This data contains values of bare sand area, modelled wind speed, aspect and slope at a 2.5 m spatial resolution for four UK coastal dune fields, Abberfraw (Wales), Ainsdale (England), Morfa Dyffryn (Wales), Penhale (England). Data is stored as a .csv file. Data is available for 620,756.25 m2 of dune at Abberfraw, 550,962.5 m2 of dune at Ainsdale, 1,797,756.25 m2 of dune at Morfa Dyffryn and 2,275,056.25 m2 of dune at Penhale. All values were calculated from aerial imagery and digital terrain models collected between 2014 and 2016. For each location, areas of bare sand were mapped in QGIS using the semi-automatic classification plugin (SCP) and the minimum distance algorithm on true-colour RGB images. The slope and aspect of the dune surface at each site was calculated in QGIS from digital terrain models. Wind speed at 0.4 m above the surface of the digital terrain model at each site was calculated using a steady state computational fluid dynamics (CFD). Data was collected to statistically test the relationship between bare sand and three abiotic physical factors on coastal dunes (wind speed, dune slope and dune slope aspect). Vertical aerial imagery was sourced from EDINA Aerial Digimap Service and digital terrain models from EDINA LIDAR Digimap Service. Wind speed data was generated and interpreted by Dr Thomas Smyth (University of Huddersfield). Full details about this dataset can be found at https://doi.org/10.5285/972599af-0cc3-4e0e-a4dc-2fab7a6dfc85

[This dataset is embargoed until November 10, 2025]. The following dataset contains information on saplings of woody plant species in invaded subtropical mountain forests (Yungas) over three years. The forests were located in the Horco Molle Experimental Reserve and Parque Sierra de San Javier, Tucumán, Argentina. The data was collected as part of an experiment to investigate the impact of management control on the invasion of non-native species such as Ligustrum lucidum, and other less abundant non-native species, on the dynamics of the woody community. The experiment was conducted between June 2020 and November 2023. This work was carried out as part of NERC grant NE/S011641/1 “Optimising the long-term management of invasive species affecting biodiversity and the rural economy using adaptive management”. Full details about this dataset can be found at https://doi.org/10.5285/4311fa93-fdcc-43bd-bb2e-185118c06ed7

[This dataset is embargoed until November 30, 2024]. This is a transdisciplinary dataset from ten smallholder farming villages in Patarasi Rural Municipality, Jumla District, Nepal collected during 2021 and 2022. The human component of the dataset includes fortnightly 24-hour dietary recall surveys and monthly anthropometry surveys of 721 participants (adult males, adult females, adolescent girls and children under five) from 200 smallholder households collected over a twelve-month period. For each household, there is also data on socioeconomic status, farming practices, cooking practices and beekeeping practices. The ecological component of the dataset includes plant-pollinator interaction data and flowering phenology data from the same ten farming villages as well as the results of a pollinator exclusion field experiment in fifteen replicate sites along an altitudinal gradient in this region. Taken together, these datasets enable us to understand more about: a) people’s diets, nutritional status and socioeconomic status in rural Nepal; b) which crops provide their nutrients and how these crops are grown; c) which insects pollinate these crops, and; d) how climate change is likely to impact the system. Full details about this dataset can be found at https://doi.org/10.5285/d7434d83-c30d-4186-aab0-9764821cd807

[This dataset is embargoed until November 1, 2024]. These data encompass land cover data and sediment geochemistry from the Rio Santa catchment of the Peruvian Andes. Sediment samples were collected within the SIGMA: Peru project between 2019-2020. Geochemistry data include major and minor elements in sediment samples determined by X-Ray Fluorescence (XRF), organic matter determined by loss-on-ignition (LOI), and particle size data, and are provided for both the wider Rio Santa catchment and the Ranrahirca sub-catchment. The research was supported by the Natural Environment Research Council and the Newton Fund (grant NE/S013245/1). Full details about this dataset can be found at https://doi.org/10.5285/20837a27-414c-4597-a6d2-3edc1d2e9a98

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

These data include greenhouse gas concentrations and physio-chemical water properties for the Clyde estuary in Scotland to support understanding of the GHG sources and sinks and their associated mechanisms in a highly stratified, temperate urban estuary. These measurements look at the changes in GHG along the Clyde estuary taking measurements from land to sea down the estuary on the ebb tide at both the surface and bed so the impact of location, river flow, wastewater treatment outflows and stratifications can be understood. Full details about this dataset can be found at https://doi.org/10.5285/a22b495e-b2cd-43cd-95b7-8712b64dc0da

This is a dataset of spot gauged river flows (m3 s-1) at multiple sites along the River Frome, Dorset, UK, conducted during the year 2022. All sites are contained within the stretch of river between the Environment Agency gauging stations located at Dorchester and East Stoke, i.e. the lower part of the River Frome. The monitoring sites included the major tributaries along this river reach, which are: the South Winterbourne, Tadnoll Brook, and the River Win. In total, 19 river channels were spot gauged at 11 river cross-sectional locations. Due to the braided nature of the river, some locations required multiple channels to be measured to produce a total cross-sectional flow for that part of the river. The river cross-sectional locations were evenly spaced, approximately every 3 km along the river reach. Measurements were taken on multiple flow accretion survey days between 12/04/2022 and 05/11/2022. On each day, as many of the sites were spot gauged as possible, working upstream to downstream. Full details about this dataset can be found at https://doi.org/10.5285/0d5c7e45-2c43-4276-af0d-8d941db2e124

These datasets contain aphid/parasitoid abundances and glucosinolate concentrations associated with Brassica napus plants within eight field-based diesel exhaust and ozone fumigation rings located at the University of Reading’s Sonning farm. Full details about this dataset can be found at https://doi.org/10.5285/b28c13f2-7355-4c4b-8c34-10470e1772d1

These databases contain collated trait data for 925 species of macro- and micro-moths recorded on the Landscape-scale Species monitoring of Agri-Environment Schemes (LandSpAES) project, on farmland in six regions of England (The Fens, High Weald, South Suffolk / North Essex, Warwickshire, Yorkshire Dales, Dartmoor) during 2017-2021. The traits collated include life cycle ecology and phenology, conservation status and relative abundance, host plant specificity and characteristics, adult feeding, pupal habitat, breeding habitat, and morphological characteristics. Broader categories, such as breeding habitat, are also split into sub-categories. Full details about this dataset can be found at https://doi.org/10.5285/8f9bb7c8-42b6-46f3-9718-84755810be7a

This dataset is a model output from the European Monitoring and Evaluation Programme (EMEP) model applied to the UK (EMEP4UK) driven by Weather and Research Forecast model meteorology (WRF). It provides annual total atmospheric deposition of cadmium, copper, nickel, lead, zinc, sulphur, and nitrogen over the UK on a 3x3 km2 grid for the years 2040, 2070 and 2100 under the Shared Socioeconomic Pathways (SSPs) 1-5. SSPs are future scenarios based on narratives of possible socio-economic pathways. The EMEP4UK model version used here is rv4.36, and the WRF model version is the 4.2.2. 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/eec9634d-ba2b-4553-a65d-ef6ce4c40ebc