Diverse Developmental Responses to Warming Temperatures Underlie Changes in Flowering Phenologies

Climate change has resulted in increased temperature means across the globe. Many angiosperms flower earlier in response to rising temperature and the phenologies of these species are reasonably well predicted by models that account for spring (early growing season) and winter temperatures. Surprisingly, however, exceptions to the general pattern of precocious flowering are common. Many species either do not appear to respond or even delay flowering in, or following, warm growing seasons. Existing phenological models have not fully addressed such exceptions to the common association of advancing phenologies with warming temperatures. The phenological events that are typically recorded (e.g., onset of flowering) are but one phase in a complex developmental process that often begins one or more years previously, and flowering time may be strongly influenced by temperature over the entire multi-year course of flower development. We propose a series of models that explore effects of growing-season temperature increase on the multiple processes of flower development and how changes in development may impact the timing of anthesis. We focus on temperate forest trees, which are characterized by preformation, the initiation of flower primordia one or more years prior to anthesis. We then synthesize the literature on flower development to evaluate the models. Although fragmentary, the existing data suggest the potential for temperature to affect all aspects of flower development in woody perennials. But, even for relatively well studied taxa, the critical developmental responses that underlie phenological patterns are difficult to identify. Our proposed models explain the seemingly counter-intuitive observations that warmer growing-season temperatures delay flowering in many species. Future research might concentrate on taxa that do not appear to respond to temperature, or delay flowering in response to warm temperatures, to understand what processes contribute to this pattern.