The total uptake of carbon dioxide by ecosystems via photosynthesis (gross primary productivity, GPP) is the largest flux in the global carbon cycle. A key ecosystem functional property determining GPP is the photosynthetic capacity at light saturation (GPPsat), and its interannual variability (IAV) is propagated to the net land–atmosphere exchange of CO2. Given the importance of understanding the IAV in CO2 fluxes for improving the predictability of the global carbon cycle, we have tested a range of alternative hypotheses to identify potential drivers of the magnitude of IAV in GPPsat in forest ecosystems. Our results show that while the IAV in GPPsat within sites is closely related to air temperature and soil water availability fluctuations, the magnitude of IAV in GPPsat is related to stand age and biodiversity (R2 = 0.55, P < 0.0001). We find that the IAV of GPPsat is greatly reduced in older and more diverse forests, and is higher in younger forests with few dominant species. Older and more diverse forests seem to dampen the effect of climate variability on the carbon cycle irrespective of forest type. Preserving old forests and their diversity would therefore be beneficial in reducing the effect of climate variability on Earth's forest ecosystems.

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From Max-Planck Institute for Biogeochemistry we thank U. Weber, M. Jung for providing data, and K. Morris and R. Nair for a language check. We thank P. Jassal from the University of British Columbia and Jens Schumacher from University of Jena for their helpful comments. The authors T.M., M.M., M.D.M., J.K., C.W. and M.R. affiliated with the MPI BGC acknowledge funding by the European Union’s Horizon 2020 project BACI under grant agreement no. 640176. 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, TCOS-Siberia and USCCC. The ERA-Interim reanalysis data are provided by ECMWF and processed by LSCE. The FLUXNET eddy covariance data processing and harmonization was carried out by the European Fluxes Database Cluster, AmeriFlux Management Project, and Fluxdata project of FLUXNET, with the support of CDIAC and ICOS Ecosystem Thematic Center, and the OzFlux, ChinaFlux and AsiaFlux offices. T.M. acknowledges the International Max Planck Research School for global biogeochemical cycles.

Author information


  1. Max Planck Institute for Biogeochemistry, 07745 Jena, Germany

    • Talie Musavi
    • , Mirco Migliavacca
    • , Markus Reichstein
    • , Jens Kattge
    •  & Miguel D. Mahecha
  2. German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, 04103 Leipzig, Germany

    • Markus Reichstein
    • , Jens Kattge
    • , Christian Wirth
    •  & Miguel D. Mahecha
  3. Institute of Special Botany and Functional Biodiversity, University of Leipzig, 04103 Leipzig, Germany

    • Christian Wirth
  4. Biometeorology and Soil Physics Group, Faculty of Land and Food Systems, University of British Columbia, 2329 West Mall, Vancouver, British Columbia, Canada

    • T. Andrew Black
  5. University of Antwerpen, Department of Biology, 2610 Wilrijk, Belgium

    • Ivan Janssens
  6. Bioclimatology, Georg-August University of Göttingen, 37077 Göttingen, Germany

    • Alexander Knohl
    •  & Rijan Tamrakar
  7. INRA, ISPA, Centre de Bordeaux Aquitaine, 71 Avenue Edouard Bourlaux, 33140 Villenave-d’Ornon, France.

    • Denis Loustau
  8. UMR Ecologie Fonctionnelle and Biogéochimie des Sols et Agroécosystèmes, SupAgro-CIRAD-INRA-IRD, Montpellier, France

    • Olivier Roupsard
  9. A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Moscow, 119071, Russia

    • Andrej Varlagin
  10. Centre d'Ecologie Fonctionnelle et Evolutive, CEFE, UMR 5175, CNRS, Montpellier, France

    • Serge Rambal
  11. Universidade Federal de Lavras, Lavras, MG, 37200-000, Brazil

    • Serge Rambal
  12. European Commission, Joint Research Centre, Directorate for Sustainable Resources, 21027, Ispra, Italy

    • Alessandro Cescatti
  13. Department of Sustainable Agro-Ecosystems and Bioresources, Research and Innovation Center, Fondazione Edmund Mach, 38010 San Michele all’ Adige Trento, Italy

    • Damiano Gianelle
  14. Foxlab Joint CNR-FEM Initiative, Via E. Mach 1, 38010 San Michele all'Adige, Italy

    • Damiano Gianelle
  15. National Institute of Advanced Industrial Science and Technology (AIST), Onogawa, Tsukuba, Ibaraki, 305-8561, Japan

    • Hiroaki Kondo


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T.M. wrote the manuscript and performed the analysis. T.M., M.M., M.D.M. and M.R. designed the study. M.M., M.D.M., M.R., J.K., I.J., A.K., A.C., C.W., T.A.B. and A.V. discussed the interpretation of the results. M.M., M.D.M., M.R., J.K., C.W., T.A.B., A.C., A.K., D.L. and O.R. contributed significantly to editing the paper. S.R., R.T. and D.G. contributed to editing the paper. T.A.B., I.J., A.K., D.L., O.R., A.V., S.R., A.C., H.K. and T.F. contributed data.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Talie Musavi.

Supplementary information

PDF files

  1. 1.

    Supplementary information

    Supplementary Figures 1–11; Supplementary Tables 1–2

Text files

  1. 1.

    Supplementary R code

    R code used in analyses

CSV files

  1. 1.

    Supplementary Dataset 1

    Information on the sites used in this study including site identifier (site.code), coefficient of variation of GPPsat (cvGPPsat), Number of years with data (No_years), number of abundant species at the sites (Sp.no90), stand age (Age), plant functional type (PFT), Climate Group, canopy height (Height), canopy cover, nutrient availability classes (Nutrient_availability), cv of leaf area index (cvLAI), mean of LAI (mean.LAI), maximum LAI (LAI max), standard deviation of growing season water availability index (sdWAI), sd of growing season air temperature (sdTair), sd of growing season cumulative precipitation (sdPrecip), latitude (LAT), longitude (LONG).

  2. 2.

    Supplementary Dataset 2

    Annual information on the GPPsat, leaf area index (LAI), mean growing season air temperature (avgTair), mean growing season cumulative precipitation (avgPrecip), mean growing season water availability index (avgWAI). site.code is the identifier of the sites.

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