How Important Is Budding Speciation for Comparative Studies?

The acknowledgment of evolutionary dependence among species has fundamentally changed how we ask biological questions. Phylogenetic models became the standard approach for studies with 3 or more lineages, in particular those using extant species. Most phylogenetic comparative methods (PCMs) translate relatedness into covariance, meaning that evolutionary changes before lineages split should be interpreted together whereas after the split lineages are expected to change independently. This clever realization has shaped decades of research. Here, we discuss one element of the comparative method often ignored or assumed as unimportant: if nodes of a phylogeny represent the dissolution of the ancestral lineage into two new ones or if the ancestral lineage can survive speciation events (i.e., budding). Budding speciation is often reported in paleontological studies, due to the nature of the evidence for budding in the fossil record, but it is surprisingly absent in comparative methods. Here, we show that many PCMs assume that divergence happens as a symmetric split, even if these methods do not explicitly mention this assumption. We discuss the properties of trait evolution models for continuous and discrete traits and their adequacy under a scenario of budding speciation. We discuss the effects of budding speciation under a series of plausible evolutionary scenarios and show when and how these can influence our estimates. We also propose that long-lived lineages that have survived through a series of budding speciation events and given birth to multiple new lineages can produce evolutionary patterns that challenge our intuition about the most parsimonious history of trait changes in a clade. We hope our discussion can help bridge comparative approaches in paleontology and neontology as well as foster awareness about the assumptions we make when we use phylogenetic trees.

The Major Features of Macroevolution

Evolutionary dynamics operating across deep time leave footprints in the shapes of phylogenetic trees. For the last several decades, researchers have used increasingly large and robust phylogenies to study the evolutionary history of individual clades and to investigate the causes of the glaring disparities in diversity among groups. Whereas typically not the focal point of individual clade-level studies, many researchers have remarked on recurrent patterns that have been observed across many different groups and at many different time scales. Whereas previous studies have documented various such regularities in topology and branch length distributions, they have typically focused on a single pattern and used a disparate collection (oftentimes, of quite variable reliability) of trees to assess it. Here we take advantage of modern megaphylogenies and unify previous disparate observations about the shapes embedded in the Tree of Life to create a catalog of the "major features of macroevolution." By characterizing such a large swath of subtrees in a consistent way, we hope to provide a set of phenomena that process-based macroevolutionary models of diversification ought to seek to explain.

Causes and Consequences of Apparent Timescaling Across All Estimated Evolutionary Rates

Evolutionary rates play a central role in connecting micro- and macroevolution. All evolutionary rate estimates, including rates of molecular evolution, trait evolution, and lineage diversification, share a similar scaling pattern with time: The highest rates are those measured over the shortest time interval. This creates a disconnect between micro- and macroevolution, although the pattern is the opposite of what some might expect: Patterns of change over short timescales predict that evolution has tremendous potential to create variation and that potential is barely tapped by macroevolution. In this review, we discuss this shared scaling pattern across evolutionary rates. We break down possible explanations for scaling into two categories, estimation error and model misspecification, and discuss how both apply to each type of rate. We also discuss the consequences of this ubiquitous pattern, which can lead to unexpected results when comparing ratesover different timescales. Finally, after addressing purely statistical concerns, we explore a few possibilities for a shared unifying explanation across the three types of rates that results from a failure to fully understand and account for how biological processes scale over time.

Evolutionary Sample Size and Consilience in Phylogenetic Comparative Analysis

Phylogenetic comparative methods (PCMs) are commonly used to study evolution and adaptation. However, frequently used PCMs for discrete traits mishandle single evolutionary transitions. They erroneously detect correlated evolution in these situations. For example, hair and mammary glands cannot be said to have evolved in a correlated fashion because each evolved only once in mammals, but a commonly used model (Pagel's Discrete) statistically supports correlated (dependent) evolution. Using simulations, we find that rate parameter estimation, which is central for model selection, is poor in these scenarios due to small effective (evolutionary) sample sizes of independent character state change. Pagel's Discrete model also tends to favor dependent evolution in these scenarios, in part, because it forces evolution through state combinations unobserved in the tip data. This model prohibits simultaneous dual transitions along branches. Models with underlying continuous data distributions (e.g., Threshold and GLMM) are less prone to favor correlated evolution, but are still susceptible when evolutionary sample sizes are small. We provide three general recommendations for researchers who encounter these common situations: 1) Create study designs that evaluate a priori hypotheses and maximize evolutionary sample sizes; 2) assess the suitability of evolutionary models-for discrete traits, we introduce the phylogenetic imbalance ratio; and 3) evaluate evolutionary hypotheses with a consilience of evidence from disparate fields, like biogeography and developmental biology. Consilience plays a central role in hypothesis testing within the historical sciences where experiments are difficult or impossible to conduct, such as many hypotheses about correlated evolution. These recommendations are useful for investigations that employ any type of PCM.

Re-evaluation of the "law of constant extinction" for ruminants at different taxonomical scales

The "law of constant extinction," proposed by Van Valen, states that long and short-lived taxa have equal chances of going extinct. This pattern of age-independent extinction was originally inferred using the fossil record of several different taxa and relied on survivorship curves built from the literal reading of the fossil record. Van Valen's seminal work was mostly done at higher taxonomic levels, hence its prevalence at the species level could not be directly inferred. The surprisingly few subsequent studies done at the species level have challenged the prevalence of age-independent extinction, but those have, for the most part, failed to explicitly incorporate inherent biases of the fossil record. Using a recent Bayesian framework that accounts for several of those biases, including the fact that very short-living lineages might never make to the record itself, we showed that Ruminantia species present age-dependent extinction, where extinction probability decreases with species age. An analysis at the genus level suggested age-independent extinction but further examination suggested that the pattern might be more complex than previously reported by Van Valen. Our results indicate that different taxonomic levels may present different extinction regimes, which could justify the development of new macroevolutionary theory and methods.

An Effective Mutualism? The Role of Theoretical Studies in Ecology and Evolution

Theoretical models often have fundamentally different goals than do empirical studies of the same topic. Models can test the logic of existing hypotheses, explore the plausibility of new hypotheses, provide expectations that can be tested with data, and address aspects of topics that are currently inaccessible empirically. Theoretical models are common in ecology and evolution and are generally well cited, but I show that many citations appearing in nontheoretical studies are general to topic and that a substantial proportion are incorrect. One potential cause of this pattern is that some functions of models are rather abstract, leading to miscommunication between theoreticians and empiricists. Such misunderstandings are often triggered by simplifying logistical assumptions that modelers make. The 2018 Vice Presidential Symposium of the American Society of Naturalists included a variety of mathematical models in ecology and evolution from across several topics. Common threads that appear in the use of the models are identified, highlighting the power of a theoretical approach and the role of the assumptions that such models make.