"Handling uncertainty in fisheries management: Developing tools in support of Management Strategy Evaluation" presented by Amanda R. Hart

Monday, April 27, 2026 at 1:30pm to 2:30pm

Department of Fisheries Oceanography

PhD Dissertation Defense
"Handling uncertainty in fisheries management: Developing tools in support of Management Strategy Evaluation"
By: Amanda R. Hart

Advisor
Dr. Gavin Fay (UMass Dartmouth)

Committee Members

Dr. Steven X. Cadrin (UMass Dartmouth), Dr. Lauran Brewster (UMass Dartmouth), Dr. Geret DePiper (Texas A&M University Corpus Christi), and Dr. Allan Hicks (International Pacific Halibut Commission)

Monday April 27, 2026
1:30 PM
SMAST East 101-103
836 S. Rodney French Blvd, New Bedford
and via Zoom

Abstract:

Sustainable fisheries management requires an understanding of interactions between fish, marine environments, fishing activities, and fisheries governance. Managing with imperfect information about these interactions can result in undesirable differences between the expected and realized management outcomes. Management Strategy Evaluation (MSE) is a model simulation method that rigorously tests management alternatives before they are implemented to help align expected and realized management outcomes. Tests can be conducted in the context of natural variability, uncertain stock status, and imperfect management implementation to assess potential trade-offs between management alternatives and identify alternatives that are robust to these uncertainties. The goal of this dissertation is to develop tools that support the integration of MSE into existing management processes, using three case studies from the Northeast U.S. as examples.

Chapter 1 demonstrates the viability of statistical tree analysis to synthesize MSE results for an Ecosystem-Based Fisheries Management (EBFM) case study. Chapter 2 expands the realism of this MSE framework to include technical interactions for multi-species groundfish fisheries and assess their impact on EBFM performance. Chapter 3 develops a novel visualization tool to communicate MSE outcomes for Atlantic herring. These studies highlight opportunities to advance MSE applications to support both scientific and regulatory decision making by improving workflow reproducibility, streamlining results communication and leveraging synchronicity between MSE and EBFM to advance modeling.

Join Meeting
https://umassd.zoom.us/j/94634734564
Note: Meeting ID and passcode required, email contact to obtain
For additional information, please contact Callie Rumbut at c.rumbut@umassd.edu

SMAST East 101-103 : 836 S. Rodney French Boulevard, New Bedford MA 02744
Callie Rumbut
c.rumbut@umassd.edu
https://umassd.zoom.us/j/94634734564