Unpacking the Allee effect: determining individual-level mechanisms that drive global population dynamics

Author:

Fadai Nabil T.1ORCID,Johnston Stuart T.23ORCID,Simpson Matthew J.4ORCID

Affiliation:

1. School of Mathematical Sciences, University of Nottingham, Nottingham NG7 2RD, UK

2. Systems Biology Laboratory, School of Mathematics and Statistics, and Department of Biomedical Engineering, University of Melbourne, Parkville, Victoria 3010, Australia

3. ARC Centre of Excellence in Convergent Bio-Nano Science and Technology, Melbourne School of Engineering, University of Melbourne, Parkville, Victoria 3010, Australia

4. School of Mathematical Sciences, Queensland University of Technology, Brisbane, Queensland 4001, Australia

Abstract

We present a solid theoretical foundation for interpreting the origin of Allee effects by providing the missing link in understanding how local individual-based mechanisms translate to global population dynamics. Allee effects were originally proposed to describe population dynamics that cannot be explained by exponential and logistic growth models. However, standard methods often calibrate Allee effect models to match observed global population dynamics without providing any mechanistic insight. By introducing a stochastic individual-based model, with proliferation, death and motility rates that depend on local density, we present a modelling framework that translates particular global Allee effects to specific individual-based mechanisms. Using data from ecology and cell biology, we unpack individual-level mechanisms implicit in an Allee effect model and provide simulation tools for others to repeat this analysis.

Funder

Australian Research Council

Publisher

The Royal Society

Subject

General Physics and Astronomy,General Engineering,General Mathematics

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