Mathematical modelling and uncertainty quantification for analysis of biphasic coral reef recovery patterns
David J. Warne, Kerryn Crossman, Grace E. M. Heron, Jesse A. Sharp, Wang Jin, Paul Pao-Yen Wu, Matthew J. Simpson, Kerrie Mengersen, Juan-Carlos Ortiz

TL;DR
This paper introduces a biphasic coral reef recovery model using Bayesian inference to better understand and predict recovery patterns, aiding management strategies amid climate change impacts.
Contribution
A novel biphasic recovery model based on Richards' growth with change points, applied to GBR data for improved uncertainty quantification and understanding of coral recovery.
Findings
Model predictions align with observed recovery trajectories.
Biphasic recovery patterns are prevalent in GBR reefs.
Uncertainty quantification enhances understanding of recovery dynamics.
Abstract
Coral reefs are increasingly subjected to major disturbances threatening the health of marine ecosystems. Substantial research underway to develop intervention strategies that assist reefs in recovery from, and resistance to, inevitable future climate and weather extremes. To assess potential benefits of interventions, mechanistic understanding of coral reef recovery and resistance patterns is essential. Recent evidence suggests that more than half of the reefs surveyed across the Great Barrier Reef (GBR) exhibit deviations from standard recovery modelling assumptions when the initial coral cover is low (\%). New modelling is necessary to account for these observed patterns to better inform management strategies. We consider a new model for reef recovery at the coral cover scale that accounts for biphasic recovery patterns. The model is based on a multispecies Richards' growth…
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Taxonomy
TopicsReservoir Engineering and Simulation Methods
