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The physiological basis for estimating photosynthesis from Chla fluorescence.
Han, Jimei; Chang, Christine Y-Y; Gu, Lianhong; Zhang, Yongjiang; Meeker, Eliot W; Magney, Troy S; Walker, Anthony P; Wen, Jiaming; Kira, Oz; McNaull, Sarah; Sun, Ying.
  • Han J; School of Integrative Plant Science, Soil and Crop Science Section, Cornell University, Ithaca, NY, 14850, USA.
  • Chang CY; School of Integrative Plant Science, Soil and Crop Science Section, Cornell University, Ithaca, NY, 14850, USA.
  • Gu L; USDA, Agricultural Research Service, Adaptive Cropping Systems Laboratory, Beltsville, MD, 20705, USA.
  • Zhang Y; Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA.
  • Meeker EW; School of Biology and Ecology, University of Maine, Orono, ME, 04469, USA.
  • Magney TS; Department of Chemical Engineering, University of California, Davis, CA, 95616, USA.
  • Walker AP; Department of Plant Sciences, University of California, Davis, CA, 95616, USA.
  • Wen J; Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, TN, 37831, USA.
  • Kira O; School of Integrative Plant Science, Soil and Crop Science Section, Cornell University, Ithaca, NY, 14850, USA.
  • McNaull S; School of Integrative Plant Science, Soil and Crop Science Section, Cornell University, Ithaca, NY, 14850, USA.
  • Sun Y; Department of Civil and Environmental Engineering, Ben-Gurion University of the Negev, Negev, 8410501, Israel.
New Phytol ; 234(4): 1206-1219, 2022 05.
Article en En | MEDLINE | ID: mdl-35181903
ABSTRACT
Solar-induced Chl fluorescence (SIF) offers the potential to curb large uncertainties in the estimation of photosynthesis across biomes and climates, and at different spatiotemporal scales. However, it remains unclear how SIF should be used to mechanistically estimate photosynthesis. In this study, we built a quantitative framework for the estimation of photosynthesis, based on a mechanistic light reaction model with the Chla fluorescence of Photosystem II (SIFPSII ) as an input (MLR-SIF). Utilizing 29 C3 and C4 plant species that are representative of major plant biomes across the globe, we confirmed the validity of this framework at the leaf level. The MLR-SIF model is capable of accurately reproducing photosynthesis for all C3 and C4 species under diverse light, temperature, and CO2 conditions. We further tested the robustness of the MLR-SIF model using Monte Carlo simulations, and found that photosynthesis estimates were much less sensitive to parameter uncertainties relative to the conventional Farquhar, von Caemmerer, Berry (FvCB) model because of the additional independent information contained in SIFPSII . Once inferred from direct observables of SIF, SIFPSII provides 'parameter savings' to the MLR-SIF model, compared to the mechanistically equivalent FvCB model, and thus avoids the uncertainties arising as a result of imperfect model parameterization. Our findings set the stage for future efforts to employ SIF mechanistically to improve photosynthesis estimates across a variety of scales, functional groups, and environmental conditions.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Fotosíntesis / Clorofila Tipo de estudio: Prognostic_studies Idioma: En Año: 2022 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Fotosíntesis / Clorofila Tipo de estudio: Prognostic_studies Idioma: En Año: 2022 Tipo del documento: Article