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“Why so variable: can genetic variance in flowering thresholds be maintained by fluctuating selection?”

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Mark Rees and Stephen P. Ellner (July 2019)

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Why populations are genetically variable is a puzzle: Here is why fluctuating selection might hold the key

A typical <i>Carlina vulgaris</i> which, having waited to flower for several years, is about to flower then die.<br />(Credit: Mark Rees)
A typical Carlina vulgaris which, having waited to flower for several years, is about to flower then die.
(Credit: Mark Rees)

Many processes are thought to allow the maintenance of genetic variation in natural populations. However, determining which ones operate in the wild is difficult. The authors’ previous work exploring the evolution of flowering thresholds (the critical size a plant must achieve before it can flower) suggested that even in a variable environment, where the conditions for growth, survival, and reproduction vary from year to year, a single strategy was best and so the maintenance of genetic variation was not possible.

Here the researchers extend their models to include quantitative genetic variation and ask whether a gene which increases the mutation rate would be adaptive. For one species where they assume a constant environment, selection does not favor an increase in mutation rate, and genetic variation in the threshold size for flowering is maladaptive. In contrast, for the other species where they assume a variable environment, an increase in mutation rate is adaptive. The authors suggest this is a consequence of disruptive selection which favors genotypes in the tails of the flowering threshold distribution. They suspect this mechanism may operate in many natural systems.


We use integral projection models (IPM) and individual-based simulations to study the evolution of genetic variance in two monocarpic plant systems. Previous approaches combining IPMs with an Adaptive Dynamics-style invasion analysis predicted that genetic variability in the size threshold for flowering will not be maintained, which conflicts with empirical evidence. We ask if this discrepancy can be resolved by making more realistic assumptions about the underlying genetic architecture: assuming a multilocus quantitative trait in an outcrossing diploid species. To do this, we embed the infinitesimal model of quantitative genetics into an IPM for a sizestructured cosexual plant species. The resulting IPM describes the joint dynamics of individual size and breeding value of the evolving trait. We apply this general framework to the monocarpic perennials Oenothera glazioviana and Carlina vulgaris. The evolution of heritable variation in threshold size is explored, in both individual-based models (IBMs) and IPMs, using a mutation rate modifier approach. In the Oenothera model, where the environment is constant, there is selection against producing genetically variable offspring. In the Carlina model, where the environment varies between years, genetically variable offspring provide a selective advantage, allowing the maintenance of genetic variability. The contrasting predictions of Adaptive Dynamics and Quantitative Genetics models for the same system suggest that fluctuating selection may be more effective at maintaining genetic variation than previously thought.