Chin J Plant Ecol ›› 2009, Vol. 33 ›› Issue (4): 698-705.DOI: 10.3773/j.issn.1005-264x.2009.04.008

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BIOMASS OF CANOPY AND SHRUB LAYERS OF KARST FORESTS IN PUDING, GUIZHOU, CHINA

LIU Chang-Cheng1,2, WEI Ya-Fen1,2, LIU Yu-Guo1,2, GUO Ke1,*()   

  1. 1State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
    2Graduate University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2008-05-26 Revised:2009-02-10 Online:2009-05-26 Published:2009-07-30
  • Contact: GUO Ke

Abstract:

Aims Information on community biomass is very important for understanding the structure, function and productivity of ecosystems; however, the biomass of karst forests is difficult to measure because of high habitat heterogeneity, complex and irregular growth forms, etc., and it seldom has been studied. Our objective was to study the biomass of karst forests to learn the structure and function of the ecosystems.
Methods We estimated biomass and allocation of tree and shrub layers in three karst forest communities at an ecological research station in Puding, Guizhou, using allometric analysis and sampling harvest methods.
Important findings Biomass regression models were established for three diameter classes (<1 cm, 1-5 cm and >5 cm) and 15 abundant species: Platycarya longipes, Lithocarpus confinis, Itea yunnanesis, Kalopanax septemlobus, Machilus cavaleriei, Quercus aliena, Lindera communis, Lindera pulcherrima var. hemsleyana, Rhamnus hetrophylla, Stachyurus obovatus, Rhamnus leptophylla, Zanthoxylum esquirolii, Zanthoxylum planispinum, Myrsine africana and Zanthoxylum dimorphophyllum var. spinifolium. Average biomass of canopy and shrub layers was 88.7×103 kg·hm-2, with the tree layer accounting for about 98% of the total. Biomass allocation among different diameter classes was concentrated in the individuals >10 cm diameter at breast height. Ten species made up about 98% of the total biomass of canopy and shrub layers, and the total biomass was concentrated in the dominant trees.

Key words: biomass, regression models, biomass allocation, karst forest