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Title: Chlorophyll Fluorescence Better Captures Seasonal and Interannual Gross Primary Productivity Dynamics Across Dryland Ecosystems of Southwestern North America

Abstract

Satellite remote sensing provides unmatched spatiotemporal information on vegetation gross primary productivity (GPP). Yet understanding of the relationship between GPP and remote sensing observations and how it changes with factors such as scale, biophysical constraint, and vegetation type remains limited. This knowledge gap is especially apparent for dryland ecosystems, which have characteristic high spatiotemporal variability and are under–represented by long–term field measurements. Here we utilize an eddy covariance (EC) data synthesis for southwestern North America in an assessment of how accurately satellite–derived vegetation proxies capture seasonal to interannual GPP dynamics across dryland gradients. We evaluate the enhanced vegetation index, solar–induced fluorescence (SIF), and the photochemical reflectivity index. We find evidence that SIF is more accurately capturing seasonal GPP dynamics particularly for evergreen–dominated EC sites and more accurately estimating the full magnitude of interannual GPP dynamics for all dryland EC sites. Furthermore, these results suggest that incorporation of SIF could significantly improve satellite–based GPP estimates.

Authors:
ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [2]; ORCiD logo [1];  [3]; ORCiD logo [3];  [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [4]
  1. Univ. of Arizona, Tucson, AZ (United States)
  2. USDA Agricultural Research Service, Tucson, AZ (United States)
  3. Univ. of Montana, Missoula, MT (United States)
  4. Univ. of New Mexico, Albuquerque, NM (United States)
Publication Date:
Research Org.:
Princeton Univ., NJ (United States)
Sponsoring Org.:
USDOE Office of Science (SC)
OSTI Identifier:
1537304
Grant/Contract Number:  
SC0016011
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Geophysical Research Letters
Additional Journal Information:
Journal Volume: 45; Journal Issue: 2; Journal ID: ISSN 0094-8276
Publisher:
American Geophysical Union
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES; geology; gross primary productivity; dryland vegetation dynamics; chlorophyll fluorescence; photochemical reflectivity index; enhanced vegetation index; satellite remote sensing

Citation Formats

Smith, W. K., Biederman, J. A., Scott, R. L., Moore, D. J. P., He, M., Kimball, J. S., Yan, D., Hudson, A., Barnes, M. L., MacBean, N., Fox, A. M., and Litvak, M. E. Chlorophyll Fluorescence Better Captures Seasonal and Interannual Gross Primary Productivity Dynamics Across Dryland Ecosystems of Southwestern North America. United States: N. p., 2018. Web. doi:10.1002/2017gl075922.
Smith, W. K., Biederman, J. A., Scott, R. L., Moore, D. J. P., He, M., Kimball, J. S., Yan, D., Hudson, A., Barnes, M. L., MacBean, N., Fox, A. M., & Litvak, M. E. Chlorophyll Fluorescence Better Captures Seasonal and Interannual Gross Primary Productivity Dynamics Across Dryland Ecosystems of Southwestern North America. United States. doi:10.1002/2017gl075922.
Smith, W. K., Biederman, J. A., Scott, R. L., Moore, D. J. P., He, M., Kimball, J. S., Yan, D., Hudson, A., Barnes, M. L., MacBean, N., Fox, A. M., and Litvak, M. E. Thu . "Chlorophyll Fluorescence Better Captures Seasonal and Interannual Gross Primary Productivity Dynamics Across Dryland Ecosystems of Southwestern North America". United States. doi:10.1002/2017gl075922. https://www.osti.gov/servlets/purl/1537304.
@article{osti_1537304,
title = {Chlorophyll Fluorescence Better Captures Seasonal and Interannual Gross Primary Productivity Dynamics Across Dryland Ecosystems of Southwestern North America},
author = {Smith, W. K. and Biederman, J. A. and Scott, R. L. and Moore, D. J. P. and He, M. and Kimball, J. S. and Yan, D. and Hudson, A. and Barnes, M. L. and MacBean, N. and Fox, A. M. and Litvak, M. E.},
abstractNote = {Satellite remote sensing provides unmatched spatiotemporal information on vegetation gross primary productivity (GPP). Yet understanding of the relationship between GPP and remote sensing observations and how it changes with factors such as scale, biophysical constraint, and vegetation type remains limited. This knowledge gap is especially apparent for dryland ecosystems, which have characteristic high spatiotemporal variability and are under–represented by long–term field measurements. Here we utilize an eddy covariance (EC) data synthesis for southwestern North America in an assessment of how accurately satellite–derived vegetation proxies capture seasonal to interannual GPP dynamics across dryland gradients. We evaluate the enhanced vegetation index, solar–induced fluorescence (SIF), and the photochemical reflectivity index. We find evidence that SIF is more accurately capturing seasonal GPP dynamics particularly for evergreen–dominated EC sites and more accurately estimating the full magnitude of interannual GPP dynamics for all dryland EC sites. Furthermore, these results suggest that incorporation of SIF could significantly improve satellite–based GPP estimates.},
doi = {10.1002/2017gl075922},
journal = {Geophysical Research Letters},
issn = {0094-8276},
number = 2,
volume = 45,
place = {United States},
year = {2018},
month = {1}
}

Journal Article:
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Cited by: 23 works
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Figures / Tables:

Figure 1 Figure 1: Multiscalemaps of the Southwest EC flux tower network. (a) View of the EC sites used in the analysis with regional mean MODIS EVI. (b) View of the cluster of flux tower sites in southeast Arizona. (c) View of the Santa Rita Mesquite (SRM) flux tower site within themore » southeast Arizona cluster. The white gridlines correspond to the pixels of SIFGOME2. The EC site marker colors in Figures 1a and 1b indicate subregional groupings of sites sharing similar seasonal climatic and ecological dynamics. Innermost and outermost circles around each flux tower site indicate the 3 km fine-resolution and 0.5° coarse-resolution EC footprints analyzed in this study. The colored points in Figure 1c correspond to the day of year of available SIFOCO2 observations for the year 2016, whereas the underlying tan color indicates areas classified as shrubland. For site codes and descriptions, see Table S1.« less

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