Combining NDVI, PRI and the quantum yield of solar-induced fluorescence improves estimations of carbon fluxes in deciduous and evergreen forests.

We used automated spectroradiometers to continuously monitor changes in the optical parameters of phenological and photosynthetic traits in beech and spruce forests. We examined seasonal variations in the normalized difference vegetation index (NDVI), photochemical reflectance index (PRI), and solar-induced fluorescence in the oxygen A band (SIFA) that was estimated using a 3-FLD discrimination method from radiance data. The optical parameters tracked the activation and cessation of photosynthesis in spring and autumn. Data at photon fluxes >1200 μmol m s during extended noon hours were used to link the seasonal PRI and SIFA variations to the dynamics of photosynthesis. Seasonal PRI was significantly correlated with photosynthetic light-use efficiency (LUE) with R values of 0.66 and 0.48 for the measurements in beech and spruce forests, respectively. SIFA emissions were significantly correlated with the gross primary production (GPP) of the evergreen spruce forest (R = 0.47), but R was only 0.13 when measured in the beech forest. The correlations between the optical parameters and GPP or LUE, however, tended to be lower when using a dataset with constant NDVI. Introducing an equation combining NDVI, PRI, and the quantum yield of SIFA emission increased R for LUE estimation to 0.77 in the spruce forest and 0.63 in the beech forest. GPP was estimated from the parametric equation with improved accuracy reaching R = 0.53 and RMSE = 5.95 μmol CO m s in spruce forest and R = 0.58 and RMSE = 5.23 μmol CO m s in beech forest. Parametric equations were more efficient in estimating photosynthesis in datasets that consisted of an entire season's data. By combining NDVI, PRI and the quantum yield of SIFA, we could thus substantially improve estimations of carbon fluxes in diverse deciduous and evergreen canopies.