Junbin Zhao
Research Scientist
Biography
My work ranges from plant level ecophysiological processes to ecosystem level carbon, water and energy balance. I am particularly interested in the impact of climate change (including relevant extreme events, e.g., drought, flooding, snow storm, etc.) on these processes and their climate feedbacks. I use many state-of-the-art techniques in my research work, including eddy covariance for ecosystem level gas exchange observations, automatic static/dynamic chambers for plot-level or whole-plant-level gas exchange measurements and machine learning models for data analysis and prediction.
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Professional appointments
2019 – present Research Scientist Norwegian Institute of Bioeconomy Research (NIBIO)
2016 – 2019 Postdoctoral associate Florida International University (FIU)
2013 – 2015 Postdoctoral researcher Swedish University of Agricultural Sciences (SLU)
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Education
2013 Ph. D University of Chinese Academy of Sciences, Beijing, China
2011 – 2012 Visiting Ph.D student Max Planck Institute for Biogeochemistry, Jena, Germany
2007 B. S. Yunnan University, Kunming, China
Authors
Junbin Zhao Simon Weldon Alexandra Barthelmes Erin Swails Kristell Hergoualc’h Ülo Mander Chunjing Qiu John Connolly Whendee L. Silver David I. CampbellAbstract
No abstract has been registered
Abstract
In terrestrial ecosystems, forest stands are the primary drivers of atmospheric moisture and local climate regulation, making the quantification of transpiration (T) at the stand level both highly relevant and scientifically important. Stand-level T quantification complements evapotranspiration monitoring by eddy-covariance systems, providing valuable insight into the water use efficiency of forested ecosystems in addition to serving as important inputs for the calibration and validation of global transpiration monitoring products based on satellite observations. Stand level T estimates are typically obtained by scaling up individual tree estimates of water movement within the xylem – or sap flow. This movement affects the radius of a tree stem, whose fluctuations over the diel cycle provide pertinent information about tree water relations which can be readily detected by point (or precision) dendrometers. While sap flow measurements have greatly advanced our understanding of water consumption (T) at the level of individual trees, deploying conventional sap flow monitoring equipment to quantify T at the level of entire forested stands (or ecosystems) can quickly become costly since sap flow measurements from many trees are required to reduce the uncertainty of the upscaling. Using a boreal old-growth Norway spruce stand at an ICOS site in Southern Norway as a case study, we assess the potential of augmenting conventional sap flow monitoring systems with sap flow modeling informed by point dendrometer measurements to reduce the uncertainty of stand level T estimation at the daily resolution. We test the hypothesis that the uncertainty reduction afforded by a boosted tree sample size more than offsets the propagation of uncertainty originating from the point dendrometer-based sap flow estimates.
Abstract
Climatic drought and changes in precipitation patterns are key features of the ongoing and predicted climatic changes in northern latitudes such as the boreal forest of Norway. Recent droughts highlight on the possible difficult future of spruce forests in southern Norway. To better understand and monitor these forests under a more extreme climate, it is crucial to gain a better understanding of the water relations of spruce trees across forest stands. Sap flow sensors are typically used for directly measuring the water demands for transpiration in individual trees. There are however limitations to their use in examining the hydraulic and physiological responses to extreme water supply variability: i) manufactured high-resolution sensors such as those following the Heat Ratio Method (HRM) or Heat Field Deformation (HFD) are expensive, limiting their deployment to a few trees in a stand, and ii) the sap flow sensors only measure the movement of water within the active sapwood, not accessing other physiological mechanisms and responses (radial growth, water storage) associated with stress response. Point dendrometers have become increasingly used, monitoring sub-daily stem size fluctuations resulting from both seasonal patterns of radial growth increment and the dynamics of plant tissue water balance. Manufactured point dendrometers are much cheaper to buy and easier to install and maintain than manufactured sap flow sensors. They can therefore be much more extensively deployed across forest stands. We aimed to analyse the relationship between sub-daily stem diameter changes and sap flow using point dendrometers and HRM sap flow sensors installed in a Norway spruce forest located 50 km north of Oslo, Norway. We linked these relationships with individual tree physical attributes, meteorology and soil climate over two growing seasons in 2022 and 2023. Our goal was to assess whether a predictive model of sap flow could be built from measured diameter changes, tree properties and climate, to ultimately reduce the uncertainty of stand level transpiration estimation at the daily resolution across entire forest stands.
