**ABSTRACT NOT FOR CITATION WITHOUT AUTHOR PERMISSION. The title, authors, and abstract for this completion report are provided below. For a copy of the full completion report, please contact the author via e-mail at email@example.com. Questions? Contact the GLFC via email at firstname.lastname@example.org or via telephone at 734-662-3209.**
Jiao, Y. and C. Zhou
1 Department of Fish and Wildlife Conservation, Virginia Tech University, 540-231-5749
Natural mortality (M) has been found to be one of the most uncertain and most influential parameters in walleye fisheries stock assessment which needs to be addressed. The difficulty to estimate M arises from model structure, data uncertainty and the confounding effect from other parameters in the model. How to treat M in stock assessment models is a controversial topic involving considerations on both the degree of realism in the model structure and the amount of information available on M in the data. In our study, we integrate tagging, catch, and survey data to estimate Lake Erie walleye M through a Bayesian approach. Catch and abundance indices were modeled following the basic structure of the current assessment model, tag-recapture was modeled using the traditional Brownie process, and the age-length distributions of tagged fish were inferred through a concurrent biological survey. Four types of hypotheses on the variation of M were integrated in the SCA modeling framework of walleye and these hypotheses on M are: a) M is constant over time and age but is unknown; b) M changes over age; c) M changes over time; d) M changes over both age and time. We first analyzed M based on tagging data and based on catch-at-age data separately, which both suggested temporal and age-specific variations in M. Then, we integrated these two sources of data, and the integrated model yielded consistent parameter estimates with reduced uncertainty for M and other primary population quantities, such as abundances. This study provides evidence on the temporal and age class variations in Lake Erie walleye M. Factors that may cause the variation of M over age and/or time were related to climate changes and/or predator abundance, and were further tested. Walleye natural mortality variation tends to be influence by multiple factors and may vary over time because of the variations in the ecosystem characteristics in Lake Erie. The incorporation of extra tagging information facilitates improvement of estimation of critical population parameters in the assessment model. Extra simulation studies were conducted to verify the robustness of the supported hypothesis and illustrate the possible misunderstanding of walleye population dynamics and management. Our study also provided a framework for modeling M within an integrated assessment context for Lake Erie walleye.