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Rapid and unpredictable changes of the G ‐matrix in a natural bird population over 25 years
Author(s) -
Björklund M.,
Husby A.,
Gustafsson L.
Publication year - 2013
Publication title -
journal of evolutionary biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.289
H-Index - 128
eISSN - 1420-9101
pISSN - 1010-061X
DOI - 10.1111/jeb.12044
Subject(s) - biology , evolutionary biology , microevolution , natural selection , trait , genetic drift , matrix (chemical analysis) , natural population growth , population , stability (learning theory) , evolutionarily stable strategy , selection (genetic algorithm) , ecology , zoology , genetic variation , genetics , demography , computer science , materials science , machine learning , artificial intelligence , sociology , gene , composite material , programming language
Knowledge of the genetic variances and covariances of traits (the G ‐matrix) is fundamental for the understanding of evolutionary dynamics of populations. Despite its essential importance in evolutionary studies, empirical tests of the temporal stability of the G ‐matrix in natural populations are few. We used a 25‐year‐long individual‐based field study on almost 7000 breeding attempts of the collared flycatcher ( F icedula albicollis ) to estimate the stability of the G ‐matrix over time. Using animal models to estimate G for several time periods, we show that the structure of the time‐specific G ‐matrices changed significantly over time. The temporal changes in the G ‐matrix were unpredictable, and the structure at one time period was not indicative of the structure at the next time period. Moreover, we show that the changes in the time‐specific G ‐matrices were not related to changes in mean trait values or due to genetic drift. Selection, differences in acquisition/allocation patterns or environment‐dependent allelic effects are therefore likely explanations for the patterns observed, probably in combination. Our result cautions against assuming constancy of the G ‐matrix and indicates that even short‐term evolutionary predictions in natural populations can be very challenging.