Differentiating refilling and transpiration from night-time sap flux based on time series modelling

被引:6
|
作者
Zhao Xiaowei [1 ]
Ping Zhao [1 ]
Zhu, Liwei [1 ]
机构
[1] Chinese Acad Sci, Key Lab Vegetat Restorat & Management Degraded Ec, Guangdong Prov Key Lab Appl Bot, South China Bot Garden, Guangzhou 510650, Guangdong, Peoples R China
来源
TREES-STRUCTURE AND FUNCTION | 2022年 / 36卷 / 05期
基金
中国国家自然科学基金;
关键词
ARMAX model; Night-time sap flux; Water refilling; Night-time transpiration; White noise; NOCTURNAL WATER-LOSS; POPULUS-EUPHRATICA; VAPOR-PRESSURE; SOIL-WATER; FLOW; LEAF; CONDUCTANCE; TREES; SIMULATION; RESPONSES;
D O I
10.1007/s00468-022-02316-x
中图分类号
S7 [林业];
学科分类号
0829 ; 0907 ;
摘要
Key message Although night-time transpiration occurs most of the time, stem refilling contributed more to the amount of night-time sap flux, which indicates that there was no water loss in Schima superba at night-time. It has been historically shown to be difficult to identify the night-time transpiration (E-n) and stem refilling (R-n) components from night-time sap flux (NFt). We applied an autoregressive moving-average (ARMA) model with exogenous variables (ARMAX) fitting E-n to distinguish NFt of Schima superba for avoiding autocorrelation. In total, 23 optimum models were chosen at the node moments of the night in the dry and wet seasons. Models performed seasonal variations in involving environmental factors and build time. Vapor pressure deficit (VPDt) alone or with wind speed (WSt) drove positively NFt in most of the time in both seasons. SMt dominated NFt only at the beginning of the night-time in the dry season. E-n occurred 1 h later and was lower in the wet than in the dry season (ca. 1.09 kg h(-1) vs 1.82 kg h(-1)), and R-n is the opposite (ca. 2.36 kg h(-1) vs 1.9 kg h(-1)). This may cause by greater water storage deficit in the trunk due to stronger day-time transpiration. We found that NFt was minor compared to day-time sap flux (DFt), and the mean ratio of night-time sap flow (Q(n)) to daily sap flow (Q(w)) was only 0.02. Our results showed that there were no seasonal differences on the contribution of NFt to the 24-h F-t, and no water loss at the daily scale in Schima superba in both seasons (R-n > E-n). This study first quantifies E-n and R-n, and reveals seasonal variations in tree night-time water use and provides a basis for better understanding of E-n function.
引用
收藏
页码:1621 / 1632
页数:12
相关论文
共 50 条
  • [31] An estimation model of population in China using time series DMSP night-time satellite imagery from 2002-2010
    Zhang Xiaoyong
    Zhang Zhijie
    Chang Yuguang
    Chen Zhengchao
    [J]. INTERNATIONAL CONFERENCE ON INTELLIGENT EARTH OBSERVING AND APPLICATIONS 2015, 2015, 9808
  • [32] EXPERIMENTAL EVALUATION OF LATENT HEAT-FLUX DURING NIGHT-TIME RADIATIVE HOARFROST
    SEVERINI, M
    OLIVIERI, B
    [J]. BOUNDARY-LAYER METEOROLOGY, 1980, 19 (01) : 119 - 124
  • [33] Does soil nutrient availability influence night-time water flux of aspen saplings?
    Kupper, Priit
    Rohula, Gristin
    Saksing, Liina
    Sellin, Arne
    Lohmus, Krista
    Ostonen, Ivika
    Helmisaari, Helja-Sisko
    Sober, Anu
    [J]. ENVIRONMENTAL AND EXPERIMENTAL BOTANY, 2012, 82 : 37 - 42
  • [34] Seasonal variation of night-time sap flow of a young olive orchard: the unconsidered process for evapotranspiration estimations
    Lopez-Olivari, R.
    Fuentes, S.
    Ortega-Farias, S.
    [J]. XXIX INTERNATIONAL HORTICULTURAL CONGRESS ON HORTICULTURE: SUSTAINING LIVES, LIVELIHOODS AND LANDSCAPES (IHC2014): INTERNATIONAL SYMPOSIA ON WATER, ECO-EFFICIENCY AND TRANSFORMATION OF ORGANIC WASTE IN HORTICULTURAL PRODUCTION, 2016, 1112 : 81 - 86
  • [35] Day and Night Place Recognition Based on Low-quality Night-time Images
    Liu, Linrunjia
    Cappelle, Cindy
    Ruichek, Yassine
    [J]. 2020 IEEE 23RD INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), 2020,
  • [37] Monitoring urban expansion using time series of night-time light data: a case study in Wuhan, China
    Xin, Xin
    Liu, Bin
    Di, Kaichang
    Zhu, Zhe
    Zhao, Zhongyuan
    Liu, Jia
    Yue, Zongyu
    Zhang, Guo
    [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING, 2017, 38 (21) : 6110 - 6128
  • [38] Identifying and Classifying Shrinking Cities Using Long-Term Continuous Night-Time Light Time Series
    Dong, Baiyu
    Ye, Yang
    You, Shixue
    Zheng, Qiming
    Huang, Lingyan
    Zhu, Congmou
    Tong, Cheng
    Li, Sinan
    Li, Yongjun
    Wang, Ke
    [J]. REMOTE SENSING, 2021, 13 (16)
  • [39] A novel cross-sensor calibration method to generate a consistent night-time lights time series dataset
    Tu, Ying
    Zhou, Hanlin
    Lang, Wei
    Chen, Tingting
    Li, Xun
    Xu, Bing
    [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING, 2020, 41 (14) : 5482 - 5502
  • [40] Image-based fusion for video enhancement of night-time surveillance
    Rao, Yunbo
    Lin, Weiyao
    Chen, Leiting
    [J]. OPTICAL ENGINEERING, 2010, 49 (12)