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Table S1 Samples from Pennsylvania collected in 2002-2003 and used in the fine-scale spatial analyses. Counties are listed alphabetically, numbered accordingly, and collection sites are identified by Township unless otherwise noted (“boro” indicates borough). “Date” refers to the time the field collections were made and “n” is the sample size. ◊ West, † East, ‡ Central groups (for nad4 analyses)

Fig. S1 Dataset is Aedes j. japonicus specimens collected in 1999-2000. Calculation of the most likely number of groups (or clusters, K) from a Bayesian multilocus analysis (software STRUCTURE, Pritchard et al 2000). We ran 20 replicates assuming K=1 through 5 using 10,000 burnin steps and 100,000 Markov Chain Monte Carlo (MCMC) steps. We assumed admixture and allowed the program to infer alpha (the degree of admixture). Graphs a) through d) depicts the four steps of the graphic method developed by Evanno et al. 2005 (please see this reference for detailed explanation of the calculations). a) Mean log likelihood (± 1 SD) associated with each number of groups (K) taken directly from the program’s output (ln P(D) or ln(K)); b) Mean rate of change in the likelihood distribution (ln(K)-ln(K-1) ± 1SD) with increasing number of groups (K); c) Mean second order rate of change in the likelihood distribution (± 1SD); d) Absolute value of &Dgr;K (delta K) associated with each putative number of groups (K). The highest value of &Dgr;K indicates the “true” K.

Fig. S2 Dataset is Aedes j. japonicus specimens collected both in 1999-2000 and 2004-05. Calculation of the most likely number of groups (or clusters, K) from a Bayesian multilocus analysis (software STRUCTURE, Pritchard et al 2000). We ran 20 replicates assuming K=1 through 5 using 10,000 burnin steps and 100,000 Markov Chain Monte Carlo (MCMC) steps. We assumed admixture and allowed the program to infer alpha (the degree of admixture). Graphs a) through d) depicts the four steps of the graphic method developed by Evanno et al. 2005 (please see this reference for detailed explanation of the calculations). a) Mean log likelihood (± 1 SD) associated with each number of groups (K) taken directly from the program’s output (ln P(D) or ln(K)); b) Mean rate of change in the likelihood distribution (ln(K)-ln(K-1) ± 1SD) with increasing number of groups (K); c) Mean second order rate of change in the likelihood distribution (± 1SD); d) Absolute value of &Dgr;K (delta K) associated with each putative number of groups (K). The highest value of &Dgr;K indicates the “true” K.

Fig. S3 Dataset is Aedes j. japonicus specimens collected both in 1999-2000 and 2004-05. We increased the number of putative groups to 10 to examine the possibility that the two temporal collections may cluster separately. The calculations are the same as in Figures 1 and 2. The log-likelihood peaks at K=6 but &Dgr;K still peaks at 2.

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