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Diurnal variation of photosynthesis of different plants in summer in Yintan wetland of Lanzhou section of Yellow River.

KANG Ya-rong1, ZHANG Hua1,2**   

  1. (1College of Geographic and Environmental Sciences, Northwest Normal University, Lanzhou 730070, China; 2State Key Laboratory of Grassland Agricultural System, Lanzhou University, Lanzhou 730000, China)
  • Online:2014-09-10 Published:2014-09-10

Abstract:

In order to understand the photosynthetic characteristics of dominant species in Yintan wetland of Lanzhou section of Yellow River in summer, ten species were selected, including Lythrum salicaria, Phragmites communis, Polygonum lapathifolium, Echinochloa crusgalli, Solanum nigrum, Amaranthus retroflexus, Datura stramonium, Onobrychis viciaefolia, Scirpus triqueter, and Juncellus serotinus. Then, the diurnal variations of photosynthetically active radiation (PAR), net photosynthetic rate (Pn), transpiration rate (Tr), stomatal conductance (Gs), intercellular CO2 concentration (Ci) of the mature leaves of each plant, and the atmospheric temperature (Ta) and atmospheric CO2 concentration (Ca) were measured by employing the CI-340 portable photosynthetic system. The curves of diurnal variation of Pn in leaves of seven plants showed two peaks, suggesting a remarkable photosynthetic “midday depression”, which was caused by stomatal limitation and nonstomatal limitation. Correlation analysis and stepwise regression analysis showed that there was good correlation between Pn and Tr, Gs, PAR in most plants, and each factor had different coefficients of contribution to Pn, indicating that the main physiological and ecological factors influencing the photosynthetic rate were different among species. Moreover, strong light and high temperature at noon intensified the transpiration rate of wetland plants. Our study provides information on understanding the relationship between photosynthetic characteristics and environmental factors of the dominant species, and on species selection of planting wetland plants.
 

Key words: SOFM neural network, ecosystem service bundles, Inner Mongolia Autonomous Region, ecological function zoning