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Thursday, September 2, 2021. 3:00 PM. Webinar: State Space Stock Assessment Models: Previous Applications, Future Potential. Emily Liljestrand, Michigan State University. Sponsored by NOAA. Register here.

State-space modeling (SSM), in which the process variation is estimated independently from variation due to observation error, has been employed in fisheries stock assessment for decades. Software such as Template Model Builder (TMB) sparked new interest in SSM because theoretical advantages such as estimating error variances could be realized thanks to the computationally efficient integration of process error from the marginal likelihood. I use my own research in rewriting existing age-based assessment models of Lake Whitefish with SSM elements (e.g., multiple time-varying processes) to make broader conclusions about the applicability SSM.

Emily Liljestrand is a PhD candidate at Michigan State University in the Quantitative Fisheries Center, under the guidance of Dr. Jim Bence, and a NMFS-Sea Grant Joint Fellow under the mentorship of Dr. Jon Deroba. She is broadly interested in population dynamics and stock assessment modeling, and how alternative model design can influence accuracy and precision, and even how to quantify these qualities. Her favorite fish are coelacanths.