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19,493 results for “Populism”
Data from: Specialists and generalists coexist within a population of spider-hunting mud dauber wasps
Individual foraging specialization describes the phenomenon where conspecifics within a population of generalists exhibit differences in foraging behavior, each specializing on different prey types. Individual specialization is widespread in animals, yet is understudied in invertebrates, despite potential impacts to food web and population dynamics. Sceliphron caementarium (Hymenoptera: Sphecidae) is an excellent system to examine individual specialization. Females of these mud-dauber wasps capture and paralyze spiders which they store in mud nests to provision their offspring. Individuals may make hundreds of prey choices in their short lifespan and fully intact prey items can be easily excavated from their mud nests, where each distinct nest cell represents a discrete foraging bout. Using data collected from a single population of S. caementarium (where all individuals had access to the same resources), we found evidence of strong individual specialization; individuals utilized different resources (with respect to prey taxa, prey ecological guild, and prey size) to provision their nests. The extent of individual specialization differed widely within the population with some females displaying extreme specialization (taking only prey from a single species) while others were generalists (taking prey from up to six spider families). We also found evidence of temporal consistency in individual specialization over multiple foraging events. We discuss these findings broadly in the context of search images, responses to changing prey availability, and intraspecific competition pressure.
Data from: Climate change and functional traits affect population dynamics of a long-lived seabird
1. Recent studies unravelled the effect of climate changes on populations through their impact on functional traits and demographic rates in terrestrial and freshwater ecosystems, but such understanding in marine ecosystems remains incomplete. 2. Here, we evaluate the impact of the combined effects of climate and functional traits on population dynamics of a long-lived migratory seabird breeding in the southern ocean: the black-browed albatross (Thalassarche melanophris, BBA). We address the following prospective question: ''Of all the changes in the climate and functional traits, which would produce the biggest impact on the BBA population growth rate?'' 3. We develop a structured matrix population model that includes the effect of climate and functional traits on the complete BBA life cycle. A detailed sensitivity analysis is conducted to understand the main pathway by which climate and functional trait changes affect the population growth rate. 4. The population growth rate of BBA is driven by the combined effects of climate over various seasons and multiple functional traits with carry-over effects across seasons on demographic processes. Changes in Sea Surface Temperature (SST) during late winter cause the biggest changes in the population growth rate, through their effect on juvenile survival. Adults appeared to respond to changes in winter climate conditions by adapting their migratory schedule rather than by modifying their at-sea foraging activity. However, the sensitivity of the population growth rate to SST affecting BBA migratory schedule is small. BBA foraging activity during the pre-breeding period has the biggest impact on population growth rate among functional traits. Finally, changes in SST during the breeding season have little effect on the population growth rate. 5. These results highlight the importance of early life histories and carry-over effects of climate and functional traits on demographic rates across multiple seasons in population response to climate change. Robust conclusions about the roles of various phases of the life cycle and functional traits in population response to climate change rely on an understanding of the relationships of traits to demographic rates across the complete life cycle.
Supplementary Material for Frontiers Plant Genetics and Genomics 'Novel R tools for analysis of genome-wide population genetic data with emphasis on clonality'
<p>Authors</p> <p>Zhian N. Kamvar, Jonah C. Brooks, and Niklaus J. Grünwald</p>
VCF file for a population of Drosophila melanogaster
<p>This file is the set of single nucleotide polymorphisms and insertion/deletions in a population of Drosophila melanoagaster. The zipped file is in a simple text file. This VCF file is part of the following larger body of work: <strong>Patterns of genetic regulation of expression variation in a natural population of Drosophila melanogaster provide evidence for buffering and GRN robustness</strong></p>
Intersession reliability of population receptive field estimates
<p>Proccessed pRF data comparing parameter estimates in visual regions across two days. Requires Matlab and SamSrf toolbox (https://figshare.com/articles/SamSrf_toolbox_for_pRF_mapping/1344765).</p>
Genotypes for the Spanish Autochthonous Beef Cattle Populations
<p>A total of 171 triplets (sire/dam/offspring) were collected from seven Spanish beef cattle populations (Asturiana de los Valles, n=25; Avileña-Negra Ibérica; Bruna dels Pirineus, n=25; Morucha, n=25; Pirenaica, n=24; Retinta, n=24; Rubia Gallega, n=24). The parents were chosen by minimizing the genealogical coancestry among them with the aim of capturing the existing variability within the populations.</p> <p> Individuals were genotyped using the BovineHD 777K BeadChip (Illumina Inc., USA), The SNPs present in the data file belonged to the autosomal chromosomes and those that were in repeated positions were excluded. Additional requirements were Mendelian error rates below 0.05 and call rates over 95% for both, individuals and SNPs. The quality control was made using the PLINK 1.0.7 software. Phasing was performed with BEAGLE with the "trio" option.</p> <p>Files are on PLINK format with the following name:</p> <p>Beagle.'Pop'.cromo'Cr'.pre_phase.bgl.phased.</p> <p>where Pop is from 1 (Asturiana de los Valles) to 7 (Rubia Gallega) and Cr is from 1 to 29.</p> <p> </p> <p> </p>
Drosophila simulans VCF: The set of single nucleotide polymorphisms and insertion/deletions in a population of 170 Drosophila simulans lines.
<p>Heritable phenotypic variation in natural populations exceeds the levels predicted under mutation-selection balance where purifying selection removes variation. Balancing selection, inefficient or weak selection, polygenic adaptation, and non-equilibrium populations are all possible explanations for excess variation. Yet, available genomic data indicate an abundance of directional selection. One potential explanation is that fleeting directional selection drives beneficial mutations to high frequency in rapid waves resulting in many intermediate frequency haplotypes. This hypothesis is supported by the genomic data from a panel of 170 D. simulans genotypes established from a single stable population which show evidence for an abundance of incomplete soft sweeps. Demography, admixture, and balancing selection cannot entirely explain the patterns in these data, while transient selective sweeps can account for all the patterns of variation observed in this population. One interpretation is that constant environmental shifts rapidly change the optimal phenotype within Drosophila populations, leaving a signature of adaptive responses.</p>
Synthetic J-H-K-W1-W2-W3-G-B-V photometry for random population of binary & single stars
<p>Table of synthetic photometry for ~800k stars, randomly distributed in the following ranges:</p> <ul> <li>mass_A = (0.2, 2.0)</li> <li>log10(age) = (8.0, 9.9)</li> <li>feh = N(0, 0.2)</li> <li>distance = (50, 2000) [pc]</li> <li>A_V = (0, 1)</li> <li>q (mass ratio) = (0.2, 1); mass_B = q * mass_A</li> </ul> <p>The table has columns for all the synthetic photometry as well as columns for the true properties and a boolean column for "is_binary"; the synthetic photometry is only a sum of the two stars if is_binary is True; otherwise the photometry is just for the primary star. Synthetic photometry is done using the MIST model grids, implemented by isochrones (github.com/timothydmorton/isochrones)</p> <p>The purpose of this table is to act a synthetic training set for single/binary classification algorithms.</p>
Lifespan Data for: Genetic dissection of nutrition-induced plasticity in insulin/insulin-like growth factor signaling and median lifespan in a Drosophila multiparent population
<p>Daily mortality records. Columns are:</p> <p>setDate: date vial was set up</p> <p>flipDate: date flies moved to new food and mortality recorded</p> <p>Age: age in days of flies (from set up date)</p> <p>RIL: DSPR recombinant inbred line ID</p> <p>rilid: alternate id</p> <p>replicate: replicate id</p> <p>riltreat: unique RIL, treatment identifier</p> <p>Dead: # dead</p> <p>Censored: # escaped or inadvertently killed individuals </p> <p>Carried: # dead flies inadvertently moved to fresh food</p>
Figure 3. from: A first integrative study of the identity and origins of the British Dwarf Pill Millipede populations, Trachysphaera cf. lobata (Diplopoda, Glomerida, Glomeridae) - Biodiversity Data Journal 3: e5176 (09 June 2015) https://doi.org/10.3897/BDJ.3.e5176
Figure 3. - TW18: T.lobata, female, Isle of Wight
Summary statistics of North American plant populations
<p>Summary statistics of North American plant populations calculated by using the microsatellites of invasive and native species from multiple studies. The packages “hierfstat” (Goudet and Jombart, 2015), “vegan” (Oksanen <em>et al.</em>, 2017) and “sp” (Pebesma and Bivand, 2005; Bivand <em>et al.</em>, 2013) were used in RStudio to calculate the averaged heterozygosity over all subpopulations (<em>H</em><sub>S</sub>), the proportion of genetic variation due to differences among populations (<em>F</em><sub>ST</sub>p), the degree of non-random mating within subpopulations (<em>F</em><sub>IS</sub>) and the correlation between geographic and genetic distance (<em>r)</em>. STRUCTURE (Pritchard <em>et al.</em>, 2000) was used to calculate the number of genetic clusters (<em>K)</em> (5 iterations, burnin length 1000, 10000 MCMC reps after burnin). STRUCTURE HARVESTER (Earl & vonHoldt, 2012) was consulted to determine Evanno’s ΔK (Evanno <em>et al.</em>, 2005).</p>
Replication data for Anterior Cruciate Ligament Injury: identifying information sources and risk factor awareness among the general population
<p>Creating awareness about a disorder is important for prevention from the perspective of public health. However, for sports injuries, like the anterior cruciate ligament (ACL) injury, there is no study which has investigated the awareness of risk factors for the injury and prevention methods among the general population, to the best of our knowledge. The sources of information among the population are also unclear. The purpose of present study was to identify these aspects of public awareness about the ACL injury.</p> <p>A questionnaire was randomly distributed among the general population registered with a web based questionnaire supplier, to recruit 900 participants who were aware about the ACL injury. The questionnaire consisted of two parts: Question 1 asked them about their sources of information regarding the ACL injury; Question 2 asked them about the risk factors for ACL injury. Multivariate logistic regression was used to determine the information sources that provide a good understanding of the risk factors.</p> <p>The leading source of information for ACL injury was television (57.0%). However, the results of logistic regression analysis revealed that television was not an effective medium to create awareness about the risk factors, among the general population. Instead “Lecture by a coach”, “Classroom session on Health”, and “Newspaper” were significantly effective in creating a good awareness of the risk factors (p < 0.001).</p>
Pig population data complementing the annual report on the epidemiological analyses of African swine fever (ASF) in the European Union - Lithuania
<p>This dataset contains swine population data.</p> <p><strong>Reporting authorities contributing to the data collection:</strong></p> <ul> <li>ASF2024_POP_EXTRACTION_LT - State Food and Veterinary Service (SFVS)</li> <li>ASF2023_POP_EXTRACTION_LT - State Food and Veterinary Service (SFVS)</li> <li>ASF2022_POP_EXTRACTION_LT - State Food and Veterinary Service (SFVS)*</li> <li>ASF2022_POP_EXTRACTION_LT - State Food and Veterinary Service (SFVS)</li> </ul> <p> </p> <p> </p> <p>*This version of the animal population data has been republished with the establishment and subnit identification code (estabId, subUnitId) columns empty due to data protection reasons</p>
Pig population data complementing the annual report on the epidemiological analyses of African swine fever (ASF) in the European Union - Slovakia
<p>This dataset contains swine population data.</p> <p><strong>Reporting authorities contributing to the data collection:</strong></p> <ul> <li>ASF2024_POP_EXTRACTION_SK - State Veterinary and Food Institute (SVPU)</li> <li>ASF2023_POP_EXTRACTION_SK - State Veterinary and Food Institute (SVPU)</li> <li>ASF2022_POP_EXTRACTION_SK - State Veterinary and Food Institute (SVPU)*</li> <li>ASF2022_POP_EXTRACTION_SK - State Veterinary and Food Institute (SVPU)</li> </ul> <p> </p> <p> </p> <p>*This version of the animal population data has been republished with the establishment and subnit identification code (estabId, subUnitId) columns empty due to data protection reasons</p>
Pig population data complementing the annual report on the epidemiological analyses of African swine fever (ASF) in the European Union - Latvia
<p>This dataset contains swine population data.</p> <p><strong>Reporting authorities contributing to the data collection:</strong></p> <ul> <li>ASF2024_POP_EXTRACTION_LV - Agricultural Data Centre (LDC)</li> <li>ASF2023_POP_EXTRACTION_LV - Agricultural Data Centre (LDC)</li> <li>ASF2022_POP_EXTRACTION_LV - Agricultural Data Centre (LDC)*</li> <li>ASF2022_POP_EXTRACTION_LV - Agricultural Data Centre (LDC)</li> </ul> <p> </p> <p> </p> <p>*This version of the animal population data has been republished with the establishment and subnit identification code (estabId, subUnitId) columns empty due to data protection reasons</p>
Pig population data complementing the annual report on the epidemiological analyses of African swine fever (ASF) in the European Union - Italy
<p>This dataset contains swine population data.</p> <p><strong>Reporting authorities contributing to the data collection:</strong></p> <ul> <li>ASF2024_POP_EXTRACTION_IT - Istituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise (IZSAM)</li> <li>ASF2023_POP_EXTRACTION_IT - Istituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise (IZSAM)</li> <li>ASF2022_POP_EXTRACTION_IT - Istituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise (IZSAM)*</li> <li>ASF2022_POP_EXTRACTION_IT - Istituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise (IZSAM)</li> </ul> <p> </p> <p> </p> <p>*This version of the animal population data has been republished with the establishment and subnit identification code (estabId, subUnitId) columns empty due to data protection reasons</p>
Pig population data complementing the annual report on the epidemiological analyses of African swine fever (ASF) in the European Union - Estonia
<p>This dataset contains swine population data.</p> <p><strong>Reporting authorities contributing to the data collection:</strong></p> <ul> <li>ASF2024_POP_EXTRACTION_EE - Agricultural Registers and Information Board (ARIB)</li> <li>ASF2023_POP_EXTRACTION_EE - Agricultural Registers and Information Board (ARIB)</li> <li>ASF2022_POP_EXTRACTION_EE - Agricultural Registers and Information Board (ARIB)*</li> <li>ASF2022_POP_EXTRACTION_EE - Agricultural Registers and Information Board (ARIB)</li> </ul> <p> </p> <p> </p> <p>*This version of the animal population data has been republished with the establishment and subnit identification code (estabId, subUnitId) columns empty due to data protection reasons</p>
Pig population data complementing the annual report on the epidemiological analyses of African swine fever (ASF) in the European Union - Romania
<p>This dataset contains swine population data.</p> <p><strong>Reporting authorities contributing to the data collection:</strong></p> <ul> <li>ASF2024_POP_EXTRACTION_RO - National Sanitary Veterinary and Food Safety Authority (ANSVSA)</li> <li>ASF2023_POP_EXTRACTION_RO - National Sanitary Veterinary and Food Safety Authority (ANSVSA)</li> <li>ASF2022_POP_EXTRACTION_RO - National Sanitary Veterinary and Food Safety Authority (ANSVSA)*</li> <li>ASF2022_POP_EXTRACTION_RO - National Sanitary Veterinary and Food Safety Authority (ANSVSA)</li> </ul> <p> </p> <p>*This version of the animal population data has been republished with the establishment and subnit identification code (estabId, subUnitId) columns empty due to data protection reasons</p>
Pig population data complementing the annual report on the epidemiological analyses of African swine fever (ASF) in the European Union - North Macedonia
<p>This dataset contains swine population data.</p> <p><strong>Reporting authorities contributing to the data collection:</strong></p> <ul> <li>ASF2024_POP_EXTRACTION_MK - Food and Veterinary Agency (FVA)</li> <li>ASF2023_POP_EXTRACTION_MK - Food and Veterinary Agency (FVA)</li> <li>ASF2022_POP_EXTRACTION_MK - Food and Veterinary Agency (FVA)*</li> <li>ASF2022_POP_EXTRACTION_MK - Food and Veterinary Agency (FVA)</li> </ul> <p> </p> <p> </p> <p>*This version of the animal population data has been republished with the establishment and subnit identification code (estabId, subUnitId) columns empty due to data protection reasons</p> <p> </p>
Pig population data complementing the annual report on the epidemiological analyses of African swine fever (ASF) in the European Union - Greece
<p>This dataset contains swine population data.</p> <p><strong>Reporting authorities contributing to the data collection:</strong></p> <ul> <li>ASF2024_POP_EXTRACTION_GR - Hellenic Ministry of Rural Development and Food (MINAGRIC)</li> <li>ASF2023_POP_EXTRACTION_GR - Hellenic Ministry of Rural Development and Food (MINAGRIC)</li> </ul>
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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.
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DANDI Archive for NWB datasets
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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.