Sustainable use and stewardship of natural resources is essential to the long-term persistence of human societies and the natural world. Understanding the interdependent behavior of social and natural systems and the factors that affect how these linked systems respond to sudden natural or political-economic shocks or ongoing stresses is a major challenge for science. Resilience is the ability of a system to absorb or adapt to change without altering its basic parts and functions. An important line of research therefore is to investigate the resilience of coupled human-natural systems in the face of major stresses and to understand how environmental governance, including both formal policies and informal institutions, affects resilience. Previously developed theories suggest that local resource-management institutions may contribute to resilience and enable communities to adapt more successfully to climate change. Mongolia is an ideal place to test this theory because it has experienced one of the most significant warming trends on Earth over the past 40 years. Furthermore, more than 2,000 community-based rangeland management organizations have formed in Mongolia since 1999, an unprecedented social experiment that creates an opportunity for rigorous policy learning. This interdisciplinary research project will assess the vulnerability of Mongolian pastoral social-ecological systems to climate change, evaluate the effects of community-based rangeland management on the resilience of Mongolian pastoral systems, strengthen linkages between science and policy making in Mongolia, and build the capacity of participating Mongolian and U.S. researchers and students to analyze the dynamics of complex coupled natural-human systems. The investigators will use a range of methods in this project, include remote sensing and climate and hydrological modeling to assess changes in climate and land use over time and the effects of those changes on rangeland hydrology and productivity. They will use observational approaches like interviews, household surveys, and plant and livestock field sampling to compare ecological, social, and resilience indicators in districts with community-based management and those without, and they will conduct targeted grazing removal experiments to improve understanding of the relative importance of weather and grazing in determining pasture conditions in different ecological zones. Data will be analyzed and integrated using a combination of statistics, statistical and process modeling, and geospatial 3-D visualization techniques. The project will educate and train graduate students and secondary school teachers in the U.S. and Mongolia and will directly involve stakeholders and policy makers through participatory system modeling and scenario planning workshops.
By examining the performance and outcomes of community-based institutions in rangelands using a large-sample, case-control design that accounts for variation in ecological and regional contexts, this project will contribute significantly to basic understanding of community-based rangeland management institutions in Mongolia and elsewhere. The project will make methodological contributions by evaluating the effects of community-based management across multiple scales and by integrating physical, ecological and social sampling and data analysis at each scale, thereby advancing understanding of cross-scale dynamics in complex systems. The results of this project will have significant implications for environmental policy in Mongolia and elsewhere, and they will benefit stakeholders like herders, and policy makers through their engagement in participatory-modeling and scenario-planning workshops. The project will have relevance for a broad range of arid and semiarid rangelands around the globe where pastoralists and policy makers are seeking ways to cope with a changing climate and develop management institutions that build resilience and promote sustainability in dryland systems. This project is supported by the NSF Dynamics of Coupled Natural and Human Systems (CNH) Program and by the NSF Office of International Science and Engineering.
