This is a vector data set representing the land surface of Great Britain, classified into 21 UKCEH land cover classes, based upon Biodiversity Action Plan broad habitats. This vector Land Parcel dataset is the result of intersecting the 10m raster classified pixel datasets with the UKCEH Land Parcel Spatial Framework to generate summary land parcel attributes for each land cover parcel. A full description of this and all UKCEH LCM2022 products are available from the LCM2022 product documentation. Full details about this dataset can be found at https://doi.org/10.5285/80abddf7-3feb-43f8-9244-c5fdb6980075

Data comprise reservoir inflows and release data (including spills), evaporation loss and optimised monthly rule curve ordinates (upper, lower and critical) for Pong and Bhakra reservoirs in Northern India. Also included in the rule curve data are associated reservoir rationing ratios that can be applied to gross demand when rationing is also indicated. Data contain monthly Inflows, net-evaporation loss and release (all in million cubic metres, i.e. x 10^6 m^3) as simulated by WEAP for the Pong and Bhakra reservoir for the baseline (1989 - 2008); mid-century (2032-2050) and end-century (2082-2100) periods. The future inflows were based on forcing the WEAP model of the basin with climate projections of the GFDL-CM3 CMIP model The data were collected by Heriot-Watt University under the Sustaining Himalayan Water Resources in a Changing Climate (SusHi-Wat) project funded by NERC. Full details about this dataset can be found at https://doi.org/10.5285/46135938-cc6c-44a0-b35b-f6e5f5dd1221

This dataset consists of polygon and polyline layers containing categorised soil erosion and disturbance features collected as part of the Environment and Rural Affairs Monitoring & Modelling Programme (ERAMMP) National Field Survey (NFS) between 2021-2023. Data include extent and categorised type of soil erosion and disturbance (SED) features from a desk-based survey of aerial imagery and mapped by field surveyors between 2021-2023. This dataset also includes a raster map of the primary groups of controls on SED feature density in Wales. ERAMMP NFS is a resurvey of all of the 300 locations from the initial Glastir Monitoring and Evaluation Programme (GMEP) monitoring program (300 1km squares) on a rolling annual basis, with the aim to resurvey all sites between 2021 and 2025. SED features were identified from aerial images of 261 squares. Between 2021-2023 ERAMMP NFS field surveyors surveyed zones within 225 squares for SED features. The initial monitoring program, GMEP, was set up by the Welsh Government in 2013 to report national trends and monitor the effects of the Glastir agri-environment scheme on the environment and ran from 2013 to 2016. The field survey element was based on a stratified random sampling design of 300 x 1km square sites across Wales, and was managed by the UK Centre for Ecology & Hydrology. Full details about this dataset can be found at https://doi.org/10.5285/b7003a63-dc97-4044-9201-ccc5d8deffa6

This data set contains satellite-derived information on geomorphic river mobility for ten catchments in the Philippines. We applied the locational probability approach to map the proportion of time that a river channel occupies a particular location. We quantified satellite-derived locational probabilities for 600 km2 of riverbed. The information is useful for predicting and developing resilience to river-related hazards in dynamic landscapes. We provide example Google Earth Engine (GEE) and MATLAB codes to replicate satellite-derived locational probability analyses, and provide outputs for each catchment. Data sets include: (1) example GEE codes to run satellite imagery analyses; (2) example MATLAB codes and data to generate locational probabilities; (3) example MATLAB codes and data to produce longitudinal analyses; and, (4) processed locational probability outputs for the ten catchments. The work was supported by the Natural Environment Research Council (NERC) and Department of Science and Technology - Philippine Council for Industry, Energy and Emerging Technology Research and Development (DOST-PCIEERD) – Newton Fund grant NE/S003312. Full details about this dataset can be found at https://doi.org/10.5285/a2bcc66e-4dcc-4ed1-897d-cdf36dde246d

This dataset presents daily data from temperature and soil moisture sensors in each experimental plot (n=9 plots). Soil temperature is measured at 5 cm and 20 cm soil depth (degrees Celsius), and soil moisture is measured as soil volumetric water content (m3 per m3). Data were collected from the climate change field site Climoor that is located in Clocaenog forest, NE Wales. The experimental field site consists of three untreated control plots (Plots 3, 6 and 9), three plots where the plant canopy air is artificially warmed during night time hours (Plots 1, 2 and 7) and three plots where rainfall is excluded from the plots at least during the plants growing season (Plots 4, 5 and 8). Data is an extension for the micromet datasets 1998-2015, 2015-2016, 2016-2021 and 2022-2023 covering the time period January 2024 to December 2024. Soil temperatures are measured with a T107 sensor from Campbell scientific. Soil moisture is measured with CS616 sensors from Campbell scientific. Temperature and moisture data are logged in minute intervals and are averaged as half-hourly. The Climoor field experiment intents to answer questions regarding the effects of warming and drought on ecosystem processes. The reported plot level temperature and soil moisture data are important to evaluate the effect of the imposed climatic treatments on ecosystem processes and functioning. Data collection, processing and quality checks were carried out by UKCEH staff. More detailed information about the field site, measurements and related datasets can be found in the documentation accompanying the data. Full details about this dataset can be found at https://doi.org/10.5285/21e8957f-48b2-4e29-8aa5-247cf060a59c

This is a 10m pixel data set representing the land surface of Northern Ireland, classified into 21 UKCEH land cover classes, based upon Biodiversity Action Plan broad habitats. It is a two-band raster in GeoTiff format. The first band gives the most likely land cover type; the second band gives the per-parcel probability of the land cover. A full description of this and all UKCEH LCM2021 products are available from the LCM2021 product documentation. Full details about this dataset can be found at https://doi.org/10.5285/e44ae9bd-fa32-4aab-9524-fbb11d34a20a

This data resource consists of two files: (a) 1x1 km resolution Average Accumulated Exceedance (AAE) data summarising the exceedances of acidity critical loads for eight habitats; (b) 1x1 km resolution AAE data summarising the exceedances of nutrient nitrogen critical loads for thirteen habitats. The data provide information on the amount of excess acid or nitrogen deposition above the critical load values set to protect acid- and nitrogen-sensitive habitats in the UK. The AAE has been calculated using UK 5x5 km Concentration Based Estimated Deposition (CBED) data for 2016-18 (https://doi.org/10.5285/5999d471-fe1d-45fa-889d-3156edb785a7). The data were generated under Defra-funded work to assess the potential areas of acid and nitrogen sensitive habitats at risk of adverse impacts from excess atmospheric acid and nitrogen deposition. Reducing the area and amount of critical load exceedance continues to be a driver of Government policy on reducing emissions of acidic and nitrogen-containing air pollutants (sulphur dioxide, nitrogen oxides and ammonia). Full details about this dataset can be found at https://doi.org/10.5285/41da8be9-729b-455c-a5c8-093fd0486de1

This dataset consists of plant species presence and abundance in different sizes of plots recorded from 100 1km squares across Great Britain in 2025, as part of a rolling soil and vegetation monitoring program of 500 1km squares, beginning in 2019 and repeated every 5 years. 2025 represents the second year of a new cycle. The UKCEH Countryside Survey is a unique study or 'audit' of the natural resources of the UK's countryside. The sample sites are chosen from a stratified random sample, based on a 15 by 15 km grid of GB. Surveys have previously been carried out in 1978, 1984, 1990, 1998 and 2007 by the UK Centre for Ecology & Hydrology (UKCEH) and predecessors, with repeated visits to the majority of squares. The countryside is sampled and surveyed using rigorous scientific methods, allowing us to compare new results with those from previous surveys. In this way, we can detect the gradual and subtle changes that occur in the UK's countryside over time. In addition to vegetation data, soil data are also gathered by the current phase of the Countryside Survey. This research was supported by NERC, through the UKCEH National Capability for UK Challenges Programme NE/Y006208/1 (www.countrysidesurvey.org.uk) Full details about this dataset can be found at https://doi.org/10.5285/bf8be82a-a189-4767-9a9a-ebb92d233b8e

This data set comprises water quality data from five tributaries of the River Thames, UK. Sampling sites at each river were from both upstream and downstream of sewage effluent point sources. Parameters measured were phosphorus and nitrogen species, dissolved organic carbon and major dissolved anions (fluoride, chloride, sulphate). This work was carried out as a part of the NERC project: “The environmental REsistome: confluence of Human and Animal Biota in antibiotic resistance spread (REHAB)” (Project reference NE/N019660/1). Full details about this dataset can be found at https://doi.org/10.5285/80710d5e-06cf-4757-93c5-87fcbe421352

This dataset includes key leaf functional trait data collected from three common garden sites along an elevation/temperature gradient in the Colombian Andes. From eight species, there are a selection of leaf structural (leaf mass per unit area, leaf thickness, leaf dry matter content, leaf area, leaf width) nutrient (nitrogen and phosphorus, expressed on area- and mass-bases) and water-use efficiency (13C and g1) traits. Values for these traits were obtained by a combination of laboratory analysis, raw measurements with handheld equipment, and processing with packages in the ‘R’ environment. Full details about this dataset can be found at https://doi.org/10.5285/55ed98e7-f150-43c8-9b93-d639c1c8af3e