Abstract

Typically, population genetic information is applied to fisheries management in the delineation of stocks; however, this data can provide particular insight into the patterns of effective reproduction. In marine systems, effective population size is often seen to be much smaller than anticipated given species’ census size. Hypotheses relating shifts in population demography or large variation in underlying patterns of reproductive success are commonly invoked to explain this phenomenon. While we often observe the former in fisheries data, high levels of uncertainty surround the effect of the latter and assume it to be of principal importance. This approach leaves great ambiguity in our understanding of what drives population dynamics and genetics in marine systems. It also undermines our ability to expand the use of genetic data in determining when unappreciated mechanisms could lead to effective patterns in reproduction differing markedly from observations based on demography. Gag groupers, Mycteroperca microlepis, on the West Florida Shelf present an interesting case in this regard. Given the large amount of demographic data associated with stock assessment efforts and independent genetic data, we have the unique opportunity to assess these different hypotheses in a rigorous fashion and reconcile these data. With this intent, an Approximate Bayesian Compuational (ABC) approach is applied to an individual-based simulation model, which is parameterized on both genetic and demographic data. Modeling efforts reveal the strong influence of demographic changes on population genetics as well as likely important areas of uncertainty in the stock assessment description of gag life history.

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