晋西黄土区2种典型森林树种夜间液流特征及对环境因子的响应

doi:10.17521/cjpe.2023.0219

摘要/Abstract

摘要：

了解晋西黄土区典型森林树种夜间水分利用对准确评价流域水循环和碳循环至关重要。但目前对于晋西黄土区典型森林树种夜间液流的变化特征及对夜间环境因子的响应尚不明晰。为了探究该地区典型树种的夜间液流分配特征及对环境因子的响应, 于2021年6-10月, 采用热扩散探针(TDP)对山西省吉县蔡家川小流域刺槐(Robinia pseudoacacia)人工林和蒙古栎(Quercus mongolica)天然林中树木树干液流、土壤水分和小气候进行连续监测, 利用时间序列模型(ARMAX model)区分夜间液流中夜间蒸腾(Tn)和茎干补水(Re)。利用机器学习模型XGboost和SHAP解释框架分析夜间液流量(Q_Nighttime)与夜间环境因子的关系。结果表明: 生长季刺槐和蒙古栎夜间蒸腾量占比(Tn/Q_Nighttime)分别为73.97%和30.12%, 茎干补水占比(Re/Q_Nighttime)分别为26.03%和69.88%。机器学习XGboost模型结果表明夜间饱和水汽压差(VPD)和夜间土壤水分含量(SWC)是分别影响刺槐和蒙古栎夜间液流的主导因子。VPD、夜间气温(T_a)、夜间相对湿度(RH)和整日液流量(Q_Daily)分别达到0.30 kPa、19.84 ℃、85.3%和339.11 kg·h^-1后对刺槐夜间液流起促进作用。VPD达到1.5 kPa后对蒙古栎夜间液流起抑制作用, T_a和夜间风速(WS)分别达到23.11 ℃和0.58 m·s^-1后促进蒙古栎夜间液流。SWC对刺槐和蒙古栎夜间液流的影响具有一致性, 即SWC在0-12.9%范围内会促进夜间液流。因此构建夜间液流模型时应考虑环境因子的影响。刺槐夜间液流主要用于夜间蒸腾作用, 而蒙古栎夜间液流主要用于茎干补水。夜间VPD和SWC分别是影响刺槐和蒙古栎夜间液流的主导因子。该研究揭示了晋西黄土区2种典型树种夜间液流分配特征及与环境因子的响应, 这对于准确理解气候变化下黄土区典型森林树种的稳定性具有重要意义。

关键词: 夜间液流, 环境因子, 夜间蒸腾, 黄土地区, 机器学习模型

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

付照琦, 胡旭, 田沁瑞, 葛艳灵, 周红娟, 吴小云, 陈立欣. 晋西黄土区2种典型森林树种夜间液流特征及对环境因子的响应. 植物生态学报, 2024, 48(9): 1128-1142. DOI: 10.17521/cjpe.2023.0219

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. Chinese Journal of Plant Ecology, 2024, 48(9): 1128-1142. DOI: 10.17521/cjpe.2023.0219

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链接本文: https://www.plant-ecology.com/CN/10.17521/cjpe.2023.0219

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

图/表 11

图1 晋西黄土区刺槐人工林(A)和蒙古栎天然林(B)林分胸径(DBH)分布频率。

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.

表1 晋西黄土区刺槐及蒙古栎样树统计表

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

图2 晋西黄土区刺槐人工林(A)及蒙古栎天然林(B)林分不同土层深度土壤含水量变化。

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.

图3 晋西黄土区观测期间刺槐人工林和蒙古栎天然林日间及夜间环境因子变化特征。p < 0.05代表日间和夜间环境因子的差异显著。

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.

图4 晋西黄土区刺槐(A、B)和蒙古栎(C、D)不同胸径(DBH)树木树干液流速率变化(平均值±标准差)。A、C代表日间; B、D代表夜间。

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.

表2 晋西黄土区不同林分液流量配对样本t检验结果(平均值±标准差)

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

图5 晋西黄土区刺槐人工林(A)和蒙古栎天然林(B)林分液流量及各林分夜间液流占比(C)日变化。

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.

图6 晋西黄土区刺槐人工林(A、C)和蒙古栎天然林(B、D)夜间蒸腾和茎干补水的逐时分布(平均值±标准差)及夜间蒸腾与茎干补水占比。QNighttime, 夜间液流。

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.

图7 基于XGboost模型的晋西黄土区刺槐人工林(A)和蒙古栎天然林(B)在测试集上液流预测值与实际值拟合曲线。MAE, 平均绝对误差; MSE, 均方误差; RMSE, 均方根误差; R2, 决定系数。

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.

图8 晋西黄土区刺槐人工林和蒙古栎天然林SHAP摘要图(A、B)和SHAP特征重要性柱状图(C、D)。

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.

图9 晋西黄土区刺槐人工林(A-F)和蒙古栎天然林(G-I)夜间液流与环境因子的SHAP依赖图。

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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