Robust coexistence in competitive ecological communities


Contact
srilena.kundu [ at ] hifmb.de

Abstract

Darwin already recognized that competition is fiercest among conspecifics, a principle that later made intraspecific competition central to ecological theory through concepts such as niche differentiation and limiting similarity. Beyond shaping coexistence, strong intraspecific competition can also stabilize community dynamics by ensuring that populations return to equilibrium after disturbance. Here we investigate a more fundamental question: how intraspecific competition influences the very existence of a steady state (feasibility) in large random ecological communities dominated by competition. We show that, in analogy with classical results on stability, there is a critical level of intraspecific competition above which a feasible steady state is guaranteed to exist. We derive a general expression for the probability of feasibility and prove that, asymptotically (as species number grows), the transition to stability occurs before the transition to feasibility with probability one. Thus, in large competitive communities, any feasible equilibrium is automatically stable. This ordering persists even when many species in the initial pool cannot coexist and extinctions occur: the dynamics prune the community, shifting feasibility and stability thresholds but never reversing their order. These results imply that large competitive communities generically converge to a globally stable equilibrium, making sustained oscillations or chaos unlikely—consistent with experimental observations.



Item Type
Article
Authors
Divisions
Primary Division
Primary Topic
Publication Status
Published
Eprint ID
60671
DOI 10.1038/s41467-026-69151-3

Cite as
Lechón-Alonso, P. , Kundu, S. , Lemos-Costa, P. , Capitán, J. A. and Allesina, S. (2026): Robust coexistence in competitive ecological communities , Nature Communications . doi: 10.1038/s41467-026-69151-3


Download
[thumbnail of Lechon-Alonso_et_al_2026.pdf]
Preview
PDF
Lechon-Alonso_et_al_2026.pdf - Other

Download (813kB) | Preview

Share
Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email


Citation

Research Platforms
N/A


Actions
Edit Item Edit Item