Mapping the global distribution of C4 vegetation using observations and optimality theory

Mapping the global distribution of C4 vegetation using observations and optimality theory

09 February 2024 | Xiangzhong Luo, Haoran Zhou, Tin W. Satriawan, Jiaqi Tian, Ruiying Zhao, Trevor F. Keenan, Daniel M. Griffith, Stephen Sitch, Nicholas G. Smith & Christopher J. Still
This study investigates the global distribution and changes in C4 vegetation, including natural grasses and crops, using observations, remote sensing, and an optimality theory-based photosynthesis model. The authors found that from 2001 to 2019, the global coverage of C4 vegetation decreased from 17.7% to 17.1% of the land surface. This decrease was primarily due to a reduction in C4 natural grass cover, which was influenced by elevated CO2 levels favoring C3-type photosynthesis, and an increase in C4 crop cover, mainly from corn expansion. The study estimated that C4 vegetation contributed 19.5% of global photosynthetic carbon assimilation, higher than the ensemble mean of dynamic global vegetation models (14 ± 13%). The findings highlight the critical role of C4 plants in the global carbon cycle and the need for more accurate models to predict their responses to climate change.This study investigates the global distribution and changes in C4 vegetation, including natural grasses and crops, using observations, remote sensing, and an optimality theory-based photosynthesis model. The authors found that from 2001 to 2019, the global coverage of C4 vegetation decreased from 17.7% to 17.1% of the land surface. This decrease was primarily due to a reduction in C4 natural grass cover, which was influenced by elevated CO2 levels favoring C3-type photosynthesis, and an increase in C4 crop cover, mainly from corn expansion. The study estimated that C4 vegetation contributed 19.5% of global photosynthetic carbon assimilation, higher than the ensemble mean of dynamic global vegetation models (14 ± 13%). The findings highlight the critical role of C4 plants in the global carbon cycle and the need for more accurate models to predict their responses to climate change.
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