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These were combined into daily averages after correcting for environmental effects in the sensor readings.\n\nThis dataset was created to study the potential for using distributed cosmic ray sensors to support data driven irrigation optimisation, supported by NERC (NE/W004364/1).\n","documentType":"GEMINI_DOCUMENT","familyName":["Stowell","Soler-Silva","Madari","Torre-Neto","Kamienski"],"fullName":["Stowell, P.","Soler-Silva, M.","Madari, B.","Torre-Neto, A.","Kamienski, C."],"funder":["Natural Environment Research Council","FAPESP"],"givenName":["P.","M.","B.","A.","C. "],"grant":["NE/W004364/1"],"identifier":"36df3345-277d-4efa-9b98-9140dbea5c4f","incomingCitationCount":0,"keyword":["Agriculture","cosmic-ray sensor","soil moisture","time series","hydrology"],"keywordsOther":["cosmic-ray sensor","soil moisture","time series","hydrology"],"keywordsTheme":["Agriculture"],"licence":"Open government licence","lineage":"Soil moisture data collected on a prototype FiWare sensing platform. Corrections for background cosmic ray variations, air humidity and temperature were applied using weather station data from a co-deployed environmental monitoring station before being averaged over each day.","locations":["POLYGON((-49.298 -16.5, -49.298 -16.495, -49.293 -16.495, -49.293 -16.5, -49.298 -16.5))"],"metadataDate":"2026-06-29T18:17:18.000Z","orcid":["https://orcid.org/0000-0002-6930-0509","https://orcid.org/0000-0003-1043-0592","https://orcid.org/0000-0002-6242-6619","https://orcid.org/0000-0001-6475-1469","https://orcid.org/0000-0002-3087-9234"],"organisation":["University of Sheffield","Embrapa - Rice & Bean","Embrapa - Instrumentation","Federal University of ABC","NERC EDS Environmental Information Data Centre","Durham University"],"publicationDate":"2025-06-30T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/36df3345-277d-4efa-9b98-9140dbea5c4f","10.5285/36df3345-277d-4efa-9b98-9140dbea5c4f","doi:10.5285/36df3345-277d-4efa-9b98-9140dbea5c4f"],"resourceType":"Dataset","rightsHolder":["Durham University"],"ror":["https://ror.org/05krs5044","https://ror.org/0482b5b22","https://ror.org/028kg9j04","https://ror.org/04xw4m193","https://ror.org/01v29qb04"],"shortenedDescription":"This dataset contains daily soil moisture estimates measured using prototype cosmic ray neutron sensors. The sensors were deployed in a rain-fed site in the state of Goias, Brazil. Volumetric water containment measurements were taken hourly between August and December,…","state":"published","title":"Soil moisture data obtained from prototype neutron probes at a rain-fed field site, Goias state, Brazil, 2023","topic":["0/Agriculture/"],"version":1.0,"view":["public","jashun"]},{"authorAffiliation":["University of Stirling","University of O'Higgins"],"authorFamilyName":["Jump","Greenwood","Venegas González","Paredes Berríos"],"authorFullName":["Jump, A.","Greenwood, S.","Venegas González, A.","Paredes Berríos, P."],"authorGivenName":["Alistair","Sarah","Alejandro","Pablo"],"authorOrcid":["https://orcid.org/0000-0002-2167-6451","https://orcid.org/0000-0001-9104-7936","https://orcid.org/0000-0003-4568-4533","https://orcid.org/0009-0004-8188-8044"],"authorRor":["https://ror.org/045wgfr59","https://ror.org/044cse639"],"availability":"Embargoed","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)"],"description":"This dataset contains forest structure and microclimate measurements collected from 60 plots of 125 m² each in La Campana National Park, Chile. The forest structure data record tree identity, species, condition, canopy cover, stem and resprouting characteristics, as well as biometric variables such as perimeter, height, and diameter at breast height. Plot-level information includes elevation and tree identifiers.\nMicroclimate data include soil moisture and temperature measured at three levels: underground, at ground level, and 30 cm above ground. These measurements provide fine-scale information on local environmental conditions within the forest.\nData were collected during the 2023-2024 austral summer season using systematic field surveys and standard forestry instruments. The dataset is designed to support research into forest mortality and resilience in Mediterranean-type ecosystems, where climate stress and disturbance are key drivers of change.\nThe resource was produced through collaboration between the University of Stirling (Scotland) and Universidad de O'Higgins (Chile), led by Prof. Alistair Jump, Dr. Sarah Greenwood, and Dr. Alejandro Venegas González.","documentType":"GEMINI_DOCUMENT","familyName":["Paredes-Berríos","Jump","Greenwood","Venegas González","Paredes Berríos"],"fullName":["Paredes-Berríos, P.","Jump, A.","Greenwood, S.","Venegas González, A.","Paredes Berríos, P."],"funder":["Natural Environment Research Council"],"givenName":["Pablo","Alistair","Sarah","Alejandro"],"grant":["NERC NE/Y004205/1"],"identifier":"23f751c8-11af-4991-8f37-a9baef1961eb","incomingCitationCount":0,"keyword":["Climate and climate change","Biodiversity","Central Chile","drought","forest ecology","Forest mortality","Mediterranean climate","Mediterranean forest","Mediterranean wood","tree mortality"],"keywordsOther":["Central Chile","drought","forest ecology","Forest mortality","Mediterranean climate","Mediterranean forest","Mediterranean wood","tree mortality"],"keywordsTheme":["Climate and climate change","Biodiversity"],"licence":"Open government licence","lineage":"The dataset was generated through systematic field surveys conducted during the 2023-2024 austral summer in La Campana National Park, Chile. Data collection was carried out across 60 temporary forest plots, each covering 125 m², established to characterise forest structure and near-ground microclimatic conditions.\nForest structure data were recorded for all trees with a minimum diameter at breast height (DBH) of 5 cm. Tree perimeter was measured in the field using diameter tapes, and DBH values were derived from perimeter measurements during data processing. Tree height was measured using a Haglöf Vertex 5 hypsometer. Additional variables collected included species identity, tree condition, canopy cover, stem characteristics, and resprouting status. Resprouting was recorded in the field and aggregated into a dedicated column within the dataset. Plot-level attributes, including elevation and tree identifiers, were also recorded.\nMicroclimate data were collected using TOMST TMS dataloggers deployed within each plot. Sensors recorded soil moisture and temperature at three vertical positions: below ground, at ground level, and 30 cm above ground. Measurements were logged at 15-minute intervals, providing high-resolution temporal data on local microclimatic conditions.\nFollowing field collection, datasets were compiled and standardised into consistent units (C°) and formats. Diameter values were calculated from measured perimeters. Data cleaning procedures were applied to remove void entries and obvious outliers resulting from recording or sensor errors. Basic consistency checks were performed to ensure logical ranges and internal coherence across variables.\nFormal calibration of instruments was not undertaken prior to field deployment. Measurements reflect standard forestry field practices.\nThe data represent a single-season snapshot and are therefore limited in their ability to capture interannual variability. The absence of formal sensor calibration may introduce minor systematic measurement uncertainty in microclimate variables. Visual or instrument-based estimates (e.g. canopy cover and height) may also be subject to observer-related variability. Despite these limitations, the dataset provides robust, fine-scale information suitable for assessing forest structure, microclimate, and ecological resilience in Mediterranean-type ecosystems.","locations":["POLYGON((-71.145 -32.985, -71.145 -32.95, -71.1 -32.95, -71.1 -32.985, -71.145 -32.985))"],"metadataDate":"2026-06-27T19:14:36.000Z","orcid":["https://orcid.org/0000-0002-2167-6451","https://orcid.org/0000-0001-9104-7936","https://orcid.org/0000-0003-4568-4533","https://orcid.org/0009-0004-8188-8044"],"organisation":["University of Stirling","University of O'Higgins","NERC EDS Environmental Information Data Centre"],"publicationDate":"2026-05-28T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/23f751c8-11af-4991-8f37-a9baef1961eb","10.5285/23f751c8-11af-4991-8f37-a9baef1961eb","doi:10.5285/23f751c8-11af-4991-8f37-a9baef1961eb"],"resourceType":"Dataset","rightsHolder":["University of Stirling"],"ror":["https://ror.org/045wgfr59","https://ror.org/044cse639","https://ror.org/04xw4m193"],"shortenedDescription":"This dataset contains forest structure and microclimate measurements collected from 60 plots of 125 m² each in La Campana National Park, Chile. The forest structure data record tree identity, species, condition, canopy cover, stem and resprouting characteristics, as…","state":"published","title":"Forest structure, canopy health and microclimate condition assessments in La Campana National Park, Chile, during 2023-2024 season","topic":["0/Climate and climate change/","0/Biodiversity/"],"version":1.0,"view":["public","tinzha"]},{"authorAffiliation":["University of Exeter"],"authorFamilyName":["Parker","Lewis","Galloway"],"authorFullName":["Parker, B.","Lewis, C.","Galloway, T."],"authorGivenName":["Ben","Ceri","Tamara"],"authorOrcid":["https://orcid.org/0000-0001-6731-7852","https://orcid.org/0000-0002-3564-2906","https://orcid.org/0000-0002-7466-6775"],"authorRor":["https://ror.org/03yghzc09"],"availability":"Available","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)"],"description":"The resource includes data extracted from published laboratory studies investigating the impacts of microfibres (fibres < 5 mm in size) on various traits within aquatic organisms. Data were accessible on 19/06/2024 and represent studies from 2015 to 2024.\nThe dataset includes measured responses in a range of aquatic organisms after microfibre exposure. Measures correspond to the following defined traits: \n1.\tDevelopment-Healthy molting and growth of organs and structures. \n2.\tFecundity-Number of offspring and quality of gametes.\n3.\tFeeding-Intake, handling and egestion of resources.\n4.\tGrowth-Change in organism weight, length or derived measures.\n5.\tHatching\t-Number, emergence time and morphology of offspring.\n6.\tNon-apical endpoints-Indices and measures of general organism wellbeing.\n7.\tSurvival-Organisms alive at a particular time point.\n\nThis dataset was created to collate microfibre study findings for meta-analyses and also to identify gaps within the literature. This work was supported by NERC (NE/Y003985/1) as part of the Future Fibres Networking Grant.\n\nThis dataset is a corrected version of https://doi.org/10.5285/e4d566bf-b571-460e-816e-0efa1ab3335a ","documentType":"GEMINI_DOCUMENT","familyName":["Parker","Lewis","Galloway"],"fullName":["Ben Parker","Parker, B.","Lewis, C.","Galloway, T."],"funder":["Natural Environment Research Council"],"givenName":["Ben","Ceri","Tamara"],"grant":["NE/Y003985/1"],"identifier":"8b7fcc6c-ac73-4f28-b82f-ea818b064915","incomingCitationCount":0,"keyword":["Pollution","Aquatic","Ecotoxicology","Fibres","Meta-analysis","Sustainability","Textiles"],"keywordsOther":["Aquatic","Ecotoxicology","Fibres","Meta-analysis","Pollution","Sustainability","Textiles"],"keywordsTheme":["Pollution"],"licence":"Open government licence","lineage":"The dataset was generated from an initial Web of Science database search of studies investigating the exposure impacts of microfibres (small fibres < 5 mm in size) on the responses of aquatic organisms. Web of Science results were evaluated and then the citing and cited studies from these results also screened. Finally, the compiled results were then assessed for eligibility as detailed in the supporting information and only eligible responses extracted. QA steps were used to exclude a number of studies and responses as outlined in the resource supporting information.\n\nThis dataset is a corrected version of https://doi.org/10.5285/e4d566bf-b571-460e-816e-0efa1ab3335a which had several incorrectly calculated standard exposures and consequently incorrect assignment to standard exposure categories. This new version includes details on how these standard exposures were calculated as well as including more details on the assignment of several categories. Finally, \"Health\" endpoints are now referred to as \"non-apical endpoints\".","metadataDate":"2026-06-29T18:16:24.000Z","orcid":["https://orcid.org/0000-0001-6731-7852","https://orcid.org/0000-0002-3564-2906","https://orcid.org/0000-0002-7466-6775"],"organisation":["University of Exeter","NERC EDS Environmental Information Data Centre"],"publicationDate":"2025-06-04T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/8b7fcc6c-ac73-4f28-b82f-ea818b064915","10.5285/8b7fcc6c-ac73-4f28-b82f-ea818b064915","doi:10.5285/8b7fcc6c-ac73-4f28-b82f-ea818b064915"],"resourceType":"Non-geographic dataset","rightsHolder":["University of Exeter"],"ror":["https://ror.org/03yghzc09","https://ror.org/04xw4m193"],"shortenedDescription":"The resource includes data extracted from published laboratory studies investigating the impacts of microfibres (fibres < 5 mm in size) on various traits within aquatic organisms. Data were accessible on 19/06/2024 and represent studies from 2015 to 2024.\nThe dataset…","state":"published","supplementalDescription":["Ben Parker, Ceri N Lewis, Tamara S Galloway, Impacts of non-petroleum and petroleum-based microfibres on aquatic organisms: ameta-analysis, Environmental Toxicology and Chemistry, 2025; vgaf113."],"title":"Trait responses of aquatic organisms from microfibre exposure studies published 2015-2024 v2","topic":["0/Pollution/"],"version":1.0,"view":["public","katwri"]},{"authorAffiliation":["UK Centre for Ecology & Hydrology"],"authorFamilyName":["Feuchtmayr","Rankin","McShane","Le Quesne"],"authorFullName":["Feuchtmayr, H.","Rankin, G.","McShane, G.","Le Quesne, K."],"authorGivenName":["H.","G.","K."],"authorOrcid":["https://orcid.org/0000-0002-2028-4843"],"authorRor":["https://ror.org/00pggkr55"],"availability":"Available","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)"],"description":"This dataset contains hourly water temperature data and hourly air temperature data of an experimental mesocosm facility from 21st April to 7th November 2023. The sixteen mesocosms (1 m deep, 2 m diameter) were filled with water from Windermere. The water temperature was measured every five minutes and an hourly average was calculated. Air temperature was measured by a weather station within the mesocosm compound. The experiment aimed to investigate different N:P nutrient ratios and water temperature was measured as this is an important factor needed to understand the results. ","documentType":"GEMINI_DOCUMENT","familyName":["Feuchtmayr","Rankin","McShane","Le Quesne"],"fullName":["Feuchtmayr, H.","Rankin, G.","McShane, G.","Le Quesne, K."],"funder":["European Commission, Directorate-General for Research & Innovation","Natural Environment Research Council"],"givenName":["H.","G.","K."],"grant":["871081 ","NE/X00497X/1"],"identifier":"406aee8f-3b85-4be6-ae7d-c92c8168a06f","incomingCitationCount":0,"keyword":["AQUACOSM-plus","Environmental survey","freshwater","mesocosm experiment","water temperature","air temperature"],"keywordsOther":["freshwater","mesocosm experiment","water temperature","air temperature"],"keywordsProject":["AQUACOSM-plus"],"keywordsTheme":["Environmental survey"],"licence":"Open government licence","lineage":"The water for the 16 mesocosms was collected from Windermere on 29th and 30th March 2023 and nutrients were added to some of the mesocosms throughout the experiment. Water temperature was measured every 5 minutes by platinum resistance thermometers (PRT) shaded by a plastic cover, sited around mid-depth, radially offset by 30 cm from the mesocosms’ side wall and logged by a Campbell Scientific Data Logger. The hourly average presented here is calculated from 5-minutely data over the following hour, e.g., the value for 1 p.m. is the average of the data between 1 and 1:55 p.m. All data are given in GMT (Greenwich Mean Time) and dates from 21st April to 7th November 2023. \n\nWhenever the difference between the hourly averaged two water temperature sensor data was less than 0.2 °C, the average between both temperatures was calculated. If the difference was larger than 0.2 °C, data were checked against the overall average of the temperature sensors recorded by each data logger. Whenever the difference was larger than 0.2 °C, one of the two temperature sensors had drifted either higher than the average or below the average temperature. In those cases, this sensor was ignored and only data from one temperature sensor was used during those occasions (see table in the supporting documentation).\n\nAir temperature was measured at a weather station within the mesocosm compound (Vaisala weather transmitter WXT520) at around 2.7m height.\n","locations":["POLYGON((-2.776 54.013, -2.776 54.015, -2.774 54.015, -2.774 54.013, -2.776 54.013))"],"metadataDate":"2026-06-27T18:21:58.000Z","orcid":["https://orcid.org/0000-0002-2028-4843"],"organisation":["UK Centre for Ecology & Hydrology","NERC EDS Environmental Information Data Centre"],"publicationDate":"2024-03-15T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/406aee8f-3b85-4be6-ae7d-c92c8168a06f","10.5285/406aee8f-3b85-4be6-ae7d-c92c8168a06f","doi:10.5285/406aee8f-3b85-4be6-ae7d-c92c8168a06f"],"resourceType":"Dataset","rightsHolder":["UK Centre for Ecology & Hydrology"],"ror":["https://ror.org/00pggkr55","https://ror.org/04xw4m193"],"shortenedDescription":"This dataset contains hourly water temperature data and hourly air temperature data of an experimental mesocosm facility from 21st April to 7th November 2023. The sixteen mesocosms (1 m deep, 2 m diameter) were filled with water from Windermere. The water temperature…","state":"published","title":"Hourly water temperature of 16 experimental mesocosms and hourly air temperature from April to November 2023","topic":["0/Environmental survey/"],"version":1.0,"view":["public","jenroe"]},{"authorAffiliation":["University of Nottingham"],"authorFamilyName":["Taylor","Dawson","D’Cruz","Jackson","Lowe","Rees","Richardson","Sains","Short","Gilbert","Reader"],"authorFullName":["Taylor, C.","Dawson, J.J.","D’Cruz, T.","Jackson, H.J.","Lowe, R.","Rees, H.","Richardson, J.","Sains, J.","Short, F.","Gilbert, F.","Reader, T."],"authorGivenName":["C.","J.J.","T.","H.J.","R.","H.","J.","F."],"authorOrcid":["https://orcid.org/0000-0003-4299-7104","https://orcid.org/0000-0002-6941-6157","https://orcid.org/0000-0002-2727-4103","https://orcid.org/0000-0001-7586-8814"],"authorRor":["https://ror.org/01ee9ar58"],"availability":"Available","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)"],"description":"Three files describe behavioural trials involving jumping spiders, crab spiders and praying mantises respectively. They include details about the individual predators, the stimuli used and the behavioural responses from the predators.","documentType":"GEMINI_DOCUMENT","familyName":["Taylor","Dawson","D’Cruz","Jackson","Lowe","Rees","Richardson","Sains","Short","Gilbert","Reader"],"fullName":["Taylor, C.","Dawson, J.J.","D’Cruz, T.","Jackson, H.J.","Lowe, R.","Rees, H.","Richardson, J.","Sains, J.","Short, F.","Gilbert, F.","Reader, T."],"funder":["Natural Environment Research Council"],"givenName":["C.","J.J.","T.","H.J.","R.","H.","J.","F."],"grant":["NE/S000623/1"],"identifier":"ee7ba05a-449b-466e-840c-8de1d3f1d4d1","incomingCitationCount":0,"keyword":["laboratory","Animal behaviour","Batesian mimicry","insect","hoverfly","Syrphidae","wasp","hymenopteran","praying mantis","Mantidae","jumping spider","spider","Salticidae","phiddipus","audax","Thomisidae","Shiny crab-spider","Synema globosum","predator"],"keywordsOther":["Batesian mimicry","insect","hoverfly","Syrphidae","wasp","hymenopteran","praying mantis","Mantidae","jumping spider","spider","Salticidae","phiddipus","audax","Thomisidae","Shiny crab-spider","Synema globosum","predator"],"keywordsPlace":["laboratory"],"keywordsTheme":["Animal behaviour"],"licence":"Open government licence","lineage":"We investigated how different species of invertebrate, all potential predators of flower-visiting insects, responded to 3D printed wasp-like and fly-like stimuli. Our predators were jumping spiders, crab spiders and praying mantises. Each received training to associate wasp stimuli with a negative experience, while fly stimuli were not associated with any positive or negative experience. We then tested predator responses to a range of novel mimetic stimuli with varying levels of similarity to the wasp stimulus. The aim was to determine how accurately a stimulus needed to mimic the negatively-conditioned wasp stimulus before it would be mistaken for the wasp by the predators .\n\nBehavioural observations were conducted in real time during the experimental trials, with video recordings taken in some cases for later reference. A stopwatch was used for timings.\n\nData have been cleaned (for example, removal of invalid or unused data points) and formatted using custom scripts in R v4.3.2.","metadataDate":"2026-06-29T16:19:49.000Z","orcid":["https://orcid.org/0000-0003-4299-7104","https://orcid.org/0000-0002-6941-6157","https://orcid.org/0000-0002-2727-4103","https://orcid.org/0000-0001-7586-8814"],"organisation":["University of Nottingham","NERC EDS Environmental Information Data Centre"],"publicationDate":"2024-07-09T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/ee7ba05a-449b-466e-840c-8de1d3f1d4d1","10.5285/ee7ba05a-449b-466e-840c-8de1d3f1d4d1","doi:10.5285/ee7ba05a-449b-466e-840c-8de1d3f1d4d1"],"resourceType":"Non-geographic dataset","rightsHolder":["University of Nottingham"],"ror":["https://ror.org/01ee9ar58","https://ror.org/04xw4m193"],"shortenedDescription":"Three files describe behavioural trials involving jumping spiders, crab spiders and praying mantises respectively. They include details about the individual predators, the stimuli used and the behavioural responses from the predators.","state":"published","title":"Invertebrate behavioural responses to 3D-printed insect replicas, featuring combinations of traits from wasps and flies, in laboratory trials","topic":["0/Animal behaviour/"],"version":1.0,"view":["public","shofer"]},{"authorAffiliation":["University of Edinburgh","Universidade Eduardo Mondlane","Universidade Lurio","Universidade Zambeze"],"authorFamilyName":["Woollen","Ryan","Nhaduco","Daude","Manguiao","Da Costa","Lisboa","Junior","Mutemba","Pais","Zavale","Cumbula","Xerinda","Buque","Meneses","Rodrigues","Mário","Ribeiro","Domingos","Mbandze","Stedham","Jennings"],"authorFullName":["Woollen, E.","Ryan, C.M.","Nhaduco, O.","Daude, I.A.","Manguiao, A.A.","Da Costa, A.A.","Lisboa, S.N.","Junior, J.F.","Mutemba, L.","Pais, A.","Zavale, M.","Cumbula, S.","Xerinda, H.","Buque, H.","Meneses, D.","Rodrigues, C.","Mário, A.M.","Ribeiro, N.","Domingos, L.P.","Mbandze, A.","Stedham, R.","Jennings, P."],"authorGivenName":["E.","C.M.","O.","I.A.","A.A.","S.N.","J.F.","L.","A.","M.","S.","H.","D.","C.","A.M.","N.","L.P.","R.","P."],"authorOrcid":["https://orcid.org/0000-0002-6504-4835","https://orcid.org/0000-0002-1802-0128"],"authorRor":["https://ror.org/01nrxwf90","https://ror.org/05n8n9378","https://ror.org/03sbnrq14","https://ror.org/02azgvq37v"],"availability":"Available","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)"],"description":"This dataset contains quantitative measurements of woodland structure and composition sampled in twenty-seven different villages across three Districts in Mozambique, Africa. Data were collected from 431 plots where tree stem structure and composition, litter and grass biomass, coarse woody debris, and canopy cover data were recorded. Woodlands within seven villages in Mabalane District, Gaza Province, ten villages in Marrupa District, Niassa Province, and ten villages in Gurue District Zambezia Province were sampled. Data were collected in Mabalane between May-Sep 2014, Marrupa between May-Aug 2015, and Gurue between Sep-Dec 2015. This dataset was collected as part of the Ecosystem Services for Poverty Alleviation (ESPA) funded ACES project , which aims to understand how changing land use impacts on ecosystem services and human wellbeing of the rural poor in Mozambique.","documentType":"GEMINI_DOCUMENT","familyName":["Woollen","Ryan","Nhaduco","Daude","Manguiao","Da Costa","Lisboa","Junior","Mutemba","Pais","Zavale","Cumbula","Xerinda","Buque","Meneses","Rodrigues","Mário","Ribeiro","Domingos","Mbandze","Stedham","Jennings"],"fullName":["Woollen, E.","Ryan, C.M.","Nhaduco, O.","Daude, I.A.","Manguiao, A.A.","Da Costa, A.A.","Lisboa, S.N.","Junior, J.F.","Mutemba, L.","Pais, A.","Zavale, M.","Cumbula, S.","Xerinda, H.","Buque, H.","Meneses, D.","Rodrigues, C.","Mário, A.M.","Ribeiro, N.","Domingos, L.P.","Mbandze, A.","Stedham, R.","Jennings, P."],"funder":["Natural Environment Research Council"],"givenName":["Emily","E.","C.M.","O.","I.A.","A.A.","S.N.","J.F.","L.","A.","M.","S.","H.","D.","C.","A.M.","N.","L.P.","R.","P."],"grant":["NE/K010395/1"],"identifier":"70b5cdda-72df-4007-b10e-d75b4046e603","incomingCitationCount":1,"keyword":["Mozambique","Mabalane District","Gaza Province","Marrupa District","Niassa Province","Gurue District","Zambezia Province","woody debris","leaf litter","grass biomass","stem measurements ","tree stem","decomposition","litter","grass","biomass","tree"],"keywordsOther":["woody debris","leaf litter","grass biomass","stem measurements ","tree stem","decomposition","litter","grass","biomass","tree"],"keywordsPlace":["Mozambique","Mabalane District","Gaza Province","Marrupa District","Niassa Province","Gurue District","Zambezia Province"],"licence":"Open government licence","lineage":"All data were quality assured by the lead author. When in the field, all teams were trained in data collection methods to ensure consistent robust measurements, and data were continually checked for errors as it was collected. All field teams had a translator to translate from the local language to Portuguese. All data were cleaned post digital entry by checking for extreme outliers in the dataset or unexpected values. Anomalous entries were corrected where possible, or were removed and treated as no record. All observations were recorded in Portuguese, and translated to English by the lead author. All of the data were collected electronically in the field for Marrupa and Gurue survey sites using tablets and ODK software. Wherever possible, pre-set answers or binary responses were used (e.g. has the plot been recently burned: true or false) to systematically record qualitative observations and avoid ambiguous results.","locations":["POLYGON((29.68 -27.479, 29.68 -10.347, 42.248 -10.347, 42.248 -27.479, 29.68 -27.479))"],"metadataDate":"2026-06-27T19:29:04.000Z","orcid":["https://orcid.org/0000-0002-6504-4835","https://orcid.org/0000-0002-1802-0128"],"organisation":["University of Edinburgh","Universidade Eduardo Mondlane","Universidade Lurio","Universidade Zambeze","NERC EDS Environmental Information Data Centre","NERC Environmental Information Data Centre"],"publicationDate":"2017-12-18T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/70b5cdda-72df-4007-b10e-d75b4046e603","10.5285/70b5cdda-72df-4007-b10e-d75b4046e603","doi:10.5285/70b5cdda-72df-4007-b10e-d75b4046e603"],"resourceType":"Dataset","rightsHolder":["University of Edinburgh"],"ror":["https://ror.org/01nrxwf90","https://ror.org/05n8n9378","https://ror.org/03sbnrq14","https://ror.org/02azgvq37v","https://ror.org/04xw4m193"],"shortenedDescription":"This dataset contains quantitative measurements of woodland structure and composition sampled in twenty-seven different villages across three Districts in Mozambique, Africa. Data were collected from 431 plots where tree stem structure and composition, litter and grass…","state":"published","title":"Structure and composition of woodlands across Mozambique","version":1.0,"view":["public","hajd"]},{"authorAffiliation":["Portland State University","University of Nottingham","Colorado State University","US Forest Service"],"authorFamilyName":["Colley","Dugdale","Field","Johnson","Mariani","Means-Brous","Pugh","Renan","Schrodt","Thorne","Valman"],"authorFullName":["Colley, M.","Dugdale, S.J.","Field, R.","Johnson, M.","Mariani, M.","Means-Brous, M.","Pugh, B.","Renan, L.","Schrodt, F.","Thorne, C.","Valman, S."],"authorGivenName":["M.","S.J.","R.","B.","L.","F.","C.","S."],"availability":"Available","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)"],"description":"Bird data comprises point counts of bird species and their abundance observed at each collection site. Data are separated into birds within 50m, greater than 50m distant and birds in flight.\n\nThese data were collected from the South Fork McKenzie river, Oregon, USA in June 2021 following the Holiday Farm wildfire in Autumn 2020. Samples were collected from a restored and unrestored reach of the South Fork McKenzie River with a view to quantifying differences in avian response to wildfire in the restored vs. unrestored river reaches.\n\nThe study was conducted by the University of Nottingham, with data collected by partners from The US Forest Service, Portland State University, Washington State University and Colorado State University. Funding for the work was received from the Natural Environment Research Council.","documentType":"GEMINI_DOCUMENT","familyName":["Colley","Dugdale","Field","Johnson","Mariani","Means-Brous","Pugh","Renan","Schrodt","Thorne","Valman"],"fullName":["Colley, M.","Dugdale, S.J.","Field, R.","Johnson, M.","Mariani, M.","Means-Brous, M.","Pugh, B.","Renan, L.","Schrodt, F.","Thorne, C.","Valman, S."],"funder":["Natural Environment Research Council"],"givenName":["M.","S.J.","R.","B.","L.","F.","C.","S."],"identifier":"dd919c8e-ccd6-48ed-a1c0-ef5cf732bdc6","incomingCitationCount":0,"keyword":["Macroinvertebrate","Avian","South fork mckenzie","Stage zero","River restoration","Wildfire","fire","river","restoration","bird"],"keywordsOther":["Macroinvertebrate","Avian","South fork mckenzie","Stage zero","River restoration","Wildfire","fire","river","restoration","bird"],"licence":"Open government licence","lineage":"Point count of bird species carried out across 41 sites (20 restored, 21 unrestored) in the South Fork McKenzie River. Point counts carried out initially over 3 minutes and then a further 2 minutes. Birds were recorded as <50m, >= 50m, or flying over. Each site was attempted to be sampled twice but in 5 cases this was not possible due to field conditions (Points 5, 17, 21,22, and 23)\nMethodology based on the following field protocols:\nRalph, C. J., G. R. Geupel, P. Pyle, T. E. Martin, and D. F. DeSante. 1993. Handbook of field methods for monitoring landbirds. General Technical Report PSW-GTR-144. Pacific Southwest Research Station, U.S. Department of Agriculture, Forest Service, Albany, California.\nStephens, J. L., S. R. Mohren, J. D. Alexander, D. A. Sarr, and K. M. Irvine. 2010. Klamath Network Landbird Monitoring Protocol. Natural Resource Report NPS/KLMN/NRR—2010/187. National Park Service, Fort Collins, Colorado.","locations":["POLYGON((-122.29 44.13, -122.29 44.16, -122.23 44.16, -122.23 44.13, -122.29 44.13))"],"metadataDate":"2026-06-29T15:38:11.000Z","organisation":["Portland State University","University of Nottingham","Colorado State University","US Forest Service","NERC EDS Environmental Information Data Centre"],"publicationDate":"2023-02-03T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/dd919c8e-ccd6-48ed-a1c0-ef5cf732bdc6","10.5285/dd919c8e-ccd6-48ed-a1c0-ef5cf732bdc6","doi:10.5285/dd919c8e-ccd6-48ed-a1c0-ef5cf732bdc6"],"resourceType":"Dataset","rightsHolder":["University of Nottingham"],"ror":["https://ror.org/04xw4m193"],"shortenedDescription":"Bird data comprises point counts of bird species and their abundance observed at each collection site. Data are separated into birds within 50m, greater than 50m distant and birds in flight.\n\nThese data were collected from the South Fork McKenzie river, Oregon, USA…","state":"published","title":"Avian data from the South Fork McKenzie River in Oregon, USA after a wildfire event, 2021","version":1.0,"view":["public","crimar"]},{"authorAffiliation":["University of Stirling"],"authorFamilyName":["Metcalf","Akinbobola","Quilliam"],"authorFullName":["Metcalf, R.","Akinbobola, A.","Quilliam, R."],"authorGivenName":["R.","A."],"authorOrcid":["https://orcid.org/0000-0002-1463-427X","https://orcid.org/0000-0002-6617-2791","https://orcid.org/0000-0001-7020-4410"],"availability":"Available","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)"],"description":"This dataset contains characterisation data, thermotolerance data, anti-fungal drug resistance data and virulence data of Candida isolates from different types of plastic pollution. Samples were collected from marine, estuarine and freshwater environments, and screened for pathogenic species of Candida. These Candida isolates were subsequently assessed for their thermotolerance, anti-fungal drug resistance, and their pathogenicity in a Galleria model of infection. \nData were collected as part of grants NE/V005847/1, Sustainable Plastic Attitudes to benefit Communities and their Environments (SPACES), and NE/S005196/1, Microbial hitch-hikers of marine plastics: the survival, persistence & ecology of microbial communities in the 'Plastisphere'.\n","documentType":"GEMINI_DOCUMENT","familyName":["Metcalf","Akinbobola","Quilliam"],"fullName":["Metcalf, R.","Akinbobola, A.","Quilliam, R."],"funder":["Natural Environment Research Council"],"givenName":["R.","A."],"grant":["NE/V005847/1","NE/S005196/1"],"identifier":"4477f77c-c1c9-44e4-baeb-3353954c8355","incomingCitationCount":0,"keyword":["Central Scotland","Pollution","antifungal resistance","environmental pollution","fungal pathogens","plastisphere","pathogenic yeast","virulence"],"keywordsOther":["antifungal resistance","environmental pollution","fungal pathogens","plastisphere","pathogenic yeast","virulence"],"keywordsPlace":["Central Scotland"],"keywordsTheme":["Pollution"],"licence":"Open government licence","lineage":"At each site, plastic was collected using sterile forceps and placed into sterile ziplock bags. Candida species were recovered from replicate composite samples of each plastic type from each site using selective media. Twenty-seven colonies were isolated, and glycerol stocks prepared and frozen at -20°C.\n\nColony PCR was carried out with primers targeting the ITS region to identify the five common pathogenic species of Candida, i.e., C. albicans, C. glabrata, C. krusei, C. parapsilosis, and C. tropicalis. Different amplicon sizes were used to differentiate between distinct Candida species and three reference clinical pathogenic strains of C. albicans (strain SC 5314), C. glabrata (strain ATCC 2001) and C. tropicalis (strain CAY676), were included as positive controls.\n\nTo further confirm the identity of each isolate, the ITS1 region was amplified and sequenced. All purified PCR products underwent Sanger sequencing and species identification was confirmed using NCBI’s Basic Local Alignment Search Tool.\n\nEach Candida isolate were subjected to minimum inhibitory concentration (MIC) analysis to determine antifungal resistance following the European Committee on Antimicrobial susceptibility testing (EUCAST) antifungal MIC method for yeasts. Resistance to four antifungals at ten concentrations was examined: amphotericin B (0.008 – 4 mg/L), caspofungin (0.008 – 4 mg/L), fluconazole (0.125 – 64 mg/L), voriconazole (0.008 – 4 mg/L).\nTo determine the thermotolerance profile, each isolate underwent an initial incubation at 18°C (simulating an environmental temperature) or 38°C (simulating human body temperature) for 24 h, before being moved to one of three different temperatures (18, 28 or 38°C) where their growth was measured. Absorbance at 570 nm was measured before and after incubation in a spectrophotometer to determine the growth of the isolates. \n\nGalleria melonella was used as an infection model to investigate the pathogenicity of the Candida isolates. Groups of 10 larvae were injected with 10 µL of Candida cells (105 CFU/larvae) into the hemocoel via the last right pro-limb. All experiments were conducted in biological triplicate. An inoculation of 10 µL PBS was used as a control to account for mortality caused by physical injury or infection by contamination. Following injection, larvae were incubated at 37°C, and survival evaluated every 24 h for a total of 120 h. Larvae were considered dead when they did not respond to a touch stimulus.\n","locations":["POLYGON((-6.196 55.398, -6.196 56.753, -0.681 56.753, -0.681 55.398, -6.196 55.398))"],"metadataDate":"2026-06-29T16:26:02.000Z","orcid":["https://orcid.org/0000-0002-1463-427X","https://orcid.org/0000-0002-6617-2791","https://orcid.org/0000-0001-7020-4410"],"organisation":["University of Stirling","NERC EDS Environmental Information Data Centre"],"publicationDate":"2024-06-26T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/4477f77c-c1c9-44e4-baeb-3353954c8355","10.5285/4477f77c-c1c9-44e4-baeb-3353954c8355","doi:10.5285/4477f77c-c1c9-44e4-baeb-3353954c8355"],"resourceType":"Dataset","rightsHolder":["University of Stirling"],"ror":["https://ror.org/04xw4m193","https://ror.org/045wgfr59"],"shortenedDescription":"This dataset contains characterisation data, thermotolerance data, anti-fungal drug resistance data and virulence data of Candida isolates from different types of plastic pollution. Samples were collected from marine, estuarine and freshwater environments, and screened…","state":"published","title":"Characterisation, minimum inhibitory concentration, thermotolerance and virulence of Candida isolated from environmental plastic pollution, Scotland, 2023","topic":["0/Pollution/"],"version":1.0,"view":["public","hajd"]},{"authorAffiliation":["University of Nottingham","Florida International University","University of Highlands and Islands","Terra Motion Limited"],"authorFamilyName":["Mitchell","Dryden","Fallaize","Andersen","Bradley","Large","Sowter"],"authorFullName":["Mitchell, E.G.","Dryden, I.L.","Fallaize, C.J.","Andersen, R.","Bradley, A.V.","Large, D.J.","Sowter, A."],"authorGivenName":["E.G.","I.L.","C.J.","R.","A.V.","D.J.","A."],"authorOrcid":["https://orcid.org/0000-0002-2581-0099","https://orcid.org/0000-0003-4900-3571","https://orcid.org/0000-0001-6148-8239","https://orcid.org/0000-0002-7782-795X","https://orcid.org/0000-0002-6702-9751","https://orcid.org/0000-0003-0559-8526"],"authorRor":["https://ror.org/01ee9ar58","https://ror.org/02gz6gg07","https://ror.org/02s08xt61"],"availability":"Available","catalogue":"eidc","dataFormat":[".R"],"description":"This model code for object oriented data analysis of surface motion time series in peatland landscapes provides the procedure to assess peatland condition using object oriented data analysis. The model code assesses peatland condition according to which cluster each surface motion time series is assigned, based on key measures capturing differences between the time series. It can be run on any machine with R.","documentType":"GEMINI_DOCUMENT","familyName":["Mitchell","Dryden","Fallaize","Andersen","Bradley","Large","Sowter"],"fullName":["Mitchell, E.G.","Dryden, I.L.","Fallaize, C.J.","Andersen, R.","Bradley, A.V.","Large, D.J.","Sowter, A."],"funder":["Natural Environment Research Council"],"givenName":["E.G.","I.L.","C.J.","R.","A.V.","D.J.","A."],"grant":["NE/T010118/1"],"identifier":"dbdb9f19-c039-4a73-b590-e1acc7f79df4","incomingCitationCount":0,"keyword":["Object oriented data analysis","Peatland condition mapping"],"keywordsOther":["Object oriented data analysis","Peatland condition mapping"],"licence":"Open government licence","lineage":"The model code has been created for the purpose of analysing peatland surface motion time series in the NERC grant number NE/T010118/1, as part of the project “Developing a statistical methodology for the assessment and management of peatland (StAMP)” in the Landscape Decisions Programme. This is the first version of the code.","locations":["POLYGON((-7.239 56.492, -7.239 58.634, -2.342 58.634, -2.342 56.492, -7.239 56.492))"],"metadataDate":"2026-06-27T20:06:22.000Z","orcid":["https://orcid.org/0000-0002-2581-0099","https://orcid.org/0000-0003-4900-3571","https://orcid.org/0000-0001-6148-8239","https://orcid.org/0000-0002-7782-795X","https://orcid.org/0000-0002-6702-9751","https://orcid.org/0000-0003-0559-8526"],"organisation":["University of Nottingham","Florida International University","University of Highlands and Islands","Terra Motion Limited","NERC EDS Environmental Information Data Centre"],"publicationDate":"2023-06-28T00:00:00.000Z","recordType":"Model","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/dbdb9f19-c039-4a73-b590-e1acc7f79df4","10.5285/dbdb9f19-c039-4a73-b590-e1acc7f79df4","doi:10.5285/dbdb9f19-c039-4a73-b590-e1acc7f79df4"],"resourceType":"Model","rightsHolder":["University of Nottingham"],"ror":["https://ror.org/01ee9ar58","https://ror.org/02gz6gg07","https://ror.org/02s08xt61","https://ror.org/04xw4m193"],"shortenedDescription":"This model code for object oriented data analysis of surface motion time series in peatland landscapes provides the procedure to assess peatland condition using object oriented data analysis. The model code assesses peatland condition according to which cluster each…","state":"published","title":"Model code for object oriented data analysis of surface motion time series in peatland landscapes","version":1.0,"view":["public","margla"]},{"authorAffiliation":["University of Liverpool","Museo Nacional de Ciencias Naturales, Madrid","University of Cambridge","Institute of Zoology"],"authorFamilyName":["Fenton","Daversa","Bosch","Serrano","Manica","Garner"],"authorFullName":["Fenton, A.","Daversa, D.R.","Bosch, J.","Serrano, C.","Manica, A.","Garner, T.W.J."],"authorGivenName":["Andy","D. R.","J. ","C.","A.","T. W. J."],"authorOrcid":["https://orcid.org/0000-0002-7676-917X","https://orcid.org/0000-0002-8984-8897","https://orcid.org/0000-0002-0099-7934","https://orcid.org/0000-0003-1895-450X","https://orcid.org/0000-0002-0336-9706"],"authorRor":["https://ror.org/04xs57h96","https://ror.org/02v6zg374","https://ror.org/013meh722"],"availability":"Available","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)"],"description":"Data were generated from a mesocosm experiment  to determine the extent to which non-reservoir hosts impact the maintenance and transmission of infections from parasites supported by reservoir hosts.  The three host species were salamanders, Tree frogs (Hyla meridiensis) and Spiny toads (Bufo spinosus). The infection used was Batrachochytrium dendrobatidis (Bd).\n\nThe experiment was executed in the late summer of 2017, at the Centre for Captive Breeding of Threatened Amphibians, located in Rascafria, Spain. ","documentType":"GEMINI_DOCUMENT","familyName":["Fenton","Daversa","Bosch","Serrano","Manica","Garner"],"fullName":["Fenton, A.","Daversa, D.R.","Bosch, J.","Serrano, C.","Manica, A.","Garner, T.W.J."],"funder":["Natural Environment Research Council"],"givenName":["Andy","D. R.","J. ","C.","A.","T. W. J."],"identifier":"093d6938-39f5-414d-b638-7d18e6dc52d3","incomingCitationCount":0,"keyword":["Environmental survey","Hyla meridiensis","Bufo spinosus","salamander","Batrachochytrium dendrobatidis"],"keywordsOther":["Hyla meridiensis","Bufo spinosus","salamander","Batrachochytrium dendrobatidis"],"keywordsTheme":["Environmental survey"],"licence":"Open government licence","lineage":"The experiment quantified Batrachochytrium dendrobatidis (Bd) infection dynamics in experimental host communities that varied in relative abundances of three host species that co-occur in the park: salamanders, Tree frogs (Hyla meridiensis), and Spiny toads (Bufo spinosus). There were five treatments total: \n\n(i) control - 24 salamanders only;\n(ii) 2 species with toads - 12 salamanders and 12 toads;\n(iii) 2 species with frogs - 12 salamanders and 12 frogs;\n(iv) 3 species non-random - 12 salamanders, 6 toads, and 6 frogs; \n(v) 3 species random - relative abundances of salamanders, toads, and frogs chosen at random.","metadataDate":"2026-06-27T18:33:47.000Z","orcid":["https://orcid.org/0000-0002-7676-917X","https://orcid.org/0000-0002-8984-8897","https://orcid.org/0000-0002-0099-7934","https://orcid.org/0000-0003-1895-450X","https://orcid.org/0000-0002-0336-9706"],"organisation":["University of Liverpool","Museo Nacional de Ciencias Naturales, Madrid","University of Cambridge","Institute of Zoology","NERC Environmental Information Data Centre","NERC EDS Environmental Information Data Centre"],"publicationDate":"2020-06-29T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/093d6938-39f5-414d-b638-7d18e6dc52d3","10.5285/093d6938-39f5-414d-b638-7d18e6dc52d3","doi:10.5285/093d6938-39f5-414d-b638-7d18e6dc52d3"],"resourceType":"Non-geographic dataset","rightsHolder":["University of Liverpool","Institute of Zoology"],"ror":["https://ror.org/04xs57h96","https://ror.org/02v6zg374","https://ror.org/013meh722","https://ror.org/04xw4m193"],"shortenedDescription":"Data were generated from a mesocosm experiment  to determine the extent to which non-reservoir hosts impact the maintenance and transmission of infections from parasites supported by reservoir hosts.  The three host species were salamanders, Tree frogs (Hyla meridiensis)…","state":"published","title":"Chytrid fungus infection data in multi-host mesocosm communities","topic":["0/Environmental survey/"],"version":1.0,"view":["public","clwe"]},{"authorAffiliation":["University of Cambridge"],"authorFamilyName":["Evans","Möller","Spencer"],"authorFullName":["Evans, B.R.","Möller, I.","Spencer, T."],"authorGivenName":["B.R.","I.","Tom"],"authorRor":["https://ror.org/013meh722"],"availability":"Available","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)"],"description":"The dataset contains estimates of the projected area of vegetation derived from the analysis of side-on photographs through the vegetation canopy and recorded for survey quadrats at six UK saltmarsh sites. Three of the sites were in Morecambe Bay, North West England and three of the sites were in Essex, South East England, each of these sites consisted of a saltmarsh area and adjacent mudflat area. Each site comprised 22 quadrats in the vegetated area of salt marsh. A calibrated camera was used to photograph through a 600 x 200mm section of vegetation against a red background. Calibrated images were then classified into vegetation and background classes and parameters of vegetation density in the horizontal were computed.\n\nThis data was collected as part of Coastal Biodiversity and Ecosystem Service Sustainability (CBESS): NE/J015644/1. The project was funded with support from the Biodiversity and Ecosystem Service Sustainability (BESS) programme - is a six-year programme (2011-2017) funded by the UK Natural Environment Research Council (NERC) and the Biotechnology and Biological Sciences Research Council (BBSRC) as part of the UK's Living with Environmental Change (LWEC) programme.","documentType":"GEMINI_DOCUMENT","familyName":["Spencer","Evans","Möller"],"fullName":["Spencer, T.","Evans, B.R.","Möller, I."],"funder":["Natural Environment Research Council"],"givenName":["Tom","B.R.","I."],"grant":["NE/J015644/1"],"identifier":"936e04d0-c8ae-47ec-a858-518a77667c70","incomingCitationCount":0,"keyword":["Essex","Morecambe Bay","United Kingdom","CBESS","BESS","vegetation density","projected area","non-destructive","image analysis","biovolume ","biomass","vegetation"],"keywordsOther":["vegetation density","projected area","non-destructive","image analysis","biovolume ","biomass","vegetation"],"keywordsPlace":["Essex","Morecambe Bay","United Kingdom"],"keywordsProject":["CBESS","BESS"],"licence":"Open government licence","lineage":"The method followed that of Möller (2006). Side-on photography was undertaken in the field using a frame to ensure consistent geometry and a calibrated Fuji Finepix XP30 camera. Photographs were rectified using Matlab and exported in TIFF format to Erdas Imagine for classification. A 20-class unsupervised classification was performed followed by manual attribution of classes into \"background\" and vegetation\". The binary image files were then analysed in Matlab based on pixel sizes derived from the camera calibration procedure against a chequerboard background. Further methodological details are contained in the supporting document.","locations":["POLYGON((-3 51.5, -3 54.25, 1 54.25, 1 51.5, -3 51.5))"],"metadataDate":"2026-06-29T16:28:44.000Z","organisation":["University of Cambridge","NERC EDS Environmental Information Data Centre","NERC Environmental Information Data Centre"],"publicationDate":"2016-02-29T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/936e04d0-c8ae-47ec-a858-518a77667c70","10.5285/936e04d0-c8ae-47ec-a858-518a77667c70","doi:10.5285/936e04d0-c8ae-47ec-a858-518a77667c70"],"resourceType":"Dataset","rightsHolder":["University of Cambridge"],"ror":["https://ror.org/013meh722","https://ror.org/04xw4m193"],"shortenedDescription":"The dataset contains estimates of the projected area of vegetation derived from the analysis of side-on photographs through the vegetation canopy and recorded for survey quadrats at six UK saltmarsh sites. Three of the sites were in Morecambe Bay, North West England…","state":"published","supplementalDescription":["Möller, I. (2006). Quantifying saltmarsh vegetation and its effect on wave height dissipation: Results from a UK East coast saltmarsh. Estuarine, Coastal and Shelf Science, 69(3-4), 337-351"],"supplementalName":["Information about the methods used to collect data"],"title":"Coastal Biodiversity and Ecosystem Service Sustainability (CBESS) projected area of vegetation in saltmarsh habitats","version":1.0,"view":["public","hajd"]},{"authorAffiliation":["University of Nottingham","Jadavpur University","Bangladesh University of Engineering and Technology","Vietnam Atomic Energy Instiute","Can Tho University","Electric Power University","Tyne Rivers Trust","Newcastle University","Utrecht University","Geological Survey of Denmark and Greenland","University of Southampton","Vietnam Academy of Science and Technology","University of Glasgow","University College London","Northumbria University","Jacobs (United Kingdom)","British Geological Survey"],"authorFamilyName":["Panizzo","Ghosh","Mashfiqus","Trinh","Van","Do","Chowdhury","Chanda","Fielding","Phan","Henderson","McGowan","Brown","Walker-Trivett","Walton","Banerjee","Nguyễn","Le","Duong","Shil","Bass","Majumdar","Rafi","Shahariar","Roberts","Salgado Bonnet","Sear","Leadbeater","Taylor","Nam","Large","Smith"],"authorFullName":["Panizzo, V.","Ghosh, T.","Mashfiqus, S.","Trinh, D.A.","Van, T.","Do, N.T.","Chowdhury, A.I.A.","Chanda, A.","Fielding, J.","Phan, T.","Henderson, A.","McGowan, S.","Brown, J.","Walker-Trivett, C.","Walton, R.","Banerjee, S.","Nguyễn, L.N.","Le, P.Q.T.","Duong, T.T.","Shil, S.","Bass, A.","Majumdar, M.A.","Rafi, N.N.","Shahariar, M.N.K.","Roberts, L.","Salgado Bonnet, J.","Sear, E.","Leadbeater, E.","Taylor, S.","Nam, T.S.","Large, A.","Smith, A."],"authorGivenName":["Virginia","Tuhin","Salehin","Duc Anh","Tri","Nga Thu","Ahmed Ishtiaque Amin","Abhra","James","Trung","Andrew","Suzanne","Jody","Chloe","Richard","Sumana","Lân Nho","Phương Quynh Thi","Thuy Thi","Souvik","Adrian","Md Anisur","Nafis Nayem","Md Nayeem Khan ","Lucy","Jorge","Emily","Eleanor","Sarah","Trần Sỹ ","Andy"],"authorOrcid":["https://orcid.org/0000-0002-3411-9945","https://orcid.org/0000-0002-3466-867X","https://orcid.org/0000-0002-1513-7240","https://orcid.org/0000-0003-4207-8845","https://orcid.org/0000-0001-7045-1753","https://orcid.org/0000-0002-0250-630X","https://orcid.org/0000-0002-3280-1959","https://orcid.org/0000-0001-6807-5955","https://orcid.org/0000-0002-5944-3135","https://orcid.org/0000-0003-4034-7140","https://orcid.org/0000-0002-1630-2076","https://orcid.org/0000-0002-2258-1374","https://orcid.org/0009-0007-4641-6078","https://orcid.org/0000-0001-7341-662X","https://orcid.org/0000-0003-4712-3668","https://orcid.org/0000-0003-1796-3850","https://orcid.org/0009-0003-9884-3048","https://orcid.org/0000-0003-3982-6582","https://orcid.org/0000-0003-4095-9120","https://orcid.org/0000-0003-0670-0334","https://orcid.org/0000-0001-6445-0076","https://orcid.org/0000-0002-3835-351X"],"authorRor":["https://ror.org/01ee9ar58","https://ror.org/02af4h012","https://ror.org/05a1qpv97","https://ror.org/04jfns044","https://ror.org/0071qz696","https://ror.org/01p4b7n26","https://ror.org/01mj2ze90","https://ror.org/01kj2bm70","https://ror.org/04pp8hn57","https://ror.org/01b40r146","https://ror.org/01ryk1543","https://ror.org/02wsd5p50","https://ror.org/00vtgdb53","https://ror.org/02jx3x895","https://ror.org/049e6bc10","https://ror.org/047khcd84","https://ror.org/04a7gbp98"],"availability":"Embargoed","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)"],"description":"This dataset contains water quality data across rivers and ponds in the Vietnamese Mekong River Delta (MRD), Vietnamese Red River Delta (RRD) and Bangladeshi and Indian Ganges Brahmaputra Meghna (GBM) Delta. The main objective of this work was to establish a baseline database for water quality, covering a wide range of water quality parameters to address emerging environmental concerns, such as anti-microbial resistance for the Bangladeshi Ganges Brahmaputra Meghna Delta. The available data are separated by delta, and are listed below.\n\nBangladeshi GBM\nThree datasets are available: river water quality, pond water quality, and phytoplankton biomonitoring.\nOne river water quality dataset is available, containing point measurements from February 2022 to February 2024 at 11 pre-selected locations of four rivers in the coastal areas of the Bangladeshi GBM. Each of the 4 rivers were sampled 5 times over different seasons. Daily measurements (during each of the 5 sampling periods) include 6-7 samples per site (from morning until 19.00).\nTwo separate pond water quality datasets are available:\n(1) The first ponds dataset contains point measurements of 40 ponds in September 2023 and March 2024. Available data and information include the site location and context - including user and use information (occupation, water source, etc.), physical properties (surface area, depth, etc.), context (region, adjacent buildings, urban setting), and treatment regimes. Available water chemistry data include temperature, pH, total suspended solids, total phosphorus, soluble reactive phosphorus, phosphate, ammonium, nitrate, silia, Δ13c, particulate organic carbon, total dissolved nitrogen, C:N, chloride, sulphate, sodium, potassium, calcium, magnesium, dissolved oxygen, SPC, alkalinity, rugged dissolved oxygen, electrical conductivity, turbidity, total coliforms, E. Coli, algal pigments, and sediment chemistry. Additionally, pond depth water chemistry profiles - including water body stratification depths and pycnoclines - are available for 39/40 ponds in September 2023.\n(2) The second ponds dataset contains point measurements of 20 ponds and groundwater tubewells from Gabura, Satkhira and South Bedkashi, Khulna from February 2022 to February 2024. Tubewells were sampled 5 times (once per day) during the same sampling period as the river water quality dataset. Parameters here include water quality variables (pH, conductivity, turbidity), microbial indicators, and selected emerging contaminants.\nOne phytoplankton biomonitoring dataset is available for 8 pond and stream sites from February-March 2022. Each sampling site has a variable number of diatom species. Measurements include concentration (number per ml), biovolume and mean cell biovolume. \n\nIndian GBM\nThree datasets are available: river water quality, pond water quality, and phytoplankton biomonitoring.\nOne river water quality monitoring dataset seasonal water quality measurements collected from multiple sampling stations across the Indian Sundarbans region. The dataset includes physicochemical, biological, and bacteriological parameters, measured under high tide and low tide conditions across nine seasonal campaigns (2021-2024). The data support environmental monitoring, estuarine studies, and biogeochemical assessments.\nOne pond water quality dataset includes point measurements from 29 ponds in the Indian GBM in three sampling periods: July 2024, December 2023 and March 2024. Data include details of the site location, context (i.e. region), user and use information, water chemistry (salinity, temperature, pH, total alkalinity, oxidation-reduction potential, dissolved oxygen, secchi depth, total dissolved solids, total phosphorus, phosphate anions, soluble reactive phosphorus, nitrate anions, total Kjedahl nitrogen, ammoniacal nitrogen, silicate, total suspended solids, conductivity, absolute conductivity, chloride anions, sodium cations, potassium cations, calcium cations, magnesium cations, sulphate anions, dissolved silica, Chl A, Chl B, Chl C, total Chl, carotenoid, total coliform and E Coli.\nOne phytoplankton biomonitoring dataset is available for 20 sites in 3 time periods - both low and high tide for December 2021, July 2022, and March 2023. Data include concentration and biovolumes, concentrations per 1 mL, concentrations per 10 mL, biovolume per 1 mL, and biovolume per 10 mL for 48 diatom species.\n\nRRD\nThree datasets are available for the Vietnamese Red River Delta: two river surface water quality datasets, and one surface pond water quality datasets.\nThe first dataset contains monthly water chemistry data in the RRD from March 2018 to February 2022. The data include pH, TDS, Ca2+, Mg2+, Na+, K+, HCO3-, SiO2, Cl-, and SO42-. Data collected at five stations namely Yen Bai, Vu Quang, Hoa Binh, Gian Khau, and Quyet Chien.\nThe Red River Delta is both a densely populated region and an area of intensive agricultural activity, implying significant potential for pollution. To provide a comprehensive assessment of water quality across the delta and evaluate the impacts of different human activities, we conducted monthly sampling at 22 sites throughout the region. These sites are strategically located across diverse land-use types and at the confluences of major rivers-including the Red, Day, and Nhue rivers-and their tributaries, enabling us to trace potential sources of pollution within the area.\nWithin the second dataset, the following data are available:\n-\tStable isotopes (July 2019-March 2024)\n-\tOrganic content - dissolved organic carbon, dissolved inorganic carbon & particulate organic carbon (July 2019-March 2024)\n-\tPhysiochemistry - temperature, dissolved oxygen, salinity, oxidation reduction potential, pH, turbidity, conductivity, total dissolved solid and total suspended solids (July 2019-March 2024)\n-\tMajor ions (Na, Mg, K, Ca, Cl, SO4, B; July 2019-March 2024)\n-\tNutrients (NO3-N, NO2-N, NH4-N, total nitrogen, soluble reactive phosphorus, TSP, total phosphorus, SIO2 & alkalinity; July 2019-March 2024)\n-\tWater discharge (01-01-2014 to 31-12-2023)\n-\tQuantitative phytoplankton for (1) the Red River (December 2019-March 2024) and (2) the Day River (July 2019-March 2024).\nLastly, one dataset containing water and sediment chemistry of 37 ponds in March 2023 is available. This includes pond user and use information, and water and sediment quality parameters for 37 sampling locations in 36 ponds in the Red River Delta taken in March 2023. The data include details of the site location, pond physical properties (i.e. age, surface area, depth), context (i.e. region, adjacent buildings, urban setting), use information (i.e. agricultural, water source), treatment regimes, water chemistry (i.e. Temp, pH, Secchi depth, Total Suspended Solids, Total Phosphorus, Soluble Reactive Phosphorus, Total Nitrogen, Nitrite, Nitrate, Ammonium, Nitrate δ15N/ δ18O, Aquatic Si, Δ13C, Particulate Organic Carbon, Dissolved Organic Carbon, Total Dissolved Nitrogen, C:N, Chloride anions, Sulphate anion, dissolved oxygen, SPC), algal pigments, and sediment chemistry.\n\nMRD\nTwo datasets are available for the Vietnamese Mekong River Delta. The first includes water quality monitoring of surface water in October 2021 in three provinces: Ca Mau, Soc Trang and Kien Giang.  Parameters include physiochemical and microbiological water quality measurements, including Ammonium (NH4+), BOD5, COD, Chloride (Cl-), DO, E. coli, Nitrate (NO3-), Nitrite (NO2-), pH, Phosphate (PO43-), Temperature (°C), Total Coliform, Total Iron (Fe), TSS, Turbidity (NTU). The total number of sampling sites is 126 across Soc Trang (N = 35), Kien Giang (N = 49) and Ca Mau (N = 42). \nThe second dataset includes further surface water quality monitoring and water quality index metric in Soc Trang and Ca Mau provinces. Cà Mau includes data from 52 stations (NM-01 to NM-52) sampled during dry and wet seasons (coded as Season 1 and Season 2) from 2015 to 2020. Sóc Trăng includes data from 21 stations (coded M1 to M21) sampled annually from 2014 to 2018. The stations cover diverse water environments including freshwater and brackish water systems. Parameters measured include field parameters (pH, temperature, dissolved oxygen, electrical conductivity), organic pollution indicators (BOD5, COD), nutrients (N-NH4, P-PO4), solids (TSS, Turbidity), metals (Fe, Hg, As, Cu etc.), anions (Cl-, SO4-), salinity, total coliform, and petroleum hydrocarbons. A Water Quality Index (WQI) derived from an Artificial Neural Network (ANN), is also calculated for most samples.","documentType":"GEMINI_DOCUMENT","familyName":["Panizzo","Ghosh","Mashfiqus","Trinh","Van","Do","Chowdhury","Chanda","Fielding","Phan","Henderson","McGowan","Brown","Walker-Trivett","Walton","Banerjee","Nguyễn","Le","Duong","Shil","Bass","Majumdar","Rafi","Shahariar","Roberts","Salgado Bonnet","Sear","Leadbeater","Taylor","Nam","Large","Smith"],"fullName":["Virginia Panizzo","Panizzo, V.","Ghosh, T.","Mashfiqus, S.","Trinh, D.A.","Van, T.","Do, N.T.","Chowdhury, A.I.A.","Chanda, A.","Fielding, J.","Phan, T.","Henderson, A.","McGowan, S.","Brown, J.","Walker-Trivett, C.","Walton, R.","Banerjee, S.","Nguyễn, L.N.","Le, P.Q.T.","Duong, T.T.","Shil, S.","Bass, A.","Majumdar, M.A.","Rafi, N.N.","Shahariar, M.N.K.","Roberts, L.","Salgado Bonnet, J.","Sear, E.","Leadbeater, E.","Taylor, S.","Nam, T.S.","Large, A.","Smith, A."],"funder":["Natural Environment Research Council"],"givenName":["Virginia","Tuhin","Salehin","Duc Anh","Tri","Nga Thu","Ahmed Ishtiaque Amin","Abhra","James","Trung","Andrew","Suzanne","Jody","Chloe","Richard","Sumana","Lân Nho","Phương Quynh Thi","Thuy Thi","Souvik","Adrian","Md Anisur","Nafis Nayem","Md Nayeem Khan ","Lucy","Jorge","Emily","Eleanor","Sarah","Trần Sỹ ","Andy"],"grant":["NE/S008926/1"],"identifier":"f311f69d-ecd2-4505-9882-e59d9b56852d","incomingCitationCount":0,"keyword":["Water quality","Pollution","Environmental survey","Environmental risk","Hydrology","Red River Delta","Vietnam","Mekong River Delta","Ganges Brahmaputra Meghna Delta","India","Bangladesh","river","pond","discharge regime","artificial neural network","surface water","monitoring","Ca Mau","Soc Trang","Kien Giang","nutrient","heavy metal","coliform bacterium","water quality index","time series","major ions","inorganic geochemistry","organic geochemistry","phytoplankton biochemistry","major ion geochemistry","pH","total dissolved solids","total coliform","physicochemical","BOD","COD","dissoved oxygen","E. coli","Sundarbans","estuarine monitoring","seasonal dataset","tidal sampling","carbon flux","mangrove ecosystem","groundwater","baseline study","antimicrobial resistance"],"keywordsOther":["Red River Delta","Vietnam","Mekong River Delta","Ganges Brahmaputra Meghna Delta","India","Bangladesh","river","pond","discharge regime","artificial neural network","surface water","monitoring","Ca Mau","Soc Trang","Kien Giang","nutrient","heavy metal","coliform bacterium","water quality index","time series","major ions","inorganic geochemistry","organic geochemistry","phytoplankton biochemistry","major ion geochemistry","pH","total dissolved solids","total coliform","physicochemical","BOD","COD","dissoved oxygen","E. coli","Sundarbans","estuarine monitoring","seasonal dataset","tidal sampling","carbon flux","mangrove ecosystem","groundwater","baseline study","antimicrobial resistance"],"keywordsTheme":["Water quality","Pollution","Environmental survey","Environmental risk","Hydrology"],"licence":"Open government licence","lineage":"Bangladeshi GBM\nSamples from the first pond water quality dataset were generated through sonde and laboratory analyses. Pond depth water chemistry profiles were collected through sonde measurements.\nSamples from the second pond water quality dataset and river water quality dataset were collected using standard water sampling protocols for rivers and tubewells - including in-situ measurements of temperature and conductivity and the collection of samples in pre-cleaned sterilised containers for subsequent laboratory analyses. Samples were analysed during standard probes and laboratory equipment. \nPhytoplankton biomonitoring data were obtained using the phytoplankton submerged bottle method, sedimentation chambers were used for analyses using the Utermohl method. Pigment data are currently being processed and the data are forthcoming.\n\nIndian GBM\nThe river water quality dataset samples were collected from Water Sampling Points (WSPs) across the Indian Sundarbans region, extending from Diamond Harbour to Hingalganj. Initially 20 stations (M21-PRM22), later expanded to 23 stations (from M22 onwards). Seasonal sampling incorporates three periods: pre-monsoon, monsoon and post-monsoon and 9 seasonal campaigns between 2021-2024. Each sampling period contains high tide and low tide measurements. Measurements were conducted using a multiparameter probe (pH, DO, conductivity, salinity, temperature, ORP), LI-COR LI-8x0 IRGA (CO₂ flux and pCO₂), anemometer (wind velocity), and Secchi disk (water transparency). Water samples were collected in sealed bottles and preserved immediately using appropriate reagents: HgCl₂ / H₂SO₄ for nutrients; Lugol's iodine for chlorophyll-a. Separate containers were used for bacteriological and chemical analysis. Laboratory analyses were conducted following APHA Standard Methods for nutrients, major ions, and bacteriological parameters (MPN method). Samples from the pond water quality dataset were generated through sonde measurements and standard laboratory analyses. Phytoplankton biomonitoring data were obtained used the filled bottle method, and analysed using Lund cell repeats.\n\nRRD\nWater samples from 22 selected sites across the Red River Delta were collected monthly. The samples were then analysed in the laboratory on the same day or within 24 hours of collection. When immediate analysis was not possible, they were stored under refrigerated or frozen conditions to preserve sample integrity, in accordance with Vietnamese standards. Physico-chemical parameters (pH, total dissolved solids [TDS]) were measured in-situ by a Hydrolab sonde DS5. Each sample was analysed in the laboratory for major cations (Ca2+, Mg2+, Na+, and K+), major anions (Cl- , SO4 2- and HCO3 - ) and dissolved silica (SiO2). Pond water chemistry data were collected with a YSI EXO probe.\n\nMRD\nFor the water quality monitoring dataset, surface water grab samples collected at field sites and transported to Can Tho University laboratory (Dept. of Environmental Sciences) for analysis. Temperature and DO measured in-situ. All analyses conducted per Vietnamese national standards (TCVN) on 25 October 2021 and certified by Head of Laboratory. \nFor the second water quality monitoring and water quality index dataset, the field procedures for surface water sampling, preservation, and transportation strictly adhere to TCVN 6663-3:2016 and associated framework standards (TCVN 6663-1:2011, 6663-4:2018, 6663-6:2018, and 8880:2011) to guarantee sample integrity. Methodologically, this entails the immediate in-situ measurement of physicochemical parameters, filtration of dissolved constituents through 0.45 µm membranes, and the application of parameter-specific chemical preservatives. All collected samples were subsequently stored in dark, insulated conditions at 3°C ± 2°C and transported to the analytical facility within a 24-hour window, accompanied by a comprehensive Chain of Custody (CoC) record. Surface water sampling was conducted in strict accordance with Vietnamese standard TCVN 6663-6:2018. Sampling locations were selected in areas with stable flow, representative of the overall water quality of the water body, with the container opening facing against the current to avoid local contamination. Samples were collected at a depth of 0.2m to 0.5m to eliminate the influence of surface scum and bottom sediments. Immediately after collection, rapidly changing parameters (pH, DO, EC, temperature) were measured in the field. Concurrently, samples were filtered, preserved with specialized chemicals, and stored under cold conditions (1°C to 5°C) during transport to the laboratory.","locations":["POLYGON((88.5 8.252, 88.5 25.571, 107.513 25.571, 107.513 8.252, 88.5 8.252))"],"metadataDate":"2026-06-27T19:36:46.000Z","orcid":["https://orcid.org/0000-0002-3411-9945","https://orcid.org/0000-0002-3466-867X","https://orcid.org/0000-0002-1513-7240","https://orcid.org/0000-0003-4207-8845","https://orcid.org/0000-0001-7045-1753","https://orcid.org/0000-0002-0250-630X","https://orcid.org/0000-0002-3280-1959","https://orcid.org/0000-0001-6807-5955","https://orcid.org/0000-0002-5944-3135","https://orcid.org/0000-0003-4034-7140","https://orcid.org/0000-0002-1630-2076","https://orcid.org/0000-0002-2258-1374","https://orcid.org/0009-0007-4641-6078","https://orcid.org/0000-0001-7341-662X","https://orcid.org/0000-0003-4712-3668","https://orcid.org/0000-0003-1796-3850","https://orcid.org/0009-0003-9884-3048","https://orcid.org/0000-0003-3982-6582","https://orcid.org/0000-0003-4095-9120","https://orcid.org/0000-0003-0670-0334","https://orcid.org/0000-0001-6445-0076","https://orcid.org/0000-0002-3835-351X"],"organisation":["University of Nottingham","Jadavpur University","Bangladesh University of Engineering and Technology","Vietnam Atomic Energy Instiute","Can Tho University","Electric Power University","Tyne Rivers Trust","Newcastle University","Utrecht University","Geological Survey of Denmark and Greenland","University of Southampton","Vietnam Academy of Science and Technology","University of Glasgow","University College London","Northumbria University","Jacobs (United Kingdom)","British Geological Survey","NERC EDS Environmental Information Data Centre"],"publicationDate":"2026-06-23T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/f311f69d-ecd2-4505-9882-e59d9b56852d","10.5285/f311f69d-ecd2-4505-9882-e59d9b56852d","doi:10.5285/f311f69d-ecd2-4505-9882-e59d9b56852d"],"resourceType":"Dataset","rightsHolder":["Newcastle University"],"ror":["https://ror.org/01ee9ar58","https://ror.org/02af4h012","https://ror.org/05a1qpv97","https://ror.org/04jfns044","https://ror.org/0071qz696","https://ror.org/01p4b7n26","https://ror.org/01mj2ze90","https://ror.org/01kj2bm70","https://ror.org/04pp8hn57","https://ror.org/01b40r146","https://ror.org/01ryk1543","https://ror.org/02wsd5p50","https://ror.org/00vtgdb53","https://ror.org/02jx3x895","https://ror.org/049e6bc10","https://ror.org/047khcd84","https://ror.org/04a7gbp98","https://ror.org/04xw4m193"],"shortenedDescription":"This dataset contains water quality data across rivers and ponds in the Vietnamese Mekong River Delta (MRD), Vietnamese Red River Delta (RRD) and Bangladeshi and Indian Ganges Brahmaputra Meghna (GBM) Delta. The main objective of this work was to establish a baseline…","state":"published","title":"Surface water quality data from rivers and ponds in the Mekong Delta, Red River Delta and Ganges Brahmaputra Meghna Delta, 2018-2024","topic":["0/Water quality/","0/Pollution/","0/Environmental survey/","0/Environmental risk/","0/Hydrology/"],"version":1.0,"view":["public","katwri"]},{"authorAffiliation":["University of Exeter"],"authorFamilyName":["Baker"],"authorFullName":["Baker, D.J."],"authorGivenName":["D.J."],"authorOrcid":["https://orcid.org/0000-0002-0466-8222"],"availability":"Unknown","catalogue":"eidc","dataFormat":["rd","r","rdata","Plain text"],"description":"The speciesRecordTools R package contains functions for examining the distribution of species records, understanding sampling trends and potential biases, and building correlative presence-background species distribution models for prediction of the distribution of species across the landscape. The package is built to work with the Environmental Record Centre for Cornwall and the Isles of Scilly's (ERCCIS) opportunistic species records.","documentType":"GEMINI_DOCUMENT","familyName":["Baker"],"fullName":["Baker, D.J."],"funder":["Natural Environment Research Council"],"givenName":["D.J."],"grant":["NE/V007726/1"],"identifier":"030b49f4-9e1f-46e9-ad98-157d8668a517","incomingCitationCount":0,"keyword":["Biodiversity","Modelling","opportunistic records","spatial sampling bias","presence-background models","species distribution"],"keywordsOther":["opportunistic records","spatial sampling bias","presence-background models","species distribution"],"keywordsTheme":["Biodiversity","Modelling"],"licence":"Open government licence","lineage":"Code supplied here can be used to analyse data held by ERCCIS (Cornwall Wildlife Trust). The data is not included in the package but can be requested https://erccis.org.uk/requesting-data. The tools provided in this package were designed in collaboration with ERCCIS to overcome some of the limitations associated with these data when used to map the distribution of species. In particular, the methods attempt to address sparse sampling and spatial sampling bias associated with sampling for many species. Distribution data is required to support planning decisions and local nature recovery strategies within the region. ","locations":["POLYGON((-6.757 49.504, -6.757 51.052, -4.043 51.052, -4.043 49.504, -6.757 49.504))"],"metadataDate":"2026-05-11T18:20:55.000Z","orcid":["https://orcid.org/0000-0002-0466-8222"],"organisation":["University of Exeter","NERC EDS Environmental Information Data Centre"],"publicationDate":"2024-10-09T00:00:00.000Z","recordType":"Software","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/030b49f4-9e1f-46e9-ad98-157d8668a517","10.5285/030b49f4-9e1f-46e9-ad98-157d8668a517","doi:10.5285/030b49f4-9e1f-46e9-ad98-157d8668a517"],"resourceType":"Software","rightsHolder":["University of Exeter"],"ror":["https://ror.org/04xw4m193"],"shortenedDescription":"The speciesRecordTools R package contains functions for examining the distribution of species records, understanding sampling trends and potential biases, and building correlative presence-background species distribution models for prediction of the distribution of…","state":"published","title":"Tools for modelling species distributions using data from the Environmental Record Centre for Cornwall and the Isles of Scilly (ERCCIS)","topic":["0/Biodiversity/","0/Modelling/"],"version":1.0,"view":["public","tinzha"]},{"authorAffiliation":["Radboud University","University of Southampton"],"authorFamilyName":["Robroek","Shepherd","Steele","Dumont"],"authorFullName":["Robroek, B.J.M.","Shepherd, H.E.R.","Steele, M.N.","Dumont, M.G."],"authorGivenName":["B.J.M.","H.E.R.","M.N.","M.G."],"authorOrcid":["https://orcid.org/0000-0002-6714-0652","https://orcid.org/0000-0002-7077-3581","https://orcid.org/0000-0001-9949-225X","https://orcid.org/0000-0002-7347-8668"],"authorRor":["https://ror.org/016xsfp80","https://ror.org/01ryk1543"],"availability":"Available","catalogue":"eidc","dataFormat":["Plain text"],"description":"This dataset contains biogeochemical and edaphic information from burned peat soil on the Stalybridge estate located near Manchester (UK), commonly referred to as Saddleworth moor. This study was conducted after a wildfire fire on the Saddleworth moor in June 2018.\n\nThe sample plots included areas with deep and shallow peat burn. The data includes geographical information (location, elevation and slope), soil temperature and soil chemical composition (carbon, nitrogen and 22 other elements).\n\nThe dataset is the result of research funded by a NERC Urgency grant entitled 'RECOUP-Moor: Restoring Ecosystem CarbOn Uptake of Post-fire Moorland' (NE/S011943/1, led by Dr. Bjorn Robroek of the University of Southampton (now Radboud University Nijmegen, the Netherlands).","documentType":"GEMINI_DOCUMENT","familyName":["Robroek","Shepherd","Steele","Dumont"],"fullName":["Robroek, B.","Robroek, B.J.M.","Shepherd, H.E.R.","Steele, M.N.","Dumont, M.G."],"funder":["Natural Environment Research Council"],"givenName":["Bjorn","B.J.M.","H.E.R.","M.N.","M.G."],"grant":["NE/S011943/1"],"identifier":"1fa8d605-b996-4687-ace2-1fa59cd5c6dd","incomingCitationCount":0,"keyword":["Environmental risk","Soil","Blanket bog","Moorland","Peatland","Wildfire","Soil biochemistry","Soil edaphics","bog","fire","soil","soil chemistry"],"keywordsOther":["Blanket bog","Moorland","Peatland","Wildfire","Soil biochemistry","Soil edaphics","bog","fire","soil","soil chemistry"],"keywordsTheme":["Environmental risk","Soil"],"licence":"Open government licence","lineage":"We established ten plots in October 2018 at the post-fire site. Each plot was 10 m x 10 m in size. We identified five of these plots as suffering a less severe (shallow) burn. The other 5 plots were in areas where a more severe (deep) burn was identified. In all plots the surface vegetation had been removed by the fire exposing the bare peat. We determined the geographical properties of each plot. This included their geographical location, elevation and slope. We also measured soil temperature at each location at multiple time points over the following 24-months.\n\nOn July 23rd 2019 we extracted small peat samples from the surface of each plot. Each sample was 5 cm x 5 cm in diameter and 2 cm in depth. The samples were homogenised and kept at c. 5 deg C until further analysis was completed to determine their chemical composition. In preparation for the chemical analysis of each sample we dried the peat at 70 deg C for 72 hours. This was then crushed forming a fine homogenous powder.\n\nTo determine the carbon and nitrogen content of each sample we extracted three sub-samples of the fine peat powder. Each sample was then combusted at 1800 deg C and the percentage of carbon and nitrogen released was quantified. This was performed using a Vario Micro Cube (Elementar). For each plot, the content of each sub-sample was compared to ensure that the observed values were consistent, and the samples were homogenous. An average of the three sub-samples was then taken to provide one value per plot.\n\nTo determine the composition of other elements within the samples, we extracted two sub-samples from each plot sample and performed Inductively Coupled Plasma-Mass-Spectrometry (ICP-MS) analysis on each of the sub-samples. This was used to determine the relative composition of 22 elements. For each plot, an average of the two sub-samples was taken.","locations":["POLYGON((-1.966 53.543, -1.966 53.546, -1.942 53.546, -1.942 53.543, -1.966 53.543))"],"metadataDate":"2026-06-29T17:13:43.000Z","orcid":["https://orcid.org/0000-0002-6714-0652","https://orcid.org/0000-0002-7077-3581","https://orcid.org/0000-0001-9949-225X","https://orcid.org/0000-0002-7347-8668"],"organisation":["Radboud University","University of Southampton","NERC EDS Environmental Information Data Centre"],"publicationDate":"2021-09-23T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/1fa8d605-b996-4687-ace2-1fa59cd5c6dd","10.5285/1fa8d605-b996-4687-ace2-1fa59cd5c6dd","doi:10.5285/1fa8d605-b996-4687-ace2-1fa59cd5c6dd"],"resourceType":"Dataset","rightsHolder":["Radboud University"],"ror":["https://ror.org/016xsfp80","https://ror.org/01ryk1543","https://ror.org/04xw4m193"],"shortenedDescription":"This dataset contains biogeochemical and edaphic information from burned peat soil on the Stalybridge estate located near Manchester (UK), commonly referred to as Saddleworth moor. This study was conducted after a wildfire fire on the Saddleworth moor in June 2018.\n\nThe…","state":"published","title":"Biogeochemical and edaphic data from burned peat soil on the Stalybridge estate (UK), October 2018","topic":["0/Environmental risk/","0/Soil/"],"version":1.0,"view":["public","clwe"]},{"authorAffiliation":["UK Centre for Ecology & Hydrology"],"authorFamilyName":["Rowland","Marston","O'Neil"],"authorFullName":["Rowland, C.S.","Marston, C.G.","O'Neil, A.W."],"authorGivenName":["C.S. ","C.G.","A.W."],"authorOrcid":["https://orcid.org/0000-0002-0459-506X","https://orcid.org/0000-0002-2070-2187","https://orcid.org/0000-0003-3591-1034"],"authorRor":["https://ror.org/00pggkr55"],"availability":"Controlled","catalogue":"eidc","dataFormat":["SpatiaLite"],"description":"This is a vector data set representing the land surface of Northern Ireland, classified into 21 UKCEH land cover classes, based upon Biodiversity Action Plan broad habitats. This vector Land Parcel dataset is the result of intersecting the 10m raster classified pixel dataset with the UKCEH Land Parcel Spatial Framework to generate summary land parcel attributes for each land cover parcel. A full description of this and all UKCEH LCM2024 products are available from the LCM2024 product documentation.","documentType":"GEMINI_DOCUMENT","familyName":["Marston","Rowland","O'Neil"],"fullName":["Marston, C.G.","Rowland, C.S.","O'Neil, A.W."],"funder":["Natural Environment Research Council"],"givenName":["C.G.","C.S. ","A.W."],"grant":["NE/Y006208/1"],"identifier":"99ecdc84-5313-48c2-9fad-6a5e8ad3953e","incomingCitationCount":0,"keyword":["Northern Ireland","Land cover","Mapping","Biodiversity Action Plan","land cover","map","habitat"],"keywordsOther":["Biodiversity Action Plan","land cover","map","habitat"],"keywordsPlace":["Northern Ireland"],"keywordsTheme":["Land cover","Mapping"],"licence":"Non-Open government licence","lineage":"UKCEH’s automated land cover algorithms classify 10 m pixels across the whole of UK. A Random Forest classifier is used to classify four composite satellite images representing per season median surface reflectance, based on training data comprising locations of known land cover for 21 land cover classes. Seasonal images were integrated with context layers (e.g., height, aspect, slope, coastal proximity, urban proximity and so forth) to reduce confusion among classes with similar spectra.  \n\nLand cover was validated by organising the 10 m pixel classification into a land parcel framework (the LCM2024 classified land parcels product). The classified land parcels were compared to known land cover producing a confusion matrix to determine overall and per class accuracy. Details are available from the product documentation.\n\nThe 25 m rasterised land parcels product is created by rasterising the corresponding land parcel product.","locations":["POLYGON((-8.178 54.022, -8.178 55.313, -5.432 55.313, -5.432 54.022, -8.178 54.022))"],"metadataDate":"2026-06-27T18:51:56.000Z","orcid":["https://orcid.org/0000-0002-2070-2187","https://orcid.org/0000-0002-0459-506X","https://orcid.org/0000-0003-3591-1034"],"organisation":["UK Centre for Ecology & Hydrology","NERC EDS Environmental Information Data Centre"],"publicationDate":"2025-07-18T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/99ecdc84-5313-48c2-9fad-6a5e8ad3953e","10.5285/99ecdc84-5313-48c2-9fad-6a5e8ad3953e","doi:10.5285/99ecdc84-5313-48c2-9fad-6a5e8ad3953e"],"resourceType":"Dataset","rightsHolder":["UK Centre for Ecology & Hydrology"],"ror":["https://ror.org/00pggkr55","https://ror.org/04xw4m193"],"shortenedDescription":"This is a vector data set representing the land surface of Northern Ireland, classified into 21 UKCEH land cover classes, based upon Biodiversity Action Plan broad habitats. This vector Land Parcel dataset is the result of intersecting the 10m raster classified pixel…","state":"published","title":"Land Cover Map 2024 (land parcels, N. Ireland)","topic":["0/Land cover/","0/Mapping/"],"version":1.0,"view":["public","jashun"]},{"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":["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":["UK Centre for Ecology & Hydrology"],"authorFamilyName":["Feuchtmayr","De Ville","Fletcher","Thackeray"],"authorFullName":["Feuchtmayr, H.","De Ville, M.M.","Fletcher, J.M.","Thackeray, S.J."],"authorGivenName":["H.","M.M.","J.M.","S.J."],"authorOrcid":["https://orcid.org/0000-0002-2028-4843","https://orcid.org/0000-0002-3808-1534","https://orcid.org/0000-0002-8788-8449"],"authorRor":["https://ror.org/00pggkr55"],"availability":"Available","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)"],"description":"The data available to download comprise hypolimnion temperature (TEMP) in degrees Celsius, and hypolimnion dissolved oxygen concentration (DO) in mg per litre. All data have been measured in a depth of 13.5 to 15 m. All data are from January 2005 until the end of 2009.  This is part of a long-term monitoring dataset from fortnightly sampling at Esthwaite Water in Cumbria, England. The data have been collected by the UK Centre for Ecology & Hydrology (UKCEH).  \n\nThis work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability.","documentType":"GEMINI_DOCUMENT","familyName":["Feuchtmayr","De Ville","Fletcher","Thackeray"],"fullName":["Feuchtmayr, H.","De Ville, M.M.","Fletcher, J.M.","Thackeray, S.J."],"funder":["Natural Environment Research Council"],"givenName":["H.","M.M.","J.M.","S.J."],"grant":["NE/R016429/1"],"identifier":"bc8708ee-cde6-4986-9bff-5508ed4ebdb5","incomingCitationCount":0,"keyword":["Lake District","Water quality","Lake monitoring","hypolimnion","dissolved oxygen","lake","water temperature of lake, stagnant surface water"],"keywordsOther":["Lake monitoring","hypolimnion","dissolved oxygen","lake","water temperature of lake, stagnant surface water"],"keywordsPlace":["Lake District"],"keywordsTheme":["Water quality"],"licence":"Open government licence","lineage":"Please note that the data presented here are raw data that have not yet been quality controlled and calibrated. However, data has been double entered and checked visually. Missing data are due to weather conditions or staff shortage.\nMeasurements are made from a boat at a marked location (buoy) at the deepest part of the lake.\n","locations":["POLYGON((-3.001 54.345, -3.001 54.374, -2.966 54.374, -2.966 54.345, -3.001 54.345))"],"metadataDate":"2026-06-29T16:23:20.000Z","orcid":["https://orcid.org/0000-0002-2028-4843","https://orcid.org/0000-0002-3808-1534","https://orcid.org/0000-0002-8788-8449"],"organisation":["UK Centre for Ecology & Hydrology","NERC EDS Environmental Information Data Centre"],"publicationDate":"2024-06-19T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/bc8708ee-cde6-4986-9bff-5508ed4ebdb5","10.5285/bc8708ee-cde6-4986-9bff-5508ed4ebdb5","doi:10.5285/bc8708ee-cde6-4986-9bff-5508ed4ebdb5"],"resourceType":"Dataset","rightsHolder":["UK Centre for Ecology & Hydrology"],"ror":["https://ror.org/00pggkr55","https://ror.org/04xw4m193"],"shortenedDescription":"The data available to download comprise hypolimnion temperature (TEMP) in degrees Celsius, and hypolimnion dissolved oxygen concentration (DO) in mg per litre. All data have been measured in a depth of 13.5 to 15 m. All data are from January 2005 until the end of 2009.…","state":"published","title":"Hypolimnion temperature and oxygen data from Esthwaite Water, UK, 2005-2009","topic":["0/Water quality/"],"version":1.0,"view":["public","simgil"]},{"authorAffiliation":["UK Centre for Ecology & Hydrology"],"authorFamilyName":["Tomlinson","Carnell","Levy","Williams","Vieno","Scheffler","Harrison","Lofts"],"authorFullName":["Tomlinson, S.J.","Carnell, E.J.","Levy, P.","Williams, M.","Vieno, M.","Scheffler, J.","Harrison, P.A.","Lofts, S."],"authorGivenName":["S.J.","E.J.","P.","M.","J.","P.A.","S."],"authorOrcid":["https://orcid.org/0000-0002-3237-7596","https://orcid.org/0000-0003-0870-1955","https://orcid.org/0000-0002-8505-1901","https://orcid.org/0000-0001-6047-8661","https://orcid.org/0000-0001-7741-9377","https://orcid.org/0000-0002-7398-4237","https://orcid.org/0000-0002-9873-3338","https://orcid.org/0000-0002-3627-851X"],"authorRor":["https://ror.org/00pggkr55"],"availability":"Available","catalogue":"eidc","dataFormat":["TIFF"],"description":"This dataset estimates and spatially distributes anthropogenic emissions of five metals (Cd, Cu, Ni, Pb & Zn) and seven air pollutants (CO, NH3, NOx, PM2.5, PM10, SOx & NMVOCs) in the UK, on a 1km x 1km resolution, from 1750 to 2100.\n\nThe data from 1970 to 2018 are represented by the UK’s National Atmospheric Emissions Inventory and, as such, the Selected Nomenclature for Air Pollution (SNAP) sector classification system is used throughout the entire time series for consistency (see https://naei.beis.gov.uk/ for details).\n\nThe work was supported by the UK-SCAPE programme funded by Natural Environmental Research Council National Capability (Award NE/R016429/1)","documentType":"GEMINI_DOCUMENT","familyName":["Tomlinson","Carnell","Levy","Williams","Vieno","Scheffler","Harrison","Lofts"],"fullName":["Tomlinson, S.","Tomlinson, S.J.","Carnell, E.J.","Levy, P.","Williams, M.","Vieno, M.","Scheffler, J.","Harrison, P.A.","Lofts, S."],"funder":["Natural Environment Research Council"],"givenName":["Sam","S.J.","E.J.","P.","M.","J.","P.A.","S."],"grant":["NE/R016429/1"],"identifier":"4b392dc0-0219-4494-8420-82e42b93b445","incomingCitationCount":0,"keyword":["UK","Pollution","historical emissions","atmospheric pollution","metals","SSP","NOx emissions","emission","ammonia","nitrogen","nitrogen oxides","air pollutant","metal"],"keywordsOther":["historical emissions","atmospheric pollution","metals","SSP","NOx emissions","emission","ammonia","nitrogen","nitrogen oxides","air pollutant","metal"],"keywordsPlace":["UK"],"keywordsTheme":["Pollution"],"licence":"Open government licence","lineage":"Key sources of emissions prior to 1970 were identified through both assessment of emissions sectors back through time from present day to 1970 and also fuel usage through the same period. Data for identified sources, pre-1970, were derived from a multitude of statistical resources, literature, government records etc. Key sources (and their emissions estimations) were matched and aggregated to the SNAP sector emissions classification.\n\nData post-2018 are informed by UK-specific versions of the shared socioeconomic pathways (SSPs) for 2040, 2070 and 2100. Emissions estimates for 2018 are scaled in-line with semi-quantitative trends for a variety of indicators. \n\nEmissions were spatially distributed at a 1km x 1km resolution, on the British National Grid, using a series of sensible proxy representatives such as population, employment record, land use, recorded statistics etc.","locations":["POLYGON((-8.648 49.864, -8.648 60.861, 1.768 60.861, 1.768 49.864, -8.648 49.864))"],"metadataDate":"2026-06-30T10:39:07.000Z","orcid":["https://orcid.org/0000-0002-3237-7596","https://orcid.org/0000-0003-0870-1955","https://orcid.org/0000-0002-8505-1901","https://orcid.org/0000-0001-6047-8661","https://orcid.org/0000-0001-7741-9377","https://orcid.org/0000-0002-7398-4237","https://orcid.org/0000-0002-9873-3338","https://orcid.org/0000-0002-3627-851X"],"organisation":["UK Centre for Ecology & Hydrology","NERC EDS Environmental Information Data Centre"],"publicationDate":"2023-01-13T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/4b392dc0-0219-4494-8420-82e42b93b445","10.5285/4b392dc0-0219-4494-8420-82e42b93b445","doi:10.5285/4b392dc0-0219-4494-8420-82e42b93b445"],"resourceType":"Dataset","rightsHolder":["UK Centre for Ecology & Hydrology"],"ror":["https://ror.org/00pggkr55","https://ror.org/04xw4m193"],"shortenedDescription":"This dataset estimates and spatially distributes anthropogenic emissions of five metals (Cd, Cu, Ni, Pb & Zn) and seven air pollutants (CO, NH3, NOx, PM2.5, PM10, SOx & NMVOCs) in the UK, on a 1km x 1km resolution, from 1750 to 2100.\n\nThe data from 1970 to 2018 are…","state":"published","title":"Estimates of anthropogenic emissions of metals and air pollutants in the UK at a 1km resolution, 1750-2100","topic":["0/Pollution/"],"version":1.0,"view":["public","matnic"]},{"authorAffiliation":["Karlsruhe Institute of Technology","University of Edinburgh","Woodland Trust","Lancaster University","UK Centre for Ecology & Hydrology"],"authorFamilyName":["Brown","Seo","Alexander","Burton","Chacón-Montalván","Dunford-Brown","Merkle","Harrison","Prestele","Robinson","Rounsevell"],"authorFullName":["Brown, C.","Seo, B.","Alexander, P.","Burton, V.","Chacón-Montalván, E.A.","Dunford-Brown, R.","Merkle, M.","Harrison, P.A.","Prestele, R.","Robinson, E.L.","Rounsevell, M."],"authorGivenName":["C.","B.","P.","V.","E.A.","R.","M.","P.A.","E.L.","M"],"authorOrcid":["https://orcid.org/0000-0001-9331-1008","https://orcid.org/0000-0002-9424-9784","https://orcid.org/0000-0001-6010-1186","https://orcid.org/0000-0001-5905-9726","https://orcid.org/0000-0001-8068-1034","https://orcid.org/0000-0002-6559-1687","https://orcid.org/0000-0003-4526-0589","https://orcid.org/0000-0002-9873-3338","https://orcid.org/0000-0003-4179-6204","https://orcid.org/0000-0002-3746-4517","https://orcid.org/0000-0001-7476-9398"],"authorRor":["https://ror.org/04t3en479","https://ror.org/01nrxwf90","https://ror.org/05e9eyh13","https://ror.org/04f2nsd36","https://ror.org/00pggkr55"],"availability":"Available","catalogue":"eidc","dataFormat":["TIFF"],"description":"The data describes future land use projections at 1 km^2 resolution developed by CRAFTY-GB.  For each of six Shared Socioeconomic Pathways (SSP-RCP) scenarios, gridded land use maps for Great Britain are provided, each as a stacked raster file with seven bands representing land use at each decadal timestep, from 2020 to 2080. \n\nCRAFTY-GB is a new agent-based model of the British land system operating at a 1 km^2 resolution and based on a broad range of available land system data .  The model is based on linked UK-RCP climate scenarios and UK-SSPs socio-economic pathway (SSP) scenarios, based on global SSPs developed by the Intergovernmental Panel on Climate Change (IPCC).  It extrapolates the impact of these on the British Land system at decadal timesteps from 2020-2080.","documentType":"GEMINI_DOCUMENT","familyName":["Brown","Seo","Alexander","Burton","Chacón-Montalván","Dunford-Brown","Merkle","Harrison","Prestele","Robinson","Rounsevell"],"fullName":["Brown, C.","Seo, B.","Alexander, P.","Burton, V.","Chacón-Montalván, E.A.","Dunford-Brown, R.","Merkle, M.","Harrison, P.A.","Prestele, R.","Robinson, E.L.","Rounsevell, M."],"funder":["Natural Environment Research Council","Helmholtz Association","Met Office"],"givenName":["Calum","C.","B.","P.","V.","E.A.","R.","M.","P.A.","E.L.","M"],"grant":["NE/R016429/1"],"identifier":"f9ab3051-4f85-415f-b691-371ff8e951f2","incomingCitationCount":0,"keyword":["Mapping","Land use","Climate and climate change","Great Britain","Agent-based modelling","ABM","Socio-ecological","IPCC","Shared Socioeconomic Pathway","SSP","RCP","Representative Concentration Pathways","UK-SCAPE"],"keywordsOther":["Great Britain","Agent-based modelling","ABM","Socio-ecological","IPCC","Shared Socioeconomic Pathway","SSP","RCP","Representative Concentration Pathways","UK-SCAPE"],"keywordsTheme":["Mapping","Land use","Climate and climate change"],"licence":"Open government licence","lineage":"The data was developed as part of research done within the SPEED project under UKSCAPE. It is built upon other work done within the group on UK-specific Climate Change and Socio-ecological scenarios. These scenarios were then used to generate different parameters and inputs to an Agent-based model which explored how these would impact the development of Great Britain’s Land-use system. \n\nThe application of the model to Great Britain was evaluated through sensitivity analyses as the model was developed, consultations with experts and stakeholders, and finally comparison to existing relevant literature on UK land use projections. The baseline allocation of agent types was compared against three (semi-)independent datasets to check its coverage and interpretation with respect to agricultural and ecological characteristics (see SI for details). ","locations":["POLYGON((-8.648 49.864, -8.648 60.861, 1.768 60.861, 1.768 49.864, -8.648 49.864))"],"metadataDate":"2026-06-30T16:29:33.000Z","orcid":["https://orcid.org/0000-0001-9331-1008","https://orcid.org/0000-0002-9424-9784","https://orcid.org/0000-0001-6010-1186","https://orcid.org/0000-0001-5905-9726","https://orcid.org/0000-0001-8068-1034","https://orcid.org/0000-0002-6559-1687","https://orcid.org/0000-0003-4526-0589","https://orcid.org/0000-0002-9873-3338","https://orcid.org/0000-0003-4179-6204","https://orcid.org/0000-0002-3746-4517","https://orcid.org/0000-0001-7476-9398"],"organisation":["Karlsruhe Institute of Technology","University of Edinburgh","Woodland Trust","Lancaster University","UK Centre for Ecology & Hydrology","NERC EDS Environmental Information Data Centre","Forest Research","Helmholtz Association"],"publicationDate":"2023-07-26T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/f9ab3051-4f85-415f-b691-371ff8e951f2","10.5285/f9ab3051-4f85-415f-b691-371ff8e951f2","doi:10.5285/f9ab3051-4f85-415f-b691-371ff8e951f2"],"resourceType":"Dataset","rightsHolder":["Karlsruhe Institute of Technology","UK Centre for Ecology & Hydrology","University of Edinburgh","Forest Research","Lancaster University","Helmholtz Association"],"ror":["https://ror.org/04t3en479","https://ror.org/01nrxwf90","https://ror.org/05e9eyh13","https://ror.org/04f2nsd36","https://ror.org/00pggkr55","https://ror.org/04xw4m193"],"shortenedDescription":"The data describes future land use projections at 1 km^2 resolution developed by CRAFTY-GB.  For each of six Shared Socioeconomic Pathways (SSP-RCP) scenarios, gridded land use maps for Great Britain are provided, each as a stacked raster file with seven bands representing…","state":"published","title":"Decadal maps of multiple alternative future land use based on UK Shared Socioeconomic Pathways (UK-SSPs) and climate projections (UK-RCPs)","topic":["0/Mapping/","0/Land use/","0/Climate and climate change/"],"version":1.0,"view":["public","phtr"]}],"rows":20,"url":"http://catalogue.ceh.ac.uk:443/eidc/documents?page=2&facet=funder%7C(The%20Saiga%20Conservation%20Alliance,%20UK%20OR%20Natural%20Environment%20Research%20Council)"}