There has been a proliferation of coupled social-ecological systems (SES) models created and published in recent years. However, the degree of coupling between natural and social systems varies widely across the different coupled models and is often a function of the disciplinary background of the team conducting the research. This manuscript examines models developed for and used by NOAA Fisheries in support of Ecosystem Based Fisheries Management (EBFM) in the United States. It provides resource managers and interdisciplinary scientists insights on the strengths and weaknesses of the most commonly used SES models: end-to-end models, conceptual models, bioeconomic models, management strategy evaluations (MSEs), fisher behavior models, integrated social vulnerability models, and regional economic impact models. These model types are not unique to the literature, but allow us to differentiate between one-way coupled models – where outputs from one model are inputs into a second model of another discipline with no feedback to the first model, and two-way coupled models – where there are linkages between the natural and social system models. For a model to provide useful strategic or tactical advice, it should only be coupled to the degree necessary to understand the important dynamics/responses of the system and to create management-relevant performance metrics or potential risks from an (in)action. However, one key finding is to not wait to integrate! This paper highlights the importance of “when” the coupling happens, as timing affects the ability to fully address management questions and multi-sectoral usage conflicts that consider the full SES for EBFM or ecosystem based management (EBM) more generally.
Interdisciplinary science and environmental management involve bringing together data and expertise at multiple spatial scales. The most challenging part of merging scales is aligning the scale of inquiry with the research application. Through the Louisiana case study relating wetland loss and commercial fishing, we examine how the nature and strength of the relationship changes depending on the scale of investigation. Resulting management implications also vary because of tradeoffs in choosing the scale of inquiry. State-level fisheries managers may miss effects of wetland loss in fishing communities because they are looking at aggregate data. Scientific information must directly address the constituent scale, where managers can enact policy. The case study demonstrates why scalar considerations should be an explicit part of the planning process for both science and management.
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