Publications by authors named "Nico Franz"

Arizona is home to many mosquito species, some of which are known vectors of infectious diseases that harm both humans and animals. Here, we provide an overview of the 56 mosquito species that have been identified in the State to date, but also discuss their known feeding preference and the diseases they can (potentially) transmit to humans and animals. This list is unlikely to be complete for several reasons: (i) Arizona's mosquitoes are not systematically surveyed in many areas, (ii) surveillance efforts often target specific species of interest, and (iii) doubts have been raised by one or more scientists about the accuracy of some collection records, which has been noted in this article.

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All aspects of biodiversity research, from taxonomy to conservation, rely on data associated with species names. Effective integration of names across multiple fields is paramount and depends on the coordination and organization of taxonomic data. We assess current efforts and find that even key applications for well-studied taxa still lack commonality in taxonomic information required for integration.

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How should billions of species observations worldwide be shared and made reusable? Many biodiversity scientists assume the ideal solution is to standardize all datasets according to a single, universal classification and aggregate them into a centralized, global repository. This ideal has known practical and theoretical limitations, however, which justifies investigating alternatives. To support better community deliberation and normative evaluation, we develop a novel conceptual framework showing how different organizational models, regulative ideals and heuristic strategies are combined to form shared infrastructures supporting data reuse.

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Background: The State of Arizona in the south-western United States supports a high diversity of insects. Digitised occurrence records, especially from preserved specimens in natural history collections, are an important and growing resource to understand biodiversity and biogeography. Underlying bias in how insects are collected and what that means for interpreting patterns of insect diversity is largely untested.

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Connecting basic data about bats and other potential hosts of SARS-CoV-2 with their ecological context is crucial to the understanding of the emergence and spread of the virus. However, when lockdowns in many countries started in March, 2020, the world's bat experts were locked out of their research laboratories, which in turn impeded access to large volumes of offline ecological and taxonomic data. Pandemic lockdowns have brought to attention the long-standing problem of so-called biological dark data: data that are published, but disconnected from digital knowledge resources and thus unavailable for high-throughput analysis.

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With over 300 species worldwide, the genus Curculio Linnaeus, 1758 is a widespread, morphologically diverse lineage of weevils that mainly parasitize nuts. Females use the rostrum, an elongate cuticular extension of the head, to excavate oviposition sites. This process causes extreme bending and deformation of the rostrum, without apparent harm to the structure.

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Centralized biodiversity data aggregation is too often failing societal needs due to pervasive and systemic data quality deficiencies. We argue for a novel approach that embodies the spirit of the Web ("small pieces loosely joined") through the decentralized coordination of data across scientific languages and communities. The upfront cost of decentralization can be offset by the long-term benefit of achieving sustained expert engagement, higher-quality data products, and ultimately more societal impact for biodiversity data.

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What should the best practices be for modeling zoonotic disease risks, e.g. to anticipate the next pandemic, when background assumptions are unsettled or evolving rapidly? This challenge runs deeper than one might expect, all the way into how we model the robustness of contemporary phylogenetic inference and taxonomic classifications.

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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).

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The collection and classification of data into meaningful categories is a key step in the process of knowledge making. In the life sciences, the design of data discovery and integration tools has relied on the premise that a formal classificatory system for expressing a body of data should be grounded in consensus definitions for classifications. On this approach, exemplified by the realist program of the Open Biomedical Ontologies Foundry, progress is maximized by grounding the representation and aggregation of data on settled knowledge.

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The acorn weevil (Curculio Linnaeus, 1758) rostrum (snout) exhibits remarkable flexibility and toughness derived from the microarchitecture of its exoskeleton. Modifications to the composite profile of the rostral cuticle that simultaneously enhance the flexibility and toughness of the distal portion of the snout are characterized. Using classical laminate plate theory, the effect of these modifications on the elastic behavior of the exoskeleton is estimated.

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Phylogenomic research is accelerating the publication of landmark studies that aim to resolve deep divergences of major organismal groups. Meanwhile, systems for identifying and integrating the products of phylogenomic inference-such as newly supported clade concepts-have not kept pace. However, the ability to verbalize node concept congruence and conflict across multiple, in effect simultaneously endorsed phylogenomic hypotheses, is a prerequisite for building synthetic data environments for biological systematics and other domains impacted by these conflicting inferences.

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This contribution adopts the taxonomic concept approach, including the use of (name sec. [] source) and region connection calculus-5 (RCC-5) articulations and alignments. Prior to this study, the broad-nosed weevil genus Horn, 1876 sec.

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Generating regional checklists for insects is frequently based on combining data sources ranging from literature and expert assertions that merely imply the existence of an occurrence to aggregated, standard-compliant data of uniquely identified specimens. The increasing diversity of data sources also means that checklist authors are faced with new responsibilities, effectively acting as filterers to select and utilize an expert-validated subset of all available data. Authors are also faced with the technical obstacle to bring more occurrences into Darwin Core-based data aggregation, even if the corresponding specimens belong to external institutions.

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We utilize an Answer Set Programming (ASP) approach to show that the principles of nomenclature are tractable in computational logic. To this end we design a hypothetical, 20 nomenclatural taxon use case, with starting conditions that embody several overarching principles of the International Code of Zoological Nomenclature, including Binomial Nomenclature, Priority, Coordination, Homonymy, Typification and the structural requirement of Gender Agreement. The use case ending conditions are triggered by the reinterpretation of the diagnostic features of one of 12 type specimens anchoring the corresponding species-level epithets.

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Background: The biodiversity domain, and in particular biological taxonomy, is moving in the direction of semantization of its research outputs. The present work introduces OpenBiodiv-O, the ontology that serves as the basis of the OpenBiodiv Knowledge Management System. Our intent is to provide an ontology that fills the gaps between ontologies for biodiversity resources, such as DarwinCore-based ontologies, and semantic publishing ontologies, such as the SPAR Ontologies.

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Growing concerns about the quality of aggregated biodiversity data are lowering trust in large-scale data networks. Aggregators frequently respond to quality concerns by recommending that biologists work with original data providers to correct errors 'at the source.' We show that this strategy falls systematically short of a full diagnosis of the underlying causes of distrust.

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The Lepidoptera of North America Network, or LepNet, is a digitization effort recently launched to mobilize biodiversity data from 3 million specimens of butterflies and moths in United States natural history collections (http://www.lep-net.org/).

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Background: Using syntactic and semantic conventions of the taxonomic concept approach (Franz et al. 2015), we describe three newly recognized fossil broad-nosed weevils (Coleoptera: Curculionidae: Entiminae) preserved in Early Miocene amber (ca. 20.

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Statistical historical biogeographic methods rely on models that represent various biogeographic processes. Until recently model selection in this domain was not widely used, and the impact of differential model selection on inferring biogeographic scenarios was not well understood. Focusing on Neotropical weevils in the Exophthalmus genus complex (EGC) (Insecta: Curculionidae: Entiminae), we compare three commonly used biogeographic models - DIVA (Dispersal-Vicariance Analysis), DEC (Dispersal-Extinction-Cladogenesis) and BayArea (Bayesian Analysis of Biogeography), and examine the impact of modeling founder-event jump dispersal on historical biogeographic reconstructions.

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Curculio longinasus Chittenden, 1927 (Coleoptera: Curculionidae), is a weevil species common throughout the southwestern United States that uses its rostrum - a very slender, curved, beak-like projection of the head - to excavate tunnels in plant organs (such as acorns) for egg laying (oviposition). Once the apical portion of the rostrum has been inserted into the preferred substrate for oviposition, the female begins rotating around the perimeter of the hole, elevating her head by extending the fore-legs, and rotating the head in place in a drilling motion. This action causes significant elastic deformation of the rostrum, which will bend until it becomes completely straight.

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Classifications and phylogenies of perceived natural entities change in the light of new evidence. Taxonomic changes, translated into Code-compliant names, frequently lead to name:meaning dissociations across succeeding treatments. Classification standards such as the Mammal Species of the World (MSW) may experience significant levels of taxonomic change from one edition to the next, with potential costs to long-term, large-scale information integration.

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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.

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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.

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