Biology subjects

Barido-Sottani, J.

Publications and source records attributed to Barido-Sottani, J..

15 recordsLinked to original sources

bioRxiv2025

Deep learning for mass extinction detection on fossilized phylogenies: power, limitations, and lessons for simulation-based phylodynamic inference

Detecting mass extinction events from phylogenies is a fundamental yet challenging task. While traditional likelihood-based methods are available, deep learning offers a powerful, simulation-based alternative. Here, we evaluate a deep learning approach using a novel hybrid model that combines Graph Neural Networks with Long Short-Term Memory networks. This model analyzes phylogenies--containing both extant species and fossils--simulated under a complex skyline Fossilized Birth-Death model that incorporates mass extinctions and fluctuating background rates. We validate the architectures effectiveness through ablation studies. Our investigation revealed that the stochasticity of the simulation was a primary obstacle, creating significant "label noise" that initially limited performance. A direct comparison showed our deep learning approach performed slightly better than Bayesian methods. It is robust to uncertainty in phylogenetic branch lengths and topology and generalizes to larger trees, but its performance degrades under model mismatch with higher background extinction rates. However, our work highlights a critical limitation: the model is highly specific to the definition of mass extinction it was trained on. Consequently, any modification to this definition necessitates retraining a new model from scratch. We conclude by summarizing the challenges and lessons learned for simulation-based inference in phylodynamics.

evolutionary biology↗

bioRxiv2025

Evaluating the impact and detectability of mass extinctions on total-evidence dating

Fossils are crucial for accurately dating phylogenetic trees because their ages provide vital constraints on the timing of macroevolutionary events, and their morphological characters offer key information on evolutionary rates and phylogenetic positions. The fossilized birth-death (FBD) process is a diversification model that incorporates both extant and extinct species, serving as a tree prior that seamlessly integrates fossils into phylogenetic inference. While the FBD model can account for mass extinctions, which caused rapid, widespread organismal loss, few studies have utilized FBD models incorporating these events in phylogenetic inference. This is likely because the detectability of mass extinctions and their impact on phylogenetic inference remain unclear. Through simulations, we assessed the influence of mass extinctions on divergence time and topology inference and evaluated the detectability of mass extinction signals in total-evidence dating. We examined three FBD tree priors: without mass extinction, with known mass extinction time and survival probability, and with known mass extinction time but unknown survival probability. Our results show that the FBD model with known mass extinction time and unknown survival probability was able to reliably detect mass extinctions when they occurred, and correctly refrained from detecting mass extinctions when they were absent. Moreover different FBD models generate similar divergence time and tree topology errors. Even when the FBD model used for tree inference did not explicitly account for mass extinction events, signals of mass extinction were still detectable on the resulting MCC trees. The accuracy of the detection was similar to the one obtained from MCC trees inferred using an FBD model that includes mass extinction parameters. We also reduced the fossilization rate and the number of morphological characters, obtaining results consistent with the aforementioned findings. However, reducing the fossilization rate decreased the accuracy of detecting mass extinctions when they occurred, and reducing the number of morphological characters decreased the accuracy of divergence time inference. Furthermore, we adjusted the priors for the existence of mass extinction and the survival probability of mass extinction. We found that the prior for the existence of mass extinction had no effect on inference, whereas the prior for the survival probability of mass extinction significantly influenced both the detection of mass extinctions and the estimation of survival probabilities. Finally, we applied these models to empirical datasets of tetraodontiform fishes and crinoids and found that, consistent with our simulation results, the inclusion of a mass extinction event in the tree prior had a negligible impact on the inferred topologies and divergence times.

evolutionary biology↗

bioRxiv2025

The Fossilized Birth Death Process with heterogeneous diversification rates unravels the link between diversification and specialisation to a carnivorous diet in Nimravidae (Carnivoraformes)

Bayesian phylogenetic inference uses more and more complex diversification models as tree priors to test new macroevolutionary hypotheses. However, those models are usually developed in a neontological framework, despite the increasing number of datasets covering both extant and fossil taxa, as well as the fact that many clades are entirely extinct. In this paper, we develop the F-ClaDS model, a Fossilized-Birth-Death (FBD) version of the cladogenetic diversification rate shift (ClaDS) model, in BEAST2. ClaDS estimates partially inherited branch-specific rates from a phylogeny, providing a nuanced and detailed perspective of the variations in diversification across the tree. Our extension allows the integration of fossil samples directly into the phylogeny. We apply our new implementation to a dataset of 36 Nimravidae, a fully extinct carnivoraform clade that spanned from the Early Eocene to the Late Miocene, which species had different degrees of specialisation to a carnivorous diet. We show that using different tree priors does not affect substantially the topology of the inferred trees, but affects the ages of nodes and tips, as well as branch-lengths. F-ClaDS also recovers more species as sampled ancestors than the homogeneous FBD model. The branches with the highest speciation and extinction rates are those corresponding to the hypercarnivorous clades (Hoplophoneus and the barbourofelins), supporting the view that specialization to a hypercarnivorous diet can spur speciation, but also increase extinction risk, especially during times of global ecosystem change, potentially due to a high position in the trophic chain.

evolutionary biology↗

bioRxiv2025

Integrating fossils samples with heterogeneous diversification rates: a combined Multi-Type Fossilized Birth-Death model

Birth-death models are widely used to describe the diversification process which leads to the observed species and phylogenies. When integrated into Bayesian phylogenetic inference, birth-death models allow the joint inference of the phylogeny and the diversification parameters from molecular information. Two major classes of extensions of the birth-death process are considered in this article. The first extends the phylogenetic tree to include fossil samples alongside extant species, allowing the inference to integrate information about the past diversity. The second extension models diversification rates which can vary between lineages, and is thus able to infer patterns of variation in speciation or extinction rates. In this work, we combine these two types of extension into a multi-type fossilized birth-death (MTFBD) process, which can perform the joint inference of a phylogeny including extinct and extant samples, and lineage-specific diversification and fossilization rates in a Bayesian framework. The MTFBD model is implemented as part of the phylogenetic inference framework BEAST2. Using simulated and empirical datasets, we demonstrate the performance and accuracy of the new model compared to a model with rate heterogeneity but using only extant samples, and compared to a model without rate variation including fossils. We demonstrate that including fossils improves the accuracy of the phylogeny and diversification rates, especially extinction rates, provided that the inference includes morphological information to accurately place the fossil samples. When this information is not available however, MTFBD estimates are strongly driven by the priors and are thus no better or even worse than estimates obtained only with extant samples. With informative fossil characters, the MTFBD model provides accurate phylogenies, and precisely characterizes how speciation, extinction and fossilization rates vary as diversification proceeds.

evolutionary biology↗

bioRxiv2022

Convergent adaptation of true crabs (Decapoda: Brachyura) to a gradient of terrestrial environments

For much of terrestrial biodiversity, the evolutionary pathways of adaptation from marine ancestors are poorly understood, and have usually been viewed as a binary trait. True crabs, the decapod crustacean infraorder Brachyura, comprise over 7,600 species representing a striking diversity of morphology and ecology, including repeated adaptation to non-marine habitats. Here, we reconstruct the evolutionary history of Brachyura using new and published sequences of 10 genes for 344 tips spanning 88 of 109 brachyuran families. Using 36 newly vetted fossil calibrations, we infer that brachyurans most likely diverged in the Triassic, with family-level splits in the late Cretaceous and early Paleogene. By contrast, the root age is underestimated with automated sampling of 328 fossil occurrences explicitly incorporated into the tree prior, suggesting such models are a poor fit under heterogeneous fossil preservation. We apply recently defined trait-by-environment associations to classify a gradient of transitions from marine to terrestrial lifestyles. We estimate that crabs left the marine environment at least seven and up to 17 times convergently, and returned to the sea from non-marine environments at least twice. Although the most highly terrestrial- and many freshwater-adapted crabs are concentrated in Thoracotremata, Bayesian threshold models of ancestral state reconstruction fail to identify shifts to higher terrestrial grades due to the degree of underlying change required. Lineages throughout our tree inhabit intertidal and marginal marine environments, corroborating the inference that the early stages of terrestrial adaptation have a lower threshold to evolve. Our framework and extensive new fossil and natural history datasets will enable future comparisons of non-marine adaptation at the morphological and molecular level. Crabs provide an important window into the early processes of adaptation to novel environments, and different degrees of evolutionary constraint that might help predict these pathways.

evolutionary biology↗

bioRxiv2022

Putting the F in FBD analyses: tree constraints or morphological data ?

1The fossilized birth-death (FBD) process provides an ideal model for inferring phylogenies from both extant and fossil taxa. Using this approach, fossils (with or without character data) are directly considered as part of the tree. This leads to a statistically coherent prior on divergence times, where the variance associated with node ages reflects uncertainty in the placement of fossil taxa in the phylogeny. Since fossils are typically not associated with molecular sequences, additional information is required to place fossils in the tree. Previously, this information has been provided in two different forms: using topological constraints, where the user specifies monophyletic clades based on established taxonomy, or so-called total-evidence analyses, which use a morphological data matrix with data for both fossil and extant specimens in addition to the molecular alignment. In this work, we use simulations to evaluate these different approaches to handling fossil placement in FBD analyses, both in ideal conditions and in datasets including uncertainty or even errors. We also explore how rate variation in fossil recovery or diversification rates impacts these approaches. We find that the extant topology is well recovered under all methods of fossil placement. Divergence times are similarly well recovered across all methods, with the exception of constraints which contain errors. These results are consistent with expectations: in FBD inferences, divergence times are mostly informed by fossil ages, so variations in the position of fossils strongly impact these estimates. On the other hand, the placement of extant taxa in the phylogeny is driven primarily by the molecular alignment. We see similar patterns in datasets which include rate variation, however one notable difference is that relative errors in extant divergence times increase when more variation is included in the dataset, for all approaches using topological constraints, and particularly for constraints with errors. Finally, we show that trees recovered under the FBD model are more accurate than those estimated using non-FBD (i.e., non-time calibrated) inference. This result holds even with the use of erroneous fossil constraints and model misspecification under the FBD. Overall, our results underscore the importance of core taxonomic research, including morphological data collection and species descriptions, irrespective of the approach to handling phylogenetic uncertainty using the FBD process.

evolutionary biology↗

bioRxiv2022

Robust phylodynamic analysis of genetic sequencing data from structured populations

The multi-type birth-death model with sampling is a phylodynamic model which enables quantification of past population dynamics in structured populations, based on phylogenetic trees. The BEAST 2 package bdmm implements an algorithm for numerically computing the probability density of a phylogenetic tree given the population dynamic parameters under this model. In the initial release of bdmm, analyses were limited computationally to trees consisting of up to approximately 250 genetic samples. We implemented important algorithmic changes to bdmm which dramatically increase the number of genetic samples that can be analyzed, and improve the numerical robustness and efficiency of the calculations. Including more samples leads to improved precision of parameter estimates, particularly for structured models with a high number of inferred parameters. Furthermore, we report on several model extensions to bdmm, inspired by properties common to empirical datasets. We apply this improved algorithm to two partly overlapping datasets of Influenza A virus HA sequences sampled around the world, one with 500 samples, the other with only 175, for comparison. We report and compare the global migration patterns and seasonal dynamics inferred from each dataset. In that way, we show what information is gained by analyzing the bigger dataset which became possible with the presented algorithmic changes to bdmm. In summary, bdmm allows for robust, faster and more general phylodynamic inference of larger datasets.

evolutionary biology↗

bioRxiv2021

RevGadgets: an R Package for visualizing Bayesian phylogenetic analyses from RevBayes

O_LIStatistical phylogenetic methods are the foundation for a wide range of evolutionary and epidemiological studies. However, as these methods grow increasingly complex, users often encounter significant challenges with summarizing, visualizing, and communicating their key results. C_LIO_LIWe present RevGadgets, an R package for creating publication-quality figures from the results of a large variety of phylogenetic analyses performed in RevBayes (and other phylogenetic software packages). C_LIO_LIWe demonstrate how to use RevGadgets through a set of vignettes that cover the most common use cases that researchers will encounter. C_LIO_LIRevGadgets is an open-source, extensible package that will continue to evolve in parallel with RevBayes, helping researchers to make sense of and communicate the results of a diverse array of analyses. C_LI [Bayesian phylogenetics, data visualization, R, RevBayes]

evolutionary biology↗

bioRxiv2021

Estimating the age of poorly dated fossil specimens and deposits using a total-evidence approach and the fossilized birth-death process

Bayesian total-evidence approaches under the fossilized birth-death model enable biologists to combine fossil and extant data while accounting for uncertainty in the ages of fossil specimens, in an integrative phylogenetic analysis. Fossil age uncertainty is a key feature of the fossil record as many empirical datasets may contain a mix of precisely dated and poorly dated fossil specimens or deposits. In this study, we explore whether reliable age estimates for fossil specimens can be obtained from Bayesian total-evidence phylogenetic analyses under the fossilized birth-death model. Through simulations based on the example of the Baltic amber deposit, we show that estimates of fossil ages obtained through such an analysis are accurate, particularly when the proportion of poorly dated specimens remains low and the majority of fossil specimens have precise dates. We confirm our results using an empirical dataset of living and fossil penguins by artificially increasing the age uncertainty around some fossil specimens and showing that the resulting age estimates overlap with the recorded age ranges. Our results are applicable to many empirical datasets where classical methods of establishing fossil ages have failed, such as the Baltic amber and the Gobi Desert deposits.

paleontology↗

bioRxiv2020

A skyline birth-death process for inferring the population size from a reconstructed tree with occurrences

Phylodynamic models generally aim at jointly inferring phylogenetic relationships, model parameters, and more recently, population size through time for clades of interest, based on molecular sequence data. In the fields of epidemiology and macroevolution these models can be used to estimate, respectively, the past number of infected individuals (prevalence) or the past number of species (paleodiversity) through time. Recent years have seen the development of "total-evidence" analyses, which combine molecular and morphological data from extant and past sampled individuals in a unified Bayesian inference framework. Even sampled individuals characterized only by their sampling time, i.e. lacking morphological and molecular data, which we call occurrences, provide invaluable information to reconstruct past population sizes. Here, we present new methodological developments around the Fossilized Birth-Death Process enabling us to (i) efficiently incorporate occurrence data while remaining computationally tractable and scalable; (ii) consider piecewise-constant birth, death and sampling rates; and (iii) reconstruct past population sizes, with or without knowledge of the underlying tree. We implement our method in the RevBayes software environment, enabling its use along with a large set of models of molecular and morphological evolution, and validate the inference workflow using simulations under a wide range of conditions. We finally illustrate our new implementation using two empirical datasets stemming from the fields of epidemiology and macroevolution. In epidemiology, we apply our model to the Covid-19 outbreak on the Diamond Princess ship. We infer the total prevalence throughout the outbreak, by taking into account jointly the case count record (occurrences) along with viral sequences for a fraction of infected individuals. In macroevolution, we present an empirical case study of cetaceans. We infer the diversity trajectory using molecular and morphological data from extant taxa, morphological data from fossils, as well as numerous fossil occurrences. Our case studies highlight that the advances we present allow us to further bridge the gap between between epidemiology and pathogen genomics, as well as paleontology and molecular phylogenetics.

evolutionary biology↗

bioRxiv2020

Ignoring fossil age uncertainty leads to inaccurate topology and divergence times in time calibrated tree inference

Time calibrated trees are challenging to estimate for many extinct groups of species due to the incompleteness of the rock and fossil records. Additionally, the precise age of a sample is typically not known as it may have occurred at any time during the time interval spanned by the rock layer. Bayesian phylogenetic approaches provide a coherent framework for incorporating multiple sources of evidence and uncertainty. In this study, we simulate datasets with characteristics typical of Palaeozoic marine invertebrates, in terms of character and taxon sampling. We use these datasets to examine the impact of different age handling methods on estimated topologies and divergence times obtained using the fossilized birth-death process. Our results reiterate the importance of modeling fossil age uncertainty, although we find that the overall impact of fossil age uncertainty depends on both fossil taxon sampling and character sampling. When character sampling is low, different approaches to handling fossil age uncertainty make little to no difference in the accuracy and precision of the results. However, when character sampling is high, sampling the fossil ages as part of the inference gives topology and divergence times estimates that are as good as those obtained by fixing ages to the truth, whereas fixing fossil ages to incorrect values results in higher error and lower coverage. Modeling fossil age uncertainty is thus critical, as fixing incorrect fossil ages will negate the benefits of improved fossil and character sampling.

evolutionary biology↗

bioRxiv2020

Improved multi-type birth-death phylodynamic inference in BEAST 2

The multi-type birth-death model with sampling is a phylodynamic model which enables quantification of past population dynamics in structured populations, based on phylogenetic trees. The BEAST 2 package bdmm implements an algorithm for numerically computing the probability density of a phylogenetic tree given the population dynamic parameters under this model. In the initial release of bdmm, analyses were limited to trees consisting of up to approximately 250 genetic samples for numerical reasons. We implemented important algorithmic changes to bdmm which dramatically increase the number of genetic samples that can be analyzed, and improve the numerical robustness and efficiency of the calculations. Being able to use bigger datasets leads to improved precision of parameter estimates. Furthermore, we report on several model extensions to bdmm, inspired by properties common to empirical datasets. We apply this improved algorithm to two partly overlapping datasets of Influenza A virus HA sequences sampled around the world, one with 500 samples, the other with only 175, for comparison. We report and compare the global migration patterns and seasonal dynamics inferred from each dataset. AvailabilityThe latest release with our updates, bdmm 0.3.5, is freely available as an open access package of BEAST 2. The source code can be accessed at https://github.com/denisekuehnert/bdmm.

evolutionary biology↗

bioRxiv2018

Ignoring stratigraphic age uncertainty leads to erroneous estimates of species divergence times under the fossilized birth-death process

Fossil information is essential for estimating species divergence times, and can be integrated into Bayesian phylogenetic inference using the fossilized birth-death (FBD) process. An important aspect of palaeontological data is the uncertainty surrounding specimen ages, which can be handled in different ways during inference. The most common approach is to fix fossil ages to a point estimate within the known age interval. Alternatively, age uncertainty can be incorporated by using priors, and fossil ages are then directly sampled as part of the inference. This study presents a comparison of alternative approaches for handling fossil age uncertainty in analysis using the FBD process. Based on simulations, we find that fixing fossil ages to the midpoint or a random point drawn from within the stratigraphic age range leads to biases in divergence time estimates, while sampling fossil ages leads to estimates that are similar to inferences that employ the correct ages of fossils. Second, we show a comparison using an empirical dataset of extant and fossil cetaceans, which confirms that different methods of handling fossil age uncertainty lead to large differences in estimated node ages. Stratigraphic age uncertainty should thus not be ignored in divergence time estimation and instead should be incorporated explicitly.

paleontology↗

bioRxiv2018

BEAST 2.5: An Advanced Software Platform for Bayesian Evolutionary Analysis

Elaboration of Bayesian phylogenetic inference methods has continued at pace in recent years with major new advances in nearly all aspects of the joint modelling of evolutionary data. It is increasingly appreciated that some evolutionary questions can only be adequately answered by combining evidence from multiple independent sources of data, including genome sequences, sampling dates, phenotypic data, radiocarbon dates, fossil occurrences, and biogeographic range information among others. Including all relevant data into a single joint model is very challenging both conceptually and computationally. Advanced computational software packages that allow robust development of compatible (sub-)models which can be composed into a full model hierarchy have played a key role in these developments.\n\nDeveloping such software frameworks is increasingly a major scientific activity in its own right, and comes with specific challenges, from practical software design, development and engineering challenges to statistical and conceptual modelling challenges. BEAST 2 is one such computational software platform, and was first announced over 4 years ago. Here we describe a series of major new developments in the BEAST 2 core platform and model hierarchy that have occurred since the first release of the software, culminating in the recent 2.5 release.\n\nAuthor summaryBayesian phylogenetic inference methods have undergone considerable development in recent years, and joint modelling of rich evolutionary data, including genomes, phenotypes and fossil occurrences is increasingly common. Advanced computational software packages that allow robust development of compatible (sub-)models which can be composed into a full model hierarchy have played a key role in these developments. Developing scientific software is increasingly crucial to advancement in many fields of biology. The challenges range from practical software development and engineering, distributed team coordination, conceptual development and statistical modelling, to validation and testing. BEAST 2 is one such computational software platform for phylogenetics, population genetics and phylodynamics, and was first announced over 4 years ago. Here we describe the full range of new tools and models available on the BEAST 2.5 platform, which expand joint evolutionary inference in many new directions, especially for joint inference over multiple data types, non-tree models and complex phylodynamics.

evolutionary biology↗

bioRxiv2018

A Multi-State Birth-Death model for Bayesian inference of lineage-specific birth and death rates

Heterogeneous populations can lead to important differences in birth and death rates across a phylogeny Taking this heterogeneity into account is thus critical to obtain accurate estimates of the underlying population dynamics. We present a new multi-state birth-death model (MSBD) that can estimate lineage-specific birth and death rates. For species phylogenies, this corresponds to estimating lineage-dependent speciation and extinction rates. Contrary to existing models, we do not require a prior hypothesis on a trait driving the rate differences and we allow the same rates to be present in different parts of the phylogeny. Using simulated datasets, we show that the MSBD 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 re-analysis of two empirical datasets and compare the results obtained by MSBD and by the existing software BAMM. The MSBD model is implemented as a package in the Bayesian inference software BEAST2, which allows joint inference of the phylogeny and the model parameters.\n\nSignificance statementPhylogenetic trees can inform about the underlying speciation and extinction processes within a species clade. Many different factors, for instance environmental changes or morphological changes, can lead to differences in macroevolutionary dynamics within a clade. We present here a new multi-state birth-death (MSBD) model that can detect these differences and estimate both the position of changes in the tree and the associated macroevolutionary parameters. The MSBD model does not require a prior hypothesis on which trait is driving the changes in dynamics and is thus applicable to a wide range of datasets. It is implemented as an extension to the existing framework BEAST2.

evolutionary biology↗