TY - JOUR
T1 - Influence of physiological phenology on the seasonal pattern of ecosystem respiration in deciduous forests
AU - Migliavacca, Mirco
AU - Reichstein, Markus
AU - Richardson, Andrew D.
AU - Mahecha, Miguel D.
AU - Cremonese, Edoardo
AU - Delpierre, Nicolas
AU - Galvagno, Marta
AU - Law, Beverly E.
AU - Wohlfahrt, Georg
AU - Andrew Black, T.
AU - Carvalhais, Nuno
AU - Ceccherini, Guido
AU - Chen, Jiquan
AU - Gobron, Nadine
AU - Koffi, Ernest
AU - William Munger, J.
AU - Perez-Priego, Oscar
AU - Robustelli, Monica
AU - Tomelleri, Enrico
AU - Cescatti, Alessandro
N1 - Publisher Copyright:
© 2014 John Wiley & Sons Ltd.
PY - 2015/1/1
Y1 - 2015/1/1
N2 - 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.
AB - 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.
KW - Deciduous forests
KW - Ecosystem respiration
KW - Eddy covariance
KW - FLUXNET La Thuile database
KW - Land-atmosphere fluxes
KW - Phenology
UR - http://www.scopus.com/inward/record.url?scp=84917736009&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84917736009&partnerID=8YFLogxK
U2 - 10.1111/gcb.12671
DO - 10.1111/gcb.12671
M3 - Article
C2 - 24990223
AN - SCOPUS:84917736009
SN - 1354-1013
VL - 21
SP - 363
EP - 376
JO - Global change biology
JF - Global change biology
IS - 1
ER -