114 research outputs found

    Home at last: the enigmatic genera Eriachaenium and Adenocaulon (Compositae, Mutisioideae, Mutisieae, Adenocaulinae)

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    The genera Eriachaenium and Adenocaulon (Compositae) have distinct but complex histories and both have been placed in a number of tribes across the family. For the first time the two genera are included in a molecular study and the results show that they are best placed in the tribe Mutisieae s.s. and are the only genera in the re-instated subtribe Adenocaulinae. When described, this subtribe contained only Adenocaulon and was found in the Inuleae. The study also confirms one of the conclusions of a recent morphological study that Eriachaenium and Adenocaulon are sister taxa. Past difficulties in tribal assignment are attributed to the distinct and unusual morphology of each genus. Both genera and the subtribe are described and a key to separate the genera is provided.Facultad de Ciencias Naturales y Muse

    A target enrichment method for gathering phylogenetic information from hundreds of loci: An example from the Compositae.

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    UnlabelledPremise of the studyThe Compositae (Asteraceae) are a large and diverse family of plants, and the most comprehensive phylogeny to date is a meta-tree based on 10 chloroplast loci that has several major unresolved nodes. We describe the development of an approach that enables the rapid sequencing of large numbers of orthologous nuclear loci to facilitate efficient phylogenomic analyses. •Methods and resultsWe designed a set of sequence capture probes that target conserved orthologous sequences in the Compositae. We also developed a bioinformatic and phylogenetic workflow for processing and analyzing the resulting data. Application of our approach to 15 species from across the Compositae resulted in the production of phylogenetically informative sequence data from 763 loci and the successful reconstruction of known phylogenetic relationships across the family. •ConclusionsThese methods should be of great use to members of the broader Compositae community, and the general approach should also be of use to researchers studying other families

    Global Genome Biodiversity Network:saving a blueprint of the Tree of Life - a botanical perspective

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    Background Genomic research depends upon access to DNA or tissue collected and preserved according to high-quality standards. At present, the collections in most natural history museums do not sufficiently address these standards, making them often hard or impossible to use for whole-genome sequencing or transcriptomics. In response to these challenges, natural history museums, herbaria, botanical gardens and other stakeholders have started to build high-quality biodiversity biobanks. Unfortunately, information about these collections remains fragmented, scattered and largely inaccessible. Without a central registry or even an overview of relevant institutions, it is difficult and time-consuming to locate the needed samples. Scope The Global Genome Biodiversity Network (GGBN) was created to fill this vacuum by establishing a one-stop access point for locating samples meeting quality standards for genome-scale applications, while complying with national and international legislations and conventions. Increased accessibility to genomic samples will further genomic research and development, conserve genetic resources, help train the next generation of genome researchers and raise the visibility of biodiversity collections. Additionally, the availability of a data-sharing platform will facilitate identification of gaps in the collections, thereby empowering targeted sampling efforts, increasing the breadth and depth of preservation of genetic diversity. The GGBN is rapidly growing and currently has 41 members. The GGBN covers all branches of the Tree of Life, except humans, but here the focus is on a pilot project with emphasis on ‘harvesting’ the Tree of Life for vascular plant taxa to enable genome-level studies. Conclusion While current efforts are centred on getting the existing samples of all GGBN members online, a pilot project, GGI-Gardens, has been launched as proof of concept. Over the next 6 years GGI-Gardens aims to add to the GGBN high-quality genetic material from at least one species from each of the approx. 460 vascular plant families and one species from half of the approx. 15 000 vascular plant genera

    Applications of deep convolutional neural networks to digitized natural history collections

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    Natural history collections contain data that are critical for many scientific endeavors. Recent efforts in mass digitization are generating large datasets from these collections that can provide unprecedented insight. Here, we present examples of how deep convolutional neural networks can be applied in analyses of imaged herbarium specimens. We first demonstrate that a convolutional neural network can detect mercury-stained specimens across a collection with 90% accuracy. We then show that such a network can correctly distinguish two morphologically similar plant families 96% of the time. Discarding the most challenging specimen images increases accuracy to 94% and 99%, respectively. These results highlight the importance of mass digitization and deep learning approaches and reveal how they can together deliver powerful new investigative tools

    Home at last: the enigmatic genera Eriachaenium and Adenocaulon (Compositae, Mutisioideae, Mutisieae, Adenocaulinae)

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    The genera Eriachaenium and Adenocaulon (Compositae) have distinct but complex histories and both have been placed in a number of tribes across the family. For the first time the two genera are included in a molecular study and the results show that they are best placed in the tribe Mutisieae s.s. and are the only genera in the re-instated subtribe Adenocaulinae. When described, this subtribe contained only Adenocaulon and was found in the Inuleae. The study also confirms one of the conclusions of a recent morphological study that Eriachaenium and Adenocaulon are sister taxa. Past difficulties in tribal assignment are attributed to the distinct and unusual morphology of each genus. Both genera and the subtribe are described and a key to separate the genera is provided.Facultad de Ciencias Naturales y Muse

    The origin of the bifurcating style in Asteraceae (Compositae)

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    Background and Aims The plant family Asteraceae (Compositae) exhibits remarkable morphological variation in the styles of its members. Lack of studies on the styles of the sister families to Asteraceae, Goodeniaceae and Calyceraceae, obscures our understanding of the origin and evolution of this reproductive feature in these groups. The aim of this work was to perform a comparative study of style morphology and to discuss the relevance of important features in the evolution of Asteraceae and its sister families. Methods The histochemistry, venation and general morphology of the styles of members of Goodeniaceae, Calyceraceae and early branching lineages of Asteraceae were analysed and put in a phylogenetic framework to discuss the relevance of style features in the evolution of these families. Key Results The location of lipophilic substances allowed differentiation of receptive from non-receptive style papillae, and the style venation in Goodeniaceae and Calyceraceae proved to be distinctive. There were several stages of style evolution from Goodeniaceae to Asteraceae involving connation and elongation of veins, development of bilobation from an initially cup-shaped style, and a redistribution of the receptive and non-receptive papillae. Conclusions These developments resulted in bifurcation in the styles of Asteraceae, with each branch face having a different function, and it is suggested here as a mechanism that promoted outcrossing, which in turn led to the great diversification in the family.Facultad de Ciencias Naturales y MuseoFacultad de Ciencias Agrarias y Forestale

    Taxonomy based on science is necessary for global conservation

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    Administrative Law as the New Federalism

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    The Importance of Getting Names Right: The Myth of Markets for Water

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