Ecological variations of woody species along an altitudinal gradient in the Qinling Mountains of Central China: area-based versus mass-based expression of leaf traits
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Leaf trait-based research has become the preferred method to understand the ecological strategies of plants. However, there is still a debate on whether area-based or mass-based traits provide different insights into environmental adaptations and responses. In this study, seven key leaf traits (maximum net photosynthetic rate, dark respiration rate, nitrogen content, photosynthetic nitrogen use efficiency, leaf mass per area, leaf dry matter contents and leaf area) of 43 woody species were quantified on the basis of both area and mass along an altitudinal gradient (1100–2700 m) in the Qinling Mountains of China. Differences in leaf traits and bivariate correlations between the two expressions were compared. By considering different expressions, the strengths and directions of the responses of leaf traits to the altitudinal gradient were determined. Leaf traits showed large variations; interspecific variations contributed more to total variance than intraspecific variations. Bivariate correlations between photosynthetic traits and structural traits (mass per area, dry matter content, and area) were weaker on a mass basis than those on an area basis. Most traits exhibited quadratic trends along the altitudinal gradient, and these patterns were more noticeable for area-based than mass-based traits. Area-based traits were more sensitive to changes in temperature and precipitation associated with altitude. These results provide evidence that mass- versus area-based traits show different ecological responses to environmental conditions associated with altitude, even if they do not contain very broad spatial scales. Our results also indicate distinction of photosynthetic acclimation among the two expressions along an altitudinal gradient, reflecting trade-offs among leaf structure and physiological traits.
KeywordsAltitude modulation Bivariate relationship Leaf trait Qinling Mountains
We gratefully acknowledge the assistance of Pengcheng Wan and Mao Wang with field work and Jiangchao Guo with data processing.
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