A continental-scale validation of ecosystem service models

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  • Simon Willcock
  • Danny A. P. Hooftman
    Centre for Ecology and Hydrology
  • Stefano Balbi
    Basque Centre of Climate Change
  • Ryan Blanchard
    Council for Scientific and Industrial Research
  • Terence P. Dawson
    King's College London
  • Patrick J. O’Farrell
    Senckenberg Biodiversity and Climate Research Centre
  • Thomas Hickler
    Goethe University, Frankfurt, Germany
  • Malcolm D. Hudson
    University of Southampton
  • Mats Lindeskog
    Lund University
  • Javier Martinez-Lopez
    Basque Centre of Climate Change
  • Mark Mulligan
    King's College London
  • Belinda Reyers
    Stellenbosch University
  • Charlie Shackleton
    Rhodes University
  • Nadia Sitas
    Council for Scientific and Industrial Research
  • Ferdinando Villa
    Basque Centre of Climate Change
  • Sophie M. Watts
    University of Southampton
  • Felix Eigenbrod
    University of Southampton
  • James M. Bullock
    Centre for Ecology and Hydrology
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.


  • Africa, beneficiary, carbon, charcoal, complexity, firewood, grazing, natural capital, water
Original languageEnglish
Early online date22 Apr 2019
Publication statusE-pub ahead of print - 22 Apr 2019

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