Hooftman, D.A.P.; Willcock, S.; Eigenbrod, F.; Bullock, J.M.

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

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.

Publication date: 2020-06-25

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This dataset is available under the terms of the Open Government Licence

This data is available as Shapefile or TIFF

You must 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

 

© UK Centre for Ecology & Hydrology

© Bangor University

Where/When

Study area

Provenance & quality

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.

Supplemental information

Other useful information regarding this dataset:

Willcock, S., Hooftman, D.A.P., Balbi, S., Blanchard, R., Dawson, T.P., O’Farrell, P.J., … Bullock, J.M. (2019). A Continental-Scale Validation of Ecosystem Service Models. Ecosystems, 22(8), 1902–1917.

Correspondence/contact details

Danny Hooftman
Lactuca: Environmental Data Analyses and Modelling
 danny.hooftman@lactuca.nl

Authors

Hooftman, D.A.P.
Lactuca: Environmental Data Analyses and Modelling
Willcock, S.
Bangor University
Eigenbrod, F.
University of Southampton
Bullock, J.M.
UK Centre for Ecology & Hydrology

Other contacts

Custodian
Environmental Information Data Centre
 info@eidc.ac.uk
Publisher
NERC Environmental Information Data Centre
 info@eidc.ac.uk

Additional metadata

Topic categories
Environment , Society
Keywords
Africa,  Carbon stocks,  Ecosystem services ensemble modelling,  grazing,  natural capital,  non-timber forest products,  poverty alleviation,  sustainable development,  water supply.
INSPIRE Theme
Funding
Natural Environment Research Council Award: NE/L001322/1
Natural Environment Research Council Award: NE/T00391X/1
Spatial representation types
Raster
Vector
Spatial reference system
WGS 84
Last updated
30 June 2020 07:57