3.6 Redundancy analysis
We used DCA and RDA to analyze the relationship between species
characteristics and environmental factors. The plant data were sorted by
DCA, and the gradient lengths of the four sorting axes were obtained, of
which the maximum value was 0.63 < 3; therefore, we selected
the RDA method. The eigenvalues of the sorting axis and the cumulative
interpretation showed that daytime temperature (DT), nighttime
temperature (NT), and soil moisture condition (SM) explained 35.70% of
the plant change variation. The first two axes explained 35.70% of the
plant change variation and 100% of the species-environment relationship
variation. The results could explain all the variation in the
species-environment relationship (Table 5).
Within a certain range, the SM had the greatest influence on the
characteristic indexes of species, followed by DT, and NT, which exerted
the least influence on the change of the characteristic plant indexes
(Figure 4). All vegetation characteristic indexes were positively
correlated with SM, which had the greatest impact on Pn and WUE
(P <0.01) and the least impact on BGB, followed by Tr,
Gs, and LWC, which had a significantly positive correlation with SM
(P <0.05). Daytime temperature exerted the greatest
positive influence on LWC and H, as it had an extremely significant
positive correlation with both (P <0.01), and the least
influence on Pn. Daytime temperature exerted the greatest negative
influence on AGB and Gs, as it had a very significant negative
correlation with these parameters (P <0.01), and the
least influence on Ci (Table 6).