LAUSR

Abstract This study presents the first evaluation of apple flowering phenology models using data from 14 sites across the globe. The dataset includes large variability in growing climates, a prerequisite to investigate phenology models for use in climate change applications. Two flowering stages, early and full, were investigated allowing for unique model evaluation based on both statistical performance and biological assumptions. Two overarching phenology models (Sequential and Chill Overlap) and two sub-models of chill (Dynamic and Triangular) and heat (GDH and Sigmoidal) were tested. Flowering times from the different sites illustrated the differing effects of contrasting winter and spring temperatures. Sites with similar springtime temperatures, but different winter temperatures, had different flowering patterns (warmer winter sites flowered later). Across all analyses, results from the Chill Overlap model were better than those from the Sequential model. Of the Chill Overlap models, those fitted with the Triangular or Dynamic chill model and the GDH heat sub-model performed well statistically and met the assumptions of the model across both flowering stages. The mild sites in the analysis were least well represented, regardless of model selection. This global evaluation demonstrated that flowering modelling in temperate fruit trees would progress through appropriate choices of overarching model, sub-models and parameters.