Stochastic Functional Kolmogorov Equations II: Extinction

TL;DR

This paper develops a framework for stochastic functional Kolmogorov equations with delays, focusing on conditions leading to population extinction, using functional Itô calculus and dynamical systems in infinite dimensions.

Contribution

It introduces a new approach to analyze extinction in stochastic delay differential equations, extending classical models to include past dependence.

Findings

Characterization of extinction conditions for stochastic delay systems

Extension of functional Itô formula to infinite-dimensional systems

Analysis of boundary behavior and occupation measures

Abstract

This work, Part II, together with its companion Part I develops a new framework for stochastic functional Kolmogorov equations, which are nonlinear stochastic differential equations depending on the current as well as the past states. Because of the complexity of the problems, it is natural to divide our contributions into two parts to answer a long-standing question in biology and ecology. What are the minimal conditions for long-term persistence and extinction of a population? Part I of our work provides characterization of persistence, whereas in this part, extinction is the main focus. The main techniques used in this paper are combination of the newly developed functional It^o formula and a dynamical system approach. Compared to the study of stochastic Kolmogorov systems without delays, the main difficulty is that infinite dimensional systems have to be treated. The extinction is characterized after investigating random occupation measures and examining behavior of functional systems around boundaries. Our characterizations of long-term behavior of the systems reduces to that of Kolmogorov systems without delay when there is no past dependence. A number of applications are also examined.