Data comprise sunflower seed predation rates (i.e. number of seeds remaining) after 24 hours under different treatments in 18 experimental plots plots established in 2013 as part of the Biodiversity and Ecosystem Function in Tropical Agriculture (BEFTA) programme. Eighteen plots were examined across three estates – plots in Ujung Tanjung and Kandista estates were planted in 1987 to 1992 and are mature or over-mature oil palm, while Libo plots were replanted in 2014. Plots were organised in triplets and in Ujung Tanjung and Kandista, for each triplet one plot was assigned to each of three vegetation treatments: Reduced vegetation cover, normal vegetation management and enhanced vegetation cover. The project 'Managing tropical agricultural ecosystems for resistance and recovery of ecosystem processes' was funded by the Natural Environment Research Council under NE/P00458X/1. Full details about this dataset can be found at https://doi.org/10.5285/1256d475-f321-4a9b-b4ed-927e5b825d3f

This data resource consists of two files: (a) 1x1 km resolution Average Accumulated Exceedance (AAE) data summarising the exceedances of acidity critical loads for eight habitats; (b) 1x1 km resolution AAE data summarising the exceedances of nutrient nitrogen critical loads for thirteen habitats. The data provide information on the amount of excess acid or nitrogen deposition above the critical load values set to protect acid- and nitrogen-sensitive habitats in the UK. The AAE has been calculated using UK 5x5 km Concentration Based Estimated Deposition (CBED) data for 2017-19 (https://doi.org/10.5285/1efa692d-76ca-406e-8736-837a457e16ee). The data were generated under Defra-funded work to assess the potential areas of acid and nitrogen sensitive habitats at risk of adverse impacts from excess atmospheric acid and nitrogen deposition. Reducing the area and amount of critical load exceedance continues to be a driver of Government policy on reducing emissions of acidic and nitrogen-containing air pollutants (sulphur dioxide, nitrogen oxides and ammonia). Full details about this dataset can be found at https://doi.org/10.5285/049b5fd2-3f12-48fc-8b43-57fa4db649ae

This dataset is a census of the heathland and associated vegetation from Dorset, UK. The Dorset heathlands are situated in South West England, and are generally associated with free-draining and acidic soils overlying Tertiary sands and gravels. The heathlands comprise a mosaic of different vegetation types, characterised by dwarf shrub communities dominated by members of the Ericaceae (e.g. Calluna vulgaris, Erica spp.), together with areas of mire, grassland, scrub and woodland. Unless they are managed heathlands undergo succession to scrub and woodland. Therefore the majority of heathland sites are currently under some form of conservation management, which is implemented to reduce succession to scrub and woodland. Management interventions include cutting and burning of vegetation, and grazing by livestock. Individual heathland patches are also managed for ecosystem services, such as recreation and timber production, as well as biodiversity conservation. Full details about this dataset can be found at https://doi.org/10.5285/4c347ec4-0beb-4355-9780-89dad718b2f3

The data provide critical loads of acidity, and of nutrient nitrogen for the distributions of UK habitats sensitive to acidification and/or eutrophication. Critical loads have been calculated and applied to UK natural and semi-natural habitats sensitive to acidification and/or eutrophication (excess nitrogen as a nutrient). Critical loads data are available for these habitat types at 1x1 km resolution for the UK. In addition, acidity critical loads are available for 1752 selected freshwater sites throughout the UK. Critical loads are defined as the maximum pollutant load (of acid or nitrogen deposition) that a sensitive element of the environment (e.g., soils, vegetation) can tolerate without adverse harmful effects occurring, according to present knowledge. Habitat distributions are defined from a combination of CEH Land Cover Map 2000 and a number of ancillary data sets (e.g., species distributions, altitude, soils), used to further refine their distributions. It should be noted that the habitat distributions maps and areas provided here and used for UK critical loads research for Defra (a) only include areas where data exist for the calculation or derivation of critical loads; (b) may differ from other national habitat distribution maps or estimates of habitat areas. This may also result in a difference in the total habitat areas mapped for acidity and for nutrient nitrogen critical loads. The data have been generated under numerous Defra-funded contracts that brought together UK experts on the impacts of air pollution on UK habitats. The acidity critical loads data were last revised in 2004 and the nutrient nitrogen critical loads data were updated in 2011. The data are based on methods agreed at national and international meetings and workshops held under the UNECE Convention on Long-Range Transboundary Air Pollution (CLRTAP). Full details about this dataset can be found at https://doi.org/10.5285/299e2779-0787-46bb-9482-03ad474eae27

These spatial layers contain risk factors and overall risk scores, representing relative risk of Phytophthora infection (Phytophthora ramorum and P. kernoviae), for Core Native Woodland and known larch fragments across Scotland. Risk factors include climate suitability, proximity to road and river networks and suitability of habitat for key hosts of Phytophthora and were broadly concurrent with the period between 2007 and 2013. This research was funded by the Scottish Government under research contract CR/2008/55, 'Study of the epidemiology of Phytophthora ramorum and Phytophthora kernoviae in managed gardens and heathlands in Scotland' and involved collaborators from St Andrews University, Science and Advice for Scottish Agriculture (SASA), Scottish Natural Heritage (SNH), Forestry Commission, the Food and Environment Research Agency (FERA) and the Centre for Ecology & Hydrology (CEH). Full details about this dataset can be found at https://doi.org/10.5285/29726cda-09f5-4661-8fd4-ddaa5555466a

Primary forest cover and forest cover loss in Wallacea for the years 2000-2018 to train a deforestation model and produce maps of projected probability of deforestation until 2053. Full details about this dataset can be found at https://doi.org/10.5285/c7148c20-c6b3-43e1-9f99-b6e38e4dfdaf

This dataset consists of landscape point feature information for points across Great Britain, surveyed in 1998. Data are presented as rows of information recorded as point features (for example individual trees, water bodies or structures), with associated plant species where relevant, within a set of 569 1km squares across Great Britain, surveyed during the Countryside Survey long term monitoring project (note: not all surveyed squares contained point features). 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 point features, habitat areas, vegetation species data, soil 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/ed10944f-40c8-4913-b3f5-13c8e844e153

Data comprise pH and bulk density measurements (location (longitude, latitude), depth, bulk density) for multiple soil profiles in the SikSik catchment, North West Territories, Canada. Samples were collected along a transect in September 2014. Soil samples were taken near additional soil pits. Soil depth and sampling location (latitude and longitude) was recorded. Bulk density was determined according to Blake and Hartge (1986). pH was determined with the 1:5 soil:water suspension method (see supporting documentation). The data were collected under Project HYDRA, a NERC funded UK research project linking Heriot Watt University, the Universities of Durham, Aberdeen and Stirling, and the Centre for Ecology & Hydrology (CEH), Edinburgh. Project HYDRA is part of the UK Arctic Research Programme. Project HYDRA studies sites in Arctic Canada to investigate the biological, chemical and physical controls on the release of greenhouse gases from permafrost into melt water and to the atmosphere and how these emissions will influence global warming. Full details about this dataset can be found at https://doi.org/10.5285/a37e6aa4-b003-49bd-9a16-619a7d0dd714

The database includes the classification of 966 active nitrogen-relevant policies from South Asia (including Afghanistan, Pakistan, India, Nepal, Bhutan, Bangladesh, the Maldives and Sri Lanka). The collection during 2020 and 2021 focuses on national level policies; some subnational policies were also collected. Data collection involved building on an existing open access global database developed by Kanter et al., 2020 that contained 51 policies for South Asia established to 2017 sourced by the environmental law ECOLEX database. Further policies were collected mostly from online sources: such as international policy databases: FAOLEX and national government and ministry websites. A protocol for policy collection and classification was established and followed to ensure consistent and thorough collections across the eight countries. Policies were classified according to a variety of parameters including the sink (air, water etc.) and sector (agriculture, industry etc.) they address and by type of policy. Policies were clustered if they had a central node policy in place and if a ‘subordinate policy’ (including amendments) did not offer anything new in terms of content related to Nitrogen management. This data was collected as part of a collective partnership that brings together leading organisations from across South Asia and the UK to reduce the adverse global impacts of nitrogen pollution on the environment, health, and wellbeing. More specifically providing a resource for both SANH partners and the wider scientific and policy community to understand the nitrogen policy landscape in the south Asian region. Furthermore, this research contributes to efforts in building a nitrogen policy arena promoting sustainable management of nitrogen, mitigating adverse effects. The dataset provides a thorough overview of available nitrogen related policies in South Asia but does not provide a complete set of all the nitrogen relevant policies available in each country. In some cases, this was due to our dependency on policy availability online, and some websites were not maintained. In addition, we excluded policies established post 2020 to avoid policy responses to COVID19 and to align more closely with the original global study. Repealed policies were omitted from the database. Full details about this dataset can be found at https://doi.org/10.5285/e2f248d5-79a1-4af9-bdd4-f739fb12ce9a

Global spatial data on yields of wheat, sugarcane and maize at 0.25 and 0.5 degrees resolution for 2000-2014. Annual data on wheat, sugarcane and maize yield have been extracted from agricultural statistics, which are recorded annually at regional and national scale depending on the country. The yield data were spatially disaggregated to produce gridded maps (0.25 and 0.5 degrees spatial resolution) of yields per crop type. The earthstat dataset, which provides gridded data on crop distribution (i.e. a crop mask for 2000q), was used to obtain information on the spatial distribution of wheat, sugarcane and maize across the world. The spatial disaggregation process was repeated for every year between 2000 and 2014. The data were produced to constrain agro-ecosystem carbon cycling estimates used in large-scale atmospheric CO2 inversion studies and to be used as inputs in agro-ecosystem biogeochemistry models. The data are provided in netcdf4 (.nc) format. Full details about this dataset can be found at https://doi.org/10.5285/3fa5921b-244a-4944-ab90-e690dbc05a7e