Population dynamics of mutualism are robustly stable, but exhibit characteristic thresholds at low density

“Mutualism has always been the ‘bastard child’ of community ecology”
from Community Ecology (Mittelbach 2012)

Mutualisms are a ubiquitous but remarkably diverse set of interactions, with species alternately providing food, defense, habitat, and facilitating growth and reproduction for each other in different circumstances. Though known to be critical for many ecosystem functions, mutualisms have not been the focus of as much ecological research as predator-prey or competition interactions (Bronstein 2015). For example, almost no empirical studies of the population dynamics of mutualisms exist, and though well-characterized, the differences in natural histories of these interactions have not been clearly tied to ecological consequences. Additionally, the historical perception that mutualism is an unstable population process (the “orgy of mutual[ism],” May 1981) has persisted in broader community ecology, despite the accumulation of a small but rich literature of theoretical studies on mutualisms. This literature has suffered from a cycle of neglect and rediscovery, perhaps due to the criticism that these works are either too abstract or too case-specific to be useful.

Here, we review historical models from the last 90 years, tracing the development of the field’s current understanding. We organize these works both conceptually and mathematically, identifying patterns in the processes that determine mutualistic interactions and the population dynamics that result. We find that, despite different inspiring systems, levels of mechanistic detail, and different derivations, surprisingly much of theory makes similar, testable predictions. For example, like the characteristic unstable oscillations of predator-prey interactions and competitive exclusion in competition interactions, mutualisms exhibit destabilizing thresholds at low density, but are otherwise stable.

This advances the study of mutualisms by providing a testable hypothesis for their population dynamics and a conceptual reframing for how to characterize these interactions outside of their natural histories. Identifying such an ecological theory of mutualism also advances the study of community ecology overall. With an understanding of the qualitative dynamics of two-species mutualisms, we can confidently study how these dynamics impact broader ecological and evolutionary contexts using networks representing guilds, communities, and ecosystems.

Citation: Hale, K. R. S. & Valdovinos, F. S. (2021). Ecological theory of mutualism: Robust patterns of stability and thresholds in two-species population models. Ecology and Evolution 11:17651–17671. https://doi.org/10.1002/ece3.8453  

Abstract: Mutualisms are ubiquitous in nature, provide important ecosystem services, and involve many species of interest for conservation. Theoretical progress on the population dynamics of mutualistic interactions, however, comparatively lagged behind that of trophic and competitive interactions, leading to the impression that ecologists still lack a generalized framework to investigate the population dynamics of mutualisms. Yet, over the last 90 years, abundant theoretical work has accumulated, ranging from abstract to detailed. Here, we review and synthesize historical models of two-species mutualisms. We find that population dynamics of mutualisms are qualitatively robust across derivations, including levels of detail, types of benefit, and inspiring systems. Specifically, mutualisms tend to exhibit stable coexistence at high density and destabilizing thresholds at low density. These dynamics emerge when benefits of mutualism saturate, whether due to intrinsic or extrinsic density dependence in intraspecific processes, interspecific processes, or both. We distinguish between thresholds resulting from Allee effects, low partner density, and high partner density, and their mathematical and conceptual causes. Our synthesis suggests that there exists a robust population dynamic theory of mutualism that can make general predictions.

Note the correction: In the caption of Figure 1, the interaction strengths listed for panels (b) and (d) were switched.