The impact of alternative trait-scaling hypotheses for the maximum photosynthetic carboxylation rate (V cmax) on global gross primary production [The impact of alternative Vcmax trait-scaling hypotheses on global gross primary production]

Walker, Anthony P.; Quaife, Tristan; van Bodegom, Peter M.; De Kauwe, Martin G.; Keenan, Trevor F.; Joiner, Joanna; Lomas, Mark R.; MacBean, Natasha; Xu, Chongang; Yang, Xiaojuan; Woodward, F. Ian

doi:10.1111/nph.14623

Title: The impact of alternative trait-scaling hypotheses for the maximum photosynthetic carboxylation rate (V _cmax) on global gross primary production [The impact of alternative V_cmax trait-scaling hypotheses on global gross primary production]

Journal Article · Fri Jun 23 00:00:00 EDT 2017 · New Phytologist

DOI:https://doi.org/10.1111/nph.14623· OSTI ID:1376330

Walker, Anthony P. ^[1]; Quaife, Tristan ^[2]; van Bodegom, Peter M. ^[3]; De Kauwe, Martin G. ^[4]; Keenan, Trevor F. ^[5]; Joiner, Joanna ^[6]; Lomas, Mark R. ^[7]; MacBean, Natasha ^[8]; Xu, Chongang ^[9];

^[10]; Woodward, F. Ian ^[7]

Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Univ. of Sheffield, Western Bank (United Kingdom)
Univ. of Reading, Reading (United Kingdom)
Leiden Univ., Leiden (The Netherlands)
Macquarie Univ., Sydney, NSW (Australia)
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
NASA Goddard Space Flight Center (GSFC), Greenbelt, MD (United States)
Univ. of Sheffield, Western Bank (United Kingdom)
Univ. Paris-Saclay, Gif-sur-Yvette (France)
Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

The maximum photosynthetic carboxylation rate (V_cmax) is an influential plant trait that has multiple scaling hypotheses, which is a source of uncertainty in predictive understanding of global gross primary production (GPP). Four trait-scaling hypotheses (plant functional type, nutrient limitation, environmental filtering, and plant plasticity) with nine specific implementations were used to predict global V_cmax distributions and their impact on global GPP in the Sheffield Dynamic Global Vegetation Model (SDGVM). Global GPP varied from 108.1 to 128.2 PgC yr^-1, 65% of the range of a recent model intercomparison of global GPP. The variation in GPP propagated through to a 27% coefficient of variation in net biome productivity (NBP). All hypotheses produced global GPP that was highly correlated (r = 0.85–0.91) with three proxies of global GPP. Plant functional type-based nutrient limitation, underpinned by a core SDGVM hypothesis that plant nitrogen (N) status is inversely related to increasing costs of N acquisition with increasing soil carbon, adequately reproduced global GPP distributions. Further improvement could be achieved with accurate representation of water sensitivity and agriculture in SDGVM. Mismatch between environmental filtering (the most data-driven hypothesis) and GPP suggested that greater effort is needed understand V_cmax variation in the field, particularly in northern latitudes.

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Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Grant/Contract Number:: AC05-00OR22725; AC02-05CH11231

OSTI ID:: 1376330

Alternate ID(s):: OSTI ID: 1476530

Journal Information:: New Phytologist, Vol. 215, Issue 4; ISSN 0028-646X

Publisher:: WileyCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 82 works

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Carbon–nitrogen coupling under three schemes of model representation: a traceability analysis Du, Zhenggang; Weng, Ensheng; Jiang, Lifen Geoscientific Model Development, Vol. 11, Issue 11 https://doi.org/10.5194/gmd-11-4399-2018	journal	January 2018
Impact of the 2015/2016 El Niño on the terrestrial carbon cycle constrained by bottom-up and top-down approaches Bastos, Ana; Friedlingstein, Pierre; Sitch, Stephen Philosophical Transactions of the Royal Society B: Biological Sciences, Vol. 373, Issue 1760 https://doi.org/10.1098/rstb.2017.0304	journal	October 2018
Improved estimates of global terrestrial photosynthesis using information on leaf chlorophyll content Luo, Xiangzhong; Croft, Holly; Chen, Jing M. Global Change Biology https://doi.org/10.1111/gcb.14624	journal	April 2019
Vegetation Functional Properties Determine Uncertainty of Simulated Ecosystem Productivity: A Traceability Analysis in the East Asian Monsoon Region Cui, Erqian; Huang, Kun; Arain, Muhammad Altaf Global Biogeochemical Cycles, Vol. 33, Issue 6 https://doi.org/10.1029/2018gb005909	journal	June 2019
Global photosynthetic capacity is optimized to the environment Smith, Nicholas G.; Keenan, Trevor F.; Colin Prentice, I. Ecology Letters, Vol. 22, Issue 3 https://doi.org/10.1111/ele.13210	journal	January 2019
Leaf-level photosynthetic capacity dynamics in relation to soil and foliar nutrients along forest–savanna boundaries in Ghana and Brazil Gvozdevaite, Agne; Oliveras, Imma; Domingues, Tomas Ferreira Tree Physiology, Vol. 38, Issue 12 https://doi.org/10.1093/treephys/tpy117	journal	November 2018
Leaf reflectance spectroscopy captures variation in carboxylation capacity across species, canopy environment and leaf age in lowland moist tropical forests Wu, Jin; Rogers, Alistair; Albert, Loren P. New Phytologist, Vol. 224, Issue 2 https://doi.org/10.1111/nph.16029	journal	June 2019
Leaf-level photosynthetic capacity dynamics in relation to soil and foliar nutrients along forest–savanna boundaries in Ghana and Brazil Gvozdevaite, Agne; Oliveras, Imma; Domingues, Tomas Ferreira Tree Physiology, Vol. 38, Issue 12 https://doi.org/10.1093/treephys/tpy136	journal	December 2018
Global carbon budget 2019 Pierre, Friedlingstein,; W., Jones, Matthew; Michael, O'Sullivan, ETH Zurich https://doi.org/10.3929/ethz-b-000385668	text	January 2019
Global Carbon Budget 2017 Le Quéré, C.; Andrew, R. M.; Friedlingstein, P. Karlsruhe https://doi.org/10.5445/ir/1000081380	text	January 2018
Impact of the 2015/2016 El Niño on the terrestrial carbon cycle constrained by bottom-up and top-down approaches Bastos, Ana; Friedlingstein, Pierre; Sitch, Stephen Royal Society of London https://doi.org/10.7892/boris.128667	text	January 2018
Global Carbon Budget 2018 Le Quéré, Corinne; Andrew, Robbie M.; Friedlingstein, Pierre Copernicus Publications https://doi.org/10.7892/boris.141541	text	January 2018
A derivation error that affects carbon balance models exists in the current implementation of the modified Arrhenius function Murphy, Bridget K.; Stinziano, Joseph R. New Phytologist, Vol. 231, Issue 6 https://doi.org/10.1111/nph.16883	journal	September 2020
Global carbon budget 2019 Friedlingstein, P.; Jones, M. W.; O’Sullivan, M. Karlsruhe https://doi.org/10.5445/ir/1000104785	text	January 2019
ORCHIDEE-PEAT (revision 4596), a model for northern peatland CO2, water, and energy fluxes on daily to annual scales Qiu, Chunjing; Zhu, Dan; Ciais, Philippe Karlsruhe https://doi.org/10.5445/ir/1000083904	text	January 2018
Estimating global gross primary productivity using chlorophyll fluorescence and a data assimilation system with the BETHY-SCOPE model Norton, Alexander J.; Rayner, Peter J.; Koffi, Ernest N. Biogeosciences Discussions https://doi.org/10.5194/bg-2018-270	journal	June 2018
Global Carbon Budget 2019 Friedlingstein, Pierre; Jones, Matthew W.; Michael, O&Apos;Sullivan, Copernicus Publications https://doi.org/10.7892/boris.141543	text	January 2019
Direct and seasonal legacy effects of the 2018 heat wave and drought on European ecosystem productivity Bastos, A.; Ciais, P.; Friedlingstein, P. Science Advances, Vol. 6, Issue 24 https://doi.org/10.1126/sciadv.aba2724	journal	June 2020

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Title: The impact of alternative trait-scaling hypotheses for the maximum photosynthetic carboxylation rate (V cmax) on global gross primary production [The impact of alternative Vcmax trait-scaling hypotheses on global gross primary production]

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Title: The impact of alternative trait-scaling hypotheses for the maximum photosynthetic carboxylation rate (V _cmax) on global gross primary production [The impact of alternative V_cmax trait-scaling hypotheses on global gross primary production]