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  • [THIS DATASET HAS BEEN WITHDRAWN]. A spatial indicator of ecological status for valuation of biodiversity across the UK, based on species occurrence records was developed. UK species occurrence data were collated from the Biological Records Centre (BRC). The mean ecological status was calculated across all taxonomic groups for the 2000 to 2013 time period, relative to the species richness maximums from the 1970-1990 time period, showing differences as colours. Full details about this dataset can be found at

  • Plant occupancy data from a survey of a disturbed urban habitat. The survey is an occupancy study of the vascular plants of 16 500 x 500 m (0.25 km2) urban grid cells, stratified by quadrant at the scale of the focal city (Sheffield, England) in order to provide more even coverage. Few systematic, randomised surveys at fine spatial grain exist for urban habitats, and even fewer of these surveys are in the public domain. This study was designed as a systematic florula (i.e. a small flora) of a relatively discrete urban habitat in order to provide a baseline that would enable robust insights into future environmental change. In addition, the dataset is likely to be useful for comparative studies of plant traits, particularly those of highly disturbed habitats. Full details about this dataset can be found at

  • Illumina short-read sequence data from targeted capture of 434 genes, including 150 chemosensory genes, in 104 individuals distributed across eight host races of the pea aphid. This data is NERC-funded but not held by the EIDC. This data is archived in the European Bioinformatics Institute SRA (Sequence Read Archive) with project accession reference PRJEB6325

  • This dataset gives axiophyte score for plants in Great Britain, based on Botanical Society of Britain and Ireland (BSBI) published lists of axiophytes for 24 counties in Great Britain. Axiophytes have been defined as 'worthy plants', that is, species that are indicative of high quality habitat within a particular region. This information product takes the county lists that were available in May 2016, and summarises the data in order to produce national (i.e. Great Britain) level scores of 'axiophyte-ness'; that is, the extent to which a species has been selected as a good indicator of high quality habitat where it occurs. This meta-list of axiophytes will be updated in the future as more county-level lists become available. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability. Full details about this dataset can be found at

  • Estimates of in-river concentrations (mg/l) and loads (kg/day) of nutrients to rivers in England and Wales from multiple sector sources, modelled with SAGIS (Source Apportionment GIS). The nutrients include nitrate (mg/l N) and ortho-phosphate (mg/l P); the estimate loads are expressed as kilograms per day (kg/day) and the in-river concentrations as milligrams per litre (mg/l). Sources are both diffuse and point. Diffuse sources include livestock farming, arable farming, highways, urban runoff, background (from soils), onsite wastewater treatment systems and atmospheric deposition. Point sources include treated wastewater effluent, combined sewer overflows and storm tanks, industrial discharges and mine water discharges. Concentrations and loads are modelled using the Environment Agency's catchment river model, SIMCAT, at the locations of model features or every 1 km along each river, taking into account all upstream sources and user defined river losses. SAGIS is a modelling framework was developed through the UK Water Industry Research Programme (UKWIR) project 'Chemical Source Apportionment under the WFD' [1], with support from the Environment Agency and SEPA. The model is also described in [2] [1] UKWIR (2012) Chemical Source Apportionment under the WFD (12/WW/02/3). Final report for UK Water Industry Research, 1 Queen Annes Gate, London, ISBN: 1 84057 637 5. [2] Comber, S.D.; Smith, R.; Daldorph, P.; Gardner, M.J.; Constantino, C.; Ellor, B. (2013) Development of a Chemical Source Apportionment Decision Support Framework for Catchment Management. Environ. Sci. Technol. 47, 9824-9832 Full details about this dataset 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

  • Data on the carbon and nitrogen cycling in soils from different geologies within the Hampshire Avon catchment, UK. The dataset also includes functional gene data, anion and cation concentrations, methane production and oxidation potential, and nitrification, denitrification and mineralization rates. Data were collected between February 2013 and November 2014. Data were collected to address the hypotheses of how the functional microbial community involved in carbon and nitrogen cycling changed seasonally and with geology. Data were collected as part of the project "The role of lateral exchange in modulating the seaward flux of C, N, P", funded under NERC's Macronutrients Cycles research programme. Full details about this dataset can be found at

  • This dataset contains nutrient data from soils and microbial biomass in soils from an experiment based at Winklebury Hill, UK. The experiment used seeds and plug plants to create different plant communities on the bare chalk on Winklebury Hill and tested the resulting carbon and nutrient cycling rates and compared these to the characteristics of different plant functional groups. The experiment ran from 2013 to 2016 and this dataset contains data from 2014 only. This experiment was part of the Wessex BESS project, a six-year (2011-2017) project aimed at understanding how biodiversity underpins the ecosystem functions and services that landscapes provide. Full details about this dataset can be found at

  • The dataset contains time series of dissolved oxygen dynamics and near-streambed light availability from selected riverine sites within the Hampshire Avon catchment (UK). Six rivers within sub-catchments of contrasting geology (clay, greensand, chalk) and associated river morphology were investigated. Data were obtained from field-based measurements in seasonal campaigns conducted between spring 2013 and winter 2014. Full details about this dataset can be found at

  • Data comprise results of a soil survey in England, Scotland and Wales carried out during 2013 and 2014 as part of the NERC Macronutrient Cycles project: LTLS : Analysing and simulating long-term and large-scale interactions of carbon nitrogen and phosphorus in UK land, freshwater and atmosphere. The data include bulk density measurements, charcoal and coal determinations, site locations and sampling dates, site vegetation data, soil chemistry and isotope data, soil classifications, information on soil cores collected and soil texture data. Full details about this dataset can be found at