There is a growing recognition that ecological systems can spend extended periods of time far away from an asymptotic state, and that ecological understanding will therefore require a deeper appreciation for how long ecological transients arise. Recent work has defined classes of deterministic mechanisms that can lead to long transients. Given the ubiquity of stochasticity in ecological systems, a similar systematic treatment of transients that includes the influence of stochasticity is important. Stochasticity can of course promote the appearance of transient dynamics by preventing systems from settling permanently near their asymptotic state, but stochasticity also interacts with deterministic features to create qualitatively new dynamics. As such, stochasticity may shorten, extend or fundamentally change a system’s transient dynamics. Here, we describe a general framework that is developing for understanding the range of possible outcomes when random processes impact the dynamics of ecological systems over realistic time scales. We emphasize that we can understand the ways in which stochasticity can either extend or reduce the lifetime of transients by studying the interactions between the stochastic and deterministic processes present, and we summarize both the current state of knowledge and avenues for future advances.

人们越来越认识到，生态系统可以在远离渐近状态的地方度过很长一段时间，因此生态理解需要更深入地了解生态瞬变的发生时间。最近的工作已经定义了可以导致长时间瞬变的确定性机制类别。考虑到生态系统中随机性的普遍性，对包括随机性影响的瞬态进行类似的系统处理很重要。随机性当然可以通过防止系统在其渐近状态附近永久稳定来促进瞬态动力学的出现，但随机性也与确定性特征相互作用以创造定性的新动力学。因此，随机性可能会缩短、扩展或从根本上改变系统的瞬态动力学。这里，我们描述了一个正在开发的通用框架，用于理解随机过程在现实时间尺度上影响生态系统动态时可能产生的结果范围。我们强调，通过研究存在的随机性和确定性过程之间的相互作用，我们可以理解随机性可以延长或减少瞬变寿命的方式，并且我们总结了当前的知识状态和未来发展的途径。