• 目次 •

### 黄土高原北部典型灌丛枝条生物量估算模型

1. 1西北农林科技大学资源环境学院, 陕西杨凌 712100;
2西北农林科技大学黄土高原土壤侵蚀与旱地农业国家重点实验室, 陕西杨凌 712100;
3中国科学院地理科学与资源研究所, 北京 100101;
• 收稿日期:2016-05-12 发布日期:2016-10-18
• 通讯作者: * E-mail: mashao@ms.iswc.ac.cn
• 作者简介:杨宪龙,男,1988年生,博士研究生. 主要从事土壤物理和生态水文学研究. E-mail: yangxianlong1988@126.com
• 基金资助:
本文由国家自然科学基金项目(41530854,41571296)资助

### 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.