3PG碳生产模型在长白山阔叶红松林总初级生产力估算中的应用

Application of 3PG carbon production model in the gross primary productivity estimation of broadleaved Korean pine forest in Changbai Mountain, China

利用ChinaFLUX长白山站阔叶红松林的通量观测数据以及同期卫星遥感数据,对3PG模型中的植被光合模型(VPM)、光能利用率模型(EC-LUE)、陆地生态系统模型(TEM)、卡内基-埃姆斯-斯坦福方法模型(CASA)4种模型进行参数重组,通过对比通量观测值与估算值的均方根误差、决定系数及平均误差确定模型的最适合参数;并利用实测的通量观测数据对优化后的模型进行拟合度验证,以提高其估算长白山阔叶红松林总初级生产力(GPP)的准确性.结果表明:采用温度、增强植被指数、地表水分指数分别表征原模型中的温度限制因子、光合有效辐射吸收比例、水分限制因子估算长白山阔叶红松林GPP时,结果最优,优化后模型的精度(R^2=0.948,RMSE=0.035 mol·m^(-2)·month^(-1))明显优于原模型(R^2=0.854,RMSE=0.177 mol·m^(-2)·month^(-1)),且能够有效改善原模型生长季明显高估的现象;通过敏感性分析可知,温度是对GPP估算不确定性影响最大的参数,其次为增强型植被指数和光合有效辐射,地表水分指数最小,且变量间的交互作用对GPP估算不确定性也存在影响.

With the flux data of ChinaFLUX and the concurrent satellite remote sensing data in Changbai Mountain,we recombined parameters of four models,i.e.,vegetation photosynthesis model(VPM),eddy covariance-light utility efficiency model(EC-LUE),terrestrial ecosystem model(TEM)and Carnegie-Ames-Stanford approach model(CASA)within 3 PG model.The most suitable parameters of 3 PG model were determined by comparing the root mean square error,coefficient of determination and average error between measured and observed flux values.To improve its accuracy in estimating gross primary productivity(GPP)of broadleaved Korean pine forest in Changbai Mountain,the fitness of the optimal model was validated using the observed flux data.The results showed that when temperature,enhanced vegetation index,and surface water index were used to characterize the temperature limiting factor,photosynthetic active radiation absorption ratio and water limiting factor in the original model to estimate GPP of broadleaved Korean pine forest,the simulation results were the best.The precision of the optimized model(R2=0.948,RMSE=0.035 mol·m-2·month-1)was better than that of the original model(R2=0.854,RMSE=0.177 mol·m-2·month-1),which could effectively improve the phenomenon of obvious overestimation of the original model in the growing season.Results from the parameter sensitivity analysis showed that the uncertainty of GPP estimation was dominated by temperature,followed by enhanced vegetation index,photosynthetically active radiation and land surface water index,as well as their interactions.