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Sun Y, Wen J, Gu L, Joiner J, Chang CY, van der Tol C, Porcar-Castell A, Magney T, Wang L, Hu L, Rascher U, Zarco-Tejada P, Barrett CB, Lai J, Han J, Luo Z. From remotely-sensed solar-induced chlorophyll fluorescence to ecosystem structure, function, and service: Part II-Harnessing data. GLOBAL CHANGE BIOLOGY 2023; 29:2893-2925. [PMID: 36802124 DOI: 10.1111/gcb.16646] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Revised: 02/09/2023] [Accepted: 02/14/2023] [Indexed: 05/03/2023]
Abstract
Although our observing capabilities of solar-induced chlorophyll fluorescence (SIF) have been growing rapidly, the quality and consistency of SIF datasets are still in an active stage of research and development. As a result, there are considerable inconsistencies among diverse SIF datasets at all scales and the widespread applications of them have led to contradictory findings. The present review is the second of the two companion reviews, and data oriented. It aims to (1) synthesize the variety, scale, and uncertainty of existing SIF datasets, (2) synthesize the diverse applications in the sector of ecology, agriculture, hydrology, climate, and socioeconomics, and (3) clarify how such data inconsistency superimposed with the theoretical complexities laid out in (Sun et al., 2023) may impact process interpretation of various applications and contribute to inconsistent findings. We emphasize that accurate interpretation of the functional relationships between SIF and other ecological indicators is contingent upon complete understanding of SIF data quality and uncertainty. Biases and uncertainties in SIF observations can significantly confound interpretation of their relationships and how such relationships respond to environmental variations. Built upon our syntheses, we summarize existing gaps and uncertainties in current SIF observations. Further, we offer our perspectives on innovations needed to help improve informing ecosystem structure, function, and service under climate change, including enhancing in-situ SIF observing capability especially in "data desert" regions, improving cross-instrument data standardization and network coordination, and advancing applications by fully harnessing theory and data.
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Affiliation(s)
- Ying Sun
- School of Integrative Plant Science, Soil and Crop Sciences Section, Cornell University, Ithaca, New York, USA
| | - Jiaming Wen
- School of Integrative Plant Science, Soil and Crop Sciences Section, Cornell University, Ithaca, New York, USA
| | - Lianhong Gu
- Environmental Sciences Division and Climate Change Science Institute, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
| | - Joanna Joiner
- National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC), Greenbelt, Maryland, USA
| | - Christine Y Chang
- US Department of Agriculture, Agricultural Research Service, Adaptive Cropping Systems Laboratory, Beltsville, Maryland, USA
| | - Christiaan van der Tol
- Affiliation Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede, The Netherlands
| | - Albert Porcar-Castell
- Optics of Photosynthesis Laboratory, Institute for Atmospheric and Earth System Research (INAR)/Forest Sciences, Viikki Plant Science Center (ViPS), University of Helsinki, Helsinki, Finland
| | - Troy Magney
- Department of Plant Sciences, University of California, Davis, Davis, California, USA
| | - Lixin Wang
- Department of Earth Sciences, Indiana University-Purdue University Indianapolis (IUPUI), Indianapolis, Indiana, USA
| | - Leiqiu Hu
- Department of Atmospheric and Earth Science, University of Alabama in Huntsville, Huntsville, Alabama, USA
| | - Uwe Rascher
- Institute of Bio- and Geosciences, Forschungszentrum Jülich GmbH, Jülich, Germany
| | - Pablo Zarco-Tejada
- School of Agriculture and Food (SAF-FVAS) and Faculty of Engineering and Information Technology (IE-FEIT), University of Melbourne, Melbourne, Victoria, Australia
| | - Christopher B Barrett
- Charles H. Dyson School of Applied Economics and Management, Cornell University, Ithaca, New York, USA
| | - Jiameng Lai
- School of Integrative Plant Science, Soil and Crop Sciences Section, Cornell University, Ithaca, New York, USA
| | - Jimei Han
- School of Integrative Plant Science, Soil and Crop Sciences Section, Cornell University, Ithaca, New York, USA
| | - Zhenqi Luo
- School of Integrative Plant Science, Soil and Crop Sciences Section, Cornell University, Ithaca, New York, USA
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Wieder WR, Butterfield Z, Lindsay K, Lombardozzi DL, Keppel‐Aleks G. Interannual and Seasonal Drivers of Carbon Cycle Variability Represented by the Community Earth System Model (CESM2). GLOBAL BIOGEOCHEMICAL CYCLES 2021; 35:e2021GB007034. [PMID: 35860341 PMCID: PMC9285408 DOI: 10.1029/2021gb007034] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/13/2021] [Revised: 06/18/2021] [Accepted: 06/25/2021] [Indexed: 06/15/2023]
Abstract
Earth system models are intended to make long-term projections, but they can be evaluated at interannual and seasonal time scales. Although the Community Earth System Model (CESM2) showed improvements in a number of terrestrial carbon cycle benchmarks, relative to its predecessor, our analysis suggests that the interannual variability (IAV) in net terrestrial carbon fluxes did not show similar improvements. The model simulated low IAV of net ecosystem production (NEP), resulting in a weaker than observed sensitivity of the carbon cycle to climate variability. Low IAV in net fluxes likely resulted from low variability in gross primary productivity (GPP)-especially in the tropics-and a high covariation between GPP and ecosystem respiration. Although lower than observed, the IAV of NEP had significant climate sensitivities, with positive NEP anomalies associated with warmer and drier conditions in high latitudes, and with wetter and cooler conditions in mid and low latitudes. We identified two dominant modes of seasonal variability in carbon cycle flux anomalies in our fully coupled CESM2 simulations that are characterized by seasonal amplification and redistribution of ecosystem fluxes. Seasonal amplification of net and gross carbon fluxes showed climate sensitivities mirroring those of annual fluxes. Seasonal redistribution of carbon fluxes is initiated by springtime temperature anomalies, but subsequently negative feedbacks in soil moisture during the summer and fall result in net annual carbon losses from land. These modes of variability are also seen in satellite proxies of GPP, suggesting that CESM2 appropriately represents regional sensitivities of photosynthesis to climate variability on seasonal time scales.
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Affiliation(s)
- William R. Wieder
- National Center for Atmospheric ResearchClimate and Global Dynamics LaboratoryBoulderCOUSA
- Institute of Arctic and Alpine ResearchUniversity of ColoradoBoulderCOUSA
| | - Zachary Butterfield
- Department of Climate and Space Sciences and EngineeringUniversity of MichiganAnn ArborMIUSA
| | - Keith Lindsay
- National Center for Atmospheric ResearchClimate and Global Dynamics LaboratoryBoulderCOUSA
| | - Danica L. Lombardozzi
- National Center for Atmospheric ResearchClimate and Global Dynamics LaboratoryBoulderCOUSA
| | - Gretchen Keppel‐Aleks
- Department of Climate and Space Sciences and EngineeringUniversity of MichiganAnn ArborMIUSA
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