scholarly journals Hidden-state-only speciation and extinction models provide accurate tip estimates of diversification rates

2021 ◽  
Author(s):  
Thais Vasconcelos ◽  
Brian C O'Meara ◽  
Jeremy M. Beaulieu
Keyword(s):  
Model Space ◽  
Comparative Methods ◽  
Character State ◽  
Large Set ◽  
Turnover Rates ◽  
Extinction Rates ◽  
State Dependent ◽  
Related Diversification ◽  
Testing Potential ◽  
Hidden States

1. State-dependent speciation and extinction (SSE) models provide a framework for testing potential correlations between the evolution of an observed trait and speciation and extinction rates. Recent expansions of these models allow for the inclusion of "hidden states" that, among other things, allow for rate heterogeneity often observed among lineages sharing a particular character state. However, in reality, multiple circumstances and interacting traits related to a focal character play a role in changing diversification dynamics of a lineage over time, restricting the use of available SSE models that require trait information to be assigned at the tips. 2. Here we introduce MiSSE, an SSE approach that infers diversification rate differences from hidden states only. It can be used similarly to other trait-free methods to estimate varying speciation, extinction, but also different functions of these parameters such as net-diversification, turnover rates, and extinction fraction. Given the size of the model space, we also describe an algorithm designed for efficiently searching through a reasonably large set of models without having to be exhaustive. 3. We compare the accuracy of rates inferred at the tips of the tree by MiSSE against popular character-free methods and demonstrate that the error associated with tip estimates is generally low. Due to certain characteristics of the SSE models, this method avoids some of the recent concerns with parameter identifiability in diversification analyses and can be used alongside regular phylogenetic comparative methods in trait-related diversification hypotheses. 4. Finally, we apply MiSSE, with a renewed focus on classic comparative methods, to understand processes happening near the present, rather than deep in the past, to examine how variation in plant height has impacted turnover rates in eucalypts, a species-rich lineage of flowering plants.

scholarly journals Diatoms diversify and turn over faster in freshwater than marine environments

2018 ◽  
Author(s):  
Teofil Nakov ◽  
Jeremy Michael Beaulieu ◽  
Andrew James Alverson
Keyword(s):  
Turnover Rate ◽  
Turnover Rates ◽  
High Turnover ◽  
Diversification Rates ◽  
Extinction Rates ◽  
State Dependent ◽  
Freshwater Diatoms ◽  
Marine Realm ◽  
Turn Over ◽  
Freshwater Environments

AbstractMany clades that span the marine-freshwater boundary are disproportionately more diverse in the younger, shorter-lived, and scarcer freshwater environments than they are in the marine realm. This disparity is thought to be related to differences in diversification rates between marine and freshwater lineages. However, marine and freshwaters are not ecologically homogeneous, so the study of diversification across the salinity divide should also account for other potentially interacting variables. In diatoms, freshwater and substrate-associated (benthic) lineages are several-fold more diverse than their marine and suspended (planktonic) counterparts. These imbalances provide an excellent system to understand whether these variables interact with diversification. Using multistate hidden-state speciation and extinction models we found that freshwater lineages diversify faster than marine lineages regardless of whether they inhabit the plankton or the benthos. Freshwater lineages also had higher turnover rates (speciation + extinction), suggesting that habitat transitions impact speciation and extinction rates jointly. The plankton-benthos contrast was also consistent with state-dependent diversification, but with modest differences in diversification and turnover rates. Asymmetric, and bidirectional transitions rejected hypotheses about the plankton and freshwaters as absorbing, inescapable habitats. Our results further suggest that the high turnover rate of freshwater diatoms is related to high turnover of freshwater systems themselves.

scholarly journals Stochastic character mapping of state-dependent diversification reveals the tempo of evolutionary decline in self-compatible Onagraceae lineages

2017 ◽  
Author(s):  
William A. Freyman ◽  
Sebastian Höhna
Keyword(s):  
Time Lag ◽  
State Transitions ◽  
Character State ◽  
Self Incompatibility ◽  
Evolutionary Transitions ◽  
Diversification Rates ◽  
Extinction Rates ◽  
Loss Of Self ◽  
State Dependent ◽  
Character Mapping

AbstractA major goal of evolutionary biology is to identify key evolutionary transitions that correspond with shifts in speciation and extinction rates. Stochastic character mapping has become the primary method used to infer the timing, nature, and number of character state transitions along the branches of a phylogeny. The method is widely employed for standard substitution models of character evolution. However, current approaches cannot be used for models that specifically test the association of character state transitions with shifts in diversification rates such as state-dependent speciation and extinction (SSE) models. Here we introduce a new stochastic character mapping algorithm that overcomes these limitations, and apply it to study mating system evolution over a time-calibrated phylogeny of the plant family Onagraceae. Utilizing a hidden state SSE model we tested the association of the loss of self-incompatibility with shifts in diversification rates. We found that self-compatible lineages have higher extinction rates and lower net-diversification rates compared to self-incompatible lineages. Furthermore, these results provide empirical evidence for the “senescing” diversification rates predicted in highly selfing lineages: our mapped character histories show that the loss of self-incompatibility is followed by a short-term spike in speciation rates, which declines after a time lag of several million years resulting in negative net-diversification. Lineages that have long been self-compatible, such as Fuchsia and Clarkia, are in a previously unrecognized and ongoing evolutionary decline. Our results demonstrate that stochastic character mapping of SSE models is a powerful tool for examining the timing and nature of both character state transitions and shifts in diversification rates over the phylogeny.

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 Changes in antennal gene expression underlying sensory system maturation in Rhodnius prolixus

2021 ◽  
Author(s):  
Jose Manuel Latorre Estivalis ◽  
Ewald Grosse-Wilde ◽  
Gabriel R Fernandes ◽  
Bill S Hansson ◽  
Marcelo Gustavo Lorenzo
Keyword(s):  
Molecular Level ◽  
Expression Profiles ◽  
Sensory System ◽  
Transcript Abundance ◽  
Blood Feeding ◽  
Rhodnius Prolixus ◽  
Large Set ◽  
Illumina Platform ◽  
State Dependent ◽  
Host Cues

Background Triatomine bugs are the blood feeding insect vectors transmitting Chagas disease to humans, a neglected tropical disease that affects over 8 million people, mainly in Latin America. The behavioral responses to host cues and bug signals in Rhodnius prolixus are state dependent, i.e., they vary as a function of post-ecdysis age. At the molecular level, these changes in behavior are probably due to a modulation of peripheral and central processes. In the present study, we report a significant modulation of the expression of a large set of sensory-related genes. Results were generated by means of antennal transcriptomes of 5th instar larvae along the first week (days 0, 2, 4, 6 and 8) after ecdysis sequenced using the Illumina platform. Results Age induced significant changes in transcript abundance were established in more than 6,120 genes (54,7 % of 11,186 genes expressed) in the R. prolixus antenna. This was especially true between the first two days after ecdysis when more than 2,500 genes had their expression significantly altered. In contrast, expression profiles were almost identical between day 6 and 8, with only a few genes showing significant modulation of their expression. A total of 86 sensory receptors, odorant carriers and odorant degrading enzymes were significantly modulated across age points and clustered into three distinct expression profiles. Conclusions The set of sensory genes whose expression increased with age (profile 3) may include candidates underlying the increased responsiveness to host cues shown by R. prolixus during the first days after molting. For the first time, we describe the maturation process undergone at the molecular level by the peripheral sensory system is described in an hemimetabolous insect.

scholarly journals Integration of Anatomy Ontologies and Evo-Devo Using Structured Markov Models Suggests a New Framework for Modeling Discrete Phenotypic Traits

2019 ◽  
Vol 68 (5) ◽  
pp. 698-716 ◽  
Author(s):  
Sergei Tarasov
Keyword(s):  
Regulatory Networks ◽  
Markov Models ◽  
Phylogenetic Inference ◽  
Phenotypic Traits ◽  
Character State ◽  
Body Parts ◽  
Ancestral Character State ◽  
State Models ◽  
Hidden States ◽  
New Framework

Abstract Modeling discrete phenotypic traits for either ancestral character state reconstruction or morphology-based phylogenetic inference suffers from ambiguities of character coding, homology assessment, dependencies, and selection of adequate models. These drawbacks occur because trait evolution is driven by two key processes—hierarchical and hidden—which are not accommodated simultaneously by the available phylogenetic methods. The hierarchical process refers to the dependencies between anatomical body parts, while the hidden process refers to the evolution of gene regulatory networks (GRNs) underlying trait development. Herein, I demonstrate that these processes can be efficiently modeled using structured Markov models (SMM) equipped with hidden states, which resolves the majority of the problems associated with discrete traits. Integration of SMM with anatomy ontologies can adequately incorporate the hierarchical dependencies, while the use of the hidden states accommodates hidden evolution of GRNs and substitution rate heterogeneity. I assess the new models using simulations and theoretical synthesis. The new approach solves the long-standing “tail color problem,” in which the trait is scored for species with tails of different colors or no tails. It also presents a previously unknown issue called the “two-scientist paradox,” in which the nature of coding the trait and the hidden processes driving the trait’s evolution are confounded; failing to account for the hidden process may result in a bias, which can be avoided by using hidden state models. All this provides a clear guideline for coding traits into characters. This article gives practical examples of using the new framework for phylogenetic inference and comparative analysis.

scholarly journals Introducing a Bayesian model of selective attention based on active inference

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
M. Berk Mirza ◽  
Rick A. Adams ◽  
Karl Friston ◽  
Thomas Parr
Keyword(s):  
Selective Attention ◽  
Formal Model ◽  
Information Gain ◽  
Active Inference ◽  
Context Sensitive ◽  
State Dependent ◽  
Expected Information Gain ◽  
Context Specific ◽  
Hidden States ◽  
Task Irrelevant

Abstract Information gathering comprises actions whose (sensory) consequences resolve uncertainty (i.e., are salient). In other words, actions that solicit salient information cause the greatest shift in beliefs (i.e., information gain) about the causes of our sensations. However, not all information is relevant to the task at hand: this is especially the case in complex, naturalistic scenes. This paper introduces a formal model of selective attention based on active inference and contextual epistemic foraging. We consider a visual search task with a special emphasis on goal-directed and task-relevant exploration. In this scheme, attention modulates the expected fidelity (precision) of the mapping between observations and hidden states in a state-dependent or context-sensitive manner. This ensures task-irrelevant observations have little expected information gain, and so the agent – driven to reduce expected surprise (i.e., uncertainty) – does not actively seek them out. Instead, it selectively samples task-relevant observations, which inform (task-relevant) hidden states. We further show, through simulations, that the atypical exploratory behaviours in conditions such as autism and anxiety may be due to a failure to appropriately modulate sensory precision in a context-specific way.

Accurate and precise estimates of origination and extinction rates

Paleobiology ◽  
10.1666/13036 ◽  
2014 ◽  
Vol 40 (3) ◽  
pp. 374-397 ◽  
Author(s):  
John Alroy
Keyword(s):  
Species Level ◽  
Marine Animal ◽  
Moving Window ◽  
Turnover Rates ◽  
Extinction Rates ◽  
Level Data ◽  
Animal Data ◽  
Apparent Reason ◽  
Log Ratio ◽  
Very High

Paleobiologists have used many different methods for estimating rates of origination and extinction. Unfortunately, all equations that consider entire age ranges are distorted by the Pull of the Recent, the Signor-Lipps effect, and simple edge effects. Attention has been paid recently to an equation of Foote's that considers counts of taxa either crossing the bottom and top of an interval or crossing one boundary but not the other. This generalized boundary-crosser (BC) method has important advantages but is still potentially subject to the major biases. The only published equation that circumvents all of them is the three-timer (3T) log ratio, which does so by focusing on a four-interval moving window. Although it is highly accurate it is noisy when turnover rates are very high or sampling is very poor. More precise values are yielded by a newly derived equation that uses the same counts. However, it also considers taxa sampled in a window's first and fourth intervals but missing from the third (i.e., gap-fillers). Simulations show that the 3T, gap-filler (GF), and BC equations yield identical values when sampling and turnover are uniform through time. When applied to Phanerozoic-scale marine animal data, 3T and GF agree well but the BC rates are systematically lower. The apparent reason is that (1) long-ranging but infrequently sampled genera are less likely to be split up by taxonomists and (2) the BC equation overweights taxa with long ranges. Thus, BC rates pertain more to rare genera that are likely to represent large clades whereas GF rates pertain more to actual species-level patterns. Given these results, all published turnover rates based either on genus-level data or on age ranges must be reconsidered because they may reflect taxonomic practices more strongly than the species-level dynamics of interest to biologists.

scholarly journals Diversification dynamics of hypermetamorphic blister beetles (Meloidae): Are homoplastic host shifts and phoresy key factors of a rushing forward strategy to escape extinction?

2021 ◽  
Author(s):  
E.K. López-Estrada ◽  
I. Sanmartín ◽  
J.E. Uribe ◽  
S. Abalde ◽  
M. García-París
Keyword(s):  
Life History ◽  
Life Cycle ◽  
Life History Traits ◽  
Complex Life Cycle ◽  
Life Strategies ◽  
Diversification Rates ◽  
Host Shifts ◽  
Extinction Rates ◽  
State Dependent ◽  
History Of

ABSTRACTChanges in life history traits, including reproductive strategies or host shifts, are often considered triggers of speciation, affecting diversification rates. Subsequently, these shifts can have dramatic effects on the evolutionary history of a lineage. In this study, we examine the consequences of changes in life history traits, in particular host-type and phoresy, within the hypermetamorphic clade of blister beetles (Meloidae). This clade exhibits a complex life cycle involving multiple metamorphoses and parasitoidism. Most tribes within the clade are bee-parasitoids, phoretic or non-phoretic, while two tribes feed on grasshopper eggs. Species richness differs greatly between bee and grasshopper specialist clades, and between phoretic and non-phoretic genera. We generated a mitogenomic phylogeny of the hypermetamorphic clade of Meloidae, including 21 newly generated complete mitogenomes. The phylogeny and estimated lineage divergence times were used to explore the association between diversification rates and changes in host specificity and phoresy, using State-Dependent Speciation and Extinction (SSE) models, while accounting for hidden factors and phylogenetic uncertainty within a Bayesian framework. The ancestor of the hypermetamorphic Meloidae was a non-phoretic bee-parasitoid, and independent transitions towards phoretic bee-parasitoidism or grasshopper specialization occurred multiple times. Bee-parasitoid lineages that are non-phoretic have significantly higher relative extinction rates and lower diversification rates than grasshopper specialists or phoretic bee-parasitoids, while no significant differences were found between the latter two strategies. This suggests that these two life strategies contributed independently to the evolutionary success of Nemognathinae and Meloinae, allowing them to escape from the evolutionary constraints imposed by their hypermetamorphic life-cycle, and that the “bee-by-crawling” strategy may be an evolutionary “dead end”. We show how SSE models can be used not only for testing diversification dependence in relation to the focal character but to identify hidden traits contributing to the diversification dynamics. The ability of blister beetles to explore new evolutionary scenarios including the development of homoplastic life strategies, are extraordinary outcomes along the evolution of a single lineage: the hypermetamorphic Meloidae.

scholarly journals Hidden state models improve the adequacy of state-dependent diversification approaches using empirical trees, including biogeographical models

2018 ◽  
Author(s):  
Daniel Caetano ◽  
Brian O'Meara ◽  
Jeremy Beaulieu
Keyword(s):  
Model Averaging ◽  
Partial Solution ◽  
Markov Modeling ◽  
Data Set ◽  
State Dependent ◽  
Heterogeneous Effects ◽  
Hidden Markov Modeling ◽  
State Models ◽  
Hidden States ◽  
Positive Results

The state-dependent speciation and extinction models (SSE) have recently been criticized due to their high rates of "false positive" results and many researchers have advocated avoiding SSE models in favor of other "non-parametric" or "semi-parametric" approaches. The hidden Markov modeling (HMM) approach provides a partial solution to the issues of model adequacy detected with SSE models. The inclusion of "hidden states" can account for rate heterogeneity observed in empirical phylogenies and allows detection of true signals of state-dependent diversification or diversification shifts independent of the trait of interest. However, the adoption of HMM into other classes of SSE models has been hampered by the interpretational challenges of what exactly a "hidden state" represents, which we clarify herein. We show that HMM models in combination with a model-averaging approach naturally account for hidden traits when examining the meaningful impact of a suspected "driver" of diversification. We also extend the HMM to the geographic state-dependent speciation and extinction (GeoSSE) model. We test the efficacy of our "GeoHiSSE" extension with both simulations and an empirical data set. On the whole, we show that hidden states are a general framework that can generally distinguish heterogeneous effects of diversification attributed to a focal character.

Augmenting Trait-Dependent Diversification Estimations with Fossil Evidence: A Case Study Using Osmoregulatory Neurovasculature

2018 ◽  
Vol 91 (3) ◽  
pp. 148-157 ◽  
Author(s):  
Haley D. O’Brien
Keyword(s):  
Brain Cooling ◽  
Selective Brain Cooling ◽  
Evaporative Water ◽  
Large Mammal ◽  
Paleontological Data ◽  
Extinction Rates ◽  
State Dependent ◽  
Key Innovation ◽  
Sister Clade ◽  
Binary Character

When comparative neuromorphological studies are extended into evolutionary contexts, traits of interest are often linked to diversification patterns. Features demonstrably associated with increases in diversification rates and the infiltration or occupation of novel niche spaces are often termed “key innovations.” Within the past decade, phylogenetically informed methods have been developed to test key innovation hypotheses and evaluate the influence these traits have had in shaping modern faunas. This is primarily accomplished by estimating state-dependent speciation and extinction rates. These methods have important caveats and guidelines related to both calculation and interpretation, which are necessary to understand in cases of discrete (qualitative) character analysis, as can be common when studying the evolution of neuromorphology. In such studies, inclusion of additional characters, acknowledgement of character codistribution, and addition of sister clade comparison should be explored to ensure model accuracy. Even so, phylogenies provide a survivor-only examination of character evolution, and paleontological contexts may be necessary to replicate and confirm results. Here, I review these issues in the context of selective brain cooling – a neurovascular-mediated osmoregulatory physiology that dampens hypothalamic responses to heat stress and reduces evaporative water loss in large-bodied mammals. This binary character provides an example of the interplay between sample size, evenness, and character codistribution. Moreover, it allows for an opportunity to compare phylogenetically constrained results with paleontological data, augmenting survivor-only analyses with observable extinction patterns. This trait- dependent diversification example indicates that selective brain cooling is significantly associated with the generation of modern large-mammal faunas. Importantly, paleontological data validate phylogenetic patterns and demonstrate how suites of characters worked in concert to establish the large-mammal communities of today.

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