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30 results for “spatial aggregation”
Spatially Aggregated Rain Radar Forecast for the Koeln Weiden, Germany
<p>radar_forecast.csv contains time series data generated by spatial aggregation of rain radar forecasts constructed using robust local optical flow extrapolation.</p>
Рис. 8. 3D–диаграммы пространственного распределениЯ обилиЯ моллюска M. catrusiana (А), фитомассы (В), твердости грунта на глубине 5–10 см (C) и доли агрегатных фракций 3–5 мм (D) на участке № 2 в 2011 г. (единицы иЗмерениЯ осей Х и Y даны в метрах). Fig. 8. 3D–diagrams of the abundance spatial distribution of the land snail M. catrusiana (A), phytomass (B), 0–10 cm layer soil penetration resistance (C), aggregate particle size 3–5 mm (D) at the site 1 in 2011 (axes X and Y presented in meters). in Analysis of the spatial distribution patterns of the land snail populations: a geostatistic method approach
Рис. 8. 3D–диаграммы пространственного распределениЯ обилиЯ моллюска M. catrusiana (А), фитомассы (В), твердости грунта на глубине 5–10 см (C) и доли агрегатных фракций 3–5 мм (D) на участке № 2 в 2011 г. (единицы иЗмерениЯ осей Х и Y даны в метрах). Fig. 8. 3D–diagrams of the abundance spatial distribution of the land snail M. catrusiana (A), phytomass (B), 0–10 cm layer soil penetration resistance (C), aggregate particle size 3–5 mm (D) at the site 1 in 2011 (axes X and Y presented in meters).
Data from: Attack and aggregation of a major squash pest: parsing the role of plant chemistry and beetle pheromones across spatial scales
<p>1. Successful management of insect crop pests requires an understanding of the cues and spatial scales at which they function to affect rates of attack of preferred and non-preferred host plants. A long-standing conceptual framework in insect-plant ecology posits that there is hierarchical structure spanning host location, acceptance, and attack that could be exploited for integrated pest management.</p> <p>2. We investigated how plant- and insect-derived chemical cues affect successive decisions of host choice in aggregating insects, and tested predictions in the Cucurbita pepo - Acalymma vittatum system. Acalymma vittatum is an aggregating specialist beetle pest that strongly prefers zucchini (C. p. pepo) to summer squash (C. p. ovifera), two independent domesticates of C. pepo. We hypothesized that subspecies-specific plant traits, especially volatile cues, interact with the male-produced aggregation pheromone to amplify beetle preference for C. p. pepo.</p> <p>3. Differential beetle attack of C. pepo subspecies in the field is not determined by plant traits that affect host finding or differential aggregation due to pheromones: across two years, beetles had strong density-dependent attraction to both subspecies when male beetles were feeding, and no interactions between plant volatiles and the male-produced pheromone were detected. In absence of male pheromone emission, beetles were equally unattracted to plants with or without beetle feeding.</p> <p>4. In contrast, plant traits that mediate insect acceptance appear to underlie differences in preference. At a local scale, beetles did not accept and emigrated from C. p. ovifera compared to C. p. pepo. Distinct volatile emissions were observed between subspecies, but further work is needed to identify if these volatiles promote emigration.</p> <p>5. Synthesis and applications: By dissecting pest preference during successive host choice decisions, we isolated a trait with implications for pest management. Beetles on cucurbits can be managed by employing cultivars with differential susceptibility (e.g. trap cropping), and the mechanistic knowledge presented here informs best practices and limitations for on-farm applications. More broadly, pest management in diversified cropping systems can be enhanced through understanding how plant preference gradients affect herbivore movement and behavior, and plant breeders can target traits to reduce herbivory in such systems.</p>
Community patch‐dynamics governs direct and indirect nutrient recycling by aggregated animals across spatial scales
<p>Animals can have pervasive effects on ecosystems as they modify their biogeochemical and physical environments. In particular, when animals occur in high densities these effects can result in dramatic changes in the physical environment and biogeochemical hotspots or hot moments. While most research to date has focused on the direct role of animals in biogeochemical cycles, few have examined how animals indirectly influence biogeochemical cycles across scales.</p> <p>Freshwater mussels occur as spatially heterogeneous, dense and species-rich aggregations in many river ecosystems worldwide. Here we examined how mussel communities (1) directly influence the flux of particulate and dissolved nutrients and (2) indirectly effect the flux of N<sub>2</sub> production, via denitrification, across a gradient of mussel biomass and differences in community composition at the patch- (0.25 m<sup>2</sup>) and stream reach-scales (60-80 m).</p> <p>We combined measurements of ammonia (N) and soluble reactive phosphorous (P) excretion and C, N, and P biodeposition rates for ten species with biomass and distribution estimates for seven mixed-species aggregations to quantify direct mussel contributions to biogeochemical cycling and the spatial heterogeneity of their impact. Additionally, we sampled sediments at a fine spatial scale to determine how mussel biomass and richness influence potential denitrification (indirect flux) rates at the patch- and reach-scales.</p> <p>We predicted that increasing mussel biomass would lead to greater direct and indirect fluxes of nutrients, manifesting in heterogeneous nutrient redistribution within and among stream reaches. We also predicted that variation in community composition would result in differential nutrient excretion and egestion stoichiometries.</p> <p>Our results indicate that mussel aggregations directly influence soluble and particulate nutrient fluxes with community composition, particularly phylogenetic tribe composition, controlling the stoichiometry. Mussel aggregations also indirectly influenced nutrient fluxes as greater mussel biomass and species richness resulted in higher denitrification rates as mediated by their interactions with the sediments and enhancement of nutrient availability. Our results underscore the importance of patchy communities in acting as biogeochemical control points.</p>
Leaf area predicts conspecific spatial aggregation of woody species
<p><strong>Aim:</strong> Addressing how woody plant species are distributed in space can reveal inconspicuous drivers that structure plant communities. The spatial structure of conspecifics varies not only at local scales across co-existing plant species but also at larger biogeographical scales with climatic parameters and habitat properties. The possibility that biogeographical drivers shape the spatial structure of plants, however, has not received sufficient attention.</p> <p><strong>Location:</strong> Global synthesis.</p> <p><strong>Time period:</strong> 1997 - 2022.</p> <p><strong>Major taxa studied:</strong> Woody angiosperms and conifers.</p> <p><strong>Methods:</strong> We carried out a quantitative synthesis to capture the interplay between local scale and larger scale drivers. We modelled conspecific spatial aggregation as a binary response through logistic models and Ripley's L statistics and the distance at which the point process was least random with mixed effects linear models. Our predictors covered a range of plant traits, climatic predictors and descriptors of the habitat.</p> <p><strong>Results:</strong> We hypothesized that plant traits, when summarized by local scale predictors, exceed in importance biogeographical drivers in determining the spatial structure of conspecifics across woody systems. This was only the case in relation to the frequency with which we observe aggregated distributions. The probability of observing spatial aggregation and the intensity of it was higher for plant species with large leaves but further depended on climatic parameters and mycorrhiza.</p> <p><strong>Main Conclusions:</strong> Compared to climatic variables, plant traits perform poorly in explaining the spatial structure of woody plant species, even though leaf area is a decisive plant trait that is related to whether we observe homogenous spatial aggregation and its intensity. Despite the limited variance explained by our models, we found that the spatial structure of woody plants is subject to consistent biogeographical constraints and that these exceed beyond descriptors of individual species, which we captured here through leaf area.</p>
Spatial aggregation and seedling survival of the Borneo Ironwood (Eusideroxylon zwageri)
<b>Description: </b><p>This dataset was collected by the Imperial College London MRes Tropical Forest Ecology Field Course as a group project in Maliau Basin. Fieldwork was carried out on 29 Jan - 1 Feb 2018. A 4-ha plot was set up to assess the spatial aggregation of the Borneo Ironwood (Eusideroxylon zwageri, local name Belian) and seedling survival. All trees with DBH >1cm were mapped with XY coordinate rounded to nearest 1m. DBH class was rounded down to the nearest 10cm, e.g. size 10, 20, 30 etc. Size class 1 refers to trees with DBH between 1 and 10cm. A swamp area on the north and northeast of ~1-ha was not assessible hence data defficient, but as Belian is not known to growth in water logged conditions the species was presumed to be absent in this swamp area. Belian seedlings were surveyed in 540 5x5m subplots in the centre zone of the 4-ha plot. In each seedling plot, healthy and damaged (primarily herbivory damage by mammals, defined as damaged when top shoot, i.e. apical meristem, was missing). Other variables recorded in seedling plots include slope angle and ground vegetation cover.</p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/152"><b>MRes Tropical Forest Ecology Field Course</b></a></p><p><b>Funding: </b>These data were collected as part of research funded by: </p><ul><li>Natural Environment Research Council (Directed grant, NE/P00363X/1, <a href="https://gtr.ukri.org/projects?ref=NE%2FP00363X%2F1">https://gtr.ukri.org/projects?ref=NE%2FP00363X%2F1</a>)</li><li>Imperial College London (MRes Tropical Forest Ecology field course program)</li></ul><p>This dataset is released under the CC-BY 4.0 licence, requiring that you cite the dataset in any outputs, but has the additional condition that you acknowledge the contribution of these funders in any outputs.</p><p></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=277">here</a></p><p><b>Files: </b>This consists of 1 file: Belian_data_for_SAFE_upload_LQ_10Jan_2019.xlsx</p><p><b>Belian_data_for_SAFE_upload_LQ_10Jan_2019.xlsx</b></p><p>This file contains dataset metadata and 2 data tables:</p><ol><li><p><b>Belian tree coordinates</b> (described in worksheet Belian trees)</p><p>Description: All trees with DBH >1cm were mapped in a 4-ha plot with XY coordinate rounded to nearest 1m. Each row corresponds to a Belian tree. DBH class was rounded down to the nearest 10cm, e.g. size 10, 20, 30 etc. Size class 1 refers to trees with DBH between 1 and 10cm. A swamp area on the north and northeast of ~1-ha was not assessible hence data defficient, but as Belian is not known to growth in water logged conditions the species was presumed to be absent in this swamp area.</p><p>Number of fields: 9</p><p>Number of data rows: 91</p><p>Fields: </p><ul><li><b>X10</b>: X coordinate of the southwest corner of 10x10 m subplot (Field type: Numeric)</li><li><b>Y10</b>: Y coordinate of the southwest corner of 10x10 m subplot (Field type: Numeric)</li><li><b>X</b>: X coordinate within the 10x10m subplot (local X) (Field type: Numeric)</li><li><b>Y</b>: Y coordinate within the 10x10m subplot (local Y) (Field type: Numeric)</li><li><b>class</b>: DBH rounded down to the nearest 10cm, e.g. size class 10, 20, 30 etc. Size class 1 refers to trees with DBH between 1 and 10cm (Field type: Numeric Trait)</li><li><b>remark</b>: remark on whether tree is a resprout from the base of an older tree and other tree condition information (Field type: Comments)</li><li><b>collected_by</b>: members of field teams: 4 groups of 4 students each (Field type: Comments)</li><li><b>X_coord</b>: X coordinate within the 4-ha plot (global X) (Field type: Numeric)</li><li><b>Y_coord</b>: Y coordinate within the 4-ha plot (global Y) (Field type: Numeric)</li></ul></li><li><p><b>Belian seedling plots</b> (described in worksheet Belian seedlings)</p><p>Description: Belian seedlings were surveyed in 540 5x5m subplots in the centre zone of the 4-ha plot. Each row corresponds to a seedling plot. In each seedling plot, healthy and damaged (primarily herbivory damage by mammals, defined as damaged when top shoot, i.e. apical meristem, was missing). Other variables recorded in seedling plots include slope angle and ground vegetation cover.</p><p>Number of fields: 10</p><p>Number of data rows: 540</p><p>Fields: </p><ul><li><b>X10</b>: X coordinate of the southwest corner of 10x10 m subplot (Field type: Numeric)</li><li><b>Y10</b>: Y coordinate of the southwest corner of 10x10 m subplot (Field type: Numeric)</li><li><b>healthy</b>: count of healthy Belian seedlings within 5x5m plot. "healthy" is defined as opposed to "damaged" (see next data column) (Field type: Abundance)</li><li><b>damaged</b>: count of damaged Belian seedlings within 5x5m plot. "damaged" is defined as when a seedling suffered severe herbivory damage (including dead seedlings) with the apical meristem entirely missing (eaten by mammals) (Field type: Abundance)</li><li><b>slope</b>: mean slope angle for each seedling subplot, a measure of habitat topography (Field type: Numeric)</li><li><b>veg_cover</b>: ground vegetation cover for each subplot, a measure of habitat and interspecific competition (Field type: Ordered Categorical)</li><li><b>cache</b>: when seedlings occur in dense clusters especially under fallen tree or in buttress crevices, this may indicate they were deposited there by rodents, i.e. caching (Field type: Comments)</li><li><b>remark</b>: remark on habitat. seedling plots on footpath or water should be excluded from data analysis (Field type: Comments)</li><li><b>collected_by</b>: members of field teams: 4 groups of 4 students each (Field type: Comments)</li><li><b>total</b>: total number of Belian seedlings (Field type: Abundance)</li></ul></li></ol><p><b>Date range: </b>2018-01-29 to 2018-02-01</p><p><b>Latitudinal extent: </b>4.7383 to 4.7383</p><p><b>Longitudinal extent: </b>116.9713 to 116.9713</p><p><b>Taxonomic coverage: </b><br> All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets.</p><div>Plantae<br> - Tracheophyta<br> -  - Magnoliopsida<br> -  -  - Laurales<br> -  -  -  - Lauraceae<br> -  -  -  -  - <i>Eusideroxylon</i><br> -  -  -  -  -  - <i>Eusideroxylon zwageri</i><br></div><p></p>
Leaf area predicts conspecific spatial aggregation of woody species
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Data from: Attack and aggregation of a major squash pest: parsing the role of plant chemistry and beetle pheromones across spatial scales
Open the record for dataset details and reuse information.
Community patch‐dynamics governs direct and indirect nutrient recycling by aggregated animals across spatial scales
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Data from: Whether larval amphibians school does not affect the parasite aggregation rule: testing the effects of host spatial heterogeneity in field and experimental studies
Almost all macroparasites show over-dispersed infections within natural host populations such that most parasites are distributed among a few heavily-infected individuals. Despite the importance of parasite aggregation for understanding system stability, the potential for population regulation, and super-spreading events, many questions persist about its underlying drivers. Theoretically, aggregation results from heterogeneity in host exposure, resistance, and tolerance. However, few studies have examined how host spatial arrangement – which likely affects both parasite encounter and density-dependent interactions – influences infection and dispersion, representing a critical gap in our current knowledge regarding the possible drivers of parasite aggregation. Using field data from over 165 ponds and 8,000 hosts, we evaluated how the spatial clustering of amphibian larvae within ponds 1) varied among different amphibian species, and 2), affected the distribution of parasites within the host population using Taylor's Power Law. A complementary mesocosm experiment used field-guided manipulations of the spatial arrangement of larval amphibians to create a gradient in host clustering while controlling host density, thereby testing for spatial effects on both infection success and aggregation by three different trematode species. Our field data indicated that larval amphibians exhibited significant spatial clustering that was well captured by Taylor's Power Law (R2 0.92 to 0.97 for different host species), but the residual variation only weakly correlated with observed patterns of trematode parasite over-dispersion. Correspondingly, experimental manipulation of host clustering had no effects on parasite infection success or the degree of parasite aggregation among cages or mesocosms. Given the importance of parasite over-dispersion for host populations and disease dynamics, we advocate for further investigations of host and parasite spatial aggregation, particularly studies that incorporate and/or control for heterogeneity in exposure and susceptibility.
Scripts for theory figures in: Spatial Correlations Drive Long-Range Transport and Trapping of Excitons in Single H-Aggregates: Experiment and Theory
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Aggregated Spatial Data by province GPKG Format | Biodiversity Publication Bias Compromises Setting Conservation Priorities
<p>Result of running https://github.com/raffael-hickisch/provincer</p>
Data from: A multistate dynamic site occupancy model for spatially aggregated sessile communities
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Data from: Bay-scale patterns in the distribution, aggregation and spatial variability of larvae of benthic invertebrates
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Data from: Using partial aggregation in Spatial Capture Recapture
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Data from: Whether larval amphibians school does not affect the parasite aggregation rule: testing the effects of host spatial heterogeneity in field and experimental studies
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Plant spatial aggregation modulates the interplay between plant competition and pollinator attraction with contrasting outcomes of plant fitness
<p>Ecosystem functions such as seed production are the result of a complex interplay between competitive plant-plant interactions and mutualistic pollinator-plant interactions. In this interplay, spatial plant aggregation could work in two different directions: it could increase hetero- and conspecific competition, thus reducing seed production; but it could also attract pollinators increasing plant fitness. To shed light on how plant spatial arrangement modulates this balance, we conducted a field study in a Mediterranean annual grassland with three focal plant species with different phenology, <em>Chamaemelum fuscatum </em>(early phenology), <em>Leontodon maroccanus </em>(middle phenology) and <em>Pulicaria paludosa </em>(late phenology), and a diverse guild of pollinators (flies, bees, beetles, and butterflies). All three species showed spatial aggregation of conspecific individuals. Additionally, we found that the two mechanisms were working simultaneously: crowded neighborhoods reduced individual seed production via plant-plant competition, but they also made individual plants more attractive for some pollinator guilds, increasing visitation rates and plant fitness. The balance between these two forces varied depending on the focal species and the spatial scale considered. Therefore, our results indicate that mutualistic interactions do not always effectively compensate for competitive interactions in situations of spatial aggregation of flowering plants, at least in our study system. We highlight the importance of explicitly considering the spatial structure at different spatial scales of multitrophic interactions to better understand individual plant fitness and community dynamics.</p>
Transcriptomic and proteomic spatial profiling of tertiary lymphoid aggregates in head and neck cancer reveal spatial tissue dynamics and profiles associated with immunotherapy response.
GEO Series GSE259279. Homo sapiens. 9 samples. Type: Other.
Transcriptomic and proteomic spatial profiling of tertiary lymphoid aggregates in head and neck cancer reveal spatial tissue dynamics and profiles associated with immunotherapy response [protein]
GEO Series GSE259280. Homo sapiens. 375 samples. Type: Other.
Spatial transcriptomics Reveals Impact of APOE4 Allele on α-Synuclein Aggregation and Cell-Cell Communication in Lewy Body Dementia
GEO Series GSE293896. Homo sapiens. 10 samples. Type: Other.
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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.