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Global change is altering the phenology and geographic ranges of flowering species, with potentially profound consequences for the timing and composition of floral resources and the seasonal structure of ecological communities. However, shifts in flowering phenology and species distributions have historically been studied in isolation due to disciplinary silos and limited data, leaving critical gaps in our understanding of their combined effects. To address this, we used millions of herbarium and occurrence records to model phenological and range shifts for 2,837 plant species in the United States across historical, recent, and projected climate and land cover conditions, enabling us to scale responses from species to communities, and from local to continental geographies. Our analysis reveals that communities are shifting toward earlier, longer flowering seasons in most biomes, with co-flowering species richness increasing at the edges of the season and declining at historical peaks—trends projected to intensify under ongoing environmental trends. Although these shifts operate concurrently, they affect different aspects of the flowering season: phenological changes primarily alter seasonality—its start, end, and duration—and co-flowering diversity at the edges of the season, while range shifts more strongly influence co-flowering species richness during historical seasonal peaks, and attributes tied to community composition, such as patterns of flowering synchrony among co-occurring species. Together, these results demonstrate that shifts in phenology and species ranges act synergistically to restructure the flowering seasons across North America, revealing wide variation in the pace and magnitude of change among biomes. 

Forecasting the impacts of changing climate on the phenology of plant populations is essential for anticipating and managing potential ecological disruptions to biotic communities. Herbarium specimens enable assessments of plant phenology across broad spatiotemporal scales. However, specimens are collected opportunistically, and it is unclear whether their collection dates – used as proxies of phenological stages – are closest to the onset, peak, or termination of a phenophase, or whether sampled individuals represent early, average, or late occurrences in their populations. Despite this, no studies have assessed whether these uncertainties limit the utility of herbarium specimens for estimating the onset and termination of a phenophase. Using simulated data mimicking such uncertainties, we evaluated the accuracy with which the onset and termination of population‐level phenological displays (in this case, of flowering) can be predicted from natural‐history collections data (controlling for biases in collector behavior), and how the duration, variability, and responsiveness to climate of the flowering period of a species and temporal collection biases influence model accuracy. Estimates of population‐level onset and termination were highly accurate for a wide range of simulated species' attributes, but accuracy declined among species with longer individual‐level flowering duration and when there were temporal biases in sample collection, as is common among the earliest and latest‐flowering species. The amount of data required to model population‐level phenological displays is not impractical to obtain; model accuracy declined by less than 1 day as sample sizes rose from 300 to 1000 specimens. Our analyses of simulated data indicate that, absent pervasive biases in collection and if the climate conditions that affect phenological timing are correctly identified, specimen data can predict the onset, termination, and duration of a population's flowering period with similar accuracy to estimates of median flowering time that are commonplace in the literature. 

Phenology varies widely over space and time because of its sensitivity to climate. However, whether phenological variation is primarily generated by rapid organismal responses (plasticity) or local adaptation remains unresolved. Here we used 1,038,027 herbarium specimens representing 1,605 species from the continental United States to measure flowering-time sensitivity to temperature over time (Stime) and space (Sspace). By comparing these estimates, we inferred how adaptation and plasticity historically influenced phenology along temperature gradients and how their contributions vary among species with different phenology and native climates and among ecoregions differing in species composition. Parameters Sspace and Stime were positively correlated (r = 0.87), of similar magnitude and more frequently consistent with plasticity than adaptation. Apparent plasticity and adaptation generated earlier flowering in spring, limited responsiveness in late summer and delayed flowering in autumn in response to temperature increases. Nonetheless, ecoregions differed in the relative contributions of adaptation and plasticity, from consistently greater importance of plasticity (for example, southeastern United States plains) to their nearly equal importance throughout the season (for example, Western Sierra Madre Piedmont). Our results support the hypothesis that plasticity is the primary driver of flowering-time variation along temperature gradients, with local adaptation having a widespread but comparatively limited role. 

Summary Anthropogenetic climate change has caused range shifts among many species. Species distribution models (SDMs) are used to predict how species ranges may change in the future. However, most SDMs rarely consider how climate‐sensitive traits, such as phenology, which affect individuals' demography and fitness, may influence species' ranges.Using > 120 000 herbarium specimens representing 360 plant species distributed across the eastern United States, we developed a novel ‘phenology‐informed’ SDM that integrates phenological responses to changing climates. We compared the ranges of each species forecast by the phenology‐informed SDM with those from conventional SDMs. We further validated the modeling approach using hindcasting.When examining the range changes of all species, our phenology‐informed SDMs forecast less species loss and turnover under climate change than conventional SDMs. These results suggest that dynamic phenological responses of species may help them adjust their ecological niches and persist in their habitats as the climate changes.Plant phenology can modulate species' responses to climate change, mitigating its negative effects on species persistence. Further application of our framework will contribute to a generalized understanding of how traits affect species distributions along environmental gradients and facilitate the use of trait‐based SDMs across spatial and taxonomic scales.