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Air temperature optima of vegetation productivity across global biomes

Nature Ecology & Evolution volume 3, pages 772–779 (2019)Cite this article

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Abstract

The global distribution of the optimum air temperature for ecosystem-level gross primary productivity (\({\it{T}}_{{\mathrm{opt}}}^{{\mathrm{eco}}}\)) is poorly understood, despite its importance for ecosystem carbon uptake under future warming. We provide empirical evidence for the existence of such an optimum, using measurements of in situ eddy covariance and satellite-derived proxies, and report its global distribution. \(T_{\mathrm{opt}}^{\mathrm{eco}}\) is consistently lower than the physiological optimum temperature of leaf-level photosynthetic capacity, which typically exceeds 30 °C. The global average \(T_{\mathrm{opt}}^{\mathrm{eco}}\) is estimated to be 23 ± 6 °C, with warmer regions having higher \(T_{\mathrm{opt}}^{\mathrm{eco}}\) values than colder regions. In tropical forests in particular, \(T_{\mathrm{opt}}^{\mathrm{eco}}\) is close to growing-season air temperature and is projected to fall below it under all scenarios of future climate, suggesting a limited safe operating space for these ecosystems under future warming.

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Fig. 1: Distribution of \({\it{T}}_{{\rm{opt}}}^{{\rm{eco}}}\) for vegetation productivity derived from flux-tower sites and satellite-based data for near-infrared reflectance of vegetation (NIRV).
Fig. 2: Relationship between \({\boldsymbol{T}}_{{\rm{max}}\,{\rm{gs}}}^{{\rm{air}}}\) and \({\boldsymbol{T}}_{{\boldsymbol{opt}}}^{{\boldsymbol{eco}}}\) across vegetation types.
Fig. 3: Change with latitude in \({\boldsymbol{T}}_{{\rm{opt}}}^{{\rm{eco}}}\) and \({\boldsymbol{T}}_{{\boldsymbol{max}}\,{\boldsymbol{gs}}}^{{\boldsymbol{air}}}\).

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All data are available in the main text or the supplementary information. All computer codes used in this study can be provided by the corresponding author upon reasonable request.

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Acknowledgements

This study was supported by the Strategic Priority Research Program (A) of the Chinese Academy of Sciences (Grant No. XDA20050101), the National Natural Science Foundation of China (41530528) and the National Key R&D Program of China (2017YFA0604702). This work used eddy covariance data acquired by the FLUXNET community and in particular by the following networks: AmeriFlux (US Department of Energy, Biological and Environmental Research, Terrestrial Carbon Program (DE-FG02-04ER63917 and DE-FG02-04ER63911)), AfriFlux, AsiaFlux, CarboAfrica, CarboEuropeIP, CarboItaly, CarboMont, ChinaFlux, Fluxnet-Canada (supported by CFCAS, NSERC, BIOCAP, Environment Canada and NRCan), GreenGrass, KoFlux, LBA, NECC, OzFlux, TCOS-Siberia and USCCC. We acknowledge the financial support to the eddy covariance data harmonization provided by CarboEuropeIP, FAO-GTOS-CO, iLEAPS, Max Planck Institute for Biogeochemistry, National Science Foundation, University of Tuscia, Université Laval and Environment Canada, and the US Department of Energy and the database development and technical support from Berkeley Water Center, Lawrence Berkeley National Laboratory, Microsoft Research eScience, Oak Ridge National Laboratory, University of California-Berkeley and University of Virginia. P.C., J.P. and I.A.J. would like to acknowledge the financial support from the European Research Council Synergy Grant No. ERC-SyG-2013-610028 IMBALANCE-P. P.C. was also supported by the French Agence Nationale de la Recherche Convergence Lab Changement climatique et usage des terres (CLAND). I.A.J. acknowledges the Methusalem funding of the Flemish Community through the Research Council of the University of Antwerp. T.F.K. was supported by the NASA Terrestrial Ecology Program IDS Award NNH17AE86I. J.M. and X.S. are supported by the Terrestrial Ecosystem Science Scientific Focus Area project funded through the Terrestrial Ecosystem Science Program in the Climate and Environmental Sciences Division of the Biological and Environmental Research Program in the US Department of Energy Office of Science. Oak Ridge National Laboratory is supported by the Office of Science of the US Department of Energy under Contract No. DE-AC05-00OR22725. M.C. was supported by a grant overseen by the French National Research Agency (ANR) as part of the Investissements d’Avenir program (ANR-11-LABX-0002-01, Lab of Excellence ARBRE).

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Authors and Affiliations

  1. Sino-French Institute for Earth System Science, Peking University, Beijing, China

    Mengtian Huang, Shilong Piao, Xuhui Wang, Shushi Peng, Kai Wang, Mengdi Gao, Yue He & Yongwen Liu

  2. Key Laboratory of Alpine Ecology and Biodiversity, Chinese Academy of Sciences, Beijing, China

    Shilong Piao & Tao Wang

  3. Center for Excellence in Tibetan Earth Science, Chinese Academy of Sciences, Beijing, China

    Shilong Piao & Tao Wang

  4. Laboratoire des Sciences du Climat et de l’Environnement, Gif-sur-Yvette, France

    Philippe Ciais

  5. Centre for Research on Ecology and Forestry Applications, Barcelona, Spain

    Josep Peñuelas

  6. CSIC, Global Ecology Unit CREAF-CSIC-UAB, Barcelona, Spain

    Josep Peñuelas

  7. Lawrence Berkeley National Laboratory, Berkeley, CA, USA

    Trevor F. Keenan

  8. Department of Environmental Science Policy and Management, UC Berkeley, Berkeley, CA, USA

    Trevor F. Keenan

  9. Department of Global Ecology, Carnegie Institution for Science, Stanford, CA, USA

    Joseph A. Berry

  10. Climate Change Science Institute and Environmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA

    Jiafu Mao & Xiaoying Shi

  11. European Commission, Joint Research Centre (JRC), Ispra, Italy

    Ramdane Alkama & Alessandro Cescatti

  12. Université de Lorraine, INRA, AgroParisTech, UMR Silva, Nancy, France

    Matthias Cuntz

  13. CAVElab Computational and Applied Vegetation Ecology, Ghent University, Gent, Belgium

    Hannes De Deurwaerder & Hans Verbeeck

  14. Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA

    Yiqi Luo

  15. Department of Earth and Environment, Boston University, Boston, MA, USA

    Ranga B. Myneni

  16. Key Laboratory of Ecosystem Network Observation and Modeling, Chinese Academy of Sciences, Beijing, China

    Shuli Niu

  17. School of Atmospheric Sciences, Sun Yat-Sen University, Guangzhou, China

    Wenping Yuan

  18. Environmental and Climate Sciences Department, Brookhaven National Laboratory, Upton, NY, USA

    Jin Wu

  19. School of Biological Sciences, University of Hong Kong, Pokfulam, Hong Kong

    Jin Wu

  20. Centre of Excellence – Plants and Vegetation Ecology, University of Antwerp, Wilrijk, Belgium

    Ivan A. Janssens

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S. Piao designed the research. M. H. performed the analysis. S. Piao drafted the paper. All authors contributed to the interpretation of the results and the text.

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Correspondence to Shilong Piao.

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Huang, M., Piao, S., Ciais, P. et al. Air temperature optima of vegetation productivity across global biomes. Nat Ecol Evol 3, 772–779 (2019). https://doi.org/10.1038/s41559-019-0838-x

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