# Estimation of Gross Primary Productivity (GPP)
## 4 Discussion
### An Optimal Spectral Proxy for Describing GPP Phenology of SRC Plantations  
Overall, our results revealed that MTCI was the most suitable proxy for describing the GPP phenology (i.e., it exhibited the lower distance in identifying the SOS- and EOS-dates (Tables 4 and 5; Figures 4 and 5), and the highest R\({}^{2}\) and lowest RMSE in reconstructing the seasonal pattern of GPP of the SRC plantation (Figure 7). MTCI described well the SOS and EOS in 2106 and detected well the EOS of the 2018 growing season (Figures 4 and 5; Table 4). The estimates of phenological metrics derived from MTCI showed small differences with GPP phenology for all years anticipating the SOS and delaying the EOS. Among all other tested VIs SIPI and PSSR failed to reproduce the seasonal GPP pattern and to represent SOS and EOS of the GPP. We found that also EVI provided quite good estimates of SOS and EOS and seasonality of GPP, albeit in all cases lower performance than MTCI. NDVI, ChlRedEdge and MCARI performed a bit weaker than EVI, at both SOS and EOS. NDVI performed weaker than EVI, which performed weaker than ChlRedEdge in simulating GPP seasonal variability (Figure 7). MTCI is well known to be a reliable proxy of canopy chlorophyll content [35; 52]. It has been successfully used as a proxy of GPP seasonal variability in several biomes [102; 103; 104; 105; 53]. Changes in canopy chlorophyll content play an important role in controlling ecosystem photosynthetic activity, i.e., GPP [49; 105]. We observed an exceptionally good representation of the seasonal GPP pattern by MTCI (Figure 3, Table 3, Figure 7) [34; 106; 35]. This tight relationship between GPP and MTCI has been attributed to the fact that MTCI does not saturate at higher chlorophyll contents [69; 107]. Figure 7: Linear correlation between Gross Primary Productivity (CPP) and the vegetation indices. (a) NVD—Normalized Vegetation Difference Index (NDVI); (b) EVI—Enhanced Vegetation Index; (c) MTCI—MERIS Terrestrial Chlorophyll Index; and (d) ChIReEdge—chlorophyll red-edge index. The blue, green and red dots represent 2016, 2017 and 2018, respectively. The lines represent the linear fitted models. The shaded areas represent the 95% confidence intervals for the slopes of the fitted lines. R\({}^{2}\), coefficient of determination; RMSE, root mean square error; \({}^{\star}\) 0.01 \(<p\) 5.05; \({}^{\star}\)\(p\)\(\leq\) 0.01. As expected, NDVI was not the best proxy for GPP (Tables 4 and 5; Figure 7). NDVI index--such as the widely used \"greenness indices\"--has been demonstrated to be a good proxy of the fraction of absorbed photosynthetically active radiation (i.e., fAPAR) and LAI [108,109]. Changes in LAI among phenophases affect the shape of the relationship between NDVI and LAI that has almost linear trends during the growing season and declining during the senescence period [110,111]. NDVI shows limitations in describing seasonal LAI variations of dense canopies because it responds mainly to variations in the red and it is relatively insensitive to variations in the NIR [37,112]. These SRC plantations reached an LAI of about 10 in 2016 (data not shown), the last year of the third rotation, when the canopies were fully developed. The very high LAI in 2016 can explain the poor performance of NDVI for the SRC plantations. LAI of natural mature forests varies between 2 and 7 [37] and it could explain the better performance of NDVI in describing the phenology of deciduous forests. The same considerations can explain also the poor performance of other VIs calculated using the NIR reflectance (Table 1: SIPI, PSSR and gNDVI). EVI is assumed to relate to green cover and, therefore, be a useful proxy for canopy phenology [113, 114, 115, 116]. Other studies also reported that EVI well represents the seasonal patterns of GPP [42,117]. EVI was formulated to be less sensitive to atmospheric effects and reflection from soil than other greenness indices such as NDVI, by incorporating blue spectral wavelengths [118] to differentiate soil from vegetation [119].