a9ae773d-b742-4d42-ae42-2b594bae5d38 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 2025-11-13T16:20:41 UK GEMINI 2.3 OSGB 1936 / British National Grid Ensemble outputs among contemporary ecosystem service models for water supply and aboveground carbon storage in the UK following 10 different methods 2021-11-22 publication https://catalogue.ceh.ac.uk/id/a9ae773d-b742-4d42-ae42-2b594bae5d38 10.5285/a9ae773d-b742-4d42-ae42-2b594bae5d38 doi: Hooftman, D.A.P., Bullock, J.M., Jones, L., Willcock, S. (2021). Ensemble outputs among contemporary ecosystem service models for water supply and aboveground carbon storage in the UK following 10 different methods. NERC EDS Environmental Information Data Centre 10.5285/a9ae773d-b742-4d42-ae42-2b594bae5d38 This data set contains UK-wide maps of ten different among-model ensemble approaches for two services: above ground Carbon stock and water supply. The data for Carbon comes as fourteen TIF maps for above ground carbon storage at a 1-km2 resolution with associated world files: ten approaches, with a double option for two of those, together with maps of variation among models and among ensembles. For water, the data comes as one shapefile with polygons per watershed, each polygon containing these fourteen estimates. For all maps, 600dpi jpg depictions are added to the supporting information. Directory location independent layer files are included to aid scaling and providing the colour palettes. 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. Full details about this dataset can be found at https://doi.org/10.5285/a9ae773d-b742-4d42-ae42-2b594bae5d38 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 Jones, L. UK Centre for Ecology & Hydrology enquiries@ceh.ac.uk https://orcid.org/0000-0002-4379-9006 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 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 Bangor University EMAIL NOT PROVIDED owner Land Cover Hydrography theme GEMET - INSPIRE themes, version 1.0 2008-06-01 publication water supply sustainable development natural capital modelling ecosystem services carbon stock GEMET - Concepts, version 4.1.3 2019-01-28 creation United Kingdom ensemble modelling weighted averaging otherRestrictions no limitations 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., Jones, L., Willcock, S. (2021). Ensemble outputs among contemporary ecosystem service models for water supply and aboveground carbon storage in the UK following 10 different methods. NERC EDS Environmental Information Data Centre https://doi.org/10.5285/a9ae773d-b742-4d42-ae42-2b594bae5d38 grid 25 10 5 20 46000 1000 10000 English utf8 inlandWaters biota -8.648 1.768 49.864 60.861 TIFF NERC EDS Environmental Information Data Centre info@eidc.ac.uk distributor https://catalogue.ceh.ac.uk/datastore/eidchub/a9ae773d-b742-4d42-ae42-2b594bae5d38 Download the data Download a copy of this data fileAccess https://data-package.ceh.ac.uk/sd/a9ae773d-b742-4d42-ae42-2b594bae5d38.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 under review in Ecosystem Services as Hooftman et al. (2022): Weighted Ensembles Reduce Uncertainty in Ecosystem Service Modelling. Relevant Matlab and Python codes can be found at github.com/EnsemblesTypes. Among model ensembles for above ground standing carbon are provided as 1-km2 gridcells; Water supply ensembles are provided per catchment polygons associated to the 519 selected National River Flow Archive gauging stations in this study. Model data included outputs from among others: InVest, ARIES, WaterWorld, LUCI, LPJ-GUESS, TEEB, Scholes, Aqueduct, Grid-to-Grid, and DECIPHeR. 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, weighted averaging with weights determined following multiple methods (deterministic and iterative), attribute weighted averaging, and trained approaches. 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.