Abstract
We defined gas exchange phenology as the seasonality of the gas exchange characteristics of a forest canopy, and investigated how the gas exchange phenology could be directly detected from an eddy covariance (EC) dataset and its influence on the canopy fluxes within an evergreen Japanese cypress forest. For the detection of gas exchange phenology, we derived three bulk parameters of the extended big-leaf model (Kosugi et al. 2005) inversely from EC flux data over a 7-year period: surface conductance (g c), maximum rate of carboxylation of the “big leaf” (V CMAX), and intercellular CO2 concentration of the “big leaf” (C I). The relationship between g c and the vapor pressure deficit declined in winter and spring. The relationship between the daily ecosystem respiration and air temperature was greater in the spring than in the other seasons. The temperature dependence curve of V CMAX decreased substantially in the winter and was different from that of an evergreen broadleaved forest. A decrease in C I was occasionally coupled with the decrease in canopy gross primary production during April and August, indicating that stomatal closure was responsible for a decline in canopy photosynthesis. Gas exchange phenology should be quantified when understanding the determining factors of the seasonality of canopy fluxes at evergreen coniferous forests.
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Acknowledgments
Eddy covariance and meteorological observations were conducted along with Mr. Masato Yano, Mr. Tatsuya Katayama, Mr. Takumi Wada, Mr. Tomonori Mitani, Mr. Yusuke Fukui, Ms. Rie Fukui, Mr. Naoto Yokoyama, Ms. Chika Soda, Mr. Takuya Matsumoto, Mr. Ryoji Nakagawa, and Mr. Shuhei Kanemitsu. This research was partially supported both by a Grant-in-Aids for Scientific Research from the Ministry of Education, Science, Sports and Culture, Japan, and by the Mitsui & Co., Ltd. Environment Fund.
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Kosugi, Y., Takanashi, S., Ueyama, M. et al. Determination of the gas exchange phenology in an evergreen coniferous forest from 7 years of eddy covariance flux data using an extended big-leaf analysis. Ecol Res 28, 373–385 (2013). https://doi.org/10.1007/s11284-012-1019-4
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DOI: https://doi.org/10.1007/s11284-012-1019-4