Climate regime effects on Pacific herring growth using coupled nutrient-phytoplankton-zooplankton and bioenergetics models

We used a nutrient-phytoplankton-zooplankton (NPZ) model coupled to a fish bioenergetics model to simulate the weight-at-age responses of Pacific herring Clupea pallasii to climate regimes. The NPZ model represents the daily dynamics of the lower trophic levels by simulating the uptake and recycling dynamics of nitrogen and silicon and the photosynthesis and grazing interactions of multiple functional groups of phytoplankton and zooplankton. The bioenergetics model simulates the number and mean weight of Pacific herring for each of 10 age-classes. Three zooplankton groups simulated in the NPZ model provide estimates of the prey used to determine the consumption component of the herring bioenergetics model. We used a spawner-recruit relationship to estimate the number of new age-1 individuals joining the herring population every year. The coupled models were applied to the coastal upwelling area off the west coast of Vancouver Island. Model simulations were performed to isolate the effects of each of four documented climate regimes on Pacific herring weights at age. The climate regimes differed in the environmental variables used in the spawner-recruit relationship as well as in the water temperature, mixed-layer depth, and nutrient influxing rate used by the NPZ model. In agreement with general opinion and with the Pacific herring data from the west coast of Vancouver Island, the model-predicted estimates of weight at age, recruitment, and spawning stock biomass were highest in regime 1 (1962-1976), intermediate in regime 2 (1977-1988), and lowest in regime 3 (1989-1999). Insufficient time has passed to adequately document the conditions and herring responses in regime 4 (1998-2002). The overall regime effect on weights at age was a mix of recruitment effects and lower trophic level effects that varied in direction and magnitude among the four regimes. Coupling bioenergetics models to physics and food web models is the next challenge in understanding and forecasting how climate change will affect fish growth and population dynamics.