## 4 Discussion
### Comparison between Evergreen Forest SiF and Other Terrestrial Ecosystems  
The seasonal midday signal of SiF, without any structural correction, was generally very noisy and did not exhibit any seasonal pattern (Figure 4B), this is in contrast to previous studies (albeit over crops and deciduous forests) that demonstrated a strongly seasonal pattern in SiF, [18; 23; 24; 25; 29; 40; 41; 42; 45; 47; 50; 64; 65; 66; 67]. We found only a very modest seasonal increase in NDVI (Figure 4E), as recorded by an independent broadband sensor installed 30 m above the canopy, likely indicative of minor changes in ecosystem APAR. In addition, because our upwelling radiation sensor was purposefully pointing towards the tree crowns, we would expect that APAR changes in the IFOV would be even smaller due to absent contribution from the ground vegetation. Taken together, these results indicate that the variation in absolute SiF of our evergreen pine canopy was dominated by incoming PAR. Normalization of SiF by incoming PAR has previously been carried out using PAR data acquired above the canopy [42], but unfortunately because of the dynamic sun/shade patterns within the IFOV during the course of the day and passing of the seasons, the actual PAR received by the foliage under examination will differ from that recorded above the canopy following complex temporal patterns and partly undermining the normalization. In an attempt to overcome this limitation, we used reflected radiance at 650 nm (\(L_{650}\), see Equation (1)) as a proxy of actual PAR received by the foliage within the IFOV. After normalization by \(L_{650}\), a clear seasonal pattern in \(SiF\)\(L_{650}\)\({}^{-1}\) emerged (Figure 4C), which more closely followed the time course of GPP (Figure 4A). The \(SiF\)\(L_{650}\)\({}^{-1}\) and indeed GPP, increased through the spring transition towards summer then declined into the autumn period. It is important to note that \(L_{650}\) normalizes the signal by PAR, but not APAR, and therefore, increase in \(SiF\)\(L_{650}\)\({}^{-1}\) could still be due to both changes in APAR (e.g., new needle cohort and shoot elongation during June, and subsequent senescence of old needle cohorts during September), as well as leaf-level adjustments if fluorescence quantum yield (related to LUE). It has been demonstrated that normalisation (using various means such as PAR and APAR) can improve the SiF-GPP relationship in some cases [76], but it is recognised that it is not always possible due to unavailability of measurements like APAR. Certainly attention to various normalisation schemes is warranted in order to understand and separate the physiological and non-physiological components. Our correlation analysis of \(SiF\), \(SiF\)\(L_{650}\)\({}^{-1}\), and \(GPP_{30}\), \(LUE_{30}\) resulted in only weak relationships (Figure 5), which were again generally weaker than the SiF-GPP relationships reported in earlier seasonal and canopy-level studies for crops and deciduous forests or at larger scales using satellite data [35; 43; 47; 50; 73; 77; 78]. This demonstrated the complexity of extracting the physiological signal component from tower based SiF studies in complex forest ecosystems. To date few studies have focused on evergreen ecosystems. [PERSON] [79], using SiF retrieved from the GAME-2 instrument,explored the seasonality in SiF in a high latitude evergreen ecosystem, and reported a strong seasonal relationship between satellite SiF and modelled GPP. Furthermore, [PERSON] (2016) studied a short time series (10 days in length) of SiF in an evergreen canopy that had experienced a short but intense heatwave, and found that during a short period of unchanging APAR, SiF was only very weakly related to the change in GPP, a change attributed to the fact APAR was almost unchanged during the analysis period. In our study, statistically significant relationships only emerged following filtering to limit analyses to midday, cloud free days with high SZA.