A generalised sigmoid population growth model with energy dependence: application to quantify the tipping point for Antarctic shallow seabed algae

TL;DR

This paper introduces a generalized sigmoid growth model that explicitly incorporates resource dependence, demonstrated through Antarctic algae data, enabling better estimation of critical tipping points in population dynamics.

Contribution

A novel family of energy-dependent sigmoid growth models is proposed, extending standard models to include resource effects and applied to Antarctic algae populations.

Findings

Models can estimate sea-ice break-out tipping points.

Energy dependence improves population growth predictions.

Models outperform standard sigmoid models in resource-limited scenarios.

Abstract

Sigmoid growth models are often used to study population dynamics. The size of a population at equilibrium commonly depends explicitly on the availability of resources, such as an energy or nutrient source, which is not explicit in standard sigmoid growth models. A simple generalised extension of sigmoid growth models is introduced that can explicitly account for this resource-dependence, demonstrated by three examples of this family of models of increasing mathematical complexity. Each model is calibrated and compared to observed data for algae under sea-ice in Antarctic coastal waters. It was found that through careful construction, models satisfying the proposed framework can estimate key properties of a sea-ice break-out controlled tipping point for the algae, which cannot be estimated using standard sigmoid growth models. The proposed broader family of energy-dependent sigmoid growth models likely has usage in many population growth contexts where resources limit population size.