Abstract
Improved knowledge of long-term social and environmental trends and their drivers in coupled human and natural systems is needed to guide nature and society along a more sustainable trajectory. Here we combine common property theory and experimental impact evaluation methods to develop an approach for analyzing long-term outcome trajectories in social-ecological systems (SESs). We constructed robust counterfactual scenarios for observed vegetation outcome trajectories in the Indian Himalaya using synthetic control matching. This approach enabled us to quantify the contribution of a set of biophysical and socioeconomic factors in shaping observed outcomes. Results show the relative importance of baseline vegetation condition, governance, and demographic change in predicting long-term ecological outcomes. More generally, the findings suggest the broad potential utility of our approach to analyze long-term outcome trajectories, target new policy interventions, and assess the impacts of policies on sustainability goals in SESs across the globe.