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Electronic supplementary material
Phylogenetic comparative analyses
Although the utility of phylogenetic comparative methods is often limited when studying life history trait variation across population within species (Losos 1999;
Niewiarowski et al . 2004), significant covariation between descent and character states is a potential problem in any comparative study (Harvey & Pagel 1991;
Ashton 2004). To test for the presence of a phylogenetic signal (Blomberg et al .
2003) in the data, we first generated a population level phylogeny for all 12 populations based on 954 bp of sequence data from COI (see Tuda et al . 2006 for details on primers and PCR). We modeled this sequence data in a Bayesian framework, using MrBayes version 3.1.2 (Ronquist & Huelsenbeck 2003) (see
Tuda et al . 2006 for parameter settings) with C. imitator as an outgroup. The majority-rule consensus tree from this analysis represented a well resolved population phylogeny with good branch support for all nodes (mean posterior probability 0.79; range 0.53 – 1.0). The amount of phylogenetic signal across traits was then estimated as K and a randomization test was used to test for any tendency of related populations to resemble one another (Blomberg et al . 2003).
The phylogenetic signal was very low for most traits and only in one case could the null hypothesis of no phylogenetic signal be rejected (population fitness K =
0.41, p = 0.78; body size PC1 K = 0.46, p = 0.32; body size PC2 K = 0.89, p =
0.071; growth rate PC1 K = 0.29, p = 0.59; growth rate PC2 K = 1.11, p = 0.042; development time PC1 K = 0.47, p = 0.58; development time PC2 K = 0.39, p =
0.62). The fact that K was generally considerably lower than unity signifies evolution across populations that is uncorrelated with the phylogeny (Blomberg et al . 2003), indicating that the inter-population comparative analyses would not benefit from incorporating phylogenetic information (Losos 1999; Niewiarowski et al . 2004). Yet, different degrees of shared ancestry across populations could in theory affect our results to some extent (Ashton 2004). We thus also tested for

2 correlated evolution using phylogenetic comparative models - phylogenetic least squares (PGLS) regressions (Rohlf 2001) as implemented in the MatLab program REGRESSION.M (Blomberg et al . 2003). We ran three sets of multiple regression models, each involving population fitness as the dependent variable and PC1 and PC2 of the life history trait in question as independent variables.
Population fitness did not show significant correlated evolution with either body size ( p dir
> 0.17 for both independent variables) or growth rate ( p dir
> 0.20 for both independent variables). In contrast, SD in development time (PC2; b = 1.12, t =
2.16, p dir
= 0.037) but not overall development time (PC1; b = -0.11, t = 1.88, p dir
= 0.06) showed correlated evolution with population fitness. Thus, the results of these PGLS models were identical to our phylogenetically uncorrected analyses, in terms of our ability or inability to reject null hypotheses.
Ashton, K. G. 2004 Comparing phylogenetic signal in intraspecific and interspecific body size datasets. J. Evol. Biol.
17 , 1157-1161.
Blomberg, S. P., Garland, T. & Ives, A. R. 2003 Testing for phylogenetic signal in comparative data: behavioral traits are more labile. Evolution 57 , 717-745.
Harvey, P. H., Pagel, M. D. 1991. The comparative method in evolutionary biology . Oxford, UK: Oxford University Press.
Losos, J. B. 1999 Uncertainty in the reconstruction of ancestral character states and limitations on the use of phylogenetic comparative methods. Anim.
Behav.
58 , 1319-1324.
Niewiarowski, P. H., Angilletta, M. J. & Leache, A. D. 2004 Phylogenetic comparative analysis of life-history variation among populations of the lizard
Sceloporus undulatus : an example and prognosis. Evolution 58 , 619-633.
Rohlf, F. J. 2001 Comparative methods for the analysis of continuous variables: geometric interpretations. Evolution 55 , 2143 –2160.
Ronquist, F. & Huelsenbeck, J. P. 2003 MrBayes 3: bayesian phylogenetic inference under mixed models. Bioinfomatics 19 , 1572 –1573.

Tuda, M.
, Rönn, J., Buranapanichpan, S., Wasano, N. & Arnqvist, G. 2006
Evolutionary diversification of the bean beetle genus Callosobruchus
(Coleoptera: Bruchidae): traits associated with stored-product pest status.
Mol. Ecol.
15 , 3541
–3551.
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