- 期刊
- OpenAccess
Influence of Environmental Factors on Variation of Soil Respiration Rate in a Wheat- Maize Rotation Field in China
並列摘要
Soil respiration in agroecosystem, especially in wheat-maize rotation system is a important component in carbon cycle, which is a key index of soil CO_2 efflux from soil to atmosphere. To discern the dynamic variation of soil respiration and the relationship between soil respiration and environmental factors, a experiment was conducted in the experimental field of Qingdao agricultural university. In this study CO_2 soil efflux was measured by automated soil CO_2 flux system (LI-8100A) during the periods from March to June (maize season) and from June to October (wheat season) in 2014, meanwhile the driving environmental factors were measured by eddy covariance system. The CO_2 emission rate from wheat soil varied from 1.093 μmol CO_2 m^(-2)s^(-1) in March to 6.028 μmol CO_2 m^(-2)s^(-1) in June and that for maize soil from 1.80 μmol CO_2 m^(-2)s^(-1) in October to 10.36 μmol CO_2 m^(-2)s^(-1) in July. The dynamics of GPP was similar to a shape ＂W＂ during wheat and maize seasons. Two peaks of GPP lied in April and August. To find the influence of the driving factors to soil respiration, the correlation analysis was processed between soil respiration and seven environment factors. The analysis showed that there was a significant correlation relationship between soil respiration rate and soil temperature at 10 cm depth and soil water content at 10 cm depth. To clearly understand the relationship between soil respiration and soil temperature and soil water content at 10 cm depth, three models (y = ae^(bx), y = ae^(bx1_) e^(cx_2), and y = ae^(bx_1)x^c_2) were used. The results showed that the bivariate compound model was the best model to depict the relationship between soil respiration rate and soil temperature and soil water content at 10 cm depth. About 88% and 78% of temporal variability in soil respiration could be explained by the variations in soil temperature and soil water content during wheat and maize season, respectively, highest in these three regression models.
延伸閱讀
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