Flowering time is sensitive to climatic conditions and has been a frequent focus of climate change research, yet the implications of phenological shifts for hybridization within plant communities have seldom been explored. Reproductive overlap between interfertile species is a key requirement for the production of hybrid (inter -species) offspring, and climate change may influence the opportunities for hybrid production through changes to species' flowering time, duration, and overlap with other species. To test how climate variation influences flowering overlap between hybridizing species, we analyzed 45 years of flowering phenology data on 2 common plants in the Rocky Mountains of Colorado that are known to produce hybrids (Potentilla pulcherrima and Potentilla hippiana, family Rosaceae). We estimated flowering overlap from flowering distributions in 2 ways that focus on how similar species are in terms of flowering time ( "symmetric overlap ") or relative floral abundance across the season ( "relative overlap "). We found that the 2 species had similar phenological responses to most climate variables. Both flowered earlier in years with warm, dry growing seasons preceded by earlier snowmelt and winters with less snow, and later in cool, wet grow-ing seasons with later snowmelt after winters with heavy snowfall. Precipitation was the best predictor of flowering time overlap. In wetter years, both species flowered later and longer, and reached peak flowering date at a more similar time in the growing season. While our results suggest that precipitation patterns influence the extent of flowering overlap between these 2 species in any given growing season, precipitation has not consistently increased or decreased in this region over the past 45 years, and therefore we do not see a consistent signature of global climate change on flowering overlap. Finally, we found that even though temperature was an important predictor of flowering phenology within each species, it was not a major driver of overlap between species, emphasizing that data on individual species responses can-not necessarily predict how climate change will affect species interactions.
