A model for chlorophyll fluorescence and photosynthesis at leaf scale

Tol, Christiaan van der; Verhoef, W.; Rosema, A.

doi:10.1016/j.agrformet.2008.07.007

Cited by 173 publications

(118 citation statements)

References 30 publications

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“…In fact, there is an ongoing discussion about how sun-induced fluorescence can best be assimilated in existing model formulations to use it to constrain GPP across ecosystems and scales. According to our knowledge only the newest version of the SCOPE model provides an explicit fluorescence interface [48,49], as well as a modified version of the community land model 4 (CLM-4) [50]. Both models facilitate a diagnostic use of sun-induced fluorescence for a GPP assessment across ecosystems and scales.…”

Section: Discussionmentioning

confidence: 99%

Combining Sun-Induced Chlorophyll Fluorescence and Photochemical Reflectance Index Improves Diurnal Modeling of Gross Primary Productivity

et al. 2016

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Sun-induced chlorophyll fluorescence (F) is a novel remote sensing parameter providing an estimate of actual photosynthetic rates. A combination of this new observable and Monteith's light use efficiency (LUE) concept was suggested for an advanced modeling of gross primary productivity (GPP). In this demonstration study, we evaluate the potential of both F and the more commonly used photochemical reflectance index (PRI) to approximate the LUE term in Monteith's equation and eventually improve the forward modeling of GPP diurnals. Both F and the PRI were derived from ground and airborne based spectrometer measurements over two different crops. We demonstrate that approximating dynamic changes of LUE using F and PRI significantly improves the forward modeling of GPP diurnals. Especially in sugar beet, a changing photosynthetic efficiency during the day was traceable with F and incorporating F in the forward modeling significantly improved the estimation of GPP. Airborne data were projected to produce F and PRI maps for winter wheat and sugar beet fields over the course of one day. We detected a significant variability of both, F and the PRI within one field and particularly between fields. The variability of F and PRI was higher in sugar beet, which also showed a physiological down-regulation of leaf photosynthesis. Our results underline the potential of F to serve as a superior indicator for the actual efficiency of the photosynthetic machinery, which is linked to physiological responses of vegetation.

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Section: Discussionmentioning

confidence: 99%

Combining Sun-Induced Chlorophyll Fluorescence and Photochemical Reflectance Index Improves Diurnal Modeling of Gross Primary Productivity

et al. 2016

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“…SIF variations at the leaf level and at short time scales may reflect changes in LUE (Agati et al, 1995; Corp et al, 2003; Long & Bernacchi, 2003; van der Tol et al, 2009); however, it is less clear whether the signal seen by coarse satellite observations over longer term period (several days) reflects mainly changes in LUE. Indeed, it appears that most of the variability of the SIF signal at the ecosystem might be explained by APAR Ch , that is, the product of fPAR Ch and PAR, thus reflecting changes in canopy structure and light absorption (Badgley et al, 2017; Li et al, 2017), at least for the far‐red signal (Du et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Reconstructed Solar‐Induced Fluorescence: A Machine Learning Vegetation Product Based on MODIS Surface Reflectance to Reproduce GOME‐2 Solar‐Induced Fluorescence

Gentine

Alemohammad

2018

Geophysical Research Letters

108

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Solar‐induced fluorescence (SIF) observations from space have resulted in major advancements in estimating gross primary productivity (GPP). However, current SIF observations remain spatially coarse, infrequent, and noisy. Here we develop a machine learning approach using surface reflectances from Moderate Resolution Imaging Spectroradiometer (MODIS) channels to reproduce SIF normalized by clear sky surface irradiance from the Global Ozone Monitoring Experiment‐2 (GOME‐2). The resulting product is a proxy for ecosystem photosynthetically active radiation absorbed by chlorophyll (fAPARCh). Multiplying this new product with a MODIS estimate of photosynthetically active radiation provides a new MODIS‐only reconstruction of SIF called Reconstructed SIF (RSIF). RSIF exhibits much higher seasonal and interannual correlation than the original SIF when compared with eddy covariance estimates of GPP and two reference global GPP products, especially in dry and cold regions. RSIF also reproduces intense productivity regions such as the U.S. Corn Belt contrary to typical vegetation indices and similarly to SIF.

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“…Interestingly, biomes with lower SiF-GPP slopes have also lower correlation and in general this happens at higher LAI values, which should be investigated further. Analysing differences in the SiF-GPP relationships for different biomes requires advanced canopy and SiF modelling using radiative transfer models such as SCOPE [44,75]. By applying models, scalerelated issues can be identified and separated from biophysical factors.…”

Section: Comparing Far-red Sif With Gpp Derived From Australian Flux mentioning

confidence: 99%

“…The physiological relationships between SiF and GPP have been described in the literature (e.g., [44][45][46][47][48][49][50][51][52]). SiF is one of many quenching mechanisms that plants use to release excess energy.…”

Section: Introductionmentioning

confidence: 99%

Spaceborne Sun-Induced Vegetation Fluorescence Time Series from 2007 to 2015 Evaluated with Australian Flux Tower Measurements

et al. 2016

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A model for chlorophyll fluorescence and photosynthesis at leaf scale

Cited by 173 publications

References 30 publications

Combining Sun-Induced Chlorophyll Fluorescence and Photochemical Reflectance Index Improves Diurnal Modeling of Gross Primary Productivity

Combining Sun-Induced Chlorophyll Fluorescence and Photochemical Reflectance Index Improves Diurnal Modeling of Gross Primary Productivity

Reconstructed Solar‐Induced Fluorescence: A Machine Learning Vegetation Product Based on MODIS Surface Reflectance to Reproduce GOME‐2 Solar‐Induced Fluorescence

Spaceborne Sun-Induced Vegetation Fluorescence Time Series from 2007 to 2015 Evaluated with Australian Flux Tower Measurements

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