Abstract
The photochemical reflectance index (PRI) has been suggested as an indicator of light use efficiency (LUE), and for use in the improvement of estimating gross primary production (GPP) in LUE models. Over the last two decades, solar-induced fluorescence (SIF) observations from remote sensing have been used to evaluate the distribution of GPP over a range of spatial and temporal scales. However, both PRI and SIF observations have been decoupled from photosynthesis under a variety of non-physiological factors, i.e., sun-view geometry and environmental variables. These observations are important for estimating GPP but rarely reported in the literature. In our study, multi-angle PRI and SIF observations were obtained during the 2018 growing season in a maize field. We evaluated a PRI-based LUE model for estimating GPP, and compared it with the direct estimation of GPP using concurrent SIF measurements. Our results showed that the observed PRI varied with view angles and that the averaged PRI from the multi-angle observations exhibited better performance than the single-angle observed PRI for estimating LUE. The PRI-based LUE model when compared to SIF, demonstrated a higher ability to capture the diurnal dynamics of GPP (the coefficient of determination (R2) = 0.71) than the seasonal changes (R2 = 0.44), while the seasonal GPP variations were better estimated by SIF (R2 = 0.50). Based on random forest analyses, relative humidity (RH) was the most important driver affecting diurnal GPP estimation using the PRI-based LUE model. The SIF-based linear model was most influenced by photosynthetically active radiation (PAR). The SIF-based linear model did not perform as well as the PRI-based LUE model under most environmental conditions, the exception being clear days (the ratio of direct and diffuse sky radiance > 2). Our study confirms the utility of multi-angle PRI observations in the estimation of GPP in LUE models and suggests that the effects of changing environmental conditions should be taken into account for accurately estimating GPP with PRI and SIF observations.
Highlights
Gross primary production (GPP) is defined as the rate of carbon (C) fixation through the process of vegetation photosynthesis
We found that the photochemical reflectance index (PRI)-based light use efficiency (LUE) model exhibited better performance than the solar-induced fluorescence (SIF)-based linear model in estimating the diurnal variations of GPPEC, while the SIF-based linear model performed better at estimating the seasonal variations of GPPEC (Table 1, Figure 4)
Our study demonstrated that the incident radiation (PAR) and sky condition (Q) were not influenced the performance of the PRI-based LUE model in estimating GPP (Figure 7a,b) because the absorbed photosynthetically active radiation (APAR) included in the model partly account for the sky radiation
Summary
Gross primary production (GPP) is defined as the rate of carbon (C) fixation through the process of vegetation photosynthesis. Further studies are needed to improve our knowledge of varying environmental conditions on the effectiveness of PRI in the estimation of GPP using LUE models. Due to its direct linkage to vegetation photochemistry, SIF provides an early and more physiologically-based method to access the functional status and changes of vegetation [39,40] It has been reported in several studies that SIF and GPP have strong empirical linear relationships [32,33,40,41,42,43,44]. SdWpeerectively; (2) to evinatleugartaeteadnadsceot mofpfiaerlde tohbeseprveartfioonrmdaatnac, einoclfuPdRinIg-bmauseltdi-aLngUleEsmpeoctdraell oabnsderSvaIFti-obnas,seedddlyinfeluaxr model for the emsteiamsuarteimonenotsf, GenPvPiroinnmtheentmal aviazreiafibleelsd, ;aannddca(n3o)ptyo setxrupcltourrealthpearmamoedteerls.pTrehfeeroebnjeccetisveusnodfeorudr ifferent environsmtuednytaalrec:o(n1)dtiotioexnpsl.ore the angular variations of observed PRI and evaluate the performance of single-angle and multi-angle spectral observations of PRI in estimating LUE for a maize canopy, 2. T1h03e.5sokgil·Pw·haas−1)irartigthaetetidme(4o5f msomwi)ngbeafnodrewtahsetoepmdreersgseednc(2e25ofkgm·Na·ihzae−1,p3la7.n5tskg(·DP·OhaY−1, 1a5n8d).37T.5he field measurekpmgla·eKnnt·sht(asD−b1)OepYgrai1on5r8to)o.nTthhJeuenefileeoln1dg6ma(teiDoansOusYrteamg1e6e.7nT)thswebehsogeianlnwtohanseJiumrrniaegia1zt6eed(Dw(O4a5Ysme1m6m7)e)brwgehfionerngetthahenedmemaeinezredgweednacsoeenomfSemergpaiitnzegember 24 (DOY 26a7n)dwenhdeend othneSemptaeimzebewr 2a4s (aDtOthYe26m7)awtuhreengthreaimnasiztaegweaps aritothretomahtaurrveegsrta.in stage prior to harvest
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