A data set consisting of seventeen functional traits collected on 43 saplings from a Control and 33 saplings from a long-term drought experiment site in a tropical rainforest in NE Amazonia, Brazil. The experiment was designed to exclude 50% of the incoming rainfall to the soil and was conducted over a 1ha area, alongside the experiment there is a control (non- drought plot) of a corresponding size. The samples were collected in 2017, fifteen years after the start of the experiment on trees with a diameter at breast height (1.3m) of 1-10cm. The purpose of the dataset was to assess if traits relating to plant metabolism (photosynthesis and respiration) and plant hydraulic processes had been significantly altered in trees growing under drought conditions. Full details about this dataset can be found at https://doi.org/10.5285/ca147ac9-ac68-4348-b5f0-dcd483ef3a85

This dataset contains time series observations of surface-atmosphere exchanges of sensible heat (H) and latent heat (LE) and momentum (τ) measured at UKCEH eddy covariance flux observation sites during summer 2019. The dataset includes ancillary weather and soil physics observations made at each site. Eddy covariance (EC) and micrometeorological observations were collected using open-path eddy covariance systems. Flux, meteorological and soil physics observations were collected and processed using harmonised protocols across all sites. 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/10.5285/0254620f-9cf1-4d5b-af3f-bd8a6af95e96

This dataset comprises seven ensembles of hydrological model estimates of monthly mean and annual maximum river flows (m3s-1) on a 0.1° × 0.1° grid (approximate grid of 10 km × 10 km) across West Africa for historical (1950 to 2005) and projected future (2006 to 2099) periods. This dataset is the output from the Hydrological Modelling Framework for West Africa, or “HMF-WA” model. The ensembles correspond to historical and three projected future climate scenarios (RCP2.6, RCP4.5 and RCP8.5) with two future scenarios of water use. The scenarios of water use are (i) future water use that varies in line with projected population increases, and (ii) future water use is the same as present day. This dataset is an output from the regional scale hydrological modelling study from African Monsoon Multidisciplinary Analysis-2050 (AMMA-2050) project. Full details about this dataset can be found at https://doi.org/10.5285/6429828f-6a06-4d2d-8f50-4910b18f7ff4

Motion activated camera traps were installed in pine woodland and regenerating heathland from 2010 as part of UK Environmental Change Network long-term monitoring in the Allt a'Mharcaidh catchment, Cairngorms National Park, Scotland. The image catalogue contains 8050 wildlife images identified to species or group where possible. This forms part of the accompanying dataset which includes information on over 66,000 classified images, recording the presence of blank (empty) images, wildlife, people, dogs and mountain bikes. Furthermore it includes group identification where a series of images occur within five minutes of each other. 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/b0c13df5-f606-4bf2-9397-a9c51a7e8d93

This data set includes counts of soil meso-fauna collected from topsoil within a wide range of land use types across Wales, collected as part of the Glastir Monitoring and Evaluation Programme (GMEP). Meso-fauna include collembola (springtails) and acari (mites). The monitoring programme was set up by the Welsh Government in 2013 to monitor the effects of the Glastir agri-environment scheme on the environment and ran from 2013 to 2016. The field survey element was based on a stratified random sampling design of 300 x 1km square sites across Wales, and was managed by the Centre for Ecology & Hydrology. Full details about this dataset can be found at https://doi.org/10.5285/1c5cf317-2f03-4fef-b060-9eccbb4d9c21

This data set consists of records of point landscape features and associated attributes from sites across Wales, collected between 2013 and 2016. Data are presented as records of features such as trees, ponds and buildings with associated species and condition measures where applicable. Features were surveyed within a set of up to 300 x 1km squares across Wales (not all sites contained point features), collected as part of the Glastir Monitoring and Evaluation Programme (GMEP). The monitoring programme was set up by the Welsh Government in 2013 to monitor the effects of the Glastir agri-environment scheme on the environment and ran from 2013 to 2016. The field survey element was based on a stratified random sampling design of 300 x 1km square sites across Wales, and was managed by the Centre for Ecology & Hydrology. Full details about this dataset can be found at https://doi.org/10.5285/9f8d9cc6-b552-4c8b-af09-e92743cdd3de

This dataset comprises seven ensembles of hydrological model estimates of monthly mean and annual maximum river flows (m3s-1) on a 0.1° × 0.1° grid (approximate grid of 10 km × 10 km) across West Africa for historical (1950 to 2014) and projected future (2015 to 2100) periods. This dataset is the output from the Hydrological Modelling Framework for West Africa, or “HMF-WA” model. The ensembles correspond to CMIP6 (Coupled Model Inter-comparison Project Phase 6) historical and three projected future climate scenarios (SSP126, SSP245 and SSP585) with two future scenarios of water use. The scenarios of water use are (i) future water use that varies in line with projected population increases, and (ii) future water use is the same as present day. This dataset is an output from the regional scale hydrological modelling study from African Monsoon Multidisciplinary Analysis-2050 (AMMA-2050) project. Full details about this dataset can be found at https://doi.org/10.5285/346124fd-a0c6-490f-b5af-eaccbb26ab6b

Data comprise concentrations of Perfluorinated compounds in the eggs of the marine sentinel species the Northern gannet (Morus bassanus), from colonies in Ailsa Craig in the Irish Sea (eastern Atlantic), and Bass Rock in the North Sea, United Kingdom. The study reports concentrations of eight perfluorinated carboxylic acids (PFCAs) and three perfluorinated sulfonates (PFSs), for 1977-2014. The data is part of the Predatory Bird Monitoring Scheme (PBMS). Full details about this dataset can be found at https://doi.org/10.5285/43487d30-ba23-424e-a2bb-d04dd121875c

Morphological and life history data collected from three bat species, Barbastella barbastellus, Plecotus auritus and Myotis escalerai, captured in England, Spain and Portugal to study adaptive responses to climate change. The data includes species identity, location of capture at 10 km resolution, date of capture, sex, age category, reproductive condition, forearm length (in millimetres) and body mass (in grams). Full details about this dataset can be found at https://doi.org/10.5285/dd90c2fa-e6c6-4fc7-a578-b7e4a622dddf

This data set consists of measurements of lengths of linear landscape features and associated attributes from sites across Wales, collected between 2013 and 2016. Data are presented as lengths of features such as hedges ('woody linear features'), fences, walls, banks and streams, with associated species and condition measures where applicable. Features were surveyed within a set of up to 300 x 1km squares across Wales (not all sites contained linear features), collected as part of the Glastir Monitoring and Evaluation Programme (GMEP). The monitoring programme was set up by the Welsh Government in 2013 to monitor the effects of the Glastir agri-environment scheme on the environment and ran from 2013 to 2016. The field survey element was based on a stratified random sampling design of 300 x 1km square sites across Wales, and was managed by the Centre for Ecology & Hydrology. Full details about this dataset can be found at https://doi.org/10.5285/f481c6bf-5774-4df8-8776-c4d7bf059d40