Age–depth relationships in sedimentary archives such as lakes, wetlands and bogs are non-linear with irregular probability distributions associated with calibrated radiocarbon dates. Bayesian approaches are thus well-suited to understanding relationships between age and depth for use in paleoecological studies. Bayesian models for the accumulation of sediment and organic matter within basins combine dated material from one or more records with prior information about the behavior of deposition times (yr/cm) based on expert knowledge. Well-informed priors are essential to good modeling of the age–depth relationship, but are particularly important in cases where data may be sparse (e.g., few radiocarbon dates), or unclear (e.g., age-reversals, coincident dates, age offsets, outliers and dates within a radiocarbon plateau).