Tip rates, phylogenies, and diversification: what are we estimating, and how good are the estimates?

AbstractSpecies-specific diversification rates, or “tip rates”, can be computed quickly from phylogenies and are widely used to study diversification rate variation in relation to geography, ecology, and phenotypes. These tip rates provide a number of theoretical and practical advantages, such as the relaxation of assumptions of rate homogeneity in trait-dependent diversification studies. However, there is substantial confusion in the literature regarding whether these metrics estimate speciation or net diversification rates. Additionally, no study has yet compared the relative performance and accuracy of tip rate metrics across simulated diversification scenarios.We compared the statistical performance of three model-free rate metrics (inverse terminal branch lengths; node density metric; DR statistic) and a model-based approach (BAMM). We applied each method to a large set of simulated phylogenies that had been generated under different diversification processes; scenarios included multi-regime time-constant and diversity-dependent trees, as well as trees where the rate of speciation evolves under a diffusion process. We summarized performance in relation to the type of rate variation, the magnitude of rate heterogeneity and rate regime size. We also compared the ability of the metrics to estimate both speciation and net diversification rates.We show decisively that model-free tip rate metrics provide a better estimate of the rate of speciation than of net diversification. Error in net diversification rate estimates increases as a function of the relative extinction rate. In contrast, error in speciation rate estimates is low and relatively insensitive to extinction. Overall, and in particular when relative extinction was high, BAMM inferred the most accurate tip rates and exhibited lower error than non-model-based approaches. DR was highly correlated with true speciation rates but exhibited high error variance, and was the best metric for very small rate regimes.We found that, of the metrics tested, DR and BAMM are the most useful metrics for studying speciation rate dynamics and trait-dependent diversification. Although BAMM was more accurate than DR overall, the two approaches have complementary strengths. Because tip rate metrics are more reliable estimators of speciation rate, we recommend that empirical studies using these metrics exercise caution when drawing biological interpretations in any situation where the distinction between speciation and net diversification is important.

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ACDC: Analysis of Congruent Diversification Classes

10.1101/2022.01.12.476142 ◽

2022 ◽

Author(s):

Sebastian Hoehna ◽

Bjoern Tore Kopperud ◽

Andrew F Magee

Keyword(s):

Congruence Class ◽

R Package ◽

Rate Function ◽

Diversification Rate ◽

Extinction Rate ◽

Diversification Rates ◽

Common Features ◽

Alternative Hypotheses ◽

Rate Functions ◽

Congruence Classes

Diversification rates inferred from phylogenies are not identifiable. There are infinitely many combinations of speciation and extinction rate functions that have the exact same likelihood score for a given phylogeny, building a congruence class. The specific shape and characteristics of such congruence classes have not yet been studied. Whether speciation and extinction rate functions within a congruence class share common features is also not known. Instead of striving to make the diversification rates identifiable, we can embrace their inherent non-identifiable nature. We use two different approaches to explore a congruence class: (i) testing of specific alternative hypotheses, and (ii) randomly sampling alternative rate function within the congruence class. Our methods are implemented in the open-source R package ACDC (https://github.com/afmagee/ACDC). ACDC provides a flexible approach to explore the congruence class and provides summaries of rate functions within a congruence class. The summaries can highlight common trends, i.e. increasing, flat or decreasing rates. Although there are infinitely many equally likely diversification rate functions, these can share common features. ACDC can be used to assess if diversification rate patterns are robust despite non-identifiability. In our example, we clearly identify three phases of diversification rate changes that are common among all models in the congruence class. Thus, congruence classes are not necessarily a problem for studying historical patterns of biodiversity from phylogenies.

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A Bayesian Approach for Detecting Mass-Extinction Events When Rates of Lineage Diversification Vary

10.1101/020149 ◽

2015 ◽

Cited By ~ 4

Author(s):

Michael R. May ◽

Sebastian Höhna ◽

Brian R. Moore

Keyword(s):

Mass Extinction ◽

Process Model ◽

Sequence Data ◽

Diversification Rate ◽

Rate Variation ◽

Specific Rate ◽

Extinction Rate ◽

Molecular Sequence Data ◽

Extinction Events ◽

Mass Extinction Events

The paleontological record chronicles numerous episodes of mass extinction that severely culled the Tree of Life. Biologists have long sought to assess the extent to which these events may have impacted particular groups. We present a novel method for detecting mass-extinction events from phylogenies estimated from molecular sequence data. We develop our approach in a Bayesian statistical framework, which enables us to harness prior information on the frequency and magnitude of mass-extinction events. The approach is based on an episodic stochastic-branching process model in which rates of speciation and extinction are constant between rate-shift events. We model three types of events: (1) instantaneous tree-wide shifts in speciation rate; (2) instantaneous tree-wide shifts in extinction rate, and; (3) instantaneous tree-wide mass-extinction events. Each of the events is described by a separate compound Poisson process (CPP) model, where the waiting times between each event are exponentially distributed with event-specific rate parameters. The magnitude of each event is drawn from an event-type specific prior distribution. Parameters of the model are then estimated using a reversible-jump Markov chain Monte Carlo (rjMCMC) algorithm. We demonstrate via simulation that this method has substantial power to detect the number of mass-extinction events, provides unbiased estimates of the timing of mass-extinction events, while exhibiting an appropriate (i.e., below 5%) false discovery rate even in the case of background diversification rate variation. Finally, we provide an empirical application of this approach to conifers, which reveals that this group has experienced two major episodes of mass extinction. This new approach?the CPP on Mass Extinction Times (CoMET) model?provides an effective tool for identifying mass-extinction events from molecular phylogenies, even when the history of those groups includes more prosaic temporal variation in diversification rate.

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Ecological causes of uneven speciation and species richness in mammals

10.1101/504803 ◽

2019 ◽

Cited By ~ 12

Author(s):

Nathan S. Upham ◽

Jacob A. Esselstyn ◽

Walter Jetz

Keyword(s):

Species Richness ◽

Species Turnover ◽

Rate Variation ◽

Ecological Traits ◽

Ecological Opportunity ◽

Diversification Rates ◽

Speciation Rate ◽

Diversity Gradient ◽

Speciation Rates

ABSTRACTBiodiversity is distributed unevenly from the poles to the equator, and among branches of the tree of life, yet how those enigmatic patterns are related is unclear. We investigated global speciation-rate variation across crown Mammalia using a novel time-scaled phylogeny (N=5,911 species, ~70% with DNA), finding that trait- and latitude-associated speciation has caused uneven species richness among groups. We identify 24 branch-specific shifts in net diversification rates linked to ecological traits. Using time-slices to define clades, we show that speciation rates are a stronger predictor of clade richness than age. Speciation is slower in tropical than extra-tropical lineages, but only at the level of clades not species tips, consistent with fossil evidence that the latitudinal diversity gradient may be a relatively young phenomenon in mammals. In contrast, species tip rates are fastest in mammals that are low dispersal or diurnal, consistent with models of ephemeral speciation and ecological opportunity, respectively. These findings juxtapose nested levels of diversification, suggesting a central role of species turnover gradients in generating uneven patterns of modern biodiversity.

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The Evolution of Nest Site Specialization and its Macroevolutionary Consequences in Passerine Birds

10.1101/2021.08.24.457563 ◽

2021 ◽

Author(s):

Rosana Zenil-Ferguson ◽

Jay P McEntee ◽

John Gordon Burleigh ◽

Renee A Duckworth

Keyword(s):

Nest Site ◽

Comparative Methods ◽

Diversification Rate ◽

Extinction Rate ◽

Passerine Birds ◽

Evolutionary Transitions ◽

Background Rate ◽

Diversification Rates ◽

Resource Specialization ◽

Dead End

A long-standing hypothesis in evolutionary biology is that the evolution of resource specialization can lead to an evolutionary dead end, where specialists have low diversification rates and limited ability to evolve into generalists. However, in recent years, advances in comparative methods investigating trait-based differences associated with diversification have enabled more robust tests of this idea and have found mixed support. Here we test the evolutionary dead end hypothesis by estimating net diversification rate differences associated with nest site specialization among 3,224 species of passerine birds. In particular, we test whether the adoption of hole-nesting, a nest site specialization that decreases predation, results in reduced diversification rates relative to nesting outside of holes. Further, we examine whether evolutionary transitions to the specialist hole-nesting state have been more frequent than transitions out of hole-nesting. Using diversification models that accounted for background rate heterogeneity and different extinction rate scenarios, we found that hole-nesting specialization was not associated with diversification rate differences. Furthermore, contrary to the assumption that specialists rarely evolve into generalists, we found that transitions out of hole-nesting occur more frequently than transitions into hole-nesting. These results suggest that interspecific competition may limit adoption of hole-nesting, but that such competition does not result in limited diversification of hole-nesters. In conjunction with other recent studies using robust comparative methods, our results add to growing evidence that evolutionary dead ends are not a typical outcome of resource specialization.

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Representation, abstraction, and simple-minded sophisticates

Behavioral and Brain Sciences ◽

10.1017/s0140525x19002942 ◽

2020 ◽

Vol 43 ◽

Author(s):

Peter Dayan

Keyword(s):

Decision Theory ◽

Predictive Coding ◽

Bayesian Decision Theory ◽

Bayesian Decision ◽

Model Based ◽

Model Free

Abstract Bayesian decision theory provides a simple formal elucidation of some of the ways that representation and representational abstraction are involved with, and exploit, both prediction and its rather distant cousin, predictive coding. Both model-free and model-based methods are involved.

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Shaping Model-Free Reinforcement-Learning with Model-Based Pseudorewards

10.32470/ccn.2018.1191-0 ◽

2018 ◽

Author(s):

Paul Krueger ◽

Thomas Griffiths

Keyword(s):

Reinforcement Learning ◽

Model Based ◽

Model Free

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Model-Based and Model-Free Social Cognition

10.31234/osf.io/ue6j2 ◽

2019 ◽

Author(s):

Leor M Hackel ◽

Jeffrey Jordan Berg ◽

Björn Lindström ◽

David Amodio

Keyword(s):

Reinforcement Learning ◽

Social Cognition ◽

Learning Strategies ◽

Memory Systems ◽

Learning Task ◽

Financial Advisors ◽

Model Based ◽

Model Free ◽

Systems Model ◽

Task Assessment

Do habits play a role in our social impressions? To investigate the contribution of habits to the formation of social attitudes, we examined the roles of model-free and model-based reinforcement learning in social interactions—computations linked in past work to habit and planning, respectively. Participants in this study learned about novel individuals in a sequential reinforcement learning paradigm, choosing financial advisors who led them to high- or low-paying stocks. Results indicated that participants relied on both model-based and model-free learning, such that each independently predicted choice during the learning task and self-reported liking in a post-task assessment. Specifically, participants liked advisors who could provide large future rewards as well as advisors who had provided them with large rewards in the past. Moreover, participants varied in their use of model-based and model-free learning strategies, and this individual difference influenced the way in which learning related to self-reported attitudes: among participants who relied more on model-free learning, model-free social learning related more to post-task attitudes. We discuss implications for attitudes, trait impressions, and social behavior, as well as the role of habits in a memory systems model of social cognition.

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