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Gross primary production (GPP) and red solar induced fluorescence (SIF) respond differently to light and seasonal environmental conditions in a subalpine conifer forest

Yang, Julia C. and Magney, Troy S. and Albert, Loren P. and Richardson, Andrew D. and Frankenberg, Christian and Stutz, Jochen and Grossmann, Katja and Burns, Sean P. and Seyednasrollah, Bijan and Blanken, Peter D. and Bowling, David R. (2022) Gross primary production (GPP) and red solar induced fluorescence (SIF) respond differently to light and seasonal environmental conditions in a subalpine conifer forest. Agricultural and Forest Meteorology, 317 . Art. No. 108904. ISSN 0168-1923. doi:10.1016/j.agrformet.2022.108904. https://resolver.caltech.edu/CaltechAUTHORS:20220318-998697000

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Abstract

The phenology of montane conifer forests is likely to shift in response to climate change and altered seasonal dynamics of light, temperature, and moisture. Solar-induced fluorescence (SIF) is expected to provide substantial improvement for mapping temporal changes in evergreen gross primary production (GPP) over greenness-based remote sensing indices. The utility of SIF to monitor seasonal changes in the phenology of conifer photosynthesis depends on the degree to which GPP and SIF respond in synchrony to key environmental drivers. However, to what extent SIF and GPP become decoupled by responding differently to the combined effects of light and other environmental conditions remains unknown. The goal of this study was to characterize the responses of GPP and SIFred to a suite of environmental drivers at the half-hour time scale and determine how these relationships change across seasons. We analyzed one year of tower-based SIFred and eddy covariance-derived GPP data from a conifer forest at Niwot Ridge, Colorado. We compared the light responses of GPP and SIFred across the year, finding that SIFred increased in response to light earlier in the year than did GPP. The light response of GPP had a positive temperature dependence in spring, and this dependency reversed in summer due to increased evaporative demand, while the light response of SIFred was less temperature dependent. Using artificial neural network ensemble analysis, we found that from spring to summer, SIFred did not exhibit a parallel response to the seasonally dynamic temperature and moisture controls on GPP. In summer SIFred was not correlated with canopy conductance, suggesting that SIF is less sensitive to stomatal control than GPP. Our results suggest that, in conifers, photosystems begin to activate in spring prior to when water becomes available for photosynthesis, presenting a challenge for the use of SIF as a phenological indicator in conifer forests.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1016/j.agrformet.2022.108904DOIArticle
ORCID:
AuthorORCID
Yang, Julia C.0000-0001-9698-9033
Magney, Troy S.0000-0002-9033-0024
Albert, Loren P.0000-0002-9674-6071
Richardson, Andrew D.0000-0002-0148-6714
Frankenberg, Christian0000-0002-0546-5857
Stutz, Jochen0000-0001-6368-7629
Grossmann, Katja0000-0002-5154-197X
Burns, Sean P.0000-0002-6258-1838
Seyednasrollah, Bijan0000-0002-5195-2074
Blanken, Peter D.0000-0002-7405-2220
Bowling, David R.0000-0002-3864-4042
Additional Information:© 2022 Elsevier. Received 22 June 2021, Revised 1 March 2022, Accepted 7 March 2022, Available online 12 March 2022, Version of Record 12 March 2022. We would like to thank Trevor Keenan for providing Matlab code to run the ANN analysis on GitHub, as well as Sovan Lek for providing Matlab code to extract the PaD, Barry Logan for providing helpful discussion, Xueqian Wang for providing flux tower footprint data, and Blake Zimmerman for helping with partial derivative calculation. J. Yang gratefully acknowledges support from the Graduate Research Fellowship Program at the U.S. National Science Foundation. This work was supported by the NSF Macrosystems Biology and NEON-Enabled Science program at NSF (award 1926090). DB was supported by NASA Awards 80NSSC20K0010 and 80NSSC19M0130. US-NR1 was supported by DOE AmeriFlux Management Project subcontract number 7542010. The US-NR1 AmeriFlux site is supported by the U.S. DOE, Office of Science through the AmeriFlux Management Project (AMP) at Lawrence Berkeley National Laboratory under Award Number 7094866. The National Center for Atmospheric Research (NCAR) is sponsored by the NSF. The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Funders:
Funding AgencyGrant Number
NSF Graduate Research FellowshipUNSPECIFIED
NSFDEB-1926090
NASA80NSSC20K0010
NASA80NSSC19M0130
Department of Energy (DOE)7542010
Lawrence Berkeley National Laboratory7094866
Subject Keywords:solar induced fluorescence; artificial neural network; light response curves; phenology; conifer forest; eddy covariance flux
DOI:10.1016/j.agrformet.2022.108904
Record Number:CaltechAUTHORS:20220318-998697000
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20220318-998697000
Official Citation:Julia C. Yang, Troy S. Magney, Loren P. Albert, Andrew D. Richardson, Christian Frankenberg, Jochen Stutz, Katja Grossmann, Sean P. Burns, Bijan Seyednasrollah, Peter D. Blanken, David R. Bowling, Gross primary production (GPP) and red solar induced fluorescence (SIF) respond differently to light and seasonal environmental conditions in a subalpine conifer forest, Agricultural and Forest Meteorology, Volume 317, 2022, 108904, ISSN 0168-1923, https://doi.org/10.1016/j.agrformet.2022.108904.
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:113969
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:18 Mar 2022 23:23
Last Modified:18 Mar 2022 23:23

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