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Inferring Speciation and Extinction Rates under Different Sampling Schemes
Stockholm University, Faculty of Science, Department of Mathematics.
Stockholm University, Faculty of Science, Department of Mathematics.
2011 (English)In: Molecular biology and evolution, ISSN 0737-4038, E-ISSN 1537-1719, Vol. 28, no 9, 2577-2589 p.Article in journal (Refereed) Published
Abstract [en]

The birth-death process is widely used in phylogenetics to model speciation and extinction. Recent studies have shown that the inferred rates are sensitive to assumptions about the sampling probability of lineages. Here, we examine the effect of the method used to sample lineages. Whereas previous studies have assumed random sampling (RS), we consider two extreme cases of biased sampling: diversified sampling (DS), where tips are selected to maximize diversity and cluster sampling (CS), where sample diversity is minimized. DS appears to be standard practice, for example, in analyses of higher taxa, whereas CS may occur under special circumstances, for example, in studies of geographically defined floras or faunas. Using both simulations and analyses of empirical data, we show that inferred rates may be heavily biased if the sampling strategy is not modeled correctly. In particular, when a diversified sample is treated as if it were a random or complete sample, the extinction rate is severely underestimated, often close to 0. Such dramatic errors may lead to serious consequences, for example, if estimated rates are used in assessing the vulnerability of threatened species to extinction. Using Bayesian model testing across 18 empirical data sets, we show that DS is commonly a better fit to the data than complete, random, or cluster sampling (CS). Inappropriate modeling of the sampling method may at least partly explain anomalous results that have previously been attributed to variation over time in birth and death rates.

Place, publisher, year, edition, pages
2011. Vol. 28, no 9, 2577-2589 p.
Keyword [en]
birth and death process, speciation, extinction, phylogenetics, species tree, sampling, inference
National Category
Evolutionary Biology Mathematics
Research subject
Mathematical Statistics
Identifiers
URN: urn:nbn:se:su:diva-68019DOI: 10.1093/molbev/msr095ISI: 000294552700018OAI: oai:DiVA.org:su-68019DiVA: diva2:471905
Note

authorCount :4

Available from: 2012-01-03 Created: 2012-01-02 Last updated: 2017-12-08Bibliographically approved
In thesis
1. Bayesian Phylogenetic Inference: Estimating Diversification Rates from Reconstructed Phylogenies
Open this publication in new window or tab >>Bayesian Phylogenetic Inference: Estimating Diversification Rates from Reconstructed Phylogenies
2013 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Phylogenetics is the study of the evolutionary relationship between species. Inference of phylogeny relies heavily on statistical models that have been extended and refined tremendously over the past years into very complex hierarchical models. Paper I introduces probabilistic graphical models to statistical phylogenetics and elaborates on the potential advantages a unified graphical model representation could have for the community, e.g., by facilitating communication and improving reproducibility of statistical analyses of phylogeny and evolution.

Once the phylogeny is reconstructed it is possible to infer the rates of diversification (speciation and extinction). In this thesis I extend the birth-death process model, so that it can be applied to incompletely sampled phylogenies, that is, phylogenies of only a subsample of the presently living species from one group. Previous work only considered the case when every species had the same probability to be included and here I examine two alternative sampling schemes: diversified taxon sampling and cluster sampling. Paper II introduces these sampling schemes under a constant rate birth-death process and gives the probability density for reconstructed phylogenies. These models are extended in Paper IV to time-dependent diversification rates, again, under different sampling schemes and applied to empirical phylogenies. Paper III focuses on fast and unbiased simulations of reconstructed phylogenies. The efficiency is achieved by deriving the analytical distribution and density function of the speciation times in the reconstructed phylogeny.

Place, publisher, year, edition, pages
Stockholm: Department of Mathematics, Stockholm University, 2013. 26 p.
Keyword
Phylogenetics, Bayesian inference, Graphical Models, Birth-Death Process, Diversification
National Category
Evolutionary Biology Mathematics
Research subject
Mathematical Statistics
Identifiers
urn:nbn:se:su:diva-95361 (URN)978-91-7447-771-9 (ISBN)
Public defence
2013-11-29, sal 14, hus 5, Kräftriket, Roslagsvägen 101, Stockholm, 10:00 (English)
Opponent
Supervisors
Note

At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 1: Manuscript. Paper 4: Accepted.

Available from: 2013-11-07 Created: 2013-10-25 Last updated: 2015-03-10Bibliographically approved

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