| Autor: |
Tian LX; Key Laboratory of Forest Ecology and Environment of State Forestry and Grassland Administration, Research Institute of Forest Ecology, Environment and Protection, Chinese Academy of Forestry, Beijing 100091, China.; Zhejiang Academy of Forestry, Hangzhou 310023, China.; Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China., Wu CP; Key Laboratory of Forest Ecology and Environment of State Forestry and Grassland Administration, Research Institute of Forest Ecology, Environment and Protection, Chinese Academy of Forestry, Beijing 100091, China.; Zhejiang Academy of Forestry, Hangzhou 310023, China.; Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China., Yang SZ; Key Laboratory of Forest Ecology and Environment of State Forestry and Grassland Administration, Research Institute of Forest Ecology, Environment and Protection, Chinese Academy of Forestry, Beijing 100091, China.; Zhejiang Academy of Forestry, Hangzhou 310023, China.; Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China., Xu Y; Key Laboratory of Forest Ecology and Environment of State Forestry and Grassland Administration, Research Institute of Forest Ecology, Environment and Protection, Chinese Academy of Forestry, Beijing 100091, China.; Zhejiang Academy of Forestry, Hangzhou 310023, China.; Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China., Huang JH; Key Laboratory of Forest Ecology and Environment of State Forestry and Grassland Administration, Research Institute of Forest Ecology, Environment and Protection, Chinese Academy of Forestry, Beijing 100091, China.; Zhejiang Academy of Forestry, Hangzhou 310023, China.; Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China., Ding Y; Key Laboratory of Forest Ecology and Environment of State Forestry and Grassland Administration, Research Institute of Forest Ecology, Environment and Protection, Chinese Academy of Forestry, Beijing 100091, China.; Zhejiang Academy of Forestry, Hangzhou 310023, China.; Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China., Zang RG; Key Laboratory of Forest Ecology and Environment of State Forestry and Grassland Administration, Research Institute of Forest Ecology, Environment and Protection, Chinese Academy of Forestry, Beijing 100091, China.; Zhejiang Academy of Forestry, Hangzhou 310023, China.; Co-Innovation Center for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing 210037, China. |
| Abstrakt: |
The numerical classification and ordination of plant communities can reveal the relationship between plant distribution and environment, with implications on vegetation restoration and forest management. Community types were classified using a clustering method based on 45 forest dynamic plots with each area of 0.04 hm 2 in Wuchaoshan, Hangzhou, Zhejiang Province, China. The ordination of plant community and the relationship between communities and edaphic variables (soil nutrient availability and topography) were explored using redundancy analysis. Results showed there were three community types in the study area, including Schima superba community type, Quercus fabri-Symplocos anomala community type, and Cyclobalanopsis glauca community type. Stem density and basal area of trees were not significantly different among those community types. Species richness in the C. glauca community was higher than that in S. superba community, but not significantly different from the Q. fabri-S. anomala community. Results from the redundancy analysis showed that community distribution was significantly related to edaphic factors. Topographic and soil factors accounted for 46.4% of the total variation in community distribution while total soil phosphorus, available phosphorus, available potassium, elevation, slope, aspect, and canopy openness had significant effects on community composition. Total soil phosphorus, available potassium, and altitude were the main factors influencing community distribution in Wuchaoshan. 53.6% of the total variation in community distribution were not explained, perhaps due to anthropogenic disturbance. |
