This dataset provides input files for LAMMPS open access molecular dynamics software ( https://www.lammps.org/ ) and contains simulation details, force field parameters, and topology information for polymer crystallisation at a surface that will enable a researcher to replicate the molecular dynamics simulations. Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/25fc1140-07bf-424a-a32c-87dbba9c426a

The data comprises river section, zone and test site delineation, winter Season average NDVI by section and zone 1989-2020, land cover maps seasonally 1989-2020, and derived land cover fractions by section and zone 1989-2020. The data was produced as part of a study to determine how changes in geomorphic form and dynamics due to human alteration to river flows and riparian land management relate to changes in vegetation communities in the Sutlej and Beas Rivers, India. Vegetated and other land cover, including water area, were quantified by winter season NDVI trends (in the plains of Punjab) and seasonal supervised classification of Landsat data for over a 30-year period. The work was supported by the Natural Environment Research Council (Grant NE/S01232X/1). Full details about this dataset can be found at https://doi.org/10.5285/9a96e199-34d0-46f9-9a64-140d300a2531

Two scripts for classifying remotely sensed data used to produce maps of peatland distribution and predicted peat thickness, using random forest classification and regression. Written in JavaScript for use with Google Earth Engine. These are versions of the scripts used in Hastie et al. (2022), https://doi.org/10.1038/s41561-022-00923-4. Users should also cite Rodríguez-Veiga et al. (2020), https://doi.org/10.3390/rs12152380 . Full details about this application can be found at https://doi.org/10.5285/e337de58-df5e-4412-8aef-28875870f965

[THIS DATASET HAS BEEN WITHDRAWN]. This dataset consists of measures of topsoil (0-15cm) physico-chemical properties from soils sampled from 49 x 1km squares across Great Britain in 2020 as part of a rolling soil and vegetation monitoring program of 500 1km squares repeated every 5 years. The properties included are: soil organic matter (loss on ignition (LOI)), derived carbon concentration, total soil organic carbon (SOC), nitrogen, Olsen-phosphorous, pH, electrical conductivity, soil bulk density of fine earth and fine earth volumetric water content. 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 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, vegetation species data are also gathered by the current phase of the 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/cc2aa8f3-95cb-4b85-b883-8ac26e69bdbe

This dataset presents modelled estimates of soil pH at 1km2 resolution across Great Britain. A Generalized Additive Model approach was used with Countryside Survey soil pH data from 2007 and including climate, atmospheric deposition, habitat, soil and spatial predictors. The model is based on soil pH data from 2446 locations across Great Britain and is representative of 0-15 cm soil depth. Soil pH was measured using 10g of field moist soil with 25ml de-ionised water giving a ratio of soil to water of 1:2.5 by weight. The Countryside Survey looks at a range of physical, chemical and biological properties of the topsoil from a representative sample of habitats across the UK. 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/10.5285/4b0e364d-61e6-48fb-8973-5eb18fb454cd

The dataset contains a scaled, semi-quantitative conceptual hydrogeological model of the Gaborone catchment along a general WSW-ENE direction including; (1) the geographic coordinates of the extremities of each segment of the polyline transect; (2) the raster, scaled image of the conceptual hydrogeological cross-section. Full details about this dataset can be found at https://doi.org/10.5285/4731c4da-91fc-4762-9c17-74c8749d4227

The dataset contains concentrations of total soil organic carbon, soil carbon fractions, soil CO2 fluxes, soil temperature and moisture in the Peruvian Andes. Measurements and sampling took place between 2010 and 2013. Data were generated as part of a larger NERC project: 'Are tropical uplands regional hotspots for methane and nitrous oxide' Full details about this dataset can be found at https://doi.org/10.5285/3813aef3-71cc-49e6-ba21-495a43363001

The data contains location and x,y,z accelerometer readings from trackers embedded into 23 boulders in the upper Bhote Koshi catchment, Nepal before the 2019 monsoon season. The data was transmitted in real time via a long-range wide-area network (LoRaWAN®) gateway to a server. The data presented cover the period May 2019 to October 2019. The data from this study was used to demonstrate how cost-effective technology can be used to monitor boulder movement in hazard-prone sites, and to show the potential for active sensors connected through a long-range wide-area network (LoRaWAN®) to be used in an early warning system in the future. Data was collected by the data authors. This was carried out as part the BOULDER: Accounting for BOUlders in Landslide-flood Disaster Evaluation and Resilience project, funded by the Natural Environment Research Council (NERC), Award reference NE/S005951/1 Full details about this dataset can be found at https://doi.org/10.5285/93518ac3-4ded-47fa-b260-38184c09dfc8

The geospatial dataset maps organic carbon (OC) storage (kg OC m-2) and OC stocks (tonnes OC) of surficial soils across 438 Great British saltmarshes. The OC density for the surficial soils (top 10 cm) is mapped across 451.65 km2 of saltmarshes, identified from current saltmarsh maps of Great Britain’s three constituent countries; Scotland, England and Wales The spatial maps are built upon surficial (top 10 cm) soil bulk density and carbon data produced by the NERC C-Side project and Marine Scotland data combined with existing saltmarsh vegetation maps. 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/cb8840f2-c630-4a86-9bba-d0e070d56f04

This dataset contains the results of a laboratory study investigating the dissolution of UO3•nH2O particles in dynamic sediment/groundwater column systems, representative of the shallow subsurface at the Sellafield Ltd. site, UK. Measurements were carried out to determine the extent of uranic particle dissolution and the speciation of dissolved uranium within the columns under contrasting biogeochemical conditions (oxic and electron-donor amended). Columns effluents were analysed periodically for key biogeochemical indicators (nitrate, sulfate) and trace metals (iron, manganese, uranium) and systems were sacrificed after 6 and 12 months of groundwater flow. Upon sacrifice, columns were cross-sectioned, and the sediment structure preserved for synchrotron micro-focus X-ray Fluorescence (XRF) mapping, and uranium L-edge X-ray Absorption Spectroscopy (XAS) measurements. Sub-samples of column sediments were also analysed for acid extractable metals, microbial abundance and classification and bioavailable Fe(II) concentrations. Experiments were performed between March 2016 and March 2017. Subsequent analyses were performed between March 2017 and December 2018. This data was collected as part of the project: Understanding radioactive ‘hot’ particle evolution in the environment funded by the UK Natural Environment Research Council (grant NE/M014088/1). Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/2702e1b0-13df-4ae4-9f91-4ac4bd07bbf1