三种经验模型模拟荒漠河岸柽柳叶片气孔导度

植物叶片气孔是控制水分和CO_2出入的通道,是植物水分蒸腾和气体交换的门户。植物叶片气孔导度地准确模拟,对于植物蒸腾作用地有效模拟以及植物与大气间能量和质量平衡的研究至关重要。基于黑河下游阿拉善群落水热平衡综合观测场实际观测数据,采用LI-COR 6400光合作用测定系统,对荒漠河岸柽柳叶片气孔导度进行观测,分析晴朗天气条件下气孔导度日变化特征,同时,结合微气象及植物生理相关数据,运用学术界3种最常用的(半)经验模型对柽柳叶片气孔导度进行模拟,结果表明:(1)柽柳叶片气孔导度日变化大致呈先升高后降低的趋势。上午随着太阳辐射逐渐增强,气温逐渐升高,气孔导度值逐渐升高,蒸腾速率也逐渐增大,在10:00—12:00时间段内达到最大值。绝大部分观测日内12:00前后气孔导度呈现出一定的波动,原因在于温度过高致使叶片气孔关闭。随后,太阳辐射减弱,气温逐渐降低,空气中相对湿度增加,柽柳叶片内外水汽压差减小,气孔导度减小导致蒸腾速率下降。(2)通过3种最常用的(半)经验模型(Jarvis、Ball-Woodrow-Berry(BWB)和Ball-Berry-Leuning(BBL))模拟气孔导度的结果可以看出,Jarvis模型的修正效率系数(0.775、0.891)、修正一致系数(0.887、0.945)和决定系数(0.590、0.645)在3个模型中均是最高或次最高的,说明其模拟精度最高。(3)BWB模型与BBL模型的模拟精度相近,说明水汽压差、大气湿度与气孔导度的密切程度相近,没有明显的区别。

Simulating the leaf stomatal conductance of the desert riparian Tamarix ramosissima Ledeb. based on three empirical models

Stomata are accesses of moisture and CO₂ and gateways for evaporation and gas exchange. Estimating leaf stomatal conductance (g_s) is pivotal for the further estimation of transpiration rates as well as the energy and mass balances between the air and plants. Based on the data collected from the Alxa Comprehensive Observation Field of the Community Hydrothermal Balance in the lower reach of the Heihe River, we measured the g_s of Tamarix ramosissima and analyzed diurnal variations under clear weather conditions using a LI-6400 portable photosynthesis system. Meanwhile, by combining micro-meteorological and physiological data, we modeled the g_s of T. ramosissima based on the three most commonly used empirical models. The results showed that: (1) the diurnal variations of the g_s of T. ramosissima first increased and then decreased. With the gradual enhancement of solar radiation in the morning, the temperature and the transpiration rate gradually increased, and g_s increased accordingly, peaking between 10:00 and 12:00 h. On most observational days, g_s fluctuated to a certain extent around 12:00 h, and this was due to the high temperatures that caused the stoma to close. Afterwards, solar radiation weakened, air temperature decreased, the relative humidity in the air increased, the water vapor pressure inside and outside the leaves decreased, and g_s decreased, which led to a decrease in the transpiration rate. (2) We modeled g_s using three commonly used (semi-) empirical models (Jarvis; Ball-Woodrow-Berry, BWB; and Ball-Berry-Leuning, BBL), and we concluded that the Jarvis model always gives the most reliable performance with a modified coefficient of efficiency (E₁), modified index of agreement (d₁), and determination coefficient (R²) at values of 0.775 and 0.891, 0.887 and 0.945, and 0.590 and 0.645 in 2015 and 2016, respectively. (3) The accuracy between the BWB and BBL models was similar, indicating that there was no obvious difference between vapor pressure and relative humidity that influenced g_s.