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

Elemental analysis of 80 soil samples taken in the Ningbo Watershed, in the Zhangxi catchment, Eastern China. Variables measured include As, Cd, Cr, Cu, Ni, P, Pb, and lead isotope ratios along with concentrations of Zn, Ca and K. Data was collected in March 2016 and analysed at Queens Belfast University. The data was collected and analysed as part of a NERC NSFC funded multi project research programme UK- China Critical Zone Observation Programme. Full details about this dataset can be found at https://doi.org/10.5285/9c2e8b85-48ab-48c9-b69d-dd676a5d086f

This dataset provides linear trends, over varying time periods, for the UK Butterfly Monitoring Scheme (UKBMS) collated Indices of individual butterfly species across the UK. The main statistical values derived from a linear regression (slope, standard error, P-value) are presented for the entire time series for each species (1976 to 2018), for the last 20 years, and for the last decade. In addition a trend class, based on slope direction and its significance, and a percentage change for that time period are provided to describe the statistical trends. These trend data are provided for 59 UK butterfly species. Trends across different time series allow us to determine the long and short-term trends for individual species. This enables us to focus conservation and research and also to assess species responses to conservation already in place. The UK Butterfly Monitoring Scheme is organized and funded by Butterfly Conservation (BC), the Centre for Ecology & Hydrology (CEH), the British Trust for Ornithology (BTO), and the Joint Nature Conservation Committee (JNCC). The UKBMS is indebted to all volunteers who contribute data to the scheme. 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/ee4b440e-2604-40b9-bca7-19d6392bd9ea

Data were collected in 2015, 2016 and 2017 to provide information on the distribution of flow depth and depth-averaged flow velocity at cross-sections on the South Saskatchewan River, Canada. Data were obtained using a Sontek M9 acoustic Doppler current profiler (aDcp) mounted onto either a small zodiac boat or a SonTek Hydroboard. Data for each cross-section is recorded in a single file. Individual points within each file represent single locations on the particular cross-section. Data were collected as part of NERC project NE/L00738X/1. Full details about this dataset can be found at https://doi.org/10.5285/e4fe2ebe-b207-47d5-8c77-9873afc63da9

These data are input files for CAESAR-Lisflood (CL), a numerical hydrodynamic-landscape evolution model. These files were created to support coupled hydrodynamic-landscape evolution modelling to evaluate the geomorphological response of river channels affected by the 7th February 2021 ice-rock avalanche and debris flow in Chamoli District, Uttarakhand, India. They include 10 m digital elevation models (DEMs) of bed rock and land surface topography in a gridded (raster) format. They also include reanalysis-derived river discharge data generated by the GEOGloWS project at the following locations: Rontigad, Rishiganga, Dhauliganga, and Alaknanda. The configuration settings and parameters for CL modelling are also included. Full details about this dataset can be found at https://doi.org/10.5285/4cdd86b3-bf58-457d-b8cf-b57aed2d56d0

This dataset provides linear trends, over varying time periods, for the Collated Indices of individual butterfly species across the UK. The main statistical values derived from a linear regression (slope, standard error, P-value) are presented for the entire time series for each species (1976# to the present year), for the last 20 years, and for the last decade. In addition, trends are classified based on the direction and significance of a linear slope together with an estimated percentage change for that time period. These trend data are provided for all UK butterfly species for which we have sufficient data (58 species). Trends are calculated by performing a linear regression on the annual Collated indices for each species. Collated indices are calculated using a log-linear model incorporating individual site indices from all monitored sites across the UK for a given species in a given year. This dataset provides linear trends, over varying time periods, for the Collated Indices of individual butterfly species across the UK. The main statistical values derived from a linear regression (slope, standard error, P-value) are presented for the entire time series for each species (1976# to the present year), for the last 20 years, and for the last decade. In addition, trends are classified based on the direction and significance of a linear slope together with an estimated percentage change for that time period. These trend data are provided for all UK butterfly species for which we have sufficient data (58 species). Trends are calculated by performing a linear regression on the annual Collated indices for each species. Collated indices are calculated using a log-linear model incorporating individual site indices from all monitored sites across the UK for a given species in a given year. Trends across different time series allow us to determine the long and short-term status of individual species. This is enables us to focus conservation and research and also to assess species responses to conservation already in place. The UK Butterfly Monitoring Scheme is organized and funded by Butterfly Conservation (BC), the UK Centre for Ecology & Hydrology (UKCEH), the British Trust for Ornithology (BTO), and the Joint Nature Conservation Committee (JNCC). The UKBMS is indebted to all volunteers who contribute data to the scheme. 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. #Because the Collated indices are only calculated for each species in years in which it was recorded on five or more sites, the starting year for the series is later than 1976 for a number of rarer species. Full details about this dataset can be found at https://doi.org/10.5285/236ee6bd-2330-4f84-a871-5a8ebe1925b5

[THIS DATASET HAS BEEN WITHDRAWN]. This dataset provides Concentration Based Estimated Deposition (CBED) values of sulphur and nitrogen atmospheric deposition for 1x1 kilometres (km) grid squares of the UK averaged over the years 2018 to 2020. The data consist of deposition values for sulphur, oxidised nitrogen and reduced nitrogen, and base cations. Total deposition is the sum of four components calculated separately: wet deposition, dry deposition of gases, dry deposition of particulate matter and cloud droplet deposition. Habitat-specific data are provided for (i) moorland/short vegetation everywhere, and (ii) forest everywhere. Additionally, the grid square average over multiple land cover types (i.e. arable, grassland, forest, moorland, urban) is also calculated. The habitat-specific data are recommended for use with critical loads for the calculation of critical load exceedances. The work in generating and compiling the dataset has been funded by the UK Centre for Ecology & Hydrology (UKCEH) and various Departments for Environment, Food & Rural Affairs (Defra) contracts. Full details about this dataset can be found at https://doi.org/10.5285/4a5a9140-96f1-4aee-b547-ef570238fdbd

This dataset contains information about moth caterpillar abundance at sites lit by streetlights (LED; high pressure sodium and low-pressure sodium) and unlit control sites. Caterpillars were sampled at 26 matched pairs of lit and unlit sites between 2018 and 2020 as part of a study of the effects of street lighting on the early life stages of moths. Full details about this dataset can be found at https://doi.org/10.5285/4d3f4c8a-5605-4990-8ca1-42f8ddf63698

This dataset contains the areas affected by landslides triggered by Typhoon Parma in the area of Itogon (Benguet, Philippines) between the 2nd and 5th October 2009. The polygons were mapped using Google Earth imagery dated 31 December 2003 for pre-event and images and 31 December 2009 for post-event images. The area has an extension of 150 km2. Full details about this dataset can be found at https://doi.org/10.5285/2e15dbd2-71c3-4e86-aa90-6029d37bd417

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 LCM2023 products are available from the LCM2023 product documentation. Full details about this dataset can be found at https://doi.org/10.5285/50b344eb-8343-423b-8b2f-0e9800e34bbd