Response of ecosystem gross primary productivity to drought in northern China based on multi-source remote sensing data

Abstract

Drought has become one of the main reasons for the loss of terrestrial ecosystems gross primary productivity (GPP) because of its more frequent occurrence under the background of global warming. Aiming to explore the response mechanism of vegetation under drought conditions, the sun-induced chlorophyll fluorescence (SIF), normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) were used to monitor vegetation drought and quantify the drought-induced GPP variabilities. MODIS GPP were used for analysis, which was verified by close-path eddy covariance flux (R2 = 0.69, p < 0.01). According to the standard precipitation evapotranspiration index (SPEI) and soil moisture (SM), the drought periods of 2010 and 2014 in the eastern piedmont of Taihang Mountains were selected to analyze drought impacts on GPP. We found that SIF had the ability to reflect the effects of drought prolonged action on vegetation and respond to GPP persistent changes during drought. SIF successfully described GPP loss during droughts in 2010 (20.91 gCm−2month−1) and 2014 (9.52 gCm−2month−1). SIF was more significantly linearly correlated with GPP (R2 = 0.89) than NDVI (R2 = 0.69) and EVI (R2 = 0.84), suggesting that SIF was more sensitive to physiological changes in vegetation. SIF correlated significantly higher to SM than SPEI, and there was a two-month lag to SM, which may be related to the adaptation mechanism of vegetation physiological recovery under drought conditions. Results showed that SIF is more accurate and sensitive than NDVI and EVI in regional vegetation drought monitoring and drought-induced GPP variations. SIF is an effective physiological index for timely detection and regional drought, and an effective tool for ecosystem management and disaster warning.