Repeatability of adaptation in experimental populations of different sizes

Abstract

The degree to which evolutionary trajectories and outcomes are repeatable across independent populations depends on the relative contribution of selection, chance and history. Population size has been shown theoretically and empirically to affect the amount of variation that arises among independent populations adapting to the same environment. Here, we measure the contribution of selection, chance and history in different-sized experimental populations of the unicellular alga Chlamydomonas reinhardtii adapting to a high salt environment to determine which component of evolution is affected by population size. We find that adaptation to salt is repeatable at the fitness level in medium (N e ¼ 5 Â 10 4 ) and large (N e ¼ 4 Â 10 5 ) populations because of the large contribution of selection. Adaptation is not repeatable in small (N e ¼ 5 Â 10 3 ) populations because of large constraints from history. The threshold between stochastic and deterministic evolution in this case is therefore between effective population sizes of 10 3 and 10 4 . Our results indicate that diversity across populations is more likely to be maintained if they are small. Experimental outcomes in large populations are likely to be robust and can inform our predictions about outcomes in similar situations.

Fitness change in relation to mutation number in spontaneous mutation accumulation lines ofChlamydomonas reinhardtii

“…We estimated the correlation between competitive fitness measured in this study with a growth rate-based fitness measure from a previous study of the same MA lines (Morgan et al 2014). Overall, the two fitness measures, as well as the respective derived relative fitness measures, were highly significantly and positively correlated, indicating that competitive fitness can be, to some degree, compared across studies to previous fitness measures obtained via growth rates in isolation (e.g., Kassen and Bell 2000;Morgan et al 2014;Lachapelle et al 2015). However, we found that competitive fitness measures consistently have higher interreplicate correlations and smaller 95% confidence intervals than growth rate-based fitness measures and are thus able to provide more precise estimates of small mutational effects.…”

“…; Lachapelle et al. ). However, we found that competitive fitness measures consistently have higher inter‐replicate correlations and smaller 95% confidence intervals than growth rate‐based fitness measures and are thus able to provide more precise estimates of small mutational effects.…”

Experimental island biogeography demonstrates the importance of island size and dispersal for the adaptation to novel habitats

“…Several studies have provided important insights into the independent roles of dispersal (Alzate et al, 2017;Bolnick & Nosil, 2007;Ching et al, 2012;Cuevas et al, 2003) and population size (Lachapelle et al, 2015) on adaptation. Evolutionary outcomes of adaptation are more robust and repeatable in larger populations than in small ones, which has been suggested to be attributable to the stronger effect of history and stochasticity on small populations (Lachapelle et al, 2015).…”

“…Several studies have provided important insights into the independent roles of dispersal (Alzate et al, 2017;Bolnick & Nosil, 2007;Ching et al, 2012;Cuevas et al, 2003) and population size (Lachapelle et al, 2015) on adaptation. Evolutionary outcomes of adaptation are more robust and repeatable in larger populations than in small ones, which has been suggested to be attributable to the stronger effect of history and stochasticity on small populations (Lachapelle et al, 2015). High rates of dispersal have often been shown to have a negative effect on the adaptation process by imposing genetic load (Alzate et al, 2017;Bolnick & Nosil, 2007;Cuevas et al, 2003; but see Ching et al, 2012), particularly when dispersal is random (Jacob et al, 2017).…”

How phenotypic convergence arises in experimental evolution

“…Understanding how populations adapt to environmental challenges is becoming increasingly important in both evolutionary biology and conservation (Franks and Hoffmann 2012;Botero et al 2015). However, we are still unsure how predictable adaptation to novel environments is (Wiser et al 2013;Lachapelle et al 2015;Lenski et al 2015;Lässig et al 2017;Orgogozo 2015). Unpredictability in evolution can be caused by different genetic backgrounds due to prior evolutionary history (see Barton and Keightley 2002;Barrett and Schluter 2008; Hansen * Both authors contributed equally to this work.…”