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    Satellite solar-induced chlorophyll fluorescence and near-infrared reflectance capture complementary aspects of dryland vegetation productivity dynamics

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    Name:
    Manusript.pdf
    Embargo:
    2023-12-31
    Size:
    5.307Mb
    Format:
    PDF
    Description:
    Final Accepted Manuscript
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    Author
    Wang, Xian
    Biederman, Joel A.
    Knowles, John F.
    Scott, Russell L.
    Turner, Alexander J.
    Dannenberg, Matthew P.
    Köhler, Philipp cc
    Frankenberg, Christian
    Litvak, Marcy E.
    Flerchinger, Gerald N.
    Law, Beverly E.
    Kwon, Hyojung
    Reed, Sasha C.
    Parton, William J.
    Barron-Gafford, Greg A.
    Smith, William K.
    Show allShow less
    Affiliation
    School of Natural Resources and the Environment, University of Arizona
    School of Geography, Development and Environment, University of Arizona
    Issue Date
    2022-03
    Keywords
    Dryland heterogeneity
    Gross primary productivity
    Near-infrared reflectance
    Remote sensing
    Solar-induced fluorescence
    
    Metadata
    Show full item record
    Publisher
    Elsevier BV
    Citation
    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., & Smith, W. K. (2022). Satellite solar-induced chlorophyll fluorescence and near-infrared reflectance capture complementary aspects of dryland vegetation productivity dynamics. Remote Sensing of Environment, 270.
    Journal
    Remote Sensing of Environment
    Rights
    © 2021 Elsevier Inc. All rights reserved.
    Collection Information
    This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
    Abstract
    Mounting evidence indicates dryland ecosystems play an important role in driving the interannual variability and trend of the terrestrial carbon sink. Nevertheless, our understanding of the seasonal dynamics of dryland ecosystem carbon uptake through photosynthesis [gross primary productivity (GPP)] remains relatively limited due in part to the limited availability of long-term data and unique challenges associated with satellite remote sensing across dryland ecosystems. Here, we comprehensively evaluated longstanding and emerging satellite vegetation proxies in their ability to capture seasonal dryland GPP dynamics. Specifically, we evaluated: 1) reflectance-based proxies normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), near infrared reflectance index (NIRv), and kernel NDVI (kNDVI) from the MODerate resolution Imaging Spectroradiometer (MODIS); and 2) newly available physiologically-based proxy solar-induced chlorophyll fluorescence (SIF) from the TROPOspheric Monitoring Instrument (TROPOMI). As a performance benchmark, we used GPP estimates from a robust network of 21 western United States eddy covariance tower sites that span representative gradients in dryland ecosystem climate and functional composition. We found that NIRv and SIF were the best performing GPP proxies and captured complementary aspects of seasonal GPP dynamics across dryland ecosystem types. NIRv offered better performance than the other proxies across relatively low-productivity, sparsely non-evergreen vegetated sites (R2 = 0.59 ± 0.13); whereas SIF best captured seasonal dynamics across relatively high-productivity sites, including evergreen-dominated sites (R2 = 0.74 ± 0.07). Notably, across grass-dominated sites, all reflectance-based proxies (NDVI, SAVI, NIRv and kNDVI) showed significant seasonal bias (hysteresis) that strengthened with the total fraction of woody vegetation cover, likely due to seasonal patterns in woody vegetation reflectance that are unrelated to or decoupled from GPP. Future efforts to fully integrate the complementary strengths of NIRv and SIF could significantly improve our understanding and representation of dryland GPP dynamics in satellite-based models.
    Note
    24 month embargo; published online: 31 December 2021
    ISSN
    0034-4257
    DOI
    10.1016/j.rse.2021.112858
    Version
    Final accepted manuscript
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.rse.2021.112858
    Scopus Count
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    UA Faculty Publications

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