Welcome to Chinese Journal of Applied Ecology! Today is Share:

Chinese Journal of Applied Ecology ›› 2016, Vol. 27 ›› Issue (10): 3164-3172.doi: 10.13287/j.1001-9332.201610.009

• CONTENTS • Previous Articles     Next Articles

Stem biomass estimation models for dominant shrubs on the northern Loess Plateau of China

YANG Xian-long1,2, WEI Xiao-rong1,2, SHAO Ming-an2,3*   

  1. 1College of Natural Resources and Environment, Northwest A&F University, Yangling 712100, Shaanxi, China;
    2State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A&F University, Yangling 712100, Shaanxi, China;
    3Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;
  • Received:2016-05-12 Published:2016-10-18
  • Contact: * E-mail: mashao@ms.iswc.ac.cn
  • Supported by:
    This work was supported by the National Natural Science Foundation of China (41530854,41571296).

Abstract: A total of 200 stems of Caragana korshinskii and 210 stems of Salix psammophila were collected in the late August of 2015 in the Liudaogou catchment of Shenmu County, Shaanxi Pro-vince, China. Basal diameter (D), length (H), water content (W0), fresh mass (WF) and dry mass (W) were measured for each stem of the two species. Exponential and allometric equations were used to establish relationship models relating stem biomass to its morphological parameters. Altogether four models were established for each species, and their accuracy of estimation was also validated. The results showed that, the allometric model that used D2H as input variable was optimal in estimating stem biomass for C. korshinskii and S. psammophila, after transformed into its linear form. Meanwhile, the heteroscedasticity of the biomass data was greatly eliminated. This model had a maximum value of coefficient of determination (R2), and meanwhile minimum values of mean error (ME), mean absolute error (MAE), total relative error (TRE), mean systematic error (MSE), and mean absolute percentage error (MPSE), thus basically meeting the requirement of the accuracy in ecological study.