High spatial-temporal resolution data across large scales are needed to transform our understanding of ecosystem services

Many assessments of ecosystem services (ESs; nature’s contribution to people [1]) are based on maps of land cover. For example, Costanza et al. [2] estimated the value of global ESs using economic valuations based on land cover and land use data. This method consists of matching an ecosystem type with the potential ESs that they pro-vide. However, within the different types of land cover or land use considered, various environmental factors occurring at finer temporal or spatial scales (e.g. climatic varia-tion) are not well captured. Thus, ES assessments are largely scale dependent, often missing important variables at both large and small scales. More in-depth studies should be encouraged to elucidate the roles of variables other than land cover [3].