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.

翻译：珊瑚礁正日益面临威胁海洋生态系统健康的重大干扰。目前正在进行大量研究，以制定干预策略，帮助珊瑚礁从未来不可避免的气候和天气极端事件中恢复并增强其抵抗力。为评估干预措施的潜在效益，对珊瑚礁恢复和抵抗模式的机理理解至关重要。近期证据表明，当初始珊瑚覆盖率较低（$\leq 10$\%）时，大堡礁（GBR）超过一半的受调查礁体表现出与标准恢复建模假设的偏离。需要建立新模型以解释这些观测到的模式，从而为管理策略提供更优信息。我们提出一种在珊瑚覆盖率尺度上解释双相恢复模式的新礁体恢复模型。该模型基于多物种Richards生长模型，并在恢复模式中引入了一个变点。采用贝叶斯推断对评估礁体健康与恢复模式的关键参数进行不确定性量化。此分析应用于澳大利亚海洋科学研究所（AIMS）的底栖调查数据。我们证明，对于1992年至2020年间发生干扰事件后至少具有两年观测记录的每条恢复轨迹，模型预测与数据均呈现一致性。这一新方法将有助于深入理解影响大堡礁双相珊瑚恢复模式持续时间和严重程度的生物、生态及环境因素。这些新见解将为管理和监测实践提供信息，以减轻气候变化对珊瑚礁的影响。