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Department of Fisheries Oceanography PhD Dissertation Proposal Defense by Cole Carrano

When: Friday, February 2, 2024
9:00 AM - 10:00 AM
Where: > See description for location
Description: The School for Marine Science and Technology

The Department of Fisheries Oceanography

PhD Dissertation Defense

Title: Modeling Index Selectivity for Fishery Stock Assessments

by Cole Carrano

Abstract: Abundance indices are crucial components of fishery stock assessments because they provide a time series of relative abundance for estimating absolute stock size. Selectivity is the relative vulnerability to a fishery or fishery-independent survey for each species or demographic group within a species (e.g., size or age class). In an age-based assessment model, selectivity relates observed stock indices to model estimates of abundance at age. Thus, selectivity estimates must be carefully modeled to ensure an accurate depiction of the stock's age structure. The objectives of this research are to improve the accuracy and utilization of indices in fisheries stock assessment models by understanding the effect of alternative approaches to estimating index selectivity. Chapter One provides a general introduction to the topic and a review of the relevant literature. Chapter Two involves splitting a fishery-independent survey into two series to account for vessel and methodological changes by estimating distinct catchability and selectivity parameters for each series. Chapter Three develops fleet-structured assessment models to improve selectivity estimates for the fishery and the fishery-dependent indices. Chapter Four involves simulation cross-testing as a method to evaluate the effect of key structural differences in stock assessment models. This work examines how decisions about modeling fleet structure or changes in survey systems affect the performance of an assessment model and how sensitive models are to these decisions. This research will emphasize the importance of selectivity estimates to stock assessment and advance our understanding of how to effectively utilize abundance indices in an assessment model.

Dissertation Committee: Steve Cadrin (SMAST, Advisor), Pingguo He (SMAST), Gavin Fay (SMAST), Lisa Kerr (University of Maine)

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Contact: > See Description for contact information
Topical Areas: SMAST, Students, Graduate