A CLASSIFICATION OF THE DYNAMICS OF THREE-DIMENSIONAL STOCHASTIC ECOLOGICAL SYSTEMS
成果类型:
Article
署名作者:
Hening, Alexandru; Nguyen, Dang H.; Schreiber, Sebastian J.
署名单位:
Tufts University; University of Alabama System; University of Alabama Birmingham; University of California System; University of California Davis
刊物名称:
ANNALS OF APPLIED PROBABILITY
ISSN/ISSBN:
1050-5164
DOI:
10.1214/21-AAP1699
发表日期:
2022
页码:
893-931
关键词:
lotka-volterra equation
Limit-cycles
Replicator dynamics
global perspective
coexistence
persistence
STABILITY
models
environments
COMPETITION
摘要:
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.
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