Impacts of drought and heatwave on the terrestrial ecosystem in China as revealed by satellite solar-induced chlorophyll fluorescence

Wang, Xiaorong; Qiu, Bo; Li, Wenkai; Zhang, Qian

doi:10.1016/j.scitotenv.2019.133627

Cited by 77 publications

(42 citation statements)

References 49 publications

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“…Evidence from observations suggests that SIF has a rapid response to the water and heat stresses due to its direct link to photosynthetic activity (Lee et al, ; Song et al, ; Wang et al, ). Satellite SIF products improve our ability to monitor and assess the influence of extreme climatic events on vegetation productivity and exhibit a timely and accurate response to environmental stress for various vegetation types, such as tropical rainforest (Lee et al, ; Qian et al, ), mixed forest (Yoshida et al, ), and cropland (Song et al, ; Sun et al, ).…”

Section: Introductionmentioning

confidence: 99%

Responses of Australian Dryland Vegetation to the 2019 Heat Wave at a Subdaily Scale

Qiu

Guo

et al. 2020

Geophysical Research Letters

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Satellite solar‐induced chlorophyll fluorescence (SIF) products from the Global Ozone Monitoring Experiment 2 (GOME‐2) and Orbiting Carbon Observatory 2 (OCO‐2) are used to investigate the responses of vegetation growth to the 2019 heat wave in Australia. Both satellite SIF data sets are more sensitive to water and heat stress than is the greenness‐based vegetation index (enhanced vegetation index). Moreover, the OCO‐2 SIF observations show a more significant reduction and earlier response to the heat stress than does GOME‐2 SIF, indicating that the two satellite SIF data sets differ in how they monitor the drought and heat wave event due to the different timing of observations. Eddy covariance measurements confirm the different responses of dryland vegetation to the 2019 heat wave at a subdaily time scale. The differences in the timing of the satellite SIF products can be used to assess different elements of the impact of heat and water stress on Australian dryland ecosystems.

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Section: Introductionmentioning

confidence: 99%

Responses of Australian Dryland Vegetation to the 2019 Heat Wave at a Subdaily Scale

Qiu

Guo

et al. 2020

Geophysical Research Letters

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“…The monthly gridded SIF dataset we used in this study was the GOME-2 product composited by the estimated daily-averaged SIF values. This dataset was also normalized by PAR, which could be used to indicate the effective fluorescence yield and eliminate the effect of variation in PAR [28,41]. Some previous studies also used the absorbed photosynthetically active radiation (APAR) to further eliminate the effect of APAR on SIF [9,22].…”

Section: Discussionmentioning

confidence: 99%

“…Satellite-based SIF data is highly correlated with aboveground crop biomass, which is directly related to crop yield [26]. It has great potential to predict crop yield [25][26][27][28]. Additionally, heat waves and drought events are likely to become more frequent with global warming, resulting in unpredictable yield loss [29].…”

Section: Introductionmentioning

confidence: 99%

Satellite Solar-Induced Chlorophyll Fluorescence Reveals Heat Stress Impacts on Wheat Yield in India

Song

Wang

2020

Remote Sensing

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With continued global warming, the frequency and severity of heat wave events increased over the past decades, threatening both regional and global food security in the future. There are growing interests to study the impacts of drought on crop. However, studies on the impacts of heat stress on crop photosynthesis and yield are still lacking. To fill this knowledge gap, we used both statistical models and satellite solar-induced chlorophyll fluorescence (SIF) data to assess the impacts of heat stress on wheat yield in a major wheat growing region, the Indo-Gangetic Plains (IGP), India. The statistical model showed that the relationships between different accumulated degree days (ADD) and reported wheat yield were significantly negative. The results confirmed that heat stress affected wheat yield across this region. Building on such information, satellite SIF observations were used to further explore the physiological basis of heat stress impacts on wheat yield. Our results showed that SIF had strong negative correlations with ADDs and was capable of monitoring heat stress. The SIF results also indicated that heat stress caused yield loss by directly impacting the photosynthetic capacity in wheat. Overall, our findings demonstrated that SIF as an effective proxy for photosynthetic activity would improve our understanding of the impacts of heat stress on wheat yield.

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“…For instance, for groundwater, direct observations of the groundwater table might not be directly available at the particular site of interest. Dynamic phenology module requires specification of a temperature, light and water dependence function, which might not be perfect, causing uncertainties in the water cycle (Zhang et al, 2019). Finally one should not overlook the essential role of humans on land management…”

Section: Groundwatermentioning

confidence: 99%

“…Since SIF is a flux more directly connected to vegetation productivity, it provides a unique estimate of vegetation water stress(Sun et al 2017;Pagán et al 2019;Hamed Alemohammad et al 2017). As such it has been used to assess the role of droughts or heat waves on ecosystem productivity(Helm et al 2020;Wang et al 2019;Sun et al 2015;Zhang et al 2018a), showing a potential even in cases where soil moisture would not necessarily be appropriate. VaglioLaurin et al 2020;Zhou et al 2018;Li et al 2013Li et al , 2015Liu et al 2011;Rodríguez-Fernández et al 2018;Piles et al 2017; Wild et al 2020) based on passive microwave remote sensing.…”

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confidence: 99%

Advances in Land Surface Models and Indicators for Drought Monitoring and Prediction

Peters‐Lidard

Mocko

et al. 2021

Bulletin of the American Meteorological Society

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Millions of people across the globe are affected by droughts every year, and recent droughts have highlighted the considerable agricultural impacts and economic costs of these events. Monitoring the state of droughts depends on integrating multiple indicators that each capture particular aspects of hydrologic impact and various types and phases of drought. As the capabilities of land-surface models and remote sensing have improved, important physical processes such as dynamic, interactive vegetation phenology, groundwater, and snow pack evolution now support a range of drought indicators that better reflect coupled water, energy and carbon cycle processes. In this work, we discuss these advances, including newer classes of indicators that can be applied to improve the characterization of drought onset, severity and duration. We utilize a new model-based drought reconstruction to illustrate the role of dynamic phenology and groundwater in drought assessment. Further, through case studies on flash droughts, snow droughts, and drought recovery, we illustrate the potential advantages of advanced model physics and observational capabilities, especially from remote sensing, in characterizing droughts.

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Impacts of drought and heatwave on the terrestrial ecosystem in China as revealed by satellite solar-induced chlorophyll fluorescence

Cited by 77 publications

References 49 publications

Responses of Australian Dryland Vegetation to the 2019 Heat Wave at a Subdaily Scale

Responses of Australian Dryland Vegetation to the 2019 Heat Wave at a Subdaily Scale

Satellite Solar-Induced Chlorophyll Fluorescence Reveals Heat Stress Impacts on Wheat Yield in India

Advances in Land Surface Models and Indicators for Drought Monitoring and Prediction

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