Abstract: On the base of observing the aboveground biomass yieds of the Artemisia sphaerocephala Stipa bungeana community on sandy grassland in Erdos Plateau from 1986—1990 monthly,monthly multi regression model of biomass to climatic factors were presented.Following regulations were concluded by those models.(1)Precipitation is a remarkable influential factor on the aboveground biomass for every month,and the biomass increases with the increase of precipitation.(2)Sunshine hours only affect the biomass remarkably in June.(3)Monthly averaged temperature doesn't affect the biomass in any moth.(4)From July to October,the biomass in every month is influenced remarkably by the biomass in the last month.Applying the monthly models,range of the biomass change in every month under three different climatic conditions was predicted.Comparing the simulated values of the biomass by the monthly models and the accumulative models with the observed results,monthly models presented in this paper is shown an improvement for the traditional accumulative models.

Key words: Artemisia sphaerocephala Stipa bungeana community, Aboveground biomass yield, Muti regression models

摘要： 在5年逐月观测基础上,利用多元分析方法,建立鄂尔多斯高原沙地油蒿-本氏针茅群落地上生物量对气候因子影响的逐月回归模型.结果表明,气候因子在不同时期对植物生长的作用差异显著.降水因子在各月都是影响生物量的显著因子,二者呈正相关.日照时数仅在月对生物量产生显著影响.平均气温在各月都不对生物量产生显著影响.7～10月各月生物量都受前月生物量的显著影响,说明植物生长的持续性对生物量的形成和积累是重要的.应用本文建立的模型对3种不同气候条件下,各月生物量的波动范围进行预测.建立累积回归模型,将逐月回归模型、累积回归模型的模拟值与实测值进行比较,结果在多数年份,逐月回归模型都比累积回归模型更接近实测值.与传统的累积回归模型相比,本模型具有三方面的优越性,即可揭示气候影响植物生长的重要细节、具有预测能力以及精度更高,因此是对传统累积气候模型进行的有益改进.

关键词: 油蒿—本氏针茅群落, 地上生物量, 多元回归分析