黄土高原苹果树叶片气孔导度的环境响应与模拟

doi:10.12118/j.issn.1000–6060.2021.02.23

干旱区地理 ›› 2021, Vol. 44 ›› Issue (2): 525-533.doi: 10.12118/j.issn.1000–6060.2021.02.23

黄土高原苹果树叶片气孔导度的环境响应与模拟

苗玉¹(),高冠龙^1,^2,³(),李伟¹

1.山西大学环境与资源学院,山西太原 030006
2.陕西省土地整治重点实验室,陕西西安 710064
3.中国科学院西北生态环境资源研究院,甘肃兰州 730000

收稿日期:2020-10-08 修回日期:2020-11-23 出版日期:2021-03-25 发布日期:2021-04-14
通讯作者: 高冠龙
作者简介:苗玉（1996-）,女,硕士研究生,研究方向为生态水文与植物生理生态研究. E-mail:my09296822@163.com
基金资助:
山西省应用基础研究面上青年基金项目(201801D221286);中国博士后科学基金资助项目(2018M643769);山西省高等学校科技创新项目(2020L0028);中央高校基本科研业务费（自然科学类）资助项目资助(300102279505)

Environmental response and modeling of stomatal conductance of apple trees on the Loess Plateau

MIAO Yu¹(),GAO Guanlong^1,^2,³(),LI Wei¹

1. College of Environment and Resource, Shanxi University, Taiyuan 030006, Shanxi,China
2. Shaanxi Key Laboratory of Land Consolidation, Chang’an University, Xi’an 710064, Shaanxi,China
3. Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, Gansu, China

Received:2020-10-08 Revised:2020-11-23 Online:2021-03-25 Published:2021-04-14
Contact: Guanlong GAO

摘要/Abstract

摘要：

气孔导度（g_s）是衡量植物与外界环境中水、CO₂等物质交换速率的重要参数,其观测与模拟可以有效指示物质交换情况及各项生理参数。通过LI-6400便携式光合测定仪对黄土高原苹果树叶片各项生理参数进行观测,分析g_s日变化特征及其与环境因子的响应关系,运用Jarvis模型和Ball-Woodrow-Berry（BWB）模型对g_s进行模拟。研究结果显示：（1）黄土高原苹果树g_s日变化在气温较高、辐射较强的8、9月观测日内呈双峰曲线。上午（8:00—12:00）随着太阳辐射逐渐增强,气孔张开,g_s在11:00—13:00出现第一次峰值;中午（12:00—14:00）由于气温（T_a）升高,为避免细胞散失过多水分,气孔关闭出现短暂的“光合午休”现象;午后（14:00—18:00）,随着T_a、光合有效辐射（PAR）下降,g_s逐渐增加并在15:00—17:00出现第二次峰值。（2）通过灰色关联度分析,发现g_s与各环境因子的关联程度依次为：PAR（0.731）>CO₂浓度（C_a,0.712）>饱和水汽压差（VPD,0.702）>T_a（0.689）>相对湿度（h_s,0.673）。g_s与各环境因子的响应关系表现为：随PAR、T_a、C_a、h_s的增大而增大,随VPD的增大而减小。（3）从g_s的模拟结果可以看出,Jarvis模型的决定系数（0.678）、修正效率系数（0.335）和修正一致系数（0.803）均优于BWB模型各值（0.329、-1.630、0.138）,而平均绝对误差（0.103）小于BWB模型（0.143）,表明Jarvis模型模拟效果较好。通过对黄土高原苹果树叶片g_s环境响应与模拟的分析研究,对于掌握苹果树叶片一天内不同时刻对水分的需求变化,进一步提高该地区苹果树种植的水资源利用效率具有重要意义。

关键词: 气孔导度, 灰色关联度, 苹果树, 黄土高原

Abstract:

In this study, stomatal conductance (g_s) was used to measure the exchange rate of water, CO₂, and other substances between plants and the external environment. The observation and simulation of g_s effectively indicated the exchange of substances and various physiological parameters. The Loess Plateau is typical of a temperate monsoon climatic zone in China and supports an agricultural area dominated by the cultivation of apple trees. In this study, an LI-6400 portable photosynthesis system was used to observe the physiological parameters of apple trees in situ on the Loess Plateau, the diurnal variation characteristics of their g_s, and the relationships of these variables with environmental factors. The g_s was simulated using the Jarvis model and the Ball-Woodrow-Berry (BWB) model. The results show that (1) the diurnal variation of g_s in apple trees on the Loess Plateau showed a bimodal curve in August and September when temperatures were high and radiation was strong. The solar radiation increased gradually in the mornings (8:00—12:00), the stomata opened, and the first peak of g_s appeared between 11:00 and 13:00. Around the noon hour (12:00—14:00), stimulated by the increase in temperature (T_a), the stomata of plants closed for a short period during the “midday depression of photosynthesis” to reduce water loss from plant cells. In the afternoon (14:00—18:00), as T_a and photosynthetically-active radiation (PAR) decreased, g_s gradually increased, and a second peak appeared between 15:00 and 17:00. (2) Using the gray correlation degree, the correlation between g_s and various environmental factors was as follows (in descending order): (PAR, 0.731)>CO₂ concentration (C_a, 0.712)>vapor pressure deficit (VPD, 0.702)>T_a (0.689)>relative humidity (h_s, 0.673). The response relationship between g_s and the various environmental factors produced the following results: (1) it increased with increases in PAR, T_a, C_a, and h_s and decreased with increases in VPD, and (2) The simulation of g_s showed that the value of the determination coefficient (0.678), the modified coefficient of efficiency (0.335), and the modified index of agreement (0.803) were higher in the Jarvis model than in the BWB model (0.329, -1.630, 0.138), and the mean absolute error (0.103) was smaller than the error in the BWB model (0.143). Comparison of the simulation accuracy of multiple models showed that the Jarvis model had superior simulation accuracy. The results of the analysis of g_s in response to environmental factors and its simulation in apple tree leaves on the Loess Plateau is important to understand how the demand for water by the leaves changes throughout the day. This knowledge can be used to improve the efficiency of water utilization and thus optimize the harvest. In the future, simulation studies of g_s for a variety of crops grown in arid and semi-arid climatic conditions may benefit from the application of the Jarvis model in resource management.

Key words: stomatal conductance, grey relational degree analysis, apple tree, Loess Plateau

苗玉,高冠龙,李伟. 黄土高原苹果树叶片气孔导度的环境响应与模拟[J]. 干旱区地理, 2021, 44(2): 525-533.

MIAO Yu,GAO Guanlong,LI Wei. Environmental response and modeling of stomatal conductance of apple trees on the Loess Plateau[J]. Arid Land Geography, 2021, 44(2): 525-533.

图/表 9

图1

图2

表1

各环境因子与气孔导度（gs）的关联系数"

PAR/W·m^-2	C_a/μmol·mol^-1	VPD/kPa	T_a/℃	$h s$ /%
0.732	0.423	0.533	0.665	0.484
0.877	0.481	0.555	0.874	0.527
0.815	0.524	0.818	0.677	0.693
0.746	0.498	0.721	0.772	0.628
0.838	0.407	0.751	0.714	0.516
0.492	0.400	0.801	0.843	0.642
0.998	0.522	0.513	0.510	0.590
0.736	0.830	0.646	0.782	0.671
0.911	0.969	0.958	0.775	0.897
0.649	0.931	1.000	0.818	0.833
0.864	0.804	0.893	0.882	0.723
0.678	0.856	0.947	0.992	0.753
0.834	0.521	0.476	0.419	0.497
0.708	0.678	0.734	0.893	0.896
0.612	0.611	0.887	0.915	0.698
0.822	0.845	0.897	0.745	0.718
0.668	0.850	0.702	0.537	0.729
0.561	0.937	0.717	0.529	0.771
0.854	0.646	0.817	0.810	0.645
0.859	0.671	0.841	0.834	0.671
0.755	0.716	0.486	0.510	0.558
0.748	0.797	0.445	0.508	0.544
0.856	0.802	0.334	0.413	0.468
0.480	0.850	0.509	0.604	0.499
0.356	0.702	0.646	0.790	0.599
0.704	0.732	0.574	0.520	0.978
0.787	0.714	0.648	0.541	0.774
0.767	0.840	0.673	0.580	0.662
0.864	0.966	0.932	0.770	0.592
0.341	0.831	0.594	0.445	0.946

表1

表2

图3

表3

2019年用于模拟苹果树叶片气孔导度的Jarvis模型结构确定"

表达式	R²	系数
$g p 1 (PAR) g D 1 (VPD) g T (T a) g c (C a)$	-	-
$g p 1 (PAR) g D 2 (VPD) g T (T a) g c (C a)$	0.677	0.997
$* g p 1 (PAR) g D 3 (VPD) g T (T a) g c (C a)$	0.678	0.756
$g p 2 (PAR) g D 1 (VPD) g T (T a) g c (C a)$	-	-
$g p 2 (PAR) g D 2 (VPD) g T (T a) g c (C a)$	0.628	-0.222
$g p 2 (PAR) g D 3 (VPD) g T (T a) g c (C a)$	0.617	-0.861
$g p 3 (PAR) g D 1 (VPD) g T (T a) g c (C a)$	-	-
$g p 3 (PAR) g D 2 (VPD) g T (T a) g c (C a)$	0.673	0.517
$g p 3 (PAR) g D 3 (VPD) g T (T a) g c (C a)$	0.677	-0.262

表3

表4

Jarvis模型、BWB模型表达式"

模型	公式	表达式	R²
Jarvis模型	$g p 1 (PAR) g D 3 (VPD) g T (T a) g c (C a)$	$g s = (0.001 + 6.885 E - 7 PAR) × 1 - 2.890 VPD 1 + 2.730 VPD × (- 128.936 + 11.444 T a - 0.150 T a 2) × (1 + 0.003 C a)$	0.678
BWB模型	$g s = m A × h s C s + g 0$	$g s = 0.001 × A × h s C s + 0.036$	0.329

表4

图4

表5

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黄土高原苹果树叶片气孔导度的环境响应与模拟

Environmental response and modeling of stomatal conductance of apple trees on the Loess Plateau

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模型	修正效率系数（E₁）/mm	修正一致系数（d₁）/mm	平均绝对误差（MAE）/mm	R²
Jarvis模型	0.335	0.803	0.103	0.678
BWB模型	-1.630	0.138	0.143	0.329

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