Dr. William T. Stockhausen1
1AFSC
May 24, 2016 9:00 (PST): FSH 105
Coupled biophysical/individual-based models: can they inform recruitment, stock assessment and/or fishery management? DisMELS lessons from the GOAIERP
One of the key hypotheses underlying NPRB’s recent Gulf of Alaska (GOA) Integrated Ecosystem Research Project (IERP) was that year-class strength for the five commercially- and ecologically-important groundfish stocks at the focus of the project was determined by success or failure in running the early life, pelagic “gauntlet” from adult spawning areas to young-of-the-year nursery areas. As part of the multi-institution, multidisciplinary effort to address this hypothesis for pollock, Pacific cod, arrowtooth flounder, sablefish, and Pacific ocean perch, a group of modelers (including the author) constructed early life, coupled biophysical/individual-based models (CBP-IBMs) for each stock. For marine species with pelagic early life stages, CBP-IBMs provide one of the best approaches to synthesizing disparate information on individual life stages (e.g., eggs, larvae) and environmental variability into an integrated picture of early life processes. Among our goals for these models was to be able to improve current stock assessments and enhance fishery management by identifying the critical drivers of recruitment variability and hindcasting (or potentially forecasting) recent trends in recruitment for the five focal species. In regard to identifying critical drivers of recruitment variability, I think we can say that variability in physical transport, i.e. where young-of-the-year end up, is less important to recruitment variability than what happens along the way. However, in regard to predicting recruitment variability itself, we were certainly not terribly successful—except perhaps for pollock, the most data-informed of all the IBMs. As an extended introduction, I’ll briefly 1) introduce the concepts behind CBP-IBMs; 2) discuss DisMELS (the Dispersal Model for Early Life Stages), a framework for creating and running CBP-IBMs; and 3) review the five species-specific IBMs created for the GOAIERP. Then I’ll discuss results from the models and what they tell us about early life processes in the GOA. Finally, I’ll present a couple of practical suggestions for some “best practices” using these types of models.