Search for: All records

Abstract BackgroundSince the mid-20th century, it has been argued by some that the transition from diploidy to polyploidy is an ‘evolutionary dead end’ in plants. Although this point has been debated ever since, multiple definitions of ‘dead end’ have been used in the polyploidy literature, without sufficient differentiation between alternative uses. ScopeHere, we focus on the two most common conceptions of the dead-end hypothesis currently discussed: the ‘lowering diversification’ hypothesis and the ‘rarely successful’ hypothesis. We discuss the evidence for both hypotheses, and we use a recently developed method of inferring tip diversification rates to demonstrate tests for the effect of ploidy on diversification in Solanaceae. ConclusionsWe find that diversification rates in the family are not strongly correlated with ploidy or with the closely related trait of breeding system. We also outline recent work in the field that moves beyond the relatively simple question of whether polyploidy increases, decreases or does not significantly affect diversification rates in plants. 

Abstract Nature is full of messy variation, which serves as the raw material for evolution. However, in comparative biology this variation is smoothed into averages. Overlooking this variation not only weakens our analyses but also risks selecting inaccurate models, generating false precision in parameter estimates, and creating artificial patterns. Furthermore, the complexity of uncertainty extends beyond traditional “measurement error,” encompassing various sources of intraspecific variance. To address this, we propose the term “tip fog” to describe the variance between the true species mean and what is recorded, without implying a specific mechanism. We show why accounting for tip fog remains critical by showing its impact on continuous comparative models and discrete comparative and diversification models. We rederive methods to estimate this variance and use simulations to assess its feasibility and importance in a comparative context. Our findings reveal that ignoring tip fog substantially affects the accuracy of rate estimates, with higher tip fog levels showing greater biases from the true rates, as well as affecting which models are chosen. The findings underscore the importance of model selection and the potential consequences of neglecting tip fog, providing insights for improving the accuracy of comparative methods in evolutionary biology. 

ABSTRACT Understanding how the intrinsic ability of populations and species to meet shifting selective demands shapes evolutionary patterns over both short and long timescales is a major question in biology. One major axis of evolutionary flexibility can be measured by phenotypic integration and modularity. The strength, scale, and structure of integration may constrain or catalyze evolution in the face of new selective pressures. We analyze a dataset of seven leaf measurements across Vitaceae to examine how correlations in trait divergence are linked to transitions between freezing and nonfreezing habitats. We assess this by applying a custom algorithm to compare the timing of habitat shifts to changes in the structure of evolutionary trait correlation at discrete points along a phylogeny. We also explore these patterns in relation to lineage diversification rates to understand how and whether patterns in the evolvability of complex multivariate phenotypes are linked to higher‐level macroevolutionary dynamics. We found that shifts in the structure, but not the overall strength, of phylogenetic integration of leaves precipitate colonization of freezing climates. Lineages that underwent associated shifts in leaf trait integration and subsequent movement into freezing habitats also displayed lower turnover and higher net diversification, suggesting a link among shifting vectors of selection, internal constraint, and lineage persistence in the face of changing environments. 

Summary Accurate divergence times are essential for interpreting and understanding the context in which lineages have evolved. Over the past several decades, debates have surrounded the discrepancies between the inferred molecular ages of crown angiosperms, often estimated from the Late Jurassic into the Permian, and the fossil record, placing angiosperms in the Early Cretaceous. That crown angiosperms could have emerged as early as the Permian or even the Triassic would have major implications for the paleoecological context of the origin of one of the most consequential clades in the tree of life. Here, we argue, and demonstrate through simulations, that the older ages inferred from molecular data and relaxed‐clock models are misled by lineage‐specific rate heterogeneity resulting from life history changes that occurred several times throughout the evolution of vascular plants. To overcome persistent discrepancies in age estimates, more biologically informed and realistic models should be developed, and our results should be considered in the context of their biological implications before we accept inferences that are a major departure from our strongest evidence. 

Abstract AimDue to the sessile nature of flowering plants, movements to new geographical areas occur mainly during seed dispersal. Frugivores tend to be efficient dispersers because animals move within the boundaries of their preferable niches, so seeds are more likely to be transported to environments that are similar to where the parent plant occurs. However, this efficiency can result in less opportunity for niche shifts over macroevolutionary time, ‘trapping’ plant lineages in particular climatic conditions. Here we test this hypothesis by analysing the role that the interaction with frugivores play in changing dynamics of climatic niche evolution in five clades of flowering plants. LocationGlobal. TaxonThe flowering plant families Apocynaceae, Ericaceae, Melastomataceae, Rosaceae and Solanaceae. MethodsWe model climatic niche evolution as a variable parameter Ornstein–Uhlenbeck process. However, rather than assuming regimes a priori, we use a hidden Markov model (HMM) to infer the complex evolutionary history associated with different modes of seed dispersal. In addition to allowing for a more accurate picture of the regimes, the use of HMMs allows partitioning the variance of climatic niche evolution to include dynamics independent of our focal character. ResultsLineages dispersed by frugivores tend to have warmer and wetter climatic optima and are generally associated with areas where potential for vegetation growth is higher. However, lineages distributed in more mesic habitats, such as rainforests, are generally associated with slower rates of climatic niche evolution regardless of their mode of seed dispersal. Main ConclusionsCharacteristics of the abiotic environment may facilitate the evolution of some types of plant–animal interactions. Association with frugivores is an important modulator of how plants move in space, but its impact on their climatic niche evolution appears to be indirect. Seed dispersal by frugivores may facilitate the establishment of lineages in closed canopy biomes, but the general slower rates of climatic niche evolution in these habitats are possibly related to other general aspects of the ‘mesic syndrome’ rather than the behaviour of the animals that disperse their seeds. 

Abstract Lineage‐specific traits determine how plants interact with their surrounding environment. Unrelated species may evolve similar phenotypic characteristics to tolerate, persist in, and invade environments with certain characteristics, resulting in some traits becoming relatively more common in certain types of habitats. Analyses of these general patterns of geographical trait distribution have led to the proposal of general principles to explain how plants diversify in space over time. Trait–environment correlation analyses quantify to what extent unrelated lineages have similar evolutionary responses to a given type of habitat. In this synthesis, I give a short historical overview on trait–environment correlation analyses, from some key observations from classic naturalists to modern approaches using trait evolution models, large phylogenies, and massive data sets of traits and distributions. I discuss some limitations of modern approaches, including the need for more realistic models, the lack of data from tropical areas, and the necessary focus on trait scoring that goes beyond macromorphology. Overcoming these limitations will allow the field to explore new questions related to trait lability and niche evolution and to better identify generalities and exceptions in how plants diversify in space over time. 

Abstract The fossilized birth–death (FBD) model is a naturally appealing way of directly incorporating fossil information when estimating diversification rates. However, an important yet often overlooked property of the original FBD derivation is that it distinguishes between two types of sampled lineages. Here, we first discuss and demonstrate the impact of severely undersampling, and even not including fossils that represent samples of lineages that also had sampled descendants. We then explore the benefits of including fossils, generally, by implementing and then testing two types of FBD models, including one that converts a fossil set into stratigraphic ranges, in more complex likelihood-based models that assume multiple rate classes across the tree. Under various simulation scenarios, including a scenario that exists far outside the set of models we evaluated, including fossils rarely outperform analyses that exclude them altogether. At best, the inclusion of fossils improves precision but does not influence bias. Similarly, we found that converting the fossil set to stratigraphic ranges, which is one way to remedy the effects of undercounting the number of k-type fossils, results in turnover rates and extinction fraction estimates that are generally underestimated. Although 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. [Fossilized birth–death; fossils; MiSSE; state speciation extinction; stratigraphic ranges; turnover rate.] 

Across a variety of biological datasets, from genomes to conservation to the fossil record, evolutionary rates appear to increase toward the present or over short time scales. This has long been seen as an indication of processes operating differently at different time scales, even potentially as an indicator of a need for new theory connecting macroevolution and microevolution. Here we introduce a set of models that assess the relationship between rate and time and demonstrate that these patterns are statistical artifacts of time-independent errors present across ecological and evolutionary datasets, which produce hyperbolic patterns of rates through time. We show that plotting a noisy numerator divided by time versus time leads to the observed hyperbolic pattern; in fact, randomizing the amount of change over time generates patterns functionally identical to observed patterns. Ignoring errors can not only obscure true patterns but create novel patterns that have long misled scientists. 

Abstract The correlation between two characters is often interpreted as evidence that there exists a significant and biologically important relationship between them. However, Maddison and FitzJohn (in The unsolved challenge to phylogenetic correlation tests for categorical characters. Syst. Biol. 2015;64:127–136) recently pointed out that evidence of correlated evolution between two categorical characters is often spurious, particularly, when the dependent relationship stems from a single replicate deep in time. Here we will show that there may, in fact, be a statistical solution to the problem posed by Maddison and FitzJohn naturally embedded within the expanded model space afforded by the hidden Markov model (HMM) framework. We demonstrate that the problem of single unreplicated evolutionary events manifests itself as rate heterogeneity within our models and that this is the source of the false correlation. Therefore, we argue that this problem is better understood as model misspecification rather than a failure of comparative methods to account for phylogenetic pseudoreplication. We utilize HMMs to develop a multirate independent model which, when implemented, drastically reduces support for correlation. The problem itself extends beyond categorical character evolution, but we believe that the practical solution presented here may lend itself to future extensions in other areas of comparative biology. [Macroevolution; model adequacy; phylogenetic comparative methods; rate heterogeneity].