AI Article Synopsis

  • The study measured photosynthetic light curves and CO2 curves for Juglans regia and Ziziphus jujuba over three seasons using a LI-6400 portable system, focusing on key parameters like maximal net photosynthetic rate, apparent quantum efficiency, carboxylation rate, and water use efficiency.
  • While Juglans regia showed peak photosynthesis later in the season and was more influenced by atmospheric humidity, Ziziphus jujuba peaked mid-season and was more affected by air temperature.
  • The findings highlight how relative humidity, temperature, and soil moisture affect photosynthesis and water use efficiency in these tree species, suggesting that understanding these physiological differences can enhance forest carbon models and predictions under climate change.

Article Abstract

Both the photosynthetic light curves and CO(2) curves of Juglans regia L. and Ziziphus jujuba Mill. var. spinosa in three seasons were measured using a LI-6400 portable photosynthesis system. The maximal net photosynthetic rate (A(max)), apparent quantum efficiency(phi), maximal carboxylation rate (V(cmax)) and water use efficiency (WUE) of the two species were calculated based on the curves. The results showed that A(max) of J. regia reached its maximum at the late-season, while the highest values of A(max) of Z. jujuba occurred at the mid-season. The A(max) of J. regia was more affected by relative humidity (RH) of the atmosphere, while that of Z. jujuba was more affected by the air temperature. Light saturation point (LSP) and Light compensation point (LCP) of J. regia had a higher correlation with RH of the atmosphere, those of Z. jujuba, however, had a higher correlation with air temperature. V(cmax) of both J. regia and Z. jujuba had negative correlation with RH of the atmosphere. WUE of J. regia would decrease with the rise of the air temperature while that of Z. jujuba increased. Thus it could be seen that RH, temperature and soil moisture had main effect on photosynthesis and WUE of J. regia and Z. jujuba. Incorporating data on the physiological differences among tree species into forest carbon models will greatly improve our ability to predict alterations to the forest carbon budgets under various environmental scenarios such as global climate change, or with differing species composition.

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Source
http://dx.doi.org/10.1111/j.1744-7909.2007.00391.xDOI Listing

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