Masting not only enhances plant reproductive efficiency and fitness but also influences entire food webs. However, quantifying the year-to-year variability in masting has been a subject of intense debate. The commonly used coefficient of variation falls short in accounting for the serial dependence and the presence of zeros in individual-level datasets, limiting its suitability for phenotypic selection, heritability, and climate change studies. To overcome these limitations, our three case studies introduce volatility and periodicity as novel metrics that capture both high and low-frequency variance, even in the presence of zeros. By examining multiple plant species, including Sorbus aucuparia, Pinus pinea, Quercus robur, Quercus pubescens, and Fagus sylvatica, we demonstrate how these new metrics greatly enhance ecological interpretations and pave the way for significant advancements in the analysis of long-term, individual-plant datasets.
New Phytologist: measuring masting
