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Can decision rules simulate carbon allocation for years with contrasting and extreme weather conditions? A case study for three temperate beech forests

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Abstract

The allocation of carbohydrates to different tree processes and organs is crucial to understand the overall carbon (C) cycling rate in forest ecosystems. Decision rules (DR) (e.g. functional balances and source-sink relationships) are widely used to model C allocation in forests. However, standard DR allocation schemes lack a strong environmental sensitivity and their ability to simulate the year-to-year variability and the impact of extreme events is questioned. In this study, we aimed to compare the performance of a standard DR allocation scheme to the performance of an improved DR allocation scheme taking into account drought-induced changes in allocation dynamics and acclimation of respiration. Model validation was performed against extensive datasets of C fluxes and C pools for a 9 years period (2000-2008) for the site of parameterisation (the beech forest of Hesse, France) and for two contrasting sites not used for parameterisation (the beech forest of Sorø, Denmark, for 1999-2006, and Collelongo, Italy, for 2005-2006). At Hesse, 2003 was characterised by a severe and extreme drought and heat wave. The standard DR allocation scheme captured the average annual dynamics of C allocation and wood growth at beech stands with contrasting climate and standing stock. However, the allocation model required high quality GPP input and errors (even modest) in GPP resulted in large errors in the growth of the tree organs lowest in the modelled sink hierarchy (woody organs). The ability of the standard DR allocation model to simulate year-to-year variability was limited. The amended DR allocation scheme improved the annual simulations and allowed capturing the stand growth dynamics at Hesse during the extreme 2003 summer and its important lag effect on next year's wood production. Modelling of drought-induced changes in fine root dynamics and of short-term thermal acclimation of maintenance respiration should not be overlooked when simulating the C cycle of forests, particularly for sites likely to experience extreme drought and heat waves. The most relevant model bias was the inaccurate estimation of leaf biomass production (up to 15%) and a poor description of its interannual variability. Future studies should focus primarily on this limitation. © 2013 Elsevier B.V.