Articles | Volume 12, issue 5
Geosci. Model Dev., 12, 2009–2032, 2019
https://doi.org/10.5194/gmd-12-2009-2019
Geosci. Model Dev., 12, 2009–2032, 2019
https://doi.org/10.5194/gmd-12-2009-2019

Methods for assessment of models 23 May 2019

Methods for assessment of models | 23 May 2019

Bayesian inference and predictive performance of soil respiration models in the presence of model discrepancy

Ahmed S. Elshall et al.

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Cited articles

Ahrens, B., Reichstein, M., Borken, W., Muhr, J., Trumbore, S. E., and Wutzler, T.: Bayesian calibration of a soil organic carbon model using Δ14C measurements of soil organic carbon and heterotrophic respiration as joint constraints, Biogeosciences, 11, 2147–2168, https://doi.org/10.5194/bg-11-2147-2014, 2014. 
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Ammann, L., Reichert, P., and Fenicia, F.: A framework for likelihood functions of deterministic hydrological models, Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2018-406, in review, 2018. 
Bagnara, M., Sottocornola, M., Cescatti, A., Minerbi, S., Montagnani, L., Gianelle, D., and Magnani, F.: Bayesian optimization of a light use efficiency model for the estimation of daily gross primary productivity in a range of Italian forest ecosystems, Ecol. Model., 306, 57–66, https://doi.org/10.1016/j.ecolmodel.2014.09.021, 2015. 
Bagnara, M., Oijen, M. Van, Cameron, D., Gianelle, D., Magnani, F., and Sottocornola, M.: Bayesian calibration of simple forest models with multiplicative mathematical structure: A case study with two Light Use Efficiency models in an alpine forest, Ecol. Model., 371, 90–100, https://doi.org/10.1016/j.ecolmodel.2018.01.014, 2018. 
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The assumptions that the residuals are independent, identically distributed, and have constant variance tend to simplify the underlying mathematics of data models for Bayesian inference. We relax these three assumptions step-wise, resulting in eight data models. Using three mechanistic soil respiration models with different levels of model discrepancy, we discuss the impacts of data models on parameter estimation and predictive performance, and provide recommendations for data model selection.