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Biogeosciences An interactive open-access journal of the European Geosciences Union
Journal topic
Preprints
https://doi.org/10.5194/bg-2020-41
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-2020-41
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  17 Feb 2020

17 Feb 2020

Review status
A revised version of this preprint was accepted for the journal BG and is expected to appear here in due course.

Decomposing reflectance spectra to track gross primary production in a subalpine evergreen forest

Rui Cheng1, Troy S. Magney1,11, Debsunder Dutta2,12, David R. Bowling3, Barry A. Logan4, Sean P. Burns5,6, Peter D. Blanken5, Katja Grossmann7,8, Sophia Lopez4, Andrew D. Richardson9, Jochen Stutz8,10, and Christian Frankenberg1,2 Rui Cheng et al.
  • 1Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA, USA
  • 2NASA Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
  • 3School of Biological Sciences, University of Utah, Salt Lake City, UT, USA
  • 4Department of Biology, Bowdoin College, Brunswick, ME, USA
  • 5Department of Geography, University of Colorado, Boulder, CO, USA
  • 6National Center for Atmospheric Research, Boulder, CO, USA
  • 7Institute of Environmental Physics, University of Heidelberg, Germany
  • 8Joint Institute for Regional Earth System Science and Engineering, University of California Los Angeles, Los Angeles, CA, USA
  • 9Center for Ecosystem Science and Society, and School of Informatics, Computing, and Cyber Systems, Northern Arizona University, AZ, USA
  • 10Department of Atmospheric and Oceanic Sciences, University of California Los Angeles, Los Angeles, CA, USA
  • 11Department of Plant Sciences, University of California, Davis, CA, USA
  • 12Department of Civil Engineering, Indian Institute of Science, Bangalore, India

Abstract. Photosynthesis by terrestrial plants represents the majority of CO2 uptake on Earth, yet it is difficult to measure directly from space. Estimating Gross Primary Production (GPP) from remote sensing indices is a primary source of uncertainty, in particular for observing seasonal variations in evergreen forests. Recent vegetation remote sensing techniques have highlighted spectral regions sensitive to dynamic changes in leaf/needle carotenoid composition, showing promise for tracking seasonal changes in photosynthesis of evergreen forests. However, continuous daily measurements of spectrally resolved canopy reflectance are limited in these ecosystems. To investigate this potential, we continuously measured vegetation reflectance (400–900 nm) using a canopy spectrometer system, PhotoSpec, mounted on top of an eddy-covariance flux tower in a subalpine evergreen forest at Niwot Ridge, Colorado, USA. We analyzed driving spectral components in the measured canopy reflectance using both statistical and process-based approaches. The decomposed spectral components relate directly to carotenoid pigments and co-vary seasonally with GPP, supporting the interpretation of the Photochemical Reflectance Index (PRI) and the Chlorophyll/Carotenoid Index (CCI). We show that using features from the entire 400–900 nm range show additional spectral changes near the red-egde but do not outperform the PRI or CCI indices for GPP predictions. In addition, we can quantitatively determine needle-scale chlorophyll to carotenoid ratios as well as anthocyanin contents using full spectrum inversions, both of which tightly correlated with seasonal GPP changes. Reconstructing GPP from vegetation reflectance using Partial Least Squares Regression (PLSR) explained approximately 87 % of the variability in observed GPP. Our results link the seasonal variation of reflectance to the pool size of photoprotective pigments, highlighting all spectral locations within 400–900 nm associated with GPP seasonality in evergreen forests.

Rui Cheng et al.

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Rui Cheng et al.

Rui Cheng et al.

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Short summary
We measured reflected sunlight from an evergreen canopy for a year to detect changes in pigments that play an important role in regulating the seasonality of photosynthesis. Results show a strong mechanistic link between spectral reflectance features and pigment content, which is validated using a biophysical model. Our results show spectrally-where, why, and when spectral features change over the course of the season and show promise for estimating photosynthesis remotely.
We measured reflected sunlight from an evergreen canopy for a year to detect changes in pigments...
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