Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Random replicators with high-order interactions

de Oliveira VM1, Fontanari

  • 1Instituto de Fisica de Sao Carlos, Universidade de Sao Paulo, Caixa Postal 369, 13560-970 Sao Carlos SP, Brazil.

Physical Review Letters
|December 2, 2000
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Population genetics approach to the quasispecies model.

Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics·1996
Same author

Dilution in a linear neural network.

Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics·1995
Same author

Calculation of learning curves for inconsistent algorithms.

Physical review. A, Atomic, molecular, and optical physics·1992
Same author

Learning noisy patterns in a Hopfield network.

Physical review. A, General physics·1989
Same author

Potts model in a random field.

Physical review. B, Condensed matter·1989
Same author

Information storage and retrieval in synchronous neural networks.

Physical review. A, General physics·1987
Same journal

Erratum: Bacterial Turbulence at Compressible Fluid Interfaces [Phys. Rev. Lett. 136, 138301 (2026)].

Physical review letters·2026
Same journal

Unveiling Light-Quark Yukawa Flavor Structure via Dihadron Fragmentation at Lepton Colliders.

Physical review letters·2026
Same journal

Adaptable Route to Fast Coherent State Transport via Bang-Bang-Bang Protocols.

Physical review letters·2026
Same journal

Topological Transition and Emergence of Elasticity of Dislocation in Skyrmion Lattice: Beyond Kittel's Magnetic-Polar Analogy.

Physical review letters·2026
Same journal

Pound-Drever-Hall Method for Superconducting-Qubit Readout.

Physical review letters·2026
Same journal

Coupling a ^{73}Ge Nuclear Spin to an Electrostatically Defined Quantum Dot in Silicon.

Physical review letters·2026
See all related articles

Higher-order species interactions in ecosystems reduce competition, decreasing extinction rates. For interactions above order two, a threshold prevents rare species, enhancing ecosystem resilience.

Area of Science:

  • Statistical mechanics
  • Ecology
  • Complex systems

Background:

  • Ecosystems comprise multiple species with intricate interactions.
  • Understanding species interactions is crucial for ecosystem stability.
  • Disordered systems offer tools to model complex ecological networks.

Purpose of the Study:

  • To analytically study ecosystem statistical properties using equilibrium statistical mechanics.
  • To investigate the impact of deterministic self-interactions of order p (p>=2) on species dynamics.
  • To assess how interaction order influences ecosystem competitiveness and robustness.

Main Methods:

  • Application of equilibrium statistical mechanics tools.
  • Analysis of disordered systems.

Related Experiment Videos

  • Mathematical modeling of N-species ecosystems with random mutual and deterministic self-interactions.

    • Main Results:

    • Increasing interaction order reduces ecosystem competitiveness.
    • The fraction of extinct species is significantly decreased with higher-order interactions.
    • A threshold value for p>2 limits surviving species concentration, preventing rare species.

    Conclusions:

    • Higher-order interactions enhance ecosystem robustness against external perturbations.
    • The study provides analytical insights into the structure and stability of complex ecosystems.
    • Findings suggest that complex interaction patterns can lead to more stable ecological communities.