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Table 3 Results of generalized dissimilarity modeling (GDM) analysis

From: Population genetic structure is shaped by historical, geographic, and environmental factors in the leguminous shrub Caragana microphylla on the Inner Mongolia Plateau of China

  Model IBD PC1 PC2 PC3 IBE  
  Dev. P β p β p β p β p β p
SSR 0.780 <0.01 0.132 0.01 0.465 0.02 0.008 0.62 0.088 0.14 0.561 0.02
cpDNA 0.748 <0.01 0.627 <0.01 0.442 <0.01 0.000 0.94 0.031 0.14 0.473 <0.01
GBS 0.892 <0.01 0.717 <0.01 0.537 <0.01 0.014 0.48 0.071 0.07 0.622 <0.01
  1. GDM provides a coefficient (β) for each predictor variable that estimates the contribution of that variable to explaining variation in a response variable, in this case genetic distance. The predictor variables used in our analysis included geographic distance (D) and the first three PC axes resulting from PCA analysis on 19 bioclimatic variables at each sampling site (PC1, PC2, and PC3). βE represents the total contribution of environmental distance (the sum of the coefficients for each PC axis)
  2. The overall model fit (Deviance Explained: Dev.) and significance (p), regression coefficients (β) and p-values for each predictor variable (geographic distance [IBD] and environmental PCs [PC1, PC2, and PC3]), and cumulative coefficient of IBE (for all PCs) are shown. Significant values are in bold