Spatio-temporal evolution of carbon sequestration in Chinese bamboo forests using OCO-2 SIF combined InTEC model and its response to phenology

Vegetation phenology is an important indicator for monitoring carbon sequestration processes in forest ecosystems and modeling vegetation productivity. The length of the phenological period leads to carbon gain and loss in the ecosystem. Bamboo forests have a strong carbon sequestration capacity. However, bamboo phenology is special and difficult to obtain accurately. The accuracy of the ecosystem carbon cycle model in estimating the productivity of bamboo forests will be limited by the uncertainty surrounding the length of the growing season (LOS). According to earlier research, the accuracy of phenological data extraction from bamboo forests can be increased by combining vegetation indices(VIs), which represent canopy structural factors, with sun-induced chlorophyll fluorescence(SIF), which represents vegetation photosynthetic activity. In this study, SVs(combination of SIF and VIs) indices based on SIF were used to extract the LOS of bamboo forests in China using a threshold method. The procedure was then incorporated into the InTEC model. The gross primary productivity(GPP) and net ecosystem productivity(NEP) estimated by the model were then validated using ground observation data. Finally, the spatial distribution of GPP and NEP of bamboo forests in China from 2001 to 2019 was simulated using the updated model, which also demonstrated how LOS and meteorological conditions affected bamboo productivity. The results showed that: (1) the R2 of GPP and NEP estimated by the improved model increased by 83.7% and 45.1%, and the RMSE decreased by 36.4% and 21.5%, respectively; (2) the mean values of GPP and NEP in bamboo forests in China were 682.98 C m-2 yr-1 and 392.64 C m-2 yr-1, respectively, and both of them showed an increasing trend; (3) LOS and temperature have significant positive and negative effects on GPP, respectively. This research elucidates bamboo forests' carbon sequestration mechanisms, advancing understanding of global carbon cycling and climate change.