Bayesian optimization of a light use efficiency model for the estimation of daily gross primary productivity in a range of Italian forest ecosystems

Maurizio Bagnara, Matteo Sottocornola, Alessandro Cescatti, Stefano Minerbi, Leonardo Montagnani, Damiano Gianelle and Federico Magnani

Ecological Modelling, 2015, vol. 306, issue C, 57-66

Abstract: In this study we applied a modified version of Prelued, a simple semi-empirical light use efficiency (LUE) model, to eight eddy-covariance Italian sites. Since this model has been successfully applied mainly to coniferous forests located at northern latitudes, in our study we aimed to test its generality, by comparing Prelued's outputs in coniferous, broadleaf forests and in a Mediterranean macchia, at different climatic and environmental conditions. The model was calibrated for daily gross primary production (GPP) observed over one year in each flux site and validated for another year. The model uncertainties on both GPP and model parameters were estimated, applying a Bayesian calibration based on a multiple chains Markov Chain Monte Carlo sampling.

Keywords: Prelued; GPP; Light use efficiency model; Eddy-covariance; Model uncertainties (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:306:y:2015:i:c:p:57-66

DOI: 10.1016/j.ecolmodel.2014.09.021

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