TY - JOUR

T1 - A continental-scale validation of ecosystem service models

AU - Willcock, Simon

AU - Hooftman, Danny A. P.

AU - Balbi, Stefano

AU - Blanchard, Ryan

AU - Dawson, Terence P.

AU - O’Farrell, Patrick J.

AU - Hickler, Thomas

AU - Hudson, Malcolm D.

AU - Lindeskog, Mats

AU - Martinez-Lopez, Javier

AU - Mulligan , Mark

AU - Reyers, Belinda

AU - Shackleton, Charlie

AU - Sitas, Nadia

AU - Villa, Ferdinando

AU - Watts, Sophie M.

AU - Eigenbrod, Felix

AU - Bullock, James M.

N1 - This work took place under 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 program (ESPA; www.espa.ac.uk). ESPA receives its funding from the UK Department for International Development, the Economic and Social Research Council and the Natural Environment Research Council.

PY - 2019/4/22

Y1 - 2019/4/22

N2 - Faced with environmental degradation, governments world-wide 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 1,675 data points across sub-Saharan Africa. We find that potential ES (biophysical supply of carbon and water) are reasonably well predicted by 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 supply-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.

AB - Faced with environmental degradation, governments world-wide 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 1,675 data points across sub-Saharan Africa. We find that potential ES (biophysical supply of carbon and water) are reasonably well predicted by 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 supply-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.

KW - Africa

KW - beneficiary

KW - carbon

KW - charcoal

KW - complexity

KW - firewood

KW - grazing

KW - natural capital

KW - water

U2 - 10.1007/s10021-019-00380-y

DO - 10.1007/s10021-019-00380-y

M3 - Article

VL - 22

SP - 1902

EP - 1917

JO - Ecosystems

JF - Ecosystems

SN - 1435-0629

IS - 8

ER -