Table S4 Model checking procedure of the approximate Bayesian computation (ABC) approach. Summary statistics (S) A He V MGW Obs. 5.86 0.57 4.57 0.68 S Scenario 1 0.513 0.511 0.797 0.057 Scenario 2 0.463 0.430 0.607 0.155 Scenario 3 0.498 0.532 0.843 0.046* Prob. (Ssimul. < Scenario 4 0.436 0.305 0.654 0.110 Qobs.) Scenario 5 0.462 0.533 0.808 0.049* Scenario 6 0.449 0.485 0.585 0.159 Scenario 7 0.414 0.454 0.842 0.028* The probability Prob. (Ssimul. < given for each summary statistic was calculated from Sobs.) 1,000 virtual datasets simulated from the posterior distributions of parameters obtained under the focal scenario. Corresponding tail-area probabilities (P-values) were obtained as Prob. (Ssimul. < and 1.0 - Prob. (Ssimul. < for Prob. (Ssimul. < 0.5 and > 0.5, Sobs.) Sobs.) Sobs.) ≤ respectively (*, **, *** = tail-area probability < 0.05, < 0.01 and < 0.001, respectively). We used the mean number of alleles per locus (A), the mean expected heterozygosity (He), the mean allele size variance (V), and the mean index across loci. Demographic scenarios MGW are shown in Figure 2. Figure S1. Population genetic structure of A and B: Inferred population Armillaria ostoyae. structure according to STRUCTURE for each value of from two to five generated from K microsatellite and SNP data, using the standard admixture model (A) and the locprior admixture model (B). Each vertical line represents an individual, and the color composition displays the probability of belonging to each of the clusters. C and D: The probability of observing the data (X) under a given number of putative clusters (K) is shown as a function of
Table S4 Model checking procedure of the approximate Bayesian computation (ABC) approach. Summary statistics (S) A He V MGW Obs. S 5.86 0.57 4.57 0.68 Prob. (Ssimul. < Qobs.) Scenario 1 0.513 0.511 0.797 0.057 Scenario 2 0.463 0.430 0.607 0.155 Scenario 3 0.498 0.532 0.843 0.046* Scenario 4 0.436 0.305 0.654 0.110 Scenario 5 0.462 0.533 0.808 0.049* Scenario 6 0.449 0.485 0.585 0.159 Scenario 7 0.414 0.454 0.842 0.028* The probability Prob. (Ssimul. < Sobs.) given for each summary statistic was calculated from 1,000 virtual datasets simulated from the posterior distributions of parameters obtained under the focal scenario. Corresponding tail-area probabilities (P-values) were obtained as Prob. (Ssimul. < Sobs.) and 1.0 - Prob. (Ssimul. < Sobs.) for Prob. (Ssimul. < Sobs.) ≤ 0.5 and > 0.5, respectively (*, **, *** = tail-area probability < 0.05, < 0.01 and < 0.001, respectively). We used the mean number of alleles per locus (A), the mean expected heterozygosity (He), the mean allele size variance (V), and the mean MGW index across loci. Demographic scenarios are shown in Figure 2. Figure S1. Population genetic structure of Armillaria ostoyae. A and B: Inferred population structure according to STRUCTURE for each value of K from two to five generated from microsatellite and SNP data, using the standard admixture model (A) and the locprior admixture model (B). Each vertical line represents an individual, and the color composition displays the probability of belonging to each of the clusters. C and D: The probability of observing the data (X) under a given number of putative clusters (K) is shown as a function of
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