Resource and population dynamics in an agent-environment interaction model

TL;DR

This paper introduces a coupled agent-environment model to study ecosystem dynamics, revealing how population size and resource distribution emerge and how counter-intuitive factors influence population growth.

Contribution

It presents a novel model linking active matter physics with movement ecology, analyzing population-resource interactions through simulations and analytical methods.

Findings

Population size inversely related to average energy per agent

Reduced resources or higher metabolic costs can increase population size

Distinct phases of agent motility identified in the model

Abstract

In any ecosystem, the conditions of the environment and the characteristics of the species that inhabit it are entangled, co-evolving in space and time. We introduce a model that couples active agents with a dynamic environment, interpreted as a nutrient source. Agents are persistent random walkers that gather food from the environment and store it in an inner energy depot. This energy is used for self-propulsion, metabolic expenses, and reproduction. The environment is a two-dimensional surface divided into patches, each of them producing food. Thus, population size and resource distribution become emergent properties of the system. Combining simulations and analytical framework to analyze limiting cases, we show that the system exhibits distinct phases separating quasi-static and highly motile regimes. We observe that, in general, population sizes are inversely proportional to the average energy per agent. Furthermore, we find that, counter-intuitively, reduced access to resources or increased metabolic expenditure can lead to a larger population size. The proposed theoretical framework provides a link between active matter and movement ecology, allowing to investigate short vs long-term strategies to resource exploitation and rationing, as well as sedentary vs wandering strategy. The introduced approach may serve as a tool to describe real-world ecological systems and to test environmental strategies to prevent species extinction.