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April 2022 A classification of the dynamics of three-dimensional stochastic ecological systems
Alexandru Hening, Dang H. Nguyen, Sebastian J. Schreiber
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Ann. Appl. Probab. 32(2): 893-931 (April 2022). DOI: 10.1214/21-AAP1699


The classification of the long-term behavior of dynamical systems is a fundamental problem in mathematics. For both deterministic and stochastic dynamics specific classes of models verify Palis’ conjecture: the long-term behavior is determined by a finite number of stationary distributions. In this paper we consider the classification problem for stochastic models of interacting species. For a large class of three-species, stochastic differential equation models, we prove a variant of Palis’ conjecture: the long-term statistical behavior is determined by a finite number of stationary distributions and, generically, three general types of behavior are possible: 1) convergence to a unique stationary distribution that supports all species, 2) convergence to one of a finite number of stationary distributions supporting two or fewer species, 3) convergence to convex combinations of single species, stationary distributions due to a rock-paper-scissors type of dynamic. Moreover, we prove that the classification reduces to computing Lyapunov exponents (external Lyapunov exponents) that correspond to the average per-capita growth rate of species when rare. Our results stand in contrast to the deterministic setting where the classification is incomplete even for three-dimensional, competitive Lotka–Volterra systems. For these SDE models, our results also provide a rigorous foundation for ecology’s modern coexistence theory (MCT) which assumes the external Lyapunov exponents determine long-term ecological outcomes.

Funding Statement

The authors acknowledge support from the NSF through the grants DMS-1853463 for Alexandru Hening, DMS-1853467 for Dang Nguyen, and DMS-1716803 for Sebastian Schreiber.


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Alexandru Hening. Dang H. Nguyen. Sebastian J. Schreiber. "A classification of the dynamics of three-dimensional stochastic ecological systems." Ann. Appl. Probab. 32 (2) 893 - 931, April 2022.


Received: 1 May 2020; Revised: 1 March 2021; Published: April 2022
First available in Project Euclid: 28 April 2022

Digital Object Identifier: 10.1214/21-AAP1699

Primary: 37H15 , 60H10 , 60J60 , 92D25

Keywords: ergodicity , Kolmogorov system , Lotka–Volterra , Lyapunov exponent , random environmental fluctuations

Rights: Copyright © 2022 Institute of Mathematical Statistics


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Vol.32 • No. 2 • April 2022
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