Towards a mechanistic foundation of evolutionary theory

Doebeli, Michael; Ispolatov, Iaroslav; Simon, Burton

doi:10.7554/elife.23804

Cited by 103 publications

(127 citation statements)

References 57 publications

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“…We find that by increasing the complexity of the model, the separation of ecological and evolutionary processes becomes more and more dicult. The emergence of such complexity in the intertwined nature of eco-evolutionary dynamics is a natural outcome of biological processes derived from mechanistic first principles [21].…”

Section: Discussionmentioning

confidence: 99%

“…This microscopic implementation of the model has the advantage of directly relating selective advantages to birth or death processes. This mechanistic way of thinking about evolutionary success has not been examined in the literature, see [21] for an essay about this. We believe that interpreting selection in a mechanistic way can give new insight into the concrete advantages of mutants and situations in which these mutants are beneficial.…”

Section: B Population Dynamicsmentioning

confidence: 99%

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Disentangling eco-evolutionary effects on trait fixation

Czuppon

Gokhale

2018

Preprint

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In population genetics, fixation of traits in a demographically changing population under frequencyindependent selection has been extensively analyzed. In evolutionary game theory, models of fixation have typically focused on fixed population sizes and frequency-dependent selection. However, combining ecological fluctuations with frequency-dependent interactions such as Lotka-Volterra dynamics and thus the analysis of eco-evolutionary fixation has received comparatively little attention. Here, we consider a two-type stochastic competitive Lotka-Volterra model with higher order interactions. The emerging individual based model allows for stochastic fluctuations not just in the frequencies of the two types but the total population size as well. Assuming weak selective di↵erences between the traits we approximate the fixation probability for di↵ering competition coe cients. We find that it resembles qualitatively the corresponding evolutionary deterministic dynamics within a population of fixed size. Furthermore, we analyze and partially disentangle the selection e↵ects into their ecological and evolutionary components. Concretely, we show that the evolutionary selection intensity has a larger e↵ect on the predictive power of our approximation than the ecological selection. However, the fixed points themselves are also a↵ected by the selection intensity which implies that a clean separation of the ecological and evolutionary impacts on the evolutionary outcome of the model is not possible. The entanglement of eco-evolutionary processes in a co-evolutionary system is thus a reality which needs to be considered when determining the fixation properties in populations of fluctuating size.

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Section: Discussionmentioning

confidence: 99%

Section: B Population Dynamicsmentioning

confidence: 99%

Disentangling eco-evolutionary effects on trait fixation

Czuppon

Gokhale

2018

Preprint

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“…In the numerical model (Appendix A), the ecological dynamic of particles is expressed by a stochastic birth-death process (Champagnat et al, 2006;Doebeli et al, 2017). Each particle of type i ∈ {0, 1} is characterised by four traits (hereafter particle traits): colour (c i , red or blue), net maximum growth rate r i , and two competition parameters (a intra i and a inter i ).…”

Section: A Nested Model Of Collective Evolutionmentioning

confidence: 99%

Eco-evolutionary dynamics of nested Darwinian populations and the emergence of community-level heredity

Doulcier

Lambert

Monte

et al. 2019

Preprint

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Interactions among microbial cells can generate new chemistries and functions, but exploitation requires establishment of communities that reliably recapitulate communitylevel phenotypes. Using mechanistic mathematical models, we show how simple manipulations to population structure can exogenously impose Darwinian-like properties on communities. Such imposition causes communities to participate directly in the process of evolution by natural selection and drives the evolution of cell-level interactions to the point where, despite underlying stochasticity, derived communities give rise to offspring communities that faithfully re-establish parental phenotype. The mechanism (developmental correction) is akin to a developmental process that arises from density dependent interactions among cells. Knowledge of ecological factors affecting evolution of developmental correction has implications for understanding the evolutionary origin of egalitarian transitions in individuality, symbioses, and for top-down engineering of microbial communities.

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“…It is believed that most major changes in animal population abundances are due to die-offs rather than population explosions (Anderson, Branch, Cooper, & Dulvy, 2017). Since evolution is a function of both birth rates and death rates (Doebeli, Ispolatov, & Simon, 2017), it would be similarly meaningful to measure the left tail of the distribution of descendants. This tail of the distribution is difficult to capture but may shed light on the relative importance of death in evolutionary processes.…”

Section: Discussionmentioning

confidence: 99%

Stochastic exits from dormancy give rise to heavy‐tailed distributions of descendants in bacterial populations

Wright

Vetsigian

2019

Molecular Ecology

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Variance in reproductive success is a major determinant of the degree of genetic drift in a population. While many plants and animals exhibit high variance in their number of progeny, far less is known about these distributions for microorganisms. Here, we used a strain barcoding approach to quantify variability in offspring number among replicate bacterial populations and developed a Bayesian method to infer the distribution of descendants from this variability. We applied our approach to measure the offspring distributions for five strains of bacteria from the genus Streptomyces after germination and growth in a homogenous laboratory environment. The distributions of descendants were heavy‐tailed, with a few cells effectively ‘winning the jackpot’ to become a disproportionately large fraction of the population. This extreme variability in reproductive success largely traced back to initial populations of spores stochastically exiting dormancy, which provided early‐germinating spores with an exponential advantage. In simulations with multiple dormancy cycles, heavy‐tailed distributions of descendants decreased the effective population size by many orders of magnitude and led to allele dynamics differing substantially from classical population genetics models with matching effective population size. Collectively, these results demonstrate that extreme variability in reproductive success can occur even in growth conditions that are far more homogeneous than the natural environment. Thus, extreme variability in reproductive success might be an important factor shaping microbial population dynamics with implications for predicting the fate of beneficial mutations, interpreting sequence variability within populations and explaining variability in infection outcomes across patients.

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Towards a mechanistic foundation of evolutionary theory

Cited by 103 publications

References 57 publications

Disentangling eco-evolutionary effects on trait fixation

Disentangling eco-evolutionary effects on trait fixation

Eco-evolutionary dynamics of nested Darwinian populations and the emergence of community-level heredity

Stochastic exits from dormancy give rise to heavy‐tailed distributions of descendants in bacterial populations

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