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155 results for “interaction scale”
Data from: Density-dependent offspring interactions do not explain macroevolutionary scaling of adult size and offspring size
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Data from: Invasion complexity at large spatial scales is an emergent property of interactions among landscape characteristics and invader traits
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Large-scale metabolic interaction network of the mouse and human gut microbiota
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Data from: Frugivore biodiversity and complementarity in interaction networks enhance landscape-scale seed dispersal function
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Data from: The influence of spatial sampling scales on ant-plant interaction network architecture
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Data from: Cross-scale interactions and the distribution-abundance relationship
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Data from: Helianthus maximiliani and species fine-scale spatial pattern affect diversity interactions in reconstructed tallgrass prairies
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A method for identifying environmental stimuli and genes responsible for genotype-by-environment interactions from a large-scale multi-environment data set
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Data from: A model of urban scaling laws based on distance dependent interactions
Socio-economic related properties of a city grow faster than a linear relationship with the population, in a log–log plot, the so-called superlinear scaling. Conversely, the larger a city, the more efficient it is in the use of its infrastructure, leading to a sublinear scaling on these variables. In this work, we addressed a simple explanation for those scaling laws in cities based on the interaction range between the citizens and on the fractal properties of the cities. To this purpose, we introduced a measure of social potential which captured the influence of social interaction on the economic performance and the benefits of amenities in the case of infrastructure offered by the city. We assumed that the population density depends on the fractal dimension and on the distance-dependent interactions between individuals. The model suggests that when the city interacts as a whole, and not just as a set of isolated parts, there is improvement of the socio-economic indicators. Moreover, the bigger the interaction range between citizens and amenities, the bigger the improvement of the socio-economic indicators and the lower the infrastructure costs of the city. We addressed how public policies could take advantage of these properties to improve cities development, minimizing negative effects. Furthermore, the model predicts that the sum of the scaling exponents of social-economic and infrastructure variables are 2, as observed in the literature. Simulations with an agent-based model are confronted with the theoretical approach and they are compatible with the empirical evidences.
Data from: Differential female sociality is linked with the fine-scale structure of sexual interactions in replicate groups of red junglefowl, Gallus gallus
Recent work indicates that social structure has extensive implications for patterns of sexual selection and sexual conflict. However, little is known about the individual variation in social behaviours linking social structure to sexual interactions. Here, we use network analysis of replicate polygynandrous groups of red junglefowl (Gallus gallus) to show that the association between social structure and sexual interactions is underpinned by differential female sociality. Sexual dynamics are largely explained by a core group of highly social, younger females, which are more fecund and more polyandrous, and thus associated with more intense postcopulatory competition for males. In contrast, less fecund females from older cohorts, which tend to be socially dominant, avoid male sexual attention by clustering together and perching on branches, and preferentially reproduce with dominant males by more exclusively associating and mating with them. Collectively, these results indicate that individual females occupy subtly different social niches, and demonstrate that female sociality can be an important factor underpinning the landscape of intra-sexual competition and the emergent structure of animal societies.
Dynamics of dominance: maneuvers, contests, and assessment in the posture-scale movements of interacting zebrafish
<p>This is the dataset of the paper "<strong>Dynamics of dominance</strong>:<strong> </strong><i><strong>maneuvers, contests, and assessment in the posture-scale movements of interacting zebrafish</strong></i>".</p><h2>Contents</h2><h4>Very useful data</h4><ol><li>tracking_results.zip. This file contains the tracking results for all 22 experiments. <strong>This is the most useful file to download.</strong></li><li>fight_detection_data.zip. This file contains the data that was originally clustered to build the fight detector (see the paper). This is the same data that you need if you want to use the fight detector yourself.</li></ol><h4>Other data</h4><ol><li>Files of the form FishTank*.zip. These contain the raw output of idtracker.ai and SLEAP that were used to track the experiments. These files are only useful if you want to re-track from the very beginning. Even then, a slightly modified verison of this data is available in tracking_results.zip (for all experiments), and that may be what you want. These files are mainly for posterity.</li><li>PCA_data.zip. This is cached data that can be recomputed from the trajectory data. See the paper, and the code in the github.</li><li>tmat_and_infomap_generation_data.zip & infomap_data.zip & infomap_tau_sweep_data.zip. These contain the output of the calculations for the main infomap calculation, and the tau sweep calculation. See the paper and github.</li></ol><p> </p><h2>Code</h2><p>See <a href="https://github.com/liamshock/Dynamics_of_dominance">https://github.com/liamshock/Dynamics_of_dominance</a></p>
Supplementary material 1 from: Piry S, Berthier K, Streiff R, Cros-Arteil S, Foucart A, Tatin L, Bröder L, Hochkirch A, Chapuis M-P (2018) Fine-scale interactions between habitat quality and genetic variation suggest an impact of grazing on the critically endangered Crau Plain grasshopper (Pamphagidae: Prionotropis rhodanica). Journal of Orthoptera Research 27(1): 61-73. https://doi.org/10.3897/jor.27.15036
: Explanation note: Supplementary tables and figures.
Figure 4 from: Piry S, Berthier K, Streiff R, Cros-Arteil S, Foucart A, Tatin L, Bröder L, Hochkirch A, Chapuis M-P (2018) Fine-scale interactions between habitat quality and genetic variation suggest an impact of grazing on the critically endangered Crau Plain grasshopper (Pamphagidae: Prionotropis rhodanica). Journal of Orthoptera Research 27(1): 61-73. https://doi.org/10.3897/jor.27.15036
Figure 4 Relationships between intra-circle grasshopper density and A. Loiselle kinship coefficient, B. expected heterozygosity and C. FIS.
Figure 7 from: Piry S, Berthier K, Streiff R, Cros-Arteil S, Foucart A, Tatin L, Bröder L, Hochkirch A, Chapuis M-P (2018) Fine-scale interactions between habitat quality and genetic variation suggest an impact of grazing on the critically endangered Crau Plain grasshopper (Pamphagidae: Prionotropis rhodanica). Journal of Orthoptera Research 27(1): 61-73. https://doi.org/10.3897/jor.27.15036
Figure 7 Spatial cross-correlograms between A. grasshopper density and NDVI, B. grasshopper density and the mean genetic differentiation between individuals (MAPI cell values) and, C. NDVI and the mean genetic differentiation between individuals. The x-intercept of the spline-correlogram is the estimate of the distance at which the correlation between variables is not different than expected by chance alone. Dotted lines represent the 95% confidence envelope based on 500 bootstrap resamples.
Figure 1 from: Piry S, Berthier K, Streiff R, Cros-Arteil S, Foucart A, Tatin L, Bröder L, Hochkirch A, Chapuis M-P (2018) Fine-scale interactions between habitat quality and genetic variation suggest an impact of grazing on the critically endangered Crau Plain grasshopper (Pamphagidae: Prionotropis rhodanica). Journal of Orthoptera Research 27(1): 61-73. https://doi.org/10.3897/jor.27.15036
Figure 1 Map of France and location of A. the plain of Crau (Bouches-du-Rhône, France), B. the sampling site located between the sheepfolds 'La Grosse du Levant' and 'La Grosse du Centre', and C. the circles surveyed to detect and sample P. rhodanica. A00-A65: names of circles of the grid A; B04-B51: names of circles of the grid B; C1: additional circle of 100 m diameter (see Material and methods).
Figure 6 from: Piry S, Berthier K, Streiff R, Cros-Arteil S, Foucart A, Tatin L, Bröder L, Hochkirch A, Chapuis M-P (2018) Fine-scale interactions between habitat quality and genetic variation suggest an impact of grazing on the critically endangered Crau Plain grasshopper (Pamphagidae: Prionotropis rhodanica). Journal of Orthoptera Research 27(1): 61-73. https://doi.org/10.3897/jor.27.15036
Figure 6 Maps of A. density of grasshopper in number of individuals per hectare, B. rescale NDVI values and C. mean genetic differentiation between individuals resulting from the MAPI analysis.
Figure 3 from: Piry S, Berthier K, Streiff R, Cros-Arteil S, Foucart A, Tatin L, Bröder L, Hochkirch A, Chapuis M-P (2018) Fine-scale interactions between habitat quality and genetic variation suggest an impact of grazing on the critically endangered Crau Plain grasshopper (Pamphagidae: Prionotropis rhodanica). Journal of Orthoptera Research 27(1): 61-73. https://doi.org/10.3897/jor.27.15036
Figure 3 Illustrations of the Coussoul habitat of Prionotropis rhodanica with A. sheep accompanied by cattle egrets and B. researchers surveying the species using a circle-based method.
Figure 5 from: Piry S, Berthier K, Streiff R, Cros-Arteil S, Foucart A, Tatin L, Bröder L, Hochkirch A, Chapuis M-P (2018) Fine-scale interactions between habitat quality and genetic variation suggest an impact of grazing on the critically endangered Crau Plain grasshopper (Pamphagidae: Prionotropis rhodanica). Journal of Orthoptera Research 27(1): 61-73. https://doi.org/10.3897/jor.27.15036
Figure 5 Linear regression between genetic distance â and geographical distances computed between pairs of individuals. Variation in point density is represented by colors, from blue (low density) to red (high density).
Data from: A model of urban scaling laws based on distance dependent interactions
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Data from: Avian brood parasitism and ectoparasite richness – scale-dependent diversity interactions in a three-level host-parasite system
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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.