Towards a more reliable GPP estimation: A systematic assessment of using the photochemical reflectance index as a proxy for non-photochemical quenching

Resolving the global terrestrial CO2 budget remains a pressing challenge with implications for achieving internationally agreed emissions targets. To this end, remote sensing of solar-induced chlorophyll fluorescence (SIF) is rapidly advancing in accurately estimating gross primary productivity (GPP) on a global scale. While to this date, matching flux tower footprints with remote sensing data provides some insights, current satellite missions are constrained by insufficient spectral, spatial, or temporal resolution. However, this limitation is expected to be addressed to some extent by the European Space Agency's (ESA) upcoming Fluorescence Explorer (FLEX) mission.

Despite these technical aspects, the relationship between SIF and GPP under diverse environmental conditions remains complex because non-photochemical quenching (NPQ), which dissipates excess light energy, competes for the same energy pool that drives photosynthesis. The challenge of disentangling these processes is especially pronounced during periods of vegetation stress which is increasingly observed with higher frequency of extreme weather events.

To determine NPQ, the photochemical reflectance index (PRI) has been employed in case studies but systematic assessments across diverse ecosystems and environmental gradients are lacking. To address this, we investigate the SIF-GPP relationship using a comprehensive dataset consisting of Fluorescence Box (FloX) spectrometer and chlorophyll fluorometers (PAM) measurements at seven European flux tower sites, spanning five growing seasons. These sites represent a diverse range of plant functional types, including forests, managed grasslands, an agricultural field, and a savanna.
Our results indicate that while PRI can serve as a sensitive proxy for NPQ at individual sites, the relationship does not hold universally across sites. This variability is likely due to an inability to fully separate structural influences from physiological effects and differences in scale. However, an investigation of physiology-structure interactions is underway using data from a controlled mesocosm experiment together with SCOPE simulations.