A multivariate vegetation analysis of Mahasheer National Park, Azad Jammu and Kashmir

By

Safeer, Sajid
Qureshi, Rahmatullah
Sabir, Shakeel
Ul Hassan, Ubaid
Anwar, Sheikh Muhammad Farhan

Type

Article

Date of Publication

2024-5-23

Original Publication

Silva Balcanica

Volume

25

Series / Issue

Issue: 1

Pages

59--71

Subjects

AJK , canonical correspondence analysis (CCA) , Cluster analysis , general linear model (GLM) , Mahseer

Contributed by

Pensoft Publishers

Language

English

Published by

Sofia, Bulgaria Forest Research Institute - Bulgarian Academy of Sciences (FRI-BAS) [2001]-

Identifiers

DOI: https://doi.org/10.3897/silvabalcanica.25.e116361

 

Abstract

This research work targets to evaluate the floristic composition of Mahseer National Park, Azad Jammu and Kashmir (AJK). Field data was recorded from fifteen different sites. The Quadrat method was used for vegetation sampling while the exact location of each site, altitude, exposure and geographical coordinates were documented by using geographical positioning system (GPS). To analyze the significance of environmental variables, multivariate statistical analysis was carried out by using two-way clustering, canonical correspondence analysis (CCA) and general linear model (GLM) response curve analysis. Floristically, 109 plant species belonging to 45 families were recorded. Among families, Poaceae was most commonly distributed, accounting for 15 species in total. Two-way cluster analysis categorized the vegetation into four major plant communities. CCA was used to analyze the vegetation-environment relation. Plant species showed a significant correlation response against altitudinal gradient, total nitro-gen, electrical conductivity and calcium contents. The GLM response curve and IVI demonstrated that Cynodon dactylon was the most dominant species followed by Dalbergia sissoo and Adhatoda zeylinica. This study provided the baseline information about the eco-floristic composition. It suggested that the area is floristically rich, and needs to be analyzed in detail by future researchers.