Stem and leaf traits as co-determinants of canopy water flux

doi:10.1016/j.pld.2019.06.003

Abstract

Abstract: 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 (G_s) 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 G_s previously reported by Gao et al. (2015) using a quantile regression model. The results indicated that the reference G_s (G_sref, G_s at 1 kPa) was negatively correlated with wood density at each quantile, which confirmed previous data; however, G_sref 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.

Key words: G_sref, Quantile regression, Stomatal density, Water flux, Wood density

Jianguo Gao, Kai Tian. Stem and leaf traits as co-determinants of canopy water flux[J]. Plant Diversity, 2019, 41(04): 258-265.

Figures/Tables 6

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

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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