm based on direct sampling and multi-resolution images

NASA Astrophysics Data System (ADS)

Julien, S.; Renard, P.; Chugunova, T.

2017-12-01

Multiple Point Statistics (MPS) has become popular for more than one decade in Earth Sciences, because these methods allow to generate random fields reproducing highly complex spatial features given in a conceptual model, the training image, while classical geostatistics techniques based on bi-point statistics (covariance or variogram) fail to generate realistic models. Among MPS methods, the direct sampling consists in borrowing patterns from the training image to populate a simulation grid. This latter is sequentially filled by visiting each of these nodes in a random order, and then the patterns, whose the number of nodes is fixed, become narrower during the simulation process, as the simulation grid is more densely informed. Hence, large scale structures are caught in the beginning of the simulation and small scale ones in the end. However, MPS may mix spatial characteristics distinguishable at different scales in the training image, and then loose the spatial arrangement of different structures. To overcome this limitation, we propose to perform MPS simulation using a decomposition of the training image in a set of images at multiple resolutions. Applying a Gaussian kernel onto the training image (convolution) results in a lower resolution image, and iterating this process, a pyramid of images depicting fewer details at each level is built, as it can be done in image processing for example to lighten the space storage of a photography. The direct sampling is then employed to simulate the lowest resolution level, and then to simulate each level, up to the finest resolution, conditioned to the level one rank coarser. This scheme helps reproduce the spatial structures at any scale of the training image and then generate more realistic models. We illustrate the method with aerial photographies (satellite images) and natural textures. Indeed, these kinds of images often display typical structures at different scales and are well-suited for MPS simulation techniques.

Wildlife monitoring across multiple spatial scales using grid-based sampling

Treesearch

Kevin S. McKelvey; Samuel A. Cushman; Michael K. Schwartz; Leonard F. Ruggiero

2009-01-01

Recently, noninvasive genetic sampling has become the most effective way to reliably sample occurrence of many species. In addition, genetic data provide a rich data source enabling the monitoring of population status. The combination of genetically based animal data collected at known spatial coordinates with vegetation, topography, and other available covariates...

The effect of Appalachian mountaintop mining on interior forest

Treesearch

J.D. Wickham; Kurt H. Riitters; T.G. Wade; M. Coan; C. Homer

2007-01-01

Southern Appalachian forests are predominantly interior because they are spatially extensive with little disturbance imposed by other uses of the land. Appalachian mountaintop mining increased substantially during the 1990s, posing a threat to the interior character of the forest. We used spatial convolution to identify interior forest at multiple scales on circa 1992...

Spatial and temporal ecology of eastern spadefoot toads on a Florida landscape

Treesearch

Cathryn H. Greenberg; George W. Tanner

2005-01-01

Effective amphibian conservation must consider population and landscape processes, but information at multiple scales is rare. We explore spatial and temporal patterns of breeding and recruitment by eastern spadefoot toads (Scaphiopus holbrookii), using nine years of data from continuous monitoring with drift fences and pitfall traps at eight...

Remote sensing for restoration planning: how the big picture can inform stakeholders

Treesearch

Susan Cordell; Erin J. Questad; Gregory P. Asner; Kealoha M. Kinney; Jarrod M. Thaxton; Amanda Uowolo; Sam Brooks; Mark W. Chynoweth

2016-01-01

The use of remote sensing in ecosystem management has transformed how land managers, practitioners, and policymakers evaluate ecosystem loss, gain, and change at multiple spatial and temporal scales. Less developed is the use of these spatial tools for planning, implementing, and evaluating ecosystem restoration projects and especially so in multifunctional...

Modeling stream network-scale variation in Coho salmon overwinter survival and smolt size

Treesearch

Joseph L. Ebersole; Mike E. Colvin; Parker J. Wigington; Scott G. Leibowitz; Joan P. Baker; Jana E. Compton; Bruce A. Miller; Michael A. Carins; Bruce P. Hansen; Henry R. La Vigne

2009-01-01

We used multiple regression and hierarchical mixed-effects models to examine spatial patterns of overwinter survival and size at smolting in juvenile coho salmon Oncorhynchus kisutch in relation to habitat attributes across an extensive stream network in southwestern Oregon over 3 years. Contributing basin area explained the majority of spatial...

Den use and selection by northern flying squirrels in fragmented landscapes

Treesearch

Sanjay Pyare; Winston P. Smith; Colin S. Shanley

2010-01-01

We studied den use and den-habitat selection by the Prince of Wales Island flying squirrel (Glaucomys sabrinus griseifrons) at multiple spatial scales in fragmented temperate rain-forest habitats because of the role dens play in the distribution, reproduction, and population density of this endemic subspecies. We observed differences in spatial...

Scale-dependent variation in forest structures in naturally dynamic boreal forest landscapes

NASA Astrophysics Data System (ADS)

Kulha, Niko; Pasanen, Leena; De Grandpré, Louis; Kuuluvainen, Timo; Aakala, Tuomas

2017-04-01

Natural forest structures vary at multiple spatial scales. This variation reflects the occurrence of driving factors, such as disturbances and variation in soil or topography. To explore and understand the linkages of forest structural characteristics and factors driving their variation, we need to recognize how the structural characteristics vary in relation to spatial scale. This can be achieved by identifying scale-dependent features in forest structure within unmanaged forest landscapes. By identifying these features and examining their relationship with potential driving factors, we can better understand the dynamics of forest structural development. Here, we examine the spatial variation in forest structures at multiple spatial scales, utilizing data from old-growth boreal forests in two regions with contrasting disturbance regimes: northern Finland and north-eastern Québec, Canada ( 67° 45'N, 29° 36'E, 49° 39'N, 67° 55'W, respectively). The three landscapes (4 km2 each) in Finland are dominated by Pinus sylvestris and Picea abies, whereas the two landscapes in Québec are dominated by Abies balsamea and Picea mariana. Québec's forests are a subject to cyclic outbreaks of the eastern spruce budworm, causing extensive mortality especially in A. balsamea-dominated stands. In the Finnish landscapes, gap- to patch-scale disturbances due to tree senescence, fungi and wind, as well as infrequent surface fires in areas dominated by P. sylvestris, prevail. Owing to the differences in the species compositions and the disturbance regimes, we expect differing scales of variation between the landscapes. To quantify patterns of variation, we visually interpret stereopairs of recent aerial photographs. From the photographs, we collect information on forest canopy coverage, species composition and dead wood. For the interpretation, each 4 km2 plot is divided into 0.1ha square cells (4096 per plot). Interpretations are validated against field observations and compiled to raster maps. We analyze the raster maps with Bayesian scale space approach (iBSiZer), which aims in capturing credible variations at different spatial scales. As a result, we can detect structural entities (e.g. patches with higher canopy cover), which deviate credibly from their surroundings. The detected entities can further be linked to specific drivers. Our results show that the role of a particular driving factor varies in relation to spatial scale. For example, in the Finnish landscapes, topoedaphic factors exerted a stronger control on broad-scale forest structural characteristics, whereas recent disturbances (quantified as the amount of dead wood) appeared to play an important role in explaining the smaller scale variation of forest structures. Here, we showcase the methodology used in the detection of scale-dependent forest structural entities and present the results of our analysis of the spatial scales of variation in the natural boreal forest structures.

Spatial congruence in language and species richness but not threat in the world's top linguistic hotspot.

PubMed

Turvey, Samuel T; Pettorelli, Nathalie

2014-12-07

Languages share key evolutionary properties with biological species, and global-level spatial congruence in richness and threat is documented between languages and several taxonomic groups. However, there is little understanding of the functional connection between diversification or extinction in languages and species, or the relationship between linguistic and species richness across different spatial scales. New Guinea is the world's most linguistically rich region and contains extremely high biological diversity. We demonstrate significant positive relationships between language and mammal richness in New Guinea across multiple spatial scales, revealing a likely functional relationship over scales at which infra-island diversification may occur. However, correlations are driven by spatial congruence between low levels of language and species richness. Regional biocultural richness may have showed closer congruence before New Guinea's linguistic landscape was altered by Holocene demographic events. In contrast to global studies, we demonstrate a significant negative correlation across New Guinea between areas with high levels of threatened languages and threatened mammals, indicating that landscape-scale threats differ between these groups. Spatial resource prioritization to conserve biodiversity may not benefit threatened languages, and conservation policy must adopt a multi-faceted approach to protect biocultural diversity as a whole.

Evaluating Benefits of LID Practices at Multiple Spatial Scales Using SUSTAIN

EPA Science Inventory

Low impact development (LID) is a storm water management approach that essentially mimics the way nature works: infiltrate, filter, store, evaporate, and detain runoff close to its source. LID practices are distributed in nature, and they work on decentralized micro-scales and m...

A heritable symbiont and host-associated factors shape fungal endophyte communities across spatial scales

USDA-ARS?s Scientific Manuscript database

Microbial ecologists are intensely interested in the processes governing microbial community assembly, progress has been limited by a lack of studies that span multiple geographical scales and levels of biological organization. High throughput sequencing was used to characterize foliar fungal endoph...

Nitrate-Nitrogen, Landuse/Landcover, and Soil Drainage Associations at Multiple Spatial Scales

EPA Science Inventory

Managing non–point-source pollution of water requires knowledge of land use/land cover (LULC) influences at altering watershed scales. To gain improved understanding of relationships among LULC, soil drainage, and dissolved nitrate-N dynamics within the Calapooia River Basin in w...

EnviroAtlas: Incorporation of Community-Scale Data for Additional Communities

EPA Science Inventory

EnviroAtlas is ORD’s online spatial decision support tool for viewing and analyzing the supply, demand, and drivers of change related to natural and built infrastructure at multiple scales for the nation. Maps and text identify known relationships between the goods and services ...

Can basin land use effects on physical characteristics of streams be determined at broad geographic scales?

USGS Publications Warehouse

Goldstein, R.M.; Carlisle, D.M.; Meador, M.R.; Short, T.M.

2007-01-01

The environmental setting (e.g., climate, topography, geology) and land use affect stream physical characteristics singly and cumulatively. At broad geographic scales, we determined the importance of environmental setting and land use in explaining variation in stream physical characteristics. We hypothesized that as the spatial scale decreased from national to regional, land use would explain more of the variation in stream physical characteristics because environmental settings become more homogeneous. At a national scale, stepwise linear regression indicated that environmental setting was more important in explaining variability in stream physical characteristics. Although statistically discernible, the amount of variation explained by land use was not remarkable due to low partial correlations. At level II ecoregion spatial scales (southeastern USA plains, central USA plains, and a combination of the western Cordillera and the western interior basins and ranges), environmental setting variables were again more important predictors of stream physical characteristics, however, as the spatial scale decreased from national to regional, the portion of variability in stream physical characteristics explained by basin land use increased. Development of stream habitat indicators of land use will depend upon an understanding of relations between stream physical characteristics and environmental factors at multiple spatial scales. Smaller spatial scales will be necessary to reduce the confounding effects of variable environmental settings before the effects of land use can be reliably assessed. ?? Springer Science+Business Media B.V. 2006.

Impact of Spatial Scales on the Intercomparison of Climate Scenarios

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

Luo, Wei; Steptoe, Michael; Chang, Zheng

2017-01-01

Scenario analysis has been widely applied in climate science to understand the impact of climate change on the future human environment, but intercomparison and similarity analysis of different climate scenarios based on multiple simulation runs remain challenging. Although spatial heterogeneity plays a key role in modeling climate and human systems, little research has been performed to understand the impact of spatial variations and scales on similarity analysis of climate scenarios. To address this issue, the authors developed a geovisual analytics framework that lets users perform similarity analysis of climate scenarios from the Global Change Assessment Model (GCAM) using a hierarchicalmore » clustering approach.« less

From a meso- to micro-scale connectome: array tomography and mGRASP

PubMed Central

Rah, Jong-Cheol; Feng, Linqing; Druckmann, Shaul; Lee, Hojin; Kim, Jinhyun

2015-01-01

Mapping mammalian synaptic connectivity has long been an important goal of neuroscience because knowing how neurons and brain areas are connected underpins an understanding of brain function. Meeting this goal requires advanced techniques with single synapse resolution and large-scale capacity, especially at multiple scales tethering the meso- and micro-scale connectome. Among several advanced LM-based connectome technologies, Array Tomography (AT) and mammalian GFP-Reconstitution Across Synaptic Partners (mGRASP) can provide relatively high-throughput mapping synaptic connectivity at multiple scales. AT- and mGRASP-assisted circuit mapping (ATing and mGRASPing), combined with techniques such as retrograde virus, brain clearing techniques, and activity indicators will help unlock the secrets of complex neural circuits. Here, we discuss these useful new tools to enable mapping of brain circuits at multiple scales, some functional implications of spatial synaptic distribution, and future challenges and directions of these endeavors. PMID:26089781

Multiscale spatial and temporal estimation of the b-value

NASA Astrophysics Data System (ADS)

García-Hernández, R.; D'Auria, L.; Barrancos, J.; Padilla, G.

2017-12-01

The estimation of the spatial and temporal variations of the Gutenberg-Richter b-value is of great importance in different seismological applications. One of the problems affecting its estimation is the heterogeneous distribution of the seismicity which makes its estimate strongly dependent upon the selected spatial and/or temporal scale. This is especially important in volcanoes where dense clusters of earthquakes often overlap the background seismicity. Proposed solutions for estimating temporal variations of the b-value include considering equally spaced time intervals or variable intervals having an equal number of earthquakes. Similar approaches have been proposed to image the spatial variations of this parameter as well.We propose a novel multiscale approach, based on the method of Ogata and Katsura (1993), allowing a consistent estimation of the b-value regardless of the considered spatial and/or temporal scales. Our method, named MUST-B (MUltiscale Spatial and Temporal characterization of the B-value), basically consists in computing estimates of the b-value at multiple temporal and spatial scales, extracting for a give spatio-temporal point a statistical estimator of the value, as well as and indication of the characteristic spatio-temporal scale. This approach includes also a consistent estimation of the completeness magnitude (Mc) and of the uncertainties over both b and Mc.We applied this method to example datasets for volcanic (Tenerife, El Hierro) and tectonic areas (Central Italy) as well as an example application at global scale.

Confronting weather and climate models with observational data from soil moisture networks over the United States

PubMed Central

Dirmeyer, Paul A.; Wu, Jiexia; Norton, Holly E.; Dorigo, Wouter A.; Quiring, Steven M.; Ford, Trenton W.; Santanello, Joseph A.; Bosilovich, Michael G.; Ek, Michael B.; Koster, Randal D.; Balsamo, Gianpaolo; Lawrence, David M.

2018-01-01

Four land surface models in uncoupled and coupled configurations are compared to observations of daily soil moisture from 19 networks in the conterminous United States to determine the viability of such comparisons and explore the characteristics of model and observational data. First, observations are analyzed for error characteristics and representation of spatial and temporal variability. Some networks have multiple stations within an area comparable to model grid boxes; for those we find that aggregation of stations before calculation of statistics has little effect on estimates of variance, but soil moisture memory is sensitive to aggregation. Statistics for some networks stand out as unlike those of their neighbors, likely due to differences in instrumentation, calibration and maintenance. Buried sensors appear to have less random error than near-field remote sensing techniques, and heat dissipation sensors show less temporal variability than other types. Model soil moistures are evaluated using three metrics: standard deviation in time, temporal correlation (memory) and spatial correlation (length scale). Models do relatively well in capturing large-scale variability of metrics across climate regimes, but poorly reproduce observed patterns at scales of hundreds of kilometers and smaller. Uncoupled land models do no better than coupled model configurations, nor do reanalyses outperform free-running models. Spatial decorrelation scales are found to be difficult to diagnose. Using data for model validation, calibration or data assimilation from multiple soil moisture networks with different types of sensors and measurement techniques requires great caution. Data from models and observations should be put on the same spatial and temporal scales before comparison. PMID:29645013

Confronting Weather and Climate Models with Observational Data from Soil Moisture Networks over the United States

NASA Technical Reports Server (NTRS)

Dirmeyer, Paul A.; Wu, Jiexia; Norton, Holly E.; Dorigo, Wouter A.; Quiring, Steven M.; Ford, Trenton W.; Santanello, Joseph A., Jr.; Bosilovich, Michael G.; Ek, Michael B.; Koster, Randal Dean;

Confronting weather and climate models with observational data from soil moisture networks over the United States.

PubMed

Dirmeyer, Paul A; Wu, Jiexia; Norton, Holly E; Dorigo, Wouter A; Quiring, Steven M; Ford, Trenton W; Santanello, Joseph A; Bosilovich, Michael G; Ek, Michael B; Koster, Randal D; Balsamo, Gianpaolo; Lawrence, David M

2016-04-01

Four land surface models in uncoupled and coupled configurations are compared to observations of daily soil moisture from 19 networks in the conterminous United States to determine the viability of such comparisons and explore the characteristics of model and observational data. First, observations are analyzed for error characteristics and representation of spatial and temporal variability. Some networks have multiple stations within an area comparable to model grid boxes; for those we find that aggregation of stations before calculation of statistics has little effect on estimates of variance, but soil moisture memory is sensitive to aggregation. Statistics for some networks stand out as unlike those of their neighbors, likely due to differences in instrumentation, calibration and maintenance. Buried sensors appear to have less random error than near-field remote sensing techniques, and heat dissipation sensors show less temporal variability than other types. Model soil moistures are evaluated using three metrics: standard deviation in time, temporal correlation (memory) and spatial correlation (length scale). Models do relatively well in capturing large-scale variability of metrics across climate regimes, but poorly reproduce observed patterns at scales of hundreds of kilometers and smaller. Uncoupled land models do no better than coupled model configurations, nor do reanalyses outperform free-running models. Spatial decorrelation scales are found to be difficult to diagnose. Using data for model validation, calibration or data assimilation from multiple soil moisture networks with different types of sensors and measurement techniques requires great caution. Data from models and observations should be put on the same spatial and temporal scales before comparison.

Network analysis reveals multiscale controls on streamwater chemistry

USGS Publications Warehouse

McGuire, Kevin J.; Torgersen, Christian E.; Likens, Gene E.; Buso, Donald C.; Lowe, Winsor H.; Bailey, Scott W.

2014-01-01

By coupling synoptic data from a basin-wide assessment of streamwater chemistry with network-based geostatistical analysis, we show that spatial processes differentially affect biogeochemical condition and pattern across a headwater stream network. We analyzed a high-resolution dataset consisting of 664 water samples collected every 100 m throughout 32 tributaries in an entire fifth-order stream network. These samples were analyzed for an exhaustive suite of chemical constituents. The fine grain and broad extent of this study design allowed us to quantify spatial patterns over a range of scales by using empirical semivariograms that explicitly incorporated network topology. Here, we show that spatial structure, as determined by the characteristic shape of the semivariograms, differed both among chemical constituents and by spatial relationship (flow-connected, flow-unconnected, or Euclidean). Spatial structure was apparent at either a single scale or at multiple nested scales, suggesting separate processes operating simultaneously within the stream network and surrounding terrestrial landscape. Expected patterns of spatial dependence for flow-connected relationships (e.g., increasing homogeneity with downstream distance) occurred for some chemical constituents (e.g., dissolved organic carbon, sulfate, and aluminum) but not for others (e.g., nitrate, sodium). By comparing semivariograms for the different chemical constituents and spatial relationships, we were able to separate effects on streamwater chemistry of (i) fine-scale versus broad-scale processes and (ii) in-stream processes versus landscape controls. These findings provide insight on the hierarchical scaling of local, longitudinal, and landscape processes that drive biogeochemical patterns in stream networks.

Network analysis reveals multiscale controls on streamwater chemistry

PubMed Central

McGuire, Kevin J.; Torgersen, Christian E.; Likens, Gene E.; Buso, Donald C.; Lowe, Winsor H.; Bailey, Scott W.

2014-01-01

By coupling synoptic data from a basin-wide assessment of streamwater chemistry with network-based geostatistical analysis, we show that spatial processes differentially affect biogeochemical condition and pattern across a headwater stream network. We analyzed a high-resolution dataset consisting of 664 water samples collected every 100 m throughout 32 tributaries in an entire fifth-order stream network. These samples were analyzed for an exhaustive suite of chemical constituents. The fine grain and broad extent of this study design allowed us to quantify spatial patterns over a range of scales by using empirical semivariograms that explicitly incorporated network topology. Here, we show that spatial structure, as determined by the characteristic shape of the semivariograms, differed both among chemical constituents and by spatial relationship (flow-connected, flow-unconnected, or Euclidean). Spatial structure was apparent at either a single scale or at multiple nested scales, suggesting separate processes operating simultaneously within the stream network and surrounding terrestrial landscape. Expected patterns of spatial dependence for flow-connected relationships (e.g., increasing homogeneity with downstream distance) occurred for some chemical constituents (e.g., dissolved organic carbon, sulfate, and aluminum) but not for others (e.g., nitrate, sodium). By comparing semivariograms for the different chemical constituents and spatial relationships, we were able to separate effects on streamwater chemistry of (i) fine-scale versus broad-scale processes and (ii) in-stream processes versus landscape controls. These findings provide insight on the hierarchical scaling of local, longitudinal, and landscape processes that drive biogeochemical patterns in stream networks. PMID:24753575

Network analysis reveals multiscale controls on streamwater chemistry.

PubMed

McGuire, Kevin J; Torgersen, Christian E; Likens, Gene E; Buso, Donald C; Lowe, Winsor H; Bailey, Scott W

2014-05-13

By coupling synoptic data from a basin-wide assessment of streamwater chemistry with network-based geostatistical analysis, we show that spatial processes differentially affect biogeochemical condition and pattern across a headwater stream network. We analyzed a high-resolution dataset consisting of 664 water samples collected every 100 m throughout 32 tributaries in an entire fifth-order stream network. These samples were analyzed for an exhaustive suite of chemical constituents. The fine grain and broad extent of this study design allowed us to quantify spatial patterns over a range of scales by using empirical semivariograms that explicitly incorporated network topology. Here, we show that spatial structure, as determined by the characteristic shape of the semivariograms, differed both among chemical constituents and by spatial relationship (flow-connected, flow-unconnected, or Euclidean). Spatial structure was apparent at either a single scale or at multiple nested scales, suggesting separate processes operating simultaneously within the stream network and surrounding terrestrial landscape. Expected patterns of spatial dependence for flow-connected relationships (e.g., increasing homogeneity with downstream distance) occurred for some chemical constituents (e.g., dissolved organic carbon, sulfate, and aluminum) but not for others (e.g., nitrate, sodium). By comparing semivariograms for the different chemical constituents and spatial relationships, we were able to separate effects on streamwater chemistry of (i) fine-scale versus broad-scale processes and (ii) in-stream processes versus landscape controls. These findings provide insight on the hierarchical scaling of local, longitudinal, and landscape processes that drive biogeochemical patterns in stream networks.

Large-scale assessment of benthic communities across multiple marine protected areas using an autonomous underwater vehicle.

PubMed

Ferrari, Renata; Marzinelli, Ezequiel M; Ayroza, Camila Rezende; Jordan, Alan; Figueira, Will F; Byrne, Maria; Malcolm, Hamish A; Williams, Stefan B; Steinberg, Peter D

2018-01-01

Marine protected areas (MPAs) are designed to reduce threats to biodiversity and ecosystem functioning from anthropogenic activities. Assessment of MPAs effectiveness requires synchronous sampling of protected and non-protected areas at multiple spatial and temporal scales. We used an autonomous underwater vehicle to map benthic communities in replicate 'no-take' and 'general-use' (fishing allowed) zones within three MPAs along 7o of latitude. We recorded 92 taxa and 38 morpho-groups across three large MPAs. We found that important habitat-forming biota (e.g. massive sponges) were more prevalent and abundant in no-take zones, while short ephemeral algae were more abundant in general-use zones, suggesting potential short-term effects of zoning (5-10 years). Yet, short-term effects of zoning were not detected at the community level (community structure or composition), while community structure varied significantly among MPAs. We conclude that by allowing rapid, simultaneous assessments at multiple spatial scales, autonomous underwater vehicles are useful to document changes in marine communities and identify adequate scales to manage them. This study advanced knowledge of marine benthic communities and their conservation in three ways. First, we quantified benthic biodiversity and abundance, generating the first baseline of these benthic communities against which the effectiveness of three large MPAs can be assessed. Second, we identified the taxonomic resolution necessary to assess both short and long-term effects of MPAs, concluding that coarse taxonomic resolution is sufficient given that analyses of community structure at different taxonomic levels were generally consistent. Yet, observed differences were taxa-specific and may have not been evident using our broader taxonomic classifications, a classification of mid to high taxonomic resolution may be necessary to determine zoning effects on key taxa. Third, we provide an example of statistical analyses and sampling design that once temporal sampling is incorporated will be useful to detect changes of marine benthic communities across multiple spatial and temporal scales.

Large-scale assessment of benthic communities across multiple marine protected areas using an autonomous underwater vehicle

PubMed Central

Ayroza, Camila Rezende; Jordan, Alan; Figueira, Will F.; Byrne, Maria; Malcolm, Hamish A.; Williams, Stefan B.; Steinberg, Peter D.

2018-01-01

Marine protected areas (MPAs) are designed to reduce threats to biodiversity and ecosystem functioning from anthropogenic activities. Assessment of MPAs effectiveness requires synchronous sampling of protected and non-protected areas at multiple spatial and temporal scales. We used an autonomous underwater vehicle to map benthic communities in replicate ‘no-take’ and ‘general-use’ (fishing allowed) zones within three MPAs along 7o of latitude. We recorded 92 taxa and 38 morpho-groups across three large MPAs. We found that important habitat-forming biota (e.g. massive sponges) were more prevalent and abundant in no-take zones, while short ephemeral algae were more abundant in general-use zones, suggesting potential short-term effects of zoning (5–10 years). Yet, short-term effects of zoning were not detected at the community level (community structure or composition), while community structure varied significantly among MPAs. We conclude that by allowing rapid, simultaneous assessments at multiple spatial scales, autonomous underwater vehicles are useful to document changes in marine communities and identify adequate scales to manage them. This study advanced knowledge of marine benthic communities and their conservation in three ways. First, we quantified benthic biodiversity and abundance, generating the first baseline of these benthic communities against which the effectiveness of three large MPAs can be assessed. Second, we identified the taxonomic resolution necessary to assess both short and long-term effects of MPAs, concluding that coarse taxonomic resolution is sufficient given that analyses of community structure at different taxonomic levels were generally consistent. Yet, observed differences were taxa-specific and may have not been evident using our broader taxonomic classifications, a classification of mid to high taxonomic resolution may be necessary to determine zoning effects on key taxa. Third, we provide an example of statistical analyses and sampling design that once temporal sampling is incorporated will be useful to detect changes of marine benthic communities across multiple spatial and temporal scales. PMID:29547656

Disease spread across multiple scales in a spatial hierarchy: effect of host spatial structure and of inoculum quantity and distribution.

PubMed

Gosme, Marie; Lucas, Philippe

2009-07-01

Spatial patterns of both the host and the disease influence disease spread and crop losses. Therefore, the manipulation of these patterns might help improve control strategies. Considering disease spread across multiple scales in a spatial hierarchy allows one to capture important features of epidemics developing in space without using explicitly spatialized variables. Thus, if the system under study is composed of roots, plants, and planting hills, the effect of host spatial pattern can be studied by varying the number of plants per planting hill. A simulation model based on hierarchy theory was used to simulate the effects of large versus small planting hills, low versus high level of initial infections, and aggregated versus uniform distribution of initial infections. The results showed that aggregating the initially infected plants always resulted in slower epidemics than spreading out the initial infections uniformly. Simulation results also showed that, in most cases, disease epidemics were slower in the case of large host aggregates (100 plants/hill) than with smaller aggregates (25 plants/hill), except when the initially infected plants were both numerous and spread out uniformly. The optimal strategy for disease control depends on several factors, including initial conditions. More importantly, the model offers a framework to account for the interplay between the spatial characteristics of the system, rates of infection, and aggregation of the disease.

An operational ensemble prediction system for catchment rainfall over eastern Africa spanning multiple temporal and spatial scales

NASA Astrophysics Data System (ADS)

Riddle, E. E.; Hopson, T. M.; Gebremichael, M.; Boehnert, J.; Broman, D.; Sampson, K. M.; Rostkier-Edelstein, D.; Collins, D. C.; Harshadeep, N. R.; Burke, E.; Havens, K.

2017-12-01

While it is not yet certain how precipitation patterns will change over Africa in the future, it is clear that effectively managing the available water resources is going to be crucial in order to mitigate the effects of water shortages and floods that are likely to occur in a changing climate. One component of effective water management is the availability of state-of-the-art and easy to use rainfall forecasts across multiple spatial and temporal scales. We present a web-based system for displaying and disseminating ensemble forecast and observed precipitation data over central and eastern Africa. The system provides multi-model rainfall forecasts integrated to relevant hydrological catchments for timescales ranging from one day to three months. A zoom-in features is available to access high resolution forecasts for small-scale catchments. Time series plots and data downloads with forecasts, recent rainfall observations and climatological data are available by clicking on individual catchments. The forecasts are calibrated using a quantile regression technique and an optimal multi-model forecast is provided at each timescale. The forecast skill at the various spatial and temporal scales will discussed, as will current applications of this tool for managing water resources in Sudan and optimizing hydropower operations in Ethiopia and Tanzania.

Spatial variation in disease resistance: from molecules to metapopulations

PubMed Central

Laine, Anna-Liisa; Burdon, Jeremy J.; Dodds, Peter N.; Thrall, Peter H.

2010-01-01

Summary Variation in disease resistance is a widespread phenomenon in wild plant-pathogen associations. Here, we review current literature on natural plant-pathogen associations to determine how diversity in disease resistance is distributed at different hierarchical levels – within host individuals, within host populations, among host populations at the metapopulation scale and at larger regional scales. We find diversity in resistance across all spatial scales examined. Furthermore, variability seems to be the best counter-defence of plants against their rapidly evolving pathogens. We find that higher diversity of resistance phenotypes also results in higher levels of resistance at the population level. Overall, we find that wild plant populations are more likely to be susceptible than resistant to their pathogens. However, the degree of resistance differs strikingly depending on the origin of the pathogen strains used in experimental inoculation studies. Plant populations are on average 16% more resistant to allopatric pathogen strains than they are to strains that occur within the same population (48 % vs. 32 % respectively). Pathogen dispersal mode affects levels of resistance in natural plant populations with lowest levels detected for hosts of airborne pathogens and highest for waterborne pathogens. Detailed analysis of two model systems, Linum marginale infected by Melampsora lini, and Plantago lanceolata infected by Podosphaera plantaginis, show that the amount of variation in disease resistance declines towards higher spatial scales as we move from individual hosts to metapopulations, but evaluation of multiple spatial scales is needed to fully capture the structure of disease resistance. Synthesis: Variation in disease resistance is ubiquitous in wild plant-pathogen associations. While the debate over whether the resistance structure of plant populations is determined by pathogen-imposed selection versus non-adaptive processes remains unresolved, we do report examples of pathogen-imposed selection on host resistance. Here we highlight the importance of measuring resistance across multiple spatial scales, and of using sympatric strains when looking for signs of coevolution in wild plant-pathogen interactions. PMID:21243068

Multi-Timescale Analysis of the Spatial Representativeness of In Situ Soil Moisture Data within Satellite Footprints

NASA Astrophysics Data System (ADS)

Molero, B.; Leroux, D. J.; Richaume, P.; Kerr, Y. H.; Merlin, O.; Cosh, M. H.; Bindlish, R.

2018-01-01

We conduct a novel comprehensive investigation that seeks to prove the connection between spatial scales and timescales in surface soil moisture (SM) within the satellite footprint ( 50 km). Modeled and measured point series at Yanco and Little Washita in situ networks are first decomposed into anomalies at timescales ranging from 0.5 to 128 days, using wavelet transforms. Then, their degree of spatial representativeness is evaluated on a per-timescale basis by comparison to large spatial scale data sets (the in situ spatial average, SMOS, AMSR2, and ECMWF). Four methods are used for this: temporal stability analysis (TStab), triple collocation (TC), percentage of correlated areas (CArea), and a new proposed approach that uses wavelet-based correlations (WCor). We found that the mean of the spatial representativeness values tends to increase with the timescale but so does their dispersion. Locations exhibit poor spatial representativeness at scales below 4 days, while either very good or poor representativeness at seasonal scales. Regarding the methods, TStab cannot be applied to the anomaly series due to their multiple zero-crossings, and TC is suitable for week and month scales but not for other scales where data set cross-correlations are found low. In contrast, WCor and CArea give consistent results at all timescales. WCor is less sensitive to the spatial sampling density, so it is a robust method that can be applied to sparse networks (one station per footprint). These results are promising to improve the validation and downscaling of satellite SM series and the optimization of SM networks.

Achromatical Optical Correlator

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin; Liu, Hua-Kuang

1989-01-01

Signal-to-noise ratio exceeds that of monochromatic correlator. Achromatical optical correlator uses multiple-pinhole diffraction of dispersed white light to form superposed multiple correlations of input and reference images in output plane. Set of matched spatial filters made by multiple-exposure holographic process, each exposure using suitably-scaled input image and suitable angle of reference beam. Recording-aperture mask translated to appropriate horizontal position for each exposure. Noncoherent illumination suitable for applications involving recognition of color and determination of scale. When fully developed achromatical correlators will be useful for recognition of patterns; for example, in industrial inspection and search for selected features in aerial photographs.

Multi-scale variation in spatial heterogeneity for microbial community structure in an eastern Virginia agricultural field

NASA Technical Reports Server (NTRS)

Franklin, Rima B.; Mills, Aaron L.

2003-01-01

To better understand the distribution of soil microbial communities at multiple spatial scales, a survey was conducted to examine the spatial organization of community structure in a wheat field in eastern Virginia (USA). Nearly 200 soil samples were collected at a variety of separation distances ranging from 2.5 cm to 11 m. Whole-community DNA was extracted from each sample, and community structure was compared using amplified fragment length polymorphism (AFLP) DNA fingerprinting. Relative similarity was calculated between each pair of samples and compared using geostatistical variogram analysis to study autocorrelation as a function of separation distance. Spatial autocorrelation was found at scales ranging from 30 cm to more than 6 m, depending on the sampling extent considered. In some locations, up to four different correlation length scales were detected. The presence of nested scales of variability suggests that the environmental factors regulating the development of the communities in this soil may operate at different scales. Kriging was used to generate maps of the spatial organization of communities across the plot, and the results demonstrated that bacterial distributions can be highly structured, even within a habitat that appears relatively homogeneous at the plot and field scale. Different subsets of the microbial community were distributed differently across the plot, and this is thought to be due to the variable response of individual populations to spatial heterogeneity associated with soil properties. c2003 Federation of European Microbiological Societies. Published by Elsevier Science B.V. All rights reserved.

Changes in channel morphology over human time scales [Chapter 32

Treesearch

John M. Buffington

2012-01-01

Rivers are exposed to changing environmental conditions over multiple spatial and temporal scales, with the imposed environmental conditions and response potential of the river modulated to varying degrees by human activity and our exploitation of natural resources. Watershed features that control river morphology include topography (valley slope and channel...

Future of applied watershed science at regional scales

Treesearch

Lee Benda; Daniel Miller; Steve Lanigan; Gordon Reeves

2009-01-01

Resource managers must deal increasingly with land use and conservation plans applied at large spatial scales (watersheds, landscapes, states, regions) involving multiple interacting federal agencies and stakeholders. Access to a geographically focused and application-oriented database would allow users in different locations and with different concerns to quickly...

Crossing scales and disciplines to achieve forest sustainability

Treesearch

Michael J. Papaik; Brian Sturtevant; Christian Messier

2008-01-01

Forest land managers are faced with unprecedented global pressures to produce resources for human consumption (e.g., Liu and Diamond 2005), while still maintaining essential ecosystem services benefiting society at multiple spatial scales (Costanza et al. 1997). These global pressures alone present daunting challenges to sustainable forest management (SFM) worldwide (...

Large-Scale Brain Networks Supporting Divided Attention across Spatial Locations and Sensory Modalities

PubMed Central

Santangelo, Valerio

2018-01-01

Higher-order cognitive processes were shown to rely on the interplay between large-scale neural networks. However, brain networks involved with the capability to split attentional resource over multiple spatial locations and multiple stimuli or sensory modalities have been largely unexplored to date. Here I re-analyzed data from Santangelo et al. (2010) to explore the causal interactions between large-scale brain networks during divided attention. During fMRI scanning, participants monitored streams of visual and/or auditory stimuli in one or two spatial locations for detection of occasional targets. This design allowed comparing a condition in which participants monitored one stimulus/modality (either visual or auditory) in two spatial locations vs. a condition in which participants monitored two stimuli/modalities (both visual and auditory) in one spatial location. The analysis of the independent components (ICs) revealed that dividing attentional resources across two spatial locations necessitated a brain network involving the left ventro- and dorso-lateral prefrontal cortex plus the posterior parietal cortex, including the intraparietal sulcus (IPS) and the angular gyrus, bilaterally. The analysis of Granger causality highlighted that the activity of lateral prefrontal regions were predictive of the activity of all of the posteriors parietal nodes. By contrast, dividing attention across two sensory modalities necessitated a brain network including nodes belonging to the dorsal frontoparietal network, i.e., the bilateral frontal eye-fields (FEF) and IPS, plus nodes belonging to the salience network, i.e., the anterior cingulated cortex and the left and right anterior insular cortex (aIC). The analysis of Granger causality highlights a tight interdependence between the dorsal frontoparietal and salience nodes in trials requiring divided attention between different sensory modalities. The current findings therefore highlighted a dissociation among brain networks implicated during divided attention across spatial locations and sensory modalities, pointing out the importance of investigating effective connectivity of large-scale brain networks supporting complex behavior. PMID:29535614

Large-Scale Brain Networks Supporting Divided Attention across Spatial Locations and Sensory Modalities.

PubMed

Santangelo, Valerio

2018-01-01

Higher-order cognitive processes were shown to rely on the interplay between large-scale neural networks. However, brain networks involved with the capability to split attentional resource over multiple spatial locations and multiple stimuli or sensory modalities have been largely unexplored to date. Here I re-analyzed data from Santangelo et al. (2010) to explore the causal interactions between large-scale brain networks during divided attention. During fMRI scanning, participants monitored streams of visual and/or auditory stimuli in one or two spatial locations for detection of occasional targets. This design allowed comparing a condition in which participants monitored one stimulus/modality (either visual or auditory) in two spatial locations vs. a condition in which participants monitored two stimuli/modalities (both visual and auditory) in one spatial location. The analysis of the independent components (ICs) revealed that dividing attentional resources across two spatial locations necessitated a brain network involving the left ventro- and dorso-lateral prefrontal cortex plus the posterior parietal cortex, including the intraparietal sulcus (IPS) and the angular gyrus, bilaterally. The analysis of Granger causality highlighted that the activity of lateral prefrontal regions were predictive of the activity of all of the posteriors parietal nodes. By contrast, dividing attention across two sensory modalities necessitated a brain network including nodes belonging to the dorsal frontoparietal network, i.e., the bilateral frontal eye-fields (FEF) and IPS, plus nodes belonging to the salience network, i.e., the anterior cingulated cortex and the left and right anterior insular cortex (aIC). The analysis of Granger causality highlights a tight interdependence between the dorsal frontoparietal and salience nodes in trials requiring divided attention between different sensory modalities. The current findings therefore highlighted a dissociation among brain networks implicated during divided attention across spatial locations and sensory modalities, pointing out the importance of investigating effective connectivity of large-scale brain networks supporting complex behavior.

Spatial patterns of native freshwater mussels in the Upper Mississippi River

USGS Publications Warehouse

Ries, Patricia R.; DeJager, Nathan R.; Zigler, Steven J.; Newton, Teresa

2016-01-01

Multiple physical and biological factors structure freshwater mussel communities in large rivers, and their distributions have been described as clumped or patchy. However, few surveys of mussel populations have been conducted over areas large enough and at resolutions fine enough to quantify spatial patterns in their distribution. We used global and local indicators of spatial autocorrelation (i.e., Moran’s I) to quantify spatial patterns of adult and juvenile (≤5 y of age) freshwater mussels across multiple scales based on survey data from 4 reaches (navigation pools 3, 5, 6, and 18) of the Upper Mississippi River, USA. Native mussel densities were sampled at a resolution of ∼300 m and across distances ranging from 21 to 37 km, making these some of the most spatially extensive surveys conducted in a large river. Patch density and the degree and scale of patchiness varied by river reach, age group, and the scale of analysis. In all 4 pools, some patches of adults overlapped patches of juveniles, suggesting spatial and temporal persistence of adequate habitat. In pools 3 and 5, patches of juveniles were found where there were few adults, suggesting recent emergence of positive structuring mechanisms. Last, in pools 3, 5, and 6, some patches of adults were found where there were few juveniles, suggesting that negative structuring mechanisms may have replaced positive ones, leading to a lack of localized recruitment. Our results suggest that: 1) the detection of patches of freshwater mussels requires a multiscaled approach, 2) insights into the spatial and temporal dynamics of structuring mechanisms can be gained by conducting independent analyses of adults and juveniles, and 3) maps of patch distributions can be used to guide restoration and management actions and identify areas where mussels are most likely to influence ecosystem function.

Relationships of dead wood patterns with biophysical characteristics and ownership according to scale in Coastal Oregon, USA

Treesearch

Rebecca S.H. Kennedy; Thomas A. Spies; Matthew J. Gregory

2008-01-01

Dead wood patterns and dynamics vary with biophysical factors, disturbance history, ownership, and management practices; the relative importance of these factors is poorly understood, especially at landscape to regional scales. This study examined current dead wood amounts in the Coastal Province of Oregon, USA, at multiple spatial scales. Objectives were to: (1)...

Temporal change in forest fragmentation at multiple scales

Treesearch

J.D. Wickham; K.H. Riitters; T.G. Wade; J.W. Coulston

2007-01-01

Previous studies of temporal changes in fragmentation have focused almost exclusively on patch and edge statistics, which might not detect changes in the spatial scale at which forest occurs in or dominates the landscape. We used temporal land-cover data for the Chesapeake Bay region and the state of New Jersey to compare patch-based and area–density scaling measures...

From single steps to mass migration: the problem of scale in the movement ecology of the Serengeti wildebeest.

PubMed

Torney, Colin J; Hopcraft, J Grant C; Morrison, Thomas A; Couzin, Iain D; Levin, Simon A

2018-05-19

A central question in ecology is how to link processes that occur over different scales. The daily interactions of individual organisms ultimately determine community dynamics, population fluctuations and the functioning of entire ecosystems. Observations of these multiscale ecological processes are constrained by various technological, biological or logistical issues, and there are often vast discrepancies between the scale at which observation is possible and the scale of the question of interest. Animal movement is characterized by processes that act over multiple spatial and temporal scales. Second-by-second decisions accumulate to produce annual movement patterns. Individuals influence, and are influenced by, collective movement decisions, which then govern the spatial distribution of populations and the connectivity of meta-populations. While the field of movement ecology is experiencing unprecedented growth in the availability of movement data, there remain challenges in integrating observations with questions of ecological interest. In this article, we present the major challenges of addressing these issues within the context of the Serengeti wildebeest migration, a keystone ecological phenomena that crosses multiple scales of space, time and biological complexity.This article is part of the theme issue 'Collective movement ecology'. © 2018 The Author(s).

Spatial Modeling and Uncertainty Assessment of Fine Scale Surface Processes Based on Coarse Terrain Elevation Data

NASA Astrophysics Data System (ADS)

Rasera, L. G.; Mariethoz, G.; Lane, S. N.

2017-12-01

Frequent acquisition of high-resolution digital elevation models (HR-DEMs) over large areas is expensive and difficult. Satellite-derived low-resolution digital elevation models (LR-DEMs) provide extensive coverage of Earth's surface but at coarser spatial and temporal resolutions. Although useful for large scale problems, LR-DEMs are not suitable for modeling hydrologic and geomorphic processes at scales smaller than their spatial resolution. In this work, we present a multiple-point geostatistical approach for downscaling a target LR-DEM based on available high-resolution training data and recurrent high-resolution remote sensing images. The method aims at generating several equiprobable HR-DEMs conditioned to a given target LR-DEM by borrowing small scale topographic patterns from an analogue containing data at both coarse and fine scales. An application of the methodology is demonstrated by using an ensemble of simulated HR-DEMs as input to a flow-routing algorithm. The proposed framework enables a probabilistic assessment of the spatial structures generated by natural phenomena operating at scales finer than the available terrain elevation measurements. A case study in the Swiss Alps is provided to illustrate the methodology.

Fully coupled approach to modeling shallow water flow, sediment transport, and bed evolution in rivers

NASA Astrophysics Data System (ADS)

Li, Shuangcai; Duffy, Christopher J.

2011-03-01

Our ability to predict complex environmental fluid flow and transport hinges on accurate and efficient simulations of multiple physical phenomenon operating simultaneously over a wide range of spatial and temporal scales, including overbank floods, coastal storm surge events, drying and wetting bed conditions, and simultaneous bed form evolution. This research implements a fully coupled strategy for solving shallow water hydrodynamics, sediment transport, and morphological bed evolution in rivers and floodplains (PIHM_Hydro) and applies the model to field and laboratory experiments that cover a wide range of spatial and temporal scales. The model uses a standard upwind finite volume method and Roe's approximate Riemann solver for unstructured grids. A multidimensional linear reconstruction and slope limiter are implemented, achieving second-order spatial accuracy. Model efficiency and stability are treated using an explicit-implicit method for temporal discretization with operator splitting. Laboratory-and field-scale experiments were compiled where coupled processes across a range of scales were observed and where higher-order spatial and temporal accuracy might be needed for accurate and efficient solutions. These experiments demonstrate the ability of the fully coupled strategy in capturing dynamics of field-scale flood waves and small-scale drying-wetting processes.

Spatial multi-scale variability of soil nutrients in relation to environmental factors in a typical agricultural region, eastern China.

PubMed

Liu, Yang; Lv, Jianshu; Zhang, Bing; Bi, Jun

2013-04-15

Identifying the sources of spatial variability and deficiency risk of soil nutrients is a crucial issue for soil and agriculture management. A total of 1247 topsoil samples (0-20 cm) were collected at the nodes of a 2×2 km grid in Rizhao City and the contents of soil organic carbon (OC), total nitrogen (TN), and total phosphorus (TP) were determined. Factorial kriging analysis (FKA), stepwise multiple regression, and indicator kriging (IK) were appled to investigate the scale dependent correlations among soil nutrients, identify the sources of spatial variability at each spatial scale, and delineate the potential risk of soil nutrient deficiency. Linear model of co-regionalization (LMC) fitting indicated that the presence of multi-scale variation was comprised of nugget effect, an exponential structure with a range of 12 km (local scale), and a spherical structure with a range of 84 km (regional scale). The short-range variation of OC and TN was mainly dominated by land use types, and TP was controlled by terrain. At long-range scale, spatial variation of OC, TN, and TP was dominated by parent material. Indicator kriging maps depicted the probability of soil nutrient deficiency compared with the background values in eastern Shandong province. The high deficiency risk area of all nutrient integration was mainly located in eastern and northwestern parts. Copyright © 2013 Elsevier B.V. All rights reserved.

Non-monotonic changes in performance with eccentricity modeled by multiple eccentricity-dependent limitations.

PubMed

Poirier, Frédéric J A M; Gurnsey, Rick

2005-08-01

Eccentricity-dependent resolution losses are sometimes compensated for in psychophysical experiments by magnifying (scaling) stimuli at each eccentricity. The use of either pre-selected scaling factors or unscaled stimuli sometimes leads to non-monotonic changes in performance as a function of eccentricity. We argue that such non-monotonic changes arise when performance is limited by more than one type of constraint at each eccentricity. Building on current methods developed to investigate peripheral perception [e.g., Watson, A. B. (1987). Estimation of local spatial scale. Journal of the Optical Society of America A, 4 (8), 1579-1582; Poirier, F. J. A. M., & Gurnsey, R. (2002). Two eccentricity dependent limitations on subjective contour discrimination. Vision Research, 42, 227-238; Strasburger, H., Rentschler, I., & Harvey Jr., L. O. (1994). Cortical magnification theory fails to predict visual recognition. European Journal of Neuroscience, 6, 1583-1588], we show how measured scaling can deviate from a linear function of eccentricity in a grating acuity task [Thibos, L. N., Still, D. L., & Bradley, A. (1996). Characterization of spatial aliasing and contrast sensitivity in peripheral vision. Vision Research, 36(2), 249-258]. This framework can also explain the central performance drop [Kehrer, L. (1989). Central performance drop on perceptual segregation tasks. Spatial Vision, 4, 45-62] and a case of "reverse scaling" of the integration window in symmetry [Tyler, C. W. (1999). Human symmetry detection exhibits reverse eccentricity scaling. Visual Neuroscience, 16, 919-922]. These cases of non-monotonic performance are shown to be consistent with multiple sources of resolution loss, each of which increases linearly with eccentricity. We conclude that most eccentricity research, including "oddities", can be explained by multiple-scaling theory as extended here, where the receptive field properties of all underlying mechanisms in a task increase in size with eccentricity, but not necessarily at the same rate.

Assessing Habitat Suitability at Multiple Scales: A Landscape-Level Approach

Treesearch

Kurt H. Riitters; R.V. O' Neill; K.B. Jones

1997-01-01

The distribution and abundance of many plants and animals are influenced by the spatial arrangement of suitable habitats across landscapes. We derived habitat maps from a digital land cover map of the ~178,000 km2 Chesapeake Bay Watershed by using a spatial filtering algorithm. The regional amounts and patterns of habitats were different for...

Legacies of Lead in Charm City's Soil: Lessons from the Baltimore Ecosystem Study

Treesearch

Kirsten Schwarz; Richard Pouyat; Ian Yesilonis

2016-01-01

Understanding the spatial distribution of soil lead has been a focus of the Baltimore Ecosystem Study since its inception in 1997. Through multiple research projects that span spatial scales and use different methodologies, three overarching patterns have been identified: (1) soil lead concentrations often exceed state and federal regulatory limits; (2) the variability...

Large-scale monitoring of shorebird populations using count data and N-mixture models: Black Oystercatcher (Haematopus bachmani) surveys by land and sea

USGS Publications Warehouse

Lyons, James E.; Andrew, Royle J.; Thomas, Susan M.; Elliott-Smith, Elise; Evenson, Joseph R.; Kelly, Elizabeth G.; Milner, Ruth L.; Nysewander, David R.; Andres, Brad A.

2012-01-01

Large-scale monitoring of bird populations is often based on count data collected across spatial scales that may include multiple physiographic regions and habitat types. Monitoring at large spatial scales may require multiple survey platforms (e.g., from boats and land when monitoring coastal species) and multiple survey methods. It becomes especially important to explicitly account for detection probability when analyzing count data that have been collected using multiple survey platforms or methods. We evaluated a new analytical framework, N-mixture models, to estimate actual abundance while accounting for multiple detection biases. During May 2006, we made repeated counts of Black Oystercatchers (Haematopus bachmani) from boats in the Puget Sound area of Washington (n = 55 sites) and from land along the coast of Oregon (n = 56 sites). We used a Bayesian analysis of N-mixture models to (1) assess detection probability as a function of environmental and survey covariates and (2) estimate total Black Oystercatcher abundance during the breeding season in the two regions. Probability of detecting individuals during boat-based surveys was 0.75 (95% credible interval: 0.42–0.91) and was not influenced by tidal stage. Detection probability from surveys conducted on foot was 0.68 (0.39–0.90); the latter was not influenced by fog, wind, or number of observers but was ~35% lower during rain. The estimated population size was 321 birds (262–511) in Washington and 311 (276–382) in Oregon. N-mixture models provide a flexible framework for modeling count data and covariates in large-scale bird monitoring programs designed to understand population change.

Combined point and distributed techniques for multidimensional estimation of spatial groundwater-stream water exchange in a heterogeneous sand bed-stream.

NASA Astrophysics Data System (ADS)

Gaona Garcia, J.; Lewandowski, J.; Bellin, A.

2017-12-01

Groundwater-stream water interactions in rivers determine water balances, but also chemical and biological processes in the streambed at different spatial and temporal scales. Due to the difficult identification and quantification of gaining, neutral and losing conditions, it is necessary to combine techniques with complementary capabilities and scale ranges. We applied this concept to a study site at the River Schlaube, East Brandenburg-Germany, a sand bed stream with intense sediment heterogeneity and complex environmental conditions. In our approach, point techniques such as temperature profiles of the streambed together with vertical hydraulic gradients provide data for the estimation of fluxes between groundwater and surface water with the numerical model 1DTempPro. On behalf of distributed techniques, fiber optic distributed temperature sensing identifies the spatial patterns of neutral, down- and up-welling areas by analysis of the changes in the thermal patterns at the streambed interface under certain flow. The study finally links point and surface temperatures to provide a method for upscaling of fluxes. Point techniques provide point flux estimates with essential depth detail to infer streambed structures while the results hardly represent the spatial distribution of fluxes caused by the heterogeneity of streambed properties. Fiber optics proved capable of providing spatial thermal patterns with enough resolution to observe distinct hyporheic thermal footprints at multiple scales. The relation of thermal footprint patterns and temporal behavior with flux results from point techniques enabled the use of methods for spatial flux estimates. The lack of detailed information of the physical driver's spatial distribution restricts the spatial flux estimation to the application of the T-proxy method, whose highly uncertain results mainly provide coarse spatial flux estimates. The study concludes that the upscaling of groundwater-stream water interactions using thermal measurements with combined point and distributed techniques requires the integration of physical drivers because of the heterogeneity of the flux patterns. Combined experimental and modeling approaches may help to obtain more reliable understanding of groundwater-surface water interactions at multiple scales.

Satellite Remote Sensing of Harmful Algal Blooms (HABs) and a Potential Synthesized Framework

PubMed Central

Shen, Li; Xu, Huiping; Guo, Xulin

2012-01-01

Harmful algal blooms (HABs) are severe ecological disasters threatening aquatic systems throughout the World, which necessitate scientific efforts in detecting and monitoring them. Compared with traditional in situ point observations, satellite remote sensing is considered as a promising technique for studying HABs due to its advantages of large-scale, real-time, and long-term monitoring. The present review summarizes the suitability of current satellite data sources and different algorithms for detecting HABs. It also discusses the spatial scale issue of HABs. Based on the major problems identified from previous literature, including the unsystematic understanding of HABs, the insufficient incorporation of satellite remote sensing, and a lack of multiple oceanographic explanations of the mechanisms causing HABs, this review also attempts to provide a comprehensive understanding of the complicated mechanism of HABs impacted by multiple oceanographic factors. A potential synthesized framework can be established by combining multiple accessible satellite remote sensing approaches including visual interpretation, spectra analysis, parameters retrieval and spatial-temporal pattern analysis. This framework aims to lead to a systematic and comprehensive monitoring of HABs based on satellite remote sensing from multiple oceanographic perspectives. PMID:22969372

SU-F-I-10: Spatially Local Statistics for Adaptive Image Filtering

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

Iliopoulos, AS; Sun, X; Floros, D

Purpose: To facilitate adaptive image filtering operations, addressing spatial variations in both noise and signal. Such issues are prevalent in cone-beam projections, where physical effects such as X-ray scattering result in spatially variant noise, violating common assumptions of homogeneous noise and challenging conventional filtering approaches to signal extraction and noise suppression. Methods: We present a computational mechanism for probing into and quantifying the spatial variance of noise throughout an image. The mechanism builds a pyramid of local statistics at multiple spatial scales; local statistical information at each scale includes (weighted) mean, median, standard deviation, median absolute deviation, as well asmore » histogram or dynamic range after local mean/median shifting. Based on inter-scale differences of local statistics, the spatial scope of distinguishable noise variation is detected in a semi- or un-supervised manner. Additionally, we propose and demonstrate the incorporation of such information in globally parametrized (i.e., non-adaptive) filters, effectively transforming the latter into spatially adaptive filters. The multi-scale mechanism is materialized by efficient algorithms and implemented in parallel CPU/GPU architectures. Results: We demonstrate the impact of local statistics for adaptive image processing and analysis using cone-beam projections of a Catphan phantom, fitted within an annulus to increase X-ray scattering. The effective spatial scope of local statistics calculations is shown to vary throughout the image domain, necessitating multi-scale noise and signal structure analysis. Filtering results with and without spatial filter adaptation are compared visually, illustrating improvements in imaging signal extraction and noise suppression, and in preserving information in low-contrast regions. Conclusion: Local image statistics can be incorporated in filtering operations to equip them with spatial adaptivity to spatial signal/noise variations. An efficient multi-scale computational mechanism is developed to curtail processing latency. Spatially adaptive filtering may impact subsequent processing tasks such as reconstruction and numerical gradient computations for deformable registration. NIH Grant No. R01-184173.« less

Novel patch modelling method for efficient simulation and prediction uncertainty analysis of multi-scale groundwater flow and transport processes

NASA Astrophysics Data System (ADS)

Sreekanth, J.; Moore, Catherine

2018-04-01

The application of global sensitivity and uncertainty analysis techniques to groundwater models of deep sedimentary basins are typically challenged by large computational burdens combined with associated numerical stability issues. The highly parameterized approaches required for exploring the predictive uncertainty associated with the heterogeneous hydraulic characteristics of multiple aquifers and aquitards in these sedimentary basins exacerbate these issues. A novel Patch Modelling Methodology is proposed for improving the computational feasibility of stochastic modelling analysis of large-scale and complex groundwater models. The method incorporates a nested groundwater modelling framework that enables efficient simulation of groundwater flow and transport across multiple spatial and temporal scales. The method also allows different processes to be simulated within different model scales. Existing nested model methodologies are extended by employing 'joining predictions' for extrapolating prediction-salient information from one model scale to the next. This establishes a feedback mechanism supporting the transfer of information from child models to parent models as well as parent models to child models in a computationally efficient manner. This feedback mechanism is simple and flexible and ensures that while the salient small scale features influencing larger scale prediction are transferred back to the larger scale, this does not require the live coupling of models. This method allows the modelling of multiple groundwater flow and transport processes using separate groundwater models that are built for the appropriate spatial and temporal scales, within a stochastic framework, while also removing the computational burden associated with live model coupling. The utility of the method is demonstrated by application to an actual large scale aquifer injection scheme in Australia.

Asynchrony in the inter-annual recruitment of lake whitefish Coregonus clupeaformis in the Great Lakes region

USGS Publications Warehouse

Zischke, Mitchell T.; Bunnell, David B.; Troy, Cary D.; Berglund, Eric K.; Caroffino, David C.; Ebener, Mark P.; He, Ji X.; Sitar, Shawn P.; Hook, Tomas O.

2017-01-01

Spatially separated fish populations may display synchrony in annual recruitment if the factors that drive recruitment success, particularly abiotic factors such as temperature, are synchronised across broad spatial scales. We examined inter-annual variation in recruitment among lake whitefish (Coregonus clupeaformis) populations in lakes Huron, Michigan and Superior using fishery-dependent and -independent data from 1971 to 2014. Relative year-class strength (RYCS) was calculated from catch-curve residuals for each year class across multiple sampling years. Pairwise comparison of RYCS among datasets revealed no significant associations either within or between lakes, suggesting that recruitment of lake whitefish is spatially asynchronous. There was no consistent correlation between pairwise agreement and the distance between datasets, and models to estimate the spatial scale of recruitment synchrony did not fit well to these data. This suggests that inter-annual recruitment variation of lake whitefish is asynchronous across broad spatial scales in the Great Lakes. While our method primarily evaluated year-to-year recruitment variation, it is plausible that recruitment of lake whitefish varies at coarser temporal scales (e.g. decadal). Nonetheless, our findings differ from research on some other Coregonus species and suggest that local biotic or density-dependent factors may contribute strongly to lake whitefish recruitment rather than inter-annual variability in broad-scale abiotic factors.

Toward seamless hydrologic predictions across spatial scales

NASA Astrophysics Data System (ADS)

Samaniego, Luis; Kumar, Rohini; Thober, Stephan; Rakovec, Oldrich; Zink, Matthias; Wanders, Niko; Eisner, Stephanie; Müller Schmied, Hannes; Sutanudjaja, Edwin H.; Warrach-Sagi, Kirsten; Attinger, Sabine

2017-09-01

Land surface and hydrologic models (LSMs/HMs) are used at diverse spatial resolutions ranging from catchment-scale (1-10 km) to global-scale (over 50 km) applications. Applying the same model structure at different spatial scales requires that the model estimates similar fluxes independent of the chosen resolution, i.e., fulfills a flux-matching condition across scales. An analysis of state-of-the-art LSMs and HMs reveals that most do not have consistent hydrologic parameter fields. Multiple experiments with the mHM, Noah-MP, PCR-GLOBWB, and WaterGAP models demonstrate the pitfalls of deficient parameterization practices currently used in most operational models, which are insufficient to satisfy the flux-matching condition. These examples demonstrate that J. Dooge's 1982 statement on the unsolved problem of parameterization in these models remains true. Based on a review of existing parameter regionalization techniques, we postulate that the multiscale parameter regionalization (MPR) technique offers a practical and robust method that provides consistent (seamless) parameter and flux fields across scales. Herein, we develop a general model protocol to describe how MPR can be applied to a particular model and present an example application using the PCR-GLOBWB model. Finally, we discuss potential advantages and limitations of MPR in obtaining the seamless prediction of hydrological fluxes and states across spatial scales.

A rank-based approach for correcting systematic biases in spatial disaggregation of coarse-scale climate simulations

NASA Astrophysics Data System (ADS)

Nahar, Jannatun; Johnson, Fiona; Sharma, Ashish

2017-07-01

Use of General Circulation Model (GCM) precipitation and evapotranspiration sequences for hydrologic modelling can result in unrealistic simulations due to the coarse scales at which GCMs operate and the systematic biases they contain. The Bias Correction Spatial Disaggregation (BCSD) method is a popular statistical downscaling and bias correction method developed to address this issue. The advantage of BCSD is its ability to reduce biases in the distribution of precipitation totals at the GCM scale and then introduce more realistic variability at finer scales than simpler spatial interpolation schemes. Although BCSD corrects biases at the GCM scale before disaggregation; at finer spatial scales biases are re-introduced by the assumptions made in the spatial disaggregation process. Our study focuses on this limitation of BCSD and proposes a rank-based approach that aims to reduce the spatial disaggregation bias especially for both low and high precipitation extremes. BCSD requires the specification of a multiplicative bias correction anomaly field that represents the ratio of the fine scale precipitation to the disaggregated precipitation. It is shown that there is significant temporal variation in the anomalies, which is masked when a mean anomaly field is used. This can be improved by modelling the anomalies in rank-space. Results from the application of the rank-BCSD procedure improve the match between the distributions of observed and downscaled precipitation at the fine scale compared to the original BCSD approach. Further improvements in the distribution are identified when a scaling correction to preserve mass in the disaggregation process is implemented. An assessment of the approach using a single GCM over Australia shows clear advantages especially in the simulation of particularly low and high downscaled precipitation amounts.

Hotspots of Community Change: Temporal Dynamics Are Spatially Variable in Understory Plant Composition of a California Oak Woodland

PubMed Central

Spotswood, Erica N.; Bartolome, James W.; Allen-Diaz, Barbara

2015-01-01

Community response to external drivers such climate and disturbance can lead to fluctuations in community composition, or to directional change. Temporal dynamics can be influenced by a combination of drivers operating at multiple spatial scales, including external landscape scale drivers, local abiotic conditions, and local species pools. We hypothesized that spatial variation in these factors can create heterogeneity in temporal dynamics within landscapes. We used understory plant species composition from an 11 year dataset from a California oak woodland to compare plots where disturbance was experimentally manipulated with the removal of livestock grazing and a prescribed burn. We quantified three properties of temporal variation: compositional change (reflecting the appearance and disappearance of species), temporal fluctuation, and directional change. Directional change was related most strongly to disturbance type, and was highest at plots where grazing was removed during the study. Temporal fluctuations, compositional change, and directional change were all related to intrinsic abiotic factors, suggesting that some locations are more responsive to external drivers than others. Temporal fluctuations and compositional change were linked to local functional composition, indicating that environmental filters can create subsets of the local species pool that do not respond in the same way to external drivers. Temporal dynamics are often assumed to be relatively static at the landscape scale, provided disturbance and climate are continuous. This study shows that local and landscape scale factors jointly influence temporal dynamics creating hotspots that are particularly responsive to climate and disturbance. Thus, adequate predictions of response to disturbance or to changing climate will only be achieved by considering how factors at multiple spatial scales influence community resilience and recovery. PMID:26222069

Effect of Spatial Resolution for Characterizing Soil Properties from Imaging Spectrometer Data

NASA Astrophysics Data System (ADS)

Dutta, D.; Kumar, P.; Greenberg, J. A.

2015-12-01

The feasibility of quantifying soil constituents over large areas using airborne hyperspectral data [0.35 - 2.5 μm] in an ensemble bootstrapping lasso algorithmic framework has been demonstrated previously [1]. However the effects of coarsening the spatial resolution of hyperspectral data on the quantification of soil constituents are unknown. We use Airborne Visible Infrared Imaging Spectrometer (AVIRIS) data collected at 7.6m resolution over Birds Point New Madrid (BPNM) floodway for up-scaling and generating multiple coarser resolution datasets including the 60m Hyperspectral Infrared Imager (HyspIRI) like data. HyspIRI is a proposed visible shortwave/thermal infrared mission, which will provide global data over a spectral range of 0.35 - 2.5μm at a spatial resolution of 60m. Our results show that the lasso method, which is based on point scale observational data, is scalable. We found consistent good model performance (R2) values (0.79 < R2 < 0.82) and correct classifications as per USDA soil texture classes at multiple spatial resolutions. The results further demonstrate that the attributes of the pdf for different soil constituents across the landscape and the within-pixel variance are well preserved across scales. Our analysis provides a methodological framework with a sufficient set of metrics for assessing the performance of scaling up analysis from point scale observational data and may be relevant for other similar remote sensing studies. [1] Dutta, D.; Goodwell, A.E.; Kumar, P.; Garvey, J.E.; Darmody, R.G.; Berretta, D.P.; Greenberg, J.A., "On the Feasibility of Characterizing Soil Properties From AVIRIS Data," Geoscience and Remote Sensing, IEEE Transactions on, vol.53, no.9, pp.5133,5147, Sept. 2015. doi: 10.1109/TGRS.2015.2417547.

Hotspots of Community Change: Temporal Dynamics Are Spatially Variable in Understory Plant Composition of a California Oak Woodland.

PubMed

Spotswood, Erica N; Bartolome, James W; Allen-Diaz, Barbara

2015-01-01

Community response to external drivers such climate and disturbance can lead to fluctuations in community composition, or to directional change. Temporal dynamics can be influenced by a combination of drivers operating at multiple spatial scales, including external landscape scale drivers, local abiotic conditions, and local species pools. We hypothesized that spatial variation in these factors can create heterogeneity in temporal dynamics within landscapes. We used understory plant species composition from an 11 year dataset from a California oak woodland to compare plots where disturbance was experimentally manipulated with the removal of livestock grazing and a prescribed burn. We quantified three properties of temporal variation: compositional change (reflecting the appearance and disappearance of species), temporal fluctuation, and directional change. Directional change was related most strongly to disturbance type, and was highest at plots where grazing was removed during the study. Temporal fluctuations, compositional change, and directional change were all related to intrinsic abiotic factors, suggesting that some locations are more responsive to external drivers than others. Temporal fluctuations and compositional change were linked to local functional composition, indicating that environmental filters can create subsets of the local species pool that do not respond in the same way to external drivers. Temporal dynamics are often assumed to be relatively static at the landscape scale, provided disturbance and climate are continuous. This study shows that local and landscape scale factors jointly influence temporal dynamics creating hotspots that are particularly responsive to climate and disturbance. Thus, adequate predictions of response to disturbance or to changing climate will only be achieved by considering how factors at multiple spatial scales influence community resilience and recovery.

Effects of land cover, topography, and built structure on seasonal water quality at multiple spatial scales.

PubMed

Pratt, Bethany; Chang, Heejun

2012-03-30

The relationship among land cover, topography, built structure and stream water quality in the Portland Metro region of Oregon and Clark County, Washington areas, USA, is analyzed using ordinary least squares (OLS) and geographically weighted (GWR) multiple regression models. Two scales of analysis, a sectional watershed and a buffer, offered a local and a global investigation of the sources of stream pollutants. Model accuracy, measured by R(2) values, fluctuated according to the scale, season, and regression method used. While most wet season water quality parameters are associated with urban land covers, most dry season water quality parameters are related topographic features such as elevation and slope. GWR models, which take into consideration local relations of spatial autocorrelation, had stronger results than OLS regression models. In the multiple regression models, sectioned watershed results were consistently better than the sectioned buffer results, except for dry season pH and stream temperature parameters. This suggests that while riparian land cover does have an effect on water quality, a wider contributing area needs to be included in order to account for distant sources of pollutants. Copyright © 2012 Elsevier B.V. All rights reserved.

Spatial correlation and irradiance statistics in a multiple-beam terrestrial free-space optical communication link.

PubMed

Anguita, Jaime A; Neifeld, Mark A; Vasic, Bane V

2007-09-10

By means of numerical simulations we analyze the statistical properties of the power fluctuations induced by the incoherent superposition of multiple transmitted laser beams in a terrestrial free-space optical communication link. The measured signals arising from different transmitted optical beams are found to be statistically correlated. This channel correlation increases with receiver aperture and propagation distance. We find a simple scaling rule for the spatial correlation coefficient in terms of the propagation distance and we are able to predict the scintillation reduction in previously reported experiments with good accuracy. We propose an approximation to the probability density function of the received power of a spatially correlated multiple-beam system in terms of the parameters of the single-channel gamma-gamma function. A bit-error-rate evaluation is also presented to demonstrate the improvement of a multibeam system over its single-beam counterpart.

Circumpolar spatio-temporal patterns and contributing climatic factors of wildfire activity in the Arctic tundra from 2001-2015

NASA Astrophysics Data System (ADS)

Masrur, Arif; Petrov, Andrey N.; DeGroote, John

2018-01-01

Recent years have seen an increased frequency of wildfire events in different parts of Arctic tundra ecosystems. Contemporary studies have largely attributed these wildfire events to the Arctic’s rapidly changing climate and increased atmospheric disturbances (i.e. thunderstorms). However, existing research has primarily examined the wildfire-climate dynamics of individual large wildfire events. No studies have investigated wildfire activity, including climatic drivers, for the entire tundra biome across multiple years, i.e. at the planetary scale. To address this limitation, this paper provides a planetary/circumpolar scale analyses of space-time patterns of tundra wildfire occurrence and climatic association in the Arctic over a 15 year period (2001-2015). In doing so, we have leveraged and analyzed NASA Terra’s MODIS active fire and MERRA climate reanalysis products at multiple temporal scales (decadal, seasonal and monthly). Our exploratory spatial data analysis found that tundra wildfire occurrence was spatially clustered and fire intensity was spatially autocorrelated across the Arctic regions. Most of the wildfire events occurred in the peak summer months (June-August). Our multi-temporal (decadal, seasonal and monthly) scale analyses provide further support to the link between climate variability and wildfire activity. Specifically, we found that warm and dry conditions in the late spring to mid-summer influenced tundra wildfire occurrence, spatio-temporal distribution, and fire intensity. Additionally, reduced average surface precipitation and soil moisture levels in the winter-spring period were associated with increased fire intensity in the following summer. These findings enrich contemporary knowledge on tundra wildfire’s spatial and seasonal patterns, and shed new light on tundra wildfire-climate relationships in the circumpolar context. Furthermore, this first pan-Arctic analysis provides a strong incentive and direction for future studies which integrate multiple datasets (i.e. climate, fuels, topography, and ignition sources) to accurately estimate carbon emission from tundra burning and its global climate feedbacks in coming decades.

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...

Development of a spatially universal framework for classifying stream assemblages with application to conservation planning for Great Lakes lotic fish communities

USGS Publications Warehouse

McKenna, James E.; Schaeffer, Jeffrey S.; Stewart, Jana S.; Slattery, Michael T.

2015-01-01

Classifications are typically specific to particular issues or areas, leading to patchworks of subjectively defined spatial units. Stream conservation is hindered by the lack of a universal habitat classification system and would benefit from an independent hydrology-guided spatial framework of units encompassing all aquatic habitats at multiple spatial scales within large regions. We present a system that explicitly separates the spatial framework from any particular classification developed from the framework. The framework was constructed from landscape variables that are hydrologically and biologically relevant, covered all space within the study area, and was nested hierarchically and spatially related at scales ranging from the stream reach to the entire region; classifications may be developed from any subset of the 9 basins, 107 watersheds, 459 subwatersheds, or 10,000s of valley segments or stream reaches. To illustrate the advantages of this approach, we developed a fish-guided classification generated from a framework for the Great Lakes region that produced a mosaic of habitat units which, when aggregated, formed larger patches of more general conditions at progressively broader spatial scales. We identified greater than 1,200 distinct fish habitat types at the valley segment scale, most of which were rare. Comparisons of biodiversity and species assemblages are easily examined at any scale. This system can identify and quantify habitat types, evaluate habitat quality for conservation and/or restoration, and assist managers and policymakers with prioritization of protection and restoration efforts. Similar spatial frameworks and habitat classifications can be developed for any organism in any riverine ecosystem.

Multi-resource and multi-scale approaches for meeting the challenge of managing multiple species

Treesearch

Frank R. Thompson; Deborah M. Finch; John R. Probst; Glen D. Gaines; David S. Dobkin

1999-01-01

The large number of Neotropical migratory bird (NTMB) species and their diverse habitat requirements create conflicts and difficulties for land managers and conservationists. We provide examples of assessments or conservation efforts that attempt to address the problem of managing for multiple NTMB species. We advocate approaches at a variety of spatial and geographic...

Using d15 N in Fish Larvae as an Indicator of Watershed Sources of Anthropogenic Nitrogen: Response at Multiple Spatial Scales

EPA Science Inventory

The nitrogen stable isotope, 15N, is an effective tool to track anthropogenic N sources to aquatic ecosystems. It may be difficult to identify potential N sources, however, where 15N responds similarly to multiple, concurrent activities in the watershed that cause higher nutrient...

Probabilistic Downscaling of Remote Sensing Data with Applications for Multi-Scale Biogeochemical Flux Modeling.

PubMed

Stoy, Paul C; Quaife, Tristan

2015-01-01

Upscaling ecological information to larger scales in space and downscaling remote sensing observations or model simulations to finer scales remain grand challenges in Earth system science. Downscaling often involves inferring subgrid information from coarse-scale data, and such ill-posed problems are classically addressed using regularization. Here, we apply two-dimensional Tikhonov Regularization (2DTR) to simulate subgrid surface patterns for ecological applications. Specifically, we test the ability of 2DTR to simulate the spatial statistics of high-resolution (4 m) remote sensing observations of the normalized difference vegetation index (NDVI) in a tundra landscape. We find that the 2DTR approach as applied here can capture the major mode of spatial variability of the high-resolution information, but not multiple modes of spatial variability, and that the Lagrange multiplier (γ) used to impose the condition of smoothness across space is related to the range of the experimental semivariogram. We used observed and 2DTR-simulated maps of NDVI to estimate landscape-level leaf area index (LAI) and gross primary productivity (GPP). NDVI maps simulated using a γ value that approximates the range of observed NDVI result in a landscape-level GPP estimate that differs by ca 2% from those created using observed NDVI. Following findings that GPP per unit LAI is lower near vegetation patch edges, we simulated vegetation patch edges using multiple approaches and found that simulated GPP declined by up to 12% as a result. 2DTR can generate random landscapes rapidly and can be applied to disaggregate ecological information and compare of spatial observations against simulated landscapes.

Probabilistic Downscaling of Remote Sensing Data with Applications for Multi-Scale Biogeochemical Flux Modeling

PubMed Central

Stoy, Paul C.; Quaife, Tristan

2015-01-01

Upscaling ecological information to larger scales in space and downscaling remote sensing observations or model simulations to finer scales remain grand challenges in Earth system science. Downscaling often involves inferring subgrid information from coarse-scale data, and such ill-posed problems are classically addressed using regularization. Here, we apply two-dimensional Tikhonov Regularization (2DTR) to simulate subgrid surface patterns for ecological applications. Specifically, we test the ability of 2DTR to simulate the spatial statistics of high-resolution (4 m) remote sensing observations of the normalized difference vegetation index (NDVI) in a tundra landscape. We find that the 2DTR approach as applied here can capture the major mode of spatial variability of the high-resolution information, but not multiple modes of spatial variability, and that the Lagrange multiplier (γ) used to impose the condition of smoothness across space is related to the range of the experimental semivariogram. We used observed and 2DTR-simulated maps of NDVI to estimate landscape-level leaf area index (LAI) and gross primary productivity (GPP). NDVI maps simulated using a γ value that approximates the range of observed NDVI result in a landscape-level GPP estimate that differs by ca 2% from those created using observed NDVI. Following findings that GPP per unit LAI is lower near vegetation patch edges, we simulated vegetation patch edges using multiple approaches and found that simulated GPP declined by up to 12% as a result. 2DTR can generate random landscapes rapidly and can be applied to disaggregate ecological information and compare of spatial observations against simulated landscapes. PMID:26067835

Spatial variability of Chinook salmon spawning distribution and habitat preferences

USGS Publications Warehouse

Cram, Jeremy M.; Torgersen, Christian E.; Klett, Ryan S.; Pess, George R.; May, Darran; Pearsons, Todd N.; Dittman, Andrew H.

2017-01-01

We investigated physical habitat conditions associated with the spawning sites of Chinook Salmon Oncorhynchus tshawytscha and the interannual consistency of spawning distribution across multiple spatial scales using a combination of spatially continuous and discrete sampling methods. We conducted a census of aquatic habitat in 76 km of the upper main-stem Yakima River in Washington and evaluated spawning site distribution using redd survey data from 2004 to 2008. Interannual reoccupation of spawning areas was high, ranging from an average Pearson’s correlation of 0.62 to 0.98 in channel subunits and 10-km reaches, respectively. Annual variance in the interannual correlation of spawning distribution was highest in channel units and subunits, but it was low at reach scales. In 13 of 15 models developed for individual years (2004–2008) and reach lengths (800 m, 3 km, 6 km), stream power and depth were the primary predictors of redd abundance. Multiple channels and overhead cover were patchy but were important secondary and tertiary predictors of reach-scale spawning site selection. Within channel units and subunits, pool tails and thermal variability, which may be associated with hyporheic exchange, were important predictors of spawning. We identified spawning habitat preferences within reaches and channel units that are relevant for salmonid habitat restoration planning. We also identified a threshold (i.e., 2-km reaches) beyond which interannual spawning distribution was markedly consistent, which may be informative for prioritizing habitat restoration or conservation. Management actions may be improved through enhanced understanding of spawning habitat preferences and the consistency with which Chinook Salmon reoccupy spawning areas at different spatial scales.

Alternative spatial configurations to reflect landscape structure in a hydrological model: SUMMA applications to the Reynolds Creek Watershed and the Columbia River Basin

NASA Astrophysics Data System (ADS)

Nijssen, Bart; Clark, Martyn; Mizukami, Naoki; Chegwidden, Oriana

2016-04-01

Most existing hydrological models use a fixed representation of landscape structure. For example, high-resolution, spatially-distributed models may use grid cells that exchange moisture through the saturated subsurface or may divide the landscape into hydrologic response units that only exchange moisture through surface channels. Alternatively, many regional models represent the landscape through coarse elements that do not model any moisture exchange between these model elements. These spatial organizations are often represented at a low-level in the model code and its data structures, which makes it difficult to evaluate different landscape representations using the same hydrological model. Instead, such experimentation requires the use of multiple, different hydrological models, which in turn complicates the analysis, because differences in model outcomes are no longer constrained by differing spatial representations. This inflexibility in the representation of landscape structure also limits a model's capability for scaling local processes to regional outcomes. In this study, we used the Structure for Unifying Multiple Modeling Alternatives (SUMMA) to evaluate different model spatial configurations to represent landscape structure and to evaluate scaling behavior. SUMMA can represent the moisture exchange between arbitrarily shaped landscape elements in a number of different ways, while using the same model parameterizations for vertical fluxes. This allows us to isolate the effects of changes in landscape representations on modeled hydrological fluxes and states. We examine the effects of spatial configuration in Reynolds Creek, Idaho, USA, which is a research watershed with gaged areas from 1-20 km2. We then use the same modeling system to evaluate scaling behavior in simulated hydrological fluxes in the Columbia River Basin, Pacific Northwest, USA. This basin drains more than 500,000 km2 and includes the Reynolds Creek Watershed.

A Simple Iterative Model Accurately Captures Complex Trapline Formation by Bumblebees Across Spatial Scales and Flower Arrangements

PubMed Central

Reynolds, Andrew M.; Lihoreau, Mathieu; Chittka, Lars

2013-01-01

Pollinating bees develop foraging circuits (traplines) to visit multiple flowers in a manner that minimizes overall travel distance, a task analogous to the travelling salesman problem. We report on an in-depth exploration of an iterative improvement heuristic model of bumblebee traplining previously found to accurately replicate the establishment of stable routes by bees between flowers distributed over several hectares. The critical test for a model is its predictive power for empirical data for which the model has not been specifically developed, and here the model is shown to be consistent with observations from different research groups made at several spatial scales and using multiple configurations of flowers. We refine the model to account for the spatial search strategy of bees exploring their environment, and test several previously unexplored predictions. We find that the model predicts accurately 1) the increasing propensity of bees to optimize their foraging routes with increasing spatial scale; 2) that bees cannot establish stable optimal traplines for all spatial configurations of rewarding flowers; 3) the observed trade-off between travel distance and prioritization of high-reward sites (with a slight modification of the model); 4) the temporal pattern with which bees acquire approximate solutions to travelling salesman-like problems over several dozen foraging bouts; 5) the instability of visitation schedules in some spatial configurations of flowers; 6) the observation that in some flower arrays, bees' visitation schedules are highly individually different; 7) the searching behaviour that leads to efficient location of flowers and routes between them. Our model constitutes a robust theoretical platform to generate novel hypotheses and refine our understanding about how small-brained insects develop a representation of space and use it to navigate in complex and dynamic environments. PMID:23505353

Exploring the effects of spatial autocorrelation when identifying key drivers of wildlife crop-raiding.

PubMed

Songhurst, Anna; Coulson, Tim

2014-03-01

Few universal trends in spatial patterns of wildlife crop-raiding have been found. Variations in wildlife ecology and movements, and human spatial use have been identified as causes of this apparent unpredictability. However, varying spatial patterns of spatial autocorrelation (SA) in human-wildlife conflict (HWC) data could also contribute. We explicitly explore the effects of SA on wildlife crop-raiding data in order to facilitate the design of future HWC studies. We conducted a comparative survey of raided and nonraided fields to determine key drivers of crop-raiding. Data were subsampled at different spatial scales to select independent raiding data points. The model derived from all data was fitted to subsample data sets. Model parameters from these models were compared to determine the effect of SA. Most methods used to account for SA in data attempt to correct for the change in P-values; yet, by subsampling data at broader spatial scales, we identified changes in regression estimates. We consequently advocate reporting both model parameters across a range of spatial scales to help biological interpretation. Patterns of SA vary spatially in our crop-raiding data. Spatial distribution of fields should therefore be considered when choosing the spatial scale for analyses of HWC studies. Robust key drivers of elephant crop-raiding included raiding history of a field and distance of field to a main elephant pathway. Understanding spatial patterns and determining reliable socio-ecological drivers of wildlife crop-raiding is paramount for designing mitigation and land-use planning strategies to reduce HWC. Spatial patterns of HWC are complex, determined by multiple factors acting at more than one scale; therefore, studies need to be designed with an understanding of the effects of SA. Our methods are accessible to a variety of practitioners to assess the effects of SA, thereby improving the reliability of conservation management actions.

Managing aquatic ecosystems and water resources under multiple stress--an introduction to the MARS project.

PubMed

Hering, Daniel; Carvalho, Laurence; Argillier, Christine; Beklioglu, Meryem; Borja, Angel; Cardoso, Ana Cristina; Duel, Harm; Ferreira, Teresa; Globevnik, Lidija; Hanganu, Jenica; Hellsten, Seppo; Jeppesen, Erik; Kodeš, Vit; Solheim, Anne Lyche; Nõges, Tiina; Ormerod, Steve; Panagopoulos, Yiannis; Schmutz, Stefan; Venohr, Markus; Birk, Sebastian

2015-01-15

Water resources globally are affected by a complex mixture of stressors resulting from a range of drivers, including urban and agricultural land use, hydropower generation and climate change. Understanding how stressors interfere and impact upon ecological status and ecosystem services is essential for developing effective River Basin Management Plans and shaping future environmental policy. This paper details the nature of these problems for Europe's water resources and the need to find solutions at a range of spatial scales. In terms of the latter, we describe the aims and approaches of the EU-funded project MARS (Managing Aquatic ecosystems and water Resources under multiple Stress) and the conceptual and analytical framework that it is adopting to provide this knowledge, understanding and tools needed to address multiple stressors. MARS is operating at three scales: At the water body scale, the mechanistic understanding of stressor interactions and their impact upon water resources, ecological status and ecosystem services will be examined through multi-factorial experiments and the analysis of long time-series. At the river basin scale, modelling and empirical approaches will be adopted to characterise relationships between multiple stressors and ecological responses, functions, services and water resources. The effects of future land use and mitigation scenarios in 16 European river basins will be assessed. At the European scale, large-scale spatial analysis will be carried out to identify the relationships amongst stress intensity, ecological status and service provision, with a special focus on large transboundary rivers, lakes and fish. The project will support managers and policy makers in the practical implementation of the Water Framework Directive (WFD), of related legislation and of the Blueprint to Safeguard Europe's Water Resources by advising the 3rd River Basin Management Planning cycle, the revision of the WFD and by developing new tools for diagnosing and predicting multiple stressors. Copyright © 2014. Published by Elsevier B.V.

A multi-scale spatial analysis of native and exotic plant species richness within a mixed-disturbance oak savanna landscape.

PubMed

Schetter, Timothy A; Walters, Timothy L; Root, Karen V

2013-09-01

Impacts of human land use pose an increasing threat to global biodiversity. Resource managers must respond rapidly to this threat by assessing existing natural areas and prioritizing conservation actions across multiple spatial scales. Plant species richness is a useful measure of biodiversity but typically can only be evaluated on small portions of a given landscape. Modeling relationships between spatial heterogeneity and species richness may allow conservation planners to make predictions of species richness patterns within unsampled areas. We utilized a combination of field data, remotely sensed data, and landscape pattern metrics to develop models of native and exotic plant species richness at two spatial extents (60- and 120-m windows) and at four ecological levels for northwestern Ohio's Oak Openings region. Multiple regression models explained 37-77 % of the variation in plant species richness. These models consistently explained more variation in exotic richness than in native richness. Exotic richness was better explained at the 120-m extent while native richness was better explained at the 60-m extent. Land cover composition of the surrounding landscape was an important component of all models. We found that percentage of human-modified land cover (negatively correlated with native richness and positively correlated with exotic richness) was a particularly useful predictor of plant species richness and that human-caused disturbances exert a strong influence on species richness patterns within a mixed-disturbance oak savanna landscape. Our results emphasize the importance of using a multi-scale approach to examine the complex relationships between spatial heterogeneity and plant species richness.

The rich get richer: Patterns of plant invasions in the United States

USGS Publications Warehouse

Stohlgren, T.J.; Barnett, D.T.; Kartesz, J.T.

2003-01-01

Observations from islands, small-scale experiments, and mathematical models have generally supported the paradigm that habitats of low plant diversity are more vulnerable to plant invasions than areas of high plant diversity. We summarize two independent data sets to show exactly the opposite pattern at multiple spatial scales. More significant, and alarming, is that hotspots of native plant diversity have been far more heavily invaded than areas of low plant diversity in most parts of the United States when considered at larger spatial scales. Our findings suggest that we cannot expect such hotspots to repel invasions, and that the threat of invasion is significant and predictably greatest in these areas.

Long-term Spatial Distribution Patterns of Protozoa in Connected Microhabitats

NASA Astrophysics Data System (ADS)

Taghon, G. L.; Tuorto, S. J.

2016-02-01

Studies of microbial ecosystems usually assume habitat homogeneity. Recent research, however, indicates that habitat structure varies at millimeter scales and that this patchiness affects abundance and behavior of microbes. In this study, two species of ciliated protozoa were maintained, together, for multiple generations in microfluidic devices consisting of arrays of interconnected microhabitats with differing resource availability. The species differed in their population dynamics and tendency to disperse among microhabitats. Both species coexisted for over 45 days, and their coexistence likely resulted from habitat selection at millimeter scales. We demonstrate that it is not only possible, but imperative, that detailed ecological phenomena of microbial systems be studied at the relevant spatial and temporal scales.

Laura Jackson, Ph.D.

EPA Pesticide Factsheets

Research Biologist with the EPA. Her current work involves linking natural and built infrastructure to human health and well-being at multiple spatial scales, in order to develop interpretive maps and analytical tools for an interactive, web-based Atlas.

Spatial Structure of Seagrass Suggests That Size-Dependent Plant Traits Have a Strong Influence on the Distribution and Maintenance of Tropical Multispecies Meadows

PubMed Central

Ooi, Jillian L. S.; Van Niel, Kimberly P.; Kendrick, Gary A.; Holmes, Karen W.

2014-01-01

Background Seagrass species in the tropics occur in multispecies meadows. How these meadows are maintained through species co-existence and what their ecological drivers may be has been an overarching question in seagrass biogeography. In this study, we quantify the spatial structure of four co-existing species and infer potential ecological processes from these structures. Methods and Results Species presence/absence data were collected using underwater towed and dropped video cameras in Pulau Tinggi, Malaysia. The geostatistical method, utilizing semivariograms, was used to describe the spatial structure of Halophila spp, Halodule uninervis, Syringodium isoetifolium and Cymodocea serrulata. Species had spatial patterns that were oriented in the along-shore and across-shore directions, nested with larger species in meadow interiors, and consisted of multiple structures that indicate the influence of 2–3 underlying processes. The Linear Model of Coregionalization (LMC) was used to estimate the amount of variance contributing to the presence of a species at specific spatial scales. These distances were <2.5 m (micro-scale), 2.5–50 m (fine-scale) and >50 m (broad-scale) in the along-shore; and <2.5 m (micro-scale), 2.5–140 m (fine-scale) and >140 m (broad-scale) in the across-shore. The LMC suggests that smaller species (Halophila spp and H. uninervis) were most influenced by broad-scale processes such as hydrodynamics and water depth whereas large, localised species (S. isoetifolium and C. serrulata) were more influenced by finer-scale processes such as sediment burial, seagrass colonization and growth, and physical disturbance. Conclusion In this study, we provide evidence that spatial structure is distinct even when species occur in well-mixed multispecies meadows, and we suggest that size-dependent plant traits have a strong influence on the distribution and maintenance of tropical marine plant communities. This study offers a contrast from previous spatial models of seagrasses which have largely focused on monospecific temperate meadows. PMID:24497978

Spatial structure of seagrass suggests that size-dependent plant traits have a strong influence on the distribution and maintenance of tropical multispecies meadows.

PubMed

Ooi, Jillian L S; Van Niel, Kimberly P; Kendrick, Gary A; Holmes, Karen W

2014-01-01

Seagrass species in the tropics occur in multispecies meadows. How these meadows are maintained through species co-existence and what their ecological drivers may be has been an overarching question in seagrass biogeography. In this study, we quantify the spatial structure of four co-existing species and infer potential ecological processes from these structures. Species presence/absence data were collected using underwater towed and dropped video cameras in Pulau Tinggi, Malaysia. The geostatistical method, utilizing semivariograms, was used to describe the spatial structure of Halophila spp, Halodule uninervis, Syringodium isoetifolium and Cymodocea serrulata. Species had spatial patterns that were oriented in the along-shore and across-shore directions, nested with larger species in meadow interiors, and consisted of multiple structures that indicate the influence of 2-3 underlying processes. The Linear Model of Coregionalization (LMC) was used to estimate the amount of variance contributing to the presence of a species at specific spatial scales. These distances were <2.5 m (micro-scale), 2.5-50 m (fine-scale) and >50 m (broad-scale) in the along-shore; and <2.5 m (micro-scale), 2.5-140 m (fine-scale) and >140 m (broad-scale) in the across-shore. The LMC suggests that smaller species (Halophila spp and H. uninervis) were most influenced by broad-scale processes such as hydrodynamics and water depth whereas large, localised species (S. isoetifolium and C. serrulata) were more influenced by finer-scale processes such as sediment burial, seagrass colonization and growth, and physical disturbance. In this study, we provide evidence that spatial structure is distinct even when species occur in well-mixed multispecies meadows, and we suggest that size-dependent plant traits have a strong influence on the distribution and maintenance of tropical marine plant communities. This study offers a contrast from previous spatial models of seagrasses which have largely focused on monospecific temperate meadows.

A climate-change adaptation framework to reduce continental-scale vulnerability across conservation reserves

Treesearch

D.R. Magness; J.M. Morton; F. Huettmann; F.S. Chapin; A.D. McGuire

2011-01-01

Rapid climate change, in conjunction with other anthropogenic drivers, has the potential to cause mass species extinction. To minimize this risk, conservation reserves need to be coordinated at multiple spatial scales because the climate envelopes of many species may shift rapidly across large geographic areas. In addition, novel species assemblages and ecological...

Hierarchical den selection of Canada lynx in western Montana

Treesearch

John R. Squires; Nicholas J. Decesare; Jay A. Kolbe; Leonard F. Ruggiero

2008-01-01

We studied den selection of Canada lynx (Lynx canadensis; hereafter lynx) at multiple ecological scales based on 57 dens from 19 females located in western Montana, USA, between 1999 and 2006. We considered 3 spatial scales in this analysis, including den site (11-m-radius circle surrounding dens), den area (100-m-radius circle), and den environ (1-...

Managing landscapes at multiple scales for sustainability of ecosystem functions (Preface)

Treesearch

R.A. Birdsey; R. Lucas; Y. Pan; G. Sun; E.J. Gustafson; A.H.  Perera

2010-01-01

The science of landscape ecology is a rapidly evolving academic field with an emphasis on studying large-scale spatial heterogeneity created by natural influences and human activities. These advances have important implications for managing and conserving natural resources. At a September 2008 IUFRO conference in Chengdu, Sichuan, P.R. China, we highlighted both the...

Mapping fuels at multiple scales: landscape application of the fuel characteristic classification system.

Treesearch

D. McKenzie; C.L. Raymond; L.-K.B. Kellogg; R.A. Norheim; A.G. Andreu; A.C. Bayard; K.E. Kopper; E. Elman

2007-01-01

Fuel mapping is a complex and often multidisciplinary process, involving remote sensing, ground-based validation, statistical modeling, and knowledge-based systems. The scale and resolution of fuel mapping depend both on objectives and availability of spatial data layers. We demonstrate use of the Fuel Characteristic Classification System (FCCS) for fuel mapping at two...

Consistent patterns of variation in macrobenthic assemblages and environmental variables over multiple spatial scales using taxonomic and functional approaches.

PubMed

Veiga, Puri; Torres, Ana Catarina; Aneiros, Fernando; Sousa-Pinto, Isabel; Troncoso, Jesús S; Rubal, Marcos

2016-09-01

Spatial variability of environmental factors and macrobenthos, using species and functional groups, was examined over the same scales (100s of cm to >100 km) in intertidal sediments of two transitional water systems. The objectives were to test if functional groups were a good species surrogate and explore the relationship between environmental variables and macrobenthos. Environmental variables, diversity and the multivariate assemblage structure showed the highest variability at the scale of 10s of km. However, abundance was more variable at 10s of m. Consistent patterns were achieved using species and functional groups therefore, these may be a good species surrogate. Total carbon, salinity and silt/clay were the strongest correlated with macrobenthic assemblages. Results are valuable for design and interpretation of future monitoring programs including detection of anthropogenic disturbances in transitional systems and propose improvements in environmental variable sampling to refine the assessment of their relationship with biological data across spatial scales. Copyright © 2016 Elsevier Ltd. All rights reserved.

The pyramid system for multiscale raster analysis

USGS Publications Warehouse

De Cola, L.; Montagne, N.

1993-01-01

Geographical research requires the management and analysis of spatial data at multiple scales. As part of the U.S. Geological Survey's global change research program a software system has been developed that reads raster data (such as an image or digital elevation model) and produces a pyramid of aggregated lattices as well as various measurements of spatial complexity. For a given raster dataset the system uses the pyramid to report: (1) mean, (2) variance, (3) a spatial autocorrelation parameter based on multiscale analysis of variance, and (4) a monofractal scaling parameter based on the analysis of isoline lengths. The system is applied to 1-km digital elevation model (DEM) data for a 256-km2 region of central California, as well as to 64 partitions of the region. PYRAMID, which offers robust descriptions of data complexity, also is used to describe the behavior of topographic aspect with scale. ?? 1993.

Multiscale Structure of UXO Site Characterization: Spatial Estimation and Uncertainty Quantification

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

Ostrouchov, George; Doll, William E.; Beard, Les P.

2009-01-01

Unexploded ordnance (UXO) site characterization must consider both how the contamination is generated and how we observe that contamination. Within the generation and observation processes, dependence structures can be exploited at multiple scales. We describe a conceptual site characterization process, the dependence structures available at several scales, and consider their statistical estimation aspects. It is evident that most of the statistical methods that are needed to address the estimation problems are known but their application-specific implementation may not be available. We demonstrate estimation at one scale and propose a representation for site contamination intensity that takes full account of uncertainty,more » is flexible enough to answer regulatory requirements, and is a practical tool for managing detailed spatial site characterization and remediation. The representation is based on point process spatial estimation methods that require modern computational resources for practical application. These methods have provisions for including prior and covariate information.« less

The spatial and temporal domains of modern ecology.

PubMed

Estes, Lyndon; Elsen, Paul R; Treuer, Timothy; Ahmed, Labeeb; Caylor, Kelly; Chang, Jason; Choi, Jonathan J; Ellis, Erle C

2018-05-01

To understand ecological phenomena, it is necessary to observe their behaviour across multiple spatial and temporal scales. Since this need was first highlighted in the 1980s, technology has opened previously inaccessible scales to observation. To help to determine whether there have been corresponding changes in the scales observed by modern ecologists, we analysed the resolution, extent, interval and duration of observations (excluding experiments) in 348 studies that have been published between 2004 and 2014. We found that observational scales were generally narrow, because ecologists still primarily use conventional field techniques. In the spatial domain, most observations had resolutions ≤1 m 2 and extents ≤10,000 ha. In the temporal domain, most observations were either unreplicated or infrequently repeated (>1 month interval) and ≤1 year in duration. Compared with studies conducted before 2004, observational durations and resolutions appear largely unchanged, but intervals have become finer and extents larger. We also found a large gulf between the scales at which phenomena are actually observed and the scales those observations ostensibly represent, raising concerns about observational comprehensiveness. Furthermore, most studies did not clearly report scale, suggesting that it remains a minor concern. Ecologists can better understand the scales represented by observations by incorporating autocorrelation measures, while journals can promote attentiveness to scale by implementing scale-reporting standards.

Population cycles are highly correlated over long time series and large spatial scales in two unrelated species: Greater sage-grouse and cottontail rabbits

USGS Publications Warehouse

Fedy, B.C.; Doherty, K.E.

2011-01-01

Animal species across multiple taxa demonstrate multi-annual population cycles, which have long been of interest to ecologists. Correlated population cycles between species that do not share a predator-prey relationship are particularly intriguing and challenging to explain. We investigated annual population trends of greater sage-grouse (Centrocercus urophasianus) and cottontail rabbits (Sylvilagus sp.) across Wyoming to explore the possibility of correlations between unrelated species, over multiple cycles, very large spatial areas, and relatively southern latitudes in terms of cycling species. We analyzed sage-grouse lek counts and annual hunter harvest indices from 1982 to 2007. We show that greater sage-grouse, currently listed as warranted but precluded under the US Endangered Species Act, and cottontails have highly correlated cycles (r = 0. 77). We explore possible mechanistic hypotheses to explain the synchronous population cycles. Our research highlights the importance of control populations in both adaptive management and impact studies. Furthermore, we demonstrate the functional value of these indices (lek counts and hunter harvest) for tracking broad-scale fluctuations in the species. This level of highly correlated long-term cycling has not previously been documented between two non-related species, over a long time-series, very large spatial scale, and within more southern latitudes. ?? 2010 US Government.

Urban land use decouples plant-herbivore-parasitoid interactions at multiple spatial scales.

PubMed

Nelson, Amanda E; Forbes, Andrew A

2014-01-01

Intense urban and agricultural development alters habitats, increases fragmentation, and may decouple trophic interactions if plants or animals cannot disperse to needed resources. Specialist insects represent a substantial proportion of global biodiversity and their fidelity to discrete microhabitats provides a powerful framework for investigating organismal responses to human land use. We sampled site occupancy and densities for two plant-herbivore-parasitoid systems from 250 sites across a 360 km2 urban/agricultural landscape to ask whether and how human development decouples interactions between trophic levels. We compared patterns of site occupancy, host plant density, herbivory and parasitism rates of insects at two trophic levels with respect to landcover at multiple spatial scales. Geospatial analyses were used to identify landcover characters predictive of insect distributions. We found that herbivorous insect densities were decoupled from host tree densities in urban landcover types at several spatial scales. This effect was amplified for the third trophic level in one of the two insect systems: despite being abundant regionally, a parasitoid species was absent from all urban/suburban landcover even where its herbivore host was common. Our results indicate that human land use patterns limit distributions of specialist insects. Dispersal constraints associated with urban built development are specifically implicated as a limiting factor.

Urban Land Use Decouples Plant-Herbivore-Parasitoid Interactions at Multiple Spatial Scales

PubMed Central

Nelson, Amanda E.; Forbes, Andrew A.

2014-01-01

Intense urban and agricultural development alters habitats, increases fragmentation, and may decouple trophic interactions if plants or animals cannot disperse to needed resources. Specialist insects represent a substantial proportion of global biodiversity and their fidelity to discrete microhabitats provides a powerful framework for investigating organismal responses to human land use. We sampled site occupancy and densities for two plant-herbivore-parasitoid systems from 250 sites across a 360 km2 urban/agricultural landscape to ask whether and how human development decouples interactions between trophic levels. We compared patterns of site occupancy, host plant density, herbivory and parasitism rates of insects at two trophic levels with respect to landcover at multiple spatial scales. Geospatial analyses were used to identify landcover characters predictive of insect distributions. We found that herbivorous insect densities were decoupled from host tree densities in urban landcover types at several spatial scales. This effect was amplified for the third trophic level in one of the two insect systems: despite being abundant regionally, a parasitoid species was absent from all urban/suburban landcover even where its herbivore host was common. Our results indicate that human land use patterns limit distributions of specialist insects. Dispersal constraints associated with urban built development are specifically implicated as a limiting factor. PMID:25019962

Using occupancy estimation to assess the effectiveness of a regional multiple-species conservation plan: bats in the Pacific Northwest

Treesearch

Theodore Weller

2008-01-01

Regional conservation plans are increasingly used to plan for and protect biodiversity at large spatial scales however the means of quantitatively evaluating their effectiveness are rarely specified. Multiple-species approaches, particular those which employ site-occupancy estimation, have been proposed as robust and efficient alternatives for assessing the status of...

Assessing risks to multiple resources affected by wildfire and forest management using an integrated probabilistic framework

Treesearch

Steven P. Norman; Danny C. Lee; Sandra Jacobson; Christine Damiani

2010-01-01

The tradeoffs that surround forest management are inherently complex, often involving multiple temporal and spatial scales. For example, conflicts may result when fuel treatments are designed to mediate long-term fuel hazards, but activities could impair sensitive aquatic habitat or degrade wildlife habitat in the short term. This complexity makes it hard for managers...

Ultrafast Microscopy of Energy and Charge Transport

NASA Astrophysics Data System (ADS)

Huang, Libai

The frontier in solar energy research now lies in learning how to integrate functional entities across multiple length scales to create optimal devices. Advancing the field requires transformative experimental tools that probe energy transfer processes from the nano to the meso lengthscales. To address this challenge, we aim to understand multi-scale energy transport across both multiple length and time scales, coupling simultaneous high spatial, structural, and temporal resolution. In my talk, I will focus on our recent progress on visualization of exciton and charge transport in solar energy harvesting materials from the nano to mesoscale employing ultrafast optical nanoscopy. With approaches that combine spatial and temporal resolutions, we have recently revealed a new singlet-mediated triplet transport mechanism in certain singlet fission materials. This work demonstrates a new triplet exciton transport mechanism leading to favorable long-range triplet exciton diffusion on the picosecond and nanosecond timescales for solar cell applications. We have also performed a direct measurement of carrier transport in space and in time by mapping carrier density with simultaneous ultrafast time resolution and 50 nm spatial precision in perovskite thin films using transient absorption microscopy. These results directly visualize long-range carrier transport of 220nm in 2 ns for solution-processed polycrystalline CH3NH3PbI3 thin films. The spatially and temporally resolved measurements reported here underscore the importance of the local morphology and establish an important first step towards discerning the underlying transport properties of perovskite materials.

Estimation of the Relationship Between Remotely Sensed Anthropogenic Heat Discharge and Building Energy Use

NASA Technical Reports Server (NTRS)

Zhou, Yuyu; Weng, Qihao; Gurney, Kevin R.; Shuai, Yanmin; Hu, Xuefei

2012-01-01

This paper examined the relationship between remotely sensed anthropogenic heat discharge and energy use from residential and commercial buildings across multiple scales in the city of Indianapolis, Indiana, USA. The anthropogenic heat discharge was estimated with a remote sensing-based surface energy balance model, which was parameterized using land cover, land surface temperature, albedo, and meteorological data. The building energy use was estimated using a GIS-based building energy simulation model in conjunction with Department of Energy/Energy Information Administration survey data, the Assessor's parcel data, GIS floor areas data, and remote sensing-derived building height data. The spatial patterns of anthropogenic heat discharge and energy use from residential and commercial buildings were analyzed and compared. Quantitative relationships were evaluated across multiple scales from pixel aggregation to census block. The results indicate that anthropogenic heat discharge is consistent with building energy use in terms of the spatial pattern, and that building energy use accounts for a significant fraction of anthropogenic heat discharge. The research also implies that the relationship between anthropogenic heat discharge and building energy use is scale-dependent. The simultaneous estimation of anthropogenic heat discharge and building energy use via two independent methods improves the understanding of the surface energy balance in an urban landscape. The anthropogenic heat discharge derived from remote sensing and meteorological data may be able to serve as a spatial distribution proxy for spatially-resolved building energy use, and even for fossil-fuel CO2 emissions if additional factors are considered.

Bioregional monitoring design and occupancy estimation for two Sierra Nevadan amphibian taxa

EPA Science Inventory

Land-management agencies need quantitative, statistically rigorous monitoring data, often at large spatial and temporal scales, to support resource-management decisions. Monitoring designs typically must accommodate multiple ecological, logistical, political, and economic objec...

Soil Moisture fusion across scales using a multiscale nonstationary Spatial Hierarchical Model

NASA Astrophysics Data System (ADS)

Kathuria, D.; Mohanty, B.; Katzfuss, M.

2017-12-01

Soil moisture (SM) datasets from remote sensing (RS) platforms (such as SMOS and SMAP) and reanalysis products from land surface models are typically available on a coarse spatial granularity of several square km. Ground based sensors, on the other hand, provide observations on a finer spatial scale (meter scale or less) but are sparsely available. SM is affected by high variability due to complex interactions between geologic, topographic, vegetation and atmospheric variables and these interactions change dynamically with footprint scales. Past literature has largely focused on the scale specific effect of these covariates on soil moisture. The present study proposes a robust Multiscale-Nonstationary Spatial Hierarchical Model (MN-SHM) which can assimilate SM from point to RS footprints. The spatial structure of SM across footprints is modeled by a class of scalable covariance functions whose nonstationary depends on atmospheric forcings (such as precipitation) and surface physical controls (such as topography, soil-texture and vegetation). The proposed model is applied to fuse point and airborne ( 1.5 km) SM data obtained during the SMAPVEX12 campaign in the Red River watershed in Southern Manitoba, Canada with SMOS ( 30km) data. It is observed that precipitation, soil-texture and vegetation are the dominant factors which affect the SM distribution across various footprint scales (750 m, 1.5 km, 3 km, 9 km,15 km and 30 km). We conclude that MN-SHM handles the change of support problems easily while retaining reasonable predictive accuracy across multiple spatial resolutions in the presence of surface heterogeneity. The MN-SHM can be considered as a complex non-stationary extension of traditional geostatistical prediction methods (such as Kriging) for fusing multi-platform multi-scale datasets.

From watershed- to stream-reach-scale: the influence of multiple spatial scales on surface water-groundwater exchange

NASA Astrophysics Data System (ADS)

Caruso, Alice; Boano, Fulvio; Ridolfi, Luca

2015-04-01

Surface water bodies continuously interact with the subsurface and it is by now widely known that the hyporheic zone plays a key role in the mixing of river water with shallow groundwater. Hyporheic exchange occurs over a very wide range of spatial and temporal scales and the exchange processes at different scales interact and determine a complex system of nested flow cells. This intricacy results from the multiplicity of spatial scale that characterize landscape and river morphology. In the last years, many processes that regulate the surface-groundwater interactions have been elucidated and a more holistic view of groundwater and surface water has been adopted. However, despite several insights on the mechanisms of hyporheic exchange have been achieved, many important aspects remain to be clarified, i.e. how surface-groundwater interactions influence solute transport, microbial activity and biogeochemical transformations at the scale of entire watersheds. To date a deep knowledge of small-scale processes has been developed but what is lacking is a unifying overview of the role of surface water-groundwater exchange for the health of the whole water system at larger scales, i.e. the scale of the entire basin. In order to better understand the complex multiscale nature of spatial patterns of surface-subsurface exchange, we aim to assess the importance of the individual scales included in the range between watershed scale to stream reach scale. Hence, we study the large-scale subsurface flow field taking into account the surface-groundwater interactions induced by landscape topography from the basin scale to smaller scales ranging from tens of kilometers to tens of meters. The aim of this research is to analyze how individual topographic scales affect the flow field and to understand which ones are the most important and should be focused on. To study the impact of various scales of landscape topography we apply an analytical model that provides an exact solution of the underlying three dimensional groundwater flow and a numerical particle tracking routine that allows to obtain streamlines and residence time distributions from the flow field. Therefore, starting from a previously published mathematical tool we set the goal of investigating the interaction between the scales and clarifying their role. We consider real basin examples and describe subsurface flow at the landscape scale, identifying inflow patterns of groundwater to the river network, in order to obtain, in the near future, results to be used for conserving, managing and restoring of a riverine ecosystem.

Multiple spatial scale analyses provide new clues on patterns and drivers of deep-sea nematode diversity

NASA Astrophysics Data System (ADS)

Danovaro, Roberto; Carugati, Laura; Corinaldesi, Cinzia; Gambi, Cristina; Guilini, Katja; Pusceddu, Antonio; Vanreusel, Ann

2013-08-01

The deep sea is the largest biome of the biosphere. The knowledge of the spatial variability of deep-sea biodiversity is one of the main challenges of marine ecology and evolutionary biology. The choice of the observational spatial scale is assumed to play a key role for understanding processes structuring the deep-sea benthic communities and one of the most typical features of marine biodiversity distribution is the existence of bathymetric gradients. However, the analysis of biodiversity bathymetric gradients and the associated changes in species composition (beta diversity) typically compared large depth ranges (with intervals of 500 to 1000 or even 2000 m depth among sites). To test whether significant changes in alpha and beta diversity occur also at fine-scale bathymetric gradients (i.e., within few hundred-meter depth intervals) the variability of deep-sea nematode biodiversity and assemblage composition along a bathymetric transect (200-1200 m depth) with intervals of 200 m among sampling depths, was investigated. A hierarchical sampling strategy for the analysis of nematode species richness, beta diversity, functional (trophic) diversity, and related environmental variables, was used. The results indicate the lack of significant differences in taxonomic and functional diversity across sampling depths, but the presence of high beta diversity at all spatial scales investigated: between cores collected from the same box corer (on average 56%), among deployments at the same depth (58%), and between all sampling depths (62%). Such high beta diversity is influenced by the presence of small-scale patchiness in the deep sea and is also related to the large number of rare or very rare species (typically accounting for >80% of total species richness). Moreover, the number of ubiquitous nematode species across all sampling depths is quite low (ca. 15%). Multiple regression analyses provide evidence that such patterns could be related to the different availability, composition and size spectra of food particles in the sediments. Additionally, though to a lesser extent, our results indicate, that selective predation can influence the nematode trophic composition. These findings suggest that a multiple scale analysis based on a nested sampling design could significantly improve our knowledge of bathymetric patterns of deep-sea biodiversity and its drivers.

A Hierarchical Analysis of Tree Growth and Environmental Drivers Across Eastern US Temperate Forests

NASA Astrophysics Data System (ADS)

Mantooth, J.; Dietze, M.

2014-12-01

Improving predictions of how forests in the eastern United States will respond to future global change requires a better understanding of the drivers of variability in tree growth rates. Current inventory data lack the temporal resolution to characterize interannual variability, while existing growth records lack the extent required to assess spatial scales of variability. Therefore, we established a network of forest inventory plots across ten sites across the eastern US, and measured growth in adult trees using increment cores. Sites were chosen to maximize climate space explored, while within sites, plots were spread across primary environmental gradients to explore landscape-level variability in growth. Using the annual growth record available from tree cores, we explored the responses of trees to multiple environmental covariates over multiple spatial and temporal scales. We hypothesized that within and across sites growth rates vary among species, and that intraspecific growth rates increase with temperature along a species' range. We also hypothesized that trees show synchrony in growth responses to landscape-scale climatic changes. Initial analyses of growth increments indicate that across sites, trees with intermediate shade tolerance, e.g. Red Oak (Quercus rubra), tend to have the highest growth rates. At the site level, there is evidence for synchrony in response to large-scale climatic events (e.g. prolonged drought and above average temperatures). However, growth responses to climate at the landscape scale have yet to be detected. Our current analysis utilizes hierarchical Bayesian state-space modeling to focus on growth responses of adult trees to environmental covariates at multiple spatial and temporal scales. This predictive model of tree growth currently incorporates observed effects at the individual, plot, site, and landscape scale. Current analysis using this model shows a potential slowing of growth in the past decade for two sites in the northeastern US (Harvard Forest and Bartlett Experimental Forest), however more work is required to determine the robustness of this trend. Finally, these observations are being incorporated into ecosystem models using the Brown Dog informatics tools and the Predictive Ecosystem Analyzer (PEcAn) data assimilation workflow.

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.

Emergence of increased frequency and severity of multiple infections by viruses due to spatial clustering of hosts

NASA Astrophysics Data System (ADS)

Taylor, Bradford P.; Penington, Catherine J.; Weitz, Joshua S.

2016-12-01

Multiple virus particles can infect a target host cell. Such multiple infections (MIs) have significant and varied ecological and evolutionary consequences for both virus and host populations. Yet, the in situ rates and drivers of MIs in virus-microbe systems remain largely unknown. Here, we develop an individual-based model (IBM) of virus-microbe dynamics to probe how spatial interactions drive the frequency and nature of MIs. In our IBMs, we identify increasingly spatially correlated clusters of viruses given sufficient decreases in viral movement. We also identify increasingly spatially correlated clusters of viruses and clusters of hosts given sufficient increases in viral infectivity. The emergence of clusters is associated with an increase in multiply infected hosts as compared to expectations from an analogous mean field model. We also observe long-tails in the distribution of the multiplicity of infection in contrast to mean field expectations that such events are exponentially rare. We show that increases in both the frequency and severity of MIs occur when viruses invade a cluster of uninfected microbes. We contend that population-scale enhancement of MI arises from an aggregate of invasion dynamics over a distribution of microbe cluster sizes. Our work highlights the need to consider spatially explicit interactions as a potentially key driver underlying the ecology and evolution of virus-microbe communities.

Using High Spatial Resolution Satellite Imagery to Map Forest Burn Severity Across Spatial Scales in a Pine Barrens Ecosystem

NASA Technical Reports Server (NTRS)

Meng, Ran; Wu, Jin; Schwager, Kathy L.; Zhao, Feng; Dennison, Philip E.; Cook, Bruce D.; Brewster, Kristen; Green, Timothy M.; Serbin, Shawn P.

2017-01-01

As a primary disturbance agent, fire significantly influences local processes and services of forest ecosystems. Although a variety of remote sensing based approaches have been developed and applied to Landsat mission imagery to infer burn severity at 30 m spatial resolution, forest burn severity have still been seldom assessed at fine spatial scales (less than or equal to 5 m) from very-high-resolution (VHR) data. We assessed a 432 ha forest fire that occurred in April 2012 on Long Island, New York, within the Pine Barrens region, a unique but imperiled fire-dependent ecosystem in the northeastern United States. The mapping of forest burn severity was explored here at fine spatial scales, for the first time using remotely sensed spectral indices and a set of Multiple Endmember Spectral Mixture Analysis (MESMA) fraction images from bi-temporal - pre- and post-fire event - WorldView-2 (WV-2) imagery at 2 m spatial resolution. We first evaluated our approach using 1 m by 1 m validation points at the sub-crown scale per severity class (i.e. unburned, low, moderate, and high severity) from the post-fire 0.10 m color aerial ortho-photos; then, we validated the burn severity mapping of geo-referenced dominant tree crowns (crown scale) and 15 m by 15 m fixed-area plots (inter-crown scale) with the post-fire 0.10 m aerial ortho-photos and measured crown information of twenty forest inventory plots. Our approach can accurately assess forest burn severity at the sub-crown (overall accuracy is 84% with a Kappa value of 0.77), crown (overall accuracy is 82% with a Kappa value of 0.76), and inter-crown scales (89% of the variation in estimated burn severity ratings (i.e. Geo-Composite Burn Index (CBI)). This work highlights that forest burn severity mapping from VHR data can capture heterogeneous fire patterns at fine spatial scales over the large spatial extents. This is important since most ecological processes associated with fire effects vary at the less than 30 m scale and VHR approaches could significantly advance our ability to characterize fire effects on forest ecosystems.

Using high spatial resolution satellite imagery to map forest burn severity across spatial scales in a Pine Barrens ecosystem

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

Meng, Ran; Wu, Jin; Schwager, Kathy L.

As a primary disturbance agent, fire significantly influences local processes and services of forest ecosystems. Although a variety of remote sensing based approaches have been developed and applied to Landsat mission imagery to infer burn severity at 30 m spatial resolution, forest burn severity have still been seldom assessed at fine spatial scales (≤ 5 m) from very-high-resolution (VHR) data. Here we assessed a 432 ha forest fire that occurred in April 2012 on Long Island, New York, within the Pine Barrens region, a unique but imperiled fire-dependent ecosystem in the northeastern United States. The mapping of forest burn severitymore » was explored here at fine spatial scales, for the first time using remotely sensed spectral indices and a set of Multiple Endmember Spectral Mixture Analysis (MESMA) fraction images from bi-temporal — pre- and post-fire event — WorldView-2 (WV-2) imagery at 2 m spatial resolution. We first evaluated our approach using 1 m by 1 m validation points at the sub-crown scale per severity class (i.e. unburned, low, moderate, and high severity) from the post-fire 0.10 m color aerial ortho-photos; then, we validated the burn severity mapping of geo-referenced dominant tree crowns (crown scale) and 15 m by 15 m fixed-area plots (inter-crown scale) with the post-fire 0.10 m aerial ortho-photos and measured crown information of twenty forest inventory plots. Our approach can accurately assess forest burn severity at the sub-crown (overall accuracy is 84% with a Kappa value of 0.77), crown (overall accuracy is 82% with a Kappa value of 0.76), and inter-crown scales (89% of the variation in estimated burn severity ratings (i.e. Geo-Composite Burn Index (CBI)). Lastly, this work highlights that forest burn severity mapping from VHR data can capture heterogeneous fire patterns at fine spatial scales over the large spatial extents. This is important since most ecological processes associated with fire effects vary at the < 30 m scale and VHR approaches could significantly advance our ability to characterize fire effects on forest ecosystems.« less

Using high spatial resolution satellite imagery to map forest burn severity across spatial scales in a Pine Barrens ecosystem

DOE PAGES

Meng, Ran; Wu, Jin; Schwager, Kathy L.; ...

2017-01-21

As a primary disturbance agent, fire significantly influences local processes and services of forest ecosystems. Although a variety of remote sensing based approaches have been developed and applied to Landsat mission imagery to infer burn severity at 30 m spatial resolution, forest burn severity have still been seldom assessed at fine spatial scales (≤ 5 m) from very-high-resolution (VHR) data. Here we assessed a 432 ha forest fire that occurred in April 2012 on Long Island, New York, within the Pine Barrens region, a unique but imperiled fire-dependent ecosystem in the northeastern United States. The mapping of forest burn severitymore » was explored here at fine spatial scales, for the first time using remotely sensed spectral indices and a set of Multiple Endmember Spectral Mixture Analysis (MESMA) fraction images from bi-temporal — pre- and post-fire event — WorldView-2 (WV-2) imagery at 2 m spatial resolution. We first evaluated our approach using 1 m by 1 m validation points at the sub-crown scale per severity class (i.e. unburned, low, moderate, and high severity) from the post-fire 0.10 m color aerial ortho-photos; then, we validated the burn severity mapping of geo-referenced dominant tree crowns (crown scale) and 15 m by 15 m fixed-area plots (inter-crown scale) with the post-fire 0.10 m aerial ortho-photos and measured crown information of twenty forest inventory plots. Our approach can accurately assess forest burn severity at the sub-crown (overall accuracy is 84% with a Kappa value of 0.77), crown (overall accuracy is 82% with a Kappa value of 0.76), and inter-crown scales (89% of the variation in estimated burn severity ratings (i.e. Geo-Composite Burn Index (CBI)). Lastly, this work highlights that forest burn severity mapping from VHR data can capture heterogeneous fire patterns at fine spatial scales over the large spatial extents. This is important since most ecological processes associated with fire effects vary at the < 30 m scale and VHR approaches could significantly advance our ability to characterize fire effects on forest ecosystems.« less

Scaling biodiversity responses to hydrological regimes.

PubMed

Rolls, Robert J; Heino, Jani; Ryder, Darren S; Chessman, Bruce C; Growns, Ivor O; Thompson, Ross M; Gido, Keith B

2018-05-01

Of all ecosystems, freshwaters support the most dynamic and highly concentrated biodiversity on Earth. These attributes of freshwater biodiversity along with increasing demand for water mean that these systems serve as significant models to understand drivers of global biodiversity change. Freshwater biodiversity changes are often attributed to hydrological alteration by water-resource development and climate change owing to the role of the hydrological regime of rivers, wetlands and floodplains affecting patterns of biodiversity. However, a major gap remains in conceptualising how the hydrological regime determines patterns in biodiversity's multiple spatial components and facets (taxonomic, functional and phylogenetic). We synthesised primary evidence of freshwater biodiversity responses to natural hydrological regimes to determine how distinct ecohydrological mechanisms affect freshwater biodiversity at local, landscape and regional spatial scales. Hydrological connectivity influences local and landscape biodiversity, yet responses vary depending on spatial scale. Biodiversity at local scales is generally positively associated with increasing connectivity whereas landscape-scale biodiversity is greater with increasing fragmentation among locations. The effects of hydrological disturbance on freshwater biodiversity are variable at separate spatial scales and depend on disturbance frequency and history and organism characteristics. The role of hydrology in determining habitat for freshwater biodiversity also depends on spatial scaling. At local scales, persistence, stability and size of habitat each contribute to patterns of freshwater biodiversity yet the responses are variable across the organism groups that constitute overall freshwater biodiversity. We present a conceptual model to unite the effects of different ecohydrological mechanisms on freshwater biodiversity across spatial scales, and develop four principles for applying a multi-scaled understanding of freshwater biodiversity responses to hydrological regimes. The protection and restoration of freshwater biodiversity is both a fundamental justification and a central goal of environmental water allocation worldwide. Clearer integration of concepts of spatial scaling in the context of understanding impacts of hydrological regimes on biodiversity will increase uptake of evidence into environmental flow implementation, identify suitable biodiversity targets responsive to hydrological change or restoration, and identify and manage risks of environmental flows contributing to biodiversity decline. © 2017 Cambridge Philosophical Society.

Temporal Changes in Forest Contexts at Multiple Extents: Three Decades of Fragmentation in the Gran Chaco (1979-2010), Central Argentina.

PubMed

Frate, Ludovico; Acosta, Alicia T R; Cabido, Marcelo; Hoyos, Laura; Carranza, Maria Laura

2015-01-01

The context in which a forest exists strongly influences its function and sustainability. Unveiling the multi-scale nature of forest fragmentation context is crucial to understand how human activities affect the spatial patterns of forests across a range of scales. However, this issue remains almost unexplored in subtropical ecosystems. In this study, we analyzed temporal changes (1979-2010) in forest contexts in the Argentinean dry Chaco at multiple extents. We classified forests over the last three decades based on forest context amount (Pf) and structural connectivity (Pff), which were measured using a moving window approach fixed at eight different extents (from local, ~ 6 ha, to regional, ~ 8300 ha). Specific multi-scale forest context profiles (for the years 1979 and 2010) were defined by projecting Pf vs. Pff mean values and were compared across spatial extents. The distributions of Pf across scales were described by scalograms and their shapes over time were compared. The amount of agricultural land and rangelands across the scales were also analyzed. The dry Chaco has undergone an intensive process of fragmentation, resulting in a shift from landscapes dominated by forests with gaps of rangelands to landscapes where small forest patches are embedded in agricultural lands. Multi-scale fragmentation analysis depicted landscapes in which local exploitation, which perforates forest cover, occurs alongside extensive forest clearings, reducing forests to small and isolated patches surrounded by agricultural lands. In addition, the temporal diminution of Pf's variability along with the increment of the mean slope of the Pf 's scalograms, indicate a simplification of the spatial pattern of forest over time. The observed changes have most likely been the result of the interplay between human activities and environmental constraints, which have shaped the spatial patterns of forests across scales. Based on our results, strategies for the conservation and sustainable management of the dry Chaco should take into account both the context of each habitat location and the scales over which a forest pattern might be preserved, altered or restored.

Temporal Changes in Forest Contexts at Multiple Extents: Three Decades of Fragmentation in the Gran Chaco (1979-2010), Central Argentina

PubMed Central

Frate, Ludovico; Acosta, Alicia T. R.; Cabido, Marcelo; Hoyos, Laura; Carranza, Maria Laura

2015-01-01

The context in which a forest exists strongly influences its function and sustainability. Unveiling the multi-scale nature of forest fragmentation context is crucial to understand how human activities affect the spatial patterns of forests across a range of scales. However, this issue remains almost unexplored in subtropical ecosystems. In this study, we analyzed temporal changes (1979–2010) in forest contexts in the Argentinean dry Chaco at multiple extents. We classified forests over the last three decades based on forest context amount (P f) and structural connectivity (P ff), which were measured using a moving window approach fixed at eight different extents (from local, ~ 6 ha, to regional, ~ 8300 ha). Specific multi-scale forest context profiles (for the years 1979 and 2010) were defined by projecting P f vs. P ff mean values and were compared across spatial extents. The distributions of P f across scales were described by scalograms and their shapes over time were compared. The amount of agricultural land and rangelands across the scales were also analyzed. The dry Chaco has undergone an intensive process of fragmentation, resulting in a shift from landscapes dominated by forests with gaps of rangelands to landscapes where small forest patches are embedded in agricultural lands. Multi-scale fragmentation analysis depicted landscapes in which local exploitation, which perforates forest cover, occurs alongside extensive forest clearings, reducing forests to small and isolated patches surrounded by agricultural lands. In addition, the temporal diminution of P f’s variability along with the increment of the mean slope of the P f ‘s scalograms, indicate a simplification of the spatial pattern of forest over time. The observed changes have most likely been the result of the interplay between human activities and environmental constraints, which have shaped the spatial patterns of forests across scales. Based on our results, strategies for the conservation and sustainable management of the dry Chaco should take into account both the context of each habitat location and the scales over which a forest pattern might be preserved, altered or restored. PMID:26630387

Spatial, spectral and temporal patterns of tropical forest cover change as observed with multiple scales of optical satellite data.

Treesearch

D.J. Hayes; W.B. Cohen

2006-01-01

This article describes the development of a methodology for scaling observations of changes in tropical forest cover to large areas at high temporal frequency from coarse-resolution satellite imagery. The approach for estimating proportional forest cover change as a continuous variable is based on a regression model that relates multispectral, multitemporal Moderate...

Bird Habitat Conservation at Various Scales in the Atlantic Coast Joint Venture

Treesearch

Andrew Milliken; Craig Watson; Chuck Hayes

2005-01-01

The Atlantic Coast Joint Venture is a partnership focused on the conservation of habitats for migratory birds within the Atlantic Flyway/Atlantic Coast Region from Maine south to Puerto Rico. In order to be effective in planning and implementing conservation in this large and diverse area, the joint venture must work at multiple spatial scales, from the largest ?...

Dynamics of a temperate deciduous forest under landscape-scale management: Implications for adaptability to climate change

Treesearch

Matthew G. Olson; Benjamin O. Knapp; John M. Kabrick

2017-01-01

Landscape forest management is an approach to meeting diverse objectives that collectively span multiple spatial scales. It is critical that we understand the long-term effects of landscape management on the structure and composition of forest tree communities to ensure that these practices are sustainable. Furthermore, it is increasingly important to also consider...

Quantifying nitrous oxide fluxes on multiple spatial scales in the Upper Midwest, USA

USDA-ARS?s Scientific Manuscript database

This study seeks to quantify the roles of soybean and corn plants and the cropland ecosystem in the regional N2O budget of the Upper Midwest, USA. The N2O flux was measured at three scales (plant, the soil-plant ecosystem, and region) using newly designed steady-state flow-through plant chambers, a ...

Fish communities associated with cold-water corals vary with depth and substratum type

NASA Astrophysics Data System (ADS)

Milligan, Rosanna J.; Spence, Gemma; Roberts, J. Murray; Bailey, David M.

2016-08-01

Understanding the processes that drive the distribution patterns of organisms and the scales over which these processes operate are vital when considering the effective management of species with high commercial or conservation value. In the deep sea, the importance of scleractinian cold-water corals (CWCs) to fish has been the focus of several studies but their role remains unclear. We propose this may be due to the confounding effects of multiple drivers operating over multiple spatial scales. The aims of this study were to investigate the role of CWCs in shaping fish community structure and individual species-habitat associations across four spatial scales in the NE Atlantic ranging from "regions" (separated by >500 km) to "substratum types" (contiguous). Demersal fish and substratum types were quantified from three regions: Logachev Mounds, Rockall Bank and Hebrides Terrace Seamount (HTS). PERMANOVA analyses showed significant differences in community composition between all regions which were most likely caused by differences in depths. Within regions, significant variation in community composition was recorded at scales of c. 20-3500 m. CWCs supported significantly different fish communities to non-CWC substrata at Rockall Bank, Logachev and the HTS. Single-species analyses using generalised linear mixed models showed that Sebastes sp. was strongly associated with CWCs at Rockall Bank and that Neocyttus helgae was more likely to occur in CWCs at the HTS. Depth had a significant effect on several other fish species. The results of this study suggest that the importance of CWCs to fish is species-specific and depends on the broader spatial context in which the substratum is found. The precautionary approach would be to assume that CWCs are important for associated fish, but must acknowledge that CWCs in different depths will not provide redundancy or replication within spatially-managed conservation networks.

Quantitative evidence for the effects of multiple drivers on continental-scale amphibian declines

USGS Publications Warehouse

Grant, Evan H. Campbell; Miller, David A. W.; Schmidt, Benedikt R.; Adams, Michael J.; Amburgey, Staci M.; Chambert, Thierry A.; Cruickshank, Sam S.; Fisher, Robert N.; Green, David M.; Hossack, Blake R.; Johnson, Pieter T.J.; Joseph, Maxwell B.; Rittenhouse, Tracy A. G.; Ryan, Maureen E.; Waddle, J. Hardin; Walls, Susan C.; Bailey, Larissa L.; Fellers, Gary M.; Gorman, Thomas A.; Ray, Andrew M.; Pilliod, David S.; Price, Steven J.; Saenz, Daniel; Sadinski, Walt; Muths, Erin L.

2016-01-01

Since amphibian declines were first proposed as a global phenomenon over a quarter century ago, the conservation community has made little progress in halting or reversing these trends. The early search for a “smoking gun” was replaced with the expectation that declines are caused by multiple drivers. While field observations and experiments have identified factors leading to increased local extinction risk, evidence for effects of these drivers is lacking at large spatial scales. Here, we use observations of 389 time-series of 83 species and complexes from 61 study areas across North America to test the effects of 4 of the major hypothesized drivers of declines. While we find that local amphibian populations are being lost from metapopulations at an average rate of 3.79% per year, these declines are not related to any particular threat at the continental scale; likewise the effect of each stressor is variable at regional scales. This result - that exposure to threats varies spatially, and populations vary in their response - provides little generality in the development of conservation strategies. Greater emphasis on local solutions to this globally shared phenomenon is needed.

A Hierarchical and Dynamic Seascape Framework for Scaling and Comparing Ocean Biodiversity Observations

NASA Astrophysics Data System (ADS)

Kavanaugh, M.; Muller-Karger, F. E.; Montes, E.; Santora, J. A.; Chavez, F.; Messié, M.; Doney, S. C.

2016-02-01

The pelagic ocean is a complex system in which physical, chemical and biological processes interact to shape patterns on multiple spatial and temporal scales and levels of ecological organization. Monitoring and management of marine seascapes must consider a hierarchical and dynamic mosaic, where the boundaries, extent, and location of features change with time. As part of a Marine Biodiversity Observing Network demonstration project, we conducted a multiscale classification of dynamic coastal seascapes in the northeastern Pacific and Gulf of Mexico using multivariate satellite and modeled data. Synoptic patterns were validated using mooring and ship-based observations that spanned multiple trophic levels and were collected as part of several long-term monitoring programs, including the Monterey Bay and Florida Keys National Marine Sanctuaries. Seascape extent and habitat diversity varied as a function of both seasonal and interannual forcing. We discuss the patterns of in situ observations in the context of seascape dynamics and the effect on rarefaction, spatial patchiness, and tracking and comparing ecosystems through time. A seascape framework presents an effective means to translate local biodiversity measurements to broader spatiotemporal scales, scales relevant for modeling the effects of global change and enabling whole-ecosystem management in the dynamic ocean.

Variance in composition of inquiline communities in leaves of Sarracenia purpurea L. on multiple spatial scales.

PubMed

Harvey, E; Miller, T E

1996-11-01

A survey of the abundances of species that inhabit the water-bearing leaves of the pitcher plant Sarracenia purpurea was conducted at several different spatial scales in northern Florida. Individual leaves are hosts to communities of inquiline species, including mosquitoes, midges, mites, copepods, cladocerans, and a diverse bacterial assemblage. Inquiline communities were quantified from four pitchers per plant, three plants per subpopulation, two subpopulations per population, and three populations. Species varied in abundance at different spatial scales. Variation in the abundances of mosquitoes and copepods was not significantly associated with any spatial scale. Midges varied in abundance at the level of populations; one population contained significantly more midges than the other two. Cladocerans varied at the level of the subpopulation, whereas mites varied at the level of the individual plants. Bacterial communities were described by means of Biolog plates, which quantify the types of carbon media used by the bacteria in each pitcher. Bacterial communities were found to vary significantly in composition among individual plants but not among populations or subpopulations. These results suggest that independent factors determining the abundances of individual species are important in determining community patterns in pitcher-plant inquilines.

Influence of land use on water quality in a tropical landscape: a multi-scale analysis

PubMed Central

Yackulic, Charles B.; Lim, Yili; Arce-Nazario, Javier A.

2015-01-01

There is a pressing need to understand the consequences of human activities, such as land transformations, on watershed ecosystem services. This is a challenging task because different indicators of water quality and yield are expected to vary in their responsiveness to large versus local-scale heterogeneity in land use and land cover (LUC). Here we rely on water quality data collected between 1977 and 2000 from dozens of gauge stations in Puerto Rico together with precipitation data and land cover maps to (1) quantify impacts of spatial heterogeneity in LUC on several water quality indicators; (2) determine the spatial scale at which this heterogeneity influences water quality; and (3) examine how antecedent precipitation modulates these impacts. Our models explained 30–58% of observed variance in water quality metrics. Temporal variation in antecedent precipitation and changes in LUC between measurements periods rather than spatial variation in LUC accounted for the majority of variation in water quality. Urbanization and pasture development generally degraded water quality while agriculture and secondary forest re-growth had mixed impacts. The spatial scale over which LUC influenced water quality differed across indicators. Turbidity and dissolved oxygen (DO) responded to LUC in large-scale watersheds, in-stream nitrogen concentrations to LUC in riparian buffers of large watersheds, and fecal matter content and in-stream phosphorus concentration to LUC at the sub-watershed scale. Stream discharge modulated impacts of LUC on water quality for most of the metrics. Our findings highlight the importance of considering multiple spatial scales for understanding the impacts of human activities on watershed ecosystem services. PMID:26146455

The spatial scaling of species interaction networks.

PubMed

Galiana, Nuria; Lurgi, Miguel; Claramunt-López, Bernat; Fortin, Marie-Josée; Leroux, Shawn; Cazelles, Kevin; Gravel, Dominique; Montoya, José M

2018-05-01

Species-area relationships (SARs) are pivotal to understand the distribution of biodiversity across spatial scales. We know little, however, about how the network of biotic interactions in which biodiversity is embedded changes with spatial extent. Here we develop a new theoretical framework that enables us to explore how different assembly mechanisms and theoretical models affect multiple properties of ecological networks across space. We present a number of testable predictions on network-area relationships (NARs) for multi-trophic communities. Network structure changes as area increases because of the existence of different SARs across trophic levels, the preferential selection of generalist species at small spatial extents and the effect of dispersal limitation promoting beta-diversity. Developing an understanding of NARs will complement the growing body of knowledge on SARs with potential applications in conservation ecology. Specifically, combined with further empirical evidence, NARs can generate predictions of potential effects on ecological communities of habitat loss and fragmentation in a changing world.

OpenMP parallelization of a gridded SWAT (SWATG)

NASA Astrophysics Data System (ADS)

Zhang, Ying; Hou, Jinliang; Cao, Yongpan; Gu, Juan; Huang, Chunlin

2017-12-01

Large-scale, long-term and high spatial resolution simulation is a common issue in environmental modeling. A Gridded Hydrologic Response Unit (HRU)-based Soil and Water Assessment Tool (SWATG) that integrates grid modeling scheme with different spatial representations also presents such problems. The time-consuming problem affects applications of very high resolution large-scale watershed modeling. The OpenMP (Open Multi-Processing) parallel application interface is integrated with SWATG (called SWATGP) to accelerate grid modeling based on the HRU level. Such parallel implementation takes better advantage of the computational power of a shared memory computer system. We conducted two experiments at multiple temporal and spatial scales of hydrological modeling using SWATG and SWATGP on a high-end server. At 500-m resolution, SWATGP was found to be up to nine times faster than SWATG in modeling over a roughly 2000 km2 watershed with 1 CPU and a 15 thread configuration. The study results demonstrate that parallel models save considerable time relative to traditional sequential simulation runs. Parallel computations of environmental models are beneficial for model applications, especially at large spatial and temporal scales and at high resolutions. The proposed SWATGP model is thus a promising tool for large-scale and high-resolution water resources research and management in addition to offering data fusion and model coupling ability.

Integrating hydrologic and geophysical data to constrain coastal surficial aquifer processes at multiple spatial and temporal scales

USGS Publications Warehouse

Schultz, Gregory M.; Ruppel, Carolyn; Fulton, Patrick; Hyndman, David W.; Day-Lewis, Frederick D.; Singha, Kamini

2007-01-01

Since 1997, repeated, coincident geophysical surveys and extensive hydrologic studies in shallow monitoring wells have been used to study static and dynamic processes associated with surface water-groundwater interaction at a range of spatial scales at the estuarine and ocean boundaries of an undeveloped, permeable barrier island in the Georgia part of the U.S. South Atlantic Bight. Because geophysical and hydrologic data measure different parameters, at different resolution and precision, and over vastly different spatial scales, reconciling the coincident data or even combining complementary inversion, hydrogeochemcial analyses and well-based groundwater monitoring, and, in some cases, limited vegetation mapping to demonstrate the utility of an integrative, multidisciplinary approach for elucidating groundwater processes at spatial scales (tens to thousands of meters) that are often difficult to capture with traditional hydrologic approaches. The case studies highlight regional aquifer characteristics, varying degrees of lateral saltwater intrusion at estuarine boundaries, complex subsurface salinity gradients at the ocean boundary, and imaging of submarsh groundwater discharge and possible free convection in the pore waters of a clastic marsh. This study also documents the use of geophysical techniques for detecting temporal changes in groundwater salinity regimes under natural (not forced) gradients at intratidal to interannual (1998-200 Southeastern U.S.A. drought) time scales.

Evaluating the status of individuals and populations: Advantages of multiple approaches and time scales: Chapter 6

USGS Publications Warehouse

Monson, Daniel H.; Bowen, Lizabeth

2015-01-01

Overall, a variety of indices used to measure population status throughout the sea otter’s range have provided insights for understanding the mechanisms driving the trajectory of various sea otter populations, which a single index could not, and we suggest using multiple methods to measure a population’s status at multiple spatial and temporal scales. The work described here also illustrates the usefulness of long-term data sets and/or approaches that can be used to assess population status retrospectively, providing information otherwise not available. While not all systems will be as amenable to using all the approaches presented here, we expect innovative researchers could adapt analogous multi-scale methods to a broad range of habitats and species including apex predators occupying the top trophic levels, which are often of conservation concern.

A perturbation analysis of a mechanical model for stable spatial patterning in embryology

NASA Astrophysics Data System (ADS)

Bentil, D. E.; Murray, J. D.

1992-12-01

We investigate a mechanical cell-traction mechanism that generates stationary spatial patterns. A linear analysis highlights the model's potential for these heterogeneous solutions. We use multiple-scale perturbation techniques to study the evolution of these solutions and compare our solutions with numerical simulations of the model system. We discuss some potential biological applications among which are the formation of ridge patterns, dermatoglyphs, and wound healing.

Landscape-scale spatial patterns of winter injury to red spruce foliage in a year of heavy region-wide injury

Treesearch

Brynne E. Lazarus; Paul G. Schaberg; Gary J. Hawley; Donald H. DeHayes

2006-01-01

Red spruce (Picea rubens Sarg.) winter injury is caused by freezing damage that results in the abscission of the most recent foliar age-class. Injury was widespread and severe in the northeastern United States in 2003 and was assessed at multiple elevations at 23 sites in Vermont and adjacent states. This paper presents a spatial analysis of these...

Integrated Modeling for Environmental Assessment of Ecosystem Services

EPA Science Inventory

The U.S. Environmental Protection Agency uses environmental models to inform rulemaking and policy decisions at multiple spatial and temporal scales. In this study, several sophisticated modeling technologies are seamlessly integrated to facilitate a baseline assessment of the re...

Understanding the Patterns and Drivers of Air Pollution on Multiple Time Scales: The Case of Northern China.

PubMed

Liu, Yupeng; Wu, Jianguo; Yu, Deyong; Hao, Ruifang

2018-06-01

China's rapid economic growth during the past three decades has resulted in a number of environmental problems, including the deterioration of air quality. It is necessary to better understand how the spatial pattern of air pollutants varies with time scales and what drive these changes. To address these questions, this study focused on one of the most heavily air-polluted areas in North China. We first quantified the spatial pattern of air pollution, and then systematically examined the relationships of air pollution to several socioeconomic and climatic factors using the constraint line method, correlation analysis, and stepwise regression on decadal, annual, and seasonal scales. Our results indicate that PM 2.5 was the dominant air pollutant in the Beijing-Tianjin-Hebei region, while PM 2.5 and PM 10 were both important pollutants in the Agro-pastoral Transitional Zone (APTZ) region. Our statistical analyses suggest that energy consumption and gross domestic product (GDP) in the industry were the most important factors for air pollution on the decadal scale, but the impacts of climatic factors could also be significant. On the annual and seasonal scales, high wind speed, low relative humidity, and long sunshine duration constrained PM 2.5 accumulation; low wind speed and high relative humidity constrained PM 10 accumulation; and short sunshine duration and high wind speed constrained O 3 accumulation. Our study showed that analyses on multiple temporal scales are not only necessary to determine key drivers of air pollution, but also insightful for understanding the spatial patterns of air pollution, which was important for urban planning and air pollution control.

Indicators of biodiversity and ecosystem services: A synthesis across ecosystems and spatial scales

USGS Publications Warehouse

Feld, C.K.; Da Silva, P.M.; Sousa, J.P.; De Bello, F.; Bugter, R.; Grandin, U.; Hering, D.; Lavorel, S.; Mountford, O.; Pardo, I.; Partel, M.; Rombke, J.; Sandin, Leonard; Jones, K. Bruce; Harrison, P.

2009-01-01

According to the Millennium Ecosystem Assessment, common indicators are needed to monitor the loss of biodiversity and the implications for the sustainable provision of ecosystem services. However, a variety of indicators are already being used resulting in many, mostly incompatible, monitoring systems. In order to synthesise the different indicator approaches and to detect gaps in the development of common indicator systems, we examined 531 indicators that have been reported in 617 peer-reviewed journal articles between 1997 and 2007. Special emphasis was placed on comparing indicators of biodiversity and ecosystem services across ecosystems (forests, grass- and shrublands, wetlands, rivers, lakes, soils and agro-ecosystems) and spatial scales (from patch to global scale). The application of biological indicators was found most often focused on regional and finer spatial scales with few indicators applied across ecosystem types. Abiotic indicators, such as physico-chemical parameters and measures of area and fragmentation, are most frequently used at broader (regional to continental) scales. Despite its multiple dimensions, biodiversity is usually equated with species richness only. The functional, structural and genetic components of biodiversity are poorly addressed despite their potential value across habitats and scales. Ecosystem service indicators are mostly used to estimate regulating and supporting services but generally differ between ecosystem types as they reflect ecosystem-specific services. Despite great effort to develop indicator systems over the past decade, there is still a considerable gap in the widespread use of indicators for many of the multiple components of biodiversity and ecosystem services, and a need to develop common monitoring schemes within and across habitats. Filling these gaps is a prerequisite for linking biodiversity dynamics with ecosystem service delivery and to achieving the goals of global and sub-global initiatives to halt the loss of biodiversity. ?? 2009 Oikos.

Understanding the Patterns and Drivers of Air Pollution on Multiple Time Scales: The Case of Northern China

NASA Astrophysics Data System (ADS)

Liu, Yupeng; Wu, Jianguo; Yu, Deyong; Hao, Ruifang

2018-06-01

China's rapid economic growth during the past three decades has resulted in a number of environmental problems, including the deterioration of air quality. It is necessary to better understand how the spatial pattern of air pollutants varies with time scales and what drive these changes. To address these questions, this study focused on one of the most heavily air-polluted areas in North China. We first quantified the spatial pattern of air pollution, and then systematically examined the relationships of air pollution to several socioeconomic and climatic factors using the constraint line method, correlation analysis, and stepwise regression on decadal, annual, and seasonal scales. Our results indicate that PM2.5 was the dominant air pollutant in the Beijing-Tianjin-Hebei region, while PM2.5 and PM10 were both important pollutants in the Agro-pastoral Transitional Zone (APTZ) region. Our statistical analyses suggest that energy consumption and gross domestic product (GDP) in the industry were the most important factors for air pollution on the decadal scale, but the impacts of climatic factors could also be significant. On the annual and seasonal scales, high wind speed, low relative humidity, and long sunshine duration constrained PM2.5 accumulation; low wind speed and high relative humidity constrained PM10 accumulation; and short sunshine duration and high wind speed constrained O3 accumulation. Our study showed that analyses on multiple temporal scales are not only necessary to determine key drivers of air pollution, but also insightful for understanding the spatial patterns of air pollution, which was important for urban planning and air pollution control.

Seasonal variability shapes resilience of small-scale fisheries in Baja California Sur, Mexico.

PubMed

Pellowe, Kara E; Leslie, Heather M

2017-01-01

Small-scale fisheries are an important source of food and livelihoods to coastal communities around the world. Understanding the seasonality of fisheries catch and composition is crucial to fisheries management, particularly in the context of changing environmental and socioeconomic conditions. While seasonal variability directly impacts the lives of fishers, most fisheries studies focus on longer-term change. Here we examine seasonal variability in the small-scale fisheries of Baja California Sur, Mexico based on 13 years of government fisheries data. We investigate how four fisheries indicators with direct relevance to ecological resilience-magnitude and variance of landed fish biomass, taxon richness and the proportion of top-trophic-level taxa in total catch-vary within and among years and at multiple spatial scales. We find that these resilience indicators vary both seasonally and spatially. These results highlight the value of finer-scale monitoring and management, particularly for data-poor fisheries.

Seasonal variability shapes resilience of small-scale fisheries in Baja California Sur, Mexico

PubMed Central

Leslie, Heather M.

2017-01-01

Small-scale fisheries are an important source of food and livelihoods to coastal communities around the world. Understanding the seasonality of fisheries catch and composition is crucial to fisheries management, particularly in the context of changing environmental and socioeconomic conditions. While seasonal variability directly impacts the lives of fishers, most fisheries studies focus on longer-term change. Here we examine seasonal variability in the small-scale fisheries of Baja California Sur, Mexico based on 13 years of government fisheries data. We investigate how four fisheries indicators with direct relevance to ecological resilience–magnitude and variance of landed fish biomass, taxon richness and the proportion of top-trophic-level taxa in total catch–vary within and among years and at multiple spatial scales. We find that these resilience indicators vary both seasonally and spatially. These results highlight the value of finer-scale monitoring and management, particularly for data-poor fisheries. PMID:28783740

Homogenization techniques for population dynamics in strongly heterogeneous landscapes.

PubMed

Yurk, Brian P; Cobbold, Christina A

2018-12-01

An important problem in spatial ecology is to understand how population-scale patterns emerge from individual-level birth, death, and movement processes. These processes, which depend on local landscape characteristics, vary spatially and may exhibit sharp transitions through behavioural responses to habitat edges, leading to discontinuous population densities. Such systems can be modelled using reaction-diffusion equations with interface conditions that capture local behaviour at patch boundaries. In this work we develop a novel homogenization technique to approximate the large-scale dynamics of the system. We illustrate our approach, which also generalizes to multiple species, with an example of logistic growth within a periodic environment. We find that population persistence and the large-scale population carrying capacity is influenced by patch residence times that depend on patch preference, as well as movement rates in adjacent patches. The forms of the homogenized coefficients yield key theoretical insights into how large-scale dynamics arise from the small-scale features.

Change detection using vegetation indices and multiplatform satellite imagery at multiple temporal and spatial scales

USGS Publications Warehouse

Glenn, Edward P.; Nagler, Pamela L.; Huete, Alfredo R.; Weng, Qihao

2014-01-01

This chapter describes emerging methods for using satellite imagery across temporal and spatial scales using a case study approach to illustrate some of the opportunities now available for combining observations across scales. It explores the use of multiplatform sensor systems to characterize ecological change, as exemplified by efforts to scale the effects of a biocontrol insect (the leaf beetle Diorhabda carinulata) on the phenology and water use of Tamarix shrubs (Tamarix ramosissima and related species and hybrids) targeted for removal on western U.S. rivers, from the level of individual leaves to the regional level of measurement. Finally, the chapter summarizes the lessons learned and emphasize the need for ground data to calibrate and validate remote sensing data and the types of errors inherent in scaling point data over wide areas, illustrated with research on evapotranspiration (ET) of Tamarix using a wide range of ground measurement and remote sensing methods.

Spatial aspects of building and population exposure data and their implications for global earthquake exposure modeling

USGS Publications Warehouse

Dell’Acqua, F.; Gamba, P.; Jaiswal, K.

2012-01-01

This paper discusses spatial aspects of the global exposure dataset and mapping needs for earthquake risk assessment. We discuss this in the context of development of a Global Exposure Database for the Global Earthquake Model (GED4GEM), which requires compilation of a multi-scale inventory of assets at risk, for example, buildings, populations, and economic exposure. After defining the relevant spatial and geographic scales of interest, different procedures are proposed to disaggregate coarse-resolution data, to map them, and if necessary to infer missing data by using proxies. We discuss the advantages and limitations of these methodologies and detail the potentials of utilizing remote-sensing data. The latter is used especially to homogenize an existing coarser dataset and, where possible, replace it with detailed information extracted from remote sensing using the built-up indicators for different environments. Present research shows that the spatial aspects of earthquake risk computation are tightly connected with the availability of datasets of the resolution necessary for producing sufficiently detailed exposure. The global exposure database designed by the GED4GEM project is able to manage datasets and queries of multiple spatial scales.

Training Systems Modelers through the Development of a Multi-scale Chagas Disease Risk Model

NASA Astrophysics Data System (ADS)

Hanley, J.; Stevens-Goodnight, S.; Kulkarni, S.; Bustamante, D.; Fytilis, N.; Goff, P.; Monroy, C.; Morrissey, L. A.; Orantes, L.; Stevens, L.; Dorn, P.; Lucero, D.; Rios, J.; Rizzo, D. M.

2012-12-01

The goal of our NSF-sponsored Division of Behavioral and Cognitive Sciences grant is to create a multidisciplinary approach to develop spatially explicit models of vector-borne disease risk using Chagas disease as our model. Chagas disease is a parasitic disease endemic to Latin America that afflicts an estimated 10 million people. The causative agent (Trypanosoma cruzi) is most commonly transmitted to humans by blood feeding triatomine insect vectors. Our objectives are: (1) advance knowledge on the multiple interacting factors affecting the transmission of Chagas disease, and (2) provide next generation genomic and spatial analysis tools applicable to the study of other vector-borne diseases worldwide. This funding is a collaborative effort between the RSENR (UVM), the School of Engineering (UVM), the Department of Biology (UVM), the Department of Biological Sciences (Loyola (New Orleans)) and the Laboratory of Applied Entomology and Parasitology (Universidad de San Carlos). Throughout this five-year study, multi-educational groups (i.e., high school, undergraduate, graduate, and postdoctoral) will be trained in systems modeling. This systems approach challenges students to incorporate environmental, social, and economic as well as technical aspects and enables modelers to simulate and visualize topics that would either be too expensive, complex or difficult to study directly (Yasar and Landau 2003). We launch this research by developing a set of multi-scale, epidemiological models of Chagas disease risk using STELLA® software v.9.1.3 (isee systems, inc., Lebanon, NH). We use this particular system dynamics software as a starting point because of its simple graphical user interface (e.g., behavior-over-time graphs, stock/flow diagrams, and causal loops). To date, high school and undergraduate students have created a set of multi-scale (i.e., homestead, village, and regional) disease models. Modeling the system at multiple spatial scales forces recognition that the system's structure generates its behavior; and STELLA®'s graphical interface allows researchers at multiple educational levels to observe patterns and trends as the system changes over time. Graduate students and postdoctoral researchers will utilize these initial models to more efficiently communicate and transfer knowledge across disciplines prior to generating more novel and complex disease risk models. The hope is that these models will improve causal viewpoints, understanding of the system patterns, and how to best mitigate disease risk across multiple spatial scales. Yasar O, Landau RH (2003) Elements of computational science and engineering education. Siam Review 45(4): 787-805.

Downscaling SMAP Soil Moisture Using Geoinformation Data and Geostatistics

NASA Astrophysics Data System (ADS)

Xu, Y.; Wang, L.

2017-12-01

Soil moisture is important for agricultural and hydrological studies. However, ground truth soil moisture data for wide area is difficult to achieve. Microwave remote sensing such as Soil Moisture Active Passive (SMAP) can offer a solution for wide coverage. However, existing global soil moisture products only provide observations at coarse spatial resolutions, which often limit their applications in regional agricultural and hydrological studies. This paper therefore aims to generate fine scale soil moisture information and extend soil moisture spatial availability. A statistical downscaling scheme is presented that incorporates multiple fine scale geoinformation data into the downscaling of coarse scale SMAP data in the absence of ground measurement data. Geoinformation data related to soil moisture patterns including digital elevation model (DEM), land surface temperature (LST), land use and normalized difference vegetation index (NDVI) at a fine scale are used as auxiliary environmental variables for downscaling SMAP data. Generalized additive model (GAM) and regression tree are first conducted to derive statistical relationships between SMAP data and auxiliary geoinformation data at an original coarse scale, and residuals are then downscaled to a finer scale via area-to-point kriging (ATPK) by accounting for the spatial correlation information of the input residuals. The results from standard validation scores as well as the triple collocation (TC) method against soil moisture in-situ measurements show that the downscaling method can significantly improve the spatial details of SMAP soil moisture while maintain the accuracy.

A Multi-Scale Distribution Model for Non-Equilibrium Populations Suggests Resource Limitation in an Endangered Rodent

PubMed Central

Bean, William T.; Stafford, Robert; Butterfield, H. Scott; Brashares, Justin S.

2014-01-01

Species distributions are known to be limited by biotic and abiotic factors at multiple temporal and spatial scales. Species distribution models, however, frequently assume a population at equilibrium in both time and space. Studies of habitat selection have repeatedly shown the difficulty of estimating resource selection if the scale or extent of analysis is incorrect. Here, we present a multi-step approach to estimate the realized and potential distribution of the endangered giant kangaroo rat. First, we estimate the potential distribution by modeling suitability at a range-wide scale using static bioclimatic variables. We then examine annual changes in extent at a population-level. We define “available” habitat based on the total suitable potential distribution at the range-wide scale. Then, within the available habitat, model changes in population extent driven by multiple measures of resource availability. By modeling distributions for a population with robust estimates of population extent through time, and ecologically relevant predictor variables, we improved the predictive ability of SDMs, as well as revealed an unanticipated relationship between population extent and precipitation at multiple scales. At a range-wide scale, the best model indicated the giant kangaroo rat was limited to areas that received little to no precipitation in the summer months. In contrast, the best model for shorter time scales showed a positive relation with resource abundance, driven by precipitation, in the current and previous year. These results suggest that the distribution of the giant kangaroo rat was limited to the wettest parts of the drier areas within the study region. This multi-step approach reinforces the differing relationship species may have with environmental variables at different scales, provides a novel method for defining “available” habitat in habitat selection studies, and suggests a way to create distribution models at spatial and temporal scales relevant to theoretical and applied ecologists. PMID:25237807

Spatial and temporal aspects of chromatic adaptation and their functional significance for colour constancy.

PubMed

Werner, Annette

2014-11-01

Illumination in natural scenes changes at multiple temporal and spatial scales: slow changes in global illumination occur in the course of a day, and we encounter fast and localised illumination changes when visually exploring the non-uniform light field of three-dimensional scenes; in addition, very long-term chromatic variations may come from the environment, like for example seasonal changes. In this context, I consider the temporal and spatial properties of chromatic adaptation and discuss their functional significance for colour constancy in three-dimensional scenes. A process of fast spatial tuning in chromatic adaptation is proposed as a possible sensory mechanism for linking colour constancy to the spatial structure of a scene. The observed middlewavelength selectivity of this process is particularly suitable for adaptation to the mean chromaticity and the compensation of interreflections in natural scenes. Two types of sensory colour constancy are distinguished, based on the functional differences of their temporal and spatial scales: a slow type, operating at a global scale for the compensation of the ambient illumination; and a fast colour constancy, which is locally restricted and well suited to compensate region-specific variations in the light field of three dimensional scenes. Copyright © 2014 Elsevier B.V. All rights reserved.

Conspecific and Heterospecific Plant Densities at Small-Scale Can Drive Plant-Pollinator Interactions

PubMed Central

Janovský, Zdeněk; Mikát, Michael; Hadrava, Jiří; Horčičková, Eva; Kmecová, Kateřina; Požárová, Doubravka; Smyčka, Jan; Herben, Tomáš

2013-01-01

Generalist pollinators are important in many habitats, but little research has been done on small-scale spatial variation in interactions between them and the plants that they visit. Here, using a spatially explicit approach, we examined whether multiple species of flowering plants occurring within a single meadow showed spatial structure in their generalist pollinator assemblages. We report the results for eight plant species for which at least 200 individual visits were recorded. We found that for all of these species, the proportions of their general pollinator assemblages accounted for by particular functional groups showed spatial heterogeneity at the scale of tens of metres. This heterogeneity was connected either with no or only subtle changes of vegetation and flowering species composition. In five of these species, differences in conspecific plant density influenced the pollinator communities (with greater dominance of main pollinators at low-conspecific plant densities). The density of heterospecific plant individuals influenced the pollinator spectrum in one case. Our results indicate that the picture of plant-pollinator interactions provided by averaging data within large plots may be misleading and that within-site spatial heterogeneity should be accounted for in terms of sampling effort allocation and analysis. Moreover, spatially structured plant-pollinator interactions may have important ecological and evolutionary consequences, especially for plant population biology. PMID:24204818

Formation of proto-multiple systems in a magnetized, fragmenting filament

NASA Astrophysics Data System (ADS)

Hull, Charles L. H.

2016-01-01

In just the past few years, it has become clear that filamentary structure is present in the star-formation process across many orders of magnitude in spatial scale, from the galactic scales probed by Planck and Herschel all the way down to the AU-scale structures that ALMA has revealed within protoplanetary disks. A similar story can be told of magnetic fields, which play a role in star formation across the same vast range of size scales. Here I will show filamentary structure near three protostars in the Serpens Main star-forming region, as seen with both CARMA (at 1000 AU scales) and ALMA (at 150 AU scales!). Even at such high resolution, these sources have a number of nearby, filamentary blobs/condensations/companions, which may be the beginnings of multiple star systems. Additionally, the filamentary structures along which these companions lie coincide in a tantalizing way with the magnetic fields we mapped with CARMA.

Evaluation of spatial models to predict vulnerability of forest birds to brood parasitism by cowbirds

USGS Publications Warehouse

Gustafson, E.J.; Knutson, M.G.; Niemi, G.J.; Friberg, M.

2002-01-01

We constructed alternative spatial models at two scales to predict Brown-headed Cowbird (Molothrus ater) parasitism rates from land cover maps. The local-scale models tested competing hypotheses about the relationship between cowbird parasitism and distance of host nests from a forest edge (forest-nonforest boundary). The landscape models tested competing hypotheses about how landscape features (e.g., forests, agricultural fields) interact to determine rates of cowbird parasitism. The models incorporate spatial neighborhoods with a radius of 2.5 km in their formulation, reflecting the scale of the majority of cowbird commuting activity. Field data on parasitism by cowbirds (parasitism rate and number of cowbird eggs per nest) were collected at 28 sites in the Driftless Area Ecoregion of Wisconsin, Minnesota, and Iowa and were compared to the predictions of the alternative models. At the local scale, there was a significant positive relationship between cowbird parasitism and mean distance of nest sites from the forest edge. At the landscape scale, the best fitting models were the forest-dependent and forest-fragmentation-dependent models, in which more heavily forested and less fragmented landscapes had higher parasitism rates. However, much of the explanatory power of these models results from the inclusion of the local-scale relationship in these models. We found lower rates of cowbird parasitism than did most Midwestern studies, and we identified landscape patterns of cowbird parasitism that are opposite to those reported in several other studies of Midwestern songbirds. We caution that cowbird parasitism patterns can be unpredictable, depending upon ecoregional location and the spatial extent, and that our models should be tested in other ecoregions before they are applied there. Our study confirms that cowbird biology has a strong spatial component, and that improved spatial models applied at multiple spatial scales will be required to predict the effects of landscape and forest management on cowbird parasitism of forest birds.

Variability in results from negative binomial models for Lyme disease measured at different spatial scales.

PubMed

Tran, Phoebe; Waller, Lance

2015-01-01

Lyme disease has been the subject of many studies due to increasing incidence rates year after year and the severe complications that can arise in later stages of the disease. Negative binomial models have been used to model Lyme disease in the past with some success. However, there has been little focus on the reliability and consistency of these models when they are used to study Lyme disease at multiple spatial scales. This study seeks to explore how sensitive/consistent negative binomial models are when they are used to study Lyme disease at different spatial scales (at the regional and sub-regional levels). The study area includes the thirteen states in the Northeastern United States with the highest Lyme disease incidence during the 2002-2006 period. Lyme disease incidence at county level for the period of 2002-2006 was linked with several previously identified key landscape and climatic variables in a negative binomial regression model for the Northeastern region and two smaller sub-regions (the New England sub-region and the Mid-Atlantic sub-region). This study found that negative binomial models, indeed, were sensitive/inconsistent when used at different spatial scales. We discuss various plausible explanations for such behavior of negative binomial models. Further investigation of the inconsistency and sensitivity of negative binomial models when used at different spatial scales is important for not only future Lyme disease studies and Lyme disease risk assessment/management but any study that requires use of this model type in a spatial context. Copyright © 2014 Elsevier Inc. All rights reserved.

Multi-scale connectivity and graph theory highlight critical areas for conservation under climate change

USGS Publications Warehouse

Dilts, Thomas E.; Weisberg, Peter J.; Leitner, Phillip; Matocq, Marjorie D.; Inman, Richard D.; Nussear, Ken E.; Esque, Todd C.

2016-01-01

Conservation planning and biodiversity management require information on landscape connectivity across a range of spatial scales from individual home ranges to large regions. Reduction in landscape connectivity due changes in land-use or development is expected to act synergistically with alterations to habitat mosaic configuration arising from climate change. We illustrate a multi-scale connectivity framework to aid habitat conservation prioritization in the context of changing land use and climate. Our approach, which builds upon the strengths of multiple landscape connectivity methods including graph theory, circuit theory and least-cost path analysis, is here applied to the conservation planning requirements of the Mohave ground squirrel. The distribution of this California threatened species, as for numerous other desert species, overlaps with the proposed placement of several utility-scale renewable energy developments in the American Southwest. Our approach uses information derived at three spatial scales to forecast potential changes in habitat connectivity under various scenarios of energy development and climate change. By disentangling the potential effects of habitat loss and fragmentation across multiple scales, we identify priority conservation areas for both core habitat and critical corridor or stepping stone habitats. This approach is a first step toward applying graph theory to analyze habitat connectivity for species with continuously-distributed habitat, and should be applicable across a broad range of taxa.

Evaluation of an index of biotic integrity approach used to assess biological condition in western U.S. streams and rivers at varying spatial scales

USGS Publications Warehouse

Meador, M.R.; Whittier, T.R.; Goldstein, R.M.; Hughes, R.M.; Peck, D.V.

2008-01-01

Consistent assessments of biological condition are needed across multiple ecoregions to provide a greater understanding of the spatial extent of environmental degradation. However, consistent assessments at large geographic scales are often hampered by lack of uniformity in data collection, analyses, and interpretation. The index of biotic integrity (IBI) has been widely used in eastern and central North America, where fish assemblages are complex and largely composed of native species, but IBI development has been hindered in the western United States because of relatively low fish species richness and greater relative abundance of alien fishes. Approaches to developing IBIs rarely provide a consistent means of assessing biological condition across multiple ecoregions. We conducted an evaluation of IBIs recently proposed for three ecoregions of the western United States using an independent data set covering a large geographic scale. We standardized the regional IBIs and developed biological condition criteria, assessed the responsiveness of IBIs to basin-level land uses, and assessed their precision and concordance with basin-scale IBIs. Standardized IBI scores from 318 sites in the western United States comprising mountain, plains, and xeric ecoregions were significantly related to combined urban and agricultural land uses. Standard deviations and coefficients of variation revealed relatively low variation in IBI scores based on multiple sampling reaches at sites. A relatively high degree of corroboration with independent, locally developed IBIs indicates that the regional IBIs are robust across large geographic scales, providing precise and accurate assessments of biological condition for western U.S. streams. ?? Copyright by the American Fisheries Society 2008.

Separating spatial search and efficiency rates as components of predation risk

PubMed Central

DeCesare, Nicholas J.

2012-01-01

Predation risk is an important driver of ecosystems, and local spatial variation in risk can have population-level consequences by affecting multiple components of the predation process. I use resource selection and proportional hazard time-to-event modelling to assess the spatial drivers of two key components of risk—the search rate (i.e. aggregative response) and predation efficiency rate (i.e. functional response)—imposed by wolves (Canis lupus) in a multi-prey system. In my study area, both components of risk increased according to topographic variation, but anthropogenic features affected only the search rate. Predicted models of the cumulative hazard, or risk of a kill, underlying wolf search paths validated well with broad-scale variation in kill rates, suggesting that spatial hazard models provide a means of scaling up from local heterogeneity in predation risk to population-level dynamics in predator–prey systems. Additionally, I estimated an integrated model of relative spatial predation risk as the product of the search and efficiency rates, combining the distinct contributions of spatial heterogeneity to each component of risk. PMID:22977145

Should Data Frameworks be Inherently Multiscalar? A Use Case of the Living Atlas of the World

NASA Astrophysics Data System (ADS)

Wright, D. J.

2015-12-01

In addition to an individual research project, many researchers are involved in at least one major partnership, perhaps one ocean observatory, or one collaborative. The accompanying data framework may be focused on a subdiscipline of oceanography (i.e., marine geology and geophysics, physical oceanography, marine ecology, etc.) or particular study region. The data framework obviously exists to support research, but also collaboration in data collection, spatial analysis, visualization, and communication of the science to multiple audience. These interactions likely take place at multiple scales: the scale of the individual researcher, of small workgroups within a lab, or of inter-organizational collaboration. There are also frameworks that cut horizontally across discipline and region, connecting to broader national or global initiatives such as NSF EarthCube, other NSF-funded Research Coordination Networks, GEOSS, or ODIP. The Living Atlas of the World is presented as a use case of a data framework seeking to cut effectively across multiple spatial and temporal scales. The Living Atlas was first created in 2014 to make authoritative geographic information accessible via hosted cloud services so that users could more quickly address scientific and societal problems and decisions at spatial scales ranging from a small study area the entire globe, while using a range of interactive map functions to tell engaging narratives along the way (aka "story maps"). What began as a way to build trusted, authoritative, and freely available *basemaps* from data contributed online by the GIS community, has grown to a larger program extending far beyond basemap layers to satellite imagery, bathymetry, water column layers, and hydrology, as well elevation, human population, and 3D web scenes. The Living Atlas is continually under construction with new efforts that now extend beyond just the reading and serving of dataset, to the provisioning of spatial analysis on these *data services* in the cloud, as well as the crosswalking and sharing of workflows and use cases, additional apps for mobile, web, and desktop, community-building events where people gather face-to-face, and close interlinkages to other platforms such as ODIP and NSF EarthCube.

Wave resource variability: Impacts on wave power supply over regional to international scales

NASA Astrophysics Data System (ADS)

Smith, Helen; Fairley, Iain; Robertson, Bryson; Abusara, Mohammad; Masters, Ian

2017-04-01

The intermittent, irregular and variable nature of the wave energy resource has implications for the supply of wave-generated electricity into the grid. Intermittency of renewable power may lead to frequency and voltage fluctuations in the transmission and distribution networks. A matching supply of electricity must be planned to meet the predicted demand, leading to a need for gas-fired and back-up generating plants to supplement intermittent supplies, and potentially limiting the integration of intermittent power into the grid. Issues relating to resource intermittency and their mitigation through the development of spatially separated sites have been widely researched in the wind industry, but have received little attention to date in the less mature wave industry. This study analyses the wave resource over three different spatial scales to investigate the potential impacts of the temporal and spatial resource variability on the grid supply. The primary focus is the Southwest UK, a region already home to multiple existing and proposed wave energy test sites. Concurrent wave buoy data from six locations, supported by SWAN wave model hindcast data, are analysed to assess the correlation of the resource across the region and the variation in wave power with direction. Power matrices for theoretical nearshore and offshore devices are used to calculate the maximum step change in generated power across the region as the number of deployment sites is increased. The step change analysis is also applied across national and international spatial scales using output from the European Centre for Medium-range Weather Forecasting (ECMWF) ERA-Interim hindcast model. It is found that the deployment of multiple wave energy sites, whether on a regional, national or international scale, results in both a reduction in step changes in power and reduced times of zero generation, leading to an overall smoothing of the wave-generated electrical power. This has implications for the planning and siting of future wave energy arrays when the industry reaches the point of large-scale deployment.

Linking Resilience of Aquatic Species to Watershed Condition

NASA Astrophysics Data System (ADS)

Flitcroft, R. L.

2017-12-01

Watershed condition means different things to different people. From the perspective of aquatic ecology, watershed condition may be interpreted to mean the capacity of a watershed to support life history diversity of native species. Diversity in expression of life history is thought to confer resilience allowing portions of the broader population to survive stressful conditions. Different species have different life history strategies, many of which were developed through adaptation to regional or local environmental conditions and natural disturbance regimes. By reviewing adaptation strategies for species of interest at regional scales, characteristics of watersheds that confer resilience may be determined. Such assessments must be completed at multiple levels of spatial organization (i.e. sub-watershed, watershed, region) allowing assessments to be inferred across broad spatial extents. In a project on the Wenatchee River watershed, we guided models of wildfire effects on bull trout and spring Chinook from a meta-population perspective to determine risks to survival at local and population scales over multiple extents of spatial organization. In other work in the Oregon Coast Range, we found that historic landslides continue to exert habitat-forming pressure at local scales, leading to patchiness in distribution of habitats for different life stages of coho salmon. Further, climate change work in Oregon estuaries identified different vulnerabilities in terms of juvenile rearing habitat depending on the species of interest and the intensity of future changes in climate. All of these studies point to the importance of considering physical conditions in watersheds at multiple spatial extents from the perspective of native aquatic species in order to understand risks to long-term survival. The broader implications of watershed condition, from this perspective, is the determination of physical attributes that confer resilience to native biota. This may require regionally specific metrics, and across-species synthesis of survival strategies and environmental conditions that confer resilience.

How Many Grid Points are Required for Time Accurate Simulations Scheme Selection and Scale-Discriminant Stabilization

DTIC Science & Technology

2015-11-24

spatial concerns: ¤ how well are gradients captured? (resolution requirement) spatial/temporal concerns: ¤ dispersion and dissipation error...distribution is unlimited. Gradient Capture vs. Resolution: Single Mode FFT: Solution/Derivative: Convergence: f x( )= sin(x) with x∈[0,2π ] df dx...distribution is unlimited. Gradient Capture vs. Resolution: 
 Multiple Modes FFT: Solution/Derivative: Convergence: 6 __ CD02 __ CD04 __ CD06

Habitat models to predict wetland bird occupancy influenced by scale, anthropogenic disturbance, and imperfect detection

USGS Publications Warehouse

Glisson, Wesley J.; Conway, Courtney J.; Nadeau, Christopher P.; Borgmann, Kathi L.

2017-01-01

Understanding species–habitat relationships for endangered species is critical for their conservation. However, many studies have limited value for conservation because they fail to account for habitat associations at multiple spatial scales, anthropogenic variables, and imperfect detection. We addressed these three limitations by developing models for an endangered wetland bird, Yuma Ridgway's rail (Rallus obsoletus yumanensis), that examined how the spatial scale of environmental variables, inclusion of anthropogenic disturbance variables, and accounting for imperfect detection in validation data influenced model performance. These models identified associations between environmental variables and occupancy. We used bird survey and spatial environmental data at 2473 locations throughout the species' U.S. range to create and validate occupancy models and produce predictive maps of occupancy. We compared habitat-based models at three spatial scales (100, 224, and 500 m radii buffers) with and without anthropogenic disturbance variables using validation data adjusted for imperfect detection and an unadjusted validation dataset that ignored imperfect detection. The inclusion of anthropogenic disturbance variables improved the performance of habitat models at all three spatial scales, and the 224-m-scale model performed best. All models exhibited greater predictive ability when imperfect detection was incorporated into validation data. Yuma Ridgway's rail occupancy was negatively associated with ephemeral and slow-moving riverine features and high-intensity anthropogenic development, and positively associated with emergent vegetation, agriculture, and low-intensity development. Our modeling approach accounts for common limitations in modeling species–habitat relationships and creating predictive maps of occupancy probability and, therefore, provides a useful framework for other species.

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

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

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

Individual species affect plant traits structure in their surroundings: evidence of functional mechanisms of assembly.

PubMed

Chacón-Labella, Julia; de la Cruz, Marcelino; Pescador, David S; Escudero, Adrián

2016-04-01

Evaluating community assembly through the use of functional traits is a promising tool for testing predictions arising from Niche and Coexistence theories. Although interactions among neighboring species and their inter-specific differences are known drivers of coexistence with a strong spatial signal, assessing the role of individual species on the functional structure of the community at different spatial scales remains a challenge. Here, we ask whether individual species exert a measurable effect on the spatial organization of different functional traits in local assemblages. We first propose and compute two functions that describe different aspects of functional trait organization around individual species at multiple scales: individual weighted mean area relationship and individual functional diversity area relationship. Secondly, we develop a conceptual model on the relationship and simultaneous variation of these two metrics, providing five alternative scenarios in response to the ability of some target species to modify its neighbor environment and the possible assembly mechanisms involved. Our results show that some species influence the spatial structure of specific functional traits, but their effects were always restricted to the finest spatial scales. In the basis of our conceptual model, the observed patterns point to two main mechanisms driving the functional structure of the community at the fine scale, "biotic" filtering meditated by individual species and resource partitioning driven by indirect facilitation rather than by competitive mechanisms.

Managing data from multiple disciplines, scales, and sites to support synthesis and modeling

USGS Publications Warehouse

Olson, R. J.; Briggs, J. M.; Porter, J.H.; Mah, Grant R.; Stafford, S.G.

1999-01-01

The synthesis and modeling of ecological processes at multiple spatial and temporal scales involves bringing together and sharing data from numerous sources. This article describes a data and information system model that facilitates assembling, managing, and sharing diverse data from multiple disciplines, scales, and sites to support integrated ecological studies. Cross-site scientific-domain working groups coordinate the development of data associated with their particular scientific working group, including decisions about data requirements, data to be compiled, data formats, derived data products, and schedules across the sites. The Web-based data and information system consists of nodes for each working group plus a central node that provides data access, project information, data query, and other functionality. The approach incorporates scientists and computer experts in the working groups and provides incentives for individuals to submit documented data to the data and information system.

Abundant Topological Outliers in Social Media Data and Their Effect on Spatial Analysis.

PubMed

Westerholt, Rene; Steiger, Enrico; Resch, Bernd; Zipf, Alexander

2016-01-01

Twitter and related social media feeds have become valuable data sources to many fields of research. Numerous researchers have thereby used social media posts for spatial analysis, since many of them contain explicit geographic locations. However, despite its widespread use within applied research, a thorough understanding of the underlying spatial characteristics of these data is still lacking. In this paper, we investigate how topological outliers influence the outcomes of spatial analyses of social media data. These outliers appear when different users contribute heterogeneous information about different phenomena simultaneously from similar locations. As a consequence, various messages representing different spatial phenomena are captured closely to each other, and are at risk to be falsely related in a spatial analysis. Our results reveal indications for corresponding spurious effects when analyzing Twitter data. Further, we show how the outliers distort the range of outcomes of spatial analysis methods. This has significant influence on the power of spatial inferential techniques, and, more generally, on the validity and interpretability of spatial analysis results. We further investigate how the issues caused by topological outliers are composed in detail. We unveil that multiple disturbing effects are acting simultaneously and that these are related to the geographic scales of the involved overlapping patterns. Our results show that at some scale configurations, the disturbances added through overlap are more severe than at others. Further, their behavior turns into a volatile and almost chaotic fluctuation when the scales of the involved patterns become too different. Overall, our results highlight the critical importance of thoroughly considering the specific characteristics of social media data when analyzing them spatially.

LAPSUS: soil erosion - landscape evolution model

NASA Astrophysics Data System (ADS)

van Gorp, Wouter; Temme, Arnaud; Schoorl, Jeroen

2015-04-01

LAPSUS is a soil erosion - landscape evolution model which is capable of simulating landscape evolution of a gridded DEM by using multiple water, mass movement and human driven processes on multiple temporal and spatial scales. It is able to deal with a variety of human landscape interventions such as landuse management and tillage and it can model their interactions with natural processes. The complex spatially explicit feedbacks the model simulates demonstrate the importance of spatial interaction of human activity and erosion deposition patterns. In addition LAPSUS can model shallow landsliding, slope collapse, creep, solifluction, biological and frost weathering, fluvial behaviour. Furthermore, an algorithm to deal with natural depressions has been added and event-based modelling with an improved infiltration description and dust deposition has been pursued. LAPSUS has been used for case studies in many parts of the world and is continuously developing and expanding. it is now available for third-party and educational use. It has a comprehensive user interface and it is accompanied by a manual and exercises. The LAPSUS model is highly suitable to quantify and understand catchment-scale erosion processes. More information and a download link is available on www.lapsusmodel.nl.

Describing a multitrophic plant-herbivore-parasitoid system at four spatial scales

NASA Astrophysics Data System (ADS)

Cuautle, M.; Parra-Tabla, V.

2014-02-01

Herbivore-parasitoid interactions must be studied using a multitrophic and multispecies approach. The strength and direction of multiple effects through trophic levels may change across spatial scales. In this work, we use the herbaceous plant Ruellia nudiflora, its moth herbivore Tripudia quadrifera, and several parasitoid morphospecies that feed on the herbivore to answer the following questions: Do herbivore and parasitoid attack levels vary depending on the spatial scale considered? With which plant characteristics are the parasitoid and the herbivore associated? Do parasitoid morphospecies vary in the magnitude of their positive indirect effect on plant reproduction? We evaluated three approximations of herbivore and parasitoid abundance (raw numbers, ratios, and attack rates) at four spatial scales: regional (three different regions which differ in terms of abiotic and biotic characteristics); population (i.e. four populations within each region); patch (four 1 m2 plots in each population); and plant level (using a number of plant characteristics). Finally, we determined whether parasitoids have a positive indirect effect on plant reproductive success (seed number). Herbivore and parasitoid numbers differed at three of the spatial scales considered. However, herbivore/fruit ratio and attack rates did not differ at the population level. Parasitoid/host ratio and attack rates did not differ at any scale, although there was a tendency of a higher attack in one region. At the plant level, herbivore and parasitoid abundances were related to different plant traits, varying the importance and the direction (positive or negative) of those traits. In addition, only one parasitoid species (Bracon sp.) had a positive effect on plant fitness saving up to 20% of the seeds in a fruit. These results underline the importance of knowing the scales that are relevant to organisms at different trophic levels and distinguish between the specific effects of species.

Estimates of reservoir methane emissions based on a spatially ...

EPA Pesticide Factsheets

Global estimates of methane (CH4) emissions from reservoirs are poorly constrained, partly due to the challenges of accounting for intra-reservoir spatial variability. Reservoir-scale emission rates are often estimated by extrapolating from measurement made at a few locations; however, error and bias associated with this approach can be large and difficult to quantify. Here we use a generalized random tessellation survey (GRTS) design to generate estimates of central tendency and variance at multiple spatial scales in a reservoir. GRTS survey designs are probabilistic and spatially balanced which eliminates bias associated with expert judgment in site selection. GRTS surveys also allow for variance estimates that account for spatial pattern in emission rates. Total CH4 emission rates (i.e. sum of ebullition and diffusive emissions) were 4.8 (±2.1), 33.0 (±10.7), and 8.3 (±2.2) mg CH4 m-2 h-1 in open-waters, tributary associated areas, and the entire reservoir for the period in August 2014 during which 115 sites were sampled across an 7.98 km2 reservoir in Southwestern, Ohio, USA. Tributary areas occupy 12% of the reservoir surface, but were the source of 41% of total CH4 emissions, highlighting the importance of riverine-lacustrine transition zones. Ebullition accounted for >90% of CH4 emission at all spatial scales. Confidence interval estimates that incorporated spatial pattern in CH4 emissions were up to 29% narrower than when spatial independence

Moving to stay in place: behavioral mechanisms for coexistence of African large carnivores.

PubMed

Vanak, Abi Tamim; Fortin, Daniel; Thaker, Maria; Ogden, Monika; Owen, Cailey; Greatwood, Sophie; Slotow, Rob

2013-11-01

Most ecosystems have multiple predator species that not only compete for shared prey, but also pose direct threats to each other. These intraguild interactions are key drivers of carnivore community structure, with ecosystem-wide cascading effects. Yet, behavioral mechanisms for coexistence of multiple carnivore species remain poorly understood. The challenges of studying large, free-ranging carnivores have resulted in mainly coarse-scale examination of behavioral strategies without information about all interacting competitors. We overcame some of these challenges by examining the concurrent fine-scale movement decisions of almost all individuals of four large mammalian carnivore species in a closed terrestrial system. We found that the intensity ofintraguild interactions did not follow a simple hierarchical allometric pattern, because spatial and behavioral tactics of subordinate species changed with threat and resource levels across seasons. Lions (Panthera leo) were generally unrestricted and anchored themselves in areas rich in not only their principal prey, but also, during periods of resource limitation (dry season), rich in the main prey for other carnivores. Because of this, the greatest cost (potential intraguild predation) for subordinate carnivores was spatially coupled with the highest potential benefit of resource acquisition (prey-rich areas), especially in the dry season. Leopard (P. pardus) and cheetah (Acinonyx jubatus) overlapped with the home range of lions but minimized their risk using fine-scaled avoidance behaviors and restricted resource acquisition tactics. The cost of intraguild competition was most apparent for cheetahs, especially during the wet season, as areas with energetically rewarding large prey (wildebeest) were avoided when they overlapped highly with the activity areas of lions. Contrary to expectation, the smallest species (African wild dog, Lycaon pictus) did not avoid only lions, but also used multiple tactics to minimize encountering all other competitors. Intraguild competition thus forced wild dogs into areas with the lowest resource availability year round. Coexistence of multiple carnivore species has typically been explained by dietary niche separation, but our multi-scaled movement results suggest that differences in resource acquisition may instead be a consequence of avoiding intraguild competition. We generate a more realistic representation of hierarchical behavioral interactions that may ultimately drive spatially explicit trophic structures of multi-predator communities.

Large-scale conservation planning in a multinational marine environment: cost matters.

PubMed

Mazor, Tessa; Giakoumi, Sylvaine; Kark, Salit; Possingham, Hugh P

2014-07-01

Explicitly including cost in marine conservation planning is essential for achieving feasible and efficient conservation outcomes. Yet, spatial priorities for marine conservation are still often based solely on biodiversity hotspots, species richness, and/or cumulative threat maps. This study aims to provide an approach for including cost when planning large-scale Marine Protected Area (MPA) networks that span multiple countries. Here, we explore the incorporation of cost in the complex setting of the Mediterranean Sea. In order to include cost in conservation prioritization, we developed surrogates that account for revenue from multiple marine sectors: commercial fishing, noncommercial fishing, and aquaculture. Such revenue can translate into an opportunity cost for the implementation of an MPA network. Using the software Marxan, we set conservation targets to protect 10% of the distribution of 77 threatened marine species in the Mediterranean Sea. We compared nine scenarios of opportunity cost by calculating the area and cost required to meet our targets. We further compared our spatial priorities with those that are considered consensus areas by several proposed prioritization schemes in the Mediterranean Sea, none of which explicitly considers cost. We found that for less than 10% of the Sea's area, our conservation targets can be achieved while incurring opportunity costs of less than 1%. In marine systems, we reveal that area is a poor cost surrogate and that the most effective surrogates are those that account for multiple sectors or stakeholders. Furthermore, our results indicate that including cost can greatly influence the selection of spatial priorities for marine conservation of threatened species. Although there are known limitations in multinational large-scale planning, attempting to devise more systematic and rigorous planning methods is especially critical given that collaborative conservation action is on the rise and global financial crisis restricts conservation investments.

Post-processing ECMWF precipitation and temperature ensemble reforecasts for operational hydrologic forecasting at various spatial scales

NASA Astrophysics Data System (ADS)

Verkade, J. S.; Brown, J. D.; Reggiani, P.; Weerts, A. H.

2013-09-01

The ECMWF temperature and precipitation ensemble reforecasts are evaluated for biases in the mean, spread and forecast probabilities, and how these biases propagate to streamflow ensemble forecasts. The forcing ensembles are subsequently post-processed to reduce bias and increase skill, and to investigate whether this leads to improved streamflow ensemble forecasts. Multiple post-processing techniques are used: quantile-to-quantile transform, linear regression with an assumption of bivariate normality and logistic regression. Both the raw and post-processed ensembles are run through a hydrologic model of the river Rhine to create streamflow ensembles. The results are compared using multiple verification metrics and skill scores: relative mean error, Brier skill score and its decompositions, mean continuous ranked probability skill score and its decomposition, and the ROC score. Verification of the streamflow ensembles is performed at multiple spatial scales: relatively small headwater basins, large tributaries and the Rhine outlet at Lobith. The streamflow ensembles are verified against simulated streamflow, in order to isolate the effects of biases in the forcing ensembles and any improvements therein. The results indicate that the forcing ensembles contain significant biases, and that these cascade to the streamflow ensembles. Some of the bias in the forcing ensembles is unconditional in nature; this was resolved by a simple quantile-to-quantile transform. Improvements in conditional bias and skill of the forcing ensembles vary with forecast lead time, amount, and spatial scale, but are generally moderate. The translation to streamflow forecast skill is further muted, and several explanations are considered, including limitations in the modelling of the space-time covariability of the forcing ensembles and the presence of storages.

Spatially explicit modeling of particulate nutrient flux in Large global rivers

NASA Astrophysics Data System (ADS)

Cohen, S.; Kettner, A.; Mayorga, E.; Harrison, J. A.

2017-12-01

Water, sediment, nutrient and carbon fluxes along river networks have undergone considerable alterations in response to anthropogenic and climatic changes, with significant consequences to infrastructure, agriculture, water security, ecology and geomorphology worldwide. However, in a global setting, these changes in fluvial fluxes and their spatial and temporal characteristics are poorly constrained, due to the limited availability of continuous and long-term observations. We present results from a new global-scale particulate modeling framework (WBMsedNEWS) that combines the Global NEWS watershed nutrient export model with the spatially distributed WBMsed water and sediment model. We compare the model predictions against multiple observational datasets. The results indicate that the model is able to accurately predict particulate nutrient (Nitrogen, Phosphorus and Organic Carbon) fluxes on an annual time scale. Analysis of intra-basin nutrient dynamics and fluxes to global oceans is presented.

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

Scales of snow depth variability in high elevation rangeland sagebrush

NASA Astrophysics Data System (ADS)

Tedesche, Molly E.; Fassnacht, Steven R.; Meiman, Paul J.

2017-09-01

In high elevation semi-arid rangelands, sagebrush and other shrubs can affect transport and deposition of wind-blown snow, enabling the formation of snowdrifts. Datasets from three field experiments were used to investigate the scales of spatial variability of snow depth around big mountain sagebrush ( Artemisia tridentata Nutt.) at a high elevation plateau rangeland in North Park, Colorado, during the winters of 2002, 2003, and 2008. Data were collected at multiple resolutions (0.05 to 25 m) and extents (2 to 1000 m). Finer scale data were collected specifically for this study to examine the correlation between snow depth, sagebrush microtopography, the ground surface, and the snow surface, as well as the temporal consistency of snow depth patterns. Variograms were used to identify the spatial structure and the Moran's I statistic was used to determine the spatial correlation. Results show some temporal consistency in snow depth at several scales. Plot scale snow depth variability is partly a function of the nature of individual shrubs, as there is some correlation between the spatial structure of snow depth and sagebrush, as well as between the ground and snow depth. The optimal sampling resolution appears to be 25-cm, but over a large area, this would require a multitude of samples, and thus a random stratified approach is recommended with a fine measurement resolution of 5-cm.

Spatially-Distributed Cost–Effectiveness Analysis Framework to Control Phosphorus from Agricultural Diffuse Pollution

PubMed Central

Geng, Runzhe; Wang, Xiaoyan; Sharpley, Andrew N.; Meng, Fande

2015-01-01

Best management practices (BMPs) for agricultural diffuse pollution control are implemented at the field or small-watershed scale. However, the benefits of BMP implementation on receiving water quality at multiple spatial is an ongoing challenge. In this paper, we introduce an integrated approach that combines risk assessment (i.e., Phosphorus (P) index), model simulation techniques (Hydrological Simulation Program–FORTRAN), and a BMP placement tool at various scales to identify the optimal location for implementing multiple BMPs and estimate BMP effectiveness after implementation. A statistically significant decrease in nutrient discharge from watersheds is proposed to evaluate the effectiveness of BMPs, strategically targeted within watersheds. Specifically, we estimate two types of cost-effectiveness curves (total pollution reduction and proportion of watersheds improved) for four allocation approaches. Selection of a ‘‘best approach” depends on the relative importance of the two types of effectiveness, which involves a value judgment based on the random/aggregated degree of BMP distribution among and within sub-watersheds. A statistical optimization framework is developed and evaluated in Chaohe River Watershed located in the northern mountain area of Beijing. Results show that BMP implementation significantly (p >0.001) decrease P loss from the watershed. Remedial strategies where BMPs were targeted to areas of high risk of P loss, deceased P loads compared with strategies where BMPs were randomly located across watersheds. Sensitivity analysis indicated that aggregated BMP placement in particular watershed is the most cost-effective scenario to decrease P loss. The optimization approach outlined in this paper is a spatially hierarchical method for targeting nonpoint source controls across a range of scales from field to farm, to watersheds, to regions. Further, model estimates showed targeting at multiple scales is necessary to optimize program efficiency. The integrated model approach described that selects and places BMPs at varying levels of implementation, provides a new theoretical basis and technical guidance for diffuse pollution management in agricultural watersheds. PMID:26313561

Spatially-Distributed Cost-Effectiveness Analysis Framework to Control Phosphorus from Agricultural Diffuse Pollution.

PubMed

Geng, Runzhe; Wang, Xiaoyan; Sharpley, Andrew N; Meng, Fande

2015-01-01

Best management practices (BMPs) for agricultural diffuse pollution control are implemented at the field or small-watershed scale. However, the benefits of BMP implementation on receiving water quality at multiple spatial is an ongoing challenge. In this paper, we introduce an integrated approach that combines risk assessment (i.e., Phosphorus (P) index), model simulation techniques (Hydrological Simulation Program-FORTRAN), and a BMP placement tool at various scales to identify the optimal location for implementing multiple BMPs and estimate BMP effectiveness after implementation. A statistically significant decrease in nutrient discharge from watersheds is proposed to evaluate the effectiveness of BMPs, strategically targeted within watersheds. Specifically, we estimate two types of cost-effectiveness curves (total pollution reduction and proportion of watersheds improved) for four allocation approaches. Selection of a ''best approach" depends on the relative importance of the two types of effectiveness, which involves a value judgment based on the random/aggregated degree of BMP distribution among and within sub-watersheds. A statistical optimization framework is developed and evaluated in Chaohe River Watershed located in the northern mountain area of Beijing. Results show that BMP implementation significantly (p >0.001) decrease P loss from the watershed. Remedial strategies where BMPs were targeted to areas of high risk of P loss, deceased P loads compared with strategies where BMPs were randomly located across watersheds. Sensitivity analysis indicated that aggregated BMP placement in particular watershed is the most cost-effective scenario to decrease P loss. The optimization approach outlined in this paper is a spatially hierarchical method for targeting nonpoint source controls across a range of scales from field to farm, to watersheds, to regions. Further, model estimates showed targeting at multiple scales is necessary to optimize program efficiency. The integrated model approach described that selects and places BMPs at varying levels of implementation, provides a new theoretical basis and technical guidance for diffuse pollution management in agricultural watersheds.

A statistically rigorous sampling design to integrate avian monitoring and management within Bird Conservation Regions.

PubMed

Pavlacky, David C; Lukacs, Paul M; Blakesley, Jennifer A; Skorkowsky, Robert C; Klute, David S; Hahn, Beth A; Dreitz, Victoria J; George, T Luke; Hanni, David J

2017-01-01

Monitoring is an essential component of wildlife management and conservation. However, the usefulness of monitoring data is often undermined by the lack of 1) coordination across organizations and regions, 2) meaningful management and conservation objectives, and 3) rigorous sampling designs. Although many improvements to avian monitoring have been discussed, the recommendations have been slow to emerge in large-scale programs. We introduce the Integrated Monitoring in Bird Conservation Regions (IMBCR) program designed to overcome the above limitations. Our objectives are to outline the development of a statistically defensible sampling design to increase the value of large-scale monitoring data and provide example applications to demonstrate the ability of the design to meet multiple conservation and management objectives. We outline the sampling process for the IMBCR program with a focus on the Badlands and Prairies Bird Conservation Region (BCR 17). We provide two examples for the Brewer's sparrow (Spizella breweri) in BCR 17 demonstrating the ability of the design to 1) determine hierarchical population responses to landscape change and 2) estimate hierarchical habitat relationships to predict the response of the Brewer's sparrow to conservation efforts at multiple spatial scales. The collaboration across organizations and regions provided economy of scale by leveraging a common data platform over large spatial scales to promote the efficient use of monitoring resources. We designed the IMBCR program to address the information needs and core conservation and management objectives of the participating partner organizations. Although it has been argued that probabilistic sampling designs are not practical for large-scale monitoring, the IMBCR program provides a precedent for implementing a statistically defensible sampling design from local to bioregional scales. We demonstrate that integrating conservation and management objectives with rigorous statistical design and analyses ensures reliable knowledge about bird populations that is relevant and integral to bird conservation at multiple scales.

A statistically rigorous sampling design to integrate avian monitoring and management within Bird Conservation Regions

PubMed Central

Hahn, Beth A.; Dreitz, Victoria J.; George, T. Luke

2017-01-01

Monitoring is an essential component of wildlife management and conservation. However, the usefulness of monitoring data is often undermined by the lack of 1) coordination across organizations and regions, 2) meaningful management and conservation objectives, and 3) rigorous sampling designs. Although many improvements to avian monitoring have been discussed, the recommendations have been slow to emerge in large-scale programs. We introduce the Integrated Monitoring in Bird Conservation Regions (IMBCR) program designed to overcome the above limitations. Our objectives are to outline the development of a statistically defensible sampling design to increase the value of large-scale monitoring data and provide example applications to demonstrate the ability of the design to meet multiple conservation and management objectives. We outline the sampling process for the IMBCR program with a focus on the Badlands and Prairies Bird Conservation Region (BCR 17). We provide two examples for the Brewer’s sparrow (Spizella breweri) in BCR 17 demonstrating the ability of the design to 1) determine hierarchical population responses to landscape change and 2) estimate hierarchical habitat relationships to predict the response of the Brewer’s sparrow to conservation efforts at multiple spatial scales. The collaboration across organizations and regions provided economy of scale by leveraging a common data platform over large spatial scales to promote the efficient use of monitoring resources. We designed the IMBCR program to address the information needs and core conservation and management objectives of the participating partner organizations. Although it has been argued that probabilistic sampling designs are not practical for large-scale monitoring, the IMBCR program provides a precedent for implementing a statistically defensible sampling design from local to bioregional scales. We demonstrate that integrating conservation and management objectives with rigorous statistical design and analyses ensures reliable knowledge about bird populations that is relevant and integral to bird conservation at multiple scales. PMID:29065128

Multiscale Modeling in the Clinic: Drug Design and Development

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

Clancy, Colleen E.; An, Gary; Cannon, William R.

A wide range of length and time scales are relevant to pharmacology, especially in drug development, drug design and drug delivery. Therefore, multi-scale computational modeling and simulation methods and paradigms that advance the linkage of phenomena occurring at these multiple scales have become increasingly important. Multi-scale approaches present in silico opportunities to advance laboratory research to bedside clinical applications in pharmaceuticals research. This is achievable through the capability of modeling to reveal phenomena occurring across multiple spatial and temporal scales, which are not otherwise readily accessible to experimentation. The resultant models, when validated, are capable of making testable predictions tomore » guide drug design and delivery. In this review we describe the goals, methods, and opportunities of multi-scale modeling in drug design and development. We demonstrate the impact of multiple scales of modeling in this field. We indicate the common mathematical techniques employed for multi-scale modeling approaches used in pharmacology and present several examples illustrating the current state-of-the-art regarding drug development for: Excitable Systems (Heart); Cancer (Metastasis and Differentiation); Cancer (Angiogenesis and Drug Targeting); Metabolic Disorders; and Inflammation and Sepsis. We conclude with a focus on barriers to successful clinical translation of drug development, drug design and drug delivery multi-scale models.« less

Spatial correlations between browsing on balsam fir by white-tailed deer and the nutritional value of neighboring winter forage.

PubMed

Champagne, Emilie; Moore, Ben D; Côté, Steeve D; Tremblay, Jean-Pierre

2018-03-01

Associational effects, that is, the influence of neighboring plants on herbivory suffered by a plant, are an outcome of forage selection. Although forage selection is a hierarchical process, few studies have investigated associational effects at multiple spatial scales. Because the nutritional quality of plants can be spatially structured, it might differently influence associational effects across multiple scales. Our objective was to determine the radius of influence of neighbor density and nutritional quality on balsam fir ( Abies balsamea ) herbivory by white-tailed deer ( Odocoileus virginianus ) in winter. We quantified browsing rates on fir and the density and quality of neighboring trees in a series of 10-year-old cutovers on Anticosti Island (Canada). We used cross-correlations to investigate relationships between browsing rates and the density and nutritional quality of neighboring trees at distances up to 1,000 m. Balsam fir and white spruce ( Picea glauca ) fiber content and dry matter in vitro true digestibility were correlated with fir browsing rate at the finest extra-patch scale (across distance of up to 50 m) and between cutover areas (300-400 m). These correlations suggest associational effects, that is, low nutritional quality of neighbors reduces the likelihood of fir herbivory (associational defense). Our results may indicate associational effects mediated by intraspecific variation in plant quality and suggest that these effects could occur at scales from tens to hundreds of meters. Understanding associational effects could inform strategies for restoration or conservation; for example, planting of fir among existing natural regeneration could be concentrated in areas of low nutritional quality.

Fractals and Spatial Methods for Mining Remote Sensing Imagery

NASA Technical Reports Server (NTRS)

Lam, Nina; Emerson, Charles; Quattrochi, Dale

2003-01-01

The rapid increase in digital remote sensing and GIS data raises a critical problem -- how can such an enormous amount of data be handled and analyzed so that useful information can be derived quickly? Efficient handling and analysis of large spatial data sets is central to environmental research, particularly in global change studies that employ time series. Advances in large-scale environmental monitoring and modeling require not only high-quality data, but also reliable tools to analyze the various types of data. A major difficulty facing geographers and environmental scientists in environmental assessment and monitoring is that spatial analytical tools are not easily accessible. Although many spatial techniques have been described recently in the literature, they are typically presented in an analytical form and are difficult to transform to a numerical algorithm. Moreover, these spatial techniques are not necessarily designed for remote sensing and GIS applications, and research must be conducted to examine their applicability and effectiveness in different types of environmental applications. This poses a chicken-and-egg problem: on one hand we need more research to examine the usability of the newer techniques and tools, yet on the other hand, this type of research is difficult to conduct if the tools to be explored are not accessible. Another problem that is fundamental to environmental research are issues related to spatial scale. The scale issue is especially acute in the context of global change studies because of the need to integrate remote-sensing and other spatial data that are collected at different scales and resolutions. Extrapolation of results across broad spatial scales remains the most difficult problem in global environmental research. There is a need for basic characterization of the effects of scale on image data, and the techniques used to measure these effects must be developed and implemented to allow for a multiple scale assessment of the data before any useful process-oriented modeling involving scale-dependent data can be conducted. Through the support of research grants from NASA, we have developed a software module called ICAMS (Image Characterization And Modeling System) to address the need to develop innovative spatial techniques and make them available to the broader scientific communities. ICAMS provides new spatial techniques, such as fractal analysis, geostatistical functions, and multiscale analysis that are not easily available in commercial GIS/image processing software. By bundling newer spatial methods in a user-friendly software module, researchers can begin to test and experiment with the new spatial analysis methods and they can gauge scale effects using a variety of remote sensing imagery. In the following, we describe briefly the development of ICAMS and present application examples.

Seeing the forest through the trees: Considering roost-site selection at multiple spatial scales

USGS Publications Warehouse

Jachowski, David S.; Rota, Christopher T.; Dobony, Christopher A.; Ford, W. Mark; Edwards, John W.

2016-01-01

Conservation of bat species is one of the most daunting wildlife conservation challenges in North America, requiring detailed knowledge about their ecology to guide conservation efforts. Outside of the hibernating season, bats in temperate forest environments spend their diurnal time in day-roosts. In addition to simple shelter, summer roost availability is as critical as maternity sites and maintaining social group contact. To date, a major focus of bat conservation has concentrated on conserving individual roost sites, with comparatively less focus on the role that broader habitat conditions contribute towards roost-site selection. We evaluated roost-site selection by a northern population of federally-endangered Indiana bats (Myotis sodalis) at Fort Drum Military Installation in New York, USA at three different spatial scales: landscape, forest stand, and individual tree level. During 2007–2011, we radiotracked 33 Indiana bats (10 males, 23 females) and located 348 roosting events in 116 unique roost trees. At the landscape scale, bat roost-site selection was positively associated with northern mixed forest, increased slope, and greater distance from human development. At the stand scale, we observed subtle differences in roost site selection based on sex and season, but roost selection was generally positively associated with larger stands with a higher basal area, larger tree diameter, and a greater sugar maple (Acer saccharum) component. We observed no distinct trends of roosts being near high-quality foraging areas of water and forest edges. At the tree scale, roosts were typically in American elm (Ulmus americana) or sugar maple of large diameter (>30 cm) of moderate decay with loose bark. Collectively, our results highlight the importance of considering day roost needs simultaneously across multiple spatial scales. Size and decay class of individual roosts are key ecological attributes for the Indiana bat, however, larger-scale stand structural components that are products of past and current land use interacting with environmental aspects such as landform also are important factors influencing roost-tree selection patterns.

Perspectives on why digital ecologies matter: combining population genetics and ecologically informed agent-based models with GIS for managing dipteran livestock pests.

PubMed

Peck, Steven L

2014-10-01

It is becoming clear that handling the inherent complexity found in ecological systems is an essential task for finding ways to control insect pests of tropical livestock such as tsetse flies, and old and new world screwworms. In particular, challenging multivalent management programs, such as Area Wide Integrated Pest Management (AW-IPM), face daunting problems of complexity at multiple spatial scales, ranging from landscape level processes to those of smaller scales such as the parasite loads of individual animals. Daunting temporal challenges also await resolution, such as matching management time frames to those found on ecological and even evolutionary temporal scales. How does one deal with representing processes with models that involve multiple spatial and temporal scales? Agent-based models (ABM), combined with geographic information systems (GIS), may allow for understanding, predicting and managing pest control efforts in livestock pests. This paper argues that by incorporating digital ecologies in our management efforts clearer and more informed decisions can be made. I also point out the power of these models in making better predictions in order to anticipate the range of outcomes possible or likely. Copyright © 2014 International Atomic Energy Agency 2014. Published by Elsevier B.V. All rights reserved.

Multiscale connectivity and graph theory highlight critical areas for conservation under climate change.

PubMed

Dilt, Thomas E; Weisberg, Peter J; Leitner, Philip; Matocq, Marjorie D; Inman, Richard D; Nussear, Kenneth E; Esque, Todd C

2016-06-01

Conservation planning and biodiversity management require information on landscape connectivity across a range of spatial scales from individual home ranges to large regions. Reduction in landscape connectivity due changes in land use or development is expected to act synergistically with alterations to habitat mosaic configuration arising from climate change. We illustrate a multiscale connectivity framework to aid habitat conservation prioritization in the context of changing land use and climate. Our approach, which builds upon the strengths of multiple landscape connectivity methods, including graph theory, circuit theory, and least-cost path analysis, is here applied to the conservation planning requirements of the Mohave ground squirrel. The distribution of this threatened Californian species, as for numerous other desert species, overlaps with the proposed placement of several utility-scale renewable energy developments in the American southwest. Our approach uses information derived at three spatial scales to forecast potential changes in habitat connectivity under various scenarios of energy development and climate change. By disentangling the potential effects of habitat loss and fragmentation across multiple scales, we identify priority conservation areas for both core habitat and critical corridor or stepping stone habitats. This approach is a first step toward applying graph theory to analyze habitat connectivity for species with continuously distributed habitat and should be applicable across a broad range of taxa.

A National Approach for Mapping and Quantifying Habitat-based Biodiversity Metrics Across Multiple Spatial Scales

EPA Science Inventory

Ecosystem services, i.e., "services provided to humans from natural systems," have become a key issue of this century in resource management, conservation planning, and environmental decision analysis. Mapping and quantifying ecosystem services have become strategic national inte...

Agroforestry, climate change, and food security

USDA-ARS?s Scientific Manuscript database

Successfully addressing global climate change effects on agriculture will require a holistic, sustained approach incorporating a suite of strategies at multiple spatial scales and time horizons. In the USA of the 1930’s, bold and innovative leadership at high levels of government was needed to enact...

Region-specific patterns and drivers of macroscale forest plant invasions

Treesearch

Basil V. Iannone; Christopher M. Oswalt; Andrew M. Liebhold; Qinfeng Guo; Kevin M. Potter; Gabriela C. Nunez-Mir; Sonja N. Oswalt; Bryan C. Pijanowski; Songlin Fei; Bethany Bradley

2015-01-01

Aim Stronger inferences about biological invasions may be obtained when accounting for multiple invasion measures and the spatial heterogeneity occurring across large geographic areas. We pursued this enquiry by utilizing a multimeasure, multiregional framework to investigate forest plant invasions at a subcontinental scale. ...

Wolverine conservation and management.

Treesearch

L.F. Ruggiero; K.S. McKelvey; K.B. Aubry; J.P. Copeland; D.H. Pletscher; M.G. Hornocker

2007-01-01

This Special Section includes 8 peer-reviewed papers on the wolverine (Gulo gulo) in southern North America. These papers provide new information on current and historical distribution, habitat relations at multiple spatial scales, and interaction with humans. In aggregate, these papers substantially increase our knowledge of wolverine ecology and...

Wolverine conservation and management

Treesearch

Leonard F. Ruggiero; Kevin S. Mckelvey; Keith B. Aubry; Jeffrey P. Copeland; Daniel H. Pletscher; Maurice G. Hornocker

2007-01-01

This Special Section includes 8 peer-reviewed papers on the wolverine (Gulo gulo) in southern North America. These papers provide new information on current and historical distribution, habitat relations at multiple spatial scales, and interactions with humans. In aggregate, these papers substantially increase our knowledge of wolverine ecology and...

Body size distributions signal a regime shift in a lake ecosystem

EPA Science Inventory

Communities of organisms, from mammals to microorganisms, have discontinuous distributions of body size. This pattern of size structuring is a conservative trait of community organization and is a product of processes that occur at multiple spatial and temporal scales. In this st...

Modeling stream network-scale variation in coho salmon overwinter survival and smolt size

EPA Science Inventory

We used multiple regression and hierarchical mixed-effects models to examine spatial patterns of overwinter survival and size at smolting in juvenile coho salmon Oncorhynchus kisutch in relation to habitat attributes across an extensive stream network in southwestern Oregon over ...

Local variations in spatial synchrony of influenza epidemics.

PubMed

Stark, James H; Cummings, Derek A T; Ermentrout, Bard; Ostroff, Stephen; Sharma, Ravi; Stebbins, Samuel; Burke, Donald S; Wisniewski, Stephen R

2012-01-01

Understanding the mechanism of influenza spread across multiple geographic scales is not complete. While the mechanism of dissemination across regions and states of the United States has been described, understanding the determinants of dissemination between counties has not been elucidated. The paucity of high resolution spatial-temporal influenza incidence data to evaluate disease structure is often not available. We report on the underlying relationship between the spread of influenza and human movement between counties of one state. Significant synchrony in the timing of epidemics exists across the entire state and decay with distance (regional correlation=62%). Synchrony as a function of population size display evidence of hierarchical spread with more synchronized epidemics occurring among the most populated counties. A gravity model describing movement between two populations is a stronger predictor of influenza spread than adult movement to and from workplaces suggesting that non-routine and leisure travel drive local epidemics. These findings highlight the complex nature of influenza spread across multiple geographic scales.

Local Variations in Spatial Synchrony of Influenza Epidemics

PubMed Central

Stark, James H.; Cummings, Derek A. T.; Ermentrout, Bard; Ostroff, Stephen; Sharma, Ravi; Stebbins, Samuel; Burke, Donald S.; Wisniewski, Stephen R.

2012-01-01

Background Understanding the mechanism of influenza spread across multiple geographic scales is not complete. While the mechanism of dissemination across regions and states of the United States has been described, understanding the determinants of dissemination between counties has not been elucidated. The paucity of high resolution spatial-temporal influenza incidence data to evaluate disease structure is often not available. Methodology and Findings We report on the underlying relationship between the spread of influenza and human movement between counties of one state. Significant synchrony in the timing of epidemics exists across the entire state and decay with distance (regional correlation = 62%). Synchrony as a function of population size display evidence of hierarchical spread with more synchronized epidemics occurring among the most populated counties. A gravity model describing movement between two populations is a stronger predictor of influenza spread than adult movement to and from workplaces suggesting that non-routine and leisure travel drive local epidemics. Conclusions These findings highlight the complex nature of influenza spread across multiple geographic scales. PMID:22916274

Risk assessment of salinity and turbidity in Victoria (Australia) to stream insects' community structure does not always protect functional traits.

PubMed

Kefford, Ben J; Schäfer, Ralf B; Metzeling, Leon

2012-01-15

Ecological risk assessments mostly consider measures of community composition (structure) across large spatial scales. These assessments, using species sensitivity distributions (SSDs) or the relative species retention (RSR), may not be protective of ecosystem functions and services at smaller spatial scales. Here we examine how changes in biological traits, as proxy for ecosystem functions/services, at a fine spatial scale relate to larger scale assessment of structure. We use functional traits of stream insect species in south-east Australia in two habitats (riffle and edge/pool). We find that the protection of community structure in terms of 95% of species over multiple sites against adverse effects of salinity (as electrical conductivity) and turbidity will mostly, but not always, protect traits at smaller scales. Considering different combinations of trait modalities, contaminants and habitat, a mean of 17.5% (range 0%-36.8) of cases would result in under-protection of trait modalities despite protecting species composition (in terms of Jaccard's Index). This under-protection of trait modalities is only because of the different spatial scales that community structure and the traits were considered. We recommend that where the protection of biological traits, ecosystem functions or ecosystem services from stressors is a management goal, protective targets should not be solely set using measures of community structure such as SSDs or RSR. To protect both structural and functional attributes separate risk assessments should be done. Copyright © 2011 Elsevier B.V. All rights reserved.

Influence of snowpack and melt energy heterogeneity on snow cover depletion and snowmelt runoff simulation in a cold mountain environment

NASA Astrophysics Data System (ADS)

DeBeer, Chris M.; Pomeroy, John W.

2017-10-01

The spatial heterogeneity of mountain snow cover and ablation is important in controlling patterns of snow cover depletion (SCD), meltwater production, and runoff, yet is not well-represented in most large-scale hydrological models and land surface schemes. Analyses were conducted in this study to examine the influence of various representations of snow cover and melt energy heterogeneity on both simulated SCD and stream discharge from a small alpine basin in the Canadian Rocky Mountains. Simulations were performed using the Cold Regions Hydrological Model (CRHM), where point-scale snowmelt computations were made using a snowpack energy balance formulation and applied to spatial frequency distributions of snow water equivalent (SWE) on individual slope-, aspect-, and landcover-based hydrological response units (HRUs) in the basin. Hydrological routines were added to represent the vertical and lateral transfers of water through the basin and channel system. From previous studies it is understood that the heterogeneity of late winter SWE is a primary control on patterns of SCD. The analyses here showed that spatial variation in applied melt energy, mainly due to differences in net radiation, has an important influence on SCD at multiple scales and basin discharge, and cannot be neglected without serious error in the prediction of these variables. A single basin SWE distribution using the basin-wide mean SWE (SWE ‾) and coefficient of variation (CV; standard deviation/mean) was found to represent the fine-scale spatial heterogeneity of SWE sufficiently well. Simulations that accounted for differences in (SWE ‾) among HRUs but neglected the sub-HRU heterogeneity of SWE were found to yield similar discharge results as simulations that included this heterogeneity, while SCD was poorly represented, even at the basin level. Finally, applying point-scale snowmelt computations based on a single SWE depth for each HRU (thereby neglecting spatial differences in internal snowpack energetics over the distributions) was found to yield similar SCD and discharge results as simulations that resolved internal energy differences. Spatial/internal snowpack melt energy effects are more pronounced at times earlier in spring before the main period of snowmelt and SCD, as shown in previously published work. The paper discusses the importance of these findings as they apply to the warranted complexity of snowmelt process simulation in cold mountain environments, and shows how the end-of-winter SWE distribution represents an effective means of resolving snow cover heterogeneity at multiple scales for modelling, even in steep and complex terrain.

Spatially telescoping measurements for improved characterization of groundwater-surface water interactions

USGS Publications Warehouse

Kikuchi, Colin; Ferre, Ty P.A.; Welker, Jeffery M.

2012-01-01

The suite of measurement methods available to characterize fluxes between groundwater and surface water is rapidly growing. However, there are few studies that examine approaches to design of field investigations that include multiple methods. We propose that performing field measurements in a spatially telescoping sequence improves measurement flexibility and accounts for nested heterogeneities while still allowing for parsimonious experimental design. We applied this spatially telescoping approach in a study of ground water-surface water (GW-SW) interaction during baseflow conditions along Lucile Creek, located near Wasilla, Alaska. Catchment-scale data, including channel geomorphic indices and hydrogeologic transects, were used to screen areas of potentially significant GW-SW exchange. Specifically, these data indicated increasing groundwater contribution from a deeper regional aquifer along the middle to lower reaches of the stream. This initial assessment was tested using reach-scale estimates of groundwater contribution during baseflow conditions, including differential discharge measurements and the use of chemical tracers analyzed in a three-component mixing model. The reach-scale measurements indicated a large increase in discharge along the middle reaches of the stream accompanied by a shift in chemical composition towards a regional groundwater end member. Finally, point measurements of vertical water fluxes -- obtained using seepage meters as well as temperature-based methods -- were used to evaluate spatial and temporal variability of GW-SW exchange within representative reaches. The spatial variability of upward fluxes, estimated using streambed temperature mapping at the sub-reach scale, was observed to vary in relation to both streambed composition and the magnitude of groundwater contribution from differential discharge measurements. The spatially telescoping approach improved the efficiency of this field investigation. Beginning our assessment with catchment-scale data allowed us to identify locations of GW-SW exchange, plan measurements at representative field sites and improve our interpretation of reach-scale and point-scale measurements.

Progress towards the use of publicly available data networks to conduct cross-scale historical reconstructions of carbon dynamics in US Drylands

NASA Astrophysics Data System (ADS)

Washington-Allen, R. A.; Landolt, K.; Emanuel, R. E.; Therrell, M. D.; Nagle, N.; Grissino-Mayer, H. D.; Poulter, B.

2016-12-01

Emergent scale properties of water-limited or Dryland ecosystem's carbon flux are unknown at spatial scales from local to global and time scales of 10 - 1000 years or greater. The width of a tree ring is a metric of production that has been correlated with the amount of precipitation. This relationship has been used to reconstruct rainfall and fire histories in the Drylands of the southwestern US. The normalized difference vegetation index (NDVI) is globally measured by selected satellite sensors and is highly correlated with the fraction of solar radiation which is absorbed for photosynthesis by plants (FPAR), as well as with vegetation biomass, net primary productivity (NPP), and tree ring width. Publicly available web-based archives of free NDVI and tree ring data exist and have allowed historical temporal reconstructions of carbon dynamics for the past 300 to 500 years. Climate and tree ring databases have been used to spatially reconstruct drought dynamics for the last 500 years in the western US. In 2007, we hypothesized that NDVI and tree ring width could be used to spatially reconstruct carbon dynamics in US Drylands. In 2015, we succeeded with a 300-year historical spatial reconstruction of NPP in California using a Blue Oak tree ring chronology. Online eddy covariance flux tower measures of NPP are well correlated with satellite measures of NPP. This suggests that net ecosystem exchange (NEE = NPP - soil Respiration) could be historically reconstructed across Drylands. Ongoing research includes 1) scaling historical spatial reconstruction to US Drylands, 2) comparing the use of single versus multiple tree ring species (r2 = 68) and 3) use of the eddy flux tower network, remote sensing, and tree ring data to historically spatially reconstruct Dryland NEE.

Impacts of spatial resolution and representation of flow connectivity on large-scale simulation of floods

NASA Astrophysics Data System (ADS)

Mateo, Cherry May R.; Yamazaki, Dai; Kim, Hyungjun; Champathong, Adisorn; Vaze, Jai; Oki, Taikan

2017-10-01

Global-scale river models (GRMs) are core tools for providing consistent estimates of global flood hazard, especially in data-scarce regions. Due to former limitations in computational power and input datasets, most GRMs have been developed to use simplified representations of flow physics and run at coarse spatial resolutions. With increasing computational power and improved datasets, the application of GRMs to finer resolutions is becoming a reality. To support development in this direction, the suitability of GRMs for application to finer resolutions needs to be assessed. This study investigates the impacts of spatial resolution and flow connectivity representation on the predictive capability of a GRM, CaMa-Flood, in simulating the 2011 extreme flood in Thailand. Analyses show that when single downstream connectivity (SDC) is assumed, simulation results deteriorate with finer spatial resolution; Nash-Sutcliffe efficiency coefficients decreased by more than 50 % between simulation results at 10 km resolution and 1 km resolution. When multiple downstream connectivity (MDC) is represented, simulation results slightly improve with finer spatial resolution. The SDC simulations result in excessive backflows on very flat floodplains due to the restrictive flow directions at finer resolutions. MDC channels attenuated these effects by maintaining flow connectivity and flow capacity between floodplains in varying spatial resolutions. While a regional-scale flood was chosen as a test case, these findings should be universal and may have significant impacts on large- to global-scale simulations, especially in regions where mega deltas exist.These results demonstrate that a GRM can be used for higher resolution simulations of large-scale floods, provided that MDC in rivers and floodplains is adequately represented in the model structure.

Layout-aware simulation of soft errors in sub-100 nm integrated circuits

NASA Astrophysics Data System (ADS)

Balbekov, A.; Gorbunov, M.; Bobkov, S.

2016-12-01

Single Event Transient (SET) caused by charged particle traveling through the sensitive volume of integral circuit (IC) may lead to different errors in digital circuits in some cases. In technologies below 180 nm, a single particle can affect multiple devices causing multiple SET. This fact adds the complexity to fault tolerant devices design, because the schematic design techniques become useless without their layout consideration. The most common layout mitigation technique is a spatial separation of sensitive nodes of hardened circuits. Spatial separation decreases the circuit performance and increases power consumption. Spacing should thus be reasonable and its scaling follows the device dimensions' scaling trend. This paper presents the development of the SET simulation approach comprised of SPICE simulation with "double exponent" current source as SET model. The technique uses layout in GDSII format to locate nearby devices that can be affected by a single particle and that can share the generated charge. The developed software tool automatizes multiple simulations and gathers the produced data to present it as the sensitivity map. The examples of conducted simulations of fault tolerant cells and their sensitivity maps are presented in this paper.

Visualization of Spatio-Temporal Relations in Movement Event Using Multi-View

NASA Astrophysics Data System (ADS)

Zheng, K.; Gu, D.; Fang, F.; Wang, Y.; Liu, H.; Zhao, W.; Zhang, M.; Li, Q.

2017-09-01

Spatio-temporal relations among movement events extracted from temporally varying trajectory data can provide useful information about the evolution of individual or collective movers, as well as their interactions with their spatial and temporal contexts. However, the pure statistical tools commonly used by analysts pose many difficulties, due to the large number of attributes embedded in multi-scale and multi-semantic trajectory data. The need for models that operate at multiple scales to search for relations at different locations within time and space, as well as intuitively interpret what these relations mean, also presents challenges. Since analysts do not know where or when these relevant spatio-temporal relations might emerge, these models must compute statistical summaries of multiple attributes at different granularities. In this paper, we propose a multi-view approach to visualize the spatio-temporal relations among movement events. We describe a method for visualizing movement events and spatio-temporal relations that uses multiple displays. A visual interface is presented, and the user can interactively select or filter spatial and temporal extents to guide the knowledge discovery process. We also demonstrate how this approach can help analysts to derive and explain the spatio-temporal relations of movement events from taxi trajectory data.

Changeable camouflage: how well can flounder resemble the colour and spatial scale of substrates in their natural habitats?

PubMed Central

Akkaynak, Derya; Siemann, Liese A.; Barbosa, Alexandra

2017-01-01

Flounder change colour and pattern for camouflage. We used a spectrometer to measure reflectance spectra and a digital camera to capture body patterns of two flounder species camouflaged on four natural backgrounds of different spatial scale (sand, small gravel, large gravel and rocks). We quantified the degree of spectral match between flounder and background relative to the situation of perfect camouflage in which flounder and background were assumed to have identical spectral distribution. Computations were carried out for three biologically relevant observers: monochromatic squid, dichromatic crab and trichromatic guitarfish. Our computations present a new approach to analysing datasets with multiple spectra that have large variance. Furthermore, to investigate the spatial match between flounder and background, images of flounder patterns were analysed using a custom program originally developed to study cuttlefish camouflage. Our results show that all flounder and background spectra fall within the same colour gamut and that, in terms of different observer visual systems, flounder matched most substrates in luminance and colour contrast. Flounder matched the spatial scales of all substrates except for rocks. We discuss findings in terms of flounder biology; furthermore, we discuss our methodology in light of hyperspectral technologies that combine high-resolution spectral and spatial imaging. PMID:28405370

Changeable camouflage: how well can flounder resemble the colour and spatial scale of substrates in their natural habitats?

PubMed

Akkaynak, Derya; Siemann, Liese A; Barbosa, Alexandra; Mäthger, Lydia M

2017-03-01

Flounder change colour and pattern for camouflage. We used a spectrometer to measure reflectance spectra and a digital camera to capture body patterns of two flounder species camouflaged on four natural backgrounds of different spatial scale (sand, small gravel, large gravel and rocks). We quantified the degree of spectral match between flounder and background relative to the situation of perfect camouflage in which flounder and background were assumed to have identical spectral distribution. Computations were carried out for three biologically relevant observers: monochromatic squid, dichromatic crab and trichromatic guitarfish. Our computations present a new approach to analysing datasets with multiple spectra that have large variance. Furthermore, to investigate the spatial match between flounder and background, images of flounder patterns were analysed using a custom program originally developed to study cuttlefish camouflage. Our results show that all flounder and background spectra fall within the same colour gamut and that, in terms of different observer visual systems, flounder matched most substrates in luminance and colour contrast. Flounder matched the spatial scales of all substrates except for rocks. We discuss findings in terms of flounder biology; furthermore, we discuss our methodology in light of hyperspectral technologies that combine high-resolution spectral and spatial imaging.

Plasticity and stability of visual field maps in adult primary visual cortex

PubMed Central

Wandell, Brian A.; Smirnakis, Stelios M.

2010-01-01

Preface It is important to understand the balance between cortical plasticity and stability in various systems and spatial scales in the adult brain. We review measurements of adult plasticity in primary visual cortex (V1), a structure that has a key role in distributing visual information. There are claims of plasticity at multiple spatial scales in adult V1, but many inconsistencies in the data raise questions about the extent and nature of such plasticity. Understanding is further limited by a lack of quantitative models to guide the interpretation of the data. These problems limit efforts to translate research findings about adult cortical plasticity into significant clinical, educational and policy applications. PMID:19904279

Community assembly of the ferns of Florida.

PubMed

Sessa, Emily B; Chambers, Sally M; Li, Daijiang; Trotta, Lauren; Endara, Lorena; Burleigh, J Gordon; Baiser, Benjamin

2018-03-01

Many ecological and evolutionary processes shape the assembly of organisms into local communities from a regional pool of species. We analyzed phylogenetic and functional diversity to understand community assembly of the ferns of Florida at two spatial scales. We built a phylogeny for 125 of the 141 species of ferns in Florida using five chloroplast markers. We calculated mean pairwise dissimilarity (MPD) and mean nearest taxon distance (MNTD) from phylogenetic distances and functional trait data for both spatial scales and compared the results to null models to assess significance. Our results for over vs. underdispersion in functional and phylogenetic diversity differed depending on spatial scale and metric considered. At the county scale, MPD revealed evidence for phylogenetic overdispersion, while MNTD revealed phylogenetic and functional underdispersion, and at the conservation area scale, MPD revealed phylogenetic and functional underdispersion while MNTD revealed evidence only of functional underdispersion. Our results are consistent with environmental filtering playing a larger role at the smaller, conservation area scale. The smaller spatial units are likely composed of fewer local habitat types that are selecting for closely related species, with the larger-scale units more likely to be composed of multiple habitat types that bring together a larger pool of species from across the phylogeny. Several aspects of fern biology, including their unique physiology and water relations and the importance of the independent gametophyte stage of the life cycle, make ferns highly sensitive to local, microhabitat conditions. © 2018 The Authors. American Journal of Botany is published by Wiley Periodicals, Inc. on behalf of the Botanical Society of America.

A Comprehensive Specimen-Specific Multiscale Data Set for Anatomical and Mechanical Characterization of the Tibiofemoral Joint

PubMed Central

Chokhandre, Snehal; Colbrunn, Robb; Bennetts, Craig; Erdemir, Ahmet

2015-01-01

Understanding of tibiofemoral joint mechanics at multiple spatial scales is essential for developing effective preventive measures and treatments for both pathology and injury management. Currently, there is a distinct lack of specimen-specific biomechanical data at multiple spatial scales, e.g., joint, tissue, and cell scales. Comprehensive multiscale data may improve the understanding of the relationship between biomechanical and anatomical markers across various scales. Furthermore, specimen-specific multiscale data for the tibiofemoral joint may assist development and validation of specimen-specific computational models that may be useful for more thorough analyses of the biomechanical behavior of the joint. This study describes an aggregation of procedures for acquisition of multiscale anatomical and biomechanical data for the tibiofemoral joint. Magnetic resonance imaging was used to acquire anatomical morphology at the joint scale. A robotic testing system was used to quantify joint level biomechanical response under various loading scenarios. Tissue level material properties were obtained from the same specimen for the femoral and tibial articular cartilage, medial and lateral menisci, anterior and posterior cruciate ligaments, and medial and lateral collateral ligaments. Histology data were also obtained for all tissue types to measure specimen-specific cell scale information, e.g., cellular distribution. This study is the first of its kind to establish a comprehensive multiscale data set for a musculoskeletal joint and the presented data collection approach can be used as a general template to guide acquisition of specimen-specific comprehensive multiscale data for musculoskeletal joints. PMID:26381404

A multi-scale evaluation of pack stock effects on subalpine meadow plant communities in the Sierra Nevada

USGS Publications Warehouse

Lee, Steven R.; Berlow, Eric L.; Ostoja, Steven M.; Brooks, Matthew L.; Génin, Alexandre; Matchett, John R.; Hart, Stephen C.

2017-01-01

We evaluated the influence of pack stock (i.e., horse and mule) use on meadow plant communities in Sequoia and Yosemite National Parks in the Sierra Nevada of California. Meadows were sampled to account for inherent variability across multiple scales by: 1) controlling for among-meadow variability by using remotely sensed hydro-climatic and geospatial data to pair stock use meadows with similar non-stock (reference) sites, 2) accounting for within-meadow variation in the local hydrology using in-situ soil moisture readings, and 3) incorporating variation in stock use intensity by sampling across the entire available gradient of pack stock use. Increased cover of bare ground was detected only within “dry” meadow areas at the two most heavily used pack stock meadows (maximum animals per night per hectare). There was no difference in plant community composition for any level of soil moisture or pack stock use. Increased local-scale spatial variability in plant community composition (species dispersion) was detected in “wet” meadow areas at the two most heavily used meadows. These results suggest that at the meadow scale, plant communities are generally resistant to the contemporary levels of recreational pack stock use. However, finer-scale within-meadow responses such as increased bare ground or spatial variability in the plant community can be a function of local-scale hydrological conditions. Wilderness managers can improve monitoring of disturbance in Sierra Nevada meadows by adopting multiple plant community indices while simultaneously considering local moisture regimes.

Quantifying the metabolic activities of human-associated microbial communities across multiple ecological scales

PubMed Central

Maurice, Corinne Ferrier; Turnbaugh, Peter James

2013-01-01

Humans are home to complex microbial communities, whose aggregate genomes and their encoded metabolic activities are referred to as the human microbiome. Recently, researchers have begun to appreciate that different human body habitats and the activities of their resident microorganisms can be better understood in ecological terms, as a range of spatial scales encompassing single cells, guilds of microorganisms responsive to a similar substrate, microbial communities, body habitats, and host populations. However, the bulk of the work to date has focused on studies of culturable microorganisms in isolation or on DNA sequencing-based surveys of microbial diversity in small to moderately sized cohorts of individuals. Here, we discuss recent work that highlights the potential for assessing the human microbiome at a range of spatial scales, and for developing novel techniques that bridge multiple levels: for example, through the combination of single cell methods and metagenomic sequencing. These studies promise to not only provide a much-needed epidemiological and ecological context for mechanistic studies of culturable and genetically tractable microorganisms, but may also lead to the discovery of fundamental rules that govern the assembly and function of host-associated microbial communities. PMID:23550823

Ecohydrological consequences of vegetation interactions within the critical zone in the tropical Andes: multi-scale assessment of vegetation change consequences

NASA Astrophysics Data System (ADS)

Villegas, J. C.; Salazar, J. F.; Arias, P. A.; León, J. D.

2017-12-01

Land cover transformation is currently one of the most important challenges in tropical South America. These transformations occur both because of climate-related ecological perturbations, as well as in response to ongoing socio-economic processes. A fundamental difference between those two drivers is the spatial and temporal scale at which they operate. However, when considered in a larger context, both drivers affect the ability of ecosystems to provide fundamental services to society. In this work, we use a multi-scale approach to identify key-mechanisms through which land cover transformation significantly affects ecological, hydrological and ecoclimatological dynamics, potentially leading to loss of societally-critical regulation services. We propose a suite of examples spanning multiple spatial and temporal scales that illustrate the effects of land cover trnasformations in ecological, hydrological, biogeochemical and climatic functions in tropical South America. These examples highlight important global-change-effects management challenges, as well as the need to consider the feedbacks and interactions between multi-scale processes.

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

USGS Publications Warehouse

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

2001-01-01

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

Simulating Mercury And Methyl Mercury Stream Concentrations At Multiple Scales in a Wetland Influenced Coastal Plain Watershed (McTier Creek, SC, USA)

EPA Science Inventory

Use of Mechanistic Models to?Improve Understanding: Differential, mass balance, process-based Spatial and temporal resolution Necessary simplifications of system complexity Combing field monitoring and modeling efforts Balance between capturing complexity and maintaining...

EnviroAtlas: Two Use Cases in the EnviroAtlas

EPA Science Inventory

EnviroAtlas is an online spatial decision support tool for viewing and analyzing the supply, demand, and drivers of change related to natural and built infrastructure at multiple scales for the nation. To maximize usefulness to a broad range of users, EnviroAtlas contains trainin...

Biotic homogenization can decrease landscape-scale forest multifunctionality.

PubMed

van der Plas, Fons; Manning, Pete; Soliveres, Santiago; Allan, Eric; Scherer-Lorenzen, Michael; Verheyen, Kris; Wirth, Christian; Zavala, Miguel A; Ampoorter, Evy; Baeten, Lander; Barbaro, Luc; Bauhus, Jürgen; Benavides, Raquel; Benneter, Adam; Bonal, Damien; Bouriaud, Olivier; Bruelheide, Helge; Bussotti, Filippo; Carnol, Monique; Castagneyrol, Bastien; Charbonnier, Yohan; Coomes, David Anthony; Coppi, Andrea; Bastias, Cristina C; Dawud, Seid Muhie; De Wandeler, Hans; Domisch, Timo; Finér, Leena; Gessler, Arthur; Granier, André; Grossiord, Charlotte; Guyot, Virginie; Hättenschwiler, Stephan; Jactel, Hervé; Jaroszewicz, Bogdan; Joly, François-Xavier; Jucker, Tommaso; Koricheva, Julia; Milligan, Harriet; Mueller, Sandra; Muys, Bart; Nguyen, Diem; Pollastrini, Martina; Ratcliffe, Sophia; Raulund-Rasmussen, Karsten; Selvi, Federico; Stenlid, Jan; Valladares, Fernando; Vesterdal, Lars; Zielínski, Dawid; Fischer, Markus

2016-03-29

Many experiments have shown that local biodiversity loss impairs the ability of ecosystems to maintain multiple ecosystem functions at high levels (multifunctionality). In contrast, the role of biodiversity in driving ecosystem multifunctionality at landscape scales remains unresolved. We used a comprehensive pan-European dataset, including 16 ecosystem functions measured in 209 forest plots across six European countries, and performed simulations to investigate how local plot-scale richness of tree species (α-diversity) and their turnover between plots (β-diversity) are related to landscape-scale multifunctionality. After accounting for variation in environmental conditions, we found that relationships between α-diversity and landscape-scale multifunctionality varied from positive to negative depending on the multifunctionality metric used. In contrast, when significant, relationships between β-diversity and landscape-scale multifunctionality were always positive, because a high spatial turnover in species composition was closely related to a high spatial turnover in functions that were supported at high levels. Our findings have major implications for forest management and indicate that biotic homogenization can have previously unrecognized and negative consequences for large-scale ecosystem multifunctionality.

Biotic homogenization can decrease landscape-scale forest multifunctionality

PubMed Central

van der Plas, Fons; Manning, Pete; Soliveres, Santiago; Allan, Eric; Scherer-Lorenzen, Michael; Verheyen, Kris; Wirth, Christian; Zavala, Miguel A.; Ampoorter, Evy; Baeten, Lander; Barbaro, Luc; Bauhus, Jürgen; Benavides, Raquel; Benneter, Adam; Bonal, Damien; Bouriaud, Olivier; Bruelheide, Helge; Bussotti, Filippo; Carnol, Monique; Castagneyrol, Bastien; Charbonnier, Yohan; Coppi, Andrea; Bastias, Cristina C.; Dawud, Seid Muhie; De Wandeler, Hans; Domisch, Timo; Finér, Leena; Granier, André; Grossiord, Charlotte; Guyot, Virginie; Hättenschwiler, Stephan; Jactel, Hervé; Jaroszewicz, Bogdan; Joly, François-xavier; Jucker, Tommaso; Koricheva, Julia; Milligan, Harriet; Mueller, Sandra; Muys, Bart; Nguyen, Diem; Pollastrini, Martina; Ratcliffe, Sophia; Raulund-Rasmussen, Karsten; Selvi, Federico; Stenlid, Jan; Valladares, Fernando; Vesterdal, Lars; Zielínski, Dawid; Fischer, Markus

2016-01-01

Many experiments have shown that local biodiversity loss impairs the ability of ecosystems to maintain multiple ecosystem functions at high levels (multifunctionality). In contrast, the role of biodiversity in driving ecosystem multifunctionality at landscape scales remains unresolved. We used a comprehensive pan-European dataset, including 16 ecosystem functions measured in 209 forest plots across six European countries, and performed simulations to investigate how local plot-scale richness of tree species (α-diversity) and their turnover between plots (β-diversity) are related to landscape-scale multifunctionality. After accounting for variation in environmental conditions, we found that relationships between α-diversity and landscape-scale multifunctionality varied from positive to negative depending on the multifunctionality metric used. In contrast, when significant, relationships between β-diversity and landscape-scale multifunctionality were always positive, because a high spatial turnover in species composition was closely related to a high spatial turnover in functions that were supported at high levels. Our findings have major implications for forest management and indicate that biotic homogenization can have previously unrecognized and negative consequences for large-scale ecosystem multifunctionality. PMID:26979952

Construction of multi-scale consistent brain networks: methods and applications.

PubMed

Ge, Bao; Tian, Yin; Hu, Xintao; Chen, Hanbo; Zhu, Dajiang; Zhang, Tuo; Han, Junwei; Guo, Lei; Liu, Tianming

2015-01-01

Mapping human brain networks provides a basis for studying brain function and dysfunction, and thus has gained significant interest in recent years. However, modeling human brain networks still faces several challenges including constructing networks at multiple spatial scales and finding common corresponding networks across individuals. As a consequence, many previous methods were designed for a single resolution or scale of brain network, though the brain networks are multi-scale in nature. To address this problem, this paper presents a novel approach to constructing multi-scale common structural brain networks from DTI data via an improved multi-scale spectral clustering applied on our recently developed and validated DICCCOLs (Dense Individualized and Common Connectivity-based Cortical Landmarks). Since the DICCCOL landmarks possess intrinsic structural correspondences across individuals and populations, we employed the multi-scale spectral clustering algorithm to group the DICCCOL landmarks and their connections into sub-networks, meanwhile preserving the intrinsically-established correspondences across multiple scales. Experimental results demonstrated that the proposed method can generate multi-scale consistent and common structural brain networks across subjects, and its reproducibility has been verified by multiple independent datasets. As an application, these multi-scale networks were used to guide the clustering of multi-scale fiber bundles and to compare the fiber integrity in schizophrenia and healthy controls. In general, our methods offer a novel and effective framework for brain network modeling and tract-based analysis of DTI data.

Abundant Topological Outliers in Social Media Data and Their Effect on Spatial Analysis

PubMed Central

Zipf, Alexander

2016-01-01

Twitter and related social media feeds have become valuable data sources to many fields of research. Numerous researchers have thereby used social media posts for spatial analysis, since many of them contain explicit geographic locations. However, despite its widespread use within applied research, a thorough understanding of the underlying spatial characteristics of these data is still lacking. In this paper, we investigate how topological outliers influence the outcomes of spatial analyses of social media data. These outliers appear when different users contribute heterogeneous information about different phenomena simultaneously from similar locations. As a consequence, various messages representing different spatial phenomena are captured closely to each other, and are at risk to be falsely related in a spatial analysis. Our results reveal indications for corresponding spurious effects when analyzing Twitter data. Further, we show how the outliers distort the range of outcomes of spatial analysis methods. This has significant influence on the power of spatial inferential techniques, and, more generally, on the validity and interpretability of spatial analysis results. We further investigate how the issues caused by topological outliers are composed in detail. We unveil that multiple disturbing effects are acting simultaneously and that these are related to the geographic scales of the involved overlapping patterns. Our results show that at some scale configurations, the disturbances added through overlap are more severe than at others. Further, their behavior turns into a volatile and almost chaotic fluctuation when the scales of the involved patterns become too different. Overall, our results highlight the critical importance of thoroughly considering the specific characteristics of social media data when analyzing them spatially. PMID:27611199

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

PubMed Central

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

2014-01-01

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

Multilevel water governance and problems of scale: setting the stage for a broader debate.

PubMed

Moss, Timothy; Newig, Jens

2010-07-01

Environmental governance and management are facing a multiplicity of challenges related to spatial scales and multiple levels of governance. Water management is a field particularly sensitive to issues of scale because the hydrological system with its different scalar levels from small catchments to large river basins plays such a prominent role. It thus exemplifies fundamental issues and dilemmas of scale in modern environmental management and governance. In this introductory article to an Environmental Management special feature on "Multilevel Water Governance: Coping with Problems of Scale," we delineate our understanding of problems of scale and the dimensions of scalar politics that are central to water resource management. We provide an overview of the contributions to this special feature, concluding with a discussion of how scalar research can usefully challenge conventional wisdom on water resource management. We hope that this discussion of water governance stimulates a broader debate and inquiry relating to the scalar dimensions of environmental governance and management in general.

Scale-dependent intrinsic entropies of complex time series.

PubMed

Yeh, Jia-Rong; Peng, Chung-Kang; Huang, Norden E

2016-04-13

Multi-scale entropy (MSE) was developed as a measure of complexity for complex time series, and it has been applied widely in recent years. The MSE algorithm is based on the assumption that biological systems possess the ability to adapt and function in an ever-changing environment, and these systems need to operate across multiple temporal and spatial scales, such that their complexity is also multi-scale and hierarchical. Here, we present a systematic approach to apply the empirical mode decomposition algorithm, which can detrend time series on various time scales, prior to analysing a signal's complexity by measuring the irregularity of its dynamics on multiple time scales. Simulated time series of fractal Gaussian noise and human heartbeat time series were used to study the performance of this new approach. We show that our method can successfully quantify the fractal properties of the simulated time series and can accurately distinguish modulations in human heartbeat time series in health and disease. © 2016 The Author(s).

Reach-scale channel sensitivity to multiple human activities and natural events: Lower Santa Clara River, California, USA

NASA Astrophysics Data System (ADS)

Downs, Peter W.; Dusterhoff, Scott R.; Sears, William A.

2013-05-01

Understanding the cumulative impact of natural and human influences on the sensitivity of channel morphodynamics, a relative measure between the drivers for change and the magnitude of channel response, requires an approach that accommodates spatial and temporal variability in the suite of primary stressors. Multiple historical data sources were assembled to provide a reach-scale analysis of the lower Santa Clara River (LSCR) in Ventura County, California, USA. Sediment supply is naturally high due to tectonic activity, earthquake-generated landslides, wildfires, and high magnitude flow events during El Niño years. Somewhat typically for the region, the catchment has been subject to four reasonably distinct land use and resource management combinations since European-American settlement. When combined with analysis of channel morphological response (quantifiable since ca. 1930), reach-scale and temporal differences in channel sensitivity become apparent. Downstream reaches have incised on average 2.4 m and become narrower by almost 50% with changes focused in a period of highly sensitive response after about 1950 followed by forced insensitivity caused by structural flood embankments and a significant grade control structure. In contrast, the middle reaches have been responsive but are morphologically resilient, and the upstream reaches show a mildly sensitive aggradational trend. Superimposing the natural and human drivers for change reveals that large scale stressors (related to ranching and irrigation) have been replaced over time by a suite of stressors operating at multiple spatial scales. Lower reaches have been sensitive primarily to 'local' scale impacts (urban growth, flood control, and aggregate mining) whereas, upstream, catchment-scale influences still prevail (including flow regulation and climate-driven sediment supply factors). These factors illustrate the complexity inherent to cumulative impact assessment in fluvial systems, provide evidence for a distinct Anthropocene fluvial response, and underpin the enormity of the challenge faced in trying to sustainably manage and restore rivers.

An Active Fire Temperature Retrieval Model Using Hyperspectral Remote Sensing

NASA Astrophysics Data System (ADS)

Quigley, K. W.; Roberts, D. A.; Miller, D.

2017-12-01

Wildfire is both an important ecological process and a dangerous natural threat that humans face. In situ measurements of wildfire temperature are notoriously difficult to collect due to dangerous conditions. Imaging spectrometry data has the potential to provide some of the most accurate and highest temporally-resolved active fire temperature retrieval information for monitoring and modeling. Recent studies on fire temperature retrieval have used have used Multiple Endmember Spectral Mixture Analysis applied to Airborne Visible applied to Airborne Visible / Infrared Imaging Spectrometer (AVIRIS) bands to model fire temperatures within the regions marked to contain fire, but these methods are less effective at coarser spatial resolutions, as linear mixing methods are degraded by saturation within the pixel. The assumption of a distribution of temperatures within pixels allows us to model pixels with an effective maximum and likely minimum temperature. This assumption allows a more robust approach to modeling temperature at different spatial scales. In this study, instrument-corrected radiance is forward-modeled for different ranges of temperatures, with weighted temperatures from an effective maximum temperature to a likely minimum temperature contributing to the total radiance of the modeled pixel. Effective maximum fire temperature is estimated by minimizing the Root Mean Square Error (RMSE) between modeled and measured fires. The model was tested using AVIRIS collected over the 2016 Sherpa Fire in Santa Barbara County, California,. While only in situ experimentation would be able to confirm active fire temperatures, the fit of the data to modeled radiance can be assessed, as well as the similarity in temperature distributions seen on different spatial resolution scales. Results show that this model improves upon current modeling methods in producing similar effective temperatures on multiple spatial scales as well as a similar modeled area distribution of those temperatures.

Multi-scale responses of soil stability and invasive plants to removal of non-native grazers from an arid conservation reserve

USGS Publications Warehouse

Beever, Erik A.; Huso, Manuela M. P.; Pyke, David A.

2006-01-01

Disturbances and ecosystem recovery from disturbance both involve numerous processes that operate on multiple spatial and temporal scales. Few studies have investigated how gradients of disturbance intensity and ecosystem responses are distributed across multiple spatial resolutions and also how this relationship changes through time during recovery. We investigated how cover of non-native species and soil-aggregate stability (a measure of vulnerability to erosion by water) in surface and subsurface soils varied spatially during grazing by burros and cattle and whether patterns in these variables changed after grazer removal from Mojave National Preserve, California, USA. We compared distance from water and number of ungulate defecations — metrics of longer-term and recent grazing intensity, respectively, — as predictors of our response variables. We used information-theoretic analyses to compare hierarchical linear models that accounted for important covariates and allowed for interannual variation in the disturbance–response relationship at local and landscape scales. Soil stability was greater under perennial vegetation than in bare interspaces, and surface soil stability decreased with increasing numbers of ungulate defecations. Stability of surface samples was more affected by time since removal of grazers than was stability of subsurface samples, and subsurface soil stability in bare spaces was not related to grazing intensity, time since removal, or any of our other predictors. In the high rainfall year (2003) after cattle had been removed for 1–2 years, cover of all non-native plants averaged nine times higher than in the low-rainfall year (2002). Given the heterogeneity in distribution of large-herbivore impacts that we observed at several resolutions, hierarchical analyses provided a more complete understanding of the spatial and temporal complexities of disturbance and recovery processes in arid ecosystems.

A data-model integration approach toward improved understanding on wetland functions and hydrological benefits at the catchment scale

NASA Astrophysics Data System (ADS)

Yeo, I. Y.; Lang, M.; Lee, S.; Huang, C.; Jin, H.; McCarty, G.; Sadeghi, A.

2017-12-01

The wetland ecosystem plays crucial roles in improving hydrological function and ecological integrity for the downstream water and the surrounding landscape. However, changing behaviours and functioning of wetland ecosystems are poorly understood and extremely difficult to characterize. Improved understanding on hydrological behaviours of wetlands, considering their interaction with surrounding landscapes and impacts on downstream waters, is an essential first step toward closing the knowledge gap. We present an integrated wetland-catchment modelling study that capitalizes on recently developed inundation maps and other geospatial data. The aim of the data-model integration is to improve spatial prediction of wetland inundation and evaluate cumulative hydrological benefits at the catchment scale. In this paper, we highlight problems arising from data preparation, parameterization, and process representation in simulating wetlands within a distributed catchment model, and report the recent progress on mapping of wetland dynamics (i.e., inundation) using multiple remotely sensed data. We demonstrate the value of spatially explicit inundation information to develop site-specific wetland parameters and to evaluate model prediction at multi-spatial and temporal scales. This spatial data-model integrated framework is tested using Soil and Water Assessment Tool (SWAT) with improved wetland extension, and applied for an agricultural watershed in the Mid-Atlantic Coastal Plain, USA. This study illustrates necessity of spatially distributed information and a data integrated modelling approach to predict inundation of wetlands and hydrologic function at the local landscape scale, where monitoring and conservation decision making take place.

Soil Bacteria and Fungi Respond on Different Spatial Scales to Invasion by the Legume Lespedeza cuneata.

PubMed

Yannarell, Anthony C; Busby, Ryan R; Denight, Michael L; Gebhart, Dick L; Taylor, Steven J

2011-01-01

The spatial scale on which microbial communities respond to plant invasions may provide important clues as to the nature of potential invader-microbe interactions. Lespedeza cuneata (Dum. Cours.) G. Don is an invasive legume that may benefit from associations with mycorrhizal fungi; however, it has also been suggested that the plant is allelopathic and may alter the soil chemistry of invaded sites through secondary metabolites in its root exudates or litter. Thus, L. cuneata invasion may interact with soil microorganisms on a variety of scales. We investigated L. cuneata-related changes to soil bacterial and fungal communities at two spatial scales using multiple sites from across its invaded N. American range. Using whole-community DNA fingerprinting, we characterized microbial community variation at the scale of entire invaded sites and at the scale of individual plants. Based on permutational multivariate analysis of variance, soil bacterial communities in heavily invaded sites were significantly different from those of uninvaded sites, but bacteria did not show any evidence of responding at very local scales around individual plants. In contrast, soil fungi did not change significantly at the scale of entire sites, but there were significant differences between fungal communities of native versus exotic plants within particular sites. The differential scaling of bacterial and fungal responses indicates that L. cuneata interacts differently with soil bacteria and soil fungi, and these microorganisms may play very different roles in the invasion process of this plant.

Avian movements and wetland connectivity in landscape conservation

USGS Publications Warehouse

Haig, Susan M.; Mehlman, D.W.; Oring, L.W.

1998-01-01

The current conservation crisis calls for research and management to be carried out on a long-term, multi-species basis at large spatial scales. Unfortunately, scientists, managers, and agencies often are stymied in their effort to conduct these large-scale studies because of a lack of appropriate technology, methodology, and funding. This issue is of particular concern in wetland conservation, for which the standard landscape approach may include consideration of a large tract of land but fail to incorporate the suite of wetland sites frequently used by highly mobile organisms such as waterbirds (e.g., shorebirds, wading birds, waterfowl). Typically, these species have population dynamics that require use of multiple wetlands, but this aspect of their life history has often been ignored in planning for their conservation. We outline theoretical, empirical, modeling, and planning problems associated with this issue and suggest solutions to some current obstacles. These solutions represent a tradeoff between typical in-depth single-species studies and more generic multi-species studies. They include studying within- and among-season movements of waterbirds on a spatial scale appropriate to both widely dispersing and more stationary species; multi-species censuses at multiple sites; further development and use of technology such as satellite transmitters and population-specific molecular markers; development of spatially explicit population models that consider within-season movements of waterbirds; and recognition from funding agencies that landscape-level issues cannot adequately be addressed without support for these types of studies.

Hadoop-GIS: A High Performance Spatial Data Warehousing System over MapReduce.

PubMed

Aji, Ablimit; Wang, Fusheng; Vo, Hoang; Lee, Rubao; Liu, Qiaoling; Zhang, Xiaodong; Saltz, Joel

2013-08-01

Support of high performance queries on large volumes of spatial data becomes increasingly important in many application domains, including geospatial problems in numerous fields, location based services, and emerging scientific applications that are increasingly data- and compute-intensive. The emergence of massive scale spatial data is due to the proliferation of cost effective and ubiquitous positioning technologies, development of high resolution imaging technologies, and contribution from a large number of community users. There are two major challenges for managing and querying massive spatial data to support spatial queries: the explosion of spatial data, and the high computational complexity of spatial queries. In this paper, we present Hadoop-GIS - a scalable and high performance spatial data warehousing system for running large scale spatial queries on Hadoop. Hadoop-GIS supports multiple types of spatial queries on MapReduce through spatial partitioning, customizable spatial query engine RESQUE, implicit parallel spatial query execution on MapReduce, and effective methods for amending query results through handling boundary objects. Hadoop-GIS utilizes global partition indexing and customizable on demand local spatial indexing to achieve efficient query processing. Hadoop-GIS is integrated into Hive to support declarative spatial queries with an integrated architecture. Our experiments have demonstrated the high efficiency of Hadoop-GIS on query response and high scalability to run on commodity clusters. Our comparative experiments have showed that performance of Hadoop-GIS is on par with parallel SDBMS and outperforms SDBMS for compute-intensive queries. Hadoop-GIS is available as a set of library for processing spatial queries, and as an integrated software package in Hive.

Hadoop-GIS: A High Performance Spatial Data Warehousing System over MapReduce

PubMed Central

Aji, Ablimit; Wang, Fusheng; Vo, Hoang; Lee, Rubao; Liu, Qiaoling; Zhang, Xiaodong; Saltz, Joel

2013-01-01

Support of high performance queries on large volumes of spatial data becomes increasingly important in many application domains, including geospatial problems in numerous fields, location based services, and emerging scientific applications that are increasingly data- and compute-intensive. The emergence of massive scale spatial data is due to the proliferation of cost effective and ubiquitous positioning technologies, development of high resolution imaging technologies, and contribution from a large number of community users. There are two major challenges for managing and querying massive spatial data to support spatial queries: the explosion of spatial data, and the high computational complexity of spatial queries. In this paper, we present Hadoop-GIS – a scalable and high performance spatial data warehousing system for running large scale spatial queries on Hadoop. Hadoop-GIS supports multiple types of spatial queries on MapReduce through spatial partitioning, customizable spatial query engine RESQUE, implicit parallel spatial query execution on MapReduce, and effective methods for amending query results through handling boundary objects. Hadoop-GIS utilizes global partition indexing and customizable on demand local spatial indexing to achieve efficient query processing. Hadoop-GIS is integrated into Hive to support declarative spatial queries with an integrated architecture. Our experiments have demonstrated the high efficiency of Hadoop-GIS on query response and high scalability to run on commodity clusters. Our comparative experiments have showed that performance of Hadoop-GIS is on par with parallel SDBMS and outperforms SDBMS for compute-intensive queries. Hadoop-GIS is available as a set of library for processing spatial queries, and as an integrated software package in Hive. PMID:24187650

Spatial organization of a model 15-member human gut microbiota established in gnotobiotic mice

PubMed Central

Mark Welch, Jessica L.; Hasegawa, Yuko; McNulty, Nathan P.; Gordon, Jeffrey I.; Borisy, Gary G.

2017-01-01

Knowledge of the spatial organization of the gut microbiota is important for understanding the physical and molecular interactions among its members. These interactions are thought to influence microbial succession, community stability, syntrophic relationships, and resiliency in the face of perturbations. The complexity and dynamism of the gut microbiota pose considerable challenges for quantitative analysis of its spatial organization. Here, we illustrate an approach for addressing this challenge, using (i) a model, defined 15-member consortium of phylogenetically diverse, sequenced human gut bacterial strains introduced into adult gnotobiotic mice fed a polysaccharide-rich diet, and (ii) in situ hybridization and spectral imaging analysis methods that allow simultaneous detection of multiple bacterial strains at multiple spatial scales. Differences in the binding affinities of strains for substrates such as mucus or food particles, combined with more rapid replication in a preferred microhabitat, could, in principle, lead to localized clonally expanded aggregates composed of one or a few taxa. However, our results reveal a colonic community that is mixed at micrometer scales, with distinct spatial distributions of some taxa relative to one another, notably at the border between the mucosa and the lumen. Our data suggest that lumen and mucosa in the proximal colon should be conceptualized not as stratified compartments but as components of an incompletely mixed bioreactor. Employing the experimental approaches described should allow direct tests of whether and how specified host and microbial factors influence the nature and functional contributions of “microscale” mixing to the dynamic operations of the microbiota in health and disease. PMID:29073107

Geovisual analytics to enhance spatial scan statistic interpretation: an analysis of U.S. cervical cancer mortality

PubMed Central

Chen, Jin; Roth, Robert E; Naito, Adam T; Lengerich, Eugene J; MacEachren, Alan M

2008-01-01

Background Kulldorff's spatial scan statistic and its software implementation – SaTScan – are widely used for detecting and evaluating geographic clusters. However, two issues make using the method and interpreting its results non-trivial: (1) the method lacks cartographic support for understanding the clusters in geographic context and (2) results from the method are sensitive to parameter choices related to cluster scaling (abbreviated as scaling parameters), but the system provides no direct support for making these choices. We employ both established and novel geovisual analytics methods to address these issues and to enhance the interpretation of SaTScan results. We demonstrate our geovisual analytics approach in a case study analysis of cervical cancer mortality in the U.S. Results We address the first issue by providing an interactive visual interface to support the interpretation of SaTScan results. Our research to address the second issue prompted a broader discussion about the sensitivity of SaTScan results to parameter choices. Sensitivity has two components: (1) the method can identify clusters that, while being statistically significant, have heterogeneous contents comprised of both high-risk and low-risk locations and (2) the method can identify clusters that are unstable in location and size as the spatial scan scaling parameter is varied. To investigate cluster result stability, we conducted multiple SaTScan runs with systematically selected parameters. The results, when scanning a large spatial dataset (e.g., U.S. data aggregated by county), demonstrate that no single spatial scan scaling value is known to be optimal to identify clusters that exist at different scales; instead, multiple scans that vary the parameters are necessary. We introduce a novel method of measuring and visualizing reliability that facilitates identification of homogeneous clusters that are stable across analysis scales. Finally, we propose a logical approach to proceed through the analysis of SaTScan results. Conclusion The geovisual analytics approach described in this manuscript facilitates the interpretation of spatial cluster detection methods by providing cartographic representation of SaTScan results and by providing visualization methods and tools that support selection of SaTScan parameters. Our methods distinguish between heterogeneous and homogeneous clusters and assess the stability of clusters across analytic scales. Method We analyzed the cervical cancer mortality data for the United States aggregated by county between 2000 and 2004. We ran SaTScan on the dataset fifty times with different parameter choices. Our geovisual analytics approach couples SaTScan with our visual analytic platform, allowing users to interactively explore and compare SaTScan results produced by different parameter choices. The Standardized Mortality Ratio and reliability scores are visualized for all the counties to identify stable, homogeneous clusters. We evaluated our analysis result by comparing it to that produced by other independent techniques including the Empirical Bayes Smoothing and Kafadar spatial smoother methods. The geovisual analytics approach introduced here is developed and implemented in our Java-based Visual Inquiry Toolkit. PMID:18992163

Geovisual analytics to enhance spatial scan statistic interpretation: an analysis of U.S. cervical cancer mortality.

PubMed

Chen, Jin; Roth, Robert E; Naito, Adam T; Lengerich, Eugene J; Maceachren, Alan M

2008-11-07

Kulldorff's spatial scan statistic and its software implementation - SaTScan - are widely used for detecting and evaluating geographic clusters. However, two issues make using the method and interpreting its results non-trivial: (1) the method lacks cartographic support for understanding the clusters in geographic context and (2) results from the method are sensitive to parameter choices related to cluster scaling (abbreviated as scaling parameters), but the system provides no direct support for making these choices. We employ both established and novel geovisual analytics methods to address these issues and to enhance the interpretation of SaTScan results. We demonstrate our geovisual analytics approach in a case study analysis of cervical cancer mortality in the U.S. We address the first issue by providing an interactive visual interface to support the interpretation of SaTScan results. Our research to address the second issue prompted a broader discussion about the sensitivity of SaTScan results to parameter choices. Sensitivity has two components: (1) the method can identify clusters that, while being statistically significant, have heterogeneous contents comprised of both high-risk and low-risk locations and (2) the method can identify clusters that are unstable in location and size as the spatial scan scaling parameter is varied. To investigate cluster result stability, we conducted multiple SaTScan runs with systematically selected parameters. The results, when scanning a large spatial dataset (e.g., U.S. data aggregated by county), demonstrate that no single spatial scan scaling value is known to be optimal to identify clusters that exist at different scales; instead, multiple scans that vary the parameters are necessary. We introduce a novel method of measuring and visualizing reliability that facilitates identification of homogeneous clusters that are stable across analysis scales. Finally, we propose a logical approach to proceed through the analysis of SaTScan results. The geovisual analytics approach described in this manuscript facilitates the interpretation of spatial cluster detection methods by providing cartographic representation of SaTScan results and by providing visualization methods and tools that support selection of SaTScan parameters. Our methods distinguish between heterogeneous and homogeneous clusters and assess the stability of clusters across analytic scales. We analyzed the cervical cancer mortality data for the United States aggregated by county between 2000 and 2004. We ran SaTScan on the dataset fifty times with different parameter choices. Our geovisual analytics approach couples SaTScan with our visual analytic platform, allowing users to interactively explore and compare SaTScan results produced by different parameter choices. The Standardized Mortality Ratio and reliability scores are visualized for all the counties to identify stable, homogeneous clusters. We evaluated our analysis result by comparing it to that produced by other independent techniques including the Empirical Bayes Smoothing and Kafadar spatial smoother methods. The geovisual analytics approach introduced here is developed and implemented in our Java-based Visual Inquiry Toolkit.

Time takes space: selective effects of multitasking on concurrent spatial processing.

PubMed

Mäntylä, Timo; Coni, Valentina; Kubik, Veit; Todorov, Ivo; Del Missier, Fabio

2017-08-01

Many everyday activities require coordination and monitoring of complex relations of future goals and deadlines. Cognitive offloading may provide an efficient strategy for reducing control demands by representing future goals and deadlines as a pattern of spatial relations. We tested the hypothesis that multiple-task monitoring involves time-to-space transformational processes, and that these spatial effects are selective with greater demands on coordinate (metric) than categorical (nonmetric) spatial relation processing. Participants completed a multitasking session in which they monitored four series of deadlines, running on different time scales, while making concurrent coordinate or categorical spatial judgments. We expected and found that multitasking taxes concurrent coordinate, but not categorical, spatial processing. Furthermore, males showed a better multitasking performance than females. These findings provide novel experimental evidence for the hypothesis that efficient multitasking involves metric relational processing.

Disentangling the pathways of land use impacts on the functional structure of fish assemblages in Amazon streams

EPA Science Inventory

Agricultural land use is a primary driver of environmental impacts on streams. However, the causal processes that shape these impacts operate through multiple pathways and at several spatial scales. This complexity undermines the development of more effective management approache...

GLOBAL ASSESSMENT OF WASTEWATER IRRIGATION: UNDERSTANDING HEALTH RISKS AND CONTRIBUTIONS TO FOOD SECURITY USING AN ENVIRONMENTAL SYSTEMS APPROACH

EPA Science Inventory

This research will quantify the extent of de facto reuse of untreated wastewater at the global scale. Through the integration of multiple existing spatial data sources, this project will produce rigorous analyses assessing the relationship between wastewater irrigation, hea...

An Integrative Approach to Ecosystem Goods and Services – Putting the Pieces Together for the Tampa Bay Region

EPA Science Inventory

Ecosystem goods and services production, delivery, and use by humans involve multiple systems working together at various different spatial and temporal scales. Assessments of ecosystem goods and services and their benefits to current and or future human populations in any given ...

A Macroecological Approach to Forecasting Fisheries Services: How much Energy Does it Take to Catch a Fish?

EPA Science Inventory

The U.S. Environmental Protection Agency is currently developing methods to quantify freshwater fisheries services (e.g., standing-stock abundance and/or biomass) at multiple spatial scales, and to forecast their future distributions. One approach uses linked, ecosystem process ...

Chapter 6: Managing forests for wildlife communities

Treesearch

M North; P. Manley

2012-01-01

Forest management to maintain native wildlife communities is an important, yet complex objective. The complexities stem from two primary sources: habitat requirements for native species are diverse and span multiple spatial scales and seral stages, and habitat is a species-specific concept making multispecies community response difficult to predict. Given these...

ACCURACY OF THE 1992 NATIONAL LAND COVER DATASET AREA ESTIMATES: AN ANALYSIS AT MULTIPLE SPATIAL EXTENTS

EPA Science Inventory

Abstract for poster presentation:

Site-specific accuracy assessments evaluate fine-scale accuracy of land-use/land-cover(LULC) datasets but provide little insight into accuracy of area estimates of LULC

classes derived from sampling units of varying size. Additiona...

COMBINING EVIDENCE ON AIR POLLUTION AND DAILY MORTALITY FROM 20 LARGEST U.S. CITIES: A HIERARCHICAL MODELING STRATEGY

EPA Science Inventory

Environmental science and management are fed by individual studies of pollution effects, often focused on single locations. Data are encountered data, typically from multiple sources and on different time and spatial scales. Statistical issues including publication bias and m...

Nitrogen mineralization in riparian soils along a river continuum within a multi-landuse basin

EPA Science Inventory

Nitrogen dynamics in riparian systems are often addressed within one landuse type and are rarely studied on watershed scales involving multiple land uses. This study tested for both temporal trends and watershed-wide spatial patterns in N mineralization and identified site fact...

LFNet: A Novel Bidirectional Recurrent Convolutional Neural Network for Light-Field Image Super-Resolution.

PubMed

Wang, Yunlong; Liu, Fei; Zhang, Kunbo; Hou, Guangqi; Sun, Zhenan; Tan, Tieniu

2018-09-01

The low spatial resolution of light-field image poses significant difficulties in exploiting its advantage. To mitigate the dependency of accurate depth or disparity information as priors for light-field image super-resolution, we propose an implicitly multi-scale fusion scheme to accumulate contextual information from multiple scales for super-resolution reconstruction. The implicitly multi-scale fusion scheme is then incorporated into bidirectional recurrent convolutional neural network, which aims to iteratively model spatial relations between horizontally or vertically adjacent sub-aperture images of light-field data. Within the network, the recurrent convolutions are modified to be more effective and flexible in modeling the spatial correlations between neighboring views. A horizontal sub-network and a vertical sub-network of the same network structure are ensembled for final outputs via stacked generalization. Experimental results on synthetic and real-world data sets demonstrate that the proposed method outperforms other state-of-the-art methods by a large margin in peak signal-to-noise ratio and gray-scale structural similarity indexes, which also achieves superior quality for human visual systems. Furthermore, the proposed method can enhance the performance of light field applications such as depth estimation.

Temporal and spatial scaling of the genetic structure of a vector-borne plant pathogen.

PubMed

Coletta-Filho, Helvécio D; Francisco, Carolina S; Almeida, Rodrigo P P

2014-02-01

The ecology of plant pathogens of perennial crops is affected by the long-lived nature of their immobile hosts. In addition, changes to the genetic structure of pathogen populations may affect disease epidemiology and management practices; examples include local adaptation of more fit genotypes or introduction of novel genotypes from geographically distant areas via human movement of infected plant material or insect vectors. We studied the genetic structure of Xylella fastidiosa populations causing disease in sweet orange plants in Brazil at multiple scales using fast-evolving molecular markers (simple-sequence DNA repeats). Results show that populations of X. fastidiosa were regionally isolated, and that isolation was maintained for populations analyzed a decade apart from each other. However, despite such geographic isolation, local populations present in year 2000 were largely replaced by novel genotypes in 2009 but not as a result of migration. At a smaller spatial scale (individual trees), results suggest that isolates within plants originated from a shared common ancestor. In summary, new insights on the ecology of this economically important plant pathogen were obtained by sampling populations at different spatial scales and two different time points.

Exploring the limits to energy scaling and distant-target delivery of high-intensity midinfrared pulses

NASA Astrophysics Data System (ADS)

Panagiotopoulos, Paris; Kolesik, Miroslav; Moloney, Jerome V.

2016-09-01

We numerically investigate the scaling behavior of midinfrared filaments at extremely high input energies. It is shown that, given sufficient power, kilometer-scale, low-loss atmospheric filamentation is attainable by prechirping the pulse. Fully resolved four-dimensional (x y z t ) simulations show that, while in a spatially imperfect beam the modulation instability can lead to multiple hot-spot formation, the individual filaments are still stabilized by the recently proposed mechanism that relies on the temporal walk-off of short-wavelength radiation.

Multi-scale assimilation of remotely sensed snow observations for hydrologic estimation

NASA Astrophysics Data System (ADS)

Andreadis, K.; Lettenmaier, D.

2008-12-01

Data assimilation provides a framework for optimally merging model predictions and remote sensing observations of snow properties (snow cover extent, water equivalent, grain size, melt state), ideally overcoming limitations of both. A synthetic twin experiment is used to evaluate a data assimilation system that would ingest remotely sensed observations from passive microwave and visible wavelength sensors (brightness temperature and snow cover extent derived products, respectively) with the objective of estimating snow water equivalent. Two data assimilation techniques are used, the Ensemble Kalman filter and the Ensemble Multiscale Kalman filter (EnMKF). One of the challenges inherent in such a data assimilation system is the discrepancy in spatial scales between the different types of snow-related observations. The EnMKF represents the sample model error covariance with a tree that relates the system state variables at different locations and scales through a set of parent-child relationships. This provides an attractive framework to efficiently assimilate observations at different spatial scales. This study provides a first assessment of the feasibility of a system that would assimilate observations from multiple sensors (MODIS snow cover and AMSR-E brightness temperatures) and at different spatial scales for snow water equivalent estimation. The relative value of the different types of observations is examined. Additionally, the error characteristics of both model and observations are discussed.

Spatial and Temporal Variability in Biogenic Gas Accumulation and Release in The Greater Everglades at Multiple Scales of Measurement

NASA Astrophysics Data System (ADS)

McClellan, M. D.; Cornett, C.; Schaffer, L.; Comas, X.

2017-12-01

Wetlands play a critical role in the carbon (C) cycle by producing and releasing significant amounts of greenhouse biogenic gasses (CO2, CH4) into the atmosphere. Wetlands in tropical and subtropical climates (such as the Florida Everglades) have become of great interest in the past two decades as they account for more than 20% of the global peatland C stock and are located in climates that favor year-round C emissions. Despite the increase in research involving C emission from these types of wetlands, the spatial and temporal variability involving C production, accumulation and release is still highly uncertain, and is the focus of this research at multiple scales of measurement (i.e. lab, field and landscape). Spatial variability in biogenic gas content, build up and release, at both the lab and field scales, was estimated using a series of ground penetrating radar (GPR) surveys constrained with gas traps fitted with time-lapse cameras. Variability in gas content was estimated at the sub-meter scale (lab scale) within two extracted monoliths from different wetland ecosystems at the Disney wilderness Preserve (DWP) and the Blue Cypress Preserve (BCP) using high frequency GPR (1.2 GHz) transects across the monoliths. At the field scale (> 10m) changes in biogenic gas content were estimated using 160 MHz GPR surveys collected within 4 different emergent wetlands at the DWP. Additionally, biogenic gas content from the extracted monoliths was used to developed a landscape comparison of C accumulation and emissions for each different wetland ecosystem. Changes in gas content over time were estimated at the lab scale at high temporal resolution (i.e. sub-hourly) in monoliths from the BCP and Water Conservation Area 1-A. An autonomous rail system was constructed to estimate biogenic gas content variability within the wetland soil matrix using a series of continuous, uninterrupted 1.2 GHz GPR transects along the samples. Measurements were again constrained with an array of gas traps fitted with time-lapse cameras. This research seeks to better understand the spatial and temporal variability of biogenic gas content within wetlands from the Greater Everglades Watershed. Such understanding may help to identify potential hotspots (both in space and time) and their implication for the flux estimates used as input in climate models.

Spatial-temporal consistency between gross primary productivity and solar-induced chlorophyll fluorescence of vegetation in China during 2007-2014.

PubMed

Ma, Jun; Xiao, Xiangming; Zhang, Yao; Doughty, Russell; Chen, Bangqian; Zhao, Bin

2018-10-15

Accurately estimating spatial-temporal patterns of gross primary production (GPP) is important for the global carbon cycle. Satellite-based light use efficiency (LUE) models are regarded as an efficient tool in simulating spatial-temporal dynamics of GPP. However, the accuracy assessment of GPP simulations from LUE models at both spatial and temporal scales remains a challenge. In this study, we simulated GPP of vegetation in China during 2007-2014 using a LUE model (Vegetation Photosynthesis Model, VPM) based on MODIS (moderate-resolution imaging spectroradiometer) images with 8-day temporal and 500-m spatial resolutions and NCEP (National Center for Environmental Prediction) climate data. Global Ozone Monitoring Instrument 2 (GOME-2) solar-induced chlorophyll fluorescence (SIF) data were used to compare with VPM simulated GPP (GPP VPM ) temporally and spatially using linear correlation analysis. Significant positive linear correlations exist between monthly GPP VPM and SIF data over a single year (2010) and multiple years (2007-2014) in most areas of China. GPP VPM is also significantly positive correlated with GOME-2 SIF (R 2  > 0.43) spatially for seasonal scales. However, poor consistency was detected between GPP VPM and SIF data at yearly scale. GPP dynamic trends have high spatial-temporal variation in China during 2007-2014. Temperature, leaf area index (LAI), and precipitation are the most important factors influence GPP VPM in the regions of East Qinghai-Tibet Plateau, Loss Plateau, and Southwestern China, respectively. The results of this study indicate that GPP VPM is temporally and spatially in line with GOME-2 SIF data, and space-borne SIF data have great potential for evaluating LUE-based GPP models. Copyright © 2018 Elsevier B.V. All rights reserved.

Characterizing riverbed sediment using high-frequency acoustics 1: spectral properties of scattering

USGS Publications Warehouse

Buscombe, Daniel D.; Grams, Paul E.; Kaplinski, Matt A.

2014-01-01

Bed-sediment classification using high-frequency hydro-acoustic instruments is challenging when sediments are spatially heterogeneous, which is often the case in rivers. The use of acoustic backscatter to classify sediments is an attractive alternative to analysis of topography because it is potentially sensitive to grain-scale roughness. Here, a new method is presented which uses high-frequency acoustic backscatter from multibeam sonar to classify heterogeneous riverbed sediments by type (sand, gravel,rock) continuously in space and at small spatial resolution. In this, the first of a pair of papers that examine the scattering signatures from a heterogeneous riverbed, methods are presented to construct spatially explicit maps of spectral properties from geo-referenced point clouds of geometrically and radiometrically corrected echoes. Backscatter power spectra are computed to produce scale and amplitude metrics that collectively characterize the length scales of stochastic measures of riverbed scattering, termed ‘stochastic geometries’. Backscatter aggregated over small spatial scales have spectra that obey a power-law. This apparently self-affine behavior could instead arise from morphological- and grain-scale roughnesses over multiple overlapping scales, or riverbed scattering being transitional between Rayleigh and geometric regimes. Relationships exist between stochastic geometries of backscatter and areas of rough and smooth sediments. However, no one parameter can uniquely characterize a particular substrate, nor definitively separate the relative contributions of roughness and acoustic impedance (hardness). Combinations of spectral quantities do, however, have the potential to delineate riverbed sediment patchiness, in a data-driven approach comparing backscatter with bed-sediment observations (which is the subject of part two of this manuscript).

Multiscale patterns and drivers of arbuscular mycorrhizal fungal communities in the roots and root-associated soil of a wild perennial herb.

PubMed

Rasmussen, Pil U; Hugerth, Luisa W; Blanchet, F Guillaume; Andersson, Anders F; Lindahl, Björn D; Tack, Ayco J M

2018-03-24

Arbuscular mycorrhizal (AM) fungi form diverse communities and are known to influence above-ground community dynamics and biodiversity. However, the multiscale patterns and drivers of AM fungal composition and diversity are still poorly understood. We sequenced DNA markers from roots and root-associated soil from Plantago lanceolata plants collected across multiple spatial scales to allow comparison of AM fungal communities among neighbouring plants, plant subpopulations, nearby plant populations, and regions. We also measured soil nutrients, temperature, humidity, and community composition of neighbouring plants and nonAM root-associated fungi. AM fungal communities were already highly dissimilar among neighbouring plants (c. 30 cm apart), albeit with a high variation in the degree of similarity at this small spatial scale. AM fungal communities were increasingly, and more consistently, dissimilar at larger spatial scales. Spatial structure and environmental drivers explained a similar percentage of the variation, from 7% to 25%. A large fraction of the variation remained unexplained, which may be a result of unmeasured environmental variables, species interactions and stochastic processes. We conclude that AM fungal communities are highly variable among nearby plants. AM fungi may therefore play a major role in maintaining small-scale variation in community dynamics and biodiversity. © 2018 The Authors New Phytologist © 2018 New Phytologist Trust.

A field comparison of multiple techniques to quantify groundwater - surface-water interactions

USGS Publications Warehouse

González-Pinzón, Ricardo; Ward, Adam S; Hatch, Christine E; Wlostowski, Adam N; Singha, Kamini; Gooseff, Michael N.; Haggerty, Roy; Harvey, Judson; Cirpka, Olaf A; Brock, James T

2015-01-01

Groundwater–surface-water (GW-SW) interactions in streams are difficult to quantify because of heterogeneity in hydraulic and reactive processes across a range of spatial and temporal scales. The challenge of quantifying these interactions has led to the development of several techniques, from centimeter-scale probes to whole-system tracers, including chemical, thermal, and electrical methods. We co-applied conservative and smart reactive solute-tracer tests, measurement of hydraulic heads, distributed temperature sensing, vertical profiles of solute tracer and temperature in the stream bed, and electrical resistivity imaging in a 450-m reach of a 3rd-order stream. GW-SW interactions were not spatially expansive, but were high in flux through a shallow hyporheic zone surrounding the reach. NaCl and resazurin tracers suggested different surface–subsurface exchange patterns in the upper ⅔ and lower ⅓ of the reach. Subsurface sampling of tracers and vertical thermal profiles quantified relatively high fluxes through a 10- to 20-cm deep hyporheic zone with chemical reactivity of the resazurin tracer indicated at 3-, 6-, and 9-cm sampling depths. Monitoring of hydraulic gradients along transects with MINIPOINT streambed samplers starting ∼40 m from the stream indicated that groundwater discharge prevented development of a larger hyporheic zone, which progressively decreased from the stream thalweg toward the banks. Distributed temperature sensing did not detect extensive inflow of ground water to the stream, and electrical resistivity imaging showed limited large-scale hyporheic exchange. We recommend choosing technique(s) based on: 1) clear definition of the questions to be addressed (physical, biological, or chemical processes), 2) explicit identification of the spatial and temporal scales to be covered and those required to provide an appropriate context for interpretation, and 3) maximizing generation of mechanistic understanding and reducing costs of implementing multiple techniques through collaborative research.

Driving magnetic turbulence using flux ropes in a moderate guide field linear system

NASA Astrophysics Data System (ADS)

Brookhart, Matthew I.; Stemo, Aaron; Waleffe, Roger; Forest, Cary B.

2017-12-01

We present a series of experiments on novel, line-tied plasma geometries as a study of the generation of chaos and turbulence in line-tied systems. Plasma production and the injection scale for magnetic energy is provided by spatially discrete plasma guns that inject both plasma and current. The guns represent a technique for controlling the injection scale of magnetic energy. A two-dimensional (2-D) array of magnetic probes provides spatially resolved time histories of the magnetic fluctuations at a single cross-section of the experimental cylinder, allowing simultaneous spatial measurements of chaotic and turbulent behaviour. The first experiment shows chaotic fluctuations and self-organization in a hollow-current line-tied screw pinch. These dynamics is modulated primarily by the applied magnetic field and weakly by the plasma current and safety factor. The second experiment analyses the interactions of multiple line-tied flux ropes. The flux ropes all exhibit chaotic behaviour, and under certain conditions develop an inverse cascade to larger scales and a turbulent inertial range with magnetic energy ( ) related to perpendicular wave number ( \\bot $ ) as \\bot -2.5\\pm 0.5$ .

Remote-sensing supported monitoring of global biodiversity change

NASA Astrophysics Data System (ADS)

Jetz, W.; Tuanmu, M. N.; W, A.; Melton, F. S.; Parmentier, B.; Amatulli, G.; Guzman, A.

2016-12-01

Remote sensing combined with biodiversity observation offers an unrivalled tool for understanding and predicting species distributions and their changes at the planetary scale. I will illustrate recently developed high-resolution remote-sensing based layers targeted for spatiotemporal biodiversity modeling, addressing climate, environment, topography, and habitat heterogeneity. In particular, I will illustrate the development and use of global MODIS-derived environmental layers for biodiversity assessment and change monitoring. Remote-sensing based capture of these putative predictors of biodiversity dynamics provides more a reliable signal than spatially interpolated layers and avoids inflated spatial autocorrelation. The layers result in more accurate models of species occurrence and are more readily able to address the scale of processes underpinning species distributions, e.g. when combined with emerging hierarchical, cross-scale models. I illustrate the multiple ways in which this type of information, based on continuously collected data, supports the prediction of not just spatial but also temporal variation in biodiversity. Using implementations in the Map of Life infrastructure I will showcase new indicators of species distribution and change that demonstrate these new opportunities.

Characterizing Urban Air Quality to Provide Actionable Information

NASA Astrophysics Data System (ADS)

Lary, D. J.

2017-12-01

The urbanization of national and global populations is associated with increasing challenges to creation of sustainable and livable communities. In urban environments, there is currently a lack of accurate actionable information on atmospheric composition on fine spatial and temporal scales. There is a pressing need to better characterize the complex spatial distribution of environmental features of cityscapes and improve understanding of their relationship to health and quality of life. This talk gives an overview of integrating sensing of atmospheric composition on multiple scales using a wide range of devices from distributed low cost-sensors, to aerial vehicles, to satellites. Machine learning plays a key role in providing both the cross-calibration and turning the exposure dosimetry into actionable insights for urban environments.

Gray scale operation of a multichannel optical convolver using the Semetex magnetooptic spatial light modulator

NASA Technical Reports Server (NTRS)

Davis, Jeffrey A.; Day, Timothy; Lilly, Roger A.; Taber, Donald B.; Liu, Hua-Kuang

1988-01-01

A new multichannel optical correlator/convolver architecture which uses an acoustooptic light modulator for the input channel and a Semetex magnetooptic spatial light modulator (MOSLM) for the set of parallel reference channels is presented. Details of the anamorphic optical system are discussed. Experimental results illustrate the use of the system as a convolver for performing digital multiplication by analog convolution (DMAC). A limited gray scale capability for data stored by the MOSLM is demonstrated by implementing this DMAC algorithm with trinary logic. Use of the MOSLM allows the number of parallel channels for the convolver to be increased significantly compared with previously reported techniques while retaining the capability for updating both channels at high speeds.

Gray Scale Operation Of A Multichannel Optical Convolver Using The Semetex Magnetooptic Spatial Light Modulator

NASA Astrophysics Data System (ADS)

Davis, Jeffrey A.; Day, Timothy; Lilly, Roger A.; Taber, Donald B.; Liu, Hua-Kuang; Davis, J. A.; Day, T.; Lilly, R. A.; Taber, D. B.; Liu, H.-K.

1988-02-01

We present a new multichannel optical correlator/convolver architecture which uses an acoustooptic light modulator (AOLM) for the input channel and a Semetex magnetooptic spatial light modulator (MOSLM) for the set of parallel reference channels. Details of the anamorphic optical system are discussed. Experimental results illustrate use of the system as a convolver for performing digital multiplication by analog convolution (DMAC). A limited gray scale capability for data stored by the MOSLM is demonstrated by implementing this DMAC algorithm with trinary logic. Use of the MOSLM allows the number of parallel channels for the convolver to be increased significantly compared with previously reported techniques while retaining the capability for updating both channels at high speeds.

Gray scale operation of a multichannel optical convolver using the Semetex magnetooptic spatial light modulator

NASA Astrophysics Data System (ADS)

Davis, Jeffrey A.; Day, Timothy; Lilly, Roger A.; Taber, Donald B.; Liu, Hua-Kuang

A new multichannel optical correlator/convolver architecture which uses an acoustooptic light modulator for the input channel and a Semetex magnetooptic spatial light modulator (MOSLM) for the set of parallel reference channels is presented. Details of the anamorphic optical system are discussed. Experimental results illustrate the use of the system as a convolver for performing digital multiplication by analog convolution (DMAC). A limited gray scale capability for data stored by the MOSLM is demonstrated by implementing this DMAC algorithm with trinary logic. Use of the MOSLM allows the number of parallel channels for the convolver to be increased significantly compared with previously reported techniques while retaining the capability for updating both channels at high speeds.

An optimal merging technique for high-resolution precipitation products: OPTIMAL MERGING OF PRECIPITATION METHOD

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

Shrestha, Roshan; Houser, Paul R.; Anantharaj, Valentine G.

2011-04-01

Precipitation products are currently available from various sources at higher spatial and temporal resolution than any time in the past. Each of the precipitation products has its strengths and weaknesses in availability, accuracy, resolution, retrieval techniques and quality control. By merging the precipitation data obtained from multiple sources, one can improve its information content by minimizing these issues. However, precipitation data merging poses challenges of scale-mismatch, and accurate error and bias assessment. In this paper we present Optimal Merging of Precipitation (OMP), a new method to merge precipitation data from multiple sources that are of different spatial and temporal resolutionsmore » and accuracies. This method is a combination of scale conversion and merging weight optimization, involving performance-tracing based on Bayesian statistics and trend-analysis, which yields merging weights for each precipitation data source. The weights are optimized at multiple scales to facilitate multiscale merging and better precipitation downscaling. Precipitation data used in the experiment include products from the 12-km resolution North American Land Data Assimilation (NLDAS) system, the 8-km resolution CMORPH and the 4-km resolution National Stage-IV QPE. The test cases demonstrate that the OMP method is capable of identifying a better data source and allocating a higher priority for them in the merging procedure, dynamically over the region and time period. This method is also effective in filtering out poor quality data introduced into the merging process.« less

Modelling habitat associations with fingernail clam (Family: Sphaeriidae) counts at multiple spatial scales using hierarchical count models

USGS Publications Warehouse

Gray, B.R.; Haro, R.J.; Rogala, J.T.; Sauer, J.S.

2005-01-01

1. Macroinvertebrate count data often exhibit nested or hierarchical structure. Examples include multiple measurements along each of a set of streams, and multiple synoptic measurements from each of a set of ponds. With data exhibiting hierarchical structure, outcomes at both sampling (e.g. Within stream) and aggregated (e.g. Stream) scales are often of interest. Unfortunately, methods for modelling hierarchical count data have received little attention in the ecological literature. 2. We demonstrate the use of hierarchical count models using fingernail clam (Family: Sphaeriidae) count data and habitat predictors derived from sampling and aggregated spatial scales. The sampling scale corresponded to that of a standard Ponar grab (0.052 m(2)) and the aggregated scale to impounded and backwater regions within 38-197 km reaches of the Upper Mississippi River. Impounded and backwater regions were resampled annually for 10 years. Consequently, measurements on clams were nested within years. Counts were treated as negative binomial random variates, and means from each resampling event as random departures from the impounded and backwater region grand means. 3. Clam models were improved by the addition of covariates that varied at both the sampling and regional scales. Substrate composition varied at the sampling scale and was associated with model improvements, and reductions (for a given mean) in variance at the sampling scale. Inorganic suspended solids (ISS) levels, measured in the summer preceding sampling, also yielded model improvements and were associated with reductions in variances at the regional rather than sampling scales. ISS levels were negatively associated with mean clam counts. 4. Hierarchical models allow hierarchically structured data to be modelled without ignoring information specific to levels of the hierarchy. In addition, information at each hierarchical level may be modelled as functions of covariates that themselves vary by and within levels. As a result, hierarchical models provide researchers and resource managers with a method for modelling hierarchical data that explicitly recognises both the sampling design and the information contained in the corresponding data.

Linking Pattern Formation and Alternative Stable States: Ecohydrologic Thresholds and Critical Transitions in the Everglades Peatlands

NASA Astrophysics Data System (ADS)

Heffernan, J. B.; Ross, M. S.; Sah, J. P.; Isherwood, E.; Cohen, M. J.

2015-12-01

Spatial patterning occurs in a variety of ecosystems, and is important for the functional properties of landscapes; for testing spatial models of ecological processes; and as an indicator of landscape condition and resilience. Theory suggests that regular patterns arise from coupled local- and landscape-scale feedbacks that can also create multiple stable landscape states. In the Florida Everglades, hydrologic modification has degraded much of the historically-extensive ridge-slough landscape, a patterned peatland mosaic with distinct, flow-parallel patches. However, in the Everglades and in general, the hypothesis that patterned landscapes have homogeneous alternative states has little direct empirical support. Here we use microtopographic and vegetative heterogeneity, and their relation to hydrologic conditions, to infer the existence of multiple landscape equilibria and identify the hydrologic thresholds for critical transitions between these states. Dual relationships between elevation variance and water depth, and bi-modal distributions of both elevation variance and plant community distinctness, are consistent with generic predictions of multiple states, and covariation between these measures suggests that microtopography is the leading indicator of landscape degradation. Furthermore, a simple ecohydrologic multiple-state model correctly predicts the hydrologic thresholds for persistence of distinct ridges and sloughs. Predicted ridge-slough elevation differences and their relation to water depth are much greater than observed in the contemporary Everglades, but correspond closely with historical observations of pre-drainage conditions. These multiple lines of evidence represent the broadest and most direct support for the link between regular spatial pattern and landscape-scale alternative states in any ecosystem, and suggest that other patterned landscapes could undergo sudden collapse in response to changing environmental conditions. Hydrologic thresholds and leading indicators of critical transitions should guide management of the Everglades ridge-slough landscape, whose preservation is a central goal of one of the world's largest ecosystem restoration efforts.

Kite aerial photography for low-cost, ultra-high spatial resolution multi-spectral mapping of intertidal landscapes.

PubMed

Bryson, Mitch; Johnson-Roberson, Matthew; Murphy, Richard J; Bongiorno, Daniel

2013-01-01

Intertidal ecosystems have primarily been studied using field-based sampling; remote sensing offers the ability to collect data over large areas in a snapshot of time that could complement field-based sampling methods by extrapolating them into the wider spatial and temporal context. Conventional remote sensing tools (such as satellite and aircraft imaging) provide data at limited spatial and temporal resolutions and relatively high costs for small-scale environmental science and ecologically-focussed studies. In this paper, we describe a low-cost, kite-based imaging system and photogrammetric/mapping procedure that was developed for constructing high-resolution, three-dimensional, multi-spectral terrain models of intertidal rocky shores. The processing procedure uses automatic image feature detection and matching, structure-from-motion and photo-textured terrain surface reconstruction algorithms that require minimal human input and only a small number of ground control points and allow the use of cheap, consumer-grade digital cameras. The resulting maps combine imagery at visible and near-infrared wavelengths and topographic information at sub-centimeter resolutions over an intertidal shoreline 200 m long, thus enabling spatial properties of the intertidal environment to be determined across a hierarchy of spatial scales. Results of the system are presented for an intertidal rocky shore at Jervis Bay, New South Wales, Australia. Potential uses of this technique include mapping of plant (micro- and macro-algae) and animal (e.g. gastropods) assemblages at multiple spatial and temporal scales.

Explaining local-scale species distributions: relative contributions of spatial autocorrelation and landscape heterogeneity for an avian assemblage

USGS Publications Warehouse

Mattsson, Brady J.; Zipkin, Elise F.; Gardner, Beth; Blank, Peter J.; Sauer, John R.; Royle, J. Andrew

2013-01-01

Understanding interactions between mobile species distributions and landcover characteristics remains an outstanding challenge in ecology. Multiple factors could explain species distributions including endogenous evolutionary traits leading to conspecific clustering and endogenous habitat features that support life history requirements. Birds are a useful taxon for examining hypotheses about the relative importance of these factors among species in a community. We developed a hierarchical Bayes approach to model the relationships between bird species occupancy and local landcover variables accounting for spatial autocorrelation, species similarities, and partial observability. We fit alternative occupancy models to detections of 90 bird species observed during repeat visits to 316 point-counts forming a 400-m grid throughout the Patuxent Wildlife Research Refuge in Maryland, USA. Models with landcover variables performed significantly better than our autologistic and null models, supporting the hypothesis that local landcover heterogeneity is important as an exogenous driver for species distributions. Conspecific clustering alone was a comparatively poor descriptor of local community composition, but there was evidence for spatial autocorrelation in all species. Considerable uncertainty remains whether landcover combined with spatial autocorrelation is most parsimonious for describing bird species distributions at a local scale. Spatial structuring may be weaker at intermediate scales within which dispersal is less frequent, information flows are localized, and landcover types become spatially diversified and therefore exhibit little aggregation. Examining such hypotheses across species assemblages contributes to our understanding of community-level associations with conspecifics and landscape composition.

Kite Aerial Photography for Low-Cost, Ultra-high Spatial Resolution Multi-Spectral Mapping of Intertidal Landscapes

PubMed Central

Bryson, Mitch; Johnson-Roberson, Matthew; Murphy, Richard J.; Bongiorno, Daniel

2013-01-01

Intertidal ecosystems have primarily been studied using field-based sampling; remote sensing offers the ability to collect data over large areas in a snapshot of time that could complement field-based sampling methods by extrapolating them into the wider spatial and temporal context. Conventional remote sensing tools (such as satellite and aircraft imaging) provide data at limited spatial and temporal resolutions and relatively high costs for small-scale environmental science and ecologically-focussed studies. In this paper, we describe a low-cost, kite-based imaging system and photogrammetric/mapping procedure that was developed for constructing high-resolution, three-dimensional, multi-spectral terrain models of intertidal rocky shores. The processing procedure uses automatic image feature detection and matching, structure-from-motion and photo-textured terrain surface reconstruction algorithms that require minimal human input and only a small number of ground control points and allow the use of cheap, consumer-grade digital cameras. The resulting maps combine imagery at visible and near-infrared wavelengths and topographic information at sub-centimeter resolutions over an intertidal shoreline 200 m long, thus enabling spatial properties of the intertidal environment to be determined across a hierarchy of spatial scales. Results of the system are presented for an intertidal rocky shore at Jervis Bay, New South Wales, Australia. Potential uses of this technique include mapping of plant (micro- and macro-algae) and animal (e.g. gastropods) assemblages at multiple spatial and temporal scales. PMID:24069206

Explaining local-scale species distributions: relative contributions of spatial autocorrelation and landscape heterogeneity for an avian assemblage.

PubMed

Mattsson, Brady J; Zipkin, Elise F; Gardner, Beth; Blank, Peter J; Sauer, John R; Royle, J Andrew

2013-01-01

Understanding interactions between mobile species distributions and landcover characteristics remains an outstanding challenge in ecology. Multiple factors could explain species distributions including endogenous evolutionary traits leading to conspecific clustering and endogenous habitat features that support life history requirements. Birds are a useful taxon for examining hypotheses about the relative importance of these factors among species in a community. We developed a hierarchical Bayes approach to model the relationships between bird species occupancy and local landcover variables accounting for spatial autocorrelation, species similarities, and partial observability. We fit alternative occupancy models to detections of 90 bird species observed during repeat visits to 316 point-counts forming a 400-m grid throughout the Patuxent Wildlife Research Refuge in Maryland, USA. Models with landcover variables performed significantly better than our autologistic and null models, supporting the hypothesis that local landcover heterogeneity is important as an exogenous driver for species distributions. Conspecific clustering alone was a comparatively poor descriptor of local community composition, but there was evidence for spatial autocorrelation in all species. Considerable uncertainty remains whether landcover combined with spatial autocorrelation is most parsimonious for describing bird species distributions at a local scale. Spatial structuring may be weaker at intermediate scales within which dispersal is less frequent, information flows are localized, and landcover types become spatially diversified and therefore exhibit little aggregation. Examining such hypotheses across species assemblages contributes to our understanding of community-level associations with conspecifics and landscape composition.

Explaining Local-Scale Species Distributions: Relative Contributions of Spatial Autocorrelation and Landscape Heterogeneity for an Avian Assemblage

PubMed Central

Mattsson, Brady J.; Zipkin, Elise F.; Gardner, Beth; Blank, Peter J.; Sauer, John R.; Royle, J. Andrew

2013-01-01

Understanding interactions between mobile species distributions and landcover characteristics remains an outstanding challenge in ecology. Multiple factors could explain species distributions including endogenous evolutionary traits leading to conspecific clustering and endogenous habitat features that support life history requirements. Birds are a useful taxon for examining hypotheses about the relative importance of these factors among species in a community. We developed a hierarchical Bayes approach to model the relationships between bird species occupancy and local landcover variables accounting for spatial autocorrelation, species similarities, and partial observability. We fit alternative occupancy models to detections of 90 bird species observed during repeat visits to 316 point-counts forming a 400-m grid throughout the Patuxent Wildlife Research Refuge in Maryland, USA. Models with landcover variables performed significantly better than our autologistic and null models, supporting the hypothesis that local landcover heterogeneity is important as an exogenous driver for species distributions. Conspecific clustering alone was a comparatively poor descriptor of local community composition, but there was evidence for spatial autocorrelation in all species. Considerable uncertainty remains whether landcover combined with spatial autocorrelation is most parsimonious for describing bird species distributions at a local scale. Spatial structuring may be weaker at intermediate scales within which dispersal is less frequent, information flows are localized, and landcover types become spatially diversified and therefore exhibit little aggregation. Examining such hypotheses across species assemblages contributes to our understanding of community-level associations with conspecifics and landscape composition. PMID:23393564

Towards anatomic scale agent-based modeling with a massively parallel spatially explicit general-purpose model of enteric tissue (SEGMEnT_HPC).

PubMed

Cockrell, Robert Chase; Christley, Scott; Chang, Eugene; An, Gary

2015-01-01

Perhaps the greatest challenge currently facing the biomedical research community is the ability to integrate highly detailed cellular and molecular mechanisms to represent clinical disease states as a pathway to engineer effective therapeutics. This is particularly evident in the representation of organ-level pathophysiology in terms of abnormal tissue structure, which, through histology, remains a mainstay in disease diagnosis and staging. As such, being able to generate anatomic scale simulations is a highly desirable goal. While computational limitations have previously constrained the size and scope of multi-scale computational models, advances in the capacity and availability of high-performance computing (HPC) resources have greatly expanded the ability of computational models of biological systems to achieve anatomic, clinically relevant scale. Diseases of the intestinal tract are exemplary examples of pathophysiological processes that manifest at multiple scales of spatial resolution, with structural abnormalities present at the microscopic, macroscopic and organ-levels. In this paper, we describe a novel, massively parallel computational model of the gut, the Spatially Explicitly General-purpose Model of Enteric Tissue_HPC (SEGMEnT_HPC), which extends an existing model of the gut epithelium, SEGMEnT, in order to create cell-for-cell anatomic scale simulations. We present an example implementation of SEGMEnT_HPC that simulates the pathogenesis of ileal pouchitis, and important clinical entity that affects patients following remedial surgery for ulcerative colitis.

Population Genetics of the Eastern Hellbender (Cryptobranchus alleganiensis alleganiensis) across Multiple Spatial Scales

PubMed Central

Unger, Shem D.; Rhodes, Olin E.; Sutton, Trent M.; Williams, Rod N.

2013-01-01

Conservation genetics is a powerful tool to assess the population structure of species and provides a framework for informing management of freshwater ecosystems. As lotic habitats become fragmented, the need to assess gene flow for species of conservation management becomes a priority. The eastern hellbender (Cryptobranchus alleganiensis alleganiensis) is a large, fully aquatic paedamorphic salamander. Many populations are experiencing declines throughout their geographic range, yet the genetic ramifications of these declines are currently unknown. To this end, we examined levels of genetic variation and genetic structure at both range-wide and drainage (hierarchical) scales. We collected 1,203 individuals from 77 rivers throughout nine states from June 2007 to August 2011. Levels of genetic diversity were relatively high among all sampling locations. We detected significant genetic structure across populations (Fst values ranged from 0.001 between rivers within a single watershed to 0.218 between states). We identified two genetically differentiated groups at the range-wide scale: 1) the Ohio River drainage and 2) the Tennessee River drainage. An analysis of molecular variance (AMOVA) based on landscape-scale sampling of basins within the Tennessee River drainage revealed the majority of genetic variation (∼94–98%) occurs within rivers. Eastern hellbenders show a strong pattern of isolation by stream distance (IBSD) at the drainage level. Understanding levels of genetic variation and differentiation at multiple spatial and biological scales will enable natural resource managers to make more informed decisions and plan effective conservation strategies for cryptic, lotic species. PMID:24204565

Landscape effects on mallard habitat selection at multiple spatial scales during the non-breeding period

USGS Publications Warehouse

Beatty, William S.; Webb, Elisabeth B.; Kesler, Dylan C.; Raedeke, Andrew H.; Naylor, Luke W.; Humburg, Dale D.

2014-01-01

Previous studies that evaluated effects of landscape-scale habitat heterogeneity on migratory waterbird distributions were spatially limited and temporally restricted to one major life-history phase. However, effects of landscape-scale habitat heterogeneity on long-distance migratory waterbirds can be studied across the annual cycle using new technologies, including global positioning system satellite transmitters. We used Bayesian discrete choice models to examine the influence of local habitats and landscape composition on habitat selection by a generalist dabbling duck, the mallard (Anas platyrhynchos), in the midcontinent of North America during the non-breeding period. Using a previously published empirical movement metric, we separated the non-breeding period into three seasons, including autumn migration, winter, and spring migration. We defined spatial scales based on movement patterns such that movements >0.25 and <30.00 km were classified as local scale and movements >30.00 km were classified as relocation scale. Habitat selection at the local scale was generally influenced by local and landscape-level variables across all seasons. Variables in top models at the local scale included proximities to cropland, emergent wetland, open water, and woody wetland. Similarly, variables associated with area of cropland, emergent wetland, open water, and woody wetland were also included at the local scale. At the relocation scale, mallards selected resource units based on more generalized variables, including proximity to wetlands and total wetland area. Our results emphasize the role of landscape composition in waterbird habitat selection and provide further support for local wetland landscapes to be considered functional units of waterbird conservation and management.

Low-Cost Ultra-High Spatial and Temporal Resolution Mapping of Intertidal Rock Platforms

NASA Astrophysics Data System (ADS)

Bryson, M.; Johnson-Roberson, M.; Murphy, R.

2012-07-01

Intertidal ecosystems have primarily been studied using field-based sampling; remote sensing offers the ability to collect data over large areas in a snapshot of time which could compliment field-based sampling methods by extrapolating them into the wider spatial and temporal context. Conventional remote sensing tools (such as satellite and aircraft imaging) provide data at relatively course, sub-meter resolutions or with limited temporal resolutions and relatively high costs for small-scale environmental science and ecology studies. In this paper, we describe a low-cost, kite-based imaging system and photogrammetric pipeline that was developed for constructing highresolution, 3D, photo-realistic terrain models of intertidal rocky shores. The processing pipeline uses automatic image feature detection and matching, structure-from-motion and photo-textured terrain surface reconstruction algorithms that require minimal human input and only a small number of ground control points and allow the use of cheap, consumer-grade digital cameras. The resulting maps combine colour and topographic information at sub-centimeter resolutions over an area of approximately 100m, thus enabling spatial properties of the intertidal environment to be determined across a hierarchy of spatial scales. Results of the system are presented for an intertidal rock platform at Cape Banks, Sydney, Australia. Potential uses of this technique include mapping of plant (micro- and macro-algae) and animal (e.g. gastropods) assemblages at multiple spatial and temporal scales.

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.

Wetland characteristics linked to broad-scale patterns in Culiseta melanura abundance and eastern equine encephalitis virus infection.

PubMed

Skaff, Nicholas K; Armstrong, Philip M; Andreadis, Theodore G; Cheruvelil, Kendra S

2017-10-18

Eastern equine encephalitis virus (EEEV) is an expanding mosquito-borne threat to humans and domestic animal populations in the northeastern United States. Outbreaks of EEEV are challenging to predict due to spatial and temporal uncertainty in the abundance and viral infection of Cs. melanura, the principal enzootic vector. EEEV activity may be closely linked to wetlands because they provide essential habitat for mosquito vectors and avian reservoir hosts. However, wetlands are not homogeneous and can vary by vegetation, connectivity, size, and inundation patterns. Wetlands may also have different effects on EEEV transmission depending on the assessed spatial scale. We investigated associations between wetland characteristics and Cs. melanura abundance and infection with EEEV at multiple spatial scales in Connecticut, USA. Our findings indicate that wetland vegetative characteristics have strong associations with Cs. melanura abundance. Deciduous and evergreen forested wetlands were associated with higher Cs. melanura abundance, likely because these wetlands provide suitable subterranean habitat for Cs. melanura development. In contrast, Cs. melanura abundance was negatively associated with emergent and scrub/shrub wetlands, and wetland connectivity to streams. These relationships were generally strongest at broad spatial scales. Additionally, the relationships between wetland characteristics and EEEV infection in Cs. melanura were generally weak. However, Cs. melanura abundance was strongly associated with EEEV infection, suggesting that wetland-associated changes in abundance may be indirectly linked to EEEV infection in Cs. melanura. Finally, we found that wet hydrological conditions during the transmission season and during the fall/winter preceding the transmission season were associated with higher Cs. melanura abundance and EEEV infection, indicating that wet conditions are favorable for EEEV transmission. These results expand the broad-scale understanding of the effects of wetlands on EEEV transmission and help to reduce the spatial and temporal uncertainty associated with EEEV outbreaks.

Crystalline metamaterials for topological properties at subwavelength scales

PubMed Central

Yves, Simon; Fleury, Romain; Berthelot, Thomas; Fink, Mathias; Lemoult, Fabrice; Lerosey, Geoffroy

2017-01-01

The exciting discovery of topological condensed matter systems has lately triggered a search for their photonic analogues, motivated by the possibility of robust backscattering-immune light transport. However, topological photonic phases have so far only been observed in photonic crystals and waveguide arrays, which are inherently physically wavelength scaled, hindering their application in compact subwavelength systems. In this letter, we tackle this problem by patterning the deep subwavelength resonant elements of metamaterials onto specific lattices, and create crystalline metamaterials that can develop complex nonlocal properties due to multiple scattering, despite their very subwavelength spatial scale that usually implies to disregard their structure. These spatially dispersive systems can support subwavelength topological phases, as we demonstrate at microwaves by direct field mapping. Our approach gives a straightforward tabletop platform for the study of photonic topological phases, and allows to envision applications benefiting the compactness of metamaterials and the amazing potential of topological insulators. PMID:28719573

Multi-scale integration and predictability in resting state brain activity

PubMed Central

Kolchinsky, Artemy; van den Heuvel, Martijn P.; Griffa, Alessandra; Hagmann, Patric; Rocha, Luis M.; Sporns, Olaf; Goñi, Joaquín

2014-01-01

The human brain displays heterogeneous organization in both structure and function. Here we develop a method to characterize brain regions and networks in terms of information-theoretic measures. We look at how these measures scale when larger spatial regions as well as larger connectome sub-networks are considered. This framework is applied to human brain fMRI recordings of resting-state activity and DSI-inferred structural connectivity. We find that strong functional coupling across large spatial distances distinguishes functional hubs from unimodal low-level areas, and that this long-range functional coupling correlates with structural long-range efficiency on the connectome. We also find a set of connectome regions that are both internally integrated and coupled to the rest of the brain, and which resemble previously reported resting-state networks. Finally, we argue that information-theoretic measures are useful for characterizing the functional organization of the brain at multiple scales. PMID:25104933

Crystalline metamaterials for topological properties at subwavelength scales

NASA Astrophysics Data System (ADS)

Yves, Simon; Fleury, Romain; Berthelot, Thomas; Fink, Mathias; Lemoult, Fabrice; Lerosey, Geoffroy

2017-07-01

The exciting discovery of topological condensed matter systems has lately triggered a search for their photonic analogues, motivated by the possibility of robust backscattering-immune light transport. However, topological photonic phases have so far only been observed in photonic crystals and waveguide arrays, which are inherently physically wavelength scaled, hindering their application in compact subwavelength systems. In this letter, we tackle this problem by patterning the deep subwavelength resonant elements of metamaterials onto specific lattices, and create crystalline metamaterials that can develop complex nonlocal properties due to multiple scattering, despite their very subwavelength spatial scale that usually implies to disregard their structure. These spatially dispersive systems can support subwavelength topological phases, as we demonstrate at microwaves by direct field mapping. Our approach gives a straightforward tabletop platform for the study of photonic topological phases, and allows to envision applications benefiting the compactness of metamaterials and the amazing potential of topological insulators.

Context-dependent colonization dynamics: Regional reward contagion drives local compression in aquatic beetles.

PubMed

Pintar, Matthew R; Resetarits, William J

2017-09-01

Habitat selection by colonizing organisms is an important factor in determining species abundance and community dynamics at multiple spatial scales. Many organisms select habitat patches based on intrinsic patch quality, but patches exist in complex landscapes linked by dispersal and colonization, forming metapopulations and metacommunities. Perceived patch quality can be influenced by neighbouring patches through spatial contagion, wherein perceived quality of one patch can extend beyond its borders and either increase or decrease the colonization of neighbouring patches and localities. These spatially explicit colonization dynamics can result in habitat compression, wherein more colonists occupy a patch or locality than in the absence of spatial context dependence. Previous work on contagion/compression focused primarily on the role of predators in driving colonization patterns. Our goal was to determine whether resource abundance can drive multi-scale colonization dynamics of aquatic beetles through the processes of contagion and compression in naturally colonized experimental pools. We established two levels (high/low quality) of within-patch resource abundances (leaf litter) using an experimental landscape of mesocosms, and assayed colonization by 35 species of aquatic beetles. Patches were arranged in localities (sets of two patches), which consisted of a combination of two patch-level resource levels in a 2 × 2 factorial design, allowing us to assay colonization at both locality and patch levels. We demonstrate that patterns of species abundance and richness of colonizing aquatic beetles are determined by patch quality and context-dependent processes at multiple spatial scales. Localities that consisted of at least one high-quality patch were colonized at equivalent rates that were higher than localities containing only low-quality patches, displaying regional reward contagion. In localities that consisted of one high- and one low-quality patch, reward contagion produced by higher leaf litter levels resulted in greater abundance of beetles in such localities, which then compressed into the highest quality patches. Our results provide further support for the critical roles of habitat selection and spatial context, particularly the quality of neighbouring habitat patches, in generating patterns of species abundances and community structure across landscapes. © 2017 The Authors. Journal of Animal Ecology © 2017 British Ecological Society.

A test of multiple hypotheses for the species richness gradient of South American owls.

PubMed

Diniz-Filho, José Alexandre Felizola; Rangel, Thiago F L V B; Hawkins, Bradford A

2004-08-01

Many mechanisms have been proposed to explain broad scale spatial patterns in species richness. In this paper, we evaluate five explanations for geographic gradients in species richness, using South American owls as a model. We compared the explanatory power of contemporary climate, landcover diversity, spatial climatic heterogeneity, evolutionary history, and area. An important aspect of our analyses is that very different hypotheses, such as history and area, can be quantified at the same observation scale and, consequently can be incorporated into a single analytical framework. Both area effects and owl phylogenetic history were poorly associated with richness, whereas contemporary climate, climatic heterogeneity at the mesoscale and landcover diversity explained ca. 53% of the variation in species richness. We conclude that both climate and environmental heterogeneity should be retained as plausible explanations for the diversity gradient. Turnover rates and scaling effects, on the other hand, although perhaps useful for detecting faunal changes and beta diversity at local and regional scales, are not strong explanations for the owl diversity gradient.

Effects of an individual 12-week community-located "start-to-run" program on physical capacity, walking, fatigue, cognitive function, brain volumes, and structures in persons with multiple sclerosis.

PubMed

Feys, Peter; Moumdjian, Lousin; Van Halewyck, Florian; Wens, Inez; Eijnde, Bert O; Van Wijmeersch, Bart; Popescu, Veronica; Van Asch, Paul

2017-11-01

Exercise therapy studies in persons with multiple sclerosis (pwMS) primarily focused on motor outcomes in mid disease stage, while cognitive function and neural correlates were only limitedly addressed. This pragmatic randomized controlled study investigated the effects of a remotely supervised community-located "start-to-run" program on physical and cognitive function, fatigue, quality of life, brain volume, and connectivity. In all, 42 pwMS were randomized to either experimental (EXP) or waiting list control (WLC) group. The EXP group received individualized training instructions during 12 weeks (3×/week), to be performed in their community aiming to participate in a running event. Measures were physical (VO 2max , sit-to-stand test, Six-Minute Walk Test (6MWT), Multiple Sclerosis Walking Scale-12 (MSWS-12)) and cognitive function (Rao's Brief Repeatable Battery (BRB), Paced Auditory Serial Attention Test (PASAT)), fatigue (Fatigue Scale for Motor and Cognitive Function (FSMC)), quality of life (Multiple Sclerosis Impact Scale-29 (MSIS-29)), and imaging. Brain volumes and diffusion tensor imaging (DTI) were quantified using FSL-SIENA/FIRST and FSL-TBSS. In all, 35 pwMS completed the trial. Interaction effects in favor of the EXP group were found for VO 2max , sit-to-stand test, MSWS-12, Spatial Recall Test, FSMC, MSIS-29, and pallidum volume. VO 2max improved by 1.5 mL/kg/min, MSWS-12 by 4, FSMC by 11, and MSIS-29 by 14 points. The Spatial Recall Test improved by more than 10%. Community-located run training improved aerobic capacity, functional mobility, visuospatial memory, fatigue, and quality of life and pallidum volume in pwMS.

A multi-scale evaluation of pack stock effects on subalpine meadow plant communities in the Sierra Nevada

PubMed Central

Berlow, Eric L.; Ostoja, Steven M.; Brooks, Matthew L.; Génin, Alexandre; Matchett, John R.; Hart, Stephen C.

2017-01-01

We evaluated the influence of pack stock (i.e., horse and mule) use on meadow plant communities in Sequoia and Yosemite National Parks in the Sierra Nevada of California. Meadows were sampled to account for inherent variability across multiple scales by: 1) controlling for among-meadow variability by using remotely sensed hydro-climatic and geospatial data to pair stock use meadows with similar non-stock (reference) sites, 2) accounting for within-meadow variation in the local hydrology using in-situ soil moisture readings, and 3) incorporating variation in stock use intensity by sampling across the entire available gradient of pack stock use. Increased cover of bare ground was detected only within “dry” meadow areas at the two most heavily used pack stock meadows (maximum animals per night per hectare). There was no difference in plant community composition for any level of soil moisture or pack stock use. Increased local-scale spatial variability in plant community composition (species dispersion) was detected in “wet” meadow areas at the two most heavily used meadows. These results suggest that at the meadow scale, plant communities are generally resistant to the contemporary levels of recreational pack stock use. However, finer-scale within-meadow responses such as increased bare ground or spatial variability in the plant community can be a function of local-scale hydrological conditions. Wilderness managers can improve monitoring of disturbance in Sierra Nevada meadows by adopting multiple plant community indices while simultaneously considering local moisture regimes. PMID:28609464

Large-scale recovery of an endangered amphibian despite ongoing exposure to multiple stressors

USGS Publications Warehouse

Knapp, Roland A.; Fellers, Gary M.; Kleeman, Patrick M.; Miller, David A. W.; Vrendenburg, Vance T.; Rosenblum, Erica Bree; Briggs, Cheryl J.

2016-01-01

Amphibians are one of the most threatened animal groups, with 32% of species at risk for extinction. Given this imperiled status, is the disappearance of a large fraction of the Earth’s amphibians inevitable, or are some declining species more resilient than is generally assumed? We address this question in a species that is emblematic of many declining amphibians, the endangered Sierra Nevada yellow-legged frog (Rana sierrae). Based on >7,000 frog surveys conducted across Yosemite National Park over a 20-y period, we show that, after decades of decline and despite ongoing exposure to multiple stressors, including introduced fish, the recently emerged disease chytridiomycosis, and pesticides, R. sierrae abundance increased sevenfold during the study and at a rate of 11% per year. These increases occurred in hundreds of populations throughout Yosemite, providing a rare example of amphibian recovery at an ecologically relevant spatial scale. Results from a laboratory experiment indicate that these increases may be in part because of reduced frog susceptibility to chytridiomycosis. The disappearance of nonnative fish from numerous water bodies after cessation of stocking also contributed to the recovery. The large-scale increases in R. sierrae abundance that we document suggest that, when habitats are relatively intact and stressors are reduced in their importance by active management or species’ adaptive responses, declines of some amphibians may be partially reversible, at least at a regional scale. Other studies conducted over similarly large temporal and spatial scales are critically needed to provide insight and generality about the reversibility of amphibian declines at a global scale.

Large-scale recovery of an endangered amphibian despite ongoing exposure to multiple stressors.

PubMed

Knapp, Roland A; Fellers, Gary M; Kleeman, Patrick M; Miller, David A W; Vredenburg, Vance T; Rosenblum, Erica Bree; Briggs, Cheryl J

2016-10-18

Amphibians are one of the most threatened animal groups, with 32% of species at risk for extinction. Given this imperiled status, is the disappearance of a large fraction of the Earth's amphibians inevitable, or are some declining species more resilient than is generally assumed? We address this question in a species that is emblematic of many declining amphibians, the endangered Sierra Nevada yellow-legged frog (Rana sierrae). Based on >7,000 frog surveys conducted across Yosemite National Park over a 20-y period, we show that, after decades of decline and despite ongoing exposure to multiple stressors, including introduced fish, the recently emerged disease chytridiomycosis, and pesticides, R. sierrae abundance increased sevenfold during the study and at a rate of 11% per year. These increases occurred in hundreds of populations throughout Yosemite, providing a rare example of amphibian recovery at an ecologically relevant spatial scale. Results from a laboratory experiment indicate that these increases may be in part because of reduced frog susceptibility to chytridiomycosis. The disappearance of nonnative fish from numerous water bodies after cessation of stocking also contributed to the recovery. The large-scale increases in R. sierrae abundance that we document suggest that, when habitats are relatively intact and stressors are reduced in their importance by active management or species' adaptive responses, declines of some amphibians may be partially reversible, at least at a regional scale. Other studies conducted over similarly large temporal and spatial scales are critically needed to provide insight and generality about the reversibility of amphibian declines at a global scale.

Large-scale recovery of an endangered amphibian despite ongoing exposure to multiple stressors

PubMed Central

Knapp, Roland A.; Fellers, Gary M.; Kleeman, Patrick M.; Miller, David A. W.; Rosenblum, Erica Bree; Briggs, Cheryl J.

2016-01-01

Amphibians are one of the most threatened animal groups, with 32% of species at risk for extinction. Given this imperiled status, is the disappearance of a large fraction of the Earth’s amphibians inevitable, or are some declining species more resilient than is generally assumed? We address this question in a species that is emblematic of many declining amphibians, the endangered Sierra Nevada yellow-legged frog (Rana sierrae). Based on >7,000 frog surveys conducted across Yosemite National Park over a 20-y period, we show that, after decades of decline and despite ongoing exposure to multiple stressors, including introduced fish, the recently emerged disease chytridiomycosis, and pesticides, R. sierrae abundance increased sevenfold during the study and at a rate of 11% per year. These increases occurred in hundreds of populations throughout Yosemite, providing a rare example of amphibian recovery at an ecologically relevant spatial scale. Results from a laboratory experiment indicate that these increases may be in part because of reduced frog susceptibility to chytridiomycosis. The disappearance of nonnative fish from numerous water bodies after cessation of stocking also contributed to the recovery. The large-scale increases in R. sierrae abundance that we document suggest that, when habitats are relatively intact and stressors are reduced in their importance by active management or species’ adaptive responses, declines of some amphibians may be partially reversible, at least at a regional scale. Other studies conducted over similarly large temporal and spatial scales are critically needed to provide insight and generality about the reversibility of amphibian declines at a global scale. PMID:27698128

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Validation of walk score for estimating neighborhood walkability: an analysis of four US metropolitan areas.

PubMed

Duncan, Dustin T; Aldstadt, Jared; Whalen, John; Melly, Steven J; Gortmaker, Steven L

2011-11-01

Neighborhood walkability can influence physical activity. We evaluated the validity of Walk Score(®) for assessing neighborhood walkability based on GIS (objective) indicators of neighborhood walkability with addresses from four US metropolitan areas with several street network buffer distances (i.e., 400-, 800-, and 1,600-meters). Address data come from the YMCA-Harvard After School Food and Fitness Project, an obesity prevention intervention involving children aged 5-11 years and their families participating in YMCA-administered, after-school programs located in four geographically diverse metropolitan areas in the US (n = 733). GIS data were used to measure multiple objective indicators of neighborhood walkability. Walk Scores were also obtained for the participant's residential addresses. Spearman correlations between Walk Scores and the GIS neighborhood walkability indicators were calculated as well as Spearman correlations accounting for spatial autocorrelation. There were many significant moderate correlations between Walk Scores and the GIS neighborhood walkability indicators such as density of retail destinations and intersection density (p < 0.05). The magnitude varied by the GIS indicator of neighborhood walkability. Correlations generally became stronger with a larger spatial scale, and there were some geographic differences. Walk Score(®) is free and publicly available for public health researchers and practitioners. Results from our study suggest that Walk Score(®) is a valid measure of estimating certain aspects of neighborhood walkability, particularly at the 1600-meter buffer. As such, our study confirms and extends the generalizability of previous findings demonstrating that Walk Score is a valid measure of estimating neighborhood walkability in multiple geographic locations and at multiple spatial scales.

Variation in spatial scale of competing polydomous twig-nesting ants in coffee agroecosystems

PubMed Central

Mathis, Kaitlyn A.; Philpott, Stacy M.; Ramirez, Santiago R.

2016-01-01

Arboreal ants are both highly diverse and ecologically dominant in the tropics. This ecologically important group is particularly useful in ongoing efforts to understand processes that regulate species diversity and coexistence. Our study addresses how polydomy can influence patterns of nest occupation in competing arboreal ants. We examined the spatial structure of nest occupation (nest distance, abundance and density) in three polydomous co-occurring twig-nesting ant species (Pseudomyrmex simplex, P. ejectus and P. PSW-53) by mapping twigs occupied by ants from each species within plots in our study site. We then used two colony structure estimators (intraspecific aggression and cuticular hydrocarbon variation) to determine the relative degree of polydomy for each species. All work was conducted in coffee agroforests in Chiapas, Mexico. Our results revealed that the two species with highest abundance and nest density were also highly polydomous, where both species had either single or multiple non-aggressive colonies occupying nests on a large spatial scale (greater than the hectare level). Our results also indicate that the species with the lowest abundance and density is less polydomous, occupying several overlapping and territorial colonies at the hectare level in which multiple colonies never co-occur on the same host plant. These results contribute evidence that successful coexistence and highly polydomous colony structure may allow ants, through reduced intraspecific aggression, to successfully occupy more nests more densely than ant species that have multiple territorial colonies. Furthermore our study highlights the importance of considering intraspecific interactions when examining community assembly of ants. PMID:27795573

Combining Monitoring Data Spanning Multiple Temporal and Spatial Scales To Evaluate Water Quality Affecting Seagrass Habitat Extent in northwest Florida Estuaries

EPA Science Inventory

The ability to understand and manage ecological changes caused by anthropogenic stressors is often impeded by a lack of sufficient information to resolve pattern and change with sufficient resolution and extent. Increasingly, different types of environmental data are available t...

Spatial application of WEPS for estimating wind erosion in the Pacific Northwest

USDA-ARS?s Scientific Manuscript database

The Wind Erosion Prediction System (WEPS) is used to simulate soil erosion on croplands and was originally designed to run field scale simulations. This research is an extension of the WEPS model to run on multiple fields (grids) covering a larger region. We modified the WEPS source code to allow it...

Spatial application of WEPS for estimating wind erosion in the Pacific Northwest

USDA-ARS?s Scientific Manuscript database

The Wind Erosion Prediction System (WEPS) is used to simulate soil erosion on cropland and was originally designed to run simulations on a field-scale size. This study extended WEPS to run on multiple fields (grids) independently to cover a large region and to conduct an initial investigation to ass...

Comparison of Habitat-Specific Nutrient Removal and Release in Pacific NW Salt Marshes at Multiple Spatial Scales

EPA Science Inventory

Wetlands can be sources, sinks and transformers of nutrients, although it is their role in nutrient removal that is valued as a water purification ecosystem service. In order to quantify that service for any wetland, it is important to understand the drivers of nutrient removal w...

Hierarchical analysis of species distributions and abundance across environmental gradients

Treesearch

Jeffery Diez; Ronald H. Pulliam

2007-01-01

Abiotic and biotic processes operate at multiple spatial and temporal scales to shape many ecological processes, including species distributions and demography. Current debate about the relative roles of niche-based and stochastic processes in shaping species distributions and community composition reflects, in part, the challenge of understanding how these processes...

Using landscape disturbance and succession models to support forest management

Treesearch

Eric J. Gustafson; Brian R. Sturtevant; Anatoly S. Shvidenko; Robert M. Scheller

2010-01-01

Managers of forested landscapes must account for multiple, interacting ecological processes operating at broad spatial and temporal scales. These interactions can be of such complexity that predictions of future forest ecosystem states are beyond the analytical capability of the human mind. Landscape disturbance and succession models (LDSM) are predictive and...

RELATIONSHIPS BETWEEN DISSOLVED NITROGEN AND LANDUSE/LANDCOVER AT TWO SPATIAL SCALES IN THE CALAPOOIA RIVER WATERSHED, OREGON

EPA Science Inventory

The Calapooia River, a major tributary to the Willamette River in Oregon, provides an outstanding opportunity to study dynamics of dissolved nitrogen (DN) in a multiple landuse watershed. The watershed is typical of many found in the Willamette basin, with National Forest land i...

An Integrated Modeling Framework for Performing Environmental Assessments: Application to Ecosystem Services in the Albemarle-Pamlico Basins (NC and VA,USA)

EPA Science Inventory

The U.S. Environmental Protection Agency uses environmental models to inform rulemaking and policy decisions at multiple spatial and temporal scales. As decision-making has moved towards integrated thinking and assessment (e.g. media, site, region, services), the increasing compl...

Spatial scaling and multi-model inference in landscape genetics: Martes americana in northern Idaho

Treesearch

Tzeidle N. Wasserman; Samuel A. Cushman; Michael K. Schwartz; David O. Wallin

2010-01-01

Individual-based analyses relating landscape structure to genetic distances across complex landscapes enable rigorous evaluation of multiple alternative hypotheses linking landscape structure to gene flow. We utilize two extensions to increase the rigor of the individual-based causal modeling approach to inferring relationships between landscape patterns and gene flow...

Multiscale sagebrush rangeland habitat modeling in southwest Wyoming

USGS Publications Warehouse

Homer, Collin G.; Aldridge, Cameron L.; Meyer, Debra K.; Coan, Michael J.; Bowen, Zachary H.

2009-01-01

Sagebrush-steppe ecosystems in North America have experienced dramatic elimination and degradation since European settlement. As a result, sagebrush-steppe dependent species have experienced drastic range contractions and population declines. Coordinated ecosystem-wide research, integrated with monitoring and management activities, would improve the ability to maintain existing sagebrush habitats. However, current data only identify resource availability locally, with rigorous spatial tools and models that accurately model and map sagebrush habitats over large areas still unavailable. Here we report on an effort to produce a rigorous large-area sagebrush-habitat classification and inventory with statistically validated products and estimates of precision in the State of Wyoming. This research employs a combination of significant new tools, including (1) modeling sagebrush rangeland as a series of independent continuous field components that can be combined and customized by any user at multiple spatial scales; (2) collecting ground-measured plot data on 2.4-meter imagery in the same season the satellite imagery is acquired; (3) effective modeling of ground-measured data on 2.4-meter imagery to maximize subsequent extrapolation; (4) acquiring multiple seasons (spring, summer, and fall) of an additional two spatial scales of imagery (30 meter and 56 meter) for optimal large-area modeling; (5) using regression tree classification technology that optimizes data mining of multiple image dates, ratios, and bands with ancillary data to extrapolate ground training data to coarser resolution sensors; and (6) employing rigorous accuracy assessment of model predictions to enable users to understand the inherent uncertainties. First-phase results modeled eight rangeland components (four primary targets and four secondary targets) as continuous field predictions. The primary targets included percent bare ground, percent herbaceousness, percent shrub, and percent litter. The four secondary targets included percent sagebrush (Artemisia spp.), percent big sagebrush (Artemisia tridentata), percent Wyoming sagebrush (Artemisia tridentata wyomingensis), and sagebrush height (centimeters). Results were validated by an independent accuracy assessment with root mean square error (RMSE) values ranging from 6.38 percent for bare ground to 2.99 percent for sagebrush at the QuickBird scale and RMSE values ranging from 12.07 percent for bare ground to 6.34 percent for sagebrush at the full Landsat scale. Subsequent project phases are now in progress, with plans to deliver products that improve accuracies of existing components, model new components, complete models over larger areas, track changes over time (from 1988 to 2007), and ultimately model wildlife population trends against these changes. We believe these results offer significant improvement in sagebrush rangeland quantification at multiple scales and offer users products that have been rigorously validated.

Enhanced protective role in materials with gradient structural orientations: Lessons from Nature.

PubMed

Liu, Zengqian; Zhu, Yankun; Jiao, Da; Weng, Zhaoyong; Zhang, Zhefeng; Ritchie, Robert O

2016-10-15

Living organisms are adept at resisting contact deformation and damage by assembling protective surfaces with spatially varied mechanical properties, i.e., by creating functionally graded materials. Such gradients, together with multiple length-scale hierarchical structures, represent the two prime characteristics of many biological materials to be translated into engineering design. Here, we examine one design motif from a variety of biological tissues and materials where site-specific mechanical properties are generated for enhanced protection by adopting gradients in structural orientation over multiple length-scales, without manipulation of composition or microstructural dimension. Quantitative correlations are established between the structural orientations and local mechanical properties, such as stiffness, strength and fracture resistance; based on such gradients, the underlying mechanisms for the enhanced protective role of these materials are clarified. Theoretical analysis is presented and corroborated through numerical simulations of the indentation behavior of composites with distinct orientations. The design strategy of such bioinspired gradients is outlined in terms of the geometry of constituents. This study may offer a feasible approach towards generating functionally graded mechanical properties in synthetic materials for improved contact damage resistance. Living organisms are adept at resisting contact damage by assembling protective surfaces with spatially varied mechanical properties, i.e., by creating functionally-graded materials. Such gradients, together with multiple length-scale hierarchical structures, represent the prime characteristics of many biological materials. Here, we examine one design motif from a variety of biological tissues where site-specific mechanical properties are generated for enhanced protection by adopting gradients in structural orientation at multiple length-scales, without changes in composition or microstructural dimension. The design strategy of such bioinspired gradients is outlined in terms of the geometry of constituents. This study may offer a feasible approach towards generating functionally-graded mechanical properties in synthetic materials for improved damage resistance. Published by Elsevier Ltd.

Evaluation of multiple-scale 3D characterization for coal physical structure with DCM method and synchrotron X-ray CT.

PubMed

Wang, Haipeng; Yang, Yushuang; Yang, Jianli; Nie, Yihang; Jia, Jing; Wang, Yudan

2015-01-01

Multiscale nondestructive characterization of coal microscopic physical structure can provide important information for coal conversion and coal-bed methane extraction. In this study, the physical structure of a coal sample was investigated by synchrotron-based multiple-energy X-ray CT at three beam energies and two different spatial resolutions. A data-constrained modeling (DCM) approach was used to quantitatively characterize the multiscale compositional distributions at the two resolutions. The volume fractions of each voxel for four different composition groups were obtained at the two resolutions. Between the two resolutions, the difference for DCM computed volume fractions of coal matrix and pores is less than 0.3%, and the difference for mineral composition groups is less than 0.17%. This demonstrates that the DCM approach can account for compositions beyond the X-ray CT imaging resolution with adequate accuracy. By using DCM, it is possible to characterize a relatively large coal sample at a relatively low spatial resolution with minimal loss of the effect due to subpixel fine length scale structures.

Polychaete richness and abundance enhanced in anthropogenically modified estuaries despite high concentrations of toxic contaminants.

PubMed

Dafforn, Katherine A; Kelaher, Brendan P; Simpson, Stuart L; Coleman, Melinda A; Hutchings, Pat A; Clark, Graeme F; Knott, Nathan A; Doblin, Martina A; Johnston, Emma L

2013-01-01

Ecological communities are increasingly exposed to multiple chemical and physical stressors, but distinguishing anthropogenic impacts from other environmental drivers remains challenging. Rarely are multiple stressors investigated in replicated studies over large spatial scales (>1000 kms) or supported with manipulations that are necessary to interpret ecological patterns. We measured the composition of sediment infaunal communities in relation to anthropogenic and natural stressors at multiple sites within seven estuaries. We observed increases in the richness and abundance of polychaete worms in heavily modified estuaries with severe metal contamination, but no changes in the diversity or abundance of other taxa. Estuaries in which toxic contaminants were elevated also showed evidence of organic enrichment. We hypothesised that the observed response of polychaetes was not a 'positive' response to toxic contamination or a reduction in biotic competition, but due to high levels of nutrients in heavily modified estuaries driving productivity in the water column and enriching the sediment over large spatial scales. We deployed defaunated field-collected sediments from the surveyed estuaries in a small scale experiment, but observed no effects of sediment characteristics (toxic or enriching). Furthermore, invertebrate recruitment instead reflected the low diversity and abundance observed during field surveys of this relatively 'pristine' estuary. This suggests that differences observed in the survey are not a direct consequence of sediment characteristics (even severe metal contamination) but are related to parameters that covary with estuary modification such as enhanced productivity from nutrient inputs and the diversity of the local species pool. This has implications for the interpretation of diversity measures in large-scale monitoring studies in which the observed patterns may be strongly influenced by many factors that covary with anthropogenic modification.

Polychaete Richness and Abundance Enhanced in Anthropogenically Modified Estuaries Despite High Concentrations of Toxic Contaminants

PubMed Central

Dafforn, Katherine A.; Kelaher, Brendan P.; Simpson, Stuart L.; Coleman, Melinda A.; Hutchings, Pat A.; Clark, Graeme F.; Knott, Nathan A.; Doblin, Martina A.; Johnston, Emma L.

2013-01-01

Ecological communities are increasingly exposed to multiple chemical and physical stressors, but distinguishing anthropogenic impacts from other environmental drivers remains challenging. Rarely are multiple stressors investigated in replicated studies over large spatial scales (>1000 kms) or supported with manipulations that are necessary to interpret ecological patterns. We measured the composition of sediment infaunal communities in relation to anthropogenic and natural stressors at multiple sites within seven estuaries. We observed increases in the richness and abundance of polychaete worms in heavily modified estuaries with severe metal contamination, but no changes in the diversity or abundance of other taxa. Estuaries in which toxic contaminants were elevated also showed evidence of organic enrichment. We hypothesised that the observed response of polychaetes was not a ‘positive’ response to toxic contamination or a reduction in biotic competition, but due to high levels of nutrients in heavily modified estuaries driving productivity in the water column and enriching the sediment over large spatial scales. We deployed defaunated field-collected sediments from the surveyed estuaries in a small scale experiment, but observed no effects of sediment characteristics (toxic or enriching). Furthermore, invertebrate recruitment instead reflected the low diversity and abundance observed during field surveys of this relatively ‘pristine’ estuary. This suggests that differences observed in the survey are not a direct consequence of sediment characteristics (even severe metal contamination) but are related to parameters that covary with estuary modification such as enhanced productivity from nutrient inputs and the diversity of the local species pool. This has implications for the interpretation of diversity measures in large-scale monitoring studies in which the observed patterns may be strongly influenced by many factors that covary with anthropogenic modification. PMID:24098816

Experimental demonstration of spatially coherent beam combining using optical parametric amplification.

PubMed

Kurita, Takashi; Sueda, Keiichi; Tsubakimoto, Koji; Miyanaga, Noriaki

2010-07-05

We experimentally demonstrated coherent beam combining using optical parametric amplification with a nonlinear crystal pumped by random-phased multiple-beam array of the second harmonic of a Nd:YAG laser at 10-Hz repetition rate. In the proof-of-principle experiment, the phase jump between two pump beams was precisely controlled by a motorized actuator. For the demonstration of multiple-beam combining a random phase plate was used to create random-phased beamlets as a pump pulse. Far-field patterns of the pump, the signal, and the idler indicated that the spatially coherent signal beams were obtained on both cases. This approach allows scaling of the intensity of optical parametric chirped pulse amplification up to the exa-watt level while maintaining diffraction-limited beam quality.

A Physically Based Runoff Routing Model for Land Surface and Earth System Models

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

Li, Hongyi; Wigmosta, Mark S.; Wu, Huan

2013-06-13

A new physically based runoff routing model, called the Model for Scale Adaptive River Transport (MOSART), has been developed to be applicable across local, regional, and global scales. Within each spatial unit, surface runoff is first routed across hillslopes and then discharged along with subsurface runoff into a ‘‘tributary subnetwork’’ before entering the main channel. The spatial units are thus linked via routing through the main channel network, which is constructed in a scale-consistent way across different spatial resolutions. All model parameters are physically based, and only a small subset requires calibration.MOSART has been applied to the Columbia River basinmore » at 1/ 168, 1/ 88, 1/ 48, and 1/ 28 spatial resolutions and was evaluated using naturalized or observed streamflow at a number of gauge stations. MOSART is compared to two other routing models widely used with land surface models, the River Transport Model (RTM) in the Community Land Model (CLM) and the Lohmann routing model, included as a postprocessor in the Variable Infiltration Capacity (VIC) model package, yielding consistent performance at multiple resolutions. MOSART is further evaluated using the channel velocities derived from field measurements or a hydraulic model at various locations and is shown to be capable of producing the seasonal variation and magnitude of channel velocities reasonably well at different resolutions. Moreover, the impacts of spatial resolution on model simulations are systematically examined at local and regional scales. Finally, the limitations ofMOSART and future directions for improvements are discussed.« less

Spatial dynamics of large-scale, multistage crab (Callinectes sapidus) dispersal: Determinants and consequences for recruitment

USGS Publications Warehouse

Etherington, L.L.; Eggleston, D.B.

2003-01-01

We assessed determinants and consequences of multistage dispersal on spatial recruitment of the blue crab, Callinectes sapidus, within the Croatan, Albemarle, Pamlico Estuarine System (CAPES), North Carolina, U.S.A. Large-scale sampling of early juvenile crabs over 4 years indicated that spatial abundance patterns were size-dependent and resulted from primary post-larval dispersal (pre-settlement) and secondary juvenile dispersal (early post-settlement). In general, primary dispersal led to high abundances within more seaward habitats, whereas secondary dispersal (which was relatively consistent) expanded the distribution of juveniles, potentially increasing the estuarine nursery capacity. There were strong relationships between juvenile crab density and specific wind characteristics; however, these patterns were spatially explicit. Various physical processes (e.g., seasonal wind events, timing and magnitude of tropical cyclones) interacted to influence dispersal during multiple stages and determined crab recruitment patterns. Our results suggest that the nursery value of different habitats is highly dependent on the dispersal potential (primary and secondary dispersal) to and from these areas, which is largely determined by the relative position of habitats within the estuarine landscape.

Multi-sensor fusion of Landsat 8 thermal infrared (TIR) and panchromatic (PAN) images.

PubMed

Jung, Hyung-Sup; Park, Sung-Whan

2014-12-18

Data fusion is defined as the combination of data from multiple sensors such that the resulting information is better than would be possible when the sensors are used individually. The multi-sensor fusion of panchromatic (PAN) and thermal infrared (TIR) images is a good example of this data fusion. While a PAN image has higher spatial resolution, a TIR one has lower spatial resolution. In this study, we have proposed an efficient method to fuse Landsat 8 PAN and TIR images using an optimal scaling factor in order to control the trade-off between the spatial details and the thermal information. We have compared the fused images created from different scaling factors and then tested the performance of the proposed method at urban and rural test areas. The test results show that the proposed method merges the spatial resolution of PAN image and the temperature information of TIR image efficiently. The proposed method may be applied to detect lava flows of volcanic activity, radioactive exposure of nuclear power plants, and surface temperature change with respect to land-use change.

Spatial Heterogeneity, Scale, Data Character and Sustainable Transport in the Big Data Era

NASA Astrophysics Data System (ADS)

Jiang, Bin

2018-04-01

In light of the emergence of big data, I have advocated and argued for a paradigm shift from Tobler's law to scaling law, from Euclidean geometry to fractal geometry, from Gaussian statistics to Paretian statistics, and - more importantly - from Descartes' mechanistic thinking to Alexander's organic thinking. Fractal geometry falls under the third definition of fractal - that is, a set or pattern is fractal if the scaling of far more small things than large ones recurs multiple times (Jiang and Yin 2014) - rather than under the second definition of fractal, which requires a power law between scales and details (Mandelbrot 1982). The new fractal geometry is more towards living geometry that "follows the rules, constraints, and contingent conditions that are, inevitably, encountered in the real world" (Alexander et al. 2012, p. 395), not only for understanding complexity, but also for creating complex or living structure (Alexander 2002-2005). This editorial attempts to clarify why the paradigm shift is essential and to elaborate on several concepts, including spatial heterogeneity (scaling law), scale (or the fourth meaning of scale), data character (in contrast to data quality), and sustainable transport in the big data era.

epiDMS: Data Management and Analytics for Decision-Making From Epidemic Spread Simulation Ensembles.

PubMed

Liu, Sicong; Poccia, Silvestro; Candan, K Selçuk; Chowell, Gerardo; Sapino, Maria Luisa

2016-12-01

Carefully calibrated large-scale computational models of epidemic spread represent a powerful tool to support the decision-making process during epidemic emergencies. Epidemic models are being increasingly used for generating forecasts of the spatial-temporal progression of epidemics at different spatial scales and for assessing the likely impact of different intervention strategies. However, the management and analysis of simulation ensembles stemming from large-scale computational models pose challenges, particularly when dealing with multiple interdependent parameters, spanning multiple layers and geospatial frames, affected by complex dynamic processes operating at different resolutions. We describe and illustrate with examples a novel epidemic simulation data management system, epiDMS, that was developed to address the challenges that arise from the need to generate, search, visualize, and analyze, in a scalable manner, large volumes of epidemic simulation ensembles and observations during the progression of an epidemic. epiDMS is a publicly available system that facilitates management and analysis of large epidemic simulation ensembles. epiDMS aims to fill an important hole in decision-making during healthcare emergencies by enabling critical services with significant economic and health impact. © The Author 2016. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail journals.permissions@oup.com.

Multiscale Mechanics of Articular Cartilage: Potentials and Challenges of Coupling Musculoskeletal, Joint, and Microscale Computational Models

PubMed Central

Halloran, J. P.; Sibole, S.; van Donkelaar, C. C.; van Turnhout, M. C.; Oomens, C. W. J.; Weiss, J. A.; Guilak, F.; Erdemir, A.

2012-01-01

Articular cartilage experiences significant mechanical loads during daily activities. Healthy cartilage provides the capacity for load bearing and regulates the mechanobiological processes for tissue development, maintenance, and repair. Experimental studies at multiple scales have provided a fundamental understanding of macroscopic mechanical function, evaluation of the micromechanical environment of chondrocytes, and the foundations for mechanobiological response. In addition, computational models of cartilage have offered a concise description of experimental data at many spatial levels under healthy and diseased conditions, and have served to generate hypotheses for the mechanical and biological function. Further, modeling and simulation provides a platform for predictive risk assessment, management of dysfunction, as well as a means to relate multiple spatial scales. Simulation-based investigation of cartilage comes with many challenges including both the computational burden and often insufficient availability of data for model development and validation. This review outlines recent modeling and simulation approaches to understand cartilage function from a mechanical systems perspective, and illustrates pathways to associate mechanics with biological function. Computational representations at single scales are provided from the body down to the microstructure, along with attempts to explore multiscale mechanisms of load sharing that dictate the mechanical environment of the cartilage and chondrocytes. PMID:22648577

Small-scale spatial heterogeneity of ecosystem properties, microbial community composition and microbial activities in a temperate mountain forest soil.

PubMed

Štursová, Martina; Bárta, Jiří; Šantrůčková, Hana; Baldrian, Petr

2016-12-01

Forests are recognised as spatially heterogeneous ecosystems. However, knowledge of the small-scale spatial variation in microbial abundance, community composition and activity is limited. Here, we aimed to describe the heterogeneity of environmental properties, namely vegetation, soil chemical composition, fungal and bacterial abundance and community composition, and enzymatic activity, in the topsoil in a small area (36 m 2 ) of a highly heterogeneous regenerating temperate natural forest, and to explore the relationships among these variables. The results demonstrated a high level of spatial heterogeneity in all properties and revealed differences between litter and soil. Fungal communities had substantially higher beta-diversity than bacterial communities, which were more uniform and less spatially autocorrelated. In litter, fungal communities were affected by vegetation and appeared to be more involved in decomposition. In the soil, chemical composition affected both microbial abundance and the rates of decomposition, whereas the effect of vegetation was small. Importantly, decomposition appeared to be concentrated in hotspots with increased activity of multiple enzymes. Overall, forest topsoil should be considered a spatially heterogeneous environment in which the mean estimates of ecosystem-level processes and microbial community composition may confound the existence of highly specific microenvironments. © FEMS 2016. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Scale and plant invasions: A theory of biotic acceptance

USGS Publications Warehouse

Stohlgren, T.J.; Jarnevich, C.; Chong, G.W.; Evangelista, P.H.

2006-01-01

We examined the relationship between native and alien plant species richness, cover, and estimated biomass at multiple spatial scales. The large dataset included 70511-m2 subplots, 1443 10-m2 subplots, and 727100-m2 subplots, nested in 727 1000-m2 plots in 37 natural vegetation types in seven states in the central United States. We found that native and alien species richness (averaged across the vegetation types) increased significantly with plot area. Furthermore, the relationship between native and alien species richness became increasingly positive and significant from the plant neighbourhood scale (1-m2) to the 10-m2, 100-m2, and the 1000-m2 scale where over 80% of the vegetation types had positive slopes between native and alien species richness. Both native and alien plant species may be responding to increased resource availability and/or habitat heterogeneity with increased area. We found significant positive relationships between the coefficient of variation of native cover in 1-m2 subplots in a vegetation type (i.e. a measure of habitat heterogeneity), and both the relative cover and relative biomass of alien plant species. At the 1000-m2 scale, we did find weak negative relationships between native species richness and the cover, biomass, and relative cover of alien plant species. However, we found very strong positive relationships between alien species richness and the cover, relative cover, and relative biomass of alien species at regional scales. These results, along with many other field studies in natural ecosystems, show that the dominant genera pattern in invasion ecology at multiple spatial scales is one of "biotic acceptance" where natural ecosystems tend to accommodate the establishment and coexistence of introduced species despite the presence and abundance of native species.

Spatial and Temporal Scales of Surface Water-Groundwater Interactions

NASA Astrophysics Data System (ADS)

Boano, F.

2016-12-01

The interfaces between surface water and groundwater (i.e., river and lake sediments) represent hotspots for nutrient transformation in watersheds. This intense biochemical activity stems from the peculiar physicochemical properties of these interface areas. Here, the exchange of water and nutrients between surface and subsurface environments creates an ecotone region that can support the presence of different microbial species responsible for nutrient transformation. Previous studies have elucidated that water exchange between rivers and aquifers is organized in a complex system of nested flow cells. Each cell entails a range of residence timescales spanning multiple order of magnitudes, providing opportunities for different biochemical reactions to occur. Physically-bases models represent useful tools to deal with the wide range of spatial and temporal scales that characterize surface-subsurface water exchange. This contribution will present insights about how hydrodynamic processes control scale organization for surface water - groundwater interactions. The specific focus will be the influence of exchange processes on microbial activity and nutrient transformation, discussing how groundwater flow at watershed scale controls flow conditions and hence constrain microbial reactions at much smaller scales.

A Parameter Estimation Scheme for Multiscale Kalman Smoother (MKS) Algorithm Used in Precipitation Data Fusion

NASA Technical Reports Server (NTRS)

Wang, Shugong; Liang, Xu

2013-01-01

A new approach is presented in this paper to effectively obtain parameter estimations for the Multiscale Kalman Smoother (MKS) algorithm. This new approach has demonstrated promising potentials in deriving better data products based on data of different spatial scales and precisions. Our new approach employs a multi-objective (MO) parameter estimation scheme (called MO scheme hereafter), rather than using the conventional maximum likelihood scheme (called ML scheme) to estimate the MKS parameters. Unlike the ML scheme, the MO scheme is not simply built on strict statistical assumptions related to prediction errors and observation errors, rather, it directly associates the fused data of multiple scales with multiple objective functions in searching best parameter estimations for MKS through optimization. In the MO scheme, objective functions are defined to facilitate consistency among the fused data at multiscales and the input data at their original scales in terms of spatial patterns and magnitudes. The new approach is evaluated through a Monte Carlo experiment and a series of comparison analyses using synthetic precipitation data. Our results show that the MKS fused precipitation performs better using the MO scheme than that using the ML scheme. Particularly, improvements are significant compared to that using the ML scheme for the fused precipitation associated with fine spatial resolutions. This is mainly due to having more criteria and constraints involved in the MO scheme than those included in the ML scheme. The weakness of the original ML scheme that blindly puts more weights onto the data associated with finer resolutions is overcome in our new approach.

Temporal and spatial patterns of wetland extent influence variability of surface water connectivity in the Prairie Pothole Region, United States

USGS Publications Warehouse

Vanderhoof, Melanie; Alexander, Laurie C.; Todd, Jason

2016-01-01

Context. Quantifying variability in landscape-scale surface water connectivity can help improve our understanding of the multiple effects of wetlands on downstream waterways. Objectives. We examined how wetland merging and the coalescence of wetlands with streams varied both spatially (among ecoregions) and interannually (from drought to deluge) across parts of the Prairie Pothole Region. Methods. Wetland extent was derived over a time series (1990-2011) using Landsat imagery. Changes in landscape-scale connectivity, generated by the physical coalescence of wetlands with other surface water features, were quantified by fusing static wetland and stream datasets with Landsat-derived wetland extent maps, and related to multiple wetness indices. The usage of Landsat allows for decadal-scale analysis, but limits the types of surface water connections that can be detected. Results. Wetland extent correlated positively with the merging of wetlands and wetlands with streams. Wetness conditions, as defined by drought indices and runoff, were positively correlated with wetland extent, but less consistently correlated with measures of surface water connectivity. The degree of wetland-wetland merging was found to depend less on total wetland area or density, and more on climate conditions, as well as the threshold for how wetland/upland was defined. In contrast, the merging of wetlands with streams was positively correlated with stream density, and inversely related to wetland density. Conclusions. Characterizing the degree of surface water connectivity within the Prairie Pothole Region in North America requires consideration of 1) climate-driven variation in wetness conditions and 2) within-region variation in wetland and stream spatial arrangements.

Partitioning sources of variation in vertebrate species richness

USGS Publications Warehouse

Boone, R.B.; Krohn, W.B.

2000-01-01

Aim: To explore biogeographic patterns of terrestrial vertebrates in Maine, USA using techniques that would describe local and spatial correlations with the environment. Location: Maine, USA. Methods: We delineated the ranges within Maine (86,156 km2) of 275 species using literature and expert review. Ranges were combined into species richness maps, and compared to geomorphology, climate, and woody plant distributions. Methods were adapted that compared richness of all vertebrate classes to each environmental correlate, rather than assessing a single explanatory theory. We partitioned variation in species richness into components using tree and multiple linear regression. Methods were used that allowed for useful comparisons between tree and linear regression results. For both methods we partitioned variation into broad-scale (spatially autocorrelated) and fine-scale (spatially uncorrelated) explained and unexplained components. By partitioning variance, and using both tree and linear regression in analyses, we explored the degree of variation in species richness for each vertebrate group that Could be explained by the relative contribution of each environmental variable. Results: In tree regression, climate variation explained richness better (92% of mean deviance explained for all species) than woody plant variation (87%) and geomorphology (86%). Reptiles were highly correlated with environmental variation (93%), followed by mammals, amphibians, and birds (each with 84-82% deviance explained). In multiple linear regression, climate was most closely associated with total vertebrate richness (78%), followed by woody plants (67%) and geomorphology (56%). Again, reptiles were closely correlated with the environment (95%), followed by mammals (73%), amphibians (63%) and birds (57%). Main conclusions: Comparing variation explained using tree and multiple linear regression quantified the importance of nonlinear relationships and local interactions between species richness and environmental variation, identifying the importance of linear relationships between reptiles and the environment, and nonlinear relationships between birds and woody plants, for example. Conservation planners should capture climatic variation in broad-scale designs; temperatures may shift during climate change, but the underlying correlations between the environment and species richness will presumably remain.

Reconfigurable Optical Interconnections Via Dynamic Computer-Generated Holograms

NASA Technical Reports Server (NTRS)

Liu, Hua-Kuang (Inventor); Zhou, Shao-Min (Inventor)

1996-01-01

A system is presented for optically providing one-to-many irregular interconnections, and strength-adjustable many-to-many irregular interconnections which may be provided with strengths (weights) w(sub ij) using multiple laser beams which address multiple holograms and means for combining the beams modified by the holograms to form multiple interconnections, such as a cross-bar switching network. The optical means for interconnection is based on entering a series of complex computer-generated holograms on an electrically addressed spatial light modulator for real-time reconfigurations, thus providing flexibility for interconnection networks for large-scale practical use. By employing multiple sources and holograms, the number of interconnection patterns achieved is increased greatly.

Spatial patterns of giant sequoia (Sequoiadendron giganteum) in two sequoia groves in Sequoia National Park, California

USGS Publications Warehouse

Stohlgren, Thomas J.

1993-01-01

Although Muir Grove and Castle Creek Grove are similar in area, elevation, and number of giant sequoias, various spatial pattern analysis techniques showed that they had dissimilar spatial patterns for similar-sized trees. Two-dimensional and transect two-term local quadrat variance techniques detected general trends in the spatial patterns of different-sized trees, detected multiple-scale patterns within individual size classes, and provided information on the scale and intensity of patches of individual size classes of trees in Muir and Castle Creek groves. In Muir Grove, midsized sequoias (1.5 to 2.4 m DBH classes) had major pattern scales 350–450 m in diameter, whereas the same-sized trees in Castle Creek Grove had pattern scales >1000 m in diameter. Many size classes of trees had minor patches superimposed on larger scale patterns in both groves. There may be different recruitment patterns in core (i.e., central) areas compared with peripheral areas of sequoia groves; core areas of both groves had more small live sequoias and dead sequoias than peripheral areas of the groves. Higher densities of sequoias and, perhaps, more rapid turnover of individuals in core areas may indicate (i) differences in disturbance histories and favorability of microsites in the core and peripheral areas of groves; (ii) different responses to disturbance due to shifts in the species composition of the stand and thus, the relative influences of intra- to inter-specific competition; or (iii) slower growth or lower survivorship rates in marginal habitat (i.e., peripheral areas).

Mobility, expansion and management of a multi-species scuba diving fishery in East Africa.

PubMed

Eriksson, Hampus; de la Torre-Castro, Maricela; Olsson, Per

2012-01-01

Scuba diving fishing, predominantly targeting sea cucumbers, has been documented to occur in an uncontrolled manner in the Western Indian Ocean and in other tropical regions. Although this type of fishing generally indicates a destructive activity, little attention has been directed towards this category of fishery, a major knowledge gap and barrier to management. With the aim to capture geographic scales, fishing processes and social aspects the scuba diving fishery that operate out of Zanzibar was studied using interviews, discussions, participant observations and catch monitoring. The diving fishery was resilient to resource declines and had expanded to new species, new depths and new fishing grounds, sometimes operating approximately 250 km away from Zanzibar at depths down to 50 meters, as a result of depleted easy-access stock. The diving operations were embedded in a regional and global trade network, and its actors operated in a roving manner on multiple spatial levels, taking advantage of unfair patron-client relationships and of the insufficient management in Zanzibar. This study illustrates that roving dynamics in fisheries, which have been predominantly addressed on a global scale, also take place at a considerably smaller spatial scale. Importantly, while proposed management of the sea cucumber fishery is often generic to a simplified fishery situation, this study illustrates a multifaceted fishery with diverse management requirements. The documented spatial scales and processes in the scuba diving fishery emphasize the need for increased regional governance partnerships to implement management that fit the spatial scales and processes of the operation.

Mobility, Expansion and Management of a Multi-Species Scuba Diving Fishery in East Africa

PubMed Central

Eriksson, Hampus; de la Torre-Castro, Maricela; Olsson, Per

2012-01-01

Background Scuba diving fishing, predominantly targeting sea cucumbers, has been documented to occur in an uncontrolled manner in the Western Indian Ocean and in other tropical regions. Although this type of fishing generally indicates a destructive activity, little attention has been directed towards this category of fishery, a major knowledge gap and barrier to management. Methodology and Principal Findings With the aim to capture geographic scales, fishing processes and social aspects the scuba diving fishery that operate out of Zanzibar was studied using interviews, discussions, participant observations and catch monitoring. The diving fishery was resilient to resource declines and had expanded to new species, new depths and new fishing grounds, sometimes operating approximately 250 km away from Zanzibar at depths down to 50 meters, as a result of depleted easy-access stock. The diving operations were embedded in a regional and global trade network, and its actors operated in a roving manner on multiple spatial levels, taking advantage of unfair patron-client relationships and of the insufficient management in Zanzibar. Conclusions and Significance This study illustrates that roving dynamics in fisheries, which have been predominantly addressed on a global scale, also take place at a considerably smaller spatial scale. Importantly, while proposed management of the sea cucumber fishery is often generic to a simplified fishery situation, this study illustrates a multifaceted fishery with diverse management requirements. The documented spatial scales and processes in the scuba diving fishery emphasize the need for increased regional governance partnerships to implement management that fit the spatial scales and processes of the operation. PMID:22530034

Spatial patterns in the abundance of the coastal horned lizard

USGS Publications Warehouse

Fisher, Robert N.; Suarez, Andrew V.; Case, Ted J.

2002-01-01

Coastal horned lizards (   Phrynosoma coronatum) have undergone severe declines in southern California and are a candidate species for state and federal listing under the Endangered Species Act. Quantitative data on their habitat use, abundance, and distribution are lacking, however. We investigated the determinants of abundance for coastal horned lizards at multiple spatial scales throughout southern California. Specifically, we estimated lizard distribution and abundance by establishing 256 pitfall trap arrays clustered within 21 sites across four counties. These arrays were sampled bimonthly for 2–3 years. At each array we measured 26 “local” site descriptors and averaged these values with other “regional” measures to determine site characteristics. Our analyses were successful at identifying factors within and among sites correlated with the presence and abundance of coastal horned lizards. These factors included the absence of the invasive Argentine ant (  Linepithema humile) (and presence of native ant species eaten by the lizards), the presence of chaparral community plants, and the presence of sandy substrates. At a regional scale the relative abundance of Argentine ants was correlated with the relative amount of developed edge around a site. There was no evidence for spatial autocorrelation, even at the scale of the arrays within sites, suggesting that the determinants of the presence or absence and abundance of horned lizard can vary over relatively small spatial scales ( hundreds of meters). Our results suggest that a gap-type approach may miss some of the fine-scale determinants of species abundance in fragmented habitats.

Doubly stochastic Poisson process models for precipitation at fine time-scales

NASA Astrophysics Data System (ADS)

Ramesh, Nadarajah I.; Onof, Christian; Xie, Dichao

2012-09-01

This paper considers a class of stochastic point process models, based on doubly stochastic Poisson processes, in the modelling of rainfall. We examine the application of this class of models, a neglected alternative to the widely-known Poisson cluster models, in the analysis of fine time-scale rainfall intensity. These models are mainly used to analyse tipping-bucket raingauge data from a single site but an extension to multiple sites is illustrated which reveals the potential of this class of models to study the temporal and spatial variability of precipitation at fine time-scales.

Speciation of Soil Phosphorus Assessed by XANES Spectroscopy at Different Spatial Scales

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

Hesterberg, Dean; McNulty, Ian; Thieme, Juergen

Precise management of soil phosphorus (P) to meet competing demands of agriculture and environmental protection can benefit from more comprehensive characterization of P speciation in soils. Our objectives were to provide spatial context for spectroscopic analyses of soil P speciation in relation to molecular-scale species and landscape-scale management of P, and to compare soil P-species diversity from spectroscopic measurements at submicron and millimeter scales. The spatial range of ~26 orders of magnitude between atomic and field scales presents a challenge to upscaling and downscaling information from spectroscopic analyses of soils. Scanning fluorescence X-ray microscopy images of a 50-mm ´ 45-mmmore » area of an organic soil sample showed heterogeneous distributions of P, Al, and Si. Microscale X-ray absorption near edge structure (μ-XANES) spectra collected at the P K-edge from 12 spots on the soil sample exhibited diverse features that indicated variations in highly localized P speciation. Linear combination fitting analysis of the μ-XANES spectra included various proportions of three standards that appeared in fits for most spots and five standards that appeared in fits for one spot each. The fit to a bulk-soil spectrum was dominated by two of the common standards in the μ-XANES fits, and a fit to the sum of m-XANES spectra included four of the standards. Lastly, these results illustrate a gain in P species sensitivity from spatially resolved XANES analysis. Integrating spectroscopic analyses from multiple scales determines soil P species diversity and will ultimately help connect speciation to the chemical reactivity and mobility of P in soils.« less

Speciation of Soil Phosphorus Assessed by XANES Spectroscopy at Different Spatial Scales

DOE PAGES

Hesterberg, Dean; McNulty, Ian; Thieme, Juergen

2017-07-27

Precise management of soil phosphorus (P) to meet competing demands of agriculture and environmental protection can benefit from more comprehensive characterization of P speciation in soils. Our objectives were to provide spatial context for spectroscopic analyses of soil P speciation in relation to molecular-scale species and landscape-scale management of P, and to compare soil P-species diversity from spectroscopic measurements at submicron and millimeter scales. The spatial range of ~26 orders of magnitude between atomic and field scales presents a challenge to upscaling and downscaling information from spectroscopic analyses of soils. Scanning fluorescence X-ray microscopy images of a 50-mm ´ 45-mmmore » area of an organic soil sample showed heterogeneous distributions of P, Al, and Si. Microscale X-ray absorption near edge structure (μ-XANES) spectra collected at the P K-edge from 12 spots on the soil sample exhibited diverse features that indicated variations in highly localized P speciation. Linear combination fitting analysis of the μ-XANES spectra included various proportions of three standards that appeared in fits for most spots and five standards that appeared in fits for one spot each. The fit to a bulk-soil spectrum was dominated by two of the common standards in the μ-XANES fits, and a fit to the sum of m-XANES spectra included four of the standards. Lastly, these results illustrate a gain in P species sensitivity from spatially resolved XANES analysis. Integrating spectroscopic analyses from multiple scales determines soil P species diversity and will ultimately help connect speciation to the chemical reactivity and mobility of P in soils.« less

Spatial correlation of auroral zone geomagnetic variations

NASA Astrophysics Data System (ADS)

Jackel, B. J.; Davalos, A.

2016-12-01

Magnetic field perturbations in the auroral zone are produced by a combination of distant ionospheric and local ground induced currents. Spatial and temporal structure of these currents is scientifically interesting and can also have a significant influence on critical infrastructure.Ground-based magnetometer networks are an essential tool for studying these phenomena, with the existing complement of instruments in Canada providing extended local time coverage. In this study we examine the spatial correlation between magnetic field observations over a range of scale lengths. Principal component and canonical correlation analysis are used to quantify relationships between multiple sites. Results could be used to optimize network configurations, validate computational models, and improve methods for empirical interpolation.

Soil moisture observations using L-, C-, and X-band microwave radiometers

NASA Astrophysics Data System (ADS)

Bolten, John Dennis

The purpose of this thesis is to further the current understanding of soil moisture remote sensing under varying conditions using L-, C-, and X-band. Aircraft and satellite instruments are used to investigate the effects of frequency and spatial resolution on soil moisture sensitivity. The specific objectives of the research are to examine multi-scale observed and modeled microwave radiobrightness, evaluate new EOS Aqua Advanced Microwave Scanning Radiometer (AMSR-E) brightness temperature and soil moisture retrievals, and examine future satellite-based technologies for soil moisture sensing. The cycling of Earth's water, energy and carbon is vital to understanding global climate. Over land, these processes are largely dependent on the amount of moisture within the top few centimeters of the soil. However, there are currently no methods available that can accurately characterize Earth's soil moisture layer at the spatial scales or temporal resolutions appropriate for climate modeling. The current work uses ground truth, satellite and aircraft remote sensing data from three large-scale field experiments having different land surface, topographic and climate conditions. A physically-based radiative transfer model is used to simulate the observed aircraft and satellite measurements using spatially and temporally co-located surface parameters. A robust analysis of surface heterogeneity and scaling is possible due to the combination of multiple datasets from a range of microwave frequencies and field conditions. Accurate characterization of spatial and temporal variability of soil moisture during the three field experiments is achieved through sensor calibration and algorithm validation. Comparisons of satellite observations and resampled aircraft observations are made using soil moisture from a Numerical Weather Prediction (NWP) model in order to further demonstrate a soil moisture correlation where point data was unavailable. The influence of vegetation, spatial scaling, and surface heterogeneity on multi-scale soil moisture prediction is presented. This work demonstrates that derived soil moisture using remote sensing provides a better coverage of soil moisture spatial variability than traditional in-situ sensors. Effects of spatial scale were shown to be less significant than frequency on soil moisture sensitivity. Retrievals of soil moisture using the current methods proved inadequate under some conditions; however, this study demonstrates the need for concurrent spaceborne frequencies including L-, C, and X-band.

[Estimating medicinal yield of Seutellaria baicalensis in Beijing-Tianjin-Hebei region based on 3S technology].

PubMed

Liu, Jin-xinp; Lu, Heng; Zeng, Yan; Yue, Jian-wei; Meng, Fan-yun; Zhang, Yi-guang

2012-09-01

Resources survey of traditional Chinese medicine and reserves estimation are found to be the most important issues for the protection and utilization of traditional Chinese medicine resources, this paper used multi-spatial resolution remote sensing images (RS) , geographic information systems (GIS) and global positioning system (GPS) , to establish Scutellaria resources survey of 3S data platform. Combined with the traditional field survey methods, small-scale habitat types were established based on different skullcap reserve estimation model, which can estimate reserves of the wild Scutellaria in Beijing-Tianjin-Hebei region and improve the estimation accuracy. It can provide an important parameter for the fourth national survey of traditional Chinese medicine resources and traditional Chinese medicine reserves estimates based on 3S technology by multiple spatial scales model.

Operationalizing the social-ecological systems framework to assess sustainability.

PubMed

Leslie, Heather M; Basurto, Xavier; Nenadovic, Mateja; Sievanen, Leila; Cavanaugh, Kyle C; Cota-Nieto, Juan José; Erisman, Brad E; Finkbeiner, Elena; Hinojosa-Arango, Gustavo; Moreno-Báez, Marcia; Nagavarapu, Sriniketh; Reddy, Sheila M W; Sánchez-Rodríguez, Alexandra; Siegel, Katherine; Ulibarria-Valenzuela, José Juan; Weaver, Amy Hudson; Aburto-Oropeza, Octavio

2015-05-12

Environmental governance is more effective when the scales of ecological processes are well matched with the human institutions charged with managing human-environment interactions. The social-ecological systems (SESs) framework provides guidance on how to assess the social and ecological dimensions that contribute to sustainable resource use and management, but rarely if ever has been operationalized for multiple localities in a spatially explicit, quantitative manner. Here, we use the case of small-scale fisheries in Baja California Sur, Mexico, to identify distinct SES regions and test key aspects of coupled SESs theory. Regions that exhibit greater potential for social-ecological sustainability in one dimension do not necessarily exhibit it in others, highlighting the importance of integrative, coupled system analyses when implementing spatial planning and other ecosystem-based strategies.

Facing the scaling problem: A multi-methodical approach to simulate soil erosion at hillslope and catchment scale

NASA Astrophysics Data System (ADS)

Schmengler, A. C.; Vlek, P. L. G.

2012-04-01

Modelling soil erosion requires a holistic understanding of the sediment dynamics in a complex environment. As most erosion models are scale-dependent and their parameterization is spatially limited, their application often requires special care, particularly in data-scarce environments. This study presents a hierarchical approach to overcome the limitations of a single model by using various quantitative methods and soil erosion models to cope with the issues of scale. At hillslope scale, the physically-based Water Erosion Prediction Project (WEPP)-model is used to simulate soil loss and deposition processes. Model simulations of soil loss vary between 5 to 50 t ha-1 yr-1 dependent on the spatial location on the hillslope and have only limited correspondence with the results of the 137Cs technique. These differences in absolute soil loss values could be either due to internal shortcomings of each approach or to external scale-related uncertainties. Pedo-geomorphological soil investigations along a catena confirm that estimations by the 137Cs technique are more appropriate in reflecting both the spatial extent and magnitude of soil erosion at hillslope scale. In order to account for sediment dynamics at a larger scale, the spatially-distributed WaTEM/SEDEM model is used to simulate soil erosion at catchment scale and to predict sediment delivery rates into a small water reservoir. Predicted sediment yield rates are compared with results gained from a bathymetric survey and sediment core analysis. Results show that specific sediment rates of 0.6 t ha-1 yr-1 by the model are in close agreement with observed sediment yield calculated from stratigraphical changes and downcore variations in 137Cs concentrations. Sediment erosion rates averaged over the entire catchment of 1 to 2 t ha-1 yr-1 are significantly lower than results obtained at hillslope scale confirming an inverse correlation between the magnitude of erosion rates and the spatial scale of the model. The study has shown that the use of multiple methods facilitates the calibration and validation of models and might provide a more accurate measure for soil erosion rates in ungauged catchments. Moreover, the approach could be used to identify the most appropriate working and operational scales for soil erosion modelling.

Design of an omnidirectional single-point photodetector for large-scale spatial coordinate measurement

NASA Astrophysics Data System (ADS)

Xie, Hongbo; Mao, Chensheng; Ren, Yongjie; Zhu, Jigui; Wang, Chao; Yang, Lei

2017-10-01

In high precision and large-scale coordinate measurement, one commonly used approach to determine the coordinate of a target point is utilizing the spatial trigonometric relationships between multiple laser transmitter stations and the target point. A light receiving device at the target point is the key element in large-scale coordinate measurement systems. To ensure high-resolution and highly sensitive spatial coordinate measurement, a high-performance and miniaturized omnidirectional single-point photodetector (OSPD) is greatly desired. We report one design of OSPD using an aspheric lens, which achieves an enhanced reception angle of -5 deg to 45 deg in vertical and 360 deg in horizontal. As the heart of our OSPD, the aspheric lens is designed in a geometric model and optimized by LightTools Software, which enables the reflection of a wide-angle incident light beam into the single-point photodiode. The performance of home-made OSPD is characterized with working distances from 1 to 13 m and further analyzed utilizing developed a geometric model. The experimental and analytic results verify that our device is highly suitable for large-scale coordinate metrology. The developed device also holds great potential in various applications such as omnidirectional vision sensor, indoor global positioning system, and optical wireless communication systems.

Annual water, sediment, nutrient, and organic carbon fluxes in river basins: A global meta-analysis as a function of scale

NASA Astrophysics Data System (ADS)

Mutema, M.; Chaplot, V.; Jewitt, G.; Chivenge, P.; Blöschl, G.

2015-11-01

Process controls on water, sediment, nutrient, and organic carbon exports from the landscape through runoff are not fully understood. This paper provides analyses from 446 sites worldwide to evaluate the impact of environmental factors (MAP and MAT: mean annual precipitation and temperature; CLAY and BD: soil clay content and bulk density; S: slope gradient; LU: land use) on annual exports (RC: runoff coefficients; SL: sediment loads; TOCL: organic carbon losses; TNL: nitrogen losses; TPL: phosphorus losses) from different spatial scales. RC was found to increase, on average, from 18% at local scale (in headwaters), 25% at microcatchment and subcatchment scale (midreaches) to 41% at catchment scale (lower reaches of river basins) in response to multiple factors. SL increased from microplots (468 g m-2 yr-1) to plots (901 g m-2 yr-1), accompanied by decreasing TOCL and TNL. Climate was a major control masking the effects of other factors. For example, RC, SL, TOCL, TNL, and TPL tended to increase with MAP at all spatial scales. These variables, however, decreased with MAT. The impact of CLAY, BD, LU, and S on erosion variables was largely confined to the hillslope scale, where RC, SL, and TOCL decreased with CLAY, while TNL and TPL increased. The results contribute to better understanding of water, nutrient, and carbon cycles in terrestrial ecosystems and should inform river basin modeling and ecosystem management. The important role of spatial climate variability points to a need for comparative research in specific environments at nested spatiotemporal scales.

Field Scale Optimization for Long-Term Sustainability of Best Management Practices in Watersheds

NASA Astrophysics Data System (ADS)

Samuels, A.; Babbar-Sebens, M.

2012-12-01

Agricultural and urban land use changes have led to disruption of natural hydrologic processes and impairment of streams and rivers. Multiple previous studies have evaluated Best Management Practices (BMPs) as means for restoring existing hydrologic conditions and reducing impairment of water resources. However, planning of these practices have relied on watershed scale hydrologic models for identifying locations and types of practices at scales much coarser than the actual field scale, where landowners have to plan, design and implement the practices. Field scale hydrologic modeling provides means for identifying relationships between BMP type, spatial location, and the interaction between BMPs at a finer farm/field scale that is usually more relevant to the decision maker (i.e. the landowner). This study focuses on development of a simulation-optimization approach for field-scale planning of BMPs in the School Branch stream system of Eagle Creek Watershed, Indiana, USA. The Agricultural Policy Environmental Extender (APEX) tool is used as the field scale hydrologic model, and a multi-objective optimization algorithm is used to search for optimal alternatives. Multiple climate scenarios downscaled to the watershed-scale are used to test the long term performance of these alternatives and under extreme weather conditions. The effectiveness of these BMPs under multiple weather conditions are included within the simulation-optimization approach as a criteria/goal to assist landowners in identifying sustainable design of practices. The results from these scenarios will further enable efficient BMP planning for current and future usage.

Effects of Fine-Scale Landscape Variability on Satellite-Derived Land Surface Temperature Products Over Sparse Vegetation Canopies

NASA Astrophysics Data System (ADS)

Powell, R. L.; Goulden, M.; Peterson, S.; Roberts, D. A.; Still, C. J.

2015-12-01

Temperature is a primary environmental control on biological systems and processes at a range of spatial and temporal scales, from controlling biochemical processes such as photosynthesis to influencing continental-scale species distribution. The Landsat satellite series provides a long record (since the mid-1980s) of relatively high spatial resolution thermal infrared (TIR) imagery, from which we derive land surface temperature (LST) grids. Here, we investigate fine spatial resolution factors that influence Landsat-derived LST over a spectrally and spatially heterogeneous landscape. We focus on paired sites (inside/outside a 1994 fire scar) within a pinyon-juniper scrubland in Southern California. The sites have nearly identical micro-meteorology and vegetation species composition, but distinctly different vegetation abundance and structure. The tower at the unburned site includes a number of in-situ imaging tools to quantify vegetation properties, including a thermal camera on a pan-tilt mount, allowing hourly characterization of landscape component temperatures (e.g., sunlit canopy, bare soil, leaf litter). We use these in-situ measurements to assess the impact of fine-scale landscape heterogeneity on estimates of LST, including sensitivity to (i) the relative abundance of component materials, (ii) directional effects due to solar and viewing geometry, (iii) duration of sunlit exposure for each compositional type, and (iv) air temperature. To scale these properties to Landsat spatial resolution (~100-m), we characterize the sub-pixel composition of landscape components (in addition to shade) by applying spectral mixture analysis (SMA) to the Landsat Operational Land Imager (OLI) spectral bands and test the sensitivity of the relationships established with the in-situ data at this coarser scale. The effects of vegetation abundance and cover height versus other controls on satellite-derived estimates of LST will be assessed by comparing estimates at the burned vs. unburned sites across multiple seasons (~30 dates).

FLARE: a New User Facility for Studies of Magnetic Reconnection Through Simultaneous, in-situ Measurements on MHD Scales, Ion Scales and Electron Scales

NASA Astrophysics Data System (ADS)

Ji, H.; Bhattacharjee, A.; Goodman, A.; Prager, S.; Daughton, W. S.; Cutler, R.; Fox, W.; Hoffmann, F.; Kalish, M.; Kozub, T.; Jara-Almonte, J.; Myers, C. E.; Ren, Y.; Sloboda, P.; Yamada, M.; Yoo, J.; Bale, S. D.; Carter, T.; Dorfman, S. E.; Drake, J. F.; Egedal, J.; Sarff, J.; Wallace, J.

2017-12-01

The FLARE device (Facility for Laboratory Reconnection Experiments; flare.pppl.gov) is a new laboratory experiment under construction at Princeton for the studies of magnetic reconnection in the multiple X-line regimes directly relevant to space, solar, astrophysical, and fusion plasmas, as guided by a reconnection phase diagram [Ji & Daughton, (2011)]. The whole device has been successfully assembled with rough leak check completed. The first plasmas are expected in the fall to winter. The main diagnostic is an extensive set of magnetic probe arrays to cover multiple scales from local electron scales ( ˜2 mm), to intermediate ion scales ( ˜10 cm), and global MHD scales ( ˜1 m), simultaneously providing in-situ measurements over all these relevant scales. By using these laboratory data, not only the detailed spatial profiles around each reconnecting X-line are available for direct comparisons with spacecraft data, but also the global conditions and consequences of magnetic reconnection, which are often difficult to quantify in space, can be controlled or studied systematically. The planned procedures and example topics as a user facility will be discussed in detail.

Changing Pattern of Indian Monsoon Extremes: Global and Local Factors

NASA Astrophysics Data System (ADS)

Ghosh, Subimal; Shastri, Hiteshri; Pathak, Amey; Paul, Supantha

2017-04-01

Indian Summer Monsoon Rainfall (ISMR) extremes have remained a major topic of discussion in the field of global change and hydro-climatology over the last decade. This attributes to multiple conclusions on changing pattern of extremes along with poor understanding of multiple processes at global and local scales associated with monsoon extremes. At a spatially aggregate scale, when number of extremes in the grids are summed over, a statistically significant increasing trend is observed for both Central India (Goswami et al., 2006) and all India (Rajeevan et al., 2008). However, such a result over Central India does not satisfy flied significance test of increase and no decrease (Krishnamurthy et al., 2009). Statistically rigorous extreme value analysis that deals with the tail of the distribution reveals a spatially non-uniform trend of extremes over India (Ghosh et al., 2012). This results into statistically significant increasing trend of spatial variability. Such an increase of spatial variability points to the importance of local factors such as deforestation and urbanization. We hypothesize that increase of spatial average of extremes is associated with the increase of events occurring over large region, while increase in spatial variability attributes to local factors. A Lagrangian approach based dynamic recycling model reveals that the major contributor of moisture to wide spread extremes is Western Indian Ocean, while land surface also contributes around 25-30% of moisture during the extremes in Central India. We further test the impacts of local urbanization on extremes and find the impacts are more visible over West central, Southern and North East India. Regional atmospheric simulations coupled with Urban Canopy Model (UCM) shows that urbanization intensifies extremes in city areas, but not uniformly all over the city. The intensification occurs over specific pockets of the urban region, resulting an increase in spatial variability even within the city. This also points to the need of setting up multiple weather stations over the city at a finer resolution for better understanding of urban extremes. We conclude that the conventional method of considering large scale factors is not sufficient for analysing the monsoon extremes and characterization of the same needs a blending of both global and local factors. Ghosh, S., Das, D., Kao, S-C. & Ganguly, A. R. Lack of uniform trends but increasing spatial variability in observed Indian rainfall extremes. Nature Clim. Change 2, 86-91 (2012) Goswami, B. N., Venugopal, V., Sengupta, D., Madhusoodanan, M. S. & Xavier, P. K. Increasing trend of extreme rain events over India in a warming environment. Science 314, 1442-1445 (2006). Krishnamurthy, C. K. B., Lall, U. & Kwon, H-H. Changing frequency and intensity of rainfall extremes over India from 1951 to 2003. J. Clim. 22, 4737-4746 (2009). Rajeevan, M., Bhate, J. & Jaswal, A. K. Analysis of variability and trends of extreme rainfall events over India using 104 years of gridded daily rainfall data. Geophys. Res. Lett. 35, L18707 (2008).

An event map of memory space in the hippocampus

PubMed Central

Deuker, Lorena; Bellmund, Jacob LS; Navarro Schröder, Tobias; Doeller, Christian F

2016-01-01

The hippocampus has long been implicated in both episodic and spatial memory, however these mnemonic functions have been traditionally investigated in separate research strands. Theoretical accounts and rodent data suggest a common mechanism for spatial and episodic memory in the hippocampus by providing an abstract and flexible representation of the external world. Here, we monitor the de novo formation of such a representation of space and time in humans using fMRI. After learning spatio-temporal trajectories in a large-scale virtual city, subject-specific neural similarity in the hippocampus scaled with the remembered proximity of events in space and time. Crucially, the structure of the entire spatio-temporal network was reflected in neural patterns. Our results provide evidence for a common coding mechanism underlying spatial and temporal aspects of episodic memory in the hippocampus and shed new light on its role in interleaving multiple episodes in a neural event map of memory space. DOI: http://dx.doi.org/10.7554/eLife.16534.001 PMID:27710766

Integrated photoacoustic, ultrasound and fluorescence platform for diagnostic medical imaging-proof of concept study with a tissue mimicking phantom.

PubMed

James, Joseph; Murukeshan, Vadakke Matham; Woh, Lye Sun

2014-07-01

The structural and molecular heterogeneities of biological tissues demand the interrogation of the samples with multiple energy sources and provide visualization capabilities at varying spatial resolution and depth scales for obtaining complementary diagnostic information. A novel multi-modal imaging approach that uses optical and acoustic energies to perform photoacoustic, ultrasound and fluorescence imaging at multiple resolution scales from the tissue surface and depth is proposed in this paper. The system comprises of two distinct forms of hardware level integration so as to have an integrated imaging system under a single instrumentation set-up. The experimental studies show that the system is capable of mapping high resolution fluorescence signatures from the surface, optical absorption and acoustic heterogeneities along the depth (>2cm) of the tissue at multi-scale resolution (<1µm to <0.5mm).

Separating the effects of environment and space on tree species distribution: from population to community.

PubMed

Lin, Guojun; Stralberg, Diana; Gong, Guiquan; Huang, Zhongliang; Ye, Wanhui; Wu, Linfang

2013-01-01

Quantifying the relative contributions of environmental conditions and spatial factors to species distribution can help improve our understanding of the processes that drive diversity patterns. In this study, based on tree inventory, topography and soil data from a 20-ha stem-mapped permanent forest plot in Guangdong Province, China, we evaluated the influence of different ecological processes at different spatial scales using canonical redundancy analysis (RDA) at the community level and multiple linear regression at the species level. At the community level, the proportion of explained variation in species distribution increased with grid-cell sizes, primarily due to a monotonic increase in the explanatory power of environmental variables. At the species level, neither environmental nor spatial factors were important determinants of overstory species' distributions at small cell sizes. However, purely spatial variables explained most of the variation in the distributions of understory species at fine and intermediate cell sizes. Midstory species showed patterns that were intermediate between those of overstory and understory species. At the 20-m cell size, the influence of spatial factors was stronger for more dispersal-limited species, suggesting that much of the spatial structuring in this community can be explained by dispersal limitation. Comparing environmental factors, soil variables had higher explanatory power than did topography for species distribution. However, both topographic and edaphic variables were highly spatial structured. Our results suggested that dispersal limitation has an important influence on fine-intermediate scale (from several to tens of meters) species distribution, while environmental variability facilitates species distribution at intermediate (from ten to tens of meters) and broad (from tens to hundreds of meters) scales.

Modeling fuel treatment leverage: Encounter rates, risk reduction, and suppression cost impacts

Treesearch

Matthew P. Thompson; Karin L. Riley; Dan Loeffler; Jessica R. Haas

2017-01-01

The primary theme of this study is the cost-effectiveness of fuel treatments at multiple scales of investment. We focused on the nexus of fuel management and suppression response planning, designing spatial fuel treatment strategies to incorporate landscape features that provide control opportunities that are relevant to fire operations. Our analysis explored the...

Comparison of Habitat-Specific Nutrient Removal and Release in Pacific NW Salt Marshes at Multiple Spatial Scales - CERF

EPA Science Inventory

Wetlands can be sources, sinks and transformers of nutrients, although it is their role in nutrient removal that is valued as a water purification ecosystem service. In order to quantify that service for any wetland, it is important to understand the drivers of nutrient removal w...

A framework for developing urban forest ecosystem services and goods indicators

Treesearch

Cynnamon Dobbs; Francisco J. Escobedo; Wayne C. Zipperer

2011-01-01

The social and ecological processes impacting on urban forests have been studied at multiple temporal and spatial scales in order to help us quantify, monitor, and value the ecosystem services that benefit people. Few studies have comprehensively analyzed the full suite of ecosystem services, goods (ESG), and ecosystem disservices provided by an urban forest....

Alternative Natural Resource Monitoring Strategies in the Mexican States of Jalisco and Colima

Treesearch

Cele Aguirre-Bravo; Hans Schreuder

2005-01-01

This paper presents a strategy for inventorying and monitoring the natural resources in the Mexican states of Jalisco and Colima. The strategy emphasizes a strong linkage between remote sensing with field sampling design to produce statistical summaries and spatial estimates at multiple scales and resolution levels. Outputs derived from this strategy are expected to...

Watershed management contributions to land stewardship: Case studies in the Southeast

Treesearch

Wayne T. Swank; David R. Tilley

2000-01-01

We describe three examples of watershed management studies, at different spatial scales, that provide approaches and information useful in enhancing natural resource stewardship in the southern Appalachians. A multiple use “pilot” study, initiated 35 years ago at the Coweeta Hydrologic Laboratory, demonstrates that southern Appalachian forests can be successfully...

Wildfire risk as a socioecological pathology

Treesearch

A Paige Fischer; Thomas A Spies; Toddi A Steelman; Cassandra Moseley; Bart R Johnson; John D Bailey; Alan A Ager; Patrick Bourgeron; Susan Charnley; Brandon M Collins; Jeff Kline; Jessica E Leahy; Jeremy S Littell; James DA Millington; Max Nielsen-Pincus; Christine S Olsen; Travis B Paveglio; Christopher I Roos; Michelle M Steen-Adams; Forrest R Stevens; Jelena Vukomanovic; Eric White; David MJS Bowman

2016-01-01

Wildfire risk in temperate forests has become a nearly intractable problem that can be characterized as a socioecological “pathology”: that is, a set of complex and problematic interactions among social and ecological systems across multiple spatial and temporal scales. Assessments of wildfire risk could benefit from recognizing and accounting for these interactions in...

Model-based scenario planning to develop climate change adaptation strategies for rare plant populations in grassland reserves

Treesearch

Laura Phillips-Mao; Susan M. Galatowitsch; Stephanie A. Snyder; Robert G. Haight

2016-01-01

Incorporating climate change into conservation decision-making at site and population scales is challenging due to uncertainties associated with localized climate change impacts and population responses to multiple interacting impacts and adaptation strategies. We explore the use of spatially explicit population models to facilitate scenario analysis, a conservation...

Ecological and Topographic Features of Volcanic Ash-Influenced Forest Soils

Treesearch

Mark Kimsey; Brian Gardner; Alan Busacca

2007-01-01

Volcanic ash distribution and thickness were determined for a forested region of north-central Idaho. Mean ash thickness and multiple linear regression analyses were used to model the effect of environmental variables on ash thickness. Slope and slope curvature relationships with volcanic ash thickness varied on a local spatial scale across the study area. Ash...

Landscape epidemiology and control of pathogens with cryptic and long-distance dispersal: Sudden oak death in northern Californian forests

Treesearch

Joao A. N. Filipe; Richard C. Cobb; Ross K. Meentemeyer; Christopher A. Lee; Yana S. Valachovic; Alex R. Cook; David M. Rizzo; Christopher A. Gilligan

2012-01-01

Exotic pathogens and pests threaten ecosystem service, biodiversity, and crop security globally. If an invasive agent can disperse asymptomatically over long distances, multiple spatial and temporal scales interplay, making identification of effective strategies to regulate, monitor, and control disease extremely difficult. The management of outbreaks is also...

Landscape forest cover and edge effects on songbird nest predation vary by nest predator

Treesearch

W. Andrew Cox; Frank R. III Thompson; John Faaborg

2012-01-01

Rates of nest predation for birds vary between and within species across multiple spatial scales, but we have a poor understanding of which predators drive such patterns. We video-monitored nests and identified predators at 120 nests of the Acadian Flycatcher (Empidonax virescens) and the Indigo Bunting (Passerina cyanea) at eight...

Multiple constraint analysis of regional land-surface carbon flux

Treesearch

D.P. Turner; M. Göckede; B.E. Law; W.D. Ritts; W.B. Cohen; Z. Yang; T. Hudiburg; R. Kennedy; M. Duane

2011-01-01

We applied and compared bottom-up (process model-based) and top-down (atmospheric inversion-based) scaling approaches to evaluate the spatial and temporal patterns of net ecosystem production (NEP) over a 2.5 × 105 km2 area (the state of Oregon) in the western United States. Both approaches indicated a carbon sink over this...

Small mammal communities of high elevation central Appalachian wetlands

Treesearch

Karen E. Francl; Steven B. Castleberry; W. Mark Ford

2004-01-01

We surveyed small mammal assemblages at 20 high-elevation wetlands in West Virginia and Maryland and examined relationships among mammal capture rates, richness and evenness and landscape features at multiple spatial scales. In 24,693 trap nights we captured 1451 individuals of 12 species. Small mammal species richness increased with wetland size and was negatively...

Multilevel landscape utilization of the Siberian flying squirrel: Scale effects on species habitat use.

PubMed

Remm, Jaanus; Hanski, Ilpo K; Tuominen, Sakari; Selonen, Vesa

2017-10-01

Animals use and select habitat at multiple hierarchical levels and at different spatial scales within each level. Still, there is little knowledge on the scale effects at different spatial levels of species occupancy patterns. The objective of this study was to examine nonlinear effects and optimal-scale landscape characteristics that affect occupancy of the Siberian flying squirrel, Pteromys volans , in South- and Mid-Finland. We used presence-absence data ( n  = 10,032 plots of 9 ha) and novel approach to separate the effects on site-, landscape-, and regional-level occupancy patterns. Our main results were: landscape variables predicted the placement of population patches at least twice as well as they predicted the occupancy of particular sites; the clear optimal value of preferred habitat cover for species landscape-level abundance is a surprisingly low value (10% within a 4 km buffer); landscape metrics exert different effects on species occupancy and abundance in high versus low population density regions of our study area. We conclude that knowledge of regional variation in landscape utilization will be essential for successful conservation of the species. The results also support the view that large-scale landscape variables have high predictive power in explaining species abundance. Our study demonstrates the complex response of species occurrence at different levels of population configuration on landscape structure. The study also highlights the need for data in large spatial scale to increase the precision of biodiversity mapping and prediction of future trends.

Towards Anatomic Scale Agent-Based Modeling with a Massively Parallel Spatially Explicit General-Purpose Model of Enteric Tissue (SEGMEnT_HPC)

PubMed Central

Cockrell, Robert Chase; Christley, Scott; Chang, Eugene; An, Gary

2015-01-01

Perhaps the greatest challenge currently facing the biomedical research community is the ability to integrate highly detailed cellular and molecular mechanisms to represent clinical disease states as a pathway to engineer effective therapeutics. This is particularly evident in the representation of organ-level pathophysiology in terms of abnormal tissue structure, which, through histology, remains a mainstay in disease diagnosis and staging. As such, being able to generate anatomic scale simulations is a highly desirable goal. While computational limitations have previously constrained the size and scope of multi-scale computational models, advances in the capacity and availability of high-performance computing (HPC) resources have greatly expanded the ability of computational models of biological systems to achieve anatomic, clinically relevant scale. Diseases of the intestinal tract are exemplary examples of pathophysiological processes that manifest at multiple scales of spatial resolution, with structural abnormalities present at the microscopic, macroscopic and organ-levels. In this paper, we describe a novel, massively parallel computational model of the gut, the Spatially Explicitly General-purpose Model of Enteric Tissue_HPC (SEGMEnT_HPC), which extends an existing model of the gut epithelium, SEGMEnT, in order to create cell-for-cell anatomic scale simulations. We present an example implementation of SEGMEnT_HPC that simulates the pathogenesis of ileal pouchitis, and important clinical entity that affects patients following remedial surgery for ulcerative colitis. PMID:25806784

The statistical power to detect cross-scale interactions at macroscales

USGS Publications Warehouse

Wagner, Tyler; Fergus, C. Emi; Stow, Craig A.; Cheruvelil, Kendra S.; Soranno, Patricia A.

2016-01-01

Macroscale studies of ecological phenomena are increasingly common because stressors such as climate and land-use change operate at large spatial and temporal scales. Cross-scale interactions (CSIs), where ecological processes operating at one spatial or temporal scale interact with processes operating at another scale, have been documented in a variety of ecosystems and contribute to complex system dynamics. However, studies investigating CSIs are often dependent on compiling multiple data sets from different sources to create multithematic, multiscaled data sets, which results in structurally complex, and sometimes incomplete data sets. The statistical power to detect CSIs needs to be evaluated because of their importance and the challenge of quantifying CSIs using data sets with complex structures and missing observations. We studied this problem using a spatially hierarchical model that measures CSIs between regional agriculture and its effects on the relationship between lake nutrients and lake productivity. We used an existing large multithematic, multiscaled database, LAke multiscaled GeOSpatial, and temporal database (LAGOS), to parameterize the power analysis simulations. We found that the power to detect CSIs was more strongly related to the number of regions in the study rather than the number of lakes nested within each region. CSI power analyses will not only help ecologists design large-scale studies aimed at detecting CSIs, but will also focus attention on CSI effect sizes and the degree to which they are ecologically relevant and detectable with large data sets.

A Fine-Scale Functional Logic to Convergence from Retina to Thalamus.

PubMed

Liang, Liang; Fratzl, Alex; Goldey, Glenn; Ramesh, Rohan N; Sugden, Arthur U; Morgan, Josh L; Chen, Chinfei; Andermann, Mark L

2018-05-31

Numerous well-defined classes of retinal ganglion cells innervate the thalamus to guide image-forming vision, yet the rules governing their convergence and divergence remain unknown. Using two-photon calcium imaging in awake mouse thalamus, we observed a functional arrangement of retinal ganglion cell axonal boutons in which coarse-scale retinotopic ordering gives way to fine-scale organization based on shared preferences for other visual features. Specifically, at the ∼6 μm scale, clusters of boutons from different axons often showed similar preferences for either one or multiple features, including axis and direction of motion, spatial frequency, and changes in luminance. Conversely, individual axons could "de-multiplex" information channels by participating in multiple, functionally distinct bouton clusters. Finally, ultrastructural analyses demonstrated that retinal axonal boutons in a local cluster often target the same dendritic domain. These data suggest that functionally specific convergence and divergence of retinal axons may impart diverse, robust, and often novel feature selectivity to visual thalamus. Copyright © 2018 Elsevier Inc. All rights reserved.

A multi-scale spatial approach to address environmental effects of small hydropower development.

PubMed

McManamay, Ryan A; Samu, Nicole; Kao, Shih-Chieh; Bevelhimer, Mark S; Hetrick, Shelaine C

2015-01-01

Hydropower development continues to grow worldwide in developed and developing countries. While the ecological and physical responses to dam construction have been well documented, translating this information into planning for hydropower development is extremely difficult. Very few studies have conducted environmental assessments to guide site-specific or widespread hydropower development. Herein, we propose a spatial approach for estimating environmental effects of hydropower development at multiple scales, as opposed to individual site-by-site assessments (e.g., environmental impact assessment). Because the complex, process-driven effects of future hydropower development may be uncertain or, at best, limited by available information, we invested considerable effort in describing novel approaches to represent environmental concerns using spatial data and in developing the spatial footprint of hydropower infrastructure. We then use two case studies in the US, one at the scale of the conterminous US and another within two adjoining rivers basins, to examine how environmental concerns can be identified and related to areas of varying energy capacity. We use combinations of reserve-design planning and multi-metric ranking to visualize tradeoffs among environmental concerns and potential energy capacity. Spatial frameworks, like the one presented, are not meant to replace more in-depth environmental assessments, but to identify information gaps and measure the sustainability of multi-development scenarios as to inform policy decisions at the basin or national level. Most importantly, the approach should foster discussions among environmental scientists and stakeholders regarding solutions to optimize energy development and environmental sustainability.

Spatial dependence and correlation of rainfall in the Danube catchment and its role in flood risk assessment.

NASA Astrophysics Data System (ADS)

Martina, M. L. V.; Vitolo, R.; Todini, E.; Stephenson, D. B.; Cook, I. M.

2009-04-01

The possibility that multiple catastrophic events occur within a given timespan and affect the same portfolio of insured properties may induce enhanced risk. For this reason, in the insurance industry it is of interest to characterise not only the point probability of catastrophic events, but also their spatial structure. As far as floods are concerned it is important to determine the probability of having multiple simultaneous events in different parts of the same basin: in this case, indeed, the loss in a portfolio can be significantly different. Understanding the spatial structure of the precipitation field is a necessary step for the proper modelling of the spatial dependence and correlation of river discharge. Several stochastic models are available in the scientific literature for the multi-site generation of precipitation. Although most models achieve good performance in modelling mean values, temporal variability and inter-site dependence of extremes are still delicate issues. In this work we aim at identifying the main spatial characteristics of the precipitation structure and then at analysing them in a real case. We consider data from a large network of raingauges in the Danube catchment. This catchment is a good example of a large-scale catchment where the spatial correlation of flood events can radically change the effect in term of flood damage.

Examining fire-induced forest changes using novel remote sensing technique: a case study in a mixed pine-oak forest

NASA Astrophysics Data System (ADS)

Meng, R.; Wu, J.; Zhao, F. R.; Cook, B.; Hanavan, R. P.; Serbin, S.

2017-12-01

Fire-induced forest changes has long been a central focus for forest ecology and global carbon cycling studies, and is becoming a pressing issue for global change biologists particularly with the projected increases in the frequency and intensity of fire with a warmer and drier climate. Compared with time-consuming and labor intensive field-based approaches, remote sensing offers a promising way to efficiently assess fire effects and monitor post-fire forest responses across a range of spatial and temporal scales. However, traditional remote sensing studies relying on simple optical spectral indices or coarse resolution imagery still face a number of technical challenges, including confusion or contamination of the signal by understory dynamics and mixed pixels with moderate to coarse resolution data (>= 30 m). As such, traditional remote sensing may not meet the increasing demand for more ecologically-meaningful monitoring and quantitation of fire-induced forest changes. Here we examined the use of novel remote sensing technique (i.e. airborne imaging spectroscopy and LiDAR measurement, very high spatial resolution (VHR) space-borne multi-spectral measurement, and high temporal-spatial resolution UAS-based (Unmanned Aerial System) imagery), in combination with field and phenocam measurements to map forest burn severity across spatial scales, quantify crown-scale post-fire forest recovery rate, and track fire-induced phenology changes in the burned areas. We focused on a mixed pine-oak forest undergoing multiple fire disturbances for the past several years in Long Island, NY as a case study. We demonstrate that (1) forest burn severity mapping from VHR remote sensing measurement can capture crown-scale heterogeneous fire patterns over large-scale; (2) the combination of VHR optical and structural measurements provides an efficient means to remotely sense species-level post-fire forest responses; (3) the UAS-based remote sensing enables monitoring of fire-induced forest phenology changes at unprecedented temporal and spatial resolutions. This work provides the methodological approach monitor fire-induced forest changes in a spatially explicit manner across scales, with important implications for fire-related forest management and for constraining/benchmarking process models.

Structured Multi-level Data Fusion and Modelling of Heterogeneous Environmental Data for Future Internet Applications

NASA Astrophysics Data System (ADS)

Sabeur, Zoheir; Chakravarthy, Ajay; Bashevoy, Maxim; Modafferi, Stefano

2013-04-01

The rapid increase in environmental observations which are conducted by Small to Medium Enterprise communities and volunteers using affordable in situ sensors at various scales, in addition to the more established observatories set up by environmental and space agencies using airborne and space-borne sensing technologies is generating serious amounts of BIG data at ever increasing speeds. Furthermore, the emergence of Future Internet technologies and the urgent requirements for the deployment of specific enablers for the delivery of processed environmental knowledge in real-time with advanced situation awareness to citizens has reached paramount importance. Specifically, it has become highly critical now to build and provide services which automate the aggregation of data from various sources, while surmounting the semantic gaps, conflicts and heterogeneity in data sources. The early stage aggregation of data will enable the pre-processing of data from multiple sources while reconciling the temporal gaps in measurement time series, and aligning their respective a-synchronicities. This low level type of data fusion process needs to be automated and chained to more advanced level of data fusion services specialising in observation forecasts at spaces where sensing is not deployed; or at time slices where sensing has not taken place yet. As a result, multi-level fusion services are required among the families of specific enablers for monitoring environments and spaces in the Future Internet. These have been intially deployed and piloted in the ongoing ENVIROFI project of the FI-PPP programme [1]. Automated fusion and modelling of in situ and remote sensing data has been set up and the experimentation successfully conducted using RBF networks for the spatial fusion of water quality parameters measurements from satellite and stationary buoys in the Irish Sea. The RBF networks method scales for the spatial data fusion of multiple types of observation sources. This important approach provides a strong basis for the delivery of environmental observations at desired spatial and temporal scales to multiple users with various needs of spatial and temporal resolutions. It has also led to building robust future internet specific enablers on data fusion, which can indeed be used for multiple usage areas above and beyond the environmental domains of the Future Internet. In this paper, data and processing workflow scenarios shall be described. The fucntionalities of the multi-level fusion services shall be demonstrated and made accessible to the wider communities of the Fututre Internet. [1] The Environmental Observation Web and its Service Applications within the Future Internet. ENVIROFI IP. FP7-2011-ICT-IF Pr.No: 284898 http://www.envirofi.eu/

Mathematical modelling of fluid transport and its regulation at multiple scales.

PubMed

Chara, Osvaldo; Brusch, Lutz

2015-04-01

Living matter equals water, to a first approximation, and water transport across barriers such as membranes and epithelia is vital. Water serves two competing functions. On the one hand, it is the fundamental solvent enabling random mobility of solutes and therefore biochemical reactions and intracellular signal propagation. Homeostasis of the intracellular water volume is required such that messenger concentration encodes the stimulus and not inverse volume fluctuations. On the other hand, water flow is needed for transport of solutes to and away from cells in a directed manner, threatening volume homeostasis and signal transduction fidelity of cells. Feedback regulation of fluid transport reconciles these competing objectives. The regulatory mechanisms often span across multiple spatial scales from cellular interactions up to the architecture of organs. Open questions relate to the dependency of water fluxes and steady state volumes on control parameters and stimuli. We here review selected mathematical models of feedback regulation of fluid transport at the cell scale and identify a general "core-shell" structure of such models. We propose that fluid transport models at other spatial scales can be constructed in a generalised core-shell framework, in which the core accounts for the biophysical effects of fluid transport whilst the shell reflects the regulatory mechanisms. We demonstrate the applicability of this framework for tissue lumen growth and suggest future experiments in zebrafish to test lumen size regulation mechanisms. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

An automated approach for extracting Barrier Island morphology from digital elevation models

NASA Astrophysics Data System (ADS)

Wernette, Phillipe; Houser, Chris; Bishop, Michael P.

2016-06-01

The response and recovery of a barrier island to extreme storms depends on the elevation of the dune base and crest, both of which can vary considerably alongshore and through time. Quantifying the response to and recovery from storms requires that we can first identify and differentiate the dune(s) from the beach and back-barrier, which in turn depends on accurate identification and delineation of the dune toe, crest and heel. The purpose of this paper is to introduce a multi-scale automated approach for extracting beach, dune (dune toe, dune crest and dune heel), and barrier island morphology. The automated approach introduced here extracts the shoreline and back-barrier shoreline based on elevation thresholds, and extracts the dune toe, dune crest and dune heel based on the average relative relief (RR) across multiple spatial scales of analysis. The multi-scale automated RR approach to extracting dune toe, dune crest, and dune heel based upon relative relief is more objective than traditional approaches because every pixel is analyzed across multiple computational scales and the identification of features is based on the calculated RR values. The RR approach out-performed contemporary approaches and represents a fast objective means to define important beach and dune features for predicting barrier island response to storms. The RR method also does not require that the dune toe, crest, or heel are spatially continuous, which is important because dune morphology is likely naturally variable alongshore.

Patterns of genetic diversity in the polymorphic ground snake (Sonora semiannulata).

PubMed

Cox, Christian L; Chippindale, Paul T

2014-08-01

We evaluated the genetic diversity of a snake species with color polymorphism to understand the evolutionary processes that drive genetic structure across a large geographic region. Specifically, we analyzed genetic structure of the highly polymorphic ground snake, Sonora semiannulata, (1) among populations, (2) among color morphs (3) at regional and local spatial scales, using an amplified fragment length polymorphism dataset and multiple population genetic analyses, including FST-based and clustering analytical techniques. Based upon these methods, we found that there was moderate to low genetic structure among populations. However, this diversity was not associated with geographic locality at either spatial scale. Similarly, we found no evidence for genetic divergence among color morphs at either spatial scale. These results suggest that despite dramatic color polymorphism, this phenotypic diversity is not a major driver of genetic diversity within or among populations of ground snakes. We suggest that there are two mechanisms that could explain existing genetic diversity in ground snakes: recent range expansion from a genetically diverse founder population and current or recent gene flow among populations. Our findings have further implications for the types of color polymorphism that may generate genetic diversity in snakes.

Ultrafast all-optical imaging technique using low-temperature grown GaAs/AlxGa1 - xAs multiple-quantum-well semiconductor

NASA Astrophysics Data System (ADS)

Gao, Guilong; Tian, Jinshou; Wang, Tao; He, Kai; Zhang, Chunmin; Zhang, Jun; Chen, Shaorong; Jia, Hui; Yuan, Fenfang; Liang, Lingliang; Yan, Xin; Li, Shaohui; Wang, Chao; Yin, Fei

2017-11-01

We report and experimentally demonstrate an ultrafast all-optical imaging technique capable of single-shot ultrafast recording with a picosecond-scale temporal resolution and a micron-order two-dimensional spatial resolution. A GaAs/AlxGa1 - xAs multiple-quantum-well (MQW) semiconductor with a picosecond response time, grown using molecular beam epitaxy (MBE) at a low temperature (LT), is used for the first time in ultrafast imaging technology. The semiconductor transforms the signal beam information to the probe beam, the birefringent delay crystal time-serializes the input probe beam, and the beam displacer maps different polarization probe beams onto different detector locations, resulting in two frames with an approximately 9 ps temporal separation and approximately 25 lp/mm spatial resolution in the visible range.

Dynamic hydro-climatic networks in pristine and regulated rivers

NASA Astrophysics Data System (ADS)

Botter, G.; Basso, S.; Lazzaro, G.; Doulatyari, B.; Biswal, B.; Schirmer, M.; Rinaldo, A.

2014-12-01

Flow patterns observed at-a-station are the dynamical byproduct of a cascade of processes involving different compartments of the hydro-climatic network (e.g., climate, rainfall, soil, vegetation) that regulates the transformation of rainfall into streamflows. In complex branching rivers, flow regimes result from the heterogeneous arrangement around the stream network of multiple hydrologic cascades that simultaneously occur within distinct contributing areas. As such, flow regimes are seen as the integrated output of a complex "network of networks", which can be properly characterized by its degree of temporal variability and spatial heterogeneity. Hydrologic networks that generate river flow regimes are dynamic in nature. In pristine rivers, the time-variance naturally emerges at multiple timescales from climate variability (namely, seasonality and inter-annual fluctuations), implying that the magnitude (and the features) of the water flow between two nodes may be highly variable across different seasons and years. Conversely, the spatial distribution of river flow regimes within pristine rivers involves scale-dependent transport features, as well as regional climatic and soil use gradients, which in small and meso-scale catchments (A < 103 km2) are usually mild enough to guarantee quite uniform flow regimes and high spatial correlations. Human-impacted rivers, instead, constitute hybrid networks where observed spatio-temporal patterns are dominated by anthropogenic shifts, such as landscape alterations and river regulation. In regulated rivers, the magnitude and the features of water flows from node to node may change significantly through time due to damming and withdrawals. However, regulation may impact river regimes in a spatially heterogeneous manner (e.g. in localized river reaches), with a significant decrease of spatial correlations and network connectivity. Provided that the spatial and temporal dynamics of flow regimes in complex rivers may strongly impact important biotic processes involved in the river food web (e.g. biofilm and riparian vegetation dynamics), the study of rivers as dynamic networks provides important clues to water management strategies and freshwater ecosystem studies.

Termites Are Resistant to the Effects of Fire at Multiple Spatial Scales.

PubMed

Avitabile, Sarah C; Nimmo, Dale G; Bennett, Andrew F; Clarke, Michael F

2015-01-01

Termites play an important ecological role in many ecosystems, particularly in nutrient-poor arid and semi-arid environments. We examined the distribution and occurrence of termites in the fire-prone, semi-arid mallee region of south-eastern Australia. In addition to periodic large wildfires, land managers use fire as a tool to achieve both asset protection and ecological outcomes in this region. Twelve taxa of termites were detected by using systematic searches and grids of cellulose baits at 560 sites, clustered in 28 landscapes selected to represent different fire mosaic patterns. There was no evidence of a significant relationship between the occurrence of termite species and time-since-fire at the site scale. Rather, the occurrence of species was related to habitat features such as the density of mallee trees and large logs (>10 cm diameter). Species richness was greater in chenopod mallee vegetation on heavier soils in swales, rather than Triodia mallee vegetation of the sandy dune slopes. At the landscape scale, there was little evidence that the frequency of occurrence of termite species was related to fire, and no evidence that habitat heterogeneity generated by fire influenced termite species richness. The most influential factor at the landscape scale was the environmental gradient represented by average annual rainfall. Although termites may be associated with flammable habitat components (e.g. dead wood), they appear to be buffered from the effects of fire by behavioural traits, including nesting underground, and the continued availability of dead wood after fire. There is no evidence to support the hypothesis that a fine-scale, diverse mosaic of post-fire age-classes will enhance the diversity of termites. Rather, termites appear to be resistant to the effects of fire at multiple spatial scales.

Termites Are Resistant to the Effects of Fire at Multiple Spatial Scales

PubMed Central

Avitabile, Sarah C.; Nimmo, Dale G.; Bennett, Andrew F.; Clarke, Michael F.

2015-01-01

Termites play an important ecological role in many ecosystems, particularly in nutrient-poor arid and semi-arid environments. We examined the distribution and occurrence of termites in the fire-prone, semi-arid mallee region of south-eastern Australia. In addition to periodic large wildfires, land managers use fire as a tool to achieve both asset protection and ecological outcomes in this region. Twelve taxa of termites were detected by using systematic searches and grids of cellulose baits at 560 sites, clustered in 28 landscapes selected to represent different fire mosaic patterns. There was no evidence of a significant relationship between the occurrence of termite species and time-since-fire at the site scale. Rather, the occurrence of species was related to habitat features such as the density of mallee trees and large logs (>10 cm diameter). Species richness was greater in chenopod mallee vegetation on heavier soils in swales, rather than Triodia mallee vegetation of the sandy dune slopes. At the landscape scale, there was little evidence that the frequency of occurrence of termite species was related to fire, and no evidence that habitat heterogeneity generated by fire influenced termite species richness. The most influential factor at the landscape scale was the environmental gradient represented by average annual rainfall. Although termites may be associated with flammable habitat components (e.g. dead wood), they appear to be buffered from the effects of fire by behavioural traits, including nesting underground, and the continued availability of dead wood after fire. There is no evidence to support the hypothesis that a fine-scale, diverse mosaic of post-fire age-classes will enhance the diversity of termites. Rather, termites appear to be resistant to the effects of fire at multiple spatial scales. PMID:26571383

SoilSCAPE in-Situ Observations of Soil Moisture for SMAP Validation: Pushing the Envelopes of Spatial Coverage and Energy Efficiency in Sparse Wireless Sensor Networks (Invited)

NASA Astrophysics Data System (ADS)

Moghaddam, M.; Silva, A.; Clewley, D.; Akbar, R.; Entekhabi, D.

2013-12-01

Soil Moisture Sensing Controller and oPtimal Estimator (SoilSCAPE) is a wireless in-situ sensor network technology, developed under the support of NASA ESTO/AIST program, for multi-scale validation of soil moisture retrievals from the Soil Moisture Active and Passive (SMAP) mission. The SMAP sensor suite is expected to produce soil moisture retrievals at 3 km scale from the radar instrument, at 36 km from the radiometer, and at 10 km from the combination of the two sensors. To validate the retrieved soil moisture maps at any of these scales, it is necessary to perform in-situ observations at multiple scales (ten, hundreds, and thousands of meters), representative of the true spatial variability of soil moisture fields. The most recent SoilSCAPE network, deployed in the California central valley, has been designed, built, and deployed to accomplish this goal, and is expected to become a core validation site for SMAP. The network consists of up to 150 sensor nodes, each comprised of 3-4 soil moisture sensors at various depths, deployed over a spatial extent of 36 km by 36 km. The network contains multiple sub-networks, each having up to 30 nodes, whose location is selected in part based on maximizing the land cover diversity within the 36 km cell. The network has achieved unprecedented energy efficiency, longevity, and spatial coverage using custom-designed hardware and software protocols. The network architecture utilizes a nested strategy, where a number of end devices (EDs) communicate to a local coordinator (LC) using our recently developed hardware with ultra-efficient circuitry and best-effort-timeslot allocation communication protocol. The LCs in turn communicates with the base station (BS) via text messages and a new compression scheme. The hardware and software technologies required to implement this latest deployment of the SoilSCAPE network will be presented in this paper, and several data sets resulting from the measurements will be shown. The data are available publicly in near-real-time from the project web site, and are also available and searchable via an extensive set of metadata fields through the ORNL-DAAC.