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Bayesian species delimitation in Pleophylla chafers (Coleoptera) – the importance of prior choice and morphology

Overview of attention for article published in BMC Ecology and Evolution, May 2016
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  • Good Attention Score compared to outputs of the same age (66th percentile)
  • Average Attention Score compared to outputs of the same age and source

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Title
Bayesian species delimitation in Pleophylla chafers (Coleoptera) – the importance of prior choice and morphology
Published in
BMC Ecology and Evolution, May 2016
DOI 10.1186/s12862-016-0659-3
Pubmed ID
Authors

Jonas Eberle, Rachel C. M. Warnock, Dirk Ahrens

Abstract

Defining species units can be challenging, especially during the earliest stages of speciation, when phylogenetic inference and delimitation methods may be compromised by incomplete lineage sorting (ILS) or secondary gene flow. Integrative approaches to taxonomy, which combine molecular and morphological evidence, have the potential to be valuable in such cases. In this study we investigated the South African scarab beetle genus Pleophylla using data collected from 110 individuals of eight putative morphospecies. The dataset included four molecular markers (cox1, 16S, rrnL, ITS1) and morphometric data based on male genital morphology. We applied a suite of molecular and morphological approaches to species delimitation, and implemented a novel Bayesian approach in the software iBPP, which enables continuous morphological trait and molecular data to be combined. Traditional morphology-based species assignments were supported quantitatively by morphometric analyses of the male genitalia (eigenshape analysis, CVA, LDA). While the ITS1-based delineation was also broadly congruent with the morphospecies, the cox1 data resulted in over-splitting (GMYC modelling, haplotype networks, PTP, ABGD). In the most extreme case morphospecies shared identical haplotypes, which may be attributable to ILS based on statistical tests performed using the software JML. We found the strongest support for putative morphospecies based on phylogenetic evidence using the combined approach implemented in iBPP. However, support for putative species was sensitive to the use of alternative guide trees and alternative combinations of priors on the population size (θ) and rootage (τ 0 ) parameters, especially when the analysis was based on molecular or morphological data alone. We demonstrate that continuous morphological trait data can be extremely valuable in assessing competing hypotheses to species delimitation. In particular, we show that the inclusion of morphological data in an integrative Bayesian framework can improve the resolution of inferred species units. However, we also demonstrate that this approach is extremely sensitive to guide tree and prior parameter choice. These parameters should be chosen with caution - if possible - based on independent empirical evidence, or careful sensitivity analyses should be performed to assess the robustness of results. Young species provide exemplars for investigating the mechanisms of speciation and for assessing the performance of tools used to delimit species on the basis of molecular and/or morphological evidence.

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The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 85 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 2 2%
United States 1 1%
Unknown 82 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 16%
Researcher 13 15%
Student > Bachelor 11 13%
Professor > Associate Professor 6 7%
Student > Master 6 7%
Other 19 22%
Unknown 16 19%
Readers by discipline Count As %
Agricultural and Biological Sciences 44 52%
Biochemistry, Genetics and Molecular Biology 12 14%
Environmental Science 3 4%
Nursing and Health Professions 1 1%
Philosophy 1 1%
Other 4 5%
Unknown 20 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 13 June 2016.
All research outputs
#7,777,586
of 25,371,288 outputs
Outputs from BMC Ecology and Evolution
#1,778
of 3,714 outputs
Outputs of similar age
#102,342
of 312,436 outputs
Outputs of similar age from BMC Ecology and Evolution
#42
of 79 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 3,714 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.5. This one has gotten more attention than average, scoring higher than 51% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 312,436 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
We're also able to compare this research output to 79 others from the same source and published within six weeks on either side of this one. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.