3.4 Influence of landscape on genetic diversity
Analysis of the db-RDA model in Shunchang County showed that different
landscape types had significant effects on the genetic diversity at
three scales (Table 4). At the three scales of 300 m, 800 m, and 1,000
m, the percentage of P. massoniana was significantly related to
the genetic diversity of this species (P (300 m) = 0.031;P (800 m) = 0.022; P (1,000 m) = 0.006), explaining
47.478%, 45.730%, and 43.342% of the variation, respectively (Table
4). Urban landscape was significantly correlated with the genetic
diversity only at 800 m (P = 0.046), whereas mixed forest with
hosts had significant effects at scales of 800 m and 1,000 m
(P (800 m) = 0.038; P (1,000 m) = 0.031). At the 1,000 m
scale, additional types of landscapes had significant correlations,
including P. elliottii (P = 0.04), farmland (P =
0.018), and roads (P = 0.046) (Table 4). In Xiapu, in addition to
the influence of P. massoniana at the three scales, other
landscape types at different scales also showed significance (Table 5).
At the 800 m scale, P. elliottii was significantly correlated
with the genetic diversity (P = 0.019), explaining 23.237% of
the variation (Table 5). At the 1,000 m scale, similar to Shunchang,
there were more relevant landscape variables than at the two smaller
scales, primarily including mixed forest with hosts (P = 0.032),
roads (P = 0.032), farmland (P = 0.007), and urban
(P = 0.041) (Table 5). In both areas, the different landscape
types could affect the genetic diversity of M. alternatus , and
the number of landscape types with effects increased with the increase
in scale.
GAM analysis was performed to explain the nonlinear relationship in the
db-RDA analysis. According to the results, the landscape variables fit
well on the first two dimensions of the PCoA ordination (Figures 5
(Shunchang) and 6 (Xiapu)). Pinus massoniana increased gradually
with the first PCoA axis or the second axis in both areas, indicating
that P. massoniana was positively correlated with genetic
diversity (Figure 5A, B, E; Figure 6A, B, E). The landscape types that
increased along the first PCoA axis also included roads in Shunchang
(Figure 5I), whereas mixed forest with hosts and P. elliottiimainly increased with the second PCoA axis (Figure 5C, F, G). In Xiapu,
mixed forest with hosts at the 800 m scale and P. elliottii and
mixed forest with hosts at the 1,000 m scale also increased with the
first PCoA axis (Figure 6C, D, F, H). Urban decreased with the second
PCoA axis in both areas (Figure 5D; Figure 6G), whereas farmland
decreased with the first PCoA axis or the second axis (Figure 5H or
Figure 6I), which indicated that the genetic diversity was negatively
correlated with urban and farmland landscapes.