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3,101 results for “Historical”
Canadian historical Snow Water Equivalent dataset (CanSWE, 1928-2024)
<p><strong>Description</strong> (in English, French follows)</p> <p>The Canadian historical Snow Water Equivalent dataset (CanSWE) includes manual and automated pan-Canadian observations of Snow Water Equivalent (SWE) collected by national, provincial and territorial agencies, hydropower companies and their partners, as well as academic institutions. Snow depth and derived bulk snow density are also included when available. A code describes the SWE measurement method for each site following World Meteorological Organization (WMO) standards (WMO, 2019). This new dataset supersedes the most recent update of the Canadian Historical Snow Survey (CHSSD) dataset published by Brown et al. (2019) and available at <a href="https://doi.org/10.18164/cf337b6b-9a87-4ffd-a8e5-41e6498b1474">https://doi.org/10.18164/cf337b6b-9a87-4ffd-a8e5-41e6498b1474</a>. The creation of CanSWE used the 2019 CHSSD update as a starting point and involved three main steps: (i) correction and cleaning of the 2019 CHSSD update (correction of metadata, removal of duplicates), (ii) update of this cleaned dataset until July 2020 and addition of snow data from new stations and agencies, and (iii) consistent quality control of the final dataset. The version 6 of CanSWE includes over one million SWE measurements from 2945 different locations across Canada over the snow seasons 1928 – 2024 where a snow season is defined as starting August 01 and ending July 31. CanSWE is described in detail in Vionnet et al. (2021).</p> <p>The data are distributed in 2 formats: a NetCDF file (CanSWE-CanEEN_1928-2024_v7.nc) and a zip file containing a csv version of CanSWE (CanSWE-CanEEN_1928-2024_v7.zip). More details about the dataset, the file format and the update made in CanSWEv7 are given in the files ReadMe_CanSWE_v7.pdf (in English) and LisezMoi_CanEEN_v7.pdf (in French).</p> <p><strong>Description</strong> (Francais)</p> <p>La base données historiques canadiennes d’Equivalent en Eau de la Neige (CanEEN) comprend des observations manuelles et automatiques de l’Equivalent en Eau de la Neige (EEN) à l’échelle du Canada collectées par des agences nationales, provinciales et territoriales, des compagnies productrices d’hydroélectricité et leurs partenaires ainsi que par des universités. Les informations sur la hauteur de neige et la masse volumique moyenne du manteau neigeux sont incluses lorsqu’elles sont disponibles. Un code qui suit les règles de l’Organisation Mondiale de la Météorologie (OMM, 2019) décrit la méthode de mesure de l’EEN pour chaque site. Cette nouvelle base de données remplace le jeu de données des Relevés Nivométriques Canadiens (RNC) publié par Brown et al. (2019) et disponible à l’adresse : <a href="https://doi.org/10.18164/cf337b6b-9a87-4ffd-a8e5-41e6498b1474">https://doi.org/10.18164/cf337b6b-9a87-4ffd-a8e5-41e6498b1474</a>. La création de CanEEN se base sur la version de 2019 des RNC et se décompose en 3 étapes principales : (i) correction et nettoyage de la version 2019 des RNC (correction des métadonnées, suppression des duplicata), (ii) mise à jour de ce jeu de données nettoyé avec des données disponibles jusqu’en Juillet 2020 et ajout de données historiques provenant de nouvelles stations et de nouveaux partenaires, (iii) contrôle qualité appliqué à l’ensemble du jeu de données. La version 7 de CanEEN inclut plus d’un million de mesures de l’EEN collectées dans 2945 stations à travers le Canada pour les années nivologiques 1928 à 2023 où une année nivologique est définie pour la période allant du 1 août au 31 juillet. CanEEN est décrit en détail dans Vionnet et al. (2021).</p> <p>Les données sont distribuées sous deux formats: un fichier au format NetCDF (CanSWE-CanEEN_1928-2024_v7.nc) et une archive zip contenant un fichier au format csv (CanSWE-CanEEN_1928-2024_v7.csv). Des informations complémentaires sur le jeu de données, leur format ainsi que les modifications apportées dans la version 6 sont fournies dans les fichiers ReadMe_CanSWE_v7.pdf (en Anglais) et LisezMoi_CanEEN_v7.pdf (en Francais).</p> <p><strong>References/Références: </strong></p> <p>Brown, R. D., Fang, B., and Mudryk, L.: Update of Canadian historical snow survey data and analysis of snow water equivalent trends, 1967–2016. Atmos. Ocean, 57, 149 156, <a href="https://doi.org/10.1080/07055900.2019.1598843">https://doi.org/10.1080/07055900.2019.1598843</a>, 2019</p> <p>Vionnet, V., Mortimer, C., Brady, M., Arnal, L., and Brown, R.: Canadian historical Snow Water Equivalent dataset (CanSWE, 1928–2020), Earth Syst. Sci. Data, 13, 4603–4619, https://doi.org/10.5194/essd-13-4603-2021, 2021.</p> <p>WMO (World Meteorological Organization): Global Cryosphere Watch: Improvements in the international reporting of Snow Depth, WIGOS Newsletter, 5, 3-4, <a href="https://community.wmo.int/wigos-newsletters-archive">https://community.wmo.int/wigos-newsletters-archive</a>, 2019</p>
EncycNet: A Knowledge Graph of Historical German Encyclopedias
<p><strong>EncycNet</strong> is an automatically constructed knowledge graph that uses historical German encyclopedias as a data source. You can read more about the project here: <a href="https://encycnet.github.io/">https://encycnet.github.io/</a></p> <p>The first version of the graph (0.1) contains <em>Meyers Großes Konversations-Lexikon </em>(1905), with 5 more encyclopedias to be added in 2024. Formatted in RDF Turtle.</p> <p>The second version of the graph (0.2) contains 3 encyclopedias in total, meaning triples were changed to quads (see code example at <a href="https://github.com/EncycNet/Encyc-Relations">https://github.com/EncycNet/Encyc-Relations</a>):</p> <ul> <li><em>Meyers Großes Konversations-Lexikon </em>(1905)</li> <li><em>Herders Conversations-Lexikon</em> (1854)</li> <li><em>Brockhaus Bilder-Conversations-Lexikon</em> (1837)</li> </ul> <p>The second version also handled some bug fixes concerning wrongly matched Wikidata entries.</p> <p>The third version (0.3) now additionally contains</p> <ul> <li><em>Brockhaus Conversations-Lexikon oder kurzgefaßtes Handwörterbuch</em> (1809)</li> </ul> <p>It also impoved some namespace issues and introduced <a href="https://www.wikidata.org/wiki/Property:P8371">P8371</a> as encyclopedic refeferences in this case.</p>
Four historical tree-ring chronologies and underlying data derived from dendrochronological research on Batavia shipwreck timbers
<p>This dataset comprises four tree-ring chronologies and underlying tree-ring data derived from the dendrochronological research on the shipwreck timbers of the <em>Batavia</em> shipwreck. The undated tree-ring series have also been included.</p> <p>For context information about this dendrochronological dataset, please refer to the publication:</p> <p>Daly A, Domínguez-Delmás M, van Duivenvoorde W (2021) <em>Batavia</em> shipwreck timbers reveal a key to Dutch success in 17th-century world trade. PLOS ONE 16(10): e0259391. <a href="https://doi.org/10.1371/journal.pone.0259391">https://doi.org/10.1371/journal.pone.0259391</a> </p> <p> </p>
Dataset for "Winter inverse lake stratification under historic and future climate change"
<p>Summary results for Woolway et al., Winter inverse lake stratification under historic and future climate change. See README file for specific information on the variables provided.</p>
Fire danger indices historical data from the Copernicus Emergency Management Service
<p>June, July August consolidated data.</p> <p>Generated using Copernicus Climate Change Service information 2021.</p>
Historical Data for paper "When will humanity notice its impacts on atmospheric rivers?"
<p>The repository contains the historical scenario simulation (one ensemble member) of GFDL SPEAR large ensemble data. The data is used to support the finding in the paper entitled "When will humanity notice its impacts on atmospheric rivers?" by Tseng et al. </p>
Data from: Historical surveys reveal a long-term decline in muskrat populations
<p>The muskrat (<i>Ondatra zibethicus</i>) is an iconic species in Canada, valued for both its fur and its integral role in wetland ecosystems, and widely regarded for its perseverance. However, the resilience of this semi-aquatic mammal seems to be in question now as increasing evidence points to widespread population declines. Recent analyses of harvest data across North America suggest a reduction in their numbers, but this has not been widely corroborated by population surveys. In this study we replicated historic muskrat house count surveys at two large Great Lakes coastal wetlands and present confirmation that declines in muskrat harvest correspond to actual declines in muskrat abundance. At the Point Pelee National Park marsh and the Matchedash Bay-Gray Marsh wetland we found that mean muskrat house counts declined by 93% and 91% respectively between historic surveys 40-50 years ago and contemporary surveys over the past seven years. The factors responsible for these dramatic declines remain unclear but there may be a relationship with changes in the habitat quality of these wetlands that have occurred over the same time frame. Not only is the loss of muskrats an issue for the resulting loss of the wetland ecosystem services they provide, but it may be an indication of broader marsh ecosystem degradation. As such, a scarcity of muskrats should be considered a red flag for the state of biodiversity in our wetlands. Continued surveys and ongoing research are needed to shed more light on the current status of muskrat populations and their marsh habitats across their native range.</p>
Hoplodactylus duvaucelii sequencing reads (FastQ) - modern, historic and ancient
<p class="MsoNormal"><span>Methodological and technological improvements are continually revolutionizing the field of ancient DNA. Most ancient DNA extraction methods require the partial (or complete) destruction of finite museum specimens, which disproportionately impacts small or fragmentary subfossil remains, and future analyses. We present a minimally destructive ancient DNA extraction method optimized for small vertebrate remains. We applied these methods to detect lost mainland genetic diversity in the large New Zealand diplodactylid gecko genus <em>Hoplodactylus, </em></span>which is presently restricted to predator-free island and mainland sanctuaries. <span>We present the first mitochondrial genomes for New Zealand diplodactylid geckos, recovered from 19 modern, six historic/archival </span>(1898 to 2011) <span>and 16 Holocene <em>Hoplodactylus duvaucelii</em> <em>sensu latu</em> specimens, and one modern <em>Woodworthia</em> sp. specimen. No obvious damage was observed in post-extraction micro-CT reconstructions. All 'large gecko' specimens examined from extinct populations were found to be conspecific with extant <em>Hoplodactylus</em> species, suggesting their large relative size evolved only once in the New Zealand diplodactylid radiation. Phylogenetic analyses of <em>Hoplodactylus </em>samples recovered two genetically (and morphologically) distinct North and South Island clades, probably corresponding to distinct species. Finer phylogeographic structuring within <em>Hoplodactylus </em>spp<em>.</em> highlighted the impacts of Late-Cenozoic biogeographic barriers, including the opening and closure of Pliocene marine straits, fluctuations in size and suitability of glacial refugia, and eustatic sea-level change. Recent mainland extinction obscured these signals from the modern tissue derived data. </span>These results highlight the utility of minimally destructive DNA extraction in genomic analyses of less well studied small vertebrate taxa, and the conservation of natural history collections.</p>
Dataset on the Chemistry of Australian Plant Exudates from Historical Collection
<p>FT-IR.zip: FT-IR dataset<br> GC-MS.zip: GC-MS dataset<br> ICP-MS.zip: ICP-MS dataset<br> Py-GC-MS.zip: Py-GC-MS dataset<br> XRS C K-edge.zip: X-ray Raman spectroscopy dataset at the carbon K edge<br> XRS O K-edge.zip: X-ray Raman spectroscopy dataset at the carbon O edge</p>
Life history data on married women of the historical population of île aux Coudres
<p>Evidence from natural populations shows that changes in environmental conditions can cause rapid modifications in the evolutionary potential of phenotypes, partly through genotype-by-environment interactions (G×E). Therefore, the overall rate of microevolution should depend on fluctuations in environmental conditions, even when directional selection is sustained over several generations. We tested this hypothesis in a preindustrial human population that experienced a microevolutionary change in age at first reproduction (AFR) of mothers, using the annual infant mortality rate (IMR) as an indicator of environmental conditions during their early life. Using quantitative genetics analyses, we found that G×Es explained a non-negligible fraction of the additive genetic variance in AFR and in relative fitness, as well as of the genetic covariance between AFR and fitness (i.e. the Robertson-Price covariance). The covariance was stronger for individuals exposed to unfavorable early-life environmental conditions. Our results unravel the presence of G×Es in an important life history trait and its impact on the rate of microevolution, which appears to have been sensitive to short-term fluctuations in local environmental conditions.</p>
Data set - Island area and historical geomorphological dynamics shape multifaceted diversity of barrier island floras
<div> <p><span>The influence of island dynamics and characteristics on taxonomic diversity, particularly species richness, are well studied. Yet, our knowledge on the influence of island dynamics and characteristics on other facets of diversity, namely functional and phylogenetic diversity, is limited, constraining our understanding of assembly processes on islands (e.g., biogeographic history, dispersal and environmental filtering, and species interactions). Using barrier islands, a highly dynamic and so far, understudied island type, we investigate how multiple facets of vascular plant diversity (functional, phylogenetic and taxonomic diversity) are shaped by island geomorphology, modern and historic area, and habitat heterogeneity. In line with our expectation, historical dynamics in island geomorphology affected phylogenetic and taxonomic diversity via habitat heterogeneity. However, island area was the best predictor across all facets of diversity. Specifically, larger islands had higher functional and phylogenetic diversity than expected by chance while most of the smaller islands had lower diversity. The influence of area on functional diversity acted via habitat heterogeneity, with habitat heterogeneity influencing negatively functional diversity. Our results suggest that larger islands accumulate functionally and phylogenetically unique species. Further, results for functional diversity pointed towards potential area-heterogeneity trade-offs, with these trade-offs likely resulting from increased interspecific competition favoring a specific set of trait values (of stronger competitors), particularly on smaller islands. Together, these results demonstrate that going beyond taxonomic diversity contributes to identifying underlying processes shaping diversity-area relationships. </span></p> </div>
South-East US historical and projected population per county for FUTURES urban growth modeling in GRASS GIS
<p>South East US historical (2001-2019) and projected (2020-2100) population per county for 6 states (NC, SC, TN, GA, AL, FL). Historical data come from The National Vital Statistics System (https://seer.cancer.gov/popdata/download.html) and future data are projected by Hauer 2019 (https://doi.org/10.1038/sdata.2019.5) for SSP2 scenario. Data are formatted for r.futures.demand module, which is a GRASS GIS addon for computing future land demand for FUTURES urban growth model. </p>
Historical IVT data of SPEAR-LE (ens02)
<p>The repository contains the historical scenario simulation (2nd ensemble) of GFDL SPEAR large ensemble data. The data is used to support the finding in the paper entitled "When will humanity notice its impacts on atmospheric rivers?" by Tseng et al. </p>
Historical IVT data of SPEAR-LE (ens04)
<p>The repository contains the historical scenario simulation (4th ensemble) of GFDL SPEAR large ensemble data. The data is used to support the finding in the paper entitled "When will humanity notice its impacts on atmospheric rivers?" by Tseng et al. </p>
Historical IVT data of SPEAR-LE (ens03)
<p>The repository contains the historical scenario simulation (3rd ensemble) of GFDL SPEAR large ensemble data. The data is used to support the finding in the paper entitled "When will humanity notice its impacts on atmospheric rivers?" by Tseng et al. </p>
Historical IVT data of SPEAR-LE (ens05)
<p>The repository contains the historical scenario simulation (5th ensemble) of GFDL SPEAR large ensemble data. The data is used to support the finding in the paper entitled "When will humanity notice its impacts on atmospheric rivers?" by Tseng et al. </p>
Historical context modifies plant diversity–community productivity relationships in alpine grassland
<p class="MsoNormal"><span>While most studies yield positive relationships between biodiversity (B) and ecosystem functioning (EF), awareness is growing that BEF relationships can vary with ecological context. The awareness has led to increased efforts to understand how contemporary environmental context modifies BEF relationships, but the role of historical context, and the mechanisms by which it may influence biodiversity effects, remains poorly understood.</span></p> <p class="MsoNormal"><span>We examined how historical context alters plant diversity‒community productivity relationships via plant species interactions in alpine grassland. We also tested how historical context modifies interactions between plants and arbuscular mycorrhizal (AM) fungi, which can potentially mediate the above processes.</span></p> <p class="MsoNormal"><span>We studied biodiversity effects on plant community productivity at two grassland sites with different histories related to grazing intensity — heavy versus light livestock grazing — but similar current management. We assembled experimental communities of identical species composition with plants from each of the two sites in disturbed soil from a contemporary heavily grazed grassland, ranging in species richness from one to two, three and six species. Moreover, we carried out a mycorrhizal hyphae-exclusion experiment to test how plant interactions with AM fungi influence plant responses to historical context.</span></p> <p class="MsoNormal"><span>We detected a significantly positive diversity‒productivity relationship that was driven by complementarity effects in communities composed of plants from the site without heavy-grazing history, but no such relationship in plant communities composed of plants from the site with heavy-grazing history</span><span class="MsoCommentReference"><span>.</span></span><span> </span><span>Plants from the site with heavy-grazing history had increased competitive ability and increased yields in low-diversity communities but disrupted complementarity effects in high-diversity communities. </span><span>Moreover, plants of one species from the site with heavy-grazing history benefitted more from AM fungal communities than did plants from the site without such history.</span></p> <p class="MsoNormal"><span>Synthesis: Using the same experimental design and species, communities assembled by plants from two sites with different historical contexts showed different plant diversity</span><span>‒community productivity relationships</span><span>. Our results suggest that historical context can alter plant diversity</span><span>‒community productivity relationships via plant species interactions and potentially </span><span>plant</span><span>‒soil interactions. Therefore, considering historical contexts of ecological communities is of importance for advancing our understanding of long-term impacts of anthropogenic disturbance on ecosystem functioning.</span></p>
Historical AR data of SPEAR-LE (ens03)
<p>The repository contains the historical scenario simulation (3rd ensemble) of GFDL SPEAR large ensemble data. The data is used to support the finding in the paper entitled "When will humanity notice its impacts on atmospheric rivers?" by Tseng et al. </p>
Historical AR data of SPEAR-LE (ens04)
<p>The repository contains the historical scenario simulation (4th ensemble) of GFDL SPEAR large ensemble data. The data is used to support the finding in the paper entitled "When will humanity notice its impacts on atmospheric rivers?" by Tseng et al. </p>
Historical AR data of SPEAR-LE (ens02)
<p>The repository contains the historical scenario simulation (2nd ensemble) of GFDL SPEAR large ensemble data. The data is used to support the finding in the paper entitled "When will humanity notice its impacts on atmospheric rivers?" by Tseng et al. </p>
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.