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1,940 results for “data sample”
Data for: Sampling local ant diversities and the importance of trait analyses
<p>Ants are an incredibly diverse and ubiquitous group of invertebrates in most terrestrial ecosystems. Although extensively sampled, the majority of ant inventories do not evaluate the effect of different sampling techniques in capturing non-traditional metrics of diversity. We aimed to quantify TD (taxonomic) and FD (functional) diversities for a local ant assemblage by integrating metrics and evaluating complementarity of pitfall traps and Winkler extractors for the leaf-litter vs. epigaeic ant faunas and to determine the effect of sampling techniques on functional composition (community-weighted means of 11 morphological traits, see <strong>Table S1</strong> in the Excel file and <strong>Trait_base_data.csv</strong> in this dataset) and functional diversity (multi-trait morphospace measured with three different metrics, see <strong>Table S2</strong> in Excel file). We sampled the local community (<strong>Table S3</strong> and <strong>Table S4 </strong>in the Excel file) in an Atlantic Forest fragment using week-long pitfall traps and 1m<sup>2</sup> leaf litter samples submitted to Winkler extractors and quantified the contribution on the technique (refer to <strong>Community_data.csv</strong> in this dataset) to uniquely capture the ant morphospace by applying a new index (PWindex). Although ant TD overlapped, FD was significantly affected by the sampling technique. By controlling for TD effects, the community collected by each technique was differentially structured. Higher TD did not translate into wider morphospace for Winklers. Pitfalls recovered more functionally overdispersed assemblages. Pitfalls and Winklers overlapped in the sampling of the overall community, but each sampling method contributed with a unique spectrum to the ant morphospace. Our results suggest the importance of incorporating FD metrics in local ant inventories and the importance of sampling techniques when measuring the magnitude of FD and community structure. Our PWindex further illuminates sampling effects for ant assemblages.</p>
Fish sampling and physicochemical data for aquatic habitats in the Santarem region of the Lower Amazon, Brazil
<p>Explaining the mechanisms underlying spatial and temporal variation in community composition is a major challenge. Nevertheless, the processes controlling temporal variation at a site (i.e., temporal β-diversity, including its turnover and nestedness components) are less understood than those affecting variation among sites (i.e., spatial β-diversity). Short-term temporal turnover (e.g., throughout an annual cycle) is expected to correlate positively with seasonal environmental variability and landscape connectivity, but also species pool size (γ-diversity). We use the megadiverse Amazonian freshwater ichthyofauna as a model to ask whether seasonality and landscape connectivity drive variation in temporal species turnover among geomorphological habitat types, while accounting for between-habitat variation in γ-diversity. 11,397 fish representing 260 species were collected during a year-long sampling program from an area containing the lowland Amazon's four major geomorphological habitat types: rivers, floodplains, terra firme streams, and shield streams. River-floodplain systems exhibit strong but predictable seasonality (via a high-amplitude annual flood pulse), high connectivity, and high species richness with many rare species. Terra firme and shield streams exhibit low seasonality, low connectivity, and low species richness with proportionally fewer rare species. Based on these parameters we predicted that river-floodplain systems should have higher temporal turnover than stream systems. Using a null model approach combined with β-deviation calculations, we confirmed that rivers and floodplains do exhibit higher turnover (but not nestedness) than terra firme and shield streams, even when controlling for the potentially confounding effect of higher species richness in river-floodplain systems. All habitats exhibit low temporal nestedness, indicating that short-term changes in community composition result primarily from temporal species turnover. Our results provide a timely reminder that efforts to conserve the Amazon's threatened aquatic biodiversity should account for the distinct temporal dynamics of habitat types and variation in hydrological seasonality.</p>
DNA metabarcoding data from faecal samples of the lesser (Myotis blythii) and the greater (Myotis myotis) mouse-eared bats from Bulgaria
<p>A comprehensive understanding of trophic interactions in terrestrial ecosystems is crucial for ecological research and conservation. Recent advances in non-invasive methods, such as DNA metabarcoding, have enabled researchers to collect vast amounts of data on wild animal diets. However, sharing this data and metadata effectively and transparently presents new challenges. To address this, a new type of scholarly journal publication has emerged that aims to describe datasets rather than report research investigations. In this paper, we present a dataset of consumed prey species and parasites based on the metabarcoding of 113 faecal samples from the greater and lesser mouse-eared bats (<em>Myotis myotis</em> and <em>Myotis blythii</em>), along with a detailed description of the data sampling, laboratory analysis, and bioinformatics pipeline. Our dataset comprises 1018 unique Barcode Index Numbers (BINs) from 12 Classes and 43 Orders. In addition, we provide interactive Krona charts to visually summarize the taxonomic relationships and relative read abundance of the consumed prey species and parasites. This data can be used for meta-analysis, exploring new predator-prey and host-parasite interactions, studying inter and intraspecific ecological interactions, and informing protected area management, among other applications. By sharing this dataset, we hope to encourage other researchers to use it to answer additional ecological questions and advance our understanding of trophic interactions in terrestrial ecosystems.</p>
Sample extraction and SNP sequencing data for: Identification of sex-linked SNP markers in wild populations of monomorphic birds
<p><span>Single-nucleotide polymorphism (SNP) analyses are a powerful tool for population genetics, pedigree reconstruction and phenotypic trait mapping. However, the untapped potential of SNP markers to discriminate the sex of individuals in species with reduced sexual dimorphism or of individuals during immature stages remains a largely unexplored avenue. Here, we develop a novel protocol for molecular sexing of birds based on the detection of unique Z- and W-linked SNP markers. Our method is based on the identification of two unique loci, one in each sexual chromosome. Individuals are considered males when they show no calls for the W-linked SNP and are heterozygotic or homozygotic for the Z-linked SNP, while females show both Z- and W-linked SNP calls. We validated the method in the Jackdaw (<em>Corvus</em> <em>monedula</em>). The reduced sexual dimorphism in this species makes it difficult to sex individuals in the wild. We assessed the reliability of the method using 36 individuals of known sex and found that their sex was correctly assigned in 100% of cases. The sex-linked markers also proved to be widely applicable to discriminate males and females from a sample of 927 genotyped individuals of different maturity stages with an accuracy of 99.5%. Given that SNP markers are increasingly used in quantitative genetic analyses of wild populations, the approach we propose has a great potential to be integrated into broader genetic research programmes without the need for additional sexing techniques.</span></p>
Data for validation and norming of the Danish KIDSCREEN-10 child/adolescent version in a national representative sample of school pupils in grades five through eight
<p>Data for for analyses in Measuring child and adolescent well-being in Denmark: validation and norming of the Danish KIDSCREEN-10 child/adolescent version in a national representative sample of school pupils in grades five through eight. Contains the following variables:</p> <p>Variables Kid1 to Kid10 are the KISDCREEN 10 items. Category labels are the orginal from the KIDSCREEN consortium (Danish version). Items Kid3 and Kid4 are reversed coded according to the KIDSCREEN coding manual. Valus have been recoded from 1-5 to 0-4 for the purpose of item analyses.</p> <p>Language (spoken in the home): 1 = Danish, 2 = other</p> <p>School: 1 = public, 2 = private</p> <p>Sex: 1 = boy, 2 = girl</p> <p>Grade (level): 1 = 5th grade, 2 = 6th grade, 3 = 7th grade, 4 = 8th grade</p> <p>Sample (random): 1 to 7</p>
Data from: Robustness of Felsenstein's versus transfer bootstrap supports with respect to taxon sampling
<p><span>The bootstrap method is based on resampling sequence alignments and re-estimating trees. Felsenstein's bootstrap proportions (FBP) is the most common approach to assess the reliability and robustness of sequence-based phylogenies. However, when increasing taxon sampling (i.e., the number of sequences) to hundreds or thousands of taxa, FBP tends to return low supports for deep branches. The Transfer Bootstrap Expectation (TBE) has been recently suggested as an alternative to FBP. TBE is measured using a continuous transfer index in [0,1] for each bootstrap tree, instead of the binary {0,1} index used in FBP to measure the presence/absence of the branch of interest. TBE has been shown to yield higher and more informative supports, while inducing a very low number of falsely supported branches.</span> <span>Nonetheless, it has been argued that TBE must be used with care due to sampling issues, especially in datasets with high number of closely related taxa. In this study, we conduct multiple experiments by varying taxon sampling and comparing FBP and TBE support values on different phylogenetic depth, using empirical datasets. Our results show that the main critique of TBE stands in extreme cases with shallow branches and highly unbalanced sampling among clades, but that TBE is still robust in most cases, while FBP is inescapably negatively impacted by high taxon sampling. We suggest guidelines and good practices in TBE (and FBP) computing and interpretation.</span></p>
Tornado Detection From Full-Resolution Polarimetric Weather Radar Data (SAMPLE)
<p>This dataset contains a small sample of the tornado dataset described in the talk "A Tornado Detection Algorithm using Deep Neural Networks, Full-Resolution Polarimetric Weather Radar Data, and Explainable AI" presented at the 40th Conference on Radar Meteorology on Aug 31st 2023.</p> <p>The files contained in this data represent approximately 1% of the full dataset that will be released upon final publication.</p> <p>For questions please contact</p> <p>James.Kurdzo@ll.mit.edu and mark.veillette@ll.mit.edu</p>
Sample data for the evaluation of pNARA v1.0
<p>This dataset provides the sample data used in the evaluation of pNARA v1.0. For the AOD evaluation, the pNARA v1.0, MERRA-2, and CAMSRA are NARA-1.0_AOD_2016010100.nc4, MERRA2_400.inst3_2d_gas_Nx.20160101.nc4, and cams_aods_20160101.nc, respectively. The aerosol mass mixing ratios on pressure levels (at 100, 250, 400, 500, 600, 700, 850, 925, and 1000 hPa) for each product are fv3_aeros_2016010100_pll.nc (pNARA v1.0), MERRA2_aeros.20160101.nc4 (MERRA-2), and cams_aeros_20160101.nc (CAMSRA). The aerosol mixing ratios on model level for pNARA v1.0 (NARA-1.0_aero_2016010100.nc4) and MERRA-2 (MERRA2_400.inst3_3d_aer_Nv.20160101.nc4) are also included.</p>
Data for A Far-Red Fluorescent Probe to Visualize Staphylococcus aureus in Patient Samples
<p>Raw and processed data supporting the manuscript "A Far-Red Fluorescent Probe to Visualize <em>Staphylococcus aureus</em> in Patient Samples"</p>
Dustonly - Sample Data
<p><strong>Test case for dust simulations with Dustonly: Sahara Desert</strong></p> <p>Model Description:<br> Dustonly is the standalone version of the dust emission scheme used in the aerosol transport model MUSCAT (<a href="http://doi.org/10.1029/2006jd007443">Heinold et al.,2007</a>; <a href="http://doi.org/10.1016/j.atmosenv.2012.02.085">Wolke et al.,2012</a>).<br> The Dustonly source code is available on <a href="https://github.com/Dustonly/Dustonly">GitHub</a>.</p> <p>File Description:</p> <ul> <li>10-m wind data (48h with 1h increment), calculated with the COSMO model v5.05 (<a href="http://doi.org/10.5676/DWD_PUB/NWV/COSMO-DOC_5.05_I">Doms and Baldauf, 2018</a>).</li> <li>Soil texture data from the SoilGrids database (<a href="http://doi.org/10.5194/soil-7-217-2021">Poggio et al., 2021</a>)</li> <li>Mineralogical data from the GMINER database (<a href="http://doi.org/10.5194/acp-12-845-2012">Nickovic et al., 2012</a>)</li> <li>Vegetation cover from Copernicus Global Land Service (<a href="http://doi.org/10.3390/rs12061017">Fuster et al., 2020</a>)</li> <li>Grid file in CDO format, describing the model domain.</li> <li>Dustony NAMELIST, configuration to run the test case.</li> <li>The expected model output.</li> </ul>
Data from: Sampling methodology influences habitat suitability modeling for Chiropteran species
<p>Technological advances increase opportunities for novel wildlife survey methods. With increased detection methods, many organizations and agencies are creating habitat suitability models (HSMs) to identify critical habitats and prioritize conservation measures. However, multiple occurrence data types are utilized independently to create these HSMs with little understanding of how biases inherent to those data might impact HSM efficacy.</p> <p>We sought to understand how different data types can influence HSMs using three bat species (<em>L. borealis</em>, <em>L. cinereus</em>, and <em>P. subflavus</em>). We compared the overlap of models created from passive-only (acoustics), active-only (mist-netting and wind turbine mortalities), and combined occurrences to identify the effect of multiple data types and detection bias.</p> <p>For each species, the active-only models had the highest discriminatory ability to tell occurrence from background points and for two of the three species, active-only models performed best at maximizing the discrimination between presence and absence values. By comparing the niche overlaps of HSMs between data types, we found a high amount of variation with no species having over 45% overlap between the models. Passive models showed more suitable habitat in agricultural lands, while active models showed higher suitability in forested land, reflecting sampling bias.</p> <p>Overall, our results emphasize the need to carefully consider the influences of detection and survey biases on modeling, especially when combining multiple data types or using single data types to inform management interventions. Biases from sampling, behavior at the time of detection, false positive rates, and species life history intertwine to create striking differences among models. The final model output should consider biases of each detection type, particularly when the goal is to inform management decisions, as one data type may support very different management strategies than another. </p>
Data from: Stability assessment of organic sulfur and organosulfate compounds in filter samples for quantification by Fourier Transform-Infrared Spectroscopy and Ion Chromatography
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Data from: Measuring behavior patterns and evaluating time sampling methodology to characterize brush use in weaned beef cattle
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Data from: Refining sampling efforts for fish diversity assessment in subtropical urban estuarine and oceanic waters using environmental DNA with multiple primers
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Data from: Fine-tuning the nested structure of pollination networks by adaptive interaction switching, biogeography and sampling effect in the Galápagos Islands
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Data from: The effect of sampling methods on the validity and reliability of the estimation of the orbital stability of human gait
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Data from: Flexible methods for species distribution modeling with small samples
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Bulk Carbon and Amino Acid nitrogen isotope data from Baltic cod (Gadus morhua) and European flounder (Platichthys flesus) muscle tissue samples from the western and central Baltic Sea
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Data from: Overcoming the challenge of small effective sample sizes in home-range estimation
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Data from: Landscape genetic inferences vary with sampling scenario for a pond breeding amphibian
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ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.