云南省思茅松林群落数量分类及物种多样性与自然环境的关系  

Quantitative classification of Pinus kesiya var. langbianensis communities and their species richness in relation to the environmental factors in Yunnan Province of Southwest China.

作　　者：李帅锋[1,2] 苏建荣[1,2] 刘万德[1,2] 郎学东[1,2] 张志钧[1,2] 苏磊[1,2] 杨华景 

机构地区：[1]中国林业科学研究院资源昆虫研究所,昆明650224 [2]国家林业局普洱森林生态系统定位研究站,昆明650224 [3]云南省普洱市林业科学研究所,云南普洱665000

出　　处：《生态学杂志》2013年第12期3152-3159,共8页Chinese Journal of Ecology

基　　金：中国林科院中央级公益性科研院所基本科研业务费专项(riricaf2012001Z)资助

摘　　要：通过对云南省中南部和西南部9个县天然分布的思茅松林群落的调查,应用双向指示种分析(TWINSPAN)对群落进行数量分类,采用主成分分析(PCA)、冗余分析(RDA)和广义可加模型(GAM)等方法对群落类型进行排序,分析群落类型、物种分布及物种多样性与环境因子的关系。结果表明:(1)研究区域的思茅松林可分为8个主要群落。(2)对群落和物种分布产生显著影响的主导因子是海拔,其次是年均气温、年均降雨量和坡度。RDA的排序轴反映思茅松林群落物种尤其是优势物种分布随海拔、年均气温、年均降雨量和坡度的变化而变化,思茅松的分布与海拔和年均降雨量有显著的负相关,与年均气温和坡度有显著正相关。(3)GAM拟合结果显示,海拔和年均降雨量对物种丰富度的影响达极显著水平(P<0.001)。A field survey was conducted on the naturally distributed Pinus kesiya var. laugbi- auensis communities in nine counties of south-central and southwest Yunnan Province. The two- way indicators species analysis （TWINSPAN） was applied to quantitatively classify the communi- ties, and the principal component analysis （PCA） and redundancy analysis （RDA） were adopt- ed to coordinate the communities, with the relationships between the community type, species distribution, species diversity, and environmental factors analyzed. In the study area, the P. kesiya var. laugbiauensis communities could be classified into eight major communities. The dominant environmental factors affecting the communities and species distribution were in the or- der of altitude, mean annual air temperature, mean annual precipitation, and slope. The RDA ordination axes indicated that the distribution of the species, especially of the dominant species, varied with the variations of altitude, mean annual air temperature, mean annual precipitation, and slope. The distribution of P. kesiya var. laugbianeusis had significant negative correlations with altitude and mean annual precipitation, and significant positive correlations with mean annu- al temperature and slope. The generalized additive model （GAM） fitted the responses of species richness to various environmental factors, with the effects of altitude and mean annual precipitati- on on the species richness being significant （ P 〈0. 001 ）.

关 键 词：双向指示种分析 冗余分析 主成分分析 广义可加模型 物种丰富度 群落类型 

分 类 号：Q948[生物学—植物学]