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The effect of temperature and wing morphology on quantitative genetic variation in the cricket Gryllus firmus , with an appendix examining the statistical properties of the Jackknife–manova method of matrix comparison
Author(s) -
Bégin M.,
Roff D. A.,
Debat V.
Publication year - 2004
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/j.1420-9101.2004.00772.x
Subject(s) - jackknife resampling , wing , biology , multivariate analysis of variance , quantitative genetics , evolutionary biology , variation (astronomy) , cricket , trait , quantitative trait locus , principal component analysis , genetic variation , zoology , statistics , genetics , mathematics , physics , estimator , astrophysics , computer science , engineering , gene , programming language , aerospace engineering
We investigated the effect of temperature and wing morphology on the quantitative genetic variances and covariances of five size‐related traits in the sand cricket, Gryllus firmus . Micropterous and macropterous crickets were reared in the laboratory at 24, 28 and 32 °C. Quantitative genetic parameters were estimated using a nested full‐sib family design, and (co)variance matrices were compared using the T method, Flury hierarchy and Jackknife– manova method. The results revealed that the mean phenotypic value of each trait varied significantly among temperatures and wing morphs, but temperature reaction norms were not similar across all traits. Micropterous individuals were always smaller than macropterous individuals while expressing more phenotypic variation, a finding discussed in terms of canalization and life‐history trade‐offs. We observed little variation between the matrices of among‐family (co)variation corresponding to each combination of temperature and wing morphology, with only one matrix of six differing in structure from the others. The implications of this result are discussed with respect to the prediction of evolutionary trajectories.