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Area of Science:

  • Ecology
  • Theoretical Ecology
  • Network Theory

Background:

  • Ecological networks often focus on single interaction types (e.g., food webs).
  • Integrating multiple interaction types (mutualistic, antagonistic) provides a more comprehensive ecosystem view.
  • Understanding the stability of merged ecological networks is crucial for ecosystem functioning.

Purpose of the Study:

  • To investigate the stability of tripartite ecological networks formed by merging mutualistic and antagonistic bipartite networks.
  • To analyze the impact of the ratio of mutualistic to antagonistic interactions on network stability.
  • To explore how network size and interaction disorder affect stability dynamics.

Main Methods:

  • Construction of tripartite networks by merging random mutualistic and antagonistic bipartite networks.
  • Analysis of network stability using the spectrum of the community matrix.
  • Application of random-matrix theory to study eigenvalue phase transitions in large networks.
  • Derivation of results for finite-sized networks and networks with interaction disorder.

Main Results:

  • An eigenvalue phase transition occurs in the asymptotic limit of large species numbers.
  • Increased ratio of mutualists to antagonists leads to abrupt network destabilization.
  • The destabilization transition is observable in finite-sized networks and with interaction disorder.

Conclusions:

  • Merged ecological networks exhibit complex stability dynamics influenced by the balance of interaction types.
  • Random-matrix theory provides a valuable baseline for understanding stability in complex ecological networks.
  • The findings highlight the critical role of interaction ratios in maintaining ecosystem stability.