Figure 1 : a) Sampling locations of Embothrium coccineum . Circles, triangles and diamonds represent samples from the northern, center and southern part of the species distribution, respectively.Embothrium coccineum distribution area is highlighted in light grey and hatched lines represent ice limits from UMG. b)Principal component analysis (PCA) based on a 2,155 SNPs data set of Embothrium coccineum samples. Symbols and colors used for each locality are as in Figure 1a.
Figure 2: Structure analyses, for K = 2 (a) and K = 4 (b) of 38Embothrium coccineum individuals based on a 2.155 SNPs data set . Each individual is displayed from north to south represented by a vertical bar. Sampling location codes are as in Supplementary table 1. Color corresponds to genetic group and proportion of the genome assigned to each genetic group is given along the Y-axis.
Figure3: NJ tree reconstructed based on Nei´s distance between Embothrium coccineum individuals. NJ reconstruction based on (a) the PG_dataset of 2.155 SNPs, and (b) the 59 outlier loci putatively under selection. Sampling location codes are as in Supplementary table 1. Nodes with high support (> 0,95) are filled in black.
Figure4: Predictor overall importance plot. The R2 weighted importance of environmental variables with low level of covariance explaining the genetic variation across sampling locations as obtained from GF analysis. Environmental variables used in the analyses are the same as in Supplementary table 1; bio 14, Precipitation of the driest month (mm); bio 8, Mean temperature of the wettest quarter (°C); elevation, Elevation (masl); bio 9, Mean temperature of the driest quarter (°C); bio 4, Temperature seasonality (°C); bio 3, Isothermality (%); bio 13, Precipitation of the wettest month (mm).
Figure5: Estimation of divergence time in Embothrium coccineum based on Bayesian coalescent analysis using SNAPP. Nodes with high support (posterior probability > 0.99) are filled in black. Median ages are provided above nodes with 95% highest posterior densities (HDP) below. The divergence time was inferred only for the nodes showing high support (posterior probability > 0.99). Sampling location codes are as in Supplementary table 1; colored symbol for each sampling location match Fig. 1a.
Table 1: Genetic diversity of Embothrium coccineum in each sampling locality. Localities ID are as in Supplementary table 1. n, number of genotyped individuals; He, expected heterozygosity; Ho, Observed heterozygosity; FIS, inbreeding coefficient; PPL, percentage of polymorphic loci; PA, private alleles.
Table 2: Average FST values for pairwise comparisons among sampling locations of Embothrium coccineum in Chile based on a set of 2,155 SNPs. All p-values are significant (<0.05). Sampling location codes are as in Supplementary table 1. North: Ch, Cu and Nah; Center: PM, ChlN, ChlS and Pu; South: Coy, ChCh and TP.
Table 3: Redundancy analysis (RDA) partitioning among-population genetic variation in Embothrium coccineum into three components: environmental (Env), geographic (Geo) and North / Center-South coancestry (Anc). All p values <0.001.
Supplementary Table 1 : Environmental characteristics of each sampling location ofEmbothrium coccineum.
GPS coordinates are given for each sampling location. Environmental variables: bio 14, Precipitation of the driest month (mm); bio 8, Mean temperature of the wettest quarter (°C); Elv, Elevation (mamsl); bio 9, Mean temperature of the driest quarter (°C); bio 4, Temperature seasonality (°C); bio 3, Isothermality (%); bio 13, Precipitation of the wettest month (mm).