Potential and limitations of inferring ecosystem photosynthetic capacity from leaf functional traits

Talie Musavi, Mirco Migliavacca, Martine Janet van de Weg, Jens Kattge, Georg Wohlfahrt, Peter M. van Bodegom, Markus Reichstein, Michael Bahn, Arnaud Carrara, Tomas F. Domingues, Michael Gavazzi, Damiano Gianelle, Cristina Gimeno, André Granier, Carsten Gruening, Kateřina Havránková, Mathias Herbst, Charmaine Hrynkiw, Aram Kalhori, Thomas KaminskiKatja Klumpp, Pasi Kolari, Bernard Longdoz, Stefano Minerbi, Leonardo Montagnani, Eddy Moors, Walter C. Oechel, Peter B. Reich, Shani Rohatyn, Alessandra Rossi, Eyal Rotenberg, Andrej Varlagin, Matthew Wilkinson, Christian Wirth, Miguel D. Mahecha

Research output: Contribution to journalArticlepeer-review

25 Scopus citations


The aim of this study was to systematically analyze the potential and limitations of using plant functional trait observations from global databases versus in situ data to improve our understanding of vegetation impacts on ecosystem functional properties (EFPs). Using ecosystem photosynthetic capacity as an example, we first provide an objective approach to derive robust EFP estimates from gross primary productivity (GPP) obtained from eddy covariance flux measurements. Second, we investigate the impact of synchronizing EFPs and plant functional traits in time and space to evaluate their relationships, and the extent to which we can benefit from global plant trait databases to explain the variability of ecosystem photosynthetic capacity. Finally, we identify a set of plant functional traits controlling ecosystem photosynthetic capacity at selected sites. Suitable estimates of the ecosystem photosynthetic capacity can be derived from light response curve of GPP responding to radiation (photosynthetically active radiation or absorbed photosynthetically active radiation). Although the effect of climate is minimized in these calculations, the estimates indicate substantial interannual variation of the photosynthetic capacity, even after removing site-years with confounding factors like disturbance such as fire events. The relationships between foliar nitrogen concentration and ecosystem photosynthetic capacity are tighter when both of the measurements are synchronized in space and time. When using multiple plant traits simultaneously as predictors for ecosystem photosynthetic capacity variation, the combination of leaf carbon to nitrogen ratio with leaf phosphorus content explains the variance of ecosystem photosynthetic capacity best (adjusted R2 = 0.55). Overall, this study provides an objective approach to identify links between leaf level traits and canopy level processes and highlights the relevance of the dynamic nature of ecosystems. Synchronizing measurements of eddy covariance fluxes and plant traits in time and space is shown to be highly relevant to better understand the importance of intra- and interspecific trait variation on ecosystem functioning.

Original languageEnglish (US)
Pages (from-to)7352-7366
Number of pages15
JournalEcology and Evolution
Issue number20
StatePublished - Oct 1 2016

Bibliographical note

Funding Information:
We thank all the people who made this study possible by participating in leaf sampling and sharing flux and plant trait data. We appreciate all the good discussions at the Max Planck Institute of Biogeochemistry. We thank Ulrich Weber for preparing part of the flux and remote sensing data. We thank Jurgen van Hal and Richard van Logtesteijn at the VU University in Amsterdam for measuring the plant traits and Katrin Fleischer for helping for leaf sampling at NL-Loo site. We also thank Martina Mund for sending us litter fall data from species of DE-Hai from which we estimated the abundances. We thank the anonymous reviewers and the associate editor for their constructive comments that improved both the readability and the robustness of the manuscript. The authors affiliated with the MPI BGC acknowledge funding by the European Union's Horizon 2020 project BACI under grant agreement No. 640176. The study has been supported by the TRY initiative on plant traits (http://www.try-db.org), hosted at the Max Planck Institute for Biogeochemistry, Jena, Germany. TRY is currently supported by DIVERSITAS/Future Earth and the German Center for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig. This work used eddy covariance data acquired by the FLUXNET community and in particular by the following networks: AmeriFlux [U.S. 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 the USCCC. We acknowledge the financial support to the eddy covariance data harmonization provided by CarboEuropeIP, FAO-GTOS-TCO, iLEAPS, Max Planck Institute for Biogeochemistry, National Science Foundation, University of Tuscia, Université Laval, Environment Canada and 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 the University of Virginia, and the IceMe of NUIST. The authors would like to thank all the PIs of eddy covariance sites, technicians, postdoctoral fellows, research associates, and site collaborators involved in FLUXNET who are not included as coauthors of this article, but without whose work this analysis would not have been possible. K.H. acknowledges funding from the Ministry of Education, Youth and Sports of Czech Republic within the National Sustainability Program I (NPU I), grant number LO1415. T. Musavi acknowledges the International Max Planck Research School for global biogeochemical cycles.

Publisher Copyright:
© 2016 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.


  • TRY database
  • ecosystem functional property
  • eddy covariance
  • interannual variability
  • photosynthetic capacity
  • plant traits
  • spatiotemporal variability


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