Population effects of fear-inducing signals in digital songbirds

Anthropogenic environments are rapidly changing. Reactions to these changes within prey populations can become detrimental since behavioral strategies for foraging and vigilance are adapted to the ancestral environment. Ecology of Fear studies show that fear alone can halve songbird populations in five years, not considering lasting transgenerational impacts. Ecologists point towards the need for explanations for this phenomenon, but theoretical models have yet to tackle the challenge of predicting how rapid environmental changes affect prey behavior and survival. This thesis presents a new, object-oriented model that bridges ecology and subjective cognition. It simulates how evolved emotions governed by two genes related to fear and hunger shape the behavioral patterns of digital songbirds experiencing a sudden increase in perceived risk. The thesis model consists of two phases: First, it evolves digital songbirds equipped with genes for fear and hunger through a genetic algorithm. Then, it exposes these evolved digital songbirds to greater levels of predator presence, exceeding that of their ancestral environment. By disabling the predator attack, the model predicts how fear alone changes evolved behavioral patterns in the simulated population. The model results show that as fear levels increase, all simulated populations experience a decrease in average body mass and, consequently, in expected fecundity. Additionally, the simulated populations with unique evolved gene pools each exhibited distinct patterns of body mass distribution as fear levels increased, indicating altered foraging strategies under heightened fear conditions. However, due to its current simplicity, the model is not yet suitable for real-world application.

Masteroppgave i biologi

BIO399

MAMN-HAVSJ

MAMN-BIO