Abstract
The impacts of drought on the terrestrial gross primary production (GPP) are the most intense and widespread in all extreme climate events. Solar-induced chlorophyll fluorescence (SIF) is considered as a direct representative of actual vegetation photosynthesis and has better performance in monitoring vegetation conditions than greenness-based vegetation indices (VI <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</sub> ) during drought events. Based on the spatially downscaled SIF (SIF <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ds</sub> ), VI <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</sub> and GPP products, we explored the potential of SIF <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ds</sub> to monitor drought effects on GPP in winter wheat. First, the spatiotemporal dynamics of hydrometeorological factors and vegetation variables in winter wheat during drought events were observed. Then, the SIF <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ds</sub> —GPP relationships in different phenological stages were examined in the rainfed area. Finally, the drought-induced GPP losses in different phenological stages were evaluated by scaling SIF <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ds</sub> to GPP based on the linear SIF <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ds</sub> –GPP relationship in the rainfed area. Results showed that SIF <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ds</sub> could capture the spatiotemporal dynamics of drought-induced GPP variations in winter wheat during drought events, and it could quantify accurately the drought-induced GPP losses, with higher sensitivities to GPP changes during the vigorous growing periods. Our study reveals the applicability of SIF <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ds</sub> to achieve regional agricultural drought detection and drought-induced GPP loss assessment, which can provide some help for crop adaptation management.
Highlights
Terrestrial vegetation fix carbon dioxide (CO2) as organic compounds through photosynthesis, a carbon (C) flux known as gross primary production (GPP) at the ecosystem level [1]
Previous studies have shown that satellitebased Solar-induced chlorophyll fluorescence (SIF) is correlated significantly with GPP observations derived from ground-based eddy covariance [8,9,10], which demonstrates the potential of SIF to estimate GPP due to the linear relationship between them based on the similar light-use efficiency (LUE) theory [11,12]
In order to make vegetation indices (VIs) that carried no information on radiation and SIFds comparable, we further used VIs to calculate absorbed photosynthetically active radiation (APAR) [63], which was accomplished by assuming a linear relationship between VIs and FPAR [64], and we found that SIFds exhibited more consistent declines with drought-induced GPP losses than did APAR estimations, where APAR had obvious lagged responses compared with SIFds (Fig. S4)
Summary
Terrestrial vegetation fix carbon dioxide (CO2) as organic compounds through photosynthesis, a carbon (C) flux known as gross primary production (GPP) at the ecosystem level [1]. SIF can respond faster to soil moisture (SM) deficits than the greennessbased vegetation indices (VIs), such as the normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI). It reasonably captures the spatial-temporal dynamics of drought development, and exhibits a more significant reduction and earlier response during the early stages of drought [13,14], during the peak growing months of vegetation [15,16]. SIF has been used to characterize the spatial-temporal dynamics of GPP anomalies, and estimate the drought-induced GPP losses [17]
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