Resilience Analysis for Competing Populations

Abstract

Ecological resilience refers to the ability of a system to retain its state when subject to state variables perturbations or parameter changes. While understanding and quantifying resilience is crucial to anticipate the possible regime shifts, characterizing the influence of the system parameters on resilience is the first step towards controlling the system to avoid undesirable critical transitions. In this paper, we apply tools of qualitative theory of differential equations to study the resilience of competing populations as modeled by the classical Lotka-Volterra system. Within the high interspecific competition regime, such model exhibits bistability, and the boundary between the basins of attraction corresponding to exclusive survival of each population is the stable manifold of a saddle-point. Studying such manifold and its behavior in terms of the model parameters, we characterized the populations resilience: while increasing competitiveness leads to higher resilience, it is not always the case with respect to reproduction. Within a pioneering context where both populations initiate with few individuals, increasing reproduction leads to an increase in resilience; however, within an environment previously dominated by one population and then invaded by the other, an increase in resilience is obtained by decreasing the reproduction rate. Besides providing interesting insights for the dynamics of competing population, this work brings near to each other the theoretical concepts of ecological resilience and the mathematical methods of differential equations and stimulates the development and application of new mathematical tools for ecological resilience.

Spatial Optimization of Tourist-Oriented Villages by Space Syntax Based on Population Analysis

“…Yun et al proposed a demographic analysis (APA) approach to complement and expand the framework of PA analysis [30]. Artur et al applied PA variables to eco-elastic systems to broaden the application of competing population theory for qualitative system modeling of differential equations [31]. The theory translates multidimensional and complex content into a systematic and intuitive language, while maintaining the stability of variables and parameters, thereby enriching theory and solving practical content and expanding the thinking and application of population analysis in various fields.…”