Table 3.

Summary of landscape effects on measures of pairwise genetic differentiation (G’’_ST and D_PS) as resulting from MLPE models at the link level, separately for (a) Anemone nemorosa, (b) Oxalis acetosella, and (c) Polygonatum multiflorum

Landscape metrics	G''ST	DPS
(a) Anemone nemorosa
FOREST_1:3	/	∩
pcARABvsGRASS_1:3a	X
pcARABvsGRASS_1:2b		X
LFRINGE_1:3	/	/
Marginal R2	0.16	0.25
Landscape R2	0.16	0.25
% Landscape	99.2	100.0
(b) Oxalis acetosella
FOREST_1:3	X	X
ARABLE_1:3		/
RAPE_1:2	X
LWOOD_1:7		X
LWATER_1:3	\
LROAD_1:5	\
SHANNON_2:3		\
Marginal R2	0.11	0.10
Landscape R2	0.11	0.09
% Landscape	99.9	99.4
(c) Polygonatum multiflorum
FOREST_1:2	X
SEMNATGRASS_1:3	/U	/
ORCHARD_2:3		/
LWOOD_1:5		\
LROAD_1:7	X
LROAD_1:2		\
Marginal R2	0.18	0.33
Landscape R2	0.17	0.30
% Landscape	95.7	91.4

All important effects, i.e., those with an importance value ≥ 0.5 (see main text), are symbolized as follows: / positive effect, \ negative effect, X interactive effect (see Fig. 3), ∩ and ∪ unimodal effect with maximum and minimum, respectively, at an intermediate level of the landscape metric, /∩, \∩ and /∪ asymmetric unimodal effects with positive or negative trend, respectively. In addition, R² values for each model are provided: marginal R² (variation explained by fixed effects, i.e. jointly by basic population genetic determinants and landscape metrics), landscape R² (variation explained uniquely by landscape metrics) and the percentage of the marginal R² that can be uniquely attributed to landscape effects (%Landscape). See Table 1 for explanations on variable names. The ratio added to each variable name corresponds to the most influential width-to-length radio of the landscape strips. See Table S6.2 for complete model results. Visualizations of the effects are presented in Figs. 2, 3, and S6.1 to S6.3

^aPrincipal component from CEREAL_1:3 (r = 0.95), RAPE_1:3 (r = 0.90) and GRASS_1:3 (r = − 0.92)

^bPrincipal component from CEREAL_1:2 (r = 0.96), RAPE_1:2 (r = 0.90) and GRASS_1:2 (r = − 0.92)