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 SilvaGregory 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

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

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 languageEnglish (US)
Article number3948
JournalNature communications
Volume14
Issue number1
DOIs
StatePublished - Dec 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.

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.

Publisher Copyright:
© 2023, The Author(s).

PubMed: MeSH publication types

  • Journal Article
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

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