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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. 

We present the whole genome sequences of Dryas alaskensis, D. ajanensis, and D. integrifolia from plants collected from interior Alaska. We performed deep Illumina sequencing of a single leaf of each voucher. The sequence reads were then de novo assembled and conserved regions across all preassemblies were used to join contigs in a finishing step. The raw and assembled data is publicly available via Genbank. 

We present the whole genome sequences of 56 wild Erythroxylum species from Africa, China, and the American tropics. Deep Illumina sequencing was performed on a single leaf of each voucher. We de novo assembled sequence reads and then identified and used conserved regions across all preassemblies join contigs in a finishing step. The raw and assembled data is publicly available via Genbank. 

Erythroxylum macrophyllum is a morphologically variable and widely distributed species complex in Central and South America with several sub-specific taxa and numerous species included in its synonymy. A single variety grows in the Colombo-Venezuelan savanna region which can be distinguished from the rest of the E. macrophyllum complex by the size of leaves, cataphyll and stipule characteristics, and shape of calyx lobes. A molecular phylogeny reconstructed from 519 nuclear genes also reveals that the savanna variety is more closely related to E. acuminatum and E. pauciflorum than E. macrophyllum. This phylogenomic evidence also suggests Erythroxylum sect. Macrocalyx, to which E. macrophyllum belongs, is a polyphyletic taxonomic section. We thus propose elevating this variety to specific status, as Erythroxylum savannarum. We provide an updated taxonomic description, information about its habitat and distribution, and justify its informal IUCN cat- egorization of Near Threatened (NT) 

We report the rediscovery of the Critically Endangered cloud forest herb Gasteranthus extinctus , not seen since 1985. In 2019 and 2021, G. extinctus was recorded at five sites in the western foothills of the Ecuadorian Andes, 4–25 km from the type locality at the celebrated Centinela ridge. We describe the species’ distribution, abundance, habitat and conservation status and offer recommendations for further research and conservation efforts focused on G. extinctus and the small, disjunct forest remnants it occupies. 

Summary Leaf reflectance spectroscopy is emerging as an effective tool for assessing plant diversity and function. However, the ability of leaf spectra to detect fine‐scale plant evolutionary diversity in complicated biological scenarios is not well understood.We test if reflectance spectra (400–2400 nm) can distinguish species and detect fine‐scale population structure and phylogenetic divergence – estimated from genomic data – in two co‐occurring, hybridizing, ecotypically differentiated species ofDryas. We also analyze the correlation among taxonomically diagnostic leaf traits to understand the challenges hybrids pose to classification models based on leaf spectra.Classification models based on leaf spectra identified two species ofDryaswith 99.7% overall accuracy and genetic populations with 98.9% overall accuracy. All regions of the spectrum carried significant phylogenetic signal. Hybrids were classified with an average overall accuracy of 80%, and our morphological analysis revealed weak trait correlations within hybrids compared to parent species.Reflectance spectra captured genetic variation and accurately distinguished fine‐scale population structure and hybrids of morphologically similar, closely related species growing in their home environment. Our findings suggest that fine‐scale evolutionary diversity is captured by reflectance spectra and should be considered as spectrally‐based biodiversity assessments become more prevalent.