Evolutionary repeatability of emergent properties of ecological communities

Abstract

Most species belong to ecological communities where their interactions give rise to emergent community-level properties, such as diversity and productivity. Understanding and predicting how these properties change over time has been a major goal in ecology, with important practical implications for sustainability and human health. Less attention has been paid to the fact that community-level properties can also change because member species evolve. Yet, our ability to predict long-term eco-evolutionary dynamics hinges on how repeatably community-level properties change as a result of species evolution. Here, we review studies of evolution of both natural and experimental communities and make the case that community-level properties at least sometimes evolve repeatably. We discuss challenges faced in investigations of evolutionary repeatability. In particular, only a handful of studies enable us to quantify repeatability. We argue that quantifying repeatability at the community level is critical for approaching what we see as three major open questions in the field: (i) Is the observed degree of repeatability surprising? (ii) How is evolutionary repeatability at the community level related to repeatability at the level of traits of member species? (iii) What factors affect repeatability? We outline some theoretical and empirical approaches to addressing these questions. Advances in these directions will not only enrich our basic understanding of evolution and ecology but will also help us predict eco-evolutionary dynamics. This article is part of the theme issue ‘Interdisciplinary approaches to predicting evolutionary biology’.

‘Evolutionary poker’: an agent‐based model of interactome emergence and epistasis tested against Lenski's long‐term E. coli experiments

“…'Evolutionary poker' or 'EPOKER' models evolutionary processes among non-sexually reproducing organisms, such as the E. coli studied in the LTEE. [This limitation is common to mathematical models of bacterial evolution and particularly of LTEE data (Agarwal, 2013;Deshpande & Fronhofer, 2022;Hintze & Adami, 2008;Jones et al, 2014;Lenski et al, 2003;Schinazi, 2019;Wiser et al, 2013;Yuan, 2017). The extrapolation of the model to sexually reproducing organisms is possible and will be addressed in the Discussion.]…”

“…The ultimate limitation of the music analogy, and indeed with EPOKER and all the other models outlined above (e.g. Agarwal, 2013;Deshpande & Fronhofer, 2022;Hintze & Adami, 2008;Jones et al, 2014;Lenski et al, 2003;Schinazi, 2019;Wiser et al, 2013;Yuan, 2017), is that none defines testable molecular, cellular or organismal mechanisms by which organization results. Selection cannot simply be on genes/cards/notes but must be on higher orders of organization, such as epistasis, to yield the types of results seen in LTEE.…”

“…Although historical contingency, evolutionary irreversibility and epistasis were not addressed directly by the model, it is arguable that these features are present in the results, particularly through the a priori choice of instructions capable of interacting to form more complex instruction sets. Wiser et al (2013) addressed more directly this central role of epistasis in determining the power law dynamics governing the decay rate of emergence of increased fitness. Jones et al ( 2014) have produced a model of epistasis emergence that, like EPOKER, is based on the random production of variants, in their case by Monte Carlo simulation, that are constrained by increasingly networked 'gene' interactions (Jones et al, 2014).…”

“…It must be stressed that many models of the emergence of networks within living systems have been proposed previously (e.g. Agarwal, 2013;Deshpande & Fronhofer, 2022;Hintze & Adami, 2008;Jones et al, 2014), which include several models specific to the Lenski experiments (Lenski et al, 2003;Schinazi, 2019;Wiser et al, 2013;Yuan, 2017). However, most of these are mathematically complex, involve massive computational methods and are non-intuitive to those without the requisite mathematics training.…”

Interdisciplinary approaches to predicting evolutionary biology

“…Understanding and predicting how these properties change over time is a primary goal in ecology, with important implications for sustainability and human health. Venkataram & Kryazhimskiy [ 15 ] review studies of the evolution of both natural and experimental communities and make the case that community-level properties at least sometimes evolve repeatably. They argue that quantifying repeatability at the community level is not only critical to enriching our fundamental understanding of evolution and ecology but it will also help us to predict eco-evolutionary dynamics.…”