Abstract: Although there is a quantitative method that is commonly used for identifying mast-seeding behaviour of a plant population based on the coefficient of variation (i.e. CV is standard deviation/mean>1), there is no general quantitative method for delineating “mast” as opposed to “non-mast” years. Mast years are, however, described qualitatively as years when “large”, “unusually large” and “high” seed production occurs. The use of a consistent and generally applicable method for delineating mast years across species and plant populations is important for synthesizing knowledge of the causes and consequences of mast seeding, which could be confounded by using different methods among studies. We examine six quantitative methods for identifying mast years: four methods from the literature and two methods developed here. We use 36 seed production datasets covering a variety of species with ≥10 years of data to test the performance of these six methods. For each method, we quantify the percentage of the datasets to which the method could be successfully applied, the magnitude of the mast year relative to the mean, the frequency of mast years and the occurrence of consecutive mast years. The majority of the methods failed to meet the criteria for a suitable method. The best method used the number of standard deviates (standardized deviate method) of the annual mean seed production from the long-term mean of the dataset to identify mast-seeding years. General results from the standardized deviate method include that the occurrence of mast-seeding years is largely unrelated to plant population CV, but similar across species and data collection methods.