Weissmann Haim, Shnerb Nadav M
Department of Physics, Bar-Ilan University, Ramat-Gan IL52900, Israel.
Department of Physics, Bar-Ilan University, Ramat-Gan IL52900, Israel.
J Theor Biol. 2016 May 21;397:128-34. doi: 10.1016/j.jtbi.2016.02.033. Epub 2016 Mar 9.
Catastrophic shifts are known to pose a serious threat to ecology, and a reliable set of early warning indicators is desperately needed. However, the tools suggested so far have two problems. First, they cannot discriminate between a smooth transition and an imminent irreversible shift. Second, they aimed at predicting the tipping point where a state loses its stability, but in noisy spatial system the actual transition occurs when an alternative state invades. Here we suggest a cluster tracking technique that solves both problems, distinguishing between smooth and catastrophic transitions and to identify an imminent shift in both cases. Our method may allow for the prediction, and thus hopefully the prevention of such transitions, avoiding their destructive outcomes.
已知灾难性转变会对生态构成严重威胁，因此迫切需要一套可靠的早期预警指标。然而，到目前为止所提出的工具存在两个问题。第一，它们无法区分平稳过渡和即将发生的不可逆转变。第二，它们旨在预测一种状态失去稳定性的临界点，但在有噪声的空间系统中，当一种替代状态侵入时实际转变才会发生。在此，我们提出一种聚类跟踪技术，该技术能解决这两个问题，区分平稳转变和灾难性转变，并在两种情况下识别即将发生的转变。我们的方法可能有助于预测，从而有望预防此类转变，避免其破坏性后果。
