Understanding the effects of landscape structure (composition and configuration) on ecosystem services (ES) is vital for their sustainable management. Predicting the effects of landscape structure on ES is more challenging than predicting the effects of landscape structure on biodiversity due to the coupled socio-ecological nature of ES. Here, we present an integrative spatially explicit modelling framework that extends John Wien's classical focal patch for predicting the effects of spatial structure on biodiversity to ecosystem services. The central tenet of our framework is that predictive modelling of ES should explicitly consider the spatial scale at which each relevant social and ecological predictors should be measured. In other words, we argue that the key to predictive modelling of ES is to recognize each predictor of the distribution of a given ES has a spatial scale that is most appropriate for assessing its role in determining the distribution of an ES, including relevant components of landscape structure. This approach differs somewhat from most ES modelling frameworks in which predictor variables are assigned to a common scale of analysis. A major benefit of our approach is that it means that the relative contribution of landscape structure on the distributions relative to other predictors can be quantified for a given ES in a given socio-ecological context. Moreover, we hypothesize that a clear understanding of the degree to which the most important spatial scale of different socio-ecological predictors of different ES varies by location will greatly improve the predictive power of spatial models of ES.
In addition to presenting the overall rationale behind our modelling framework, we present preliminary empirical work testing our framework for multiple ES in Britain, as well as outlining how simulation modelling approaches can assist with this methodological approach.