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Potential and limitations of inferring ecosystem photosynthetic capacity from leaf functional traits |
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| Authors: | 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 Kate?ina Havránková Mathias Herbst Charmaine Hrynkiw Aram Kalhori Thomas Kaminski Katja 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 |
| Affiliation: | 1. Max Planck Institute for Biogeochemistry, Jena, Germany;2. Amsterdam Global Change Institute, VU University Amsterdam, Amsterdam, The Netherlands;3. German Centre for Integrative Biodiversity Research (iDiv) Halle‐Jena‐Leipzig, Leipzig, Germany;4. Institute of Ecology, University of Innsbruck, Innsbruck, Austria;5. Institute of Environmental Sciences, Leiden University, Leiden, The Netherlands;6. Mediterranean Center for Environmental Studies (Foundation CEAM), Valencia, Spain;7. FFCLRP‐USP, Ribeir?o Preto, Brasil;8. Eastern Forest Environmental Threat Assessment Center, USDA Forest Service, Raleigh, NC, USA;9. Department of Sustainable Agro‐Ecosystems and Bioresources, Research and Innovation Center, Fondazione Edmund Mach, Trento, Italy;10. Foxlab Joint CNR‐FEM Initiative, Trento, Italy;11. UMR 1137 Ecologie et Ecophysiologie Forestierès, INRA, Champenoux, France;12. European Commission, Joint Research Centre, Institute for Environment and Sustainability, Ispra, Italy;13. Department of Matters and Energy Fluxes, Global Change Research Institute CAS, Brno, Czech Republic;14. Johann Heinrich von Thünen Institute, Federal Research Institute for Rural Areas, Forestry and Fisheries, Braunschweig, Germany;15. National Hydrology Research Centre (NHRC), Saskatoon, Saskatchewan, Canada;16. Department of Biology, San Diego State University, San Diego, CA, USA;17. The Inversion Lab, Hamburg, Germany;18. INRA, Grassland Ecosystem Research (UR874), Clermont Ferrand, France;19. Department of Physics, University of Helsinki, Helsinki, Finland;20. Provincia Autonoma di Bolzano Servizi Forestali, Bolzano, Italy;21. Faculty of Science and Technology, Free University of Bolzano, Bolzano, Italy;22. Alterra Green World Research, Wageningen, The Netherlands;23. Department of Environment, Earth and Ecosystems, The Open University, Milton Keynes, UK;24. Department of Forest Resources, University of Minnesota Twin Cities, Saint Paul, MN, USA;25. Hawkesbury Institute for the Environment, Western Sydney University, Penrith, New South Wales, Australia;26. Soil and Water Department, Faculty of Agricultural, Food and Environmental Quality Sciences, The Hebrew University of Jerusalem, Rehovot, Israel;27. Department of Earth and Planetary Sciences, Weizmann Institute of Science, Rehovot, Israel;28. A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Moscow, Russia;29. Environmental and Human Sciences Division, Forest Research, Alice Holt Lodge, Farnham, Surrey, UK;30. Institute of Special Botany and Functional Biodiversity, University of Leipzig, Leipzig, Germany |
| Abstract: | 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. |
| Keywords: | ecosystem functional property eddy covariance FLUXNET interannual variability photosynthetic capacity plant traits spatiotemporal variability TRY database |
