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This article in SSSAJ

  1. Vol. 68 No. 4, p. 1256-1265
    Received: Nov 12, 2003

    * Corresponding author(s): weijin.wang@nrm.qld.gov.au
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Predicting Soil Nitrogen Mineralization Dynamics with a Modified Double Exponential Model

  1. W. J. Wang *ac,
  2. C. J. Smithb and
  3. D. Chena
  1. a School of Resource Management, the Univ. of Melbourne, Parkville 3052, Victoria, Australia
    c Present address: NR&M, 80 Meiers Rd, Indooroopilly, Brisbane, Qld. 4068, Australia
    b CSIRO Land and Water, GPO Box 1666, Canberra 2601, ACT, Australia


The double exponential model that separates mineralizable soil organic N into active (N a) and slow (N s) pools has been widely used to describe net N mineralization dynamics. However, the biological meanings of the model parameters and their relationships to soil properties and environmental conditions remain to be elucidated. In the present study, 18 soils were incubated at 35°C and 55% water-holding capacity (WHC) for 41 wk and two soils at 16 factorial combinations of temperature (5, 15, 25, or 35°C) and moisture (8, 11, 15, or 19%) for 29 wk. Although the model closely fitted the net N mineralization data, the model parameters often appeared to lack biological meanings and could vary with incubation time, temperature, and soil moisture in unpredictable manners. Thus, the conventional double exponential model was modified by (i) using defined mineralization rate constants for N a and N s under standard temperature (35°C) and moisture (approximately 55% WHC); and (ii) using soil-specific and fixed N a and N s values to estimate temperature- and moisture-dependent rate constants under non-standard conditions. This technique basically eliminated the time effect on the estimates of pool sizes and resulted in the rate constants with a consistent Q 10 response to temperature and linear response to moisture changes. Predictions of soil net N mineralization dynamics under field conditions using the parameters estimated in laboratory agreed closely with the measured data. Multiple regression analysis indicated that the size of N a is correlated with the initial water-soluble organic N and microbial biomass in soil, whereas N s represents the combined effects of all the factors regulating long-term net N mineralization.

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