Theorizing benefits and constraints in collaborative environmental governance: a transdisciplinary social-ecological network approach for empirical investigations
Örjan Bodin, Stockholm Resilience Centre, Stockholm University; Duke University Marine Laboratory, Nicholas School of the Environment, Duke University
Garry Robins, Melbourne School of Psychological Sciences, University of Melbourne
Ryan R. J. McAllister, CSIRO
Angela M. Guerrero, Australian Research Council Centre of Excellence for Environmental Decisions, University of Queensland; School of Biological Sciences, University of Queensland
Beatrice Crona, Global Economic Dynamics and the Biosphere, Royal Swedish Academy of Sciences; Stockholm Resilience Centre, Stockholm University
Maria Tengö, Stockholm Resilience Centre, Stockholm University
Mark Lubell, Department of Environmental Science and Policy, University of California at Davis
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When environmental processes cut across socioeconomic boundaries, traditional top-down government approaches struggle to effectively manage and conserve ecosystems. In such cases, governance arrangements that foster multiactor collaboration are needed. The effectiveness of such arrangements, however, depends on how well any ecological interdependencies across governed ecosystems are aligned with patterns of collaboration. This inherent interdisciplinary and complex problem has impeded progress in developing a better understanding of how to govern ecosystems for conservation in an increasingly interconnected world. We argue for the development of empirically informed theories, which are not only able to transcend disciplinary boundaries, but are also explicit in taking these complex social-ecological interdependences into account. We show how this emerging research frontier can be significantly improved by incorporating recent advances in stochastic modeling of multilevel social networks. An empirical case study from an agricultural landscape in Madagascar is reanalyzed to demonstrate these improvements.
collaborative governance; connectivity; exponential random graph models (ERGM); interdisciplinary; networks; social-ecological fit; social-ecological networks; social-ecological systems
Copyright © 2016 by the author(s). Published here under license by The Resilience Alliance. This article is under a Creative Commons Attribution 4.0 International License. You may share and adapt the work provided the original author and source are credited, you indicate whether any changes were made, and you include a link to the license.