Campus Units

Ecology, Evolution and Organismal Biology

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Publication Version

Accepted Manuscript

Publication Date


Journal or Book Title

Molecular Phylogenetics and Evolution




Paederinae is one of the most diverse subfamilies among rove beetles, yet their evolutionary history remains poorly understood. This is attributed to the limited number of phylogenetic studies, which either sought answers at a shallower taxonomic level or included limited taxon sampling. Especially problematic is the position of the rare Neotropical tribe Cylindroxystini, morphologically one of the most puzzling groups of Paederinae. The phylogenetic position of this group within Paederinae was never understood, though its rank in the classification has already been shifted twice. We assembled molecular and morphological data matrices sampled from all currently recognized Paederinae subtribes, including both genera of Cylindroxystini, and used these data to estimate phylogenetic relationships using Bayesian inference. A total of 123 morphological characters and 4,631 bp of nuclear (28S, TP, Wg, CADA, CADC, ArgK) and mitochondrial (COI) sequences were analyzed for 76 taxa. The current tribe Cylindroxystini was resolved as a monophylum within the tribe Lathrobiini as sister to the genus Pseudolathra, and together they are sister to the so-called ‘Medonina and allied taxa’ clade. Based on these results, we downgraded Cylindroxystini back to the subtribal level, Cylindroxystina status reinstated, now with a known sister group. The resulting phylogeny is the largest of the subfamily Paederinae to date and lays the foundation for establishing a natural classification of the group.


This is a manuscript of an article published as Żyła, Dagmara, Amalia Bogri, Tracy A. Heath, and Alexey Solodovnikov. "Total-evidence analysis resolves the phylogenetic position of an enigmatic group of Paederinae rove beetles (Coleoptera: Staphylinidae)." Molecular Phylogenetics and Evolution (2020): 107059. doi: 10.1016/j.ympev.2020.107059.

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Copyright Owner

Elsevier Inc.



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Available for download on Tuesday, December 28, 2021

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