img

官方微信

高级检索

中国沙漠 ›› 2018, Vol. 38 ›› Issue (3): 553-559.DOI: 10.7522/j.issn.1000-694X.2018.00033

• 生物与土壤 • 上一篇    下一篇

科尔沁沙地优势固沙灌木的生物量预测模型

童新风1, 杨红玲2,3, 宁志英2,3, 张子谦2,3, 李玉霖2   

  1. 1. 宁城县忙农镇农牧业综合服务中心, 内蒙古 宁城 024200;
    2. 中国科学院西北生态环境资源研究院 奈曼沙漠化研究站, 甘肃 兰州 730000;
    3. 中国科学院大学, 北京 100049
  • 收稿日期:2018-03-12 修回日期:2018-04-10 出版日期:2018-05-20 发布日期:2018-11-06
  • 通讯作者: 李玉霖(E-mail:liyl@lzb.ac.cn)
  • 作者简介:童新风(1967-),女,内蒙古宁城人,高级工程师,主要从事水土保持规划与设计工作。E-mail:1109758419@qq.com
  • 基金资助:
    国家重点研发计划项目(2016YFC0500907);国家自然科学基金项目(41471083)

Biomass Estimation Models for Dominant Sand-fixing Shrubs in Horqin Sand Land

Tong Xinfeng1, Yang Hongling2,3, Ning Zhiying2,3, Zhang Ziqian2,3, Li Yulin2   

  1. 1. Husbandry Service Center of Mangnong Town, Ningcheng 024200, Inner Mengolia, China;
    2. Naiman Desertification Research Station, Northwest Institute of Eco-environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China;
    3. University of Chinese Academy of Sciences, Beijing 100049, China
  • Received:2018-03-12 Revised:2018-04-10 Online:2018-05-20 Published:2018-11-06

摘要: 灌木生物量预测模型对于快速估算固沙灌木林生产力具有重要作用。以科尔沁沙地3种常见的固沙灌木小叶锦鸡儿(Caragana microphylla)、差不嘎蒿(Artemisia halondendron)、黄柳(Salix gordejevii)为对象,基于对灌木地上、根系和整株生物量及高度、冠幅等的测定,建立3种灌木地上、根系和总生物量的估算模型,通过决定系数(R2)、估计值的标准误(SEE)和回归检验显著水平(P<0.05)筛选最优的生物量预测模型。结果表明:小叶锦鸡儿和黄柳生物量的最佳估算变量为冠幅体积,而差不嘎蒿的最佳预测变量为冠幅面积。幂函数回归模型具有最大的R2和较小的SEE,说明相对生长方程是估算小叶锦鸡儿、黄柳、差不嘎蒿灌木生物量较理想的模型。通过实测值检验,3种灌木幂函数模型预测生物量的预估精度在93%以上,具有较好的预测精度。

关键词: 固沙灌木林, 生物量, 预测模型, 预估精度, 科尔沁沙地

Abstract: Biomass estimation modelling is essential to rapidly evaluate the productivity of sand-fixing shrub forest. In this study, estimation model of above-ground, root and whole plant biomass was constructed after the proper independent variables were determined for 3 dominant sand-fixing shrubs, Caragana microphylla, Artemisia halondendron, and Salix gordejevii, in Kerqin Sand Land. The optimal models were selected according to the largest determination coefficients (R2), the smallest standard error of estimates (SEE) and significance level (P<0.05). The results showed that shrub canopy volume was the best independent variable of biomass estimation for C. microphylla and S. gordejevii, and shrub canopy area was the best independent variable for A. halondendron. Subsequently, the largest R2 and the smallest SEE were detected in power function equations for above-ground, root and whole plant biomass of 3 shrubs. In addition, prediction precisions of power function equations for 3 shrubs exceeded 93%, suggesting that allometric growth equation was the optimal biomass models for dominant sand-fixing shrubs. These optimal biomass estimation models will be helpful for productivity evaluation of sand-fixing shrub forest, and thereby supply scientific basis for human management and involvement of sand-fixing shrub forest.

Key words: sand-fixing shrub forest, biomass, estimation model, prediction precision, Horqin Sand Land

中图分类号: