南方丘陵区油茶气孔导度模型修正

为探求南方丘陵地区油茶叶片气孔导度最优响应模型,该研究于2020年和2021年对油茶叶片的气孔导度、净光合速率、CO2浓度等参数进行观测,运用9种不同组合的Jarvis模型以及2种不同CO2浓度（叶片CO2浓度和胞间CO2浓度）计算的Ball-Woodrow-Berry（BWB）模型和Ball-Berry-Leuning（BBL）模型对油茶叶片气孔导度进行模拟,并引入油茶叶片叶气温差、气孔内外CO2浓度差对Jarvis模型和BBL模型进行修正和比较。结果表明：去除土壤水分函数提高了Jarvis模型的模拟效果,说明在南方丘陵区利用Jarvis模型时可以忽略土壤水分这一因子的影响。Jarvis-8模型以及用叶片CO2浓度计算出的BWB和BBL模型对油茶气孔导度模拟效果较好。在三种经典模型中,BBL模型的相关系数最大（R2=0.76）,绝对值平均误差最小（0.015）,说明其对油茶气孔导度模拟的效果较好。在引入两种参数后,叶气温差对Jarvis-8模型和BBL模型的模拟效果有所提高,但不显著;气孔内外CO2浓度差对Jarvis-8模型无明显改变,但显著提高了BBL模型的精度,引入气孔内外CO2浓度差后的BBL-C模型相关系数从BBL模型的0.76提高到了0.95,模型斜率非常接近于1（1.004）,模拟结果贴近于实测的气孔导度值,很好地模拟了2020年（R2=0.92）和2021年（R2=0.95）油茶生长关键期的叶片气孔导度值以及不同场景下的油茶气孔导度日变化值。因此推荐引入气孔内外CO2浓度差的 BBL模型作为南方丘陵区油茶叶片气孔导度响应模型。研究结果可为南方丘陵区油茶气孔导度模型选取提供参考依据。

Modifying the stomatal conductance model of Camellia oleifera in the southern hilly region of China

This study aims to determine the optimal response model of stomatal conductance to the Camellia oleifera leaves in hilly areas of south China. A portable photosynthetic apparatus (LCI-SD) was used to observe the leaves of three healthy Camellia oleifera trees in four directions of southeast, northwest every 10 days from June to September in 2020 and 2021. The field test was performed at Hunan National Camellia oleifera Engineering Technology Research Center in Changsha City, Hunan Province, China. A miniature automatic meteorological observation U30 Station (HOBO ware) was utilized to record synchronously the stomatal conductance, net photosynthetic rate, and CO2 concentration in the leaves, together with the meteorological data, such as atmospheric temperature, relative humidity, and photosynthetically active radiation. Then, the stomatal conductance of leaf was simulated using the Jarvis models with nine combinations, the Ball-Woodrow-Berry (BWB) and Ball-Berry-Leuning (BBL) model with two CO2 concentrations of leaf and intercellular. The Jarvis-8 and BBL model were modified to compare the introduced temperature of camellia oil leaves, and the CO2 concentration inside and outside stomata. A nonlinear regression and least square method were used to determine each parameter by the SPSS25.0 software platform. The results show that the influence of soil water or leaf water potential could be ignored when using the Jarvis model in the hilly region of southern China. It infers that the Jarvis model was dependent mainly on the photosynthetically active radiation, saturation vapor pressure deficit and temperature. Therefore, the soil water or leaf water potential was be ignored, when the Jarvis model was used in the hilly region of southern China. A better simulation effect was achieved in the Jarvis-8, BWB, and BBL model calculated by the leaf CO2 concentration. Among them, the BBL model presented the largest correlation coefficient (R2=0.754) and the smallest absolute mean error (MAE=0.015), indicating the best effect. By contrast, the BWB model presented the smallest correlation coefficient (R2=0.599), and the maximum absolute mean error (MAE=0.020), indicating the worst simulation effect. After two parameters were introduced, the simulation effect of leaf temperature difference was improved in the Jarvis-8 and BBL model, but not significantly. The CO2 concentration difference between inside and outside the stomatal was significantly improved the accuracy of the BBL model, where the correlation coefficient increased from 0.763 to 0.970, and the slope of the model was very close to 1 (1.003), indicating the better consistence between the simulation and the measured stomatal conductance value. But, there was no change of the Jarvis-8 model in this case. A better simulation was achieved for the stomatal conductance values of leaves in the key growth periods of Camellia oleifera in 2020 (R2=0.92) and 2021 (R2=0.95), and the variation values of stomatal conductance degree-days under different scenarios. On the whole, the simulation performance was ranked in the descending order of the BBL-C model, BBL-Tmodel, BBL model, Jarvis-T model, Jarvis model, and Jarvis-C model. Therefore, the stomatal conductance response model of Camellia oleifera leaves can be recommended to introduce the BBL model with the CO2 concentration difference between stomatal. These findings can provide a strong reference to select a suitable stomatal conductance model for the large-scale Camellia oleifera in the hilly region of southern China.