Badillo-Interiano, M., Rohmer, J., Le Cozannet, G., and Duvat, V. Assessing atoll island future habitability in the context of climate change using Bayesian networks, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2024-3884, 2025.
Atoll islands are threatened by multiple climate change impacts, such as sea-level rise, extreme sea-level events, ocean warming, and acidification. A recent approach to assessing climate change risk to these islands is to use multi-criteria expert judgment methods. These approaches can serve as a basis for the development of Bayesian Networks (BNs) 10 integrating expert knowledge and uncertainties to perform climate risk assessments. Here, we use the multi-criteria expert-based assessment of Duvat et al. (2021), who assessed future risk to habitability for four Indian and Pacific Oceans’ atoll islands, in order to discuss the advantages and limitations of the BN model. Advantages of the approach include the explicit treatment of uncertainties and the possibility to query expert knowledge in a non-trivial manner. For example, expert knowledge can be used to assess risks to habitability and future uncertainties and to explore inverse problems such as which 15 drivers can exceed specific risk thresholds. Our work suggests that BN, though requiring a certain level of implementation expertise, could be used to assess climate change risk and support climate adaptation.
Probability of the risk to habitability under the RCP 2.6 and RCP 8.5 scenarios in 2050 and 2090 for the four islands. In 2050, Malé, Tabiteuea, and Nolhivaranfaru show low to moderate risk, slightly higher under the RCP 8.5. In contrast, the risk to habitability is higher for Fogafale than for the other islands. In 2090, the risk remains low to moderate under RCP 2.6 except for Fongafale (moderate to high). In the RCP 8.5 scenario, all islands could experience moderate to high risk levels.