Environmental change, if unaccounted, prevents detection of cryptic evolution in a wild population

T Potter, RD Bassar, P Bentzen… - The American …, 2021 - journals.uchicago.edu
The American Naturalist, 2021journals.uchicago.edu
Detecting contemporary evolution requires demonstrating that genetic change has occurred.
Mixed effects models allow estimation of quantitative genetic parameters and are widely
used to study evolution in wild populations. However, predictions of evolution based on
these parameters frequently fail to match observations. Here, we applied three commonly
used quantitative genetic approaches to predict the evolution of size at maturity in a wild
population of Trinidadian guppies. Crucially, we tested our predictions against evolutionary …
Abstract
Detecting contemporary evolution requires demonstrating that genetic change has occurred. Mixed effects models allow estimation of quantitative genetic parameters and are widely used to study evolution in wild populations. However, predictions of evolution based on these parameters frequently fail to match observations. Here, we applied three commonly used quantitative genetic approaches to predict the evolution of size at maturity in a wild population of Trinidadian guppies. Crucially, we tested our predictions against evolutionary change observed in common-garden experiments performed on samples from the same population. We show that standard quantitative genetic models underestimated or failed to detect the cryptic evolution of this trait as demonstrated by the common-garden experiments. The models failed because (1) size at maturity and fitness both decreased with increases in population density, (2) offspring experienced higher population densities than their parents, and (3) selection on size was strongest at high densities. When we accounted for environmental change, predictions better matched observations in the common-garden experiments, although substantial uncertainty remained. Our results demonstrate that predictions of evolution are unreliable if environmental change is not appropriately captured in models.
The University of Chicago Press
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