Kun Huang
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Kun Huang has a total of 22 co-authors. Here are the top co-authors by number of shared publications:
- Jianyang Xia
Research Center for Global Change and Ecological Forecasting, School of Ecological and Environmental Science, East China Normal University, Shanghai, China
2 shared publications - Chenyu Bian
Zhejiang Tiantong Forest Ecosystem National Observation and Research Station, Research Center for Global Change and Ecological Forecasting, School of Ecological and Environmental Sciences, Institute of Eco-Chongming, East China Normal University, Shanghai, China
1 shared publication - Danica Lombardozzi
Colorado State University
1 shared publication - Daniel Sebastian Goll
Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91191 Gif-sur-Yvette, France
1 shared publication - Erqian Cui
Research Center for Global Change and Ecological Forecasting, Institute of Eco‐Chongming, School of Ecological and Environmental Sciences East China Normal University Shanghai China
1 shared publication - Haoyu Peng
Hubei Key Laboratory of Regional Ecology and Environmental Change, School of Geography and Information Engineering, China University of Geosciences, Wuhan, Hubei, China
1 shared publication
Latest Publications
- 1 January 2025
- Published by American Association for the Advancement of Science (AAAS) in Journal of Remote Sensing
- Vol. 5
Response of Vegetation Photosynthesis to the 2022 Drought in Yangtze River Basin by Diurnal Orbiting Carbon Observatory-2/3 Satellite Observations
Global warming has triggered a surge in severe drought worldwide, disrupting vegetation photosynthesis and profoundly altering the global carbon cycle. However, the immediate and time-lagged responses of vegetation photosynthesis to warming drought remain unclear. Most current research on regional-scale solar-induced chlorophyll fluorescence (SIF) drought stress relies on daily or even monthly datasets, limiting insights into the diurnal dynamics of photosynthesis under drought. To address these gaps, we developed a continuous hourly SIF dataset (HC-SIF OCO ) based on observations from Orbiting Carbon Observatory-2 (OCO-2) and OCO-3. HC-SIF OCO exhibited accuracy comparable to that of tower-based observations in terms of diurnal photosynthesis [SIF: R 2 ≥ 0.89, GPP (gross primary productivity): R 2 ≥ 0.94]. Then, we used this dataset to investigate the drought in the Yangtze River Basin in 2022. According to our analysis, the initial signs of drought-induced stress are reflected in a decrease in vegetation fluorescence efficiency, followed by anomalies in SIF and, finally, abnormalities in canopy structure. Drought has led to an approximately 3% increase in midday depression compared to previous years while also causing an advancement in the seasonal peak. Furthermore, immediate decreases in atmospheric moisture were responsible for more than 70% of the decline in vegetation photosynthesis, with soil dryness playing a 2-month-later role. Although temperature generally benefited photosynthesis, this effect diminished dramatically at midday. In summary, we present a new method for obtaining high-resolution temporal SIF data, providing new insights into the vegetation’s diurnal response to drought.
- 1 January 2025
- Published by American Association for the Advancement of Science (AAAS) in Journal of Remote Sensing
- Vol. 5
Response of Vegetation Photosynthesis to the 2022 Drought in Yangtze River Basin by Diurnal Orbiting Carbon Observatory-2/3 Satellite Observations
Global warming has triggered a surge in severe drought worldwide, disrupting vegetation photosynthesis and profoundly altering the global carbon cycle. However, the immediate and time-lagged responses of vegetation photosynthesis to warming drought remain unclear. Most current research on regional-scale solar-induced chlorophyll fluorescence (SIF) drought stress relies on daily or even monthly datasets, limiting insights into the diurnal dynamics of photosynthesis under drought. To address these gaps, we developed a continuous hourly SIF dataset (HC-SIF OCO ) based on observations from Orbiting Carbon Observatory-2 (OCO-2) and OCO-3. HC-SIF OCO exhibited accuracy comparable to that of tower-based observations in terms of diurnal photosynthesis [SIF: R 2 ≥ 0.89, GPP (gross primary productivity): R 2 ≥ 0.94]. Then, we used this dataset to investigate the drought in the Yangtze River Basin in 2022. According to our analysis, the initial signs of drought-induced stress are reflected in a decrease in vegetation fluorescence efficiency, followed by anomalies in SIF and, finally, abnormalities in canopy structure. Drought has led to an approximately 3% increase in midday depression compared to previous years while also causing an advancement in the seasonal peak. Furthermore, immediate decreases in atmospheric moisture were responsible for more than 70% of the decline in vegetation photosynthesis, with soil dryness playing a 2-month-later role. Although temperature generally benefited photosynthesis, this effect diminished dramatically at midday. In summary, we present a new method for obtaining high-resolution temporal SIF data, providing new insights into the vegetation’s diurnal response to drought.
- Open Access
- 18 May 2023
- Published by American Geophysical Union (AGU) in Journal of Advances in Modeling Earth Systems
- Vol. 15 (5)
Uncertainty and Emergent Constraints on Enhanced Ecosystem Carbon Stock by Land Greening
Significant land greening since the 1980s has been detected through satellite observation, forest inventory, and Earth system modeling. However, whether and to what extent global land greening enhances ecosystem carbon stock remains uncertain. Here, using 40 global models, we first detected a positive correlation between the terrestrial ecosystem carbon stock and leaf area index (LAI) over time. Then, we diagnose the source of uncertainty of simulated the sensitivities of ecosystem carbon stock to LAI based on a traceability analysis. We found that the sensitivity of gross primary productivity (GPP) to LAI is the largest contributor to the model uncertainty in more than 60% of the vegetated grids. Using the ensemble of four long‐term global data sets of GPP and three satellite LAI products from 1982 to 2014, we provided an emergent constraint on the ecosystem carbon stock increase as 0.75 ± 0.46 kg C m−2 per unit LAI over global land areas. Furthermore, the biome‐based results reveal that the tropical forest regions have the highest inter‐model variation and model bias. Overall, this study identifies the uncertainty source and provides constrained estimates of the greening effect on ecosystem carbon stock at the global scale.
- 18 May 2023
- Published by American Geophysical Union (AGU) in Journal of Advances in Modeling Earth Systems
- Vol. 15 (5)
Open AccessUncertainty and Emergent Constraints on Enhanced Ecosystem Carbon Stock by Land Greening
Significant land greening since the 1980s has been detected through satellite observation, forest inventory, and Earth system modeling. However, whether and to what extent global land greening enhances ecosystem carbon stock remains uncertain. Here, using 40 global models, we first detected a positive correlation between the terrestrial ecosystem carbon stock and leaf area index (LAI) over time. Then, we diagnose the source of uncertainty of simulated the sensitivities of ecosystem carbon stock to LAI based on a traceability analysis. We found that the sensitivity of gross primary productivity (GPP) to LAI is the largest contributor to the model uncertainty in more than 60% of the vegetated grids. Using the ensemble of four long‐term global data sets of GPP and three satellite LAI products from 1982 to 2014, we provided an emergent constraint on the ecosystem carbon stock increase as 0.75 ± 0.46 kg C m−2 per unit LAI over global land areas. Furthermore, the biome‐based results reveal that the tropical forest regions have the highest inter‐model variation and model bias. Overall, this study identifies the uncertainty source and provides constrained estimates of the greening effect on ecosystem carbon stock at the global scale.
- 5 July 2019
- Published by Wiley in Global Change Biology
- Vol. 25 (10) , 3494-3503
High ecosystem stability of evergreen broadleaf forests under severe droughts
Global increase in drought occurrences threatens the stability of terrestrial ecosystem functioning. Evergreen broadleaf forests (EBFs) keep leaves throughout the year, and therefore could experience higher drought risks than other biomes. However, the recent temporal variability of global vegetation productivity or land carbon sink is mainly driven by non‐evergreen ecosystems, such as semiarid grasslands, croplands, and boreal forests. Thus, we hypothesize that EBFs have higher stability than other biomes under the increasingly extreme droughts. Here we use long‐term Standardized Precipitation and Evaporation Index (SPEI) data and satellite‐derived Enhanced Vegetation Index (EVI) products to quantify the temporal stability (ratio of mean annual EVI to its SD), resistance (ability to maintain its original levels during droughts), and resilience (rate of EVI recovering to pre‐drought levels) at biome and global scales. We identified significantly increasing trends of annual drought severity (SPEI range: −0.08 to −1.80), area (areal fraction range: 2%–19%), and duration (month range: 7.9–9.1) in the EBF biome over 2000–2014. However, EBFs showed the highest resistance of EVI to droughts, but no significant differences in resilience of EVI to droughts were found among biomes (forests, grasslands, savannas, and shrublands). Global resistance and resilience of EVI to droughts were largely affected by temperature and solar radiation. These findings suggest that EBFs have higher stability than other biomes despite the greater drought exposure. Thus, the conservation of EBFs is critical for stabilizing global vegetation productivity and land carbon sink under more‐intense climate extremes in the future.
- 5 July 2019
- Published by Wiley in Global Change Biology
- Vol. 25 (10) , 3494-3503
High ecosystem stability of evergreen broadleaf forests under severe droughts
Global increase in drought occurrences threatens the stability of terrestrial ecosystem functioning. Evergreen broadleaf forests (EBFs) keep leaves throughout the year, and therefore could experience higher drought risks than other biomes. However, the recent temporal variability of global vegetation productivity or land carbon sink is mainly driven by non‐evergreen ecosystems, such as semiarid grasslands, croplands, and boreal forests. Thus, we hypothesize that EBFs have higher stability than other biomes under the increasingly extreme droughts. Here we use long‐term Standardized Precipitation and Evaporation Index (SPEI) data and satellite‐derived Enhanced Vegetation Index (EVI) products to quantify the temporal stability (ratio of mean annual EVI to its SD), resistance (ability to maintain its original levels during droughts), and resilience (rate of EVI recovering to pre‐drought levels) at biome and global scales. We identified significantly increasing trends of annual drought severity (SPEI range: −0.08 to −1.80), area (areal fraction range: 2%–19%), and duration (month range: 7.9–9.1) in the EBF biome over 2000–2014. However, EBFs showed the highest resistance of EVI to droughts, but no significant differences in resilience of EVI to droughts were found among biomes (forests, grasslands, savannas, and shrublands). Global resistance and resilience of EVI to droughts were largely affected by temperature and solar radiation. These findings suggest that EBFs have higher stability than other biomes despite the greater drought exposure. Thus, the conservation of EBFs is critical for stabilizing global vegetation productivity and land carbon sink under more‐intense climate extremes in the future.