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Updated: Nov 4, 2025

The Calibration and Use of Capacitance Sensors to Monitor Stem Water Content in Trees
Published on: December 27, 2017
[Effects of environment and canopy structure on stem sap flow in a Larix principis-rupprechtii plantation.]
Hao-Ping Qin1,2, Ze-Bin Liu1, Jian-Bin Guo2
1Research Institute of Forest Ecology, Environment and Protection, Chinese Academy of Fores-try/Key Laboratory of Forestry Ecology and Environment of National Forestry and Grassland Administration, Beijing 100091, China.
Abstract:
Accurately quantifying the impacts of environmental factors and canopy structure on stem sap flow is of great significance for deeply understanding water use strategies of trees in changing environment. The stem sap flow of Larix principis-rupprechtii plantation was observed using thermal diffusion probes from June to September of 2019 in the Xiangshuihe small watershed of Liupan Mountains, with the meteorological conditions, root-zone soil water content and canopy structure being simultaneously recorded. We first analyzed the relationships of sap flow rate (Jc) to potential evapotranspiration (PET), relative extract water (REW) and canopy leaf area index (LAI), and then quantified their relative contribution to Jc. The results showed that the response of Jc to PET, LAI, and REW conformed to binomial, linearly increase and saturated exponential function, respectively. The Jc model coupling multiple factors was established as a continuous multiplication of the response functions of Jc to PET, REW and LAI, which had good simulation precision. PET was the main factor leading to the difference of Jc in different weather conditions. The average contribution rate of PET had obvious difference in sunny (with a contribution rate of 40.3%), cloudy (4.3%), and rainy days (-26.3%). PET and LAI were the leading factors affecting the Jc variation among months. The ranges of the contribution rates of PET and LAI were from -23.1% to 16.8% and from -12.3% to 11.0%, respectively. The Jc model coupling the multi-factor effect developed in this study could be used to predict Jc, and quantify the impacts of each leading factor, which had the potential to be an effective tool to analyze the water use of trees in the changing environment.
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