Temporal Patterns in Species Flowering in Sky Islands of the Sonoran Desert Ecoregion

Highly variable moisture conditions in the Sonoran Desert play a significant role in shaping the composition and phenology of plants in this water-limited region. The flowering patterns of plants of the
Finger Rock trail, located in the Santa Catalina Mountains of southern Arizona, have been very carefully documented on approximately a weekly basis for nearly three decades. These observations, made along a gradient encompassing more than 4,000 ft in elevation, have revealed that flower presence, timing, and duration vary dramatically from year to year for many species in this unique environment. We developed a daily probability of flowering estimate for each species from the empirical records of presence or absence of flowering and implemented a clustering algorithm to elucidate recurrent temporal flowering patterns among groups of species. Several patterns emerged, and these patterns are consistent with plant functional types. First, across the elevation gradient, over half of all species that have been documented exhibit very low (<10%) probabilities of flowering in any given year, a pattern that exemplifies the high degree of variability and opportunism in this water-limited environment. In addition, there are small groups of species that are consistently seen in flower nearly every year and at nearly the same day of year, regardless of the preceding or concurrent climate conditions. The reliability with which these species in these groups flower, both from year to year and at the same time every year, increases with increasing elevation, and is also higher in summer than in the spring season. Clusters comprised mainly of annual species tended to show lower flowering probabilities and therefore greater variability in flowering; the opposite was generally true for perennial and woody species. The baseline patterns established in this analysis enhance our current understanding of seasonal flowering patterns in this region and serve as a critical step toward understanding
how the system may change under future climate conditions.