Genetic Tools for Marine Fisheries Management

Traditional stock assessments rely on diverse tools and techniques to estimate the dynamics of fish populations and how they are impacted by fishing pressure. Population monitoring, via fisherydependent or -independent data sources, provides fisheries scientists with information critical for a stock assessment. However, commonly used methods can have substantial sources of uncertainty and bias. The use of novel genetic-based techniques in stock assessments is increasing rapidly and has the ability to provide comparable information more efficiently with substantially less uncertainty. For example, genetic tagging techniques and kinship analyses have the potential to allow fisheries scientists to estimate stock dynamics with less uncertainty and bias than traditional stock assessments alone. In this study, I will 1) develop a tagging simulator to determine the feasibility of genetic and conventional based tagging approaches to estimate exploitation rates for the U.S. South Atlantic red snapper fishery; 2) explore sensitivity of abundance estimates from close-kin mark-recapture (CKMR) to uncertainty in life history and fishery parameters; and, 3) investigate the utility of kinship data within a CKMR framework to estimate changes in population abundance over time. During the requested 2 years of support, I aim to explore these approaches by developing an operating population model integrated with an individual based model, linking it to a CKMR simulation model, and assessing the utility of genetic tools to inform age-structured stock assessments, interim analyses, and management.