TOPOGRAPHIC AND EDAPHIC CONTROL OF ARBOREAL VEGETATION AND THE DISTRIBUTION AND GROWTH OF TREE SPECIES IN MOIST TEMPERATE AREAS OF HIMALAYAN AND HINDUKUSH REGIONS OF PAKISTAN

Abstract

The role of edaphic and topographic variables on the distribution pattern of conifer species in moist temperate area of western Himalayan and Hindukush region of Pakistan is investigated. Arboreal vegetation of 41 sites was analyzed using point-centered quarter method. Soil samples from 41 different sites were collected to determine the edaphic characteristics and two stratifying variables i.e., elevation and slope were noted. Both classification and ordination methods were used to determine the underlying group structure and vegetation composition. For the purpose of ordination principal component analysis (PCA) and for classification Ward’s cluster analysis was employed. Four groups of species were separated on the basis of topographic and edaphic variables by Ward’s cluster analysis. Group 1 was dominated by Pinus wallichiana, group II & III were dominated by Abies pindrow while group IV was compose of two dominant species Cedrus deodara and Pinus wallichiana. The four groups also differentiated with respect to elevation, slope, salinity and electrical conductivity. The first component of PCA ordination of vegetation was correlated with elevation, soil organic matter (OM), pH, water holding capacity and soil conductivity; the second component exhibited association with elevation, slope, OM and conductivity while the third with slope, soil salinity and conductivity. Four principal component axes were well correlated with topographic and edaphic factors. Axis 1 was highly (p<0.001) significantly correlated with pH, organic matter and conductivity while axis 2 showed significant correlation (p<0.001) with elevation, slope, pH and conductivity. Axis 3 significantly correlated (p<0.001) with salinity and conductivity. Axis 4 exhibited marked relationship (p<0.001) with organic matter of soil and slope angle. Correlation coefficient between PCA vegetation and PCA environmental variables was also sought that exhibited significant correlation between components 2.