Data from: The Physiological Basis for Estimating Photosynthesis from Chlorophyll a Fluorescence

Han, Jimei; Gu, Lianhong; Zhang, Yongjiang; Sun, Ying

Data from: The Physiological Basis for Estimating Photosynthesis from Chlorophyll a Fluorescence

dc.contributor.author	Han, Jimei
dc.contributor.author	Gu, Lianhong
dc.contributor.author	Zhang, Yongjiang
dc.contributor.author	Sun, Ying
dc.date.accessioned	2022-02-17T16:41:48Z
dc.date.available	2022-02-17T16:41:48Z
dc.date.issued	2022-02-17
dc.description	Please cite as: Jimei Han, Lianhong Gu, Yongjiang Zhang, Ying Sun. (2022) Data from: The Physiological Basis for Estimating Photosynthesis from Chlorophyll a Fluorescence. [dataset] Cornell University eCommons Repository. https://doi.org/10.7298/q3hb-zq56	en_US
dc.description.abstract	These files contain data supporting all results reported in Han et. al. The Physiological Basis for Estimating Photosynthesis from Chlorophyll a Fluorescence. In Han et al. we found: The availability of Solar-Induced chlorophyll Fluorescence (SIF) offers potential to curb large uncertainties in estimating photosynthesis across biomes, climates, and scales. However, it remains unclear how SIF should be used to mechanistically estimate photosynthesis. This study built a quantitative framework to estimate photosynthesis, based on a mechanistic light reaction model with chlorophyll a fluorescence from PSII (SIFPSII) as an input (MLR-SIF). Utilizing 29 C3 and C4 plant species representative of major plant biomes across the globe, we verified such a framework at the leaf level. MLR-SIF is capable of accurately reproducing photosynthesis for all C3 and C4 species under diverse light, temperature, and CO2 conditions. We further tested the robustness of MLR-SIF using Monte Carlo simulations, and found that the estimated photosynthesis is much less sensitive to parameter uncertainties relative to the conventional Farquhar, von Caemmerer, Berry (FvCB) model because of additional independent information contained in SIFPSII. SIFPSII, once inferred from direct observables of SIF, provides “parameter savings” to the MLR-SIF as compared to the mechanistically equivalent FvCB and thus shortcuts the uncertainties propagated from imperfect model parameterization. Our findings set the stage for future efforts employing SIF mechanistically to improve photosynthesis estimation across scales, functional groups, and environmental conditions.
dc.description.sponsorship	This work was supported in part through NSF Macrosystem Biology to YS, Grant #:1926488; USDA-NIFA Hatch Award to YS, Grant #: 1014740; NASA MEaSures project to YS; USDA-NIFA and Agriculture Hatch Fund to YZ, Grant #: ME022021; This research is also supported by the US Department of Energy (DOE), Office of Science, Biological and Environmental Research Program. ORNL is managed by UT-Battelle, LLC, for DOE under contract DE-AC05-00OR22725.	en_US
dc.identifier.doi	https://doi.org/10.7298/q3hb-zq56
dc.identifier.uri	https://hdl.handle.net/1813/110978
dc.language.iso	en_US	en_US
dc.relation.isreferencedby	Han J., Chang C. Y., Gu L., Zhang Y., Meeker E.W., Magney T.S., Walker A.P., Wen J., Kira O., McNaull S., Sun Y. (2022) The Physiological Basis for Estimating Photosynthesis from Chlorophyll a Fluorescence. New Phytologist, 234(4), 1206–1219. https://doi.org/10.1111/nph.18045
dc.relation.isreferencedbyuri	https://doi.org/10.1111/nph.18045
dc.rights	Attribution 4.0 International	*
dc.rights.uri	http://creativecommons.org/licenses/by/4.0/	*
dc.subject	photosynthesis model
dc.subject	Non-Photochemical Quenching (NPQ)
dc.subject	parameter uncertainty
dc.subject	redox state of PSII reaction centers
dc.title	Data from: The Physiological Basis for Estimating Photosynthesis from Chlorophyll a Fluorescence	en_US
dc.type	dataset	en_US
schema.accessibilityHazard	none	en_US