Global and time-resolved monitoring of crop photosynthesis with chlorophyll fluorescence
- Luis Guantera,1,2,
- Yongguang Zhanga,1,
- Martin Jungb,
- Joanna Joinerc,
- Maximilian Voigta,
- Joseph A. Berryd,
- Christian Frankenberge,
- Alfredo R. Huetef,
- Pablo Zarco-Tejadag,
- Jung-Eun Leeh,
- M. Susan Morani,
- Guillermo Ponce-Camposi,
- Christian Beerj,
- Gustavo Camps-Vallsk,
- Nina Buchmannl,
- Damiano Gianellem,
- Katja Klumppn,
- Alessandro Cescattio,
- John M. Bakerp, and
- Timothy J. Griffisq
- aInstitute for Space Sciences, Freie Universität Berlin, 12165 Berlin, Germany;
- bDepartment for Biogeochemical Systems, Max Planck Institute for Biogeochemistry, 07745 Jena, Germany;
- cLaboratory for Atmospheric Chemistry and Dynamics (Code 614) National Aeronautics and Space Administration Goddard Space Flight Center, Greenbelt, MD 20771;
- dDepartment of Global Ecology, Carnegie Institution for Science, Stanford, CA 94305;
- eJet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109;
- fPlant Functional Biology and Climate Change Cluster, University of Technology Sydney, Sydney, 2007, Australia;
- gInstituto de Agricultura Sostenible, Consejo Superior de Investigaciones Científicas, 14004 Córdoba, Spain;
- hGeological Sciences, Brown University, Providence, RI 02912;
- iSouthwest Watershed Research, Agricultural Research Service, US Department of Agriculture, Tucson, AZ 85719;
- jDepartment of Applied Environmental Science and Bolin Centre for Climate Research, Stockholm University, 10691 Stockholm, Sweden;
- kImage Processing Laboratory, Universitat de València, 46980 València, Spain;
- lAgricultural Sciences, Eidgenössiche Technische Hochschule Zurich, 8092 Zurich, Switzerland;
- mSustainable Agro-ecosystems and Bioresources Department, Research and Innovation Centre, Fondazione Edmund Mach, 38010 San Michele all'Adige, Italy;
- nGrassland Ecosystem Research Unit, Institut National de la Recherche Agronomique, Clermont-Ferrand, France 63122;
- oInstitute for Environment and Sustainability, Joint Research Centre, European Commission, 20127 Ispra, Italy;
- pSoil and Water Management Research, Agricultural Research Service, US Department of Agriculture, St. Paul, MN 55108; and
- qDepartment of Soil, Water, and Climate, University of Minnesota, St. Paul, MN 55108
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Edited by Gregory P. Asner, Carnegie Institution for Science, Stanford, CA, and approved February 25, 2014 (received for review October 24, 2013)
Significance
Global food and biofuel production and their vulnerability in a changing climate are of paramount societal importance. However, current global model predictions of crop photosynthesis are highly uncertain. Here we demonstrate that new space-based observations of chlorophyll fluorescence, an emission intrinsically linked to plant biochemistry, enable an accurate, global, and time-resolved measurement of crop photosynthesis, which is not possible from any other remote vegetation measurement. Our results show that chlorophyll fluorescence data can be used as a unique benchmark to improve our global models, thus providing more reliable projections of agricultural productivity and climate impact on crop yields. The enormous increase of the observational capabilities for fluorescence in the very near future strengthens the relevance of this study.
Abstract
Photosynthesis is the process by which plants harvest sunlight to produce sugars from carbon dioxide and water. It is the primary source of energy for all life on Earth; hence it is important to understand how this process responds to climate change and human impact. However, model-based estimates of gross primary production (GPP, output from photosynthesis) are highly uncertain, in particular over heavily managed agricultural areas. Recent advances in spectroscopy enable the space-based monitoring of sun-induced chlorophyll fluorescence (SIF) from terrestrial plants. Here we demonstrate that spaceborne SIF retrievals provide a direct measure of the GPP of cropland and grassland ecosystems. Such a strong link with crop photosynthesis is not evident for traditional remotely sensed vegetation indices, nor for more complex carbon cycle models. We use SIF observations to provide a global perspective on agricultural productivity. Our SIF-based crop GPP estimates are 50–75% higher than results from state-of-the-art carbon cycle models over, for example, the US Corn Belt and the Indo-Gangetic Plain, implying that current models severely underestimate the role of management. Our results indicate that SIF data can help us improve our global models for more accurate projections of agricultural productivity and climate impact on crop yields. Extension of our approach to other ecosystems, along with increased observational capabilities for SIF in the near future, holds the prospect of reducing uncertainties in the modeling of the current and future carbon cycle.
Footnotes
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↵1L.G. and Y.Z. contributed equally to this work.
- ↵2To whom correspondence should be addressed. E-mail: luis.guanter{at}wew.fu-berlin.de.
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Author contributions: L.G., Y.Z., M.J., and J.A.B. designed research; L.G., Y.Z., M.V., A.R.H., P.Z.-T., J.-E.L., M.S.M., and G.P.-C. performed research; L.G., Y.Z., M.J., J.J., C.B., G.C.-V., N.B., D.G., K.K., A.C., J.M.B., and T.J.G. contributed new reagents/analytic tools; L.G., Y.Z., J.J., M.V., and C.F. analyzed data; and L.G., Y.Z., J.A.B., C.F., and A.R.H. wrote the paper.
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The authors declare no conflict of interest.
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This article is a PNAS Direct Submission.
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This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1320008111/-/DCSupplemental.
