Trophic modeling of Eastern Boundary Current Systems: a review and prospectus for solving the “Peruvian Puzzle”

Abstract

Eastern Boundary Current systems (EBCSs) are among the most productive fishing areas in the world. High primary and secondary productivity supports a large biomass of small planktivorous pelagic fish, “small pelagics”, which are important drivers of production to the entire system whereby they can influence both higher and lower trophic levels. Environmental variability causes changes in plankton (food) quality and quantity, which can affect population sizes, distribution and domi-nance among small pelagics. This variability combined with impacts from the fishery complicate the development of management strategies. Consequently, much recent work has been in the development of multispecies trophic models to better understand interdependencies and system dynamics. Despite similarities in extent, structure and primary productivity between EBCSs, the Peruvian system greatly differs from the others in the magnitude of fish catches, due mainly to the incredible production of the anchovy Engraulis ringens. This paper reviews literature concerning EBCSs dynamics and the state-of-the-art in the trophic modeling of EBCSs. The objective is to critically analyze the potential of this approach for system understanding and management and to adapt existing steady-state models of the Peruvian system for use in (future) dynamic simulations. A guideline for the construction of trophodynamic models is presented taking into account the important trophic and environmental interactions. In consideration of the importance of small pelagics for the system dynamics, emphasis is placed on developing appropriate model compartmentalization and spatial delineation that facilitates dynamic simulations. Methods of model validation to historical changes are presented to support hypotheses concerning EBCS dynamics and as a critical step to the development of predictive models. Finally, the identification of direct model links to easily obtainable abiotic parameters is emphasized to add practicality to the model as a predictive tool.