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Multivariate analyses of the vegetation of the western Himalayan forests of Muzaffarabad district, Azad Jammu and Kashmir, Pakistan

机译:巴基斯坦,阿扎克拉巴德区西部喜马拉雅林植被的多元分析

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Muzaffarabad district, Azad Jammu and Kashmir, Pakistan is part of the western Himalaya and rich in phytodiversity, but until now little was known about its plant diversity on larger spatial scale and vegetation composition through multivariate statistical tools. To fill this research gap, the whole district was ecologically explored for the collection of field data from August 2014 to July 2016. For vegetation studies, a total of 16 altitudinal transects comprising 110 sampling stations (samples) with 990 plots were studied by using a stratified random vegetation sampling method. Different multivariate statistical tools including Monte Carlo permutation test, Indicator species analysis, hierarchical clustering, ordination, variation partitioning and multi-response permutation procedures tests were used for the first time for the study area to elucidate the number of significant vegetation groups, ranking and placement of plant species in these groups, classification of vegetation units, detection of important gradients, importance of groups of environmental variables and pairwise compositional differences of the species groups respectively. The results showed that all the recorded 343 plant species belong to seven significant plant associations which were further placed into 5 major forest types. Out of the total 19 variables studied, CCA detected the significant contribution of the majority (simple effects: 12; unique effects: 8) of them. The latter (unique effects) in descending order included altitude, forest cover, deforestation, community maturity, forest density, latitude, slope aspect, and longitudinal variations. Similarly, variation partitioning results depicted that topography was the leading driver affecting vegetation distribution, followed by the biotic and edaphic factors. The forest edges, especially the sub-alpine ecosystem, were most diverse, supported higher tree density and also faced maximum deforestation pressure. Furthermore, rangelands in the temperate to alpine zones were affected by heavy overgrazing. Due to the disrupted local ecosystem functioning, the study area needs proper management and conservations plans to save its biodiversity wealth in this part of western Himalaya.
机译:巴基斯坦穆扎牧场区,阿扎德·卡姆和克什米尔,是喜马拉雅西部的一部分,富裕的幽灵大学,但到目前为止,通过多元统计工具,在较大的空间尺度和植被组合上众所周知。为了填补这项研究差距,整个地区从2014年8月到2016年7月的现场数据进行了生态探索。对于植被研究,通过使用A研究了总共16种,总共16个加入站(样本),其中包含了990个地块的110个采样站(样品)。分层随机植被采样方法。包括Monte Carlo置换测试,指示物种分析,分层聚类,秩序,变化分区和多响应置换过程测试的不同多变量统计工具是第一次用于阐明重要植被组的数量,排名和放置的数量这些群体中的植物种类,植被单位的分类,分别检测重要梯度,环境变量群的重要性和物种组的成对成分差异。结果表明,所有记录的343种植物种属于七种重要植物关联,进一步置于5种主要森林类型。除了19种变量中,CCA检测到大多数(简单效果:12;独特效果:8)的重大贡献。后期(独特效果)下降包括海拔高度,森林覆盖,森林砍伐,社区成熟,森林密度,纬度,斜坡方面和纵向变异。类似地,描绘了地形的变化分区结果是影响植被分布的主要驾驶员,其次是生物和助理因素。森林边缘,特别是亚高山生态系统,最多样化,支持更高的树密度,并且面临最大的森林砍伐压力。此外,温带到高山区的牧场受重额过高的影响。由于扰乱了当地生态系统运作,研究区需要适当的管理和保护计划,以便在大喜马拉雅西部的这一部分储存其生物多样性财富。

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