Stabilization of extensive fine-scale diversity by ecologically driven spatiotemporal chaos

Abstract

It has recently become apparent that the diversity of microbial life extends far below the species level to the finest scales of genetic differences. Remarkably, extensive fine-scale diversity can coexist spatially. How is this diversity stable on long timescales, despite selective or ecological differences and other evolutionary processes? Most work has focused on stable coexistence or assumed ecological neutrality. We present an alternative: extensive diversity maintained by ecologically driven spatiotemporal chaos, with no assumptions about niches or other specialist differences between strains. We study generalized Lotka–Volterra models with antisymmetric correlations in the interactions inspired by multiple pathogen strains infecting multiple host strains. Generally, these exhibit chaos with increasingly wild population fluctuations driving extinctions. But the simplest spatial structure, many identical islands with migration between them, stabilizes a diverse chaotic state. Some strains (subspecies) go globally extinct, but many persist for times exponentially long in the number of islands. All persistent strains have episodic local blooms to high abundance, crucial for their persistence as, for many, their average population growth rate is negative. Snapshots of the abundance distribution show a power law at intermediate abundances that is essentially indistinguishable from the neutral theory of ecology. But the dynamics of the large populations are much faster than birth–death fluctuations. We argue that this spatiotemporally chaotic “phase” should exist in a wide range of models, and that even in rapidly mixed systems, longer-lived spores could similarly stabilize a diverse chaotic phase.

Chaos may lurk under a cloak of neutrality

“…Yet, it is difficult to imagine that the dynamics of enormously abundant species like Prochlorococcus are controlled primarily by neutral processes, which could be disrupted by even tiny differences between strains (9). In PNAS, Pearce et al (10) show analytically how alternative nicheless models can produce the same neutral abundance patterns from a dynamics that could hardly be more nonneutral: rapid spatiotemporal chaos generated by ecological interactions and random dispersal. Pearce et al (10) highlight that widely observed static patterns, believed to be hallmarks of neutrality, are too insensitive to distinguish pertinent scenarios, reinforcing the need for spatiotemporal data (11,12) in microbial ecology.…”

“…Do species go extinct en masse or become somehow stabilized dynamically? These are the central dynamical questions that Pearce et al (10) set out to answer because populations of closely related strains are, with only weak niche differences, poised to be May-unstable. Pearce et al (10) develop analytical techniques within the framework of dynamical mean-field theory that, like May's approach, leverage the simplicity that emerges in the large S limit.…”

“…These are the central dynamical questions that Pearce et al (10) set out to answer because populations of closely related strains are, with only weak niche differences, poised to be May-unstable. Pearce et al (10) develop analytical techniques within the framework of dynamical mean-field theory that, like May's approach, leverage the simplicity that emerges in the large S limit. Supported by simulations, they find that the population dynamics become chaotic outside the stability region, as the ecological interactions provide sufficient negative feedback to prevent any one strain from outcompeting most of the others.…”

“…Neutral theories typically assume the existence of a "mainland" from which species migrate, which serves to buffer species from purely stochastic extinction (7,15). However, in Pearce et al's (10) self-contained metacommunity model, species self-organize into a dynamic state, without the need for imposing the presence of a mainland. This self-consistency allows them to equate a strain's longtime abundance distribution with its island-averaged abundance distribution, which in turn leads to fascinating analytic insights and testable quantitative predictions.…”

“…Chaotic dynamics have indeed been indicated in several microbial experiments with plankton (16), viruses (17), and oceanic bacteria (18). Crucially, while ecological models with assumed local chaotic dynamics have been studied before (19), Pearce et al (10) provide a firm mathematical description of how Pearce et al highlight that widely observed static patterns, believed to be hallmarks of neutrality, are too insensitive to distinguish pertinent scenarios, reinforcing the need for spatiotemporal data in microbial ecology.…”