title: Diversity of woodland communities and plant species along an altitudinal gradient in the Guancen Mountains, China.
abstract: Study on plant diversity is the base of woodland conservation. The Guancen Mountains are the northern end of Luliang mountain range in North China. Fifty-three quadrats of 10 m × 20 m of woodland communities were randomly established along an altitudinal gradient. Data for species composition and environmental variables were measured and recorded in each quadrat. To investigate the variation of woodland communities, a Two-Way Indicator Species Analysis (TWINSPAN) and a Canonical Correspondence Analysis (CCA) were conducted, while species diversity indices were used to analyse the relationships between species diversity and environmental variables in this study. The results showed that there were eight communities of woodland vegetation; each of them had their own characteristics in composition, structure, and environment. The variation of woodland communities was significantly related to elevation and also related to slope, slope aspect, and litter thickness. The cumulative percentage variance of species-environment relation for the first three CCA axes was 93.5%. Elevation was revealed as the factor which most influenced community distribution and species diversity. Species diversity was negatively correlated with elevation, slope aspect, and litter thickness, but positively with slope. Species richness and heterogeneity increased first and then decreased but evenness decreased significantly with increasing elevation. Species diversity was correlated with slope, slope aspect, and litter thickness.
authors.affiliation: Institute of Loess Plateau, Shanxi University, Taiyuan 030006, China.
authors.forename: Dongping
authors.initials: D
authors.lastname: Meng
authors.forename: Jin-Tun
authors.initials: JT
authors.lastname: Zhang
authors.forename: Min
authors.initials: M
authors.lastname: Li
mesh_terms: D000531:Altitude; D044822:Biodiversity; D002681:China; D004777:Environment; D005843:Geography; D009010:Monte Carlo Method; D015999:Multivariate Analysis; D013696:Temperature; D014197:Trees / Q000502:physiology*