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Predictive models for the selection of thermally tolerant corals based on offspring survival

Author

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  • K. M. Quigley

    (Australian Institute of Marine Science)

  • M. J. H. Oppen

    (Australian Institute of Marine Science
    The University of Melbourne)

Abstract

Finding coral reefs resilient to climate warming is challenging given the large spatial scale of reef ecosystems. Methods are needed to predict the location of corals with heritable tolerance to high temperatures. Here, we combine Great Barrier Reef-scale remote sensing with breeding experiments that estimate larval and juvenile coral survival under exposure to high temperatures. Using reproductive corals collected from the northern and central Great Barrier Reef, we develop forecasting models to locate reefs harbouring corals capable of producing offspring with increased heat tolerance of an additional 3.4° heating weeks (~3 °C). Our findings predict hundreds of reefs (~7.5%) may be home to corals that have high and heritable heat-tolerance in habitats with high daily and annual temperature ranges and historically variable heat stress. The locations identified represent targets for protection and consideration as a source of corals for use in restoration of degraded reefs given their potential to resist climate change impacts and repopulate reefs with tolerant offspring.

Suggested Citation

  • K. M. Quigley & M. J. H. Oppen, 2022. "Predictive models for the selection of thermally tolerant corals based on offspring survival," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-28956-8
    DOI: 10.1038/s41467-022-28956-8
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    1. Marie E. Strader & Kate M. Quigley, 2022. "The role of gene expression and symbiosis in reef-building coral acquired heat tolerance," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
    2. Yunhe Hong & Nicholas Birse & Brian Quinn & Yicong Li & Wenyang Jia & Philip McCarron & Di Wu & Gonçalo Rosas Silva & Lynn Vanhaecke & Saskia Ruth & Christopher T. Elliott, 2023. "Data fusion and multivariate analysis for food authenticity analysis," Nature Communications, Nature, vol. 14(1), pages 1-14, December.

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