UC Riverside

Shifts in the timing of life history events have become an important source of information about how organisms are responding to climate change. Phenological data have generally been treated as purely temporal, with scant attention to the inherent spatial aspects of such data. However, phenological data are tied to a specific location, and considerations of sampling design, both over space and through time, can critically affect the patterns that emerge. Focusing on flowering phenology, we describe how purely spatial shifts, such as adding new study plots, or the colonization of a study plot by a new species, can masquerade as temporal shifts. Such shifts can look like responses to climate change but are not. Furthermore, the same aggregate phenological curves can be composed of individuals with either very different or very similar phenologies. We conclude with a set of recommendations to avoid ambiguities arising from the spatiotemporal duality of phenological data.