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138 results for “population coding”
Data and R computer code from: Summer elk calf survival in a partially migratory population
<p>These data and computer code (written in R, https://www.r-project.org) were created to statistically evaluate a suite of intrinsic and extrinsic risk factors related to calf elk and their mothers' body condition and age. Specifically, known-fate data were collected from 94 elk calves monitored from 2013-2016 in a partially migratory elk (<em>Cervus</em> <em>canadensis</em>) population in Alberta, Canada. Along with adult female data on pregnancy status, age, and body condition, we created a time-to-event dataset that allowed us to analyze calf mortality risk in a time-to-event approach. We also estimated pooled survivorship and cause-specific mortality, as well as stratifying these metrics by migration tactic (resident vs. eastern migrant). Cox proportional hazards models were used to evaluate calf mortality risk in terms of forage biomass (kg/ha), bear predation risk (from an RSF), and other factors that varied between migration tactics. We tested for differences in a number of maternal reproductive parameters (e.g., pregnancy status) and for calf explanatory variables between migrant and resident elk segments. We also use cumulative incidence functions to estimate cause-specific mortality in this multiple carnivore system. Ultimately, we hope that this work helps wildlife managers anticipate how elk calf survival and partial migration dynamics are affected by grizzly bear predation, and our study builds on a long-term partial migration study at the Ya Ha Tinda Ranch in Alberta, Canada. </p>
Data and code from: Evaluating genomic offset predictions in a forest tree with high population genetic structure
<p>Predicting how tree populations will respond to climate change is an urgent societal concern. An increasingly popular way to make such predictions is the genomic offset (GO) approach, which aims to use genomic and climate data to identify populations that may experience climate maladaptation in the near future. More precisely, GO tries to represent the change in allele frequencies required to maintain the current gene-climate relationships under climate change. However, the GO approach has major limitations and, despite promising validation of its predictions using height data from common gardens, it still lacks broad empirical testing. In the present study, we evaluated the consistency and empirical validity of GO predictions in maritime pine (<em>Pinus pinaster</em> Ait.), a tree species from southwestern Europe and North Africa with a marked population genetic structure. First, gene-climate relationships were estimated using 9,817 SNPs genotyped in 454 trees from 34 populations; and candidate SNPs potentially involved in climate adaptation were identified. Second, GO was predicted using four methods, namely Gradient Forest (GF), Redundancy Analysis (RDA), latent factor mixed model (LFMM) and Generalised Dissimilarity Modeling (GDM), two sets of SNPs (candidate and control SNPs) and five climate general circulation models (GCMs) to account for uncertainty in future climate predictions. Last, the empirical validity of GO predictions was evaluated within a Bayesian framework by estimating the associations between GO predictions and two independent data sources: mortality data from National Forest Inventories (NFI), and mortality and height data from five common gardens in contrasting environments. We found high variability in GO predictions across methods, SNP sets and GCMs. Regarding validation, GO predictions with GDM and GF (and to a lesser extent RDA) based on the candidate SNPs showed the strongest and most consistent associations with mortality rates in common gardens and NFI plots. We found almost no association between GO predictions and tree height in common gardens, most likely due to the overwhelming effect of population genetic structure on tree height in this species. Our study demonstrates the imperative to validate GO predictions with a range of independent data sources before they can be used as informative and reliable metrics in conservation or management strategies.</p>
Рис. 1. Размещение трансект (спΛошные черные Λинии) и Αаты провеΑения учетов в Охотском море и сопреΑеΛьных воΑах Тихого океана и Японского моря в февраΛе — мае 2020 г. РыбоΛовные районы: 05.1 — Северо-Охотоморская поΑзона; 05.2 — ЗапаΑно-Камчатская поΑзона; 05.3 — Восточно-СахаΛинская поΑзона; 05.4 — Камчатско-КуриΛьская поΑзона; 03 — Северо-КуриΛьская зона; 04 — Южно-КуриΛьская зона; 06 — зона Японское море. Пунктиром показана 200-метровая изобата Fig. 1. Transect locations (solid black lines) and dates of surveys in the Sea of Okhotsk and adjacent waters of the Pacific Ocean and the Sea of Japan in February–May 2020. Codes of the fishery areas are as follows: 05.1 — Northern Sea of Okhotsk Subzone; 05.2 — West Kamchatka Subzone; 05.3 — East Sakhalin Subzone; 05.4 — Kamchatka-Kuril Subzone; 03 — North Kuril Zone; 04 — South Kuril Zone; 06 — Sea of Japan Zone. Dotted line indicates a 200 m isobath in Population of seabirds in the Sea of Okhotsk and adjacent waters of the Pacific Ocean and the Sea of Japan during the winter-spring period of 2020
Рис. 1. Размещение трансект (спΛошные черные Λинии) и Αаты провеΑения учетов в Охотском море и сопреΑеΛьных воΑах Тихого океана и Японского моря в февраΛе — мае 2020 г. РыбоΛовные районы: 05.1 — Северо-Охотоморская поΑзона; 05.2 — ЗапаΑно-Камчатская поΑзона; 05.3 — Восточно-СахаΛинская поΑзона; 05.4 — Камчатско-КуриΛьская поΑзона; 03 — Северо-КуриΛьская зона; 04 — Южно-КуриΛьская зона; 06 — зона Японское море. Пунктиром показана 200-метровая изобата Fig. 1. Transect locations (solid black lines) and dates of surveys in the Sea of Okhotsk and adjacent waters of the Pacific Ocean and the Sea of Japan in February–May 2020. Codes of the fishery areas are as follows: 05.1 — Northern Sea of Okhotsk Subzone; 05.2 — West Kamchatka Subzone; 05.3 — East Sakhalin Subzone; 05.4 — Kamchatka-Kuril Subzone; 03 — North Kuril Zone; 04 — South Kuril Zone; 06 — Sea of Japan Zone. Dotted line indicates a 200 m isobath
Code and data associated with Christiansen et al. 2021 "Facilitating population genomics of non-model organisms through optimized experimental design for reduced representation sequencing"
<p>All code and data input and output files (except reference genome and raw sequencing data) needed to reproduce the results of Christiansen et al. 2021 as released on <a href="https://github.com/notothen/radpilot">https://github.com/notothen/radpilot</a> alongside journal publication. See published paper:</p> <p>Christiansen, H., Heindler, F.M., Hellemans, B. <em>et al.</em> Facilitating population genomics of non-model organisms through optimized experimental design for reduced representation sequencing. <em>BMC Genomics</em> <strong>22, </strong>625 (2021). <a href="https://doi.org/10.1186/s12864-021-07917-3">https://doi.org/10.1186/s12864-021-07917-3</a></p>
Distinct population code for movement kinematics and changes of ongoing movements in human subthalamic nucleus
<p>The subthalamic nucleus (STN) is theorized to globally suppress movement through connections with downstream basal ganglia structures. Current theories are supported by increased STN activity when subjects withhold an uninitiated action plan, but a critical test of these theories requires studying STN responses when an ongoing action is replaced with an alternative. We perform this test in subjects with Parkinson's disease using an extended reaching task where the movement trajectory changes mid-action. We show that STN activity decreases during action switches, contrary to prevalent theories. Further, beta oscillations in the STN local field potential, which are associated with movement inhibition, do not show increased power or spiking entrainment during switches. We report an inhomogeneous population neural code in STN, with one sub-population encoding movement kinematics and direction and another encoding unexpected action switches. We suggest an elaborate neural code in STN that contributes to planning actions and changing the plans.</p>
Populations of local direction-selective cells encode global motion patterns generated by self-motion. Data, Code and Model.
<p>Directional tuning of the population of local motion detectors T4/T5 in the visual system of the fruit fly <em>Drosophila melanogaster</em>. Direction tuning and receptive field location was measured by recording responses to visual stimuli containing dark or bright edges/stripes moving into 8 directions. All provided MATLAB scripts were used to analyze and illustrate data show in the manuscript 'Populations of local direction-selective cells encode global motion patterns generated by self-motion.'</p> <p>All data were obtained using <em>in vivo </em>two photon microscopy. Image time series were preprocessed using SIMA python software for motion alignment and further processed using custom written matlab or python code.</p> <p>Please find all relevant information to use the code in the README file.</p>
Data and code for: Plastic and quantitative genetic divergence mirror environmental gradients among wild, fragmented populations of Impatiens capensis
<p><strong>Premise of the study:</strong> Habitat fragmentation generates molecular genetic divergence among isolated populations but few studies have assessed phenotypic divergence and fitness in populations where the genetic consequences of habitat fragmentation are known. Phenotypic divergence could reflect plasticity, local adaptation, and/or genetic drift.</p> <p><strong>Methods:</strong> We examined patterns and potential drivers of phenotypic divergence among 12 populations of jewelweed (<em>Impatiens capensis </em>Meerb.) that show strong molecular genetic signals of isolation and drift among fragmented habitats. We measured morphological and reproductive traits in both maternal plants within natural populations and their self-fertilized progeny grown together in a common garden. We also quantified environmental divergence between home sites and the common garden.</p> <p><strong>Key results: </strong>Populations with less molecular genetic variation expressed less maternal phenotypic variation. Progeny in the common garden converged in phenotypes relative to their wild mothers but retained among-population differences in morphology, survival, and reproduction. Among-population phenotypic variance was 3-10x greater in home sites than in the common garden for 6 of 7 morphological traits measured. Patterns of phenotypic divergence paralleled environmental gradients in ways suggestive of adaptation. Progeny resembled their mothers less as the environmental distance between their home site and the common garden increased.</p> <p><strong>Conclusions: </strong>Despite strong molecular signatures of isolation and drift, phenotypic differences among these <em>Impatiens </em>populations appear to reflect both adaptive quantitative genetic divergence and plasticity. Quantifying the extent of local adaptation and plasticity and how these covary with molecular and phenotypic variation help us predict when populations may lose their adaptive capacity. </p>
Code and data for: Emergence of spatially structured populations by area-concentrated search
<p>The idea that populations are spatially structured has become a very powerful concept in ecology, raising interest in many research areas. However, despite dispersal being a core component of the concept, it typically does not consider the movement behavior underlying any dispersal. Using individual-based simulations in continuous space, we investigate the emergence of a spatially structured population in landscapes with spatially heterogeneous resource distribution and with organisms following simple area-concentrated search (ACS); individuals do not, however, perceive or respond to any habitat attributes per se but only to their foraging success. We investigated effects of different resource clustering patterns in landscapes (single large cluster vs. many small clusters) and different resource densities on spatial structure of populations and movement between resource clusters of individuals. As the results, we found that foraging success increased with increasing resource density and decreasing number of resource clusters. In a wide parameter space, the system exhibited attributes of a spatially structured population with individuals concentrated in areas of high resource density, searching within areas of resources, and 'dispersing' in a straight line between resource patches. 'Emigration' was more likely from patches that were small or of low quality (low resource density), but we observed an interaction effect between these two parameters. With the ACS implemented, individuals tended to move deeper into a resource cluster in scenarios with moderate resource density than in scenarios with high resource density. 'Looping' from patches was more likely if patches were large and of high quality. Our simulations demonstrate that spatial structure in populations may emerge if critical resources are heterogeneously distributed and if individuals follow simple movement rules (such as ACS). Neither the perception of habitat nor an explicit decision to emigrate from a patch on the side of acting individuals is necessary for the emergence of spatial structure.</p>
Data and code for paper "Freihardt (2024): Perceptions of environmental changes among a climate-vulnerable population from Bangladesh. Climatic Change. DOI 10.1007/s10584-024-03678-6"
<p>This dataset contains the temperature, precipitation, erosion, and perception data, as well as the analysis code in R necessary to replicate the results of the paper:</p> <p>Freihardt, J. (2024): Perceptions of environmental changes among a climate-vulnerable population from Bangladesh. Climatic Change, 177, 25. DOI: 10.1007/s10584-024-03678-6.</p>
Datasets and codes for De Lorm et al. 2023: Optimising the automated recognition of individual animals to support population monitoring
<p>Reliable estimates of population size and demographic rates are central to assessing the status of threatened species. However, obtaining individual-based demographic rates requires long-term data, which is often costly and difficult to collect. Photographic data offer an inexpensive, non-invasive method for individual-based monitoring of species with unique markings, and could therefore increase available demographic data for many species. However, selecting suitable images and identifying individuals from photographic catalogues is prohibitively time-consuming. Automated identification software can significantly speed up this process. Nevertheless, automated methods for selecting suitable images are lacking, as are studies comparing the performance of the most prominent identification software packages.</p> <p> </p> <p>In this study, we develop a framework that automatically selects images suitable for individual identification, and compare the performance of three commonly used identification software packages; Hotspotter, I<sup>3</sup>S-Pattern, and WildID. As a case study, we consider the African wild dog <em>Lycaon pictus</em>, a species whose conservation is limited by a lack of cost-effective large-scale monitoring. To evaluate intra-specific variation in the performance of software packages, we compare identification accuracy between two populations (in Kenya and Zimbabwe) that have markedly different coat colouration patterns. </p> <p> </p> <p>The process of selecting suitable images was automated using Convolutional Neural Nets that crop individuals from images, filter out unsuitable images, separate left and right flanks, and remove image backgrounds. Hotspotter had the highest image-matching accuracy for both populations. However, the accuracy was significantly lower for the Kenyan population (62%), compared to the Zimbabwean population (88%). </p> <p> </p> <p>Our automated image pre-processing has immediate application for expanding monitoring based on image-matching. However, the difference in accuracy between populations highlights that population-specific detection rates are likely and may influence certainty in derived statistics. For species such as the African wild dog, where monitoring is both challenging and expensive, automated individual recognition could greatly expand and expedite conservation efforts. </p>
Data and code for: Failure to purge: Population and individual inbreeding effects on fitness across generations of wild Impatiens capensis
<p>Inbreeding exposes deleterious recessive alleles in homozygotes, lowering fitness and generating inbreeding depression (ID). Both purging (via selection) and fixation (via drift) should reduce segregating deleterious mutations and ID in more inbred populations. These theoretical predictions are not well-tested in wild populations, which is concerning given purging/fixation have opposite fitness outcomes. We examined how individual- and population-level inbreeding and genomic heterozygosity affected maternal and progeny fitness within and among 12 wild populations of <em>Impatiens capensis</em>. We quantified maternal fitness in home sites, maternal multilocus heterozygosity (using 12,560 SNPs), and lifetime fitness of selfed and predominantly outcrossed progeny in a common garden. These populations spanned a broad range of individual- (<span class="s1"><em>f</em></span><span class="s2"><sub>i</sub></span><em> </em>= -0.17–0.98) and population-level inbreeding (<span class="s1"><em>F</em></span><span class="s2"><sub>IS</sub></span> = 0.25–0.87). More inbred populations contained fewer polymorphic loci, less fecund mothers, and smaller progeny, suggesting higher fixed loads. However, despite appreciable ID (mean: 8.8 lethal equivalents per gamete), ID did not systematically decline in more inbred population. More heterozygous mothers were more fecund and produced fitter progeny in outcrossed populations, but this pattern unexpectedly reversed in highly inbred populations. These observations suggest that persistent overdominance or some other force acts to forestall purging and fixation in these populations.</p>
Data and codes from "How does dispersal shape the genetic structure of animal populations in European cities? A simulation approach"
<p>Codes and data used for "Savary et al. How does dispersal shape the genetic structure of animal populations in European cities? A simulation approach".</p> <p> </p>
Data and code for: Plastic and quantitative genetic divergence mirror environmental gradients among wild, fragmented populations of Impatiens capensis
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Distinct population code for movement kinematics and changes of ongoing movements in human subthalamic nucleus
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Data and code from: Variety is the spice of life: nongenetic variation in life histories influences population growth and evolvability
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Data and R code used in: Plant geographic distribution influences chemical defenses in native and introduced Plantago lanceolata populations
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Data and code for: Realized genetic gains via recurrent selection in a tropical maize haploid inducer population and optimizing simultaneous selection for the next cycles
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Data and code from: Evaluating genomic offset predictions in a forest tree with high population genetic structure
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Data and R code from: Relics of beavers past: time and population density drive scale-dependent patterns of ecosystem engineering
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Sequential and efficient neural-population coding of complex task information
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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)
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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.