Navigating the blue frontier: A review of machine learning approaches for sustainable marine bioresource utilization

The sustainable management and utilization of marine bioresources faces increasing challenges due to environmental variability, data scarcity, and the complexity of marine ecosystems. Addressing these issues demands advanced technological methods that enhance efficiency, precision, and environmental management. This review aims to examine how machine learning (ML) is transforming the field of marine bioresources by enabling precise species tracking, early detection of harmful algal blooms, rapid identification of bioactive compounds, and innovations in biofuels and sustainable fisheries. The novelty of this review lies in synthesizing recent developments in ML applications across these domains while critically analyzing emerging paradigms of hybrid and interpretable ML models. It highlights key algorithms, including artificial neural networks, random forests, gradient boosting, support vector machines, and adaptive neuro-fuzzy inference systems, emphasizing their potential to improve scalability and prediction performance. The review provides discussions on unresolved challenges, ethical integration pathways, and future directions for sustainable marine bioeconomy practices. Besides technological progress, the review highlights a governance and ethics perspective, emphasizing the need to align ML applications with ocean governance frameworks, environmental laws, and principles of social and ecological justice. By connecting technological innovation with institutional responsibility, this work provides a comprehensive roadmap for developing ML-driven systems that support rather than undermine ocean stewardship. • Review of machine learning uses in marine bioresource research and industries • Focus on ML methods for species ID, biofuel, fisheries, and algal bloom forecasts • Discusses data, interpretability, and real-time sensor integration challenges • Links ML progress with ocean governance, environmental law, and social justice.