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E. L.","R.","B. V."],"authorOrcid":["https://orcid.org/0000-0002-1643-1046","https://orcid.org/0009-0001-2611-3391","https://orcid.org/0000-0003-0334-5867","https://orcid.org/0000-0003-2675-9464","https://orcid.org/0000-0002-9154-7954","https://orcid.org/0000-0001-8151-2769","https://orcid.org/0000-0001-5140-2710"],"authorRor":["https://ror.org/00pggkr55","https://ror.org/03rzp5127"],"availability":"Available","catalogue":"eidc","dataFormat":["TIFF","GeoPackage"],"description":"This dataset maps the risks of Phytophthora ramorum infection for 79062 larch fragments identified in Scotland, of which 79060 were assigned a risk score. Two fragments without climate and/or habitat suitability scores were excluded. Fragment risk scores integrate multiple risk factors. The primary risk factor is climate suitability for P. ramorum using pathogen-specific temperature-dependent growth curves and a relative humidity threshold. Other risk factors integrated are proximity to larch/infected larch within 500m or 5000m and other (non-Larch) wider environment infections within 1500m. Presence of alternative hosts are scored using habitat suitability within the fragment for sporulating hosts (Vaccinium myrtillus, V. vitis-idaea, Acrostaphylos uva-versi) and the reservoir host Rhododendron ponticum. Additionally, proximity to inspected premises with confirmed infections and the presence of water courses are also assessed. The maximum possible risk score for a larch fragment is 12. Fragments were also classified as low, medium or high risk. ","documentType":"GEMINI_DOCUMENT","familyName":["Barwell","Turvey","Amankwaa","Asaaga","Cooke","Mitchell","Purse"],"fullName":["Louise Barwell","Barwell, L.","Turvey, K.","Amankwaa, G.","Asaaga, F.","Cooke, D.E.L.","Mitchell, R.","Purse, B.V."],"funder":["Natural Environment Research Council","Scotland's Plant Health Centre","Department for Environment Food and Rural Affairs"],"givenName":["L","L.","K.","G.","F.","D. E. L.","R.","B. V."],"grant":["NE/V019813/1","PHC2023/02","TH12224FR10"],"identifier":"f6809e00-91cb-494d-babd-5d60d938ad97","incomingCitationCount":1,"keyword":["Environmental risk","Phytophthora ramorum","Larch","Scotland","forestry","exotic species","habitat","pathogenic organism","pest","phytopathology","risk assessment"],"keywordsOther":["Phytophthora ramorum","Larch","Scotland","forestry","exotic species","habitat","pathogenic organism","pest","phytopathology","risk assessment"],"keywordsTheme":["Environmental risk"],"licence":"Open government licence","lineage":"We employed an iterative and collaborative co-production process that brought together stakeholders with diverse expertise from across Scotland’s plant health sector, including forestry, conservation, horticulture, and government agencies to co-design the risk framework. Larch fragments in Scotland were compiled from the National Forest Estate Sub-compartments Scotland 2019, the Native Woodland Survey of Scotland, survey data, Statutory Plant Health Notices and larch layers from Scottish Forestry, and a Phytophthora database. Any areas felled since 2013 were identified and removed using the National Forest Inventory GB from 2013 to 2023 and completed Statutory Plant Health Notices. Key risk factors and their scoring were agreed with 15 cross-sectoral stakeholders through a self-completion survey and two workshops. The risk scoring has been adjusted to reduce the emphasis on proximity to inspected premises as a pathway of spread, reflecting stakeholder perspectives on improved biosecurity practices in trade.  The previous risk analysis for P. ramorum infection for Scotland’s larch fragments (https://doi.org/10.5285/29726cda-09f5-4661-8fd4-ddaa5555466a) has been updated to reflect the removal of larch since 2013 through Statutory Plant Health Notices and other clear-felling, to include new P. ramorum detection data in larch woodlands and inspected premises provided by Scottish Forestry and SASA. In addition, new climate suitability models of pathogen growth are used to score risk of establishment and new species distribution models have been used to score risks of transmission from alternative host species of P. ramorum. The scored fragment data were intersected with the boundaries of local authorities, Scottish Forestry Conservancies, and P. ramorum policy zones to summarise the distribution of risks across regions in Scotland.\n\nThe final report was peer reviewed by the Plant Health Centre. In addition, a knowledge integration and validation workshop (November 13, 2024) examined the adequacy of the outputs for horizon scanning and decision-making across sectors. Validation of the climate suitability models for P. ramorum has been attempted using independent UK and European detections for P. ramorum. This spatial risk framework cannot yet be fully validated until future detection data are available, because previous detections are used within the model and are not independent of the risk scores assigned. However, the previous risk framework for Larch has been cross-validated against subsequent, independent P. ramorum detections, as proof of concept.","locations":["POLYGON((-8.648 54.634, -8.648 60.861, -0.728 60.861, -0.728 54.634, -8.648 54.634))"],"metadataDate":"2026-06-29T18:31:34.000Z","orcid":["https://orcid.org/0000-0002-1643-1046","https://orcid.org/0009-0001-2611-3391","https://orcid.org/0000-0003-0334-5867","https://orcid.org/0000-0003-2675-9464","https://orcid.org/0000-0002-9154-7954","https://orcid.org/0000-0001-8151-2769","https://orcid.org/0000-0001-5140-2710"],"organisation":["UK Centre for Ecology & Hydrology","James Hutton Institute","NERC EDS Environmental Information Data Centre"],"publicationDate":"2025-10-17T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/f6809e00-91cb-494d-babd-5d60d938ad97","10.5285/f6809e00-91cb-494d-babd-5d60d938ad97","doi:10.5285/f6809e00-91cb-494d-babd-5d60d938ad97"],"resourceType":"Dataset","rightsHolder":["UK Centre for Ecology & Hydrology"],"ror":["https://ror.org/00pggkr55","https://ror.org/03rzp5127","https://ror.org/04xw4m193"],"shortenedDescription":"This dataset maps the risks of Phytophthora ramorum infection for 79062 larch fragments identified in Scotland, of which 79060 were assigned a risk score. Two fragments without climate and/or habitat suitability scores were excluded. Fragment risk scores integrate multiple…","state":"published","title":"Spatial risk analysis for Phytophthora ramorum infection in Larch fragments in Scotland","topic":["0/Environmental risk/"],"version":1.0,"view":["public","tinzha"]},{"authorAffiliation":["UK Centre for Ecology & Hydrology"],"authorFamilyName":["Noguera","Bulut","Chevuturi","Barker","Hannaford"],"authorFullName":["Noguera, I.","Bulut, B.","Chevuturi, A.","Barker, L.J.","Hannaford, J."],"authorGivenName":["I","B","A","L.J","J"],"authorOrcid":["https://orcid.org/0000-0002-0696-9504","https://orcid.org/0000-0003-4567-5258","https://orcid.org/0000-0003-2815-7221","https://orcid.org/0000-0002-2913-0664","https://orcid.org/0000-0002-5256-3310"],"authorRor":["https://ror.org/00pggkr55"],"availability":"Available","catalogue":"eidc","dataFormat":["NetCDF"],"description":"Here, we present the Global Multi-Index Drought (GMID) dataset, which includes some of the most used and widely recommended standardised drought indices: the Standardized Precipitation Index (SPI), the Evaporative Drought Demand Index (EDDI), the Standardized Precipitation Evapotranspiration Index (SPEI), the Standardized Evapotranspiration Deficit Index (SEDI), and the Standardized Vapor Pressure Deficit Index (SVPDI). This dataset is available on a global scale covering 1-12, 18, 24, 48-month time scales for the period 1980 to 2024, with high spatial (0.1 degrees) and temporal (weekly and monthly) resolution. GMID was generated using different meteorological input datasets, including: Multi-Source Weighted-Ensemble Precipitation (MSWEP) v2.8 (https://www.gloh2o.org/mswep/), Global Land Evaporation Amsterdam Model (GLEAM) v4.2a (https://www.gleam.eu/), and Multi-Source Weather (MSWX) vMSWX-Past (https://www.gloh2o.org/mswx/).\n\nThe GMID dataset is provided weekly and monthly, including two versions of the five drought indices: one generated using the \"reference\" approach (i.e., based on the probability distribution typically recommended in the literature for calculating these drought indices), and another using the \"best-fit\" approach (i.e., based on the probability distributions that provide better normalised resulting series for each case). GMID represents a comprehensive and robust global long-term dataset for drought (and flash drought) assessment, which will be further updated annually as input data become available.","documentType":"GEMINI_DOCUMENT","familyName":["Noguera","Bulut","Chevuturi","Barker","Hannaford"],"fullName":["Ivan Noguera","Noguera, I.","Bulut, B.","Chevuturi, A.","Barker, L.J.","Hannaford, J."],"funder":["Natural Environment Research Council"],"givenName":["I","B","A","L.J","J"],"grant":["NE/X006247/1"],"identifier":"f5ce92b0-03e8-4719-82ff-c62e6ebe927b","incomingCitationCount":0,"keyword":["Climate and climate change","Hydrology","Agriculture","Environmental risk","drought","flash drought","Standardized Precipitation Index (SPI)","Evaporative Drought Demand Index (EDDI)","Standardized Precipitation Evapotranspiration Index (SPEI)","Standardized Evapotranspiration Deficit Index (SEDI)","Standardized Vapor Pressure Deficit Index (SVPDI)","standardized drought indices","multiscalar"],"keywordsOther":["drought","flash drought","Standardized Precipitation Index (SPI)","Evaporative Drought Demand Index (EDDI)","Standardized Precipitation Evapotranspiration Index (SPEI)","Standardized Evapotranspiration Deficit Index (SEDI)","Standardized Vapor Pressure Deficit Index (SVPDI)","standardized drought indices","multiscalar"],"keywordsTheme":["Climate and climate change","Hydrology","Agriculture","Environmental risk"],"licence":"Open government licence","lineage":"The drought indices were obtained by the standardization of different meteorological variables: precipitation, potential evapotranspiration, climatic water balance, evapotranspiration deficit and vapor pressure deficit.\n\nTwo different methods (\"reference\" and \"best-fit\" approach) were employed to standardize the variables. Reference version of the indices was calculated the probability distribution recommended by previous studies that explored the suitability of different probability distributions to calculate each drought index. By contrast, Best-fit version of the indices was calculated based on the probability distributions that provide better normalised resulting series for each case according to Shapiro-Wilks test.","locations":["POLYGON((-180 -90, -180 90, 180 90, 180 -90, -180 -90))"],"metadataDate":"2026-06-29T18:26:08.000Z","orcid":["https://orcid.org/0000-0002-0696-9504","https://orcid.org/0000-0003-4567-5258","https://orcid.org/0000-0003-2815-7221","https://orcid.org/0000-0002-2913-0664","https://orcid.org/0000-0002-5256-3310"],"organisation":["UK Centre for Ecology & Hydrology","NERC EDS Environmental Information Data Centre"],"publicationDate":"2026-03-31T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/f5ce92b0-03e8-4719-82ff-c62e6ebe927b","10.5285/f5ce92b0-03e8-4719-82ff-c62e6ebe927b","doi:10.5285/f5ce92b0-03e8-4719-82ff-c62e6ebe927b"],"resourceType":"Dataset","rightsHolder":["UK Centre for Ecology & Hydrology"],"ror":["https://ror.org/00pggkr55","https://ror.org/04xw4m193"],"shortenedDescription":"Here, we present the Global Multi-Index Drought (GMID) dataset, which includes some of the most used and widely recommended standardised drought indices: the Standardized Precipitation Index (SPI), the Evaporative Drought Demand Index (EDDI), the Standardized Precipitation…","state":"published","supplementalDescription":["Wang, X., Alharbi, R. S., Baez-Villanueva, O. M., Green, A., McCabe, M. F., Wada, Y., Van Dijk, A. I. J. M.,\nAbid, M. A., & Beck, H. E., (2025). Saudi Rainfall (SaRa): Hourly 0.1° Gridded Rainfall (1979-Present)\nfor Saudi Arabia via Machine Learning Fusion of Satellite and Model Data. Hydrology and Earth\nSystem Sciences 29, 4983-5003.","Miralles, D.G., Bonte, O., Koppa, A., Baez-Villanueva, O.M., Tronquo, E., Zhong, F., Beck, H.E., Hulsman, P., Dorigo, W.A., Verhoest, N.E.C., Haghdoost, S.,  GLEAM4: global land evaporation and soil moisture dataset at 0.1° resolution from 1980 to near present, Scientific Data, 12, 416, 2025","Beck, H. E., van Dijk, A. I. J. M., Larraondo, P. R., McVicar, T. R., Pan, M., Dutra, E., and Miralles, D. G., MSWX: global 3‑hourly 0.1° bias-corrected meteorological data including near real-time updates and forecast ensembles. Bulletin of the American Meteorological Society 103, E710-E732."],"title":"High-resolution Global Multi-Index Drought (GMID) dataset, 1980-2024","topic":["0/Climate and climate change/","0/Hydrology/","0/Agriculture/","0/Environmental risk/"],"version":1.0,"view":["public","dgwr"]},{"authorAffiliation":["University of Hull","Newcastle University","University of Leeds","Liverpool John Moores University","University of Exeter","University of Plymouth","The University of Queensland","University of Manchester","UK Centre for Ecology & Hydrology","University of Glasgow","University of Cagliari"],"authorFamilyName":["Riley","Mayes","Jarvis","Amezaga","Burke","Byrne","Crane","Comber","Gandy","Hudson-Edwards","Jennings","Lewis","Lofts","MacDonald","Malcolm","Onnis","Olszewska","Spears"],"authorFullName":["Riley, A.L.","Mayes, W.M.","Jarvis, A.P.","Amezaga, J.M.","Burke, I.T.","Byrne, P.","Crane, R.A.","Comber, S.D.W.","Gandy, C.J.","Hudson-Edwards, K.A.","Jennings, E.","Lewis, E.","Lofts, S.","MacDonald, J.M.","Malcolm, H.","Onnis, P.","Olszewska, J.","Spears, B."],"authorGivenName":["A. L.","W. M.","A. P.","J. M.","I. T.","P.","R. A.","S. D. W.","C. J.","K. A.","E.","S.","H.","J.","B."],"authorOrcid":["https://orcid.org/0000-0003-3547-3791"],"authorRor":["https://ror.org/04nkhwh30","https://ror.org/01kj2bm70","https://ror.org/024mrxd33","https://ror.org/04zfme737","https://ror.org/03yghzc09","https://ror.org/008n7pv89","https://ror.org/00rqy9422","https://ror.org/00pggkr55","https://ror.org/00vtgdb53","https://ror.org/003109y17"],"availability":"Available","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)"],"description":"This dataset contains the output of a national-scale prioritisation exercise aimed at determining the risks posed by 30,310 legacy waste sites and historical landfill sites to the coastal environment of England and Wales. The analysis was repeated under three future coastal change scenarios (short-, medium-, and long-term), and is sortable based on the overall risk score for each climate scenario.","documentType":"GEMINI_DOCUMENT","familyName":["Riley","Mayes","Jarvis","Amezaga","Burke","Byrne","Crane","Comber","Gandy","Hudson-Edwards","Jennings","Lewis","Lofts","MacDonald","Malcolm","Onnis","Olszewska","Spears"],"fullName":["Adam Jarvis","Riley, A.L.","Mayes, W.M.","Jarvis, A.P.","Amezaga, J.M.","Burke, I.T.","Byrne, P.","Crane, R.A.","Comber, S.D.W.","Gandy, C.J.","Hudson-Edwards, K.A.","Jennings, E.","Lewis, E.","Lofts, S.","MacDonald, J.M.","Malcolm, H.","Onnis, P.","Olszewska, J.","Spears, B."],"funder":["Natural Environment Research Council"],"givenName":["A. L.","W. M.","A. P.","J. M.","I. T.","P.","R. A.","S. D. W.","C. J.","K. A.","E.","S.","H.","J.","B."],"grant":["NE/T003286/1","NE/T003022/1","NE/T002824/1","NE/T003200/1"],"identifier":"2501589d-1a13-4e6e-a25b-b74993c5b758","incomingCitationCount":0,"keyword":["Climate and climate change","Environmental survey","Environmental risk","coast","impact assessment","landfill","landfill leachate","pollution","waste","water quality","geochemistry"],"keywordsOther":["coast","impact assessment","landfill","landfill leachate","pollution","waste","water quality","geochemistry"],"keywordsTheme":["Climate and climate change","Environmental survey","Environmental risk"],"licence":"Non-Open government licence","lineage":"A combination of publicly available and proprietary shapefiles of waste deposits were analysed using GIS methods. Output data were then fed into a prioritisation method based on source-pathway-receptor models. A suite of spatial data has been integrated in order to score potential risks associated with waste type (Source), likelihood of pollutant release relating to current and future flood and erosion climate projections, alongside current management infrastructure (Pathway), and proximity to sensitive ecological features or proxies of human use in coastal areas (Receptors).","locations":["POLYGON((-8.648 49.864, -8.648 60.861, 1.768 60.861, 1.768 49.864, -8.648 49.864))"],"metadataDate":"2026-06-29T18:16:28.000Z","orcid":["https://orcid.org/0000-0003-3547-3791"],"organisation":["Newcastle University","University of Hull","University of Leeds","Liverpool John Moores University","University of Exeter","University of Plymouth","The University of Queensland","University of Manchester","UK Centre for Ecology & Hydrology","University of Glasgow","University of Cagliari","NERC EDS Environmental Information Data Centre"],"publicationDate":"2026-03-19T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/2501589d-1a13-4e6e-a25b-b74993c5b758","10.5285/2501589d-1a13-4e6e-a25b-b74993c5b758","doi:10.5285/2501589d-1a13-4e6e-a25b-b74993c5b758"],"resourceType":"Dataset","rightsHolder":["University of Hull"],"ror":["https://ror.org/01kj2bm70","https://ror.org/04nkhwh30","https://ror.org/024mrxd33","https://ror.org/04zfme737","https://ror.org/03yghzc09","https://ror.org/008n7pv89","https://ror.org/00rqy9422","https://ror.org/00pggkr55","https://ror.org/00vtgdb53","https://ror.org/003109y17","https://ror.org/04xw4m193"],"shortenedDescription":"This dataset contains the output of a national-scale prioritisation exercise aimed at determining the risks posed by 30,310 legacy waste sites and historical landfill sites to the coastal environment of England and Wales. The analysis was repeated under three future…","state":"published","supplementalDescription":["Riley AL, Amezaga J, Burke IT, Byrne P, Cooper N, Crane RA, Comber SDW, Gandy CJ, Hudson-Edwards KA, Jennings E, Lewis E, Lofts S, MacDonald JM, Malcolm H, Mayes WM, Onnis P, Olszewska J, Spears B and Jarvis AP (2022) Incorporating conceptual site models into national-scale environmental risk assessments for legacy waste in the coastal zone. Front. Environ. Sci. 10:1045482. doi: 10.3389/fenvs.2022.1045482"],"title":"List of legacy waste deposits (including historical landfill sites) across England and Wales, ranked by environmental risk to the coastal environment under future climate scenarios","topic":["0/Climate and climate change/","0/Environmental survey/","0/Environmental risk/"],"version":1.0,"view":["public","katwri"]},{"authorAffiliation":["University of Aberdeen","Sun Yat-Sen University","University of Manchester","The James Hutton Institute","University of Salford","University of York","The University of Hong Kong"],"authorFamilyName":["Burslem","Liu","Johnson","Taylor","Helgason","Chen","Liang"],"authorFullName":["Burslem, D.","Liu, X.","Johnson, D.","Taylor, A.","Taylor, J.","Helgason, T.","Chen, Y.","Liang, M."],"authorGivenName":["David","X.","D.","A.","J.","T.","Y.","M."],"authorOrcid":["https://orcid.org/0000-0001-6033-0990","https://orcid.org/0000-0002-4705-0975"],"authorRor":["https://ror.org/016476m91","https://ror.org/0064kty71","https://ror.org/027m9bs27","https://ror.org/03rzp5127","https://ror.org/01tmqtf75","https://ror.org/04m01e293","https://ror.org/02zhqgq86"],"availability":"Available","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)"],"description":"This dataset reports metrics of plant growth, including height, total biomass and the biomass of component plant parts, and percentage root colonisation by mycorrhizas, for tree seedlings of eight tropical and seven subtropical growing in pots of soil that had been amended by addition of various sources of phosphorus (inorganic phosphate, adenosine monophosphate, phytic, or a mixture of all three) plus an unfertilized control treatment with no P additions. The aim of the experiment was to test the hypothesis that seedlings of species that associate with different types of root-inhabiting mycorrhizal fungi would respond differently to the range of P sources applied in the experiment. \n\nThe experiments were conducted as part of a NERC Discovery Science project with the title Explaining niche separation in tropical forests: feedbacks from root-fungal symbioses and soil phosphorus partitioning led by Professor David Burslem (University of Aberdeen) reference NE/M004848/1.","documentType":"GEMINI_DOCUMENT","familyName":["Burslem","Liu","Johnson","Taylor","Helgason","Chen","Liang"],"fullName":["Burslem, D.","Liu, X.","Johnson, D.","Taylor, A.","Taylor, J.","Helgason, T.","Chen, Y.","Liang, M."],"funder":["Natural Environment Research Council"],"givenName":["David","X.","D.","A.","J.","T.","Y.","M."],"grant":["NE/M004864/1"],"identifier":"3ad644c9-e341-4a15-ab35-311076defc33","incomingCitationCount":1,"keyword":["Environmental risk","Soil","phosphorus","tree biomass","mycorrhiza"],"keywordsOther":["phosphorus","tree biomass","mycorrhiza"],"keywordsTheme":["Environmental risk","Soil"],"licence":"Open government licence","lineage":"The experiments were conducted by Xubing Liu with input from all authors. Data quality checks were conducted by all authors. The data-set provides raw data on growth metrics for each seedling, plus identifying codes for the two sites where the experiment was conducted, reflecting the tropical and subtropical origin of the seedlings, as well as experimental block, P treatment, botanical names for the tree species, and mycorrhizal type. Full details of materials and methods are provided in the paper reporting the results of the study (doi: 10.1111/ele.12939).","locations":["POLYGON((111.53 5, 111.53 23.27, 117.57 23.27, 117.57 5, 111.53 5))"],"metadataDate":"2026-06-29T16:27:06.000Z","orcid":["https://orcid.org/0000-0001-6033-0990","https://orcid.org/0000-0002-4705-0975"],"organisation":["University of Aberdeen","Sun Yat-Sen University","University of Manchester","The James Hutton Institute","University of Salford","University of York","The University of Hong Kong","NERC EDS Environmental Information Data Centre","NERC Environmental Information Data Centre"],"publicationDate":"2019-09-30T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/3ad644c9-e341-4a15-ab35-311076defc33","10.5285/3ad644c9-e341-4a15-ab35-311076defc33","doi:10.5285/3ad644c9-e341-4a15-ab35-311076defc33"],"resourceType":"Dataset","ror":["https://ror.org/016476m91","https://ror.org/0064kty71","https://ror.org/027m9bs27","https://ror.org/03rzp5127","https://ror.org/01tmqtf75","https://ror.org/04m01e293","https://ror.org/02zhqgq86","https://ror.org/04xw4m193"],"shortenedDescription":"This dataset reports metrics of plant growth, including height, total biomass and the biomass of component plant parts, and percentage root colonisation by mycorrhizas, for tree seedlings of eight tropical and seven subtropical growing in pots of soil that had been…","state":"published","title":"Growth, biomass allocation and tissue nutrient concentrations of subtropical and tropical tree seedlings in response to experimental manipulation of soil phosphorus pools","topic":["0/Environmental risk/","0/Soil/"],"version":1.0,"view":["public","clwe"]},{"authorAffiliation":["University of Stirling"],"authorFamilyName":["Ormsby","Woodford","White","Fellows","Oliver","Quilliam"],"authorFullName":["Ormsby, M.","Woodford, L.","White, H.","Fellows, R.","Oliver, D.","Quilliam, R."],"authorGivenName":["Michael","Luke","Hannah","Rosie","David","Richard"],"authorOrcid":["https://orcid.org/0000-0002-3991-2336","https://orcid.org/0000-0003-2530-2120","https://orcid.org/0009-0003-8928-2189","https://orcid.org/0000-0002-6200-562X","https://orcid.org/0000-0001-7020-4410"],"authorRor":["https://ror.org/045wgfr59"],"availability":"Available","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)"],"description":"This dataset contains information relating to the survival and persistence of clinically relevant strains of toxigenic Vibrio cholerae on plastic and vegetation, under environmentally relevant conditions. The data encompass bacterial strain identity, material type, timepoints (days), bacterial concentration (CFU/ml) and survival percentages. Data were sampled over a 28-day period using culture-based approaches; and the ability of isolates to cause disease following their recovery was determined through the use of a Galleria mellonella model. The ability of isolates to persist on materials, dissociate from materials into water bodies, and recolonise materials was also determined.\n\nThis work was supported by the UKRI Natural Environment Research Council (NERC) as part of the GCRF SPACES project [grant number NE/V005847/1] and the Plastic Vectors project, “Microbial hitch-hikers of marine plastics: the survival, persistence & ecology of microbial communities in the ‘Plastisphere’” [grant number NE/S005196/1].","documentType":"GEMINI_DOCUMENT","familyName":["Ormsby","Woodford","White","Fellows","Oliver","Quilliam"],"fullName":["Michael Ormsby","Ormsby, M.","Woodford, L.","White, H.","Fellows, R.","Oliver, D.","Quilliam, R."],"funder":["Natural Environment Research Council"],"givenName":["Michael ","Michael","Luke","Hannah","Rosie","David","Richard"],"grant":["NE/V005847/1","NE/S005196/1"],"identifier":"b9bfdb6f-5e5e-496f-bf0c-bb9931f6046b","incomingCitationCount":0,"keyword":["Environmental risk","Climate and climate change","Water quality","Biofilm","Human Pathogens","Plastic Pollution","Plastisphere","Public Health"],"keywordsOther":["Biofilm","Human Pathogens","Plastic Pollution","Plastisphere","Public Health"],"keywordsTheme":["Environmental risk","Climate and climate change","Water quality"],"licence":"Open government licence","lineage":"Data were generated through laboratory experiments investigating the persistence, virulence, and survival of clinically relevant strains of toxigenic Vibrio cholerae. Bacteria were cultured on materials (Polyethylene [PE], polypropylene [PP] and banana leaf [BL]) and analysed for persistence over time (up to 28 days) and virulence using Galleria mellonella larvae. Materials (PE, PP and BL) were prepared and inoculated under controlled laboratory conditions. V. cholerae strains were inoculated onto materials in nutrient-rich and surface water environments. Sampling was taken at defined time points (7, 14, 21, 28 days). G. mellonella larvae were used to evaluate virulence, and survival was assessed over 72 h. The experiments utilised standard laboratory equipment such as 96-well plates and incubators. G. mellonella larvae were sourced from a local supplier and used within one week of delivery. Instrumentation used for bacterial enumeration, including the plate reader, was calibrated according to standard laboratory protocols. The data underwent rigorous quality control through replication (biological triplicates), statistical analysis (ANOVA), and controlled experimental conditions (e.g., temperature and material consistency). Statistical methods including ANOVA and Tukey’s post-hoc tests were applied to assess treatment effects and survival outcomes.\n","metadataDate":"2026-06-29T16:46:44.000Z","orcid":["https://orcid.org/0000-0002-3991-2336","https://orcid.org/0000-0003-2530-2120","https://orcid.org/0009-0003-8928-2189","https://orcid.org/0000-0002-6200-562X","https://orcid.org/0000-0001-7020-4410"],"organisation":["University of Stirling","NERC EDS Environmental Information Data Centre"],"publicationDate":"2025-06-12T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/b9bfdb6f-5e5e-496f-bf0c-bb9931f6046b","10.5285/b9bfdb6f-5e5e-496f-bf0c-bb9931f6046b","doi:10.5285/b9bfdb6f-5e5e-496f-bf0c-bb9931f6046b"],"resourceType":"Non-geographic dataset","rightsHolder":["University of Stirling"],"ror":["https://ror.org/045wgfr59","https://ror.org/04xw4m193"],"shortenedDescription":"This dataset contains information relating to the survival and persistence of clinically relevant strains of toxigenic Vibrio cholerae on plastic and vegetation, under environmentally relevant conditions. The data encompass bacterial strain identity, material type,…","state":"published","title":"Survival and persistence of clinically relevant strains of toxigenic Vibrio cholerae on plastic and vegetation, under environmentally relevant conditions","topic":["0/Environmental risk/","0/Climate and climate change/","0/Water quality/"],"version":1.0,"view":["public","clwe"]},{"authorAffiliation":["Centre for Ecology & Hydrology","Centre for Environment, Fisheries & Aquaculture Science"],"authorFamilyName":["Pottinger","Cook","Matthiessen"],"authorFullName":["Pottinger, T.G.","Cook, A.","Matthiessen, P."],"authorGivenName":["T.G.","A.","P."],"authorOrcid":["https://orcid.org/0000-0001-7661-9369"],"authorRor":["https://ror.org/00pggkr55"],"availability":"Available","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)"],"description":"This dataset comprises characteristics of three-spined stickleback fish including length, weight, sex, condition factor (K-factor), cortisol and glucose concentration, RNA:DNA ratio and ethoxyresorufin-O-deethylase activity normalised to liver homogenate protein concentration.  These data were collected by the Centre for Ecology & Hydrology from three-spined sticklebacks (Gasterosteus aculeatus L.) captured in the River Ray (south west England) at sites downstream of an urban waste water treatment works (Rodborne WWTW) prior to (2005-2007), and following (2008), remediation of the WWTW effluent with granular activated carbon (GAC) tertiary treatment. During the same period fish were also sampled from neighbouring reference rivers (R. Ock, Childrey Brook). ","documentType":"GEMINI_DOCUMENT","familyName":["Pottinger","Cook","Matthiessen"],"fullName":["Pottinger, T.G.","Cook, A.","Matthiessen, P."],"givenName":["T. G.","T.G.","A.","P."],"identifier":"3322cccd-95fe-4cc9-baf8-48cddd03433d","incomingCitationCount":0,"keyword":["River Ray","South West","River Ock","Childrey Brook","EDCAT","Water quality","Environmental risk","Environmental survey","Pollution","Gasterosteus aculeatus L."],"keywordsOther":["Gasterosteus aculeatus L."],"keywordsPlace":["River Ray","South West","River Ock","Childrey Brook"],"keywordsProject":["EDCAT"],"keywordsTheme":["Water quality","Environmental risk","Environmental survey","Pollution"],"licence":"Open government licence","lineage":"The fish were captured with a hand net, then processed and analysed at the Centre for Ecology & Hydrology, Lancaster.  See supporting documentation for further information.","locations":["POLYGON((-2.006 51.433, -2.006 51.649, -1.524 51.649, -1.524 51.433, -2.006 51.433))"],"metadataDate":"2026-06-29T16:09:08.000Z","orcid":["https://orcid.org/0000-0001-7661-9369"],"organisation":["UK Centre for Ecology & Hydrology","Centre for Ecology & Hydrology","Centre for Environment, Fisheries & Aquaculture Science","NERC EDS Environmental Information Data Centre","NERC Environmental Information Data Centre"],"publicationDate":"2017-05-26T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/3322cccd-95fe-4cc9-baf8-48cddd03433d","10.5285/3322cccd-95fe-4cc9-baf8-48cddd03433d","doi:10.5285/3322cccd-95fe-4cc9-baf8-48cddd03433d"],"resourceType":"Dataset","rightsHolder":["UK Centre for Ecology & Hydrology"],"ror":["https://ror.org/00pggkr55","https://ror.org/04xw4m193"],"shortenedDescription":"This dataset comprises characteristics of three-spined stickleback fish including length, weight, sex, condition factor (K-factor), cortisol and glucose concentration, RNA:DNA ratio and ethoxyresorufin-O-deethylase activity normalised to liver homogenate protein concentration.…","state":"published","title":"Somatic and physiological data for three-spined sticklebacks, 2005-2008 [Endocrine Disruption in Catchments (EDCAT)]","topic":["0/Water quality/","0/Environmental risk/","0/Environmental survey/","0/Pollution/"],"version":1.0,"view":["public","clamw"]},{"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":["https://orcid.org/0000-0002-1516-6834","https://orcid.org/0000-0003-1142-4039","https://orcid.org/0000-0001-9294-5826","https://orcid.org/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. NERC-Environmental Information Data Centre https://doi.org/10.5285/f1cd5e33-2633-4304-bbc2-b8d34711d902","locations":["POLYGON((-7.557 49.766, -7.557 61.026, 3.5540000000000003 61.026, 3.5540000000000003 49.766, -7.557 49.766))"],"metadataDate":"2026-06-27T19:01:34.000Z","orcid":["https://orcid.org/0000-0002-1516-6834","https://orcid.org/0000-0003-1142-4039","https://orcid.org/0000-0001-9294-5826","https://orcid.org/0000-0002-5256-3310"],"organisation":["UK Centre for Ecology & Hydrology","Centre for Ecology & Hydrology","NERC Environmental Information Data Centre","NERC EDS Environmental Information Data Centre"],"publicationDate":"2015-05-22T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["1432105852978","CEH:EIDC::1432105852978","https://catalogue.ceh.ac.uk/id/dfd59438-2170-4472-b810-bab33a83d09f","10.5285/dfd59438-2170-4472-b810-bab33a83d09f","doi:10.5285/dfd59438-2170-4472-b810-bab33a83d09f"],"resourceType":"Dataset","ror":["https://ror.org/00pggkr55","https://ror.org/04xw4m193"],"shortenedDescription":"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…","state":"published","supplementalName":["CEH droughts portal"],"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":["Bangor University"],"authorFamilyName":["Graf","Chadwick","Jones"],"authorFullName":["Graf, M.","Chadwick, D.R.","Jones, D.L."],"authorGivenName":["Martine","David R","Davey L"],"authorOrcid":["https://orcid.org/0000-0001-7994-0529"],"authorRor":["https://ror.org/006jb1a24"],"availability":"Available","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)"],"description":"This dataset comprises observations from treatments comparing conventional (LDPE) and biodegradable (PLA/PBAT) plastic mulch films in both new and field-weathered conditions. The dataset was generated from a controlled mesocosm experiment designed by researchers to investigate the effects of plastic mulch films on soil and plant systems. The data were collected during the experimental period and include measurements of soil properties, plant growth, nitrogen dynamics, greenhouse gas emissions, and microbial activity.\nPlastic materials were applied to soil at three concentrations (0.05%, 0.5%, and 1.5% w/w) and as realistic size mixtures of macro-, meso-, and microplastic fractions (1:1:1). The experiment was conducted using radish (Raphanus sativus L.) grown under controlled mesocosm conditions.\nData were collected through a combination of soil sampling, plant measurements, and laboratory analyses. These include soil physicochemical properties (e.g. bulk density, moisture), plant biomass and nutrient uptake (including ¹⁵N fertiliser partitioning), greenhouse gas emissions (e.g. N₂O, CO₂), and indicators of microbial activity. The dataset captures responses across different plastic types, degradation states, and concentrations, providing a structured comparison of their effects under controlled conditions.\nFurther methodological details and experimental procedures are provided in the lineage field and the supporting documentation.","documentType":"GEMINI_DOCUMENT","familyName":["Graf","Chadwick","Jones"],"fullName":["Graf, M.","Chadwick, D.R.","Jones, D.L."],"funder":["Natural Environment Research Council"],"givenName":["M.","Martine","David R","Davey L"],"grant":["NE/V005871/1"],"identifier":"c2d4f068-e6bb-4613-8c43-e96b0aae25e8","incomingCitationCount":0,"keyword":["Agriculture","Environmental risk","Soil","agricultural pollution","crop production","mulch","plastic","pollution","soil"],"keywordsOther":["agricultural pollution","crop production","mulch","plastic","pollution","soil"],"keywordsTheme":["Agriculture","Environmental risk","Soil"],"licence":"Open government licence","lineage":"Plant:\n-\tBiomass (root, bulb, shoot): Dry biomass weighed on 2-decimal scale. Data recorded in paper notebook, transferred to Excel file, exported as csv.\n-\tHeight: Measured using measuring tape. Data recorded in paper notebook, transferred to Excel file, exported as csv.\n-\tLeaf chlorophyll content: Recorded using a SPAD meter. Data recorded in paper notebook, transferred to Excel, exported as csv.\n-\tC, N, P, K, S concentration: Measured using CN analyser and TXRF spectroscopy. Data exported as Excel file, exported as csv.\n-\t15N retention: Measured using CN analyser. Data exported as Excel file, exported as csv.\nSoil:\n-\tpH and electrical conductivity: Measured using standard electrodes in a 1:2.5 soil:distilled water solution. Data recorded in paper notebook, transferred to Excel file, exported as csv.\n-\tNutrients (ammonium, nitrate, phosphate, DOC): Measured using colorimetric methods on a 1:5 soil: 0.5 M K2SO4 (NH4, NO3) or 0.5M acetic acid (PO4) extracts. DOC determined using TOC analyser on a 1:5 0.5M K2SO4 extract. Data exported as Excel files, exported as csv.\n-\tCumulative N2O emissions: Data analysed using gas chromatography, exported as Excel file, exported as csv.\n-\tCumulative 14CO2 respiration: Analysed using scintillation counter, data exported as Excel file, exported as csv.\n-\tC, N, P, K, S concentration: Measured using CN analyser and TXRF spectroscopy. Data exported as Excel file, exported as csv.\n-\t15N retention: Measured using CN analyser. Data exported as Excel file, exported as csv.\nPlastic:\n-\tFTIR spectra: Measured using ATR-FTIR spectroscopy. Data exported as csv.","locations":["POLYGON((-4.019 53.236, -4.019 53.241, -4.011 53.241, -4.011 53.236, -4.019 53.236))"],"metadataDate":"2026-06-29T16:36:29.000Z","orcid":["https://orcid.org/0000-0001-7994-0529"],"organisation":["Bangor University","NERC EDS Environmental Information Data Centre"],"publicationDate":"2026-05-06T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/c2d4f068-e6bb-4613-8c43-e96b0aae25e8","10.5285/c2d4f068-e6bb-4613-8c43-e96b0aae25e8","doi:10.5285/c2d4f068-e6bb-4613-8c43-e96b0aae25e8"],"resourceType":"Dataset","rightsHolder":["Bangor University"],"ror":["https://ror.org/006jb1a24","https://ror.org/04xw4m193"],"shortenedDescription":"This dataset comprises observations from treatments comparing conventional (LDPE) and biodegradable (PLA/PBAT) plastic mulch films in both new and field-weathered conditions. The dataset was generated from a controlled mesocosm experiment designed by researchers to…","state":"published","title":"Soil and plant properties in a mesocosm experiment exposed to both new and aged plastic mulch film","topic":["0/Agriculture/","0/Environmental risk/","0/Soil/"],"version":1.0,"view":["public","tinzha"]},{"authorAffiliation":["Centre for Ecology & Hydrology"],"authorFamilyName":["Hewitt"],"authorFullName":["Hewitt, D."],"authorGivenName":["D."],"authorOrcid":["https://orcid.org/0000-0001-8297-0294"],"authorRor":["https://ror.org/00pggkr55"],"availability":"Available","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)"],"description":"The data are biomass and ozone-injury data for white clover (Trifolium repens). Dataset concerns a 2014 study on the effects of Jasmonic acid/cutting in modulating the response of clover to ozone. A short-term (4-week) ozone-exposure experiment was conducted in 2014 to investigate the interactive effects of cutting on ozone-induced responses in white clover (Trifolium repens). A strong interaction was found in root biomass and root nodule biomass in cut white clover plants in a high ozone background (45-67 parts per billion (ppb) treatment mean), suggesting ozone-impacts on root nodule biomass occur through limitation of carbon availability. The work was carried out as part of a NERC funded PhD.","documentType":"GEMINI_DOCUMENT","familyName":["Mills","Hewitt"],"fullName":["Mills, G.","Hewitt, D."],"givenName":["Gina","D."],"identifier":"10c6df00-c7ef-444b-951f-33a2c0072bec","incomingCitationCount":0,"keyword":["Abergwyngregyn","Environmental risk","Pollution","Trifolium repens","Jasmonic acid"],"keywordsOther":["Trifolium repens","Jasmonic acid"],"keywordsPlace":["Abergwyngregyn"],"keywordsTheme":["Environmental risk","Pollution"],"licence":"Open government licence","lineage":"A short-term (four-week) ozone-exposure experiment was conducted in 2014 to investigate the interactive effects of cutting on ozone-induced responses in white clover (Trifolium repens). Seedlings were propagated in early Spring 2014. After three weeks, to introduce a soil microbe, pots were inoculated with a soil slurry mixture. Pots were then divided between 3 treatments: uncut pots (controls), with a single cut to four centimetre (cm)m height immediately prior to ozone exposure and uncut, with a weekly application of Methyl-Jasmonate solution during the experiment. The seedlings were grown on for four weeks then exposed to random ozone profiles for four weeks. \nA representative quarter of each pot was selected and recordings of healthy, injured or senesced leaves made on in weeks 2, 3 and 4. The harvest of above and below-ground biomass was performed after four weeks on each pot. Shoot biomass, and root biomass from a representative quarter of the pot, were dried for a minimum of 48 hours at 60 degrees Celsius. Root nodule biomass was also excised from the root system, and was air dried, sized and weighed. Root biomass, nodule mass and nodule numbers per pot were calculated. Leaf area index (LAI) of undamaged leaves was determined from dried forage. Mean injury and senescence data across the recordings was determined for each pot, and was arcsine transformed prior to analysis. Injury and senescence data, and selected biomass data, were then analysed by analysis of variance (ANOVA), with ozone background and treatment applied as factors. \n\nPost-hoc Tukey's honest significant difference tests were used to determine the significance of factors where appropriate. Relationships between total root nodule biomass and biomass, and raw injury parameters for each treatment were also investigated via Pearson's correlation analysis. All analyses were conducted in R Software (version 3.1.2).  \n\nData was first recorded in the field in field notebooks, and was then transferred to electronic copies (MS Excel worksheets). Data was then exported as .csv files for ingestion into the Environmental Information Data Centre.","locations":["POLYGON((-4.018 53.237, -4.018 53.239, -4.016 53.239, -4.016 53.237, -4.018 53.237))"],"metadataDate":"2026-06-29T17:08:44.000Z","orcid":["https://orcid.org/0000-0001-8297-0294"],"organisation":["UK Centre for Ecology & Hydrology","Centre for Ecology & Hydrology","NERC Environmental Information Data Centre","NERC EDS Environmental Information Data Centre"],"publicationDate":"2017-04-21T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/10c6df00-c7ef-444b-951f-33a2c0072bec","10.5285/10c6df00-c7ef-444b-951f-33a2c0072bec","doi:10.5285/10c6df00-c7ef-444b-951f-33a2c0072bec"],"resourceType":"Dataset","rightsHolder":["UK Centre for Ecology & Hydrology"],"ror":["https://ror.org/00pggkr55","https://ror.org/04xw4m193"],"shortenedDescription":"The data are biomass and ozone-injury data for white clover (Trifolium repens). Dataset concerns a 2014 study on the effects of Jasmonic acid/cutting in modulating the response of clover to ozone. A short-term (4-week) ozone-exposure experiment was conducted in 2014…","state":"published","title":"Influence of Jasmonic acid on the response of pasture to ozone","topic":["0/Environmental risk/","0/Pollution/"],"version":1.0,"view":["public","danor"]},{"authorAffiliation":["University of Leeds","APEM Limited"],"authorFamilyName":["Shannon","Stebbing","Quinn","Warren","Dunn"],"authorFullName":["Shannon, C.F.","Stebbing, P.D.","Quinn, C.H.","Warren, D.A.","Dunn, A.M."],"authorGivenName":["C.F.","P.D.","C.H.","D.A.","A.M."],"authorOrcid":["https://orcid.org/0000-0001-9718-2899","https://orcid.org/0000-0001-7189-4409","https://orcid.org/0000-0002-2085-0446","https://orcid.org/0000-0002-2073-7857","https://orcid.org/0000-0002-4855-1077"],"authorRor":["https://ror.org/024mrxd33"],"availability":"Available","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)"],"description":"This data contains the results of student and professional perceptions surveys conducted in the UK before and after e-Learning training, as part of a project to determine the effectiveness of e-Learning as a training tool. The dataset include two surveys; before and after e-Learning training. Students and professionals were given two separate surveys which were combined to create one dataset. The surveys were collected between September 2015 and July 2018.\n\nThe objective of the survey was to collect data on participants’ awareness, risk perceptions and self-reported behaviours on biosecurity for invasive species. The topics on both the before and after survey included age, role at institution, field of work/study, field activity environments, cleaning methods for equipment, outerwear/footwear and transport and awareness and perceptions of risk around invasive species and biosecurity campaigns. The data does not include the aggregated cleaning scores that were used for the analysis nor has it excluded any participants that were not used in the final data analysis. The dataset has been anonymised by removing names of respondents, email addresses, departments or organisations worked for or studied in, and text responses which could have made the participant identifiable.\n\nThe research was funded by NERC project no NE/N008391/1.","documentType":"GEMINI_DOCUMENT","familyName":["Shannon","Stebbing","Quinn","Warren","Dunn"],"fullName":["Shannon, C.","Shannon, C.F.","Stebbing, P.D.","Quinn, C.H.","Warren, D.A.","Dunn, A.M."],"funder":["Natural Environment Research Council"],"givenName":["Caitriona","C.F.","P.D.","C.H.","D.A.","A.M."],"grant":["NE/N008391/1"],"identifier":"ac271791-b722-489c-9b68-b37316ec826c","incomingCitationCount":0,"keyword":["Invasive species","Environmental risk","opinion survey"],"keywordsOther":["opinion survey"],"keywordsTheme":["Invasive species","Environmental risk"],"licence":"Open government licence","lineage":"All data was collected online using Online Surveys. Information of each survey is detailed in the supporting information. Both the before training and after training surveys took less than 10 minutes to complete. The number of the respondents in the before training survey was 804, and the number of respondents in the post training survey was 79. The spreadsheet has been converted to a CSV file. ","metadataDate":"2026-06-29T18:19:46.000Z","orcid":["https://orcid.org/0000-0001-9718-2899","https://orcid.org/0000-0001-7189-4409","https://orcid.org/0000-0002-2085-0446","https://orcid.org/0000-0002-2073-7857","https://orcid.org/0000-0002-4855-1077"],"organisation":["University of Leeds","APEM Limited","NERC EDS Environmental Information Data Centre","NERC Environmental Information Data Centre"],"publicationDate":"2020-01-24T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/ac271791-b722-489c-9b68-b37316ec826c","10.5285/ac271791-b722-489c-9b68-b37316ec826c","doi:10.5285/ac271791-b722-489c-9b68-b37316ec826c"],"resourceType":"Non-geographic dataset","rightsHolder":["University of Leeds"],"ror":["https://ror.org/024mrxd33","https://ror.org/04xw4m193"],"shortenedDescription":"This data contains the results of student and professional perceptions surveys conducted in the UK before and after e-Learning training, as part of a project to determine the effectiveness of e-Learning as a training tool. The dataset include two surveys; before and…","state":"published","title":"UK public perceptions around invasive species and biosecurity before and one year after undertaking e-Learning, 2015-2018","topic":["0/Invasive species/","0/Environmental risk/"],"version":1.0,"view":["public","clwe"]},{"authorAffiliation":["Anofa Engineering, Planning and Informatics Ltd.","National Society for Earthquake Technology","University College London","Gebze Technical University","An-Najah National University","Ardhi University","Africa Research and Impact Network","Chittagong University of Engineering & Technology","Centro de Informacion Urbana de Quito"],"authorFamilyName":["Menteşe","Özer","Rawal","Comelli","Cetin","Dabeek","Kyesii","Chengo","Zisan","Cubillo"],"authorFullName":["Menteşe, E.Y.","Özer, E.","Rawal, P.","Comelli, T.","Cetin, N.İ.","Dabeek, J.","Kyesii, A.","Chengo, V.","Zisan, B.","Cubillo, P."],"authorGivenName":["E.Y.","E.","P.","T.","N.İ.","J.","A.","V.","B."],"authorOrcid":["https://orcid.org/0000-0002-7187-4384","https://orcid.org/0000-0003-3484-4183","https://orcid.org/0000-0001-7940-8014","https://orcid.org/0000-0003-3173-2602","https://orcid.org/0000-0002-8141-8112","https://orcid.org/0000-0001-8369-4105","https://orcid.org/0000-0002-7058-5070","https://orcid.org/0000-0001-5116-5874","https://orcid.org/0000-0002-6959-0235","https://orcid.org/0009-0009-6117-9466"],"authorRor":["https://ror.org/058m30p27","https://ror.org/02jx3x895","https://ror.org/01sdnnq10","https://ror.org/0046mja08","https://ror.org/05k903r09","https://ror.org/052qsay17"],"availability":"Available","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)","json","GeoJSON","qmd"],"description":"This dataset includes synthetically produced data from 10 different cities (Istanbul, Nablus, Chattogram, Cox’s Bazaar, Nairobi, Nakuru, Quito, Kokhana, Rapti and Darussalam) for a future urban context. The data includes physical elements in a city such as buildings, roads, and power networks, as well as social elements such as households and individuals. The dataset contains a maximum of 9 different data types, described below. For some cities power and road network data were not considered due to context specific priorities. \n\nlanduse: The land use plan data depicting how the land will be zoned and used in the next fifty years within the area or interest. The attributes include the land use type, areal coverage in hectares, maximum population density and existing population. \n\nbuilding: Data representing the building footprints that will emerge as a result of the future exposure generation procedure. It includes the attributes of the building such as its identifier number, construction type, number of floors, footprint area, occupation type and construction code level.\n\nroad nodes: Data representing the points where road segments (edges) are connected to each other, including the identifier number for each node.\n\nroad edges: Data representing the road segments, including the ID numbers of the starting and ending point (node).\n\npower nodes: Data representing the points where power lines (edges) are connected to each other, including the identifier number for each node.\n\npower edges: Data representing the power segments, including the including the ID numbers of the starting and ending point (node).\n\nhousehold: Data that contains social attributes of a household living in a building. The attributes include number of individuals, income level and commonly used facility ID (such as hospital). \n\nindividual: Data that contains the attributes of the individuals that are a part of a household. The attributes are age, gender, school ID (if relevant), workplace ID (if relevant) and last attained education level.\n\nDistribution table: The future projections for each city that identifies the socio-demographic changes and expected physical development in the next 50 years.\n\nThe data can be used in geospatial platforms. The nomenclature for the data is as follows:\n“CitynameFutureExposureDataset/Cityname_CommunityCode_DataType”. This dataset was created as case studies for the Tomorrows Cities: Tomorrowville virtual testbed. It is supported by NERC as part of the GCRF Urban Disaster Risk Hub (NE/S009000/1).","documentType":"GEMINI_DOCUMENT","familyName":["Menteşe","Özer","Rawal","Comelli","Cetin","Dabeek","Kyesii","Chengo","Zisan","Cubillo"],"fullName":["Menteşe, E.Y.","Özer, E.","Rawal, P.","Comelli, T.","Cetin, N.İ.","Dabeek, J.","Kyesii, A.","Chengo, V.","Zisan, B.","Cubillo, P."],"funder":["Natural Environment Research Council"],"givenName":["E.Y.","E.","P.","T.","N.İ.","J.","A.","V.","B."],"grant":["NE/S009000/1"],"identifier":"cdfea06f-d47c-4967-99d4-cc71bddea45d","incomingCitationCount":0,"keyword":["Environmental risk","Future","risk exposure","exposure","hazard","urban","Tomorrow's cities","GCRF Urban Disaster Risk Hub"],"keywordsOther":["Future","risk exposure","exposure","hazard","urban","Tomorrow's cities","GCRF Urban Disaster Risk Hub"],"keywordsTheme":["Environmental risk"],"licence":"Open government licence","lineage":"For generating the future exposure dataset for each city, a specific computational algorithm that takes into account the land use plan and user defined future projections is used. The algorithm is explained in detail by Mentese et al., 2023.\n\nThe production of the land use plan relies on a community based process, that includes different community groups’ involvement and participatory engagement. In these engagements, in each city, specific groups are identified with the guidance of local experts as part of the Tomorrow’s Cities Project. After the identification, experts from Tomorrow’s Cities Project, local experts and community representatives from the community groups gather for participatory spatial planning for their future urban contexts.\n\nThen, the produced land use plan is integrated (using the software algorithm) with the future socio-demographic projections and expected physical development defined by the local experts and existing literature on the context. As a result of this procedures, building data, socio-demographic datasets and network related data (where relevant) is produced.\n","locations":["POLYGON((-82.267 -13.582, -82.267 44.214, 77.696 44.214, 77.696 -13.582, -82.267 -13.582))"],"metadataDate":"2026-06-29T16:22:16.000Z","orcid":["https://orcid.org/0000-0002-7187-4384","https://orcid.org/0000-0003-3484-4183","https://orcid.org/0000-0001-7940-8014","https://orcid.org/0000-0003-3173-2602","https://orcid.org/0000-0002-8141-8112","https://orcid.org/0000-0001-8369-4105","https://orcid.org/0000-0002-7058-5070","https://orcid.org/0000-0001-5116-5874","https://orcid.org/0000-0002-6959-0235","https://orcid.org/0009-0009-6117-9466"],"organisation":["Anofa Engineering, Planning and Informatics Ltd.","National Society for Earthquake Technology","University College London","Gebze Technical University","An-Najah National University","Ardhi University","Africa Research and Impact Network","Chittagong University of Engineering & Technology","Centro de Informacion Urbana de Quito","NERC EDS Environmental Information Data Centre","University of Edinburgh"],"publicationDate":"2025-08-20T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/cdfea06f-d47c-4967-99d4-cc71bddea45d","10.5285/cdfea06f-d47c-4967-99d4-cc71bddea45d","doi:10.5285/cdfea06f-d47c-4967-99d4-cc71bddea45d"],"resourceType":"Dataset","rightsHolder":["University of Edinburgh"],"ror":["https://ror.org/058m30p27","https://ror.org/02jx3x895","https://ror.org/01sdnnq10","https://ror.org/0046mja08","https://ror.org/05k903r09","https://ror.org/052qsay17","https://ror.org/04xw4m193","https://ror.org/01nrxwf90"],"shortenedDescription":"This dataset includes synthetically produced data from 10 different cities (Istanbul, Nablus, Chattogram, Cox’s Bazaar, Nairobi, Nakuru, Quito, Kokhana, Rapti and Darussalam) for a future urban context. The data includes physical elements in a city such as buildings,…","state":"published","supplementalDescription":["Menteşe, E. Y., Cremen, G., Gentile, R., Galasso, C., Filippi, M. E., & McCloskey, J. (2023). Future exposure modelling for risk-informed decision making in urban planning. International Journal of Disaster Risk Reduction, 90, 103651."],"title":"Exposure datasets representing a synthetic future urban context, including socio-demographic, building, and land-use data from 10 cities, for natural hazard risk modelling","topic":["0/Environmental risk/"],"version":1.0,"view":["public","jashun"]},{"authorAffiliation":["Swansea University","US Forest Service"],"authorFamilyName":["Laino","Cabo","Parsons","Hudak","Doerr","Santin"],"authorFullName":["Laino, D.","Cabo, C.","Parsons, R.A.","Hudak, A.T.","Doerr, S.","Santin, C."],"authorGivenName":["D.","C.","R.A.","A.T.","S"],"authorOrcid":["https://orcid.org/0000-0002-7106-0559","https://orcid.org/0000-0002-0387-9052","https://orcid.org/0000-0001-5091-8993","https://orcid.org/0000-0001-7480-1458","https://orcid.org/0000-0002-8700-9002","https://orcid.org/0000-0001-9901-2658"],"authorRor":["https://ror.org/053fq8t95","https://ror.org/03zmjc935"],"availability":"Available","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)","OUT","PRT5","S3D","SF","BND","GBND","Q","SMV","SZ","TXT"],"description":"This dataset contains outputs of wildfire simulations in Fire Dynamics Simulator (FDS) in forest environments. It includes three simulations, each representing different simulation parameters. The forest plot used for the simulations consists of a 40 x 40 m Pinus ponderosa plot scanned with a Riegl-VZ400i in Sycan Marsh, Oregon, USA, during the summer of 2019. The inputs of the simulations are available at Cabo et al., 2025 https://doi.org/10.5285/467a735f-b03c-4c30-8781-82f0e11aec28 . These simulations serve as an example on how ground-based LiDAR data can be used to run 3D-spatially explicit wildfire simulations.\n\nThe dataset includes CSV files containing the numeric results of the simulations; OUT, TXT, and INI files containing the specifications of the simulation (software version, date, number of threads, simulation domain, units, etc.); and FDS-specific output files which contain data related to the simulation paramaters : .PRT5 (Part 5 / Particle Files), .S3D(3D Smoke Files), .SF (Slice Files), .BND (Boundary Files), .GBND (Gas/Global Boundary Files), .Q (Plot3D Files), .smv (Smokeview Files), and .SZ (Smokeview Sizing Files).","documentType":"GEMINI_DOCUMENT","familyName":["Laino","Cabo","Parsons","Hudak","Doerr","Santin"],"fullName":["Diego Laino","Laino, D.","Cabo, C.","Parsons, R.A.","Hudak, A.T.","Doerr, S.","Santin, C."],"funder":["Natural Environment Research Council"],"givenName":["D.","C.","R.A.","A.T.","S"],"grant":["NE/T001194/1"],"identifier":"f9180989-6528-404e-8110-e3dcc205a6a1","incomingCitationCount":0,"keyword":["Environmental risk","Modelling","Climate and climate change","wildfire","forestry","computational fluid dynamics models","FDS","LiDAR"],"keywordsOther":["wildfire","forestry","computational fluid dynamics models","FDS","LiDAR"],"keywordsTheme":["Environmental risk","Modelling","Climate and climate change"],"licence":"Open government licence","lineage":"One 40x40 m2 plot point cloud was manually labelled into the different fuel layers present in the scene, Each point was labelled into either \"ground\", \"understorey\", \"stem\" or \"canopy\". Each layer was then voxelized at 20 cm for simulations 1 and 2 and 10 cm for simulation 3, and each voxel was assigned a layer-specific averaged bulk density value. Then the voxels were converted into Fire Dynamics Simulator (FDS) BDF input files.\n\nFire Dynamics Simulator (FDS) 6.9.1 was used to run three wildfire simulations. Simulations 1 and 2 were run using 9 MPI processes and took approximately 25 min, whereas simulation 3 was run using 16 and took approximately 68.16 h.\n\nThe simulations were run in April-May 2024 on an MSI laptop equipped with a 13th-generation Intel Core i9-13980HX processor (2.20 GHz) and an NVIDIA RTX 3500 Ada Generation Laptop GPU (12 GB VRAM).","locations":["POLYGON((-121.169 42.84, -121.169 42.857, -121.153 42.857, -121.153 42.84, -121.169 42.84))"],"metadataDate":"2026-07-02T16:12:37.000Z","orcid":["https://orcid.org/0000-0002-7106-0559","https://orcid.org/0000-0002-0387-9052","https://orcid.org/0000-0001-5091-8993","https://orcid.org/0000-0001-7480-1458","https://orcid.org/0000-0002-8700-9002","https://orcid.org/0000-0001-9901-2658"],"organisation":["Swansea University","US Forest Service","NERC EDS Environmental Information Data Centre"],"publicationDate":"2026-07-02T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/f9180989-6528-404e-8110-e3dcc205a6a1","10.5285/f9180989-6528-404e-8110-e3dcc205a6a1","doi:10.5285/f9180989-6528-404e-8110-e3dcc205a6a1"],"resourceType":"Dataset","rightsHolder":["Swansea University"],"ror":["https://ror.org/053fq8t95","https://ror.org/03zmjc935","https://ror.org/04xw4m193"],"shortenedDescription":"This dataset contains outputs of wildfire simulations in Fire Dynamics Simulator (FDS) in forest environments. It includes three simulations, each representing different simulation parameters. The forest plot used for the simulations consists of a 40 x 40 m Pinus ponderosa…","state":"published","supplementalDescription":["These files can be viewed on the free software Smokeview, a specialized visualization and analysis tool for FDS output."],"title":"Wildfire simulation outputs from Fire Dynamics Simulator (FDS) using real-world fuel data from forest plots, Oregon, USA, 2019","topic":["0/Environmental risk/","0/Modelling/","0/Climate and climate change/"],"version":1.0,"view":["public","glenn"]},{"authorAffiliation":["UK Centre for Ecology & Hydrology"],"authorFamilyName":["Trill","Robotham","Old","Rameshwaran","Bishop"],"authorFullName":["Trill, E.","Robotham, J.","Old, G.","Rameshwaran, P.","Bishop, J."],"authorGivenName":["E.","J.","G.","P."],"authorOrcid":["https://orcid.org/0000-0002-6233-8942","https://orcid.org/0000-0002-1223-8345","https://orcid.org/0000-0002-4713-1070","https://orcid.org/0000-0002-8972-953X"],"authorRor":["https://ror.org/00pggkr55"],"availability":"Available","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)"],"description":"This dataset contains high-resolution (5-minute) raw, atmospheric corrected and mean sea level adjusted water level data for 9 flood storage areas (FSAs) in the Littlestock Brook catchment (a tributary of the River Evenlode, Thames Basin) from 2018 to 2022. The dataset also includes the estimated 9 x FSA stored volume time-series, estimated using a depth-stored volume lookup table for each FSA, produced from a digital elevation model of each feature and a depth-area-volume toolset. The annual barometric pressure time-series used to correct water level is also provided.\n\nThis dataset was collected by UKCEH as part of a hydrological monitoring programme for the Littlestock Brook Natural Flood Management scheme. This work was supported by the SPITFIRE NERC DTP (NE/L002531/1) and the SCENARIO NERC DTP (NE/L002566/1).","documentType":"GEMINI_DOCUMENT","familyName":["Trill","Robotham","Old","Rameshwaran","Bishop"],"fullName":["Trill, E.","Robotham, J.","Old, G.","Rameshwaran, P.","Bishop, J."],"funder":["Natural Environment Research Council"],"givenName":["E.","J.","G.","P."],"grant":["NE/L002531/1","NE/L002566/1"],"identifier":"cf70f798-442a-4775-963c-b6600023830f","incomingCitationCount":0,"keyword":["Oxfordshire","Cotswolds","Thames Basin","Hydrology","Environmental risk","natural flood management (NFM)","flood storage area (FSA)","bund","hydrology","flood","flood risk management"],"keywordsOther":["natural flood management (NFM)","flood storage area (FSA)","bund","hydrology","flood","flood risk management"],"keywordsPlace":["Oxfordshire","Cotswolds","Thames Basin"],"keywordsTheme":["Hydrology","Environmental risk"],"licence":"Open government licence","lineage":"Data were generated using pressure sensors supplied with a factory calibration. A barometric correction was applied to sensor pressure time-series. Barometric corrected pressure data were then calibrated to stage using a linear regression developed between these data and observed stage board readings. After this correction data were quality controlled to flag any spurious readings, which were removed and interpolated if appropriate. Flood Storage Area (FSA) volume for each feature was estimated using a Digital Elevation Model (DEM) produced with LiDAR data. If LiDAR data were not available, as-built manual survey data were interpolated using the Natural Neighbour method. The DEMs were imported into ArcGIS to create a raster and apply a depth-area-volume toolset for each FSA. The continuous corrected water level time-series in each FSA was then used to produce a time-series of stored volume for each FSA, by matching the water level time-series to the depth-stored volume lookup table produced from ArcGIS.","locations":["POLYGON((-1.6 51.85, -1.6 51.88, -1.66 51.88, -1.66 51.85, -1.6 51.85))"],"metadataDate":"2026-06-29T18:02:32.000Z","orcid":["https://orcid.org/0000-0002-6233-8942","https://orcid.org/0000-0002-1223-8345","https://orcid.org/0000-0002-4713-1070","https://orcid.org/0000-0002-8972-953X"],"organisation":["UK Centre for Ecology & Hydrology","NERC EDS Environmental Information Data Centre"],"publicationDate":"2022-09-06T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/cf70f798-442a-4775-963c-b6600023830f","10.5285/cf70f798-442a-4775-963c-b6600023830f","doi:10.5285/cf70f798-442a-4775-963c-b6600023830f"],"resourceType":"Dataset","rightsHolder":["UK Centre for Ecology & Hydrology"],"ror":["https://ror.org/00pggkr55","https://ror.org/04xw4m193"],"shortenedDescription":"This dataset contains high-resolution (5-minute) raw, atmospheric corrected and mean sea level adjusted water level data for 9 flood storage areas (FSAs) in the Littlestock Brook catchment (a tributary of the River Evenlode, Thames Basin) from 2018 to 2022. The dataset…","state":"published","title":"High-resolution time-series of flood storage area water levels and estimated stored volumes in the Littlestock Brook, Thames Basin, England, 2018-2022","topic":["0/Hydrology/","0/Environmental risk/"],"version":1.0,"view":["public","margla"]},{"authorAffiliation":["University of Exeter","AECOM"],"authorFamilyName":["Abancó","Jones"],"authorFullName":["Abancó, C.","Jones, J.N."],"authorGivenName":["C.","J.N."],"authorOrcid":["https://orcid.org/0000-0002-2169-5409","https://orcid.org/0000-0002-8992-1572"],"authorRor":["https://ror.org/03yghzc09","https://ror.org/030p6ep86"],"availability":"Available","catalogue":"eidc","dataFormat":["Shapefile"],"description":"This dataset contains the areas affected by landslides triggered by Typhoon Mangkhut in the area of Itogon (Benguet, Philippines) between the 13th and 15th of September 2018. The polygons were mapped using very high-resolution satellite imagery from before and after the typhoon. The pre-typhoon images were captured on 18/02/2018 and the post-typhoon images were captured on 02/03/2019 using the World-View 2 satellite. Google Earth imagery was also used as a supplementary source. The study area covers 570 km2.","documentType":"GEMINI_DOCUMENT","familyName":["Abancó","Jones"],"fullName":["Abancó, C.","Jones, J.N."],"givenName":["C.","J.N."],"identifier":"32765a61-8510-4dfc-b7c7-58bad12f8497","incomingCitationCount":0,"keyword":["Philippines","Itogon","Mapping","Environmental risk","debris flow","Typhoon Mangkhut","hazard","typhoon","landslide"],"keywordsOther":["Itogon","debris flow","Typhoon Mangkhut","hazard","typhoon","landslide"],"keywordsPlace":["Philippines","Itogon"],"keywordsTheme":["Mapping","Environmental risk"],"licence":"Open government licence","lineage":"The polygons of the landslides were mapped by a member of team. The technique to map them was visual observation of evidences of change before and after the typhoon, that would correspond to the appearance of a landslide. The inventory was checked by a different person afterwards.","locations":["POLYGON((120.566 16.328, 120.566 16.529, 120.798 16.529, 120.798 16.328, 120.566 16.328))"],"metadataDate":"2026-06-29T15:39:53.000Z","orcid":["https://orcid.org/0000-0002-2169-5409","https://orcid.org/0000-0002-8992-1572"],"organisation":["University of Exeter","AECOM","NERC EDS Environmental Information Data Centre"],"publicationDate":"2023-07-28T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/32765a61-8510-4dfc-b7c7-58bad12f8497","10.5285/32765a61-8510-4dfc-b7c7-58bad12f8497","doi:10.5285/32765a61-8510-4dfc-b7c7-58bad12f8497"],"resourceType":"Dataset","rightsHolder":["University of Exeter"],"ror":["https://ror.org/03yghzc09","https://ror.org/030p6ep86","https://ror.org/04xw4m193"],"shortenedDescription":"This dataset contains the areas affected by landslides triggered by Typhoon Mangkhut in the area of Itogon (Benguet, Philippines) between the 13th and 15th of September 2018. The polygons were mapped using very high-resolution satellite imagery from before and after…","state":"published","title":"Areas affected by landslides following Typhoon Mangkhut in Itogon, Philippines, September 2018","topic":["0/Mapping/","0/Environmental risk/"],"version":1.0,"view":["public","phtr"]},{"authorAffiliation":["Swansea University","US Forest Service"],"authorFamilyName":["Cabo","Laino","Doerr","Parsons","Hudak","Santin"],"authorFullName":["Cabo, C.","Laino, D.","Doerr, S.H.","Parsons, R.A.","Hudak, A.T.","Santin, C."],"authorGivenName":["C.","D.","S.H.","R.A.","A.T."],"authorOrcid":["https://orcid.org/0000-0002-0387-9052","https://orcid.org/0000-0002-7106-0559","https://orcid.org/0000-0002-8700-9002","https://orcid.org/0000-0001-5091-8993","https://orcid.org/0000-0001-7480-1458","https://orcid.org/0000-0001-9901-2658"],"authorRor":["https://ror.org/053fq8t95","https://ror.org/03zmjc935"],"availability":"Available","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)"],"description":"This dataset consists of high-resolution individual tree attributes specifically formatted for 3D fuel modeling and physics-based fire simulation. The primary data resource is a structured inventory of forest vegetation, where each entry represents an individual tree. Key variables include precise spatial coordinates (X, Y, Z), Diameter at Breast Height (DBH), and Total Height (TH). These parameters serve as the foundational inputs required to synthesize complex 3D fuel beds within the FastFuels modeling environment that can be later be used as inputs for wildfire simulation softwares FIRETEC and QUIC-Fire.\n\nThe data was extracted from terrestrial 3D LiDAR point clouds of a Pinus ponderosa plot scanned with a Riegl-VZ400i TLS scanner in Sycan Marsh, Oregon, USA during the summer of 2019. This resource was developed to provide \"ground truth\" fuel data for the validation and calibration of next-generation wildfire models, enabling researchers to simulate fire behaviour-such as crown fire initiation and heat flux-with higher physical fidelity.","documentType":"GEMINI_DOCUMENT","familyName":["Cabo","Laino","Doerr","Parsons","Hudak","Santin"],"fullName":["Diego Laino","Cabo, C.","Laino, D.","Doerr, S.H.","Parsons, R.A.","Hudak, A.T.","Santin, C."],"funder":["Natural Environment Research Council","Agencia Estatal de Investigacion","Department of Defense Strategic Environmental Research and Development Program"],"givenName":["C.","D.","S.H.","R.A.","A.T."],"grant":["NE/T001194/1","PID2021-126790NB-I00","RC20-1025","RC23-7626"],"identifier":"bc67144d-91c4-446d-8691-248a793bf4f4","incomingCitationCount":0,"keyword":["Climate and climate change","Modelling","Environmental risk","forest fire","remote sensing","forestry","computation fluid dynamics models","LiDAR","fuel"],"keywordsOther":["forest fire","remote sensing","forestry","computation fluid dynamics models","LiDAR","fuel"],"keywordsTheme":["Climate and climate change","Modelling","Environmental risk"],"licence":"Open government licence","lineage":"Point cloud acquisition was done between 8th and 12th July 2019 in a 200x200 m2 study plot of a ponderosa pine woodland in Sycan Marsh preserve, Oregon, USA. \nTLS point cloud sampling was performed along a 50 m grid to create a synoptic scan. The point clouds have been acquired with a RIEGL-VZ400i TLS system with a laser sampling rate 750 kHz and a vertical sampling density of 0.21 degrees, mounted on a tripod at a minimum height of 1.5 m. Point cloud was georeferenced using the integrated L1 GPS receiver, compass and inclination sensors of the TLS system and ground control points whose coordinates were recorded were recorded using an RTK/Differential GPS receiver/base combination.\n\nThe raw scans were pre-processed using Riegl's proprietary software RiSCAN PRO to assign metadata (scanner position, scan ID, date/time), align all scans into a common coordinate system and divide the total study area in 40 x 40 m2 plots (n = 25 plots). These resulting plots were finally stored into LAZ files.\n\nLAZ files were processed using 3DFin software (https://github.com/3DFin/3DFin) to compute forest inventory metrics. Then, a random sample of 150 trees across the plot were extracted. Real-world coordinates (X, Y), Diameter at Breast Height (DBH) and tree Total Height (TH) are provided for each tree.","locations":["POLYGON((-121.169 42.84, -121.169 42.857, -121.151 42.857, -121.151 42.84, -121.169 42.84))"],"metadataDate":"2026-06-29T16:12:44.000Z","orcid":["https://orcid.org/0000-0002-0387-9052","https://orcid.org/0000-0002-7106-0559","https://orcid.org/0000-0002-8700-9002","https://orcid.org/0000-0001-5091-8993","https://orcid.org/0000-0001-7480-1458","https://orcid.org/0000-0001-9901-2658"],"organisation":["Swansea University","US Forest Service","NERC EDS Environmental Information Data Centre"],"publicationDate":"2026-06-03T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/bc67144d-91c4-446d-8691-248a793bf4f4","10.5285/bc67144d-91c4-446d-8691-248a793bf4f4","doi:10.5285/bc67144d-91c4-446d-8691-248a793bf4f4"],"resourceType":"Dataset","rightsHolder":["Swansea University"],"ror":["https://ror.org/053fq8t95","https://ror.org/03zmjc935","https://ror.org/04xw4m193"],"shortenedDescription":"This dataset consists of high-resolution individual tree attributes specifically formatted for 3D fuel modeling and physics-based fire simulation. The primary data resource is a structured inventory of forest vegetation, where each entry represents an individual tree.…","state":"published","title":"Real-world tree attribute input data for 3D fuel modelling in FastFuels from Oregon, USA, 2019","topic":["0/Climate and climate change/","0/Modelling/","0/Environmental risk/"],"version":1.0,"view":["public","glenn"]},{"authorAffiliation":["University of Dundee"],"authorFamilyName":["Connolly","Moffat"],"authorFullName":["Connolly, C.N.","Moffat, C."],"authorGivenName":["C.N.","C."],"authorRor":["https://ror.org/03h2bxq36"],"availability":"Available","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)"],"description":"This dataset contains a colony performance indicator monitored from Bumblebee colonies of similar mass after 43-48 days in the field. The weight in milligrams (mg) is given of each surviving bee recorded as it was removed from the outside of the nest as we progressed towards the nest core. Bumblebee colonies of similar mass were provided with sugar syrup (UT, n=12), containing chlorpyrifos (CP, 150  nanomolar nM, n=6) imidacloprid (IMD, 10 nM, n= 6) or both (IMD + CP, n=12). No pollen was provided and bees were free to forage in a wilderness/grassland area in the west of Scotland.  The data were collected as part of a project within the UK Insect Pollinators Initiative (2010-2015).","documentType":"GEMINI_DOCUMENT","familyName":["Connolly","Moffat"],"fullName":["Connolly, C.N.","Moffat, C."],"givenName":["C.N.","C."],"identifier":"341414f8-e88a-43e5-ade3-c30623c1586d","incomingCitationCount":0,"keyword":["Wester Ross","Environmental risk","Pollinators","Bumblebee","Bombus terrestris audax"],"keywordsOther":["Bumblebee","Bombus terrestris audax"],"keywordsPlace":["Wester Ross"],"keywordsTheme":["Environmental risk","Pollinators"],"licence":"Open government licence","lineage":"The data was generated as follows: Nests were anaesthetised using carbon dioxide until the bees became slow/immobilised.  The nest was opened and each bee was removed and weighed on a top pan balance before being killed rapidly in ice-cold water containing detergent before full awakening.","locations":["POLYGON((-5.823 57.353, -5.823 57.968, -5.174 57.968, -5.174 57.353, -5.823 57.353))"],"metadataDate":"2026-06-27T13:35:29.000Z","organisation":["University of Dundee","NERC Environmental Information Data Centre","NERC EDS Environmental Information Data Centre"],"publicationDate":"2015-04-30T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/341414f8-e88a-43e5-ade3-c30623c1586d","10.5285/341414f8-e88a-43e5-ade3-c30623c1586d","doi:10.5285/341414f8-e88a-43e5-ade3-c30623c1586d"],"resourceType":"Dataset","ror":["https://ror.org/03h2bxq36","https://ror.org/04xw4m193"],"shortenedDescription":"This dataset contains a colony performance indicator monitored from Bumblebee colonies of similar mass after 43-48 days in the field. The weight in milligrams (mg) is given of each surviving bee recorded as it was removed from the outside of the nest as we progressed…","state":"published","title":"The number and individual weight of bumblebees (Bombus terrestris audax) from nests containing neonicotinoids in Wester Ross, UK","topic":["0/Environmental risk/","0/Pollinators/"],"version":1.0,"view":["public","hajd"]},{"availability":"Available","catalogue":"eidc","dataFormat":["Tab delimited text"],"description":"This dataset is from five boreholes located on an improved grassland hillslope transect within the Pontbren study site in mid-Wales, UK. Groundwater was measured using pressure transducers installed in each of the boreholes with a pressure transducer used to account for variations in barometric pressure. Groundwater monitoring was carried out between 2005-2009 as part of the Pontbren Catchment Study Land Use and Management Multi-Scale Experimental Programme. \n\nBoreholes 1 and 2 are located in the improved grassland field immediately above the Bowl study site, borehole 3 is located within the Bowl study site and boreholes 4 and 5 are located in improved grassland field below the Bowl, known as the hillslope with tree shelterbelt. Data is presented in terms of height of water (cm) relative to the soil surface. Groundwater temperature (deg C) is also given. \n\nGroundwater height was initially sampled every 10 minutes until October 2006 when it was changed to sampling every 30 minutes. Groundwater was measured in all 5 boreholes up until March 2008 at which point sampling was reduced to measurements taken from borehole 3 up until the end of 2009. Within the 'Pontbren Groundwater' dataset folder there are five other sub-folders which contain the dataset from the respective boreholes. \n\nData are provided in the form of .txt files and generally split into 6 month blocks. Associated with each data point in the .txt file is a quality assurance code, QA code, in the adjacent column. Details of the dataset, the quality assurance coding system and monitoring locations are provided in the supporting documentation. Also provided are the details of the borehole logs at the time they were drilled. Other measurements taken at the bowl and hillslope study site include monitoring runoff from an improved grassland field in the form of overland and drain flow, soil water tension, soil volumetric moisture content, groundwater height and precipitation. Datasets of these other parameters are also provided by the EIDC.","documentType":"GEMINI_DOCUMENT","familyName":["Marshall"],"fullName":["Marshall, M."],"givenName":["Miles"],"identifier":"2b7bdff7-cfac-459e-8c50-360da7ba4468","incomingCitationCount":0,"keyword":["United Kingdom","Wales","Pontbren","Soil","Hydrology","Environmental risk","Flood risk management","Water","hydrology","flooding","soil"],"keywordsOther":["Flood risk management","Water","hydrology","flooding","soil"],"keywordsPlace":["United Kingdom","Wales","Pontbren"],"keywordsTheme":["Soil","Hydrology","Environmental risk"],"licence":"Non-Open government licence","lineage":"Digital data subject to manual validation procedures during capture and transfer to the main geo database and through subsequent statistical analysis and modelling.  Full details provided in the 'Pontbren data catalogue'.","locations":["POLYGON((-3.447 52.632, -3.447 52.656, -3.391 52.656, -3.391 52.632, -3.447 52.632))"],"metadataDate":"2026-06-27T19:00:31.000Z","organisation":["NERC EDS Environmental Information Data Centre","UK Centre for Ecology & Hydrology","NERC Environmental Information Data Centre"],"publicationDate":"2012-04-02T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/2b7bdff7-cfac-459e-8c50-360da7ba4468"],"resourceType":"Dataset","ror":["https://ror.org/04xw4m193","https://ror.org/00pggkr55"],"shortenedDescription":"This dataset is from five boreholes located on an improved grassland hillslope transect within the Pontbren study site in mid-Wales, UK. Groundwater was measured using pressure transducers installed in each of the boreholes with a pressure transducer used to account…","state":"published","supplementalDescription":["Marshall, M. R., Francis, O. J., Frogbrook, Z. L., Jackson, B. M., McIntyre, N., Reynolds, B., ... Chell, J. (2009). The impact of upland land management on flooding: results from an improved pasture hillslope. Hydrological Processes, 23(3), 464-475.","Wheater, H., Reynolds, B., McIntyre, N., Marshall, M., Jackson, B., Frogbrook, Z., Solloway, I., Francis, O. and Chell, J.  2008.  Impacts of upland management on flood risk: multi-scale modelling on methodology and results from the Pontbren Experiment.  FRMRC Research Report UR 16.  December 2008. Click on, Land Use, Sediments and Flooding, to view report."],"supplementalName":["The Flood Risk Management Research Consortium website"],"title":"Pontbren groundwater data","topic":["0/Soil/","0/Hydrology/","0/Environmental risk/"],"version":1.0,"view":["public","bpu"]},{"availability":"Available","catalogue":"eidc","dataFormat":["Tab delimited text"],"description":"This dataset includes data collected from the Bowl site located with the Pontbren study catchment in mid Wales, UK. The Bowl is an area of improved grassland and was instrumented between 2004 to 2010 and monitored as part of the Pontbren Catchment Study Land Use and Management Multi Scale Experimental Programme. Variables measured and included in this dataset are the drain flow from a field drain, overland flow runoff and soil water tension within the improved grassland hillslope. Other variables measured at the Bowl but not included in this dataset are: climatic data from an automatic weather station, precipitation, groundwater height, and soil moisture data (using a neutron probe); these other datasets are also available.   Within this Pontbren Bowl study site folder are a series of sub-folders with different datasets all associated with the Bowl study site. The Bowl runoff folder includes all runoff data from the Bowl study site. Runoff from the Bowl in the form of overland and drain flow was monitored using a combination of tipping bucket and weir box monitoring systems. Flow is measured in litres/second (ls-1) and runoff data from the bowl was collected for the period end of 2004 to 2010. Differences in sampling time occurred throughout the monitoring period due to logger limitations. Changes in sampling time can be found by examining specific data files. Changes in the size of the bucket of the tipping bucket system also occurred during the monitoring period. It is considered that the weir boxes provide a more accurate prediction of the highest flows, however there are times when they are not operation. The Bowl tensiometers folder contains soil water tension (cm H2O) data collected from two transects with arrays of tensiometers measuring soil water tension at 10 cm, 30 cm and 50 cm depth. Soil water tension data for the Bowl study site exist for the period 2005-2009. Data are provided in the form of .txt files and generally split into 6 month blocks. Associated with each data point in the .txt file is a quality assurance code, QA code, in the adjacent column. Note that for the Bowl tensiometer data in the early years of monitoring data from both transects are provided in one file. From March 2008 onwards there is a reduction in the number of tensiometers installed and the data files are split. Files with BotQC in the title contain data from the lower array of tensiometers and files with TopQC in the title contain data from the array of tensiometers further up the hillslope of the Bowl study site.  Details of the dataset and the quality assurance coding system are provided in the supporting documentation. ","documentType":"GEMINI_DOCUMENT","familyName":["Marshall"],"fullName":["Marshall, M."],"givenName":["Miles"],"identifier":"11caad35-4a33-4ad8-852b-6c120fd250e2","incomingCitationCount":0,"keyword":["United Kingdom","Wales","Pontbren","Soil","Environmental risk","Hydrology","flooding","hydrology","water (geographic)","flood risk management"],"keywordsOther":["flooding","hydrology","water (geographic)","flood risk management"],"keywordsPlace":["United Kingdom","Wales","Pontbren"],"keywordsTheme":["Soil","Environmental risk","Hydrology"],"licence":"Non-Open government licence","lineage":"Digital data subject to manual validation procedures during capture and transfer to the main geo database and through subsequent statistical analysis and modelling.  Full details provided in the 'Pontbren Catchment Study Data catalogue'.","locations":["POLYGON((-3.447 52.632, -3.447 52.656, -3.391 52.656, -3.391 52.632, -3.447 52.632))"],"metadataDate":"2026-06-27T19:26:13.000Z","organisation":["NERC EDS Environmental Information Data Centre","UK Centre for Ecology & Hydrology","NERC Environmental Information Data Centre"],"publicationDate":"2012-04-02T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["1331814014953","CEH:EIDC::1331814014953","https://catalogue.ceh.ac.uk/id/11caad35-4a33-4ad8-852b-6c120fd250e2"],"resourceType":"Dataset","ror":["https://ror.org/04xw4m193","https://ror.org/00pggkr55"],"shortenedDescription":"This dataset includes data collected from the Bowl site located with the Pontbren study catchment in mid Wales, UK. The Bowl is an area of improved grassland and was instrumented between 2004 to 2010 and monitored as part of the Pontbren Catchment Study Land Use and…","state":"published","supplementalDescription":["The Flood Risk Management Research Consortium website.","Marshall, M.R., Francis, O.J., Frogbrook, Z.L., Jackson, B.M., McIntyre, N., Reynolds, B., Solloway, I., Wheater, H.S. and Chell, J.  2009. The impact of upland land management on flooding: results from an improved pasture hillslope.  Hydrological Processes, 23, 464-475.","Wheater, H., Reynolds, B., McIntyre, N., Marshall, M., Jackson, B., Frogbrook, Z., Solloway, I., Francis, O. and Chell, J.  2008.  Impacts of upland management on flood risk: multi-scale modelling on methodology and results from the Pontbren Experiment.  FRMRC Research Report UR 16.  December 2008.  "],"supplementalName":["FRMRC website"],"title":"Pontbren Bowl study site runoff and soil water tension data","topic":["0/Soil/","0/Environmental risk/","0/Hydrology/"],"version":1.0,"view":["public","bpu"]},{"authorAffiliation":["University of Stirling"],"authorFamilyName":["Ormsby","Woodford","Fellows","White","Quilliam"],"authorFullName":["Ormsby, M.","Woodford, L.","Fellows, R.","White, H.","Quilliam, R."],"authorGivenName":["Michael","Luke","Rosie","Hannah","Richard"],"authorOrcid":["https://orcid.org/0000-0002-3991-2336","https://orcid.org/0000-0003-2530-2120","https://orcid.org/0009-0003-8928-2189","https://orcid.org/0000-0001-9842-7798","https://orcid.org/0000-0001-7020-4410"],"authorRor":["https://ror.org/045wgfr59"],"availability":"Available","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)"],"description":"This dataset contains information relating to the rate of colonisation of E. coli O157 on plastic and banana leaf, under simulated environmental conditions. The data encompass bacterial strain identity, material type, timepoints (days), temperature (°C), and bacterial concentration (CFU/ml). Data were sampled over defined periods using culture-based approaches.\n\nThis work was supported by the UKRI Natural Environment Research Council (NERC) as part of the GCRF SPACES project [grant number NE/V005847/1] and the Plastic Vectors project, “Microbial hitch-hikers of marine plastics: the survival, persistence & ecology of microbial communities in the ‘Plastisphere’” [grant number NE/S005196/1].","documentType":"GEMINI_DOCUMENT","familyName":["Ormsby","Woodford","Fellows","White","Quilliam"],"fullName":["Michael Ormsby","Ormsby, M.","Woodford, L.","Fellows, R.","White, H.","Quilliam, R."],"funder":["Natural Environment Research Council"],"givenName":["Michael","Luke","Rosie","Hannah","Richard"],"grant":["NE/V005847/1","NE/S005196/1"],"identifier":"abbc69c2-b799-4892-a339-fb1ffa4ea2f0","incomingCitationCount":0,"keyword":["Environmental risk","Water quality","Plastisphere","Biofilm","Wastewater","E. coli O157","AMR"],"keywordsOther":["Plastisphere","Biofilm","Wastewater","E. coli O157","AMR"],"keywordsTheme":["Environmental risk","Water quality"],"licence":"Open government licence","lineage":"Data were generated through laboratory experiments investigating the persistence,  and survival of a clinically relevant strain of E. coli. Bacteria were cultured on materials (Banana Leaf and HDPE) and analysed for persistence over time. Materials (Banana Leaf and HDPE) were prepared and inoculated under controlled laboratory conditions. E. coli strains were inoculated onto materials in nutrient-rich and surface water environments. Sampling was taken at defined time points (7, 14, 21, 28 days).  The experiments utilised standard laboratory equipment such as 96-well plates and incubators. Instrumentation used for bacterial enumeration, including the plate reader, was calibrated according to standard laboratory protocols. The data underwent rigorous quality control through replication (biological triplicates), statistical analysis (ANOVA), and controlled experimental conditions (e.g., temperature and material consistency). Statistical methods including ANOVA and Tukey’s post-hoc tests were applied to assess treatment effects and survival outcomes.\n","metadataDate":"2026-06-29T16:25:00.000Z","orcid":["https://orcid.org/0000-0002-3991-2336","https://orcid.org/0000-0003-2530-2120","https://orcid.org/0009-0003-8928-2189","https://orcid.org/0000-0001-9842-7798","https://orcid.org/0000-0001-7020-4410"],"organisation":["University of Stirling","NERC EDS Environmental Information Data Centre"],"publicationDate":"2025-06-12T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/abbc69c2-b799-4892-a339-fb1ffa4ea2f0","10.5285/abbc69c2-b799-4892-a339-fb1ffa4ea2f0","doi:10.5285/abbc69c2-b799-4892-a339-fb1ffa4ea2f0"],"resourceType":"Non-geographic dataset","rightsHolder":["University of Stirling"],"ror":["https://ror.org/045wgfr59","https://ror.org/04xw4m193"],"shortenedDescription":"This dataset contains information relating to the rate of colonisation of E. coli O157 on plastic and banana leaf, under simulated environmental conditions. The data encompass bacterial strain identity, material type, timepoints (days), temperature (°C), and bacterial…","state":"published","title":"Colonisation rates of E. coli on plastic and banana leaf under simulated environmental conditions","topic":["0/Environmental risk/","0/Water quality/"],"version":1.0,"view":["public","clwe"]},{"authorAffiliation":["Centre for Ecology & Hydrology","Albert-Ludwigs-University of Freiburg"],"authorFamilyName":["Tanguy","Bachmair","Stahl","Hannaford"],"authorFullName":["Tanguy, M.","Bachmair, S.","Stahl, K.","Hannaford, J."],"authorGivenName":["M.","S.","K.","J."],"authorOrcid":["https://orcid.org/0000-0002-1516-6834","https://orcid.org/0000-0002-5256-3310"],"authorRor":["https://ror.org/00pggkr55","https://ror.org/0245cg223"],"availability":"Available","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)"],"description":"This dataset consists in a collection of remotely sensed drought indicators time series. The data was extracted from CEH's gridded remotely sensed drought indicators product (Tanguy et al., 2016; http://doi.org/10.5285/4e0d0e50-2f9c-4647-864d-5c3b30bb5f4b), which has gridded data for Europe for three drought indicators:\n - the Vegetation Condition Index (VCI) based on satellite product NDVI (Normalised Difference Vegetation Index);\n - the Temperature Condition Index (TCI) based on remotely sensed LST (Land Surface Temperature);\n - the Vegetation Health Index (VHI) which is a combination of VCI and TCI.\n\nThese three drought indicators have been extracted for European NUTS regions (level 0, 1, 2 and 3). These have been masked with a land use land cover map to be able to study different responses for various land cover types. A simplified LULC was created, with only four classes: forest, crop, shrub and grass. One extra time series was created for all classes together.","documentType":"GEMINI_DOCUMENT","familyName":["Tanguy","Bachmair","Stahl","Hannaford"],"fullName":["Tanguy, M.","Bachmair, S.","Stahl, K.","Hannaford, J."],"givenName":["M.","S.","K.","J."],"identifier":"5b3fcf9f-19d4-4ad3-a8bb-0a5ea02c857e","incomingCitationCount":1,"keyword":["Environmental risk","Vegetation Condition Index ","VCI","Normalised Difference Vegetation Index","NVDI","moderate-resolution imaging spectroradiometer","MODIS","Land Surface Temperature","LST","Temperature Condition Index ","TCI","DrIVER","NUTS","crops","shrubs","monitoring and early warning system","Nomenclature of Territorial Units for Statistics","Nomenclature des unités territoriales statistiques","drought","grass","forest","land cover","land use"],"keywordsOther":["Vegetation Condition Index ","VCI","Normalised Difference Vegetation Index","NVDI","moderate-resolution imaging spectroradiometer","MODIS","Land Surface Temperature","LST","Temperature Condition Index ","TCI","DrIVER","NUTS","crops","shrubs","monitoring and early warning system","Nomenclature of Territorial Units for Statistics","Nomenclature des unités territoriales statistiques","drought","grass","forest","land cover","land use"],"keywordsTheme":["Environmental risk"],"licence":"Open government licence","lineage":"Time series for three drought indicators based on remote sensing have been extracted for European NUTS regions (level 0, 1, 2 and 3). The Nomenclature of Territorial Units for Statistics, (NUTS, for the French Nomenclature des unités territoriales statistiques), developed by the European Union, is a geocode standard for referencing the administrative divisions of countries for statistical purposes. A land use mask was applied to extract the time series, to differentiate the contribution of crops, grass, forest and shrubs. There is also one time series for each NUTS region which includes all classes. The land cover product used to produce the mask was remote sensing MODIS product MCD12C1 (year 2012) which has a 0.05 degree resolution. The three drought indicators extracted are (i) the Vegetation Condition Index (VCI) based on satellite product NDVI (Normalised Difference Vegetation Index) (ii) the Temperature Condition Index based on remotely sensed LST (Land Surface Temperature) and (iii) the Vegetation Health Index (VHI) which is a combination of VCI and TCI. These indicators were first calculated as a gridded product for Europe with a 0.05 degree resolution and monthly time step (2000-2015), using MODIS product MOD13C2 for NDVI, and MODIS product MOD11C3 for LST, following methodology described by Kogan (1995; https://doi.org/10.1016/0273-1177(95)00079-T). The time series were then extracted applying the simplified land use classification mask (crops, forest, grass, shrubs) to each NUTS region, and an additional time series for all classes. For each time step, a value was produced only if at least 50% of the pixels within the non-masked area had valid values.\n\nNOTE: there are two types of \"No Data\" value. Value '--' means there were no pixels with valid values within the non-masked area. Value 'nan' means there were some pixels with valid values within the non-masked area, but these covered less than 50% of the area. These time steps were discarded as less than 50% was considered not representative enough of the whole area.\n","locations":["POLYGON((-15 30, -15 75, 45 75, 45 30, -15 30))"],"metadataDate":"2026-06-29T16:27:11.000Z","orcid":["https://orcid.org/0000-0002-1516-6834","https://orcid.org/0000-0002-5256-3310"],"organisation":["UK Centre for Ecology & Hydrology","Centre for Ecology & Hydrology","Albert-Ludwigs-University of Freiburg","NERC Environmental Information Data Centre","NERC EDS Environmental Information Data Centre"],"publicationDate":"2016-07-11T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/5b3fcf9f-19d4-4ad3-a8bb-0a5ea02c857e","10.5285/5b3fcf9f-19d4-4ad3-a8bb-0a5ea02c857e","doi:10.5285/5b3fcf9f-19d4-4ad3-a8bb-0a5ea02c857e"],"resourceType":"Dataset","rightsHolder":["UK Centre for Ecology & Hydrology"],"ror":["https://ror.org/00pggkr55","https://ror.org/0245cg223","https://ror.org/04xw4m193"],"shortenedDescription":"This dataset consists in a collection of remotely sensed drought indicators time series. The data was extracted from CEH's gridded remotely sensed drought indicators product (Tanguy et al., 2016; http://doi.org/10.5285/4e0d0e50-2f9c-4647-864d-5c3b30bb5f4b), which has…","state":"published","title":"Drought indicator time series for European NUTS regions based on remote sensing data (2000-2015)","topic":["0/Environmental risk/"],"version":1.0,"view":["public","phtr"]}],"rows":20,"url":"http://catalogue.ceh.ac.uk:443/eidc/documents?page=2&facet=topic%7C0/Environmental%20risk/"}