[1]张绘芳,高亚琪,朱雅丽,等. 新疆雪岭杉生物量模型对比研究[J].西北林学院学报,2015,30(06):52-58.[doi:doi:10.3969/j.issn.1001-7461.2015.06.09]
　ZHANG Hui-fang,GAO Ya-qi,ZHU Ya-li,et al. A Comparative Study on Biomass Models for Picea schrenkiana in Xinjiang[J].JOURNAL OF NORTHWEST FORESTRY UNIVERSITY,2015,30(06):52-58.[doi:doi:10.3969/j.issn.1001-7461.2015.06.09]
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 新疆雪岭杉生物量模型对比研究()
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《西北林学院学报》[ISSN:1001-7461/CN:61-1202/S]

卷:
第30卷
期数:
2015年06期
页码:
52-58
栏目:
出版日期:
2015-11-30

文章信息/Info

Title:
 A Comparative Study on Biomass Models for Picea schrenkiana in Xinjiang
文章编号:
1001-7461(2015)06-0052-07
作者:
 张绘芳1; 高亚琪1; 朱雅丽1; 地力夏提·包尔汉1; 李霞2
 (1. 新疆林业科学院 现代林业研究所，新疆 乌鲁木齐 830000；2. 新疆农业大学 草业与环境学院，新疆 乌鲁木齐 830052)
Author(s):
 ZHANG Hui-fang1;  GAO Ya-qi1;  ZHU Ya-li1;  DILIXIATI-baoerhan1;  LI Xia2
 （1. Modern Forestry Research Institute, Xinjiang Academy of Forestry, Urumqi, Xinjiang 830000, China; 2. College of Grassland and Environment Sciences, Xinjiang Agricultural University, Urumqi，Xinjiang 830052, China）
关键词:
 ; 新疆; 雪岭杉; 生物量; 模型评价
Keywords:
 ; Xinjiang;  Picea schrenkiana;  biomass;  model estimation
分类号:
S791.189
DOI:
doi:10.3969/j.issn.1001-7461.2015.06.09
文献标志码:
A
摘要:
 基于80株样木的实测数据，运用相关分析和回归分析方法构建了雪岭杉的地上部组织、地下部和各组分器官的生物量估测模型，并根据评价指标对比分析各种模型。结果表明：地上各部分生物量一元模型精度除树叶为77%，其他均在90%以上，可以满足大尺度森林生物量估计；地上各生物量二元模型拟合效果要优于一元模型，但是不同组分生物量模型适合的因子组合不同，地上生物量和树干生物量模型W=aDbHc相对最优，预估精度97.38%和97.26%，树枝、树叶生物量模型W=a(D3/H)b最优，预估精度93.96%和90.37%；地下生物量模型以根茎比方程建立的一元模型最优，预估精度89.01%。建立的地上及各组分生物量模型和地下生物量模型可用于新疆天山山区雪岭杉生物量估计。
Abstract:
 Based on the measured data of 80 sample trees, models that were used to estimate the biomass of the different parts of Picea schrenkiana were established and compared according to the evaluation index analysis. The results showed that the precisions of the single-variable models for aboveground biomass estimation were over 90% except for that used for leaf biomass estimation (with a precision of 77%), indicating that these models could be applied in large-scale-biomass estimation Binary models for aboveground biomass estimation were superior to single-variable models, however, optimum factor combinations were different among the models. W=aDbHc was the best model for aboveground and trunk biomass estimation with estimation precisions of 97.38% and 97.26%, respectively. For branch and leaf biomass, the best model was W=(D3/H)b, with estimation precisions of 93.96% and 90.37%, respectively. For the estimation of underground biomass, the single-variable model based on root-shoot ratio equation was the best, with a precision of 89.01%. The models established could be used for the biomass estimation of P. schrenkiana in Tianshan Mountain in Xinjiang.

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备注/Memo

备注/Memo:
 收稿日期：2015-01-19 修回日期：2015-07-30
基金项目：新疆林业厅新疆林业数表构建项目（新林计字【2014】835号）；新疆维吾尔自治区公益性科研院所基本科研业务经费资助项目（XMBM000001953）。 
作者简介：张绘芳，女，助理研究员，研究方向：森林资源监测和遥感技术应用。E-mail:396930128@qq.com
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