Nocturnal sap flow characteristics of two typical forest tree species and responses to environmental factors in the loess region of West Shanxi, China

doi:10.17521/cjpe.2023.0219

Abstract

Abstract:

Aims Understanding the nighttime water use of typical forest tree species in the west Loess Plateau is crucial for accurately evaluating the watershed-scale water and carbon cycles. However, the nighttime sap flow dynamics and its response to environmental factors are currently unclear for typical forest species in the west Loess Plateau.

Methods We monitored the sap flow with thermal dissipation probes (TDP) and concurrent environmental factors of Robinia pseudoacaciaplantation and Quercus mongolica natural forest in the Caijiachuan watershed from June to September 2021. The time series model (ARMAX model) was used to distinguish between nighttime transpiration (Tn) and stem water replenishment (Re) in nocturnal sap flow (Q_Nighttime). We used the machine learning model XGboost and Shapley additive interpretation framework to analyze and explain the relationship between Q_Nighttime and nighttime environmental factors.

Important findings The proportion of nighttime transpiration (Tn/Q_Nighttime) was 73.97% and 30.12% for the R. pseudoacacia and the Q. mongolica, respectively, during the growing season. The proportion of stem water filling (Re/Q_Nighttime) was 26.03% and 69.88% for the two species, respectively. The XGboost model showed that nighttime vapor pressure deficit (VPD) and nighttime soil water content (SWC) were the main factors driving Q_Nighttime in R. pseudoacacia and Q. mongolica, respectively. VPD, nighttime air temperature (T_a), nighttime relative humidity (RH), and daily sap flow (Q_Daily) can promote the Q_Nighttime when they reach 0.30 kPa, 19.84 °C, 85.3%, and 339.11 kg·h^-1. For Q. mongolica, VPD inhibited Q_Nighttime when it reached 1.5 kPa, while T_a and nighttime wind speed (WS) promoted Q_Nighttime when it reached 23.11 ℃ and 0.58 m·s^-1, respectively. The effects of SWC on Q_Nighttime in R. pseudoacacia and Q. mongolica were similar. The SWC within 0-12.9% range would promote the occurrence of Q_Nighttime. Therefore, our study highlights the importance of considering the magnitude of all environmental factors in establishing the nocturnal sap flow model. This study revealed the characteristics of Q_Nighttime composition and their responses to environmental factors of two typical tree species in the west Loess Plateau. Our findings are of great significance for accurately understanding the stability of typical forest tree species in the loess region under climate change.

Key words: nocturnal sap flow, environmental factor, nocturnal transpiration, the loess area, machine learning model

FU Zhao-Qi, HU Xu, TIAN Qin-Rui, GE Yan-Ling, ZHOU Hong-Juan, WU Xiao-Yun, CHEN Li-Xin. Nocturnal sap flow characteristics of two typical forest tree species and responses to environmental factors in the loess region of West Shanxi, China[J]. Chin J Plant Ecol, 2024, 48(9): 1128-1142.

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URL: https://www.plant-ecology.com/EN/10.17521/cjpe.2023.0219

https://www.plant-ecology.com/EN/Y2024/V48/I9/1128

Figures/Tables 11

Fig. 1 Diameter at breast height (DBH) distribution frequency of Robinia pseudoacacia plantation (A) and Quercus mongolica natural forest (B) in the loess region of West Shanxi.

Table 1 Statistical table of sample trees of Robinia pseudoacacia and Quercus mongolica in the loess region of West Shanxi, China

树种 Species	编号 No. of sample trees	胸径 Diameter at breast height (cm)	树高 Tree height (m)	冠幅面积 Crown area (m²)	边材面积 Sapwood area (cm²)
刺槐 R. pseudoacacia	R1	23.0	14.5	5.0	197.1
刺槐 R. pseudoacacia	R2	25.0	14.5	17.5	226.5
	R3	12.0	10.0	2.0	66.4
	R4	18.7	13.5	14.0	139.4
	R5	8.5	10.5	0.6	37.3
	R6	15.3	13.0	4.0	99.7
蒙古栎 Q. mongolica	Q1	18.0	10.8	14.0	99.4
蒙古栎 Q. mongolica	Q2	13.0	10.5	8.7	55.3
	Q3	6.9	8.5	3.0	17.6
	Q4	19.2	10.1	5.0	111.6
	Q5	9.0	9.5	2.5	28.5

Fig. 2 Changes of soil water content at different soil depths of Robinia pseudoacacia plantation (A) and Quercus mongolica natural forest (B) in the loess region of West Shanxi.

Fig. 3 Variations of environmental factors during the observation period in the Robinia pseudoacacia plantation and Quercus mongolica forest in the loess area of West Shanxi. p < 0.05 represents the significant difference between daytime and nighttime environmental factors.

Fig. 4 Sap flow rate of Robinia pseudoacacia (A, B) and Quercus mongolica (C, D) of sample trees with different diameter at breast height (DBH) in the loess area of West Shanxi (mean ± SD). A, C represent daytime; B, D represent nighttime.

Table 2 The t-test result of sap flux of different stand in the loess area of West Shanxi (mean ± SD)

林分 Stand	整日液流 Daily sap flow (mm)	日间液流 Daytime sap flow (mm)	夜间液流 Nighttime sap flow (mm)	夜间液流占比 Proportion of nighttime sap flow (%)
刺槐人工林 Robinia pseudoacacia plantation	0.42 ± 0.26^a	0.38 ± 0.23^a	0.03 ± 0.01^a	10.68 ± 1.05^b
蒙古栎天然林 Quercus mongolica forest	0.31 ± 0.25^b	0.29 ± 0.16^b	0.02 ± 0.00^b	12.75 ± 1.50^a

Fig. 5 Daily variations of stand sap flow for Robinia pseudoacacia plantation (A) and Quercus mongolica forest (B) and proportions of nocturnal sap flow to total daily sap flow (C) in the loess area of West Shanxi.

Fig. 6 Hourly evaluation and distribution (mean ± SD) of nocturnal transpiration (Tn) and stem water refilling (Re) to nighttime sap flow (QNighttime) in Robinia pseudoacacia (A, C) plantation and Quercus mongolica forest (B, D) and partitioning of QNighttime into Tn and Re in the loess area of West Shanxi.

Fig. 7 Predicted and observed nighttime sap flow curves of Robinia pseudoacacia plantation (A) and Quercus mongolica forest (B) based on the XGboost model on the test set on hourly scale in the loess area of West Shanxi. MAE, mean absolute error; MSE, mean-square error; RMSE, root mean square error; R2, the coefficient of determination.

Fig. 8 SHAP summary plot (A, B) and importance matrix (C, D) of Robinia pseudoacacia plantation and Quercus mongolica forest in the loess area of West Shanxi. QDaily, daily sap flow; RH, relative humidity; SWC, soil water content; Ta, air temperature; VPD, vapor pressure deficit; WS, wind speed.

Fig. 9 SHAP dependence plot of nighttime sap flow and environmental factors of Robinia pseudoacacia plantation (A-F) and Quercus mongolica forest (G-I) in the loess area of West Shanxi. QDaily, daily sap flow; RH, relative humidity; SWC, soil water content; Ta, air temperature; VPD, vapor pressure deficit; WS, wind speed.

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