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| 2. |
- Antonelli, Alexandre, 1978, et al.
(författare)
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Mass Extinction, Gradual Cooling, or Rapid Radiation? Reconstructing the Spatiotemporal Evolution of the Ancient Angiosperm Genus Hedyosmum (Chloranthaceae) Using Empirical and Simulated Approaches
- 2011
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Ingår i: Systematic Biology. - : Oxford University Press (OUP). - 1063-5157 .- 1076-836X. ; 60:5, s. 596-615
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Tidskriftsartikel (refereegranskat)abstract
- Chloranthaceae is a small family of flowering plants (65 species) with an extensive fossil record extending back to the Early Cretaceous. Within Chloranthaceae, Hedyosmum is remarkable because of its disjunct distribution-1 species in the Paleotropics and 44 confined to the Neotropics-and a long "temporal gap" between its stem age (Early Cretaceous) and the beginning of the extant radiation (late Cenozoic). Is this gap real, reflecting low diversification and a recent radiation, or the signature of extinction? Here we use paleontological data, relaxed-clock molecular dating, diversification analyses, and parametric ancestral area reconstruction to investigate the timing, tempo, and mode of diversification in Hedyosmum. Our results, based on analyses of plastid and nuclear sequences for 40 species, suggest that the ancestor of Chloranthaceae and the Hedyosmum stem lineages were widespread in the Holarctic in the Late Cretaceous. High extinction rates, possibly associated with Cenozoic climatic fluctuations, may have been responsible for the low extant diversity of the family. Crown group Hedyosmum originated c.36-43 Ma and colonized South America from the north during the Early-Middle Miocene (c.20 Ma). This coincided with an increase in diversification rates, probably triggered by the uplift of the Northern Andes from the Mid-Miocene onward. This study illustrates the advantages of combining paleontological, phylogenetic, and biogeographic data to reconstruct the spatiotemporal evolution of an ancient lineage, for which the extant diversity is only a remnant of past radiations. It also shows the difficulties of inferring patterns of lineage diversification when incomplete taxon sampling is combined with high extinction rates.
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| 3. |
- Bergsten, Johannes, et al.
(författare)
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Bayesian Tests of Topology Hypotheses with an Example from Diving Beetles
- 2013
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Ingår i: Systematic Biology. - : Oxford University Press (OUP). - 1063-5157 .- 1076-836X. ; 62:5, s. 660-673
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Tidskriftsartikel (refereegranskat)abstract
- We review Bayesian approaches to model testing in general and to the assessment of topological hypotheses in particular. We show that the standard way of setting up Bayes factor tests of the monophyly of a group, or the placement of a sample sequence in a known reference tree, can be misleading. The reason for this is related to the well-known dependency of Bayes factors on model-specific priors. Specifically, when testing tree hypotheses it is important that each hypothesis is associated with an appropriate tree space in the prior. This can be achieved by using appropriately constrained searches or by filtering trees in the posterior sample, but in a more elaborate way than typically implemented. If it is difficult to find the appropriate tree sets to be contrasted, then the posterior model odds may be more informative than the Bayes factor. We illustrate the recommended techniques using an empirical test case addressing the issue of whether two genera of diving beetles (Coleoptera: Dytiscidae), Suphrodytes and Hydroporus, should be synonymized. Our refined Bayes factor tests, in contrast to standard analyses, show that there is strong support for Suphrodytes nesting inside Hydroporus, and the genera are therefore synonymized.
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| 4. |
- Bergsten, Johannes, et al.
(författare)
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The Effect of Geographical Scale of Sampling on DNA Barcoding
- 2012
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Ingår i: Systematic Biology. - : Oxford University Press (OUP). - 1063-5157 .- 1076-836X. ; 61:5, s. 851-869
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Tidskriftsartikel (refereegranskat)abstract
- Eight years after DNA barcoding was formally proposed on a large scale, CO1 sequences are rapidly accumulating from around the world. While studies to date have mostly targeted local or regional species assemblages, the recent launch of the global iBOL project (International Barcode of Life), highlights the need to understand the effects of geographical scale on Barcoding's goals. Sampling has been central in the debate on DNA Barcoding, but the effect of the geographical scale of sampling has not yet been thoroughly and explicitly tested with empirical data. Here, we present a CO1 data set of aquatic predaceous diving beetles of the tribe Agabini, sampled throughout Europe, and use it to investigate how the geographic scale of sampling affects 1) the estimated intraspecific variation of species, 2) the genetic distance to the most closely related heterospecific, 3) the ratio of intraspecific and interspecific variation, 4) the frequency of taxonomically recognized species found to be monophyletic, and 5) query identification performance based on 6 different species assignment methods. Intraspecific variation was significantly correlated with the geographical scale of sampling (R-square = 0.7), and more than half of the species with 10 or more sampled individuals (N = 29) showed higher intraspecific variation than 1%, sequence divergence. In contrast, the distance to the closest heterospecific showed a significant decrease with increasing geographical scale of sampling. The average genetic distance dropped from >7% for samples within 1 km, to <3.5% for samples up to >6000 km apart. Over a third of the species were not monophyletic, and the proportion increased through locally, nationally, regionally, and continentally restricted subsets of the data. The success of identifying queries decreased with increasing spatial scale of sampling; liberal methods declined from 100% to around 90%, whereas strict methods dropped to below 50% at continental scales. The proportion of query, identifications considered uncertain (more than one species <1% distance from query) escalated from zero at local, to 50% at continental scale. Finally, by resampling the most widely sampled species we show that even if samples are collected to maximize the geographical coverage, up to 70 individuals are required to sample 95%, of intraspecific variation. The results show that the geographical scale of sampling has a critical impact on the global application of DNA barcoding. Scale-effects result from the relative importance of different processes determining the composition of regional species assemblages (dispersal and ecological assembly) and global clades (demography, speciation, and extinction). The incorporation of geographical information, where available, will be required to obtain identification rates at global scales equivalent to those in regional barcoding studies. Our result hence provides an impetus for both smarter barcoding tools and sprouting national barcoding initiatives smaller geographical scales deliver higher accuracy.
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| 5. |
- Bokma, Folmer, et al.
(författare)
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50 years of inordinate fondness
- 2014
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Ingår i: Systematic Biology. - : Oxford University Press. - 1063-5157 .- 1076-836X. ; 63:2, s. 251-256
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Tidskriftsartikel (refereegranskat)
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| 6. |
- Bokma, Folmer
(författare)
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Speciation and Patterns of Diversity
- 2010
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Ingår i: Systematic Biology. - : Oxford University Press. - 1063-5157 .- 1076-836X. ; 59:3, s. 365-367
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Recension (refereegranskat)
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| 7. |
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| 8. |
- Ekman, Stefan, 1965-, et al.
(författare)
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The Devil in the Details : Interactions between the Branch-Length Prior and Likelihood Model Affect Node Support and Branch Lengths in the Phylogeny of the Psoraceae
- 2011
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Ingår i: Systematic Biology. - : Oxford University Press (OUP). - 1063-5157 .- 1076-836X. ; 60:4, s. 541-561
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Tidskriftsartikel (refereegranskat)abstract
- In popular use of Bayesian phylogenetics, a default branch-length prior is almost universally applied without knowing how a different prior would have affected the outcome. We performed Bayesian and maximum likelihood (ML) inference of phylogeny based on empirical nucleotide sequence data from a family of lichenized ascomycetes, the Psoraceae, the morphological delimitation of which has been controversial. We specifically assessed the influence of the combination of Bayesian branch-length prior and likelihood model on the properties of the Markov chain Monte Carlo tree sample, including node support, branch lengths, and taxon stability. Data included two regions of the mitochondrial ribosomal RNA gene, the internal transcribed spacer region of the nuclear ribosomal RNA gene, and the protein-coding largest subunit of RNA polymerase II. Data partitioning was performed using Bayes' factors, whereas the best-fitting model of each partition was selected using the Bayesian information criterion (BIC). Given the data and model, short Bayesian branch-length priors generate higher numbers of strongly supported nodes as well as short and topologically similar trees sampled from parts of tree space that are largely unexplored by the ML bootstrap. Long branch-length priors generate fewer strongly supported nodes and longer and more dissimilar trees that are sampled mostly from inside the range of tree space sampled by the ML bootstrap. Priors near the ML distribution of branch lengths generate the best marginal likelihood and the highest frequency of "rogue" (unstable) taxa. The branch-length prior was shown to interact with the likelihood model. Trees inferred under complex partitioned models are more affected by the stretching effect of the branch-length prior. Fewer nodes are strongly supported under a complex model given the same branch-length prior. Irrespective of model, internal branches make up a larger proportion of total tree length under the shortest branch-length priors compared with longer priors. Relative effects on branch lengths caused by the branch-length prior can be problematic to downstream phylogenetic comparative methods making use of the branch lengths. Furthermore, given the same branch-length prior, trees are on average more dissimilar under a simple unpartitioned model compared with a more complex partitioned models. The distribution of ML branch lengths was shown to better fit a gamma or Pareto distribution than an exponential one. Model adequacy tests indicate that the best-fitting model selected by the BIC is insufficient for describing data patterns in 5 of 8 partitions. More general substitution models are required to explain the data in three of these partitions, one of which also requires nonstationarity. The two mitochondrial ribosomal RNA gene partitions need heterotachous models. We found no significant correlations between, on the one hand, the amount of ambiguous data or the smallest branch-length distance to another taxon and, on the other hand, the topological stability of individual taxa. Integrating over several exponentially distributed means under the best-fitting model, node support for the family Psoraceae, including Psora, Protoblastenia, and the Micarea sylvicola group, is approximately 0.96. Support for the genus Psora is distinctly lower, but we found no evidence to contradict the current classification.
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| 9. |
- Guschanski, Katerina, Dr. 1978-, et al.
(författare)
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Next-Generation Museomics Disentangles One of the Largest Primate Radiations
- 2013
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Ingår i: Systematic Biology. - : Oxford University Press (OUP). - 1063-5157 .- 1076-836X. ; 62:4, s. 539-554
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Tidskriftsartikel (refereegranskat)abstract
- Guenons (tribe Cercopithecini) are one of the most diverse groups of primates. They occupy all of sub-Saharan Africa and show great variation in ecology, behavior, and morphology. This variation led to the description of over 60 species and subspecies. Here, using next-generation DNA sequencing (NGS) in combination with targeted DNA capture, we sequenced 92 mitochondrial genomes from museum-preserved specimens as old as 117 years. We infer evolutionary relationships and estimate divergence times of almost all guenon taxa based on mitochondrial genome sequences. Using this phylogenetic framework, we infer divergence dates and reconstruct ancestral geographic ranges. We conclude that the extraordinary radiation of guenons has been a complex process driven by, among other factors, localized fluctuations of African forest cover. We find incongruences between phylogenetic trees reconstructed from mitochondrial and nuclear DNA sequences, which can be explained by either incomplete lineage sorting or hybridization. Furthermore, having produced the largest mitochondrial DNA data set from museum specimens, we document how NGS technologies can “unlock” museum collections, thereby helping to unravel the tree-of-life. [Museum collection; next-generation DNA sequencing; primate radiation; speciation; target capture.]
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| 10. |
- Hansen, T. F., et al.
(författare)
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Interpreting the Evolutionary Regression: The Interplay Between Observational and Biological Errors in Phylogenetic Comparative Studies
- 2012
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Ingår i: Systematic Biology. - Oxford : Oxford University Press (OUP). - 1063-5157 .- 1076-836X. ; 61:3, s. 413-425
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Tidskriftsartikel (refereegranskat)abstract
- Regressions of biological variables across species are rarely perfect. Usually, there are residual deviations from the estimated model relationship, and such deviations commonly show a pattern of phylogenetic correlations indicating that they have biological causes. We discuss the origins and effects of phylogenetically correlated biological variation in regression studies. In particular, we discuss the interplay of biological deviations with deviations due to observational or measurement errors, which are also important in comparative studies based on estimated species means. We show how bias in estimated evolutionary regressions can arise from several sources, including phylogenetic inertia and either observational or biological error in the predictor variables. We show how all these biases can be estimated and corrected for in the presence of phylogenetic correlations. We present general formulas for incorporating measurement error in linear models with correlated data. We also show how alternative regression models, such as major axis and reduced major axis regression, which are often recommended when there is error in predictor variables, are strongly biased when there is biological variation in any part of the model. We argue that such methods should never be used to estimate evolutionary or allometric regression slopes.
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