Estimating global annual gross primary production based on satellite-derived phenology and maximal carbon uptake capacity

Xiaojun Xu; Danna Chen

doi:10.1016/j.envres.2024.119063

Estimating global annual gross primary production based on satellite-derived phenology and maximal carbon uptake capacity

Environ Res. 2024 May 11;252(Pt 4):119063. doi: 10.1016/j.envres.2024.119063. Online ahead of print.

Authors

Xiaojun Xu¹, Danna Chen²

Affiliations

¹ State Key Laboratory of Subtropical Silviculture, Zhejiang A&F University, Hangzhou, 311300, Zhejiang, China; Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration of Zhejiang Province, Zhejiang A&F University, Hangzhou, 311300, Zhejiang, China; College of Environment and Resources, College of Carbon Neutrality, Zhejiang A&F University, Hangzhou, 311300, Zhejiang, China. Electronic address: 20140004@zafu.edu.cn.
² State Key Laboratory of Subtropical Silviculture, Zhejiang A&F University, Hangzhou, 311300, Zhejiang, China; Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration of Zhejiang Province, Zhejiang A&F University, Hangzhou, 311300, Zhejiang, China; College of Environment and Resources, College of Carbon Neutrality, Zhejiang A&F University, Hangzhou, 311300, Zhejiang, China.

PMID: 38740292
DOI: 10.1016/j.envres.2024.119063

Abstract

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.

Keywords: Carbon uptake capacity; FLUXNET; Gross primary production; MODIS; Phenology.