Abstract

With the acceleration of global warming, droughts are expected to both intensify and become more frequent. More so than forests, the productivity of grasslands is largely controlled by soil moisture and is highly susceptible to drought. Drought can impact grasslands though the effects may lag and accumulate over time. Because prior research has mainly focused on the annual or growing season scale, it remains unclear whether there are seasonal differences in the cumulative and lagged effects (CALEs) of drought. This study uses Normalized Difference Vegetation Index (NDVI) and Standardized Precipitation Evapotranspiration Index (SPEI) data to explore the seasonal characteristics of the CALEs of drought on grassland growth in East Asia from 2001 to 2020. The main results include the following: (1) More than 40% of grasslands are significantly affected by the CALEs of drought for all three seasons (spring, summer, and autumn). (2) Grasslands are more sensitive to the CALEs of drought in summer. The spatial variability of the cumulative time scale is the greatest in spring, whereas the spatial variability of the lagged time scale is the greatest in summer. The lag time scale gradually shortens as moisture decreases in summer and autumn but shows an inverted U-shape in spring. As drought conditions intensify, the cumulative time scale gradually increases in spring and autumn, while gradually decreasing in summer. (3) The dominant drought effects vary among different seasons: the lagged effect (LE) predominates in spring and autumn, whereas in summer it is the cumulative effect (CE) that dominates. The LE exceeds the CE in 54.89% of the study area during the growing season. We emphasize that annual- or growing season-scale studies of drought CE and LE may obscure seasonal response characteristics. Given the seasonal nature of droughts and the seasonally varying sensitivities of grassland growth to these droughts, the impacts on vegetation fluctuate significantly across different seasons. The results help us more accurately predict grassland ecosystem changes under the background of global warming and the increasing probability of severe drought, providing important reference values for future grassland ecological protection and planning.

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