Seasonal and Diurnal Dynamics of Sun-Induced Fluorescence and Photosynthesis in Fagus sylvatica and Tilia cordata.

Sun-Induced chlorophyll Fluorescence (SIF) is an emerging and promising remote sensing signal for monitoring photosynthetic activity across spatial and temporal scales. SIF offers insights into the functionality of photosystems, particularly through the quantum yield of fluorescence (Φ_F), which encodes information on dynamic photosynthetic adaptations to ambient environmental conditions. However, interpreting plant physiology from top of the canopy SIF under stress conditions is aggravated by changes and differences in plant structure (e.g. leaf angle), and environmental conditions (e.g. heat, drought). These interacting processes must be disentangled in order to use the  SIF signal as a robust proxy for photosynthesis. 

During the growing season of 2022, we conducted continuous measurements of top of canopy SIF and reflectance factors, leaf electron transport rate, leaf angle, and meteorological conditions for two temperate tree species: European beech (Fagus sylvatica L.) and small-leaved lime (Tilia cordata MILL.). We characterized the seasonal and diurnal dynamics of SIF, Φ_F, and associated photosynthetic parameters while analyzing the effect of structural and physiological changes.

Our findings highlight distinct differences in the diurnal SIF dynamics between Fagus sylvatica and Tilia cordata, particularly under heat and drought conditions. These differences, such as variations in the timing of peak emission, underscore the potential for individual- or species-specific variations in photosynthetic performance and the interpretation of fluorescence signals. By analyzing the influence of canopy structure, light distribution, and environmental factors on these dynamics, we improve our understanding of the relationship between SIF and photosynthesis. We will provide critical insights into its interpretation under varying stress conditions and discuss the remaining challenges in transforming SIF into a robust tool for monitoring plant physiological states across different scales.