The Concept of Force in Population Dynamics

TL;DR

This paper introduces a force-based framework for analyzing population dynamics models, using symbolic notation and feedback loop pathways to explain variable behavior and stability in biological systems.

Contribution

It develops a novel method to interpret influences in differential equation models as forces, enhancing understanding of model dynamics through a Newtonian perspective.

Findings

Force dominance clarifies intervention points in population models

Dissipative forces are crucial for stability in predator-prey systems

The approach provides a causal, mechanical interpretation of model behavior

Abstract

The area of population dynamics has a rich history of the development and analysis of models of biological and social phenomena using ordinary differential equations. This paper describes a method for understanding the influence one variable exerts on another in such models as a force, with the relative effects of these forces providing a narrative explanation of the curvature in variable behaviour. Using the stock/flow form of a model, a symbolic notation is developed that identifies the forces with the causal pathways of the model's feedback loops. A force is measured by its impact, defined as the ratio of acceleration to rate of change, computed by differentiation along its associated pathway between variables. Different phases of force dominance are determined to enhance the standard stability analysis of the models, providing an explanation of model behaviour in Newtonian mechanical terms. The concepts developed are applied to well-known models from mathematical biology: the Spruce Budworm model, where force dominance identifies scenarios that give clarity to intervention points; and the Lotka-Volterra predator-prey model where the analysis highlights the importance of dissipative forces in achieving stability. Conclusions are drawn on the explanatory power of this approach, with suggestions made for future work.