对阿扎德查谟和克什米尔马哈希尔国家公园的多变量植被分析

S. Safeer, Rahmatullah Qureshi, Shakeel Sabir, Ubaid ul Hassan, S. Anwar
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引用次数: 0

摘要

这项研究旨在评估阿扎德查谟和克什米尔(AJK)马赫塞尔国家公园的植物组成。从 15 个不同地点记录了实地数据。采用四分法进行植被取样,同时使用地理定位系统(GPS)记录每个地点的确切位置、海拔高度、暴露程度和地理坐标。为了分析环境变量的重要性,采用了双向聚类、典型对应分析(CCA)和一般线性模型(GLM)响应曲线分析等方法进行多元统计分析。从植物学角度看,共记录了隶属于 45 个科的 109 个植物物种。在各科中,禾本科植物分布最广,共有 15 种。双向聚类分析将植被分为四大植物群落。采用 CCA 分析植被与环境的关系。植物种类与海拔梯度、总硝化甘油、电导率和钙含量呈明显的相关响应。GLM 反应曲线和 IVI 表明,Cynodon dactylon 是最主要的物种,其次是 Dalbergia sissoo 和 Adhatoda zeylinica。这项研究提供了有关生态植物组成的基础信息。它表明,该地区植物种类丰富,需要未来的研究人员进行详细分析。
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A multivariate vegetation analysis of Mahasheer National Park, Azad Jammu and Kashmir
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.
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审稿时长
12 weeks
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