Fisheries quota management plays a critical role in ensuring the sustainability of commercial fishing practices, particularly in the United States, where overfishing and resource depletion pose significant challenges to marine ecosystems. This review explores the mathematical approaches utilized to manage fisheries quotas effectively and sustainably. The paper examines key mathematical models, including population dynamics, bioeconomic models, game theory, and Catch-per-Unit-Effort (CPUE) models, highlighting their role in maintaining fish stock levels and regulating fishing activities. Through case studies from U.S. fisheries, such as the New England groundfish and Alaska pollock fisheries, the review assesses the effectiveness of these models in real-world applications. Additionally, it explores how advances in technology, such as satellite tracking, big data, and artificial intelligence, are enhancing the accuracy and adaptability of fisheries management models. The review concludes with insights into future directions for mathematical approaches in fisheries management, emphasizing the need for continuous innovation to support sustainable commercial fishing practices. By integrating advanced mathematical techniques and data-driven models, this paper aims to provide a pathway for policymakers and fisheries managers to achieve long-term sustainability in U.S. commercial fisheries.
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