Visiting Scientists

Dr. Sheng-Ping Wang
Department of Environmental Biology and Fisheries Science, National Taiwan Ocean University, Keelung, Taiwan
Dr Wang will be working with CAPAM colaborators from the Inter-American Tropical tuna Commission and the National Marine Fisheries Service on projects related to the selectivity component of the Good Practices in Stock Assessment Modeling Program. Sheng-Ping was a visiting scientist from February 24 to March 24, 2013 under funding from the International Seafood Sustainability Foundation (ISSF).
Selectivity’s distortion of the production function and its influence on management advice
Surplus production models (e.g. the Schaefer and Pella-Tomlinson models) aggregated the dynamics of a fish population into a simple function of abundance and do not explicitly represent biological and fishing processes. It has been clearly shown using age-structured models that the symmetrical production function of the Schaefer model is inappropriate for most fish species and the shape of the production function depends on biological parameters such natural mortality, growth, and the stock-recruitment relationship. It also depends on the age-specific selectivity of the fishery. We evaluate the influence of the selectivity curve on the shape of the production function and compare it with the influence of biological parameters. We then compare results of a stock assessment roughly based on bigeye tuna in the eastern Pacific Ocean when the production function does not match the selectivity curve and when the selectivity curve changes over time. Our results provide one more nail in the Schaefer model’s coffin.
Virgin recruitment profiling as a diagnostic for selectivity curve mispecification in integrated stock assessment models
We describe and test a method for diagnosing selectivity misspecification based on likelihood profiling of virgin recruitment. Virgin recruitment (R0; the equilibrium recruitment in the absence of fishing) is a common parameter in stock assessment that scales the population size. Information on population size comes from two main sources: 1) how catch changes indices of relative abundance and 2) how the relative abundance changes in consecutive ages of age composition data (or appropriately adjusted length composition data). Francis (Can. J. Fish. Aquat. Sci. 68, 1124–1138.) argues that abundance information should primarily come from indices of abundance and not from composition data. This is particularly true if the selectivity curve is not asymptotic. The selectivity diagnostic indicates a misspecification in selectivity when the associated composition component of the likelihood profile for R0 provides information about how low or how high R0 can be. The selectivity curve for the fishery or survey related to that composition data should be modified so that the composition data has little information on R0. We use simulation analysis roughly based on the stock assessment of bigeye tuna in the eastern Pacific Ocean to test how well the selectivity diagnostic works when selectivity is mispecified and if it incorrectly identifies selectivity misspecification when selectivity is specified correctly. We then apply the selectivity diagnostic to a stock assessment of swordfish in the Indian Ocean.