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) 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. Natural Environment Research Council doi:10.5285/11689000-f791-4fdb-8e12-08a7d87ad75f [Dataset]

Abstract

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.,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.

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Contributors

Contributor: F. Eigenbrod

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