Socio-Environmental Networks of Common Pool Resources

Full Title

Using integrated socio-environmental networks to improve the management of environmental systems


Note: This project is part of a larger initiative, in partnership with Resources for the Future, focused on advancing the field of coupled socio-environmental analysis by emphasizing the deeper integration and reconciliation of natural science and economic systems models.

An ongoing sustainability challenge is to manage common pool resources, like forests, fisheries or groundwater. Such resources and the people who rely on them form complex socio-environmental systems with dynamic linked social, economic, physical, and biological processes. This means that predicting system response to potential management options requires integrated knowledge and theory across ecology, economics, and other social sciences. Performing this integration is difficult, especially for large systems with high degrees of connectivity, but doing so could improve policy design and system management.

Our project will develop an integrated modeling framework of linked ecological, economic and social networks to enable the design and analysis of environmental policy or management decisions in social-ecological systems.  A network framing has multiple advantages. First, networks are mathematical tools that can be used consistently across disciplines, e.g., to represent connectivity within and between ecological and social systems. Second, network descriptions are well-suited to analyze how system-level behaviors—robustness, resilience, and distributional outcomes—respond to change. Although there have been calls for more prescriptive uses of network representations and statistics to guide management of social-ecological systems, new interdisciplinary work is needed to harness the potential.  We aim to answer this call by integrating traditional theory on system dynamics from ecological, economic, and social disciplines into a framework that includes these fundamentals and includes complexity in linkages and system dynamics to enable policy applications.

Project Type
Team Synthesis Project
Matthew Ashenfarb, Resources for the Future
Gwen Iacona, University of Queensland
Fernanda Valdovinos, University of Michigan
Dane Taylor, SUNY Buffalo
Gourab Ghoshal, University of Rochester
Jeffrey Johnson, University of Florida
Iadine Chades, CSIRO
Rebecca Epanchin-Niell, Resources for the Future; University of Maryland
Matthew Hamilton, The Ohio State University
Angela Guerrero, The University of Queensland
Michelle Girvan, University of Maryland
Tyler Treakle, Resources for the Future

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