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Ecosystems can appear stable for extended periods, only to abruptly shift into drastically different states. One way this type of behavior can arise is through so-called ‘long transients'. Imagine a system lingering near an unstable state, seemingly unchanging, before a sudden, dramatic regime shift. In this talk, we will explore how the dynamics of these long transients are altered by the addition of stochasticity into the models. We will discuss challenges for connecting these mathematical models to real-world data, and highlight how first passage time theory provides some mathematical tools and a coherent framework for thinking about the length of a stochastic long transient. I will also introduce some intriguing and non-intuitive results (and several open questions) about how the placement and correlation structure of the stochasticity affects the duration of the ‘long’ transients. 

Also available on Zoom: https://ucdavis.zoom.us/j/98969645841