When the drivers of biological turnover in space are the same as those that drive turnover through time, space can be substituted for time to model how patterns of variation are predicted to change into the future. These space-for-time substitutions are widely used in ecological modeling but have only recently been applied to the study of microevolutionary processes, particularly over relatively fine spatial and temporal scales. Here, we review recent examples that have employed space-for-time substitution to study genetic patterns on stationary and non-stationary landscapes and examine whether space can reliably substitute for time in studies of population divergence, genetic structure, and adaptive evolution. Although there are only a relatively few examples, several recent studies were excellently crafted to provide valuable insights into the conditions governing the validity of space-for-time substitutions applied to population genetic data. We found that, although caution should be taken, spacefor-time substitutions appear valid for studying microevolutionary processes on both stationary and non-stationary landscapes. Further studies can help to evaluate the conditions under which space-for-time substitutions are reliable. When these methods are reliable, they will play an important role in modeling genetic responses to environmental change, population viability on non-stationary landscapes, and patterns of divergence and adaptation.