Figure 1.
Hainan map and distribution of the 108 sample plots of the field survey.
The red circles indicate plots.
Table 1.
Principal component values, eigenvalues, and contribution rate of variables in principal components analysis.
Figure 2.
Canonical correspondence analysis (CCA) between (A), total species; (B), orchid species; (C), non-orchid species with extremely small populations and eight factors.
The numbers from 1 to 20 represent the 20 species with extremely small populations, as shown in Appendix S1. E1, canopy density; E2, altitude; E3, slope aspect; E4, slope gradient; E5, road quality; E6, distance between population and road; E7, surrounding population density; E8, land use type.
Table 2.
Bivariate correlation analysis between the appearance of the extremely small populations and the measured variables.
Figure 3.
The relationship between eight factors and the species richness of extremely small populations (mean and standard errors).
(A), distance between populations and road (Road 1, Road 2, Road 3, and Road 4 represent rural sandstone road, rural cement road, township road, and county road, respectively); (B), different levels of surrounding population density and land use; (C), different levels of altitudes; (D), coefficient similarity values of neighboring altitudes (the numbers from 1 to 6 represent altitude ranges of 0–300 m, 300–600 m, 600–900 m, 900–1200 m, 1200–1500 m, and 1500–1800 m); (E), different levels of slope aspects; (F), different levels of slope gradients; (G), different levels of canopy density. Different Lowercase letters (a, b, c) indicate significant difference at p<0.05.
Table 3.
Frequency of extremely small populations appearing on different slope aspects.
Table 4.
Distance correlation analysis between extremely small populations and different slope gradients.
Table 5.
Distance correlation analysis between extremely small populations and different canopy densities.