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103 results for “Spatial processes”
Spatial phylogenetic and phenotypic patterns reveal ontogenetic shifts in ecological processes of plant community assembly
The analysis of spatial phylogenetic and phenotypic structure of plant communities provides insight into the underlying processes and interactions governing their assembly, and how these may change during plant ontogeny. We used point pattern analysis to find out if saplings and adult plants are surrounded by phylogenetically and phenotypically more similar or dissimilar neighbours than expected by chance, and whether these associations change from the sapling to the adult stage. To this end, we combined information on the phylogenetic structure and eight phenotypic traits of 15 woody plant species in two Mediterranean mixed forests of southeastern Spain. At the community level, we found that the sapling bank at both sites did not show phylogenetic or phenotypic spatial patterns, but adults showed phylogenetic clustering (i.e., heterospecific neighbours were more similar than expected). At the species level, we found frequently repulsive patterns in the sapling bank of less abundant species (i.e., heterospecific sapling or adult neighbours were more dissimilar than expected) in both, phylogenetic and phenotypic analyses. For the adult stage, we found phylogenetic attraction (i.e., more similar neighbours) in just one species and phenotypic clustering in four species. The processes driving the assembly of the communities of saplings and adults leave detectable signals in the spatial phylogenetic and phenotypic structure of our two forest communities. Our findings reinforce the existence of ontogenetic shifts in the mechanisms involved in plant community assembly. Facilitation between phylogenetically distant and phenotypically divergent species favours the recruitment of less abundant species. However, processes acting later in the ontogeny ameliorate the competition between close relatives and determine the spatial structure of adult plants. Nevertheless, the role of phenotype in shaping adult-adult interactions was context- and trait-dependent. The use of spatial point pattern analysis allowed a nuanced interpretation of the phylogenetic and phenotypic structures of the plant community.
Establishment of mountain birch (Betula pubescens ssp. tortuosa) on a glacial outwash plain: spatial patterns and decadal processes
<p><span>Most of the Earth's surface has now been modified by humans. In many countries, natural and semi-natural ecosystems mostly occur as islands, isolated by land converted to agriculture and a variety of other land-uses. In this fragmented state, long-distance dispersal may be the only option for species to adapt their ranges in response to changing climate. The order of arrival of species may leave a lasting imprint on community assembly. Although mostly studied at and above the species level, such priority effects also apply at the intraspecific level. We suggest that this may be particularly important in subarctic and arctic ecosystems. </span>Mountain birch (Betula pubescens ssp. tortuosa) is characterised by great intraspecific variation. We explored spatio-temporal patterns of the first two mountain birch generations on a homogeneous, early successional glacial outwash plain in SE Iceland that was the recipient of spatially extensive long-distance dispersal ca. 30 years ago. We evaluated the decadal progress of the young population by remeasuring in 2018, tree density and growth form, plant size, and reproductive effort on 30 transects (150 m2) established in 2008 at four sites on the plain and two adjacent sites ca. 10 km away. All measured variables showed positive increases, but contrary to our predictions of converging dynamics among sites, they had significantly diverged. Thus, two of the sites (only 500 m apart) could not be distinguished in 2008 but by 2018, one of them had much faster growth rates than the other, a higher growth form index reflecting more upright tree stature, greater reproductive effort, and much greater second-generation seedling recruitment. We discuss two hypotheses that may explain the diverging dynamics, site-scale environmental heterogeneity and legacies of intraspecific priority effects. </p>
Processed CODEX Datasets from - Discovery and Generalization of Tissue Structures from Spatial Omics Data
<p>This entry provides access to processed CODEX data files of four studies analyzed in the article "Discovery and Generalization of Tissue Structures from Spatial Omics Data". Details of datasets can be found in the STAR Methods section of the article.</p> <p>For each dataset, a zip file containing multiple comma-separated values (CSV) files is included.</p> <p>Each region is assigned an unique identifier (e.g., DKD_kidney_001), and its related data files are:</p> <ul> <li>`{region_id}.cell_data.csv`, a table containing three columns: "CELL_ID", "X", and "Y". This table provides centroid locations for all cells segmented in this region.</li> <li>`{region_id}.expression.csv`, a table containing multiple columns: "CELL_ID", "DAPI", "CD45", etc. This table provides detailed protein biomarker expression quantified for all cells in this region.</li> <li>`{region_id}.scgp_annotations.csv`, a table containing two columns: "CELL_ID" and "SCGP". This table provides SCGP/SCGP-Extension annotations for all cells in this region.</li> </ul> <p>Code base for SCGP is also included in this entry. Please refer to <a href="https://gitlab.com/enable-medicine-public/scgp">https://gitlab.com/enable-medicine-public/scgp</a> for the latest codes, questions, and/or issues. Raw CODEX data and images will be accessible through links posted at the code base. Raw data will also be available from lead contact (A.E.T.) upon request.</p>
Saccades Exert Spatial Control of Motion Processing for Smooth Pursuit Eye Movements
<p>Saccades modulate the relationship between visual motion and smooth eye movement. Before a saccade, pursuit eye movements reflect a vector average of motion across the visual field. After a saccade, pursuit primarily reflects the motion of the target closest to the endpoint of the saccade. We tested the hypothesis that the saccade produces a spatial weighting of motion around the endpoint of the saccade. Using a moving pursuit stimulus that stepped to a new spatial location just before a targeting saccade, we controlled the distance between the endpoint of the saccade and the position of the moving target. We demonstrate that the smooth eye velocity following the targeting saccade weights the presaccadic visual motion inputs by the distance from their location in space to the endpoint of the saccade, defining the extent of a spatiotemporal filter for driving the eyes. The center of the filter is located at the endpoint of the saccade in space, not at the position of the fovea. The filter is stable in the face of a distracter target, is present for saccades to stationary and moving targets, and affects both the speed and direction of the postsaccadic eye movement. The spatial filter can explain the target-selecting gain change in postsaccadic pursuit, and has intriguing parallels to the process by which perceptual decisions about a restricted region of space are enhanced by attention. The effect of the spatial saccade plan on the pursuit response to a given retinal motion describes the dynamics of a coordinate transformation.</p>
Processed CODEX Datasets from - Graph deep learning for the characterization of tumour microenvironments from spatial protein profiles in tissue specimens
<p>This entry provides access to processed CODEX data files of three studies analyzed in the article "Graph deep learning for the characterization of tumour microenvironments from spatial protein profiles in tissue specimens". Details of datasets can be found in the Methods section of the article.</p> <p>For each dataset:</p> <ul> <li>A comma-separated values (CSV) file containing metadata of regions is included</li> <li>A zip file containing multiple CSV files is included: <ul> <li>`{region_id}.cell_data.csv`, a table containing three columns: "CELL_ID", "X", and "Y". This table provides centroid locations for all cells segmented in this region.</li> <li>`{region_id}.expression.csv`, a table containing multiple columns: "CELL_ID", "DAPI", "CD45", etc. This table provides detailed protein biomarker expression quantified and normalized for all cells in this region.</li> <li>`{region_id}.cell_types.csv`, a table containing two columns: "CELL_ID" and "CELL_TYPE". This table provides cell type annotations for all cells in this region.</li> <li>`{region_id}.cell_features.csv`, a table containing two columns: "CELL_ID" and "SIZE". This table provides morphology descriptors (only containing cell size for these studies) for all cells in this region.</li> </ul> </li> </ul> <p>These data files are also available through the Enable Medicine Public Study page: <a href="https://app.enablemedicine.com/portal/atlas-library/studies/92394a9f-6b48-4897-87de-999614952d94?sid=1168">https://app.enablemedicine.com/portal/atlas-library/studies/92394a9f-6b48-4897-87de-999614952d94?sid=1168</a>. Raw multiplexed immunofluorescence images will be accessible through the visualizer app of Enable Medicine Portal.</p> <p>Codes for this study are stored in <a href="https://gitlab.com/enable-medicine-public/space-gm">https://gitlab.com/enable-medicine-public/space-gm</a>. Please direct all further questions and/or issues to the gitlab repository or lead contact (A.E.T.).</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>
Including a spatial predictive process in band recovery models improves inference for Lincoln estimates of animal abundance
<p>Abundance estimation is a critical component of conservation planning, particularly for exploited species where managers set regulations to restrict harvest based on current population size. An increasingly common approach for abundance estimation is through integrated population modeling (IPM), which uses multiple data sources in a joint likelihood to estimate abundance and additional demographic parameters. Lincoln estimators are one commonly used IPM component for harvested species, which combine information on the rate and the total number of individuals harvested within an integrated band-recovery framework to estimate abundance at large scales.</p> <p>A major assumption of the Lincoln estimator is that banding and recoveries are representative of the whole population, which may be violated if major sources of spatial heterogeneity in survival or harvest rates are not incorporated into the model. We developed an approach to account for spatial variation in harvest rates using a spatial predictive process, which we incorporated into a Lincoln estimator IPM.</p> <p>We simulated data under different configurations of sample sizes, harvest rates, and sources of spatial heterogeneity in harvest rate to assess potential model bias in parameter estimates. We then applied the model to data collected from a field study of wild turkeys (<em>Meleagris gallapavo</em>) to estimate local and statewide abundance in Maine, USA.</p> <p>We found that the band recovery model that incorporated a spatial predictive process consistently provided estimates of adult and juvenile abundance with low bias across a variety of spatial configurations of harvest rate and sampling intensities. When applied to data collected on wild turkeys, a model that did not incorporate spatial heterogeneity underestimated the harvest rate in some sub-regions. Consistent with simulation results, this led to over-estimation of both local and statewide abundance.</p> <p>Our work demonstrates that a spatial predictive process is a viable mechanism to account for spatial variation in harvest rates and limit bias in abundance estimates. This approach could be extended to large-scale band recovery datasets and has applicability for the estimation of population parameters in other ecological models as well.</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>
Spatial controls on eco-evolutionary processes in microbial communities
<div> <p><span>Microorganisms are the most biodiverse life forms on our planet, yet we know little about the spatial processes underlying their ecology and evolution. Here, we highlight the importance of two spatial processes that act on individual cells – spatial intermixing of different populations and mechanical cell shoving during growth – to improve our understanding of microbial eco-evolutionary dynamics. Using an individual-based model, we show that the coexistence between slow- and fast-growing populations becomes highly constrained under two conditions: when the slow- and fast-growing populations are highly spatially intermixed and when the ability to shove other cells (both conspecific and heterospecific) is weak. The potential for evolution through plasmid-mediated horizontal gene transfer between slow- and fast- growing populations also becomes restricted in the same scenario. Our modeling highlights that ecological constraints can dampen evolutionary opportunities within microbial communities due to variation in spatial intermixing and mechanical shoving at the cellular scale.</span></p> </div>
Hearing Aid Processing and Working Memory in Realistic Spatial Conditions
ClinicalTrials.gov study NCT04521166. IPD Sharing: NO. Countries: 1. Publications: 1.
Establishment of mountain birch (Betula pubescens ssp. tortuosa) on a glacial outwash plain: spatial patterns and decadal processes
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Data for: A spatially explicit trait-based approach uncovers changes in assembly processes under warming
Open the record for dataset details and reuse information.
Including a spatial predictive process in band recovery models improves inference for Lincoln estimates of animal abundance
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Lineage-specific phylogenetic structure of boreal habitats suggests different assembly processes across phylogenetic and spatial scales
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Spatial controls on eco-evolutionary processes in microbial communities
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Understanding complex spatial dynamics from mechanistic models through spatio-temporal point processes
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Community metabarcoding reveals the relative role of environmental filtering and spatial processes in metacommunity dynamics of soil microarthropods across a mosaic of montane forests
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Spatial phylogenetic and phenotypic patterns reveal ontogenetic shifts in ecological processes of plant community assembly
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Data from: Phylogenetic and morphological relationships between nonvolant small mammals reveal assembly processes at different spatial scales
The relative roles of historical processes, environmental filtering, and ecological interactions in the organization of species assemblages vary depending on the spatial scale. We evaluated the phylogenetic and morphological relationships between species and individuals (i.e., inter- and intraspecific variability) of Neotropical nonvolant small mammals coexisting in grassland-forest ecotones, in landscapes and in regions, that is, three different scales. We used a phylogenetic tree to infer evolutionary relationships, and morphological traits as indicators of performance and niche similarities between species and individuals. Subsequently, we applied phylogenetic and morphologic indexes of diversity and distance between species to evaluate small mammal assemblage structures on the three scales. The results indicated a repulsion pattern near forest edges, showing that phylogenetically similar species coexisted less often than expected by chance. The strategies for niche differentiation might explain the phylogenetic repulsion observed at the edge. Phylogenetic and morphological clustering in the grassland and at the forest interior indicated the coexistence of closely related and ecologically similar species and individuals. Coexistence patterns were similar whether species-trait values or individual values were used. At the landscape and regional scales, assemblages showed a predominant pattern of phylogenetic and morphological clustering. Environmental filters influenced the coexistence patterns at three scales, showing the importance of phylogenetically conserved ecological tolerances in enabling taxa co-occurrence. Evidence of phylogenetic repulsion in one region indicated that other processes beyond environmental filtering are important for community assembly at broad scales. Finally, ecological interactions and environmental filtering seemed important at the local scale, while environmental filtering and historical colonization seemed important for community assembly at broader scales.
Data from: Ant diversity in Neotropical savannas: hierarchical processes acting at multiple spatial scales
1. Understanding what creates and maintains macroscale biodiversity gradients is a central focus of ecological and evolutionary research. Spatial patterns in diversity are driven by a hierarchy of factors operating at multiple scales. Historical and climatic factors drive large-scale patterns of diversity by affecting the size of regional species pools, while habitat heterogeneity or microhabitat characteristics further influence species coexistence at small scales. 2. We tested the degree to which the species-energy, historical factors, habitat heterogeneity and local environment hypotheses explain observed patterns of ant diversity across hierarchical spatial scales. 3. We sampled ground-dwelling ants at 29 sites within a Neotropical savanna region, the Brazilian Cerrado. We measured species density – an abundance-dependent diversity metric – and rarefied species richness – an abundance-independent metric – at spatial scales with varying grain sizes. For each hypothesis, two correlates were used to predict ant diversity patterns: i) species-energy: rainfall and productivity; ii) historical factors: historical variation in rainfall and refugial areas; iii) habitat heterogeneity: heterogeneity in greenness and diversity of land cover; iv) local factors: contents of sand and coarse fragments in the soil. 4. Ant diversity patterns correlated to net primary productivity and to the proportion of coarse fragments in the soil, corroborating the species-energy and local environment hypotheses, respectively. Soil negatively influenced species density, but not rarefied species richness, which was positively influenced by productivity. We found scale dependencies in the effects of soil/productivity on species density; productivity best predicted species density patterns at large scales, since sampling completeness offset the abundance-driven effects of soil. 5. Considering abundance differences may help to discern the mechanisms underlying the relationship between macroscale diversity patterns and its ecological drivers. Plant productivity affected ant diversity independently of abundance, possibly by limiting the size of regional species pools. On the other hand, soil properties had an abundance-dependent effect on ant diversity, indicating a sampling mechanism. Our findings are consistent with predictions of the hierarchical theory of diversity. Large-scale patterns of productivity limit regional diversity, an effect that cascades down to finer spatial scales, where soil properties influence the number of coexisting species.
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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.
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.