An official website of the United States government
Abstract Biodiversity research has advanced by testing expectations of ecological and evolutionary hypotheses through the linking of large-scale genetic, distributional, and trait datasets. The rise of molecular systematics over the past 30 years has resulted in a wealth of DNA sequences from around the globe. Yet, advances in molecular systematics also have created taxonomic instability, as new estimates of evolutionary relationships and interpretations of species limits have required widespread scientific name changes. Taxonomic instability, colloquially “splits, lumps, and shuffles,” presents logistical challenges to large-scale biodiversity research because (1) the same species or sets of populations may be listed under different names in different data sources, or (2) the same name may apply to different sets of populations representing different taxonomic concepts. Consequently, distributional and trait data are often difficult to link directly to primary DNA sequence data without extensive and time-consuming curation. Here, we present RANT: Reconciliation of Avian NCBI Taxonomy. RANT applies taxonomic reconciliation to standardize avian taxon names in use in NCBI GenBank, a primary source of genetic data, to a widely used and regularly updated avian taxonomy: eBird/Clements. Of 14,341 avian species/subspecies names in GenBank, 11,031 directly matched an eBird/Clements; these link to more than 6 million nucleotide sequences. For the remaining unmatched avian names in GenBank, we used Avibase’s system of taxonomic concepts, taxonomic descriptions in Cornell’s Birds of the World, and DNA sequence metadata to identify corresponding eBird/Clements names. Reconciled names linked to more than 600,000 nucleotide sequences, ~9% of all avian sequences on GenBank. Nearly 10% of eBird/Clements names had nucleotide sequences listed under 2 or more GenBank names. Our taxonomic reconciliation is a first step towards rigorous and open-source curation of avian GenBank sequences and is available at GitHub, where it can be updated to correspond to future annual eBird/Clements taxonomic updates.
more »
« less
Geographic name resolution service: A tool for the standardization and indexing of world political division names, with applications to species distribution modeling
Massive biological databases of species occurrences, or georeferenced locations where a species has been observed, are essential inputs for modeling present and future species distributions. Location accuracy is often assessed by determining whether the observation geocoordinates fall within the boundaries of the declared political divisions. This otherwise simple validation is complicated by the difficulty of matching political division names to the correct geospatial object. Spelling errors, abbreviations, alternative codes, and synonyms in multiple languages present daunting name disambiguation challenges. The inability to resolve political division names reduces usable data, and analysis of erroneous observations can lead to flawed results. Here, we present the Geographic Name Resolution Service (GNRS), an application for correcting, standardizing, and indexing world political division names. The GNRS resolves political division names against a reference database that combines names and codes from GeoNames with geospatial object identifiers from the Global Administrative Areas Database (GADM). In a trial resolution of political division names extracted from >270 million species occurrences, only 1.9%, representing just 6% of occurrences, matched exactly to GADM political divisions in their original form. The GNRS was able to resolve, completely or in part, 92% of the remaining 378,568 political division names, or 86% of the full biodiversity occurrence dataset. In assessing geocoordinate accuracy for >239 million species occurrences, resolution of political divisions by the GNRS enabled the detection of an order of magnitude more errors and an order of magnitude more error-free occurrences. By providing a novel solution to a significant data quality impediment, the GNRS liberates a tremendous amount of biodiversity data for quantitative biodiversity research. The GNRS runs as a web service and is accessible via an API, an R package, and a web-based graphical user interface. Its modular architecture is easily integrated into existing data validation workflows.
more »
« less
- Award ID(s):
- 1934790
- PAR ID:
- 10398738
- Editor(s):
- Romanach, Stephanie S.
- Date Published:
- Journal Name:
- PLOS ONE
- Volume:
- 17
- Issue:
- 11
- ISSN:
- 1932-6203
- Page Range / eLocation ID:
- e0268162
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
null (Ed.)“What is crucial for your ability to communicate with me… pivots on the recipient’s capacity to interpret—to make good inferential sense of the meanings that the declarer is able to send” (Rescher 2000, p148). Conventional approaches to reconciling taxonomic information in biodiversity databases have been based on string matching for unique taxonomic name combinations (Kindt 2020, Norman et al. 2020). However, in their original context, these names pertain to specific usages or taxonomic concepts, which can subsequently vary for the same name as applied by different authors. Name-based synonym matching is a helpful first step (Guala 2016, Correia et al. 2018), but may still leave considerable ambiguity regarding proper usage (Fig. 1). Therefore, developing "taxonomic intelligence" is the bioinformatic challenge to adequately represent, and subsequently propagate, this complex name/usage interaction across trusted biodiversity data networks. How do we ensure that senders and recipients of biodiversity data not only can share messages but do so with “good inferential sense” of their respective meanings? Key obstacles have involved dealing with the complexity of taxonomic name/usage modifications through time, both in terms of accounting for and digitally representing the long histories of taxonomic change in most lineages. An important critique of proposals to use name-to-usage relationships for data aggregation has been the difficulty of scaling them up to reach comprehensive coverage, in contrast to name-based global taxonomic hierarchies (Bisby 2011). The Linnaean system of nomenclature has some unfortunate design limitations in this regard, in that taxonomic names are not unique identifiers, their meanings may change over time, and the names as a string of characters do not encode their proper usage, i.e., the name “Genus species” does not specify a source defining how to use the name correctly (Remsen 2016, Sterner and Franz 2017). In practice, many people provide taxonomic names in their datasets or publications but not a source specifying a usage. The information needed to map the relationships between names and usages in taxonomic monographs or revisions is typically not presented it in a machine-readable format. New approaches are making progress on these obstacles. Theoretical advances in the representation of taxonomic intelligence have made it increasingly possible to implement efficient querying and reasoning methods on name-usage relationships (Chen et al. 2014, Chawuthai et al. 2016, Franz et al. 2015). Perhaps most importantly, growing efforts to produce name-usage mappings on a medium scale by data providers and taxonomic authorities suggest an all-or-nothing approach is not required. Multiple high-profile biodiversity databases have implemented internal tools for explicitly tracking conflicting or dynamic taxonomic classifications, including eBird using concept relationships from AviBase (Lepage et al. 2014); NatureServe in its Biotics database; iNaturalist using its taxon framework (Loarie 2020); and the UNITE database for fungi (Nilsson et al. 2019). Other ongoing projects incorporating taxonomic intelligence include the Flora of Alaska (Flora of Alaska 2020), the Mammal Diversity Database (Mammal Diversity Database 2020) and PollardBase for butterfly population monitoring (Campbell et al. 2020).more » « less
-
The 3i World Auchenorrhyncha database (http://dmitriev.speciesfile.org) is being migrated into TaxonWorks (http://taxonworks.org) 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 (https://github.com/SpeciesFileGroup/nomen).more » « less
-
Abstract Against a background of the climate and biodiversity crises, there is an urgent need for robust and citable biodiversity information for policy and management decisions. Species are fundamental units of biodiversity and underpin communication in biology. Delineating, describing, and naming species provide the foundation for tracking biodiversity. Taxonomists recognise over 2 million described species, the scientific names of which follow provisions of codes of nomenclature, providing stability for communication about biodiversity. However, described species represent only a fraction of global biodiversity. Current advances in the fields of molecular biology and the growing use of image-based identifications have resulted in an explosion of informal species names globally, herein referred to as temporary names, increasing the rate of discovery of undescribed species and cryptic species complexes. We define two categories of temporary names: Type 1 names that are delineated in a local context but not further assessed; and Type 2 names that have been taxonomically assessed and recognised as either new or part of an unresolved species complex. We explore the different types and uses of temporary names, indicate how they can be managed in a robust and standardised manner and demonstrate how biodiversity databases, such as WoRMS, can be expanded to allow the tracking of both formal and informal scientific names. We propose a solution for the expanding problem of temporary names by defining and recommending the addition of Type 2 temporary names to nomenclatural databases such as WoRMS. We provide practical recommendations on how such names should be selected for entry and then entered to databases in a standardised way. These recommendations are a small step forward, but their broad adoption would support the robust integration of informal and formal taxonomies.more » « less
-
TaxonWorks (http://taxonworks.org) in an integrated, open-source, cybertaxonomic web application serving taxonomists and biodiversity scientists. It is designed to facilitate efficient data capture, storage, manipulation, and retrieval. It integrates a wide variety of data types used by biodiversity scientists, including, but not limited to, taxonomy (with validation based on codes of zoological, botanical, bacterial, and viral nomenclature), specimen data, bibliographies, media (images, PDFs, sounds, videos), morphology (character/trait matrices), distribution, biological associations. Available TaxonWorks web interfaces currently provide various data entry forms for simple and advanced querying of the database. TaxonWorks has integrated batch uploader functionality. But, for larger datasets, specialized migration scripts were used. Several projects, historically build in 3i (http://dmitriev.speciesfile.org), MX (http://mx.phenomix.org), SpeciesFiles (http://software.speciesfile.org), and other databases, have been or are being migrated into TaxonWorks. Of the projects moving into TaxonWorks, it is worth mentioning several: 3i World Auchenorrhyncha Database, LepIndex, Universal Chalcidoidea Database, Orthoptera SpeciesFile, Plecoptera SpeciesFile, Illinois Natural History Survey Insect Collection database, and several others. An experience of the data migration will be shared during the presentation.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1371/journal.pone.0268162
