Mechanistic modelling of gross primary production from sun-induced fluorescence measurements on a wheat canopy in Belgium

Abstract

In the context of global climate change, extreme weather events are expected to intensify, threatening agricultural systems. Meanwhile, food demand is likely to grow due to increas- ing human population. Accordingly, being able to assess and predict dynamic behaviours of crops under changing climatic conditions is crucial to ensure food security. For that purpose, photosynthesis is the key process to characterise. According to the literature, sun-induced flu- orescence (SIF) represents a potential indicator of photosynthesis. Recently, the mechanistic light response model (MLR) estimating gross primary production (GPP) from SIF has been established. Firstly, this study aims to assess the relationship between SIF and GPP from the MLR model perspective for a winter wheat canopy in Belgium. Secondly, the dynamics of the main model parameters depending on environmental conditions have been studied. Continuous measurements of micro-meteorological, flux and SIF data have been carried out for five months by an ICOS station. Moreover, leaf-level gas exchange and fluorescence parameters have been measured manually using a portable photosynthesis system. Similar temporal evolutions of SIF and GPP in response to light have been observed, supporting the use of SIF as an indicator of photosynthesis. The model provides a relatively moderate performance at half-hourly scale which improved at daily scale. In particular, the model seems to correctly reproduce the SIF- GPP relationship only under low light intensities and high soil moisture which is in agreement with the main model assumption. Overall, these results point out the need for more accurate characterization of the model underlying processes and parameters dynamics regarding envi- ronmental conditions.