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上海高家庄园人工植物群落现状分析与优化对策
引用本文:高健,张国栋,孙文,龚秋华. 上海高家庄园人工植物群落现状分析与优化对策[J]. 上海交通大学学报(农业科学版), 2014, 32(5): 20-24, 32
作者姓名:高健  张国栋  孙文  龚秋华
作者单位:1. 上海高家庄农业发展有限公司,上海,202154
2. 上海市闵行区动植物检验检测中心,上海,201101
3. 上海市林业站,上海,200072
4. 崇明县林业站,上海,202150
摘    要:针对上海高家庄园不同功能区景点的人工植物群落结构特征进行系统调查,通过对不同功能区景点的人工植物群落类型进行分析,以及对不同功能区景点的人工植物群落不同林分类型的碳储量进行估算,在进一步对高家庄园人工植物群落现状分析的基础上,根据不同功能区的特点建设群落结构完整、物种多样性丰富、生物量高、趋于稳定状态、后期少人工管护的低碳型人工群落配置模式,并提出相应的优化对策,对崇明岛地区绿地人工植物群落稳定及有效经营维护提供理论依据。

关 键 词:高家庄园  人工植物群落  现状分析  优化对策
收稿时间:2013-10-29

Status Analysis and Optimization Policies of Artificial Plant Communities in Gao's Manor
GAO Jian,ZHANG Guo-dong,SUN Wen and GONG Qiu-hua. Status Analysis and Optimization Policies of Artificial Plant Communities in Gao's Manor[J]. Journal of Shanghai Jiaotong University (Agricultural Science), 2014, 32(5): 20-24, 32
Authors:GAO Jian  ZHANG Guo-dong  SUN Wen  GONG Qiu-hua
Affiliation:GAO Jian,ZHANG Guo-dong,SUN Wen,GONG Qiu-hua( 1.Shanghai Gaojiazhuang Agricultural Development Co., Ltd., Shanghai 202154 ,China; 2.Shanghai Minhang District Animal & Plant Inspection and Test Center, Shanghai 201101 ,China; 3.Shanghai Forestry Station, Shanghai 200072, China; 4.Chongming Forestry Station, Shanghai 202150, China)
Abstract:This essay systematically investigated the structure of artificial plant communities in different functional area of Gao's manor.Based on the analysis of artificial plant community types and the estimate of carbon stocks of different forest types in different functional areas,this essay manage to establish a lowcarbon community models that has complete commuriity structure,species diversity,high biomass,less artificial management in later period and tends to be stable.With further analysis of current situation of artificial plant communities in Gao 's Manor the essay offers corresponding optimization policies and provides the theoretical basis of effectively managing gand maintaining a stable artificial plant communities in Chongming Island.
Keywords:Gao's manor  artificial plant community  status analysis  optimization policies
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