关于全球初级生产总值(3GPP)的高度不确定性仍未解决。本研究探讨了物候之间的关系,生理学,和年度阵,为准确估计提供可行的替代方案。使用来自145个FLUXNET站点的GMP数据开发了综合物候和生理学(SMIPP)的统计模型,以估算各种植被类型的年度GMP。通过采用由全球碳吸收期(CUP)和最大碳吸收能力(GPPmax)的卫星数据集驱动的SMIPP模型,估计2001年至2018年期间的全球年度计划。结果表明,SMIPP模型准确地预测了每年的3GPP,森林类型的相对均方根误差值为11.20至19.29%,非森林类型的相对均方根误差值为20.49-35.71%。然而,湿地,灌木丛,和常绿森林表现出相对较低的准确性。平均,趋势,2001-2018年全球3GPP年际变化分别为132.6PgCyr-1、0.25PgCyr-2和1.57PgCyr-1。它们在其他全球3GPP产品中估计的范围内。敏感性分析显示,GPPmax在高纬度地区的影响与CUP相当,但在全球范围内的影响明显更大。GPPmax的灵敏度系数为0.85±0.23,CUP的灵敏度系数为0.46±0.28。本研究提供了一种简单实用的方法来估计全球年度GP1,并强调了GPPmax和CUP对全球规模年度GP1的影响。
The high uncertainty regarding global gross primary production (GPP) remains unresolved. This study explored the relationships between phenology, physiology, and annual GPP to provide viable alternatives for accurate estimation. A statistical model of integrated phenology and physiology (SMIPP) was developed using GPP data from 145 FLUXNET sites to estimate the annual GPP for various vegetation types. By employing the SMIPP model driven by satellite-derived datasets of the global carbon uptake period (CUP) and maximal carbon uptake capacity (GPPmax), the global annual GPP was estimated for the period from 2001 to 2018. The results demonstrated that the SMIPP model accurately predicted annual GPP, with relative root mean square error values ranging from 11.20 to 19.29% for forest types and 20.49-35.71% for non-forest types. However, wetlands, shrublands, and evergreen forests exhibited relatively low accuracies. The average, trend, and interannual variation of global GPP during 2001-2018 were 132.6 Pg C yr-1, 0.25 Pg C yr-2, and 1.57 Pg C yr-1, respectively. They were within the ranges estimated in other global GPP products. Sensitivity analysis revealed that GPPmax had comparable effects to CUP in high-latitude regions but significantly greater impacts at the global scale, with sensitivity coefficients of 0.85 ± 0.23 for GPPmax and 0.46 ± 0.28 for CUP. This study provides a simple and practical method for estimating global annual GPP and highlights the influence of GPPmax and CUP on global-scale annual GPP.