Soil temperature and biotic factors drive the seasonal variation of soil respiration in a maize (Zea mays L.) agricultural ecosystem

• Published in: Plant and soil 2007-02, Vol.291 (1/2), p.15-26
• Main Authors: Han, Guangxuan, Zhou, Guangsheng, Xu, Zhenzhu, Yang, Yang, Liu, Jingli, Shi, Kuiqiao
• Format: Article
• Language: English
• Subjects: Agricultural ecosystems; Agricultural soils; Agronomy. Soil science and plant productions; Biochemistry and biology; Biological and medical sciences; Biotic factors; Chemical, physicochemical, biochemical and biological properties; Corn; Forest soils; Fundamental and applied biological sciences. Psychology; Generalities; Growing seasons; Physics, chemistry, biochemistry and biology of agricultural and forest soils; Seasonal variations; Soil biochemistry; Soil ecology; Soil microorganisms; Soil respiration; Soil science; Soil temperature; Soil water; Zea mays
• ISSN: 0032-079X; 1573-5036
• DOI: 10.1007/s11104-006-9170-8

The diurnal and seasonal variation of soil respiration (SR) and their driving environmental factors were studied in a maize ecosystem during the growing season 2005. The diurnal variation of SR showed asymmetric patterns, with the minimum occurring around early morning and the maximum around 13:00 h. SR fluctuated greatly during the growing season. The mean SR rate was 3.16 μmol CO2 m-2 s-1, with a maximum of 4.87 pmol CO2 m-2 s-1 on July 28 and a minimum of 1.32 μmol CO2 m-2 s-1 on May 4. During the diurnal variation of SR, there was a significant exponential relationship between SR and soil temperature (T) at 10 cm depth: SR = αeβT. At a seasonal scale, the coefficient α and β fluctuated because the biomass (B) increased α, and the net primary productivity (NPP) of maize markedly increased β of the exponential equation. Based on this, we developed the equation SR = (aB + b)e(cNPP+d)T to estimate the magnitude of SR and to simulate its temporal variation during the growth season of maize. Most of the temporal variability (93%) in SR could be explained by the variations in soil temperature, biomass and NPP of maize. This model clearly demonstrated that soil temperature, biomass and NPP of maize combined to drive the seasonal variation of SR during the growing season. However, only taking into account the influence of soil temperature on SR, an exponential equation over- or underestimated the magnitude of SR and resulted in an erroneous representation of the seasonal variation in SR. Our results highlighted the importance of biotic factors for the estimation of SR during the growing season. It is suggested that the models of SR on agricultural sites should not only take into account the influence of soil temperature, but also incorporate biotic factors as they affect SR during the growing season.