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林业科学 ›› 2016, Vol. 52 ›› Issue (1): 136-142.doi: 10.11707/j.1001-7488.20160116

• 研究简报 • 上一篇    下一篇

灰胡杨叶片气孔导度特征及数值模拟

王海珍1,2, 韩路1,2, 徐雅丽1, 牛建龙1, 于军1   

  1. 1. 塔里木大学植物科学学院 阿拉尔843300;
    2. 新疆生产建设兵团塔里木盆地生物资源保护利用重点实验室 阿拉尔 843300
  • 收稿日期:2014-11-04 修回日期:2015-10-21 出版日期:2016-01-25 发布日期:2016-02-26
  • 基金资助:
    国家科技支撑计划项目(2014BAC14B00);国家自然科学基金项目(31260058,30960033);中科院"西部之光"人才培养项目(RCPY201209)。

Characteristics of Stomatal Conductance of Populus pruinosa and the Quantitative Simulation

Wang Haizhen1,2, Han Lu1,2, Xu Yali1, Niu Jianlong1, Yu Jun1   

  1. 1. College of Plant Science, Tarim University Alar 843300;
    2. Key Laboratory of Protection and Utilization of Biological Resource in Tarim Basin, Xinjiang Production & Construction Groups Alar 843300
  • Received:2014-11-04 Revised:2015-10-21 Online:2016-01-25 Published:2016-02-26

摘要: [目的] 构建适用于极端干旱荒漠区灰胡杨叶片气孔导度对环境因子响应的数学模型,为准确定量探讨灰胡杨叶片气孔调节和构建干旱荒漠区的水碳循环耦合机制模型奠定基础。[方法] 以塔里木河流域荒漠河岸林建群种灰胡杨为研究对象,利用LI-6400光合测定仪于2012年7-9月、2013年6-9月测定灰胡杨叶片气体交换参数与环境因子的日变化,利用逐步回归方法分析灰胡杨叶片气孔导度(Gs)对环境因子的响应,并应用国际上2类构建机制不同的代表性气孔导度模型对其气孔导度变化进行模拟及验证比较。[结果] 不同年份生长季各月灰胡杨叶片Gs的日变化均呈单峰曲线,峰值大小、出现时间与变幅不同,其中以9月峰值出现时间最早,日变幅最大,6月日变幅最小。Gs对环境因子变化敏感,与光合有效辐射(PAR)、大气CO2浓度(Ca)、大气湿度(RH)呈正相关,而与水汽压亏缺(VPD)、大气温度(Tair)呈负相关,尤其是PAR,VPD和Tair对全天与上午时段Gs的影响最显著,而下午时段Gs还受Ca,RH影响,表明不同时段灰胡杨Gs受不同的环境因子调控。利用国际上2类代表性Gs模型拟合并建立全天、上午与下午不同时段灰胡杨Gs的数学模型,Jarvis气孔导变模型对Gs变异程度的总体解释能力分别为69.1%,62.2%和63.3%,Leuning-Ball气孔导变模型对Gs变异程度的总体解释能力分别为53.5%,30.6%和44.5%。Jarvis气孔导变模型拟合全天、上午与下午时段Gs的效果均优于Leuning-Ball气孔导变模型,而Leuning-Ball气孔导变模型拟合下午时段Gs的效果优于上午时段,这与不同时段调控Gs的环境因子不同有关。依据野外实测数据对2类代表性Gs模型验证表明,Jarvis气孔导变模型比Leuning-Ball气孔导变模型更适合灰胡杨叶片Gs模拟,其可有效改善气孔导度环境响应行为的数值模拟效果。[结论] 生长季不同时段影响灰胡杨Gs的环境因子不同,Jarvis非线性气孔导度模型构建的不同时段灰胡杨气孔导度模型均优于Leuning-Ball线性气孔导度模型,其在极端干旱荒漠区具有更好的适用性。据此,构建适用于塔里木极端干旱荒漠区灰胡杨叶片气孔导度对环境因子的响应模型;Gs=PAR(0.001T2air+0.013Tair-0.090)/((260.443+PAR)(-0.219+VPD))。

关键词: 极端干旱区, 灰胡杨, 气孔导度, 环境因子, 模拟

Abstract: [Objective] The responses model of leaf stomatal conductance to environmental factors of Populus pruinosa in different periods constructed would be very helpful to elucidate stomatal regulation behavior of P. pruinosa, and to further simulate the dynamics of leaf photosynthesis and to develop a new water-carbon coupling cycle model in an extreme arid terrestrial ecosystem. P. pruinosa has been declining in recent years because of the increasingly worsening ecological environment, mainly caused by increased human water consumption. Up to now, the adjustment mechanisms of its stomatal conductance (Gs) are not clear. Our study is to elucidate current understanding of the mechanism that underlay the responses of stomatal conductance to variable environmental factors, and thereby to build up a model that expresses the relationship between stomatal conductance and environmental factors. This study would help us to further understand the photo-physiological characteristics of P. pruinosa and provide valuable information for protection of this vulnerable species. [Method] P. pruinosa, a constructive species of desert riparian forests in an extreme arid region in northwest China, was used as experimental material in this study. The leaf gas exchange parameters and environmental factors were measured with Li-6400 portable photosynthesis system during June to September in 2012 and 2013. The dynamic characteristics and the relationship between stomatal conductance and environmental factors were analyzed based on field observation data. Further, Jarvis and Leuning-Ball models were used to simulate the dynamic process of leaf stomatal conductance, and applicability of the two models in extreme arid region was compared. [Result] The diurnal courses of stomatal conductance of P. pruinosa were a single peak curve in growth season, there were obviously differences in peak values, time and amplitude in every months. Especially, peak time appeared the earliest and largest amplitude in September, and minimum amplitude of peak value in June. The leaf stomatal conductance was sensitive to photosynthesis active radiation, vapor pressure deficit and air temperature. The leaf stomatal conductance increased with photosynthesis active radiation, atmospheric CO2 concentration and air humidity, and decreased with increase of the vapor pressure deficit and air temperature. Statistical analysis showed that photosynthesis active radiation, vapor pressure deficit and air temperature significantly affected stomatal conductance of whole day and forenoon, while the stomatal conductance in afternoon was affected obviously by atmospheric CO2 concentration and air humidity. Stomatal conductance of P. pruinosa in different periods was regulated by the different environmental factors. The fitted models of stomatal conductance of P. pruinosa in different periods were simulated and constructed with two representative stomatal conductance models, Jarvis model could explain on average 69.1%, 62.2%, and 63.3% of variation and Leuning-Ball model could explain on average 53.5%, 30.6%, and 44.5% of variation in the observed stomatal conductance at whole day, forenoon and afternoon, respectively. The sensitivity and fitting effect of Jarvis model was better than that of Leunning-Ball model at different periods. The fitting effect of Leunning-Ball model in afternoon was better than that in forenoon, indicating that the environmental factors that affected stomatal conductance were different in different periods. The validations of Leuning-Ball linear and Jarvis non-linear models based on field data of leaf stomatal conductance indicated that Jarvis model was better estimation of stomatal conductance than Leuning-Ball model, and Jarvis model could improve the simulation effect of stomatal conductance. [Conclusion] The environmental factors of different periods affecting stomatal conductance of P. pruinosa were obviously different in growth seasons. The sensitivity and fitting effect of Jarvis non-linear stomatal conductance models were better than that of Leunning-Ball linear model at different periods, it had better applicability in the extremely arid-desert region. The relationship among leaf Gs and environmental factors in extremely arid Tarim basin could be expressed as:Gs=PAR(0.001Tair2+ 0.013 Tair -0.090)/((260.443+PAR)(-0.219+VPD)).

Key words: extreme arid region, Populus pruinosa, stomatal conductance, environmental factors, simulation

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