# Investigating the Performance of Red and Far-Red SIF for Monitoring GPP of Alpine Meadow Ecosystems
Thereby high PAR, air temperature, and VPD would weaken the correlation between SIF-GPP in mangrove ecosystem [39]. [PERSON] et al. [25] exhibited that variations in relative humidity and temperature had obvious effects on the ratio of GPP to \(\text{SIF}_{\text{Far-red}}\) for rice. At the same humidity level, the ratio of GPP to \(\text{SIF}_{\text{Far-red}}\) diminished with elevated temperature, while at the same temperature level, the ratio of GPP to \(\text{SIF}_{\text{Far-red}}\) showed an increase with elevated relative humidity. In a subalpine coniferous forest ecosystem, [PERSON] et al. [40] found that there were differences in the relative importance of environmental factors driving changes in GPP and \(\text{SIF}_{\text{Red}}\) from spring to winter. Moreover, \(\text{SIF}_{\text{Red}}\) responded to light earlier than GPP after winter dormancy ends, potentially making it challenging to capture the onset of the photosynthetic season using \(\text{SIF}_{\text{Red}}\). Regarding a coastal salt marsh ecosystem, tidal inundation had a negative effect on the relationship between \(\text{SIF}_{\text{Far-red}}\) and GPP, mainly due to its different degrees of effects on the light use efficiency (LUE), fluorescence escape probability, and fluorescence quantum yield of vegetation in coastal salt marshes, which affected the performance of \(\text{SIF}_{\text{Far-red}}\) in accurately estimating GPP [29]. Across global scales, [PERSON] et al. [41] showed that moisture availability had a remarkable moderating effect on the SIF-GPP relationship and that the most important environmental factors influencing the SIF-GPP relationship differed in diverse climatic zones. Furthermore, [PERSON] et al. [42] focused on the Northern Hemisphere SIF-GPP relationship and found that the seasonal variation in the SIF-GPP relationship was strongest in regions of moderate temperature and precipitation. Evidently, the effects of environmental factors on the SIF-GPP relationship display different patterns in different regions, making it very essential to consider the transformation of the SIF-GPP relationship at different levels of various environmental factors. Although advances have been made in the SIF-GPP relationship and its response to environmental factors in some ecosystems, apparently the SIF-GPP relationship varies with ecosystem shifts. Even in the same ecosystem, the SIF-GPP relationship varies significantly due to the different stages of vegetation growth and the effects of changes in different environmental factors on vegetation. The SIF-GPP relationship in the whole terrestrial ecosystem is not clarified, therefore, it is necessary to investigate the SIF-GPP relationship under different ecosystems and the influence of environment on this relationship. However, for some special ecosystems, such as alpine meadow, there has rarely been research on how SIF and GPP relate to each other and the effects of environmental factors on their relationships. Furthermore, since researchers investigated the relationship between \(\text{SIF}_{\text{Far-red}}\) and GPP much more frequently than the relationship between \(\text{SIF}_{\text{Red}}\) and GPP in various ecosystems, this has resulted in the scarcity of information on diurnal and seasonal variations of \(\text{SIF}_{\text{Red}}\) and \(\text{SIF}_{\text{Red}}\)-GPP relationships in various ecosystems. However, \(\text{SIF}_{\text{Red}}\), mainly generated from photosystem II, reveals more information related to plant physiological changes than \(\text{SIF}_{\text{Far-red}}\) and, therefore, has theoretically more potential for the accurate monitoring of GPP [14; 15; 20; 43]. We are aware of still no research on the use of tower-based continuous observations to study SIF-GPP relationships for alpine meadow ecosystems. Hence, in this study, we collected canopy reflectance spectral data, SIF spectral data, meteorological variables data, and carbon flux data of alpine meadows for two growing seasons using a continuous automatic tower-based observation system.