The use of Artificial Intelligence (AI) systems in enhancing sustainable management and utilization of fisheries resources

Artificial Intelligence (AI) encompasses machine systems’ ability to learn, apply knowledge, and make intelligent actions, heralding significant transformations across various industries. In the field of fisheries, AI applications are particularly promising, given the critical challenges such industries face. These include overfishing, illegal fishing activities, and environmental pressures like pollution and climate change, which jeopardize the stability of marine ecosystems. The recent upsurge in AI utilization across sectors reflects a growing recognition of its potential to boost efficiency, spark innovation, and mitigate human error, thereby reshaping employment landscapes and expanding our capabilities.

This Research Topic aims to explore the innovative applications of AI in enhancing the management and conservation of fisheries resources globally. It seeks to uncover how AI can be applied to address the multifaceted challenges faced by wild capture fisheries, which are vital yet vulnerable sectors due to excessive fishing pressures, environmental degradation, and regulatory challenges. With about 25% of global fish stocks depleted or overexploited, and unlawful fishing practices persisting, there is a pressing need for more robust, AI-enhanced management systems that can lead to sustainable fishing practices.

To gather further insights in the potential of AI within fisheries science, we welcome articles addressing, but not limited to, the following themes:

• Bycatch management
• Monitoring, control, and surveillance systems
• Implementation of electronic and vessel monitoring systems
• Species identification for better stock management
• Tackling illegal, unreported, and unregulated (IUU) fishing
• Data-driven approaches for sustainable fishing
• Management of protected areas and habitat preservation
• Strategies for biodiversity conservation
• Policy formulation and governance improvements
• AI-driven solutions for climate change adaptation in fisheries

Existing initiatives such as the deployment of observers, fleet monitoring systems, and seasonal or area-based fishing restrictions underscore the ongoing efforts to enhance fisheries management, but AI offers an avenue to significantly elevate these measures. Manuscripts that showcase novel AI applications, demonstrate effectiveness, and articulate benefits for stakeholders are particularly encouraged, fostering a future where fisheries management aligns closely with ecological sustainability and economic needs.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Community Case Study
• Curriculum, Instruction, and Pedagogy
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Community Case Study
• Curriculum, Instruction, and Pedagogy
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy and Practice Reviews
• Policy Brief
• Review
• Systematic Review
• Technology and Code

Keywords: Sustainable, fisheries management, fisheries, monitoring, technology, conservation

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.