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Abstract

The most widely used method to quantify gross N transforination rates in soils is based on N-15 dilution and enrichment principles. To identify rate parameters, N-15-tracing experiments are analysed by models that are linked to algorithins that try to minimize the misfit between modelled and observed data. In Currently available N-15-tracing models optimization algorithms are based oil the Levenberg-Marquardt method that is suitable for the determination of small number of parameters. Therefore, these models are restricted to a few processes. Methods based on Monte Carlo sampling have the potential to overcome restrictions on parameter numbers but have not been tested for application in N-15-tracing models. Here, for the first time, we use a Markov chain Monte Carlo (MCMC) method with a tracing model to simultaneously determine the probability density functions (PDFs) of the whole set of parameters for a previously published data set [Muller, C., Stevens, R.J., Laughlin, R.J., 2004. A N-15 tracing model to analyse N transformations in old grassland soil. Soil Biology & Biochemistry 36, 619-632]. We show that the MCMC method can simultaneously determine PDFs of more than 8 parameters and demonstrate for the first time that it is possible to optimize models where transformations are described by Michaelis-Menten kinetics. Setting the NH4+ oxidation rate to Michaelis-Menten kinetics reduced the misfit by 19%. Together with monitoring diagnostics for parameter convergence, the MCMC method is a very efficient and robust technique to determine PDFs for parameters in N-15-tracing models that Contain large number of N transformations and complex process descriptions. (c) 2006 Elsevier Ltd. All rights reserved. [References: 29]