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  1. ; ; ( , Applications in Plant Sciences)
    Premise

    Herbarium specimens have been used to detect climate‐induced shifts in flowering time by using the day of year of collection (DOY) as a proxy for first or peak flowering date. Variation among herbarium sheets in their phenological status, however, undermines the assumption thatDOYaccurately represents any particular phenophase. Ignoring this variation can reduce the explanatory power of pheno‐climatic models (PCMs) designed to predict the effects of climate on flowering date.

     Methods

    Here we present a protocol for the phenological scoring of imaged herbarium specimens using an ImageJ plugin, and we introduce a quantitative metric of a specimen's phenological status, the phenological index (PI), which we use inPCMs to control for phenological variation among specimens ofStreptanthus tortuosus(Brassicaceeae) when testing for the effects of climate onDOY. We demonstrate that includingPIas an independent variable improves model fit.

     Results

    IncludingPIinPCMs increased the modelR2relative toPCMs that excludedPI; regression coefficients for climatic parameters, however, remained constant.

     Discussion

    Our protocol provides a simple, quantitative phenological metric for any observed plant. IncludingPIinPCMs increasesR2and enables predictions of theDOYof any phenophase under any specified climatic conditions.

     
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  2. ; ; ; ; ; ; ; ; ; ; et al ( , Applications in Plant Sciences)
    Premise of the Study

    Phenological annotation models computed on large‐scale herbarium data sets were developed and tested in this study.

     Methods

    Herbarium specimens represent a significant resource with which to study plant phenology. Nevertheless, phenological annotation of herbarium specimens is time‐consuming, requires substantial human investment, and is difficult to mobilize at large taxonomic scales. We created and evaluated new methods based on deep learning techniques to automate annotation of phenological stages and tested these methods on four herbarium data sets representing temperate, tropical, and equatorial American floras.

     Results

    Deep learning allowed correct detection of fertile material with an accuracy of 96.3%. Accuracy was slightly decreased for finer‐scale information (84.3% for flower and 80.5% for fruit detection).

     Discussion

    The method described has the potential to allow fine‐grained phenological annotation of herbarium specimens at large ecological scales. Deeper investigation regarding the taxonomic scalability of this approach is needed.

     
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  3. ; ( , Ecography)
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  4. ; ; ; ( , PhytoKeys)
    In an earlier molecular phylogenetic study, a sample of what was originally identified as Cryptantha hispida (Boraginaceae) from Chile, grouped with species of the genus Johnstonella . This sample was subsequently shown not to be C. hispida , but an undescribed species, endemic to the dry Puna of Chile. This new species is described here as Johnstonella punensis , along with a key to all South American species of the genus. Johnstonella punensis resembles other members of that genus in having an ovate fruit shape, ovate nutlets and a long style that extends beyond the nutlets. It is unusual in the genus in having a non-tuberculate, dimpled to rugulose nutlet surface sculpturing. Its closest relative within the genus is likely the South American J. diplotricha . 
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  5. ; ; ; ; ( , Madroño)
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  6. ; ( , Phytotaxa)
    A review of the species Cryptantha maritima (Boraginaceae) supports the continued recognition of the three varieties, these differing in corolla size, ovule and nutlet number, and calyx vestiture. Mapping of these taxa from verified specimens demonstrates some geographic trends, but also some overlap in ranges. In the process of our study, we discovered a new taxonomic entity. Cryptantha maritima var. vizcainensis is described as new. This variety is restricted to the Vizcaíno Desert of Baja California Sur, Mexico and should be considered rare, as it is known to date from only eleven collections. It differs from the other three varieties of the species in having a canescent, appressed-strigose stem vestiture lacking spreading trichomes, in having a relatively large corolla, and in having a fruit derived from two 1-ovuled ovary lobes, developing into two heteromorphic nutlets. We also discovered that the species Cryptantha pondii, previously treated as a synonym of C. patula, should be resurrected as a distinct taxon. Cryptantha pondii is restricted to the western Vizcaíno Desert and to Natividad Island of Baja California Sur. It is morphologically distinctive in having bracteate flowers, relatively large corollas, and four smooth nutlets heteromorphic by size. It is to date known from only three collections and should be considered extremely rare. We also reviewed the morphological and phylogenetic status of Johnstonella echinosepala. This taxon shows similarities to Cryptantha maritima and also exhibits some morphological discontinuity between Pacific and Gulf populations in Baja California Sur. Evidence from both morphological and phylogenetic studies supports the transfer of this species from the genus Johnstonella back to the genus Cryptantha. Finally, we propose that both C. pondii and C. echinosepala are likely close relatives of C. maritima, all of the “Maritimae clade,” a group distantly related to the main core of the genus Cryptantha. This study confirms the great importance of studying herbarium specimens in taxonomic research. 
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  7. ; ( , Madroño)
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  8. ; ; ; ; ; ; ; ; ; ; et al ( , Madroño)
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