AUTHOR=Luczkovich Joseph J. , Johnson Jeffrey C. , Deehr Rebecca A. , Hart Kevin J. , Clough Lisa , Griffith David C. TITLE=Linking Fishing Behavior and Ecosystem Dynamics Using Social and Ecological Network Models JOURNAL=Frontiers in Ecology and Evolution VOLUME=9 YEAR=2021 URL=https://www.frontiersin.org/journals/ecology-and-evolution/articles/10.3389/fevo.2021.662412 DOI=10.3389/fevo.2021.662412 ISSN=2296-701X ABSTRACT=
One goal of ecosystem-based management is studying an ecosystem and its people, the socio-ecological system, in a qualitative and quantitative modeling approach that can provide management agencies with possible outcomes of their actions using scenario forecasting. Ecosystem-based fisheries management strives to use the socio-ecological system approach, including direct and indirect impacts on multiple species including the behavioral responses of fishers after a regulatory change (a gillnet ban). Here, we link fisher behavioral networks with a mass-balanced food-web ECOPATH network model of an estuarine ecosystem and its commercial fisheries for an analysis of fishing impacts after a gillnet ban on multiple species using ECOSIM. We modeled fisher behavioral networks using reported catches of species from individual fishers along with the gear fished to create nodes in a gear/species affiliation network. Individual fishers with common gear/species use are indicative of common fishing behavior. When such fishers have high network centrality and are engaged in multiple gear/species fisheries, they can transition to other gear/species fisheries along “switching pathways” when facing a regulatory change. We used an index of joint gear participation to identify likely gear switching pathways, and we predicted changes in fishing effort after a gill net ban. We simulated the gill net ban in ECOSIM under two scenarios of fishing effort: Scenario 1, gill net fishing effort of 0%; Scenario 2, gill net fishing effort of 0% with increased effort in the alternative gear fisheries using the predicted switching pathways for the affiliation network. Scenario 1 predicted an increase in flounder (