Facts, Conventions, and the Levels of Selection

Doulcier

Rose

et al. 2022

eLife

Self Cite

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.

Section: Introductionmentioning

confidence: 65%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Tradeoff breaking as a model of evolutionary transitions in individuality and limits of the fitness-decoupling metaphor

Doulcier

Rose

et al. 2022

eLife

Self Cite

“…More precisely, either fitness at the particle and the collective level are commensurably computed— that is, with respect to the same biological object and in the same reference environment—in which case they are equal ( F and f 3 ), or they refer to different biological settings ( f 1 or f 2 and F ) and, thus, the biological significance of their differential dynamics is not immediately clear. Note that this result requires that the population reaches a stable size distribution; only if the collectives are able to grow (or shrink) indefinitely, which is not a realistic assumption for ETIs, could genuine fitness decoupling be observed (see Bourrat, 2021b, Chapter 5 for details) .…”

Section: Resultsmentioning

confidence: 99%

Tradeoff breaking as model of evolutionary transitions in individuality and the limits of the fitness decoupling metaphor

Doulcier

Rose

et al. 2021

Preprint

Self Cite

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. Using a mathematical approach we show this concept to be problematic in that the fitness of particles and collectives can never decouple: calculations of particle and collective fitness performed over appropriate and equivalent time intervals are necessarily the same. By way of solution, we draw attention to the value of mechanistic approaches that emphasise traits as opposed to fitness and tradeoffs among traits. 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 rupture of such tradeoffs. Tradeoff-breaking thus stands as a useful marker for ETIs.

“…When the dispersal time is long, the growth rate of the cells decreases over generations of the model. This phenomenon has previously been called "fitness decoupling", referring to the fact that fitness at the two levels is no longer aligned (Michod, 1999;Okasha, 2008;Black et al, 2020;Bourrat, 2021). With a single cell bottleneck, the evolutionary outcomes and dynamics of the system can be understood using a simple fitness landscape approach (Nowak et al, 2010).…”

Section: Single Cell Bottleneck Dynamicsmentioning

confidence: 99%

The Effect of Bottleneck Size on Evolution in Nested Darwinian Populations

Nitschke

Black

et al. 2022

Preprint

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Previous work has shown how a minimal ecological structure consisting of patchily distributed resources and recurrent dispersal between patches can scaffold Darwinian properties onto collections of cells. When the timescale of dispersal is long compared with the time to consume resources, patches evolve such that their size increases, but at the expense of cells whose growth rate decreases within patches. This creates the conditions that initiate evolutionary transitions in individuality. A key assumption of this scaffolding is that a bottleneck is created during dispersal, so patches are founded by single cells. The bottleneck decreases competition within patches and hence creates a strong hereditary link at the level of patches. Here we construct a fully stochastic model of nested Darwinian populations and investigate how larger bottlenecks affect the evolutionary dynamics at both cell and collective levels. It is shown that, up to a point, larger bottlenecks simply slow the dynamics, but at some point, which depends on the parameters of the within-patch model, the direction of evolution toward the equilibrium is reversed. Introducing random bottleneck sizes with some positive probability of smaller sizes can counteract this, even if the probability of smaller bottlenecks is small.