祁连山国家公园青海片区森林大样地生物多样性特征

Q948.1%S718.5; [目的]通过监测森林大样地植物群落特征的长期动态变化,揭示物种多样性空间格局及维持机制,为该区域的生物多样性保护提供科学依据.[方法]以祁连山区青海云杉林生态系统为研究对象,采用相邻格子法进行大样地乔木植株每木调查,并解析其生物多样性调控因素.[结果]青海云杉林生态系统的乔木总数为35 835株,青海云杉和祁连圆柏分别占据57.84%和23.82%.物种丰富度和平均株高分别为3种和10.7 m.Shannon-Wiener 指数和Simpson指数分别为0.74和0.43,Shannon-Wiener指数偏低,但Simpson指数较高,存在物种数量集中度较高现象....

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Published in西北植物学报 Vol. 44; no. 12; pp. 1973 - 1979
Main Authors 王定晖, 索南才让, 于红妍, 杜岩功
Format Journal Article
LanguageChinese
Published 青海省环境工程技术评估中心,西宁 810008%青海省饲草料技术推广站,西宁 810007%祁连山国家公园青海服务保障中心,西宁 810056%中国科学院西北高原生物研究所,西宁 810001 2024
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ISSN1000-4025
DOI10.7606/j.issn.1000-4025.20240336

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Abstract Q948.1%S718.5; [目的]通过监测森林大样地植物群落特征的长期动态变化,揭示物种多样性空间格局及维持机制,为该区域的生物多样性保护提供科学依据.[方法]以祁连山区青海云杉林生态系统为研究对象,采用相邻格子法进行大样地乔木植株每木调查,并解析其生物多样性调控因素.[结果]青海云杉林生态系统的乔木总数为35 835株,青海云杉和祁连圆柏分别占据57.84%和23.82%.物种丰富度和平均株高分别为3种和10.7 m.Shannon-Wiener 指数和Simpson指数分别为0.74和0.43,Shannon-Wiener指数偏低,但Simpson指数较高,存在物种数量集中度较高现象.森林大样地Shannon-Wiener受乔木高度、物种丰富度和Simpson指数的极显著影响.机器学习模型训练集和测试集的决定系数分别为0.95和0.93,均方根误差分别为0.06和0.08,表明模型对Shannon-Wiener 指数的解释能力和预测精度均较高.[结论]青海云杉林物种多样性较低且受乔木高度、物种丰富度和Simpson指数的显著影响,其对维持该区域的生物多样性具有重要作用.
AbstractList Q948.1%S718.5; [目的]通过监测森林大样地植物群落特征的长期动态变化,揭示物种多样性空间格局及维持机制,为该区域的生物多样性保护提供科学依据.[方法]以祁连山区青海云杉林生态系统为研究对象,采用相邻格子法进行大样地乔木植株每木调查,并解析其生物多样性调控因素.[结果]青海云杉林生态系统的乔木总数为35 835株,青海云杉和祁连圆柏分别占据57.84%和23.82%.物种丰富度和平均株高分别为3种和10.7 m.Shannon-Wiener 指数和Simpson指数分别为0.74和0.43,Shannon-Wiener指数偏低,但Simpson指数较高,存在物种数量集中度较高现象.森林大样地Shannon-Wiener受乔木高度、物种丰富度和Simpson指数的极显著影响.机器学习模型训练集和测试集的决定系数分别为0.95和0.93,均方根误差分别为0.06和0.08,表明模型对Shannon-Wiener 指数的解释能力和预测精度均较高.[结论]青海云杉林物种多样性较低且受乔木高度、物种丰富度和Simpson指数的显著影响,其对维持该区域的生物多样性具有重要作用.
Abstract_FL [Objective]Long-term monitoring of plant community dynamics in large forest plots helps re-veal the spatial patterns and underlying mechanisms that sustain species diversity.These insights form a solid scientific foundation for biodiversity conservation in the region.[Methods]Taking the typical forest ecosystem as the research object in the Qinghai area of Qilian Mountain National Park,we used the adja-cent grid method to conduct a survey of each tree in a 24 hm2large sample plot.[Results]There was a to-tal of 35 835 trees,of which Picea crassifolia and Juniperus przewalskii accounted for 57.84%and 23.82%,respectively.Species richness and plant height were 3 species and 10.7 m,respectively.Shan-non-Wiener and Simpson index of spruce forest were 0.74 and 0.43,respectively,Shannon-Wiener index was relatively low.The Shannon-Wiener index was significantly influenced by tree height,species rich-ness,and Simpson index.As the tree height increased,the Shannon-Wiener was decreased,while the spe-cies richness and Simpson index were increased significantly.The coefficients of determination for the training and testing sets of the machine learning model were 0.95 and 0.93,respectively,with root mean square errors of only 0.06 and 0.08.This indicated that the model had a high explanatory power and pre-diction accuracy for the Shannon-Wiener data.[Conclusion]The species diversity of the Qinghai spruce forest is relatively low and is significantly influenced by tree height,species richness,and the Simpson in-dex.These factors play a crucial role in maintaining the biodiversity of the region.
Author 王定晖
杜岩功
索南才让
于红妍
AuthorAffiliation 青海省环境工程技术评估中心,西宁 810008%青海省饲草料技术推广站,西宁 810007%祁连山国家公园青海服务保障中心,西宁 810056%中国科学院西北高原生物研究所,西宁 810001
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Author_FL SUONAN Cairang
YU Hongyan
WANG Dinghui
DU Yangong
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DocumentTitle_FL Biodiversity characteristics of large forest plots in Qinghai area of Qilian Mountain National Park
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Keywords Shannon-Wiener指数
species richness
祁连山南坡
Qinghai spruce forest
Shannon-Wiener index
物种丰富度
Southern slope of Qilian Mountains
青海云杉林
forest large sample plots
森林大样地
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PublicationTitle 西北植物学报
PublicationTitle_FL Acta Botanica Boreali-Occidentalia Sinica
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