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of Bonn","United States Department of Agriculture – Agricultural Research Service  (USDA‐ARS)","Stockholm Environment Institute at York","Chinese Academy of Sciences","The University of Tokyo","Banaras Hindu University"],"authorFamilyName":["Sharps","Mills","Simpson","Pleijel","Frei","Burkey","Emberson","Uddling","Broberg","Feng","Kobayashi","Agrawal"],"authorFullName":["Sharps, K.","Mills, G.","Simpson, D.","Pleijel, H.","Frei, M.","Burkey, K.","Emberson, L.","Uddling, J.","Broberg, M.","Feng, Z.","Kobayashi, K.","Agrawal, M."],"authorGivenName":["K.","G. ","D. ","H. ","M. ","K. ","L. ","J. ","Z.","M."],"authorOrcid":["0000-0003-3265-1505","0000-0001-9538-3208","0000-0002-6975-5984","0000-0002-2474-6558","0000-0001-5370-4894"],"authorRor":["https://ror.org/00pggkr55","https://ror.org/001n36p86","https://ror.org/01tm6cn81","https://ror.org/041nas322","https://ror.org/02d2m2044","https://ror.org/051xgzg37","https://ror.org/034t30j35","https://ror.org/057zh3y96","https://ror.org/04cdn2797"],"availability":"Available","catalogue":"eidc","dataFormat":["Shapefile"],"description":"Modelled average percentage yield loss due to ground-level ozone pollution (per 1 degree by 1 degree grid cell) are presented for the crops maize (Zea mays), rice (Oryza sativa), soybean (Glycine max) and wheat (Triticum aestivum) for the period 2010-2012. Data are on a global scale, based on the distribution of production for each crop, according to the Food and Agriculture Organisation’s (FAO) Global Agro-Ecological Zones (GAEZ) crop production data for the year 2000. Modelled ozone data (2010-2012) needed for yield loss calculations were derived from the EMEP MSC-W (European Monitoring and Evaluation Programme, Meteorological Synthesising Centre-West) chemical transport model (version 4.16). Mapping the global crop yield losses due to ozone highlights the impact of ozone on crops and allows areas at high risk of ozone damage to be identified, which is one of the first steps towards mitigation of the problem. \n\nThe yield loss calculations were done as part of the NERC funded SUNRISE project and National Capability Project NC-Air quality impacts on food security, ecosystems and health.","documentType":"GEMINI_DOCUMENT","familyName":["Sharps","Mills","Simpson","Pleijel","Frei","Burkey","Emberson","Uddling","Broberg","Feng","Kobayashi","Agrawal"],"fullName":["Sharps, K.","Mills, G.","Simpson, D.","Pleijel, H.","Frei, M.","Burkey, K.","Emberson, L.","Uddling, J.","Broberg, M.","Feng, Z.","Kobayashi, K.","Agrawal, M."],"funder":["Natural Environment Research Council"],"givenName":["K.","G. ","D. ","H. ","M. ","K. ","L. ","J. ","Z.","M."],"grant":["NE/R000131/1"],"identifier":"2a932995-f040-4724-ad21-3e92ae8a2540","incomingCitationCount":1,"keyword":["SUNRISE","Agriculture","Environmental risk","Triticum aestivum","Glycine max","Zea may","Oryza sativa"],"keywordsOther":["Triticum aestivum","Glycine max","Zea may","Oryza sativa"],"keywordsProject":["SUNRISE"],"keywordsTheme":["Agriculture","Environmental risk"],"licence":"Open government licence","lineage":"A 1 degree by 1 degree grid was created using ArcMap. Crop production data (0.0833 degree resolution) from the Food and Agriculture Organisation’s (FAO) Global Agro-Ecological Zones (GAEZ) dataset (for the year 2000) was downloaded. Irrigated and non-irrigated production data was collected for each crop type. For each crop, total production was summed per 1 degree by 1 degree grid cell. Then average production for the period 2010-2012 for each grid cell was estimated using a conversion factor from FAO national crop production data, based on the difference between average production for the period 1999-2001 and 2010-2012. For each crop, only grid cells with greater than 500 tonnes crop production were included when mapping yield loss.\n\nEach grid cell was classed as either irrigated (greater than 75 percent irrigated crop production) or non-irrigated. Grid cells were also assigned to a hemisphere (Northern or Southern) and a climatic zone. For each hemisphere/climatic zone combination, a 90-day growing period was set, based on the main growing season per year for each crop.\n\nThe EMEP MSC-W (European Monitoring and Evaluation Programme, Meteorological Synthesising Centre‐West) chemical transport model (version 4.16) was used to calculate daily ozone flux (POD3IAM; phytotoxic ozone dose above 3 nmol m−2 s−1, parameterized for integrated assessment modelling) for the years 2010 - 2012. For each crop, the accumulated 90-day POD3IAM was calculated per grid cell based on the climate-specific growing period for the cell, and an average value calculated for the period 2010-2012.\n\nYield loss was calculated using the ozone dose-response relationship for wheat, following the most recent methodology adopted by the Convention for Long-Range Transboundary Air Pollution (CLRTAP) in 2017. First, a reference value of POD3IAM = 0.1mmol/m2 (used to represent ozone uptake at pre-industrial or natural ozone levels) was subtracted before yield loss was calculated. This value was the mean POD3IAM for the experimental conditions included in the dose-response relationship, assuming constant 10 ppb ozone throughout the 90-day period.\n\nThe equation used to calculate percentage yield loss was as follows:\n     percentage Yield Loss = (POD3IAM – 0.1) * 0.64                                                                         \nwhere 0.64 is the slope of the relationship between POD3IAM and percentage yield reduction and represents the percentage reduction per mmol/m2 POD3IAM.\n\nFor maize, rice and soybean, the POD3IAM values per grid cell were first used to calculate percentage yield loss using the equation for wheat. Then the relative ozone sensitivity of each crop compared to wheat was calculated by dividing the slope of the M7 (7-hour mean ozone concentration) response function for the crop by that for wheat. For each grid cell, the percentage yield loss for wheat was multiplied by the relative ozone sensitivity value, to calculate the final estimated percentage yield loss for each crop. \n\nPercentage yield loss values were added to the 1 degree by 1 degree grid and saved as GIS shapefiles, one per crop for ingestion into the EIDC.\n\nAn evaluation of EMEP model performance found a strong correlation between modelled and measured ozone data from Global Atmosphere Watch (GAW) sites. The EMEP model was found to capture spatial and temporal variations in ozone across regions.","locations":["POLYGON((-180 -90, -180 90, 180 90, 180 -90, -180 -90))"],"metadataDate":"2026-09-15T09:55:19.000Z","orcid":["0000-0003-3265-1505","0000-0001-9538-3208","0000-0002-6975-5984","0000-0002-2474-6558","0000-0001-5370-4894"],"organisation":["UK Centre for Ecology & Hydrology","Norwegian Meteorological Institute","University of Gothenburg","University of Bonn","United States Department of Agriculture – Agricultural Research Service  (USDA‐ARS)","Stockholm Environment Institute at York","Chinese Academy of Sciences","The University of Tokyo","Banaras Hindu University","NERC Environmental Information Data Centre","NERC EDS Environmental Information Data Centre"],"publicationDate":"2020-07-10T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/2a932995-f040-4724-ad21-3e92ae8a2540","10.5285/2a932995-f040-4724-ad21-3e92ae8a2540","doi:10.5285/2a932995-f040-4724-ad21-3e92ae8a2540"],"resourceType":"Dataset","ror":["https://ror.org/00pggkr55","https://ror.org/001n36p86","https://ror.org/01tm6cn81","https://ror.org/041nas322","https://ror.org/02d2m2044","https://ror.org/051xgzg37","https://ror.org/034t30j35","https://ror.org/057zh3y96","https://ror.org/04cdn2797","https://ror.org/04xw4m193"],"shortenedDescription":"Modelled average percentage yield loss due to ground-level ozone pollution (per 1 degree by 1 degree grid cell) are presented for the crops maize (Zea mays), rice (Oryza sativa), soybean (Glycine max) and wheat (Triticum aestivum) for the period 2010-2012. Data are…","state":"published","supplementalDescription":["Mills, G., Sharps, K., Simpson, D., Pleijel, H., Broberg, M., Uddling, J., … Van Dingenen, R. (2018). Ozone pollution will compromise efforts to increase global wheat production. Global Change Biology, 24(8), 3560–3574.\n\n","Simpson, D., Benedictow, A., Berge, H., Bergström, R., Emberson, L. D., Fagerli, H., Flechard, C. R., Hayman, G. D., Gauss, M., Jonson, J. E., Jenkin, M. E., Nyíri, A., Richter, C., Semeena, V. S., Tsyro, S., Tuovinen, J.-P., Valdebenito, Á., & Wind, P. (2012). The EMEP MSC-W chemical transport model – technical description. Atmospheric Chemistry and Physics, 12(16), 7825–7865. "],"supplementalName":["Report","SUNRISE website","EMEP website"],"temporalExtentText":"Data collected from 2010 to 2012","title":"Modelled annual average percentage yield loss due to ozone damage for four global staple crops, 2010-2012 version 2","topic":["0/Agriculture/","0/Environmental risk/"],"version":2.0,"view":["public","danor"]},{"authorAffiliation":["Centre for Ecology & Hydrology"],"authorFamilyName":["Tanguy","Kral","Fry","Svensson","Hannaford"],"authorFullName":["Tanguy, M.","Kral, F.","Fry, M.","Svensson, C.","Hannaford, J."],"authorGivenName":["Maliko","Filip","Matt","Claus","Jamie"],"authorOrcid":["0000-0002-1516-6834","0000-0003-1142-4039","0000-0001-9294-5826","0000-0002-5256-3310"],"authorRor":["https://ror.org/00pggkr55"],"availability":"Available","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)"],"description":"Standardised Precipitation Index (SPI) data for Integrated Hydrological Units (IHU) groups (Kral et al. [1]). SPI is a drought index based on the probability of precipitation for a given accumulation period as defined by McKee et al. [2]. SPI is calculated for different accumulation periods: 1, 3, 6, 12, 18, 24 months. Each of these is in turn calculated for each of the twelve calendar months. Note that values in monthly (and for longer accumulation periods also annual) time series of the data therefore are likely to be autocorrelated. The standard period which was used to fit the gamma distribution is 1961-2010. The dataset covers the period from 1961 to 2012. \n\n[1] Kral, F., Fry, M., Dixon, H. (2015). Integrated Hydrological Units of the United Kingdom: Groups. NERC-Environmental Information Data Centre https://doi.org/10.5285/f1cd5e33-2633-4304-bbc2-b8d34711d902\n[2] McKee, T. B., Doesken, N. J., Kleist, J. (1993). The Relationship of Drought Frequency and Duration to Time Scales. Eighth Conference on Applied Climatology, 17-22 January 1993, Anaheim, California.","documentType":"GEMINI_DOCUMENT","familyName":["Tanguy","Kral","Fry","Svensson","Hannaford"],"fullName":["Tanguy, M.","Kral, F.","Fry, M.","Svensson, C.","Hannaford, J."],"givenName":["Maliko","Filip","Matt","Claus","Jamie"],"identifier":"dfd59438-2170-4472-b810-bab33a83d09f","incomingCitationCount":0,"keyword":["Environmental risk","Hydrology","SPI","indicator","accumulation period","Integrated Hydrological Units","IHU","rainfall extremes","drought","atmospheric precipitation"],"keywordsOther":["SPI","indicator","accumulation period","Integrated Hydrological Units","IHU","rainfall extremes","drought","atmospheric precipitation"],"keywordsTheme":["Environmental risk","Hydrology"],"licence":"Non-Open government licence","lineage":"SPI is calculated as originally defined in McKee et al. [1]. SPI is based on the cumulative probability of a given rainfall amount occurring at a location. The historic rainfall data of the station is fitted to a statistical distribution. For this dataset, the statistical distribution used is the gamma distribution, which has been extensively used and is recommended as a default choice for Europe by Stagge et al. [2]. The L-moments method was used to estimate the gamma distribution parameters, as the maximum likehood method was failing to fit a realistic distribution in some isolated cases (more details on the choice of methodology in Tanguy et al. [3]). To calculate SPI, the R package SCI was used (Gudmundsson & Stagge [4]), but modified to use L-moments (instead of Maximum Likelihood). The input data used is the monthly rainfall grids from CEH-Gridded Estimates of Areal Rainfall [CEH-GEAR] (Tanguy et al. [5], Keller et al. [6]) which has been area-averaged over each of the Integrated Hydrological Units (IHU) groups(Kral et al. [7]). \n\n[1] McKee, T. B., Doesken, N. J., Kleist, J. (1993). The Relationship of Drought Frequency and Duration to Time Scales. Eighth Conference on Applied Climatology, 17-22 January 1993, Anaheim, California.\n[2] Stagge, J. H., Tallaksen, L. M., Gudmundsson, L., Van Loon, A. F. and Stahl, K. (2015), Candidate Distributions for Climatological Drought Indices (SPI and SPEI). Int. J. Climatol. https://doi.org/10.1002/joc.4267\n[3] Tanguy et al. (2015), in preparation.\n[4] Gudmundsson, L. & Stagge, J. H. (2014). Package 'SCI': Standardized Climate Indices such as SPI, SRI or SPEI. Repository CRAN, http://cran.r-project.org/web/packages/SCI/SCI.pdf\n[5] Tanguy, M., Dixon, H., Prosdocimi, I., Morris, D. G., Keller, V. D. J. (2014). Gridded estimates of daily and monthly areal rainfall for the United Kingdom (1890-2012) [CEH-GEAR]. NERC-Environmental Information Data Centre https://doi.org/10.5285/5dc179dc-f692-49ba-9326-a6893a503f6e\n[6] Keller, V. D. J., Tanguy, M. , Prosdocimi, I. , Terry, J. A. , Hitt, O., Cole, S. J. , Fry, M., Morris, D. G., Dixon, H. (2015) CEH-GEAR: 1km resolution daily and monthly areal rainfall estimates for the UK for hydrological use. Earth Syst. Sci. Data Discuss., 8, 83-112, www.earth-syst-sci-data-discuss.net/8/83/2015/ https://doi.org/10.5194/essdd-8-83-2015.\n[7] Kral, F., Fry, M., Dixon, H. (2015). Integrated Hydrological Units of the United Kingdom: Groups. 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[1]). SPI is a drought index based on the probability of precipitation for a given accumulation period as defined by McKee et al. [2]. SPI is calculated for different…","state":"published","supplementalName":["CEH droughts portal"],"temporalExtentText":"Data collected from 1961 to 2012","title":"Standardised Precipitation Index time series for Integrated Hydrological Units Groups (1961-2012)","topic":["0/Environmental risk/","0/Hydrology/"],"version":1.0,"view":["public","nuri"]},{"authorAffiliation":["Asian Institute of Technology","University of Exeter"],"authorFamilyName":["Khadka","Abatan","Babel","Collins","Djordjevic"],"authorFullName":["Khadka, D.","Abatan, A.A.","Babel, M.S.","Collins, M.","Djordjevic, S."],"authorGivenName":["D.","A.A.","M.S. 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","M.","S."],"grant":["NE/S002901/1"],"identifier":"b11c040d-c3c0-43c5-a7c0-442b067dc526","incomingCitationCount":0,"keyword":["Thailand","climate model","bias correction","Southeast Asia","drought","climate change"],"keywordsOther":["climate model","bias correction","Southeast Asia","drought","climate change"],"keywordsPlace":["Thailand"],"licence":"Open government licence","lineage":"The raw climate data were accessed from the \"Earth System Grid Federation (ESGF)\" portal in December 2020. Climate data were re-gridded to 0.25 degrees using bilinear interpolation. Climate data has been bias-corrected using the Quantile mapping method with reference to 1981-2010 period observations. Bias correction of rainfall data is carried out using empirical distribution, which avoids assumptions about distribution fitting and corrects rainfall intensity and frequency. This method is more effective in reducing biases than using a theoretical distribution. For future rainfall values larger than those during the reference period, a correction factor for the highest quantile is used. Bias correction of temperature is carried out by fitting in a normal distribution.","locations":["POLYGON((101.3 14, 101.3 16, 105.3 16, 105.3 14, 101.3 14))"],"metadataDate":"2026-07-25T12:53:32.000Z","orcid":["0000-0002-5703-5306","0000-0003-2330-3322","0000-0003-4203-0059","0000-0003-3785-6008","0000-0003-1682-1383"],"organisation":["Asian Institute of Technology","University of Exeter","NERC EDS Environmental Information Data Centre"],"publicationDate":"2023-03-17T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/b11c040d-c3c0-43c5-a7c0-442b067dc526","10.5285/b11c040d-c3c0-43c5-a7c0-442b067dc526","doi:10.5285/b11c040d-c3c0-43c5-a7c0-442b067dc526"],"resourceType":"Dataset","rightsHolder":["University of Exeter"],"ror":["https://ror.org/04xw4m193","https://ror.org/03yghzc09"],"shortenedDescription":"This dataset provides the projections of meteorological, hydrological, and agricultural droughts for the near-future period (2021-2050) for the Mun River basin, in Northeast Thailand. Near future drought characteristics (duration, intensity, and severity) are projected…","state":"published","temporalExtentText":"Data collected from 2021 to 2050","title":"Climate change projections and drought assessments for the Mun River basin, northeast Thailand 2021-2050","version":1.0,"view":["public","glenn"]},{"authorAffiliation":["Macaulay Land Use Research Institute","Centre for Ecology & Hydrology"],"authorFamilyName":["Buckland","Burt-Smith","Scott"],"authorFullName":["Buckland, S.","Burt-Smith, G.","Scott, R."],"authorGivenName":["S.","G.","R."],"authorRor":["https://ror.org/00pggkr55"],"availability":"Available","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)"],"description":"The data set comprises biomass values and mineral nutrient values from experimental plots located at Sourhope, Scotland.  On five occasions throughout each of the 1999, 2000, 2001 and 2002 growing seasons, grass cuttings were collected from a 50 x 50 cm cell area from each of the four main sub-plots within each of a set of experimental main-plots, and biomass values calculated. In addition, mineral nutrient analysis was carried out for the July 1999 grass cuttings.  The work was part of the NERC Soil Biodiversity Thematic Programme, which was established in 1999 and was centred upon the intensive study of a large field experiment located at the Macaulay Land Use Research Institute (now the James Hutton Institute) farm at Sourhope in the Scottish Borders (Grid reference: NT 8545 1963).  During the experiment, the site was monitored to assess changes in above-ground biomass production (productivity), species composition and relative abundance (diversity). \n\nThe primary aims of the Programme were to achieve simultaneously an understanding of the biological diversity of the soil biota and the functional roles played by soil organisms in key ecological processes. In seeking to achieve these aims, 24 separate research projects were funded to study soil structure, soil processes (such as the carbon and nitrogen cycles) and the roles of micro-fauna and flora (Bacteria, Nematoda, Protozoa and Fungi), microarthropods (including Collembola and Acari), invertebrate root feeders (Tipulid, Bidionid and Scarabeid larvae), meso-fauna (such as Enchytraeidae) and macro-fauna (including Megadrili, Mollusca and Coleoptera).","documentType":"GEMINI_DOCUMENT","familyName":["Buckland","Burt-Smith","Scott","Sier"],"fullName":["Buckland, S.","Burt-Smith, G.","Scott, R.","Sier, A."],"funder":["Natural Environment Research Council"],"givenName":["S.","G.","R.","A."],"identifier":"1a278fbf-b8b2-472d-9100-5fb432095f63","incomingCitationCount":0,"keyword":["NERC Soil Biodiversity Programme","Soil","Biodiversity","biomass","biological diversity"],"keywordsOther":["biomass","biological diversity"],"keywordsProject":["NERC Soil Biodiversity Programme"],"keywordsTheme":["Soil","Biodiversity"],"licence":"Open government licence","lineage":"Data were collected as part of the NERC Soil Biodiversity Thematic Programme, which was established in 1999 and was centred upon the intensive study of a large field experiment located at the Macaulay Land Use Research Institute (MLURI) (now the James Hutton Institute) farm at Sourhope in the Scottish Borders (Grid reference: NT 8545 1963).  Data were collected by staff employed by MLURI and were managed by the Centre for Ecology & Hydrology. ","locations":["POLYGON((-2.238 55.468, -2.238 55.477, -2.222 55.477, -2.222 55.468, -2.238 55.468))"],"metadataDate":"2026-07-24T19:14:54.000Z","organisation":["Macaulay Land Use Research Institute","Centre for Ecology & Hydrology","UK Centre for Ecology & Hydrology","NERC Environmental Information Data Centre","NERC EDS Environmental Information Data Centre"],"publicationDate":"2017-11-17T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/1a278fbf-b8b2-472d-9100-5fb432095f63","10.5285/1a278fbf-b8b2-472d-9100-5fb432095f63","doi:10.5285/1a278fbf-b8b2-472d-9100-5fb432095f63"],"resourceType":"Dataset","ror":["https://ror.org/00pggkr55","https://ror.org/04xw4m193"],"shortenedDescription":"The data set comprises biomass values and mineral nutrient values from experimental plots located at Sourhope, Scotland.  On five occasions throughout each of the 1999, 2000, 2001 and 2002 growing seasons, grass cuttings were collected from a 50 x 50 cm cell area from…","state":"published","supplementalDescription":["Website for the NERC Soil Biodiversity Programme"],"supplementalName":["Soil Biodiversity website "],"temporalExtentText":"Data collected from 1999 to 2002","title":"Biomass data from Sourhope field experiment site, Scotland, 1999-2002 [NERC Soil Biodiversity Programme]","topic":["0/Soil/","0/Biodiversity/"],"version":1.0,"view":["public","clamw"]},{"authorAffiliation":["Botswana International University of Science and Technology","University of Aberdeen"],"authorFamilyName":["Franchi","Comte"],"authorFullName":["Franchi, F.","Comte, J.C."],"authorGivenName":["F.","J.C."],"authorOrcid":["0000-0002-5129-8391"],"authorRor":["https://ror.org/04cr2sq58","https://ror.org/016476m91"],"availability":"Available","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)"],"description":"The data set contains grain size distributions, organic matter (OM) contents and trace metals distribution metal distribution (Fe, Zn, Cu, Cr and Pb) of seven (7) shallow cores of sediments from the Notwane Dam (southern Botswana). The cores have been collected with a push corer using PVC pipes of 5 cm diameter by a team from BIUST led by Dr. Franchi between November 2017 and February 2018. The data were collected as part of the PULA project, which aimed at understanding the immediate effect of heavy rainfall and floods on water resources in arid Botswana and their transitional hydrologic readjustment towards the dry period, and the role of these events in supporting either or both resources replenishment and contamination. Grain size profiles of the cores have been obtained by analyzing wet sediments with a laser diffraction particle size analyzer. The OM content of the sediments was obtained by measuring the loss on ignition (LOI) of bulk sediments after calcination in a muffle furnace. The sediments have been analyzed for trace metal distribution using a Microwave Plasma-Atomic Emission Spectrometer (MP-AES). The grain size distribution has allowed to pinpoint the presence of flood couplets, characterized by coarse lags followed by fine grained materials. The trace metal distribution profiles have been compared with the flood couplets to assess the entity of metal mobilization during floods and subsequent droughts.","documentType":"GEMINI_DOCUMENT","familyName":["Franchi","Comte"],"fullName":["Franchi, F.","Comte, J.C.","Comte, J."],"givenName":["F.","J.C.","Jean-Christophe"],"identifier":"022b3fff-55d7-46f5-b11f-2f7366e508b0","incomingCitationCount":0,"keyword":["Botswana","Notwane Dam","grain size","trace metals","chromium","copper","zinc","lead","organic matter","iron","sediment"],"keywordsOther":["grain size","trace metals","chromium","copper","zinc","lead","organic matter","iron","sediment"],"keywordsPlace":["Botswana","Notwane Dam"],"licence":"Open government licence","lineage":"Seven cores of sediments were collected at scattered locations in the Notwane dam over 2 days (22/11/2017 and 19/02/2018) for further sedimentological and geochemical analyses. Core collection was realised with 50 mm diameter PVC pipes though use of a push corer equipped with extension rods from shore or from a small boat. They were subsequently stored the same day at 4 ˚C in a refrigerator at the Botswana International University of Science and Technology (BIUST) to allow for water retention. Before analysis, core were split in half, photographed and sub-sampled at selected intervals for lab analysis. Grain size distribution for each interval was obtained through dispersing a few grams of sediment into distilled water which was analysed with a Malvern Mastersizer 3000 laser diffraction particle size analyser at BIUST. The organic matter (OM) content was measured at BIUST through measuring the loss on ignition (LOI) of bulk sediments after calcination in a muffle furnace. The porcelain crucibles were pre-heated in a muffle furnace for 1 hour at 375°C and after cooling transferred into a desiccator for further cooling and weighed. Samples were dried at 105°C for 24 hours and weighed. The dried samples were then heated for 16h at 550°C. 95 samples of sediments from selected intervals of the cores were further analysed for trace metal distribution (Fe, Zn, Cu, Cr and Pb) using an Agilent 4200 Microwave Plasma-Atomic Emission Spectrometer (MP-AES) at BIUST. About 1 g of sample was treated with 10-15 ml of 65% nitric acid at 60°C for a period of 4 hours. The samples were then filtered at <0.45 µm and brought to 50 ml adding Milli-Q distilled water. Average standard deviations were as follows: Fe %RSD = 1.81; Zn %RSD = 4.02; Cu %RSD = 1.43; Cr %RSD = 0.82; Pb %RSD = 1.72. Detection limits for the metals reported here (as weight of dry sediment) were as follows: Cr = 0.8 µg kg-1, Fe = 1.7 µg kg-1; Cu = 0.5 µg kg-1; Zn = 28 µg kg-1; Pb = 2.5 µg kg-1","locations":["POLYGON((25.743 -24.845, 25.743 -24.608, 26.04 -24.608, 26.04 -24.845, 25.743 -24.845))"],"metadataDate":"2026-09-15T08:43:29.000Z","orcid":["0000-0002-5129-8391"],"organisation":["Botswana International University of Science and Technology","University of Aberdeen","NERC Environmental Information Data Centre","NERC EDS Environmental Information Data Centre"],"publicationDate":"2019-11-18T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/022b3fff-55d7-46f5-b11f-2f7366e508b0","10.5285/022b3fff-55d7-46f5-b11f-2f7366e508b0","doi:10.5285/022b3fff-55d7-46f5-b11f-2f7366e508b0"],"resourceType":"Dataset","ror":["https://ror.org/04cr2sq58","https://ror.org/016476m91","https://ror.org/04xw4m193"],"shortenedDescription":"The data set contains grain size distributions, organic matter (OM) contents and trace metals distribution metal distribution (Fe, Zn, Cu, Cr and Pb) of seven (7) shallow cores of sediments from the Notwane Dam (southern Botswana). The cores have been collected with…","state":"published","temporalExtentText":"Data collected from 2017 to 2018","title":"Sediment records of the 2016-2017 flood from Notwane dam, Upper Limpopo basin, Botswana","version":1.0,"view":["public","glenn"]},{"availability":"Available","catalogue":"eidc","dataFormat":["JPEG","PNG","TIFF"],"description":"This web map service provides a 1km resolution gridded coverage of wooded areas in riparian zones (river- or streamsides) across Great Britain.\n\nThe areas classified as riparian in this dataset are defined by a 50 metre buffer applied to the CEH 1:50000 watercourse network. Wooded areas within this zone are identified as those classified by the Land Cover Map of Great Britain 2007 as either coniferous or deciduous woodland. The data are aggregated to a 1km resolution.","documentType":"GEMINI_DOCUMENT","identifier":"e4b36270-8246-4afa-8eff-6781210a0477","incomingCitationCount":0,"keyword":["infoMapAccessService"],"keywordsOther":["infoMapAccessService"],"licence":"Non-Open government licence","locations":["POLYGON((-8.648 49.864, -8.648 60.861, 1.768 60.861, 1.768 49.864, -8.648 49.864))"],"metadataDate":"2026-08-12T11:41:50.000Z","organisation":["NERC Environmental Information Data Centre","NERC EDS Environmental Information Data Centre"],"publicationDate":"2022-07-04T00:00:00.000Z","recordType":"Map (web service)","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/e4b36270-8246-4afa-8eff-6781210a0477"],"resourceType":"Service","ror":["https://ror.org/04xw4m193"],"shortenedDescription":"This web map service provides a 1km resolution gridded coverage of wooded areas in riparian zones (river- or streamsides) across Great Britain.\n\nThe areas classified as riparian in this dataset are defined by a 50 metre buffer applied to the CEH 1:50000 watercourse…","state":"published","title":"WMS of wooded riparian zones in Great Britain","version":1.0,"view":["public","phtr"]},{"authorAffiliation":["UK Centre for Ecology & Hydrology"],"authorFamilyName":["Morton","Marston","O'Neil","Rowland"],"authorFullName":["Morton, R.D.","Marston, C.G.","O'Neil, A.W.","Rowland, C.S."],"authorGivenName":["R.D.","C.G.","A.W.","C.S."],"authorOrcid":["0000-0003-3947-6463","0000-0002-2070-2187","0000-0003-3591-1034","0000-0002-0459-506X"],"authorRor":["https://ror.org/00pggkr55"],"availability":"Available","catalogue":"eidc","dataFormat":["TIFF"],"description":"This 1 km summary pixel data set represents the land surface of Great Britain and Northern Ireland, classified using two classification schemas, target and aggregate classes. The target class schema comprise 21 UKCEH land cover classes based upon Biodiversity Action Plan broad habitats. The aggregate class schema comprises 10 aggregate classes that are groupings of the 21 target classes. The aggregate classes group some of the more specialised target classes into more general classes. For example, the five coastal classes in the target class are grouped into a single aggregate class.\n\nThe 1km percentage product provides the percentage cover for each of the 21 land cover classes for 1km x 1km pixels. This product contains one band per habitat class, producing 21 and 10 band images for the target and aggregate class products respectively. The 1km dominant coverage product is based on the 1km percentage product, and reports the land cover class with the highest percentage cover for each 1km pixel. A full description of this and all UKCEH LCM2019 products are available from the LCM2017-19 product documentation.","documentType":"GEMINI_DOCUMENT","familyName":["Morton","Marston","O'Neil","Rowland"],"fullName":["Morton, R.D.","Marston, C.G.","O'Neil, A.W.","Rowland, C.S."],"funder":["Natural Environment Research Council"],"givenName":["R.D.","C.G.","A.W.","C.S."],"grant":["NE/R016429/1"],"identifier":"e5632f1b-040c-4c39-8721-4834ada6046a","incomingCitationCount":1,"keyword":["Great Britain","Land cover","Biodiversity Action Plan","UK-SCAPE","mapping","habitat","land cover"],"keywordsOther":["Biodiversity Action Plan","UK-SCAPE","mapping","habitat","land cover"],"keywordsPlace":["Great Britain"],"keywordsTheme":["Land cover"],"licence":"Non-Open government licence","lineage":"UKCEH's automated land cover algorithms classify 10m pixels across the whole of UK. A Random Forest classifier used these to classify four composite images representing per season median surface reflectance. Seasonal images were integrated with context layers (e.g., height, aspect, slope, coastal proximity, urban proximity and so forth) to reduce confusion among classes with similar spectra.  \n\nLand cover was validated by organising the 10 m pixel classification into a land parcel framework (the LCM2019 classified land parcels product). The classified land parcels were compared to known land cover producing a confusion matrix to determine overall and per class accuracy. Details are available from the product documentation.\n\nThe 1 km percentage and dominant products are created by calculating the percentage cover for each land cover classes for every 1km x 1km pixel, then reporting the dominant land cover class with the highest percentage cover for each 1km pixel.","locations":["POLYGON((-8.648 49.864, -8.648 60.861, 1.768 60.861, 1.768 49.864, -8.648 49.864))"],"metadataDate":"2026-07-25T14:49:48.000Z","orcid":["0000-0003-3947-6463","0000-0002-2070-2187","0000-0003-3591-1034","0000-0002-0459-506X"],"organisation":["UK Centre for Ecology & Hydrology","NERC EDS Environmental Information Data Centre"],"publicationDate":"2022-10-31T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/e5632f1b-040c-4c39-8721-4834ada6046a","10.5285/e5632f1b-040c-4c39-8721-4834ada6046a","doi:10.5285/e5632f1b-040c-4c39-8721-4834ada6046a"],"resourceType":"Dataset","rightsHolder":["UK Centre for Ecology & Hydrology"],"ror":["https://ror.org/00pggkr55","https://ror.org/04xw4m193"],"shortenedDescription":"This 1 km summary pixel data set represents the land surface of Great Britain and Northern Ireland, classified using two classification schemas, target and aggregate classes. The target class schema comprise 21 UKCEH land cover classes based upon Biodiversity Action…","state":"published","temporalExtentText":"Data collected from 2019 to 2019","title":"Land Cover Map 2019 (1km summary rasters, GB and N. Ireland)","topic":["0/Land cover/"],"version":1.0,"view":["public","matnic"]},{"authorAffiliation":["Centre for Ecology & Hydrology"],"authorFamilyName":["Jones","Feuchtmayr"],"authorFullName":["Jones, I.","Feuchtmayr, H."],"authorGivenName":["I.","H."],"authorOrcid":["0000-0002-6898-1429","0000-0002-2028-4843"],"authorRor":["https://ror.org/00pggkr55"],"availability":"Available","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)"],"description":"This dataset consists of hourly lake temperature, air temperature, solar irradiance and wind speed data from an automatic water monitoring buoy on Bassenthwaite Lake, a lake in the North West of England. The lake temperatures are measured in various depths of the lake (see supporting documentation). Measurements were taken every 4 minutes and calculated as hourly averages. The data were collected by the Centre for Ecology & Hydrology between 2008 and 2011 inclusive. This dataset has been used in various publications, please see supporting documentation for more detail.","documentType":"GEMINI_DOCUMENT","familyName":["Jones","Feuchtmayr"],"fullName":["Jones, I.","Feuchtmayr, H."],"givenName":["I.","H."],"identifier":"ce702019-77fe-4ca7-b1d4-a7e4eb6e40c0","incomingCitationCount":0,"keyword":["England","Lake District","Bassenthwaite Lake","Environmental survey","Water quality","temperature profile ","lake","freshwater","meteorological parameter","temperature"],"keywordsOther":["temperature profile ","lake","freshwater","meteorological parameter","temperature"],"keywordsPlace":["England","Lake District","Bassenthwaite Lake"],"keywordsTheme":["Environmental survey","Water quality"],"licence":"Open government licence","lineage":"Data from the automatic water quality buoy on Bassenthwaite Lake are collated and processed by the Centre for Ecology & Hydrology at Lancaster. Data are available for download from 2008 to 2011. See supporting documentation for further information. Data has been checked visually and any obvious errors introduced by hardware malfunctioning have been removed.","locations":["POLYGON((-3.258 54.62, -3.258 54.683, -3.174 54.683, -3.174 54.62, -3.258 54.62))"],"metadataDate":"2026-09-15T08:38:39.000Z","orcid":["0000-0002-6898-1429","0000-0002-2028-4843"],"organisation":["Centre for Ecology & Hydrology","UK Centre for Ecology & Hydrology","NERC Environmental Information Data Centre","NERC EDS Environmental Information Data Centre"],"publicationDate":"2017-02-10T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/ce702019-77fe-4ca7-b1d4-a7e4eb6e40c0","10.5285/ce702019-77fe-4ca7-b1d4-a7e4eb6e40c0","doi:10.5285/ce702019-77fe-4ca7-b1d4-a7e4eb6e40c0"],"resourceType":"Dataset","rightsHolder":["UK Centre for Ecology & Hydrology"],"ror":["https://ror.org/00pggkr55","https://ror.org/04xw4m193"],"shortenedDescription":"This dataset consists of hourly lake temperature, air temperature, solar irradiance and wind speed data from an automatic water monitoring buoy on Bassenthwaite Lake, a lake in the North West of England. The lake temperatures are measured in various depths of the lake…","state":"published","temporalExtentText":"Data collected from 2008 to 2011","title":"Data from automatic water monitoring buoy from Bassenthwaite Lake,  2008 to 2011","topic":["0/Environmental survey/","0/Water quality/"],"version":1.0,"view":["public","clamw"]},{"authorAffiliation":["Edge Hill University"],"authorFamilyName":["Richardson"],"authorFullName":["Richardson, J."],"authorGivenName":["J."],"authorOrcid":["0000-0001-7052-422X"],"authorRor":["https://ror.org/028ndzd53"],"availability":"Available","catalogue":"eidc","dataFormat":["Shapefile"],"description":"Erosion risk mapping showing soil erosion potential (tonnes/yr) using the Soil Water Assessment Tool (SWAT) for the Yorkshire River Derwent, UK. The modelled data includes 29 years of weather data (1990-2019). Outputs were validated using SUFI2. This dataset builds on previous modelling using SCIMAP.","documentType":"GEMINI_DOCUMENT","familyName":["Richardson"],"fullName":["Richardson, J."],"funder":["Natural Environment Research Council"],"givenName":["J.","Janet"],"grant":["NE/V018701/2"],"identifier":"822646a9-6c20-4755-97af-eb22dd43fee3","incomingCitationCount":0,"keyword":["Hydrology","soil erosion"],"keywordsOther":["soil erosion"],"keywordsTheme":["Hydrology"],"licence":"Open government licence","lineage":"The SWAT model needs the following datasets: digital elevation model, soil information and weather data. These data are detailed in the supplementary data. The SWAT model contains 29 years of weather data and was calibrated/validated against flow gauges in the catchment using the SWAT-CUP SUFI2 method. ","locations":["POLYGON((-1.461 53.706, -1.461 54.648, -0.165 54.648, -0.165 53.706, -1.461 53.706))"],"metadataDate":"2026-07-25T08:36:38.000Z","orcid":["0000-0001-7052-422X"],"organisation":["Edge Hill University","NERC EDS Environmental Information Data Centre"],"publicationDate":"2025-04-03T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/822646a9-6c20-4755-97af-eb22dd43fee3","10.5285/822646a9-6c20-4755-97af-eb22dd43fee3","doi:10.5285/822646a9-6c20-4755-97af-eb22dd43fee3"],"resourceType":"Dataset","rightsHolder":["Edge Hill University"],"ror":["https://ror.org/028ndzd53","https://ror.org/04xw4m193"],"shortenedDescription":"Erosion risk mapping showing soil erosion potential (tonnes/yr) using the Soil Water Assessment Tool (SWAT) for the Yorkshire River Derwent, UK. The modelled data includes 29 years of weather data (1990-2019). Outputs were validated using SUFI2. This dataset builds…","state":"published","supplementalDescription":["Richardson, J. C., Hodgson, D. M., Kay, P., Aston, B. J., & Walker, A. C. (2019). Muddying the Picture? Forecasting Particulate Sources and Dispersal Patterns in Managed Catchments. In Frontiers in Earth Science (Vol. 7). Frontiers Media SA. https://doi.org/10.3389/feart.2019.00277"],"temporalExtentText":"Data collected from 1990 to 2019","title":"Soil erosion potential from the Soil Water Assessment Tool (SWAT) for the River Derwent, Yorkshire, UK","topic":["0/Hydrology/"],"version":1.0,"view":["public","clwe"]},{"authorAffiliation":["UK Centre for Ecology & Hydrology","Office for National Statistics","Department for Environment Food and Rural Affairs","Wood PLC","Environment Information Services","King's College"],"authorFamilyName":["Ridding","Wickenden","Orsler","Rowland","Hampton","Mitchell","Edwardes","Mullin","Haughton","Thurston","Pola","Sinclair","Shaw","Pywell"],"authorFullName":["Ridding, L.E.","Wickenden, A.R.","Orsler, Z.","Rowland, C.S.","Hampton, J.M.","Mitchell, B.","Edwardes, A.","Mullin, K.","Haughton, G.","Thurston, N.","Pola, I.","Sinclair, G.","Sinclair, M.R.","Shaw, J.","Pywell, R.F."],"authorGivenName":["L.E","A.R","Z","C.S","J.M","B","A","K","G","N","I","M.R","J","R.F"],"authorOrcid":["0000-0003-3141-8795"],"authorRor":["https://ror.org/00pggkr55","https://ror.org/021fhft25","https://ror.org/00tnppw48"],"availability":"Available","catalogue":"eidc","dataFormat":["Shapefile"],"description":"This is a vector dataset representing land use in the 1960s across a selection of areas in England and Wales. The land use data is digitised from 110 published maps of the 1960s Second Land Utilisation Survey (2LUS) which was directed by Professor Alice Coleman. The published maps were digitised using a semi-automated supervised classification, followed by extensive post-processing to clean the vector dataset. The resulting dataset maps 11 land-use categories including “Arable”, “Broadleaved and mixed woodland”, “Coastal”, “Coniferous woodland”, “Grassland”, “Heath, moorland and rough land”, “Market gardening and orchards”, “Open space”, “Settlement”, “Unvegetated land”, “Water and Marsh”. ","documentType":"GEMINI_DOCUMENT","familyName":["Ridding","Wickenden","Orsler","Rowland","Hampton","Mitchell","Edwardes","Mullin","Haughton","Thurston","Pola","Sinclair","Shaw","Pywell"],"fullName":["Ridding, L.E.","Wickenden, A.R.","Orsler, Z.","Rowland, C.S.","Hampton, J.M.","Mitchell, B.","Edwardes, A.","Mullin, K.","Haughton, G.","Thurston, N.","Pola, I.","Sinclair, G.","Sinclair, M.R.","Shaw, J.","Pywell, R.F."],"funder":["Natural Environment Research Council"],"givenName":["L.E","A.R","Z","C.S","J.M","B","A","K","G","N","I","M.R","J","R.F","L.E."],"grant":["NE/T000244/1","NE/W005050/1"],"identifier":"03940756-afe9-428b-8c69-275e6b889251","incomingCitationCount":0,"keyword":["Land use","Land cover","England","Wales","habitat","land cover","land use","mapping"],"keywordsOther":["England","Wales","habitat","land cover","land use","mapping"],"keywordsTheme":["Land use","Land cover"],"licence":"Open government licence","lineage":"All 110 published Second Land Utilisation Survey (2LUS) maps were digitised using a semi-automated supervised classification method. Firstly, maps were scanned and saved as Tiff images at 300 dots per inch at a colour depth of 8 bits per channel (24-bit depth). These were georeferenced in ArcGIS v10.7 using the Ordnance Survey (OS) 1km National Grid. For the classification, georeferenced 3-band images were converted to 16-bit single band images (256 colours). A manual look-up table was created for each map image identifying the dominant unique pixel values of the different land use classes. Any “noise” present on the images including text, contour lines and symbols were assigned a single blank value of 0. Similarly, pixel values which were common to multiple land use classes, such as the white colour were also assigned to 0. For these reasons it was not possible to classify either the “unvegetated land” or the “derelict land” land use categories. The model reclassified the 256 colours within a range of 0 to 10, representing the 10 land use categories and the noise category (pixel value = 0), with the latter being removed and replaced. Classified images were vectorised and manually cleaned using eliminate functions in ArcGIS. All “unvegetated land” was manually digitised as this could not be classified, along with a new category for “coastal” areas which were not classified. Railway lines, roads and very small rivers were inconsistently classified and were therefore removed, while “industry” and “transport” classes were grouped with “settlement” to ensure uniformity. “Derelict land” could not be classified but was often mapped in the classification as “settlement”, so this was later grouped with this category. Woodland was manually split into broadleaved and coniferous using the woodland symbology provided on the OS background, this usually aligned with the manual over-printed symbols but the latter was not present for all woodlands, thus the OS backdrop was used. The date of each OS basemap varied, however these were largely published or reprinted in the 1960s and were largely consistent with the surveyed land cover data, though there were exceptions e.g. Bristol East. \n\nTo validate the classified 2LUS maps, 3,000 random points were generated across the digitised maps. For each point, a manual assessment was undertaken assigning the most representative land cover class to the point based on the raw georeferenced 3-band images. A confusion matrix between the manually assigned points and the classified 2LUS maps revealed an overall accuracy of 95.8%. Please see supporting documentation for more information.\n","locations":["POLYGON((-6.452 49.864, -6.452 55.812, 1.768 55.812, 1.768 49.864, -6.452 49.864))"],"metadataDate":"2026-09-02T11:47:55.000Z","orcid":["0000-0003-3141-8795"],"organisation":["UK Centre for Ecology & Hydrology","Office for National Statistics","Department for Environment Food and Rural Affairs","Wood PLC","Environment Information Services","King's College","NERC EDS Environmental Information Data Centre"],"publicationDate":"2025-09-24T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/03940756-afe9-428b-8c69-275e6b889251","10.5285/03940756-afe9-428b-8c69-275e6b889251","doi:10.5285/03940756-afe9-428b-8c69-275e6b889251"],"resourceType":"Dataset","rightsHolder":["UK Centre for Ecology & Hydrology"],"ror":["https://ror.org/00pggkr55","https://ror.org/021fhft25","https://ror.org/00tnppw48","https://ror.org/04xw4m193"],"shortenedDescription":"This is a vector dataset representing land use in the 1960s across a selection of areas in England and Wales. The land use data is digitised from 110 published maps of the 1960s Second Land Utilisation Survey (2LUS) which was directed by Professor Alice Coleman. The…","state":"published","temporalExtentText":"Data collected from 1960 to 1960","title":"Vector maps of the 1960 Second Land Utilisation Survey in England and Wales, from 110 published maps","topic":["0/Land use/","0/Land cover/"],"version":1.0,"view":["public","tinzha"]},{"authorAffiliation":["University of Aberdeen"],"authorFamilyName":["McLean","Cash","Fisher"],"authorFullName":["McLean, C.J.","Cash, G.L.","Fisher, D.N."],"authorGivenName":["C.J.","G.L.","D.N."],"authorOrcid":["0000-0003-4402-8550","0009-0001-9587-280X","0000-0002-4444-4450"],"authorRor":["https://ror.org/016476m91"],"availability":"Available","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)"],"description":"Records of offspring production for 192 female cockroaches (Blaptica dubia) kept at either 50% or 30% relative humidity for two weeks during gestation. We then kept all females alone at 50% humidity for 10 weeks and counted the number of nymphs each female produced in up to two clutches.","documentType":"GEMINI_DOCUMENT","familyName":["McLean","Cash","Fisher"],"fullName":["McLean, C.J.","Cash, G.L.","Fisher, D.N."],"funder":["Natural Environment Research Council"],"givenName":["C.J.","G.L.","D.N."],"grant":["NE/X013227/1"],"identifier":"5c404d9f-8b66-48a6-8d9d-250dea74d57a","incomingCitationCount":0,"keyword":["cockroach","fitness","reproduction","humidity"],"keywordsOther":["cockroach","fitness","reproduction","humidity"],"licence":"Open government licence","lineage":"Female cockroaches were obtained from the Evolutionary Ethology Lab stock population, maintained at the University of Aberdeen since 2021. Each female was given the opportunity to mate with two different males from the stock population during a two-week period. The females were then exposed to an experimental treatment of either 50% or 30% relative humidity for two weeks during gestation. Subsequently, all females were kept at 50% relative humidity for 10 weeks, after which the number of nymphs and clutches per female were counted. Data collection took place from 29/12/23 to 23/01/24. Quality checking against original laboratory notebooks and reformatting took place from 18/03/24 to 05/08/24.","metadataDate":"2026-07-24T23:09:34.000Z","orcid":["0000-0003-4402-8550","0009-0001-9587-280X","0000-0002-4444-4450"],"organisation":["University of Aberdeen","NERC EDS Environmental Information Data Centre"],"publicationDate":"2024-08-27T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/5c404d9f-8b66-48a6-8d9d-250dea74d57a","10.5285/5c404d9f-8b66-48a6-8d9d-250dea74d57a","doi:10.5285/5c404d9f-8b66-48a6-8d9d-250dea74d57a"],"resourceType":"Non-geographic dataset","rightsHolder":["University of Aberdeen"],"ror":["https://ror.org/016476m91","https://ror.org/04xw4m193"],"shortenedDescription":"Records of offspring production for 192 female cockroaches (Blaptica dubia) kept at either 50% or 30% relative humidity for two weeks during gestation. We then kept all females alone at 50% humidity for 10 weeks and counted the number of nymphs each female produced…","state":"published","title":"Cockroach reproduction records in the laboratory at 50% and 30% relative humidity","version":1.0,"view":["public","elsdhi"]},{"availability":"Available","catalogue":"eidc","dataFormat":["JPEG","PNG","TIFF"],"description":"This service provides a view of Environmental Change Network (ECN) site locations from which data are collected. There are 12 terrestrial sites and 45 freshwater sites. Sites range from upland to lowland, moor land to chalk grassland, small ponds and streams to large rivers and lakes. ECN is the UK's long-term environmental monitoring programme. A wide range of integrated physical, chemical and biological variables which drive and respond to environmental change are collated, quality controlled and made freely available for scientific research. The data form an important evidence base for UK environmental policy development. ECN is a multi-agency programme sponsored by a consortium of fourteen government departments and agencies. These organisations contribute to the programme through funding either site monitoring and/or network co-ordination activities. These organisations are: Agri-Food and Biosciences Institute, Biotechnology and Biological Sciences Research Council, Cyfoeth Naturiol Cymru - Natural Resources Wales, Defence Science & Technology Laboratory, Department for Environment, Food and Rural Affairs, Environment Agency, Forestry Commission, Llywodraeth Cymru - Welsh Government, Natural England, Natural Environment Research Council, Northern Ireland Environment Agency, Scottish Environment Protection Agency, Scottish Government and Scottish Natural Heritage.","documentType":"GEMINI_DOCUMENT","identifier":"b1540d75-bbec-4181-902f-f0b43eeee359","incomingCitationCount":0,"keyword":["Environmental survey","Environmental Change Network","ECN","LTER","ILTER"],"keywordsOther":["Environmental Change Network","ECN","LTER","ILTER"],"keywordsTheme":["Environmental survey"],"licence":"Non-Open government licence","lineage":"These data are derived from a GIS. Location information has been confirmed by site contacts. ","locations":["POLYGON((-9.08 50.17, -9.08 58.17, 2.63 58.17, 2.63 50.17, -9.08 50.17))"],"metadataDate":"2026-07-25T12:53:44.000Z","organisation":["UK Centre for Ecology & Hydrology","NERC EDS Environmental Information Data Centre"],"publicationDate":"2007-05-01T00:00:00.000Z","recordType":"Map (web service)","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/b1540d75-bbec-4181-902f-f0b43eeee359"],"resourceType":"Service","ror":["https://ror.org/00pggkr55","https://ror.org/04xw4m193"],"shortenedDescription":"This service provides a view of Environmental Change Network (ECN) site locations from which data are collected. There are 12 terrestrial sites and 45 freshwater sites. Sites range from upland to lowland, moor land to chalk grassland, small ponds and streams to large…","state":"published","title":"Environmental Change Network (ECN) monitoring sites view service","topic":["0/Environmental survey/"],"version":1.0,"view":["public","clamw"]},{"authorAffiliation":["University of Leeds","IISER, Pune","Unaffiliated","St. Joseph's college, Calicut"],"authorFamilyName":["Gloor","Barua","Galbraith","Hegde","Sunny","Tiwari"],"authorFullName":["Gloor, E.","Barua, D.","Galbraith, D.R.","Hegde, B.","Sunny, R.","Tiwari, R."],"authorGivenName":["E.","D.","D.R.","B.","R."],"authorOrcid":["0000-0002-9384-6341","0000-0002-8761-0084","0000-0002-5555-4823","0000-0002-8723-607X","0000-0002-2191-769X"],"availability":"Available","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)"],"description":"This dataset includes time-series of pre-dawn and mid-day leaf water potentials for 10 tree species. The time-series covers one year with leaf water potentials measured every three months. These data when combined with hydraulic conductance vulnerability curves (also measured during this project) are an indicator of a tree's safe operating space under dry and high vapour pressure deficit conditions.\n\nThe overall purpose of the measurements made by this project is to determine eco-physiological limits of functioning of tropical trees in Western Ghats India and to relate them to continuously measured temperature and water status of tropical forest trees at a representative forest site (Sirsi).","documentType":"GEMINI_DOCUMENT","familyName":["Gloor","Barua","Galbraith","Hegde","Sunny","Tiwari"],"fullName":["Gloor, E.","Barua, D.","Galbraith, D.R.","Hegde, B.","Sunny, R.","Tiwari, R."],"givenName":["E.","D.","D.R.","B.","R.","Emanuel"],"identifier":"252b6a14-8a0e-4a6f-a879-99dff46fec71","incomingCitationCount":0,"keyword":["Tree safety margins to climate extremes","Tree traits","tropical forest","tree","leaf"],"keywordsOther":["Tree safety margins to climate extremes","Tree traits","tropical forest","tree","leaf"],"licence":"Open government licence","lineage":"Leaf water potential was measured on detached leaves using a Scholander pressure chamber (Model 1505D, PMS Instrument, Oregon, USA). Predawn water potential measurements were done between 4am to 6am/sunrise, mid-day water potentials between 12:30PM and 3PM. Measurements were made every two months over one year starting September 2020. Per species and for a given month measurements were made on one leaf each of five individuals.","locations":["POLYGON((74.823 14.6, 74.823 14.63, 74.845 14.63, 74.845 14.6, 74.823 14.6))"],"metadataDate":"2026-07-24T19:25:30.000Z","orcid":["0000-0002-9384-6341","0000-0002-8761-0084","0000-0002-5555-4823","0000-0002-8723-607X","0000-0002-2191-769X"],"organisation":["University of Leeds","IISER, Pune","Unaffiliated","St. Joseph's college, Calicut","NERC EDS Environmental Information Data Centre"],"publicationDate":"2023-02-08T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/252b6a14-8a0e-4a6f-a879-99dff46fec71","10.5285/252b6a14-8a0e-4a6f-a879-99dff46fec71","doi:10.5285/252b6a14-8a0e-4a6f-a879-99dff46fec71"],"resourceType":"Dataset","rightsHolder":["University of Leeds"],"ror":["https://ror.org/04xw4m193","https://ror.org/024mrxd33"],"shortenedDescription":"This dataset includes time-series of pre-dawn and mid-day leaf water potentials for 10 tree species. The time-series covers one year with leaf water potentials measured every three months. These data when combined with hydraulic conductance vulnerability curves (also…","state":"published","temporalExtentText":"Data collected from 2020 to 2021","title":"Leaf water potential of tropical forest tree species, Sirsi, Western Ghats, India, 2020-2021","version":1.0,"view":["public","clwe"]},{"authorAffiliation":["Centre for Ecology & Hydrology","Nature Conservancy"],"authorFamilyName":["Bunce","Brown","Shaw","White","Gardiner","Procter","Birkett","McAllister","Smith","Parrington","Wrigley","Wood"],"authorFullName":["Bunce, R.G.H.","Brown, A.H.F.","Shaw, M.W.","White, E.J.","Gardiner, A.","Procter, J.E.A.","Birkett, J.S.","McAllister, J.","Smith, C.","Parrington, J.","Wrigley, J.","Wood, C.M."],"authorGivenName":["R.G.H","A.H.F.","M.W.","E.J.","A.","J.E.A.","J.S.","J.","C.","C.M."],"authorOrcid":["0000-0002-0394-2998"],"authorRor":["https://ror.org/00pggkr55"],"availability":"Available","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)"],"description":"The data contains details about plant species, trees, shrubs and soils, collected using standardized survey methods from within a selection of 48 semi-natural woodlands in the English Lake District.  Nearly 300 plots were surveyed from sites across the north west of England, selected objectively from different woodland group types identified in the Lake District.  The survey was carried out by the Nature Conservancy in 1969.","documentType":"GEMINI_DOCUMENT","familyName":["Bunce","Brown","Shaw","White","Gardiner","Procter","Birkett","McAllister","Smith","Parrington","Wrigley","Wood"],"fullName":["Bunce, R.G.H.","Brown, A.H.F.","Shaw, M.W.","White, E.J.","Gardiner, A.","Procter, J.E.A.","Birkett, J.S.","McAllister, J.","Smith, C.","Parrington, J.","Wrigley, J.","Wood, C.M.","Wood, C."],"givenName":["R.G.H","A.H.F.","M.W.","E.J.","A.","J.E.A.","J.S.","J.","C.","C.M.","Claire"],"identifier":"272a131f-7d57-47b4-a643-c3828722d663","incomingCitationCount":0,"keyword":["Lake District","Biodiversity","Environmental survey","Soil","woodlands"],"keywordsOther":["woodlands"],"keywordsPlace":["Lake District"],"keywordsTheme":["Biodiversity","Environmental survey","Soil"],"licence":"Open government licence","lineage":"Data were collected on paper field sheets in the summer of 1969 by staff at the Nature Conservancy, Merlewood, Grange-over-Sands, Cumbria.  Data were collected using standardized survey methods from within a selection of 48 semi-natural woodlands in the English Lake District.  Data were digitised between 2004 and 2017, then checked and documented at the Centre for Ecology & Hydrology Lancaster.  Further supporting information may be downloaded from this record.","locations":["POLYGON((-3.826 54.027, -3.826 54.731, -2.079 54.731, -2.079 54.027, -3.826 54.027))"],"metadataDate":"2026-09-15T08:41:20.000Z","orcid":["0000-0002-0394-2998"],"organisation":["Centre for Ecology & Hydrology","Nature Conservancy","UK Centre for Ecology & Hydrology","NERC Environmental Information Data Centre","NERC EDS Environmental Information Data Centre"],"publicationDate":"2018-05-29T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/272a131f-7d57-47b4-a643-c3828722d663","10.5285/272a131f-7d57-47b4-a643-c3828722d663","doi:10.5285/272a131f-7d57-47b4-a643-c3828722d663"],"resourceType":"Dataset","rightsHolder":["UK Centre for Ecology & Hydrology"],"ror":["https://ror.org/00pggkr55","https://ror.org/04xw4m193"],"shortenedDescription":"The data contains details about plant species, trees, shrubs and soils, collected using standardized survey methods from within a selection of 48 semi-natural woodlands in the English Lake District.  Nearly 300 plots were surveyed from sites across the north west of…","state":"published","temporalExtentText":"Data collected from 1969 to 1969","title":"Tree, vegetation and soil information from an ecological survey of semi-natural woodlands in the English Lake District, 1969","topic":["0/Biodiversity/","0/Environmental survey/","0/Soil/"],"version":1.0,"view":["public","clwe"]},{"authorAffiliation":["Lancaster University","Universidade Estadual Paulista","Unaffiliated"],"authorFamilyName":["Berenguer","Rossi","Seixas","Barlow"],"authorFullName":["Berenguer, E.","Rossi, L.C.","Seixas, M.M.M.","Barlow, J."],"authorGivenName":["E.","L.C.","M.M.M.","J."],"authorOrcid":["0000-0001-8157-8792"],"authorRor":["https://ror.org/04f2nsd36"],"availability":"Available","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)"],"description":"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.","documentType":"GEMINI_DOCUMENT","familyName":["Berenguer","Rossi","Seixas","Barlow"],"fullName":["Berenguer, E.","Rossi, L.C.","Seixas, M.M.M.","Barlow, J."],"funder":["Natural Environment Research Council"],"givenName":["E.","L.C.","M.M.M.","J.","Erika"],"identifier":"e5f361b3-b434-4d11-9407-e5f48fe442b0","incomingCitationCount":0,"keyword":["Brazilian Amazon","Human modified tropical forests","HMTF","Land use","Soil","Forest fire","Soil respiration","forest ecology","soil","fire"],"keywordsOther":["Forest fire","Soil respiration","forest ecology","soil","fire"],"keywordsPlace":["Brazilian Amazon"],"keywordsProject":["Human modified tropical forests","HMTF"],"keywordsTheme":["Land use","Soil"],"licence":"Open government licence","lineage":"We measured total soil respiration in 20 study plots (0.25ha) distributed along a gradient of forest disturbance in Eastern Amazonia: undisturbed primary forests (n = 5), logged primary forests (n = 5), logged-and-burned primary forests (n = 5), and secondary forests (n = 5). Forest disturbance classes were based on both an analysis of canopy disturbance in a chronosequence of satellite images (1988 to 2010) and on field assessments of fire scars, charcoal, and logging debris.\n \nIn each plot, we installed five PVC collars 50 m apart. Each collar was approximately 7 cm in size and were installed so approximately 2 cm stayed belowground and 5 cm aboveground. Collars had a 10 cm diameter. After installation, all collars were left to ‘settle’ for at least a week before the first measurement.  The collar was connected to an infrared gas analyser (EGM5®) to measure the soil CO2 efflux (i.e. soil respiration). Immediately after every soil respiration measurement, both the soil temperature and humidity were measured inside and outside the collar. We also took note on the collar height. Measures were taken every month. After measuring the soil respiration, we also measured the temperature inside and outside the collar, as well as the soil moisture, the latter with the aid of a HydroSense II. \n\n","locations":["POLYGON((-55 -3.5, -55 -2.5, -54.5 -2.5, -54.5 -3.5, -55 -3.5))"],"metadataDate":"2026-07-25T14:50:06.000Z","orcid":["0000-0001-8157-8792"],"organisation":["Lancaster University","Universidade Estadual Paulista","Unaffiliated","NERC Environmental Information Data Centre","NERC EDS Environmental Information Data Centre"],"publicationDate":"2019-01-29T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/e5f361b3-b434-4d11-9407-e5f48fe442b0","10.5285/e5f361b3-b434-4d11-9407-e5f48fe442b0","doi:10.5285/e5f361b3-b434-4d11-9407-e5f48fe442b0"],"resourceType":"Dataset","ror":["https://ror.org/04f2nsd36","https://ror.org/04xw4m193"],"shortenedDescription":"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…","state":"published","temporalExtentText":"Data collected from 2015 to 2017","title":"Soil respiration in human-modified forests of Eastern Amazonia","topic":["0/Land use/","0/Soil/"],"version":1.0,"view":["public","phtr"]},{"authorAffiliation":["University College London"],"authorFamilyName":["Finnegan","Nitsche","Monandi","Camus","Fowler","Pomiankowski"],"authorFullName":["Finnegan, S.","Nitsche, L.","Monandi, M.","Camus, M.F.","Fowler, K.","Pomiankowski, A."],"authorGivenName":["S.","L.","M.","M.F.","K.","A."],"authorOrcid":["0000-0001-6893-7068","0000-0003-0626-6865","0000-0001-9737-7549","0000-0002-5171-8755"],"availability":"Available","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)"],"description":"These data are the recorded outcomes of binary male choice experiments. Teleopsis dalmanni males were able to choose to mate with either a large or a small female. Individuals were taken from laboratory stock populations. Also included is information on male genotype indicating if he is a carrier of a sex-ratio distorting or nondistorting X chromosome, and a calculation of male preference. The second dataset additionally contains measures of male eyespan and thorax length obtained by measuring images.","documentType":"GEMINI_DOCUMENT","familyName":["Finnegan","Nitsche","Monandi","Camus","Fowler","Pomiankowski"],"fullName":["Finnegan, S.","Nitsche, L.","Monandi, M.","Camus, M.F.","Fowler, K.","Pomiankowski, A."],"givenName":["S.","L.","M.","M.F.","K.","A.","Sam"],"identifier":"d6c36f89-07f1-4bcc-96a0-f5302fd3ccec","incomingCitationCount":0,"keyword":["Environmental survey","condition-dependent","male mate preference","mate choice","meiotic drive","selfish genetic element","sexual selection","stalk-eyed fly","Teleopsis"],"keywordsOther":["condition-dependent","male mate preference","mate choice","meiotic drive","selfish genetic element","sexual selection","stalk-eyed fly","Teleopsis"],"keywordsTheme":["Environmental survey"],"licence":"Open government licence","lineage":"All data were generated by the authors. Mating observations were standardised by only admitting mating behaviour that lasted longer than a pre-determined amount of time. ","metadataDate":"2026-07-25T14:20:48.000Z","orcid":["0000-0001-6893-7068","0000-0003-0626-6865","0000-0001-9737-7549","0000-0002-5171-8755"],"organisation":["University College London","NERC Environmental Information Data Centre","NERC EDS Environmental Information Data Centre"],"publicationDate":"2021-03-19T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/d6c36f89-07f1-4bcc-96a0-f5302fd3ccec","10.5285/d6c36f89-07f1-4bcc-96a0-f5302fd3ccec","doi:10.5285/d6c36f89-07f1-4bcc-96a0-f5302fd3ccec"],"resourceType":"Non-geographic dataset","ror":["https://ror.org/04xw4m193"],"shortenedDescription":"These data are the recorded outcomes of binary male choice experiments. Teleopsis dalmanni males were able to choose to mate with either a large or a small female. Individuals were taken from laboratory stock populations. Also included is information on male genotype…","state":"published","title":"Male mate size preference in Teleopsis dalmanni","topic":["0/Environmental survey/"],"version":1.0,"view":["public","clwe"]},{"authorAffiliation":["Manchester Metropolitan University","University of the Sunshine Coast","Wageningen University & Research","University of Rwanda","Norwegian University of Life Sciences","Cary Institute of Ecosystem Studies"],"authorFamilyName":["Sullivan","Ngute","Batumike","Zoletto","Petridis","Kaplin","Cuni-Sanchez","Gora"],"authorFullName":["Sullivan, M.","Ngute, A.","Batumike, R.","Zoletto, B.","Petridis, N.","Kaplin, B.","Cuni-Sanchez, A.","Gora, E."],"authorGivenName":["Martin","A.","R.","B.","N.","E."],"authorOrcid":["0000-0002-5955-0483"],"authorRor":["https://ror.org/02hstj355","https://ror.org/016gb9e15","https://ror.org/04qw24q55","https://ror.org/00286hs46","https://ror.org/04a1mvv97","https://ror.org/01dhcyx48"],"availability":"Available","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)"],"description":"The dataset details the locations and attributes of canopy disturbances in Nyungwe National Park, Rwanda, that were suspected to have been caused by lightning strikes. Disturbances were located by surveying 23 km of trails and assessing whether disturbances (clusters of dead or damaged trees) had damage signatures consistent with lighting. Only disturbances that were thought to potentially have been caused by lightning were recorded. As well as providing a qualitative assessment of the confidence that the damage was caused by lightning, the dataset contains the number of dead and damaged trees in different size classes, as well as the taxonomic identity and degree of crown damage experienced by canopy trees within the putative strike. Photographs of a subset of strikes are also provided.\n\nData were collected as part of the project Lightning in African tropical forests: from tree mortality to carbon dynamics (NE/W003872/1).","documentType":"GEMINI_DOCUMENT","familyName":["Sullivan","Ngute","Batumike","Zoletto","Petridis","Kaplin","Cuni-Sanchez","Gora"],"fullName":["Sullivan, M.","Ngute, A.","Batumike, R.","Zoletto, B.","Petridis, N.","Kaplin, B.","Cuni-Sanchez, A.","Gora, E."],"funder":["Natural Environment Research Council"],"givenName":["Martin","A.","R.","B.","N.","E."],"grant":["NE/W003872/1"],"identifier":"d47e78bc-2227-4bc7-90ae-9ec871c52bec","incomingCitationCount":0,"keyword":["photograph","tropical forest","Afromontane forest","Rwanda","Africa","African tropical forests","Climate and climate change"],"keywordsInstrument":["photograph"],"keywordsPlace":["tropical forest","Afromontane forest","Rwanda","Africa"],"keywordsProject":["African tropical forests"],"keywordsTheme":["Climate and climate change"],"licence":"Open government licence","lineage":"A total of 23.3 km of trails were surveyed in Nyungwe National Park in June 2022, covering the majority of trails accessible from the Uwinka station. Canopy disturbances (i.e. clusters of dead or damaged trees) encountered along these trails were inspected to assess for flashover damage (visually apparent as the defoliation of the two nearest branches of neighbouring trees in a directionally biased pattern). If a tree exhibited potential flashover damage to two or more neighbours, it was selected for more detailed surveys to assess whether patterns of damage were consistent with lightning.\n\nThe presumptive directly struck tree was identified as the canopy tree at the centre of observed flashover damage. Tree-level surveys of lightning damage were conducted for this tree, along with any other tree with a diameter at breast height > 50 cm within the lightning strike area.\n\nA subset of trails was resurveyed in October 2023, revisiting existing strike locations on these trails and surveying new disturbances.","locations":["POLYGON((29.1 -2.5, 29.1 -2.3, 29.3 -2.3, 29.3 -2.5, 29.1 -2.5))"],"metadataDate":"2026-07-25T14:19:21.000Z","orcid":["0000-0002-5955-0483"],"organisation":["Manchester Metropolitan University","University of the Sunshine Coast","Wageningen University & Research","University of Rwanda","Norwegian University of Life Sciences","Cary Institute of Ecosystem Studies","NERC EDS Environmental Information Data Centre"],"publicationDate":"2024-12-17T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/d47e78bc-2227-4bc7-90ae-9ec871c52bec","10.5285/d47e78bc-2227-4bc7-90ae-9ec871c52bec","doi:10.5285/d47e78bc-2227-4bc7-90ae-9ec871c52bec"],"resourceType":"Dataset","rightsHolder":["Manchester Metropolitan University"],"ror":["https://ror.org/02hstj355","https://ror.org/016gb9e15","https://ror.org/04qw24q55","https://ror.org/00286hs46","https://ror.org/04a1mvv97","https://ror.org/01dhcyx48","https://ror.org/04xw4m193","https://ror.org/00pggkr55"],"shortenedDescription":"The dataset details the locations and attributes of canopy disturbances in Nyungwe National Park, Rwanda, that were suspected to have been caused by lightning strikes. Disturbances were located by surveying 23 km of trails and assessing whether disturbances (clusters…","state":"published","temporalExtentText":"Data collected from 2022 to 2023","title":"Lightning strike locations and characteristics in Nyungwe National Park, Rwanda, surveyed in June 2022 and October 2023","topic":["0/Climate and climate change/"],"version":1.0,"view":["public","rafbar"]},{"authorAffiliation":["University of Nottingham"],"authorFamilyName":["Dugdale","Field","Johnson","Mariani","Pugh","Schrodt","Thorne"],"authorFullName":["Dugdale, S.J.","Field, R.","Johnson, M.","Mariani, M.","Pugh, B.","Schrodt, F.","Thorne, C."],"authorGivenName":["S.J.","R.","M.","B.","F.","C."],"availability":"Available","catalogue":"eidc","dataFormat":["TIFF"],"description":"The data comprise Sentinel-2 derived burn severity rasters covering restored and unrestored reaches of the South Fork McKenzie river, Oregon USA. The data were collected in order to quantify differences in burn severity in restored and unrestored river reaches following the Holiday Farm wildfire in 2020.\n\nRaw satellite imagery acquired in June 2020 and June 2021 was processed to calculate Normalised Burn Ratio (NBR), giving pre- and post-fire burn severity information. Data consist of 10 m .TIF raster imagery where a digital number gives a measure of burn severity; high NBR values indicate healthy vegetation, whereas lower values indicate burnt areas or bare ground.\n\nThe study was conducted by the University of Nottingham, in partnership with the US Forest Service, Portland State University, Washington State University and Colorado State University. Funding for the work was received from the Natural Environment Research Council.","documentType":"GEMINI_DOCUMENT","familyName":["Dugdale","Field","Johnson","Mariani","Pugh","Schrodt","Thorne"],"fullName":["Dugdale, S.J.","Field, R.","Johnson, M.","Mariani, M.","Pugh, B.","Schrodt, F.","Thorne, C."],"givenName":["S.J.","R.","M.","B.","F.","C."],"identifier":"8162887a-5481-440f-a7f2-427eee793efd","incomingCitationCount":0,"keyword":["Burn severity","Normalised burn ratio","Sentinel-2","South fork mckenzie","Stage zero","Wildfire","fire","river","restoration"],"keywordsOther":["Burn severity","Normalised burn ratio","Sentinel-2","South fork mckenzie","Stage zero","Wildfire","fire","river","restoration"],"licence":"Open government licence","lineage":"20 m bands of Two Sentinel-2A images of study site (pre/post-fire; June 2020 and 2021) were super-resolved to 10m following Lanaras et al (2018)\n\nThese data were subsequently used to generate raster files depicting 10m resolution Normalised Burn Ratio (NBR) across South Fork McKenzie River, where NBR = (Sentinel Band B08 - B12) / (B08 + B12), following the methodology outlined in Keeley (2009).  Subtraction of postfire from prefire NBR rasters facilitates estimation of burn severity by highlighting vegetation burn in relation to pre-burnt state.\n\nLanaras, C., Bioucas-Dias, J., Galliani, S., Baltsavias, E., & Schindler, K. (2018). Super-resolution of Sentinel-2 images: Learning a globally applicable deep neural network. ISPRS Journal of Photogrammetry and Remote Sensing, 146, 305-319 https://doi.org/10.1016/j.isprsjprs.2018.09.018\n\nKeeley, J.E. (2009). Fire intensity, fire severity and burn severity: a brief review and suggested usage. International Journal of Wildland Fire, 18, 116-126. https://doi.org/10.1071/WF07049\n\n","locations":["POLYGON((-122.29 44.13, -122.29 44.16, -122.23 44.16, -122.23 44.13, -122.29 44.13))"],"metadataDate":"2026-07-25T08:36:05.000Z","organisation":["University of Nottingham","NERC EDS Environmental Information Data Centre"],"publicationDate":"2023-01-17T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/8162887a-5481-440f-a7f2-427eee793efd","10.5285/8162887a-5481-440f-a7f2-427eee793efd","doi:10.5285/8162887a-5481-440f-a7f2-427eee793efd"],"resourceType":"Dataset","rightsHolder":["University of Nottingham"],"ror":["https://ror.org/04xw4m193"],"shortenedDescription":"The data comprise Sentinel-2 derived burn severity rasters covering restored and unrestored reaches of the South Fork McKenzie river, Oregon USA. The data were collected in order to quantify differences in burn severity in restored and unrestored river reaches following…","state":"published","supplementalDescription":["Lanaras, C., Bioucas-Dias, J., Galliani, S., Baltsavias, E., & Schindler, K. (2018). Super-resolution of Sentinel-2 images: Learning a globally applicable deep neural network. ISPRS Journal of Photogrammetry and Remote Sensing, 146, 305-319","Keeley, J.E. (2009). Fire intensity, fire severity and burn severity: a brief review and suggested usage. International Journal of Wildland Fire, 18, 116-126."],"temporalExtentText":"Data collected from 2020 to 2021","title":"High resolution burn severity data (derived from satellite imagery) for the South Fork McKenzie River in Oregon, USA, before and after a wildfire event, 2020 and 2021","version":1.0,"view":["public","crimar"]},{"authorAffiliation":["Centre for Ecology & Hydrology"],"authorFamilyName":["Morrison","Cooper","Rowe","Evans","McNamara"],"authorFullName":["Morrison, R.","Cooper, H.M.","Rowe, R.L.","Evans, J.G.","McNamara, N.P."],"authorGivenName":["R.","H.M.","R.L.","J.G.","N.P."],"authorOrcid":["0000-0002-1847-3127","0000-0002-5143-5819"],"authorRor":["https://ror.org/00pggkr55"],"availability":"Available","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)"],"description":"This dataset contains time series observations of surface-atmosphere exchanges of net ecosystem carbon dioxide exchange (NEE), sensible heat (H) and latent heat (LE), and momentum (τ) measured at a short rotation coppice willow plantation in Lincolnshire, UK. Turbulent flux densities were monitored using the micrometeorological eddy covariance (EC) technique between 9 January 2014 and 26 November 2017. The dataset includes ancillary weather and soil physics observations, as well as variables describing atmospheric turbulence and the quality of the turbulent flux observations. \n\nThis work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability.","documentType":"GEMINI_DOCUMENT","familyName":["Morrison","Cooper","Rowe","Evans","McNamara"],"fullName":["Morrison, R.","Cooper, H.M.","Rowe, R.L.","Evans, J.G.","McNamara, N.P."],"funder":["Natural Environment Research Council"],"givenName":["R.","H.M.","R.L.","J.G.","N.P."],"grant":["NE/R016429/1"],"identifier":"bf0d7332-4cfe-4277-bd99-3caf35332a7b","incomingCitationCount":1,"keyword":["Lincolnshire","Climate and climate change","Salix viminalis"],"keywordsOther":["Salix viminalis"],"keywordsPlace":["Lincolnshire"],"keywordsTheme":["Climate and climate change"],"licence":"Open government licence","lineage":"Eddy covariance (EC) and micrometeorological observations were made above the willow canopy using an open-path eddy covariance system.  Ancillary meteorological and soil physics observations were made from a scaffold tower at the northern end of the plantation.  \n\nTurbulent flux densities were calculated from the raw EC data using the EddyPRO® Flux Calculation Software Version 6.1. \n\nQuality Control of EC data involved removal of statistical outliers and tests that theoretical requirements for the successful application of the EC technique were not violated significantly.  Data gaps in EC data (NEE, LE, H) were filled using the Marginal Distribution Sampling approach.  Gaps in key meteorological variables (SWin, LWin, Ta, RH) were filled using linear relationships derived from weather stations located in adjacent fields. \n\nFurther details are available in the supporting documentation.","locations":["POLYGON((-0.619 53.294, -0.619 53.345, -0.523 53.345, -0.523 53.294, -0.619 53.294))"],"metadataDate":"2026-09-15T08:43:23.000Z","orcid":["0000-0002-1847-3127","0000-0002-5143-5819"],"organisation":["Centre for Ecology & Hydrology","UK Centre for Ecology & Hydrology","NERC Environmental Information Data Centre","NERC EDS Environmental Information Data Centre"],"publicationDate":"2019-02-14T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/bf0d7332-4cfe-4277-bd99-3caf35332a7b","10.5285/bf0d7332-4cfe-4277-bd99-3caf35332a7b","doi:10.5285/bf0d7332-4cfe-4277-bd99-3caf35332a7b"],"resourceType":"Dataset","rightsHolder":["UK Centre for Ecology & Hydrology"],"ror":["https://ror.org/00pggkr55","https://ror.org/04xw4m193"],"shortenedDescription":"This dataset contains time series observations of surface-atmosphere exchanges of net ecosystem carbon dioxide exchange (NEE), sensible heat (H) and latent heat (LE), and momentum (τ) measured at a short rotation coppice willow plantation in Lincolnshire, UK. Turbulent…","state":"published","supplementalDescription":["Drewer, J. et al., 2012. How do soil emissions of N2O, CH4 and CO2 from perennial bioenergy crops differ from arable annual crops? GCB Bioenergy, 4(4), pp.408–419."],"temporalExtentText":"Data collected from 2014 to 2017","title":"Eddy covariance measurements of carbon dioxide, energy and water fluxes at a short rotation coppice plantation, Lincolnshire, UK, 2014-2017","topic":["0/Climate and climate change/"],"version":1.0,"view":["public","marharv"]},{"availability":"Available","catalogue":"eidc","dataFormat":["JPEG","PNG","TIFF"],"description":"This web map service (WMS) show Concentration Based Estimated Deposition (CBED) values of sulphur and nitrogen atmospheric deposition for 5x5 kilometre (km) grid squares of the UK averaged over the years 2013 to 2015.\n\nThe maps show deposition values (kg ha-1 year-1) for oxidised nitrogen (NO2/NO3), reduced nitrogen (NH3/NH4) , non-marine sulphur (SO2/SO4) and base cations (Ca+Mg) . These total deposition values are the sum of four components calculated separately: wet deposition, dry deposition of gases, dry deposition of particulate matter and cloud droplet deposition. \n\nHabitat-specific data are provided for (i) moorland/short vegetation everywhere, and (ii) forest everywhere. Additionally, the grid square average over multiple land cover types (i.e. arable, grassland, forest, moorland, urban) is also provided.","documentType":"GEMINI_DOCUMENT","familyName":["Bealey"],"fullName":["Bealey, B."],"givenName":["Bill"],"identifier":"fe7886dc-1953-40f1-acf7-2fc32ebe1105","incomingCitationCount":0,"keyword":["nitrogen","base cations","sulphur","deposition","pollutant","Concentration Based Estimated Deposition (CBED)","infoMapAccessService"],"keywordsOther":["nitrogen","base cations","sulphur","deposition","pollutant","Concentration Based Estimated Deposition (CBED)","infoMapAccessService"],"licence":"Non-Open government licence","lineage":"The Concentration Based Estimated Deposition (CBED) methodology generates 5x5 km resolution maps of wet and dry deposition of sulphur, oxidised and reduced nitrogen, and base cations from measured concentrations of gases and particulate matter in air and measured concentrations of ions in precipitation. These data are collected at sites in the UK Eutrophying and Acidifying Pollutants (UKEAP) network. The site-based measurements are first interpolated to generate maps of concentrations for the UK. The ion concentrations in precipitation are combined with an annual precipitation map from the UK Meteorological Office to generate values of wet deposition. Gas and particulate matter concentration maps are combined with spatially distributed estimates of habitat-specific deposition velocities to generate dry deposition for 5 land cover categories: forest, moorland, grassland, arable and urban. The deposition to the 5 land cover categories are combined, depending on the relative proportions of different land cover categories in the 5x5 km grid square, to generate values for grid square averaged deposition. Dry deposition includes deposition of gases (Sulphur Dioxide (SO2), Nitric Acid (HNO3), Nitrogen Dioxide (NO2) and Ammonia (NH3) and particulate matter (sulphate, nitrate, ammonium, calcium and magnesium) to vegetation. For critical load exceedance calculations, deposition values for moorland are applied to all non-woodland habitats, and deposition values for forest are applied to all woodland habitats.\n\nData processing was done using the GenStat programme and results output as text files, these were then converted to tif images to generate this web map service.","locations":["POLYGON((-8.648 49.864, -8.648 60.861, 1.768 60.861, 1.768 49.864, -8.648 49.864))"],"metadataDate":"2026-08-12T11:43:11.000Z","organisation":["Centre for Ecology & Hydrology","NERC EDS Environmental Information Data Centre"],"publicationDate":"2018-09-11T00:00:00.000Z","recordType":"Map (web service)","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/fe7886dc-1953-40f1-acf7-2fc32ebe1105"],"resourceType":"Service","ror":["https://ror.org/00pggkr55","https://ror.org/04xw4m193"],"shortenedDescription":"This web map service (WMS) show Concentration Based Estimated Deposition (CBED) values of sulphur and nitrogen atmospheric deposition for 5x5 kilometre (km) grid squares of the UK averaged over the years 2013 to 2015.\n\nThe maps show deposition values (kg ha-1 year-1)…","state":"published","temporalExtentText":"Data collected from 2013 to 2015","title":"WMS for sulphur and nitrogen atmospheric Concentration Based Estimated Deposition (CBED), 2013-2015","version":1.0,"view":["public","phtr"]}],"rows":20,"semanticEnabled":false,"url":"https://catalogue.ceh.ac.uk/eidc/documents"}