Soil respiration (SR) is a major component of the global carbon cycle and plays a fundamental role in ecosystem feedback to climate change. Empirical modelling is an essential tool for predicting ecosystem responses to environmental change, and also provides important data for calibrating and corroborating process-based models. In this study, we evaluated the performance of three empirical temperature–SR response functions (exponential, Lloyd–Taylor and Gaussian) at seven shrublands located within three climatic regions (Atlantic, Mediterranean and Continental) across Europe. We investigated the performance of SR models by including the interaction between soil moisture and soil temperature. We found that the best fit for the temperature functions depended on the site-specific climatic conditions. Including soil moisture, we identified thresholds in the three different response functions that improved the model fit in all cases. The direct soil moisture effect on SR, however, was weak at the annual time scale. We conclude that the exponential soil temperature function may only be a good predictor for SR in a narrow temperature range, and that extrapolating predictions for future climate based on this function should be treated with caution as modelled outputs may underestimate SR. The addition of soil moisture thresholds improved the model fit at all sites, but had a far greater ecological significance in the wet Atlantic shrubland where a fundamental change in the soil CO2 efflux would likely have an impact on the whole carbon budget.