Centre for Networks and Collective Behaviour, Department of Mathematical Sciences, University of Bath, Bath, UK.
Beijing Institute of Radiation Medicine, Beijing, PR China.
Nat Commun. 2021 Jun 15;12(1):3625. doi: 10.1038/s41467-021-23757-x.
Understanding the relationship between complexity and stability in large dynamical systems-such as ecosystems-remains a key open question in complexity theory which has inspired a rich body of work developed over more than fifty years. The vast majority of this theory addresses asymptotic linear stability around equilibrium points, but the idea of 'stability' in fact has other uses in the empirical ecological literature. The important notion of 'temporal stability' describes the character of fluctuations in population dynamics, driven by intrinsic or extrinsic noise. Here we apply tools from random matrix theory to the problem of temporal stability, deriving analytical predictions for the fluctuation spectra of complex ecological networks. We show that different network structures leave distinct signatures in the spectrum of fluctuations, and demonstrate the application of our theory to the analysis of ecological time-series data of plankton abundances.
理解大型动力系统(如生态系统)中的复杂性和稳定性之间的关系,仍然是复杂性理论中的一个关键开放性问题,这一问题激发了五十多年来丰富的研究工作。该理论的绝大多数内容都涉及围绕平衡点的渐近线性稳定性,但实际上,“稳定性”这一概念在经验生态学文献中有其他用途。“时间稳定性”这一重要概念描述了由内在或外在噪声驱动的种群动力学波动的特征。在这里,我们将随机矩阵理论的工具应用于时间稳定性问题,为复杂生态网络的波动谱导出了分析预测。我们表明,不同的网络结构在波动谱中留下了不同的特征,并展示了我们的理论在分析浮游生物丰度的生态时间序列数据中的应用。