User-Participatory Management Strategy Evaluation for North Pacific Albacore Tuna Harvest using Multi-Criteria Decision Analysis

Keywords:  North Pacific Albacore, Harvest Control Rule, Sensitivity Analysis, TOPSIS, Decision Support, Multi-Criteria Decision Model
Abstract Type: Paper Abstract

Abstract

The north pacific albacore tuna constitutes a major portion of the fish industry of the west coast of the United State. Its harvest strategies depend not only on the biological properties of the local species, such as seasonality and migration patterns, the natural environment, such as the ocean flow current and temperature change, but also on the preferences of region managers, stakeholders, and the local fisherman community. Inspired by the need of better transparency and efficiency of Harvest Control Rules (HCR), A MSE tool is previously developed with 5 quantified management objectives, but the final HCR rankings currently only base on a weighted sum algorithm. While having certain merits such as intuitiveness and computational efficiency, the weighted sum algorithm often dooe not yield the most reflective results of the best interest. In this article, we propose Technique for Order Preference by Similarity to Ideal Solution Method (TOPSIS) as efficient alternative algorithms for HCR decisions and conduct a sensitivity analysis among management objectives under the current framework. Two initial conclusion are drawn: (1) The alteration in the overall ranking of HCRs is present, and its influence could be substantial depending on the user preference. (2) It's common to notice ranking shifts in the ranking for higher-ranked HCRs, which contributes valuable insights for practical decision-making.