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Comparison of Kinetic Models for Describing Net Sulfur and Nitrogen Mineralization
Author(s) -
Ellert B. H.,
Bettany J. R.
Publication year - 1988
Publication title -
soil science society of america journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.836
H-Index - 168
eISSN - 1435-0661
pISSN - 0361-5995
DOI - 10.2136/sssaj1988.03615995005200060035x
Subject(s) - mineralization (soil science) , incubation , soil water , nitrogen cycle , nitrogen , chemistry , nonlinear regression , soil science , environmental science , environmental chemistry , mineralogy , mathematics , regression analysis , statistics , biochemistry , organic chemistry
Net S and N mineralization in forested and cultivated Typic Cryoboralfic soils was monitored over 37 wk in a laboratory incubation experiment with intermittent leaching. Patterns of net S and N release depended on the management histories of the soils. Several kinetic models were evaluated for the ability to accommodate continuously decreasing rates, a large initial flush of mineralization, a mineralization lag within the first 13 wk of incubation, or a constant rate of release near the end of incubation. Mineralization in the forest E horizon was best described by a modified first‐order model with contributions from an easily mineralizable pool to account for an initial flush of S mineralization. Initial flushes of mineralization could be described by two simultaneous first‐order reactions, but the additional complexity of the model was unjustified, because contributions from the rapidly mineralizing pool did not extend beyond the first incubation interval. Soils from a field cultivated since 1905, a recently cleared field and, the organic layer from a native forest had fluctuating mineralization rates which appeared as lags in the cumulative amounts of inorganic element released over time. The lagged mineralization patterns were best described by consecutive reaction or Gompertz models. The Guggenheim method of fitting the first‐order model was demonstrated as an alternative to nonlinear regression. Fitting nonlinear kinetic models to incremental data from each incubation interval was superior to conventional approaches which use cumulative data obtained by summing the incremental observations. Information from net mineralization patterns was maximized by improving the methods of data analysis.