Bio-optical signatures of in situ photosymbionts predict bleaching severity prior to thermal stress in the Caribbean coral species Acropora palmata

The identification of bleaching tolerant traits among individual corals is a major focus for many restoration and conservation initiatives but often relies on large scale or high-throughput experimental manipulations which may not be accessible to many front-line restoration practitioners. Here, we...

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Bibliographic Details
Published in:Coral reefs 2024-02, Vol.43 (1), p.151-164
Main Authors: Hoadley, Kenneth D., Lowry, Sean, McQuagge, Audrey, Dalessandri, Shannon, Lockridge, Grant, O’Donnell, Sibelle, Elder, Holland, Ruggeri, Maria, Karabelas, Eleftherios, Klepac, Courtney, Kenkel, Carly, Muller, Erinn M.
Format: Article
Language:English
Subjects:
Absorbance
Acropora palmata
Algorithms
Biomedical and Life Sciences
Bleaching
Chlorophyll
Chlorophyll a
Clusters
Coral reefs
Corals
Fluorescence
Freshwater & Marine Ecology
Genotypes
Life Sciences
Light effects
Machine learning
Oceanography
Phenotypes
Physiology
Prediction models
Resampling
Restoration
Symbionts
Thermal stress
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Summary:The identification of bleaching tolerant traits among individual corals is a major focus for many restoration and conservation initiatives but often relies on large scale or high-throughput experimental manipulations which may not be accessible to many front-line restoration practitioners. Here, we evaluate a machine learning technique to generate a predictive model which estimates bleaching severity using non-destructive chlorophyll-a fluorescence photo-physiological metrics measured with a low-cost and open access bio-optical tool. First, a 4-week long thermal bleaching experiment was performed on 156 genotypes of Acropora palmata at a land-based restoration facility. Resulting bleaching responses (percent change in Fv/Fm or Absorbance) significantly differed across the four distinct light-response phenotypes (clusters) generated via a photo-physiology-based dendrogram, indicating strong concordance between fluorescence-based photo-physiological metrics and future bleaching severity. The proportion of thermally tolerant Clade D symbionts also differed significantly across photo-physiology-based dendrogram clusters, linking light-response phenotypes and bleaching response with underlying symbiont species. Next, these correlations were used to train and then test a Random Forest algorithm-based model using a bootstrap resampling technique. Correlation between predicted and actual bleaching responses in test corals was significant ( p  
ISSN:0722-4028
1432-0975
DOI:10.1007/s00338-023-02458-5