This dataset consists of measures of topsoil (0-15 cm) physico-chemical properties from soils sampled from 110 x 1-km squares across Great Britain in 2022 as part of a rolling soil and vegetation monitoring program of 500 1-km squares repeated every 5 years. The properties included are: pH, soil organic matter (loss on ignition, LOI), derived carbon concentration and carbon stock (SOC), soil group, soil bulk density of fine earth, soil moisture of wet soil, fine earth volumetric water content (dry), nitrogen concentration and stock, and Olsen-phosphorus concentration. 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 been carried out in 1978, 1984, 1990, 1998 and 2007 by the UK Centre for Ecology & Hydrology (UKCEH) and predecessors, with repeated visits to most of the 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 soil data, vegetation species data are also gathered by the current phase of the UKCEH Countryside Survey. 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 https://doi.org/10.5285/d53fdf1d-767a-4046-821a-ea645001ddd3

The dataset consists of slope, aspect, locations, descriptions and habitat categories from plots and sites in 103 woodlands surveyed across Great Britain in 1971 and again over the growing seasons of 2000, 2002 and 2003 (referred to as '2001 survey'), using exactly the same field methods. Data were collected under projects managed by The Nature Conservancy (in 1971) and the Centre for Ecology & Hydrology (in 2001). Full details about this dataset can be found at https://doi.org/10.5285/d6409d40-58fe-4fa7-b7c8-71a105b965b4

This dataset provides the location details of Environmental Change Network (ECN) sites from which data are collected. There are 12 terrestrial sites and 45 freshwater sites. Sites range from upland to lowland, moor land to chalk grassland, small ponds and streams to large rivers and lakes. ECN is the UK's long-term environmental monitoring programme. A wide range of integrated physical, chemical and biological variables which drive and respond to environmental change are collated, quality controlled and made freely available for scientific research. The data form an important evidence base for UK environmental policy development. ECN is a multi-agency programme sponsored by a consortium of fourteen government departments and agencies. These organisations contribute to the programme through funding either site monitoring and/or network co-ordination activities. These organisations are: Agri-Food and Biosciences Institute, Biotechnology and Biological Sciences Research Council, Cyfoeth Naturiol Cymru - Natural Resources Wales, Defence Science & Technology Laboratory, Department for Environment, Food and Rural Affairs, Environment Agency, Forestry Commission, Llywodraeth Cymru - Welsh Government, Natural England, Natural Environment Research Council, Northern Ireland Environment Agency, Scottish Environment Protection Agency, Scottish Government and Scottish Natural Heritage.

This dataset contains time series observations of surface-atmosphere exchanges of net ecosystem carbon dioxide exchange (NEE), sensible heat (H) and latent heat (LE), and momentum (τ) measured at an area of organically managed grassland located on the Berkshire Downs, UK. Turbulent flux densities were monitored using the micrometeorological eddy covariance (EC) technique between 1st January 2017 and 31st July 2019. The dataset includes ancillary weather and soil physics observations, as well as variables describing atmospheric turbulence and the quality of the turbulent flux observations. 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 https://doi.org/10.5285/5a93161f-0124-4650-a2c9-7e8aaea7e6bb

Data from literature search systematically conducted using two widely-used academic databases: Web of Science (WoS) and Scopus . Data include the annual amount of KM publication in China and across the world, in WoS, the total amount of knowledge management (KM) publication during the searched years for each country (top 20), in Scopus, the total amount of KM publication during the searched years for each country (top 20), information about the retained KM publication for environmental management in China. The data were generated during the NERC grant 'The transmissive critical zone: understanding the karst hydrology-biogeochemical interface for sustainable management' reference NE/N007425/1 undertaken as part of the NERC Using Critical Zone Science to Understand Sustaining the Ecosystem Service of Soil & Water (CZO) programme. Full details about this dataset can be found at https://doi.org/10.5285/9bbcbd03-0b6d-409d-9ad1-650c25f5ac73

The data comprise measurements of the 'soluble', 'chemically exchangeable' and 'isotopically exchangeable' U concentrations in a diverse set of soils following experimental addition of UO22+ and incubation in the laboratory under controlled temperature conditions for ca. 1.7 years. The long term behaviour of U in aerobic soils was studied by conducting a laboratory-based experiment in which a set of twenty topsoils from central England with contrasting properties (e.g. pH, organic matter content, land use) were contaminated with a solution containing UO22+ in soluble form and incubated in the dark, in a moist but aerobic condition, at a temperature of 10 deg C for 619 days. The transformations of U in each soil microcosm were periodically monitored by means of soil extractions conducted on subsamples of incubated soils. The resulting dataset enabled quantification of the kinetics of UO22+ transformations in aerobic soils and the relationships with soil properties and land uses (arable, grassland and moorland/woodland). The dataset will be useful in developing models of long-term U bioavailability in aerobic soils under temperate conditions. Full details about this dataset can be found at https://doi.org/10.5285/0d8b2aea-574c-4cff-a8bd-17115a0b90fc

This dataset contains data that are meant to be used in conjunction with the “Digital Elevation Model of an experimental river generated in a flume under variable discharge conditions” dataset. There are three data files. The Sed_fluxes.csv file contains mass balance information i.e., the sediment flux injected in the channel and that collected at the outlet. The other two files detail the evolution of the channel morphology before and after each of the experimental flood events. Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/9457cd25-b8d6-4319-8e75-e9fdc7a171ab

The products represent biomass estimates for four areas of interest in the Corridor Ankeniheny Zahamena (CAZ), Madagascar, generated using very high resolution imagery and based on field-collected plot information. The study extent aims to capture the drivers of deforestation in the Corridor Ankeniheny-Zahamena (CAZ). Multiple variables were incorporated into the sampling design, including elevation, slope, bioclimate zone, length of dry season, soil type, deforestation history (by epoch and elevation), and access. Based on these criteria, four Zones of Interest (ZOIs) were identified and modified in an iterative approach involving preliminary reconnaissance work, information on access provided by partners, and initial analyses of spatial data layers. The products were generated as part of a project, 'Can Paying 4 Global Ecosystem Services reduce poverty?' (P4GES), funded by the Ecosystem Services for Poverty Alleviation (ESPA) programme Full details about this dataset can be found at https://doi.org/10.5285/9b516d3e-ac72-4453-a6de-b29d2ba2ef4f

Data are presented showing grass productivity as grammes per 100 square centimetres under four different nutrient treatments (water, nitrogen, phosphorus and nitrogen & phosphorus combined). An experimental hillslope in the Conwy catchment was selected in August 2016. Three transects, were identified across the hillslope. Along each transect, a 1 x 1 square metre quadrat was used to delineate randomly selected sampling areas. Within each quadrat 5 individual 10 x 10 x 10 centimetre (cm) swards were collected using a spade and transported to the laboratory in Bangor University for the nutrient addition. Three different harvests at different stages (initial cut, first harvest, second harvest) were conducted in order to measure grass productivity. Harvest included removal of all vegetation within the quadrat down to approximately 1 cm in height. The data were collected to identify the nutrient limitations within the hillslope by trained members of staff from Bangor University and the Centre for Ecology & Hydrology. The data were 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 https://doi.org/10.5285/6e395915-ab5c-43f4-b4de-c9a3c5c1b956

This dataset includes the PROTECH validation output against a yearlong monitoring study conducted during 2016 in the lake and catchment of Rostherne Mere and the PROTECH output files following changes in internal and external nutrient loads and future climate scenarios based on the UK Climate Projections (UKCP09) data. These data were collected to demonstrate the future possible trajectories of change with alterations in air temperature, internal nutrient loads and external nutrient loads. Validation data is presented as daily model outputs, while all future projection data is presented as collated annual average model output data for each future change scenario. The PROTECH model (Phytoplankton RespOnses To Environmental CHange) simulates the in situ dynamics of phytoplankton in lakes and reservoirs, specialising in predicting phytoplankton species, particularly Cyanobacteria (blue-green algae) The work was carried out as part of a Natural Environment Research Council (NERC) funded PhD [grant number NE/L002493/1]. Full details about this dataset can be found at https://doi.org/10.5285/2f0eae1c-1512-4823-9cbe-cb54f05ee996