bd940dad-9bf4-40d9-891b-161f3dfe8e86 English ISO/IEC 8859-1 (also known as Latin 1) dataset dataset NERC EDS Environmental Information Data Centre Lancaster Environment Centre, Library Avenue, Bailrigg Lancaster LA1 4AP UK info@eidc.ac.uk https://eidc.ac.uk/ EIDC website The Environmental Information Data Centre (EIDC) is the UK's national data centre for terrestrial and freshwater sciences. information pointOfContact 2025-11-13T16:25:58 UK GEMINI 2.3 WGS 84 Global ensembles of Ecosystem Service map outputs modelled at 1km resolution for water supply, recreation, carbon storage, fuelwood and forage production 2023-01-23 publication https://catalogue.ceh.ac.uk/id/bd940dad-9bf4-40d9-891b-161f3dfe8e86 10.5285/bd940dad-9bf4-40d9-891b-161f3dfe8e86 doi: Hooftman, D.A.P., Bullock, J.M., Neugarten, R.A., Chaplin-Kramer, R., Willcock, S. (2023). Global ensembles of Ecosystem Service map outputs modelled at 1km resolution for water supply, recreation, carbon storage, fuelwood and forage production. NERC EDS Environmental Information Data Centre 10.5285/bd940dad-9bf4-40d9-891b-161f3dfe8e86 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 Hooftman, D.A.P. Lactuca: Environmental Data Analyses and Modelling Danny.hooftman@lactuca.nl https://orcid.org/0000-0001-9835-6897 ORCID record ORCID is an open, non-profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers. information author Bullock, J.M. UK Centre for Ecology & Hydrology enquiries@ceh.ac.uk https://orcid.org/0000-0003-0529-4020 ORCID record ORCID is an open, non-profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers. information author Neugarten, R.A. Cornell University ran63@cornell.edu https://orcid.org/0000-0003-0647-0516 ORCID record ORCID is an open, non-profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers. information author Chaplin-Kramer, R. Natural Capital Project rchaplin@umn.edu https://orcid.org/0000-0002-1539-5231 ORCID record ORCID is an open, non-profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers. information author Willcock, S. Bangor University s.willcock@bangor.ac.uk https://orcid.org/0000-0001-6704-3548 ORCID record ORCID is an open, non-profit, community-driven effort to create and maintain a registry of unique researcher identifiers and a transparent method of linking research activities and outputs to these identifiers. information author Bangor University EMAIL NOT PROVIDED owner Hooftman, D.A.P. Lactuca: Environmental Data Analyses and Modelling Danny.hooftman@lactuca.nl pointOfContact NERC EDS Environmental Information Data Centre info@eidc.ac.uk custodian NERC EDS Environmental Information Data Centre info@eidc.ac.uk publisher Environmental Monitoring Facilities Land Use theme GEMET - INSPIRE themes, version 1.0 2008-06-01 publication natural capital recreation water supply livestock ecosystem services sustainable development GEMET - Concepts, version 4.1.3 2019-01-28 creation Carbon stocks Ensemble modelling Fuelwood Global maps Weighted averaging otherRestrictions Registration is required to access this data otherRestrictions This resource is available under the terms of the Open Government Licence otherRestrictions If you reuse this data, you should cite: Hooftman, D.A.P., Bullock, J.M., Neugarten, R.A., Chaplin-Kramer, R., Willcock, S. (2023). Global ensembles of Ecosystem Service map outputs modelled at 1km resolution for water supply, recreation, carbon storage, fuelwood and forage production. NERC EDS Environmental Information Data Centre https://doi.org/10.5285/bd940dad-9bf4-40d9-891b-161f3dfe8e86 grid vector 1000 English utf8 environment economy -180 180 -90 90 TIFF Shapefile NERC EDS Environmental Information Data Centre info@eidc.ac.uk distributor https://catalogue.ceh.ac.uk/datastore/eidchub/bd940dad-9bf4-40d9-891b-161f3dfe8e86 Download the data Download a copy of this data fileAccess https://data-package.ceh.ac.uk/sd/bd940dad-9bf4-40d9-891b-161f3dfe8e86.zip Supporting information Supporting information available to assist in re-use of this dataset information dataset dataset Commission Regulation (EU) No 1089/2010 of 23 November 2010 implementing Directive 2007/2/EC of the European Parliament and of the Council as regards interoperability of spatial data sets and services 2010-12-08 The ensembles, their approach methodology, and their validations are currently in revision after review in Science Advances as Willcock et al. (2023): Model Ensembles of Ecosystem Services Fill Global Certainty and Capacity Gaps. Relevant Matlab and Python codes can be found at https://github.com/GlobalEnsembles Global among model ensembles for recreation, carbon storage, and biomass for fuelwood and forage production are provided as 1-km2 gridcells; water supply ensembles are provided per catchment polygons associated to the 15,289 worldwide HydroSHEDS catchment definitions (https://www.hydrosheds.org/). Model data included outputs from among others: InVEST, ARIES, WaterWorld, Co$ting Nature, LPJ-GUESS, TEEB, Scholes, Aqueduct, FAO livestock distributions, and a wide variety of biomass models such as from ESA CCI Biomass Climate Change Initiative, GEOCARBON global forest biomass and Global Forest Watch. These data sets are not provided here, but a full list with links to these data sets or software, where applicable, can be found in the supporting documentation. Note that license restrictions could apply. Ensembles approaches include: unweighted (mean and median) approaches and weighted averaging with weights determined following multiple methods according to Hooftman et al. (2022): the deterministic correlation coefficient among models, the first principal component among models and weights iterated as regression to the median and leave-one-out cross validation. Uncertainty is presented by the Standard Error of Mean among contributing model outputs and among ensemble approaches, calculated as the standard deviation corrected with the amount of contributing models/ensembles per cell. Prior to ensemble calculations: all individual model outputs have been normalised against the lower 2.5% and upper 97.5% percentile. Afterwards, the resulting Ensembles have been identically re-normalised to ensure a 0-1 scale. For all details about the individual model approaches, their synchronisation, ensemble algorithms and their validation we refer to the supporting documentation and associated publication.