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.
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