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  • This dataset is an inventory of reservoir details for the UK. It provides information, including reservoir location, type (impounding or non-impounding), use (water resources, hydro-electric, ecological, flood storage, canal), capacity, planning date, construction date, catchment National River Flow Archive (NRFA) gauge references and membership of a reservoir group, based on current usage within the CEH Monthly Hydrological Summary ( The dataset comprises 273 individual reservoirs, which amount to approximately 90% of total UK reservoir storage. Data quality has been recorded, using a data flag system and a notes section, with references relevant to each reservoir provided. Full details about this dataset can be found at

  • The resource consists of genome sequence data for the Drosophila C virus that has been serially passaged through different species of Drosophila in the laboratory. The genomes were sequenced and aligned to the reference genome. The frequency of variants at both biallelic and triallelic sites was then calculated. We also generated a phylogeny of the species involved using published data. This data was generated to understand how viruses adapt to new host species by Francis Jiggins and his co workers. The work was carried out between July 2016 and September 2017 and was funded by NERC under award reference NE/L004232/1 Full details about this nonGeographicDataset can be found at

  • The data consist of soil carbon in kilogrammes (kg) of carbon per metre squared. Soil cores were taken to a depth of 1 metre and divided into 15 cm depth increments. Soil carbon (kg carbon per metre squared) was determined for all soil depth increments. The soil samples were taken in the Conwy catchment in North West Wales. Samples were collected in the spring of 2014 across a land use intensification gradient ranging from semi-natural peatlands, acid grasslands to improved grasslands and arable fields. Soil parameters were tested across a land use intensification gradient to detect parameters that can predict aboveground biomass production across different land management types. Data were used to enhance the predictions of biomass production in the Joint UK Land Environment Simulator model (JULES). Measurements informed the improvement of the nitrogen cycle component in the model. This dataset is part of a data series where plant and soil measurements were collected together to increase our understanding of coupled aboveground and belowground processes. Measurements were undertaken by trained members of staff from Bangor University, the Centre for Ecology & Hydrology and Exeter University. This data was collected for the NERC project 'The Multi-Scale Response of Water quality, Biodiversity and Carbon Sequestration to Coupled Macronutrient Cycling from Source to Sea' (NE/J011991/1). The project is also referred to as Turf2Surf. Full details about this dataset can be found at

  • This dataset contains calculated terrestrial fluxes of methane and nitrous oxide using static chambers from the Sodankylä region of Northern Finland across both forest and wetland ecosystems. Measurements were carried out during growing season 2012 in two measurement campaigns (Summer: 12th July - 2nd August; Autumn: 22nd September - 14th October) using 60 static chambers (21 within the forest and 39 within the wetland). Fluxes were measured on approximately 2 day intervals resulting in a total of 10 measurements for all chambers during the summer campaign, and 7 for the forest and 8 for the wetland chambers during the autumn campaign. In addition to fluxes, auxiliary measurements include soil temperature, water table depth (wetland only), soil moisture (forest only) and soil respiration. The data was collected as part of the MAMM project (Methane and other greenhouse gases in the Arctic: Measurements, process studies and Modelling, funded by the UK Natural Environment Research Council (grant NE/I029293/1) involving partners from CEH and the Finnish Meteorological Institute (Climate Change Research, FI-00101 Helsinki, Finland). Full details about this dataset can be found at

  • This dataset contains the transcripts of interviews and discussion groups from seven villages in the Mabalane district, Gaza province, Mozambique. The seven villages were selected from a forest degradation gradient running from villages with abundant undisturbed forest areas to those with degraded forests, mainly driven by charcoal production. The villages had similar infrastructure, soils, rainfall, and vegetation types. The dataset contains information on seasonality, how availability and use of products from the forest has changed over time (trend analysis), wealth ranking within the villages and differences between wealth statuses, and profiles/characteristics of each village. Interviews were conducted with groups in each village or the leader of the village, between May and September 2014. Data were collected as part of a project funded under the Ecosystem Services for Poverty Alleviation (ESPA) programme. Full details about this dataset can be found at

  • [THIS DATASET HAS BEEN WITHDRAWN]. This dataset contains calculated breeding success rates for six seabird species from representative colonies on the Isle of May, off the East coast of Scotland. Annual breeding success has been measured as the number of chicks fledged per active nest for the Atlantic puffin (Fratercula arctica, since 1982), common guillemot (Uria aalge, since 1982), razorbill (Alca torda, since 1982), European shag (Phalacrocorax aristotelis, since 1987), black-legged kittiwake (Rissa tridactyla, since 1987) and northern fulmar (Fulmarus glacialis, since 1987). The number of active nests recorded are also provided. Data were collected as part of the Isle of May long-term study (IMLOTS), which aims to identify the impact of environmental change on seabirds and their associated ecosystems. This monitoring has been ongoing since 1974, by essentially the same team of scientists, using the same well-documented methods throughout this time. Full details about this dataset can be found at

  • Hourly precipitation (mm) recorded at distributed points around Kampala between April 2019 and March 2020. Only timestamps where data were available from all sensors have been included. There are 8094 records in total and no missing values. Timestamps are recorded as “YYYY-MM-DD hh:mm:ss”. The geographic coordinates of the sensors are provided in GeoJSON format. The column names in the CSV file correspond to the “id” field in the GeoJSON file. Full details about this dataset can be found at

  • This dataset contains height, foliage height diversity, mean crown area, tree count, bedrock, elevation, age, aspect and slope data for woodlands under 1ha in size that were also covered by Defra’s LiDAR survey in the year 2011 in the Isle of Wight. These data were collected to see if the presence of an adjacent older neighbour affects woodland structure and height in recently created woodlands. Data was processed by the author under NERC Grant NE/S007458/1 PANORAMA - A Yorkshire partnership for training in environmental careers Full details about this dataset can be found at

  • This dataset comes from Moringa oleifera and M. stenopetala seed pod collections harvested from known provenances in Kenya. The data includes both pod and seed traits as well as canopy and coppicing information for the mother trees. Full details about this dataset can be found at

  • This dataset is part of Integrated Hydrological Units (IHU) of the UK, a set of geographical reference units for hydrological purposes including river flow measurement and hydrometric data collection. Hydrometric Areas are either integral river catchments having one or more outlets to the sea or tidal estuary, or they may include several contiguous river catchments having topographical similarity but separate tidal outlets. Hydrometric Areas are the coarsest units of the IHU in terms of spatial resolution. This dataset represents the same entities as the Hydrometric Areas with Coastline. The coastline of Hydrometric Areas without Coastline follows the boundaries of the CEH Integrated Hydrological Digital Terrain Model, from which IHU were derived, while the coastline used in Hydrometric Areas with Coastline was derived from Ordnance Survey data. The Hydrometric Areas without Coastline currently covers Great Britain only as no dataset with river geometries and names with suitable detail is available for Northern Ireland. Full details about this dataset can be found at