Convergence to stationary distributions in two-species stochastic competition models.
Two sets of sufficient conditions are given for convergence to stationary distributions, for some general models of two species competing in a randomly varying environment. The models are nonlinear stochastic difference equations which define Markov chains. One set of sufficient conditions involves strong continuity and phi-irreducibility of the transition probability for the chain. The second set has a much weaker irreducibility condition, but is only applicable to monotonic models. The results are applied to a stochastic two-species Ricker model, and to Chesson's "lottery model with vacant space", to illustrate how the assumptions can be checked in specific models.
Department of Statistics, North Carolina State University, Raleigh 27695-8203.
S
S
Ellner
D004463:Ecology; D004777:Environment; D015233:Models, Statistical; D011153:Population; D011336:Probability; D013269:Stochastic Processes