## 1 Introduction  
Gross primary production (GPP) can reflect the total organic carbon fixed by vegetation through photosynthesis, directly driving the ecosystem carbon cycle and directly or indirectly affecting the function, biodiversity, and sustainability of terrestrial ecosystems [1, 2]. Therefore, the accurate understanding and rapid assessment of GPP and its dynamic changes are indispensable to understand the response and adaptation of ecosystem to environmental changes, and to provide important support for research of global change and ecosystem service across different time and space scales [3]. Solar-induced fluorescence (SIF) is assumed widely related to actual plant photochemistry. When chlorophyll absorbs sunlight, it rises from the stable and lowest energy state to an unstable and high-energy excited state, and then quickly turns to the low-energy state, and the emitted energy is consumed in the form of heat and fluorescence [4]. Under natural light conditions, chlorophyll fluorescence accounts only for 0.5-2% of sunlight energy absorbed by vegetation, and the amount of chlorophyll fluorescence emitted is directly proportional to that of photosynthesis. Therefore, variations related to plant photosynthesis can be potentially detected by fluorescence [5], and SIF is also considered to be an effective indicator of plant photosynthesis [6]. In recent years, the estimation of GPP based on observed SIF has received more attention. Some studies found that the SIF obtained via GOSAT satellite showed a strong linear correlation with GPP [7, 8]. [PERSON] et al. carried out the first global analysis of the relationship between SIF from OCO-2 satellite and GPP from flux observations, and they found that SIF and GPP showed a strong linear correlation among eight ecosystems, in which the slope of evergreen broad-leaved forests was the lowest, and the slopes of evergreen coniferous forests and deciduous broad-leaved forests were similar [9]. Using SIF from GOME-2 satellite, [PERSON] et al. indicated that satellite SIF were significantly correlated with GPP of different ecosystems in China, and the slopes were the lowest in both temperate coniferous and broadleaved mixed forests, while higher in evergreen forests [10]. However, the satellite SIF was utilized in most studies to examine the relationship between SIF and GPP, the utilization of local observed SIF was still deficient. The relationship between SIF and GPP differs greatly in different vegetation types mainly due to the influence of canopy structure, vegetation physiological status, and the environmental variations. [PERSON] et al. found that the seasonal variation of SIF and GPP were similar which yielded a linear correlation in a temperate deciduous forest [11]. [PERSON] et al. found that SIF can be used to characterize the variation of GPP, while the slope is relatively low in subalpine coniferous forests [6]. [PERSON] et al. analyzed the phenology of high-latitude forest vegetation in Eurasia and North America, and they found that the spring SIF was lagged behind that of the vegetation index due to the limitation of the available radiation on carbon assimilation, while a better consistency between GPP and SIF was exhibited in autumn [12]. [PERSON] et al. found a weak correlation between daily SIF and GPP, and such a correlation was not significant in diurnal scale and in sunny conditions [13]. In recent studies, SIF has been widely used to estimate regional and global GPP, but some studies have shown that GPP will be saturated under strong light, resulted in a nonlinear relationship between GPP and SIF in short time scales, which becomes more linear with the increase in spatial and temporal scales [14; 15; 16]. At present, most studies were limited to middle and high latitudes, the observations in low latitude ecosystems, especially the coniferous forest, remain relatively lack. Therefore, the capability of SIF to characterize the variations of GPP change needs further studies across more ecosystems and regions.