This research was funded by the NASA Carbon Monitoring Systems program Award 80NSSC20K0010 and the National Science Foundation Graduate Research Fellowship Program Award #2139322. Additional funding was provided by the US National Science Foundation Macrosystems Biology and NEON-Enabled Science (Award 1926090) and Division of Environmental Biology (Award 1929709) programs.
Satellite-based solar-induced fluorescence tracks seasonal and elevational patterns of photosynthesis in California's Sierra Nevada mountains
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1.
University of Utah
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2.
National Center for Atmospheric Research
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3.
California Institute of Technology
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4.
Jet Propulsion Lab
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European Organisation for the Exploitation of Meteorological Satellites
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6.
Massachusetts Institute of Technology
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University of California, Irvine
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Max Planck Institute for Biogeochemistry
Abstract
Robust carbon monitoring systems are needed for land managers to assess and mitigate the changing effects of ecosystem stress on western United States forests, where most aboveground carbon is stored in mountainous areas. Atmospheric carbon uptake via gross primary productivity (GPP) is an important indicator of ecosystem function and is particularly relevant to carbon monitoring systems. However, limited ground-based observations in remote areas with complex topography represent a significant challenge for tracking regional-scale GPP. Satellite observations can help bridge these monitoring gaps, but the accuracy of remote sensing methods for inferring GPP is still limited in montane evergreen needleleaf biomes, where (a) photosynthetic activity is largely decoupled from canopy structure and chlorophyll content, and (b) strong heterogeneity in phenology and atmospheric conditions is difficult to resolve in space and time. Using monthly solar-induced chlorophyll fluorescence (SIF) sampled at ∼4 km from the TROPOspheric Monitoring Instrument (TROPOMI), we show that high-resolution satellite-observed SIF followed ecological expectations of seasonal and elevational patterns of GPP across a 3000 m elevation gradient in the Sierra Nevada mountains of California. After accounting for the effects of high reflected radiance in TROPOMI SIF due to snow cover, the seasonal and elevational patterns of SIF were well correlated with GPP estimates from a machine-learning model (FLUXCOM) and a land surface model (CLM5.0-SP), outperforming other spectral vegetation indices. Differences in the seasonality of TROPOMI SIF and GPP estimates were likely attributed to misrepresentation of moisture limitation and winter photosynthetic activity in FLUXCOM and CLM5.0 respectively, as indicated by discrepancies with GPP derived from eddy covariance observations in the southern Sierra Nevada. These results suggest that satellite-observed SIF can serve as a useful diagnostic and constraint to improve upon estimates of GPP toward multiscale carbon monitoring systems in montane, evergreen conifer biomes at regional scales.
Copyright and License
© 2023 The Author(s). Published by IOP Publishing Ltd.
Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 license. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI.
Funding
Data Availability
The eddy covariance data were provided by the AmeriFlux Network and the National Ecological Observatory Network (NEON). NEON is a program sponsored by the National Science Foundation and operated under the cooperative agreement of Battelle. This material is based in part on work supported by the National Science Foundation through the NEON program.
The data that support the findings of this study are openly available at the following URL/DOI: https://doi.org/10.5281/zenodo.8239702.
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Additional details
- National Aeronautics and Space Administration
- 80NSSC20K0010
- National Science Foundation
- DGE-2139322
- National Science Foundation
- DEB-1926090
- National Science Foundation
- DEB-1929709
- Accepted
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2023-10-26Accepted
- Available
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2023-11-30Published
- Caltech groups
- Division of Geological and Planetary Sciences
- Publication Status
- Published