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1,868 results for “Spatial Data”
Data from: Spatial phylogenetics of the North American flora
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Data from: The influence of spatially heterogeneous anthropogenic change on bill size evolution in a coastal songbird
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Data from: Complementarity in spatial subsidies of carbon associated with resource partitioning along multiple niche axes
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Geodatabase for the Baltimore Ecosystem Study Spatial Data
The establishment of a BES Multi-User Geodatabase (BES-MUG) allows for the storage, management, and distribution of geospatial data associated with the Baltimore Ecosystem Study. At present, BES data is distributed over the internet via the BES website. While having geospatial data available for download is a vast improvement over having the data housed at individual research institutions, it still suffers from some limitations. BES-MUG overcomes these limitations; improving the quality of the geospatial data available to BES researches, thereby leading to more informed decision-making. BES-MUG builds on Environmental Systems Research Institute's (ESRI) ArcGIS and ArcSDE technology. ESRI was selected because its geospatial software offers robust capabilities. ArcGIS is implemented agency-wide within the USDA and is the predominant geospatial software package used by collaborating institutions. Commercially available enterprise database packages (DB2, Oracle, SQL) provide an efficient means to store, manage, and share large datasets. However, standard database capabilities are limited with respect to geographic datasets because they lack the ability to deal with complex spatial relationships. By using ESRI's ArcSDE (Spatial Database Engine) in conjunction with database software, geospatial data can be handled much more effectively through the implementation of the Geodatabase model. Through ArcSDE and the Geodatabase model the database's capabilities are expanded, allowing for multiuser editing, intelligent feature types, and the establishment of rules and relationships. ArcSDE also allows users to connect to the database using ArcGIS software without being burdened by the intricacies of the database itself. For an example of how BES-MUG will help improve the quality and timeless of BES geospatial data consider a census block group layer that is in need of updating. Rather than the researcher downloading the dataset, editing it, and resubmitting to through ORS, acces
Data for modelling spatial patterns and determinants of atmospheric carbon dioxide concentrations in Phoenix metro area
The purpose of this work is to describe determinants and spatial patterns of atmospheric carbon dioxide (CO2) in Phoenix, Arizona. Specifically, we use geographic information systems (GIS) and regression-based analyses to identify the human and biological factors that contribute to spatial and temporal variations in near-surface atmospheric CO2 levels. We use these factors to create estimated surfaces of CO2 for the urban area. We validate our surfaces using independently collected records of CO2 from several monitoring stations and transects. To investigate the temporal patterns and variations of CO2, we were able to generate CO2 surfaces for the early mornings and the afternoons, and on weekdays when traffic is heavy and spatially focused and on weekends when it is lighter and more spatially dispersed. Our findings suggest there is a distinct relationship between the structure of Phoenix CO2 levels and spatial patterns of human activities and vegetation densities. Morning CO2 levels are higher than afternoon levels and correspond closely to the density of traffic, population, and employment. The spatial structure of human activity explains the pattern of CO2 better on weekdays than on weekends. CO2 surfaces reflect declining densities of human activity with distance from the city center, the pattern of irrigated agriculture in the Phoenix area, and riparian habitats on the urban fringe. Spatial and temporal patterns of CO2 are useful in understanding urban climate and ecosystem processes.
Data for "Coherent phonon dynamics in spatially-separated graphene mechanical resonators"
<p>Data for "Coherent phonon dynamics in spatially-separated graphene mechanical resonators"</p>
Investigating the dynamics of microbial consortia in spatially structured environments - Source Data
<p>Source data and model code for the following publication:</p> <p><strong>Investigating the dynamics of microbial consortia in spatially structured environments</strong></p>
Data from: Mapping phosphorus hotspots in Sydney's organic wastes: a spatially-explicit inventory to facilitate urban phosphorus recycling
Phosphorus is an essential element for food production whose main global sources are becoming scarce and expensive. Furthermore, losses of phosphorus throughout the food production chain can also cause serious aquatic pollution. Recycling urban organic waste resources high in phosphorus could simultaneously address scarcity concerns for agricultural producers who reply on phosphorus fertilisers, and waste managers seeking to divert waste from landfills to decrease environmental burdens. Recycling phosphorus back to agricultural lands however requires careful logistical planning to maximize benefits and minimize costs including, processing and transportation. The first step towards such analyses is quantifying recycling potential in a spatially-explicit way. Here we present such inventories and scenarios for the Greater Sydney Basin's recyclable phosphorus supply and agricultural demand. In 2011, there was fifteen times more phosphorus available in organic waste than agricultural demand for phosphorus in Sydney. Hypothetically, if future city residents shifted to a plant-based diet, eliminated edible food waste, and removed animal production in the Greater Sydney Basin, available phosphorus supply would decrease to 7.25 kt of phosphorus per year, even when accounting for population growth by 2031, and demand would also decrease to 0.40 kt of phosphorus per year. Creating a circular phosphorus economy for Sydney, in all scenarios considered, would require effective recycling strategies which include transport outside of the Greater Sydney Basin. These spatially explicit scenarios can be used as a tool to facilitate stakeholders engagement to identify opportunities and barriers for appropriate organic waste recycling strategies.
Data from: Why we should care about movements: Using spatially explicit integrated population models to assess habitat source-sink dynamics
<p>1. Assessing the source-sink status of populations and habitats is of major importance for understanding population dynamics and for the management of natural populations. Sources produce a net surplus of individuals (per capita contribution to the metapopulation >1) and will be the main contributors for self-sustaining populations, whereas sinks produce a deficit (contribution < 1). However, making these types of assessments is generally hindered by the problem of separating mortality from permanent emigration, especially when survival probabilities as well as moved distances are habitat-specific.<br> 2. To address this long-standing issue, we propose a spatial multi-event Integrated Population Model (IPM) that incorporates habitat-specific dispersal distances of individuals. Using information about local movements, this IPM adjusts survival estimates for emigration outside the study area.<br> 3. Analyzing 24 years of data on a farmland passerine (the northern wheatear Oenanthe oenanthe) we assessed habitat-specific contributions, and hence the source-sink status and temporal variation of two key breeding habitats, while accounting for habitat- and sex-specific local dispersal distances of juveniles and adults. We then examined the sensitivity of the source-sink analysis by comparing results with and without accounting for these local movements.<br> 4. Estimates of first-year survival, and consequently habitat-specific contributions, were higher when local movement data were included. The consequences from including movement data were sex specific, with contribution shifting from sink to likely source in one habitat for males, and previously noted habitat differences for females disappearing.<br> 5. Assessing the source-sink status of habitats is extremely challenging. We show that our spatial IPM accounting for local movements can reduce biases in estimates of the contribution by different habitats, and thus reduce the overestimation of the occurrence of sink habitats. This approach allows combining all available data on demographic rates and movements, which will allow better assessment of source-sink dynamics and better informed conservation interventions.</p>
Anuran accents: Continental-scale citizen science data reveal spatial and temporal patterns of call variability
<p>Data and code associated with the 2020 publication in Ecology and Evolution (doi:10.1002/ece3.6833).</p>
Spatially anonymized data from: Novel step selection analyses on energy landscapes reveal how linear features alter migrations of soaring birds
<p>This dataset consists of spatially anonymized movement data as well as environmental covariate data to estimate energy landscape step selection selections for migratory golden eagles that summer in Alaska.</p> <ol> <li>Human modification of landscapes includes extensive addition of linear features, such as roads and transmission lines. These can alter animal movement and space use and affect the intensity of interactions among species, including predation and competition. Effects of linear features on animal movement have seen relatively little research in avian systems, despite ample evidence of their effects in mammalian systems and that some types of linear features, including both roads and transmission lines, are substantial sources of mortality.</li> <li>Here, we used satellite telemetry combined with step selection functions designed to explicitly incorporate the energy landscape (el‐SSFs) to investigate the effects of linear features and habitat on movements and space use of a large soaring bird, the golden eagle <em>Aquila chrysaetos</em>, during migration. Our sample consisted of 32 adult eagles tracked for 45 spring and 39 fall migrations from 2014 to 2017.</li> <li>Fitted el‐SSFs indicated eagles had a strong general preference for south‐facing slopes, where thermal uplift develops predictably, and that these areas are likely important aspects of migratory pathways. el‐SSFs also provided evidence that roads and railroads affected movement during both spring and fall migrations, but eagles selected areas near roads to a greater degree in spring compared to fall and at higher latitudes compared to lower latitudes. During spring, time spent near linear features often occurred during slower‐paced or stopover movements, perhaps in part to access carrion produced by vehicle collisions.</li> <li>Regardless of the behavioural mechanism of selection, use of these features could expose eagles and other soaring species to elevated risk via collision with vehicles and/or transmission lines. Linear features have previously been documented to affect the ecology of terrestrial species (e.g. large mammals) by modifying individuals' movement patterns; our work shows that these effects on movement extend to avian taxa.</li> </ol>
The spatial landscape of lung pathology during COVID-19 progression - processed IMC data
<p>Recent studies have provided insights into the pathology and immune response to coronavirus disease 2019 (COVID-19). However thorough interrogation of the interplay between infected cells and the immune system at sites of infection is lacking. We use high parameter imaging mass cytometry9 targeting the expression of 36 proteins, to investigate at single cell resolution, the cellular composition and spatial architecture of human acute lung injury including SARS-CoV-2. This spatially resolved, single-cell data unravels the disordered structure of the infected and injured lung alongside the distribution of extensive immune infiltration. Neutrophil and macrophage infiltration are hallmarks of bacterial pneumonia and COVID-19, respectively. We provide evidence that SARS-CoV-2 infects predominantly alveolar epithelial cells and induces a localized hyper-inflammatory cell state associated with lung damage. By leveraging the temporal range of COVID-19 severe fatal disease in relation to the time of symptom onset, we observe increased macrophage extravasation, mesenchymal cells, and fibroblasts abundance concomitant with increased proximity between these cell types as the disease progresses, possibly as an attempt to repair the damaged lung tissue. This spatially resolved single-cell data allowed us to develop a biologically interpretable landscape of lung pathology from a structural, immunological and clinical standpoint. This spatial single-cell landscape enabled the pathophysiological characterization of the human lung from its macroscopic presentation to the single-cell, providing an important basis for the understanding of COVID-19, and lung pathology in general.</p>
Spatially anonymized data for: Multistate Ornstein-Uhlenbeck approach for practical estimation of movement and resource selection around central places
<p>1. Home range dynamics and movement are central to a species' ecology and strongly mediate both intra- and interspecific interactions. Numerous methods have been introduced to describe animal home ranges, but most lack predictive ability and cannot capture effects of dynamic environmental patterns, such as the impacts of air and water flow on movement.</p> <p>2. Here, we develop a practical, multi-stage approach for statistical inference into the behavioral mechanisms underlying how habitat and dynamic energy landscapes---in this case how airflow increases or decreases the energetic efficiency of flight---shape animal home ranges based around central places. We validated the new approach using simulations, then applied it to a sample of 12 adult golden eagles (Aquila chrysaetos) tracked with satellite telemetry. </p> <p>3. The application to golden eagles revealed effects of habitat variables that align with predicted behavioral ecology. Further, we found that males and females partition their home ranges dynamically based on uplift. Specifically, changes in wind and sun angle drove differential space use between sexes, especially later in the breeding season when energetic demands of growing nestlings require both parents to forage more widely. </p> <p>4. This method is easily implemented using widely available programming languages and is based on a hierarchical multistate Ornstein-Uhlenbeck space use process that incorporates habitat and energy landscapes. The underlying mathematical properties of the model allow straightforward computation of predicted utilization distributions, permitting estimation of home range size and visualization of space use patterns under varying conditions.</p>
Data from: Mountain Plover habitat selection and nest survival in relation to weather variability and spatial attributes of Black-tailed Prairie Dog disturbance
<p>Habitat loss and altered disturbance regimes have led to declines in many species of grassland and sagebrush birds, including the imperiled Mountain Plover (<i>Charadrius montanus</i>). In certain parts of their range Mountain Plovers rely almost exclusively on Black-Tailed Prairie Dog (<i>Cynomys ludovicianus</i>) colonies as nesting habitat. Previous studies have examined Mountain Plover nest and brood survival on prairie dog colonies, but little is known about how colony size and shape influence these vital rates or patterns of habitat selection. We examined how 1) adult habitat utilization, 2) nest-site selection, and 3) nest success responded to a suite of local- and site-level variables on large prairie dog colony complexes in northeastern Wyoming. Abundance of adult Mountain Plovers was highest on points within older, "medium"-sized (100–500 ha) colonies with high cover of annual forbs and bare ground (5.8 birds/km<sup>2</sup>), but lower on extremely large (>2000 ha) colonies (2.1 birds/km<sup>2</sup>). Nest sites were characterized by high proportions of annual forbs and bare ground and low cactus cover and vegetation height. Nest survival was higher for older nests, and nests with lower cactus cover, and decreased with increasing temperatures. Uncertainty was high for models of daily nest survival, potentially because of two competing sources of nest failure: nest depredation and nest abandonment or inviability of eggs. Drivers of these two sources of nest failure differed, with inclement weather and higher temperatures associated with nest abandonment or egg inviability. We highlight how prairie dogs alter vegetation structure and bare ground heterogeneously across the landscape, and how this in turn influences bird abundance and nest distribution at different temporal and spatial scales. Furthermore, our work reveals how partitioning the causes of nest failure during nest survival analyses enhances understanding of survival rate covariates.</p>
Data from: Spatially-explicit avian frugivory, fruit availability, and seed rain in a latitudinal gradient of the Americas
<p>Network metrics are widely used to infer the roles of mutualistic animals in plant communities and to predict the effect of species' loss. However, their empirical validation is scarce. Here we parameterized a joint species model of frugivory and seed dispersal with bird movement and foraging data from tropical and temperate communities. With this model we investigate the effect of frugivore loss on seed rain, and compare our predictions to those of standard coextinction models and network metrics. Topological coextinction models underestimated species loss after the removal of highly-linked frugivores with unique foraging behaviors. Network metrics informed about changes in seed rain quantity after frugivore loss. However, changes in seed rain composition were only predicted by partner diversity. Nestedness, closeness, and d' specialization could not anticipate the effects of rearrangements in plant-frugivore communities following species loss. Accounting for behavioral differences among mutualists is critical to improve predictions from network models.</p>
Data from: Metacommunity structure of stream insects across three hierarchical spatial scales
<p>A major challenge in community ecology is to understand the underlying factors driving metacommunity (i.e. a set of local communities connected through species dispersal) dynamics. However, little is known about the effects of varying spatial scale on the relative importance of environmental and spatial (i.e. dispersal related) factors in shaping metacommunities and on the relevance of different dispersal pathways. Using a hierarchy of insect metacommunities at three spatial scales (a small, within-stream scale, intermediate, among-stream scale, and large, among-sub-basin scale), we assessed whether the relative importance of environmental and spatial factors shaping metacommunity structure varies predictably across spatial scales, and tested how the importance of different dispersal routes vary across spatial scales. We also studied if different dispersal ability groups differ in the balance between environmental and spatial control. Variation partitioning showed that environmental factors relative to spatial factors were more important for community composition at the within-stream scale. In contrast, spatial factors (i.e. eigenvectors from Moran's eigenvector maps) relative to environmental factors were more important at the among-sub-basin scale. These results indicate that environmental filtering is likely to be more important at the smallest scale with highest connectivity, while dispersal limitation seems to be more important at the largest scale with lowest connectivity. Community variation at the among-stream and among-sub-basin scales were strongly explained by geographical and topographical distances, indicating that overland pathways might be the main dispersal route at the larger scales among more isolated sites. The relative effect of environmental and spatial factors on insect communities varied between low and high dispersal ability groups; this variation was inconsistent among three hierarchical scales. In sum, our study indicates that spatial scale, connectivity and dispersal ability jointly shape stream metacommunities.</p>
Genotype, spatial and morphological data of adults and progeny in a natural population of Leucadendron rubrum
<p>We provide a dataset containing data on both female and male plants measured in a natural population of <em>Leucadendron rubrum</em> about plant architecture, and leaf morphology, thus informing about sexual dimorphism in this species. Genotypes of these males and females on eight microsatellites combined with corresponding genotype data in their progeny permits to undertake parentage analyses. Finally, the spatial distribution of both parents and juveniles allows to account for potential spatial biases in sampling juveniles in parentage analyses.</p>
Data from: Species' range dynamics affect the evolution of spatial variation in plasticity under environmental change
While clines in environmental tolerance and phenotypic plasticity along a single species' range have been reported repeatedly and are of special interest in the context of adaptation to environmental changes, we know little about their evolution. Recent empirical findings in ectotherms suggest that processes underlying dynamic species' ranges can give rise to spatial differences in environmental tolerance and phenotypic plasticity within species. We used individual-based simulations to investigate how plasticity and tolerance evolve in the course of three scenarios of species' range shifts and range expansions on environmental gradients. We found that regions of a species' range which experienced a longer history or larger extent of environmental change generally exhibited increased plasticity or tolerance. Such regions may be at the trailing edge when a species is tracking its ecological niche in space (e.g., in a climate change scenario) or at the front edge when a species expands into a new habitat (e.g., in an expansion/invasion scenario). Elevated tolerance and plasticity in the distribution center was detected when asymmetric environmental change (e.g., polar amplification) led to a range expansion. However, tolerance and plasticity clines were transient and slowly flattened out after range dynamics because of genetic assimilation.
Data from: Non-invasive monitoring of temporal and spatial blood flow during bone graft healing using diffuse correlation spectroscopy
Vascular infiltration and associated alterations in microvascular blood flow are critical for complete bone graft healing. Therefore, real-time, longitudinal measurement of blood flow has the potential to successfully predict graft healing outcomes. Herein, we non-invasively measure longitudinal blood flow changes in bone autografts and allografts using diffuse correlation spectroscopy in a murine femoral segmental defect model. Blood flow was measured at several positions proximal and distal to the graft site before implantation and every week post-implantation for a total of 9 weeks (autograft n = 7 and allograft n = 10). Measurements of the ipsilateral leg with the graft were compared with those of the intact contralateral control leg. Both autografts and allografts exhibited an initial increase in blood flow followed by a gradual return to baseline levels. Blood flow elevation lasted up to 2 weeks in autografts, but this duration varied from 2 to 6 weeks in allografts depending on the spatial location of the measurement. Intact contralateral control leg blood flow remained at baseline levels throughout the 9 weeks in the autograft group; however, in the allograft group, blood flow followed a similar trend to the graft leg. Blood flow difference between the graft and contralateral legs (ΔrBF), a parameter defined to estimate graft-specific changes, was elevated at 1–2 weeks for the autograft group, and at 2–4 weeks for the allograft group at the proximal and the central locations. However, distal to the graft, the allograft group exhibited significantly greater ΔrBF than the autograft group at 3 weeks post-surgery (p < 0.05). These spatial and temporal differences in blood flow supports established trends of delayed healing in allografts versus autografts.
Data from: Are categorical spatial relations encoded by shifting visual attention between objects?
Perceiving not just values, but relations between values, is critical to human cognition. We tested the predictions of a proposed mechanism for processing categorical spatial relations between two objects—the shift account of relation processing—which states that relations such as 'above' or 'below' are extracted by shifting visual attention upward or downward in space. If so, then shifts of attention should improve the representation of spatial relations, compared to a control condition of identity memory. Participants viewed a pair of briefly flashed objects and were then tested on either the relative spatial relation or identity of one of those objects. Using eye tracking to reveal participants' voluntary shifts of attention over time, we found that when initial fixation was on neither object, relational memory showed an absolute advantage for the object following an attention shift, while identity memory showed no advantage for either object. This result is consistent with the shift account of relation processing. When initial fixation began on one of the objects, identity memory strongly benefited this fixated object, while relational memory only showed a relative benefit for objects following an attention shift. This result is also consistent, although not as uniquely, with the shift account of relation processing. Taken together, we suggest that the attention shift account provides a mechanistic explanation for the overall results. This account can potentially serve as the common mechanism underlying both linguistic and perceptual representations of spatial relations.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.