Fine-scale interplay between decline and growth determines the spatial recovery of coral communities within a reef

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Julie Vercelloni, Chris Roelfsema, Eva Kovacs, Manuel Gonzalez Rivero, Matt Moores, Murray Logan, Kerrie Mengersen


As coral reefs endure increasing levels of disturbance, understanding patterns of recovery following disturbance(s) is paramount to assessing the sustainability of these ecosystems. Given the slow dynamics of coral reefs and the increasing frequency of environmental pressures, management strategies focus on understanding recovery patterns to drive efforts and actively promote the recovery of key coral populations. However, the fine spatial scale heterogeneity of coral dynamics challenges our capacity to understand recovery patterns at large spatial scales and guide effective management actions. In this study, we developed a spatio-temporal statistical model to estimate the long-term trajectories of branching, plate and massive corals at fine-spatial scales and predict their recovery patterns at unobserved locations within a reef. We parameterized the model using repeated and georeferenced observations from 783 locations during 16 years at Heron Reef (Great Barrier Reef, Australia). We then developed indicators of recovery that capture the interplay between coral growth and relative decline from disturbance(s) across time, space and growth morphology. Our results reveal that successful recoveries, expressed in terms of probability, are associated with minimum growth rate thresholds of 4.3\% and 6.4\% (absolute growth, y-2) for branching and plate corals in reef locations that were impacted by disturbance(s) at medium-high levels and historically abundant. As a product of the data revolution, predictive maps from statistical models support the development of new indicators that can support the identification of areas of concern to prioritise management intervention. They should be used into larger spatially explicit modelling framework for decision-making in reef conservation and restoration.



Life Sciences


Branching coral, Coral cover, disturbance, management, mapping, resilience, restoration, Spatio-temporal modelling, Recovery indicators


Published: 2023-01-25 15:46


CC-BY Attribution-NonCommercial 4.0 International

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Conflict of interest statement:

Data and Code Availability Statement:
Data are already published and publicly available, with those items properly 20 cited in this submission. Data sets utilized for this research are as follows: https: 21 // (Roelfsema et al., 22 2019) and 23 (Roelfsema et al., 2021).

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