An agent-based model of an endangered population of the Arctic fox from Mednyi Island

TL;DR

This paper presents an agent-based model combined with probabilistic graphical models to simulate and analyze the survival and population dynamics of Arctic foxes on Mednyi Island, providing insights into their decline and persistence.

Contribution

It introduces a novel integration of agent-based modeling with probabilistic graphical models for ecological simulation of Arctic foxes, based on empirical data.

Findings

Identifies key factors influencing fox population decline.

Simulates various environmental scenarios affecting survival.

Provides insights into evolutionary mechanisms of persistence.

Abstract

Artificial Intelligence techniques such as agent-based modeling and probabilistic reasoning have shown promise in modeling complex biological systems and testing ecological hypotheses through simulation. We develop an agent-based model of Arctic foxes from Medniy Island while utilizing Probabilistic Graphical Models to capture the conditional dependencies between the random variables. Such models provide valuable insights in analyzing factors behind catastrophic degradation of this population and in revealing evolutionary mechanisms of its persistence in high-density environment. Using empirical data from studies in Medniy Island, we create a realistic model of Arctic foxes as agents, and study their survival and population dynamics under a variety of conditions.