Diurnal and nocturnal changes in stem sap flow of <i>Robinia pseudoacacia</i> during growing season and its response to meteorological factors

ZHANG Rong; BI Huaxing; JIAO Zhenhuan; WANG Ning; ZHAO Danyang; YUN Huiya; HUANG Jinghan

doi:10.11833/j.issn.2095-0756.20220159

Volume 39 Issue 6

Nov. 2022

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Article Navigation > Journal of Zhejiang A&F University > 2022 > 39(6): 1238-1246

ZHANG Rong, BI Huaxing, JIAO Zhenhuan, WANG Ning, ZHAO Danyang, YUN Huiya, HUANG Jinghan. Diurnal and nocturnal changes in stem sap flow of Robinia pseudoacacia during growing season and its response to meteorological factors[J]. Journal of Zhejiang A&F University, 2022, 39(6): 1238-1246. doi: 10.11833/j.issn.2095-0756.20220159

Citation:

ZHANG Rong, BI Huaxing, JIAO Zhenhuan, WANG Ning, ZHAO Danyang, YUN Huiya, HUANG Jinghan. Diurnal and nocturnal changes in stem sap flow of Robinia pseudoacacia during growing season and its response to meteorological factors[J]. Journal of Zhejiang A&F University, 2022, 39(6): 1238-1246. doi: 10.11833/j.issn.2095-0756.20220159

Diurnal and nocturnal changes in stem sap flow of Robinia pseudoacacia during growing season and its response to meteorological factors

doi: 10.11833/j.issn.2095-0756.20220159

ZHANG Rong^1
,,
BI Huaxing^{1, 2, 3, 4, 5
,
,},
JIAO Zhenhuan⁶,
WANG Ning¹,
ZHAO Danyang¹,
YUN Huiya¹,
HUANG Jinghan¹

1.
College of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China
2.
Ji County Station, Chinese National Ecosystem Research Network (CNERN), Beijing 100083, China
3.
Key Laboratory of National Forestry and Grassland Administration on Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China
4.
Beijing Engineering Research Center of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China
5.
Engineering Research Center of Forestry Ecological Engineering, Ministry of Education, Beijing Forestry University, Beijing 100083, China
6.
Changping Hydrology and Water Quality Monitoring Center, Beijing 102200, China

Received Date: 2022-02-13
Accepted Date: 2022-06-19
Rev Recd Date: 2022-06-12

Available Online: 2022-11-21

Publish Date: 2022-12-20

Abstract

Objective The objective is to analyze the diurnal and nocturnal changes in stem sap flow of Robinia pseudoacacia in the growing season and explore the impact of meteorological factors on transpiration of R. pseudoacacia , so as to provide theoretical basis for estimating forest water consumption and forest water resource management. Method Eight sample trees were selected from R. pseudoacacia sample plots in Caijiachuan watershed, Ji County of Shanxi Province. From May to September 2021, thermal diffusion probe (TDP) was used to continuously observe stem sap flow of sample trees, and meteorological factors such as solar radiation, air temperature, soil temperature, wind speed and relative humidity were monitored simultaneously. Random forest and stepwise linear regression were used to analyze the influence of meteorological factors on stem sap flow. Result (1) The order of diurnal sap flow rate from small to large in the growing season was September, May, June, August and July, and the contribution rate of diurnal sap flow to full-day sap flow was 88%−93%. The nocturnal sap flow rate ranging from small to large was September, May, August, July and June, and the contribution rate of nocturnal sap flow to full-day sap flow was 7%−12%. (2) The main meteorological factors affecting the diurnal sap flow rate were basically the same, mainly solar radiation and air temperature. The dominant meteorological factors affecting nocturnal sap flow were different in each month. The main factors were soil temperature and water vapor pressure deficit in May and June, air temperature in July, water vapor pressure deficit and relative humidity in August, and wind speed and water vapor pressure deficit in September. (3) The fitting degree of the monthly day-night flow rate model constructed by random forest regression method was better than that by stepwise regression method. Conclusion There are obvious differences in diurnal and nocturnal sap flow rate in each month. The effect of nocturnal sap flow on water consumption of R. pseudoacacia should not be ignored, and the effect of meteorological factors on diurnal and nocturnal sap flow rate is different. Daytime and nighttime should be distinguished when simulating water consumption of tree transpiration according to meteorological factors. [Ch, 3 fig. 6 tab. 24 ref.]
- Robinia pseudoacacia,
- sap flow rate,
- growing season,
- diurnal variation,
- meteorological factors,
- loess region of western Shanxi Province

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黄土高原是干旱半干旱地区，降水量少，降水分布不均，生态环境脆弱。自20世纪50年代以来，该地区采取了一系列的植被恢复措施，并取得了显著成效，但由于不合理的植被建设，导致林水矛盾激化，部分林地出现“小老头树”和土壤水分亏缺等现象^[1-3]。基于此，研究黄土高原地区林地树种耗水规律尤为重要。99.8%以上的植物蒸腾耗水来自树干液流，液流速率可以较为准确地描述单木蒸腾耗水过程^[4-5]。早期对植物蒸腾研究多集中于昼间，忽略夜间液流的存在。随着观测技术的发展与研究时间尺度的精细化，越来越多的研究发现整日树干液流可划分为昼间与夜间，昼夜液流变化特征具有差异性^[6]。昼间液流量占整日液流量的80%~96%，是植物生长的主要环节，研究昼间液流的变化特征有助于理解植物的生长策略^[7]；夜间液流量占比为4%~20%^[8]，占比较少，但目前研究普遍认为^[9]：夜间液流有助于植物适应干旱环境，在补充水分、传输营养、供应氧气等方面发挥着重要的作用，因此在研究植物蒸腾耗水时，夜间液流不可被忽视。

已经有大量的研究表明：植物液流速率受自身生理结构和气象因子的影响。任启文等^[10]研究发现：冀北山地油松Pinus tabulaeformis液流速率与气温、太阳辐射、水汽压亏缺、风速呈正相关，与空气湿度呈负相关；贾国栋等^[11]通过研究北方土石山区的油松、刺槐Robinia pseudoacacia发现：影响植物蒸腾速率的主要气象因子为太阳辐射、水汽压亏缺和风速；也有研究认为^[12]：不同时间尺度下树干液流与气象因子的响应不同。上述研究关注于整日树干液流与气象因子关系研究，然而昼夜树干液流对环境因子响应机制不同，若不考虑昼夜液流变化特征及其对环境因子响应差异性，可能会降低植物耗水估算精度，影响林地水资源管理。目前，关于晋西黄土区生长季刺槐昼夜树干液流速率的研究较少，不同月份气象因子对昼夜树干液流速率的影响有待进一步研究。基于此，本研究以山西省吉县蔡家川流域的主要造林树种刺槐作为研究对象，定位观测其树干液流和气象因子。主要研究目的是①分析刺槐昼夜树干液流变化特征；②分析各月夜间树干液流对总液流的贡献率；③探究各月昼夜树干液流变化对气象因子的响应；④建立各月昼夜树干液流与气象因子关系模型，估算样地林分耗水量。

1. 研究区概况

研究区位于晋西黄土残塬沟壑区山西省吉县蔡家川流域(36°14′27″~36°18′23″N，110°39′45″~110°47′45″E)，属于黄河支流，流域面积为40.10 km²。该地区海拔为900~1500 m，属暖温带大陆性季风气候，年平均气温为10.0 ℃，年平均降水量为575.9 mm，降水分布不均，4—10月降水量约占全年的85% (489.5 mm)，年平均蒸发量为1 723.9 mm。研究区土壤为褐土，黄土母质。

研究样地为人工刺槐纯林，林分密度为1625株·hm⁻²，平均树高为9.4 m，平均胸径为18.4 cm。林地灌木稀少，草本植物以萝藦Metaplexis japonica、鼠尾粟Sporobolus fertilis、艾蒿Artemisia lavandulaefolia、茜草Rubia cordifolia、短尾铁线莲Clematis brevicaudata、龙芽草Agrimonia pilosa等为主。

2. 研究方法

2.1. 树干液流测定

选取生长良好，树干通直，无病虫害的刺槐标准木8株。样木基本情况如表1。各样树树干液流采用Granier热扩散探针(TDP)观测，观测时间为2021年5月1日至9月30日。在大约1.3 m胸高处选择观测点，并刮去树干死皮，用配套工具沿垂直方向钻2个小孔，将热源探针插入上方孔中，感应探针插在下方孔中，使用固体胶将树体与探针的空隙涂抹密封。将电缆线固定在树干上并与电源连接，用铝箔纸将安装部位整个树干包裹起来，防止阳光直射和雨水造成数据误差。将数据采集器设置为30 s采集1次数据，隔15 min计算平均值并记录。

样树编号胸径/cm 树高/m 边材面积/cm² 样树编号胸径/cm 树高/m 边材面积/cm²

1 22.5 10.2 142.2 5 16.8 9.5 85.2
2 21.9 11.2 141.5 6 18.0 11.0 93.4
3 20.6 9.8 138.7 7 17.4 10.3 90.2
4 21.3 11.2 140.2 8 18.2 10.8 92.6

Table 1. Main parameters of sample trees

树干液流速率采用Granier经验公式获得。计算公式为：

式(1)中：ΔT_m为无液流时加热探针与参考探针的最大温差(℃)；ΔT为瞬时温差值(℃)；F_d为树干液流速率(cm³·h⁻¹·cm⁻²)

2.2. 气象因子测定

研究区刺槐样地里安装有全自动气象站，可全天观测林冠上方(距地面20 m)气象因子。气温(T，℃)和空气相对湿度(H_R，%)采用HMP155A空气温湿度传感器观测，太阳辐射(R_s，W·m⁻²)采用CMP-3总辐射传感器观测，风速(S_W，m·s⁻¹)采用010C-1风速传感器观测，林内20 cm土壤温度(T_s，℃) 采用109土壤温度传感器观测。设置数据采集时间间隔为30 min，并采用CR1000数据采集与记录器收集数据。选取水汽压亏缺(D_VP)指标综合反映空气相对湿度与空气温度的协同效应。

2.3. 数据处理

采用baseliner软件将温差数据转化为液流数据，使用Excel整理和计算树干液流、气象因子数据，使用SPSS软件与R语言进行相关分析，使用Origin绘图。图表中所用数据均为平均值±标准差。采用配对样本t检验分析各月整日树干液流量与昼间树干液流量的差异性；采用Pearson相关分析法分析气象因子与树干液流的相关关系；采用随机森林回归模型中相对重要性得分指标[IncMSE，IncMSE指去除自变量后随机森林回归模型预测误差的百分数，自变量关于IncMSE得分越高，说明自变量越重要]与逐步回归方程中因子进入方程时拟合度(R²)的变化值分析气象因子对树干液流的影响程度(随机森林是基于分类树的算法^[13]，该算法预测精度较高，被多个领域用于评估指标重要性)；采用随机森林回归法与逐步回归法构建气象因子与树干液流速率相关模型。

4. 讨论

4.1. 树干液流昼夜特征

刺槐在不同月份的单日树干液流速率均呈先增后减的变化趋势，在日出前后液流启动，峰值时间在12:00左右，并且在10:00—16:00保持较高水平。这与赵楠^[14]、凡超等^[15]、吴旭等^[16]的研究结果一致。各月昼间树干液流速率从小到大依次为9月、5月、6月、8月、7月，说明刺槐昼间蒸腾速率满足生长盛期(6—8月)最大，生长初期(5月)次之，生长末期(9月)最小的规律，且生长季各月昼间树干液流速率对整日液流速率贡献率均在88%以上，说明生长季刺槐白天的蒸腾活动较为强烈。

刺槐在各月夜间树干液流速率从小到依次为9月、5月、8月、7月、6月，生长盛期的夜间树干液流速率显著大于生长初期与生长末期夜间树干液流速率。目前，有关夜间树干液流贡献率的研究较多，如王志超等^[17]、HAYAT等^[18]研究表明：尾叶桉Larix kaempferi与沙柳Salix psammophila夜间树干液流分别占整日树干液流的6.62%和11.00%。本研究发现：各月夜间液流对整日液流的贡献率范围为7.00%~12.00%，夜间树干液流对整日树干液流的贡献率从大到小依次为生长末期、生长初期、生长盛期，而徐志彬等^[19]、张婕等^[8]研究表明：生长初期夜间树干液流速率与贡献率较大，可能是研究树种与研究区气象要素不同导致研究结果出现差异。此外，研究不同树种树干液流在不同时间尺度上动态变化的目的是为了能够精准估算各树种耗水变化。本研究发现：生长季各月昼夜树干液流差异较大，夜间树干液流的占比不可忽视，因此今后在月尺度上估算刺槐蒸腾耗水量时需要考虑到月尺度的差异性以及夜间树干液流差异性。

4.2. 气象因子对昼夜树干液流的影响

植物树干液流速率的变化受到周围环境的影响。本研究发现：刺槐各月昼间树干液流速率与太阳辐射、气温、水汽压亏缺、土壤温度呈正相关，与相对湿度呈负相关。这与刘崴等^[20]、YIN等^[21]研究结果基本一致。主导昼间树干液流速率的气象因子在各月差异不显著，主要为气温与太阳辐射。气温升高有助于加快叶片表面的水分散发，促进植物根系吸水从而增强植物蒸腾作用。但孙旭等^[22]研究认为：土壤温度是影响油松树干液流的主导因子之一，与本研究的结果不一致。可能是研究的时间尺度、植被类型、植被覆盖度差异导致，因此关于树种耗水的研究需要综合考虑时间尺度与地下植被的影响。

目前，关于气象因子对夜间树干液流速率影响统一的结论是太阳辐射与夜间液流没有相关性。本研究结果显示：刺槐各月夜间液流速率与气温、水汽压亏缺、土壤温度、风速呈正相关，与相对湿度呈负相关。各月主导刺槐夜间树干液流速率的气象因子存在差异，5—6月土壤温度与水汽压亏缺是影响夜间树干液流速率的主导因子；7月气温是影响夜间树干液流速率的主要因子；8月水汽压亏缺与相对湿度是影响夜间树干液流速率的主导因子；9月风速与水汽压亏缺是影响夜间树干液流速率的主导因子。周翠鸣等^[23]从季节尺度上分析了广州地区木荷Schima superba夜间树干液流和环境因子的关系，认为夜间液流产生的主要原因是树形特征和生物量而非气象因子；李洁等^[24]对晋西北山地油松和落叶松Larix principis-rupprechtii研究发现：影响植物夜间液流速率的环境因子有气温、水汽压亏缺、土壤温度，其中土壤温度是主要驱动因子。可见，树种、地点都会影响树干液流速率对环境因子的响应。

4.3. 夜间液流的作用

随着研究的深入，普遍认为夜间液流主要用途为补充树体水分与植物蒸腾^[8-9]。区分两者的方法主要有2种：一种为通过仪器测量比较树干上下枝液流量差异来判断，另一种为根据液流速率与环境因子的关系来判断。本研究采用第2种方法来区分各月刺槐夜间树干液流的主要作用。刺槐生长季各月夜间树干液流速率与水汽压亏缺均有相关性，表明各月夜间树干液流均有蒸腾作用。除7月外，水汽压亏缺是各月主导环境因子之一，说明5、6、8、9月夜间树干液流用于蒸腾比例较大，7月夜间树干液流用于树体补水比例较大，因为水汽压亏缺通过改变叶片的气孔导度来影响植物蒸腾，水汽压亏缺能很好地解释夜间液流变化则说明夜间液流主要为蒸腾。由于夜间蒸腾与补水是同步发生的，本研究根据气象因子只能分辨出夜间液流的主要作用，因此在今后的研究中应该探索植物生理特性，以便更好地了解植物的夜间液流机制。

5. 结论

在生长季，刺槐昼间与夜间树干液流速率特征具有规律性。刺槐夜间液流量对整日液流量的贡献率远远小于昼间液流的贡献率，但夜间树干液流弥补了昼间蒸腾造成的水分亏缺，因此夜间树干液流的重要性不可忽视。生长季不同月份影响刺槐昼夜蒸腾速率的主导气象因子存在差异，且构建昼夜液流速率与气象因子关系模型时，不同月份模型参数与因子不同。综上，生长季各月在根据气象因子构建蒸腾模型时需考虑昼夜差异。

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月份	昼间平均液流速率/ (cm³·h⁻¹·cm⁻²)	贡献率/%	夜间平均液流速率/ (cm³·h⁻¹·cm⁻²)	贡献率/%
5	2.71±1.07	91.26	0.29±0.23	8.74
6	2.94±1.05	91.16	0.43±0.21	8.84
7	3.24±0.85	92.25	0.35±0.17	7.75
8	3.18±1.61	92.52	0.33±0.18	7.48
9	1.74±1.26	88.39	0.27±0.12	11.61

月份	相关分析		配对样本t检验
月份	R²	P	t	P
5	0.991	0.000	12.582	0.000
6	0.993	0.000	9.261	0.000
7	0.998	0.000	9.054	0.000
8	0.976	0.000	8.234	0.000
9	0.993	0.000	7.982	0.000

昼夜	月份	太阳辐射	气温	土壤温度	水汽压亏缺	相对湿度	风速
昼间	5	0.575**	0.483**	0.429**	0.290**	−0.278**	0.067
	6	0.670**	0.539**	0.331**	0.389**	−0.305**	−0.031
	7	0.762**	0.767**	0.497**	0.691**	−0.722**	0.192**
	8	0.689**	0.747**	0.546**	0.641**	−0.638**	0.295**
	9	0.674**	0.737**	0.608**	0.696**	−0.692**	0.331*

夜间	5		0.582**	0.585**	0.556**	−0.266**	0.351**
	6		0.213**	0.224**	0.043**	−0.049**	0.123**
	7		0.512**	0.475**	0.483**	−0.394**	0.338**
	8		0.747**	0.546**	0.641**	−0.638**	0.295**
	9		0.141**	0.160**	0.107**	−0.058**	0.215**
说明：*表示极显著相关(P＜0.01); 表示显著相关(P＜0.05)

因子	逐步回归R²变化量
	昼间					夜间
	5月	6月	7月	8月	9月	5月	6月	7月	8月	9月
太阳辐射	−	0.449	0.095	0.015	0.040	−	−	−	−	−
气温	0.334	0.026	0.589	0.559	0.543	0.127	−	0.362	−	0.008
水汽压亏缺	0.152	0.150	0.016	0.029	−	0.057	0.148	0.005	0.360	0.232
相对湿度	0.087	−	0.032	0.053	−	0.014	0.084	0.050	0.117	0.008
土壤温度	−	0.007	0.007	0.074	0.014	0.342	0.350	−	−	−
风速	−	−	0.002	0.029	0.018	0.042	−	0.158	0.030	0.246
说明：−表示气象因子未进入到逐步回归方程，以上数据均具有显著性

昼夜	月份	逐步回归模型		随机森林回归法拟合度/%
昼夜	月份	模型	拟合度/%	随机森林回归法拟合度/%
昼间	5	y=−1.29+0.579x₂−3.427x₄−0.063x₅	57.3	67.3
	6	y=−0.767+0.003x₁+0.301x₂−0.149x₃−0.869x₄	63.2	73.2
	7	y=1.509+0.002x₁+0.444x₂−0.194x₃−1.862x₄−0.053x₅+0.071x₆	74.1	86.3
	8	y=1.864+0.001x₁+0.506x₂−0.208x₃−2.468x₄−0.065x₅+0.144x₆	75.9	90.6
	9	y=1.104+0.001x₁+0.300x₂−0.204x₃+0.297x₆	61.5	81.1

夜间	5	y=2.852+0.002x₁+0.182x₂−0.279x₃+0.154x₆	48.2	59.4
	6	y=4.943+0.003x₁+0.346x₂−0.363x₃−1.252x₄−0.025x₅−0.110x₆	61.6	67.7
	7	y=3.966+0.003x₁+0.415x₂−0.209x₃−2.094x₄−0.069x₅	57.5	61.6
	8	y=4.869+0.002x₁+0.486x₂−0.311x₃−2.296x₄−0.074x₅+0.091x₆	50.7	63.9
	9	y=−5.886+0.502x₂−3.033x₄	49.4	54.6
说明：y表示液流速率，x₁表示太阳辐射，x₂表示气温，x₃表示土壤温度，x₄表示水汽压亏缺，x₅表示相对湿度，x₆表示风速