Physiological responses of Abies faxoniana populations from different elevations to increased CO2 and N application |
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Authors: | Yongping?Li,Tingfa?Dong,Baoli?Duan,Yuanbin?Zhang author-information" > author-information__contact u-icon-before" > mailto:zhangyb@imde.ac.cn" title=" zhangyb@imde.ac.cn" itemprop=" email" data-track=" click" data-track-action=" Email author" data-track-label=" " >Email author |
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Affiliation: | 1.Key Laboratory of Mountain Surface Processes and Ecological Regulation, Institute of Mountain Hazards and Environment,Chinese Academy of Sciences,Chengdu,China;2.School of Agriculture,Yunnan University,Kunming,China;3.Chengdu Institute of Biology,Chinese Academy of Sciences,Chengdu,China;4.University of Chinese Academy of Sciences,Beijing,China |
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Abstract: | The altitude-related responses to the increased application of CO2, N, and their combination were investigated in two Abies faxoniana populations, which originated from a subalpine coniferous forest at elevations of 2,580 and 3,200 m using closed-top chambers. The two contrasting populations were subjected to two CO2 regimes (350 and 700 µmol mol?1) and two N levels (0 and 5 g N m?2 year?1). Their net photosynthetic rate, non-structural carbohydrate concentration, and photosynthetic N use efficiency (PNUE) increased under elevated CO2. However, the increases detected in the high-elevation (HE) population were significantly greater than those found in the low-elevation (LE) population. Under elevated CO2 and N application, the maximal carboxylation rate (V cmax) increased in HE population, whereas no effects were found on V cmax in LE population. The C to N ratio decreased under N application in both populations. N application also induced the HE population to show greater increases in free amino acids, soluble proteins, N concentration, and PNUE than LE population. These results suggested that the population from HE was more sensitive to elevated CO2 and (or) N application than LE population. Results of this study provided valuable knowledge for predicting forest development under increased atmospheric CO2 concentration and (or) N deposition. |
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