Influence of physiological phenology on the seasonal pattern of ecosystem respiration in deciduous forests |
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| Authors: | Mirco Migliavacca Markus Reichstein Andrew D. Richardson Miguel D. Mahecha Edoardo Cremonese Nicolas Delpierre Marta Galvagno Beverly E. Law Georg Wohlfahrt T. Andrew Black Nuno Carvalhais Guido Ceccherini Jiquan Chen Nadine Gobron Ernest Koffi J. William Munger Oscar Perez‐Priego Monica Robustelli Enrico Tomelleri Alessandro Cescatti |
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| Affiliation: | 1. Max Planck Institute for Biogeochemistry, Jena, Germany;2. Remote Sensing of Environmental Dynamics Lab, DISAT, University of Milano‐Bicocca, Milan, Italy;3. Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, USA;4. Regional Agency for Environmental Protection Valle d'Aosta (ARPA), Aosta, Italy;5. UMR 8079 Ecologie Systematique et Evolution, Universite Paris‐Sud, Orsay, France;6. Department of Forest Ecosystems and Society, Oregon State University, Corvallis, OR, USA;7. Institute for Ecology, University of Innsbruck, Innsbruck, Austria;8. Biometeorology and Soil Physics Group, Faculty of Land and Food Systems, University of British Columbia, Vancouver, BC, Canada;9. Departamento de Ciencias e Engenharia do Ambiente, DCEA, Faculdade de Ciências e Tecnologia, FCT, Universidade Nova de Lisboa, Monte da Caparica, Portugal;10. Institute for Environment and Sustainability, Climate Risk Management Unit, European Commission, Joint Research Centre, Ispra, VA, Italy;11. International Center for Ecology, Meteorology and Environment (IceMe), Nanjing University of Information Science and Technology, Nanjing, China;12. CGCEO/Geography, Michigan State University, East Lansing, MI, USA;13. Division of Engineering and Applied Science/Department of Earth and Planetary Science, Harvard University, Cambridge, MA, USA;14. Institute for Applied Remote Sensing, EURAC, Bolzano, Italy |
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| Abstract: | Understanding the environmental and biotic drivers of respiration at the ecosystem level is a prerequisite to further improve scenarios of the global carbon cycle. In this study we investigated the relevance of physiological phenology, defined as seasonal changes in plant physiological properties, for explaining the temporal dynamics of ecosystem respiration (RECO) in deciduous forests. Previous studies showed that empirical RECO models can be substantially improved by considering the biotic dependency of RECO on the short‐term productivity (e.g., daily gross primary production, GPP) in addition to the well‐known environmental controls of temperature and water availability. Here, we use a model‐data integration approach to investigate the added value of physiological phenology, represented by the first temporal derivative of GPP, or alternatively of the fraction of absorbed photosynthetically active radiation, for modeling RECO at 19 deciduous broadleaved forests in the FLUXNET La Thuile database. The new data‐oriented semiempirical model leads to an 8% decrease in root mean square error (RMSE) and a 6% increase in the modeling efficiency (EF) of modeled RECO when compared to a version of the model that does not consider the physiological phenology. The reduction of the model‐observation bias occurred mainly at the monthly time scale, and in spring and summer, while a smaller reduction was observed at the annual time scale. The proposed approach did not improve the model performance at several sites, and we identified as potential causes the plant canopy heterogeneity and the use of air temperature as a driver of ecosystem respiration instead of soil temperature. However, in the majority of sites the model‐error remained unchanged regardless of the driving temperature. Overall, our results point toward the potential for improving current approaches for modeling RECO in deciduous forests by including the phenological cycle of the canopy. |
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| Keywords: | deciduous forests ecosystem respiration eddy covariance FLUXNET La Thuile database land– atmosphere fluxes phenology |
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