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A continental scale validation of ecosystem service models

A continental scale validation of ecosystem service models
A continental scale validation of ecosystem service models
Faced with environmental degradation, governments worldwide are developing policies to safeguard ecosystem services (ES). Many ES models exist to support these policies, but they are generally poorly validated, especially at large scales, which undermines their credibility. To address this gap, we describe a study of multiple models of five ES, which we validate at an unprecedented scale against 1675 data points across sub-Saharan Africa. We find that potential ES (biophysical supply of carbon and water) are reasonably well predicted by the existing models. These potential ES models can also be used as inputs to new models for realised ES (use of charcoal, firewood, grazing resources and water), by adding information on human population density. We find that increasing model complexity can improve estimates of both potential and realised ES, suggesting that developing more detailed models of ES will be beneficial. Furthermore, in 85% of cases, human population density alone was as good or a better predictor of realised ES than ES models, suggesting that it is demand, rather than supply that is predominantly determining current patterns of ES use. Our study demonstrates the feasibility of ES model validation, even in data-deficient locations such as sub-Saharan Africa. Our work also shows the clear need for more work on the demand side of ES models, and the importance of model validation in providing a stronger base to support policies which seek to achieve sustainable development in support of human well-being.
1432-9840
1902-1917
Willcock, Simon
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Hooftman, Danny A.P.
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Balbi, Stefano
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Blanchard, Ryan
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Dawson, Terrence P.
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O’Farrell, Patrick
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Hickler, Thomas
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Hudson, Malcolm
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Lindeskog, Mats
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Martínez-López, Javier
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Mulligan, Mark
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Reyers, Belinda
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Shackleton, Charlie M.
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Sitas, Nadia
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Villa, Ferdinando
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Watts, Sophie M.
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Eigenbrod, Felix
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Bullock, James M.
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Willcock, Simon
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Hooftman, Danny A.P.
715d0810-9c09-47d4-9d33-07202d110112
Balbi, Stefano
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Blanchard, Ryan
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Dawson, Terrence P.
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O’Farrell, Patrick
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Hickler, Thomas
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Hudson, Malcolm
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Lindeskog, Mats
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Martínez-López, Javier
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Mulligan, Mark
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Reyers, Belinda
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Shackleton, Charlie M.
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Sitas, Nadia
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Villa, Ferdinando
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Watts, Sophie M.
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Eigenbrod, Felix
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Bullock, James M.
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Willcock, Simon, Hooftman, Danny A.P., Balbi, Stefano, Blanchard, Ryan, Dawson, Terrence P., O’Farrell, Patrick, Hickler, Thomas, Hudson, Malcolm, Lindeskog, Mats, Martínez-López, Javier, Mulligan, Mark, Reyers, Belinda, Shackleton, Charlie M., Sitas, Nadia, Villa, Ferdinando, Watts, Sophie M., Eigenbrod, Felix and Bullock, James M. (2019) A continental scale validation of ecosystem service models. Ecosystems, 22 (8), 1902-1917. (doi:10.1007/s10021-019-00380-y).

Record type: Article

Abstract

Faced with environmental degradation, governments worldwide are developing policies to safeguard ecosystem services (ES). Many ES models exist to support these policies, but they are generally poorly validated, especially at large scales, which undermines their credibility. To address this gap, we describe a study of multiple models of five ES, which we validate at an unprecedented scale against 1675 data points across sub-Saharan Africa. We find that potential ES (biophysical supply of carbon and water) are reasonably well predicted by the existing models. These potential ES models can also be used as inputs to new models for realised ES (use of charcoal, firewood, grazing resources and water), by adding information on human population density. We find that increasing model complexity can improve estimates of both potential and realised ES, suggesting that developing more detailed models of ES will be beneficial. Furthermore, in 85% of cases, human population density alone was as good or a better predictor of realised ES than ES models, suggesting that it is demand, rather than supply that is predominantly determining current patterns of ES use. Our study demonstrates the feasibility of ES model validation, even in data-deficient locations such as sub-Saharan Africa. Our work also shows the clear need for more work on the demand side of ES models, and the importance of model validation in providing a stronger base to support policies which seek to achieve sustainable development in support of human well-being.

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Accepted/In Press date: 22 March 2019
e-pub ahead of print date: 22 April 2019
Published date: December 2019

Identifiers

Local EPrints ID: 429726
URI: http://eprints.soton.ac.uk/id/eprint/429726
ISSN: 1432-9840
PURE UUID: fd1a3a5d-79cf-4dfb-82fc-2b8c854506d3
ORCID for Felix Eigenbrod: ORCID iD orcid.org/0000-0001-8982-824X

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Date deposited: 04 Apr 2019 16:30
Last modified: 16 Mar 2024 07:43

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Contributors

Author: Simon Willcock
Author: Danny A.P. Hooftman
Author: Stefano Balbi
Author: Ryan Blanchard
Author: Terrence P. Dawson
Author: Patrick O’Farrell
Author: Thomas Hickler
Author: Malcolm Hudson
Author: Mats Lindeskog
Author: Javier Martínez-López
Author: Mark Mulligan
Author: Belinda Reyers
Author: Charlie M. Shackleton
Author: Nadia Sitas
Author: Ferdinando Villa
Author: Sophie M. Watts
Author: Felix Eigenbrod ORCID iD
Author: James M. Bullock

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