An adaptable agent-based model for guiding multi-species Pacific salmon fisheries management within a SES framework
Authored by Martin Cenek, Maxwell Franklin
Date Published: 2017
DOI: 10.1016/j.ecolmodel.2017.06.024
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Abstract
Informing fishery management decisions using coupled socio-ecological
systems (CSES) models requires model construction that captures the
systems interactions with high precision. Ecological uncertainty in
fishery models is easily reduced using existing scientific literature,
but social drivers are often poorly defined or understood. The lack of
knowledge about fishermen behavior results in inaccurate models of
questionable utility for fishery managers. We designed and constructed a
high fidelity agent based model (ABM) using the socio-ecological
framework that reduces social system uncertainty by capturing complex
behaviors using data-driven bounded rationality and feedback. The
resulting generalized ABM of CSES dynamics was instantiated to Pacific
salmon fisheries at Kenai river in Upper Cook Inlet, Alaska. The
data-driven model construction fuses multiple data-sets for
classification of social and ecological fishery regimes into stochastic
distributions; the agent behaviors were generalized by evolving
parametrized equations using data-driven machine learning; multiple
non-trivial metrics on multiple scales verified model's accuracy and
predictive capacity. The verified model of CSES dynamics at the Kenai
river revealed recent instability in the dipnet fishery coupled
dynamics, historic instability in the drift gillnet fishery coupled
dynamics due to a compensatory and aggressive fishing strategy, and in
the future the model will be used for scenario-based studies to
understand the outcomes of alternative management strategies. (C) 2017
Elsevier B.V. All rights reserved.
Tags
Agent-based model
Social-Ecological System
Social-ecological systems
Fisheries management
Coupled social-ecological system
Decision support tool
Pacific
salmon
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