Data from: The Physiological Basis for Estimating Photosynthesis from Chlorophyll a Fluorescence

Abstract

These files contain data supporting all results reported in Han et. al. The Physiological Basis for Estimating Photosynthesis from Chlorophyll a Fluorescence. In Han et al. we found: The availability of Solar-Induced chlorophyll Fluorescence (SIF) offers potential to curb large uncertainties in estimating photosynthesis across biomes, climates, and scales. However, it remains unclear how SIF should be used to mechanistically estimate photosynthesis. This study built a quantitative framework to estimate photosynthesis, based on a mechanistic light reaction model with chlorophyll a fluorescence from PSII (SIFPSII) as an input (MLR-SIF). Utilizing 29 C3 and C4 plant species representative of major plant biomes across the globe, we verified such a framework at the leaf level. MLR-SIF is capable of accurately reproducing photosynthesis for all C3 and C4 species under diverse light, temperature, and CO2 conditions. We further tested the robustness of MLR-SIF using Monte Carlo simulations, and found that the estimated photosynthesis is much less sensitive to parameter uncertainties relative to the conventional Farquhar, von Caemmerer, Berry (FvCB) model because of additional independent information contained in SIFPSII. SIFPSII, once inferred from direct observables of SIF, provides “parameter savings” to the MLR-SIF as compared to the mechanistically equivalent FvCB and thus shortcuts the uncertainties propagated from imperfect model parameterization. Our findings set the stage for future efforts employing SIF mechanistically to improve photosynthesis estimation across scales, functional groups, and environmental conditions.