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Abstract Many plant species alter both the timing and duration of their flowering in response to changing climate and often differ with respect to the magnitudes or directions of their phenological responses to climate changes. These shifts may have cumulative effects on the diversity of species simultaneously in flower throughout a given flowering season, resulting in periods of disproportionately high or low species richness of actively flowering community members relative to historical conditions. Although the potential for such changes to occur is well appreciated, few studies have assessed how climate trends have affected patterns of co‐flowering synchrony due to a scarcity of long‐term datasets documenting flowering duration across species in a community. In this study, we leveraged 1,908,706 plant specimens collected in flower to model the effects of warming throughout the past century on the daily species richness of actively flowering species by developing species‐specific phenoclimate models for 1848 plant species inhabiting 16 well‐documented plant communities across California. These communities are located across a variety of ecoregions, ranging from coastal marshes and grasslands to deserts, chaparral shrublands, and coniferous forests. The recurring patterns in the modeled community‐level flowering displays indicate that recent warming has consistently shortened the period during which many species flower concurrently, and that the bloom season has advanced by nearly 5 days on average. Accordingly, within every flora, recent warming was predicted to increase the daily species richness of flowers early in the local growing season, with corresponding reductions in species richness of flowers later in the growing season. Notably, patterns of change in community‐level bloom displays were driven primarily by differences among species in the timing of flowering onset, as termination dates tended to advance in unison with onset dates, resulting in minor changes to flowering duration among species. 

ABSTRACT 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 2837 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 range and phenology shifts operate concurrently, they predominantly 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 the identity and degree of flowering synchrony among co‐occurring species pairs. Together, these results demonstrate that shifts in phenology and species ranges act synergistically to restructure the flowering seasons across the conterminous United States, revealing wide variation in the pace and direction of change among biomes. 

Summary Phenological response to global climate change can impact ecosystem functions. There are various data sources from which spatiotemporal and taxonomic phenological data may be obtained: mobilized herbaria, community science initiatives, observatory networks, and remote sensing. However, analyses conducted to date have generally relied on single sources of these data. Siloed treatment of data in analyses may be due to the lack of harmonization across different data sources that offer partially nonoverlapping information and are often complementary. Such treatment precludes a deeper understanding of phenological responses at varying macroecological scales. Here, we describe a detailed vision for the harmonization of phenological data, including the direct integration of disparate sources of phenological data using a common schema. Specifically, we highlight existing methods for data harmonization that can be applied to phenological data: data design patterns, metadata standards, and ontologies. We describe how harmonized data from multiple sources can be integrated into analyses using existing methods and discuss the use of automated extraction techniques. Data harmonization is not a new concept in ecology, but the harmonization of phenological data is overdue. We aim to highlight the need for better data harmonization, providing a roadmap for how harmonized phenological data may fill gaps while simultaneously being integrated into analyses. 

Abstract Anthropogenic pressures on biodiversity necessitate efficient and highly scalable methods to predict global species distributions. Current species distribution models (SDMs) face limitations with large-scale datasets, complex interspecies interactions, and data quality. Here, we introduce EcoVAE, a framework of autoencoder-based generative models trained separately on nearly 124 million georeferenced occurrences from taxa including plants, butterflies and mammals, to predict their global distributions at both genus and species levels. EcoVAE achieves high precision and speed, captures underlying distribution patterns through unsupervised learning, and reveals interspecies interactions viain silicoperturbation analyses. Additionally, it evaluates global sampling efforts and interpolates distributions without relying on environmental variables, offering new applications for biodiversity exploration and monitoring. 

Summary Natural history collections (NHCs) are essential for studying biodiversity. Although spatial, temporal, and taxonomic biases in NHCs affect analyses, the influence of collector practices on biases remains largely unexplored.We utilized one million digitized specimens collected in the northeastern United States byc.10 000 collectors to investigate how collector practices shape spatial, temporal, and taxonomic biases in NHCs; and similarities and differences between practices of more‐ and less‐prolific collectors.We identified six common collector practices, or collection norms: collectors generally collected different species, from multiple locations, from sites sampled by others, during the principal growing season, species identifiable outside peak collecting months, and species from species‐poor families and genera. Some norms changed over decades, with different taxa favored during different periods. Collection norms have increased taxonomic coverage in NHCs; however, collectors typically avoided large, taxonomically complex groups, causing their underrepresentation in NHCs. Less‐prolific collectors greatly enhanced coverage by collecting during more months and from less‐sampled locations.We assert that overall collection biases are shaped by shared predictable collection norms rather than random practices of individual collectors. Predictable biases offer an opportunity to more effectively address biases in future biodiversity models. 

Abstract Global warming has caused widespread shifts in plant phenology among species in the temperate zone, but it is unclear how population‐level responses will scale to alter the structure of the flowering season at the community level. This knowledge gap exists largely because—while the climatic sensitivity of first flowering within populations has been studied extensively—little is known about the responsiveness of the duration of a population's flowering period. This limits our ability to anticipate how the entire flowering periods of co‐occurring species may continue to change under warming. Nonetheless, flowering sensitivity to temperature often varies predictably among species between and within communities, which may help forecast temperature‐related changes to a community's flowering season. However, no studies—empirical or theoretical—have assessed how patterns of variation in flowering sensitivity among species could scale to alter community‐level flowering changes under warming. Here, we provide a conceptual overview of how variation in the sensitivity of flowering onset and duration among species can mediate changes to a community's flowering season due to warming trends. Specifically, we focus on the effects of differences in (1) the mean sensitivity of flowering onset and duration among communities and (2) the sensitivity of flowering onsets and durations among species flowering sequentially through the season within a community. We evaluated the manner and degree in which these forms of between‐species variation in sensitivity might affect the structure of the flowering season—both independently and interactively—using simulations, which covered a wide but empirically informed range of parameter values and combinations representing distinct community‐level patterns. Our findings predict that communities across the temperate zone will exhibit varied and often contrasting flowering responses to warming across biomes, underscoring that accounting for the temperature sensitivity of both phenological onset and duration among species is essential for understanding community‐level flowering dynamics in a warming world. 

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. 

Darwin’s Naturalization Conundrum holds that both functional similarity and distinctiveness can facilitate biological invasions: invaders similar to natives may succeed through preadaptation to local abiotic conditions, whereas functionally distinct invaders may succeed by reducing competition. Yet the contexts in which either mechanism dominates are unclear. Prior research has primarily attributed variability in native–invasive differentiation to shifts in the balance between biotic and climatic barriers to invasion from local to regional scales. However, similarity and distinctiveness are frequent at both local and regional levels, indicating key drivers of native–invasive differentiation remain overlooked. Crucially, theory and evidence show that as climatic stress increases, competition weakens. This implies that harsh climates should favor invaders functionally similar to natives, whereas mesic climates should favor distinctiveness. However, this hypothesis has not been tested across climate regimes and functional traits. We addressed this gap by combining models of species distributions and flowering phenology for 2,810 species across the United States, estimating phylogenetic distance and phenological differentiation between natives and invasives relative to differentiation among co-occurring natives. In warm, humid regions, invasives flowered earlier, less synchronously, and were more distantly related to natives. In cold or dry regions, they flowered at similar or later times, more synchronously, and were more closely related than natives themselves. Across all climates, invasives consistently exhibited longer flowering durations, with little evidence of greater phenological plasticity. These findings reveal that Darwin’s Conundrum reflects a predictable continuum shaped by environmental context, highlighting climate as a key axis of invasion success. 

Climate change is altering the timing of species’ life-cycle events (i.e., phenology), but the rates of phenological shifts vary across taxa. These mismatches in phenological response may disrupt interactions between interdependent species, such as plants and their pollinators, which may lead to reduced plant reproduction via pollen limitation and thus contribute to secondary extinction risks for plants. However, secondary extinction risk is rarely assessed under future climate-change scenarios. Here, we used ca. 15,000 crowdsourced specimen records ofViolaspecies and their solitary bee pollinators, spanning 120 y across the eastern United States, and integrated climate data, phenological information, and species distribution models to quantify the risk of secondary plant extinction associated with phenological mismatch with their bee pollinators. We further examined geographical patterns in secondary extinction risk for plants and explored how their interactions between plants and generalist versus specialist pollinators influence such risk. Secondary local extinction risk ofViolaspp. increases with latitude, indicating that future climate change will pose a greater threat to plant–bee pollinator networks at northern latitudes. Additionally, the sensitivity of secondary local extinction risk to phenological mismatch with both generalist and specialist bee pollinators varies by latitude, with specialist bees showing a sharper decline at higher latitudes. Our findings demonstrate that existing conservation priorities based solely on primary extinction risk directly caused by climate change may be insufficient to support self-sustaining populations of plants. Thus, incorporating secondary extinction risk resulting from ecological mismatches between plants and pollinators into future global conservation frameworks should be carefully considered.