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From 1 - 10 / 19
  • This dataset contains instream dissolved oxygen data collected continuously at one minute intervals for five sites in the Hampshire Avon catchment in the United Kingdom. Data were collected between August 2014 and August 2015 using miniDOT loggers. Full details about this dataset can be found at https://doi.org/10.5285/840228a7-40a1-4db4-aef0-a9fea2079987

  • The Pantheon database contains habitat-related traits, feeding guilds, conservation status (including rarity and threat status), legal protection data and associations with other taxa for just over 11,700 invertebrates. The database has been developed for invertebrates within England so the data should be used with caution when applying it to invertebrates of other countries. The data have been extracted from numerous sources within the published literature and compiled and categorised by entomological experts over a number of years. The database also includes (and supersedes) species assemblage types (SATs) from the Invertebrate Species-habitat Information System (ISIS). Species names have been linked with the Taxon Version Key (TVK; unique identifier) from the UK Species Inventory, held by the Natural History Museum, where possible. Overall the database holds 154,072 records. The database was developed by Natural England and the Centre for Ecology & Hydrology as part of a development of online analytical tools to benefit invertebrate conservation and site assessments. Full details about this dataset can be found at https://doi.org/10.5285/2a353d2d-c1b9-4bf7-8702-9e78910844bc

  • Field-pathological findings of 33 saiga antelope carcasses (adults and new-born) found in two sites (Tengiz and Turgai, Kazakhstan) during a mass die-off event in May 2015. In Kazakhstan May 2015, approximately 200,000 saiga antelopes died within a month-period causing a loss of two-thirds of the global population. The dramatic event occurred during calving season when females and young males stop migrating and form massive aggregations for calving purposes. With 100% morbidity and 100% mortality of affected herds observed, the 2015 die-off left the largest saiga population, Betpak-Dala, with approximately 30,000 survivors based on post mortality census, highlighting the imminent extinction threats to this critically endangered species. The lack of pathological investigations during historical mass mortality events has limited our understanding of disease-related mortalities in saiga antelope. Generally, aetiological agents were isolated from dead saiga, but the disease course and a full necropsy were not performed nor present in the records. However, for the first time, a full pathology report was possible during 2015. Full details about this dataset can be found at https://doi.org/10.5285/30cbfba7-f9a1-47d5-abdb-f2741041e487

  • Spatial data files holding gridded parameter maps of surface soil hydraulic parameters derived from a selection of pedotransfer functions. Modern land surface model simulations capture soil profile water movement through the use of soil hydraulics sub-models, but good hydraulic parameterisations are often lacking - especially in the tropics - and it is this lack that we fill here in the context of South America. Optimal hydraulic parameter values are given for the Brooks and Corey, Campbell, van Genuchten-Mualem and van Genuchten-Burdine soil hydraulic models, which are widely-used hydraulic sub-models in many land surface models (e.g. Joint UK Land Environment Simulator JULES). Full details about this dataset can be found at https://doi.org/10.5285/4078678b-768f-43ff-abba-b87712f648e9

  • [This dataset is embargoed until January 22, 2021]. This dataset includes measurements of soil respiration in 20 plots (250 x 10 m each) in the Brazilian Amazon. Study plots were distributed across a gradient of forest disturbance, including: undisturbed primary forests , logged primary forests, logged-and-burned primary forests, and secondary forests. Data were collected from January 2015 until November 2017. In December 2015, during the El Niño-mediated drought, eight of our study plots were affected by understory fires. Full details about this dataset can be found at https://doi.org/10.5285/e5f361b3-b434-4d11-9407-e5f48fe442b0

  • [This dataset is embargoed until January 24, 2021]. This dataset includes measurements of stem radial growth in 20 plots (250 x 10 m each) in the Brazilian Amazon. Study plots were distributed across a gradient of forest disturbance, including: undisturbed primary forests , logged primary forests, logged-and-burned primary forests, and secondary forests. Data were collected from December 2014 until October 2018. In December 2015, during the El Niño-mediated drought, eight of our study plots were affected by understory fires. Full details about this dataset can be found at https://doi.org/10.5285/c8bc6982-d4de-4e6f-aadb-08aac877b263

  • [This dataset is embargoed until February 23, 2021]. This dataset includes measurements of stem respiration in 20 plots (250 x 10 m each) in the Brazilian Amazon. Study plots were distributed across a gradient of forest disturbance, including: undisturbed primary forests , logged primary forests, logged-and-burned primary forests, and secondary forests. Data were collected from June 2015 until July 2018. In December 2015, during the El Niño-mediated drought, eight of our study plots were affected by understory fires. Full details about this dataset can be found at https://doi.org/10.5285/4826f7c3-d6f2-47e5-8dda-c084e54720f6

  • [This dataset is embargoed until January 24, 2021]. This dataset includes measurements of soil respiration in 20 plots (250 x 10 m each) in the Brazilian Amazon. Study plots were distributed across a gradient of forest disturbance, including: undisturbed primary forests , logged primary forests, logged-and-burned primary forests, and secondary forests. Data were collected from October 2014 until May 2018. In December 2015, during the El Niño-mediated drought, eight of our study plots were affected by understory fires. Full details about this dataset can be found at https://doi.org/10.5285/def51d3d-d653-40ca-8231-a238b0c66975

  • Gridded daily meteorological variables over Great Britain for the years 1961-2017 at 1 km resolution. This dataset contains time series of daily mean values of air temperature (K), specific humidity (kg kg-1), wind speed (m s-1), downward longwave radiation (W m-2), downward shortwave radiation (W m-2), precipitation (kg m-2 s-2) and air pressure (Pa), plus daily temperature range (K). These are the variables required to run the JULES land surface model with daily disaggregation. The data are provided in gridded netCDF files. There is one file for each variable for each month of the data set. This data set supersedes the previous version as temporal coverage has been extended to include the years 2016-2017 and the netCDF metadata has been updated and improved. Full details about this dataset can be found at https://doi.org/10.5285/2ab15bf0-ad08-415c-ba64-831168be7293

  • Gridded potential evapotranspiration over Great Britain for the years 1961-2017 at 1 km resolution. This dataset contains two potential evapotranspiration variables: daily total potential evapotranspiration (PET; kg m-2) for a well-watered grass and daily total potential evapotranspiration with interception correction (PETI; kg m-2). The data are provided in gridded netCDF files. There is one file for each variable for each month of the data set. This data set supersedes the previous version as bugs in the calculation of the variables have been fixed (for all years), temporal coverage of both variables has been extended to include the years 2016-2017 and the netCDF metadata has been updated and improved. Full details about this dataset can be found at https://doi.org/10.5285/9116e565-2c0a-455b-9c68-558fdd9179ad