Predicting the stability of large structured food webs

Area of Science:

• Ecology
• Network Theory
• Theoretical Ecology

Background:

• Ecological stability is a core concept in ecology.
• Random matrix theory has been used to understand stability in random ecological networks.
• Empirical food webs exhibit non-random structures like broad degree distributions and intervality.

Purpose of the Study:

• To develop an approximation for ecological food web stability based on realistic network structures.
• To assess the accuracy of this approximation for cascade, empirical, and niche models.
• To identify key structural drivers of food web stability.

Main Methods:

• Derivation of a stability approximation for food webs generated by the cascade model.
• Validation of the approximation against empirical food web data and the niche model.
• Analysis of the influence of structural properties (intervality, degree distribution, interaction strength) on stability.

Main Results:

• The derived approximation accurately predicts the stability of cascade model food webs.
• The approximation also performs well for empirically structured and niche model food webs.
• Intervality and broad degree distributions were found to be significant stabilizing factors.

Conclusions:

• Realistic food web structures, particularly intervality and broad degree distributions, are crucial for ecological stability.
• The derived approximation offers a more accurate method for assessing food web stability than random network approaches.
• Average interaction strength has a less significant impact on stability compared to network structure variations.