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

Cheng, Rui and Magney, Troy S. and Dutta, Debsunder and Bowling, David R. and Logan, Barry A. and Burns, Sean P. and Blanken, Peter D. and Grossmann, Katja and Lopez, Sophia and Richardson, Andrew D. and Stutz, Jochen and Frankenberg, Christian (2020) Decomposing reflectance spectra to track gross primary production in a subalpine evergreen forest. Biogeosciences, 17 (18). pp. 4523-4544. ISSN 1726-4189. https://resolver.caltech.edu/CaltechAUTHORS:20210125-151645884

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Abstract

Photosynthesis by terrestrial plants represents the majority of CO₂ uptake on Earth, yet it is difficult to measure directly from space. Estimation of gross primary production (GPP) from remote sensing indices represents 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, these have mostly been investigated with intermittent field campaigns or with narrow-band spectrometers 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 co-varied with carotenoid content and GPP, supporting the interpretation of the photochemical reflectance index (PRI) and the chlorophyll/carotenoid index (CCI). Although the entire 400–900 nm range showed additional spectral changes near the red edge, it did not provide significant improvements in GPP predictions. We found little seasonal variation in both normalized difference vegetation index (NDVI) and the near-infrared vegetation index (NIRv) in this ecosystem. In addition, we quantitatively determined needle-scale chlorophyll-to-carotenoid ratios as well as anthocyanin contents using full-spectrum inversions, both of which were 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 linked the seasonal variation in reflectance to the pool size of photoprotective pigments, highlighting all spectral locations within 400–900 nm associated with GPP seasonality in evergreen forests.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.5194/bg-17-4523-2020DOIArticle
https://doi.org/10.5194/bg-17-4523-2020-supplementDOISupplement
https://doi.org/10.22002/D1.1597DOIData
https://doi.org/10.22002/d1.1231DOIData
https://github.com/CliMA/LandRelated ItemCode
ORCID:
AuthorORCID
Cheng, Rui0000-0002-3003-8339
Magney, Troy S.0000-0002-9033-0024
Dutta, Debsunder0000-0001-5727-1045
Bowling, David R.0000-0002-3864-4042
Burns, Sean P.0000-0002-6258-1838
Blanken, Peter D.0000-0002-7405-2220
Grossmann, Katja0000-0002-5154-197X
Richardson, Andrew D.0000-0002-0148-6714
Stutz, Jochen0000-0001-6368-7629
Frankenberg, Christian0000-0002-0546-5857
Additional Information:© Author(s) 2020. This work is distributed under the Creative Commons Attribution 4.0 License. Received: 6 February 2020 – Discussion started: 17 February 2020. Revised: 11 June 2020 – Accepted: 2 August 2020 – Published: 15 September 2020. We thank the sponsors from the Caltech Graduate First-year Fellowship for Rui Cheng and NASA Carbon Monitoring Systems program for David R. Bowling. The US-NR1 site is a part of the AmeriFlux Management Project (AMP). The National Center for Atmospheric Research (NCAR) is sponsored by the NSF. Our data presented in this paper are provided at https://doi.org/10.22002/D1.1597 (Cheng et al., 2020) and https://doi.org/10.22002/d1.1231 (Magney et al., 2019b). The PROSAIL model in the Julia programming language used in our study can be obtained from https://github.com/CliMA/Land (CliMA, 2020). Supplement. The supplement related to this article is available online at: https://doi.org/10.5194/bg-17-4523-2020-supplement. Author contributions. RC, TSM, DD, and CF designed research. RC, TSM, DD, DRB, BAL, SPB, PDB, KG, SL, ADR, JS, and CF performed data analyses. RC, TSM, DD, DRB, BAL, SPB, PDB, KG, SL, ADR, JS, and CF wrote the paper. The authors declare that they have no conflict of interest. This research has been supported by the NASA Carbon Monitoring Systems program (grant no. NNX16AP33G) and the DOE, Office of Science through the AmeriFlux Management Project (AMP) at Lawrence Berkeley National Laboratory (grant no. 7094866). Review statement. This paper was edited by Sönke Zaehle and reviewed by Shari Van Wittenberghe and one anonymous referee.
Funders:
Funding AgencyGrant Number
NASANNX16AP33G
Department of Energy (DOE)UNSPECIFIED
Lawrence Berkeley National Laboratory7094866
CaltechUNSPECIFIED
NSFUNSPECIFIED
Issue or Number:18
Record Number:CaltechAUTHORS:20210125-151645884
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20210125-151645884
Official Citation:Cheng, R., Magney, T. S., Dutta, D., Bowling, D. R., Logan, B. A., Burns, S. P., Blanken, P. D., Grossmann, K., Lopez, S., Richardson, A. D., Stutz, J., and Frankenberg, C.: Decomposing reflectance spectra to track gross primary production in a subalpine evergreen forest, Biogeosciences, 17, 4523–4544, https://doi.org/10.5194/bg-17-4523-2020, 2020
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:107717
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:26 Jan 2021 18:40
Last Modified:26 Jan 2021 18:40

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