Abstract
Despite their complexity, microbial ecosystems appear to be at least partially “coarse-grainable” in that some properties of interest can be adequately described by effective models of dimension much smaller than the number of interacting lineages. This is especially puzzling, since recent studies demonstrate that a surprising amount of functionally relevant diversity is present at all levels of resolution, down to strains differing by 100 nucleotides or fewer. Rigorously defining coarse-grainability and understanding the conditions for its emergence is of critical importance for understanding microbial ecosystems. To begin addressing these questions, we propose a minimal model for investigating hierarchically structured ecosystems within the framework of resource competition. We use our model to operationally define coarse-graining quality based on reproducibility of the outcomes of a specified experiment and show that a coarse-graining can be operationally valid despite grouping together functionally diverse strains. Furthermore, we demonstrate that a high diversity of strains (while nominally more complex) may, in fact, facilitate coarse-grainability and that, at least within our model, coarse-grainability is maximized when a community is assembled in its “native” environment. Our modeling framework offers a path toward building a theoretical understanding of which ecosystem properties, and in which environmental conditions, might be predictable by coarse-grained models.
- Received 5 August 2021
- Revised 14 March 2022
- Accepted 13 April 2022
DOI:https://doi.org/10.1103/PhysRevX.12.021038
Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI.
Published by the American Physical Society
Physics Subject Headings (PhySH)
Popular Summary
Microbial ecosystems present a paradox. On one hand, they often harbor hundreds of diverse, coexisting species, and small differences in their genomes can alter the outcome of their interactions. On the other hand, some ecosystem properties can be predicted by coarse-grained descriptions, where much of this diversity is ignored. Since most natural ecosystems are too complex for detailed characterization, understanding which properties can be predicted with simpler models, and under what conditions, is an important challenge. To that end, we construct an ecoevolutionary model where we can reproduce and thus reconcile the paradox above. Specifically, we show that coarse-graining can be valid even when the strains grouped together are functionally diverse.
Our approach builds on a classic model of resource competition by incorporating one additional ingredient: trait interactions within a phenotype. We show that these interactions endow ecosystems with a structure that naturally lends itself to coarse-graining, grouping strains by the traits they share. We propose a simple way to assess the “quality” of a coarse-grained description, by checking whether neglecting fine-scale details of an organism’s description modifies the outcome of some specified experiment. This setup lets us rigorously define what it means for an ecosystem to be “coarse-grainable” and investigate how this property depends on its environment and on the choice of the experiment.
Intriguingly, our findings suggest that predicting how two species would interact in a laboratory may sometimes require more knowledge about microscopic details than when the same species are studied in their native context of a diverse community, even though the latter is nominally more complex.
