Articles | Volume 9, issue 1
https://doi.org/10.5194/bg-9-13-2012
https://doi.org/10.5194/bg-9-13-2012
Research article
 | 
03 Jan 2012
Research article |  | 03 Jan 2012

Effects of climate variability and functional changes on the interannual variation of the carbon balance in a temperate deciduous forest

J. Wu, L. van der Linden, G. Lasslop, N. Carvalhais, K. Pilegaard, C. Beier, and A. Ibrom

Abstract. The net ecosystem exchange of CO2 (NEE) between the atmosphere and a temperate beech forest showed a significant interannual variation (IAV) and a decadal trend of increasing carbon uptake (Pilegaard et al., 2011). The objectives of this study were to evaluate to what extent and at which temporal scale, direct climatic variability and changes in ecosystem functional properties regulated the IAV of the carbon balance at this site. Correlation analysis showed that the sensitivity of carbon fluxes to climatic variability was significantly higher at shorter than at longer time scales and changed seasonally. Ecosystem response anomalies implied that changes in the distribution of climate anomalies during the vegetation period will have stronger impacts on future ecosystem carbon balances than changes in average climate. We improved a published modelling approach which distinguishes the direct climatic effects from changes in ecosystem functioning (Richardson et al., 2007) by employing the semi empirical model published by Lasslop et al. (2010b). Fitting the model in short moving windows enabled large flexibility to adjust the parameters to the seasonal course of the ecosystem functional state. At the annual time scale as much as 80% of the IAV in NEE was attributed to the variation in photosynthesis and respiration related model parameters. Our results suggest that the observed decadal NEE trend at the investigated site was dominated by changes in ecosystem functioning. In general this study showed the importance of understanding the mechanisms of ecosystem functional change. Incorporating ecosystem functional change into process based models will reduce the uncertainties in long-term predictions of ecosystem carbon balances in global climate change projections.

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