Spatiotemporal noise stabilizes unbounded diversity in strongly-competitive communities
Amer Al-Hiyasat, Daniel W. Swartz, Jeff Gore, Mehran Kardar

TL;DR
This paper demonstrates that the combination of spatial structure and environmental fluctuations enables highly diverse ecological communities to remain stable, resolving the longstanding diversity-stability paradox.
Contribution
It introduces a generalized Lotka-Volterra model incorporating spatiotemporal noise, showing how combined effects promote stable coexistence despite strong competition.
Findings
Spatiotemporal noise allows arbitrarily many species to coexist stably.
Noise induces an anomalous scaling of abundance fluctuations, consistent with empirical Taylor's law.
Community stability emerges from an effective sublinear self-inhibition mechanism.
Abstract
Classical ecological models predict that large, diverse communities should be unstable, presenting a central challenge to explaining the stable biodiversity seen in nature. We revisit this long-standing problem by extending the generalized Lotka-Volterra model to include both spatial structure and environmental fluctuations across space and time. We find that neither space nor environmental noise alone can resolve the tension between diversity and stability, but that their combined effects permit arbitrarily many species to stably coexist despite strongly disordered competitive interactions. We analytically characterize the noise-induced transition to coexistence, showing that spatiotemporal noise drives an anomalous scaling of abundance fluctuations, known empirically as Taylor's law. At the community level, this manifests as an effective sublinear self-inhibition that renders the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsEcosystem dynamics and resilience · stochastic dynamics and bifurcation · Nonlinear Dynamics and Pattern Formation
