Changes in the timing of species life cycle events (phenological shifts) disrupt ecosystems by altering the timing and duration of species interactions. Most phenology research identifies phenological shifts by changes in a single metric (e.g., mean, first), but since individuals vary in their timing, single metrics of phenology may be uninformative at the population level (i.e., first and mean phenological events do not shift uniformly). Therefore, in order to assess effects of phenological shifts on biological interactions, it is important to consider the distribution of phenological timing among a population. Analysis of high resolution phenological data for multiple systems (representing vertebrates, invertebrates, and plants) was used to see how well shifts in single metrics of phenology for two interacting species could predict shift in the timing and strength of their overlap.
Results/Conclusions
Results show that population level phenological distributions do not change uniformly and therefore single metrics could not predict changes in species overlap. This indicates that single metrics of phenology are inadequate for identifying the effect of phenological shifts on species interactions and predicting net outcomes at the community and ecosystem levels. Examining the entire distribution of phenological events enables better predictions about how phenological shifts affect population dynamics, interspecific interactions, and community composition. With climate change rapidly altering species phenologies, it is increasingly important to be able to accurately track phenological shifts and predict the net effects. We show that this requires consideration of individual variation in phenology.