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Scientia Silvae Sinicae ›› 2014, Vol. 50 ›› Issue (9): 1-9.doi: 10.11707/j.1001-7488.20140901

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Above-Ground Biomass Distribution Models for Arbor Layer of Eight Subtropical Forest Types

Fu Tian, Zhu Jianhua, Xiao Wenfa, Zeng Lixiong   

  1. Research Institute of Forest Ecosystem Environment and Protection, CAF Beijing 100091
  • Received:2013-05-24 Revised:2014-08-01 Online:2014-09-25 Published:2014-09-30
  • Contact: 肖文发

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Abstract:

In this study, the volume-to-biomass conversion models and the proportion models for biomass components of 8 subtropical forest types in China were established by using the power function model and multinomial logit model, respectively. The results show that the fitting results of the volume-to-biomass conversion models for every forest type except the evergreen broad-leaved forest exhibit significant relations (R2>0.5, P<0.001) between volume and biomass, and the predicting residuals increase with the increment of the independent variable value. The root mean square errors are all controlled within 6.520~23.123 t·hm-2. The testing accuracy is between 31.14%-91.79%, which are all above 70% except for evergreen broad-leaved forest. On the other hand, the fitting results of proportion models for the biomass components reach significant level (P <0.05) except for the evergreen broad-leaved forest, and the predicting residuals decrease with the increased independent variable value. The root mean square errors of stem, bark, branch and leaf biomass proportion of total tree biomass are all less than 0.1, that is 0.031~0.085, 0.005~0.041, 0.029~0.103 and 0.016~0.083. The prediction accuracy reaches 91.04%~96.14%, 62.71%~94.48%, 63.70%~94.47%, and －8.86%~83.92%, respectively. The volume-to-biomass conversion models and the proportion models for biomass components in this paper are reasonable models for the 8 subtropical forest types except for the evergreen broad-leaved forest, and the obtained model parameters also can provide a reference for studying biomass distribution of the other subtropical forests

Key words: power function, multinomial logit model, volume-to-biomass conversion, biomass proportion

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