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Related Experiment Videos

Foraging biology predicts food web complexity.

Andrew P Beckerman1, Owen L Petchey, Philip H Warren

  • 1Department of Animal and Plant Sciences, University of Sheffield, Western Bank, Sheffield S10 2TN, United Kingdom. a.beckerman@sheffield.ac.uk

Proceedings of the National Academy of Sciences of the United States of America
|September 7, 2006
PubMed
Summary

Optimal foraging behavior explains food web complexity. Individual diet breadth constraints emerge as a fundamental biological driver of connectance, a key measure of food web structure and stability.

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Area of Science:

  • Ecology
  • Theoretical Ecology
  • Behavioral Ecology

Background:

  • Food webs illustrate feeding links crucial for ecosystem structure, stability, and function.
  • Food web complexity, or connectance, is linked to stability but lacks a fundamental biological explanation.
  • Optimal foraging theory describes how animals maximize energy intake per unit time.

Purpose of the Study:

  • To propose and test a mechanistic explanation for connectance in food webs.
  • To demonstrate how individual foraging behavior can explain emergent network properties.
  • To synthesize foraging theory and food web theory.

Main Methods:

  • Developed a simple diet breadth model based on optimal foraging principles.
  • Predicted connectance values from individual foraging behavior.

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  • Compared model predictions with empirical data from real food webs, considering aggregation and sampling effects.

    • Main Results:

    • The diet breadth model successfully predicted constrained values of connectance.
    • Model predictions aligned with observed connectance levels and scaling with species richness in real food webs.
    • Demonstrated emergent network properties from individual-level behavior.

    Conclusions:

    • Optimal foraging constraints on diet breadth provide a mechanistic explanation for food web connectance.
    • This synthesis bridges foraging and food web theories, explaining network structure from individual behavior.
    • Offers a novel perspective on the fundamental drivers of ecological network complexity.