4.7 Article

Estimating the active and total soil microbial biomass by kinetic respiration analysis

Journal

BIOLOGY AND FERTILITY OF SOILS
Volume 32, Issue 1, Pages 73-81

Publisher

SPRINGER-VERLAG
DOI: 10.1007/s003740000219

Keywords

active microbial biomass; substrate-induced respiration; sustaining microbial biomass; growth-response description

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A model describing the respiration curves of glucose-amended soils was applied to the characterization of microbial biomass. Both lag and exponential growth phases were simulated. Fitted parameters were used for the determination of the growing and sustaining fractions of the microbial biomass as well as its specific growth rate (mu (max)) These microbial biomass characteristics were measured periodically in a loamy silt and a sandy loam soil incubated under laboratory conditions. Less than 1% of the biomass oxidizing glucose was able to grow immediately due to the chronic starvation of the microbial populations in situ. Glucose applied at a rate of 0.5 mg C g(-1) increased that portion to 4-10%. Both soils showed similar dynamics with a peak in the growing biomass at day 3 after initial glucose amendment, while the total (sustaining plus growing) biomass was maximum at day 7. The microorganisms in the loamy silt soil showed a larger growth potential, with the growing biomass increasing 16-fold after glucose application compared to a sevenfold increase in the sandy loam soil. The results gained by the applied kinetic approach were compared to those obtained by the substrate-induced respiration (SIR) technique for soil microbial biomass estimation, and with results from a simple exponential model used to describe the growth response. SIR proved to be only suitable for soils that contain a sustaining microbial biomass and no growing microbial biomass. The exponential model was unsuitable for situations where a growing microbial biomass was associated with a sustaining biomass. The kinetic model tested in this study (Panikov and Sizova 1996) proved to describe all situations in a meaningful, quantitative and statistically reliable way.

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