摘要
应用生物量回归模型和生产力方程，研究了西双版纳原始热带湿性季节雨林生物量及净初级生产量（NPP）。雨林总生物量为692．590t·hm-2，总生物量分配为：乔木层占98．66％、灌木层占0．76％、木质藤本层占0．50％、草本层占0．09％，生物量主要集中于乔木层。雨林年平均NPP为25．764t·hm-2·a－1，其中各层次的NPP分别为（t·hm-2·a－1）：乔木层23．972（占总NPP的93．04％）、灌木层0．749（占2．91％）、木质藤本层0．431（占1．67％）和草本层0．612（占2．38％）。乔木层NPP分配为（t·hm－2·a-1）：凋落量11．566、叶虫食量0．694和生物量增量11．712。结果表明：西双版纳虽地处热带北缘，当地原始热带湿性季节雨林同样具有典型热带雨林一样高的生物量和NPP。
In this paper tree biomass regression medels and a forest net primary preductivity medel (NPP-△B＋L＋G) were used to study the biomass and net primary preduction (NPP) of the primary tropical seasonal rain forest by measuring biomass accumulation (an), litterfall and tree fall (L) and leaf herbivory (G) in the rain forest in Menglun (21°58'N, 101°12'E), Xishuangbanna.The total biomass of the forest was 692. 590t·hm-2, with by far the greatest proportion, 683. 291t·hm-2 (98. 66 % of the total),found in the tree layer. The remaining layers each accounted for less than 1 % of the total: shrub layer 5. 243t·hm-2 (0. 76 % ),wdriy liana layer 3. 444t·hm-2 (0. 50% ), herb layer 0. 612t·hm-2 (0. 09 % ). The annual mean NPP of the rain forest was 25. 764t·hm-2·a-1. This was also not evenly distributed among the different layers of the forest: the tree layer, with a mean annual preduction of 23. 972t·hm-2·a-1 accounted for 93. 04 % of the rain forest NPP. The other layers contributed relatively little: shrub layer,0. 749t·hm-2·a-1 (2. 91 % ); woody liana layer, 0. 431t·hm-2·a-1 (1. 67% ); herb layer, 0. 612t·hm-2·a-1 (2. 38% ). Within thetree layer litterfall accounted for 48. 25 % of annual net primary production and leaf herbivory accounted for 2. 90 %. Biomass accumulation made up the remaining 48. 86%. The result showed that the biomass and net primary preduction of primary tropical wetseasonal rain forest in Xishuangbanna, at the northern edge of the tropics, are as high as those of typical tropical rain forests elsewhere.
出处
《植物生态学报》
CAS
CSCD
北大核心
2000年第2期197-203,共7页
Chinese Journal of Plant Ecology
基金
中国科学院生态系统研究网络项目!KZ95T-04-02
云南省科学基金!1999C0090M
中国科学院"九.五"重点项目!KZ952-Sl-101
中国科学院
