## 4 Discussion
### Future Prospects for Capturing Phenology Metrics in Pan-Arctic regions
Efforts were made to distinguish the effective greening up of spring from snow melt such as developing new methods including winter NDVI, which is the NDVI outside the growing season, in monitoring vegetation activities in deciduous and ever green forest in northern Scandinavia [30]. Another possible solution would be including more newly released MODIS reflectance product Collection 6 (C6). A recent study found that, in the Tibetan Plateau, NDVI from Collection 5 (C5) SOS was more consistent than C6 SOS in terms of ground-observed green-up dates for alpine grassland [63]. Although there was improved quality at high latitudes from use of all available observations in C6 than C5 who used only four observations per day. The results showed there was no significant improvement for C6 in extracting phenological metrics (Table 2), suggesting that the use of C6 may not help tackle the influence of snow, soil moisture on estimates of phenological metrics. However, further study is still needed. Figure 6: Averaged VI sensitivities to the variation of snow coverage in ENF site of FI-Hyy in Finland during 2000-2014 and in GRA site of SE-Deg in Sweden during 2001-2006. Pink solid line shows snow activity indicated by the NDSI. Alternatively, after the first retrievals of chlorophyll fluorescence from satellite measurements on a global scale [64], strong correlations were found between tower-based GPP and satellite-derived SIF. Chlorophyll absorbs photons to provide energy for photosynthesis, and some photons are then released at longer wavelengths in the form of fluorescence. A recent study found that canopy-level SIF retained a strong linear correlation with GPP in deciduous forests (R\({}^{2}\) = 0.82) [65]. However, correlations between SIF and GPP are affected by factors such as wavelength, biomass, ecosystem, canopy structure, and timescale [66]. We tested if SIF could capture the phenological transition dates of ENF in pan-Arctic regions. In relatively homogeneous ENF EC sites in pan-Arctic regions, SIF and tower-based GPP showed similar seasonal cycles in highly homogenous EC sites (Figure 7). Both SIF and EC based GPP also indicated the onset of photosynthetic activity in early April. The high correlation in annual dynamic changes suggested that SIF could be used as a phenology indicator in pan-Arctic regions. SIF was more closely related to GPP in ENF sites than in OSH sites. This could be explained by the fact that the carbon sequestration capacity of the OSH itself was not very strong, as well as by noise during the non-growing season and errors caused by the remote sensing algorithm. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & & \multicolumn{2}{c}{**Collection 6**} & \multicolumn{2}{c}{**Collection 5**} \\ \hline
**Metrics** & **Indices** & **R\({}^{2}\)** & **RMSE** & **R\({}^{2}\)** & **RMSE** \\ \hline \multirow{4}{*}{SOS} & NDVI & 0.001 & 10.73 & 0.38 & 7.68 \\  & EVI & 0.39 & 9.392 & 0.09 & 12.54 \\  & PI & 0.08 & 9.705 & 0.14 & 8.08 \\  & PPI & 0.14 & 8.175 & 0.2 & 8.14 \\  & NDVI & 0.02 & 18.37 & 0.23 & 19.34 \\  & EVI & 0.07 & 19.07 & 0.1 & 17.78 \\  & PI & 0.08 & 17.91 & 0.01 & 15.87 \\  & PPI & 0.03 & 16.11 & 0.14 & 14.35 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: SOS and EOS extracted by MODIS reflectance product Collection 5 and Collection 6 at FI-Hyy. The comparison is done with GPP. RMSE stands for root-mean-square error. Figure 7: Seasonal cycles of tower-based GPP observations and SIF measurements from GOME-2 in three relatively spatially homogenous FLUX sites (FI-Sod, RU-Cok, and FI-Hyy), where the dominate plant function type accounted for 87.6%, 75.3%, and 73.3%, respectively  
In ENF sites, the relationship between SIF-based and GPP-based estimates was significant for both SOS and EOS (\(p<0.05\)). SIF-based SOS demonstrated a better relationship with GPP (R\({}^{2}\) = 0.34; Figure 8), whereas NDVI performed best among the four indices, although with relatively low R\({}^{2}\) (R\({}^{2}\) = 0.17; Table A3).