Bird Name-a-thon: Categorizing English bird names using crowdsourcing

Morrison, E. S.; Pandolfi, G. P.; Aguillon, S. M.; Ali, J. R.; Archard, O.; Baldassarre, D. T.; Baquero, I.; Bennett, K. F. P.; Bonney, K. M.; Bryant, R.; Catanach, R. M.; Catanach, T. A.; Chavoshan, I.; Davis, S. N.; Goodman, B. D.; Gulson-Castillo, E. R.; Hack, M.; Hudon, J.; Leighton, G. M.; Long, K. M.; Ma, Z.; McCoy, D. E.; McLaughlin, J. F.; Rueda Moreno, G.; Mota, T. M.; Noguchi, L.; Nwigwe, U.; Pegan, T.; Provost, K.; Rasband, S. A.; Salter, J. F.; Silvernail, L. C.; Simard, J. A.; Skeen, H. R.; Soto-Patino, J.; Suh, Y. H.; Wang, Q.; Warshauer, M. E.; Yan, S.; Zalinski, B.; Zhao, Z.; S

doi:10.1101/2024.09.13.612884

Home/Archive/bioRxiv

bioRxiv · 10.1101/2024.09.13.612884

Bird Name-a-thon: Categorizing English bird names using crowdsourcing

View original source ↗Export metadata ↓

Abstract

Common names of species are important for communicating with the general public. In principle, these names should provide an accessible way to engage with and identify species. The common names of species have historically been labile without standard guidelines, even within a language. Currently, there is no systematic assessment of how often common names communicate identifiable and biologically relevant characteristics about species. This is a salient issue in ornithology, where common names are used more often than scientific names for species of birds in written and spoken English, even by professional researchers. To gain a better understanding of the types of terminology used in the English-language common names of bird species, a group of 85 professional ornithologists and non-professional contributors classified unique descriptors in the common names of all recognized species of birds. In the AvianLexiconAtlas database produced by this work, each species common name is assigned to one of ten categories associated with aspects of avian biology, ecology, or human culture. Across 10,906 species of birds, 89% have names describing the biology of the species, while the remaining 11% of species have names derived from human cultural references, human names, or local non-English languages. Species with common names based on features of avian biology are more likely to be related to each other or be from the same geographic region. The crowdsourced data collection also revealed that many common names contain specialized or historic terminology unknown to many of the data collectors, and we include these terms in a glossary and gazetteer alongside the dataset. The AvianLexiconAtlas can be used as a quantitative resource to assess the state of terminology in English-language common names of birds. Future research using the database can shed light on historical approaches to nomenclature and how people engage with species through their names.

Source connections

Published article ↗

Explore related subjects

zoology Preprint

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Morrison, E. S., Pandolfi, G. P., Aguillon, S. M., Ali, J. R., Archard, O., Baldassarre, D. T., Baquero, I., Bennett, K. F. P., Bonney, K. M., Bryant, R., Catanach, R. M., Catanach, T. A., Chavoshan, I., Davis, S. N., Goodman, B. D., Gulson-Castillo, E. R., Hack, M., Hudon, J., Leighton, G. M., Long, K. M., Ma, Z., McCoy, D. E., McLaughlin, J. F., Rueda Moreno, G., Mota, T. M., Noguchi, L., Nwigwe, U., Pegan, T., Provost, K., Rasband, S. A., Salter, J. F., Silvernail, L. C., Simard, J. A., Skeen, H. R., Soto-Patino, J., Suh, Y. H., Wang, Q., Warshauer, M. E., Yan, S., Zalinski, B., Zhao, Z., S. 2024-09-16. Bird Name-a-thon: Categorizing English bird names using crowdsourcing. https://doi.org/10.1101/2024.09.13.612884

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Glutamatergic system in the pelagic tunicates

Tunicates are a sister lineage to vertebrates, with compact, relatively simple nervous systems featuring a single central ganglion, reflecting a minimal complement of chordate functional architecture. Although glutamatergic neurons are the most abundant population in vertebrates, their ancestry remains unclear. Here, we used glutamate immunohistochemical labeling (Glutamate IR) to identify glutamatergic elements in the neural system of the pelagic tunicate Doliolum sp. (Thaliacea). Glutamate IR was observed in all major nerves of the central ganglion, including motor-like terminals on the circular bundles of swim muscles, which were themselves labeled. However, the neuronal somata in the central ganglion were not labeled, suggesting glutamate accumulation in axonal processes and terminals. In contrast, we did not identify GABA-containing neural elements. This study suggests that glutamatergic systems were elaborated in the common ancestor of tunicates and vertebrates, although the functional role of glutamate and its role in muscular control need further investigation in these pelagic tunicates.

zoology↗

bioRxiv2026

The enlightened entomologist: fast, non-destructive whole-arthropod clearing for three-dimensional imaging

Arthropods are a strikingly diverse phylum of invertebrates with segmented bodies, chitinous exoskeletons, and jointed limbs, many of which are colloquially referred to as insects. Their pigmented and optically dense bodies pose a considerable challenge for microscopy. While early naturalists focused on external features, modern approaches combining tissue clearing and fluorescence microscopy seek to explore internal anatomy in three dimensions. However, both chemical clearing and three-dimensional (3-D) microscopy are specialized techniques and often require considerable adaptation and optimization across species. Here, we introduce a versatile, fast, effective and non-toxic clearing method that renders diverse arthropods transparent within hours to days. Existing upright microscopes or macroscopes can be upgraded with a modular and affordable light-sheet microscope, allowing rapid volumetric imaging of arthropods. Our pipeline is fully compatible with dye staining and immunofluorescence labeling, while endogenous autofluorescence provides valuable anatomical context and facilitates 3-D reconstruction.

zoology↗

bioRxiv2026

Wildlife disease surveillance under uncertainty: an adaptive search-theoretic framework for early detection of transboundary animal diseases

Rapid detection is critical for successful management of transboundary animal disease incursions in wild host populations. However, decisions about how best to allocate wildlife disease surveillance effort must be made under high uncertainty. Risk-based surveillance can improve efficiency but approaches that focus surveillance too narrowly on expected high risk areas could have low power to detect unexpected events. We developed and field-tested an adaptive, search-theoretic surveillance framework for detecting transboundary animal disease incursions in wild ungulates in New South Wales, Australia. Key principles that guided the frameworks development included accommodating uncertainty, regularly updating search priorities based on expected risk and spatial coverage, and a flexible structure that allows the system to respond to changing information or conditions over time. We created a coarse state-wide risk map that served as a weakly informative prior describing expected variability in disease incursion risk, loosely focused on foot and mouth disease virus (FMDv). Risk and search values were updated every three months based on realised surveillance effort and estimated detection probabilities over the preceding 12 months, meaning that areas of persistently high risk could nonetheless have low search value if they had recently been intensively searched. Surveillance activities collected blood and swab samples from 1,964 wild pigs (Sus scrofa) during 110 sampling occasions over a two-year evaluation and refinement period. Activities sought to simulate FMDv surveillance operations, but FMDv serological tests were not available at the time. Effort was consistently concentrated in areas of high search value, with at least 74% of sampled cells in the highest risk class. Estimated surveillance system sensitivity ranged from 0.86 to 0.93 over five successive updating cycles and increased as operational procedures were refined. Although the surveillance program was based on FMDv incursion risk, it also fulfilled its secondary objective of detecting unexpected events, including detecting Japanese encephalitis virus in wild pigs before detections in humans and domestic animals. By combining risk-based surveillance with adaptive updating of search priorities in a modular structure, the framework provided a flexible and generalisable approach for early detection of transboundary and emerging animal disease incursions in wildlife populations under high uncertainty.

zoology↗