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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. 

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. 

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 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. 

Last month, Duke University in North Carolina announced that it was shuttering its herbarium. The collection consists of nearly 1 million specimens representing the most comprehensive and historic set of plants from the southeastern United States. It also includes extensive holdings from other regions of the world, especially Mexico, Central America, and the West Indies. Duke plans to disperse these samples to other institutions for use or storage over the next 2 to 3 years, but this decision reflects a lack of awareness by academia that such collections are being leveraged as never before. With modern technologies spanning multiple fields of study, the holdings in herbaria and other natural history collections are not only facilitating a deeper and broader understanding of the past and present world but are also providing tools to meet both known and unforeseen challenges facing humanity. Science and society can hardly risk the loss of such an important resource.