4.2 Article

The genetic variance but not the genetic covariance of life-history traits changes towards the north in a time-constrained insect

期刊

JOURNAL OF EVOLUTIONARY BIOLOGY
卷 31, 期 6, 页码 853-865

出版社

WILEY
DOI: 10.1111/jeb.13269

关键词

genetic correlation; G-matrix; latitude; life history; seasonal time constraint

资金

  1. National Science Centre [UMO-2012/05/N/NZ8/00981, 2014/12/T/NZ8/00522, 2015/16/T/NZ8/00392, UMO-2015/18/E/NZ8/00505]
  2. Institute of Nature Conservation Polish Academy of Sciences
  3. Swedish Research Council

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Seasonal time constraints are usually stronger at higher than lower latitudes and can exert strong selection on life-history traits and the correlations among these traits. To predict the response of life-history traits to environmental change along a latitudinal gradient, information must be obtained about genetic variance in traits and also genetic correlation between traits, that is the genetic variance-covariance matrix, G. Here, we estimated G for key life-history traits in an obligate univoltine damselfly that faces seasonal time constraints. We exposed populations to simulated native temperatures and photoperiods and common garden environmental conditions in a laboratory set-up. Despite differences in genetic variance in these traits between populations (lower variance at northern latitudes), there was no evidence for latitude-specific covariance of the life-history traits. At simulated native conditions, all populations showed strong genetic and phenotypic correlations between traits that shaped growth and development. The variance-covariance matrix changed considerably when populations were exposed to common garden conditions compared with the simulated natural conditions, showing the importance of environmentally induced changes in multivariate genetic structure. Our results highlight the importance of estimating variance-covariance matrixes in environments that mimic selection pressures and not only trait variances or mean trait values in common garden conditions for understanding the trait evolution across populations and environments.

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