## 4 Discussion
### Explaining the Differential Performance of Vegetation Indices  
The PROSAIL analyses showed that NDVI is particularly sensitive to LAI and C\({}_{\rm ab}\) (Figure 5; [11; 19]), while EVI and NIR\({}_{\rm v}\) are sensitive to LAI and LMA. EVI and NIR\({}_{\rm v}\)'s increased sensitivity to LMA is the main characteristic that separates these VIs from NDVI, and that we believe leads to their more general relationships with GPP. The relationships between LMA and EVI and NIR\({}_{\rm v}\) are apparently driven by a decrease in NIR reflectance with progressively thicker leaves. LMA is not a dominant controller of leaf-level NIR reflectance [60], but becomes important at the canopy level due to the absorption of light by lignin and cellulose [61]. Thicker, higher LMA leaves with more lignin and cellulose absorb more NIR for a given LAI, leading to increased light absorption, and reduced canopy-level NIR reflectance, and consequently reduced EVI and NIR\({}_{\rm v}\)[51].  
LMA is one of several leaf traits that co-vary along the leaf economic spectrum [32]. Thicker leaves with a higher LMA are globally correlated with longer leaf life spans, lower leaf nitrogen concentrations, and lower rates of leaf photosynthesis. The leaf economic relationships are strongest when compared  
Figure 7: Relationships at all ten study sites between (**a**) MODIS Enhanced Vegetation Index (EVI) and NIR\({}_{\rm v}\) and between (**b**) MODIS NDVI and EVI.  
on a mass vs mass basis, whereas our LMA vs A\({}_{\text{leaf}}\) relationship is presumably mediated by leaf biochemistry and should be thought of as a mass vs area comparison [31; 32; 56; 57]. Nonetheless, previous studies have found that leaf nitrogen content per mass combined with LAI largely explains GPP variation across sites and biomes [15; 28; 62].  
LMA may be thought of as a proxy for leaf nitrogen content and photosynthetic rate, and VIs that are influenced by both LAI and LMA will provide more general predictions of GPP than ones that are influenced mainly by LAI. Hence, seasonal or interannual GPP shifts associated with the initial flushing of young, lower LMA, rapidly photosynthesizing leaves, and the gradual aging to thicker leaves with lower photosynthetic rates [39; 63; 64; 65; 66] may be effectively explored with VIs such as EVI and NIR\({}_{\text{v}}\). Likewise, the GPP effects of seasonal, interannual, or successful shifts from herbaceous to evergreen leaf importance may be detected using VIs such as EVI and NIR\({}_{\text{v}}\).  
We have argued that EVI and NIR\({}_{\text{v}}\) are particularly well correlated with GPP because they are influenced by both LAI and LMA. However, we have also shown that NDVI is sensitive to C\({}_{\text{ab}}\) content (Figure 5b), which is also correlated with leaf level CO\({}_{2}\) uptake [21], raising the question of the apparent insensitivity of NDVI to the leaf-level component of GPP. Previous studies have assumed that a weaker relationship between NDVI and GPP is caused by saturation at high LAI or environmental influences that are not related to plant physiology [18]. Here we have shown that NDVI saturates at relatively low values of C\({}_{\text{ab}}\) (Figure 6a) due to strong chlorophyll absorption at red wavelengths (Figure 5a). Hence, NDVI is relatively insensitive to C\({}_{\text{ab}}\) over the typical conditions observed for upper-canopy leaves, and NDVI lacks strong sensitivity to a leaf trait that is well correlated with A\({}_{\text{leaf}}\). In contrast, the effect of LMA on EVI and NIR\({}_{\text{v}}\) shows minor saturation across a realistic range of leaf thicknesses (Figure 5c,d).