Search for: All records

Summary Reflectance spectroscopy is a rapid method for estimating traits and discriminating species. Spectral libraries from herbarium specimens represent an untapped resource for generating broad phenomic datasets across space, time, and taxa.We conducted a proof‐of‐concept study using trait data and spectra from herbarium specimens up to 179 yr old, alongside data from recently dried and pressed leaves. We validated model accuracy and transferability for trait prediction and taxonomic discrimination.Trait models from herbarium spectra predicted leaf mass per area (LMA) withR² = 0.94 and %RMSE = 4.86%. Models for LMA prediction were transferable between herbarium and pressed spectra, achievingR² = 0.88, %RMSE = 8.76% for herbarium to pressed spectra, andR² = 0.76, %RMSE = 10.5% for the reverse transfer. Discriminant models classified leaf spectra from 25 species with 74% accuracy, and classification probabilities were significantly associated with several herbarium specimen quality metrics.The results validate herbarium spectral data for trait prediction and taxonomic discrimination, and demonstrate that trait modeling can benefit from the complementary use of pressed‐leaf and herbarium‐leaf spectral datasets. These promising advancements help to justify the spectral digitization of plant biodiversity collections and support their application in broad ecological and evolutionary investigations. 

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. 

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. 

We investigate the roles of linguistic and sensory experience in the early-produced visual, auditory, and abstract words of congenitally-blind toddlers, deaf toddlers, and typicallysighted/ hearing peers. We also assess the role of language access by comparing early word production in children learning English or American Sign Language (ASL) from birth, versus at a delay. Using parental report data on child word production from the MacArthur-Bates Communicative Development Inventory, we found evidence that while children produced words referring to imperceptible referents before age 2, such words were less likely to be produced relative to words with perceptible referents. For instance, blind (vs. sighted) children said fewer highly visual words like “blue” or “see”; deaf signing (vs. hearing) children produced fewer auditory signs like HEAR. Additionally, in spoken English and ASL, children who received delayed language access were less likely to produce words overall. These results demonstrate and begin to quantify how linguistic and sensory access may influence which words young children produce. 

We describe Diastrophus wushei Davis & Nastasi sp. nov. and D. renai Davis & Nastasi sp. nov., two gall wasp species collected on Wushe Mountain, Taiwan by the late Henry Townes. These species represent the first Diastrophini and potentially the first non-Fagaceae associated species of gall wasp described from Taiwan. We speculate on potential hosts plants for further study and possible avenues to elucidate their biology.  

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.