Dual Fear Mechanisms Shaping Stochastic Population Dynamics under the Allee Effect

TL;DR

This paper introduces a stochastic population model incorporating dual fear mechanisms affecting the Allee effect, with analytical solutions revealing noise-induced regime changes and implications for conservation biology.

Contribution

It presents a novel cubic population model with two channels of fear influence, including an analytical steady state distribution under stochastic effects.

Findings

Fear causes noise-induced transitions between population states.

The model explains conflicting empirical observations on fear effects.

Analytical solutions reveal non-monotonic distribution changes due to fear.

Abstract

Traditional population models that include predator-prey interactions attribute demographic changes directly to predation-related effects. However, predator-induced fear in prey has increasingly been recognised as an important factor shaping population dynamics. In this study, we propose a cubic population model in which fear acts through two distinct functional channels for a single-species population exhibiting the Allee effect. In this model, fear reduces the intrinsic growth rate through a multiplicative suppression mechanism while also playing an integrated role in modulating the growth and interaction dynamics by rescaling the saturation structure of the Holling type III interaction term. The stochastic extension of the model is described by a Langevin formalism containing correlated additive and multiplicative Gaussian noise, and the steady state probability distribution (SSPD) is analytically obtained using the corresponding Fokker-Planck equation. The analytical solution is validated by numerical simulations. The SSPD reveals both noise-induced transitions and fear-controlled regime changes between low- and high-density states, with the two-channel effect of fear producing structural competition and non-monotonic changes in the distribution. These are analysed through phenomenological bifurcation (P-bifurcation) diagrams and three-dimensional distribution surfaces. Additionally, statistical properties, parameter sensitivity, and escape dynamics are investigated through normalised moments, Fisher information, and mean first-passage time (MFPT) calculations. Notably, our model treats fear as an independent control parameter and provides a natural explanation for several conflicting empirical findings in the literature on fear-mediated population dynamics, while also offering an analytical basis for conservation biology and ecosystem management.