基于FLUXNET观测数据与VPM模型的森林生态系统光合作用关键参数优化及验证

Optimization and evaluation of key photosynthesis parameters in forest ecosystems based on FLUXNET data and VPM model

生态系统总初级生产力(GPP)是全球生态系统碳循环研究的重要组成部分.植被最大光能利用率(ε_(max))是陆地生态系统GPP模拟的关键参数.本文基于植被光合模型(VPM)和全球通量网(FLUXNET)40个站点(179条站点年数据)的涡度相关通量观测数据,采用单因素轮换法对VPM模型进行参数敏感性分析,并利用交叉验证法对全球森林生态系统的光合作用关键参数进行优化和验证.结果表明:森林生态系统GPP模型受ε_(max)、光合最高温度(T_(max))以及光合最适温度(T_(opt))的影响最大;优化后的ε_(max)在不同植被类型之间存在明显差异,介于0.05~0.08μmol CO_2·μmol^(-1)PAR,常绿阔叶林>常绿针叶林>混交林>落叶阔叶林;优化后的森林生态系统Tmax为38~48℃,Topt为18~22℃;利用分植被类型优化后的模型关键参数,VPM模型可较好地模拟全球主要森林生态系统GPP的季节和年际变化.

Gross primary productivity（ GPP） plays an important role in global carbon cycle.Vegetation maximum light use efficiency（ ε_（max）） is the key parameter for GPP simulation of terrestrial ecosystem.Based on the vegetation photosynthesis model（ VPM） and the eddy covariance flux data at 40 stations from FLUXNET（ 179 site-years of data）,we identified the key model parameters influencing the simulation of GPP with VPM through one-at-a-time（ OAT） method.The cross validation method was employed to optimize the key model parameters and evaluate the model performance for global forest ecosystems.The results showed that the prediction of GPP was mostly affected by ε_（max）,maximum temperature for photosynthesis（ T_（max））,and optimum temperature for photosynthesis（ T_（opt））.There were distinguishable differences for the key optimized parameters among different forest ecosystems.The optimized ε_（max）ranged from 0.05 to 0.08 μmol CO_2·μmol^（-1） PAR（ evergreen broad-leaved forest〉evergreen coniferous forest〉mixed forestd〉eciduous broad-leaved forest）.The optimized Tmaxranged from 38 to 48 ℃,while Toptranged from 18 to 22 ℃.With the optimized key parameters based on ecosystem types,the VPM was able to simulate the seasonal and inter-annual variations of GPP in four forest ecosystems.