Global decadal variability of plant carbon isotope discrimination and its link to gross primary production

Lavergne, Aliénor; Hemming, Deborah; Prentice, Iain Colin; Guerrieri, Rossella; Oliver, Rebecca J. ORCID: https://orcid.org/0000-0002-5897-4815; Graven, Heather. 2022 Global decadal variability of plant carbon isotope discrimination and its link to gross primary production. Global Change Biology, 28 (2). 524-541. https://doi.org/10.1111/gcb.15924

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Official URL: http://dx.doi.org/10.1111/gcb.15924

Abstract/Summary

Carbon isotope discrimination (Δ13C) in C3 woody plants is a key variable for the study of photosynthesis. Yet how Δ13C varies at decadal scales, and across regions, and how it is related to gross primary production (GPP), are still incompletely understood. Here we address these questions by implementing a new Δ13C modelling capability in the land-surface model JULES incorporating both photorespiratory and mesophyll-conductance fractionations. We test the ability of four leaf-internal CO2 concentration models embedded in JULES to reproduce leaf and tree-ring (TR) carbon isotopic data. We show that all the tested models tend to overestimate average Δ13C values, and to underestimate interannual variability in Δ13C. This is likely because they ignore the effects of soil water stress on stomatal behavior. Variations in post-photosynthetic isotopic fractionations across species, sites and years, may also partly explain the discrepancies between predicted and TR-derived Δ13C values. Nonetheless, the “least-cost” (Prentice) model shows the lowest biases with the isotopic measurements, and lead to improved predictions of canopy-level carbon and water fluxes. Overall, modelled Δ13C trends vary strongly between regions during the recent (1979–2016) historical period but stay nearly constant when averaged over the globe. Photorespiratory and mesophyll effects modulate the simulated global Δ13C trend by 0.0015 ± 0.005‰ and –0.0006 ± 0.001‰ ppm−1, respectively. These predictions contrast with previous findings based on atmospheric carbon isotope measurements. Predicted Δ13C and GPP tend to be negatively correlated in wet-humid and cold regions, and in tropical African forests, but positively related elsewhere. The negative correlation between Δ13C and GPP is partly due to the strong dominant influences of temperature on GPP and vapor pressure deficit on Δ13C in those forests. Our results demonstrate that the combined analysis of Δ13C and GPP can help understand the drivers of photosynthesis changes in different climatic regions.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1111/gcb.15924
UKCEH and CEH Sections/Science Areas:	Hydro-climate Risks (Science Area 2017-)
ISSN:	1354-1013
Additional Information. Not used in RCUK Gateway to Research.:	Open Access paper - full text available via Official URL link.
Additional Keywords:	carbon isotope discrimination, forest ecosystems, gross primary production, JULES model, land carbon uptake, tree rings
NORA Subject Terms:	Ecology and Environment
Date made live:	15 Dec 2021 12:27 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/531579

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.1111/gcb.15924

UKCEH and CEH Sections/Science Areas:

Hydro-climate Risks (Science Area 2017-)

ISSN:

1354-1013

Additional Information. Not used in RCUK Gateway to Research.:

Open Access paper - full text available via Official URL link.

Additional Keywords:

carbon isotope discrimination, forest ecosystems, gross primary production, JULES model, land carbon uptake, tree rings