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110 results for “Spatially explicit”
A framework for assessing the habitat correlates of spatially explicit population trends
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spectre: An R package to estimate spatially-explicit community composition using sparse data
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Data from: Complementary strengths of spatially-explicit and multi-species distribution models
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Data from: Continuous-time spatially explicit capture-recapture models, with an application to a jaguar camera-trap survey
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Data and code: Assessing fish-fishery dynamics from a spatially explicit metapopulation perspective reveals winners and losers in fisheries management
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Data from: Spatially-explicit depiction of a floral epiphytic bacterial community reveals role for environmental filtering within petals
<p>The microbiome of flowers (anthosphere) is an understudied compartment of the plant microbiome. Within the flower, petals represent a heterogeneous environment for microbes in terms of resources and environmental stress. Yet little is known of drivers of structure and function of the epiphytic microbial community at the within-petal scale. We characterized the petal microbiome in two co-flowering plants that differ in pattern of ultraviolet (UV) absorption along their petals. Bacterial communities were similar between plant hosts, with only rare phylogenetically distant species contributing to differences. The epiphyte community was highly culturable (75% of families) lending confidence to the spatially-explicit isolation and characterization of bacteria. In one host, petals were heterogeneous in UV absorption along their length and in these there was a negative relationship between growth rate and position on the petal, as well as lower UV tolerance in strains isolated from the UV absorbing base than from UV reflecting tip. A similar pattern was not seen in microbes isolated from a second host whose petals had uniform patterning along their length. Across strains, variation in carbon utilization and chemical tolerance followed common phylogenetic patterns. This work highlights the value of petals for spatially-explicit explorations of bacteria of the anthosphere.</p>
Data from: Mate choice strategies in a spatially-explicit model environment
Decisions about the choice of a mate can greatly impact both individual fitness and selection processes. We developed a novel agent-based model to investigate two common mate choice rules that may be used by female gray treefrogs (Hyla versicolor). In this model environment, female agents using the minimum-threshold strategy found higher quality mates and traveled shorter distances on average, compared with female agents using the best-of-n strategy. Females using the minimum-threshold strategy, however, incur significant lost opportunity costs, depending on the male population quality average. The best-of-n strategy leads to significant female:female competition that limits their ability to find high quality mates. Thus, when the sex ratio is 0.8, best-of-5 and best-of-2 strategies yield mates of nearly identical quality. Although the distance traveled by females in the mating task varied depending on male spatial distribution in the environment, this did not interact with female choice for the best-of-n or minimum-threshold strategies. By incorporating empirical data from the frogs in this temporally- and spatially-explicit model, we thus show the emergence of novel interactions of common decision-making rules with realistic environmental variables.
Spatially explicit habitat selection: testing contagion and the ideal free distribution with culex mosquitoes
<p>Since its inception, attempts have been made to improve Ideal Free Distribution (IFD) Theory in order make it better fit real-world data. Spatial contagion is a newer ecological concept that suggests the perceived quality of a patch can be affected by the quality of its neighbor patches. Here, we present a series of experiments testing for potential contagion effects, examining how contagion can interact with the IFD, and determining whether spatial context affects assessment of habitat quality. First, we tested whether the presence of conspecific competitors negatively impacts oviposition habitat selection by female mosquitoes (<em>Culex restuans</em>). We then used a more complex spatial landscape to determine whether competition can create a spatial contagion effect. Finally, we examined whether the density of conspecifics can adjust the contagion effect of nutrient availability. We found that while females avoided patches containing conspecifics, there was no effect of competition/density on neighboring patches. Additionally, we found that resource availability was a significant predictor of where egg rafts were laid, but resource availability did not have a contagion effect. These results provide further support for the utility of the IFD, as individuals were able to accurately assess patch-level habitat quality.<br> </p>
Spatially explicit genetic capture-recapture data from black bears in Ontario, Canada, 2017-2019
<p>The Ontario Ministry of Northern Development, Mines, Natural Resources and Forestry sampled black bear (<em>Ursus americanus</em>) DNA at baited barbed wire hair corrals on 77 independent study areas in Ontario Canada, 2017-2019. Spatially explicit capture-recapture data from these surveys (>12 000 independent, spatially referenced detections of nearly 4000 individual bears) are archived here. This data set will be cited in manuscripts presenting different analyses of the entire data set or subsets thereof.</p>
MetaSqueeze: A spatially-explicit metapopulation model for Banksia hookeriana in south-west Australia
<p>Climate change, with warming and drying weather conditions, is reducing the growth, seed production, and survival of fire-adapted plants in fire-prone regions such as Mediterranean-type ecosystems. These effects of climate change on local plant demographics have recently been shown to reduce the persistence time of local populations of the fire-killed shrub <em>Banksia hookeriana</em> dramatically. In principle, extinctions of local populations may be partly compensated by recolonization events through long-distance dispersal mechanisms of seeds, such as post-fire wind and bird-mediated dispersal, facilitating persistence in spatially structured metapopulations. However, to what degree and under which assumptions metapopulation dynamics might compensate for the drastically increased local extinction risk remains to be explored. Given the long timespans involved and the complexity of interwoven local and regional processes, mechanistic, process-based models are one of the most suitable approaches to systematically explore the potential role of metapopulation dynamics and its underlying ecological assumptions for fire-prone ecosystems. Here we extend a recent mechanistic, process-based, spatially implicit population model for the well-studied fire-killed and serotinous shrub species <em>B</em><em>.</em><em> hookeriana</em> to a spatially explicit metapopulation model. We systematically tested the effects of different ecological processes and assumptions on metapopulation dynamics under past (1988–2002) and current (2003–2017) climatic conditions, including (i) effects of different spatiotemporal fires, (ii) effects of (likely) reduced intraspecific plant competition under current conditions, and (iii) effects of variation in plant performance among and within patches. In general, metapopulation dynamics had the potential to increase the overall regional persistence of <em>B</em><em>.</em><em> hookeriana</em>. However, increased population persistence only occurred under specific optimistic assumptions. In both climate scenarios, the highest persistence occurred with larger fires and intermediate to long inter-fire intervals. The assumption of lower intraspecific plant competition caused by lower densities under current conditions alone was not sufficient to increase persistence significantly. To achieve long-term persistence (defined as > 400 years) it was necessary to additionally consider empirically observed variation in plant performance among and within patches, i.e., improved habitat quality in some large habitat patches (≥ seven) that could function as source patches and a higher survival rate and seed production for a subset of plants, specifically the top 25% of flower producers based on current climate conditions monitoring data. Our model results demonstrate that the impacts of ongoing climate change on plant demographics are so severe that even under optimistic assumptions, the existing metapopulation dynamics shift to an unstable source-sink dynamic state. Based on our findings, we recommend increased research efforts to understand the consequences of intraspecific trait variation on plant demographics, emphasizing the variation of individual traits both among and within populations. From a conservation perspective, we encourage fire and land managers to revise their prescribed fire plans, which are typically short interval, small fires, as they conflict with the ecologically appropriate spatio-temporal fire regime for <em>B. hookeriana</em>, and likely as well for many other fire-killed species.</p>
R code and simulation output for Efford, M. G. & Boulanger, J. 2019. Fast evaluation of study designs for spatially explicit capture-recapture. Methods in Ecology and Evolution
<p>R code and simulation output for Efford, M. G. & Boulanger,<br> J. 2019. Fast evaluation of study designs for spatially explicit<br> capture-recapture. Methods in Ecology and Evolution In press.</p> <p>R code draws on previously published R packages 'secr' and 'secrdesign' available from CRAN:</p> <p><a href="https://CRAN.R-project.org/package=secr">https://CRAN.R-project.org/package=secr</a></p> <p><a href="https://CRAN.R-project.org/package=secrdesign">https://CRAN.R-project.org/package=secrdesign</a></p>
Dataset from: Transport and water age dynamics in soils: a comparative study of spatially-integrated and spatially-explicit models
<p>This dataset contains high-resolution vegetated lysimeter experimental dataset carried out in EPFL, Lausanne, Switzerland in March-August 2016. The lysimeter is 100 cm long with a diameter of 120 cm. During this experiment, a simultaneous spike injection of five different solutes (2,5-DFBA, 2-TFMBA, 3,4-DFBA, 2,6-DFBA, 3-TFMBA) took place on the 3rd of March 2016 at 14:00 in an hour. The solutes' mass recovery at the bottom of lysimeter was observed for these solutes.</p> <p>This dataset contains three files which are described in the following:</p> <ul> <li>"hydrologic_data.dat" contains the hourly fluxes (precipitation, irrigation, evapotranspiration measured from load cells, and the water draining at the bottom of lysimeter ) in mm/hr between the 19th of Feb-the 1st of Sep 2016.</li> <li>"tracer_data.dat" contains the tracer concentration observed at the bottom of lysimeter in mg/L. These samples are collected at variable frequencies with an approximate average of 1.5 samples per day.</li> <li>"additional_data.dat" informs you on dry mass and soil volume in the lysimeter, vegetation type, and volume of injection per solute.</li> </ul> <p> </p>
Estimating migration of the cold-tolerant leaf beetle Gonioctena quinquepunctata inside a mountain range in a spatially explicit context
<p>The cold-tolerant leaf beetle <em>Gonioctena quinquepunctata</em> displays a large but fragmented European distribution and is restricted to mountain regions in the southern part of its range. Using a RAD-seq-generated large SNP data set (> 10,000 loci), we investigated the geographic distribution of genetic variation within the Vosges mountains, where the species is common. To translate this pattern of variation in an estimate of its capacity to disperse, we simulated SNP data under a spatially explicit model of population evolution and compared the simulated and real data with an approximate Bayesian computation (ABC) approach. For this purpose, we propose a new SNP statistic summarizing genetic variation in a spatially explicit context. The estimated number of effective migrants inferred with this statistic was compared to that derived from a combination of standard population genetic statistics often used in population genetic analyses. We conducted this ABC analysis with a relatively low number of data points compared to traditional ABC analyses, because spatially explicit models require long simulation times. A test of our overall strategy was conducted with simulated data and showed that it could provide a good estimate of the level of dispersal of an organism over its continuous geographic range. We suggest that the lower number of explored data points were at least partially compensated by the much larger number of simulations per data point associated with a large SNP data set. The results of our analyses suggested that this insect disperses well within the Vosges mountains, much more than was initially expected given the current and probably past fragmentation of its habitat and given the results of previous studies on genetic variation in other mountain leaf beetles.</p>
Measurement-Based Spatially Explicit Methane Emission Inventory (EI-ME)
<p>Accurate and comprehensive assessment of methane emissions, a powerful climate warming pollutant, is a key first step in reducing these emissions, while supporting the ability to track progress toward such reductions over time. While national bottom-up source-level inventories are useful for understanding the sources of methane emissions, they are often unrepresentative across spatial scales, adn their reliance on generic emission factors produces underestimations when compared with measurement-based inventories.</p> <p>In this work, we compile and analyze previous peer-reviewed measurement-based data on facility-level methane emissions in the US oil and gas sector and use these data to develop statistically robust emissions models from which we estimate total methane emissions for the population of major US oil and gas facilities.</p> <p>This dataset (EI_ME_v1.0.gpkg) aggregates the results of this measurement-based methane emission inventory (EI-ME), which is focused on oil and gas methane emissions in the US onshore production regions. The emissions estimates are spatially resolved at 0.1 x 0.1 degree spatial scales.</p> <p>The data layers in the GeoPackage are:</p> <ul> <li><em>EI-ME_gridded_ch4_emissions:</em> estimated methane emissions, spatially resolved at 0.1x0.1 degree spatial grids</li> <li><em>EI-ME_US_oil_gas_basins:</em> major US oil and gas basin boundaries, based on <a href="https://www.eia.gov/maps/maps.php">EIA</a> basin boundary definitions.</li> <li><em>EI-ME_facility_ch4_measurements_data: </em>A compilation of previous peer-reviewed facility-level measurement-based data for oil and gas methane emissions in the US.</li> </ul> <p>We also provide a netcdf version ("EI_ME_2021_inventory_CONUS_point1_degrees_v1.nc") which includes estimated mean oil and gas methane emissions over the contiguous US (excludes Alaska) aggregated over a slightly offset spatial grid compared to the full domain in the above .gpkg.</p> <p>Complete details of the emissions model development and dataset creation can be found in the following manuscript:</p> <ul> <li><strong>How to cite: </strong>Omara, M., Himmelberger, A., MacKay, K., Williams, J. P., Benmergui, J., Sargent, M., Wofsy, S. C., and Gautam, R.: Constructing a measurement-based spatially explicit inventory of US oil and gas methane emissions (2021), Earth Syst. Sci. Data, 16, 3973–3991, https://doi.org/10.5194/essd-16-3973-2024, 2024.</li> </ul> <p>-----------------------------------------------------------------------------------------------------------------------------------------------------------</p> <p>UPDATE (10/10/2025):</p> <p>The spatially explicit measurement-based oil and gas methane emissions inventory (EI-ME) is developed by MethaneSAT, a wholly owned subsidiary of Environmental Defense Fund, to support comprehensive oil and gas methane assessment, methane source attribution, and mitigation. The inventory combines ground-based measurement-based data with statistically robust methane emissions modeling to provide representative estimates of total methane emissions for key facility categories in the contiguous US oil and gas supply chain, including well sites, natural-gas compressor stations, processing plants, crude-oil refineries, and pipelines. It is spatially resolved at 0.1x.0.1 degree spatial scales.</p> <p> Version 1 of the EI-ME inventory for the contiguous United States was published in 2024 and provided an estimate of the 2021 oil and gas methane emissions and uncertainties that are spatially resolved at 0.1x0.1 degree spatial scales.</p> <p> Here, we provide an update to the EI-ME inventory for the years 2023 and 2024. In this update, we follow the same methodology and use the same input emissions datasets as described in detail in Omara et al. (2024), https://doi.org/10.5194/essd-16-3973-2024. We incorporate the latest available oil and gas activity data for the years 2023 and 2024 based on data from Enverus Prism (<a href="http://www.eneverus.com/">www.eneverus.com</a>), supplemented with additional information from the Oil and Gas Infrastructure Mapping database (OGIM v2.7, <a href="https://doi.org/10.5281/zenodo.15103476">https://doi.org/10.5281/zenodo.15103476</a>) and global annual gas flaring data from VIIRS (Visible Infraed Imagin Radiometer Suite), available from the Earth Observation Group (<a href="https://eogdata.mines.edu/products/vnf/global_gas_flare.html">https://eogdata.mines.edu/products/vnf/global_gas_flare.html</a>).</p> <p>---</p> <p>Contact at Environmental Defense Fund: Mark Omara (momara@edf.org), Anthony Himmelberger (ahimmelberger@methanesat.org)</p> <p>---</p>
Validation of a new spatially-explicit process-based model (HETEROFOR) to simulate structurally and compositionally complex stands in Eastern North-America : Dataset
<p>This dataset is linked to the paper “Validation of a new spatially-explicit process-based model (HETEROFOR) to simulate structurally and compositionally complex stands in Eastern North-America" published in Geoscientific Model Development (https://doi.org/10.5194/gmd-16-1661-2023). It contains the installer of the model, its user guide, as well as all the input files (inventory, thinning, meteorology and soil horizons files for each stand used in the evaluation and calibration steps), the R scripts and associated data used to analyse the model outputs.</p>
Data for: A spatially explicit trait-based approach uncovers changes in assembly processes under warming
<p><span>The re-assembly of plant communities during climate warming depends on several concurrent processes. Here we present a novel framework that integrates spatially explicit sampling, plant trait information and a warming experiment to quantify shifts in these assembly processes. By accounting for spatial distance between individuals, our framework allows separation of potential signals of environmental filtering from those of different types of competition. When applied to an elevational transplant experiment in the French Alps, we found common signals of environmental filtering and competition in all communities. Signals of environmental filtering were generally stronger in alpine than in subalpine control communities, and warming reduced this filter. Competition signals depended on treatments and traits: Symmetrical competition was dominant in control and warmed alpine communities, while hierarchical competition was present in subalpine communities. Our study highlights how distance dependent frameworks can contribute to a better understanding of transient re-assembly dynamics during environmental change.</span></p>
Data from: Mate choice strategies in a spatially-explicit model environment
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Data from: Spatially-explicit depiction of a floral epiphytic bacterial community reveals role for environmental filtering within petals
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Data for: A spatially explicit trait-based approach uncovers changes in assembly processes under warming
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Data from: Spatially explicit analysis sheds new light on the Pleistocene megafaunal extinction in North America
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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.
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DANDI Archive for NWB datasets
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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.