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气孔通过调节植物体水分散失和CO2吸收在植物适应环境变化和环境胁迫中发挥重要作用。该文在对极端干旱区多枝柽柳(Tamarix ramosissma)叶片气体交换参数观测的基础上,引入诊断函数f(H)对BWB模型和BBL模型提出的气孔导度(gs)模型中的空气湿度(hs或Ds)进行了评价,并将评价结果引入叶子飘和于强推导出的gs机理模型。结果表明:(1)BWB和BBL模型对hs(或Ds)的模拟效果存在很大差异:BWB模型拟合效果较好(R2=0.5354),BBL模型的结果显著但效果较差(R2=0.1103)。试验结果显示:随hs(或Ds)的增大,gs呈先增大后减小的趋势,可用Gauss模型进行拟合,R2分别为0.593和0.258,说明gs与hs的关系要比Ds更密切;(2)叶子飘和于强给出的简化模型(Simple模型)和该文给出的指数模型(Gauss-h模型)均具有较好的模拟效果(R2分别为0.8707和0.8286),η值分别为0.1245和0.0171,其值均介于0-1之间;(3)模型验证中Gauss-h模型较Simple模型明显低估了观测值,当观测条件无限趋近于Simple模型的假设时,Simple模型的拟合效果可得到显著提高(R2=0.9606)。
Stomata play an important role in plant adaptation to environmental changes and environmental stress by regulating plant water loss and CO2 absorption. Based on the observation of gas exchange parameters of leaves of Tamarix ramosissma in the extremely arid region, the diagnostic function f (H) was introduced to measure the air humidity in the stomatal conductance (gs) model proposed by the BBL model hs or Ds) were evaluated, and the evaluation results were introduced into the gs mechanism model of leaf floating and strong derivation. The results show that: (1) The simulation results of hs (or Ds) are very different for BWB and BBL models: the fitting effect of BWB model is better (R2 = 0.5354), the BBL model results are obvious but the effect is poor (R2 = 0.1103 ). The results showed that gs increased firstly and then decreased with the increase of hs (or Ds), which could be fitted by Gauss model with R2 of 0.593 and 0.258, respectively. This indicated that the relationship between gs and hs was closer than Ds ; (2) Both the simplified model (Simple model) given by Ye Zhipun and Yu Qiang and the exponential model (Gauss-h model) given in this paper have good simulation results (R2 = 0.8707 and 0.8286, respectively) (0.1245 and 0.0171, respectively), all of which ranged from 0 to 1. (3) The Gauss-h model obviously underestimated the observed value compared with the Simple model in the model verification. When the observation conditions are infinitely close to the Simple model, Simple The model fitting effect can be significantly improved (R2 = 0.9606).