{"numFound":194,"page":2,"rows":20,"url":"http://catalogue.ceh.ac.uk/eidc/documents?page=2&facet=topic%7C0%2FRadioecology%2F&facet=recordType%7CDataset&facet=topic%7C0%2FEnvironmental+survey%2F&facet=funder%7CNatural+Environment+Research+Council&facet=funder%7CEnvironment+Agency&facet=topic%7C0%2FEnvironmental+risk%2F","prevPage":"http://catalogue.ceh.ac.uk/eidc/documents?facet=topic%7C0%2FRadioecology%2F&facet=recordType%7CDataset&facet=topic%7C0%2FEnvironmental+survey%2F&facet=funder%7CNatural+Environment+Research+Council&facet=funder%7CEnvironment+Agency&facet=topic%7C0%2FEnvironmental+risk%2F","nextPage":"http://catalogue.ceh.ac.uk/eidc/documents?page=3&facet=topic%7C0%2FRadioecology%2F&facet=recordType%7CDataset&facet=topic%7C0%2FEnvironmental+survey%2F&facet=funder%7CNatural+Environment+Research+Council&facet=funder%7CEnvironment+Agency&facet=topic%7C0%2FEnvironmental+risk%2F","results":[{"publicationDate":"2024-06-18T00:00:00.000+00:00","authorAffiliation":["University of Hull","UK Centre for Ecology & Hydrology","University of Portsmouth","Met Office","Wallingford HydroSolutions","UK Environment Agency","Agricultural University of Athens"],"authorGivenName":["R.F.","V.","N.","M.D.","M.","D","C.","P.","G. ","F.","I.G.","A.C.","A.D."],"authorFamilyName":["Ainsworth","Keller","Bachiller-Jareno","Jürgens","Eastman","Sadykova","Rizzo","Scarlett","Peirson","Eley","Antoniou","Cowx","Johnson","Nunn"],"authorFullName":["Ainsworth, R.F.","Keller, V.","Bachiller-Jareno, N.","Jürgens, M.D.","Eastman, M.","Sadykova, D.","Rizzo, C.","Scarlett, P.","Peirson, G.","Eley, F.","Antoniou, V.","Cowx, I.G.","Johnson, A.C.","Nunn, A.D."],"authorOrcid":["https://orcid.org/0000-0001-6669-0356","https://orcid.org/0000-0003-4489-5363","https://orcid.org/0000-0001-9732-6725","https://orcid.org/0000-0002-6526-589X","https://orcid.org/0000-0002-8212-5872","https://orcid.org/0000-0002-3930-5974","https://orcid.org/0000-0001-6242-8158","https://orcid.org/0000-0001-6011-4075","https://orcid.org/0000-0003-1570-3764","https://orcid.org/0000-0001-8370-1221"],"authorRor":["https://ror.org/00pggkr55"],"catalogue":"eidc","description":"This dataset contains monthly/annual time series of species-specific abundances and covariates for 137 targeted larval/juvenile fish surveys at sites in a range of English lowland rivers. Larval/juvenile fish data come from two different sources: The Environment Agency’s (EA) National Fish Population Database (NFPD) between 1974 and 2017 and a dataset created by the University of Hull (UoH) between 1984 and 2017 inclusive. Biological data consists of density estimates of each fish species from each survey (per metre squared) and also the average length of specified species at the end of their first year of growth. Covariate data include habitat quality indicator (River Habitat Survey), climatic variables (Gulf Stream and North Atlantic Oscillation indices), land-use change, river hydrology, water temperature, effluent dilution factor and concentrations of chemical determinands. This dataset was created as larvae and juveniles may be particularly useful indicators and respond differently than older fish to environmental stressors.\n\nThe work was supported by the Natural Environment Research Council (Grant NE/S000100/2).","documentType":"GEMINI_DOCUMENT","funder":["Natural Environment Research Council"],"grant":["NE/S000100/2"],"identifier":"c904c5f0-7f21-4759-a7d4-c262da230b53","incomingCitationCount":0,"givenName":["R.F.","V.","N.","M.D.","M.","D","C.","P.","G. ","F.","I.G.","A.C.","A.D."],"familyName":["Ainsworth","Keller","Bachiller-Jareno","Jürgens","Eastman","Sadykova","Rizzo","Scarlett","Peirson","Eley","Antoniou","Cowx","Johnson","Nunn"],"fullName":["Ainsworth, R.F.","Keller, V.","Bachiller-Jareno, N.","Jürgens, M.D.","Eastman, M.","Sadykova, D.","Rizzo, C.","Scarlett, P.","Peirson, G.","Eley, F.","Antoniou, V.","Cowx, I.G.","Johnson, A.C.","Nunn, A.D."],"keyword":["England","Environmental survey","Water quality","pollution","hydrology","river","Larval fish","Juvenile fish","NFPD","Juvenile fish densities and pollution in English rivers","land use","Larval fish densities and pollution in English rivers","chemical","fish","Fish fry","land use change"],"keywordsPlace":["England"],"keywordsTheme":["Environmental survey","Water quality"],"keywordsOther":["pollution","hydrology","river","Larval fish","Juvenile fish","NFPD","Juvenile fish densities and pollution in English rivers","land use","Larval fish densities and pollution in English rivers","chemical","fish","Fish fry","land use change"],"licence":"Open government licence","lineage":"Fish Data\nJuvenile fish density data was collected from two sources: the EA NFPD \"Freshwater Fish Counts for all species for all Areas and all Years\" dataset (1974-2017) and the UoH fish count dataset (1984-2017). Fish counts were converted into densities (numbers per m-2) by dividing species counts by the sampling area (converted NFPD units from 100 m-2 to m-2 to match UoH data). To determine the mean length of juvenile fish (chub, roach, common bream, dace, bleak, gudgeon, minnow, and three-spined sticklebacks) at the end of the growing season (last surveys between August and October), length frequency histograms were created for each species and survey using R 4.2.1. Only individuals in their first year were considered in the calculation, providing the mean length of first-year fish at the end of the growing season for each survey. Species in the NFPD dataset were assigned Chempop Species Codes adapted from EA species codes, and when multiple EA species codes matched one Chempop Species Code, their densities were summed for each survey. Data without a Chempop species code (e.g., hybrids or broad categories like \"all species\") were removed, while surveys with zero fish captures were retained in the dataset.\n\nHabitat Quality indicators\nHabitat scores were obtained from the Environment Agency's River Habitat Survey (RHS) dataset, with ArcGIS used to link fish sites to their nearest RHS site. Two key scores were extracted: the Habitat Modification Score (HMS), which reflects the degree of artificial channel modification, and the Habitat Quality Assessment (HQA), which provides a broad assessment of habitat quality based on the diversity and abundance of natural features in the river channel and riparian zone. The HQA is suitable for comparing similar river types. To enable comparisons with data from 1994, new rules for flow-types and channel vegetation were established and applied across all sites, resulting in the HQA adjusted for 1994 data. The most recent RHS survey data was extracted for this analysis.\n\nLand Use\nLand use in the catchment upstream of fish sites (NFPD) were calculated from the UKCEH Land Cover Map 2015 (25m raster, GB). The 21 land cover types were grouped to cover four broad categories of: Woodland, Arable, Seminatural and Urban. The catchment tool in DataLabs was used to extract and process the data, which were summed into percentage and areas of each land use group. The sum of the percentages of the grouped categories were checked and were found to fall in the range of 99.96-100.04 %. \n\nWater Temperature\nTo assess its influence on fish growth, the cumulative annual degree-days ≥12 degC, indicating the total temperature sum for days exceeding 12 degC in the year prior to the survey date, was calculated. Water temperature data was sourced from the EA Surface Water Temperature Archive for sites with at least 3 years of records, and daily mean air temperature was collected from the Climate Hydrology and Ecology Research Support System (CHESS). The Baseflow Index for each water temperature gauging station and fish site was determined using the UKCEH National River Flow Archive. Generalized additive mix modeling (GAMM) was chosen to model water temperature, accounting for seasonal and year-to-year variation in water temperature, along with the nonlinear relationship between air and water temperature. Seven GAMM models, each covering a 0.1 BFI range, were developed, with the best model (Model: month, time, and air temperature, using ARMA structures) identified based on evaluation metrics like RMSE, NRMSE, and SI. This model was employed to estimate water temperature for fish sites.\n\nRiver Flow\nRiver flow data was sourced from the National River Flow Archive (NRFA) hosted by UKCEH and matched with fish sites based on the shortest distance along the river network. Data was extracted for the 12 months leading up to each fish survey, and various statistics were computed, including mean, median, standard deviation, coefficient of variation, Q5/mean, and Q95/mean. Additionally, threshold statistics were calculated for different percentiles (5, 25, 75, and 95), encompassing the threshold discharge value (estimated discharge quantile), days exceeded, number of exceedance events, and average event length.\n\nWater Quality-Effluent Dilution factor\nTo gauge river pollution levels across England, the study used the LowFlows2000-WQX (lowFlows2000 Water Quality eXtension) model, which characterizes wastewater discharge by wastewater treatment works (WWTWs) in terms of location, domestic population served, dry weather flow (DWF), and treatment type. It's important to note that only significant WWTWs were considered for computational purposes, based on specific criteria: those in catchments contributing to 95% of each hydrometric area and those accounting for 95% of the total discharged DWF to the estuary, ranked by DWF. The model produced predicted wastewater percentages for all reaches in the modelled river network, which is a truncated version of the 1:50,000 digital river network derived from the UK Ordnance Survey Panorama Data Set. To estimate the percentage of wastewater at each fish site, a python script was used to link each site to the nearest reach in the river network. The results are reported in terms of mean, standard deviation, 90th percentile, and 95th percentile, denoted as EDF_Mn, EDF_SD, EDF_Q90, and EDF_Q95, respectively.\n\nChemical Determinands\nChemical concentration data spanning 1960-2017, involving 41 determinands, was extracted from the UK's Environment Agency's Water Quality Data Archive. Fish sites were matched to the nearest chemical determinand site using specific criteria like site distance, sample count, and data collection timeframe through ArcGIS. To identify and exclude erroneous data, a threshold of 10 mg/l was set for some determinands, with values exceeding this threshold omitted from statistical calculations. Handling values below the Limit of Quantification (LoQ) involved three options: setting values to LoQ (LoQ1), setting them to 0 (LoQ2), or setting them to LoQ/2 (LoQ3). For the 12 months preceding the surveys at each fish site, various statistics were computed, including minimum, maximum, median, mean, standard deviation, total sample count, and counts of samples below and above the LoQ. Some sites had to be excluded from the final dataset due to licensing restrictions.\n\nAltitude\nElevation values for each fish site were extracted from the Integrated Hydrological Digital Terrain Model (IHDTM) using Arc GIS' Extract Multi Values to Points' tool. Two elevation values were calculated: Elevation values corresponding to the value of the IHDTM cell centre. Elevation values corresponding to an average value calculated from the adjacent cells with valid values using bilinear interpolation; NoData values were ignored in the interpolation unless all adjacent cells were NoData.\n\nClimate variables\nThe Gulf Stream Index (GSI) data spanning 1975-2017 was obtained from the Plymouth Marine Laboratory website (http://www.pml-gulfstream.org.uk/data.htm). Annual mean data were employed due to substantial month-to-month variability resulting from Gulf Stream meandering (Plymouth Marine Laboratory, 2019). Positive GSI values signify a northward shift from the long-term mean location, while negative values indicate a southward movement.\n\nData for the North Atlantic Oscillation Index (NAOI) spanning 1975-2017 was obtained from the National Centre for Atmospheric Research website (https://www.ncei.noaa.gov/access/monitoring/nao). The NAOI's winter (December-March) station-based index relies on the normalized sea level pressure (SLP) difference between Lisbon, Portugal, and Reykjavik, Iceland, dating back to 1864. Positive NAOI values indicate stronger westerlies over mid-latitudes, more intense North Atlantic weather systems, and wetter/milder conditions in Western Europe.","locations":["POLYGON((-6.452 49.864, -6.452 55.812, 1.768 55.812, 1.768 49.864, -6.452 49.864))"],"orcid":["https://orcid.org/0000-0001-6669-0356","https://orcid.org/0000-0003-4489-5363","https://orcid.org/0000-0001-9732-6725","https://orcid.org/0000-0002-6526-589X","https://orcid.org/0000-0002-8212-5872","https://orcid.org/0000-0002-3930-5974","https://orcid.org/0000-0001-6242-8158","https://orcid.org/0000-0001-6011-4075","https://orcid.org/0000-0003-1570-3764","https://orcid.org/0000-0001-8370-1221"],"organisation":["University of Hull","UK Centre for Ecology & Hydrology","University of Portsmouth","Met Office","Wallingford HydroSolutions","UK Environment Agency","Agricultural University of Athens","NERC EDS Environmental Information Data Centre","The University of Hull"],"recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/c904c5f0-7f21-4759-a7d4-c262da230b53","10.5285/c904c5f0-7f21-4759-a7d4-c262da230b53"],"resourceStatus":"Embargoed","resourceType":"Dataset","rightsHolder":["The University of Hull"],"ror":["https://ror.org/00pggkr55","https://ror.org/04xw4m193"],"state":"published","title":"Larval and juvenile fish abundance, habitat, water quality, flow and climate data from English rivers, 1984-2017","topic":["0/Environmental survey/","0/Water quality/"],"version":1.0,"view":["public","tinzha"],"shortenedDescription":"This dataset contains monthly/annual time series of species-specific abundances and covariates for 137 targeted larval/juvenile fish surveys at sites in a range of English lowland rivers. Larval/juvenile fish data come from two different sources: The Environment Agency’s..."},{"publicationDate":"2023-03-03T00:00:00.000+00:00","authorAffiliation":["Unaffiliated"],"authorFullName":["National Plant Monitoring Scheme "],"catalogue":"eidc","description":"This data resource provides plot-level habitat data for the first eight years (2015-2022) of the National Plant Monitoring Scheme (covering the UK, the Channel Islands, and the Isle of Man). Data consist of surveyor-recorded habitat information on repeated samples of fixed plots at the metre-scale. Other information includes the date of sampling, data regarding the spatial location of the plot, and an assessment of whether or not the recorded broad habitat is reported to have changed between surveyor visits.\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.\n","documentType":"GEMINI_DOCUMENT","funder":["Natural Environment Research Council"],"grant":["NE/R016429/1"],"identifier":"a12b5c70-c0e2-48cf-b0b7-3e95791feca9","incomingCitationCount":0,"fullName":["National Plant Monitoring Scheme "],"keyword":["Environmental survey","National Plant Monitoring Scheme","validation","training","plant community","vegetation","earth observation","habitat","environmental monitoring"],"keywordsTheme":["Environmental survey"],"keywordsOther":["National Plant Monitoring Scheme","validation","training","plant community","vegetation","earth observation","habitat","environmental monitoring"],"licence":"Open government licence","lineage":"Data are collected directly from volunteers into a custom Indicia database system through the National Plant Monitoring Scheme (NPMS) website or app. The Indicia system is built on a PostgreSQL/PostGIS database, and the data presented here were extracted directly from this master database using appropriate SQL queries. See the associated documentation for more information on the broader Quality Assurance processes supporting the NPMS.","locations":["POLYGON((-8.648 48.137, -8.648 60.861, 2.944 60.861, 2.944 48.137, -8.648 48.137))"],"organisation":["Unaffiliated","NERC EDS Environmental Information Data Centre","Natural Environment Research Council"],"recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/a12b5c70-c0e2-48cf-b0b7-3e95791feca9","10.5285/a12b5c70-c0e2-48cf-b0b7-3e95791feca9"],"resourceStatus":"Available","resourceType":"Dataset","rightsHolder":["Natural Environment Research Council"],"ror":["https://ror.org/04xw4m193"],"state":"published","supplementalName":["Indicia database system","National Plant Monitoring Scheme website"],"title":"Habitat samples from the National Plant Monitoring Scheme, 2015-2022","topic":["0/Environmental survey/"],"version":1.0,"view":["public","margla"],"shortenedDescription":"This data resource provides plot-level habitat data for the first eight years (2015-2022) of the National Plant Monitoring Scheme (covering the UK, the Channel Islands, and the Isle of Man). Data consist of surveyor-recorded habitat information on repeated samples of..."},{"publicationDate":"2020-07-10T00:00:00.000+00:00","authorAffiliation":["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"],"authorGivenName":["K.","G. ","D. ","H. ","M. ","K. ","L. ","J. ","Z.","M."],"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."],"authorOrcid":["https://orcid.org/0000-0003-3265-1505","https://orcid.org/0000-0001-9538-3208","https://orcid.org/0000-0002-6975-5984","https://orcid.org/0000-0002-2474-6558","https://orcid.org/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"],"catalogue":"eidc","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","funder":["Natural Environment Research Council"],"grant":["NE/R000131/1"],"identifier":"2a932995-f040-4724-ad21-3e92ae8a2540","incomingCitationCount":1,"givenName":["K.","G. ","D. ","H. ","M. ","K. ","L. ","J. ","Z.","M."],"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."],"keyword":["SUNRISE","Agriculture","Environmental risk","Triticum aestivum","Glycine max","Zea may","Oryza sativa"],"keywordsProject":["SUNRISE"],"keywordsTheme":["Agriculture","Environmental risk"],"keywordsOther":["Triticum aestivum","Glycine max","Zea may","Oryza sativa"],"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))"],"orcid":["https://orcid.org/0000-0003-3265-1505","https://orcid.org/0000-0001-9538-3208","https://orcid.org/0000-0002-6975-5984","https://orcid.org/0000-0002-2474-6558","https://orcid.org/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"],"recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/2a932995-f040-4724-ad21-3e92ae8a2540","10.5285/2a932995-f040-4724-ad21-3e92ae8a2540"],"resourceStatus":"Available","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"],"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"],"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"],"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..."},{"publicationDate":"2020-03-03T00:00:00.000+00:00","authorAffiliation":["University of Brighton","Exeter University","University of Hull","University of Birmingham"],"authorGivenName":["P.","Andrew","D.","G."],"authorFamilyName":["Ashworth","Nicholas","Parsons","Sambrook Smith"],"authorFullName":["Ashworth, P.","Nicholas, A.","Parsons, D.","Sambrook Smith, G."],"authorOrcid":["https://orcid.org/0000-0002-3707-1182"],"authorRor":["https://ror.org/04kp2b655","https://ror.org/03yghzc09","https://ror.org/04nkhwh30","https://ror.org/03angcq70"],"catalogue":"eidc","description":"Data were generated to investigate the influence of bed roughness on the dynamics of large sand-bed rivers like the South Saskatchewan, Canada. The influence of roughness was investigated by using a numerical model to simulate the evolution of the river bed for a hypothetical sand-bed river modelled on the South Saskatchewan. The model generated information on the evolving river bed topography, water depth, flow velocities and sediment transport rates, over a period of 28 years as part of NERC project NE/L00738X/1","documentType":"GEMINI_DOCUMENT","funder":["Natural Environment Research Council"],"grant":["NE/L00738X/1"],"identifier":"790e507c-ce99-47ca-99b4-c97a684ee8c6","incomingCitationCount":0,"givenName":["Andrew","P.","D.","G."],"familyName":["Nicholas","Ashworth","Parsons","Sambrook Smith"],"fullName":["Nicholas, A.","Ashworth, P.","Parsons, D.","Sambrook Smith, G."],"keyword":["Environmental survey","river bed"],"keywordsTheme":["Environmental survey"],"keywordsOther":["river bed"],"licence":"Open government licence","lineage":"These files contain results from numerical simulations of river bed dynamics for a hypothetical sand-bed river modelled on the South Saskatchewan River, Canada. The aim of these simulations was to investigate the influence of changes in the representation of bed roughness and sediment transport on simulated river morphodynamics for large sand-bed rivers like the South Saskatchewan. Simulations were carried out using a 2D depth-averaged numerical model that solves the shallow water equations, coupled with equations for sediment transport and bed level change (i.e. resulting from sediment mass conservation). Results are provided for two simulations (A and B). Simulation A used a van Rijn sediment transport formulation and depth-dependent Chezy roughness law. Simulation B used an Engelund-Hanson sediment transport formulation and constant (depth-independent) Chezy roughness. In both simulations, the model was initialized with a flat bed and using banklines that were digitized for an 8 km reach of the South Saskatchewan River, Canada located immediately downstream of the town of Outlook, Saskatchewan. The model domain measures 800 cells (downstream) by 300 cells (cross-stream). Cell dimensions are 10 m (downstream) by 5 m (cross-stream). Simulations were run for 28 years using an inlet hydrograph based on gauged flow conditions for the South Saskatchewan River.\n\nFiles are named Simulation_A_ #.csv, Simulation_B_ #.csv\n\nThe # represents the results file number, where each number corresponds to a time slice in the model simulation (1 being the earliest and 56 being the latest). Simulations represent a duration of 28 years, with two time slices per year. Odd-numbered time slices represent low flow conditions and even-numbered time slices represent high flow conditions.","locations":["POLYGON((-108.105 53.43, -108.105 56.029, -103.831 56.029, -103.831 53.43, -108.105 53.43))"],"orcid":["https://orcid.org/0000-0002-3707-1182"],"organisation":["University of Exeter","University of Brighton","Exeter University","University of Hull","University of Birmingham","NERC EDS Environmental Information Data Centre","NERC Environmental Information Data Centre"],"recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/790e507c-ce99-47ca-99b4-c97a684ee8c6","10.5285/790e507c-ce99-47ca-99b4-c97a684ee8c6"],"resourceStatus":"Available","resourceType":"Dataset","ror":["https://ror.org/03yghzc09","https://ror.org/04kp2b655","https://ror.org/04nkhwh30","https://ror.org/03angcq70","https://ror.org/04xw4m193"],"state":"published","title":"Numerical simulations of river bed dynamics for the South Saskatchewan River, Canada","topic":["0/Environmental survey/"],"version":1.0,"view":["public","clwe"],"shortenedDescription":"Data were generated to investigate the influence of bed roughness on the dynamics of large sand-bed rivers like the South Saskatchewan, Canada. The influence of roughness was investigated by using a numerical model to simulate the evolution of the river bed for a hypothetical..."},{"publicationDate":"2019-06-12T00:00:00.000+00:00","authorAffiliation":["University of Leeds"],"authorGivenName":["J."],"authorFamilyName":["Richardson"],"authorFullName":["Richardson, J."],"authorOrcid":["https://orcid.org/0000-0001-7052-422X"],"authorRor":["https://ror.org/024mrxd33"],"catalogue":"eidc","description":"Erosion risk mapping showing river channel concentrations modelled using SCIMAP for the Yorkshire River Derwent, UK. Scenario mapping has been carried out and the dataset includes the following scenarios to assess variation in model output: 1) traditional land use map; 2) satellite derived land use maps; 3) long term rainfall averages; 4) integrating the artificial drainage network and 5) incorporating future climate change. ","documentType":"GEMINI_DOCUMENT","funder":["Natural Environment Research Council"],"grant":["NE/R013012/1"],"identifier":"331dd8ca-a4ff-40e6-b753-1b68468d8996","incomingCitationCount":0,"givenName":["J.","Janet"],"familyName":["Richardson"],"fullName":["Richardson, J."],"keyword":["Environmental risk","Erosion","Risk mapping","Yorkshire","River Derwent","Fine grained sediment"],"keywordsTheme":["Environmental risk"],"keywordsOther":["Erosion","Risk mapping","Yorkshire","River Derwent","Fine grained sediment"],"licence":"Open government licence","lineage":"This data was produced using SCIMAP (http://www.scimap.org.uk/), which requires the following data input – elevation (digital elevation model); rainfall and land use. This data shows erosion risk concentrations within river channels of the River Derwent, Yorkshire, UK. Seasonal erosion risk was assessed for a year, looking at a range of scenarios 1) using traditional land use maps (e.g., CORINE / CEH land use maps); 2) using seasonal satellite derived land use which can show bare land; 3) long term rainfall averages; 4) integrating the artificial drainage network and 5) incorporating future climate change using UKCP09 data. \n\nFor further details please see the supporting documentation.","locations":["POLYGON((-1.425 53.727, -1.425 54.513, -0.215 54.513, -0.215 53.727, -1.425 53.727))"],"orcid":["https://orcid.org/0000-0001-7052-422X"],"organisation":["University of Leeds","NERC EDS Environmental Information Data Centre","NERC Environmental Information Data Centre"],"recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/331dd8ca-a4ff-40e6-b753-1b68468d8996","10.5285/331dd8ca-a4ff-40e6-b753-1b68468d8996"],"resourceStatus":"Available","resourceType":"Dataset","ror":["https://ror.org/024mrxd33","https://ror.org/04xw4m193"],"state":"published","title":"Fine-grained sediment diffuse pollution risk mapping scenarios for the Yorkshire Derwent catchment ","topic":["0/Environmental risk/"],"version":1.0,"view":["public","clwe"],"shortenedDescription":"Erosion risk mapping showing river channel concentrations modelled using SCIMAP for the Yorkshire River Derwent, UK. Scenario mapping has been carried out and the dataset includes the following scenarios to assess variation in model output: 1) traditional land use map;..."},{"publicationDate":"2024-09-20T00:00:00.000+00:00","authorAffiliation":["The James Hutton Institute ","UK Centre for Ecology & Hydrology","University of the Highlands and Islands","Royal Society for the Protection of Birds","The James Hutton Institute"],"authorGivenName":["M.","E.","R.","J.","P.","A.","R.R.E."],"authorFamilyName":["Coyle","Cowdery","Morrison","Andersen","Cash","Gilbert","Johnson-Marshall","Levy","Vidis","Artz"],"authorFullName":["Coyle, M.","Cowdery, E.","Morrison, R.","Andersen, R.","Cash, J.","Gilbert, P.","Johnson-Marshall, A.","Levy, P.","Vidis, M.","Artz, R.R.E."],"authorOrcid":["https://orcid.org/0000-0002-9440-6524","https://orcid.org/0000-0002-6538-6296","https://orcid.org/0000-0002-1847-3127","https://orcid.org/0000-0002-7782-795X","https://orcid.org/0000-0002-8567-1377","https://orcid.org/0000-0003-2356-0951","https://orcid.org/0000-0002-8505-1901","https://orcid.org/0000-0002-8462-6558"],"authorRor":["https://ror.org/03rzp5127","https://ror.org/00pggkr55","https://ror.org/0138va192"],"catalogue":"eidc","description":"This dataset contains measurements of greenhouse gas exchange (carbon dioxide and methane) over a near natural blanket bog in the Flow Country, Caithness and Sutherland, using eddy-covariance, and associated meteorological and pedological measurements from 2016-10-19 to 2022-12-31 at half hourly intervals. The time series has been gap filled to allow the calculation of annual budgets for carbon exchange.\n\nThe site reference is UK_CLs ( http://www.europe-fluxdata.eu/home/sites-list )","documentType":"GEMINI_DOCUMENT","funder":["Natural Environment Research Council","Scottish Government: Rural and Environment Science and Analytical Services"],"identifier":"41acfe3e-761b-4362-bcc7-8d49ce52cc35","incomingCitationCount":0,"givenName":["M.","E.","R.","J.","P.","A.","R.R.E."],"familyName":["Coyle","Cowdery","Morrison","Andersen","Cash","Gilbert","Johnson-Marshall","Levy","Vidis","Artz"],"fullName":["Coyle, M.","Cowdery, E.","Morrison, R.","Andersen, R.","Cash, J.","Gilbert, P.","Johnson-Marshall, A.","Levy, P.","Vidis, M.","Artz, R.R.E."],"keyword":["Environmental survey","Climate and climate change","blanket bog","NEE","climate change","carbon dioxide","methane","bog","peat","meteorology","climate"],"keywordsTheme":["Environmental survey","Climate and climate change"],"keywordsOther":["blanket bog","NEE","climate change","carbon dioxide","methane","bog","peat","meteorology","climate"],"licence":"Open government licence","lineage":"The site was first installed in April 2008 by Pete Levy, UKCEH, with funding from the European Union Seventh Framework Programme project ‘Greenhouse gas management in European land-use systems’ and its operation has been maintained since then under other grants and projects. It is currently managed by the James Hutton Institute (Aberdeen) as part of the SCO2FLUX network with supporting funding from NERC (Mothership Project) and SRES (CentrePeat project). UKCEH continues to assist with supplying instrumentation for the site and analysis/interpretation of the data, while University of the Highlands and Islands are the local site operators with support from the RSPB (Royal Society for the Protection of Birds).\n\nMeasurements are made using standard instrumentation, retrieved remotely at regular intervals and processed using protocols similar to those defined by the FluxNet and ICOS projects.","locations":["POLYGON((-3.965 58.371, -3.965 58.372, -3.964 58.372, -3.964 58.371, -3.965 58.371))"],"orcid":["https://orcid.org/0000-0002-9440-6524","https://orcid.org/0000-0002-6538-6296","https://orcid.org/0000-0002-1847-3127","https://orcid.org/0000-0002-7782-795X","https://orcid.org/0000-0002-8567-1377","https://orcid.org/0000-0003-2356-0951","https://orcid.org/0000-0002-8505-1901","https://orcid.org/0000-0002-8462-6558"],"organisation":["The James Hutton Institute ","UK Centre for Ecology & Hydrology","University of the Highlands and Islands","Royal Society for the Protection of Birds","The James Hutton Institute","NERC EDS Environmental Information Data Centre"],"recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/41acfe3e-761b-4362-bcc7-8d49ce52cc35","10.5285/41acfe3e-761b-4362-bcc7-8d49ce52cc35"],"resourceStatus":"Available","resourceType":"Dataset","rightsHolder":["The James Hutton Institute"],"ror":["https://ror.org/03rzp5127","https://ror.org/00pggkr55","https://ror.org/0138va192","https://ror.org/04xw4m193"],"state":"published","title":"Carbon dioxide and methane fluxes and associated environmental observations from an unmodified blanket bog, Forsinard Flows RSPB Reserve, Scotland, 2016-2022","topic":["0/Environmental survey/","0/Climate and climate change/"],"version":1.0,"view":["elsdhi","dgwr","rebekka.artz@hutton.ac.uk","public"],"shortenedDescription":"This dataset contains measurements of greenhouse gas exchange (carbon dioxide and methane) over a near natural blanket bog in the Flow Country, Caithness and Sutherland, using eddy-covariance, and associated meteorological and pedological measurements from 2016-10-19..."},{"publicationDate":"2020-04-03T00:00:00.000+00:00","authorAffiliation":["National Institute of Amazonian Research","Nanyang Technological University","University of Exeter"],"authorGivenName":["L.F.","C.A.","K.M.","L.M.","M.P.","A.C.M.","Iain P."],"authorFamilyName":["Lugli","Quesada","Andersen","Mercado","Martins","Moraes","Hartley"],"authorFullName":["Lugli, L.F.","Quesada, C.A.","Andersen, K.M.","Mercado, L.M.","Martins, M.P.","Moraes, A.C.M.","Hartley, I.P."],"authorOrcid":["https://orcid.org/0000-0001-8404-4841","https://orcid.org/0000-0002-1460-9904","https://orcid.org/0000-0003-4069-0838","https://orcid.org/0000-0002-9183-6617"],"authorRor":["https://ror.org/01xe86309","https://ror.org/02e7b5302","https://ror.org/03yghzc09"],"catalogue":"eidc","description":"The data consists of carbon, micro and macro nutrient concentrations in fine roots (<2mm diameter) in old growth forests in Central Amazon. Fine roots younger than three months were sampled using the ingrowth core technique in a large-scale nutrient fertilisation experiment. Carbon and nutrient concentrations refer to year one of fertilisation, bulking samples from November 2017 to August 2018. Concentrations are given as a mean of the community per plot in year 1, where five points inside each plot were sampled in the 0-10 cm and 10-30 cm soil layers. The dataset depicts the concentrations of iron, zinc, manganese, calcium, magnesium, potassium, phosphorus, nitrogen and carbon in fine roots in two different soil depths. \n\nSamples were collected at the AFEX project area in Manaus, Brazil at the Biological Dynamics of Forest Fragments Project (BDFFP/ INPA). \n\nThe study was funded by NERC, BDFFP (logistical support) and Brazilian government (student scholarship).\n","documentType":"GEMINI_DOCUMENT","funder":["Natural Environment Research Council"],"identifier":"ba190356-1731-4558-be7a-3fedc570663a","incomingCitationCount":0,"givenName":["L.F.","C.A.","K.M.","L.M.","M.P.","A.C.M.","Iain P.","Laynara"],"familyName":["Lugli","Quesada","Andersen","Mercado","Martins","Moraes","Hartley"],"fullName":["Lugli, L.F.","Quesada, C.A.","Andersen, K.M.","Mercado, L.M.","Martins, M.P.","Moraes, A.C.M.","Hartley, I.P.","Lugli, L."],"keyword":["Brazil","Manaus","Soil","Environmental survey"],"keywordsPlace":["Brazil","Manaus"],"keywordsTheme":["Soil","Environmental survey"],"licence":"Open government licence","lineage":"Samples < 2mm diameter were bulked by plot and soil depth (0-10cm and 10-30cm) using root material collected in 4-time intervals, from November 2017 to August 2018. After dried, samples were ground using a knife and/ or ball mill for nutritional analysis. Micronutrients, phosphorus and cations were extracted by nitroperchloric digestion. Cations and micronutrients were determined by atomic absorption spectrophotometry, whilst phosphorus was determined by spectrophotometry. Carbon and nitrogen concentrations were determined using an automatic C and N analyser.","locations":["POLYGON((-68.5 -24.6, -68.5 5.1, -31.7 5.1, -31.7 -24.6, -68.5 -24.6))"],"orcid":["https://orcid.org/0000-0001-8404-4841","https://orcid.org/0000-0002-1460-9904","https://orcid.org/0000-0003-4069-0838","https://orcid.org/0000-0002-9183-6617"],"organisation":["National Institute of Amazonian Research","Nanyang Technological University","University of Exeter","NERC EDS Environmental Information Data Centre","NERC Environmental Information Data Centre"],"recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/ba190356-1731-4558-be7a-3fedc570663a","10.5285/ba190356-1731-4558-be7a-3fedc570663a"],"resourceStatus":"Available","resourceType":"Dataset","ror":["https://ror.org/01xe86309","https://ror.org/02e7b5302","https://ror.org/03yghzc09","https://ror.org/04xw4m193"],"state":"published","title":"Fine root nutrient concentration in fertilised plots in the Central Amazon, 2018","topic":["0/Soil/","0/Environmental survey/"],"version":1.0,"view":["public","clwe"],"shortenedDescription":"The data consists of carbon, micro and macro nutrient concentrations in fine roots (<2mm diameter) in old growth forests in Central Amazon. Fine roots younger than three months were sampled using the ingrowth core technique in a large-scale nutrient fertilisation experiment...."},{"publicationDate":"2025-05-09T00:00:00.000+00:00","authorAffiliation":["UK Centre for Ecology & Hydrology"],"authorGivenName":["Heidrun","B.A.","H.","A.G.","K.","G.","S."],"authorFamilyName":["Feuchtmayr","Dodd","Guyatt","Hunt","Le Quesne","McShane","Moorhouse","Rankin","Rhodes","Thackeray"],"authorFullName":["Feuchtmayr, H.","Dodd, B.A.","Guyatt, H.","Hunt, A.G.","Le Quesne, K.","McShane, G.","Moorhouse, H.","Rankin, G.","Rhodes, G.","Thackeray, S."],"authorOrcid":["https://orcid.org/0000-0002-2028-4843","https://orcid.org/0000-0001-7038-9881","https://orcid.org/0000-0003-0488-3843","https://orcid.org/0000-0003-3274-2706"],"authorRor":["https://ror.org/00pggkr55"],"catalogue":"eidc","description":"This is part of an ongoing long-term monitoring dataset of surface temperature, surface oxygen, water clarity, water chemistry and phytoplankton chlorophyll a from fortnightly sampling at Blelham Tarn in Cumbria, England that began in 1945 for some variables. The data have been collected by the UK Centre for Ecology & Hydrology (UKCEH). The data available to download comprise surface temperature (TEMP) in degree Celsius, surface oxygen saturation (OXYG) in % air-saturation, Secchi depth (SECC) in metres, alkalinity (ALKA) in µg per litre as CaCO3 and pH. Total ammoniacal nitrogen (NH4N), total oxidised nitrogen (TON), soluble reactive phosphate (PO4P), total phosphorus (TOTP), dissolved reactive silicon expressed as SiO2 (SIO2) and phytoplankton chlorophyll a (TOCA) are all given in µg per litre. Water samples are based on a sample integrated from 0 to 5 m. Water chemistry values below the detection limit, are indicated by a < sign in the column titled ‘sign(if