scholarly journals A Bayesian Approach for Estimating Branch-Specific Speciation and Extinction Rates

2019 ◽  
Author(s):  
Sebastian Höhna ◽  
William A. Freyman ◽  
Zachary Nolen ◽  
John P. Huelsenbeck ◽  
Michael R. May ◽  
...  
Keyword(s):  
Prior Distribution ◽  
Phylogenetic Trees ◽  
Data Augmentation ◽  
Simulated Data ◽  
Monte Carlo Sampling ◽  
Fixed Number ◽  
Diversification Rate ◽  
Diversification Rates ◽  
Extinction Rates ◽  
Birth Death

AbstractSpecies richness varies considerably among the tree of life which can only be explained by heterogeneous rates of diversification (speciation and extinction). Previous approaches use phylogenetic trees to estimate branch-specific diversification rates. However, all previous approaches disregard diversification-rate shifts on extinct lineages although 99% of species that ever existed are now extinct. Here we describe a lineage-specific birth-death-shift process where lineages, both extant and extinct, may have heterogeneous rates of diversification. To facilitate probability computation we discretize the base distribution on speciation and extinction rates into k rate categories. The fixed number of rate categories allows us to extend the theory of state-dependent speciation and extinction models (e.g., BiSSE and MuSSE) to compute the probability of an observed phylogeny given the set of speciation and extinction rates. To estimate branch-specific diversification rates, we develop two independent and theoretically equivalent approaches: numerical integration with stochastic character mapping and data-augmentation with reversible-jump Markov chain Monte Carlo sampling. We validate the implementation of the two approaches in RevBayes using simulated data and an empirical example study of primates. In the empirical example, we show that estimates of the number of diversification-rate shifts are, unsurprisingly, very sensitive to the choice of prior distribution. Instead, branch-specific diversification rate estimates are less sensitive to the assumed prior distribution on the number of diversification-rate shifts and consistently infer an increased rate of diversification for Old World Monkeys. Additionally, we observe that as few as 10 diversification-rate categories are sufficient to approximate a continuous base distribution on diversification rates. In conclusion, our implementation of the lineage-specific birth-death-shift model in RevBayes provides biologists with a method to estimate branch-specific diversification rates under a mathematically consistent model.

scholarly journals Diversification rates and the latitudinal gradient of diversity in mammals

2012 ◽  
Vol 279 (1745) ◽  
pp. 4148-4155 ◽  
Author(s):  
Víctor Soria-Carrasco ◽  
Jose Castresana
Keyword(s):  
Species Richness ◽  
Species Distribution ◽  
Phylogenetic Trees ◽  
Latitudinal Gradient ◽  
Diversification Rate ◽  
Independent Contrasts ◽  
Diversification Rates ◽  
Extinction Rates ◽  
Phylogenetically Independent Contrasts ◽  
Distribution Ranges

The latitudinal gradient of species richness has frequently been attributed to higher diversification rates of tropical groups. In order to test this hypothesis for mammals, we used a set of 232 genera taken from a mammalian supertree and, additionally, we reconstructed dated Bayesian phylogenetic trees of 100 genera. For each genus, diversification rate was estimated taking incomplete species sampling into account and latitude was assigned considering the heterogeneity in species distribution ranges. For both datasets, we found that the average diversification rate was similar among all latitudinal bands. Furthermore, when we used phylogenetically independent contrasts, we did not find any significant correlation between latitude and diversification parameters, including different estimates of speciation and extinction rates. Thus, other factors, such as the dynamics of dispersal through time, may be required to explain the latitudinal gradient of diversity in mammals.

scholarly journals A Multitype Birth–Death Model for Bayesian Inference of Lineage-Specific Birth and Death Rates

2020 ◽  
Vol 69 (5) ◽  
pp. 973-986 ◽  
Author(s):  
Joëlle Barido-Sottani ◽  
Timothy G Vaughan ◽  
Tanja Stadler
Keyword(s):  
Bayesian Inference ◽  
Simulated Data ◽  
Pathogen Transmission ◽  
Type Model ◽  
Model Parameters ◽  
Data Sets ◽  
Death Rates ◽  
Joint Inference ◽  
Extinction Rates ◽  
Birth Death

Abstract Heterogeneous populations can lead to important differences in birth and death rates across a phylogeny. Taking this heterogeneity into account is necessary to obtain accurate estimates of the underlying population dynamics. We present a new multitype birth–death model (MTBD) that can estimate lineage-specific birth and death rates. This corresponds to estimating lineage-dependent speciation and extinction rates for species phylogenies, and lineage-dependent transmission and recovery rates for pathogen transmission trees. In contrast with previous models, we do not presume to know the trait driving the rate differences, nor do we prohibit the same rates from appearing in different parts of the phylogeny. Using simulated data sets, we show that the MTBD model can reliably infer the presence of multiple evolutionary regimes, their positions in the tree, and the birth and death rates associated with each. We also present a reanalysis of two empirical data sets and compare the results obtained by MTBD and by the existing software BAMM. We compare two implementations of the model, one exact and one approximate (assuming that no rate changes occur in the extinct parts of the tree), and show that the approximation only slightly affects results. The MTBD model is implemented as a package in the Bayesian inference software BEAST 2 and allows joint inference of the phylogeny and the model parameters.[Birth–death; lineage specific rates, multi-type model.]

scholarly journals Estimating Epidemic Incidence and Prevalence from Genomic Data

2019 ◽  
Vol 36 (8) ◽  
pp. 1804-1816 ◽  
Author(s):  
Timothy G Vaughan ◽  
Gabriel E Leventhal ◽  
David A Rasmussen ◽  
Alexei J Drummond ◽  
David Welch ◽  
...  
Keyword(s):  
Sierra Leone ◽  
Particle Filtering ◽  
Phylogenetic Trees ◽  
Stochastic Dynamics ◽  
Large Population ◽  
Simulated Data ◽  
Model Parameters ◽  
Epidemiological Models ◽  
Case Count ◽  
Birth Death

Abstract Modern phylodynamic methods interpret an inferred phylogenetic tree as a partial transmission chain providing information about the dynamic process of transmission and removal (where removal may be due to recovery, death, or behavior change). Birth–death and coalescent processes have been introduced to model the stochastic dynamics of epidemic spread under common epidemiological models such as the SIS and SIR models and are successfully used to infer phylogenetic trees together with transmission (birth) and removal (death) rates. These methods either integrate analytically over past incidence and prevalence to infer rate parameters, and thus cannot explicitly infer past incidence or prevalence, or allow such inference only in the coalescent limit of large population size. Here, we introduce a particle filtering framework to explicitly infer prevalence and incidence trajectories along with phylogenies and epidemiological model parameters from genomic sequences and case count data in a manner consistent with the underlying birth–death model. After demonstrating the accuracy of this method on simulated data, we use it to assess the prevalence through time of the early 2014 Ebola outbreak in Sierra Leone.

scholarly journals Model-Based Geostatistics from a Bayesian Perspective: Investigating Area-to-Point Kriging with Small Data Sets

2019 ◽  
Vol 52 (3) ◽  
pp. 397-423
Author(s):  
Luc Steinbuch ◽  
Thomas G. Orton ◽  
Dick J. Brus
Keyword(s):  
Prior Distribution ◽  
Crop Yields ◽  
Simulated Data ◽  
Monte Carlo Sampling ◽  
Model Parameters ◽  
Small Data ◽  
Data Sets ◽  
Data Set ◽  
Minimal Impact ◽  
The Impact

AbstractArea-to-point kriging (ATPK) is a geostatistical method for creating high-resolution raster maps using data of the variable of interest with a much lower resolution. The data set of areal means is often considerably smaller ($$<\,50 $$<50 observations) than data sets conventionally dealt with in geostatistical analyses. In contemporary ATPK methods, uncertainty in the variogram parameters is not accounted for in the prediction; this issue can be overcome by applying ATPK in a Bayesian framework. Commonly in Bayesian statistics, posterior distributions of model parameters and posterior predictive distributions are approximated by Markov chain Monte Carlo sampling from the posterior, which can be computationally expensive. Therefore, a partly analytical solution is implemented in this paper, in order to (i) explore the impact of the prior distribution on predictions and prediction variances, (ii) investigate whether certain aspects of uncertainty can be disregarded, simplifying the necessary computations, and (iii) test the impact of various model misspecifications. Several approaches using simulated data, aggregated real-world point data, and a case study on aggregated crop yields in Burkina Faso are compared. The prior distribution is found to have minimal impact on the disaggregated predictions. In most cases with known short-range behaviour, an approach that disregards uncertainty in the variogram distance parameter gives a reasonable assessment of prediction uncertainty. However, some severe effects of model misspecification in terms of overly conservative or optimistic prediction uncertainties are found, highlighting the importance of model choice or integration into ATPK.

scholarly journals Mistreating birth-death models as priors in phylogenetic analysis compromises our ability to compare models

2021 ◽  
Author(s):  
Michael R May ◽  
Carl Rothfels
Keyword(s):  
Prior Distribution ◽  
Phylogenetic Trees ◽  
Model Comparison ◽  
Marginal Likelihood ◽  
Death Process ◽  
Wide Range ◽  
Tree Models ◽  
Extinction Events ◽  
Lineage Diversification ◽  
Birth Death

Time-calibrated phylogenetic trees are fundamental to a wide range of evolutionary studies. Typically, these trees are inferred in a Bayesian framework, with the phylogeny itself treated as a parameter with a prior distribution (a "tree prior"). This prior distribution is often a variant of the stochastic birth-death process, which models speciation events, extinction events, and sampling events (of extinct and/or extant lineages). However, the samples produced by this process are observations, so their probability should be viewed as a likelihood rather than a prior probability. We show that treating the samples as part of the prior results in incorrect marginal likelihood estimates and can result in model-comparison approaches disfavoring the best model within a set of candidate models. The ability to correctly compare the fit of competing tree models is critical to accurate phylogenetic estimates, especially of divergence times, and also to studying the processes that govern lineage diversification. We outline potential remedies, and provide guidance for researchers interested in comparing the fit of competing tree models.

scholarly journals Pulled Diversification Rates, Lineage-Through-Time Plots and Modern Macroevolutionary Modelling

2021 ◽  
Author(s):  
Andrew J. Helmstetter ◽  
Sylvain Glemin ◽  
Jos Käfer ◽  
Rosana Zenil-Ferguson ◽  
Hervé Sauquet ◽  
...  
Keyword(s):  
Infinite Number ◽  
Scientific Community ◽  
Phylogenetic Trees ◽  
Data Availability ◽  
Time Dependent ◽  
Evolutionary Processes ◽  
Diversification Rates ◽  
Extinction Rates ◽  
Extant Species ◽  
Technical Considerations

AbstractEstimating time-dependent rates of speciation and extinction from dated phylogenetic trees of extant species (timetrees), and determining how and why they vary is key to understanding how ecological and evolutionary processes shape biodiversity. Due to an increasing availability of phylogenies, a growing number of process-based methods relying on the birth-death model have been developed in the last decade to address a variety of questions in macroevolution. However, this methodological progress has regularly been criticised such that one may wonder how reliable the estimations of speciation and extinction rates are. In particular, using lineage-through-time (LTT) plots, a recent study (Louca and Pennell, 2020) has shown that there are an infinite number of equally likely diversification scenarios that can generate any timetree. This has led to questioning whether or not diversification rates should be estimated at all. Here we summarize, clarify, and highlight technical considerations on recent findings regarding the capacity of models and inferences to disentangle diversification histories. Using simulations we demonstrate the characteristics of pulled diversification rates and their utility. We recognize the recent findings are a step forward in understanding the behavior of macroevolutionary modelling, but they in no way suggest we should abandon diversification modelling altogether. On the contrary, the study of macroevolution using phylogenies has never been more exciting and promising than today. We still face important limitations in regard to data availability and methodological shortcomings, but by acknowledging them we can better target our joint efforts as a scientific community.

scholarly journals Fossils Do Not Substantially Improve, and May Even Harm, Estimates of Diversification Rate Heterogeneity

2021 ◽  
Author(s):  
Jeremy M Beaulieu ◽  
Brian C O'Meara
Keyword(s):  
Diversification Rate ◽  
Turnover Rates ◽  
Rate Heterogeneity ◽  
Diversification Rates ◽  
Stratigraphic Ranges ◽  
Fossil Data ◽  
The Impact ◽  
Prevailing View ◽  
Birth Death

There is a prevailing view that the inclusion of fossil data could remedy identifiability issues related to models of diversification, by drastically reducing the number of congruent models. The fossilized birth-death (FBD) model is an appealing way of directly incorporating fossil information when estimating diversification rates. Here we explore the benefits of including fossils by implementing and then testing two-types of FBD models in more complex likelihood-based models that assume multiple rate classes across the tree. We also assess the impact of severely undersampling, and even not including fossils that represent samples of lineages that also had sampled descendants (i.e., k-type fossils), as well as converting a fossil set to represent stratigraphic ranges. Under various simulation scenarios, including a scenario that exists far outside the set of models we evaluated, including fossils rarely outperforms analyses that exclude them altogether. At best, the inclusion of fossils improves precision but does not influence bias. We also found that severely undercounting the number of k-type fossils produces highly inflated rates of turnover and extinction fraction. Similarly, we found that converting the fossil set to stratigraphic ranges results in turnover rates and extinction fraction estimates that are generally underestimated. While fossils remain essential for understanding diversification through time, in the specific case of understanding diversification given an existing, largely modern tree, they are not especially beneficial.

scholarly journals Detecting hidden diversification shifts in models of trait-dependent speciation and extinction

2015 ◽  
Author(s):  
Jeremy M Beaulieu ◽  
Brian C O'Meara
Keyword(s):  
Empirical Data ◽  
Diversification Rate ◽  
Transition Rates ◽  
Diversification Rates ◽  
Extinction Rates ◽  
State Dependent ◽  
Speciation Rates ◽  
Nuanced Understanding ◽  
Hidden States ◽  
Major Criticism

The distribution of diversity can vary considerably from clade to clade. Attempts to understand these patterns often employ state-dependent speciation and extinction models to determine whether the evolution of a particular novel trait has increased speciation rates and/or decreased their extinction rates. It is still unclear, however, whether these models are uncovering important drivers of diversification, or whether they are simply pointing to more complex patterns involving many unmeasured and co-distributed factors. Here we describe an extension to the popular state-dependent speciation and extinction models that specifically accounts for the presence of unmeasured factors that could impact diversification rates estimated for the states of any observed trait, addressing at least one major criticism of BiSSE methods. Specifically, our model, which we refer to as HiSSE (Hidden-State Speciation and Extinction), assumes that related to each observed state in the model are "hidden" states that exhibit potentially distinct diversification dynamics and transition rates than the observed states in isolation. We also demonstrate how our model can be used as character-independent diversification (CID) models that allow for a complex diversification process that is independent of the evolution of a character. Under rigorous simulation tests and when applied to empirical data, we find that HiSSE performs reasonably well, and can at least detect net diversification rate differences between observed and hidden states and detect when diversification rate differences do not correlate with the observed states. We discuss the remaining issues with state-dependent speciation and extinction models in general, and the important ways in which HiSSE provides a more nuanced understanding of trait-dependent diversification.

scholarly journals Pulled Diversification Rates, Lineages-Through-Time Plots and Modern Macroevolutionary Modelling

2021 ◽  
Author(s):  
Andrew J Helmstetter ◽  
Sylvain Glemin ◽  
Jos Käfer ◽  
Rosana Zenil-Ferguson ◽  
Herv Sauquet ◽  
...  
Keyword(s):  
Infinite Number ◽  
Scientific Community ◽  
Phylogenetic Trees ◽  
Data Availability ◽  
Time Dependent ◽  
Evolutionary Processes ◽  
Diversification Rates ◽  
Extinction Rates ◽  
Extant Species ◽  
Technical Considerations

Abstract Estimating time-dependent rates of speciation and extinction from dated phylogenetic trees of extant species (timetrees), and determining how and why they vary, is key to understanding how ecological and evolutionary processes shape biodiversity. Due to an increasing availability of phylogenetic trees, a growing number of process-based methods relying on the birth-death model have been developed in the last decade to address a variety of questions in macroevolution. However, this methodological progress has regularly been criticised such that one may wonder how reliable the estimations of speciation and extinction rates are. In particular, using lineages-through-time (LTT) plots, a recent study (Louca and Pennell, 2020) has shown that there are an infinite number of equally likely diversification scenarios that can generate any timetree. This has led to questioning whether or not diversification rates should be estimated at all. Here we summarize, clarify, and highlight technical considerations on recent findings regarding the capacity of models to disentangle diversification histories. Using simulations we illustrate the characteristics of newly-proposed “pulled rates” and their utility. We recognize that the recent findings are a step forward in understanding the behavior of macroevolutionary modelling, but they in no way suggest we should abandon diversification modelling altogether. On the contrary, the study of macroevolution using phylogenetic trees has never been more exciting and promising than today. We still face important limitations in regard to data availability and methods, but by acknowledging them we can better target our joint efforts as a scientific community.

scholarly journals Estimating epidemic incidence and prevalence from genomic data

2017 ◽  
Author(s):  
Timothy G. Vaughan ◽  
Gabriel E. Leventhal ◽  
David A. Rasmussen ◽  
Alexei J. Drummond ◽  
David Welch ◽  
...  
Keyword(s):  
Sierra Leone ◽  
Particle Filtering ◽  
Phylogenetic Trees ◽  
Stochastic Dynamics ◽  
Large Population ◽  
Simulated Data ◽  
Model Parameters ◽  
Epidemiological Models ◽  
Case Count ◽  
Birth Death

AbstractModern phylodynamic methods interpret an inferred phylogenetic tree as a partial transmission chain providing information about the dynamic process of transmission and removal (where removal may be due to recovery, death or behaviour change). Birth-death and coalescent processes have been introduced to model the stochastic dynamics of epidemic spread under common epidemiological models such as the SIS and SIR models, and are successfully used to infer phylogenetic trees together with transmission (birth) and removal (death) rates. These methods either integrate analytically over past incidence and prevalence to infer rate parameters, and thus cannot explicitly infer past incidence or prevalence, or allow such inference only in the coalescent limit of large population size. Here we introduce a particle filtering framework to explicitly infer prevalence and incidence trajectories along with phylogenies and epidemiological model parameters from genomic sequences and case count data in a manner consistent with the underlying birth-death model. After demonstrating the accuracy of this method on simulated data, we use it to assess the prevalence through time of the early 2014 Ebola outbreak in Sierra Leone.

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