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Influence of physiological phenology on the seasonal pattern of ecosystem respiration in deciduous forests.

Authors :
Migliavacca, Mirco
Reichstein, Markus
Richardson, Andrew D.
Mahecha, Miguel D.
Cremonese, Edoardo
Delpierre, Nicolas
Galvagno, Marta
Law, Beverly E.
Wohlfahrt, Georg
Andrew Black, T.
Carvalhais, Nuno
Ceccherini, Guido
Chen, Jiquan
Gobron, Nadine
Koffi, Ernest
William Munger, J.
Perez‐Priego, Oscar
Robustelli, Monica
Tomelleri, Enrico
Cescatti, Alessandro
Source :
Global Change Biology; Jan2015, Vol. 21 Issue 1, p363-376, 14p, 5 Charts, 9 Graphs
Publication Year :
2015

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 ( R<subscript>ECO</subscript>) in deciduous forests. Previous studies showed that empirical R<subscript>ECO</subscript> models can be substantially improved by considering the biotic dependency of R<subscript>ECO</subscript> 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 R<subscript>ECO</subscript> 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 R<subscript>ECO</subscript> 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 R<subscript>ECO</subscript> in deciduous forests by including the phenological cycle of the canopy. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13541013
Volume :
21
Issue :
1
Database :
Complementary Index
Journal :
Global Change Biology
Publication Type :
Academic Journal
Accession number :
99973364
Full Text :
https://doi.org/10.1111/gcb.12671