Understanding The Inter-Annual Variability of Fraser River Salmon Populations with Dynamic State Space Reconstruction: A New Predictive Approach for Ecological Dynamics

University Of California-San Diego Scripps Inst Of Oceanography, La Jolla CA

Investigators

Abstract

Salmon species are tremendously important both culturally, as an icon for Native North Americans, and economically. Their populations are also among the most variable from year to year, a trait that is of considerable importance for local economies based on wild salmon fisheries because it creates a high degree of financial risk or uncertainty. Understanding what controls the dramatic annual swings of salmon stocks and predicting these swings is a matter of significant practical importance. This problem was apparent in California with the 2009 ban on salmon fishing, a management decision causing a loss to state revenues in excess of $220 million. In this project, a new paradigm for ecological dynamics will be developed, one that differs dramatically from the classical views of fisheries management and population biology that are based largely on classical ideas of equilibrium and stability. The goal of this project is to develop and use new tools from nonlinear science that use prediction, as opposed to post hoc fitting, as the ultimate measure of merit. This new paradigm does not require equilibrium concepts and stability, but views the fisheries problem as a dynamic complex system of nonlinear co-dependent interactions. It explicitly recognizes the growing evidence from field measurements on natural populations that nonlinear complexity and instability are ubiquitous, and that static or multiple equilibria, though simple and conceptually manageable, are likely to be idealized exceptions rather than the rule. The state space reconstruction methods that will be developed will use time series data to reconstruct and predict non-equilibrium salmon population dynamics for the 9 major Fraser River sockeye stocks, with the ultimate view toward implementing these methods for managing this fishery.