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Shifts in the timing of flowering are a conspicuous biological signal of climate change. These shifts have been documented across the globe for diverse communities. Although many species are flowering earlier, others have exhibited no shifts or delays in flowering., How species respond phenologically will shape interactions both with other community members and with the abiotic environment, altering fitness, abundance and ultimately persistence., To understand if variability in phenological response is influenced by evolutionary history, we tested for phylogenetic signal in shifts in flowering onset for 13 communities representing 116 families across the Northern Hemisphere. We compared the fit of models of neutral evolution (Brownian Motion) with models that incorporate selection (Ornstein-Uhlenbeck)., We found significant signal in whether species had shifted and the magnitude of response, with both traits conforming to an Ornstein-Uhlenbeck model of trait evolution., Synthesis. These results show there is global phylogenetic signal in the direction and magnitude of shifts in flowering onset and indicate selection has shaped flowering time responses of related species under climate change; thus, environmentally determined optima may constrain whether and to what degree species respond phenologically to climate change. Our findings further demonstrate the value of testing for phylogenetic signal across multiple communities and comparing multiple models of trait evolution. [ABSTRACT FROM AUTHOR]

Ecological networks of two interacting guilds of species, such as flowering plants and pollinators, are common in nature, and studying their structure can yield insights into their resilience to environmental disturbances. Here we develop analytical methods for exploring the strengths of interactions within bipartite networks consisting of two guilds of phylogenetically related species. We then apply these methods to investigate the resilience of a plant-pollinator community to anticipated climate change. The methods allow the statistical assessment of, for example, whether closely related pollinators are more likely to visit plants with similar relative frequencies, and whether closely related pollinators tend to visit closely related plants. The methods can also incorporate trait information, allowing us to identify which plant traits are likely responsible for attracting different pollinators. These questions are important for our study of 14 prairie plants and their 22 insect pollinators. Over the last 70 years, six of the plants have advanced their flowering, while eight have not. When we experimentally forced earlier flowering times, five of the six advanced-flowering species experienced higher pollinator visitation rates, whereas only one of the eight other species had more visits; this network thus appears resilient to climate change, because those species with advanced flowering have ample pollinators earlier in the season. Using the methods developed here, we show that advanced-flowering plants did not have a distinct pollinator community from the other eight species. Furthermore, pollinator phylogeny did not explain pollinator community composition; closely related pollinators were not more likely to visit the same plant species. However, differences among pollinator communities visiting different plants were explained by plant height, floral color, and symmetry. As a result, closely related plants attracted similar numbers of pollinators. By parsing out characteristics that explain why plants share pollinators, we can identify plant species that likely share a common fate in a changing climate. [ABSTRACT FROM AUTHOR]

Climate change is known to affect regional weather patterns and phenology; however, we lack understanding of how climate drives phenological change across local spatial gradients. This spatial variation is critical for determining whether subpopulations and metacommunities are changing in unison or diverging in phenology. Divergent responses could reduce synchrony both within species (disrupting gene flow among subpopulations) and among species (disrupting interspecific interactions in communities). We also lack understanding of phenological change in environments where life history events are frequently aseasonal, such as the tropical, arid, and semi-arid ecosystems that cover vast areas. Using a 33-year-long dataset spanning a 1,267-m semi-arid elevational gradient in the southwestern United States, we test whether flowering phenology diverged among subpopulations within species and among five communities comprising 590 species. Applying circular statistics to test for changes in year-round flowering, we show flowering has become earlier for all communities except at the highest elevations. However, flowering times shifted at different rates across elevations likely because of elevation-specific changes in temperature and precipitation, indicating diverging phenologies of neighboring communities. Subpopulations of individual species also diverged at mid-elevation but converged in phenology at high elevation. These changes in flowering phenology among communities and subpopulations are undetectable when data are pooled across the gradient. Furthermore, we show that nonlinear changes in flowering times over the 33-year record are obscured by traditional calculations of long-term trends. These findings reveal greater spatiotemporal complexity in phenological responses than previously recognized and indicate climate is driving phenological reshuffling across local spatial gradients. • Flowering time is diverging among communities across an elevational gradient • Divergence reflects nonlinear shifts in flowering phenology over three decades • Climatic variables have also changed differently across space and over time • Changing climate is driving phenological reshuffling across local spatial gradients Using 33 years of data, Rafferty et al. test whether flowering times have diverged for neighboring communities comprising 590 species across an elevational gradient. Divergent and nonlinear shifts in flowering time are related to elevation-specific changes in temperature and precipitation and will likely alter species interactions and gene flow. [ABSTRACT FROM AUTHOR]