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A mono-component model of carbon mineralization with a dynamic rate constant
Summary The difficulties in using complicated models of carbon mineralization and the poor performance of simple ones call for new models that are simple in use and robust in performance. We have developed a model for the mineralization of carbon from experimental data in which the organic matter is...
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Published in: | European journal of soil science 2000-09, Vol.51 (3), p.517-529 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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The difficulties in using complicated models of carbon mineralization and the poor performance of simple ones call for new models that are simple in use and robust in performance. We have developed a model for the mineralization of carbon from experimental data in which the organic matter is treated as a single component. The logarithm of the average relative mineralization rate, K, or rate constant, of a substrate considered as a whole was found to be linearly related to the logarithm of time, t, provided prevailing soil conditions remained unchanged. The equation is: logK = logR–S logt, or K = R t–S, in which R (dimension tS − 1) represents K at t = 1, and S (dimensionless, 1 ≥ S≥ 0) is a measure of the rate at which K decreases over time, also called the speed of ‘ageing’ of the substrate. The quantity of the remaining substrate, Yt, is calculated by Yt = Y0 exp(–Rt1 – S), where Y0 is the initial quantity of the substrate. The actual relative mineralization rate, k, at time t is proportional to K, according to k = (1 − S)K. The model was tested against an assembly of 136 sets of data collected from trials conducted in 14 countries all over the world. They cover materials ranging from glucose, cellulose and plant residues, to farmyard manure, peat and soil organic matter. The results lead to the conclusion that the model describes well the dynamics of organic matter in soil over time varying from months to tens of years, provided major environmental conditions remain unchanged. It can easily be applied in practice and is attractive because of its modest input requirements. |
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ISSN: | 1351-0754 1365-2389 |
DOI: | 10.1046/j.1365-2389.2000.00319.x |