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Monday, January 25 • 10:40am - 11:00am
Indexing Recruitment Fluctuations For Populations Contributing To Mixtures By Simultaneous Analysis of Age and Genetic Information

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AUTHORS: Travis Brenden*, Iyob Tsehaye, James Bence; Weihai Liu, Jeannette Kanefsky, Kim Scribner – Michigan State University

ABSTRACT: An understanding of recruitment variability in fish populations is considered critical for their effective management. Unfortunately, recruitment is also widely regarded as one of the more difficult rate functions to quantify. We describe an approach for estimating annual variation in recruitment levels for source populations contributing to mixtures. Our proposed approach incorporates age information into widely used model-based genetic stock identification analyses and can accommodate uncertainty arising from aging error. Whereas similar approaches have assumed that annual changes in recruitment levels of source populations are fairly consistent, our approach allows for annually fluctuating recruitment levels and therefore is more general. Stochastic simulations conducted to evaluate the performance of the proposed approach indicated a strong direct relationship between estimated and assumed recruitment levels. Accuracy and precision of the recruitment estimates were most influenced by mixture sample size and genetic divergence among source populations. Sensitivity analyses indicated that recruitment estimates were most sensitive to aging uncertainty. We use Saginaw Bay, Lake Huron walleye and Lake Michigan lake trout data to demonstrate empirical applications of our proposed approach. The results from the empirical applications are compared to recruitment estimates from statistical catch at age models (walleye) or historical stocking data (lake trout). We believe that this estimation approach could be applied in a variety of situations involving mixture fisheries and thus could be a widely applicable tool for managing populations.

Monday January 25, 2016 10:40am - 11:00am EST