Effective competition determines the global stability of model ecosystems

  • Antonio Ferrera
  • Alberto Pascual-García
  • Ugo Bastolla
ORIGINAL PAPER

DOI: 10.1007/s12080-016-0322-z

Cite this article as:
Ferrera, A., Pascual-García, A. & Bastolla, U. Theor Ecol (2016). doi:10.1007/s12080-016-0322-z

Abstract

We investigate the stability of Lotka-Volterra (LV) models constituted by two groups of species such as plants and animals in terms of the intragroup effective competition matrix, which allows separating the equilibrium equations of the two groups. In matrix analysis, the effective competition matrix represents the Schur complement of the species interaction matrix. It has been previously shown that the main eigenvalue of this effective competition matrix strongly influences the structural stability of the model ecosystem. Here, we show that the spectral properties of the effective competition matrix also strongly influence the dynamical stability of the model ecosystem. In particular, a necessary condition for diagonal stability of the full system, which guarantees global stability, is that the effective competition matrix is diagonally stable, which means that intergroup interactions must be weaker than intra-group competition in appropriate units. For mutualistic or competitive interactions, diagonal stability of the effective competition is a sufficient condition for global stability if the inter-group interactions are suitably correlated, in the sense that the biomass that each species provides to (removes from) the other group must be proportional to the biomass that it receives from (is removed by) it. For a non-LV mutualistic system with saturating interactions, we show that the diagonal stability of the corresponding LV system close to the fixed point is a sufficient condition for global stability.

Keywords

Ecological models Population dynamics Global stability Structural stability 

Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  1. 1.Centro de Biología Molecular Severo Ochoa (CSIC-UAM)Universidad Autónoma de MadridMadridSpain
  2. 2.Departamento de Matemática Aplicada y Estadística, E.T.S.I.Aeronáuticos Universidad Politécnica de MadridMadridSpain