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RESEARCH ARTICLE

Seasonal changes in microbial function and diversity associated with stubble retention versus burning

F. C. Hoyle A B and D. V. Murphy A
+ Author Affiliations
- Author Affiliations

A School of Earth and Geographical Science, Faculty of Natural and Agricultural Sciences, University of Western Australia, Crawley, WA 6009, Australia.

B Corresponding author. Email: fhoyle@agric.wa.gov.au

Australian Journal of Soil Research 44(4) 407-423 https://doi.org/10.1071/SR05183
Submitted: 21 November 2005  Accepted: 21 February 2006   Published: 27 June 2006

Abstract

The long-term (16-year) effect of stubble management (i.e. retained or burnt) on the size of the microbial community (microbial biomass-C and -N), microbial community structure (PLFA), and function (CO2-C evolution, gross N transformation rates, enzymatic activity, and community level physiological profiles) was investigated on 4 occasions during a single wheat-growing season using soil collected from the low-rainfall (<250 mm) region of Western Australia. Significant differences (P < 0.001) in microbial community structure and function were determined for different sampling times by phospholipid fatty acid (PLFA) analyses and community level physiological profiles (CLPP). However, neither PLFA nor CLPP analyses identified differences between stubble treatments. In contrast to total soil organic matter-C, for which no treatment differences were evident, microbial biomass-C was 34% and CO2-C evolution 61% greater in stubble-retained treatments than in burnt-stubble treatments in the 0–0.05 m soil layer. Seasonal increases in microbial biomass-C (P < 0.001) were on average twice as large and CO2-C evolution (P < 0.001) nearly 4 times greater in September during crop flowering compared with other sampling times. In contrast, microbial biomass-N remained constant throughout the entire sampling period. Stubble-retained treatments also demonstrated significantly greater (P < 0.05) levels of arginine ammonification, acid phosphatase and β-glucosidase enzyme activity on average compared with burnt-stubble treatments. However, the effect (P = 0.05) of stubble treatment on gross N mineralisation, nitrification, or immobilisation rates was seasonally dependent with burnt-stubble treatments demonstrating lower gross N mineralisation rates than retained-stubble treatments in November. Gross N mineralisation was lower (37–83% on average) than potential gross nitrification rates (estimated in the presence of excess NH4+) measured from May to September. The rate of potential gross nitrification was observed to decline significantly (P = 0.06) in November and as a result, more closely matched gross N mineralisation rates. Potential gross nitrification rates were also up to 6 times greater than microbial immobilisation of NH4+, indicating that this would be the primary consumptive process in the presence of NH4+. Whilst potential nitrification rates in the presence of excess NH4+ were high, low soil NO3 concentrations indicate that plant/microbial demand for NO3 and NH4+ exceeded the supply capacity. For example, actual gross nitrification rates (determined in the presence of 15N-labelled NO3-) were only greater than gross N mineralisation in May, indicating N supply constrained nitrification at other sampling times. Findings illustrate that increased wheat yields of 31% in this study were associated with the retention of stubble. Further they demonstrate that changes in stubble management significantly influenced the mass and activity of microorganisms (and in some cases N cycling), whilst having little influence on community diversity.

Additional keywords: 15N isotopic pool dilution, FLUAZ, nitrogen, carbon.


Acknowledgments

This work was funded by the Grains Research and Development Corporation (Soil Biology Initiative), with grant support from the Department of Agriculture and Food Western Australia and the University of Western Australia. The authors thank Glen Reithmuller for access to and maintenance of the field trial, Jaymie Norris for GC analyses of PLFA samples, and Dr Richard Cookson for multivariate statistical advice.


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