(Non)local logistic equations with Neumann conditions

TL;DR

This paper investigates a complex population dynamics model combining local and nonlocal diffusion with novel Neumann boundary conditions, analyzing eigenvalues to determine conditions for species survival.

Contribution

It introduces a new mathematical framework for logistic equations with mixed diffusion types and Neumann conditions, analyzing eigenvalues and existence of solutions.

Findings

Eigenvalue analysis differs between 1D and higher dimensions.

Existence of minimal solutions depends on resource bounds.

Resource distribution strategies can hinder survival despite abundance.

Abstract

We consider here a problem of population dynamics modeled on a logistic equation with both classical and nonlocal diffusion, possibly in combination with a pollination term. The environment considered is a niche with zero-flux, according to a new type of Neumann condition. We discuss the situations that are more favorable for the survival of the species, in terms of the first positive eigenvalue. Quite surprisingly, the eigenvalue analysis for the one dimensional case is structurally different than the higher dimensional setting, and it sensibly depends on the nonlocal character of the dispersal. The mathematical framework of this problem takes into consideration the equation $$ -\alpha\Delta u +\beta(-\Delta)^su =(m-\mu u)u+\tau\;J\star u \qquad{\mbox{in }}\; \Omega,$$ where $m$ can change sign. This equation is endowed with a set of Neumann condition that combines the classical normal derivative prescription and the nonlocal condition introduced in [S. Dipierro, X. Ros-Oton, E. Valdinoci, Rev. Mat. Iberoam. (2017)]. We will establish the existence of a minimal solution for this problem and provide a throughout discussion on whether it is possible to obtain non-trivial solutions (corresponding to the survival of the population). The investigation will rely on a quantitative analysis of the first eigenvalue of the associated problem and on precise asymptotics for large lower and upper bounds of the resource. In this, we also analyze the role played by the optimization strategy in the distribution of the resources, showing concrete examples that are unfavorable for survival, in spite of the large resources that are available in the environment.