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矮嵩草草甸生物量季节动态及其与气候因子的关系
引用本文:蒲继延,李英年,赵亮,杨时海.矮嵩草草甸生物量季节动态及其与气候因子的关系[J].草地学报,2005,13(3):238-241.
作者姓名:蒲继延  李英年  赵亮  杨时海
作者单位: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
基金项目:中国科学院知识创新工程项目 , 国家重点基础研究发展计划(973计划) , 中-日合作项目 , 中-日合作项目
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  
文章编号:1007-0435(2005)03-0238-04
收稿时间:2004-05-28
修稿时间:2005-03-20

The Relationship Between Seasonal Changes of Kobresia Humilis Meadow Biomass and the Meteorological Factors
PU Ji-yan,LI Ying-nian,ZHAO Liang,YANG Shi-hai.The Relationship Between Seasonal Changes of Kobresia Humilis Meadow Biomass and the Meteorological Factors[J].Acta Agrestia Sinica,2005,13(3):238-241.
Authors:PU Ji-yan  LI Ying-nian  ZHAO Liang  YANG Shi-hai
Institution: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
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/m~2 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.
Keywords:Kobresia humilis meadow  Biomass  Seasonal change  Meteorological factors  Prediction model
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