Articles | Volume 21, issue 5
https://doi.org/10.5194/bg-21-1259-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-21-1259-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data-based investigation of the effects of canopy structure and shadows on chlorophyll fluorescence in a deciduous oak forest
Hamadou Balde
CORRESPONDING AUTHOR
Laboratoire de Météorologie Dynamique, Sorbonne Université, IPSL, CNRS/L'École Polytechnique, 91128 Palaiseau, CEDEX, France
Ecologie Systématique et Evolution, Université Paris-Saclay, CNRS, AgroParisTech, 91190 Gif-sur-Yvette, France
Centre national d'études spatiales (CNES), 18 Av. Edouard Belin, 31400 Toulouse, France
ACRI-ST, 260 Route du Pin Montard, BP 234, 06904 Sophia Antipolis, France
Gabriel Hmimina
Laboratoire de Météorologie Dynamique, Sorbonne Université, IPSL, CNRS/L'École Polytechnique, 91128 Palaiseau, CEDEX, France
Yves Goulas
Laboratoire de Météorologie Dynamique, Sorbonne Université, IPSL, CNRS/L'École Polytechnique, 91128 Palaiseau, CEDEX, France
Gwendal Latouche
Ecologie Systématique et Evolution, Université Paris-Saclay, CNRS, AgroParisTech, 91190 Gif-sur-Yvette, France
Abderrahmane Ounis
Laboratoire de Météorologie Dynamique, Sorbonne Université, IPSL, CNRS/L'École Polytechnique, 91128 Palaiseau, CEDEX, France
Kamel Soudani
Ecologie Systématique et Evolution, Université Paris-Saclay, CNRS, AgroParisTech, 91190 Gif-sur-Yvette, France
Related authors
Hamadou Balde, Gabriel Hmimina, Yves Goulas, Gwendal Latouche, Abderrahmane Ounis, Daniel Berveiller, and Kamel Soudani
EGUsphere, https://doi.org/10.5194/egusphere-2024-657, https://doi.org/10.5194/egusphere-2024-657, 2024
Preprint archived
Short summary
Short summary
To understand the drivers of GPP and SIF changes and of their links, we examined how SIF and GPP changed at daily and seasonal scales considering canopy structure and abiotic conditions in a deciduous oak forest. The data show that leaf and canopy properties variations, seasonal cycle of PAR, and abiotic factors control not only SIF and GPP changes, but also their links. Further, during the heatwaves in 2022, we noticed that SIF was a proxy of GPP, while VIs were not.
Hamadou Balde, Gabriel Hmimina, Yves Goulas, Gwendal Latouche, and Kamel Soudani
Biogeosciences, 20, 1473–1490, https://doi.org/10.5194/bg-20-1473-2023, https://doi.org/10.5194/bg-20-1473-2023, 2023
Short summary
Short summary
This study focuses on the relationship between sun-induced chlorophyll fluorescence (SIF) and ecosystem gross primary productivity (GPP) across the ICOS European flux tower network. It shows that SIF, coupled with reflectance observations, explains over 80 % of the GPP variability across diverse ecosystems but fails to bring new information compared to reflectance alone at coarse spatial scales (~5 km). These findings have applications in agriculture and ecophysiological studies.
Arsène Druel, Julien Ruffault, Hendrik Davi, André Chanzy, Olivier Marloie, Miquel De Cáceres, Albert Olioso, Florent Mouillot, Christophe François, Kamel Soudani, and Nicolas K. Martin-StPaul
Biogeosciences, 22, 1–18, https://doi.org/10.5194/bg-22-1-2025, https://doi.org/10.5194/bg-22-1-2025, 2025
Short summary
Short summary
Accurate radiation data are essential for understanding ecosystem functions and dynamics. Traditional large-scale data lack the precision needed for complex terrain. This study introduces a new model, which accounts for sub-daily direct and diffuse radiation effects caused by terrain features, to enhance the radiation data resolution using elevation maps. Tested on a mountainous area, this method significantly improved radiation estimates, benefiting predictions of forest functions.
Hamadou Balde, Gabriel Hmimina, Yves Goulas, Gwendal Latouche, Abderrahmane Ounis, Daniel Berveiller, and Kamel Soudani
EGUsphere, https://doi.org/10.5194/egusphere-2024-657, https://doi.org/10.5194/egusphere-2024-657, 2024
Preprint archived
Short summary
Short summary
To understand the drivers of GPP and SIF changes and of their links, we examined how SIF and GPP changed at daily and seasonal scales considering canopy structure and abiotic conditions in a deciduous oak forest. The data show that leaf and canopy properties variations, seasonal cycle of PAR, and abiotic factors control not only SIF and GPP changes, but also their links. Further, during the heatwaves in 2022, we noticed that SIF was a proxy of GPP, while VIs were not.
Hamadou Balde, Gabriel Hmimina, Yves Goulas, Gwendal Latouche, and Kamel Soudani
Biogeosciences, 20, 1473–1490, https://doi.org/10.5194/bg-20-1473-2023, https://doi.org/10.5194/bg-20-1473-2023, 2023
Short summary
Short summary
This study focuses on the relationship between sun-induced chlorophyll fluorescence (SIF) and ecosystem gross primary productivity (GPP) across the ICOS European flux tower network. It shows that SIF, coupled with reflectance observations, explains over 80 % of the GPP variability across diverse ecosystems but fails to bring new information compared to reflectance alone at coarse spatial scales (~5 km). These findings have applications in agriculture and ecophysiological studies.
Kamel Soudani, Nicolas Delpierre, Daniel Berveiller, Gabriel Hmimina, Jean-Yves Pontailler, Lou Seureau, Gaëlle Vincent, and Éric Dufrêne
Biogeosciences, 18, 3391–3408, https://doi.org/10.5194/bg-18-3391-2021, https://doi.org/10.5194/bg-18-3391-2021, 2021
Short summary
Short summary
We present an exhaustive comparative survey of eight proximal methods to estimate forest phenology. We focused on methodological aspects and thoroughly assessed deviations between predicted and observed phenological dates and pointed out their main causes. We show that proximal methods provide robust phenological metrics. They can be used to retrieve long-term phenological series at flux measurement sites and help interpret the interannual variability and trends of mass and energy exchanges.
Jan Pisek, Angela Erb, Lauri Korhonen, Tobias Biermann, Arnaud Carrara, Edoardo Cremonese, Matthias Cuntz, Silvano Fares, Giacomo Gerosa, Thomas Grünwald, Niklas Hase, Michal Heliasz, Andreas Ibrom, Alexander Knohl, Johannes Kobler, Bart Kruijt, Holger Lange, Leena Leppänen, Jean-Marc Limousin, Francisco Ramon Lopez Serrano, Denis Loustau, Petr Lukeš, Lars Lundin, Riccardo Marzuoli, Meelis Mölder, Leonardo Montagnani, Johan Neirynck, Matthias Peichl, Corinna Rebmann, Eva Rubio, Margarida Santos-Reis, Crystal Schaaf, Marius Schmidt, Guillaume Simioni, Kamel Soudani, and Caroline Vincke
Biogeosciences, 18, 621–635, https://doi.org/10.5194/bg-18-621-2021, https://doi.org/10.5194/bg-18-621-2021, 2021
Short summary
Short summary
Understory vegetation is the most diverse, least understood component of forests worldwide. Understory communities are important drivers of overstory succession and nutrient cycling. Multi-angle remote sensing enables us to describe surface properties by means that are not possible when using mono-angle data. Evaluated over an extensive set of forest ecosystem experimental sites in Europe, our reported method can deliver good retrievals, especially over different forest types with open canopies.
Cited articles
Aasen, H., Van Wittenberghe, S., Sabater Medina, N., Damm, A., Goulas, Y., Wieneke, S., Hueni, A., Malenovský, Z., Alonso, L., Pacheco-Labrador, J., Cendrero-Mateo, M. P., Tomelleri, E., Burkart, A., Cogliati, S., Rascher, U., and Mac Arthur, A.: Sun-Induced Chlorophyll Fluorescence II: Review of Passive Measurement Setups, Protocols, and Their Application at the Leaf to Canopy Level, Remote Sens., 11, 927, https://doi.org/10.3390/rs11080927, 2019.
Badgley, G., Field, C. B., and Berry, J. A.: Canopy near-infrared reflectance and terrestrial photosynthesis, Sci. Adv., 3, e1602244, https://doi.org/10.1126/sciadv.1602244, 2017.
Baker, N. R.: Chlorophyll Fluorescence: A Probe of Photosynthesis In Vivo, Ann. Rev. Plant Biol., 59, 89–113, https://doi.org/10.1146/annurev.arplant.59.032607.092759, 2008.
Balde, H., Hmimina, G., Goulas, Y., Latouche, G., and Soudani, K.: Synergy between TROPOMI sun-induced chlorophyll fluorescence and MODIS spectral reflectance for understanding the dynamics of gross primary productivity at Integrated Carbon Observatory System (ICOS) ecosystem flux sites, Biogeosciences, 20, 1473–1490, https://doi.org/10.5194/bg-20-1473-2023, 2023.
Biriukova, K., Pacheco-Labrador, J., Migliavacca, M., Mahecha, M. D., Gonzalez-Cascon, R., Martín, M. P., and Rossini, M.: Performance of Singular Spectrum Analysis in Separating Seasonal and Fast Physiological Dynamics of Solar-Induced Chlorophyll Fluorescence and PRI Optical Signals, J. Geophys. Res.-Biogeo., 126, e2020JG006158, https://doi.org/10.1029/2020JG006158, 2021.
Breiman, L.: Random Forests, Mach. Learn., 45, 5–32, https://doi.org/10.1023/A:1010933404324, 2001.
Campbell, P., Huemmrich, K., Middleton, E., Ward, L., Julitta, T., Daughtry, C., Burkart, A., Russ, A., and Kustas, W.: Diurnal and Seasonal Variations in Chlorophyll Fluorescence Associated with Photosynthesis at Leaf and Canopy Scales, Remote Sens., 11, 488, https://doi.org/10.3390/rs11050488, 2019.
Chang, C. Y., Wen, J., Han, J., Kira, O., LeVonne, J., Melkonian, J., Riha, S. J., Skovira, J., Ng, S., Gu, L., Wood, J. D., Näthe, P., and Sun, Y.: Unpacking the drivers of diurnal dynamics of sun-induced chlorophyll fluorescence (SIF): Canopy structure, plant physiology, instrument configuration and retrieval methods, Remote Sens. Environ., 265, 112672, https://doi.org/10.1016/j.rse.2021.112672, 2021.
Cogliati, S., Verhoef, W., Kraft, S., Sabater, N., Alonso, L., Vicent, J., Moreno, J., Drusch, M., and Colombo, R.: Retrieval of sun-induced fluorescence using advanced spectral fitting methods, Remote Sens. Environ., 169, 344–357, https://doi.org/10.1016/j.rse.2015.08.022, 2015.
Damm, A., Guanter, L., Paul-Limoges, E., van der Tol, C., Hueni, A., Buchmann, N., Eugster, W., Ammann, C., and Schaepman, M. E.: Far-red sun-induced chlorophyll fluorescence shows ecosystem-specific relationships to gross primary production: An assessment based on observational and modeling approaches, Remote Sens. Environ., 166, 91–105, https://doi.org/10.1016/j.rse.2015.06.004, 2015.
Daumard, F., Goulas, Y., Champagne, S., Fournier, A., Ounis, A., Olioso, A., and Moya, I.: Continuous Monitoring of Canopy Level Sun-Induced Chlorophyll Fluorescence During the Growth of a Sorghum Field, IEEE Trans. Geosci. Remote Sens., 50, 4292–4300, https://doi.org/10.1109/TGRS.2012.2193131, 2012.
De Cannière, S., Vereecken, H., Defourny, P., and Jonard, F.: Remote Sensing of Instantaneous Drought Stress at Canopy Level Using Sun-Induced Chlorophyll Fluorescence and Canopy Reflectance, Remote Sens., 14, 2642, https://doi.org/10.3390/rs14112642, 2022.
Dechant, B., Ryu, Y., Badgley, G., Zeng, Y., Berry, J. A., Zhang, Y., Goulas, Y., Li, Z., Zhang, Q., Kang, M., Li, J., and Moya, I.: Canopy structure explains the relationship between photosynthesis and sun-induced chlorophyll fluorescence in crops, Remote Sens. Environ., 241, 111733, https://doi.org/10.1016/j.rse.2020.111733, 2020.
Dechant, B., Ryu, Y., Badgley, G., Köhler, P., Rascher, U., Migliavacca, M., Zhang, Y., Tagliabue, G., Guan, K., Rossini, M., Goulas, Y., Zeng, Y., Frankenberg, C., and Berry, J. A.: NIRVP: A robust structural proxy for sun-induced chlorophyll fluorescence and photosynthesis across scales, Remote Sens. Environ., 268, 112763, https://doi.org/10.1016/j.rse.2021.112763, 2022.
Delpierre, N., Berveiller, D., Granda, E., and Dufrêne, E.: Wood phenology, not carbon input, controls the interannual variability of wood growth in a temperate oak forest, New Phytol., 210, 459–470, https://doi.org/10.1111/nph.13771, 2016.
Drusch, M., Moreno, J., Del Bello, U., Franco, R., Goulas, Y., Huth, A., Kraft, S., Middleton, E. M., Miglietta, F., Mohammed, G., Nedbal, L., Rascher, U., Schuttemeyer, D., and Verhoef, W.: The FLuorescence EXplorer Mission Concept – ESA's Earth Explorer 8, IEEE Trans. Geosci. Remote Sens., 55, 1273–1284, https://doi.org/10.1109/TGRS.2016.2621820, 2017.
Frankenberg, C., Fisher, J. B., Worden, J., Badgley, G., Saatchi, S. S., Lee, J.-E., Toon, G. C., Butz, A., Jung, M., Kuze, A., and Yokota, T.: New global observations of the terrestrial carbon cycle from GOSAT: Patterns of plant fluorescence with gross primary productivity: CHLOROPHYLL FLUORESCENCE FROM SPACE, Geophys. Res. Lett., 38, L17706, https://doi.org/10.1029/2011GL048738, 2011.
Gao, S., Huete, A., Kobayashi, H., Doody, T. M., Liu, W., Wang, Y., Zhang, Y., and Lu, X.: Simulation of solar-induced chlorophyll fluorescence in a heterogeneous forest using 3-D radiative transfer modelling and airborne LiDAR, ISPRS J. Photogramm. Remote Sens., 191, 1–17, https://doi.org/10.1016/j.isprsjprs.2022.07.004, 2022.
Goulas, Y., Fournier, A., Daumard, F., Champagne, S., Ounis, A., Marloie, O., and Moya, I.: Gross Primary Production of a Wheat Canopy Relates Stronger to Far Red Than to Red Solar-Induced Chlorophyll Fluorescence, Remote Sens., 9, 97, https://doi.org/10.3390/rs9010097, 2017.
Guanter, L., Zhang, Y., Jung, M., Joiner, J., Voigt, M., Berry, J. A., Frankenberg, C., Huete, A. R., Zarco-Tejada, P., Lee, J.-E., Moran, M. S., Ponce-Campos, G., Beer, C., Camps-Valls, G., Buchmann, N., Gianelle, D., Klumpp, K., Cescatti, A., Baker, J. M., and Griffis, T. J.: Global and time-resolved monitoring of crop photosynthesis with chlorophyll fluorescence, P. Natl. Acad. Sci. USA, 111, E1327–E1333, https://doi.org/10.1073/pnas.1320008111, 2014.
He, L., Magney, T., Dutta, D., Yin, Y., Köhler, P., Grossmann, K., Stutz, J., Dold, C., Hatfield, J., Guan, K., Peng, B., and Frankenberg, C.: From the Ground to Space: Using Solar-Induced Chlorophyll Fluorescence to Estimate Crop Productivity, Geophys. Res. Lett., 47, e2020GL087474, https://doi.org/10.1029/2020GL087474, 2020.
Jonard, F., De Cannière, S., Brüggemann, N., Gentine, P., Short Gianotti, D. J., Lobet, G., Miralles, D. G., Montzka, C., Pagán, B. R., Rascher, U., and Vereecken, H.: Value of sun-induced chlorophyll fluorescence for quantifying hydrological states and fluxes: Current status and challenges, Agr. Forest Meteorol., 291, 108088, https://doi.org/10.1016/j.agrformet.2020.108088, 2020.
Li, X. and Xiao, J.: TROPOMI observations allow for robust exploration of the relationship between solar-induced chlorophyll fluorescence and terrestrial gross primary production, Remote Sens. Environ., 268, 112748, https://doi.org/10.1016/j.rse.2021.112748, 2022.
Li, Z., Zhang, Q., Li, J., Yang, X., Wu, Y., Zhang, Z., Wang, S., Wang, H., and Zhang, Y.: Solar-induced chlorophyll fluorescence and its link to canopy photosynthesis in maize from continuous ground measurements, Remote Sens. Environ., 236, 111420, https://doi.org/10.1016/j.rse.2019.111420, 2020.
Lin, J., Shen, Q., Wu, J., Zhao, W., and Liu, L.: Assessing the Potential of Downscaled Far Red Solar-Induced Chlorophyll Fluorescence from the Canopy to Leaf Level for Drought Monitoring in Winter Wheat, Remote Sens., 14, 1357, https://doi.org/10.3390/rs14061357, 2022.
Liu, Y., Chen, J. M., He, L., Zhang, Z., Wang, R., Rogers, C., Fan, W., de Oliveira, G., and Xie, X.: Non-linearity between gross primary productivity and far-red solar-induced chlorophyll fluorescence emitted from canopies of major biomes, Remote Sens. Environ., 271, 112896, https://doi.org/10.1016/j.rse.2022.112896, 2022.
Loayza, H., Moya, I., Quiroz, R., Ounis, A., and Goulas, Y.: Active and passive chlorophyll fluorescence measurements at canopy level on potato crops. Evidence of similitude of diurnal cycles of apparent fluorescence yields, Photos. Res., 155, 271–288, https://doi.org/10.1007/s11120-022-00995-8, 2023.
Lopez Gonzalez, M. d. l. L.: Seguimiento del estrés hídrico en la vid mediante técnicas de fluorescencia de la clorofila y otros métodos ópticos, Thesis, Universidad de Castilla-La-Mancha, Albacete, https://ruidera.uclm.es/items/38a54238-b996-4d8f-8076-ada1630f4073 (last access: 9 March 2024), 2015.
Lu, X., Liu, Z., Zhao, F., and Tang, J.: Comparison of total emitted solar-induced chlorophyll fluorescence (SIF) and top-of-canopy (TOC) SIF in estimating photosynthesis, Remote Sens. Environ., 251, 112083, https://doi.org/10.1016/j.rse.2020.112083, 2020.
Magney, T. S., Frankenberg, C., Fisher, J. B., Sun, Y., North, G. B., Davis, T. S., Kornfeld, A., and Siebke, K.: Connecting active to passive fluorescence with photosynthesis: a method for evaluating remote sensing measurements of Chl fluorescence, New Phytol., 215, 1594–1608, https://doi.org/10.1111/nph.14662, 2017.
Maysonnave, J., Delpierre, N., François, C., Jourdan, M., Cornut, I., Bazot, S., Vincent, G., Morfin, A., and Berveiller, D.: Contribution of deep soil layers to the transpiration of a temperate deciduous forest: quantification and implications for the modelling of productivity, Ecology, bioRxiv 2022.02.14.480025, https://doi.org/10.1101/2022.02.14.480025, 2022.
Mengistu, A. G., Mengistu Tsidu, G., Koren, G., Kooreman, M. L., Boersma, K. F., Tagesson, T., Ardö, J., Nouvellon, Y., and Peters, W.: Sun-induced fluorescence and near-infrared reflectance of vegetation track the seasonal dynamics of gross primary production over Africa, Biogeosciences, 18, 2843–2857, https://doi.org/10.5194/bg-18-2843-2021, 2021.
Meroni, M., Rossini, M., Guanter, L., Alonso, L., Rascher, U., Colombo, R., and Moreno, J.: Remote sensing of solar-induced chlorophyll fluorescence: Review of methods and applications, Remote Sens. Environ., 113, 2037–2051, https://doi.org/10.1016/j.rse.2009.05.003, 2009.
Miao, G., Guan, K., Suyker, A. E., Yang, X., Arkebauer, T. J., Walter-Shea, E. A., Kimm, H., Hmimina, G. Y., Gamon, J. A., Franz, T. E., Frankenberg, C., Berry, J. A., and Wu, G.: Varying Contributions of Drivers to the Relationship Between Canopy Photosynthesis and Far-Red Sun-Induced Fluorescence for Two Maize Sites at Different Temporal Scales, J. Geophys. Res.-Biogeo., 125, e2019JG005051, https://doi.org/10.1029/2019JG005051, 2020.
Morozumi, T., Kato, T., Kobayashi, H., Sakai, Y., Tsujimoto, K., Nakashima, N., Buareal, K., Lan, W., and Ninomiya, H.: Row orientation influences the diurnal cycle of solar-induced chlorophyll fluorescence emission from wheat canopy, as demonstrated by radiative transfer modeling, Agr. Forest Meteorol., 339, 109576, https://doi.org/10.1016/j.agrformet.2023.109576, 2023.
Moya, I., Loayza, H., López, M. L., Quiroz, R., Ounis, A., and Goulas, Y.: Canopy chlorophyll fluorescence applied to stress detection using an easy-to-build micro-lidar, Photosynth. Res., 142, 1–15, https://doi.org/10.1007/s11120-019-00642-9, 2019.
Nichol, C. J., Drolet, G., Porcar-Castell, A., Wade, T., Sabater, N., Middleton, E. M., MacLellan, C., Levula, J., Mammarella, I., Vesala, T., and Atherton, J.: Diurnal and Seasonal Solar Induced Chlorophyll Fluorescence and Photosynthesis in a Boreal Scots Pine Canopy, Remote Sens., 11, 273, https://doi.org/10.3390/rs11030273, 2019.
Ounis, A., Evain, S., Flexas, J., Tosti, S., and Moya, I.: Adaptation of a PAM-fluorometer for remote sensing of chlorophyll fluorescence, Photosyn. Res., 68, 113–120, https://doi.org/10.1023/A:1011843131298, 2001.
Ounis, A., Bach, J., Mahjoub, A., Daumard, F., Moya, I., and Goulas, Y.: Combined use of LIDAR and hyperspectral measurements for remote sensing of fluorescence and vertical profile of canopies, Rev. Teledetec., 87, 87–94, https://doi.org/10.4995/raet.2015.3982, 2016.
Paul-Limoges, E., Damm, A., Hueni, A., Liebisch, F., Eugster, W., Schaepman, M. E., and Buchmann, N.: Effect of environmental conditions on sun-induced fluorescence in a mixed forest and a cropland, Remote Sens. Environ., 219, 310–323, https://doi.org/10.1016/j.rse.2018.10.018, 2018.
Porcar-Castell, A., Tyystjärvi, E., Atherton, J., van der Tol, C., Flexas, J., Pfündel, E. E., Moreno, J., Frankenberg, C., and Berry, J. A.: Linking chlorophyll a fluorescence to photosynthesis for remote sensing applications: mechanisms and challenges, J. Exp. Bot., 65, 4065–4095, https://doi.org/10.1093/jxb/eru191, 2014.
Rascher, U., Alonso, L., Burkart, A., Cilia, C., Cogliati, S., Colombo, R., Damm, A., Drusch, M., Guanter, L., Hanus, J., Hyvärinen, T., Julitta, T., Jussila, J., Kataja, K., Kokkalis, P., Kraft, S., Kraska, T., Matveeva, M., Moreno, J., Muller, O., Panigada, C., Pikl, M., Pinto, F., Prey, L., Pude, R., Rossini, M., Schickling, A., Schurr, U., Schüttemeyer, D., Verrelst, J., and Zemek, F.: Sun-induced fluorescence – a new probe of photosynthesis: First maps from the imaging spectrometer HyPlant, Glob. Change Biol., 21, 4673–4684, https://doi.org/10.1111/gcb.13017, 2015.
Soudani, K., Hmimina, G., Dufrêne, E., Berveiller, D., Delpierre, N., Ourcival, J.-M., Rambal, S., and Joffre, R.: Relationships between photochemical reflectance index and light-use efficiency in deciduous and evergreen broadleaf forests, Remote Sens. Environ., 144, 73–84, https://doi.org/10.1016/j.rse.2014.01.017, 2014.
Soudani, K., Delpierre, N., Berveiller, D., Hmimina, G., Pontailler, J.-Y., Seureau, L., Vincent, G., and Dufrêne, É.: A survey of proximal methods for monitoring leaf phenology in temperate deciduous forests, Biogeosciences, 18, 3391–3408, https://doi.org/10.5194/bg-18-3391-2021, 2021.
Sun, Y., Gu, L., Wen, J., van der Tol, C., Porcar-Castell, A., Joiner, J., Chang, C. Y., Magney, T., Wang, L., Hu, L., Rascher, U., Zarco-Tejada, P., Barrett, C. B., Lai, J., Han, J., and Luo, Z.: From remotely sensed solar-induced chlorophyll fluorescence to ecosystem structure, function, and service: Part I – Harnessing theory, Glob. Change Biol., 29, 2926–2952, https://doi.org/10.1111/gcb.16634, 2023a.
Sun, Y., Wen, J., Gu, L., Joiner, J., Chang, C. Y., van der Tol, C., Porcar-Castell, A., Magney, T., Wang, L., Hu, L., Rascher, U., Zarco-Tejada, P., Barrett, C. B., Lai, J., Han, J., and Luo, Z.: From remotely-sensed solar-induced chlorophyll fluorescence to ecosystem structure, function, and service: Part II – Harnessing data, Glob. Change Biol., 29, 2893–2925, https://doi.org/10.1111/gcb.16646, 2023b.
Ustin, S. L. and Middleton, E. M.: Current and near-term advances in Earth observation for ecological applications, Ecol. Process., 10, 1–57, https://doi.org/10.1186/s13717-020-00255-4, 2021.
Verma, M., Schimel, D., Evans, B., Frankenberg, C., Beringer, J., Drewry, D. T., Magney, T., Marang, I., Hutley, L., Moore, C., and Eldering, A.: Effect of environmental conditions on the relationship between solar-induced fluorescence and gross primary productivity at an OzFlux grassland site: OCO SIF, MODIS, and GPP, J. Geophys. Res.-Biogeo., 122, 716–733, https://doi.org/10.1002/2016JG003580, 2017.
Wang, N., Suomalainen, J., Bartholomeus, H., Kooistra, L., Masiliūnas, D., and Clevers, J. G. P. W.: Diurnal variation of sun-induced chlorophyll fluorescence of agricultural crops observed from a point-based spectrometer on a UAV, Int. J. Appl. Earth Obs., 96, 102276, https://doi.org/10.1016/j.jag.2020.102276, 2021.
Wang, X., Biederman, J. A., Knowles, J. F., Scott, R. L., Turner, A. J., Dannenberg, M. P., Köhler, P., Frankenberg, C., Litvak, M. E., Flerchinger, G. N., Law, B. E., Kwon, H., Reed, S. C., Parton, W. J., Barron-Gafford, G. A., and Smith, W. K.: Satellite solar-induced chlorophyll fluorescence and near-infrared reflectance capture complementary aspects of dryland vegetation productivity dynamics, Remote Sens. Environ., 270, 112858, https://doi.org/10.1016/j.rse.2021.112858, 2022.
Wood, J. D., Griffis, T. J., Baker, J. M., Frankenberg, C., Verma, M., and Yuen, K.: Multiscale analyses of solar-induced florescence and gross primary production: Multiscale GPP-SIF RELATIONS, Geophys. Res. Lett., 44, 533–541, https://doi.org/10.1002/2016GL070775, 2017.
Xu, S., Atherton, J., Riikonen, A., Zhang, C., Oivukkamäki, J., MacArthur, A., Honkavaara, E., Hakala, T., Koivumäki, N., Liu, Z., and Porcar-Castell, A.: Structural and photosynthetic dynamics mediate the response of SIF to water stress in a potato crop, Remote Sens. Environ., 263, 112555, https://doi.org/10.1016/j.rse.2021.112555, 2021.
Yang, H., Yang, X., Zhang, Y., Heskel, M. A., Lu, X., Munger, J. W., Sun, S., and Tang, J.: Chlorophyll fluorescence tracks seasonal variations of photosynthesis from leaf to canopy in a temperate forest, Glob. Change Biol., 23, 2874–2886, https://doi.org/10.1111/gcb.13590, 2017.
Yang, P. and van der Tol, C.: Linking canopy scattering of far-red sun-induced chlorophyll fluorescence with reflectance, Remote Sens. Environ., 209, 456–467, https://doi.org/10.1016/j.rse.2018.02.029, 2018.
Yang, P., van der Tol, C., Campbell, P. K. E., and Middleton, E. M.: Fluorescence Correction Vegetation Index (FCVI): A physically based reflectance index to separate physiological and non-physiological information in far-red sun-induced chlorophyll fluorescence, Remote Sens. Environ., 240, 111676, https://doi.org/10.1016/j.rse.2020.111676, 2020.
Yazbeck, T., Bohrer, G., Gentine, P., Ye, L., Arriga, N., Bernhofer, C., Blanken, P. D., Desai, A. R., Durden, D., Knohl, A., Kowalska, N., Metzger, S., Mölder, M., Noormets, A., Novick, K., Scott, R. L., Šigut, L., Soudani, K., Ueyama, M., and Varlagin, A.: Site Characteristics Mediate the Relationship Between Forest Productivity and Satellite Measured Solar Induced Fluorescence, Front. For. Glob. Change, 4, 695269, https://doi.org/10.3389/ffgc.2021.695269, 2021.
Zeng, Y., Badgley, G., Dechant, B., Ryu, Y., Chen, M., and Berry, J. A.: A practical approach for estimating the escape ratio of near-infrared solar-induced chlorophyll fluorescence, Remote Sens. Environ., 232, 111209, https://doi.org/10.1016/j.rse.2019.05.028, 2019.
Zeng, Y., Chen, M., Hao, D., Damm, A., Badgley, G., Rascher, U., Johnson, J. E., Dechant, B., Siegmann, B., Ryu, Y., Qiu, H., Krieger, V., Panigada, C., Celesti, M., Miglietta, F., Yang, X., and Berry, J. A.: Combining near-infrared radiance of vegetation and fluorescence spectroscopy to detect effects of abiotic changes and stresses, Remote Sens. Environ., 270, 112856, https://doi.org/10.1016/j.rse.2021.112856, 2022a.
Zeng, Y., Hao, D., Huete, A., Dechant, B., Berry, J., Chen, J. M., Joiner, J., Frankenberg, C., Bond-Lamberty, B., Ryu, Y., Xiao, J., Asrar, G. R., and Chen, M.: Optical vegetation indices for monitoring terrestrial ecosystems globally, Nat. Rev. Earth Environ., 3, 477–493, https://doi.org/10.1038/s43017-022-00298-5, 2022b.
Zhang, Y., Zhang, Q., Liu, L., Zhang, Y., Wang, S., Ju, W., Zhou, G., Zhou, L., Tang, J., Zhu, X., Wang, F., Huang, Y., Zhang, Z., Qiu, B., Zhang, X., Wang, S., Huang, C., Tang, X., and Zhang, J.: ChinaSpec: a Network for Long-term Ground-based Measurements of Solar-induced Fluorescence in China, J. Geophys. Res.-Biogeo., 126, e2020JG006042, https://doi.org/10.1029/2020JG006042, 2021.
Zhang, Z. and Zhang, Y.: Solar angle matters: Diurnal pattern of solar-induced chlorophyll fluorescence from OCO-3 and TROPOMI, Remote Sens. Environ., 285, 113380, https://doi.org/10.1016/j.rse.2022.113380, 2023.
Short summary
We show that FyieldLIF was not correlated with SIFy at the diurnal timescale, and the diurnal patterns in SIF and PAR did not match under clear-sky conditions due to canopy structure. Φk was sensitive to canopy structure. RF models show that Φk can be predicted using reflectance in different bands. RF models also show that FyieldLIF was more sensitive to reflectance and radiation than SIF and SIFy, indicating that the combined effect of reflectance bands could hide the SIF physiological trait.
We show that FyieldLIF was not correlated with SIFy at the diurnal timescale, and the diurnal...
Altmetrics
Final-revised paper
Preprint