Canopy structure explains the relationship between photosynthesis and sun-induced chlorophyll fluorescence in crops

Abstract

Remote sensing of far-red sun-induced chlorophyll fluorescence (SIF) has emerged as an important tool for studying gross primary productivity (GPP) at the global scale. However, the relationship between SIF and GPP at the canopy scale lacks a clear mechanistic explanation. This is largely due to the poorly characterized role of the relative contributions from canopy structure and leaf physiology to the variability of the top-of-canopy, observed SIF signal. In particular, the effect of the canopy structure beyond light absorption is that only a fraction (f esc) of the SIF emitted from all leaves in the canopy can escape from the canopy due to the strong scattering of near-infrared radiation. We combined rice, wheat and corn canopy-level in-situ datasets to study how the physiological and structural components of SIF individually relate to measures of photosynthesis. At seasonal time scales, we found a considerably strong positive correlation (R 2 =0.4-0.6) of f esc to the seasonal dynamics of the photosynthetic light use efficiency (LUE P), while the estimated physiological SIF yield was almost entirely uncorrelated to LUE P both at seasonal and diurnal time scales, with the partial exception of wheat. Consistent with these findings, the canopy structure and radiation component of SIF, defined as the product of APAR and f esc , explained the relationship of observed SIF to GPP and even outperformed GPP estimation based on observed SIF at two of the three sites investigated. These results held for both half-hourly and daily mean values. In contrast, the total emitted SIF, obtained by normalizing observed SIF for f esc , improved only the relationship to APAR but considerably decreased the correlation to GPP for all three crops. Our findings demonstrate the dominant role of canopy structure in the SIF-GPP relationship and establish a strong, mechanistic link between the near-infrared reflectance of vegetation (NIR V) and the relevant canopy structure information contained in the SIF signal. These insights are expected to be useful in improving remote sensing based GPP estimates.

Wide discrepancies in the magnitude and direction of modeled solar-induced chlorophyll fluorescence in response to light conditions

“…2. φ N accounts for the ability of plants to dissipate excess energy as heat via NPQ through the regulation of xanthophyll cycle pigments (Demmig-Adams and Adams, 2006). NPQ can be represented as a sum of reversible (k R ) and sustain (k S ) components (k N = k R + k S ).…”

“…Finally, we note that our focus on a water-limited subalpine evergreen needleleaf forest represents a challenging case study for models and observations. In many cases, there is strong covariance between LAI, SIF, APAR, and GPP in cropping systems (Dechant et al, 2020), but because this study site experiences little change in canopy structure and APAR throughout the season (Magney et al, 2019b), our study sought to provide more explicit insight into the model sensitivity to photosynthesis and fluorescence. As such, it is possible that we would see more convergence of results and a reduction in confounding effects (e.g., decreased NPQ) in a well-watered high-LAI cropping system.…”

Unravelling the physical and physiological basis for the solar-induced chlorophyll fluorescence and photosynthesis relationship

“…Therefore, they must, in turn, affect the success of remote sensing relationships for SIF-GPP (Yang and Van der Tol, 2018). Likewise, these factors also affect the variability of the APAR-GPP relationship (Dechant et al, 2020;Qiu et al, 2019), and the LUE-GPP relationship (e.g., Middleton et al, 2019).…”

“…is the fraction of the emitted far-red fluorescence that escapes the canopy in the viewing direction (per solid angle), which depends on the viewing and illumination geometries and canopy structure (Porcar-Castell et al, 2014;Yang et al, 2020;Yang and Van der Tol, 2018) . From the LUE model, it is evident that the common terms iPAR and fAPAR are primarily responsible for the often-reported linear relationship between SIF and GPP (Campbell et al, 2019;Dechant et al, 2020;Miao et al, 2018;Rossini et al, 2010; https://doi.org/10.5194/bg-2020-323 Preprint. Discussion started: 8 September 2020 c Author(s) 2020.…”

“…However, these assumptions need to be verified, and we still lack a clear conclusion on the physical and physiological basis for the relationship between far-red SIF and GPP. Dechant et al (2020) explored the relationship between SIF and GPP for three in situ crop datasets. They found that correcting SIF for canopy scattering ( ) improved the correlation to APAR but not to GPP.…”