北京林业大学学报2025，Vol.47Issue(9)：1-13,13.DOI:10.12171/j.1000-1522.20250026
东北阔叶红松林净初级生产力模拟及参数优化
Simulation and parameter optimization of net primary productivity of broadleaved Korean pine forest in northeastern China
摘要
Abstract
[Objective]This paper aims to enhance the accuracy of net primary productivity(NPP)simulations by optimizing parameter estimation in the Biome-BGC model,and explores the impact mechanism of key sensitive parameters on NPP.[Method]The research focused on Korean pine-broadleaved forests in northeastern China.In the Biome-BGC model,28 physiological and ecological parameters for conifers and broadleaved trees were optimized separately using the parameter estimation model(PEST)based on leaf area index data obtained from the moderate-resolution imaging spectroradiometer(MODIS).A sensitivity analysis was conducted to identify parameters with sensitivity indices above 0.2.Simulation accuracy before and after optimization was evaluated using linear regression models.Additionally,structural equation models were employed to quantify the response of NPP to changes in highly sensitive parameters(sensitivity index>0.2).[Result](1)Parameter optimization significantly improved the goodness of fit for NPP simulations(p<0.01),with the coefficient of determination(R2)increasing from 0.15 to 0.31 and the root mean squared error(RMSE)decreasing by 59%.(2)The highly sensitive parameters shared by conifers and broadleaved trees included four key parameters:the annual fire mortality fraction,maximum stomatal conductance,boundary layer conductance,and the fraction of leaf nitrogen content in Rubisco.(3)Structural equation modeling indicated that leaf nitrogen content in Rubisco and maximum stomatal conductance is key parameters affecting simulated NPP.These parameters regulated photosynthetic capacity through carboxylation limitation and carbon dioxide diffusion.However,the regulatory effect of stomatal conductance on photosynthesis may vary with environmental conditions,potentially promoting or inhibiting photosynthetic activity.[Conclusion]Integrating observational data with the PEST system,while focusing on critical parameters such as leaf nitrogen content in Rubisco and maximum stomatal conductance,can significantly improve the accuracy and efficiency of NPP simulations in the Biome-BGC model.This study provides a theoretical foundation and methodological support for vegetation parameterization and carbon cycle simulations in the Korean pine-broadleaved forest ecosystems in northeastern China.关键词
净初级生产力/Biome-BGC模型/PEST模型/参数优化/阔叶红松林Key words
net primary productivity/Biome-BGC model/PEST model/parameter optimization/Korean pine-broadleaved forests分类
农业科技引用本文复制引用
王雪瑞,岳庆敏,郝珉辉,何怀江,张春雨,赵秀海..东北阔叶红松林净初级生产力模拟及参数优化[J].北京林业大学学报,2025,47(9):1-13,13.基金项目
国家重点研发计划(2022YFD2201003). （2022YFD2201003）
