Impacts of Triple La Niña Events on Forest Gross Primary Productivity in China from 2020 to 2022
Keywords: La Niña, Extreme Weather Events, Gross Primary Productivity, Remote Sensing Monitoring, Chinese Forests
Abstract. Based on GOSIF GPP data and climate data, this study systematically explored the impact mechanism of triple La Niña event on gross primary productivity (GPP) of forest ecosystem in China from 2020 to 2022 and its physiological and ecological driving process. The results show that GPP in China forest presents a significant dynamic response of "initial inhibition-gradual recovery" to La Niña event. The annual average GPP decreased from 1799.27 Tg C year−1 in the base period (2017–2018) to 1783.89 Tg C year−1, of which 2020 reached the lowest value of 1763.68 Tg C year−1 in the study period, but showed strong recovery ability in the following two years, rising to 1804.54 Tg C year−1. Spatially, the subtropical monsoon region realized "V" recovery through vegetation adaptation, while the temperate monsoon region was inhibited by soil moisture at root zone and phenological delay. The temperate region showed "early stage determines late stage" characteristics, and the subtropical region formed "spring and autumn compensation" pattern. These differences are mainly due to the latitudinal difference regulation of La Niña event on East Asian monsoon system. The temperate region is adjusted by mid-high latitude circulation while the subtropical region directly responds to the continuous drought caused by tropical sea surface temperature (SST) anomaly. This study clarified the response of China forest to triple La Niña event through multi-scale analysis, which provided important scientific basis for improving ecosystem model parameterization and predicting carbon sink function evolution.
