Herb stratum diversity and community structure in Gurez valley of Kashmir Himalaya: application of multivariate techniques in community analyses
收藏Mendeley Data2024-06-25 更新2024-06-27 收录
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https://tandf.figshare.com/articles/dataset/Herb_stratum_diversity_and_community_structure_in_Gurez_valley_of_Kashmir_Himalaya_application_of_multivariate_techniques_in_community_analyses/23244198
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In temperate forests, herbs comprise up to 90% of species richness yet received less attention, and their community structure, diversity patterns, and driving mechanisms still remain understudied. We provide a phytosociological overview of herb stratum to develop a vegetation model to characterize and designate vegetation groups and interpret their diversity and species distribution patterns. Multivariate analyses – classification (TWINSPAN) and ordination (indicator species analysis [ISA], non-metric multidimensional scaling [NMDS], and Canonical Correspondence Analysis [CCA]) were applied to data set collected from 32 plots across Gurez valley, Kashmir Himalaya to recognize the understory plant communities, determine the environmental predictors and highlight their significance. Altogether, 131 herbs from 38 families were recorded. TWINSPAN classified understory vegetation into three communities: Tanacetum multicule – Pedicularis pectinata – Aconitum heterophyllum (TPA), Taraxacum officinale – Trifolium repens – Plantago major (TTP), and Impatiens brachycentra – Tussilago farfara – Galium boreale (ITG). Diversity indices and species richness vary significantly, following the trend TTP>TPA>ITG. CCA revealed that disturbances, canopy, altitude, and moisture were the strongest parameters determining species differentiation. The study outlines a methodological workflow based on analytical methods and vegetation-plot data that describe vegetation groups and might be helpful in further in-depth vegetation classification syntheses and decision-making in conservation, global change issues, and management.
在温带森林生态系统中,草本植物的物种丰富度占比可达90%,但相关研究却长期被忽视,其群落结构、多样性格局及驱动机制仍未得到充分探索。本研究针对草本层开展植物社会学综述,旨在构建植被模型以表征、界定植被群丛,并阐释其多样性特征与物种分布规律。研究将多元分析方法——包括分类分析(双向指示种分析[TWINSPAN])与排序分析(指示种分析[ISA]、非度量多维标度[NMDS]、典范对应分析[CCA])——应用于采集自克什米尔喜马拉雅古雷兹山谷32个样地的数据集,以此识别林下植物群落、明确环境驱动因子并阐明其作用显著性。本次调查共记录到38科131种草本植物。双向指示种分析将林下植被划分为3个群落:菊叶蒿(*Tanacetum multicule*)– 具齿马先蒿(*Pedicularis pectinata*)– 异叶乌头(*Aconitum heterophyllum*)(TPA)、蒲公英(*Taraxacum officinale*)– 白三叶(*Trifolium repens*)– 大车前(*Plantago major*)(TTP)以及短距凤仙花(*Impatiens brachycentra*)– 款冬(*Tussilago farfara*)– 北极拉拉藤(*Galium boreale*)(ITG)。各样地的多样性指数与物种丰富度均存在显著差异,整体呈现TTP>TPA>ITG的趋势。典范对应分析结果显示,干扰强度、冠层覆盖度、海拔与土壤湿度是决定物种分异的核心环境参数。本研究基于分析方法与植被样地数据,提出了一套标准化的植被群落描述工作流程,可为后续深入开展植被分类综合研究,以及在生物多样性保护、全球变化应对与生态系统管理等领域的决策提供科学参考。
创建时间:
2023-06-28



