skip to main content

Title: TaxonWorks as a Tool for Managing Large Biodiversity Projects
Large systematic revisionary projects incorporating data for hundreds or thousands of taxa require an integrative approach, with a strong biodiversity-informatics core for efficient data management to facilitate research on the group. Our original biodiversity informatics platform, 3i (Internet-accessible Interactive Identification) combined a customized MS Access database backend with ASP-based web interfaces to support revisionary syntheses of several large genera of leafhopers (Hemiptera: Auchenorrhyncha: Cicadellidae). More recently, for our National Science Foundation sponsored project, “GoLife: Collaborative Research: Integrative genealogy, ecology and phenomics of deltocephaline leafhoppers (Hemiptera: Cicadellidae), and their microbial associates”, we selected the new open-source platform TaxonWorks as the cyberinfrastructure. In the scope of the project, the original “3i World Auchenorrhyncha Database” was imported into TaxonWorks. At the present time, TaxonWorks has many tools to automatically import nomenclature, citations, and specimen based collection data. At the time of the initial migration of the 3i database, many of those tools were still under development, and complexity of the data in the database required a custom migration script, which is still probably the most efficient solution for importing datasets with long development history. At the moment, the World Auchenorrhyncha Database comprehensively covers nomenclature of the group and includes data on 70 valid families, 6,816 valid genera, 47,064 valid species as well as synonymy and subsequent combinations (Fig. 1). In addition, many taxon records include the original citation, bibliography, type information, etymology, etc. The bibliography of the group includes 37,579 sources, about 1/3 of which are associated with PDF files. Species have distribution records, either derived from individual specimens or as country and state level asserted distribution, as well as biological associations indicating host plants, predators, and parasitoids. Observation matrices in TaxonWorks are designed to handle morphological data associated with taxa or specimens. The matrices may be used to automatically generate interactive identification keys and taxon descriptions. They can also be downloaded to be imported, for example, into Lucid builder, or to perform phylogenetic analysis using an external application. At the moment there are 36 matrices associated with the project. The observation matrix from GoLife project covers 798 taxa by 210 descriptors (most of which are qualitative multi-state morphological descriptors) (Fig. 2). Illustrations are provided for 9,886 taxa and organized in the specialized image matrix and could be used as a pictorial key for determination of species and taxa of a higher rank. For the phylogenetic analysis, a dataset was constructed for 730 terminal taxa and >160,000 nucleotide positions obtained using anchored hybrid enrichment of genomic DNA for a sample of leafhoppers from the subfamily Deltocephalinae and outgroups. The probe kit targets leafhopper genes, as well as some bacterial genes (endosymbionts and plant pathogens transmitted by leafhoppers). The maximum likelihood analyses of concatenated nucleotide and amino acid sequences as well as coalescent gene tree analysis yielded well-resolved phylogenetic trees (Cao et al. 2022). Raw sequence data have been uploaded to the Sequence Read Archive on GenBank. Occurrence and morphological data, as well as diagnostic images, for voucher specimens have been incorporated into TaxonWorks. Data in TaxonWorks could be exported in raw format, get accessed via Application Programming Interface (API), or be shared with external data aggregators like Catalogue of Life, GBIF, iDigBio.  more » « less
Award ID(s):
Author(s) / Creator(s):
; ;
Date Published:
Journal Name:
Biodiversity Information Science and Standards
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. TaxonWorks ( is an integrated workbench for taxonomists and biodiversity scientists. It is designed to capture, organize, and enrich data, share and refine it with collaborators, and package it for analysis and publication. It is based on PostgreSQL (database) and the Ruby-on-Rails programming language and framework for developing web applications ( The TaxonWorks community is built around an open software ecosystem that facilitates participation at many levels. TaxonWorks is designed to serve both researchers who create and curate the data, as well as technical users, such as programmers and informatics specialists, who act as data consumers. TaxonWorks provides researchers with robust, user friendly interfaces based on well thought out customized workflows for efficient and validated data entry. It provides technical users database access through an application programming interface (API) that serves data in JSON format. The data model includes coverage for nearly all classes of data recorded in modern taxonomic treatments primary studies of biodiversity, including nomenclature, bibliography, specimens and collecting events, phylogenetic matrices and species descriptions, etc. The nomenclatural classes are based on the NOMEN ontology ( 
    more » « less
  2. TaxonWorks is an integrated web-based application for practicing taxonomists and biodiversity specialists. It is focused on promoting collaboration between researchers and developers. TaxonWorks has a modular structure that enables various components of the application to target specific needs and requirements of different groups of users. Specific areas of interest may include nomenclature-related tasks (Yoder and Dmitriev 2021) designed to help assemble and validate scientific name checklists of a target group of organisms; and collection management tasks, including interfaces to create, filter, and edit collecting events, collection objects, and loans. This presentation focuses on matrix-related tools integrated into TaxonWorks. A matrix, which could either be used for phylogenetic analysis or to build an identification key, is structured as a table where columns represent numerous characters that could be used to describe a set of entities, taxa or specimens (presented as rows of the table). Each cell of the table may contain observations for specific character/entity combinations. TaxonWorks does not generate a table for each a particular matrix—all observations are stored as graphs. This structure allows building of a matrix of an unlimited size as well as reuse of individual observations in multiple matrices. For matrix columns, TaxonWorks supports a variety of different kinds of characters or descriptors: qualitative, presence/absence, quantitative, sample, gene, free text, and media. Each character may have specific properties, for example a qualitative descriptor may have numerous characters states, and a quantitative descriptor may have a measurement unit defined. For an entity in a matrix row, TaxonWorks supports either collection objects (specimens) or taxa as Operational Taxonomic Units (OTU). OTUs could either be linked to nomenclature or be stand alone entities (e.g., representing undescribed species). The matrix, once built, could serve several purposes. A matrix based on qualitative and quantitative characters could be used to build an interactive key (Fig. 1), construct standardized natural language descriptions for each entity, and determine a diagnosis (a minimal set of characters that separate one entity from all others). It could also be exported and used for phylogenetic analysis or to build an interactive key in an external application. TaxonWorks supports export files in several formats, including Nexus, TNT, NeXML. Application Programming Interfaces (API) are also available. A matrix based on media descriptors could be used as a pictorial identification tool (Fig. 2). 
    more » « less
  3. The 3i World Auchenorrhyncha database ( is being migrated into TaxonWorks ( and comprises nomenclatural data for all known Auchenorrhyncha taxa (leafhoppers, planthoppers, treehoppers, cicadas, spittle bugs). Of all those scientific names, 8,700 are unique genus-group names (which include valid genera and subgenera as well as their synonyms). According to the Rules of Zoological Nomenclature, a properly formed species-group name when combined with a genus-group name must agree with the latter in gender if the species-group name is or ends with a Latin or Latinized adjective or participle. This provides a double challenge for researchers describing new or citing existing taxa. For each species, the knowledge about the part of speech is essential information (nouns do not change their form when associated with different generic names). For the genus, the knowledge of the gender is essential information. Every time the species is transferred from one genus to another, its ending may need to be transformed to make a proper new scientific name (a binominal name). In modern day practice, it is important, when establishing a new name, to provide information about etymology of this name and the ways it should be used in the future publications: the grammatical gender for a genus, and the part of speech for a species. The older names often do not provide enough information about their etymology to make proper construction of scientific names. That is why in the literature, we can find numerous cases where a scientific name is not formed in conformity to the Rules of Nomenclature. An attempt was made to resolve the etymology of the generic names in Auchenorrhyncha to unify and clarify nomenclatural issues in this group of insects. In TaxonWorks, the rules of nomenclature are defined using the NOMEN onthology ( 
    more » « less
  4. Abstract

    The suborder Auchenorrhyncha (“true hoppers”) comprises nearly half of known Hemiptera, with >43,000 known species of sap‐sucking herbivores distributed worldwide, including many important agricultural pests and vectors of plant disease. More than half of the known Auchenorrhyncha belong to superfamily Membracoidea (leaf‐ and treehoppers), which has been a source of phylogenetic contention for many years. To construct an improved backbone phylogeny of this superfamily, we obtained transcriptome data for multiple representatives of all 5 previously established extant families and nearly all subfamilies to test their monophyly and relationships. 138 taxa (132 Membracoidea and 6 outgroups) were sampled with an emphasis on families Cicadellidae and Membracidae, which were paraphyletic as previously defined by most authors, several problematic subfamilies (Aphrodinae, Eurymelinae, Ledrinae, Nicomiinae, Stegaspidinae and Tartessinae). We analysed different combinations of data sets (amino acid, complete nucleotide and degeneracy‐coded nucleotide) using different modelling schemes. The resultant trees based on different analyses are congruent in most nodes. Discordant nodes mainly pertain to relationships among cicadellid subfamilies and tribal relationships within Aphrodinae and Eurymelinae. Analyses of gene‐ and site concordance factors and quartet scores indicate that this instability is largely attributable to an overall lack of informative characters across genes and sites rather than strongly supported conflict among genes. According to the congruent nodes, we make the following revisions: combine Stegaspidinae and Centrotinae into a single subfamily, Centrotinae sensu lato; restore Stenocotini from Tartessinae to its original position in the Ledrinae; and transformHoldgatiellaEvans from Nicomiinae to Melizoderinae. In addition, to solve the paraphyly of both Cicadellidae and Membracidae, a preferred option would be to combine all five previously recognized families into a single family, Membracidae sensu lato; the other option could be to render Cicadellidae monophyletic by excluding Megophthalminae and Ulopinae from Cicadellidae and elevating them to status as separate families.

    more » « less
  5. Abstract

    Contamination of a genetic sample with DNA from one or more nontarget species is a continuing concern of molecular phylogenetic studies, both Sanger sequencing studies and next-generation sequencing studies. We developed an automated pipeline for identifying and excluding likely cross-contaminated loci based on the detection of bimodal distributions of patristic distances across gene trees. When contamination occurs between samples within a data set, a comparison between a contaminated sample and its contaminant taxon will yield bimodal distributions with one peak close to zero patristic distance. This new method does not rely on a priori knowledge of taxon relatedness nor does it determine the causes(s) of the contamination. Exclusion of putatively contaminated loci from a data set generated for the insect family Cicadidae showed that these sequences were affecting some topological patterns and branch supports, although the effects were sometimes subtle, with some contamination-influenced relationships exhibiting strong bootstrap support. Long tip branches and outlier values for one anchored phylogenomic pipeline statistic (AvgNHomologs) were correlated with the presence of contamination. While the anchored hybrid enrichment markers used here, which target hemipteroid taxa, proved effective in resolving deep and shallow level Cicadidae relationships in aggregate, individual markers contained inadequate phylogenetic signal, in part probably due to short length. The cleaned data set, consisting of 429 loci, from 90 genera representing 44 of 56 current Cicadidae tribes, supported three of the four sampled Cicadidae subfamilies in concatenated-matrix maximum likelihood (ML) and multispecies coalescent-based species tree analyses, with the fourth subfamily weakly supported in the ML trees. No well-supported patterns from previous family-level Sanger sequencing studies of Cicadidae phylogeny were contradicted. One taxon (Aragualna plenalinea) did not fall with its current subfamily in the genetic tree, and this genus and its tribe Aragualnini is reclassified to Tibicininae following morphological re-examination. Only subtle differences were observed in trees after the removal of loci for which divergent base frequencies were detected. Greater success may be achieved by increased taxon sampling and developing a probe set targeting a more recent common ancestor and longer loci. Searches for contamination are an essential step in phylogenomic analyses of all kinds and our pipeline is an effective solution. [Auchenorrhyncha; base-composition bias; Cicadidae; Cicadoidea; Hemiptera; phylogenetic conflict.]

    more » « less