Many flowers require animal-mediated pollination in order to reproduce and in many cases the pollinators require plant resources for their reproduction.  While several studies have determined that bee communities, the most important group of pollinators, are not predictable over time and space, few studies report on the predictability of flowers on a community level.  It is also not known whether the predictability of flowering is a function of community type.  In this analysis, we attempt to quantify the consistency of flower communities on both a monthly and a seasonal basis in several plant community types.  Plant phenology data were collected for thirty-five years at the Rocky Mountain Biological Laboratory in Colorado, twenty years in the Santa Catalina Mountains of Arizona and nine years on the Sevilleta National Wildlife Refuge in New Mexico.  We calculated turnover rates of species in bloom from one season to the next (eg. spring to spring) and frequency of  bloom occurrences in the same month over all years of each study to determine the predictability of flowering communities across time and space.

Results/Conclusions:

Looking at the entire flower community as a resource for foraging pollinators, we found that flowers are not a reliable commodity, especially in extreme environments.  Frequency was used to look at reliability of bloom in particular months.  Only 77 of 393 (19.6%) species in Arizona bloomed in the same month every year, 4 of 71 (5.6%) in Colorado, and 9 of 109 (8.3%) in New Mexico.  Averaged for all species at a particular site, the percentage of years that a plant blooms in the same month ranges from 53.3% to 66.3%.  Turnover rates of species in bloom from one season to the next varied from 22.5% to 71.4% with annual turnover rates exceeding perennial turnover rates, except at the wet alpine meadow site in Colorado.  Turnover rates were generally higher at low elevation sites compared with high elevation sites.