Current methods for numerical zonation of biostratigraphic sequences neither assess the reliability of zones identified nor provide any means of determining the number of zones that are 'significant' (based on structure in the data set, rather than the stochastic element). These problems can be overcome by using the broken-stick model to assess the significance of zones against a model of random distribution of zones within a sequence. The broken-stick model is described and its application demonstrated on actual data sets. Additionally, simulation modelling is used to assess the uncertainty of the location of individual zone markers, given the errors of the original data. These widely-applicable methods make it possible to identify zones rigorously and consistently. The potential in biostratigraphy and correlation includes the recognition, correlation and subdivision of chronostratipraphic units in long Quaternary sequences.
Keywords: Zonation; biostratigraphy; correlation; pollen analysis.