Plant Diversity ›› 2019, Vol. 41 ›› Issue (04): 258-265.DOI: 10.1016/j.pld.2019.06.003
Jianguo Gaoa,c,d, Kai Tianb
收稿日期:
2019-04-04
修回日期:
2019-06-10
出版日期:
2019-08-25
发布日期:
2019-09-17
通讯作者:
Jianguo Gao,E-mail address:gaojg@pku.edu.cn
基金资助:
Jianguo Gaoa,c,d, Kai Tianb
Received:
2019-04-04
Revised:
2019-06-10
Online:
2019-08-25
Published:
2019-09-17
Contact:
Jianguo Gao,E-mail address:gaojg@pku.edu.cn
Supported by:
摘要: Transpiration through stomata in tree canopies plays an important role in terrestrial water cycles. However, the empirical relationship between leaf stomata anatomy and canopy stomatal conductance (Gs) is surprisingly rare, thereby the underlying biological mechanisms of terrestrial water flux are not well elucidated. To gain further insight into these mechanisms, we reanalyzed the dataset of Gs previously reported by Gao et al. (2015) using a quantile regression model. The results indicated that the reference Gs (Gsref, Gs at 1 kPa) was negatively correlated with wood density at each quantile, which confirmed previous data; however, Gsref was significantly correlated with stomatal density at the 0.6 quantile, i.e., 450 stomata mm-2. This highlighted the potential of using stomatal density as a trait to predict canopy water flux. A conceptual model of co-determinants of xylem and stomatal morphology suggests that these traits and their coordination may play a critical role in determining tree growth, physiological homeostatic response to environmental variables, water use efficiency, and drought resistance.
Jianguo Gao, Kai Tian. Stem and leaf traits as co-determinants of canopy water flux[J]. Plant Diversity, 2019, 41(04): 258-265.
Jianguo Gao, Kai Tian. Stem and leaf traits as co-determinants of canopy water flux[J]. Plant Diversity, 2019, 41(04): 258-265.
表1 2013年湿地生态系统阴天和晴天净生态系统CO2交换(NEE)和光合有效辐射(PAR)根据Michaclis-Menten模型(方程(3))模拟参数的比较
Table 1 Comparison of the analog parameters from daytime net ecosystem exchange of CO2(NEE) and photosynthetically active radiation (PAR) using a Michaelis-Menten model (Eq.(3)) between sunny days and cloudy days in the wetland
方程 Equation | R2 | p | n | |
---|---|---|---|---|
晴天 Sunny day | NEE = -0.005PAR - 0.28T + 4.06 | 0.41 | <0.001 | 288 |
阴天 Cloudy day | NEE = -0.006PAR - 0.107T + 2.67 | 0.42 | <0.001 | 288 |
阴天和晴天差量 Difference between sunny and cloudy days | ΔNEE = -0.004ΔPAR - 0.123ΔT - 2.54 | 0.63 | <0.001 | 288 |
表2 多元回归分析黄河三角洲湿地生长季阴天和晴天光合有效辐射(PAR)与气温(T)对净生态系统CO2交换(NEE), 阴天和晴天PAR差量(ΔPAR)与T差值(ΔT)对NEE差量(ΔNEE)的协同影响
Table 2 Estimated empirical coefficient of multiple liner regression models for changes in net ecosystem exchange (NEE) with photosynthetically active radiation (PAR) and air temperature (T) on sunny and cloudy days during the growing season in the Yellow River Delta
方程 Equation | R2 | p | n | |
---|---|---|---|---|
晴天 Sunny day | NEE = -0.005PAR - 0.28T + 4.06 | 0.41 | <0.001 | 288 |
阴天 Cloudy day | NEE = -0.006PAR - 0.107T + 2.67 | 0.42 | <0.001 | 288 |
阴天和晴天差量 Difference between sunny and cloudy days | ΔNEE = -0.004ΔPAR - 0.123ΔT - 2.54 | 0.63 | <0.001 | 288 |
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