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      Taxonomic revision of the Malagasy members of the Nesomyrmex angulatus species group using the automated morphological species delineation protocol NC-PART-clustering

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          Abstract

          Background. Applying quantitative morphological approaches in systematics research is a promising way to discover cryptic biological diversity. Information obtained through twenty-first century science poses new challenges to taxonomy by offering the possibility of increased objectivity in independent and automated hypothesis formation. In recent years a number of promising new algorithmic approaches have been developed to recognize morphological diversity among insects based on multivariate morphometric analyses. These algorithms objectively delimit components in the data by automatically assigning objects into clusters.

          Method. In this paper, hypotheses on the diversity of the Malagasy Nesomyrmex angulatus group are formulated via a highly automated protocol involving a fusion of two algorithms, (1) Nest Centroid clustering (NC clustering) and (2) Partitioning Algorithm based on Recursive Thresholding (PART). Both algorithms assign samples into clusters, making the class assignment results of different algorithms readily inferable. The results were tested by confirmatory cross-validated Linear Discriminant Analysis (LOOCV-LDA).

          Results. Here we reveal the diversity of a unique and largely unexplored fragment of the Malagasy ant fauna using NC-PART-clustering on continuous morphological data, an approach that brings increased objectivity to taxonomy. We describe eight morphologically distinct species, including seven new species: Nesomyrmex angulatus (Mayr, 1862), N. bidentatus sp. n., N. clypeatus sp. n., N. devius sp. n., N. exiguus sp. n., N. fragilis sp. n., N. gracilis sp. n., and N. hirtellus sp. n.. An identification key for their worker castes using morphometric data is provided.

          Conclusions. Combining the dimensionality reduction feature of NC clustering with the assignment of samples into clusters by PART advances the automatization of morphometry-based alpha taxonomy.

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          Most cited references23

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          R: A Language and environmental for statistical computing

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            A Gross Anatomy Ontology for Hymenoptera

            Hymenoptera is an extraordinarily diverse lineage, both in terms of species numbers and morphotypes, that includes sawflies, bees, wasps, and ants. These organisms serve critical roles as herbivores, predators, parasitoids, and pollinators, with several species functioning as models for agricultural, behavioral, and genomic research. The collective anatomical knowledge of these insects, however, has been described or referred to by labels derived from numerous, partially overlapping lexicons. The resulting corpus of information—millions of statements about hymenopteran phenotypes—remains inaccessible due to language discrepancies. The Hymenoptera Anatomy Ontology (HAO) was developed to surmount this challenge and to aid future communication related to hymenopteran anatomy. The HAO was built using newly developed interfaces within mx, a Web-based, open source software package, that enables collaborators to simultaneously contribute to an ontology. Over twenty people contributed to the development of this ontology by adding terms, genus differentia, references, images, relationships, and annotations. The database interface returns an Open Biomedical Ontology (OBO) formatted version of the ontology and includes mechanisms for extracting candidate data and for publishing a searchable ontology to the Web. The application tools are subject-agnostic and may be used by others initiating and developing ontologies. The present core HAO data constitute 2,111 concepts, 6,977 terms (labels for concepts), 3,152 relations, 4,361 sensus (links between terms, concepts, and references) and over 6,000 text and graphical annotations. The HAO is rooted with the Common Anatomy Reference Ontology (CARO), in order to facilitate interoperability with and future alignment to other anatomy ontologies, and is available through the OBO Foundry ontology repository and BioPortal. The HAO provides a foundation through which connections between genomic, evolutionary developmental biology, phylogenetic, taxonomic, and morphological research can be actualized. Inherent mechanisms for feedback and content delivery demonstrate the effectiveness of remote, collaborative ontology development and facilitate future refinement of the HAO.
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              Madagascar as a model region of species diversification.

              Tropical biotas provide excellent settings in which to explore mechanisms of evolutionary diversification, yet these processes remain poorly understood. Pioneering work on biodiversity patterns and diversification processes in other tropical regions has recently been complemented by studies in Madagascar. Here we review diversity models and diversification mechanisms proposed for the fauna of this island and the perspectives for testing them. Madagascar has a diverse biota that has evolved in isolation, and is characterised by regionally pronounced and locally steep environmental gradients, common patterns of microendemism across taxa and numerous evolutionary radiations. These characteristics establish Madagascar as a promising system for the study of pattern and process in species diversification.
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                Author and article information

                Contributors
                Journal
                PeerJ
                PeerJ
                PeerJ
                PeerJ
                PeerJ
                PeerJ Inc. (San Francisco, USA )
                2167-8359
                10 March 2016
                2016
                : 4
                : e1796
                Affiliations
                [-1]Entomology, California Academy of Sciences , San Francisco, CA, USA
                Article
                1796
                10.7717/peerj.1796
                4793320
                26989630
                28660b3f-5ce2-4324-b153-0d1d3b573a4c
                ©2016 Csősz and Fisher

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.

                History
                : 15 December 2015
                : 22 February 2016
                Funding
                Funded by: National Science Foundation
                Award ID: DEB-0072713
                Award ID: DEB-0344731
                Award ID: DEB-0842395
                Funded by: California Academy of Sciences
                Funded by: Ernst Mayr Travel Grant
                This study was supported by the National Science Foundation under Grant No. DEB-0072713, DEB-0344731, and DEB-0842395. Finally, SC was supported by the Schlinger Fellowship at the California Academy of Sciences and an Ernst Mayr Travel Grants to the MCZ. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Biodiversity
                Computational Biology
                Entomology
                Taxonomy
                Statistics

                morphometry,gap statistic,species delimitation,exploratory analyses,biogeography,nesomyrmex,new species

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