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Published November 28, 2022 | Supplemental Material + In Press
Journal Article Open

Vegetation clumping modulates global photosynthesis through adjusting canopy light environment

Abstract

The spatial dispersion of photoelements within a vegetation canopy, quantified by the clumping index (CI), directly regulates the within-canopy light environment and pho-tosynthesis rate, but is not commonly implemented in terrestrial biosphere models to estimate the ecosystem carbon cycle. A few global CI products have been developed recently with remote sensing measurements, making it possible to examine the global impacts of CI. This study deployed CI in the radiative transfer scheme of the Community Land Model version 5 (CLM5) and used the revised CLM5 to quantitatively evaluate the extent to which CI can affect canopy absorbed radiation and gross primary production (GPP), and for the first time, considering the uncertainty and seasonal variation of CI with multiple remote sensing products. Compared to the results without considering the CI impact, the revised CLM5 estimated that sunlit canopy absorbed up to 9-15 and 23-34 less direct and diffuse radiation, respectively, while shaded canopy absorbed 3-18 more diffuse radiation across different biome types. The CI impacts on canopy light conditions included changes in canopy light absorption , and sunlit-shaded leaf area fraction related to nitrogen distribution and thus the maximum rate of Rubisco carboxylase activity (V꜀ₘₐₓ), which together decreased photosynthesis in sunlit canopy by 5.9-7.2 PgC year⁻¹ while enhanced photosynthesis by 6.9-8.2 PgC year⁻¹ in shaded canopy. With higher light use efficiency of shaded leaves, shaded canopy increased photosynthesis compensated and exceeded the lost photosynthesis in sunlit canopy, resulting in 1.0 ± 0.12 PgC year⁻¹ net increase in GPP. The uncertainty of GPP due to the different input CI datasets was much larger than that caused by CI seasonal variations, and was up to 50% of the magnitude of GPP interannual variations in the tropical regions. This study highlights the necessity of considering the impacts of CI and its uncertainty in terrestrial biosphere models.

Additional Information

© 2022 The Authors. Global Change Biology published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. This study is supported from the National Aeronautics and Space Administration (NASA) through Remote Sensing Theory and Terrestrial Ecology programs 80NSSC21K0568 and 80NSSC21K1702. M.C. also acknowledges a support by a McIntire–Stennis grant (1027576) from the National Institute of Food and Agriculture (NIFA), United States Department of Agriculture (USDA). M.C., K.Y., and Q.Z. acknowledge the support from NASA through the Carbon Monitoring System program 20-CMS20-0039. D.H. acknowledges the support by the U.S. Department of Energy (DOE), Office of Science, Office of Biological and Environmental Research, Earth System Model Development program area, as part of the Climate Process Team projects. The research carried out at the Jet Propulsion Laboratory, California Institute of Technology, was under a contract with NASA. California Institute of Technology. Government sponsorship acknowledged. We thank the helpful communication with Dr. Gordon Bonan on the status of the multi-canopy-layer version of CLM. We acknowledge high-performance computing support from Cheyenne (doi: 10.5065/D6RX99HX) provided by NCAR's Computational and Information Systems Laboratory, sponsored by the National Science Foundation and the UW-Madison Center for High Throughput Computing (CHTC) in the Department of Computer Sciences. The CHTC is supported by UW-Madison, the Advanced Computing Initiative, the Wisconsin Alumni Research Foundation, the Wisconsin Institutes for Discovery, and the National Science Foundation, and is an active member of the OSG Consortium, which is supported by the National Science Foundation and the U.S. Department of Energy's Office of Science. The authors declare no conflict of interest. Links of used datasets and code are listed: The revised CLM5 code with clumping index: https://github.com/Fa-Li/CTSM. The multi-layer CLM model code: https://github.com/gbonan/CLM-ml_v1. The Google Earth Engine code and produced land surface data with clumping index information is from Li, Hao, et al. (2022). The data that support the findings of this study are openly available at https://doi.org/10.5281/zenodo.7212844.

Attached Files

Supplemental Material - gcb16503-sup-0001-appendixs1.pdf

In Press - Global_Change_Biology_-_2022_-_Li_-_Vegetation_clumping_modulates_global_photosynthesis_through_adjusting_canopy_light.pdf

Files

gcb16503-sup-0001-appendixs1.pdf

Additional details

Created:
August 20, 2023
Modified:
October 23, 2023