An integrated remote sensing and model approach for assessing forest carbon fluxes in China

Forest plays an important role in reducing pressure on the natural environment, weaking the influence of greenhouse effects, and sequestrating atmospheric carbon dioxide. So far, due to the lack of complete understanding of forest ecosystem processes and the limitations on the scope of application of evaluation methods, there are still great uncertainties in the researches on carbon fluxes of forest ecosystems in China at the national level. In this study, an individual tree species FORCCHN model, which could flexibly use the inventory data as the initial field (more accurately) or use the remote sensing information to inverse initial field was applied. The dynamics of key carbon cycle fluxes (net primary productivity (NPP) and net ecosystem productivity (NEP)) and carbon sequestration of forest ecosystems in China from 1982 to 2019 were simulated based on remote sensing data and FORCCHN model. The results showed that forest ecosystems in China had great carbon sequestration potential over the past 39 years. From 1982 to 2019, the NPP of Chinese forests presented a fluctuated increase. Total NPP from 2011 to 2019 ranged from 0.91 PgC·a^-1 to 1.14 PgC·a^-1. Annual average NEP of forest ecosystems in China from 2011 to 2019 was 0.199 PgC·a^-1 (1Pg = 10¹⁵ g). Influenced by climate, soil and vegetation, carbon sequestration potential in Chinese forest ecosystems presented obvious regional differences in space. The spatial distribution of NEP gradually increased from Northwest to Southeast China. From 2011 to 2019, forests in Yunnan Province had the strongest carbon storage capacity (72.79 TgC·a^-1, 1Tg = 10¹² g), followed by forests in Guangxi (18.49 TgC·a^-1) and forests in Guangdong (10.01 TgC·a^-1). Our results not only address concerns about carbon sequestration but also reflect the importance of Chinese forest resources in the development of the national economy and society.