This dataset consists of metal concentrations measured from soils sampled across Great Britain in 1998. The 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 Centre for Ecology & Hydrology, 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 soil data, habitat areas, vegetation species data, linear habitat data, and freshwater habitat data are also gathered by Countryside Survey. Full details about this dataset can be found at https://doi.org/10.5285/def15f47-6aba-43db-a833-5844628a658b

Summary output data (including soil organic carbon concentration, nitrogen, available water and carbon dioxide) from simulations of soil in a small agricultural catchment (Sunjia) in Southeast China (Jianxi province). The simulations were performed using the ECOSSE model; a pool-based carbon and nitrogen turnover model. The simulations were performed using soil and climate input data from the research farm. Input data for the simulations were provided by the soil science department of the Chinese Academy of Sciences. Simulations were conducted in 2017. Full details about this dataset can be found at https://doi.org/10.5285/2ce71612-df48-40f2-9402-03d93104c623

Data comprise soil organic carbon content from a simulation using the ECOSSE model; a pool-based carbon and nitrogen turnover model. Simulations were performed using input data from the Sunjia research farm in southeast China (Jianxi province). Data here is from simulations using the global version of the ECOSSE model, a package which applies the regular model spatially. Input data for the simulations were provided by the soil science department of the Chinese Academy of Sciences. Simulations were conducted in 2018. Full details about this dataset can be found at https://doi.org/10.5285/876fa724-c3d3-4091-8de2-8140b7c973eb

Sediment and soil samples were collected during a six-month project in 2018 looking at the sources of sediment within the River Derwent Catchment, Yorkshire, UK. The data shows the mineralogical composition of each sample site, processed using X-ray powder diffraction (XRD). The data has been used to understand where instream sediment in the River Derwent is coming from. This information can be used to inform catchment management. Full details about this dataset can be found at https://doi.org/10.5285/27a84ac6-c3fd-4c86-9540-f60b4dbfa14f

This dataset contains soil respiration data from the Climoor fieldsite in Clocaenog forest, north-east Wales. Measurements began in March 1999 at the field site, and were repeated in approximately bi-weekly intervals until June 2015 (although there are some larger gaps for technical or logistical reasons in this 14 year dataset). The data were collected using 3 different methods/machines over the years: static chambers, soil respiration chamber and Environmental Gas Monitor (EGM)-4 (from PP Systems), and soil respiration chamber and Automated Soil Gas Flux System Li8100 (from Licor Biosciences). The method used is detailed in the data and described further in the supporting documentation. Data was collected by CEH staff and PhD students trained in the use of the different methods / machines. Climoor is a climate change manipulation experiment that utilises automated roof technology to produce drought and warming experimental treatments that reflect climate change predictions for the next 20-30 years. Full details about this dataset can be found at https://doi.org/10.5285/c0822023-0ec2-425f-8bf9-a546ce281ee0

This dataset consists of mid-infrared (MIR) spectra measured on 427 archived soil samples from arable and grassland habitats across Great Britain in 2007. Data on diffuse reflectance spectra were obtained from subsamples of finely ground soil, recorded as absorbance values for wavenumber range 4000-400 cm-1. The soil samples were collected as part of the Countryside Survey monitoring programme, a unique study or 'audit' of the natural resources of the UK's countryside. The analyses were conducted as part of study aiming to quantify how soil quality indicators change across a gradient of agricultural land management and to identify conditions that determine the ability of different soils to resist and recover from perturbations. Full details about this dataset can be found at https://doi.org/10.5285/d66ca0a6-403d-4f5a-bef1-8ee177f1e1b3

This data set details the range of treatments applied to experimental plots at a field site at Sourhope, Scotland, between 1999 and 2004. The data can be used in conjunction with other experimental data sets from the NERC Soil Biodiversity Thematic Programme site as an explanatory variable. The NERC Soil Biodiversity Thematic Programme was established in 1999 and was centred upon the intensive study of a large field experiment located at the Macaulay Land Use Research Institute (now the James Hutton Institute) farm at Sourhope in the Scottish Borders (Grid reference: NT8545019630). During the experiment, the site was monitored to assess changes in above-ground biomass production (productivity), species composition and relative abundance (diversity). Full details about this dataset can be found at https://doi.org/10.5285/a83ca49d-a78d-4c64-a646-68e44438a2b6

QUEST projects both used and produced an immense variety of global data sets that needed to be shared efficiently between the project teams. These global synthesis data sets are also a key part of QUEST's legacy, providing a powerful way of communicating the results of QUEST among and beyond the UK Earth System research community. This dataset contains soil data generated from ISLSCP II. The International Satellite Land Surface Climatology Project, Initiative II (ISLSCP II) is a follow on project from The International Satellite Land Surface Climatology Project (ISLSCP). ISLSCP II had the lead role in addressing land-atmosphere interactions - process modelling, data retrieval algorithms, field experiment design and execution, and the development of global data sets.

Data are presented on earthworm abundance with distance from hedgerows was recorded for arable fields and pasture leys at Spens farm, the University of Leeds experiment farms, Yorkshire. Sampling was carried out annual from April 2015 to April 2017 with additional sampling in December 2015, and July and October 2016. Pits were excavated and soil hand sorted for earthworms. Mustard solution was then poured into the pit and any emerging earthworms collected. All earthworms were preserved in ethanol for identification using the Sims and Gerard Field studies key. At each pit the following measurements were also taken: soil moisture, soil temperature, soil bulk density. The samples were taken to determine the influence of leys on soil quality by Miranda Prendergast-Miller and colleagues as part of the SoilBioHedge project (Grant Reference NE/M017095/1) funded by the NERC Soil Security Programme. (Grant Reference NE/M017044/1). Full details about this dataset can be found at https://doi.org/10.5285/d3dcfd8a-918d-48a4-9511-ec832de34636

The data consists of total arbuscular mycorrhizal fungi colonisation in fine roots in old growth forests in Central Amazon. Fine roots younger than three months were sampled using the ingrowth core technique in a large-scale nutrient fertilisation experiment. Total mycorrhizal colonisation is given as a mean of the plant community per plot, where five points inside each plot were sampled in the 0-10 cm soil layer. The spreadsheet depicts the percentage of fine root length colonised by different arbuscular mycorrhizal structures (hyphae, arbuscules and vesicles). Samples were collected in February 2018, eight months after the nutrient fertilisation started at the AFEX project area in Manaus, Brazil at the Biological Dynamics of Forest Fragments Project (BDFFP/ INPA). The study was funded by NERC, BDFFP (logistical support) and Brazilian government (student scholarship). Full details about this dataset can be found at https://doi.org/10.5285/52f756a1-a0f6-4991-b21b-4042018a451f