Governance and Socio-Ecological Networks

Full Title

Governing social-ecological system—insights from a social-ecological network perspective

Abstract

Effectively governing complex social-ecological systems remains a fundamental and enduring challenge. This challenge is particularly acute when considering the continued degradation of natural resources, loss of critical ecosystem services, and anticipated impacts associated with climate change worldwide. Empirical studies have drawn attention to the interdependencies and feedback that exist between humans and the environment. Moreover, scholars have noted that a failure to take into consideration these feedbacks and interdependencies when developing governance strategies and policy prescriptions will likely result in unintended consequences.

However, untangling the numerous social-ecological interdependencies in the context of management has proved difficult, and understanding how different patterns of connections affect governance outcomes is poorly understood. One promising approach to address this fundamental gap is to model social-ecological systems as social-ecological networks, where actors (e.g., individuals, groups, organizations) and ecological entities (e.g., a species, forest patches, protected areas) are conceptualized as nodes, and their interdependencies as links. This study will employ a range of methods—e.g., network analysis, exponential random graph models, agent based models—to gain key insights concerning different aspects of social-ecological networks—i.e., structure, function, and dynamics. Previous in-depth research in three marine reserves in Jamaica, and associated data sets, will provide the empirical foundation. Importantly, such a cross-disciplinary integrated approach will contribute to theory development with respect to the relationship between diverse governance arrangements, managed ecosystems, and natural resource management outcomes. Furthermore, the research results will inform management strategies and policy interventions.

Project Type
Postdoctoral Fellowship
Date
2016
Principal Investigators
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