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5,538 results for “population data”
Data for: The transmission ability in a population of elite tetraploid potatoes
<p>Data set for the research article: Assessing the transmission potential of elite tetraploid potatoes.</p> <p>The dataset includes pedigree and phenotypic data of 5013 clones of an F1 population derived from an incomplete diallel cross of 18 parents of either established cultivars or elite breeding material from Danespo A/S across three market segments (starch, processing, and table). A total of 10 phenotypes are included, namely dry matter content, yield, senescence, skin finish, flesh color, length/width ratio, length, diameter, tubers/plant, and eye depth. In addition, GBS genotype data for a set of 93,170 biallelic SNPs filtered to MAF > 1 %, coverage > 5 and < 60, and missing rate < 70 %. Pedigree (A), genomic (G), and single-step combined (H) matrices are included. A README file is included with descriptions of all provided data files. </p>
Data release: Searching for binary black hole sub-populations in gravitational wave data using binned Gaussian processes
<p>The data required to reproduce the analyses of "Searching for binary black hole sub-populations in gravitational wave data using binned Gaussian processes" (<a href="https://arxiv.org/abs/2404.03166" target="_blank" rel="noopener">arxiv:2404.03166</a>). The main inference code can be found at <a href="https://github.com/AnaryaRay1/gppop/tree/spin-dev" target="_blank" rel="noopener">https://github.com/AnaryaRay1/gppop/tree/spin-dev </a> (commit: <a href="https://github.com/AnaryaRay1/gppop/commit/ee5ffc421e2c96eeed15a0e0d3839da42b982842">ee5ffc</a>). To reproduce the analyses, follow the instructions at <a href="https://github.com/AnaryaRay1/bbh-subpopulations-scripts">https://github.com/AnaryaRay1/bbh-subpopulations-scripts</a> (commit <a href="https://github.com/AnaryaRay1/bbh-subpopulations-scripts/commit/de88f931d8c1a2cb31ad2fa9d6fdf9a5a00a3c3b">de88f93</a>). Frozen versions of these repositories that were used to generate all the results are available as part of this data release, in the files "gppop_spin_dev_ee5ffc421.tar.gz" and "bbh-subpopulations-scripts_de88f931.tar.gz" respectively.</p>
CEAD Population Survey Quito: Data and Variable Code Equivalencies
<p>We conducted a cross-sectional study with 656 adults from health district 17D06, South Quito, Ecuador, using multi-stage cluster sampling. The study followed an adapted WHO STEPwise approach, considering Ecuador's 2018 STEPwise survey.</p> <p>For more information, contact Clara Blanes Mira: c.blanes@umh.es</p> <p> </p>
Data and R code from: Relics of beavers past: time and population density drive scale-dependent patterns of ecosystem engineering
<p><span>Like many ecological processes, natural disturbances exhibit scale-dependent dynamics that are largely a function of the magnitude, frequency, and scale at which they are assessed. Ecosystem engineers create patch-scale disturbances that affect ecological processes, yet we know little about how these effects scale across space or vary through time. Here, we investigate how patch disturbances by beavers (<i>Castor canadensis</i>), ecosystem engineers renowned for their pond-creation behavior, affect ecological processes across space and time. We evaluated how beaver population recovery influenced surface water dynamics in relation to population density over 70 years across multiple spatial scales (pond, watershed, and regional) in northern Minnesota. Surface water area was positively related to population density at the watershed scale; however, despite variation in beaver densities (and therefore surface water area) at the watershed scale, regional-scale surface water area was stable through time. This stability appears to have been driven by asynchronous beaver density fluctuations among watersheds, combined with the increasing importance of abandoned ponds. Beavers initially created and occupied larger ponds with greater surface water area, but through time shifted towards occupying smaller ponds. As ponds accumulated on the landscape proportionally more surface water was stored within abandoned ponds, which offset the smaller size of occupied ponds. Beaver engineering—driven by density-dependent mechanisms and the legacy effects from abandoned ponds—not only follows general patterns of patch disturbance dynamics by creating a spatial mosaic of patches, but the organism-created mosaic also appears to generate ecological stability at greater spatial scales. We suggest restoring beavers to landscapes is a viable method for increasing surface water storage and will ultimately help advance numerous conservation and rewilding objectives. Our study demonstrates that ecosystem engineering effects can be scale-dependent, indicating researchers should evaluate the ecological impact of engineers across diverse spatiotemporal scales to fully understand their functional roles in ecosystems.</span></p>
Data from: Context matters: the landscape matrix determines the population genetic structure of temperate forest herbs across Europe
<p>Context. Plant populations in agricultural landscapes are mostly fragmented and their functional connectivity often depends on seed and pollen dispersal by animals. However, little is known about how the interactions of seed and pollen dispersers with the agricultural matrix translate into gene flow among plant populations.</p> <p>Objectives. We aimed to identify effects of the landscape structure on the genetic diversity within, and the genetic differentiation among, spatially isolated populations of three temperate forest herbs. We asked, whether different arable crops have different effects, and whether the orientation of linear landscape elements relative to the gene dispersal direction matters.</p> <p>Methods. We analysed the species' population genetic structures in seven agricultural landscapes across temperate Europe using microsatellite markers. These were modelled as a function of landscape composition and configuration, which we quantified in buffer zones around, and in rectangular landscape strips between, plant populations.</p> <p>Results. Landscape effects were diverse and often contrasting between species, reflecting their association with different pollen- or seed dispersal vectors. Differentiating crop types rather than lumping them together yielded higher proportions of explained variation. Some linear landscape elements had both a channelling and hampering effect on gene flow, depending on their orientation.</p> <p>Conclusions. Landscape structure is a more important determinant of the species' population genetic structure than habitat loss and fragmentation <i>per se</i>. Landscape planning with the aim to enhance the functional connectivity among spatially isolated plant populations should consider that even species of the same ecological guild might show distinct responses to the landscape structure.</p>
Data from: Chrysolaena obovata, A SPECIES NATIVE OF BRAZILIAN CERRADO: GENETIC DIVERSITY AND STRUCTURE OF NATURAL POPULATIONS AND POTENTIAL FOR INULIN PRODUCTION
<p><em>Chrysolaena obovata</em> (Less.) M. Dematteis, an herbaceous Asteraceae species widely distributed across different Brazilian Cerrado physiognomies, has underground organs, named rhizophores, that accumulate high concentrations of inulin-type fructans. These carbohydrates are recognized as beneficial soluble fibers for human health and are currently used in the food and pharmaceutical industries. Considering that fructans, in addition to their economic potential, provide plants with greater tolerance to drought, heat and cold, it is important to understand whether their metabolism is conserved in natural populations. In this work, we aimed to investigate if the levels of genetic diversity in the populations studied allow the selection of localities with a high genetic base and higher fructan content for future programs of <em>in</em> <em>situ</em> conservation and genetic improvement for inulin production. Therefore, we characterized the diversity, structure, and gene flow of seven natural populations from Brazilian Cerrado, using nine microsatellite loci (SSR). In addition, we compared whether the fructan composition varied between populations of different Cerrado phytophysiognomies. Overall, we found that <em>C. obovata</em> populations exhibited moderate levels of genetic diversity, low genetic differentiation, and high gene flow. This study identified two populations with less genetic diversity and therefore, greater attention should be given to conservation programs including these populations. Fructan metabolism is conserved in all populations, indicating that <em>C. obovata</em> is an important genetic resource with high potential for inulin production.</p> <p><strong>File descriptions</strong></p> <p>Population_code.txt - Contains a matrix that indicates the population_code, Population_name, Brazilian-state, Phytophysiognomy, Collection coordinates and Altitudes (m).</p> <p>Date_ Diaz et al.xlsx – Contains Genotypes crude of the individuals analyzed. Primer used for nine microsatellite loci (Camacho <em>et al</em> 2017). </p> <p>Carbohydrates_Diaz et al - Contains data for carbohydrates in <em>C. obovata</em> plant rhizophores in each population (BRA, UB, SD, SP).</p> <p><strong>Location: Brazilian Cerrado</strong></p>
Data and code for "Sustainable Human Population Density in Western Europe between 560.000 and 360.000 years ago"
<p>This dataset contains the modeling results GIS data (maps) of the study “Sustainable Human Population Density in Western Europe between 560.000 and 360.000 years ago” by Rodríguez et al. (2022).</p> <p>The NPP data (npp.zip) was computed using an empirical formula (the Miami model) from palaeo temperature and palaeo precipitation data aggregated for each timeslice from the Oscillayers dataset (Gamisch, 2019), as defined in Rodríguez et al. (2022, in review).</p> <p>The Population densities file (pop_densities.zip) contains the computed minimum and maximum population densities rasters for each of the defined MIS timeslices. With the population density value Dc in logarithmic form log(Dc).</p> <p>The Species Distribution Model (sdm.7z) includes input data (folder /data), intermediate results (folder /work) and results and figures (folder /results). All modelling steps are included as an R project in the folder /scripts. The R project is subdivided into individual scripts for data preparation (1.x), sampling procedure (2.x), and model computation (3.x).</p> <p>The habitat range estimation (habitat_ranges.zip) includes the potential spatial boundaries of the hominin habitat as binary raster files with 1=presence and 0=absence. The ranges rely on a dichotomic classification of the habitat suitability with a threshold value inferred from the 5% quantile of the presence data.</p> <p>The habitat suitability (habitat_suitability.zip) is the result of the Species Distribution Modelling and describes the environmental suitability for hominin presence based on the sites considered in this study. The values range between 0=low and 1=high suitability. The dataset includes the mean (pred_mean) and standard deviation (pred_std) of multiple model runs.</p>
Data from: The evolution of thermal performance in native and invasive populations of Mimulus guttatus
<p>The rise of globalization has spread organisms beyond their natural range, allowing further opportunity for species to adapt to novel environments and potentially become invaders. Yet, the role of thermal niche evolution in promoting the success of invasive species remains poorly understood. Here, we use thermal performance curves (TPCs) to test hypotheses about thermal adaptation during the invasion process. First, we tested the hypothesis that if species largely conserve their thermal niche in the introduced range, invasive populations may not evolve distinct TPCs relative to native populations, against the alternative hypothesis that thermal niche and therefore TPC evolution has occurred in the invasive range. Second, we tested the hypothesis that clines of TPC parameters are shallower or absent in the invasive range, against the alternative hypothesis that with sufficient time, standing genetic variation, and temperature-mediated selection, invasive populations would re-establish clines found in the native range in response to temperature gradients. To test these hypotheses, we built TPCs for 18 native (United States) and 13 invasive (United Kingdom) populations of the yellow monkeyflower, <i>Mimulus guttatus</i>. We grew clones of multiple genotypes per population at six temperature regimes in growth chambers. We found that invasive populations have not evolved different thermal optima or performance breadths, providing evidence for evolutionary stasis of thermal performance between the native and invasive ranges after over 200 years post-introduction. Thermal optimum increased with mean annual temperature in the native range, indicating some adaptive differentiation among native populations which was absent in the invasive range. Further, native and invasive populations did not exhibit adaptive clines in thermal performance breadth with latitude or temperature seasonality. These findings suggest that thermal performance curves remained unaltered post-invasion, and that invasion may proceed via broad thermal tolerance and establishment in already climatically suitable areas rather than rapid evolution upon introduction.</p>
Data from: Environmental drivers of population-level variation in the migratory and diving ontogeny of an Arctic top predator
<p>The development of migratory strategies that enable juveniles to survive to recruitment is critical for species that exploit seasonal niches. For animals that forage via breath-hold diving this requires a combination of both physiological and foraging skill development. Here, we assess how migratory and dive behaviour develop over the first months of life for a migratory Arctic top predator, the harp seal, tracked using animal-borne satellite relay data loggers. We reveal similarities in migratory movements and differences in diving behaviour between juveniles from breeding populations in the Northwest Atlantic and Greenland Sea. In both regions, periods of resident and transient behaviour during migration were associated with proxies for food availability; sea ice concentration and water depth. However, while ontogenetic development of dive behaviour was similar for both groups of juveniles over the first 25 days, after this time Greenland Sea animals performed shorter and shallower dives and were more closely associated with sea ice than Northwest Atlantic animals. Together, these results highlight the role of both intrinsic and extrinsic factors in shaping early-life behaviour. Differences in the environmental conditions experienced during early-life may shape how populations respond to the rapid changes occurring in the Arctic ocean ecosystem.</p>
Data accompanying Polyphenisms and polymorphisms: genetic variation in plasticity and color variation within and among bluefin killifish populations
<p>The presence of stable color polymorphisms within populations begs the question of how genetic variation is maintained. Consistent variation among populations in coloration, especially when correlated with environmental variation, raises questions about whether environmental conditions affect either the fulcrum of those balanced polymorphisms, the plastic expression of coloration, or both. Color patterns in male bluefin killifish provoke both types of questions. Red and yellow morphs are common in all populations. Blue males are more common in tannin-stained swamps relative to clear springs. Here we combined crosses with a manipulation of light to explore how genetic variation and phenotypic plasticity shape these patterns. We found that the variation in coloration is attributable mainly to two axes of variation: (1) a red-yellow axis with yellow being dominant to red, and (2) a blue axis that can override red-yellow and is controlled by genetics, phenotypic plasticity, and genetic variation for phenotypic plasticity. The variation among populations in plasticity suggests it is adaptive in some populations but not others. The variation among sires in plasticity within the swamp population suggests balancing selection may be acting not only on the red-yellow polymorphism but also on plasticity for blue coloration.</p>
Data from: Drastic shift in flowering phenology of F1 hybrids explains the population structure of Imperata cylindrica in Japan
<p>Hybridization is a major source of phenotypic variation and a driving force for evolution. On the other hand, these novel traits can often disrupt adaptive relationships between the parental phenotypes and their environments. However, it remains unclear how new hybrid traits disrupt local adaptation. Here, we report how a new phenotype of hybrids between two ecotypes of Imperata cylindrica contributes to rapid reproductive isolation from their parents and affects hybrid fitness.</p> <p>We analyzed 350 accessions of I. cylindrica collected from the 1980s to the 2010s throughout Japan to explore the genetic population structure of the hybrids. We surveyed flowering periods, seed sets, and germination of two ecotypes and their hybrids in both natural habitats and common gardens.</p> <p>Genetic analyses of population structure revealed that the hybrid populations consisted of only F1 individuals, without post-F1 hybrids. The flowering phenology of the F1 plants was delayed to autumn, 5–6 months later than the parental ecotypes.</p> <p>The drastic shift in flowering phenology prevents F1s from backcrossing. In addition, it changes their seed dispersal time to winter. Germination is inhibited by low temperatures, and the seeds likely decay before the next spring, resulting in the absence of an F2 generation. For the first time in the field, we found environmental mismatch of F1 as a specific mechanism for the maintenance of only F1 populations.</p> <p>Synthesis. We have demonstrated that this flowering phenology mismatch promotes reproductive isolation between the parents and F1s and affects various temporal components of the hybrids, resulting in a unique hybrid population consisting only of F1s. This system sheds light on the importance of hybrid traits in terms of rapid reproductive isolation.</p>
Raw data of compounds extracted by GC-MS from each population replicate's of I. uriae ticks from Iceland.
<p>Raw data representing all the compounds extracted by GC-MS from each population replicate’s of <em>I. uriae</em> ticks from three sites in Iceland. Each replicate contain a pool of 10 living flat female ticks.</p> <p>Site: name of the site where ticks were collected.</p> <p>Host: name of the host bird.</p> <p>Replicate: number of the replicate (1 to 4).</p> <p>Peak: number of the detected peaks correponding to extracted compounds.</p> <p>Retention Time: time elapsed between sample introduction and the maximum signal of the given compound.</p> <p>Area: area under the curves of each detected coumpounds on the chromatogram.</p>
IGM Population of HFF structures using Hi-C, laminB1 DamID, 3D HIPMAp FISH and single cell SPRITE data
<p>This repository accompanies the manuscript "<strong>Integrative Genome Modeling Platform reveals essentiality of rare contact events in 3D genome organizations</strong>", to appear in Nat. Methods (2022), see also https://www.biorxiv.org/content/10.1101/2021.08.22.457288v1.</p> <p>It contains the preprocessed input data files (Hi-C, laminB1 DamID, 3D HIPMAp FISH and single cell SPRITE) for the HFF fibroblast cell line to be used in the Integrative Genome Modeling platform (IGM) developed in the Alber lab at UCLA (https://github.com/alberlab/igm).</p> <p>Also, we provide the configuration file to run IGM with those datasets, as we did in generating the HDSF population discussed in the accompanying manuscript. Such population is also provided as an "hss" file. Documentation and a simple demo/tutorial on how IGM can be run is given on the Alber lab Github @ https://github.com/alberlab/igm.</p> <p>All files can be read in using the <em>h5py</em> and <em>alabtools</em> (available @https://github.com/alberlab/alabtools) Python packages. More detailed information is provided in the manuscript and associated Supplementary Information file. </p> <p>For any inquiry/suggestions/doubts please reach out to Lorenzo Boninsegna (bonimba@g.ucla.edu) or Dr. Frank Alber (falber@g.ucla.edu).</p> <p> </p>
Data associated with the manuscript "Simple statistical models can be sufficient for testing hypotheses with population time series data"
<p>This is a revised version of the archive of R code and data used in the manuscript, <em>Simple statistical models can be sufficient for testing hypotheses with population time series data. </em>The data are in three files. <em>etodata1.csv</em> and <em>etodata2.csv</em> contain two versions of the same data for shoal-dwelling fishes in the Etowah River and associated environmental covariates. <em>knz_dat</em> contains data for small mammals collected in the Konza Prairie Biological Station and associated environmental covariates. The R code consists of four primary files that call nine auxiliary files. CaseStudy1-main_code and CaseStudy2-main_code are the primary files for running the two case studies. Simulations1 and Simulations2 are the files for running the two batteries of simulations. We thank the Konza Prairie Biological Station and Konza Prairie Long-Term Ecological Research Program supported by the National Science Foundation (DEB-1440484) for collecting and providing access to mammal community data. More details are in the manuscript and supporting information. </p>
Data from: Homogenization of populations in the wildflower Texas bluebonnet (Lupinus texensis)
Wildflowers seeds are routinely spread along highways and thoroughfares throughout North America as part of federal beautification policy, but the genetic effect of the introduction of these cultivated populations on wild populations of the same species is unknown. Interbreeding may occur between these seeded and wild populations, resulting in several possible outcomes. Here we sample 187 individuals in 12 matched pairs of neighboring wild and seeded populations of the Texas bluebonnet (Lupinus texensis), a species popular in commercially available wildflower seed mixes used by both the Texas Department of Transportation and the public. We use genotyping by sequencing to identify 11,741 genome-wide single nucleotide polymorphisms, as well as a smaller number of SNPs from the chloroplast genome, to analyze population structure and genetic diversity within and between the populations. We find a striking lack of population structure both between wild and seeded populations and amongst wild populations. STRUCTURE analyses indicate that all populations are apparently panmictic. This pattern may be explained by extensive swamping of wild populations by seeded germplasm and increased dispersal of semi-domesticated seed across this species' core native range by humans. We discuss the possible negative and positive ramifications of homogenization on the evolutionary future of this popular wildflower species.
Data from: A new population record of Critically Endangered Dipterocarpus bourdillonii Brandis from the Anamalai Tiger Reserve, Tamil Nadu
<p><strong>This dataset is based on the following manuscript/publication:</strong><br> Page, N., S. Kasinathan, K. Bhat, G. Moorthi, T. Sundarraj, Divya Mudappa, and T. R. S. Raman (2022). A new population record of Critically Endangered <em>Dipterocarpus bourdillonii</em> Brandis from the Anamalai Tiger Reserve, Tamil Nadu. <em>Journal of Threatened Taxa</em> 14(8): 21651–21659. https://doi.org/10.11609/jott.7860.14.8.21651-21659</p> <p>Please refer to the README.txt file included with the dataset for complete details and usage notes.</p> <p><strong>Geographic Coverage:</strong><br> Location/Study Area: Valparai Plateau, Tamil Nadu, India; Anamalai Tiger Reserve, Tamil Nadu, India<br> GPS coordinates: Valparai Plateau (0°15'- 10°22'N, 76°52'-76°59'E); Anamalai Tiger Reserve (10°12'-10°35'N, 76°49'-77°24'E)</p> <p><strong>Temporal Coverage:</strong><br> Begins: 2020-10-01 (Year, Month, Day)<br> Ends: 2022-05-31 (Year, Month, Day)</p> <p><strong>Funding:</strong><br> Fondation Franklinia<br> AMM Murugappa Chettiar Research Centre<br> Rohini Nilekani Philanthropies</p> <p><strong>Dataset:</strong></p> <p>The dataset includes 7 files: 1 text file (<strong>README.txt</strong>), 5 data files in comma-delimited format (CSV), and 1 KML file of seven survey routes. Details of content of each CSV data file are provided below. The following files are included:<br> <strong>README.txt:</strong> Usage notes and metadata related to the dataset<br> <strong>1_Surveys_ver2.csv:</strong> Details of trails covered where Dipterocarpus bourdillonii was recorded during the survey<br> <strong>2_Focal_tree_data_ver2.csv:</strong> Details of focal trees of Dipterocarpus bourdillonii<br> <strong>3_Tree_centred_PCQ_ver2.csv: </strong>Data from point-centred quarter (PCQ) plots sampled with focal trees at the centre<br> <strong>4_Plant_checklist_ver2.csv:</strong> Checklist of plants (mainly trees) recorded on survey trails<br> <strong>5_Seed_fruit_ver2.csv:</strong> Measurements of fruits and seeds of Dipterocarpus bourdillonii<br> <strong>06_Dipterocarpus_bourdillonii_survey_trails.kml:</strong> This file includes the GPS tracks of the seven survey trails in KML format.</p> <p>Details and data available in the columns in each of the above CSV files and the KML file are explained below.</p> <p><strong>1_Surveys_ver2.csv</strong><br> Column: Description<br> Date: Date on which the survey was done<br> Place: Name of the place where the focal tree is located. e.g., Candura, Manamboli, Iyerpadi etc<br> Route_description:Description of place or route covered<br> Trail: Name of the tree survey trail<br> Trail_distance: Distance covered on the trail in kilometres (km)<br> Track_filename_kml: Name of the file with GPS track of survey trail/route, where available, in KML format<br> Observers: Names of observers who took measurements and filled datasheet during survey<br> Remarks: Notes and additional information</p> <p><strong>2_Focal_tree_data_ver2.csv</strong><br> Column: Description<br> FT_ID: Unique numeric linking ID of each focal tree (NA for 3 individuals found in plots around other focal trees)<br> Species: Focal tree species<br> Date: Date on which the survey was done<br> Place: Name of forest range (Manamboli)<br> Waypoint: Unique location waypoint number for the focal tree and GPS instrument used<br> Time: Time when the focal tree's data was collected<br> Location: Landmark where the focal tree is located (NA, if not available)<br> Latitude: Latitude of the focal tree (decimal degrees N)<br> Longitude: Longitude of the focal tree (decimal degrees E)<br> Elevation: Elevation of the focal tree from sea-level in metres<br> Slope: Slope at focal tree location assessed with Clinometer, categorised as Flat, Gentle, Moderate, or Steep (NA, if not available)<br> ID_Notes: Any obvious signs with which to identify focal tree (NA, if not available)<br> Phenophase: Phenophase of the focal tree viz. leaf flush, buds/flowers, fruits (NA, if not available)<br> GBH: Girth of the focal tree in cm, at 1.3m from ground; measured from the higher side if tree is on slope<br> Tree_ht: Focal tree's height in m (NA, if not available)<br> Canopy_ht: Height of canopy in m where the focal tree is located (NA, if not available)<br> Substrate: Substrate where focal tree is standing viz. Earth, Rock, Streamside, Other (NA, if not available)<br> Invasives: List of invasive plant species present within 5 m radius around the focal tree (NA, if not available)<br> Stature: Stature of the focal tree relative to its surroundings (NOT of the species in general) categorised as Understorey, Mid, Canopy, Emergent (NA, if not available)<br> Relatively: Relative height of focal tree in relation to other trees within 10 m radius categorised as Shorter than most, Taller than most, Same height as most (NA, if not available)<br> Deadwood: Estimated percentage of deadwood present on the tree in 4 classes of <25%, 26-50%, 51-75%, 76-100% (NA, if not available)<br> Damage: Observed damages such as Main trunk broken, Branches broken, Hollow at base, Gaping cavity, Infected, Dried leaves (as on a dead branch) (NA, if not available)<br> Shape: Canopy shape of the focal tree (not species in general) categorised as Spreading, Oval, Fan, Column, Cone (NA, if not available)<br> Closure: Canopy closure due to foliage visually estimated standing next to trunk of focal tree and looking up, categorised as 0% (only sky and leafless branches visible), 1-25%, 26-50%, 51-75%, 76-100% (NA, if not available)<br> Seedlings: Count of conspecific seedlings (stems of girth at breast height <10 cm) around the focal tree in a 5 m radius (NA, if not available)<br> Saplings: Count of conspecific saplings (stems of girth at breast height 10-30 cm) around the focal tree in a 5 m radius (NA, if not available)<br> Trees: Count of conspecific trees (stems of girth at breast height >30 cm) around the focal tree in a 5 m radius (NA, if not available)<br> Remarks: Notes and additional information (NA, if not available)</p> <p><strong>3_Tree_centred_PCQ_ver2.csv</strong><br> Column: Description<br> FT_ID: Unique numeric linking ID of each focal tree in point-centred quarter (PCQ) plot<br> Focal_tree: Scientific name of focal tree species at the centre of the PCQ plot<br> Species: Scientific name of tree species recorded in PCQ plot around focal tree<br> GBH (cm): Girth of PCQ tree in cm, at 1.3 m from ground; measured from the higher side if tree is on a slope. Main stem only.<br> Distance: Distance from focal tree, in m; measured from the approximate centre of bole to centre of bole and not bark to bark<br> Multistem: NA if single-stemmed; if multi-stemmed, then GBH of additional stems given as notes.</p> <p><strong>4_Plant_checklist_ver2.csv</strong><br> Column: Description<br> Date: Date on which the survey was done<br> Place: Name of the place where the focal tree is located. e.g., Candura, Manamboli, Iyerpadi etc<br> Route: Route of the tree survey trail<br> Checklist_species: Scientific name of tree species observed as present along trail and within 10 m on either side<br> Remarks: Notes and additional information</p> <p><strong>5_Seed_Fruit_ver2.csv</strong><br> Column: Description<br> Sample: Serial number of sample of single winged fruit measured<br> Species: Scientific name of tree species<br> No_Seeds: Unit number of seed measured<br> Fresh_fruit_weight_g: Weight of each fruit measured on an Ohaus scale in grams<br> Nut_length_cm: Length of nut along the longitudinal axis in cm<br> Nut_width_1_cm: Width of nut in cm measured along axis perpendicular to nut length<br> Nut_width_2_cm: Width of nut in cm measured along axis perpendicular to nut length and nut width 1<br> Wing1_length_cm: Length of longer wing (sepal) in cm<br> Wing1_width_cm: Width of longer wing (sepal) in cm<br> Wing2_length_cm: Length of shorter wing (sepal) in cm<br> Wing2_width_cm: Width of shorter wing (sepal) in cm</p> <p><strong>06_Dipterocarpus_bourdillonii_survey_trails.kml</strong><br> This file includes the GPS tracks of the following seven trails in KML format:<br> 2021-01-30_Anali-Ayyankulam-Manamboli (Trail-2)<br> 2021-03-26_Ayyankulam (Trail-4)<br> 2021-04-10_Ayyankulam Parai (Trail-5)<br> 2022-03-07_Ayyankulam Parai to Ayyankulam_leftbank (Trail-8)<br> 2022-03-07_Ayyankulam Parai to Ayyankulam_rightbank (Trail-9)<br> 2022-03-09_Manamboli PH_leftbank (Trail-10)<br> 2022-03-09_Manamboli PH_rightbank (Trail-11)</p>
Code and Data associated with "Discovery of positive and purifying selection in metagenomic time series of hypermutator microbial populations"
<p>Code and data sufficient to reproduce analyses in "Discovery of positive and purifying selection in metagenomic time series of hypermutator microbial populations".</p>
Data from: What ecological factors favor parthenogenesis over sexual reproduction? A study on the facultatively parthenogenetic mayfly Alainites muticus in natural populations
<p>Different reproductive modes are characterized by costs and benefits which depend on ecological contexts. For example, sex can provide benefits under complex biotic interactions, while its costs increase under mate limitation. Furthermore, ecological contexts often vary along abiotic gradients. Here, we study how these factors simultaneously influence the frequency of sex in the facultatively parthenogenetic mayfly Alainites muticus . We first verified that parthenogenesis translates into female-biased population sex ratios. We then measured the density of individuals (a proxy for mate limitation) and community diversity (biotic interaction complexity) for 159 A. muticus populations covering a broad altitudinal gradient and used structural equation modeling to investigate their direct and indirect influences on sex ratios. We found no effect of community diversity or altitude on sex ratios. Furthermore, even when females can reproduce parthenogenetically, they generally reproduce sexually, indicating that the benefits of sex exceed its costs in most situations. Sex ratios only become female-biased under low population densities, as expected if mate limitation was the main factor selecting for parthenogenesis. Mate limitation might be widespread in mayflies because of their short adult lifespan and limited dispersal, which can generate strong selection for reproductive assurance and may provide a stepping-stone towards obligate parthenogenesis.</p>
Data from: Genetic, maternal, and environmental influences on sociality in a pedigreed primate population
<p>Various aspects of sociality in mammals (e.g., dyadic connectedness) are linked with measures of biological fitness (e.g., longevity). How within- and between-individual variation in relevant social traits arises in uncontrolled wild populations is challenging to determine but is crucial for understanding constraints on the evolution of sociality. We use an advanced statistical method, known as the 'animal model', which incorporates pedigree information, to look at social, genetic, and environmental influences on sociality in a long-lived wild primate. We leverage a longitudinal database spanning 20 years of observation on individually recognized white-faced capuchin monkeys (Cebus capucinus imitator), with a multi-generational pedigree. We analyze two measures of spatial association, using repeat sampling of 376 individuals (mean: 53.5 months per subject, range: 6-185 months per subject). Conditioned on the effects of age, sex, group size, seasonality , and El Niño–Southern Oscillation phases, we show low to moderate long-term repeatability (across years) of the proportion of time spent social (posterior mode [95% Highest Posterior Density interval]: 0.207 [0.169, 0.265]) and of average number of partners (0.144 [0.113, 0.181]) (latent scale). Most of this long-term repeatability could be explained by modest heritability (<em>h<sup>2</sup></em><sub>social</sub>: 0.152 [0.094, 0.207]; <em>h<sup>2</sup></em><sub>partners</sub>: 0.113 [0.076, 0.149]) with small long-term maternal effects (<em>m<sup>2</sup></em><sub>social</sub>: 0.000 [0.000, 0.045]; <em>m<sup>2</sup></em><sub>partners</sub>: 0.000 [0.000, 0.041]). Our models capture the majority of variance in our behavioral traits, with much of the variance explained by temporally changing factors, such as group of residence, highlighting potential limits to the evolvability of our trait due to social and environmental constraints.</p>
Data and code from: Cooperation and coordination in heterogeneous populations
<p>One landmark application of evolutionary game theory is the study of social dilemmas. This literature explores why people cooperate even when there are strong incentives to defect. Much of this literature, however, assumes that interactions are symmetric. Individuals are assumed to have the same strategic options and the same potential payoffs. Yet many interesting questions arise once individuals are allowed to differ. Here, we study asymmetry in simple coordination games. In our setup, human participants need to decide how much of their endowment to contribute to a public good. If a group's collective contributions reach a pre-defined threshold, all group members receive a reward. To account for possible asymmetries, individuals either differ in their endowments or their productivities. According to our theoretical equilibrium analysis, such games tend to have many possible solutions. In equilibrium, group members may contribute the same amount, different amounts, or nothing at all. According to the behavioral experiment, however, humans favor the equilibrium in which everyone contributes the same proportion of their endowment. We use these experimental results to highlight the nontrivial effects of inequality on cooperation, and we discuss to which extent models of evolutionary game theory can account for these effects.</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.