Using the red chromatic coordinate to characterize the phenology of forest canopy photosynthesis

Liu, Ying; Wu, Chaoyang; Sonnentag, Oliver; Desai, Ankur R.; Wang, Jian

doi:10.1016/j.agrformet.2020.107910

Title: Using the red chromatic coordinate to characterize the phenology of forest canopy photosynthesis

Journal Article · 29 January 2020 · Agricultural and Forest Meteorology

DOI: https://doi.org/10.1016/j.agrformet.2020.107910 · OSTI ID:1802806

Liu, Ying ^[1]; Wu, Chaoyang ^[2]; Sonnentag, Oliver ^[3];

^[4]; Wang, Jian ^[5]

Chinese Academy of Sciences (CAS), Beijing (China); Univ. of the Chinese Academy of Sciences, Beijing (China); OSTI
Chinese Academy of Sciences (CAS), Beijing (China); Univ. of the Chinese Academy of Sciences, Beijing (China)
Univ. de Montréal, QC (Canada)
Univ. of Wisconsin, Madison, WI (United States)
The Ohio State Univ., Columbus, OH (United States)

Vegetation phenology has received increasing attention in climate change research. Near-surface sensing using digital repeat photography has proven to be useful for ecosystem-scale monitoring of vegetation phenology. However, our understanding of the link between phenological metrics derived from digital repeat photography and the phenology of forest canopy photosynthesis is still incomplete, especially for evergreen plant species. Using 49 site-years of digital images from the PhenoCam Network from eight evergreen needleleaf forest (ENF) and six deciduous broadleaf forest (DBF) sites in North America, we explored the potential of the green chromatic (GCC) and red chromatic coordinates (RCC) in tracking forest canopy photosynthesis by comparing camera-derived start- and end-of-growing season (SOS and EOS, respectively) with corresponding estimates derived from eddy covariance-derived daily gross primary productivity (GPP). We found that for DBF sites, both GCC and RCC performed comparable in capturing SOS and EOS. However, similar to earlier studies, GCC had limited potential in capturing GPP-based SOS or EOS for ENF sites. In contrast, we found RCC was a better predictor of both GPP-based SOS and EOS for ENF sites. Environmental and ecological explanations were both provided that phenological transitions derived from RCC were highly correlated with spring and autumn meteorological conditions, as well as having overall higher correlations with phenology based on LAI, a critical variable for describing canopy development. Our results demonstrate that RCC is an underappreciated metric for tracking vegetation phenology, especially for ENF sites where GCC failed to provide reliable estimates for GPP-based SOS or EOS. Our results improve confidence in using digital repeat photography to characterize the phenology of canopy photosynthesis across forest types.

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Research Organization:: Princeton Univ., NJ (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Grant/Contract Number:: SC0016011

OSTI ID:: 1802806

Journal Information:: Agricultural and Forest Meteorology, Journal Name: Agricultural and Forest Meteorology Vol. 285-286; ISSN 0168-1923

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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