## 6 Conclusions and Perspectives  
The mechanisms involved in PRI variation can be complex due to varying spatial and temporal scales. Many physical, biochemical and physiological factors can affect diurnal and seasonal PRI patterns at foliar, canopy and ecosystem levels. Most of the variation of PRI when scaling up from diurnal to seasonal measurements is likely due to the changes in the size of the constitutive pigment pools other than facultative xanthophyllic de-epoxidation [54; 55; 67]. Other physical or external factors, such as illumination, temperature or water stress, soil background, disease and low nitrogen levels, have the potential to produce biochemical and physiological changes that can also generate PRI variation. The structural properties of canopies and the solar/spectrometric (or satellite) directions of detection at the canopy and ecosystem levels are also important factors that contribute to changes in PRI. Our analysis, however, also indicated that PRI was often significantly correlated with ecophysiological variables and RUE. \(R^{2}\) values between PRI and RUE ranged between 0.41 and 0.66 (Figure 9), even higher than in the first studies reviewed by [PERSON] et al. [20]. In particular, PRI was a good indicator of diurnal changes in RUE and a good proxy of seasonal changes in photosynthetic efficiency at different spatial scales. Our understanding of the ecophysiological mechanisms of PRI variation and the implementation of PRI, particularly for assessing carbon uptake, have progressed. Further, other photoprotective mechanisms, for example chloroplast avoidance movement, have been proposed to have an effect on light-induced optical changes related to zeaxanthin formation [159] that probably also play a role in the PRI variation. Such influences on PRI variation should be further analyzed. The correlations between PRI and RUE have been greatly improved by decreasing the impact of the canopy structure and the sizes of the pigment pools. These impacts can be decreased by subtracting the dark-adapted PRI to minimize the influence of the canopy structure and the pigment pools and by introducing the optical signal of the pigment pools or the structural-related signal. GPP, though, can be better assessed by combining the RUE-related PRI with APAR-related greenness indices, thus using the approach of the RUE model. Combining SIF with PRI is another promising opportunity for interpreting RUE and monitoring GPP from local to regional scales. Studies of the optical remote sensing of RUE, especially using PRI to estimate or model RUE, have focused mainly on temperate forests and grassland, with limited studies of tropical forests. More attention should thus be paid to the assessment of RUE and GPP using PRI for different species, especially for tropical forests. We should also further explore the PRI mechanisms across vegetation types and at various spatial and temporal scales. Unmanned aerial vehicles (UAVs) with various multispectral cameras can increasingly provide an exciting opportunity to obtain canopy PRI and also SIF with high spatiotemporal resolution [74; 75; 149; 160], which could be very beneficial for our understanding of the variation in canopy PRI. Our results indicate that corrected PRI (PRIc) proposed by [PERSON] et al. [123] is an outstanding improved PRI, which could be a promising proxy of RUE and is warranted to be tested over a wide range of species and spatiotemporal scales. Furthermore, PRIc was successfully obtained from MODIS and tracked the severe drought episode and GPP variation. Thus, we advocate efforts to produce a PRI product in platforms (e.g., MODIS PRI) as existing MODIS NDVI/EVI products. Additionally, PRI coupled with SIF or indices of greenness biomass is a promising approach to build an integrated and robust model of remotely sensed carbon uptake.