This dataset contains urine frequency and volume data measured from tri-axial accelerometers on Welsh mountain ewes free-grazing two contrasting upland field sites (semi-improved and unimproved pasture) in North Wales, across two seasons each (spring and autumn). The data, were collected using tri-axial accelerometers glued to the hind of Welsh Mountain ewes to study the urination behaviour of free-grazing sheep. Using a Boolean algorithm, the characteristic squatting position that ewes exhibit upon urination was detected in the accelerometer data. Initially the performance of the accelerometers with sheep in urine collection pens was assessed. Data were collected on the volume of each urination event and recorded the time of each observed urination event. This initial data was used to assess whether the accelerometers and Boolean algorithm were successful in identifying urination events, but also to ascertain whether the time spent in the squatting position would correlate with the volume of urine produced (thus allowing the technique to be able to estimate urine volume from squatting time only in subsequent field deployments). Information on when, where and how often livestock urinate are key data to be able to assess the scale and nature of nitrogen pollution arising from grazed agroecosystems. Urine patches deposited by grazing livestock are large sources of emissions of the greenhouse gas, nitrous oxide, due to high concentrations of nitrogen deposited over relatively small areas. These data were collected in the NERC funded Uplands-N2O project (grant award: NE/M015351/1). Full details about this dataset can be found at https://doi.org/10.5285/127afd24-d2cd-457f-b837-2dd5d328f101

This data set contains Global maps of five ecosystem services using 6 different among-model ensemble approaches: the provisioning services of water supply, biomass for fuelwood and forage production, the regulating service Carbon Storage for CO2 retention and the cultural non-material service Recreation. For water, the data comes as one shapefile with polygons per watershed, each polygon containing seven ensemble estimates. The other services – recreation, carbon storage, biomass for fuelwood and forage production – come as seven tiff- maps at a 1-km2 resolution with associated world files for each tiff-map contains 43,200 x 18,600 pixels for one ensemble approach, with LZW compressed file sizes between 400MB and 950MB. For all maps, 600dpi jpg depictions are added to the supporting information with uniform colour scaling set for the median ensemble per service. Ensemble output maps were calculated with different approaches following the supporting documentation and associated publication. Uncertainty estimates for these services are included as variation among contributing model outputs and among the employed ensemble approaches. The work was completed under the ‘EnsemblES - Using ensemble techniques to capture the accuracy and sensitivity of ecosystem service models’ project (NE/T00391X/1) funded by the UKRI Landscape Decisions programme, with additional funding from ES/R009279/1 (MobilES) & ES/T007877/1 (RUST). Full details about this dataset can be found at https://doi.org/10.5285/bd940dad-9bf4-40d9-891b-161f3dfe8e86

The dataset provides qualitative data from anonymised in-depth interviews conducted in 2017 with domestic poultry owners, commercial poultry farm workers and market sellers of live poultry in Bangladesh. The dataset comprises interview transcripts in Bangla. Household and farm interviews were carried out in rural areas of Mirzapur sub-district, Tangail. Interviews with market sellers of poultry were carried out in Dhaka city. An interview guide was used to explore themes and topics relating to poultry-raising practices, hygiene and waste disposal practices relating to poultry and use of antibiotics in poultry. The objective was to understand human behaviours and practices that may contribute to environmental contamination with antibiotic-resistant bacteria from poultry and potential pathways of transmission of antibiotic-resistant bacteria from poultry to humans. The research was part of a wider research project, Spatial and Temporal Dynamics of Antimicrobial Resistance (AMR) Transmission from the Outdoor Environment to Humans in Urban and Rural Bangladesh. The research was funded by NERC/BBSRC/MRC on behalf of the Antimicrobial Resistance Cross-Council Initiative, award NE/N019555/1. Full details about this dataset can be found at https://doi.org/10.5285/630759ac-b0ca-4561-8eec-414b47e14829

The data resource contains daily time-series of simulated streamflow, ground water levels and estimated demands, from humans, livestock and irrigation across the Narmada Basin, India. The data were generated using the Global Water Availability Assessment (GWAVA) Model 5. For the Upper Narmada, a baseline of 1970-2013 is presented along with a future time slice of 2028- 2060. For the whole Narmada, a baseline of 1981-2013 and future period of 2021-2099 is included. The data were produced to help predict how climate and land use change in the region would impact on future water security. The research was funded by NERC research grant NE/R000131/1 Full details about this dataset can be found at https://doi.org/10.5285/9fc7ab01-c622-46f1-a904-0bcd54073da3