The data provided here are model iteration objects and rasters needed to run the multi-scale modelling process and predict how the host condition affects probability of Hendra virus shedding. The dataset contains predictions of three proxies for host conditions (including food shortage, rehabilitation admissions and formation of a new roost) across eastern Australia in 2008-2019. The Roost Species Distribution Model (SDM) has predictions of roost suitability. These are monthly, spatially explicit predictions of particular conditions or probability of roost occupations. The model objects are iterations of models that were initially trained on data held in figshare (https://figshare.com/s/ddb5a1584609b20f6596). These data objects are linked with code provided at https://github.com/hanlab-ecol/BatOneHealth to be able to run the models and analyses. This includes comparisons of virus predictions of seven different multiscale model structures to observed Hendra virus shedding in field surveys. The purpose of this study was to determine if quantifying and incorporating host condition into epidemiological models improves predictions of virus shedding in space and time. The data objects relate to the 1,000 iterations run of this process to better able to account for uncertainty. Full details about this dataset can be found at https://doi.org/10.5285/93bb37c6-ef86-4386-945d-c1a3d1e2683c

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

This data set includes longitudinal occurrence of bird species at 36 forest plots – half of which burned during the 2015-16 El Niño drought – distributed across a gradient of prior human disturbance in the Brazilian Amazon. Data was collected in 2010 and 2016 (around 6 years before, and one year after the 2015-16 El Niño, respectively) as part of the projects 'Assessing ENSO-induced Fire Impacts in tropical Rainforest Ecosystems' (AFIRE) and 'Biodiversity and Ecosystem Functioning in degraded and recovering Amazonian and Atlantic Forests' (ECOFOR), within the NERC Human-Modified Tropical Forest (HTMF) programme. Full details about this dataset can be found at https://doi.org/10.5285/4b05caee-a3c8-46a7-b675-e5a94554bd9f

The greenhouse gas (GHG) emission represent the amount of greenhouse gases (nitrous oxide, methane and carbon dioxide) emissions associated with the annual production of seven livestock commodities, considering the following processes: enteric fermentation, manure deposition on grassland, manure management on farm; application of manure on feed crops and application of synthetic fertiliser on grassland and feed crops, plus other cropland emissions for feed crops (e.g. peatland drainage and methane from rice cultivation). We also provide the greenhouse gas emission intensities, which indicate the amount of greenhouse gas emissions per unit of mass of animal products produced annually. The considered livestock commodities are: bovine ('BV') meat and milk, small ruminant (sheep and goat, 'SG') meat and milk, pig (PG) meat, poultry (chicken, ducks, 'PT') meat, and poultry eggs. The resolution is 5 arc minute, across the global land area, for the period around year 2000. The greenhouse gas (GHG) emission represent the amount of greenhouse gases (nitrous oxide, methane and carbon dioxide) emissions associated with the annual production of 172 cultivated crops, considering the following processes: application of manure and synthetic fertiliser on cropland, peatland drainage, and methane from rice cultivation. Full details about this dataset can be found at https://doi.org/10.5285/ccbd5c0b-21b2-40ce-bafd-6ccea4a270a4

[THIS DATASET HAS BEEN WITHDRAWN]. The greenhouse gas (GHG) emissions represent the amount of greenhouse gases (nitrous oxide, methane and carbon dioxide) emissions associated with the annual production of seven livestock commodities, considering the following processes: enteric fermentation, manure deposition on grassland, manure management on farm; application of manure on feed crops and application of synthetic fertiliser on grassland and feed crops, plus other cropland emissions for feed crops (e.g. methane from rice cultivation). We also provide the greenhouse gas emission intensities, which indicate the amount of greenhouse gas emissions per unit of mass of animal products produced annually. The considered livestock commodities are: bovine meat and milk, small ruminant (sheep and goat) meat and milk, pig meat, poultry (chicken, ducks) meat, and poultry eggs. The resolution is 5 arc minute, across the global land area, for the period of 1997-2003. Full details about this dataset can be found at https://doi.org/10.5285/76f8c5c0-6dde-407a-9710-2bca2e041512