## 3 Results  
Four indicators were used in this study to represent the seasonal vegetation dynamics, including NDVI, NDVI \(\times\) PAR, NDVI\({}^{2}\)\(\times\) PAR and GPP. Normalized regional-mean seasonal cycles from 2009 to 2011 of the selected indicators are shown in Figure 1 by different regions and vegetation types. According to Figure 1, seasonal patterns of the four indicators stayed similar across years, showing a clear seasonal cycle with single-peak around July. North America ENF and Eurasia ENF showed similar patterns while results for Eurasia DBF show some differences. For North America and Eurasia ENF, the NDVI\({}^{2}\)\(\times\) PAR curves nearly perfectly matched the GPP curves, especially during the growing and senescence season. The small discrepancies between the two kinds of curves over peak growing season (June-August) might result from the saturation effect of NDVI. Both NDVI and NDVI \(\times\) PAR curves were found to overestimate the length of growing season, i.e., inclined earlier while declined later than NDVI\({}^{2}\)\(\times\) PAR and GPP. More discrepancies were found in the fall than in the spring among the seasonal patterns. Much steeper spring increases than fall decreases were found for NDVI over years while the other three indicators showed relatively symmetrical growing and senescence patterns (Figure 1a-f) indicating that NDVI shows more significant lag to photosynthesis (GPP) changes in the fall. Although NDVI \(\times\) PAR (as a proxy for APAR) curves were much closer to NDVI\({}^{2}\)\(\times\) PAR and GPP curves in the fall, which was consistent with previous study [9], APAR failed to alleviate but tended to aggravate the early increase in the spring (Figure 1a,c,d). Similar results were reported by [PERSON] et al. [13] when using EVI instead of NDVI. In contrast, NDVI\({}^{2}\)\(\times\) PAR curves correspond well to GPP curves in both spring and fall, indicating that besides APAR, LUE also plays an important role in the spring recovery of photosynthesis and the spring LUE changes might be tracked with NDVI. The similar patterns in the fall for the three indicators except for NDVI also indicate that radiation reduction is the main factor leading photosynthesis decrease during that season. Thus, the late fall decrease of NDVI compared to GPP, which is often reported (e.g., [2]), is expected to be alleviated when introducing radiation constraint. In addition, the regional standard deviations of NDVI are  
Figure 1: Seasonal patterns of normalized difference vegetation index (NDVI), NDVI \(\times\) PAR (photosynthetically active radiation, as a proxy for APAR), NDVI\({}^{2}\)\(\times\) PAR (vegetation index-based light use efficiency model) and gross primary production (GPP) from 2009 to 2011. Error bars indicate regional standard deviations for the specified vegetation types, i.e., North America evergreen needleleaf forest (ENF), Eurasia ENF and Eurasia deciduous broadleaf forest (DBF). Results are ordered and displayed by year (subfigures a, d and g for 2009, b, d and h for 2010 and c, f and i for) and biome (subfigures (**a–c**) for North America ENF, (**d–f**) for Eurasia ENF and (**g–i**) for Eurasia DBF). largely reduced after multiplying with radiation, indicating that more robust results are expected when using APAR or VI-based LUE model to monitor forests' seasonal dynamics rather than using NDVI itself. Compared to ENF, DBF shows narrower seasonal cycles (Figure 1g-i). This is due to the fact that in the spring DBF rely on newly grown leaves for photosynthesis while new leaves only give limited contribution to ENF's total photosynthesis, while in the fall DBF experiences more sharp decline of canopy greenness than ENF. Both NDVI and APAR show broader seasonal cycles than GPP. It is shown that for DBF, the NDVI2 \(\times\) PAR curves still slightly overestimate the duration of growing season, especially in the spring.