Table 4.

Mixed‐effect models show the correlation between pairwise genetic distance and resistance distance of different landscape variables

Model	Type of model	Variables	VIF	$R_{\mathrm{\beta }}^2$	AICc	∆AICc	Weight (w i)
A	Reduced	Aspect	1.02	0.008	−23446.40	0.00	0.73
		TC	1.03
B	Reduced	Aspect	1.02	0.008	−23443.30	3.04	0.16
		TC	1.03
		Road	2.39
C	Reduced	Aspect	1.02	0.009	−23440.30	6.13	0.03
		TC	1.03
		Road	2.39
		Vegetation	1.22
D	Reduced	Aspect	1.02	0.010	−23440.10	6.30	0.03
		TC	1.03
		Road	2.39
		Vegetation	1.22
		Elevation	1.93
E	Reduced	Aspect	1.02	0.009	−23438.40	8.02	0.01
		TC	1.03
		Road	2.39
		Elevation	1.93

To minimize colinearity among predictors, all variables with VIF values > 5 were removed. VIF: Variance Inflation Factor. The best‐fitting model was selected based on the corrected Akaike information criterion (AICc, ∆AICc, wi). We used R ² statistics ($R_{\mathrm{\beta }}^2$) to describe the amount of variation explained by the model. Models with the highest AICc support are in bold (∆AICc ≤ 2). Marginally supported models are also indicated (∆AICc ≤ 7). TC: topographical complexity.