4.7 Article

Modelling the influence of incident radiation on the SIF-based GPP estimation for maize

Journal

AGRICULTURAL AND FOREST METEOROLOGY
Volume 307, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.agrformet.2021.108522

Keywords

Solar-induced chlorophyll fluorescence (SIF); Gross primary productivity (GPP); Light use efficiency (LUE); Photosynthetically active radiation (PAR); Response model

Funding

  1. National Key Research and Development Program of China [2017YFA0603001, 2017YFA0603002]
  2. National Natural Science Foundation of China [42071310, 41825002]

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Solar-induced chlorophyll fluorescence (SIF) is a reliable indicator of vegetation gross primary productivity (GPP), but the ratio of photosynthetic light use efficiency (LUE) to total SIF quantum yield (SIFyield) can introduce uncertainty in SIF-GPP models. This study found that LUE decreases as photosynthetically active radiation (PAR) increases, impacting the accuracy of GPP estimation models. By integrating the influence of PAR on LUE, the SIF-GPP model for maize showed improved accuracy and reduced error in GPP estimation.
Solar-induced chlorophyll fluorescence (SIF) has been shown to be an ideal indicator of vegetation gross primary productivity (GPP), but the variation in the ratio of the photosynthetic light use efficiency (LUE = GPP/APAR) to the total SIF quantum yield (SIFyield = SIFtotal/APAR) is an important source of uncertainty in SIF-GPP models. Incident radiation is one of the key factors influencing LUE and SIFyield. In this study, to investigate the influence of PAR on LUE and SIFyield, pulse-amplitude-modulated (PAM) fluorometry was carried out at the leaf level along with tower-based continuous SIF-GPP measurements at the canopy level for maize. LUE was found to decrease as PAR increased, following a hyperbolic function, at both the leaf level (R-2 = 0.978) and canopy level (R-2 = 0.460 for half-hourly averaged dataset; R-2 = 0.341 for daily averaged dataset). However, the variation of SIFyield with PAR was found to be very small. By integrating the influence of PAR on LUE, the GPP estimation model based on the red band and near-infrared (NIR) band SIF for maize became more linear. For both the half-hourly and daily datasets, the values of R-2 for the SIF-GPP model increased (e.g. from 0.573 to 0.718 for the half-hourly NIR band SIF), and the RMSE for the estimated GPP reduced (e.g. from 8.30 to 6.75 mu mol CO2 m(-2) s(-1) for the half-hourly NIR band SIF). These results highlight that the ratio of LUE to SIFyield is an important source of uncertainty in SIF-GPP models and should be carefully corrected. The results also show that PAR is a key factor influencing this ratio. This PAR-based LUE model can be integrated not only in SIF-GPP models but also in other LUE-related GPP estimation models for unstressed maize.

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