The relationship between spectral and integrated sun-induced chlorophyll fluorescence and its implication for photosynthesis estimation using fluorescence observations

Chlorophyll fluorescence (ChlF) is tightly linked to photosynthetic electron transport and informs gross primary productivity (GPP) across scales. Sun-induced ChlF (SIF) is typically retrieved at specific wavelengths (e.g., Fraunhofer lines, oxygen absorption bands) within a narrow field of view (solid angle), and given in power units. This spectral SIF radiance, denoted SIFλ, is not directly photosynthetically relevant, rather, it is the integrated radiant exitance, SIFint, expressed in molar units and integrated over 660–800 nm and the full angular domain, that corresponds mechanistically to photosynthesis. It is generally assumed that the SIFλ is proportional to SIFint and that this proportionality is spatially and temporally invariant. Here we tested this assumption with spectrally resolved SIF measured in three crop and six tree species at the leaf level. We found that while SIFλ is significantly related to SIFint at individual Fraunhofer lines, this relationship varies with wavelength and leaf chlorophyll content (LCC). We therefore developed a model to predict SIFint from SIFλ using wavelength and LCC as inputs. The model performed well across the ChlF emission band, particularly in the far-red region, enabling accurate conversion from observed SIFλ to mechanistically relevant SIFint. As an exploratory extension, the model was applied at the canopy scale for C3 and C4 crops with the Mechanistic Light Response model, yielding encouraging agreement between modeled and observed GPP. The core contribution of this work is establishing the SIFλ–SIFint relationship and a transfer model at the leaf scale, while the canopy application serves as an exploratory extension illustrating its scaling potential. Together, these findings provide a more mechanistically consistent basis for SIF-based GPP estimation and strengthen the application of fluorescence observations in carbon cycle research.