Leaf-level coordination principles propagate to the ecosystem scale

Ulisse Gomarasca; Mirco Migliavacca; Jens Kattge; Jacob A. Nelson; Ülo Niinemets; Christian Wirth; Alessandro Cescatti; Michael Bahn; Richard Nair; Alicia T.R. Acosta; M. Altaf Arain; Mirela Beloiu; T. Andrew Black; Hans Henrik Bruun; Solveig Franziska Bucher; Nina Buchmann; Chaeho Byun; Arnaud Carrara; Adriano Conte; Ana C. da Silva; Gregory Duveiller; Silvano Fares; Andreas Ibrom; Alexander Knohl; Benjamin Komac; Jean Marc Limousin; Christopher H. Lusk; Miguel D. Mahecha; David Martini; Vanessa Minden; Leonardo Montagnani; Akira S. Mori; Yusuke Onoda; Josep Peñuelas; Oscar Perez-Priego; Peter Poschlod; Thomas L. Powell; Peter B. Reich; Ladislav Šigut; Peter M. van Bodegom; Sophia Walther; Georg Wohlfahrt; Ian J. Wright; Markus Reichstein

doi:10.1038/s41467-023-39572-5

Leaf-level coordination principles propagate to the ecosystem scale

Ulisse Gomarasca^*
, Mirco Migliavacca
, Jens Kattge
, Jacob A. Nelson
, Ülo Niinemets
, Christian Wirth
, Alessandro Cescatti
, Michael Bahn
, Richard Nair
, Alicia T.R. Acosta
, M. Altaf Arain
, Mirela Beloiu
, T. Andrew Black
, Hans Henrik Bruun
, Solveig Franziska Bucher
, Nina Buchmann
, Chaeho Byun
, Arnaud Carrara
, Adriano Conte
, Ana C. da Silva

Gregory Duveiller, Silvano Fares, Andreas Ibrom, Alexander Knohl, Benjamin Komac, Jean Marc Limousin, Christopher H. Lusk, Miguel D. Mahecha, David Martini, Vanessa Minden, Leonardo Montagnani, Akira S. Mori, Yusuke Onoda, Josep Peñuelas, Oscar Perez-Priego, Peter Poschlod, Thomas L. Powell, Peter B. Reich, Ladislav Šigut, Peter M. van Bodegom, Sophia Walther, Georg Wohlfahrt, Ian J. Wright, Markus Reichstein

^*Corresponding author for this work

Department of Environmental and Resource Engineering

Max Planck Institute for Biogeochemistry
Estonian University of Life Sciences
University of Innsbruck
Roma Tre University
McMaster University
Swiss Federal Institute of Technology Zurich
University of British Columbia
University of Copenhagen
Andong National University
Fundación CEAM
National Research Council of Italy
Universidade do Estado de Santa Catarina
University of Göttingen
Université de Montpellier
University of Waikato
Vrije Universiteit Brussel
Free University of Bozen-Bolzano
The University of Tokyo
Kyoto University
Centre for Ecological Research and Forestry Applications
University of Córdoba
University of Regensburg
Sewanee: The University of the South
University of Minnesota Twin Cities
Czech Academy of Sciences
Leiden University
Andorra Research + Innovation
European Commission, Joint Research Centre
European Commission Joint Research Centre Institute
German Centre for Integrative Biodiversity Research
Western Sydney University

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Abstract

Fundamental axes of variation in plant traits result from trade-offs between costs and benefits of resource-use strategies at the leaf scale. However, it is unclear whether similar trade-offs propagate to the ecosystem level. Here, we test whether trait correlation patterns predicted by three well-known leaf- and plant-level coordination theories – the leaf economics spectrum, the global spectrum of plant form and function, and the least-cost hypothesis – are also observed between community mean traits and ecosystem processes. We combined ecosystem functional properties from FLUXNET sites, vegetation properties, and community mean plant traits into three corresponding principal component analyses. We find that the leaf economics spectrum (90 sites), the global spectrum of plant form and function (89 sites), and the least-cost hypothesis (82 sites) all propagate at the ecosystem level. However, we also find evidence of additional scale-emergent properties. Evaluating the coordination of ecosystem functional properties may aid the development of more realistic global dynamic vegetation models with critical empirical data, reducing the uncertainty of climate change projections.

Original language	English
Article number	3948
Journal	Nature Communications
Volume	14
Issue number	1
Number of pages	11
ISSN	2041-1723
DOIs	https://doi.org/10.1038/s41467-023-39572-5
Publication status	Published - 2023

Bibliographical note

Funding Information:
This work used eddy covariance data acquired and shared by the FLUXNET community, including these networks: AmeriFlux, AfriFlux, AsiaFlux, CarboAfrica, CarboEuropeIP, CarboItaly, CarboMont, ChinaFlux, Fluxnet-Canada, GreenGrass, ICOS, KoFlux, LBA, NECC, OzFlux-TERN, Swiss FluxNet, TCOS-Siberia, and USCCC. The FLUXNET eddy covariance data processing and harmonization was carried out by the ICOS Ecosystem Thematic Center, AmeriFlux Management Project, and Fluxdata project of FLUXNET, with the support of CDIAC, and the OzFlux, ChinaFlux, and AsiaFlux offices. We thank Weber U., Holst J., Meyer W., Hughes H., Nave L., Kosugi Y., Stuart-Haëntjens E., Arndt S., Battles J., Desai A., Moore T., Vogel C., Munger W. J., and York R. for contributing data used in this study. U. Gomarasca and M. Migliavacca thank the International Max Planck Research School (IMPRS). M. Reichstein and G. Duveiller acknowledge funding by the European Research Council (ERC) Synergy Grant “Understanding and Modeling the Earth System with Machine Learning (USMILE)” under the Horizon 2020 research and innovation program (Grant agreement No. 855187). This work was also supported by the Swiss National Science Foundation (40FA40_154245; 20FI21_148992; 20FI20_173691; 20FI20_198227) to N. Buchmann, the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (2022R1A2C1003504) to C. Byun, the German Research Foundation DFG (INST 186/1118-1 FUGG) and the Ministry of Lower-Saxony for Science and Culture (DigitalForst: Niedersächsisches Vorab, ZN 3679) to A. Knohl, the Estonian Research Council team grant PRG537 to Ü. Niinemets, the Organismo Autónomo de Parques Nacionales (project 2822/2021) to O. Perez-Priego, the Spanish Government grant PID2019-110521GB-I00 to J. Peñuelas; the U.S. National Science Foundation, Biological Integration Institutes grant NSF‐DBI‐2021898 to P. B. Reich, the CzeCOS program (grant number LM2018123) and SustES—Adaptation strategies for sustainable ecosystem services and food security under adverse environmental conditions (CZ.02.1.01/0.0/0.0/16019/0000797) to L. Šigut, and European Space Agency Living Planet Fellowship ‘Vad3e mecum’ to S. Walther.

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Gomarasca, U., Migliavacca, M., Kattge, J., Nelson, J. A., Niinemets, Ü., Wirth, C., Cescatti, A., Bahn, M., Nair, R., Acosta, A. T. R., Arain, M. A., Beloiu, M., Black, T. A., Bruun, H. H., Bucher, S. F., Buchmann, N., Byun, C., Carrara, A., Conte, A., ... Reichstein, M. (2023). Leaf-level coordination principles propagate to the ecosystem scale. Nature Communications, 14(1), Article 3948. https://doi.org/10.1038/s41467-023-39572-5

@article{3597b596615f420e89fadab5fa2f761b,

title = "Leaf-level coordination principles propagate to the ecosystem scale",

abstract = "Fundamental axes of variation in plant traits result from trade-offs between costs and benefits of resource-use strategies at the leaf scale. However, it is unclear whether similar trade-offs propagate to the ecosystem level. Here, we test whether trait correlation patterns predicted by three well-known leaf- and plant-level coordination theories – the leaf economics spectrum, the global spectrum of plant form and function, and the least-cost hypothesis – are also observed between community mean traits and ecosystem processes. We combined ecosystem functional properties from FLUXNET sites, vegetation properties, and community mean plant traits into three corresponding principal component analyses. We find that the leaf economics spectrum (90 sites), the global spectrum of plant form and function (89 sites), and the least-cost hypothesis (82 sites) all propagate at the ecosystem level. However, we also find evidence of additional scale-emergent properties. Evaluating the coordination of ecosystem functional properties may aid the development of more realistic global dynamic vegetation models with critical empirical data, reducing the uncertainty of climate change projections.",

author = "Ulisse Gomarasca and Mirco Migliavacca and Jens Kattge and Nelson, \{Jacob A.\} and {\"U}lo Niinemets and Christian Wirth and Alessandro Cescatti and Michael Bahn and Richard Nair and Acosta, \{Alicia T.R.\} and Arain, \{M. Altaf\} and Mirela Beloiu and Black, \{T. Andrew\} and Bruun, \{Hans Henrik\} and Bucher, \{Solveig Franziska\} and Nina Buchmann and Chaeho Byun and Arnaud Carrara and Adriano Conte and \{da Silva\}, \{Ana C.\} and Gregory Duveiller and Silvano Fares and Andreas Ibrom and Alexander Knohl and Benjamin Komac and Limousin, \{Jean Marc\} and Lusk, \{Christopher H.\} and Mahecha, \{Miguel D.\} and David Martini and Vanessa Minden and Leonardo Montagnani and Mori, \{Akira S.\} and Yusuke Onoda and Josep Pe{\~n}uelas and Oscar Perez-Priego and Peter Poschlod and Powell, \{Thomas L.\} and Reich, \{Peter B.\} and Ladislav {\v S}igut and \{van Bodegom\}, \{Peter M.\} and Sophia Walther and Georg Wohlfahrt and Wright, \{Ian J.\} and Markus Reichstein",

note = "Funding Information: This work used eddy covariance data acquired and shared by the FLUXNET community, including these networks: AmeriFlux, AfriFlux, AsiaFlux, CarboAfrica, CarboEuropeIP, CarboItaly, CarboMont, ChinaFlux, Fluxnet-Canada, GreenGrass, ICOS, KoFlux, LBA, NECC, OzFlux-TERN, Swiss FluxNet, TCOS-Siberia, and USCCC. The FLUXNET eddy covariance data processing and harmonization was carried out by the ICOS Ecosystem Thematic Center, AmeriFlux Management Project, and Fluxdata project of FLUXNET, with the support of CDIAC, and the OzFlux, ChinaFlux, and AsiaFlux offices. We thank Weber U., Holst J., Meyer W., Hughes H., Nave L., Kosugi Y., Stuart-Ha{\"e}ntjens E., Arndt S., Battles J., Desai A., Moore T., Vogel C., Munger W. J., and York R. for contributing data used in this study. U. Gomarasca and M. Migliavacca thank the International Max Planck Research School (IMPRS). M. Reichstein and G. Duveiller acknowledge funding by the European Research Council (ERC) Synergy Grant “Understanding and Modeling the Earth System with Machine Learning (USMILE)” under the Horizon 2020 research and innovation program (Grant agreement No. 855187). This work was also supported by the Swiss National Science Foundation (40FA40\_154245; 20FI21\_148992; 20FI20\_173691; 20FI20\_198227) to N. Buchmann, the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (2022R1A2C1003504) to C. Byun, the German Research Foundation DFG (INST 186/1118-1 FUGG) and the Ministry of Lower-Saxony for Science and Culture (DigitalForst: Nieders{\"a}chsisches Vorab, ZN 3679) to A. Knohl, the Estonian Research Council team grant PRG537 to {\"U}. Niinemets, the Organismo Aut{\'o}nomo de Parques Nacionales (project 2822/2021) to O. Perez-Priego, the Spanish Government grant PID2019-110521GB-I00 to J. Pe{\~n}uelas; the U.S. National Science Foundation, Biological Integration Institutes grant NSF‐DBI‐2021898 to P. B. Reich, the CzeCOS program (grant number LM2018123) and SustES—Adaptation strategies for sustainable ecosystem services and food security under adverse environmental conditions (CZ.02.1.01/0.0/0.0/16019/0000797) to L. {\v S}igut, and European Space Agency Living Planet Fellowship {\textquoteleft}Vad3e mecum{\textquoteright} to S. Walther.",

year = "2023",

doi = "10.1038/s41467-023-39572-5",

language = "English",

volume = "14",

journal = "Nature Communications",

issn = "2041-1723",

publisher = "Nature Research",

number = "1",

}

Gomarasca, U, Migliavacca, M, Kattge, J, Nelson, JA, Niinemets, Ü, Wirth, C, Cescatti, A, Bahn, M, Nair, R, Acosta, ATR, Arain, MA, Beloiu, M, Black, TA, Bruun, HH, Bucher, SF, Buchmann, N, Byun, C, Carrara, A, Conte, A, da Silva, AC, Duveiller, G, Fares, S, Ibrom, A, Knohl, A, Komac, B, Limousin, JM, Lusk, CH, Mahecha, MD, Martini, D, Minden, V, Montagnani, L, Mori, AS, Onoda, Y, Peñuelas, J, Perez-Priego, O, Poschlod, P, Powell, TL, Reich, PB, Šigut, L, van Bodegom, PM, Walther, S, Wohlfahrt, G, Wright, IJ & Reichstein, M 2023, 'Leaf-level coordination principles propagate to the ecosystem scale', Nature Communications, vol. 14, no. 1, 3948. https://doi.org/10.1038/s41467-023-39572-5

TY - JOUR

T1 - Leaf-level coordination principles propagate to the ecosystem scale

AU - Gomarasca, Ulisse

AU - Migliavacca, Mirco

AU - Kattge, Jens

AU - Nelson, Jacob A.

AU - Niinemets, Ülo

AU - Wirth, Christian

AU - Cescatti, Alessandro

AU - Bahn, Michael

AU - Nair, Richard

AU - Acosta, Alicia T.R.

AU - Arain, M. Altaf

AU - Beloiu, Mirela

AU - Black, T. Andrew

AU - Bruun, Hans Henrik

AU - Bucher, Solveig Franziska

AU - Buchmann, Nina

AU - Byun, Chaeho

AU - Carrara, Arnaud

AU - Conte, Adriano

AU - da Silva, Ana C.

AU - Duveiller, Gregory

AU - Fares, Silvano

AU - Ibrom, Andreas

AU - Knohl, Alexander

AU - Komac, Benjamin

AU - Limousin, Jean Marc

AU - Lusk, Christopher H.

AU - Mahecha, Miguel D.

AU - Martini, David

AU - Minden, Vanessa

AU - Montagnani, Leonardo

AU - Mori, Akira S.

AU - Onoda, Yusuke

AU - Peñuelas, Josep

AU - Perez-Priego, Oscar

AU - Poschlod, Peter

AU - Powell, Thomas L.

AU - Reich, Peter B.

AU - Šigut, Ladislav

AU - van Bodegom, Peter M.

AU - Walther, Sophia

AU - Wohlfahrt, Georg

AU - Wright, Ian J.

AU - Reichstein, Markus

N1 - Funding Information: This work used eddy covariance data acquired and shared by the FLUXNET community, including these networks: AmeriFlux, AfriFlux, AsiaFlux, CarboAfrica, CarboEuropeIP, CarboItaly, CarboMont, ChinaFlux, Fluxnet-Canada, GreenGrass, ICOS, KoFlux, LBA, NECC, OzFlux-TERN, Swiss FluxNet, TCOS-Siberia, and USCCC. The FLUXNET eddy covariance data processing and harmonization was carried out by the ICOS Ecosystem Thematic Center, AmeriFlux Management Project, and Fluxdata project of FLUXNET, with the support of CDIAC, and the OzFlux, ChinaFlux, and AsiaFlux offices. We thank Weber U., Holst J., Meyer W., Hughes H., Nave L., Kosugi Y., Stuart-Haëntjens E., Arndt S., Battles J., Desai A., Moore T., Vogel C., Munger W. J., and York R. for contributing data used in this study. U. Gomarasca and M. Migliavacca thank the International Max Planck Research School (IMPRS). M. Reichstein and G. Duveiller acknowledge funding by the European Research Council (ERC) Synergy Grant “Understanding and Modeling the Earth System with Machine Learning (USMILE)” under the Horizon 2020 research and innovation program (Grant agreement No. 855187). This work was also supported by the Swiss National Science Foundation (40FA40_154245; 20FI21_148992; 20FI20_173691; 20FI20_198227) to N. Buchmann, the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (2022R1A2C1003504) to C. Byun, the German Research Foundation DFG (INST 186/1118-1 FUGG) and the Ministry of Lower-Saxony for Science and Culture (DigitalForst: Niedersächsisches Vorab, ZN 3679) to A. Knohl, the Estonian Research Council team grant PRG537 to Ü. Niinemets, the Organismo Autónomo de Parques Nacionales (project 2822/2021) to O. Perez-Priego, the Spanish Government grant PID2019-110521GB-I00 to J. Peñuelas; the U.S. National Science Foundation, Biological Integration Institutes grant NSF‐DBI‐2021898 to P. B. Reich, the CzeCOS program (grant number LM2018123) and SustES—Adaptation strategies for sustainable ecosystem services and food security under adverse environmental conditions (CZ.02.1.01/0.0/0.0/16019/0000797) to L. Šigut, and European Space Agency Living Planet Fellowship ‘Vad3e mecum’ to S. Walther.

PY - 2023

Y1 - 2023

N2 - Fundamental axes of variation in plant traits result from trade-offs between costs and benefits of resource-use strategies at the leaf scale. However, it is unclear whether similar trade-offs propagate to the ecosystem level. Here, we test whether trait correlation patterns predicted by three well-known leaf- and plant-level coordination theories – the leaf economics spectrum, the global spectrum of plant form and function, and the least-cost hypothesis – are also observed between community mean traits and ecosystem processes. We combined ecosystem functional properties from FLUXNET sites, vegetation properties, and community mean plant traits into three corresponding principal component analyses. We find that the leaf economics spectrum (90 sites), the global spectrum of plant form and function (89 sites), and the least-cost hypothesis (82 sites) all propagate at the ecosystem level. However, we also find evidence of additional scale-emergent properties. Evaluating the coordination of ecosystem functional properties may aid the development of more realistic global dynamic vegetation models with critical empirical data, reducing the uncertainty of climate change projections.

AB - Fundamental axes of variation in plant traits result from trade-offs between costs and benefits of resource-use strategies at the leaf scale. However, it is unclear whether similar trade-offs propagate to the ecosystem level. Here, we test whether trait correlation patterns predicted by three well-known leaf- and plant-level coordination theories – the leaf economics spectrum, the global spectrum of plant form and function, and the least-cost hypothesis – are also observed between community mean traits and ecosystem processes. We combined ecosystem functional properties from FLUXNET sites, vegetation properties, and community mean plant traits into three corresponding principal component analyses. We find that the leaf economics spectrum (90 sites), the global spectrum of plant form and function (89 sites), and the least-cost hypothesis (82 sites) all propagate at the ecosystem level. However, we also find evidence of additional scale-emergent properties. Evaluating the coordination of ecosystem functional properties may aid the development of more realistic global dynamic vegetation models with critical empirical data, reducing the uncertainty of climate change projections.

U2 - 10.1038/s41467-023-39572-5

DO - 10.1038/s41467-023-39572-5

M3 - Journal article

AN - SCOPUS:85163976571

SN - 2041-1723

VL - 14

JO - Nature Communications

JF - Nature Communications

IS - 1

M1 - 3948

ER -

Leaf-level coordination principles propagate to the ecosystem scale

Abstract

Bibliographical note

UN SDGs

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