Understanding the interplay between environmental conditions and phenotypes is a fundamental goal of biology. Unfortunately, data that include observations on phenotype and environment are highly heterogeneous and thus difficult to find and integrate. One approach that is likely to improve the status quo involves the use of ontologies to standardize and link data about phenotypes and environments. Specifying and linking data through ontologies will allow researchers to increase the scope and flexibility of large-scale analyses aided by modern computing methods. Investments in this area would advance diverse fields such as ecology, phylogenetics, and conservation biology. While several biological ontologies are well-developed, using them to link phenotypes and environments is rare because of gaps in ontological coverage and limits to interoperability among ontologies and disciplines. In this manuscript, we present (1) use cases from diverse disciplines to illustrate questions that could be answered more efficiently using a robust linkage between phenotypes and environments, (2) two proof-of-concept analyses that show the value of linking phenotypes to environments in fishes and amphibians, and (3) two proposed example data models for linking phenotypes and environments using the extensible observation ontology (OBOE) and the Biological Collections Ontology (BCO); these provide a starting point for the development of a data model linking phenotypes and environments.

This contribution adopts the taxonomic concept annotation and alignment approach. Accordingly, and where indicated, previous and newly inferred meanings of taxonomic names are individuated according to one specific source. Articulations among these concepts and pairwise, logically consistent alignments of original and revisionary classifications are also provided, in addition to conventional nomenclatural provenance information. A phylogenetic revision of the broad-nosed weevil genera Minyomerus Horn, 1876 sec. O’Brien & Wibmer (1982), and Piscatopus Sleeper, 1960 sec. O’Brien & Wibmer (1982) (Curculionidae [non-focal]: Entiminae [non-focal]: Tanymecini [non-focal]) is presented.

Prior to this study, Minyomerus sec. O’Brien & Wibmer (1982) contained seven species, whereas the monotypic Piscatopus sec. O’Brien & Wibmer (1982) was comprised solely of P. griseus Sleeper, 1960 sec. O’Brien & Wibmer (1982). We thoroughly redescribe these recognized species-level entities and furthermore describe ten species as new to science: M. bulbifrons sec. Jansen & Franz (2015) (henceforth: [JF2015]), sp. n., M. aeriballux [JF2015], sp. n., M. cracens [JF2015], sp. n., M. gravivultus [JF2015], sp. n., M. imberbus [JF2015], sp. n., M. reburrus [JF2015], sp. n., M. politus [JF2015], sp. n., M. puticulatus [JF2015], sp. n., M. rutellirostris [JF2015], sp. n., and M. trisetosus [JF2015], sp. n. A cladistic analysis using 46 morphological characters of 22 terminal taxa (5/17 outgroup/ingroup) yielded a single most-parsimonious cladogram (L = 82, CI = 65, RI = 82).

The analysis strongly supports the monophyly of Minyomerus [JF2015] with eight unreversed synapomorphies, and places P. griseus sec. O’Brien & Wibmer (1982) within the genus as sister to M. rutellirostris [JF2015]. Accordingly, Piscatopus sec. Sleeper (1960), syn. n. is changed to junior synonymy of Minyomerus [JF2015], and its sole member P. griseus sec. Sleeper (1960) is moved to Minyomerus [JF2015] as M. griseus [JF2015], comb. n. In addition, the formerly designated type M. innocuus Horn, 1876 sec. Pierce (1913), syn. n. is changed to junior synonymy of M. microps (Say, 1831) [JF2015] which has priority. The genus is widespread throughout western North America, ranging from Canada to Mexico and Baja California. Apparent patterns of interspecific diversity of exterior and genitalic morphology, varying host plant ranges, overlapping and widely extending species distributions, suggest an early origin for Minyomerus [JF2015], with a diversification that likely followed the development of North American desert biomes. Three species in the genus – i.e., M. languidus Horn, 1876 [JF2015], M. microps [JF2015], and M. trisetosus [JF2015] – are putatively considered parthenogenetic.

Classifications and phylogenetic inferences of organismal groups change in light of new insights. Over time these changes can result in an imperfect tracking of taxonomic perspectives through the re-/use of Code-compliant or informal names. To mitigate these limitations, we introduce a novel approach for aligning taxonomies through the interaction of human experts and logic reasoners. We explore the performance of this approach with the Perelleschus use case of Franz & Cardona-Duque (2013). The use case includes six taxonomies published from 1936 to 2013, 54 taxonomic concepts (i.e., circumscriptions of names individuated according to their respective source publications), and 75 expert-asserted Region Connection Calculus articulations (e.g., congruence, proper inclusion, overlap, or exclusion). An Open Source reasoning toolkit is used to analyze 13 paired Perelleschus taxonomy alignments under heterogeneous constraints and interpretations. The reasoning workflow optimizes the logical consistency and expressiveness of the input and infers the set of maximally informative relations among the entailed taxonomic concepts. The latter are then used to produce merge visualizations that represent all congruent and non-congruent taxonomic elements among the aligned input trees. In this small use case with 6-53 input concepts per alignment, the information gained through the reasoning process is on average one order of magnitude greater than in the input. The approach offers scalable solutions for tracking provenance among succeeding taxonomic perspectives that may have differential biases in naming conventions, phylogenetic resolution, ingroup and outgroup sampling, or ostensive (member-referencing) versus intensional (property-referencing) concepts and articulations.

Background: As biological disciplines extend into the ‘big data’ world, they will need a names-based infrastructure to index and interconnect distributed data. The infrastructure must have access to all names of all organisms if it is to manage all information. Those who compile lists of species hold different views as to the intellectual property rights that apply to the lists. This creates uncertainty that impedes the development of a much-needed infrastructure for sharing biological data in the digital world.

Findings: The laws in the United States of America and European Union are consistent with the position that scientific names of organisms and their compilation in checklists, classifications or taxonomic revisions are not subject to copyright. Compilations of names, such as classifications or checklists, are not creative in the sense of copyright law. Many content providers desire credit for their efforts.

Conclusions: A ‘blue list’ identifies elements of checklists, classifications and monographs to which intellectual property rights do not apply. To promote sharing, authors of taxonomic content, compilers, intermediaries, and aggregators should receive citable recognition for their contributions, with the greatest recognition being given to the originating authors. Mechanisms for achieving this are discussed.