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
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.
Authors
Palingamoorthy Gnanamoorthy Junbin Zhao Abhishek Chakraborty Pramit Kumar Deb Burman Yaoliang Chen Linjie Jiao Jing Zhang Yaqi Liu Sigamani Sivaraj Yiping Zhang Qinghai SongAbstract
Study region: The Ailaoshan National Nature Reserve forest is a mountainous water catchment area for the Lancang River basin and a subtropical ecological conservation area in southwest China. Study focus: The study aimed to understand how water fluxes in a subtropical forest responds to extreme weather disturbances and their recoveries in the post-damage years. We used eddy covariance data (2010–2019) to investigate the evapotranspiration (ET), transpiration (T), evaporation (E), and canopy conductance (Gc) before and after an extreme snow event in 2015. New Hydrological Insights: In the snow damage year, the leaf area index (LAI) decreased by 49 % compared to the pre-damage levels. The severe vegetation damage caused a significant decrease in ET, T, E, and Gc by 35 %, 36 %, 23 %, and 33 %, respectively, compared to the pre-damage levels. T returned to its pre-damage level in 2016, one year after the snow damage. In contrast, LAI, ET, E and Gc recovered to their pre-damage levels in 2018, four years after the initial damage. Reduced ET caused a strong positive RFET, which diminished forest evaporative cooling and resilience. Our results suggest that the delayed E recovery enables water reserves in the ecosystems to be used through T to support rapid understory vegetation growth. This mechanism plays critical in bolstering ecosystem resilience as it facilitates swift recovery following disturbances in subtropical forests.
Authors
Junbin Zhao Mikhail Mastepanov Carla Stadler Cornelya Klutsch Erling Fjelldal David Kniha Runar KjærAbstract
No abstract has been registered
