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Article ? AI-assigned paper type based on the abstract. Classification may not be perfect — flag errors using the feedback button. Tier 2 ? Original research — experimental, observational, or case-control study. Direct primary evidence. Marine & Wildlife Policy & Risk Sign in to save

Technology, Data and New Models for Sustainably Managing Ocean Resources

2023 17 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 45 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Jane Lubchenco, Jane Lubchenco, Jane Lubchenco, Jane Lubchenco, Peter M. Haugan, Peter M. Haugan, Mark Abbott, Peter M. Haugan, Hide Sakaguchi, Peter M. Haugan, Annie Brett, Peter M. Haugan, Ling Cao, Ling Cao, Jane Lubchenco, Kevin Chand, Yimnang Golbuu, Ling Cao, Tara Martin, Juan Mayorga, Mari S. Myksvoll

Summary

This review examines how exponential growth in ocean observing systems, satellite data, and machine learning is transforming the management of ocean resources, enabling more precise monitoring of fisheries, ecosystems, and pollution. The authors argue that new data models are essential for sustainable stewardship of global ocean resources.

Study Type Environmental

Abstract We are in the middle of an explosion in new data on the ocean, creating enormous potential for advances in our understanding and stewardship of ocean resources. An exponential increase in the number and variety of ocean observing systems and other new data sources has created the prospect of a digital ocean ecosystem. Advances in processing techniques and visualisation are rapidly expanding our ability to extract information from those data, and are enabling a wide array of tools to provide real-time information in actionable form to decision-makers, such as policymakers, resource managers, resource users, consumers and citizens.

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