We use a simulation model to generate tree-ring like data with systematic growth forcings and subject it to two methods of standardization: Regional Curve Standardization (RCS) and Negative Exponential Curve Standardization (NECS). The coherency between very low frequency forcings (hundreds of years) and the chronologies was higher when RCS was used to detrend the component series. There was no difference between standardization methods at decadal or annual time scales. We found that the detectability of systematic forcings was heavily dependent on amplitude and wavelength of the input signal as well as the number of trees simulated. These results imply that for very long tree-ring chronologies where the analyst is interested in low-frequency variability, RCS is a better method for detrending series if the requirements for that method can be met. However, in the majority of situations NECS is an acceptable detrending method. Most critically, we found that multi-centennial signals can be recovered using both methods.