Using Solar-Induced Chlorophyll Fluorescence in a Combined Index to Estimate Tree Productivity and Physiology in the 2018 and 2022 European Droughts

The European heatwaves of 2018 and 2022 led many parts of the continent into record high temperatures and extremely dry conditions compared to mean temperature and precipitation. This resulted in a decrease in forest productivity and an increase in forest fires and tree death in affected areas. As droughts increase in severity and frequency with global climate change, it is important to investigate how tree species respond to water stress, and how these responses affect ecosystem productivity. Solar-induced chlorophyll fluorescence (SIF) has been useful for estimating gross primary productivity (GPP) and assessing terrestrial carbon fluxes. Even though SIF provides a direct link for energy available for carbon fixation, SIF is heavily affected by canopy structure and sun-sensor geometry. Near-infrared radiance of vegetation (NIRvR) is a recently studied index that provides accurate information about plant canopy structure, solar irradiance, and has a positive, linear relationship with GPP. Mathematically combining SIF, NIRvR, and the enhanced vegetation index (EVI) into one index may consequently better estimate GPP since this method integrates a direct link to photosynthesis, structure, and greenness, respectively. Especially under conditions where water is limited, the combined SIF-NIRvR-EVI index could provide more instantaneous and accurate estimates of productivity and plant health when compared to the individual indices. Indeed, a recent study (Zeng et al. 2021) normalized SIF with NIRvR to calculate fluorescence yield (ΦF), incorporating photosynthesis and plant structure information into one index.  They found that ΦF accurately detects stress-induced limitations in photosynthesis in field-level data, but little is known about how this approach scales up to satellite-level data. To overcome this research gap, we isolate areas in Germany affected by drought with known dominant tree species and analyze how individual and combined measurements of florescence, canopy structure, and greenness respond to the 2018 and 2022 European droughts, as well as normal precipitation conditions (2019 – 2021). This will provide insights into how water stress affects the physiology of tree species and investigate a new combined SIF-NIRvR-EVI index. A random forest model is applied to examine how well the combined index predicts GPP during drought and non-drought conditions. The resulting model outputs are compared to satellite derived GPP products and separately with FLUXNET sites to ground truth the accuracy of the modeled GPP estimates during the study period.