On the role of reduced habitat in the phase transition of a stochastic model for seed dispersal

TL;DR

This paper models seed dispersal in limited habitats using a stochastic branching process, identifying critical parameters for species survival related to habitat size and seed production, with both continuous and discrete spatial models analyzed.

Contribution

It introduces a mathematical model of seed dispersal constrained by habitat barriers, analyzing survival thresholds using probability theory and coupling techniques.

Findings

Identified critical seed production rates for survival.

Derived exact results for discrete-space model.

Localized the phase transition point for species extinction or survival.

Abstract

Habitat loss is one of the biggest threats facing plant species nowadays. We formulate a simple mathematical model of seed dispersal on reduced habitats to discuss survival of the species in relation to the habitat size and seeds production rate. Seeds get dispersed around the mother plant via several agents in a random way. In our model seeds landing sites are distributed according to a homogeneous Poisson point process with a constant rate on $\mathbb{R}$. We will assume that each seed will successfully germinate and grow into a new plant with the same characteristics as the mother plant. The time is discrete, scaled according to generations of plants or can represent years, since annual plants go through an entire growing cycle during one year. Then we will assume there are two symmetric barriers with respect to the origin and consider that the growth can not evolve past the barriers. Imposing barriers correspond to the physical limitation of the habitat. We appeal to tools of Probability Theory to formalize and study such a model, which can be seen as a discrete-time one-dimensional branching random walk with barriers. By means of coupling techniques and the comparison with suitably constructed multi-type branching processes we localize the critical parameter of the process around which there is survival with positive probability or extinction almost surely. In addition, we consider a discrete-space version of the model for which exact results are also obtained.