4 research outputs found

    Structural and photosynthetic dynamics mediate the response of SIF to water stress in a potato crop

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    Solar-induced Fluorescence (SIF) has an advantage over greenness-based Vegetation Indices in detecting drought. This advantage is the mechanistic coupling between SIF and Gross Primary Productivity (GPP). Under water stress, SIF tends to decrease with photosynthesis, due to an increase in non-photochemical quenching (NPQ), resulting in rapid and/or sustained reductions in the fluorescence quantum efficiency (phi F). Water stress also affects vegetation structure via highly dynamic changes in leaf angular distributions (LAD) or slower changes in leaf area index (LAI). Critically, these responses are entangled in space and time and their relative contribution to SIF, or to the coupling between SIF and GPP, is unclear. In this study, we quantify the relative effect of structural and photosynthetic dynamics on the diurnal and spatial variation of canopy SIF in a potato crop in response to a replicated paired-plot water stress experiment. We measured SIF using two platforms: a hydraulic lift and an Unmanned Aerial Vehicle (UAV) to capture temporal and spatial variation, respectively. LAD parameters were estimated from point clouds and photographic data and used to assess structural dynamics. Leaf phi F estimated from PAM fluorescence measurements were used to represent variations in photosynthetic regulation. We also measured foliar pigments, operating quantum yield of photosystem II (PSII), photosynthetic gas exchange, stomatal conductance and LAI. We used a radiative transfer model (SCOPE) to provide a means of decoupling structural and photosynthetic factors across the diurnal and spatial domains. The results demonstrate that diurnal variation in SIF is driven by photosynthetic and structural dynamics. The influence of phi F was prominent in the diurnal SIF response to water stress, with reduced fluorescence efficiencies in stressed plants. Structural factors dominated the spatial response of SIF to water stress over and above phi F. The results showed that the relationship between SIF and GPP is maintained in response to water stress where adjustments in NPQ and leaf angle co-operate to enhance the correlation between SIF and GPP. This study points to the complexity of interpreting and modelling the spatiotemporal connection between SIF and GPP which requires simultaneous knowledge of vegetation structural and photosynthetic dynamics.Peer reviewe

    Multiple-constraint inversion of SCOPE. Evaluating the potential of GPP and SIF for the retrieval of plant functional traits

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    The most recent efforts to provide remote sensing (RS) estimates of plant function rely on the combination of Radiative Transfer Models (RTM) and Soil-Vegetation-Atmosphere Transfer (SVAT) models, such as the Soil-Canopy Observation Photosynthesis and Energy fluxes (SCOPE) model. In this work we used ground spectroradiometric and chamber-based CO2 flux measurements in a nutrient manipulated Mediterranean grassland in order to: 1) develop a multiple-constraint inversion approach of SCOPE able to retrieve vegetation biochemical, structural as well as key functional traits, such as chlorophyll concentration (Cab), leaf area index (LAI), maximum carboxylation rate (Vcmax) and the Ball-Berry sensitivity parameter (m); and 2) compare the potential of the of gross primary production (GPP) and sun-induced fluorescence (SIF), together with up-welling Thermal Infrared (TIR) radiance and optical reflectance factors (RF), to estimate such parameters. The performance of the proposed inversion method as well as of the different sets of constraints was assessed with contemporary measurements of water and heat fluxes and leaf nitrogen content, using pattern-oriented model evaluation. The multiple-constraint inversion approach proposed together with the combination of optical RF and diel GPP and TIR data provided reliable estimates of parameters, and improved predicted water and heat fluxes. The addition of SIF to this scheme slightly improved the estimation of m. Parameter estimates were coherent with the variability imposed by the fertilization and the seasonality of the grassland. Results revealed that fertilization had an impact on Vcmax, while no significant differences were found for m. The combination of RF, SIF and diel TIR data weakly constrained functional traits. Approaches not including GPP failed to estimate LAI; however GPP overestimated Cab in the dry period. These problems might be related to the presence of high fractions of senescent leaves in the grassland. The proposed inversion approach together with pattern-oriented model evaluation open new perspectives for the retrieval of plant functional traits relevant for land surface models, and can be utilized at various research sites where hyperspectral remote sensing imagery and eddy covariance flux measurements are simultaneously taken

    Evaluating the Performance of the SCOPE Model in Simulating Canopy Solar-Induced Chlorophyll Fluorescence

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    The SCOPE (soil canopy observation of photochemistry and energy fluxes) model has been widely used to interpret solar-induced chlorophyll fluorescence (SIF) and investigate the SIF-photosynthesis links at different temporal and spatial scales in recent years. In the SCOPE model, the fluorescence quantum efficiency in dark-adapted conditions (FQE) for Photosystem II (fqe2) and Photosystem I (fqe1) were two key parameters of SIF emission, which have always been parameterized as fixed values derived from laboratory measurements. To date, only a few studies have focused on evaluating the SCOPE model for SIF interpretation, and the variation of FQE values in the field remains controversial. In this study, the accuracy of the SCOPE model to simulate the canopy SIF was investigated using diurnal experiments on winter wheat. First, ten diurnal experiments were conducted on winter wheat, and the canopy SIF emissions and the SCOPE model’s input parameters were directly measured or indirectly retrieved from the spectral radiances, gross primary productivity (GPP) data, and meteorological records. Second, the SCOPE-simulated SIF emissions with fixed FQE values were evaluated using the observed canopy SIF data. The results show that the SCOPE model can reliably interpret the diurnal cycles of SIF variation and provide acceptable results of SIF simulations at the O2-B (SIFB) and O2-A (SIFA) bands with RRMSEs of 24.35% and 23.67%, respectively. However, the SCOPE-simulated SIFB and SIFA still contained large systematical deviations at some growth stages of wheat, and the seasonal cycles of the ratio between SIFB and SIFA (SIFA/SIFB) cannot be credibly reproduced. Finally, the SCOPE-simulated SIF emissions with variable FQE values were evaluated using the observed canopy SIF data. The simulating accuracy of SIFB and SIFA can be improved greatly using variable FQE values, and the SCOPE simulations track well with the seasonal SIFA/SIFB values with an RRMSE of 20.63%. The results indicated a clear seasonal pattern of FQE values for unbiased SIF simulation: from the erecting to the flowering stage of wheat, the ratio of fqe1 to fqe2 (fqe1/fqe2) gradually increased from 0.05–0.1 to 0.3–0.5, while the fqe2 value decreased from 0.013 to 0.007. Our quantitative results of the model assessment and the FQE adjustment support the use of the SCOPE model as a powerful tool for interpreting the SIF emissions and can serve as a significant reference for future applications of the SCOPE model

    Evaluating the Performance of the SCOPE Model in Simulating Canopy Solar-Induced Chlorophyll Fluorescence

    No full text
    The SCOPE (soil canopy observation of photochemistry and energy fluxes) model has been widely used to interpret solar-induced chlorophyll fluorescence (SIF) and investigate the SIF-photosynthesis links at different temporal and spatial scales in recent years. In the SCOPE model, the fluorescence quantum efficiency in dark-adapted conditions (FQE) for Photosystem II (fqe2) and Photosystem I (fqe1) were two key parameters of SIF emission, which have always been parameterized as fixed values derived from laboratory measurements. To date, only a few studies have focused on evaluating the SCOPE model for SIF interpretation, and the variation of FQE values in the field remains controversial. In this study, the accuracy of the SCOPE model to simulate the canopy SIF was investigated using diurnal experiments on winter wheat. First, ten diurnal experiments were conducted on winter wheat, and the canopy SIF emissions and the SCOPE model’s input parameters were directly measured or indirectly retrieved from the spectral radiances, gross primary productivity (GPP) data, and meteorological records. Second, the SCOPE-simulated SIF emissions with fixed FQE values were evaluated using the observed canopy SIF data. The results show that the SCOPE model can reliably interpret the diurnal cycles of SIF variation and provide acceptable results of SIF simulations at the O2-B (SIFB) and O2-A (SIFA) bands with RRMSEs of 24.35% and 23.67%, respectively. However, the SCOPE-simulated SIFB and SIFA still contained large systematical deviations at some growth stages of wheat, and the seasonal cycles of the ratio between SIFB and SIFA (SIFA/SIFB) cannot be credibly reproduced. Finally, the SCOPE-simulated SIF emissions with variable FQE values were evaluated using the observed canopy SIF data. The simulating accuracy of SIFB and SIFA can be improved greatly using variable FQE values, and the SCOPE simulations track well with the seasonal SIFA/SIFB values with an RRMSE of 20.63%. The results indicated a clear seasonal pattern of FQE values for unbiased SIF simulation: from the erecting to the flowering stage of wheat, the ratio of fqe1 to fqe2 (fqe1/fqe2) gradually increased from 0.05–0.1 to 0.3–0.5, while the fqe2 value decreased from 0.013 to 0.007. Our quantitative results of the model assessment and the FQE adjustment support the use of the SCOPE model as a powerful tool for interpreting the SIF emissions and can serve as a significant reference for future applications of the SCOPE model
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