Work

Advancing High‐Seas Fisheries Governance: Bayesian Models for Enhancing Compliance and Sustainability Under the BBNJ Agreement

Year: 2025

Type: article

Abstract: ABSTRACT High‐seas fisheries governance faces significant challenges due to transboundary complexities, enforcement limitations, and scientific uncertainties. The recently adopted Agreement on the Conservation and Sustainable Use of Marine Biological Diversity of Areas Beyond National Jurisdiction (BBNJ Agreement) represents a pivotal legal framework aimed at strengthening regulatory mechanisms. This study explores how Bayesian methodologies can enhance high‐seas fisheries governance by improving stock assessments, quota allocations, and compliance monitoring. Bayesian inference offers a probabilistic approach to decision‐making, integrating prior knowledge with real‐time data to optimize policy predictability and adaptive management. Through a case study approach, this research assesses the practical applicability of Bayesian models under the BBNJ framework, highlighting their potential to address legal and enforcement gaps while ensuring sustainability. The findings contribute to both legal and fisheries management scholarship, offering data‐driven recommendations for policymakers to enhance science‐based governance in areas beyond national jurisdiction.

Source: Fisheries Management and Ecology

DOI: 10.1111/fme.70042

Author: Ahmed Hany M. Abuelenin

Institution: King Abdulaziz University

Language: English

Topic: Marine and fisheries research

Subfield: Global and Planetary Change

Field: Environmental Science

Domain: Physical Sciences

SDGs: Life below water, Peace, justice, and strong institutions

Open Access status: hybrid

Estimated APC paid: $4,430