Global epistasis and the emergence of ecological function

Abstract

The functions and services provided by ecosystems emerge from myriad interactions between organisms and their environment. The difficulty of incorporating this complexity into quantitative models has hindered our ability to predictively link species-level composition with ecosystem function. This represents a major obstacle towards engineering ecological systems for environmental and biotechnological purposes. Inspired by similar findings in evolutionary genetics, here we show that the function of ecological communities often follows simple equations that allow us to accurately predict and optimize ecological function. This predictability is facilitated by emergent "species-by-ecosystem" interactions that mirror the patterns of global epistasis observed in many genetic systems. Our results illuminate an unexplored path to quantitatively linking the composition and function of ecological communities, bringing the tasks of predicting biological function at the genetic, organismal, and ecological scales under the same quantitative formalism.

The community-function landscape of microbial consortia

“…Can we extend this way of partitioning interactions to microbial consortia? In recent work, we have found that, indeed, the functional effects of adding a species to a consortium does often scale linearly with the function of the background consortium, in a way that is very similar to what has been observed in genetic systems (Díaz-Colunga et al, 2022).…”

“…The existence of these global functional interaction patterns appears to be rather general in ecosystems as we also found them in plant and algal communities (Díaz-Colunga et al, 2022). Importantly, different species within a consortium tend to have different "Functional Effect Equations" describing their unique, global functional interaction patterns (Díaz-Colunga et al, 2022). How the particular global functional patterns exhibited by a species depend on its traits, as well as the traits of the species it interacts with, is still not well understood.…”

“…Species can have less beneficial (or more deleterious) functional effects in backgrounds with higher functions (red lines), or vice-versa (blue lines). These regressions that capture the functional effect of adding a species to a gamut of different consortia have been termed "Functional Effect Equations" (FEEs) (Díaz-Colunga et al, 2022).…”

“…Data corresponds to butyrate production by synthetic gut microbial communities (Baranwal et al, 2022), biomass in plankton communities (Ghedini et al, 2022), above ground biomass in multi-species plant communities (Kuebbing et al, 2015), xylose oxidation by soil bacterial communities (Langenheder et al, 2010) and amylase secretion in bacterial consortia (Sanchez-Gorostiaga et al, 2019) (C) These functional trends can be exploited to predict the function of any combinatorial assemblage of species, and thus reconstruct entire ecological structure-function landscapes from a small subset of empirical observations. Data corresponds to the amount of pyoverdine secreted from newly assembled microbial consortia, whose function was predicted from a simple model that concatenates the Functional Effect Equations (FEEs) of each species as discussed in (Díaz-Colunga et al, 2022).…”

“…Adapting and applying these methodologies to microbial consortia is an exciting prospect (Baranwal et al, 2022), and its feasibility is encouraged by the success of simpler inference approaches. For instance, we have recently tested the predictive power of a simple model consisting of "stitching together" the Functional Effect Equations of all community members (Díaz-Colunga et al, 2022). This very simple approach does an excellent job at predicting various community functions for the full set of all possible consortia one may form with a defined set of taxa.…”