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Two miniDOT oxygen loggers were fitted with miniWIPERs and deployed at two locations in Durleigh on 30 May 2018. Both sensors were collected on 5 October 2018 and the raw data files are presented in this dataset.","documentType":"GEMINI_DOCUMENT","familyName":["Slavin","Wain"],"fullName":["Slavin, E.I.","Wain, D.J.","Slavin, E."],"funder":["Natural Environment Research Council"],"givenName":["E.I.","D.J.","Emily"],"identifier":"26b35c45-c174-4930-b82c-bcd0d23c39e1","incomingCitationCount":0,"keyword":["Water quality","Pollution","Environmental survey","reservoir"],"keywordsOther":["reservoir"],"keywordsTheme":["Water quality","Pollution","Environmental survey"],"licence":"Open government licence","lineage":"Each location was marked with a buoy (A2 size) attached to a 10 kg weight using rope. The miniDOTs were attached onto the rope near the weight (bottom of the water column) at both locations. Both miniDOTs were set up to take measurements at ten-minute intervals for dissolved oxygen (% saturation and mg l-1) and temperature (deg C)\n\nThe first site, labelled location 2, is closer to the artificial mixing devices (surface mixers) installed in the reservoir (60 m away) and deeper, with a water depth of 6 m when the MiniDOT logger was deployed. The second site, labelled location 3, is farther away from the artificial mixing devices installed in the reservoir (435 m away) and in a shallower region, with a water depth of 4 m on deployment. On the 13 June 2018 and 21 August 2018, both miniDOTs were brought to the surface to change miniWIPER batteries and remove any fouling from the sensors. Nevertheless, there were periods during the 2018 deployment where the sensors were fouled, and dissolved oxygen measurements were reading 0% saturation.","locations":["POLYGON((-3.056 51.118, -3.056 51.125, -3.037 51.125, -3.037 51.118, -3.056 51.118))"],"metadataDate":"2026-06-29T17:01:13.000Z","orcid":["https://orcid.org/0000-0001-9400-0703","https://orcid.org/0000-0001-5091-102X"],"organisation":["University of Bath","7 Lakes Alliance","NERC EDS Environmental Information Data Centre"],"publicationDate":"2020-05-05T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/26b35c45-c174-4930-b82c-bcd0d23c39e1","10.5285/26b35c45-c174-4930-b82c-bcd0d23c39e1","doi:10.5285/26b35c45-c174-4930-b82c-bcd0d23c39e1"],"resourceType":"Dataset","rightsHolder":["University of Bath"],"ror":["https://ror.org/002h8g185","https://ror.org/04xw4m193"],"shortenedDescription":"This  dataset contains Dissolved oxygen concentrations from two different locations in Durleigh Reservoir in Somerset, England. Two miniDOT oxygen loggers were fitted with miniWIPERs and deployed at two locations in Durleigh on 30 May 2018. Both sensors were collected…","state":"published","title":"Dissolved Oxygen concentrations from Durleigh Reservoir, 2018","topic":["0/Water quality/","0/Pollution/","0/Environmental survey/"],"version":1.0,"view":["public","clwe"]},{"authorAffiliation":["University of Plymouth","CSIR Forestry Research Institute of Ghana","University of Leeds"],"authorFamilyName":["Fauset","Hagan Brown","Addo-Danso","Gloor","Fyfe","Ganderton"],"authorFullName":["Fauset, S.","Hagan Brown, W.","Addo-Danso, S.A.","Gloor, E.U.","Fyfe, R.","Ganderton, P."],"authorGivenName":["S.","W.","S.A.","E.U.","R.","P."],"authorOrcid":["https://orcid.org/0000-0003-4246-1828","https://orcid.org/0000-0003-4399-0182","https://orcid.org/0000-0001-5074-1673"],"availability":"Available","catalogue":"eidc","dataFormat":["Plain text"],"description":"The dataset provides raw infrared temperature data from a thermal camera positioned on a tower at Bobiri Forest Reserve, Ghana between November 2022 and November 2023. The variable recorded is surface temperature, predominately of tree canopies (leaves, branches, stems). This site is a moist semi-deciduous tropical forest. The field of view of the camera includes a plot which was lightly selectively logged over 60 years ago. The trees included in the field of view are of a variety of species including both deciduous and evergreen species. Data were collected in order to assess the differences between species in their canopy temperature and for greater understanding of plant temperature regulation. ","documentType":"GEMINI_DOCUMENT","familyName":["Fauset","Hagan Brown","Addo-Danso","Gloor","Fyfe","Ganderton"],"fullName":["Fauset, S.","Hagan Brown, W.","Addo-Danso, S.A.","Gloor, E.U.","Fyfe, R.","Ganderton, P."],"funder":["Natural Environment Research Council"],"givenName":["S.","W.","S.A.","E.U.","R.","P."],"grant":["NE/V008366/1"],"identifier":"ae09832e-3258-4619-9b9b-65e1c1d09960","incomingCitationCount":0,"keyword":["West Africa","Ghana","Climate and climate change","Environmental survey","canopy temperature","semi-deciduous","ecophysiology","tropical forest","forest"],"keywordsOther":["canopy temperature","semi-deciduous","ecophysiology","tropical forest","forest"],"keywordsPlace":["West Africa","Ghana"],"keywordsTheme":["Climate and climate change","Environmental survey"],"licence":"Open government licence","lineage":"Data were collected using a LabView program to control the camera. Data were initially stored on a local PC, and then transferred to a University of Plymouth network server. Data provided are the raw output from the camera.","locations":["POLYGON((1.29 6.64, 1.29 6.74, 1.37 6.74, 1.37 6.64, 1.29 6.64))"],"metadataDate":"2026-06-29T17:02:54.000Z","orcid":["https://orcid.org/0000-0003-4246-1828","https://orcid.org/0000-0003-4399-0182","https://orcid.org/0000-0001-5074-1673"],"organisation":["University of Plymouth","CSIR Forestry Research Institute of Ghana","University of Leeds","NERC EDS Environmental Information Data Centre"],"publicationDate":"2025-06-19T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/ae09832e-3258-4619-9b9b-65e1c1d09960","10.5285/ae09832e-3258-4619-9b9b-65e1c1d09960","doi:10.5285/ae09832e-3258-4619-9b9b-65e1c1d09960"],"resourceType":"Dataset","rightsHolder":["University of Plymouth"],"ror":["https://ror.org/04xw4m193"],"shortenedDescription":"The dataset provides raw infrared temperature data from a thermal camera positioned on a tower at Bobiri Forest Reserve, Ghana between November 2022 and November 2023. The variable recorded is surface temperature, predominately of tree canopies (leaves, branches, stems).…","state":"published","title":"Canopy temperatures from a moist semi-deciduous tropical forest, Bobiri Forest Reserve, Ghana, 2022-2023","topic":["0/Climate and climate change/","0/Environmental survey/"],"version":1.0,"view":["public","jashun"]},{"authorAffiliation":["University of Leeds","S.R.U.C.","UK Centre for Ecology & Hydrology"],"authorFamilyName":["Young","Martin-Ortega","Glenk","Baird","Jones","Rowe","Evans","Dallimer","Reed"],"authorFullName":["Young, D.M.","Martin-Ortega, J.M.","Glenk, K.","Baird, A.J.","Jones, L.","Rowe, E.","Evans, C.D.","Dallimer, M.","Reed, M."],"authorGivenName":["D.M.","J.M.","K.","A.J.","L.","E.","C.D.","M."],"authorRor":["https://ror.org/00pggkr55"],"availability":"Available","catalogue":"eidc","dataFormat":["Plain text"],"description":"These data are the simulated peat heights and water-table depths (both in cm) from a DigiBog  run. The virtual peatland was configured as a 2-D transect of 100 x 2m x 2m columns. The data were generated for each year of a 5,100-year run. After 4,900 years, six ditches were added and the model allowed to run for a further 100 years. After this time, the ditches were ‘restored’ and the simulation continued until a total runtime of 5,100 years had elapsed.","documentType":"GEMINI_DOCUMENT","familyName":["Young","Martin-Ortega","Glenk","Baird","Jones","Rowe","Evans","Dallimer","Reed"],"fullName":["Young, D.M.","Martin-Ortega, J.M.","Glenk, K.","Baird, A.J.","Jones, L.","Rowe, E.","Evans, C.D.","Dallimer, M.","Reed, M.","Young, D."],"funder":["Natural Environment Research Council"],"givenName":["D.M.","J.M.","K.","A.J.","L.","E.","C.D.","M.","Dylan"],"grant":["NE/P00783X/1"],"identifier":"1d16b303-ca1d-43b4-93b1-c8172adc9792","incomingCitationCount":0,"keyword":["Blanket peat","DigiBog","Economic valuation","water table","peat"],"keywordsOther":["Blanket peat","DigiBog","Economic valuation","water table","peat"],"licence":"Open government licence","lineage":"The virtual peatland was set up with driving data and an underlying topography to represent a typical UK blanket peatland. The aim of the simulation was not to replicate peatland development at a specific location, but to create an analogue for blanket peat.","locations":["POLYGON((-8.648 49.864, -8.648 60.861, 1.768 60.861, 1.768 49.864, -8.648 49.864))"],"metadataDate":"2026-06-29T16:10:38.000Z","organisation":["University of Leeds","S.R.U.C.","UK Centre for Ecology & Hydrology","NERC EDS Environmental Information Data Centre"],"publicationDate":"2021-07-01T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/1d16b303-ca1d-43b4-93b1-c8172adc9792","10.5285/1d16b303-ca1d-43b4-93b1-c8172adc9792","doi:10.5285/1d16b303-ca1d-43b4-93b1-c8172adc9792"],"resourceType":"Dataset","rightsHolder":["University of Leeds"],"ror":["https://ror.org/00pggkr55","https://ror.org/04xw4m193","https://ror.org/024mrxd33"],"shortenedDescription":"These data are the simulated peat heights and water-table depths (both in cm) from a DigiBog  run. The virtual peatland was configured as a 2-D transect of 100 x 2m x 2m columns. The data were generated for each year of a 5,100-year run. After 4,900 years, six ditches…","state":"published","supplementalDescription":["Young, D. M., A. J. Baird, P. J. Morris, and J. Holden (2017). Simulating the long-term impacts of drainage and restoration on the ecohydrology of peatlands. Water Resources Research, 53(8), 6510–6522.","DigiBog website "],"title":"Simulated peat heights and water-table depths for UK blanket bog","version":1.0,"view":["public","clwe"]},{"authorAffiliation":["UK Centre for Ecology & Hydrology","Adam Mickiewicz University"],"authorFamilyName":["Cavers","Wachowiak","Perry"],"authorFullName":["Cavers, S.","Wachowiak, W.","Perry, A."],"authorGivenName":["S.","W.","A."],"authorOrcid":["https://orcid.org/0000-0003-2139-9236","https://orcid.org/0000-0003-2898-3523","https://orcid.org/0000-0002-7889-7597"],"authorRor":["https://ror.org/00pggkr55","https://ror.org/04g6bbq64"],"availability":"Available","catalogue":"eidc","dataFormat":["Plain text"],"description":"The dataset contains  genotypes for samples used to validate a 50K single nucleotide polymorphism (SNP, DNA mutation) Axiom array for Scots pine (Pinus sylvestris) and closely related members of the Pinus mugo complex.","documentType":"GEMINI_DOCUMENT","familyName":["Cavers","Wachowiak","Perry"],"fullName":["Cavers, S.","Wachowiak, W.","Perry, A."],"funder":["Natural Environment Research Council"],"givenName":["S.","W.","A.","Stephen"],"identifier":"7ee55609-d6b1-4693-8b36-2bf84fef76c2","incomingCitationCount":1,"keyword":["Biodiversity","Environmental survey","Natural selection ","Speciation ","Divergence ","Polymorphism ","Genotyping ","SNPs","Population genomics ","Genomic ","Micoarray "],"keywordsOther":["Natural selection ","Speciation ","Divergence ","Polymorphism ","Genotyping ","SNPs","Population genomics ","Genomic ","Micoarray "],"keywordsTheme":["Biodiversity","Environmental survey"],"licence":"Open government licence","lineage":"Samples &  Validation of the array was carried out using a subset of 87 samples, which included four species of pine (Pinus sylvestris: SY; P. mugo: MU; P. uncinata: UN; P. uliginosa: UL). DNA was extracted from needles using a Qiagen DNeasy 96 kit following the manufacturer’s instructions. Needles were dried on silica gel prior to extraction and DNA was quantified using a Qubit spectrophotometer to ensure a minimum standardized concentration of 35ng/µl. The quality of genomic DNA was also checked visually for fragmentation on 1%  agarose gel.\n\n Genotyping was done at Edinburgh Genomics following DNA amplification, fragmentation, chip hybridisation, single-base extension through DNA ligation and signal amplification performed according to the Affymetrix Axiom® Assay protocol. Genotyping was performed in 384-well format on a GeneTitan according to the manufacturer’s procedure. Genotype calls were performed using Axiom Analysis Suite software as recommended by the manufacturer (ThermoFisher). Samples were assigned to an analysis group based on their call rate (CR) and dish QC (DQC: a metric provided by ThermoFisher which is generated by measuring signals at multiple sites in the genome known not to vary among individuals), using the following thresholds: DQC 'high' ≥ 0.82; DQC 'low' < 0.82; CR 'high' ≥ 96; CR 'low' < 96. Analyses: 1) DQC high + CR high; 2) DQC high + CR low; 3) DQC low + CR low. High quality samples (N=529), with high CR and DQC, were used to set thresholds for allele calls. Posteriors for allele calls were subsequently used as priors for analyses 2 (N = 753) and 3 (N = 251).","locations":["POLYGON((-18.359 37.192, -18.359 67.115, 24.839 67.115, 24.839 37.192, -18.359 37.192))"],"metadataDate":"2026-06-29T16:47:46.000Z","orcid":["https://orcid.org/0000-0003-2139-9236","https://orcid.org/0000-0003-2898-3523","https://orcid.org/0000-0002-7889-7597"],"organisation":["UK Centre for Ecology & Hydrology","Adam Mickiewicz University","NERC EDS Environmental Information Data Centre","NERC Environmental Information Data Centre"],"publicationDate":"2020-03-27T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/7ee55609-d6b1-4693-8b36-2bf84fef76c2","10.5285/7ee55609-d6b1-4693-8b36-2bf84fef76c2","doi:10.5285/7ee55609-d6b1-4693-8b36-2bf84fef76c2"],"resourceType":"Dataset","rightsHolder":["UK Centre for Ecology & Hydrology"],"ror":["https://ror.org/00pggkr55","https://ror.org/04g6bbq64","https://ror.org/04xw4m193"],"shortenedDescription":"The dataset contains  genotypes for samples used to validate a 50K single nucleotide polymorphism (SNP, DNA mutation) Axiom array for Scots pine (Pinus sylvestris) and closely related members of the Pinus mugo complex.","state":"published","title":"Scots pine single nucleotide polymorphism (SNP) genotypes for Axiom array validation","topic":["0/Biodiversity/","0/Environmental survey/"],"version":1.0,"view":["public","clwe"]},{"authorAffiliation":["University of Cambridge","Bavarian State Institute of Forestry","Baruch Institute of Coastal Ecology and Forest Science","Centre de recherche sur les matériaux renouvelables","University of Melbourne","Institut Européen de la Forêt Cultivée"],"authorFamilyName":["Jackson","Wellpott","Van Bloem","Achim","James","Gardiner"],"authorFullName":["Jackson, T.","Wellpott, A.","Van Bloem, S.","Achim, A.","James, K.","Gardiner, B."],"authorGivenName":["T.","A.","S.","K. ","B."],"authorOrcid":["https://orcid.org/0000-0001-8143-6161"],"authorRor":["https://ror.org/013meh722","https://ror.org/01ej9dk98"],"availability":"Available","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)","Plain text"],"description":"This dataset contains high resolution measurements of tree motion in response to wind at six sites. The data was collected using sensors mounted directly onto the tree trunk.\n\nThe sites are: Rivox, Kershope, Kyloe and Clocaenog in the UK. Guanica in Puerto Rico and six open-grown trees from Australia.","documentType":"GEMINI_DOCUMENT","familyName":["Jackson","Wellpott","Van Bloem","Achim","James","Gardiner"],"fullName":["Jackson, T.","Wellpott, A.","Van Bloem, S.","Achim, A.","James, K.","Gardiner, B."],"funder":["Natural Environment Research Council"],"givenName":["Toby","T.","A.","S.","K. ","B.","K."],"grant":["NE/S010750/1"],"identifier":"fecff8c2-983e-4883-a0f8-ac65deba02cf","incomingCitationCount":0,"keyword":["Kyloe","Clocaenog","Guanica","Burnley","Sale","Kershope","Monash University","Mount Dandenong","Rivox","Eucalyptus tereticornis","Larix","Picea sitchensis","Coccoloba diversifolia","Exostema caribaeum","Gymnanthes lucida","Bourreria succulenta","Leucaena leucocephala","Amyris elemifera","Araucaria cunninghamii","Cupressus sempervirens","Washingtonia robusta","Agathis australis","Corymbia maculata","Eucalyptus regnans","Kauri","Mexican fan palm","Mediterranean cypress","Larch","Jumbay","tree","wind"],"keywordsOther":["Eucalyptus tereticornis","Larix","Picea sitchensis","Coccoloba diversifolia","Exostema caribaeum","Gymnanthes lucida","Bourreria succulenta","Leucaena leucocephala","Amyris elemifera","Araucaria cunninghamii","Cupressus sempervirens","Washingtonia robusta","Agathis australis","Corymbia maculata","Eucalyptus regnans","Kauri","Mexican fan palm","Mediterranean cypress","Larch","Jumbay","tree","wind"],"keywordsPlace":["Kyloe","Clocaenog","Guanica","Burnley","Sale","Kershope","Monash University","Mount Dandenong","Rivox"],"licence":"Open government licence","lineage":"The data in Rivox were collected using displacement sensors, all other sites used strain gauges. In the four UK sites, wind data were collected at 10 Hz using a 3D sonic anemometer on a tower at canopy height. Wind data for the trees in Australia were collected using a cup anemometer. No wind data was collected in Guanica.\n\nNo pre-processing, filtering or quality control has been conducted on these data. They have only been downloaded from the data loggers and merged into continuous time-series.\n\nThe data were used to estimate wind damage risk and no additional processing was needed.","locations":["POLYGON((-180 -90, -180 90, 180 90, 180 -90, -180 -90))"],"metadataDate":"2026-06-29T18:21:10.000Z","orcid":["https://orcid.org/0000-0001-8143-6161"],"organisation":["University of Cambridge","Bavarian State Institute of Forestry","Baruch Institute of Coastal Ecology and Forest Science","Centre de recherche sur les matériaux renouvelables","University of Melbourne","Institut Européen de la Forêt Cultivée","NERC EDS Environmental Information Data Centre","Forest Research"],"publicationDate":"2021-07-28T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/fecff8c2-983e-4883-a0f8-ac65deba02cf","10.5285/fecff8c2-983e-4883-a0f8-ac65deba02cf","doi:10.5285/fecff8c2-983e-4883-a0f8-ac65deba02cf"],"resourceType":"Dataset","rightsHolder":["University of Melbourne","Baruch Institute of Coastal Ecology and Forest Science","Forest Research"],"ror":["https://ror.org/013meh722","https://ror.org/01ej9dk98","https://ror.org/04xw4m193"],"shortenedDescription":"This dataset contains high resolution measurements of tree motion in response to wind at six sites. The data was collected using sensors mounted directly onto the tree trunk.\n\nThe sites are: Rivox, Kershope, Kyloe and Clocaenog in the UK. Guanica in Puerto Rico and…","state":"published","supplementalDescription":["Jackson, T.D., Sethi, S., Dellwik, E., Angelou, N., Bunce, A., van Emmerik, T., Duperat, M., Ruel, J.-C., Wellpott, A., Van Bloem, S., Achim, A., Kane, B., Ciruzzi, D.M., Loheide II, S.P., James, K., Burcham, D., Moore, J., Schindler, D., Kolbe, S., … Gardiner, B. (2021). The motion of trees in the wind: a data synthesis. Biogeosciences, 18(13), 4059–4072","James, K. R., Haritos, N., & Ades, P.K. (2006). Mechanical stability of trees under dynamic loads. American Journal of Botany, 93(10), 1522–1530","Gardiner, B.A., Stacey, G.R., Belcher, R. E., & Wood, C.J. (1997). Field and wind tunnel assessments of the implications of respacing and thinning for tree stability. Forestry, 70(3), 233–252","Hale, S.E., Gardiner, B.A., Wellpott, A. et al. Wind loading of trees: influence of tree size and competition. Eur J Forest Res 131, 203–217 (2012)"],"title":"Measurements of tree motion in the wind collated from multiple studies undertaken in the UK, Puerto Rico and Australia between 1987-2015","version":1.0,"view":["public","matnic"]},{"authorAffiliation":["University of Oxford"],"authorFamilyName":["Jackson"],"authorFullName":["Jackson, T."],"authorGivenName":["T."],"authorOrcid":["https://orcid.org/0000-0001-8143-6161"],"authorRor":["https://ror.org/052gg0110"],"availability":"Available","catalogue":"eidc","dataFormat":["Plain text"],"description":"This data contains the strain and wind data collected for 21 trees in Wytham Woods, a mature temperate woodland in southern England, from September 2015 to June 2016. This data was collected in order to (a) extract the resonant frequencies of trees, (b) to estimate the critical wind speeds at which the trees would break and (c) to test a finite element model of tree-wind dynamics. \n\nThe strain data was collected at 4Hz using two strain gauges per tree attached at 1.3metres on the trunk and approximately perpendicular to each other. The wind data provided were collected from the canopy walkway in Wytham Woods using a cup anemometer (Vector Instruments A100LK/5M) in winter and a Gill Sonic-1 in summer, the time resolution varies between these instruments. Local climate data, including long term wind data, are available from the Environmental Change Network (https://doi.org/10.5285/fc9bcd1c-e3fc-4c5a-b569-2fe62d40f2f5 or data.ecn.ac.uk).","documentType":"GEMINI_DOCUMENT","familyName":["Jackson"],"fullName":["Jackson, T."],"funder":["Natural Environment Research Council"],"givenName":["Toby","T."],"identifier":"533d87d3-48c1-4c6e-9f2f-fda273ab45bc","incomingCitationCount":3,"keyword":["Wytham Woods","strain","wind damage","resonant frequency","biomechanics","forest","tree"],"keywordsOther":["strain","wind damage","resonant frequency","biomechanics","forest","tree"],"keywordsPlace":["Wytham Woods"],"licence":"Open government licence","lineage":"This data set consists of strain measurements for 21 trees in Wytham Woods, Oxfordshire. This data can be used to estimate the characteristic swaying behaviour of trees in the wind and to characterize the wind-strain relationship. Pairs of strain gauges were attached (approximately perpendicular to each other) to the tree trunks at 1.3m height and readings were logged at 4Hz. The data provided has been calibrated, as described in the readme file. Please contact the author (tobydjackson@gmail.com) for the raw data files. Data processing scripts can be downloaded from (https://github.com/TobyDJackson/WindAndTrees_Wytham). Wind data, measured within the canopy, is also provided.","locations":["POLYGON((-1.35 51.76, -1.35 51.78, -1.32 51.78, -1.32 51.76, -1.35 51.76))"],"metadataDate":"2026-06-29T16:09:38.000Z","orcid":["https://orcid.org/0000-0001-8143-6161"],"organisation":["University of Oxford","NERC EDS Environmental Information Data Centre","NERC Environmental Information Data Centre"],"publicationDate":"2018-02-14T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["10.5285/533d87d3-48c1-4c6e-9f2f-fda273ab45bc","doi:10.5285/533d87d3-48c1-4c6e-9f2f-fda273ab45bc","https://catalogue.ceh.ac.uk/id/533d87d3-48c1-4c6e-9f2f-fda273ab45bc"],"resourceType":"Dataset","ror":["https://ror.org/052gg0110","https://ror.org/04xw4m193"],"shortenedDescription":"This data contains the strain and wind data collected for 21 trees in Wytham Woods, a mature temperate woodland in southern England, from September 2015 to June 2016. This data was collected in order to (a) extract the resonant frequencies of trees, (b) to estimate…","state":"published","title":"Strain measurements on 21 trees in Wytham Woods, UK","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","James Hutton Institute","Forest Research"],"authorFamilyName":["Perry","Beaton","Stockan","Cottrell","Iason","Cavers"],"authorFullName":["Perry, A.","Beaton, J.K.","Stockan, J.A.","Cottrell, J.E.","Iason, G.R.","Cavers, S."],"authorGivenName":["A.","J.K.","J.A.","J.E.","G.R.","S."],"authorOrcid":["https://orcid.org/0000-0002-7889-7597","https://orcid.org/0000-0001-9900-9010","https://orcid.org/0000-0003-2139-9236"],"authorRor":["https://ror.org/00pggkr55","https://ror.org/03rzp5127","https://ror.org/03wcc3744"],"availability":"Available","catalogue":"eidc","dataFormat":["Plain text"],"description":"Phenotypes (growth and phenology) for Scots pine trees in a long-term common garden trial planted in three sites in Scotland, surveyed annually from 2013 to 2020.","documentType":"GEMINI_DOCUMENT","familyName":["Perry","Beaton","Stockan","Cottrell","Iason","Cavers"],"fullName":["Perry, A.","Beaton, J.K.","Stockan, J.A.","Cottrell, J.E.","Iason, G.R.","Cavers, S."],"funder":["Natural Environment Research Council","Biotechnology and Biological Sciences Research Council","Scottish Government"],"givenName":["A.","J.K.","J.A.","J.E.","G.R.","S."],"grant":["NE/K012177/1","BB/L012243/1"],"identifier":"1c9367fb-ea87-47a1-8257-d9fed54215e7","incomingCitationCount":0,"keyword":["Phenology","Pinus sylvestris","Scots pine","Caledonian pinewood","adaptive trait variation","phenotype","common garden experiment","growth","phenology","tree"],"keywordsOther":["Pinus sylvestris","Scots pine","Caledonian pinewood","adaptive trait variation","phenotype","common garden experiment","growth","phenology","tree"],"keywordsTheme":["Phenology"],"licence":"Open government licence","lineage":"A multi-site field trial was established at three sites in Scotland in 2012 using five year old Scots pine trees. Each site contains 8 families from each of 21 native Caledonian pinewood provenances. Two of the sites (FE and FS) have four randomised blocks and the other (FW) has three randomised blocks.\n\nTree height and basal stem diameter were measured at the end of each growing season from 2013 to 2020 for trees growing at two of the field sites (FE and FW) and in 2020 for trees growing at the third (FS). \n\nPhenology assessments were performed in spring at each site from 2015 to 2019 (the survey was not completed in 2020 due to the COVID-19 pandemic).\n","locations":["POLYGON((-8.648 54.634, -8.648 60.861, -0.728 60.861, -0.728 54.634, -8.648 54.634))"],"metadataDate":"2026-06-29T16:15:35.000Z","orcid":["https://orcid.org/0000-0002-7889-7597","https://orcid.org/0000-0001-9900-9010","https://orcid.org/0000-0003-2139-9236"],"organisation":["UK Centre for Ecology & Hydrology","James Hutton Institute","Forest Research","NERC EDS Environmental Information Data Centre","The James Hutton Institute"],"publicationDate":"2022-10-11T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/1c9367fb-ea87-47a1-8257-d9fed54215e7","10.5285/1c9367fb-ea87-47a1-8257-d9fed54215e7","doi:10.5285/1c9367fb-ea87-47a1-8257-d9fed54215e7"],"resourceType":"Dataset","rightsHolder":["UK Centre for Ecology & Hydrology","Forest Research","The James Hutton Institute"],"ror":["https://ror.org/00pggkr55","https://ror.org/03rzp5127","https://ror.org/03wcc3744","https://ror.org/04xw4m193"],"shortenedDescription":"Phenotypes (growth and phenology) for Scots pine trees in a long-term common garden trial planted in three sites in Scotland, surveyed annually from 2013 to 2020.","state":"published","title":"Long-term multisite Scots pine trial, Scotland: field phenotypes, 2013-2020, version 2","topic":["0/Phenology/"],"version":1.0,"view":["public","margla"]},{"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":["University of Aberdeen"],"authorFamilyName":["Oyesiku-Blakemore","Smith","Hallett"],"authorFullName":["Oyesiku-Blakemore, J.","Smith, J.","Hallett, P."],"authorGivenName":["Joseph","J.","P."],"authorRor":["https://ror.org/016476m91"],"availability":"Available","catalogue":"eidc","dataFormat":["Plain text"],"description":"Data comprise soil organic carbon content from a simulation using the ECOSSE model; a pool-based carbon and nitrogen turnover model. Simulations were performed using input data from the Sunjia research farm in southeast China (Jianxi province). Data here is from simulations using the global version of the ECOSSE model, a package which applies the regular model spatially. Input data for the simulations were provided by the soil science department of the Chinese Academy of Sciences. Simulations were conducted in 2018. ","documentType":"GEMINI_DOCUMENT","familyName":["Oyesiku-Blakemore","Smith","Hallett"],"fullName":["Oyesiku-Blakemore, J.","Smith, J.","Hallett, P."],"funder":["Natural Environment Research Council"],"givenName":["Joseph","J.","P.","Joseph "],"grant":["NE/N007611/1"],"identifier":"876fa724-c3d3-4091-8de2-8140b7c973eb","incomingCitationCount":0,"keyword":["Soil","Environmental survey","soil","organic carbon"],"keywordsOther":["soil","organic carbon"],"keywordsTheme":["Soil","Environmental survey"],"licence":"Open government licence","lineage":"The data was collected through model simulations. These were performed to understand the response of soil carbon in the red soils of Southeast China to changes in climate. Simulations were carried out by Dr Joseph Oyesiku-Blakemore in the Environmental modelling group at the University of Aberdeen. The work was part of the UK China Critical Zone Observatory project (the Red Soil project within this group of projects), funded by NERC and NSFC. ","locations":["POLYGON((113.247 24.847, 113.247 30.146, 118.608 30.146, 118.608 24.847, 113.247 24.847))"],"metadataDate":"2026-06-29T16:50:24.000Z","organisation":["University of Aberdeen","NERC EDS Environmental Information Data Centre","NERC Environmental Information Data Centre"],"publicationDate":"2020-02-27T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/876fa724-c3d3-4091-8de2-8140b7c973eb","10.5285/876fa724-c3d3-4091-8de2-8140b7c973eb","doi:10.5285/876fa724-c3d3-4091-8de2-8140b7c973eb"],"resourceType":"Dataset","ror":["https://ror.org/016476m91","https://ror.org/04xw4m193"],"shortenedDescription":"Data comprise soil organic carbon content from a simulation using the ECOSSE model; a pool-based carbon and nitrogen turnover model. Simulations were performed using input data from the Sunjia research farm in southeast China (Jianxi province). Data here is from simulations…","state":"published","supplementalName":["Critical Zone Exploration Network"],"title":"Model output of changes in soil carbon storage and emissions for agricultural and forest land uses across the Red Soil region in China","topic":["0/Soil/","0/Environmental survey/"],"version":1.0,"view":["public","clwe"]},{"authorAffiliation":["University of Brighton","University of Exeter","University of Hull","University of Birmingham"],"authorFamilyName":["Ashworth","Nicholas","Parsons","Sambrook Smith"],"authorFullName":["Ashworth, P.","Nicholas, A.","Parsons, D.","Sambrook Smith, G."],"authorGivenName":["P.","Andrew","D.","G."],"authorOrcid":["https://orcid.org/0000-0002-3707-1182"],"authorRor":["https://ror.org/04kp2b655","https://ror.org/03yghzc09","https://ror.org/04nkhwh30","https://ror.org/03angcq70"],"availability":"Available","catalogue":"eidc","dataFormat":["Plain text"],"description":"Data were collected in 2015, 2016 and 2017 to provide Digital Surface Models (DSM) for two sections of the South Saskatchewan River, Canada. DSMs were generated using aerial plane images with a 0.06m ground resolution, captured at a height of c. 1500 m from a fixed-wing aeroplane with an UltraCamXp sensor. DSMs were generated as part of NERC project NE/L00738X/1. DSMs were constructed using imagery obtained on four occasions (13th May 2015; 2nd Sept 2016; 8th June 2017; and 12th June 2017). The dataset consists of eight DSMs; one for each of the two river sections on each of the four dates.","documentType":"GEMINI_DOCUMENT","familyName":["Ashworth","Nicholas","Parsons","Sambrook Smith"],"fullName":["Ashworth, P.","Nicholas, A.","Parsons, D.","Sambrook Smith, G."],"funder":["Natural Environment Research Council"],"givenName":["P.","Andrew","D.","G."],"grant":["NE/L00738X/1"],"identifier":"13695138-227f-4d85-9049-0a9cba9e1867","incomingCitationCount":1,"keyword":["Canada ","Saskatchewan River","Modelling","digital land model","Digital Surface Models"],"keywordsOther":["digital land model","Digital Surface Models"],"keywordsPlace":["Canada ","Saskatchewan River"],"keywordsTheme":["Modelling"],"licence":"Open government licence","lineage":"DSMs were constructed to provide information on the morphology or the river, and changes in morphology through time (e.g. due to erosion and deposition of sediment). DSMs were constructed using imagery obtained on four occasions (13th May 2015; 2nd Sept 2016; 8th June 2017; and 12th June 2017). The dataset consists of eight DSMs; one for each of the two river sections on each of the four dates. \n\nThe DSM was constructed from photogrammetric quality aerial plane images with a 0.06m ground resolution that were captured at a height of c. 1500 m from a fixed-wing aeroplane with an UltraCamXp sensor. The DSM was constructed from the images using a three stage process:\n\n(1) An orthomosaic was generated from the aerial photography (using up to 160 images) by automated image matching using the SfM program Pix4D (https://pix4d.com/) with the 'large frame' supplementary software package. Bundle adjustment was undertaken using Pix4D’s key point matching system optimised for aerial nadir imagery. Camera properties were specified using calibration certificates and were not allowed to vary during the calculation. A point cloud was then derived following the bundle adjustment.\n\n(2) The point cloud was checked for residual tilt using a network of Ground Control Points with coordinates that were determined by RTK differential GPS survey. The corrected point cloud density was reduced to a resolution of 0.5 m and the resulting dataset was filtered in MATLAB using a Chauvenet-type criterion. This procedure was implemented to derive the DSM in dry (non-submerged) areas of the river.\n\n(3) In wet (submerged) areas, bed elevations were derived using a depth-brightness model as follows. First, water surface elevations at the interface between wet and dry areas of the river bed were extracted from the corrected point cloud and interpolated to generate a water surface elevation field for the submerged bed areas. Second, water depth measurements made at the time of image acquisition were located on the orthomosaic of the river, and pixel brightness values were extracted at these locations. A log-linear regression between water depth and pixel brightness was then derived, and this relationship was used to model water depth for all sub-merged bed areas. Bed elevations in these areas were determined by subtracting the predicted depth from the water surface elevation. The final DSM was derived by combining elevation values for the dry and wet bed areas.\n","locations":["POLYGON((-107 51.5, -107 51.6, -107.1 51.6, -107.1 51.5, -107 51.5))"],"metadataDate":"2026-06-29T18:09:41.000Z","orcid":["https://orcid.org/0000-0002-3707-1182"],"organisation":["University of Brighton","University of Exeter","University of Hull","University of Birmingham","NERC EDS Environmental Information Data Centre","NERC Environmental Information Data Centre"],"publicationDate":"2019-10-29T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/13695138-227f-4d85-9049-0a9cba9e1867","10.5285/13695138-227f-4d85-9049-0a9cba9e1867","doi:10.5285/13695138-227f-4d85-9049-0a9cba9e1867"],"resourceType":"Dataset","ror":["https://ror.org/04kp2b655","https://ror.org/03yghzc09","https://ror.org/04nkhwh30","https://ror.org/03angcq70","https://ror.org/04xw4m193"],"shortenedDescription":"Data were collected in 2015, 2016 and 2017 to provide Digital Surface Models (DSM) for two sections of the South Saskatchewan River, Canada. DSMs were generated using aerial plane images with a 0.06m ground resolution, captured at a height of c. 1500 m from a fixed-wing…","state":"published","title":"Digital Surface Models for the South Saskatchewan River, Canada","topic":["0/Modelling/"],"version":1.0,"view":["public","clwe"]},{"authorAffiliation":["University of Sheffield"],"authorFamilyName":["Freckleton","Queenborough"],"authorFullName":["Freckleton, R.","Queenborough, S."],"authorGivenName":["R.","S."],"authorRor":["https://ror.org/05krs5044"],"availability":"Available","catalogue":"eidc","dataFormat":["Plain text"],"description":"This data collection results from abundance surveys of seven species of weeds in ca. 500 lowland arable fields in 49 farms over three years. Each field was divided into large grids of 20x20 metre cells, and the density of seven species was estimated three times a year. The study is part of the NERC Rural Economy and Land Use (RELU) programme. In the context of changing external and internal pressures on UK agriculture, particularly those associated with the ongoing reform of the EU Common Agricultural Policy, it is imperative to determine whether all of the various dimensions of sustainability - including the relevant economic and environmental objectives as well as social and cultural values - can be integrated successfully at the farm and landscape levels. \n\nAlthough the ways in which economic, technological, and regulatory changes are likely to affect the profitability and management of farms of varying size are reasonably well understood, there is not the knowledge or understanding to predict the resulting effects on biodiversity. For example, the effect of changes in arable farming practices on field weeds and, in turn, on habitats and food supply required to sustain farm birds is a case in point. This knowledge is critical, however, if we are to understand the ecological consequences of changes in agricultural policy. Furthermore, it is also important if we are to design and justify changes in farming methods that can not only enhance nature conservation, but do this is ways that are practical and appealing from a farmer's point of view. This understanding is essential if we are to achieve an agriculture that is sustainable in both economic and environmental terms and is widely perceived to have social and cultural value. \n\nA consistent theme in all components of this research project is to understand the behaviour (of farmers, weeds or birds) and then use this information to produce predictive models. Whilst there have been a number of models of economic behaviour, weed populations and bird populations - including many by the research team here - the really novel component of this research is to integrate these within one framework. Farmer interviews on economic attitudes and preferences associated with and importance of different land-use objectives to lowland arable farmers are available at the UK Data Archive under study number 6728 (see online resources). Further documentation for this study may be found through the RELU Knowledge Portal and the project's ESRC funding award web page (see online resources).","documentType":"GEMINI_DOCUMENT","familyName":["Sutherland","Freckleton","Queenborough","Queensborough"],"fullName":["Sutherland, W.","Freckleton, R.","Queenborough, S.","Queensborough, S."],"givenName":["W.","R.","S."],"identifier":"6762f1b5-2bcc-4062-bff6-e560d902b593","incomingCitationCount":0,"keyword":["Norfolk","Bedfordshire","Lincolnshire","Rural Economy and Land Use Programme","environmental conservation","farming systems","agricultural land","agricultural policy","weed","land use","nature conservation","bird","biodiversity","arable farming","modelling"],"keywordsOther":["environmental conservation","farming systems","agricultural land","agricultural policy","weed","land use","nature conservation","bird","biodiversity","arable farming","modelling"],"keywordsPlace":["Norfolk","Bedfordshire","Lincolnshire"],"keywordsProject":["Rural Economy and Land Use Programme"],"licence":"Non-Open government licence","lineage":"Research funded by Economic and Social Research Council, Natural Environment Research Council and Biotechnology and Biological Sciences Research Council. Award Number: RES-227-25-0025 Survey of arable weeds in ca. 500 fields in 49 farms over three years. Each field was divided into large grids of 20x20 m cells, and the density of seven species was estimated three times a year. Categorical abundance (0, low, medium, high, very high) of 7 weed species in 20x20 m grid cells in 20x20 m grid cells in 2-4 ha per field. The area was picked to maximise efficiency in order to decrease between-field transit time. The samples are random in the sense that nothing was known about their weed density beforehand.","locations":["POLYGON((-0.991 51.781, -0.991 53.826, 1.763 53.826, 1.763 51.781, -0.991 51.781))"],"metadataDate":"2026-06-27T15:22:55.000Z","organisation":["University of Cambridge","University of Sheffield","NERC EDS Environmental Information Data Centre"],"publicationDate":"2013-07-23T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["1374597694599","CEH:EIDC::1374597694599","https://catalogue.ceh.ac.uk/id/6762f1b5-2bcc-4062-bff6-e560d902b593"],"resourceType":"Dataset","ror":["https://ror.org/013meh722","https://ror.org/05krs5044","https://ror.org/04xw4m193"],"shortenedDescription":"This data collection results from abundance surveys of seven species of weeds in ca. 500 lowland arable fields in 49 farms over three years. Each field was divided into large grids of 20x20 metre cells, and the density of seven species was estimated three times a year.…","state":"published","supplementalDescription":["Complementary survey data from this same research project.","Freckleton, R. P., Sutherland, W. J., Watkinson, A. R., & Stephens, P. A. (2008). Modelling the effects of management on population dynamics: some lessons from annual weeds. Journal of Applied Ecology, 45(4), 1050-1058. ","Providing project information and links to outputs and publications"],"supplementalName":["UK Data Service catalogue record","ESRC award page","Relu Knowledge Portal"],"title":"Abundance of weeds in lowland arable fields, 2006-2009 - RELU Management options for biodiverse farming","version":1.0,"view":["public","rstu"]},{"authorAffiliation":["Politecnico di Torino ","Politecnico di Torino","University College London"],"authorFamilyName":["Tuninetti","Tamea","Dalin"],"authorFullName":["Tuninetti, M.","Tamea, S.","Dalin, C."],"authorGivenName":["M.","S.","C."],"authorOrcid":["https://orcid.org/0000-0003-2619-8783","https://orcid.org/0000-0001-6388-3283","https://orcid.org/0000-0002-2123-9622"],"authorRor":["https://ror.org/00bgk9508","https://ror.org/02jx3x895"],"availability":"Available","catalogue":"eidc","dataFormat":["Plain text"],"description":"Gridded data of water debt for year 2000. The water debt expresses the number of years required by the hydrological cycle to replenish the water source (soil moisture, surface water, ground water) that have been used to accomplish the annual production of nine major crops. The considered crops are: wheat, maize, rice, soybean, sugar cane, sugar beet, cotton, barley, sorghum.","documentType":"GEMINI_DOCUMENT","familyName":["Tuninetti","Tamea","Dalin"],"fullName":["Tuninetti, M.","Tamea, S.","Dalin, C."],"funder":["Natural Environment Research Council","European Research Council"],"givenName":["M.","S.","C."],"grant":["NE/N01524X/1","647473"],"identifier":"45cb218c-b050-4ee8-8c87-73d3895a111f","incomingCitationCount":0,"keyword":["Hydrology","Mapping","crop production","agronomy","hydrology","water resources conservation","environmental sustainability"],"keywordsOther":["crop production","agronomy","hydrology","water resources conservation","environmental sustainability"],"keywordsTheme":["Hydrology","Mapping"],"licence":"Open government licence","lineage":"Definition of the Water Debt (WD) Repayment Time: \nThe WD is calculated, at a 5' × 5' spatial resolution for the production of year 2000, as the ratio of the cell annual water footprint, WFs, cr, l, which is specific for each source s, crop cr, and location l, and the average renewable volume of water annually available in the cell.\n\nThe annual renewability rate is calculated as a long-term average along the period 1987–2013. In this way, we obtain an average measure of the water availability in the cell, which smooths out potential extremely dry or extremely wet years. The water footprint (WF) estimates are computed for year 2000 because this is the most referenced year in agricultural datasets available in the literature.\n\nThe WFs, cr, l estimate is obtained as the product of the local crop water footprint (CWF) by source, (CWFs, cr, l, expressed in cubic meters per ton of crop), and the annual crop production (Pr), (Pcr, l, expressed in tons of crop).\n\nThe total WD of the sources, arising from all the crops cultivated in the grid cell, WDs, l, equals the sum of debts generated by each crop.\n\nOwing to the simultaneous replenishment of soil water, surface water, and groundwater by precipitation, the crop WD across the threes sources, WDcr, l, is given by the maximum WDs, l, cr value across sources s.","locations":["POLYGON((-180 -90, -180 90, 180 90, 180 -90, -180 -90))"],"metadataDate":"2026-06-29T16:35:29.000Z","orcid":["https://orcid.org/0000-0003-2619-8783","https://orcid.org/0000-0001-6388-3283","https://orcid.org/0000-0002-2123-9622"],"organisation":["Politecnico di Torino ","Politecnico di Torino","University College London","Natural Environment Research Council","NERC EDS Environmental Information Data Centre"],"publicationDate":"2023-01-26T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/45cb218c-b050-4ee8-8c87-73d3895a111f","10.5285/45cb218c-b050-4ee8-8c87-73d3895a111f","doi:10.5285/45cb218c-b050-4ee8-8c87-73d3895a111f"],"resourceType":"Dataset","rightsHolder":["Natural Environment Research Council"],"ror":["https://ror.org/00bgk9508","https://ror.org/02jx3x895","https://ror.org/02b5d8509","https://ror.org/04xw4m193"],"shortenedDescription":"Gridded data of water debt for year 2000. The water debt expresses the number of years required by the hydrological cycle to replenish the water source (soil moisture, surface water, ground water) that have been used to accomplish the annual production of nine major…","state":"published","title":"Water debt for the annual production of nine major crops globally at 5 arcmin resolution for the year 2000","topic":["0/Hydrology/","0/Mapping/"],"version":1.0,"view":["public","matnic"]},{"authorAffiliation":["UK Centre for Ecology & Hydrology","Adam Mickiewicz University"],"authorFamilyName":["Perry","Wachowiak","Donnelly","Cavers"],"authorFullName":["Perry, A.","Wachowiak, W.","Donnelly, K.","Cavers, S."],"authorGivenName":["A.","W.","K.","S."],"authorOrcid":["https://orcid.org/0000-0002-7889-7597","https://orcid.org/0000-0003-2898-3523","https://orcid.org/0000-0003-2139-9236"],"authorRor":["https://ror.org/00pggkr55"],"availability":"Available","catalogue":"eidc","dataFormat":["Plain text"],"description":"This dataset contains details of the phenotypes (height, bud set and budburst) and genotypes (via SNP array) of trees from a common garden multi-species pine (Pinus sylvestris, Pinus mugo and Pinus uncinata) glasshouse trial between 2010 and 2013.","documentType":"GEMINI_DOCUMENT","familyName":["Perry","Wachowiak","Donnelly","Cavers"],"fullName":["Perry, A.","Wachowiak, W.","Donnelly, K.","Cavers, S."],"funder":["Natural Environment Research Council"],"givenName":["A.","W.","K.","S."],"grant":["NE/K012177/1"],"identifier":"55118e26-cf5c-41d6-9157-738fce6bdddf","incomingCitationCount":0,"keyword":["Phenology","budburst","height","SNP array","genotypes","Scots pine"],"keywordsOther":["budburst","height","SNP array","genotypes","Scots pine"],"keywordsTheme":["Phenology"],"licence":"Open government licence","lineage":"A common garden glasshouse trial was established in 2010 using seed from natural populations from three species of pine: Pinus sylvestris (SY), Pinus mugo (MU), Pinus uncinata (UN). Open-pollinated seeds were collected from three to five trees per population from twenty-eight natural populations in Europe covering the geographic range of each species. The collection consisted of thirteen populations of SY, nine MU, and six UN. The trial was divided into 25 randomized blocks with up to five families per population, of which the first 18 blocks were analysed by Wachowiak et al. (2018a).\n\nPhenotypes (height, bud set and budburst) were assessed in the glasshouse during spring (budburst), autumn (bud set) and winter (height) between 2010 and 2013. \n\nA subset of trees were selected to be genotyped using a multi-species SNP array. Trees were genotyped using a multi-species SNP array (Perry et al., 2020). DNA was extracted from needles using a Qiagen DNeasy 96 kit following the manufacturer’s instructions. Needles were dried on silica gel prior to extraction and DNA was quantified using a Qubit spectrophotometer to ensure a minimum standardized concentration of 35ng/µl. The quality of genomic DNA was also checked visually for fragmentation on 1 % agarose gel.\n\nGenotyping was done at Edinburgh Genomics following DNA amplification, fragmentation, chip hybridisation, single-base extension through DNA ligation and signal amplification performed according to the Affymetrix Axiom® Assay protocol. Genotyping was performed in 384-well format on a GeneTitan according to the manufacturer’s procedure. Genotype calls were performed using Axiom Analysis Suite software as recommended by the manufacturer (ThermoFisher). Samples were assigned to an analysis group based on their call rate (CR) and dish QC (DQC: a metric provided by ThermoFisher which is generated by measuring signals at multiple sites in the genome known not to vary among individuals), using the following thresholds: DQC ‘high’ ≥ 0.82; DQC ‘low’ < 0.82; CR ‘high’ ≥ 96; CR ‘low’ < 96. Analyses: 1) DQC high + CR high; 2) DQC high + CR low; 3) DQC low + CR low. High quality samples (N=529), with high CR and DQC, were used to set thresholds for allele calls. Posteriors for allele calls were subsequently used as priors for analyses 2 (N = 753) and 3 (N = 251).","locations":["POLYGON((-3.358 55.877, -3.358 56.003, -3.013 56.003, -3.013 55.877, -3.358 55.877))"],"metadataDate":"2026-06-29T18:18:34.000Z","orcid":["https://orcid.org/0000-0002-7889-7597","https://orcid.org/0000-0003-2898-3523","https://orcid.org/0000-0003-2139-9236"],"organisation":["UK Centre for Ecology & Hydrology","Adam Mickiewicz University","NERC EDS Environmental Information Data Centre"],"publicationDate":"2021-08-31T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/55118e26-cf5c-41d6-9157-738fce6bdddf","10.5285/55118e26-cf5c-41d6-9157-738fce6bdddf","doi:10.5285/55118e26-cf5c-41d6-9157-738fce6bdddf"],"resourceType":"Dataset","rightsHolder":["UK Centre for Ecology & Hydrology"],"ror":["https://ror.org/00pggkr55","https://ror.org/04xw4m193"],"shortenedDescription":"This dataset contains details of the phenotypes (height, bud set and budburst) and genotypes (via SNP array) of trees from a common garden multi-species pine (Pinus sylvestris, Pinus mugo and Pinus uncinata) glasshouse trial between 2010 and 2013.","state":"published","title":"Single nucleotide polymorphism (SNP) genotypes and phenotypes for marker-trait association analysis of three pine species grown in a glasshouse","topic":["0/Phenology/"],"version":1.0,"view":["public","margla"]},{"authorAffiliation":["University of Exeter"],"authorFamilyName":["Morrell","Hatchell","Wordingham","Bennie","Inston","Gaston"],"authorFullName":["Morrell, S.A.F.","Hatchell, J.","Wordingham, F.","Bennie, J.","Inston, M.J.","Gaston, K.J."],"authorGivenName":["S.A.F.","J.","F.","M.J.","K.J."],"authorOrcid":["https://orcid.org/0000-0001-6352-5312","https://orcid.org/0000-0002-4870-2760","https://orcid.org/0009-0008-4240-3090","https://orcid.org/0000-0003-4394-2041","https://orcid.org/0009-0008-5833-0180","https://orcid.org/0000-0002-7235-7928"],"authorRor":["https://ror.org/03yghzc09"],"availability":"Unknown","catalogue":"eidc","dataFormat":["R","Comma-separated values (CSV)","JSON","Plain text","Python","Shell scripts","TOML ","EULUMDAT (.ldt)","OBJ ","IES "],"description":"This dataset contains the material required to reproduce 3D volumetric data describing the energy density of photons within a simulated environment and heatmaps and journey lengths for ensembles of weighted walkers experiencing specific simulated environments. The dataset includes source code for snapshots of the Monte Carlo Radiative Transfer (MCRT) code used to run simulations, the weighted random walking code used to emulate the behaviour of animals experiencing the simulated environment, as well as inputs and configuration files for both codes. The MCRT software outputs 3D volumetric data describing the energy density of photons within the simulated environment. Then, the weighted random walk code takes 2D planes from this data and produces heatmaps and journey lengths for ensembles of weighted walkers experiencing these simulated environments. ","documentType":"GEMINI_DOCUMENT","familyName":["Morrell","Hatchell","Wordingham","Bennie","Inston","Gaston"],"fullName":["Morrell, S.A.F.","Hatchell, J.","Wordingham, F.","Bennie, J.","Inston, M.J.","Gaston, K.J."],"funder":["Natural Environment Research Council"],"givenName":["S.A.F.","J.","F.","M.J.","K.J."],"grant":["NE/V000497/1"],"identifier":"1b64b008-8c20-4dd4-bf54-bf1894767a56","incomingCitationCount":1,"keyword":["Exeter","Animal behaviour","Modelling","light","animal behaviour","model","ecology","light pollution","monte carlo radiative transfer","ALAN"],"keywordsOther":["light","animal behaviour","model","ecology","light pollution","monte carlo radiative transfer","ALAN"],"keywordsPlace":["Exeter"],"keywordsTheme":["Animal behaviour","Modelling"],"licence":"Open government licence","lineage":"The source codes provided were written by the authors of the dataset. The code is bundled with industry standard unit tests. Additional validation was carried out as described in supporting documentation. \nThe geometry was generated using the Defra National LIDAR 2020 1m DTM and DSM products, in tandem with the Ordnance Survey VectorMap Local product for buildings. These meshes are checked for watertightness and correct orientation of normals. \nThe emission spectra are assembled from the LICA-UCM spectral catalogue, and the spectral reflectances are taken from version 7 of the USGS Spectral Library. \n","locations":["POLYGON((-3.5164160300000002 50.7328151, -3.5164160300000002 50.73555629, -3.5056966970000003 50.73555629, -3.5056966970000003 50.7328151, -3.5164160300000002 50.7328151))"],"metadataDate":"2026-06-27T18:53:03.000Z","orcid":["https://orcid.org/0000-0001-6352-5312","https://orcid.org/0000-0002-4870-2760","https://orcid.org/0009-0008-4240-3090","https://orcid.org/0000-0003-4394-2041","https://orcid.org/0009-0008-5833-0180","https://orcid.org/0000-0002-7235-7928"],"organisation":["University of Exeter","NERC EDS Environmental Information Data Centre"],"publicationDate":"2024-01-29T00:00:00.000Z","recordType":"Model","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/1b64b008-8c20-4dd4-bf54-bf1894767a56","10.5285/1b64b008-8c20-4dd4-bf54-bf1894767a56","doi:10.5285/1b64b008-8c20-4dd4-bf54-bf1894767a56"],"resourceType":"Model","rightsHolder":["University of Exeter"],"ror":["https://ror.org/03yghzc09","https://ror.org/04xw4m193"],"shortenedDescription":"This dataset contains the material required to reproduce 3D volumetric data describing the energy density of photons within a simulated environment and heatmaps and journey lengths for ensembles of weighted walkers experiencing specific simulated environments. The dataset…","state":"published","title":"Model code to simulate animal behaviour in response to light","topic":["0/Animal behaviour/","0/Modelling/"],"version":1.0,"view":["public","rstu"]},{"authorAffiliation":["Rothamsted Research","Forest Research","University of Warwick"],"authorFamilyName":["Milne","Alonso Chavez","Brown","Parnell"],"authorFullName":["Milne, A.","Alonso Chavez, V.","Brown, N.","Parnell, S."],"authorGivenName":["A.","V.","N. ","S."],"authorOrcid":["https://orcid.org/0000-0002-4509-0578","https://orcid.org/0000-0003-3506-7603","https://orcid.org/0000-0003-3590-0538","https://orcid.org/0000-0002-3039-1159"],"authorRor":["https://ror.org/0347fy350","https://ror.org/03wcc3744","https://ror.org/01a77tt86"],"availability":"Available","catalogue":"eidc","dataFormat":["Comma-separated values (CSV)","Plain text","Header file (.h)","CPP"],"description":"This dataset contains a model, input data and outputs of the Emerald Ash Borer (EAB; Agrilus planipennis) lifecycle and spread across Great Britain. Nine different scenarios are considered related to how certain we are that EAB will arrive through known pathways related to wood imports (70%, 50%, 30%) and the probability that EAB would escape at port rather than at the onwards depots (25%, 50%, 75%).  \n\nThe model outputs can be used to predict the best places to locate surveillance technologies (i.e., girdled trees or traps) and included in this dataset are optimised trap locations for 27 scenarios (three trapping types for each of the nine different scenarios). ","documentType":"GEMINI_DOCUMENT","familyName":["Milne","Alonso Chavez","Brown","Parnell"],"fullName":["Milne, A.","Alonso Chavez, V.","Brown, N.","Parnell, S."],"funder":["Natural Environment Research Council"],"givenName":["A.","V.","N. ","S."],"grant":["NE/T007729/1"],"identifier":"6209742a-bfd6-4fbc-9b40-29d7d75d57b4","incomingCitationCount":0,"keyword":["Great Britain","Invasive species","simulated spread","optimal sampling locations","Agrilus planipennis","trade activity"],"keywordsOther":["simulated spread","optimal sampling locations","Agrilus planipennis","trade activity"],"keywordsPlace":["Great Britain"],"keywordsTheme":["Invasive species"],"licence":"Open government licence","lineage":"The model requires the entry point to be initialized. We developed maps to identify the most likely first incursion point at locations across Great Britain on a 1km x 1km grid. These maps were informed by data from the forestry commission on likely entry points, and data on firewood use. When creating these maps, we considered nine scenarios related to how certain we are that EAB will arrive through known pathways related to wood imports (70%, 50%, 30%) and the probability that EAB would escape at port rather than at the onwards depots (25%, 50%, 75%).  For each scenario we sampled 10000 realizations for likely entry points.  These form the inputs to our model.\n\nThe model is set up to run for annual time steps for 8 years. For each simulated year the larval density and tree health is recorded in infested cells and reported in output files. The model is currently set up to do this for up to 10000 realizations of entry point. The data in the output file can then be used to optimize surveillance. We did this using simulated annealing for three trapping types (Girdled, sticky straps and under bark sampling) in the nine different scenarios. \n\nThe model code was developed in Visual Studio, but plain text files have been provided so that the code can be compiled and run outside of Visual Studio. The model code was checked for errors and the outputs were validated, as far as possible, against spread characteristics from the US. ","locations":["POLYGON((-8.648 49.864, -8.648 60.861, 1.768 60.861, 1.768 49.864, -8.648 49.864))"],"metadataDate":"2026-06-29T16:52:38.000Z","orcid":["https://orcid.org/0000-0002-4509-0578","https://orcid.org/0000-0003-3506-7603","https://orcid.org/0000-0003-3590-0538","https://orcid.org/0000-0002-3039-1159"],"organisation":["Rothamsted Research","Forest Research","University of Warwick","NERC EDS Environmental Information Data Centre"],"publicationDate":"2024-02-27T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/6209742a-bfd6-4fbc-9b40-29d7d75d57b4","10.5285/6209742a-bfd6-4fbc-9b40-29d7d75d57b4","doi:10.5285/6209742a-bfd6-4fbc-9b40-29d7d75d57b4"],"resourceType":"Dataset","rightsHolder":["Rothamsted Research"],"ror":["https://ror.org/0347fy350","https://ror.org/03wcc3744","https://ror.org/01a77tt86","https://ror.org/04xw4m193"],"shortenedDescription":"This dataset contains a model, input data and outputs of the Emerald Ash Borer (EAB; Agrilus planipennis) lifecycle and spread across Great Britain. Nine different scenarios are considered related to how certain we are that EAB will arrive through known pathways related…","state":"published","title":"Simulations of Emerald Ash Borer (EAB) spread in Great Britain with optimised surveillance","topic":["0/Invasive species/"],"version":1.0,"view":["public","jenroe"]},{"authorAffiliation":["Queen's University Belfast","Institute for Animal Science","University of California, Los Angeles","Czech University of Life Sciences","Queen’s University Belfast"],"authorFamilyName":["Mortlock","Esattore","Bartoš","Lyamin","Ježek","Capellini"],"authorFullName":["Mortlock, E.","Esattore, B.","Bartoš, L.","Lyamin, O.","Ježek, M.","Capellini, I."],"authorGivenName":["E.","B.","L.","O.","M.","I."],"authorOrcid":["https://orcid.org/0000-0002-1434-7107","https://orcid.org/0000-0003-1024-794X","https://orcid.org/0000-0003-2667-5930","https://orcid.org/0000-0003-2049-0943","https://orcid.org/0000-0002-4127-9947","https://orcid.org/0000-0001-8065-2436"],"authorRor":["https://ror.org/00strmv13","https://ror.org/046rm7j60","https://ror.org/0415vcw02"],"availability":"Available","catalogue":"eidc","dataFormat":["Plain text"],"description":"This dataset contains biologging data of captive red deer Cervus elaphus, to study sleep behaviour. This includes acceleration (m/s2), magnetometer (gauss), and temperature (degrees Celsius) measurements, collected using collar-mounted accelerometer and magnetometer recorders at 20Hz.\n\nThis data was collected from 18 adult individuals; 13 male, 5 female, in 2023 over three deployments. Deployment 1 (males) 13/06/23 – 1/8/23; deployment 2 (males) 04/09/23 – 08/11/23; deployment 3 (females) 13/11/23 – 21/11/23. Deer were housed at the VUZV facility, Uhrineves, Prague, Czech Republic.\n\nThis dataset was funded by NERC, as part of project “NE/X010368/1: Sleep in the landscape of fear” and was measured to aid in the creation of a classification model to detect sleep in red deer from collar accelerometers, as well as to test arousal thresholds in sleeping deer.\n","documentType":"GEMINI_DOCUMENT","familyName":["Mortlock","Esattore","Bartoš","Lyamin","Ježek","Capellini"],"fullName":["Mortlock, E.","Esattore, B.","Bartoš, L.","Lyamin, O.","Ježek, M.","Capellini, I."],"funder":["Natural Environment Research Council"],"givenName":["E.","B.","L.","O.","M.","I."],"grant":["NE/X010368/1"],"identifier":"e7fdf789-e663-4422-92c2-ea8019b3cc26","incomingCitationCount":0,"keyword":["Animal behaviour","biologging","deer","red deer","animal behaviour","accelerometery","Cervus elaphus"],"keywordsOther":["biologging","deer","red deer","animal behaviour","accelerometery","Cervus elaphus"],"keywordsTheme":["Animal behaviour"],"licence":"Open government licence","lineage":"Biologgers were calibrated immediately prior to deployment. Deer were manipulated in a standard farm handling crush and were not immobilised for deployment. Biologgers were recovered in the same manner.\n\nData was downloaded directly from the Daily Diary logger units and stored in raw format. Data has been transformed into .txt format for reusability across different software. No other processing has taken place, other than screening for device failures, which have been removed from the dataset. \n","locations":["POLYGON((14.595 50.032, 14.595 50.043, 14.606 50.043, 14.606 50.032, 14.595 50.032))"],"metadataDate":"2026-06-29T16:07:13.000Z","orcid":["https://orcid.org/0000-0002-1434-7107","https://orcid.org/0000-0003-1024-794X","https://orcid.org/0000-0003-2667-5930","https://orcid.org/0000-0003-2049-0943","https://orcid.org/0000-0002-4127-9947","https://orcid.org/0000-0001-8065-2436"],"organisation":["Queen's University Belfast","Institute for Animal Science","University of California, Los Angeles","Czech University of Life Sciences","Queen’s University Belfast","NERC EDS Environmental Information Data Centre"],"publicationDate":"2025-08-07T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/e7fdf789-e663-4422-92c2-ea8019b3cc26","10.5285/e7fdf789-e663-4422-92c2-ea8019b3cc26","doi:10.5285/e7fdf789-e663-4422-92c2-ea8019b3cc26"],"resourceType":"Dataset","rightsHolder":["Queen's University Belfast"],"ror":["https://ror.org/00strmv13","https://ror.org/046rm7j60","https://ror.org/0415vcw02","https://ror.org/04xw4m193"],"shortenedDescription":"This dataset contains biologging data of captive red deer Cervus elaphus, to study sleep behaviour. This includes acceleration (m/s2), magnetometer (gauss), and temperature (degrees Celsius) measurements, collected using collar-mounted accelerometer and magnetometer…","state":"published","title":"Biologging data of captive red deer, Prague, Czechia, June-November 2023","topic":["0/Animal behaviour/"],"version":1.0,"view":["public","jashun"]},{"authorAffiliation":["University of Nottingham"],"authorFamilyName":["Ravinet","Rouse"],"authorFullName":["Ravinet, M.","Rouse, J."],"authorGivenName":["M.","J."],"authorOrcid":["https://orcid.org/0000-0002-2841-1798","https://orcid.org/0000-0003-1568-9122"],"availability":"Available","catalogue":"eidc","dataFormat":[".m",".jpeg",".mat"],"description":"This dataset comprises reference and deformed images of F1 hybrid and house sparrow (THE) hybrid skull prints and a short Matlab code to extract wireframe deformation model. Loading was conducted at the University of Nottingham in 2023 on a customised loading frame. A reference database is provided as an example of pre-processed data. ","documentType":"GEMINI_DOCUMENT","familyName":["Ravinet","Rouse"],"fullName":["Ravinet, M.","Rouse, J."],"funder":["Natural Environment Research Council"],"givenName":["M.","J."],"grant":["NE/X018083/1"],"identifier":"38e3bd7f-63a6-41a6-8bb3-4cad89bdb14d","incomingCitationCount":0,"keyword":["Biodiversity","craniofacial morphology","morphology","beak","sparrow","skull"],"keywordsOther":["craniofacial morphology","morphology","beak","sparrow","skull"],"keywordsTheme":["Biodiversity"],"licence":"Open government licence","lineage":"Samples were derived from the collection at the Natural History Museum, Oslo, Norway. All samples were scanned with the use of a high-resolution X-ray Waygate Technologies v|tome|x M 240kV CT system at 26μA at the Hounsfield Facility on the Sutton Bonnington Campus of the University of Nottingham, UK. \nThese were then 3D printed using polyamides at the University of Nottingham. Printed skulls were then tested for mechanical stress in a multiaxial loading frame and stresses quantified using digital image correlation. The deposited data are the results and analysis from this deformation step. \n","metadataDate":"2026-06-29T16:27:48.000Z","orcid":["https://orcid.org/0000-0002-2841-1798","https://orcid.org/0000-0003-1568-9122"],"organisation":["University of Nottingham","NERC EDS Environmental Information Data Centre"],"publicationDate":"2024-11-18T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/38e3bd7f-63a6-41a6-8bb3-4cad89bdb14d","10.5285/38e3bd7f-63a6-41a6-8bb3-4cad89bdb14d","doi:10.5285/38e3bd7f-63a6-41a6-8bb3-4cad89bdb14d"],"resourceType":"Non-geographic dataset","rightsHolder":["University of Nottingham"],"ror":["https://ror.org/04xw4m193"],"shortenedDescription":"This dataset comprises reference and deformed images of F1 hybrid and house sparrow (THE) hybrid skull prints and a short Matlab code to extract wireframe deformation model. Loading was conducted at the University of Nottingham in 2023 on a customised loading frame.…","state":"published","title":"Digital image correlation and mechanical stress test measurements on Passer sparrow skull models","topic":["0/Biodiversity/"],"version":1.0,"view":["public","glenn"]},{"authorAffiliation":["UK Centre for Ecology & Hydrology","Adam Mickiewicz University"],"authorFamilyName":["Cavers","Wachowiak","Perry"],"authorFullName":["Cavers, S.","Wachowiak, W.","Perry, A."],"authorGivenName":["S.","W.","A."],"authorOrcid":["https://orcid.org/0000-0003-2139-9236","https://orcid.org/0000-0003-2898-3523","https://orcid.org/0000-0002-7889-7597"],"authorRor":["https://ror.org/00pggkr55","https://ror.org/04g6bbq64"],"availability":"Available","catalogue":"eidc","dataFormat":["Plain text"],"description":"This dataset contains  ~50,000 single nucleotide polymorphisms (SNPs, DNA mutations) for Scots pine (Pinus sylvestris) and closely related members of the Pinus mugo complex, which were selected for inclusion on a 50K SNP Axiom array","documentType":"GEMINI_DOCUMENT","familyName":["Cavers","Wachowiak","Perry"],"fullName":["Cavers, S.","Wachowiak, W.","Perry, A."],"funder":["Natural Environment Research Council"],"givenName":["S.","W.","A.","Stephen"],"identifier":"cbaa464a-ac18-42bf-8518-c746d8d97270","incomingCitationCount":1,"keyword":["Environmental survey","Micoarray","Speciation","Natural selection ","Divergence ","Polymorphism ","Genotyping "],"keywordsOther":["Micoarray","Speciation","Natural selection ","Divergence ","Polymorphism ","Genotyping "],"keywordsTheme":["Environmental survey"],"licence":"Open government licence","lineage":"The array comprised 49,829 SNPs from several sources, as follows. The majority (N = 49,052) were obtained from transcriptome sequencing of four pine species: Pinus sylvestris, P. mugo, P. uncinata and P. uliginosa (Wachowiak et al., 2015). These included SNPs which were common to all species and also SNPs fixed in one species and polymorphic within and among others. The set of SNPs identified by Wachowiak et al. (2015) was filtered by the array manufacturer (Thermo Fisher) based on p-convert values signifying the SNP array quality, and a list of recommended and non-recommended SNP probes (avoiding SNPs with polymorphisms within 35 bp) was provided to the authors. A further set of SNPs (N = 578) were included from candidate genes (N = 279), which had been resequenced in previous population genetic studies of the pine species (Kujala & Savolainen, 2012; Mosca, Eckert, Di Pierro, et al., 2012; Palmé, Wright, & Savolainen, 2008; Wachowiak, Balk, & Savolainen, 2009; Wachowiak, Zaborowska, et al., 2018). Variation in mitochondrial DNA (mtDNA) was targeted using a set of SNPs (N = 14) which had been discovered by Donnelly et al. (2017). A set of SNPs putatively associated with susceptibility to Dothistroma needle blight (discovered in Pinus radiata, ENA accession numbers ERS1034542-53) were also included (N = 185).\n","locations":["POLYGON((-14.932 34.883, -14.932 61.601, 17.984 61.601, 17.984 34.883, -14.932 34.883))"],"metadataDate":"2026-06-29T16:13:56.000Z","orcid":["https://orcid.org/0000-0003-2139-9236","https://orcid.org/0000-0003-2898-3523","https://orcid.org/0000-0002-7889-7597"],"organisation":["UK Centre for Ecology & Hydrology","Adam Mickiewicz University","NERC EDS Environmental Information Data Centre","NERC Environmental Information Data Centre"],"publicationDate":"2020-03-27T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/cbaa464a-ac18-42bf-8518-c746d8d97270","10.5285/cbaa464a-ac18-42bf-8518-c746d8d97270","doi:10.5285/cbaa464a-ac18-42bf-8518-c746d8d97270"],"resourceType":"Dataset","rightsHolder":["UK Centre for Ecology & Hydrology"],"ror":["https://ror.org/00pggkr55","https://ror.org/04g6bbq64","https://ror.org/04xw4m193"],"shortenedDescription":"This dataset contains  ~50,000 single nucleotide polymorphisms (SNPs, DNA mutations) for Scots pine (Pinus sylvestris) and closely related members of the Pinus mugo complex, which were selected for inclusion on a 50K SNP Axiom array","state":"published","title":"Scots pine single nucleotide polymorphisms (SNP) for Axiom array","topic":["0/Environmental survey/"],"version":1.0,"view":["public","clwe"]},{"authorAffiliation":["UK Centre for Ecology & Hydrology","Adam Mickiewicz University"],"authorFamilyName":["Cavers","Wachowiak","Perry"],"authorFullName":["Cavers, S.","Wachowiak, W.","Perry, A."],"authorGivenName":["S.","W. ","A."],"authorOrcid":["https://orcid.org/0000-0003-2139-9236","https://orcid.org/0000-0003-2898-3523","https://orcid.org/0000-0002-7889-7597"],"authorRor":["https://ror.org/00pggkr55"],"availability":"Available","catalogue":"eidc","dataFormat":["Plain text"],"description":"The data comprise summary statistics for performance of a genotyping microarray for a test set of 87 samples for four pine species. The summary statistics comprise state (polymorphic, monomorphic), mean allele frequency and conversion rate, estimated for each locus as a mean across 87 sample genotypes.\n\nThe array comprised 49,829 SNPs (single nucleotide polymorphisms) from several sources. The majority (N = 49,052) were obtained from transcriptome sequencing of four pine species: Pinus sylvestris, Pinus mugo, Pinus uncinata and Pinus uliginosa. The SNP set was filtered by the array manufacturer (Thermo Fisher) based on p-convert values signifying the SNP array quality, and a list of recommended and non-recommended SNP probes (avoiding SNPs with polymorphisms within 35 bp) was provided to the authors. These included SNPs that were common to all species and also SNPs fixed in one species and polymorphic within and among others. \n\n A further set of SNPs (N = 578) were included from candidate genes (N = 279), which had been resequenced in previous population genetic studies of the pine species. Variation in mitochondrial DNA (mtDNA) was targeted by inclusion of a set of mtDNA- specific SNPs (N = 14). \n\nFinally, a set of SNPs putatively associated with susceptibility to Dothistroma needle blight (discovered in Pinus radiata, European Nucleotide Archive accession numbers ERS1034542-53) were also included (N = 185). ","documentType":"GEMINI_DOCUMENT","familyName":["Cavers","Wachowiak","Perry"],"fullName":["Cavers, S.","Wachowiak, W.","Perry, A."],"givenName":["S.","W. ","A.","Stephen"],"identifier":"0ba33e96-67cb-4650-b2bd-6ee13fa7de97","incomingCitationCount":1,"keyword":["Pinus sylvestris","Pinus mugo","Pinus uliginosa","Pinus uncinata","Genomics","Microarray","SNPs","Polymorphism","Divergence","Natural selection","Speciation","conifer"],"keywordsOther":["Pinus sylvestris","Pinus mugo","Pinus uliginosa","Pinus uncinata","Genomics","Microarray","SNPs","Polymorphism","Divergence","Natural selection","Speciation","conifer"],"licence":"Open government licence","lineage":"The dataset is a list of 49,829 SNP loci, identified by individual code with accompanying columns of basic information and statistics (Conversion type (Poly - polymorphic, Mono-monomorphic), mean allelic frequency (MAF), and call rate (CR)).\n\n","locations":["POLYGON((-9.527 35.922, -9.527 60.989, 17.764 60.989, 17.764 35.922, -9.527 35.922))"],"metadataDate":"2026-06-29T16:19:09.000Z","orcid":["https://orcid.org/0000-0003-2139-9236","https://orcid.org/0000-0003-2898-3523","https://orcid.org/0000-0002-7889-7597"],"organisation":["UK Centre for Ecology & Hydrology","Adam Mickiewicz University","NERC EDS Environmental Information Data Centre","NERC Environmental Information Data Centre"],"publicationDate":"2020-06-26T00:00:00.000Z","recordType":"Dataset","resourceIdentifier":["https://catalogue.ceh.ac.uk/id/0ba33e96-67cb-4650-b2bd-6ee13fa7de97","10.5285/0ba33e96-67cb-4650-b2bd-6ee13fa7de97","doi:10.5285/0ba33e96-67cb-4650-b2bd-6ee13fa7de97"],"resourceType":"Dataset","rightsHolder":["UK Centre for Ecology & Hydrology"],"ror":["https://ror.org/00pggkr55","https://ror.org/04xw4m193"],"shortenedDescription":"The data comprise summary statistics for performance of a genotyping microarray for a test set of 87 samples for four pine species. The summary statistics comprise state (polymorphic, monomorphic), mean allele frequency and conversion rate, estimated for each locus…","state":"published","supplementalDescription":["European Nucleotide Archive accession numbers ERS1034542"],"title":"Conversion rate, frequency and state of single nucleotide polymorphism loci for Scots pine Axiom microarray","version":1.0,"view":["public","clwe"]}],"rows":20,"url":"http://catalogue.ceh.ac.uk:443/eidc/documents?facet=dataFormat%7C(Microsoft%20Word%20(docx)%20OR%20JPEG%20images%20OR%20.mat%20OR%20Plain%20text%20OR%20xml)"}