  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
($\leq 10$\%). 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 model that
includes a change point in the recovery patterns. Bayesian inference is applied
for uncertainty quantification of key parameters for assessing reef health and
recovery patterns. This analysis is applied to benthic survey data from the
Australian Institute of Marine Sciences (AIMS). We demonstrate agreement
between model predictions and data across every recorded recovery trajectory
with at least two years of observations following disturbance events occurring
between 1992--2020. This new approach will enable new insights into the
biological, ecological and environmental factors that contribute to the
duration and severity of biphasic coral recovery patterns across the GBR. These
new insights will help to inform managements and monitoring practice to
mitigate the impacts of climate change on coral reefs.
