## 1 Introduction  
Gross Primary Production (GPP) represents the amount of organic carbon fixed by terrestrial plants through photosynthesis and is the driving force for multiple ecosystem functions [1; 2; 3]. An accurate understanding of the temporal and spatial dynamics of terrestrial ecosystem GPPs not only deepens the understanding of the mutual feedback of ecosystems and climate systems, but also helps to fully understand the carbon cycle and to formulate policies related to climate change [4; 5; 6; 7; 8]. Different ecosystems have different photosynthetic carbon absorption capacities and respond differently to changing environmental conditions. Plant leaves adjust their physiological mechanisms to maintain a balance between daylight photosynthesis and light protection. Light use efficiency (LUE) is determined by environmental factors such as nutrients, moisture, and atmospheric temperature, resulting in differences in time and space in the photochemical reaction process. The photochemical reflectance index (PRI), based on remote sensing technology, provides the possibility to establish a link between changes in LUE and changes in the spectral characteristics of vegetation [9; 10; 11]. Some previous studies have shown that LUE is not a constant value in different ecosystems [12]. Some have also reported that vegetation types, nutrients, temperature, soil moisture, and canopy structure complicate the interpretation of LUE [13; 14; 15; 16; 17; 18]. [PERSON] et al. (2010) had shown that LUE was most affected by light and is usually reduced under excessive light conditions [19]. Canopy LUE varies with the radiation received by canopy, while PRI also shows similar properties due to its sensitivity to the fraction of shaded or sunlit leaves [20]. PRI has been used widely as a proxy for LUE. PRI is a simple reflectance parameter that can be measured using a spectrometer under natural conditions [21]. First, the spectral changes of PRI are caused by changes in the pigment bank of plant leaves [22]. Secondly, on a daily scale, the change of PRI is driven by the xanthophyll cycle. On a long-term seasonal scale, the change of PRI is driven by the ratio of carotenoid to chlorophyll pigment pools [9; 23; 24; 25]. Third, some studies have found that there is a good correlation between LUE and PRI in evergreen forests [11]. PRI reflects the optical information of vegetation based on spectrometer observation. It is worth noting that the forest canopy, like most ground features, belongs to the non-Lambertian body, and it will show different degrees of anisotropy. In general, multi-angle remote sensing observations are used to obtain multi-angle information of the vegetation canopy to improve the monitoring and inversion accuracy of crop biochemical parameters [26; 27]. Recent studies provided that the eddy covariance (EC) based LUE and PRI, normalized by the bidirectional reflectance distribution function (BRDF) model, can be explored to validate the relationship [11]. However, it is unclear whether PRI can capture LUE changes in subtropical forests, which are also among the most powerful types of carbon sequestration on earth. The lack of data contributes to the uncertainty in the relationship between PRI and LUE in subtropical evergreen coniferous mixed forests [28]. The results of two Northern forest studies in Canada show that the correlations between PRI and LUE are 0.74 and 0.79, respectively [11]. A study on evergreen broad-leaved forests in Malaysia showed that the correlation between PRI and LUE reached R\({}^{2}\) = 0.12. Using different fitting methods, the impact of VPD on the relationship between PRI and LUE was 34% and 38% [29]. [PERSON] et al. research in subtropical coniferous forests showed that the correlation between PRI and LUE at half-hour and daily scales was 20% and 29%, respectively, and the correlation was small in suitable growth environments [10]. The distribution of leaves in the vegetation canopy will affect the interception of solar radiation and the efficiency of light utilization.