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A robustness metric integrating spatial and temporal information: application to coral reefs exposed to local and regional disturbances

机译：结合时空信息的鲁棒性指标：应用于暴露于局部和区域干扰的珊瑚礁

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摘要

Capturing complex ecosystem dynamics through aggregate metrics is challenging, especially against a background of climate instability and local disturbances. Robustness, a key determinant of long-term success or failure, is particularly awkward to distil, because it also conveys many different meanings. Hence, metrics tend to be limited or specialised. Herein we develop an index (Q) which captures one aspect of robustness and, unusually, integrates both spatial and temporal information. Qis defined as the probability that the value of a macroscopic system feature remains above a specified fraction of 'baseline' condition, at a proportion of spatial localities sampled over time. As a test case we analyse coral cover from a long-term survey in Thailand. Sites were subjected to dredging effects in 1986 an 1987 (Sites A and B), elevated sea temperatures and depressed sea levels especially in 1997 and 1998 (Sites A, B and C) following climate related events in the Indian Ocean. Sites A and C have similar Q values, because they experienced similar levels of overall disturbance, albeit different types of disturbance. We show that this metric can also assess specific (e.g. climate related) disturbances. The cut-off value of Q for declaring a system robust is arbitrary. However, our analyses support recent biodiversity studies that used the same coral data set, which suggest remarkable robustness of these reef flats to adverse environmental conditions. Our metric could potentially also quantify change in composition of process oriented features, such as key functional groups, a better proximal determinant of robustness of reefs to hurricanes and other agents of environmental change than coral cover. Probabilistic measures similar to Q could have even wider application, for example to quantify feedback and self-regulation. In a greenhouse world, this behaviour in ecosystems may become increasingly significant.
机译：通过总体指标来捕获复杂的生态系统动态是一项挑战，特别是在气候不稳定和局部干扰的背景下。鲁棒性是长期成功或失败的关键决定因素，因为它还传达了许多不同的含义，因此特别难以解决。因此，指标往往受到限制或专门化。在本文中，我们开发了一个索引（Q），该索引捕获了鲁棒性的一个方面，并且异常地整合了时空信息。 Qis定义为宏观系统特征的值在一定比例的空间局部性随时间推移而保持在“基准”条件的指定分数以上的概率。作为测试案例，我们从泰国的一项长期调查中分析了珊瑚的覆盖率。在印度洋发生与气候有关的事件后，这些站点在1986年和1987年（站点A和B），海水温度升高和海平面下降（尤其是1997和1998年）（站点A，B和C）受到疏dr影响。站点A和站点C具有相似的Q值，因为尽管受到了不同类型的干扰，但它们受到的整体干扰水平相似。我们表明，该指标还可以评估特定的（例如与气候相关的）干扰。用于声明系统鲁棒性的Q的截止值是任意的。但是，我们的分析支持最近的生物多样性研究，该研究使用了相同的珊瑚数据集，这表明这些礁滩对恶劣的环境条件具有显着的鲁棒性。我们的指标还可能量化面向过程的特征（例如关键功能组）的组成变化，这是珊瑚礁对飓风和其他环境变化因素的健壮性的近端决定因素，而不是珊瑚覆盖。类似于Q的概率度量可能具有更广泛的应用，例如量化反馈和自我调节。在温室世界中，生态系统中的这种行为可能变得越来越重要。

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