草地学报

›› 2005, Vol. 13 ›› Issue (3): 238-241.DOI: 10.11733/j.issn.1007-0435.2005.03.014

• 研究论文 • 上一篇    下一篇

矮嵩草草甸生物量季节动态及其与气候因子的关系

蒲继延1, 李英年2, 赵亮2, 杨时海1   

  1. 1. 青海大学农牧学院草业科学系, 青海, 西宁, 810003;
    2. 中国科学院西北高原生物研究所, 青海, 西宁, 810001
  • 收稿日期:2004-05-28 修回日期:2005-03-20 出版日期:2005-08-15 发布日期:2005-08-15
  • 通讯作者: 李英年,E-mail:ynli@nwipb.ac.cn
  • 作者简介:蒲继延(1982- ),男,青海乐都人,硕士研究生,主要从事草地生态研究工作
  • 基金资助:
    中国科学院知识创新工程重大项目(KZCX1-SW-01-01A);国家重点基础研究发展规划项目(2002CB412501);中日合作“温带高山草原生态系统的碳素动态和温暖化影响的研究”;中日合作“亚太地区环境创新战略计划(APEIS)”

The Relationship Between Seasonal Changes of Kobresia Humilis Meadow Biomass and the Meteorological Factors

PU Ji-yan1, LI Ying-nian2, ZHAO Liang2, YANG Shi-hai1   

  1. 1. Grass Department, Agriculture and Husbandry College of Qinghai University, Xining, Qinghai Province 810003, China;
    2. Institute of Northwest Plateau Biology, CAS, Xining, Qinghai Province 810001, China
  • Received:2004-05-28 Revised:2005-03-20 Online:2005-08-15 Published:2005-08-15

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摘要： 测定高寒矮嵩草(Kobresia humilis)草甸地上、地下生物量季节动态,分析生物量季节动态与气候因子的相关性,建立了地上生物量动态变化的模拟模型。结果表明:高寒矮嵩草草甸地上生物量动态变化历经萌动期、返青期、旺盛生长期、稳定期和折损减少期等5个阶段;地下生物量自5-9月表现出升高-降低-升高的变化规律,且变化幅度较高;2003年地下净生产量633.46g/m2,周转率0.3193;利用海北高寒草甸多年观测资料,建立了气象因子影响植被年生产量的预报模型。

关键词: 矮嵩草草甸, 生物量, 季节动态, 气候因子, 预报模型

Abstract: Measuring of the seasonal changes of the above-and under-ground biomass of kobresia humilis meadow, and analyzing of the relationship between the meteorological factors and seasonal changes of k. humilis biomass were done in order to set up a simulant model of above-ground biomass seasonal changes. The result shows that the k. humilis meadows undergo five phases of bourgeoning, turning green, vigorous growth, stabilizing, and shrivelling and declining in a year. From May through September, the under-ground biomass adhered to the routine of rising, then dwindling, and rising again, all with considerable scales. The net under-ground biomass production was 633.46 g/m2 in 2003, the ratio between the amount of increased under-ground biomass and the peak biomass output was 0.3193. Using data accumulated and analyzed for years in alpine meadows of northern Qinghai lake, a prediction model forecasting meteorological factors that influence the yearly vegetation biomass yield has been set up.

Key words: Kobresia humilis meadow, Biomass, Seasonal change, Meteorological factors, Prediction model

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