Doncaster C Patrick, Alonso Chávez Vasthi, Viguier Clément, Wang Rong, Zhang Enlou, Dong Xuhui, Dearing John A, Langdon Peter G, Dyke James G
Biological Sciences, Institute for Life Sciences, University of Southampton, Southampton, SO17 1BJ, UK.
Institute for Complex Systems Simulation, University of Southampton, Southampton, SO17 1BJ, UK.
Ecology. 2016 Nov;97(11):3079-3090. doi: 10.1002/ecy.1558.
Global environmental change presents a clear need for improved leading indicators of critical transitions, especially those that can be generated from compositional data and that work in empirical cases. Ecological theory of community dynamics under environmental forcing predicts an early replacement of slowly replicating and weakly competitive "canary" species by slowly replicating but strongly competitive "keystone" species. Further forcing leads to the eventual collapse of the keystone species as they are replaced by weakly competitive but fast-replicating "weedy" species in a critical transition to a significantly different state. We identify a diagnostic signal of these changes in the coefficients of a correlation between compositional disorder and biodiversity. Compositional disorder measures unpredictability in the composition of a community, while biodiversity measures the amount of species in the community. In a stochastic simulation, sequential correlations over time switch from positive to negative as keystones prevail over canaries, and back to positive with domination of weedy species. The model finds support in empirical tests on multi-decadal time series of fossil diatom and chironomid communities from lakes in China. The characteristic switch from positive to negative correlation coefficients occurs for both communities up to three decades preceding a critical transition to a sustained alternate state. This signal is robust to unequal time increments that beset the identification of early-warning signals from other metrics.
全球环境变化明确表明需要改进关键转变的领先指标,尤其是那些可以从成分数据生成且适用于实证案例的指标。环境胁迫下群落动态的生态理论预测,缓慢繁殖且竞争力弱的“金丝雀”物种会被缓慢繁殖但竞争力强的“关键”物种早期取代。进一步的胁迫会导致关键物种最终崩溃,因为在向显著不同状态的关键转变中,它们被竞争力弱但繁殖快的“杂草”物种所取代。我们在成分无序与生物多样性之间的相关性系数中识别出这些变化的诊断信号。成分无序衡量群落组成的不可预测性,而生物多样性衡量群落中的物种数量。在随机模拟中,随着关键物种超过金丝雀物种,随时间的序列相关性从正变为负,随着杂草物种占主导又变回正。该模型在中国湖泊中硅藻和摇蚊化石群落的数十年时间序列实证测试中得到了支持。在向持续交替状态的关键转变前长达三十年的时间里,两个群落的相关系数都出现了从正到负的特征性转变。该信号对于困扰从其他指标识别预警信号的不等时间增量具有鲁棒性。