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Response of soil respiration to temperature and soil moisture: Effects of different vegetation types on a small scale in the eastern Loess Plateau of China

Soil respiration is affected by vegetation and environmental conditions. The purpose of this study was to investigate the effect of vegetation type on soil respiration, temperature and water content, and their correlations on a small scale. We measured soil respiration rate (Rs) over a 3-year period at biweekly intervals in three plots in the eastern Loess Plateau of China, with the same soil texture but different vegetation types: pine forest, grassland, and shrub land. Simultaneously, soil temperature (Ts) at 10 cm depth and soil water content (Ws) within 10 cm depth were measured. The seasonal course of Rs and Ts showed a similar temporal variation in the three plots, with higher values in summer and autumn and lower values in winter and spring. No significant differences (P>0.05) were found between plots, except for Ws. The mean cumulative release of CO2 efflux from March to December was 962.5, 1027.5, and 1166.5 g C m− 2 a− 1 for plots 1, 2, and 3, respectively, with no significant difference between plots. The fitted exponential equations of Rs versus Ts from the 3-year data-set were significant (P < 0.05) with an R2 of 0.72, 0.64, and 0.72 for plots 1, 2, and 3, respectively. The calculated Q10 from the parameters of the fitted equation was 3.57, 3.52, and 3.61, and the R10 was 2.36, 2.03, and 2.37 μmol CO2 m− 2 s− 1 for plots 1, 2, and 3, respectively. Compared with the Ts, the correlations between Rs and Ws were not significant for the three plots. However, if the Ts was above 10°C, then their correlation was significant, and Ws had an impact on Rs. Four combined regression equations including two variables of Ts and Ws could be well established to model correlations between Rs and both Ts and Ws. Our study demonstrated that the exponential and power model fitted best and no significant different correlations of combined equations existed between the three plots. These results show that vegetation type had little impact on Rs, Ts, Ws, and their correlations, as well as on related parameters such as Q10 and R10. Therefore, while doing Rs research in a horizontal patchy vegetation conditions on a small area, the sampling location of measurements should focus on vertical dominant vegetation and ignore patch vegetation so as to reduce field work load.