Priority coral conservation areas under global warming in the Amami Islands, Southern Japan

Abe, Hiroya; Kumagai, Naoki H.; Yamano, Hiroya

doi:10.1007/s00338-022-02309-9

Cited by 3 publications

(1 citation statement)

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“…Another integrated linear extension rates of corals from three different islands in the same region with future SSTs to forecast coral growth rates 98 . One study used historical bleaching and sea surface temperature records to project future bleaching probabilities in the Indo-Pacific 99 , while another regional-scale study focused on larval connectivity and identified conservation areas with lower risks of coral bleaching in the Amani Islands of southern Japan 100 .…”

Section: Resultsmentioning

confidence: 99%

Systematic review of the uncertainty of coral reef futures under climate change

Klein,

Roch,

Duarte

2024

Nat Commun

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Climate change impact syntheses, such as those by the Intergovernmental Panel on Climate Change, consistently assert that limiting global warming to 1.5 °C is unlikely to safeguard most of the world’s coral reefs. This prognosis is primarily based on a small subset of available models that apply similar ‘excess heat’ threshold methodologies. Our systematic review of 79 articles projecting coral reef responses to climate change revealed five main methods. ‘Excess heat’ models constituted one third (32%) of all studies but attracted a disproportionate share (68%) of citations in the field. Most methods relied on deterministic cause-and-effect rules rather than probabilistic relationships, impeding the field’s ability to estimate uncertainty. To synthesize the available projections, we aimed to identify models with comparable outputs. However, divergent choices in model outputs and scenarios limited the analysis to a fraction of available studies. We found substantial discrepancies in the projected impacts, indicating that the subset of articles serving as a basis for climate change syntheses may project more severe consequences than other studies and methodologies. Drawing on insights from other fields, we propose methods to incorporate uncertainty into deterministic modeling approaches and propose a multi-model ensemble approach to generating probabilistic projections for coral reef futures.

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Section: Resultsmentioning

confidence: 99%