Shijia Peng

Long-term field observations typically are the “gold-standard” for inferences of phenological sensitivities in montane systems but are spatially limited. Herbarium specimens provide broader spatial coverage, but their utility to accurately capture montane phenology remains poorly known. We compared flowering phenology of 45 species inferred from herbarium specimens with comparable data from nearly 50 years of direct observations at the Rocky Mountain Biological Laboratory. Estimates of flowering time and phenological sensitivity to snow density were consistent between herbarium specimens and observations, but observations revealed secondary flowering peaks. Herbarium specimens additionally yielded shallower estimates of phenological sensitivity to spring temperature than did field observations. Across co-occurring species, “early” flowering individuals inferred from herbarium specimens, rather than the mean response across all individuals, may better approximate community-level phenological responses to temperature changes. We conclude that herbarium specimens are reliable resources for closing gaps in understanding phenological variation along elevational gradients of montane systems.

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.

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 of Viola species 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 of Viola spp. 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.

Summary: Conventional species distribution models (SDMs) typically consider only abiotic factors, thus overlooking critical biotic dimensions, including traits that play an important role in determining species' distributions in changing environments. Process‐based trait SDMs explicitly incorporate traits and have been applied to SDMs. However, their parameterization can be complex and require data that are unavailable for most species. Recently developed hierarchical trait‐based SDMs use widely available data and facilitate the incorporation of traits into SDMs at broad temporal, spatial, and taxonomic scales. However, despite their promise, existing hierarchical trait‐based SDMs fail to accommodate changing trait spaces under different climate conditions. Here, we provide a new, simplified framework for hierarchical trait‐based SDMs that integrates individuals' trait responses into forecasts of species range shifts in response to ongoing climate changes. We further briefly discuss the issue of non‐independence among species in hierarchical trait‐based SDMs. This work will contribute to an improved understanding of how traits affect species distributions along environmental and temporal gradients and facilitate the application of trait‐based SDMs at large scales under future climate change.

Climate change can lead to “secondary extinction risks” for plants owing to the decoupling of life-cycle events of plants and their pollinators (i.e., phenological mismatch). However, forecasting secondary extinction risk under future climate change remains challenging. We developed a new framework to quantify plants’ secondary extinction risk associated with phenological mismatch with bees using ca. 15,000 crowdsourced specimen records of Viola species and their solitary bee pollinators spanning 120 years across the eastern United States. We further examined latitudinal patterns in secondary extinction risk and explored how latitudinal variation in plant-pollinator specialization influence this risk. Secondary extinction risk of Viola spp. increases with latitude, indicating that future climate change likely will pose a greater threat to plant-bee pollinator networks at northern latitudes. Additionally, the sensitivity of secondary extinction risk to phenological mismatch with both generalist and specialist bee pollinators decreases with latitude: specialist bees display a sharper decrease at higher latitudes. Our findings demonstrate that existing conservation priorities identified solely based on primary extinction risk directly caused by climate change may not be sufficient to support self-sustaining populations of plants. Incorporating secondary extinction risk resulting from ecological mismatches between plants and pollinators into future global conservation frameworks should be carefully considered.

Conventional species distribution models (SDMs) typically consider only abiotic factors, thus overlooking critical biotic dimensions, including functional traits that play an important role determining species’ distributions in changing environments. Process-based models explicitly incorporate functional traits and have been applied to SDMs. However, their parameterization can be complex and require data that are unavailable for most species. Recently developed hierarchical trait-based models use widely available data and facilitate the incorporation of traits into SDMs at broad temporal, spatial, and taxonomic scales. Despite their promise, however, existing hierarchical trait-based models fail to accommodate changing trait spaces under different climate conditions. Here, we provide a new, simplified framework for hierarchical trait-based SDMs that integrate individuals’ trait responses into forecasts of species range shifts in response to ongoing climate changes. We further discuss the utility of phylogenetic information for building trait-based SDMs and holistically enhancing our understanding of species responses to global changes. This work will contribute to an improved understanding of how traits affect species distributions along environmental and temporal gradients and facilitate the application of trait-based SDMs across large temporal, spatial and taxonomic scales.

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.

Large-scale spatial patterns of species richness are one of the central issues in ecology. Although hypotheses based on effects of contemporary climate, evolutionary history and historical climate change have been employed to explain the mechanisms underlying species richness patterns, variation in relative contribution of different hypothesis remains a major challenge. Here, using newly-compiled distribution data with a spatial resolution of 100 * 100 km2 for 43,023 seed plant species in eastern Eurasia, we mapped species richness patterns for plants with different growth forms (i.e., woody vs. herbaceous) and range sizes (i.e., wide-ranged vs. narrow-ranged species), and compared the contribution of four hypotheses on these patterns, i.e., freezing tolerance hypothesis, historical climate change hypothesis, Janzen hypothesis and diversification rate hypothesis. We found that species richness of all seed plants presented a clear latitudinal gradient and was the highest in southwestern China and Central Asian mountains. Notably, species richness patterns and their dominant hypotheses differed between species groups. Historical climate change dominated richness patterns of overall, herbaceous and wide-ranged herbaceous species. The freezing tolerance hypothesis dominated those for all woody and wide-ranged woody species, while the Janzen hypothesis dominated narrow-ranged woody and herbaceous species. Our study suggests that different hypotheses contribute to large-scale species richness patterns via their dominant effects in different species groups. Interestingly, our study did not support the diversification rate hypothesis, but demonstrated high contribution of historical climate change to plant diversity, providing new perspectives on the mechanisms of plant diversity patterns in eastern Eurasia.