ABSTRACT
Understanding the patterns of development of fisheries across trophic levels and their effects on ecosystems is essential for sustainable harvests. We develop an age-structured food web model to explore some of the bioeconomic causes and consequences of fishing patterns. We illustrate some of the model behaviors using a food chain ecosystem, parameterized using species found in the northwest Atlantic. We explore the effects of different relationships between profitability (defined as total profit per unit fishing effort) and trophic level of the target species on ecosystem and fishing dynamics. Across the profitability scenarios we explore, different patterns in ecosystem and fishery dynamics emerge, with greater variability and depletion in ecosystem biomass, greater variability and less yield to the fishery, and more variable profit when lower trophic level are more profitable and subject to more intense fishing pressure. For all scenarios we calculate the mean trophic level of the catch (TLC) in each year (where trends in this metric are often assumed to be an indicator of fishing patterns and ecosystem health) and compare it with the mean trophic level of the ecosystem. The relationship between the TLC and trophic level of the ecosystem varies with the way in which the fishery develops, and also with the particular species, suggesting that the TLC may not be the best indicator of ecosystem dynamics.
Acknowledgments
Mark Plummer, who passed away during the completion of this project, was instrumental in conceiving and managing this work. We thank two anonymous reviewers for their helpful comments. Any views expressed in this article are those of the authors, and do not necessarily represent the views of the National Oceanic and Atmospheric Administration or any sub-agencies.
Funding
This work was supported by the Northwest Fisheries Science Center through a contract to Marine Resources Assessment Group Americas and by the Center for Stock Assessment Research, a partnership between the Southwest Fisheries Science Center Santa Cruz Laboratory and the University of California Santa Cruz. This work is a contribution of the California Current Integrated Ecosystem Assessment program.