北京山区大果榆树干液流的季节与昼夜环境调控

doi:10.11707/j.1001-7488.LYKX20220868

摘要/Abstract

摘要：

目的: 探究水源涵养树种树干液流在不同时间尺度的环境调控机制和蒸腾，以提高森林生态系统水源涵养功能评估的准确性，为森林可持续性经营管理提供科学支持。方法: 以北京松山地区乡土树种大果榆为研究对象，2019年和2020年生长季，采用热扩散技术法连续原位观测其树干液流，并同步观测相关环境变量，采用线性和非线性回归法分析树干液流速率（J_s）对环境的响应。结果: 连续2年生长季内大果榆单位地面面积蒸腾累计分别为334和252 mm，平均每天分别为1.82和1.37 mm。生长期J_s变化主要由短波辐射（R_s）、空气温度（T_a）、饱和水汽压差（VPD）等环境因子综合调控，J_s与R_s、T_a和VPD均呈显著正线性相关关系，决定系数R²分别为0.93、0.88和0.89，VPD对J_s的调控存在阈值（0.9 kPa）。R_s、T_a和VPD与冠层气孔导度（g_s）之间存在显著相关关系。昼夜尺度上，J_s主要受R_s控制，J_s日变化滞后R_s。结论: 季节与昼夜尺度上J_s的调控因子存在一定差异，其环境调控主要通过调节冠层气孔导度进而影响植物树干液流。树干液流对环境因子的敏感性差异及二者日变化的时滞效应能够充分反映出大果榆的耐旱性和环境适应性。

关键词: 树干液流, 环境变量, 辐射, 冠层气孔导度, 时滞

Abstract:

Objective: This study was carried out to explore the responses of the sap flow and transpiration to the environmental factors at different time scales, and the result here could provide scientific support for formulating appropriate management for forest ecosystem and improve the accuracy of assessment of water conservation function of forest ecosystem. Method: The thermal diffusion method was used to continuously monitor the sap flow of Ulmus macrocarpa in Songshan, Beijing during the growing season in 2019 and 2020, and the relevant environmental variables were observed simultaneously. Linear and non-linear regressions were used to analyze abiotic control on sap flow. Result: The cumulative transpiration was 333.85 mm and 252.27 mm in 2019 and 2020, respectively, with daily means of 1.82 mm and 1.37 mm in the two years, respectively. Seasonally, the J_s was controlled by shortwave radiation (R_s), air temperature (T_a), water vapor pressure deficit (VPD). The relationships between J_s and R_s, T_a and VPD were significantly and positively linear, with the coefficient of determination R² being 0.93, 0.88 and 0.89, respectively, and with a VPD threshold of 0.9 kPa in growing season. The relationship of J_s and R_s was stronger (higher R²) than that with both T_a and VPD in the same month. The daily variation in J_s lagged that of R_s, but preceded that of T_a and VPD. The relationships between g_s and R_s, T_a, and VPD were non-linear correlation, being different from the responses of J_s to environmental factors. Conclusion: There are differences between seasonal and diurnal scale in environmental control mechanism of sap flow, the changes of environmental factors affect the sap flow of plant mainly through inducing stomatal changes. The time lag between J_s and environmental factors is explained by the difference in response of canopy stomatal conductance (g_s) and J_s to environmental factors. The time lag and sensitivity of sap flow to environmental factors can reflect drought tolerance and environmental adaptability. These results would help estimation of transpiration under similar environmental conditions and improvment of hydrological model for assessment of water conservation function of forest ecosystem.

Key words: sap flow, environmental factors, radiation, canopy stomatal conductance, time lag

中图分类号:

S718.43

张凯,孙艳丽,隗骥超,范雅倩,韩小雪,李林,魏晓帅,李鑫豪,刘鹏,查天山. 北京山区大果榆树干液流的季节与昼夜环境调控[J]. 林业科学, 2023, 59(7): 24-34.

Kai Zhang,Yanli Sun,Jichao Wei,Yaqian Fan,Xiaoxue Han,Lin Li,Xiaoshuai Wei,Xinhao Li,Peng Liu,Tianshan Zha. Control of Environmental Factors on the Sap Flow at Daily and Seasonal Scales in Ulmus macrocarpa in Beijing, China[J]. Scientia Silvae Sinicae, 2023, 59(7): 24-34.

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编号 No.	树高 Height/ m	胸径 Diameter at breast height/cm	木质部直径 Diameter of xylem/ cm	心材直径 Diameter of heartwood/ cm	边材面积 Sapwood area/ cm²
1	5.5	9.75	8.75	4	56.13
2	4.3	10.75	8.75	3	57.88
3	5.1	11.65	6.65	4	30.73
4	4.1	9.35	6.35	2	30.67
5	6.7	13,2	10.2	5	75.46
6	7.8	18.85	14.85	5	166.95

变量 Variable	年份 Year	平均值 Mean	最小值 Minimum	最大值 Max.	标准差 Standard deviation
液流速率 Sap flow J_s /(g·cm^?2d^?1)	2019 2020	137.08 99.02	0.13 0.46	299.59 259.33	80.75 70.27
土壤含水量 Volumetric soil water content VWC /(m³·m^?3)	2019 2020	0.22 0.25	0.14 0.14	0.30 0.31	0.04 0.04
短波辐射 Shortwave radiation R_s/ (W·m^?2)	2019 2020	198.84 180.71	26.88 17.33	329.13 327.36	73.56 72.90
空气温度 Air temperature T_a / ℃	2019 2020	15.76 14.81	?0.048 1.64	25.15 22.25	4.99 5.10
饱和水汽压差 Vapor pressure deficit VPD/ kPa	2019 2020	0.88 0.63	0.03 0.01	2.15 1.97	0.40 0.37

月份Month	J_s?VWC Y = a × X + b	J_s?R_s Y = a × X + b	J_s?T_a Y = a × X + b	J_s?VPD Y = a × X + b
5月May	a = ?56.57 b = 17.69 R² = 0.04 × n = 1433	a = 0.010 b = 1.05 R² = 0.52 × n = 1433	a = 0.61 b = ?5.00 R² = 0.40 × n = 1433	a = 4.64 b = ?1.65 R² = 0.33 × n = 1433
6月June	a = ?4.24 b = 4.22 R² = 0.0004 × n = 2622	a = 0.011 b = 0.75 R² = 0.80 × n = 2622	a = 0.77 b = ?10.54 R² = 0.53 × n = 2622	a = 3.83 b = ?0.27 R² = 0.38 × n = 2622
7月July	a = ?5.06 b = 4.21 R² = 0.003 × n = 2311	a = 0.012 b = 0.61 R² = 0.76 × n = 2311	a = 0.71 b = ?10.60 R² = 0.47 × n = 2311	a = 4.30 b = ?0.22 R² = 0.41 × n = 2311
8月August	a = ?35.11 b = 12.23 R² = 0.05 × n = 2670	a = 0.013 b = 0.51 R² = 0.71 × n = 2670	a = 0.52 b = ?6.31 R² = 0.20 × n = 2670	a = 4.03 b = ?0.08 R² = 0.23 × n = 2670
9月September	a = ?17.47 b = 6.68 R² = 0.03 × n = 2718	a = 0.013 b = 0.35 R² = 0.74 × n = 2718	a = 0.73 b = ?8.05 R² = 0.51 × n = 2718	a = 6.02 b = ?1.62 R² = 0.50 × n = 2718
10月October	a = ?7.68 b = 2.12 R² = 0.04 × n = 2930	a = 0.001 b = 0.16 R² = 0.06 × n = 2930	a = 0.10 b = ?0.38 R² = 0.20 × n = 2930	a = 0.85 b = ?0.27 R² = 0.07 × n = 2930

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