11689000-f791-4fdb-8e12-08a7d87ad75f 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 2026-01-12T15:52:34 UK GEMINI 2.3 WGS 84 Ensemble outputs from Ecosystem Service models for water supply, aboveground carbon storage and use of water, grazing, charcoal and firewood by beneficiaries in sub-Saharan Africa 2020-06-25 publication https://catalogue.ceh.ac.uk/id/11689000-f791-4fdb-8e12-08a7d87ad75f 10.5285/11689000-f791-4fdb-8e12-08a7d87ad75f doi: Hooftman, D.A.P., Willcock, S., Eigenbrod, F., Bullock, J.M. (2020). Ensemble outputs from Ecosystem Service models for water supply, aboveground carbon storage and use of water, grazing, charcoal and firewood by beneficiaries in sub-Saharan Africa. NERC Environmental Information Data Centre 10.5285/11689000-f791-4fdb-8e12-08a7d87ad75f This dataset contains the gridded estimates per 1 km2 for mean and median ensemble outputs from 4-6 individual ecosystem service models for Sub-Saharan Africa, for above ground Carbon stock, firewood use, charcoal use and grazing use. Water use and supply are identically supplied as polygons. Individual model outputs are taken from previously published research. Making ensembles results in a smoothing effect whereby the individual model uncertainties are cancelled out and a signal of interest is more likely to emerge. Included ecosystem service models were: InVEST, Co$ting Nature, WaterWorld, Monetary value benefits transfer, LPJ-GUESS and Scholes models. Ensemble outputs have been normalised, therefore these ensembles project relative levels of service across the full area and can be used, for example, for optimisation or assignment of most important or sensitive areas. 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/10.5285/11689000-f791-4fdb-8e12-08a7d87ad75f Hooftman, D. Lactuca: Environmental Data Analyses and Modelling danny.hooftman@lactuca.nl pointOfContact 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 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 Eigenbrod, F. University of Southampton F.Eigenbrod@soton.ac.uk https://orcid.org/0000-0001-8982-824X 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 NERC EDS Environmental Information Data Centre info@eidc.ac.uk custodian NERC Environmental Information Data Centre info@eidc.ac.uk publisher carbon stock grazing natural capital poverty sustainable development water supply GEMET - Concepts, version 4.1.3 2019-01-28 creation Ecosystem services Africa ensemble modelling non-timber forest products poverty alleviation otherRestrictions no limitations otherRestrictions This resource is available under the terms of the Open Government Licence otherRestrictions © UK Centre for Ecology & Hydrology/Bangor University otherRestrictions If you reuse this data, you should cite: Hooftman, D.A.P., Willcock, S., Eigenbrod, F., Bullock, J.M. (2020). Ensemble outputs from Ecosystem Service models for water supply, aboveground carbon storage and use of water, grazing, charcoal and firewood by beneficiaries in sub-Saharan Africa. NERC Environmental Information Data Centre https://doi.org/10.5285/11689000-f791-4fdb-8e12-08a7d87ad75f grid vector English utf8 environment society -17.688 52.273 -35.344 18.448 Shapefile TIFF NERC EDS Environmental Information Data Centre info@eidc.ac.uk distributor https://data-package.ceh.ac.uk/data/11689000-f791-4fdb-8e12-08a7d87ad75f Download the data Download a copy of this data download https://data-package.ceh.ac.uk/sd/11689000-f791-4fdb-8e12-08a7d87ad75f.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 individual modelled ecosystem service outputs underlying the ensemble calculations originate from the"WISER: Which Ecosystem Service Models Best Capture the Needs of the Rural Poor" project (NE/L001322/1), funded by the UK Ecosystem Services for Poverty Alleviation programme (ESPA; www.espa.ac.uk). Validations of individual models and their correlation to model complexity have been published as Willcock et al. 2019: A continental-scale validation of ecosystem service models. Ecosystems, 22: 1902-1917. Among contributing model outputs means and median values were estimated per 1-km2 gridcell or per polygon for water. The standard error of mean is calculated from the standard deviation corrected with the amount of contributing models per cell. All underlying individual models have been normalised against the 95% percentile prior to calculations. 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, and their validation refer to Willcock et al. (2019) and the supporting documentation.