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      The first fossil Hybocephalini (Coleoptera: Staphylinidae: Pselaphinae) from the middle Eocene of Europe and its evolutionary and biogeographic implications

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      Arthropod Systematics & Phylogeny
      Pensoft Publishers

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          Abstract

          The extant tropical tribe Hybocephalini is a morphologically highly derived group of the subfamily Pselaphinae (Coleoptera: Staphylinidae), which is characterized most notably by the modified squamous setae that cover various parts of the body. Ten genera and 69 extant species have been found in the Afrotropical and Oriental regions, with one species found in northern Australia. Prior to this study the evolutionary history of the tribe has been remained elusive due to the dearth of known fossils. Here, we describe the first fossil representative of Hybocephalini, Europharinodes schaufussi Yin & Cai gen. et sp. nov., based on an adult male preserved in Baltic amber (ca 45.0–38.0 Ma). Using X-ray microtomography, the anatomy including the endoskeletal structures of the head, the full pattern of foveation, and the aedeagus of the beetle were reconstructed. Europharinodes shares most derived traits that are congruent with extant members of Hybocephalini, but it also possesses plesiomorphic and autapomorphic characters unknown in living relatives. In order to constrain the phylogenetic placement of Europharinodes, we created an updated morphological character matrix to explore relationships among this genus and related groups. A monophyletic Hybocephalini was recovered by maximum likelihood and parsimony analyses, with Europharinodes being well-resolved as sister to all modern relatives in the likelihood tree. The fossil thus sheds new light on the morphological evolution of Hybocephalini and suggests a broader palaeodistribution of the tribe during the middle Eocene. The disjunct distribution of an Eocene Baltic amber species and an extant Afrotropical-Oriental distribution of the tribe is probably relictual, and was shaped by global cooling during the Eocene–Oligocene transition.

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          IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies

          Large phylogenomics data sets require fast tree inference methods, especially for maximum-likelihood (ML) phylogenies. Fast programs exist, but due to inherent heuristics to find optimal trees, it is not clear whether the best tree is found. Thus, there is need for additional approaches that employ different search strategies to find ML trees and that are at the same time as fast as currently available ML programs. We show that a combination of hill-climbing approaches and a stochastic perturbation method can be time-efficiently implemented. If we allow the same CPU time as RAxML and PhyML, then our software IQ-TREE found higher likelihoods between 62.2% and 87.1% of the studied alignments, thus efficiently exploring the tree-space. If we use the IQ-TREE stopping rule, RAxML and PhyML are faster in 75.7% and 47.1% of the DNA alignments and 42.2% and 100% of the protein alignments, respectively. However, the range of obtaining higher likelihoods with IQ-TREE improves to 73.3-97.1%.
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            MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space

            Since its introduction in 2001, MrBayes has grown in popularity as a software package for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) methods. With this note, we announce the release of version 3.2, a major upgrade to the latest official release presented in 2003. The new version provides convergence diagnostics and allows multiple analyses to be run in parallel with convergence progress monitored on the fly. The introduction of new proposals and automatic optimization of tuning parameters has improved convergence for many problems. The new version also sports significantly faster likelihood calculations through streaming single-instruction-multiple-data extensions (SSE) and support of the BEAGLE library, allowing likelihood calculations to be delegated to graphics processing units (GPUs) on compatible hardware. Speedup factors range from around 2 with SSE code to more than 50 with BEAGLE for codon problems. Checkpointing across all models allows long runs to be completed even when an analysis is prematurely terminated. New models include relaxed clocks, dating, model averaging across time-reversible substitution models, and support for hard, negative, and partial (backbone) tree constraints. Inference of species trees from gene trees is supported by full incorporation of the Bayesian estimation of species trees (BEST) algorithms. Marginal model likelihoods for Bayes factor tests can be estimated accurately across the entire model space using the stepping stone method. The new version provides more output options than previously, including samples of ancestral states, site rates, site d N /d S rations, branch rates, and node dates. A wide range of statistics on tree parameters can also be output for visualization in FigTree and compatible software.
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              ModelFinder: Fast Model Selection for Accurate Phylogenetic Estimates

              Model-based molecular phylogenetics plays an important role in comparisons of genomic data, and model selection is a key step in all such analyses. We present ModelFinder, a fast model-selection method that greatly improves the accuracy of phylogenetic estimates. The improvement is achieved by incorporating a model of rate-heterogeneity across sites not previously considered in this context, and by allowing concurrent searches of model-space and tree-space.
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                Author and article information

                Contributors
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                Journal
                Arthropod Systematics & Phylogeny
                ASP
                Pensoft Publishers
                1864-8312
                1863-7221
                July 19 2022
                July 19 2022
                : 80
                : 279-294
                Article
                10.3897/asp.80.e82644
                4b004684-6013-4b30-a8d5-9d3cac6a5f46
                © 2022

                http://creativecommons.org/licenses/by/4.0/

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