Although correlations between soil respiration (R-s) and environmental factors in different ecosystems have been extensively investigated, results based on long-term experiments are limited. In this study, we analyzed the correlations between Rs and soil temperature (T-s), moisture (theta), the normalized difference vegetation index (NDVI), and soil organic matter (SOM) based on an 11-year field campaign in abandoned farmland (HD) and bare land (LD) areas with a Cambisol soil type in the eastern Loess Plateau of China. The results showed that the mean annual R-s and annual temperature sensitivity (Q(10)) values in HD were significantly larger than those in LD during the measurement period. Rs and the annual contribution ratio (R-ratio) of root respiration (R-r) to Rs in HD increased significantly with vegetation recovery years. On the annual scale, R-s was controlled primarily by T-s at both sites. However, in the summer months, R-s was controlled by. rather than T-s. A two-variable model, including T-s and theta, could more accurately predict the temporal variations in R-s at the annual and seasonal time scales than a single-variable model, and the explanatory power of the equations in HD was significantly larger than that in LD. On the interannual scale, variations in the annual R-s and R-r showed significant positive correlations with the annual theta and NDVI and SOM, and negative correlations with T-s in HD. Moreover, the annual Q10 was significantly positively related to theta in HD. In LD, the only significant relationship was between the annual Q(10) and the annual theta. All differences between HD and LD in R-s, Ts, and. and their correlations were attributed to differences in vegetation. Our findings highlight the importance of long-term observations for the accurate estimation of CO2 efflux in semiarid regions and the impact of vegetation changes on soil respiration.