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12 results for “spatial nest patterning”
Figure 2 in Spatial and temporal nesting pattern of Sea Turtles in Alas Purwo National Park, and its implications for conservation management practices
Figure 2. Trend of sea turtle nesting in the past 40 years at APNP: (A) L.olivacea, (B) C. mydas, (C) E. imbricata, and (D) D. coriacea.
Figure 1 in Spatial and temporal nesting pattern of Sea Turtles in Alas Purwo National Park, and its implications for conservation management practices
Figure 1. Study location in Alas Purwo National Park's Pancur-Cungur Coast with six hypothetical stations (dot: sector benchmark point).
Figure 4 in Spatial and temporal nesting pattern of Sea Turtles in Alas Purwo National Park, and its implications for conservation management practices
Figure 4. Number of four sea turtles nesting in each month during survey period: (A) L.olivacea, (B) C. mydas, (C) E. imbricata, and (D) D. coriacea.
Behavioral strategies and the spatial pattern formation of nesting
<p>This dataset contains data from a combined field and simulation study regarding spatial pattern formation of nesting, described in the paper: "Batsleer, F., Maes, D., Bonte, D. (2021) Behavioral strategies and the spatial pattern formation of nesting. The American Naturalist".</p> <p>The study investigates the relative importance of environmental and behavioral mechanisms in nest aggregations of the ground-nesting digger wasp <em>Bembix rostrata</em>. A field study was combined with an individual-based model that simulated the possible behaviors of spatial organisation of nesting.</p> <p>In the first analysis, a microhabitat model was built based on the location of the nests from a capture-mark-recapture study (CMR) and environmental variables NDVI (vegetation) and insolation (sun irradiance), derived from detailed remote sensing data from a drone flight.</p> <p>In the second analysis, an IBM was built that combined three possible mechanisms of nest choice to simulate the emerging spatial and network patterns found in the field. This was done by combining an environmental cue (based on the microhabitat model) and two relevant behavioral mechanisms related to local site fidelity and conspecific attraction. Strengths and combinations of the mechanisms could vary. Simulations were compared to the field data to find which combinations and strengths of mechanisms can best explain the emerging spatial and network patterns.</p> <p>The main results are that 1) the observed pattern in nature is best predicted by the simultaneous effect of a weak environmental cue and strong behavioral mechanisms. 2) individuals differ in their combination of mechanisms used and will either use local site fidelity (personal information) or conspecific attraction (inadvertent social information), but not both simultaneously. 3) We demonstrate that the nest pattern formation of a central place foraging insect cannot be considered as the sum of environmental and behavioral mechanisms.</p>
Behavioral strategies and the spatial pattern formation of nesting
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Data from: Contrasting global patterns of spatially periodic fairy circles and regular insect nests in drylands
<p>Numerical analysis of spatial pattern is widely used in ecology to describe the characteristics of floral and faunal distributions. These methods allow attribution of pattern to causal mechanisms by uncovering the specific signatures of patterns and causal agents. For example, grassland‐gap patterns called fairy circles (FCs) in Namibia and Australia are characterized by highly regular and homogenous distributions across landscapes that show spatially periodic ordering. These FCs have been suggested to be caused by both social insects and competitive plant interactions. We compared eight Namibian and Australian FC patterns and also modeled FCs to 16 patterns of social insect nests in Africa, Australia, and America that include the most regular termite mound patterns known. For pattern‐process inference, we used spatial statistics based on both nearest‐neighbor analysis and neighborhood‐density functions. None of the analyzed insect‐nest distributions attain the spatially periodic ordering that is typical of FCs. The inherently more variable patterns of termite and ant nests are commonly attributable to well documented aspects of the faunal life‐history. Our quantitative evidence from drylands shows that the more variable insect‐nest distributions in water‐limited environments cannot explain the characteristic spatial signature of FCs. The analysis demonstrates the interpretation of scale‐dependent neighborhood‐density functions and that it is the identification of unique spatial signatures in regular patterns that need to be linked to process. While our results cannot verify a specific hypothesis, they support the hypothesis that FCs in these drylands are more likely an emergent vegetation pattern caused by strong plant competition for water.</p>
data and code for "Nest entrances, spatial fidelity, and foraging patterns in the red ant Myrmica rubra: a field and theoretical study"
<p>Data set and codes used for the results, figures and simulation of the paper "Nest entrances, spatial fidelity, and foraging patterns in the red ant <em>Myrmica rubra</em>: a field and theoretical study".</p>
Data from: Contrasting global patterns of spatially periodic fairy circles and regular insect nests in drylands
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Data from: Spatial and temporal patterns of nest distribution influences sexual selection in a marine fish
In many species, the natural distribution of material resources important for reproduction can profoundly impact reproductive success among individuals and, hence, the opportunity and intensity of sexual selection. Here, we report on a field-based experiment investigating the effects of nest aggregation on sexual selection in a fish, the sand goby (Pomatoschistus minutus). We found that the distribution of potential nests (sparse versus aggregated nest treatments) affected patterns of nest colonization and reproductive success. Specifically, in the treatment with aggregated nesting resources, a greater proportion of nests remained unoccupied by sand goby males. Although the size of nesting males did not differ between treatments, eggs accumulated more rapidly when nests were sparsely distributed. We found that the opportunity for selection decreased over time with the accumulation of eggs in the nests in both the aggregated and sparse treatments. Moreover, the effect of male size on reproductive success was influenced by an interaction between nest distribution and time, with the selection gradient being highest right after nest colonization when nests were aggregated, while the opposite pattern was observed in the sparse nest treatment. Such findings highlight the vital role that environmental and social factors can play in determining the importance of male phenotypic traits (in this case, male size). More broadly, our results also underscore how the natural distribution of resources, both in space and time, can impact the strength of sexual selection acting on wild animal populations.
Figure 3 in Spatial and temporal nesting pattern of Sea Turtles in Alas Purwo National Park, and its implications for conservation management practices
Figure 3. Number of four sea turtles nesting in each hypothetical station during survey period: (A) L.olivacea, (B) C. mydas, (C) E. imbricata, and (D) D. coriacea.
Data from: Spatial and temporal patterns of nest distribution influences sexual selection in a marine fish
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NEST: Spatially-mapped cell-cell communication patterns using a deep learning-based attention mechanism
GEO Series GSE262245. Homo sapiens. 2 samples. Type: Other.
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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.