## 3 Results  
### Seasonal Variations in Canopy Photosynthesis in Pan-Arctic Regions  
The performances of the VIs such as NDVI, EVI, PI, and PPI to track canopy photosynthesis varied across different landscapes in the pan-Arctic (Figure 2). NDVI typically responded first, with EVI initiating a sharp increase after the leaves began to emerge. NDVI was always higher than the otherindices during the growing season. PPI consistently followed the GPP curve compared with other indices across different plant functional types. PPI and PI started to increase 1 or 2 weeks later in most sites compared with the initial increase in GPP. This indicated that photosynthesis might start before the accumulation of photosynthetic biomass that could be measured by remote sensing optical sensors. NDVI differed substantially between the growing season and the snow season, but was less dynamic during the growing season, except for some possible noise-induced fluctuations. EVI produced a noise-free growing-season signal and was highly correlated with ground-observed phenology scores during the growing phase. However, EVI fluctuated during the winter, creating difficulties in identifying the growing season.  
In wetland sites such as DK-NuF and US-A tq, EVI showed a declining trend before the biological recovery and an increasing trend after the growing season ended, while NDVI had a relatively better performance. In ENF sites where the seasonal dynamics were more obvious, NDVI also followed an increasing trend after the end of the growing season. Similar effects also seemed to apply to PPI in spring, as found in DK-NuF, FI-Sod, RU-Cok, SE-Sk1, and US-Atq, respectively.  
For both NDVI and EVI, abnormal values around 0.35 appeared during the transition dates in non-growing seasons. These phenomena were significant for EVI in wetland tundra, with abnormal values up to 0.73. As for PI, the growing seasons indicated by the seasonal cycles seemed to be mismatched with the EC estimates. PI seemed to indicate longer growing seasons at SE-SK1 and SE-Nor, but shorter growing seasons at US-Atq and DK-ZaH. Notably, midsummer dips in NDVI and  
Figure 2: Averaged seasonal dynamics of NDVI, EVI, PI, and PPI compared with GPP across different landscapes in the pan-Arctic during 2000–2014. Error bars represent standard deviation of indices and GPP.  
EVI in the middle of the growing season, also detected in other studies, were evident in some sites such as FI-Hyy, FI-Kaa, RU-Cok, SE-Deg, SE-Nor, and SE-SK1, respectively.  
The EC sites of FI-Sod, RU-Cok, DK-NuF, and DK-ZaH represented ENF, OSH, WET, and GRA, ecosystems, respectively, with relatively long-term observations (Figure 3). The indices showed similar but different characteristics of inter-annual dynamics across different landscapes. Most indices tended to follow the time dynamics of the phenology indicated by the GPP time series. However, the start and end of measurable photosynthesis were difficult to capture and varied inter-annually. In WET sites like DK-NuF in the pan-Arctic tundra, EVI largely failed to track the inter-annual dynamics, while NDVI, PI, and PPI showed close relationships between inter-annual variations and EC estimates for ENF, OSH, and WET, and thus tracked vegetation phenology. PI might prove useful for deciduous broadleaf forests (DBF) sites, however, the implementation of objective functions to extract SOS and EOS was challenging. Of all the curves, PPI showed relatively larger dynamics during the growing season and followed the inter-annual ground data best, with the fewest abnormal values.  
Figure 3: Seasonal cycles of remotely sensed NDVI, EVI, PI, and PPI time series fitted with daily tower-based GPP for the years 2000–2014. Fits were based on double logistic functions of time. Values \(<-1\) indicated fitted rather than original value.