Is “Evolutionary Stable Communities” the arena to link “–omics” data to ecosystem functioning?

Reproducing measured virus abundances with simple models has been difficult because combining a virus community with a predator community gives two competitors for a single, shared resource (the host=prey community). We suggest a simple solution to this.
Published in Microbiology
Is “Evolutionary Stable Communities” the arena to link “–omics” data to ecosystem functioning?

Share this post

Choose a social network to share with, or copy the shortened URL to share elsewhere

This is a representation of how your post may appear on social media. The actual post will vary between social networks

Hutchinson’s seminal 1961 paper on ”The Paradox of the Plankton” contains a small and rather overlooked paragraph on predation: ”It can be shown theoretically, as Dr. MacArthur and I have developed in conversation, that if one of two competing species is limited by a predator, while the other is either not so limited or is fed on by a different predator, co-existence of the two prey species may in some cases be possible. This should permit some diversification of both prey and predator in a homogeneous habit.” 


If Hutchinson had been just a bit more enthusiastic about the results of this “conversation”, enough to publish the theory, I believe it would have been cited as the early foundation for present theoretical attempts to understand how predators and viruses structure microbial ecosystems.  The long-lasting impact of Hutchinson’s paper is rooted in how it highlights the discrepancy between fundamental observations on biodiversity, and the theoretical framework(s) at our disposal to explain and structure these observations. Although dozens of mechanisms have been offered as solutions to the paradox (Record et al. 2013) the –omics area’s massive increase in descriptions of huge microbial biodiversity leaves an impression of a gap that is widening rather than closing. 


The “genes-to-ecosystems” vision is central to contemporary microbial ecology. A bottom-up approach towards such a unifying microbial ecology is from the –omics data on genes and gene expressions, to strains, species, and community composition, and so on to ecosystem functioning. Unfortunately, this staircase is steep and filled with high and difficult steps:  from base pairs to (known) gene functions to phenotypic traits to community composition to ecosystem function.


The never-published Hutchinson-MacArthur theory could have served the role as an early seed for a top-down approach to this staircase: with a theoretical framework that explains coexistence and food webs in terms of resources, competition and predation, the challenging steps would be to increase the resolution to community structures, organism traits and genes.


What has been poorly exploited is the complementarity of these two approaches. An interesting concept in this context is the “Evolutionary Stable Community” (ESC) (Edwards et al. 2018). The ESC is an interface between underlying gene level evolution determining what is available for selection, and forces from the outer ecosystem level determining this selection.


In this perspective, the article published in ISME J can be seen as a top-down approach where community composition drifts towards the moving target of an ESC that both depend on and change the microbial food web structure. Interestingly, this formulation also provides a simple solution to a special case of Hutchinson’s paradox: the co-existence of a virus and a predator community on a shared host=prey community.




Hutchinson GE (1961). The paradox of the plankton. AmNat 95: 137-145.

Record N, Pershing A, Maps F (2013). The paradox of the “paradox of the plankton”. ICES J Mar Sci 71.

Edwards KF, Kremer CT, Miller ET, Osmond MM, Litchman E, Klausmeier CA (2018). Evolutionarily stable communities: a framework for understanding the role of trait evolution in the maintenance of diversity. Ecol Lett 21: 1853-1868.




Please sign in or register for FREE

If you are a registered user on Research Communities by Springer Nature, please sign in