Land use changes as proxies for ecosystem services delivery: how reliable are they?

Abstract

Assessing the provision of ecosystem services (ES), whether in policy making, impact analyses or valuation studies, requires measurement of the actual amount of services delivered. However, the quantification of ES provisioning remains challenging due to a multitude of constraints (e.g. relationships between biotic and abiotic factors and services provisioning, modeling constraints, limited understanding of ecosystem dynamics). Therefore, land use and land cover (LU/LC) changes are often used as proxies to assess ecosystem services delivery, even when evidence is not straightforward. This paper draws on case studies of biophysical modeling in ES outputs in order to assess the reliability of LU/LC changes as proxies for ES delivery. In a first step, biophysical models that quantify ES delivery relative to a baseline scenario are compared with LU/LC changes from remote sensing data using spatial modeling tools. In the next step, a ‘goodness of fit’ for the LU/LC proxy to quantify changes in ES delivery will be determined for each case under analysis. The results provide an indication of (i) whether significant changes in ES outputs correspond to significant changes in LU/LC, (ii) possible differences in goodness of fit with regards to the type of ES under analysis, and of (iii) possible contrasting evidence between cases within one ES whereby significant changes in ES outputs correspond to significant LU/LC changes and where they do not. The results of this analysis could therefore support environmental impact assessments of Payments for Ecosystem Services (PES schemes) where the ability to use appropriate LU/LC proxies greatly reduces costs of monitoring and therefore increases overall financial efficiency of the scheme. Furthermore, whether quantification of ES delivery is required for policy making or valuation studies, the knowledge of the correct use of LU/LC changes as proxies for services delivery could greatly simplify quantification efforts.