Turing patterns and apparent competition in predator-prey food webs on networks

Area of Science:

• Ecology
• Mathematical Biology
• Theoretical Ecology

Background:

• Reaction-diffusion systems generate spatial patterns known as Turing patterns.
• Turing patterns are crucial for understanding pattern formation in biology, ecology, and morphogenesis.
• Previous models focused on simpler systems, leaving complex food chains understudied.

Purpose of the Study:

• To investigate the role of Turing patterns in shaping species abundance distributions in patchy landscapes.
• To extend existing models by incorporating food chains with multiple interacting prey and predator pairs.
• To analyze species distribution patterns driven by Turing instabilities in scale-free networks.

Main Methods:

• Mathematical modeling of reaction-diffusion systems.
• Extension of the Nakao and Mikhailov model to include complex food chains.
• Analysis of species distribution on scale-free networks of patches.

Main Results:

• Turing patterns significantly influence predator and prey abundance distribution in patchy environments.
• Identified species distribution patterns exhibiting strong apparent competition due to Turing instabilities.
• Demonstrated that self-organized Turing patterns can generate abundance heterogeneity dynamically.

Conclusions:

• Turing patterns play a critical role in generating spatial heterogeneity in species abundance.
• Apparent competition, driven by Turing instabilities, is a key mechanism shaping ecological communities.
• Ecological abundance patterns can arise from self-organization, not solely from environmental differences.