Johnwellsia, a new intertidal genus of Parastenheliidae (Copepoda, Harpacticoida) from the Taiwan Strait, China, including a review of the family and key to genera

A new genus of Parastenheliidae, Johnwellsia gen. nov., is proposed for its type and only species, J. bipartita sp. nov., collected from Dadeji Beach in Xiamen, Taiwan Strait, China. The intricate taxonomic history of the family is reviewed with special emphasis on its type genus Parastenhelia Thompson & Scott, 1903. It is concluded that P. hornelli Thompson & Scott, 1903 is the type of the genus and that the widely adopted previous designation of Harpacticus spinosus Fischer, 1860 as type species of Parastenhelia is invalid. The taxonomic concept of Parastenhelia is restricted to the hornelli­-group which includes four valid species: P. hornelli, P. similis Thompson & Scott, 1903, P. oligochaeta Wells & Rao, 1987, and P. willemvervoorti sp. nov. The currently accepted concept of Parastenhelia spinosa as a highly variable cosmopolitan species is rejected. The genus Microthalestris Sars, 1905 (type: Thalestris forficula Claus, 1863) is resurrected to accommodate most Parastenhelia species that were previously placed in the spinosa-group. Two species, Thalestris forficuloides Scott & Scott, 1894 and Parastenhelia antarctica Scott, 1912, are reinstated as valid members of the genus which further includes Parastenhelia gracilis Brady, 1910, Microthalestris littoralis Sars, 1911, P. costata Pallares, 1982, P. minuta Pallares, 1982, P. bulbosa Gee, 2006 and five new species: M. campbelliensis sp. nov.; M. polaris sp. nov.; M. santacruzensis sp. nov.; M. sarsi sp. nov. and M. variabilis sp. nov. Both the type species, Thalestris forficula, and Harpacticus spinosus are considered species inquirendae in Microthalestris. Three new genera are proposed to accommodate the remaining Parastenhelia species. Porirualia gen. nov. contains P. megarostrum Wells, Hicks & Coull, 1982 (type) and P. pyriformis Song, Kim & Chang, 2003, and is the sistergroup of Johnwellsia gen. nov. Parastenhelia aydini Kuru & Karaytuğ, 2015 is placed in the monotypic genus Karaytugia gen. nov. while all species with penicillate elements on the antenna and P1 are transferred to Penicillicaris gen. nov., including Thalestris pectinimana Car, 1884, which is removed from the synonyms of the Parastenhelia spinosa (Fischer, 1860) “complex”, and three new species: P. maldivensis sp. nov., P. penicillata sp. nov., and P. sewelli sp. nov. The genus Karllangia Noodt, 1964 (type: K. arenicola Noodt, 1964) is relegated to a junior subjective synonym of Thalestrella Monard, 1935a (type: T. ornatissima Monard, 1935a). New or updated diagnoses for each genus, and differential diagnoses for species where appropriate, are provided. A key to the ten currently recognized genera in the Parastenheliidae is presented as well as keys to species for Parastenhelia, Microthalestris, Thalestrella and Penicillicaris gen. nov.

Chara zeylanica J.G.Klein ex Willd. (Charophyceae, Charales, Characeae): First European Record from the Island of Sardinia, Italy

The first record of a species belonging to the genus Chara L. subgenus Chara R.D.Wood section Grovesia R.D.Wood subsect. Willdenowia R.D.Wood from Europe is presented here, thus challenging the interpretation of its distribution pattern as an intertropical group of charophytes. The morphological characters of the specimens, as well as the results of a phylogenetic analysis, clearly identified them as Chara zeylanica J.G.Klein ex Willd. Although the subsection Willdenowia has yet to receive a thorough taxonomic treatment, a discussion of its relationship to other taxa of this subsection is provided despite the lack of a commonly agreed upon taxonomic concept. The ecological conditions of the Sardinian site of C. zeylanica are presented. Moreover, the status of and threats to this taxon, and hypotheses regarding potential pathways through which it reached Europe, are discussed.

Wanted: Standards for FAIR taxonomic concept representations and relationships

Making the most of biodiversity data requires linking observations of biological species from multiple sources both efficiently and accurately (Bisby 2000, Franz et al. 2016). Aggregating occurrence records using taxonomic names and synonyms is computationally efficient but known to experience significant limitations on accuracy when the assumption of one-to-one relationships between names and biological entities breaks down (Remsen 2016, Franz and Sterner 2018). Taxonomic treatments and checklists provide authoritative information about the correct usage of names for species, including operational representations of the meanings of those names in the form of range maps, reference genetic sequences, or diagnostic traits. They increasingly provide taxonomic intelligence in the form of precise description of the semantic relationships between different published names in the literature. Making this authoritative information Findable, Accessible, Interoperable, and Reusable (FAIR; Wilkinson et al. 2016) would be a transformative advance for biodiversity data sharing and help drive adoption and novel extensions of existing standards such as the Taxonomic Concept Schema and the OpenBiodiv Ontology (Kennedy et al. 2006, Senderov et al. 2018). We call for the greater, global Biodiversity Information Standards (TDWG) and taxonomy community to commit to extending and expanding on how FAIR applies to biodiversity data and include practical targets and criteria for the publication and digitization of taxonomic concept representations and alignments in taxonomic treatments, checklists, and backbones. As a motivating case, consider the abundantly sampled North American deer mouse—Peromyscus maniculatus (Wagner 1845)—which was recently split from one continental species into five more narrowly defined forms, so that the name P. maniculatus is now only applied east of the Mississippi River (Bradley et al. 2019, Greenbaum et al. 2019). That single change instantly rendered ambiguous ~7% of North American mammal records in the Global Biodiversity Information Facility (n=242,663, downloaded 2021-06-04; GBIF.org 2021) and ⅓ of all National Ecological Observatory Network (NEON) small mammal samples (n=10,256, downloaded 2021-06-27). While this type of ambiguity is common in name-based databases when species are split, the example of P. maniculatus is particularly striking for its impact upon biological questions ranging from hantavirus surveillance in North America to studies of climate change impacts upon rodent life-history traits. Of special relevance to NEON sampling is recent evidence suggesting deer mice potentially transmit SARS-CoV-2 (Griffin et al. 2021). Automating the updating of occurrence records in such cases and others will require operational representations of taxonomic concepts—e.g., range maps, reference sequences, and diagnostic traits—that are FAIR in addition to taxonomic concept alignment information (Franz and Peet 2009). Despite steady progress, it remains difficult to find, access, and reuse authoritative information about how to apply taxonomic names even when it is already digitized. It can also be difficult to tell without manual inspection whether similar types of concept representations derived from multiple sources, such as range maps or reference sequences selected from different research articles or checklists, are in fact interoperable for a particular application. The issue is therefore different from important ongoing efforts to digitize trait information in species circumscriptions, for example, and focuses on how already digitized knowledge can best be packaged to inform human experts and artifical intelligence applications (Sterner and Franz 2017). We therefore propose developing community guidelines and criteria for FAIR taxonomic concept representations as "semantic artefacts" of general relevance to linked open data and life sciences research (Le Franc et al. 2020).

Integrating Taxonomic Names and Concepts from Paper and Digital Sources for a New Flora of Alaska

The taxonomic foundation of a new regional flora or monograph is the reconciliation of pre-existing names and taxonomic concepts (i.e., variation in usage of those names). This reconciliation is traditionally done manually, but the availability of taxonomic resources online and of text manipulation software means that some of the work can now be automated, speeding up the development of new taxonomic products. As a contribution to developing a new Flora of Alaska (floraofalaska.org), we have digitized the main pre-existing flora (Hultén 1968) and combined it with key online taxonomic name sources (Panarctic Flora, Flora of North America, International Plant Names Index - IPNI, Tropicos, Kew’s World Checklist of Selected Plant Families), to build a canonical list of names anchored to external Globally Unique Identifiers (GUIDs) (e.g., IPNI URLs). We developed taxonomically-aware fuzzy-matching software (matchnames, Webb 2020) to identify cognates in different lists. The taxa for which there are variations between different sources in accepted names and synonyms are then flagged for review by taxonomic experts. However, even though names may be consistent across previous monographs and floras, the taxonomic concept (or circumscription) of a name may differ among authors, meaning that the way an accepted name in the flora is applied may be unfamiliar to the users of previous floras. We therefore have begun to manually align taxonomic concepts across five existing floras: Panarctic Flora, Flora of North America, Cody’s Flora of the Yukon (Cody 2000), Welsh’s Flora (Welsh 1974) and Hultén’s Flora (Hultén 1968), analysing usage and recording the Region Connection Calculus (RCC-5) relationships between taxonomic concepts common to each source. So far, we have mapped taxa in 13 genera, containing 557 taxonomic concepts and 482 taxonomic concept relationships. To facilitate this alignment process we developed software (tcm, Webb 2021) to record publications, names, taxonomic concepts and relationships, and to visualize the taxonomic concept relationships as graphs. These relationship graphs have proved to be accessible and valuable in discussing the frequently complex shifts in circumscription with the taxonomic experts who have reviewed the work. The taxonomic concept data are being integrated into the larger dataset to permit users of the new flora to instantly see both the chain of synonymy and concept map for any name. We have also worked with the developer of the Arctos Collection Management Solution (a database used for the majority of Alaskan collections) on new data tables for storage and display of taxonomic concept data. In this presentation, we will describe some of the ideas and workflows that may be of value to others working to connect across taxonomic resources.

​Fuzzy Logic Expert System for Taxonomic Variation of Solonchaks

Background: The main objective of this research is to apply fuzzy logic to four Solonchaks, in order to determine their degree of remoteness or rapprochement with their central taxonomic concept. Therefore, we identify their possible seasonal taxonomic variation on the criteria established by World Reference Base (WRB). Methods: We have studied the seasonal evolution of salinity in a region of Algeria (Case of Rélizane), during two years 2012 and 2013 by applying fuzzy logic on the four soils. Result: The results reveal that the salinity increased during the dry period for all soils and it decreased during the wet period. On the taxonomic level, the application of fuzzy logic on the four soils revealed that the Solonchaks indices (Is) are always significantly higher than those of Calcisols indices (Ic). The four profiles have a similar behavior regarding the variation of Is. Indeed, when the salinity increases the soils come closer to the central taxonomic concept of the Solonchaks. Likewise, when the salinity decreases the soils move away from their central taxonomic concept. Consequently, they approach the central taxonomic concept of Calcisols. Thus, the variation of Isis closely related to the seasonal variation of salinity. Fuzzy logic, exhibited high precision concerning the membership value between soils over time. The application of fuzzy logic for other soil classifications in the world is possible.

Review of the leucotela species-group of Conura (Hymenoptera: Chalcididae) from Amazon rainforest

The leucotela species-group of Conura Spinola (Hymenoptera: Chalcididae) was initially proposed to include C. leucotela (Walker 1862) within the subgenus Spilochalcis Thomson. Despite this treatment, the accurate identification of C. leucotela is not possible based on the literature. In this paper, C. leucotela is redescribed and two new species, C. paraleucotela sp. nov. and C. pseudoleucotela sp. nov., are described within the leucotela group, with all the species based on female singletons. Additionally, diagnoses and illustrations are presented for two other unnamed species based on males. The taxonomic concept of the species group is discussed, and new diagnostic characters are proposed. An identification key and illustration of species are provided. The morphology of the coupling mechanism of the propodeum and gaster of some species of the leucotela group and its relation with possible hosts is discussed. A short discussion of rarity of the leucotela group is presented.

What is Muscari massayanum and what is not? Second species born of confusion: Muscari erzincanicum (Asparagaceae, Scilloideae), a new species from Turkey

In the Flora of Turkey, the taxonomic concept of Muscari massayanum sensu Davis & Stuart was given based on five herbarium specimens and a photograph. In the original study, type location of the species was not specified, but its photograph and brief morphological features were included. In current study, herbarium samples given by Davis & Stuart under the description of the species in the Flora of Turkey were examined, and as a result of field studies conducted at the locations where these samples were collected, it was determined that the aforementioned description included M. massayanum, as well as the later published M. erdalii, and a new taxon yet to be named. As a result of comparative and detailed morphological studies to solve this confusion, a new species, Muscari erzincanicum (Asparagaceae) from Turkey, is described and illustrated. The new species is morphologically similar to M. massayanum and M. erdalii, but differs from both by the flower, fruit and seed characteristics.

On a Non-Discrete Concept of Prokaryotic Species

The taxonomic concept of species has received continuous attention. A microbial species as a discrete box contains a limited number of highly similar microorganisms assigned to that taxon, following a polyphasic approach. In the 21st Century, with the advancements of sequencing technologies and genomics, the existence of a huge prokaryotic diversity has become well known. At present, the prokaryotic species might no longer have to be understood as discrete values (such as 1 or 2, by homology to Natural numbers); rather, it is expected that some microorganisms could be potentially distributed (according to their genome features and phenotypes) in between others (such as decimal numbers between 1 and 2; real numbers). We propose a continuous species concept for microorganisms, which adapts to the current knowledge on the huge diversity, variability and heterogeneity existing among bacteria and archaea. Likely, this concept could be extended to eukaryotic microorganisms. The continuous species concept considers a species to be delimited by the distance between a range of variable features following a Gaussian-type distribution around a reference organism (i.e., its type strain). Some potential pros and cons of a continuous concept are commented on, offering novel perspectives on our understanding of the highly diversified prokaryotic world, thus promoting discussion and further investigation in the field.

New Triassic Aviculopectinoidea (Bivalvia), with notes on the taxonomic concept of the superfamily

We describe two new genera of Triassic Aviculopectinoidea: Cristaflabellum n. gen., which is biconvex and has a strongly plicate shell, and Globodiscus n. gen., which is equiconvex and externally smooth or nearly so. Globodiscus contains the new species G. kiliani n. gen. n. sp. and G. vinzenti n. gen. n. sp. In order to make the taxonomic concept of the superfamily Aviculopectinoidea more consistent with that of its sister group Pectinoidea (scallops), we use tribes rather than families or subfamilies for accommodating the new taxa. Cristaflabellum is placed in the tribe Antijanirini (previously family Antijaniridae), whereas Globodiscus is made the type genus of the new tribe Globodiscini. Both tribes are placed within the family Aviculopectinidae, which is revised to include both equiconvex and inequiconvex taxa. We suggest that tribes are a more appropriate taxonomic rank for many of the previously erected species-poor families and subfamilies of Aviculopectinoidea. UUID: http://zoobank.org/d143663a-9016-459f-8e24-660102adcf6a

The Automated Taxonomic Concept Reasoner

We present a visual and interactive taxonomic Artificial Intelligence (AI) tool, the Automated Taxonomic Concept Reasoner (ATCR), whose graphical web interface is under development and will also become available via an Application Programming Interface (API). The tool employs automated reasoning (Beeson 2014) to align multiple taxonomies visually, in a web browser, using user or expert-provided taxonomic articulations, i.e. "Region Connection Calculus (RCC-5) relationships between taxonomic concepts, provided in a specific logical language (Fig. 1). It does this by representing the problem of taxonomic alignment under these constraints in terms of logical inference, while performing these inferences computationally and leveraging the powerful Microsoft Z3 Satisfiability Modulo Theory (SMT) solver (de Moura and Bjørner 2008). This tool represents further development of utilities for the taxonomic concept approach, which fundamentally addresses the challenge of robust biodiversity data aggregation in light of multiple conflicting sources (and source classifications) from which primary biodiversity data almost invariably originate. The approach has proven superior to aggregation, based just on the syntax and semantics provided by the Darwin Core standard Franz and Sterner 2018). Fig. 1 provides an artificial example of such an alignment. Two taxonomies, A and B, are shown. There are five taxonomic concepts, A.One, A.Two, A.Three, B.One and B.Two. A.Two and A.Three are sub-concepts (children) of A.One, and B.Two is a sub-concept (child) of B.One. These are represented by the direction of the grey arrows. The undirected mustard-coloured lines represent relationships, i.e., the articulations referred to in the previous paragraph. These may be of five kinds: congruent (==), includes (<) and included in (>), overlap (><), and disjointness. These five relationships are known in the AI literature as the Region Connection Calculus-5 (RCC-5) (Randell et al. 1992, Bennett 1994, Bennett 1994), and taken exclusively and in conjunction with each other, have certain desirable properties with respect to the representation of spatial relationships. The provided relationship (i.e. the articulation) may also be an arbitrary disjunction of these five fundamental kinds, thus allowing for representation of some degree of logical uncertainty. Then, and under three assumptions that: "sibling" concepts are disjoint in their instances, all instances of a parent concept are instances of at least one of its child concepts, and every concept has at least one instance - the SMT-based automated reasoner is able to deduce the relationships represented by the undirected green lines. It is also able to deduce disjunctive relationships where these are logically implied. "sibling" concepts are disjoint in their instances, all instances of a parent concept are instances of at least one of its child concepts, and every concept has at least one instance - the SMT-based automated reasoner is able to deduce the relationships represented by the undirected green lines. It is also able to deduce disjunctive relationships where these are logically implied. ATCR is related to Euler/X (Franz et al. 2015), an existing tool for the same kinds of taxonomic alignment problems, which was used, for example, to obtain an alignment of two influential primate classifications (Franz et al. 2016). It differs from Euler/X in that it employs a different logical encoding that enables more efficient and more informative computational reasoning, and also in that it provides a graphical web interface, which Euler/X does not.