Fig 1.
The study area containing 221 sampling plots, which was investigated in 2007, 2011, and 2012.
Pale green represents arid areas that receive an annual precipitation of less than 200 mm; medium green indicates semiarid regions, where the annual precipitation is between 200 and 500 mm; and dark green indicates humid areas, where the annual precipitation is greater than 500 mm.
Table 1.
Environmental variables used for correlation analyses between environmental variables and Didymodon diversity in the study area.
Table 2.
Environmental variables used in modeling the distribution of Didymodon in the study area.
Table 3.
Didymodon species identified in Tibet, and their relative frequency, coverage, and importance value.
Table 4.
Number of Didymodon species along the altitude gradient and under different precipitation regimes in Tibet.
Table 5.
Correlation of species diversity and environmental factors affecting Didymodon in the study area.
Fig 2.
CCA ordination of 22 Didymodon species, environmental factors, and sampling plots in the study area.
A: CCA ordination of 22 Didymodon species and environmental factors; B: CCA ordination of 22 Didymodon species and the 181 sampling plots where they were found to grow. The black triangles represent 22 species of Didymodon; the blue circles represent the 181 sampling plots where Didymodon was found. The red arrows depict environmental factors: Temp represents temperature, Veg-cove represents vegetation cover, Veg-type represents vegetation type, and TDR 3.8 represents soil moisture soil depth of 3.8 cm. S1–S22 refers to Didymodon species listed in Table 3.
Fig 3.
The presence probability of Didymodon spatial distributions in Tibet.
The red circles represent the Didymodon species in the plots that were investigated.
Fig 4.
The importance of 22 environmental variables in modeling the distribution of Didymodon in Tibet.
The training gain describes how much better the MaxEnt distribution fits the presence data compared to a uniform distribution. The names and descriptions of environmental variables are listed in Table 2. The white squares represent the effect of removing a single variable from the full model. The gray squares represent the training gains when using only one environmental variable in MaxEnt. The black square represents the training gains when all variables were run in MaxEnt (1.61).
Fig 5.
Response curves for the relationship between the probability distributions of Didymodon and environmental variables.
The curves show the change in the response of Didymodon distribution to specific environmental variables.