Abstract. Photosynthesis by terrestrial plants represents the majority of CO2 uptake on Earth, yet it is difficult to measure directly from space. Estimating Gross Primary Production (GPP) from remote sensing indices is a primary source of uncertainty, in particular for observing seasonal variations in evergreen forests. Recent vegetation remote sensing techniques have highlighted spectral regions sensitive to dynamic changes in leaf/needle carotenoid composition, showing promise for tracking seasonal changes in photosynthesis of evergreen forests. However, continuous daily measurements of spectrally resolved canopy reflectance are limited in these ecosystems. To investigate this potential, we continuously measured vegetation reflectance (400–900 nm) using a canopy spectrometer system, PhotoSpec, mounted on top of an eddy-covariance flux tower in a subalpine evergreen forest at Niwot Ridge, Colorado, USA. We analyzed driving spectral components in the measured canopy reflectance using both statistical and process-based approaches. The decomposed spectral components relate directly to carotenoid pigments and co-vary seasonally with GPP, supporting the interpretation of the Photochemical Reflectance Index (PRI) and the Chlorophyll/Carotenoid Index (CCI). We show that using features from the entire 400–900 nm range show additional spectral changes near the red-egde but do not outperform the PRI or CCI indices for GPP predictions. In addition, we can quantitatively determine needle-scale chlorophyll to carotenoid ratios as well as anthocyanin contents using full spectrum inversions, both of which tightly correlated with seasonal GPP changes. Reconstructing GPP from vegetation reflectance using Partial Least Squares Regression (PLSR) explained approximately 87 % of the variability in observed GPP. Our results link the seasonal variation of reflectance to the pool size of photoprotective pigments, highlighting all spectral locations within 400–900 nm associated with GPP seasonality in evergreen forests.;
