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Comparison of two numerical models on photosynthetic response ofQuercus mongolica leaves to air pollutants
A multiple-regression model is presented for estimating the effect of major air pollutants on net photosynthetic rate (Pn) ofQuercus mongolica leaves, of which visible injury is not shown. Photosynthetic capacity was found to be primarily a function of PPFD, air temperature (T) and ambient ozone (O3...
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Published in: | Journal of plant biology = Singmul Hakhoe chi 1999-03, Vol.42 (1), p.32-40 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | A multiple-regression model is presented for estimating the effect of major air pollutants on net photosynthetic rate (Pn) ofQuercus mongolica leaves, of which visible injury is not shown. Photosynthetic capacity was found to be primarily a function of PPFD, air temperature (T) and ambient ozone (O3) concentration. The negative direction of photosynthetic capacity response to O3 concentration indicates a potential growth reduction ofQ. mongolica due to ambient O3 concentration in the urban areas of Korea. The model was compared with a non-linear regression model including the same variables. We assessed the contribution of variables to two two models of ambient O3 affecting Pn ofQ. mongolica leaves. The mean Pn difference between the models with and without ambient O3 in the multiple-regression was smaller than that in the non-linear regression. The relative contributions of ambient O3 to multiple-regression and non-linear regression were 12.6% and 5.6%, respectively. The results indicate that multiple-regression models can be applicable for qualitative or quantitative assessment of the effect of air pollutants on Pn response of plant leaves, of which visible injury may not be shown in situ. Also, the assessment of ecophysiological effects using numerical models will have a degree of uncertainty associated with the measuring time/period of the field data used in the modelling, as well as the numerical structure of the models. |
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ISSN: | 1226-9239 1867-0725 |
DOI: | 10.1007/BF03031144 |