The development of vegetation communities is typically influenced by their response to variation in environmental, geographic and as well as physiographic gradients. The current study was planned to evaluate the influence of environmental gradients upon the structure of plant communities and to highlight their respective indicators in subalpine pastures of the Himalaya, Pakistan. In relation to this aim, ecological techniques were used following the Line transect (50 m) method to quantify the vegetation structure of the study area. Soil samples were collected from each sampling site and edaphic gradients were examined using standard protocols. Weather station data (Kestrel 4000) was used to determine the climatic gradients, GPS data was used to record the geographic and physiographic gradients. PCORD software was used to recognize communities through two-way indicator species analysis (TWINSPAN), R and CANOCO software was employed for ordination analysis to find variation directories of different plant species. A total of 56 plant species, recorded from 21 sampling sites, were grouped into four plant communities with the help of environmental gradients. The highest index of similarity was recorded between the Bergenia-Sibbaldia-Rheum and Sibbaldia-Rheum-Bergenia communities and highest dissimilarity between Bergenia-Sibbaldia-Rheum and Juniperus-Sibbaldia-Poa communities. The highest number of plant species (50 species), maximum alpha diversity (H′ = 3.38) and beta diversity was reported in Sibbaldia-Rheum-Bergenia community (0.95), but Pielou's evenness was highest (0.89) in Juniperus-Sibbaldia-Poa among all recorded communities. Besides, the edaphic (i.e. organic matter, phosphorous, pH and soil texture) and climatic factors (temperature, humidity) were the strong environmental gradients that were responsible for structuring and hosting the diverse plant communities in subalpine meadows. Techniques adapted in the current study for identification of vegetation indicators could further be used for conservation management.

植被群落的发展通常受其对环境，地理和地理梯度变化的反应的影响。计划进行本研究，以评估环境梯度对植物群落结构的影响，并突出显示巴基斯坦喜马拉雅山的亚高山草场中它们各自的指标。为此目的，按照线样（50 m）方法采用了生态技术来量化研究区域的植被结构。从每个采样点收集土壤样品，并使用标准方案检查土壤梯度。气象站数据（Kestrel 4000）用于确定气候梯度，GPS数据用于记录地理和自然梯度。使用PCORD软件通过双向指示物物种分析（TWINSPAN）识别群落，使用R和CANOCO软件进行排序分析以查找不同植物物种的变异目录。借助环境梯度，将来自21个采样点的总共56种植物物种分为四个植物群落。最高相似度指数记录在Bergenia-Sibbaldia-Rheum和Sibbaldia-Rheum-Bergenia社区以及Bergenia-Sibbaldia-Rheum和Juniperus-Sibbaldia-Poa社区之间的差异最大。西伯利亚-大黄-贝格尼亚社区的植物物种数量最多（50种），最大α多样性（H'= 3.38）和β多样性（0.95），而朱尼普鲁斯-西伯利亚-波阿省的Pielou均匀度最高（0.89）。在所有记录的社区中。此外，深层环境（即有机质，磷，pH和土壤质地）和气候因素（温度，湿度）是强烈的环境梯度，是构造和容纳亚高山草甸不同植物群落的原因。当前研究中采用的用于识别植被指标的技术可进一步用于保护管理。