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

Abstract

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

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.

Figures/Tables 9

Fig. 1

Fig. 2

Tab. 1

Correlation coefficient between each environmental factor and stomatal conductance (gs)"

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

Tab. 1

Tab. 2

Fig. 3

Tab. 3

Determination of the Jarvis model expressions for estimating stomatal conductance of apple tree in 2019, respectively"

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

Tab. 3

Tab. 4

The expressions of the Jarvis and BWB models"

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

Tab. 4

Fig. 4

Tab. 5

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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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