Photosynthetic capacity dominates the interannual variation of annual gross primary productivity in the Northern Hemisphere
2022
Zhang, Weikang | Yu, Guirui | Chen, Zhi | Zhu, Xianjin | Han, Lang | Liu, Zhaogang | Lin, Yong | Han, Shijie | Sha, Liqing | Wang, Huimin | Wang, Yanfen | Yan, Junhua | Zhang, Yiping | Gharun, Mana
Annual gross primary productivity (AGPP) of terrestrial ecosystems is the largest carbon flux component in ecosystems; however, it's unclear whether photosynthetic capacity or phenology dominates interannual variation of AGPP, and a better understanding of this could contribute to estimation of carbon sinks and their interactions with climate change. In this study, observed GPP data of 494 site-years from 39 eddy covariance sites in Northern Hemisphere were used to investigate mechanisms of interannual variation of AGPP. This study first decomposed AGPP into three seasonal dynamic attribute parameters (growing season length (CUP), maximum daily GPP (GPPₘₐₓ), and the ratio of mean daily GPP to GPPₘₐₓ (αGPP)), and then decomposed AGPP into mean leaf area index (LAIₘ) and annual photosynthetic capacity per leaf area (AGPPₗₘ). Furthermore, GPPₘₐₓ was decomposed into leaf area index of DOYₘₐₓ (the day when GPPₘₐₓ appeared) (LAIₘₐₓ) and photosynthesis per leaf area of DOYₘₐₓ (GPPₗₘₐₓ). Relative contributions of parameters to AGPP and GPPₘₐₓ were then calculated. Finally, environmental variables of DOYₘₐₓ were extracted to analyze factors influencing interannual variation of GPPₗₘₐₓ. Trends of AGPP in 39 ecosystems varied from −65.23 to 53.05 g C m⁻² yr⁻², with the mean value of 6.32 g C m⁻² yr⁻². Photosynthetic capacity (GPPₘₐₓ and AGPPₗₘ), not CUP or LAI, was the main factor dominating interannual variation of AGPP. GPPₗₘₐₓ determined the interannual variation of GPPₘₐₓ, and temperature, water, and radiation conditions of DOYₘₐₓ affected the interannual variation of GPPₗₘₐₓ. This study used the cascade relationship of “environmental variables-GPPₗₘₐₓ-GPPₘₐₓ-AGPP” to explain the mechanism of interannual variation of AGPP, which can provide new ideas for the AGPP estimation based on seasonal dynamic of GPP.
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