## 3 Results
### Community Distribution Modeling along the Environmental Gradients  
NMDS (Figure 4a-d) and PCA are used to show the relationship between identified communities and environmental gradients (Figure 4e). The most representative environmental factors that drove the plant community structure were altitude, slope angle and aspects, NE, slope SW, K, pH, OM, loam, silt, sand, clay, temperature, HI, and WS (Table 2). Environmental gradients distinguish the 23 sample sites into 3 communities in both ordinations, as TWINSPAN, CA (Figure 2), and TWCA have already revealed (Figure 3).  
Figure 3: TWCA analysis displaying three distinct communities recognized based on 162 plant species recorded from 23 stands. Each blue dot represents the existence of a species, whereas each white dot indicates its absence. (For the complete names of plant communities, see Figure 2).  
Figure 2: Cluster analysis displaying three different plant communities’ recognition based upon the grouping of 23 stands and 162 plant species. CIC, _Cedrus–Isodon–Cynodon_; CCD, _Cedrus–Cynodon–Dryopteris_; SCD, _Sambucus–Cedrus–Desmodium_.  
Figure 4: Multivariate analyses among plant communities of pure Deodar forest and environmental variables. (**a–d**) Non-Multidimensional Scaling (NMDS) of three plant communities and their ecological variables such as geographic (**a**), slope (**b**), edaphic (**c**), and climatic (**d**). (**e**) Principal Component Analysis (PCA) ordination of three communities along the environmental variables. For the complete names of plant communities, see Figure 2.  
In constrained PCA ordination, the PC1 axis accounted for the most explanatory variance (21.6%), whereas the PC2 axis accounted for the least (14%). By distinguishing the vegetation of the pure Deodar forest into three communities (Figure 4a-e), the considerable effect of the altitudinal gradient was revealed. Altitude (1936-2373 m), slope angle (25-85\({}^{\circ}\)), and sandy (29-48%) and loamy soil texture all indicated a positive and substantial association in the SCD community. Potassium (216 mg kg\({}^{-1}\)), EC (3.3 dsm\({}^{-1}\)), CaCO\({}_{3}\) (8.45 mg kg\({}^{-1}\)), and organic matter (1.03%) were the edaphic variables that shaped this plant community. Furthermore, wind speed (1.45 ms\({}^{-1}\)) and temperature (25.8 \({}^{\circ}\)C) were found to have a positive and significant association. In contrast with this, the CCD community was primarily found in the lower mountainous ranges (1580.8-1982 m.a.s.l.) and showed positive and significant relationships with the northeastern slope, silty (32-58%) and sandy (15.8-55%) loamy soil texture, and barometric pressure (814.3 pa). Nonetheless, the CIC community was recognized at the middle altitudinal range (1769.8-1869.5 m). This community revealed a significant positive correlation with the northeastern to southwestern slope, pH (6.3), wet bulb (19.7), and dew point (17.7). Since silt, sand, and clay were representative in both NMDS and PCA (Figure 4) and are expressed in percentage (Table 2), the relationship of CIC, CCD, and SCD plant communities was plotted with the said three edaphic elements in a ternary plot (Figure 5). Likewise, a clear clustering in plant communities was observed according to soil composition based on these three elements. Based on the mean values, the CCD and CIC communities were hosted by soils having the maximum silty texture, i.e., 43.7% and 42.8%, respectively. On the other hand, the SCD community was hosted on soil that comprised a higher sandy texture (41.7%). As each plant community comprised several stands, the soil-texture values recorded for each stand were found to have no significant differences (Figure 5). These results reveal that the tree layer determines the structure of the ground cover more than soil does.