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The problem of model complexity has been lively debated in environmental sciences as well as in the forest modelling community. Simple models are less input demanding and their calibration involves a lower number of parameters, but they might be suitable only at local scale. In this work we calibrated a simplified ecosystem process model (PRELES) to data from multiple sites and we tested if PRELES can be used at regional scale to estimate the carbon and water fluxes of Boreal conifer forests. We compared a multi-site (M-S) with site-specific (S-S) calibrations. Model calibrations and evaluations were carried out by the means of the Bayesian method; Bayesian calibration (BC) and Bayesian model comparison (BMC) were used to quantify the uncertainty in model parameters and model structure. To evaluate model performances BMC results were combined with more classical analysis of model-data mismatch (M-DM). Evapotranspiration (ET) and gross primary production (GPP) measurements collected in 10 sites of Finland and Sweden were used in the study. Calibration results showed that similar estimates were obtained for the parameters at which model outputs are most sensitive. No significant differences were encountered in the predictions of the multi-site and site-specific versions of PRELES with exception of a site with agricultural history (Alkkia). Although PRELES predicted GPP better than evapotranspiration, we concluded that the model can be reliably used at regional scale to simulate carbon and water fluxes of Boreal forests. Our analyses underlined also the importance of using long and carefully collected flux datasets in model calibration. In fact, even a single site can provide model calibrations that can be applied at a wider spatial scale, since it covers a wide range of variability in climatic conditions. [ABSTRACT FROM AUTHOR]

Simple models are less input demanding and their calibration involves a lower number of parameters, however their general applicability to vast areas must be tested. We analysed if a simple ecosystem model (PRELES) can be applied to estimate carbon and water fluxes of Boreal forests at regional scale. Multi-site (M-S) and site-specific (S-S) calibrations were compared using evapotranspiration (ET) and gross primary production (GPP) measurements from 10 sites. The performances of M-S were similar to S-Ss except for a site with agricultural history. Although PRELES predicted GPP better than ET, we concluded that the model can be reliably used at regional scale to simulate carbon and water fluxes of Boreal forests. We further found that, in the calibration, the use of a long and carefully collected flux dataset from one site that covers a wide range of climate variability leads to better model performance in other sites as well. [ABSTRACT FROM AUTHOR]