吴旭东, 谢应忠, 徐坤, 汪诗平, 张晓娟. 贺兰山东麓不同种植年限酿酒葡萄林生物量分配及估算模型[J]. 中国生态农业学报(中英文), 2012, 20(10): 1322-1328. DOI: 10.3724/SP.J.1011.2012.01322
引用本文: 吴旭东, 谢应忠, 徐坤, 汪诗平, 张晓娟. 贺兰山东麓不同种植年限酿酒葡萄林生物量分配及估算模型[J]. 中国生态农业学报(中英文), 2012, 20(10): 1322-1328. DOI: 10.3724/SP.J.1011.2012.01322
WU Xu-Dong, XIE Ying-Zhong, XU Kun, WANG Shi-Ping, ZHANG Xiao-Juan. Biomass allocation and estimation model at different planting ages ofwine grape forest in east Helan Mountain[J]. Chinese Journal of Eco-Agriculture, 2012, 20(10): 1322-1328. DOI: 10.3724/SP.J.1011.2012.01322
Citation: WU Xu-Dong, XIE Ying-Zhong, XU Kun, WANG Shi-Ping, ZHANG Xiao-Juan. Biomass allocation and estimation model at different planting ages ofwine grape forest in east Helan Mountain[J]. Chinese Journal of Eco-Agriculture, 2012, 20(10): 1322-1328. DOI: 10.3724/SP.J.1011.2012.01322

贺兰山东麓不同种植年限酿酒葡萄林生物量分配及估算模型

Biomass allocation and estimation model at different planting ages ofwine grape forest in east Helan Mountain

  • 摘要: 通过对贺兰山东麓同一立地类型不同种植年限的人工酿酒葡萄林形态指标和生物量的测定, 研究了葡萄林生物量随时间的分配格局, 同时利用主要构件形态指标与各构件生物量建立了生物量估测模型。结果表明: 1)供试林地葡萄树株高(H)、主蔓长(SH)、新梢长(YSH)、分枝数(BN)及茎粗(D)均基本上随林龄增加而逐渐增大。2)葡萄林各构件生物量随林分年龄的增加而增加。3)葡萄树地上部各构件生物量分配表现如下, 1~4 a林分为叶生物量>新梢生物量>主蔓生物量, 4~12 a林分为主蔓生物量>新梢生物量>叶生物量, 2~12 a林分为地上生物量>地下生物量。4)以茎粗与株高结合的D2H作为自变量建立模型, 各组分生物量最优估测模型均为幂函数W=a×(D2H)b(其中, W为生物量, D2H为茎粗D2与株高H的乘积, a和b为估测参数): 叶生物量与D2H拟合模型为W=12.909×(D2H)0.825 9(R2=0.849 9, P=0.000), 主蔓生物量与D2H拟合模型为W=3.963 4×(D2H)1.344 9 (R2=0.938 1, P=0.000), 新梢生物量与D2H拟合模型为W=6.190 6×(D2H)1.051 7 (R2=0.804 7, P=0.000), 地上生物量与D2H拟合模型为W=23.017×(D2H)1.076 6 (R2=0.938 5, P=0.000), 地下生物量与D2H拟合模型为W=27.126×(D2H)0.689 (R2=0.892 4, P=0.000)。各预测模型精确度较高。

     

    Abstract: The biomass and morphological indexes of different planting ages of wine grape forest (1~12 years) were investigated by analyzing biomass distributions in different organs of varying-age stands and the relationships of biomass with component factors in east Helan Mountain. The study then established biomass prediction models for wine grape forests in the region. The results showed that plant height (H), stem height (SH), young shoot height (YSH), branch number (BN) and stem diameter (D) gradually increased with increasing planting age. Also different aboveground organs biomass increased with increasing forest age. The distribution of aboveground biomass showed an order of leaf > young shoot > stem for forest of ages 1~4 years. Although leaf formed a principal component of aboveground biomass, stem biomass was greater than young shoot biomass which was in turn greater than leaf biomass for forest of ages 4~12 years. Aboveground biomass gradually transformed into stem and young shoot. Belowground and aboveground biomasses significantly increased for ages 1~12 years. Biomass allocation was in the order as follows: aboveground biomass > belowground biomass for forest ages of 2~12 years. The pattern of relationship between biomasses of different plant organs and D2H was uniform with age structures. The optimal biomass models were the power function models of the form W=a×(D2H)b. The relationship between leaf biomass and D2H fitted the form W=12.909×(D2H)0.825 9 (R2=0.849 9, P=0.000); that between shoot biomass and D2H fitted the form W=3.963 4×(D2H)1.344 9 (R2=0.938 1, P=0.000); also that between young shoot biomass and D2H fitted the form W=6.190 6×(D2H)1.051 7 (R2=0.804 7, P=0.000); next that between aboveground biomass and D2H fitted the form W=23.017×(D2H)1.076 6 (R2=0.938 5, P=0.000); and the relationship between belowground biomass and D2H fitted the form W=27.126×(D2H)0.689 (R2=0.892 4, P=0.000). The optimal wine grape biomass models at different planting ages showed a certain degree of generality of high accuracy.

     

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