摘要
一般认为,生态系统的总初级生产力(GPP)对光合有效辐射(LAI)的响应曲线可以用直角双曲线来描述。研究表明,在不同的生长季进行模拟,模拟的直角双曲线的两个参数Amax和α值不同。为消除模型参数季节变化对模拟结果的影响,直角双曲线模型通常应用于较短的时间尺度(如半月、10d或5d),然而,这种在较短的时间尺度上进行模拟的方法过于繁琐,并且当通量数据缺失过多时,在短的时间模拟窗口上,少量的数据不足以拟合直角双曲线模型。在这种情况下,无法利用直角双曲线模型对生态系统的GPP进行准确的模拟,或者对缺失的碳通量数据进行插补。以玉米农田生态系统为例,旨在阐明生态系统的环境因子和生物因子在不同生长季对直角双曲线模型中两个参数Amax和α值的影响。结果表明,Amax与LAI具有显著的直线关系:Amax=a LAI+b(a=0.64,b=0.15,R=0.74,P=0.002)。据此我们对直角双曲线模型进行了改进,用以预测半小时尺度的玉米农田生态系统GPP。与未改进的直角双曲线模型进行比较,在整个生长季进行模拟,改进的直角双曲线模型明显提高了模拟的精度;当在较短的时间窗口上进行模拟(半月时间尺度),改进的直角双曲线模型与之有着相似的精度。利用改进的双曲线模型不仅可以非常简捷地对生态系统GPP进行模拟,而且可以解释直角双曲线模型参数Amax值的连续变化,尤其是,当涡相关观测数据大量缺失时,可以很方便并且较为准确地插补缺失数据。
Photosynthetic light response could be expressed as a rectangular hyperbola curve with the fixed parameters AreaX and a. Seasonal variations of Am and a were observed among different ecosystems. In order to eliminate the effects of seasonal variations of Areax and a on simulated result, rectangular hyperbola model was usually fitted at shorter time intervals （e. g. half-month, 10-days, and 5-days）. However, this method is tedious and non-mechanism, especially at a shorter time intervals, small amounts of carbon flux or climate data are not enough for simulating accurately rectangular hyperbola model. In this study we tried to elaborate the effects of biotic and abiotic factors on the parameters （Amax and a） as an example of rainfed maize ecosystem. Biotic and abiotic factors may affect the seasonal dynamics of parameters c and A.,.In order to understand mechanism for the influence of these factors on parameters of model, Multiple regression between seasonal variations of parameters （c and A ax ） and ahiotic factors （e. g. air temperature, soil temperature, relative humidity, soil water content, solar radiation, air vapor pressure deficits（VPD） ） and biotic factor （LAI） were evaluated by stepwise regression analysis. The results showed that there was a significant linear relationship between Am~ and LAI, and LAI is a main factor affecting seasonal variations of Amax. The relationship between Amax and LAI could be expressed as Amax = a LAI ＋ b （a 0.64 b 0.15 R 0.74, P 0. 002）. Thus, a modified model GPP t^PAR（aLAI＋b） = , = , = = - was aPAR＋（aLAI＋b） developed to estimate half-hourly canopy gross primary production （GPP） in maize ecosystem. LAI changed rapidly in a rapid growth phase, but its observed frequency in our experiments was low （at 15--20 days interval ）. Therefore, we introduced a logistic model to interpolate daily LAI by limited observations. After that, we tested the calculated GPP against all the available observed measurements based on three different simulation methods （the original model with the fixed parameters of c~ and Amax, respectively, at half-month intervals and throughout the entire growing season ; the improved rectangular hyperbola model）. Compared with the original model which was fitted throughout the entire growing season, both the original model which was fitted at half-month intervals and our new model are better than the original model throughout the entire growing season. Compared with the original model which was fitted at half-month intervals, our new model has the similar accuracy. The new model introduced the relationship between LAI and A improved accuracy in simulating GPP throughout the growing season, elaborated the mechanism of different accuracy for simulation in GPP at different time scales. The improved model is not only simple, but also easy to explain the continuous variations of parameter Amx. Especially when the amount of missing flux data is large, and the original model is not able to be fitted at short time intervals, it is suitable for using the new model to interpolate. Evaluation of carbon dynamics in ecosystem is a key issue in model could assess ecosystem GPP expediently and accurately. global climate change research, the improved hyperbola Then, we could evaluate ecosystem carbon budget at regional and global scales expediently by the LAI from remote sensing observations. However, abiotic factors such as temperature, soil moisture, and VPD did not affect the variations of parameters of model in our studies, and these factors may affect GPP by other means. Further coupling the new model with these factors is the next logical step in understanding ecosystem carbon budget.
出处
《生态学报》
CAS
CSCD
北大核心
2013年第7期2182-2188,共7页
Acta Ecologica Sinica
基金
公益性行业(农业)科研专项经费项目(200903003)
国家重点基础研究发展计划资助(2010CB951303)
关键词
玉米
直角双曲线改进模型
叶面积指数
GPP
A mx
LAI
GPP
photosynthetic light response
rectangular hyperbola model
作者简介
通讯作者Correspondingauthor．E—mail：gszhou@ibcas．ac．cn
