Climate Change and Density Dependence in the North Pacific: Applications to Salmon Run Forecasting and Plankton Population Dynamics

Abstract

We explore the role of density dependence and climate change in impacting different trophic levels of the North Pacific Ocean which supports some of the world’s largest fisheries. First, we evaluated the use of density dependent growth in autoregressive models to improve forecasting methodology for Sockeye Salmon in Bristol Bay, Alaska. Bristol Bay supports the world’s largest fishery for sockeye salmon which are harvested during an extremely condensed time period as fish return to their natal rivers. Uncertainties in pre-season forecasts of run size challenge managers and the fishing community because of limited time to adapt management, fishing, and processing strategies within a season. Pre-season forecasts between 2005 and 2022 were off by as much as 29%, with a mean absolute percent error of 16%. We found that autoregressive models including mean length-at-age of returning sockeye salmon as well as previous year’s run size, summer sea surface temperature, and competitor abundance (i.e., pink salmon) produced accurate predictions of run size for sockeye salmon substantially earlier in the season than is currently possible via pre-season or current in-season methods. Our best model had an average mean absolute percent error between observed and predicted run sizes on June 24th of 12%, a level of error not met by current in-season methods until July 11th and better than current pre-season methods in the majority of years. This provides valuable management benefits to managers and the fishing industry.Next, we evaluated the potential role of climate change in shaping zooplankton population biomass and size structure as zooplankton provide an important food source for all Alaskan fisheries. Climate change is warming the earth and its oceans, and these trends are expected to continue for the next century. These temperature changes could have major ecosystem impacts starting at the lower trophic levels such as zooplankton and cascading up the system, potentially due to changes in zooplankton size structure with increasing temperatures. Thus, we seek to assess impacts to zooplankton population demographics in the Bering Sea using a physiologically structured population model consisting of a semi chemostat phytoplankton resource and a zooplankton consumer divided into a juvenile and adult stage. Our model predicts that increased temperatures will lead to increased extinction risk starting at around 15 C, but that decreases in size at maturity down to approximately 62 µg would allow the population to persist at higher temperatures. However, this has the added consequence of a decreased size structure of the population. Such a collapse of the forage base or decrease in size structure could have cascading impacts to the rest of the ecosystem including reductions in carrying capacity and size at age of important fish species.