Bulk elemental (carbon and nitrogen) and stable isotope (delta 13C and delta 15N) data produced from 491 samples collected between 2016-2021 from terrestrial (soil, peat, living biomass, dead biomass), intertidal (saltmarsh vegetation, saltmarsh roots, seagrass biomass, mudflat, faecal matter) and marine (macroalgae, microalgae zooplankton, finfish aquaculture waste) environments across the UK. These samples alongside analytical standard derived from natural materials (lignin, humic acid, cellulose, glucose, protein) were analysed to determine their bulk elemental (organic carbon and nitrogen) and stable isotope (delta 13C org and delta 15N) composition. These values are envisioned to be used to constrain organic carbon sources (terrestrial vs marine) in the natural environment when used alongside isotope mixing models. The work was carried out under the NERC programme - Carbon Storage in Intertidal Environment (C-SIDE), NERC grant reference NE/R010846/1. Full details about this dataset can be found at https://doi.org/10.5285/a445a7a8-528d-4e0b-9094-28cbcd449367

The data consists of estimated hourly average inflow discharge (m3s-1) and water temperature (°C) of the inflow of the inner basin of Elterwater (lat: 54.428, long: -3.034) from January 2012 to December 2019. The work was supported by the Natural Environment Research Council (Grant NE/ L002604/1). Full details about this dataset can be found at https://doi.org/10.5285/2883aaf1-6148-49cb-904a-d271a028c716

The dataset includes six files of UK physical river characteristics including five files of gridded data at 1 km x 1 km resolution and one comma separated table. The data includes: • Drainage directions (D8 flow method), ESRI coding • Drainage directions (D8 flow method), unifhy (python hydrology framework) coding • Catchment areas (km2) • Widths of bankfull rivers (m) • Depths of bankfull rivers (m) • NRFA gauging station locations (easting (m), northing (m)) Two versions of drainage directions are provided, both have the same drainage directions but different numbering systems. The comma separated NRFA (National River Flow Archive) gauging station locations table provides the best locations of 1499 river flow gauging stations on the 1km grids, together with the approximate error in the 1km × 1km gridded delineation of the upstream catchment area. All datasets are provided on the British National Grid. Full details about this dataset can be found at https://doi.org/10.5285/8df65124-68e9-4c68-8659-1c6b82c735e9

The data represent a quantitative measure of aboveground (vegetation) biomass, organic carbon content and aboveground (vegetation) carbon from 144 vegetation samples collected across ten UK saltmarshes between 2019 and 2020. Sites were chosen to represent contrasting habitat types in the United Kingdom, in particular sediment types, vegetation, and sea level history. Full details about this dataset can be found at https://doi.org/10.5285/f71c9f3e-0ae1-4318-a3ea-1dd30b7af3be

The data set contains grain size distributions, organic matter (OM) content and trace metal distribution (including Fe, Zn, Cu, Cr and Pb) of 37 shallow cores of sediments sampled from dams across the Limpopo River Basin. The dams include: Gaborone, Lotsane and Shashe dams in Botswana; Houtrivier, Nwanedi and Mutshedzi dams in South Africa; Ripple Creek and Zhovhe dams in Zimbabwe; and Massingir Dam in Mozambique. Data from two cores sampled from an oxbow lake in Mozambique are also included. The cores were collected with a gravity corer using PVC pipes of 5 cm diameter by a team from Botswana International University of Science and Technology (BIUST) led by Dr. Franchi between July 2018 and April 2021. Full details about this dataset can be found at https://doi.org/10.5285/b8db8239-3bde-454a-aa75-d1cec24c8763

Data comprise morphometric measurements, sex determination, maturity and immunological analysis of blood pathogens from wild field voles (Microtus agrestis) in Kielder Forest, Northumberland, UK in 2015-17. Full details about this dataset can be found at https://doi.org/10.5285/e5854431-6fa4-4ff0-aa02-3de68763c952

The data are derived from Alnus glutinosa plants grown in intact soil cores collected from beneath three co-occurring tree species. The data describe plant above and below ground biomass, coarse and fine root biomass, colonisation of roots by Frankia and ectomycorrhizal fungi, ecosystem carbon fluxes, capture of 13C from a pulse labelling process, 15N content of leaves, and soil nutrients. Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/8816a55a-0e2e-4414-872f-3575170585dc

[THIS DATASET HAS BEEN WITHDRAWN]. This dataset provides Concentration Based Estimated Deposition (CBED) values of sulphur and nitrogen atmospheric deposition for 1x1 kilometres (km) grid squares of the UK averaged over the years 2018 to 2020. The data consist of deposition values for sulphur, oxidised nitrogen and reduced nitrogen, and base cations. Total deposition is the sum of four components calculated separately: wet deposition, dry deposition of gases, dry deposition of particulate matter and cloud droplet deposition. Habitat-specific data are provided for (i) moorland/short vegetation everywhere, and (ii) forest everywhere. Additionally, the grid square average over multiple land cover types (i.e. arable, grassland, forest, moorland, urban) is also calculated. The habitat-specific data are recommended for use with critical loads for the calculation of critical load exceedances. The work in generating and compiling the dataset has been funded by the UK Centre for Ecology & Hydrology (UKCEH) and various Departments for Environment, Food & Rural Affairs (Defra) contracts. Full details about this dataset can be found at https://doi.org/10.5285/4a5a9140-96f1-4aee-b547-ef570238fdbd

Data comprise results of social surveys carried out in China during 2016 – 2018 to environmental scientists and the local stakeholders (farmers and village to county level officials) to understand their knowledge learning dynamics and preference. Surveys were conducted in the rural villages in Puding County, Guizhou Province, Changwu County, Shaanxi Province, and Yujiang County, Jiangxi Province. Full details about this dataset can be found at https://doi.org/10.5285/e674e08c-fbf5-411b-940c-7e31014f0e76

This dataset includes a set of modelled outputs produced as part of the DECIDE project. Three groups were modelled; butterflies, day-flying moths and night-flying moths. (For the moths, we only considered 'macro-moths'.) For each group there are three outputs; species richness, model variability and DECIDE recording priority. The outputs summarise across multiple species within each group. The model’s prediction probability of occurrence for individual species is not made available. The outputs are in a raster format on Ordnance Survey National Grid reference system (OSGB) at 100m x 100m resolution. Species richness layers are a modelled prediction of how many species are present at a location. Model variability is used to determine where a model is uncertain about its prediction of species occurrence. Model variability is combined with information about how recently a species had been recorded to produce the DECIDE recording priority. The DECIDE recording priority is a measure to prioritise locations to support adaptive sampling of where to collect species occurrence data to improve species distribution models. Full details about this dataset can be found at https://doi.org/10.5285/445381ce-f412-48a0-bc3c-2d0ef4737274