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  • 标题:Prediction models for above-ground wood of some fast growing trees of Nepal's eastern Terai
  • 本地全文:下载
  • 作者:H.B. Thapa
  • 期刊名称:Banko Janakari : A Journal of Forestry Information for Nepal
  • 印刷版ISSN:1016-0582
  • 出版年度:1999
  • 卷号:9
  • 期号:2
  • 页码:28-35
  • 语种:English
  • 出版社:Department of Forest Research and Survey
  • 摘要:Biomass study of Acacia auriculiformis, Acacia catechu, Dalbergia sissoo, Eucalyptus camaldulensis and Eucalyptus tereticornis was conducted on a five and half years old 'Fuelwood Species Trial under Short Rotation' through destructive sampling at Tarahara, Sunsari District of Nepal. The lowest Furnival Index (FI) was the main criteria for selecting a model. Among the six models tested, the transformed model Ln W= a + b Ln DBH from a power equation W = a DBHb (W = weights of stem or branch or above-ground wood in kg, DBH= Diameter at breast height in cm) was selected. Selected prediction models of tree components and above-ground wood (green as well as oven dry), and their coefficient of determination (R2) values, regression constant and coefficient, correction factor, precision and bias percent of five species are presented. With the exclusion of branchwood models, R2 is higher in a range of 88.7% for oven dry stemwood of Acacia catechu to 99.3% for above-ground wood model of Dalbergia sissoo. However, R2 is less than 80% in branchwood (green and oven dry) of Acacia auriculiformis, Eucalyptus camaldulensis , and Eucalyptus tereticornis showing moderate relationship between branchwood and DBH. In the case of E. tereticornis , precision is more than 49% which leads to low reliability in biomass estimation resulting in true biomass deviation in a range of about 49.51% to 56.74%, so biomass model's could not be used for estimation of tree components and above-ground wood. Despite it, generally, precision percent of the selected models has been found less than 15%. Bias percent was found quite large for allometric branchwood model comparatively to stemwood and above-ground wood models. D. sissoo had less than 10 % bias. Bias percent was the highest (23.11%) for green branchwood of Acacia auriculiformis. Others had in a range of 0.5% for green aboveground wood model of D. sissoo to 18.4% for green and oven dry branchwood models of E. tereticornis.
  • 关键词:Prediction models, wood biomass, fast growing trees, Terai, Nepal
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