A machine learning-based evidence map of ocean-related options for climate change mitigation and adaptation
Veytia, Devi and Mariani, Gaël and Martí Barclay, Vicky and Airoldi, Laura and Claudet, Joachim and Cooley, Sarah and Magnan, Alexandre and Neill, Simon and Sumaila, U. Rashid and Thébaud, Olivier and Voolstra, Christian R. and Williamson, Phillip and Bonnin, Marie and Langridge, Joseph and Comte, Adrien and Viard, Frédérique and Shin, Yunne-Jai and Bopp, Laurent and Gattuso, Jean-Pierre (2025) A machine learning-based evidence map of ocean-related options for climate change mitigation and adaptation. npj Ocean Sustainability, 4 (1). 60. ISSN 2731-426X (https://doi.org/10.1038/s44183-025-00159-w)
Preview |
Text.
Filename: Veytia-etal-2025-A-machine-learning-based-evidence-map-of-ocean-related-options.pdf
Final Published Version License:
Download (3MB)| Preview |
Abstract
The ocean has a vital role to play in addressing the global challenge of climate change, which requires both mitigation and adaptation actions. The exponential increase in research relating to ocean-related options (OROs) requires a rapid and reproducible method to assess the state of knowledge. We train a state-of-the-art large language model to characterise the landscape of ORO research by classifying 44,193 (±11,615) articles across various descriptors. Research proves to be unevenly distributed, concentrating on OROs with mitigation objectives (80%), while revealing research gaps including under-researched ecosystems and an observed paucity of studies simultaneously assessing different ORO types. We also uncover social inequalities driven by mismatches between the global distribution of research effort, climate change responsibility, and risk. These findings are important to maximise the efficacy of OROs, position them within broader climate action portfolios, and inform future research priorities.
ORCID iDs
Veytia, Devi, Mariani, Gaël, Martí Barclay, Vicky
ORCID: https://orcid.org/0000-0001-9547-3377, Airoldi, Laura, Claudet, Joachim, Cooley, Sarah, Magnan, Alexandre, Neill, Simon, Sumaila, U. Rashid, Thébaud, Olivier, Voolstra, Christian R., Williamson, Phillip, Bonnin, Marie, Langridge, Joseph, Comte, Adrien, Viard, Frédérique, Shin, Yunne-Jai, Bopp, Laurent and Gattuso, Jean-Pierre;
-
-
Item type: Article ID code: 94773 Dates: DateEvent19 November 2025Published25 September 2025Accepted5 December 2024SubmittedSubjects: Science > Mathematics > Electronic computers. Computer science > Other topics, A-Z > Human-computer interaction
Geography. Anthropology. Recreation > Environmental SciencesDepartment: Faculty of Engineering > Civil and Environmental Engineering Depositing user: Pure Administrator Date deposited: 20 Nov 2025 09:58 Last modified: 03 Feb 2026 01:26 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/94773
Tools
Tools






