Vegetation and species diversity patterns in conservation areas near big cities are poorly known. These are important recreational areas used also for educational purposes. Therefore, investigations of local diversity patterns are urgently needed. The Baihua Mountain Reserve is close to the city of Beijing and is the northern end of the Taihang mountain range in north China. Sixty-one 10 × 20 m quadrats of plant communities were established along gradients for elevation (750-2043 masl) and disturbance (mainly due to tourism and agriculture). Data on species composition and environmental variables were measured and recorded in each quadrat. Two-way indicator species analysis and canonical correspondence analysis (CCA) were used to analyze the relationships between vegetation and environmental variables, while species diversity indices were used to analyze the pattern of species diversity. Twelve plant communities were found, mostly secondary forests with some plantations. These communities are representative of the vegetation in the mountains west of Beijing. Each community had a different composition, structure, and environment. The variation of plant communities was significantly related to elevation and disturbance and related to litter thickness, slope, and aspect. The cumulative percentage variance of species-environment relationships for the first 4 CCA axes was 89.6%. Elevation and disturbance intensity were revealed as the factors that most influenced community distribution and species diversity. Species richness, heterogeneity, and evenness all showed a "humped" pattern along elevational and disturbance gradients-the highest species diversity appeared in the middle elevation and under medium disturbance intensity. Recommendations regarding management measures are made. © International Mountain Society.
CITATION STYLE
Zhang, J. T., Xu, B., & Li, M. (2013). Vegetation patterns and species diversity along elevational and disturbance gradients in the Baihua Mountain reserve, Beijing, China. Mountain Research and Development, 33(2), 170–178. https://doi.org/10.1659/MRD-JOURNAL-D-11-00042.1
Mendeley helps you to discover research relevant for your work.