Bren School of Environmental Science and Management, University of California, Santa Barbara, CA, 93106, USA.
UPVD-CNRS, Centre de Formation et de Recherche sur les Environnements Méditerranéens, UMR 5110, 52 avenue Paul Alduy, 66860, Perpignan, France.
Ecol Lett. 2018 Dec;21(12):1790-1799. doi: 10.1111/ele.13153. Epub 2018 Sep 11.
Predicting whether, how, and to what degree communities recover from disturbance remain major challenges in ecology. To predict recovery of coral communities we applied field survey data of early recovery dynamics to a multi-species integral projection model that captured key demographic processes driving coral population trajectories, notably density-dependent larval recruitment. After testing model predictions against field observations, we updated the model to generate projections of future coral communities. Our results indicated that communities distributed across an island landscape followed different recovery trajectories but would reassemble to pre-disturbed levels of coral abundance, composition, and size, thus demonstrating persistence in the provision of reef habitat and other ecosystem services. Our study indicates that coral community dynamics are predictable when accounting for the interplay between species life-history, environmental conditions, and density-dependence. We provide a quantitative framework for evaluating the ecological processes underlying community trajectory and characteristics important to ecosystem functioning.
预测群落能否以及以何种程度从干扰中恢复仍然是生态学中的主要挑战。为了预测珊瑚群落的恢复，我们将早期恢复动态的实地调查数据应用于多物种综合预测模型，该模型捕捉了驱动珊瑚种群轨迹的关键人口统计过程，特别是密度依赖的幼虫补充。在将模型预测与实地观测进行比较后，我们更新了模型以生成未来珊瑚群落的预测。我们的结果表明，分布在岛屿景观中的群落遵循不同的恢复轨迹，但会重新组合到珊瑚丰度、组成和大小达到干扰前的水平，从而证明了珊瑚礁栖息地和其他生态系统服务的持续存在。我们的研究表明，当考虑物种生活史、环境条件和密度依赖性之间的相互作用时，珊瑚群落动态是可以预测的。我们提供了一个定量框架，用于评估群落轨迹和对生态系统功能很重要的特征的生态过程。
