Tradeoff breaking as model of evolutionary transitions in individuality and the limits of the fitness-decoupling metaphor
Evolutionary transitions in individuality (ETIs) involve the formation of Darwinian collectives from Darwinian particles. The transition from cells to multicellular life is a prime example. During an ETI, collectives become units of selection in their own right. However, the underlying processes are poorly understood. One observation used to identify the completion of an ETI is an increase in collective-level performance accompanied by a decrease in particle-level performance, for example measured by growth rate. This seemingly counterintuitive dynamic has been referred to as 'fitness decoupling' and has been used to interpret both models and experimental data. Extending and unifying results from the literature, we show that fitness of particles and collectives can never decouple because calculations of particle and collective fitness performed over appropriate and equivalent time intervals are necessarily the same provided the population reaches a stable collective size distribution. By way of solution, we draw attention to the value of mechanistic approaches that emphasise traits, and tradeoffs among traits, as opposed to fitness. This trait-based approach is sufficient to capture dynamics that underpin evolutionary transitions. In addition, drawing upon both experimental and theoretical studies, we show that while early stages of transitions might often involve tradeoffs among particle traits, later—and critical-stages are likely to involve the rupture of such tradeoffs. Thus, when observed in the context of ETIs, tradeoff-breaking events stand as a useful marker for these transitions.
The code implementing the models is publicly available on Zenodo (https://doi.org/10.5281/zenodo.5352208)For Figure 1: Protocol described and statistical analysis performed in Hammerschmidt et al. (2014). Dataset published as Rose et al. (2018). For Figure 6b: Data taken from Colon-Lopez et al (1997); Mohr et al (2013); Misra & Tuli (2000); Berman-Frank et al (2001); Popa et al. (2007) and standardised.For Figure 6c: Data taken from the dataset published as Rose et al. (2018).
Article and author information
John Templeton Foundation (62220)
- Pierrick Bourrat
- Guilhem Doulcier
- Katrin Hammerschmidt
Max Planck Institute for Evolutionary Biology (open access funding)
- Paul B Rainey
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
- Will Ratcliff, Georgia Institute of Technology, United States
- Preprint posted: September 2, 2021 (view preprint)
- Received: September 8, 2021
- Accepted: June 28, 2022
- Accepted Manuscript published: August 17, 2022 (version 1)
- Version of Record published: September 13, 2022 (version 2)
© 2022, Bourrat et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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