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138 results for “population coding”
Data and code from: Predicting population genetic change in an autocorrelated random environment: insights from a large automated experiment
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Code and data for: Shining a light on elusive lynx: density estimation of three Eurasian lynx populations in Ukraine and Belarus
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Data and code for: Sea level rise causes shorebird population collapse before habitat drowns
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Supporting R-code and data for "Why are population growth rate estimates of past and present hunter-gatherers so different?" (Tallavaara and Jørgensen, 2020)
<p>This submission contains data and R-code that enable to reproduce the data manipulations and analyses in the paper “Why are population growth rate estimates of past and present hunter-gatherers so different?” by Miikka Tallavaara and Erlend Kirkeng Jørgensen (Philosophical transactions of the Royal Society B). Please, cite the paper and this Zenodo repository if you use the files included in this Zenodo record in your work.</p> <p>The submission includes a html-file titled “Why are population growth rate estimates of past and present hunter-gatherers so different? - Data analyses” (TJ2020.html) that contains R-code and instructions and comments for running the code (open this file in your browser). In addition, the submission includes Rdata-file (dataTJ2020.Rdata) containing all the data that are not created within the code and pure R-code (TJ2020.R).</p>
Data and code for: Stochastic bacterial population dynamics restrict the establishment of antibiotic resistance from single cells
<p>This dataset contains experimental data and custom R code for likelihood-based model-fitting associated with the manuscript "Stochastic bacterial population dynamics restrict the establishment of antibiotic resistance from single cells". In particular, we estimate the per-cell establishment probability (i.e. probability that a single cell gives rise to a large population) of a resistant strain, in the presence of antibiotics at concentrations below its standard minimum inhibitory concentration. The experiments are conducted here with <em>Pseudomonas aeruginosa</em>, while the model and methods can be applied more generally.</p>
R code, spatial and tabular data to fully reproduce STEPS simulations of population change for common brushtail possum, grassland melomys and northern brown bandicoot in northern Australia
<ol> <li> <p>The development of effective fire management for biodiversity conservation is a global challenge. The highly dynamic nature of fire, the difficulty in replicating 'real-world' fire experiments, and the need to understand population changes at large spatiotemporal scales make computer simulations particularly useful for identifying optimal fire management regimes for biodiversity conservation. </p> </li> <li> <p>We aimed to develop a flexible modelling approach with which to investigate how the spatiotemporal application of fire (i.e. management scenarios) influences savanna biodiversity. We used existing data from a landscape-scale fire experiment to develop population simulations for the common brushtail possum (<i>Trichosurus vulpecula</i>), grassland melomys (<i>Melomys burtoni</i>) and northern brown bandicoot (<i>Isoodon macrourus</i>) across the Kapalga area of Kakadu National Park in northern Australia. We simulated how populations were expected to change between 1995 and 2015 in response to the fire patterns observed at Kapalga over this period, and under a hypothetical management scenario of extensive prescribed burning.</p> </li> <li> <p>Our models predicted a substantial decline in all three species in response to the observed fire regime at Kapalga, suggesting that the fire patterns observed at Kapalga, with the associated mechanisms and interactions with other ecological processes, were not conducive with the persistence of native mammal populations. </p> </li> <li> <p>Our prescribed burning scenario had little effect on the predicted population trajectory of the common brushtail possum and grassland melomys, but markedly improved the population trajectory of the northern brown bandicoot. These inconsistencies highlight the need for a nuanced approach to fire management across northern Australian savannas, that is tailored to local conditions and management objectives. </p> </li> <li> <p>Synthesis and applications. The modelling approach outlined here, provides a basis for identifying fire patterns that are beneficial for conserving biodiversity, thereby increasing our capacity to establish clear targets for prescribed fire management. Importantly, this approach is flexible and can be easily adapted to other taxa and fire-prone ecosystems.</p> </li> </ol>
Dataset and code release for "Current population structure and pathogenicity patterns of Ascochyta rabiei in Australia"
<p>This upload contains the raw DArTseq data and code for reproducible analysis and production of output tables and plots to accompany the publication "Current population structure and pathogenicity patterns of <em>Ascochyta rabiei</em> in Australia".<br> The analysis is performed primarily in R and is run using the `A_rabiei_DArT.R` file.</p> <p>A version-controlled repository of this upload is maintained at GitHub at the following link: <a href="https://github.com/IdoBar/A_rabiei_DArT">https://github.com/IdoBar/A_rabiei_DArT</a></p> <p>The archived file is structured as follows:</p> <ul> <li>Main analysis code is in <strong>A_rabiei_DArT.R</strong></li> <li>Raw DArTseq data and <em>A. rabiei</em> isolate metadata can be found in in the <strong><em>data </em></strong>folder</li> <li>Output tables and plots in <em><strong>output</strong></em> folder</li> <li>General information (partial and slightly outdated) in the markdown <strong>A_rabiei_DArT.Rmd </strong>and knitted <strong>A_rabiei_DArT.html </strong>files</li> <li>Australian chickpea production stats and figures in <strong>Chickpea_production.R</strong></li> </ul>
Data from: Error-robust modes of the retinal population code
Across the nervous system, certain population spiking patterns are observed far more frequently than others. A hypothesis about this structure is that these collective activity patterns function as population codewords–collective modes–carrying information distinct from that of any single cell. We investigate this phenomenon in recordings of ∼150 retinal ganglion cells, the retina's output. We develop a novel statistical model that decomposes the population response into modes; it predicts the distribution of spiking activity in the ganglion cell population with high accuracy. We found that the modes represent localized features of the visual stimulus that are distinct from the features represented by single neurons. Modes form clusters of activity states that are readily discriminated from one another. When we repeated the same visual stimulus, we found that the same mode was robustly elicited. These results suggest that retinal ganglion cells' collective signaling is endowed with a form of error-correcting code–a principle that may hold in brain areas beyond retina.
Data from: The first set of universal nuclear protein-coding loci markers for avian phylogenetic and population genetic studies
Multiple nuclear markers provide genetic polymorphism data for molecular systematics and population genetic studies. They are especially required for the coalescent-based analyses that can be used to accurately estimate species trees and infer population demographic histories. However, in avian evolutionary studies, these powerful coalescent-based methods are hindered by the lack of a sufficient number of markers. In this study, we designed PCR primers to amplify 136 nuclear protein-coding loci (NPCLs) by scanning the published Red Junglefowl (Gallus gallus) and Zebra Finch (Taeniopygia guttata) genomes. To test their utility, we amplified these loci in 41 bird species representing 23 Aves orders. The sixty-three best-performing NPCLs, based on high PCR success rates, were selected which had various mutation rates and were evenly distributed across 17 avian autosomal chromosomes and the Z chromosome. To test phylogenetic resolving power of these markers, we conducted a Neoavian phylogenies analysis using 63 concatenated NPCL markers derived from 48 whole genomes of birds. The resulting phylogenetic topology, to a large extent, is congruence with results resolved by previous whole genome data. To test the level of intraspecific polymorphism in these makers, we examined the genetic diversity in four populations of the Kentish Plover (Charadrius alexandrinus) at 17 of NPCL markers chosen at random. Our results showed that these NPCL markers exhibited a level of polymorphism comparable with mitochondrial loci. Therefore, this set of pan-avian nuclear protein-coding loci has great potential to facilitate studies in avian phylogenetics and population genetics.
Data from: Heterogeneity in genetic diversity among non-coding loci fails to fit neutral coalescent models of population history
Inferring aspects of the population histories of species using coalescent analyses of non-coding nuclear DNA has grown in popularity. These inferences, such as divergence, gene flow, and changes in population size, assume that genetic data reflect simple population histories and neutral evolutionary processes. However, violating model assumptions can result in a poor fit between empirical data and the models. We sampled 22 nuclear intron sequences from at least 19 different chromosomes (a genomic transect) to test for deviations from selective neutrality in the gadwall (Anas strepera), a Holarctic duck. Nucleotide diversity among these loci varied by nearly two orders of magnitude (from 0.0004 to 0.029), and this heterogeneity could not be explained by differences in substitution rates. Using two different coalescent methods to infer models of population history and then simulating neutral genetic diversity under these models, we found that the among-locus heterogeneity in nucleotide diversity was significantly higher than expected for these simple models. Defining more complex models of population history demonstrated that a pre-divergence bottleneck was also unlikely to explain this heterogeneity. However, both selection and interspecific hybridization could account for the heterogeneity observed among loci. Regardless of the cause of the deviation, our results illustrate that violating key assumptions of coalescent models can mislead inferences of population history.
Code for: The olivocerebellum encodes tremor frequency quantitatively by populational coding
<p>MATLAB codes for data analyses performed in "The olivocerebellum encodes tremor frequency quantitatively by populational coding".</p>
Including population and environmental dynamic heterogeneities in continuum models of collective behaviour with applications to locust foraging and group structure Data and Code
<p>This dataset includes all data used for the creation of "Including dynamic population and environmental heterogeneity in continuum models of collective behaviour with applications to locust foraging and group structure" as well as a snapshot of the code used.<br><br>Each zip should be unzippable and the code should operate with only the contents of the zip file.</p>
R code and data for running models in "Rapid Growth of the Swainson's Hawk Population in California since 2005"
<p>By 1979 Swainson's Hawks (<em>Buteo swainsoni)</em> had declined to as low as 375 breeding pairs throughout their summer range in California. Shortly thereafter the species was listed as threatened in the state. To evaluate the hawk's population trend since then, we analyzed data from 1,038 locations surveyed throughout California in either 2005, 2006, 2016, or 2018. We estimated a total statewide population of 18,810 breeding pairs (95CI: 11,353–37,228) in 2018, and found that alfalfa (<em>Medicago sativa</em>, lucerne) cultivation, agricultural crop diversity, and the occurrence of non-agricultural trees for nesting were positively associated with hawk density. We also concluded that California's Swainson's Hawk summering population grew rapidly between 2005 and 2018 at a rate of 13.9% per year (95CI: 7.8–19.2%). Despite strong evidence that the species has rebounded overall in California, Swainson's Hawks remain largely extirpated from Southern California where they were historically common. Further, we note that the increase in Swainson's Hawks has been coincident with expanded orchard and vineyard cultivation which is not considered suitable for nesting. Therefore, we recommend more frequent, improved surveys to monitor the stability of the species' potential recovery and to better understand the causes. Our results are consistent with increasing raptor populations in North America and Europe that contrast with overall global declines, especially in the tropics.</p>
Codes and results for self-learning entropic population annealing for interpretable materials design
<p>Codes that can reproduce the results in the paper entitled "self-learning entropic population annealing for interpretable materials design". Results, when the number of particles is 50, are included.</p>
Data and code for the manuscript titled "Persistence of SARS-CoV-2 immunity, Omicron's footprints, and projections of epidemic resurgences in South African population cohorts"
<p>Data and code for the manuscript titled “Persistence of SARS-CoV-2 immunity, Omicron’s footprints, and projections of epidemic resurgences in South African population cohorts”</p>
Data associated with the publication 'Population-level coding of avoidance learning in medial prefrontal cortex' by Benjamin Ehret et al.
<p>This repository contains data for the following publication:</p> <p>Population-level coding of avoidance learning in medial prefrontal cortex</p> <p>Ehret B., Boehringer R., Amadei E. A., Cervera M. R., Henning C., Galgali A., Mante V., Grewe, B. F.</p> <p>Nature Neuroscience 2024</p> <p> </p> <p>The associated analysis code is published here:</p> <p>https://github.com/behret/paper_code_active_avoidance</p> <p> </p> <p>This repository contains 1) source data to reproduce all figures and 2) processed data to reproduce most analyses. </p> <p>A small subset requires access to the raw data, which is too extensive to be published online. However, raw data can be made available upon request.</p>
Distinct neural population code and causal roles of primate caudate nucleus in multimodal decision-making
<p>To replicate the results in the paper, you should:</p> <ol> <li>Download and then gunzip the dataset.</li> <li>Download the analysis code at https://github.com/ZacZeng/CN-causally-contributes-to-MSDM.</li> <li>Run code as the README in Git says to get figures in the preprint paper (<a href="https://www.biorxiv.org/content/10.1101/2024.09.03.610907v1">Distinct neural manifolds and critical roles of primate caudate nucleus in multimodal decision-making | bioRxiv</a>).</li> </ol>
Data and code for "Assessing the spatial scale of synchrony in forest tree population dynamics"
<p>The data sets and code provided here facilitate reproduction of our results from this paper on synchrony of forest tree population dynamics. </p> <h3>Description of the data and file structure</h3> <p>The analyses in the paper were conducted at three scales, and each involves its own data files:</p> <ul> <li>Local scale: The relevant data files are named, e.g., "BCI1-7,L=250m,dbh=100mm.Rdata", where "BCI1-7" indicates the ForestGEO site name ("BCI") and census intervals (1 to 7 for BCI), "L=250m" indicates the quadrat size, and "dbh=100mm" indicates the diameter-at-breast height (DBH) threshold used. There are 12 such files (two ForestGEO plots--BCI and Pasoh--times three quadrat sizes times two DBH thresholds). Each file contains a single list "N_all", whose length is equal to the number of quadrats at the given grain. Each element in the list is a data frame containing mean census times (in days), tree species' population sizes and number of survivors across the two censuses for the corresponding quadrat.</li> <li>Regional scale: The relevant data files are "Marena_data,dbh=100mm,spp_anonymised.Rdata" and "Marena_data,dbh=100mm,spp_anonymised.Rdata". Each file contains three objects: "dists" is a matrix giving the distances between all pairs of sites; "N_all1" is a list with one element for each plot, and each element being a data frame with (anonymised) species ids in the first column and abundances in the remaining columns (column names give mean census dates in days); "S_all1" has a similar structure to "N_all1" except that the data give numbers of survivors from any given census to any subsequent census (column headings indicate the two census numbers).</li> <li>Global scale: The relevant data files are "global_data,dbh=10mm,spp_anonymised.Rdata" and "global_data,dbh=100mm,spp_anonymised.Rdata". The data in the files have the same structure as in the regional-scale files.</li> </ul>
Data and code for Heterogeneous selection on exploration behavior within and among West European populations of a passerine bird
<p><span>Heterogeneous selection is often proposed as a key mechanism maintaining repeatable behavioral variation ("animal personality") in wild populations. Previous studies largely focused on temporal variation in selection within single populations. The relative importance of spatial versus temporal variation remains unexplored, despite these processes having distinct effects on local adaptation. Using data from >3500 great tits (<i>Parus major</i>) and 35 nest box plots situated within five West-European populations monitored over 4-18 years, we show that selection on exploration behavior varies primarily spatially, across populations, and study plots within populations. Exploration was, simultaneously, selectively neutral in the average population and year. These findings imply that spatial variation in selection may represent a primary mechanism maintaining animal personalities, likely promoting the evolution of local adaptation, phenotype-dependent dispersal, and nonrandom settlement. Selection also varied within populations among years, which may counteract local adaptation. Our study underlines the importance of combining multiple spatiotemporal scales in the study of behavioral adaptation.</span></p>
Data and statistical code from: Population differences in the effect of context on personality in an invasive lizard
<p>Within populations, individuals often differ consistently in their average level of behavior (i.e. animal personality), as well as their response to environmental change (i.e. behavioral plasticity). Thus, changes in environmental conditions might be expected to mediate the structure of animal personality traits. However, it is currently not well understood how personality traits change in response to environmental conditions, and whether this effect is consistent across multiple populations within the same species. Accordingly, we investigated variation in personality traits across two ecological contexts in the invasive delicate skink (<i>Lampropholis delicata</i>). Specifically, lizards from three different populations were repeatedly measured for individual activity in group behavioral assays under differing levels of food availability. We found that environmental context had a clear effect on the structure of lizard personality, where activity rates were not repeatable in the absence of food, but were repeatable in the presence of food resources. The difference in repeatability of activity rates across contexts appeared to be largely driven by an increase in among-individual variance when tested in the presence of food resources. However, this was only true for one of the populations tested, with food context having no effect on the expression of personality traits in the other two populations. Our results highlight the important role of environmental context in mediating the structure of animal personality traits and suggest that this effect may vary among populations.</p>
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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.