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    Modelling for management: Coral photo-physiology and growth potential under varying turbidity regimes

    Access Status
    Fulltext not available
    Authors
    Larsen, T.
    Browne, Nicola
    Erichsen, A.
    Tun, K.
    Todd, P.
    Date
    2017
    Type
    Journal Article
    
    Metadata
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    Citation
    Larsen, T. and Browne, N. and Erichsen, A. and Tun, K. and Todd, P. 2017. Modelling for management: Coral photo-physiology and growth potential under varying turbidity regimes. Ecological Modelling. 362: pp. 1-12.
    Source Title
    Ecological Modelling
    DOI
    10.1016/j.ecolmodel.2017.08.018
    ISSN
    0304-3800
    School
    Department of Environment and Agriculture
    URI
    http://hdl.handle.net/20.500.11937/56931
    Collection
    • Curtin Research Publications
    Abstract

    Suspended and deposited sediments can negatively impact coral health by reducing light penetration and smothering coral tissue. As coral sediment thresholds vary among species and between locations, setting sediment thresholds for the management of activities that increase sediment loads continues to be a challenging goal. Static threshold values used to date do not take into account temporal and spatial variations in a coral's ability to acclimate to high sediment loads leading to either management approaches that are overly conservative or do not protect corals. This study presents a numerical model that quantifies the relationship between coral photosynthesis and growth potential under varying turbidity-driven light regimes. The model accounts for coral acclimation potential as well as a dynamic energy transfer between host and symbiont using field data collected from nearshore reefs in Singapore combined with both established and novel mathematical relationships. The model yielded photosynthetic and respiratory outputs that were comparable to in situ data collected, illustrating the predictive capability of modelling coral growth potential to declines in light driven by suspended sediments. The inclusion of more than one coral species into the model allows for variations in responses to sediments among different coral morphologies and taxa, and will strengthen the predictive capacity for management of sediment related events. As demonstrated here, the model can be used to identify least risk scenarios for dredging operations as a means of both conserving coral reefs as well as ensuring cost-effective management practices.

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