Spatio-temporal dynamics of gross primary productivity in China from 1982 to 2017 based on different datasets

doi:10.13287/j.1001-9332.202210.027

Abstract

Abstract: Understanding the spatio-temporal variations of gross primary productivity (GPP) of terrestrial ecosystem and its relationship with climatic factors can provide important basis for vegetation restoration and protection. Based on meteorological data and three public GPP datasets (EC-LUE GPP, GLASS GPP, and NIRv GPP), we syste-matically analyzed the spatial-temporal variations of GPP and its response to climate change in China during 1982-2017. All the results based on the three GPP datasets showed that the annual and seasonal GPP in China increased annually from 1982 to 2017, with that in 1998 and 2002 significantly being higher than the average level during the study period, and that in 1989 and 1992 significantly being lower than the average annual GPP. From 1982 to 2017, GPP showed a significant upward trend in most regions of China, with the regions with significant increases accounting for 75.7%, 73.0%, and 69.6% of the whole study area, respectively. There was a significant positive correlation between annual GPP and precipitation and temperature, but spatial heterogeneity was strong. Among them, the regions with positive correlation between GPP and temperature were mainly distributed in Northwest and Central China, while the regions with positive correlation between GPP and precipitation were mainly distributed in North China. There was obvious spatial-temporal heterogeneity in regions that GPP being affected by temperature and precipitation in different seasons. Temperature was the limiting factor of GPP in spring, autumn and winter, while summer GPP was mainly affected by precipitation.

Key words: gross primary production, temporal and spatial variation, climatic factor, China

CAO Yu-juan, SONG Zhen-hua, WU Zhi-tao, DU Zi-qiang. Spatio-temporal dynamics of gross primary productivity in China from 1982 to 2017 based on different datasets[J]. Chinese Journal of Applied Ecology, 2022, 33(10): 2644-2652.

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