Speed Presentation 2024 Australian Marine Sciences Association Annual Meeting combined with NZMSS

Coral heat stress experiment and predictive modelling: An assessment of bleaching outcomes (#697)

Sophia L Ellis 1 , Mark E Baird 2 , Luke P Harrison 2 3 , Kai G Schulz 4 , Daniel P Harrison 1 5
  1. School of Environment Science and Engineering, Southern Cross University, Coffs Harbour, NSW, Australia
  2. CSIRO Environment, CSIRO, Hobart, TAS, Australia
  3. School of Aerospace, Mechanical and Mechatronic Engineering, University of Sydney, Sydney, NSW, Australia
  4. Centre for Coastal Oceanography, Southern Cross University, East Lismore, NSW, Australia
  5. School of Geosciences, University of Sydney, Sydney, NSW, Australia

Irradiance is critical to coral growth whilst also being an implicating factor in photodamage, resulting in the expulsion of symbiotic algae under increased temperatures. Numerical modelling is a valuable tool that can provide insight into the relative contribution of key processes and stressors during coral bleaching events. We describe using a process-based mechanistic and physiological model for designing a coral heat and light stress experiment. Model predicted bleaching outcomes were compared to photochemical bleaching parameters measured in a moderate degree-heating week experiment. The bleaching response of Acropora divaricata was assessed in an unshaded or 30% shade treatment. The model predicted timing for the onset of bleaching under elevated temperatures closely corresponded with an initial photochemical decline as observed in the experiment. Increased bleaching severity under elevated temperature and unshaded light was also predicted, an outcome confirmed in the experiment. This is the first experimental validation of a temperature-mediated, light-driven model of coral bleaching from the perspective of the symbiont. We demonstrate the utility of numerical modelling in predicting bleaching outcomes under multiple stressors. When forced by realistic environmental conditions, process-based mechanistic modelling could improve accuracy in predicting heterogeneous bleaching outcomes during contemporary events, and for future climate change scenarios.