Associated evolution of fruit size,fruit colour and spines in Neotropical palms

Understanding how ecological interactions have shaped the evolutionary dynamics of species traits remains a challenge in evolutionary ecology. Combining trait evolution models and phylogenies, we analysed the evolution of characters associated with seed dispersal (fruit size and colour) and herbivory (spines) in Neotropical palms to infer the role of these opposing animal–plant interactions in driving evolutionary patterns. We found that the evolution of fruit colour and fruit size was associated in Neotropical palms, supporting the adaptive interpretation of seed‐dispersal syndromes and highlighting the role of frugivores in shaping plant evolution. Furthermore, we revealed a positive association between fruit size and the presence of spines on palm leaves, bracteas and stems. We hypothesize that interactions between palms and large‐bodied frugivores/herbivores may explain the evolutionary relationship between fruit size and spines. Large‐bodied frugivores, such as extinct megafauna, besides consuming the fruits and dispersing large seeds, may also have consumed the leaves or damaged the plants, thus simultaneously favouring the evolution of large fruits and defensive structures. Our findings show how current trait patterns can be understood as the result of the interplay between antagonistic and mutualistic interactions that have happened throughout the evolutionary history of a clade.     

MGDrivE 2: A simulation framework for gene drive systems incorporating seasonality and epidemiological dynamics

Interest in gene drive technology has continued to grow as promising new drive systems have been developed in the lab and discussions are moving towards implementing field trials. The prospect of field trials requires models that incorporate a significant degree of ecological detail, including parameters that change over time in response to environmental data such as temperature and rainfall, leading to seasonal patterns in mosquito population density. Epidemiological outcomes are also of growing importance, as: i) the suitability of a gene drive construct for release will depend on its expected impact on disease transmission, and ii) initial field trials are expected to have a measured entomological outcome and a modeled epidemiological outcome. We present MGDrivE 2 (Mosquito Gene Drive Explorer 2): a significant development from the MGDrivE 1 simulation framework that investigates the population dynamics of a variety of gene drive architectures and their spread through spatially-explicit mosquito populations. Key strengths and fundamental improvements of the MGDrivE 2 framework are: i) the ability of parameters to vary with time and induce seasonal population dynamics, ii) an epidemiological module accommodating reciprocal pathogen transmission between humans and mosquitoes, and iii) an implementation framework based on stochastic Petri nets that enables efficient model formulation and flexible implementation. Example MGDrivE 2 simulations are presented to demonstrate the application of the framework to a CRISPR-based split gene drive system intended to drive a disease-refractory gene into a population in a confinable and reversible manner, incorporating time-varying temperature and rainfall data. The simulations also evaluate impact on human disease incidence and prevalence. Further documentation and use examples are provided in vignettes at the project’s CRAN repository. MGDrivE 2 is freely available as an open-source R package on CRAN (https://CRAN.R-project.org/package=MGDrivE2). We intend the package to provide a flexible tool capable of modeling gene drive constructs as they move closer to field application and to infer their expected impact on disease transmission.     

From Haeckel’s phylogenetics and Hennig’s cladistics to the method of maximum likelihood: Advantages and limitations of modern and traditional approaches to phylogeny reconstruction

The maximum likelihood and Bayesian methods are based on parametric models of character evolution. They assume that if we know these models as well as distribution of character states in studied organisms, we can infer the probability of different phylogenetic trajectories leading from ancestors to modern forms. In fact, these methods are mathematized variants of the traditional Haeckel’s approach to phylogeny reconstruction. In contrast to classical and parsimonious cladistics, they infer phylogenies without such limitations as necessity of strictly dichotomous evolution, exclusion of plesiomorphic characters, and acceptance of only holophyletic taxa. They assume that evolution may be reticulated, any homologous characters—both apomorphic and plesiomorphic—can be used for inferring phylogenies, and interpretation of evolutionary lineages as taxa is optional. Thus, the main difference between the new and more traditional approaches to phylogeny reconstruction lies not in the characters used (molecular or morphological) but in the methodology of analysis. It must be admitted that a revolution began in phylogenetics 10–20 years ago. However, the fundamental changes in phylogenetics have been carried out so calmly and neatly by the people who started this revolution, that many systematists still do not realize their importance.     

Evolution of cannibalistic traits: scenarios derived from adaptive dynamics

The evolution of cannibalistic traits in consumer populations is studied in this paper with the approach of adaptive dynamics theory. The model is kept at its minimum complexity by eliminating some environmental characteristics, like heterogeneity and seasonalities, and by hiding the size-structure of the population. Evolutionary dynamics are identified through numerical bifurcation analysis, applied both to the ecological (resident-mutant) model and to the canonical equation of adaptive dynamics. The result is a rich catalog of evolutionary scenarios involving evolutionary stable strategies and branching points both in the monomorphic and dimorphic dynamics. The possibility of evolutionary extinction of highly cannibalistic populations is also ascertained. This allows one to explain why cannibalism can be a transient stage of evolution.     

AlleleRetain: a program to assess management options for conserving allelic diversity in small,isolated populations

Preserving genetic health is an important aspect of species conservation. Allelic diversity is particularly important to conserve, as it provides capacity for adaptation and thus enables long‐term population viability. Allele retention is difficult to predict beyond one generation for real populations with complex demography and life‐history traits, so we developed a computer model to simulate allele retention in small populations. AlleleRetain is an individual‐based model implemented in r and can be applied to assess management options for conserving allelic diversity in small populations of animals with overlapping generations. AlleleRetain remedies the limitations of similar existing software, and its source code is freely available for further modification. AlleleRetain and its supporting materials can be downloaded from https://sites.google.com/site/alleleretain/ or CRAN ( http://cran.r-project.org ).     

Rapid maximum likelihood ancestral state reconstruction of continuous characters: A rerooting‐free algorithm

Ancestral state reconstruction is a method used to study the evolutionary trajectories of quantitative characters on phylogenies. Although efficient methods for univariate ancestral state reconstruction under a Brownian motion model have been described for at least 25 years, to date no generalization has been described to allow more complex evolutionary models, such as multivariate trait evolution, non‐Brownian models, missing data, and within‐species variation. Furthermore, even for simple univariate Brownian motion models, most phylogenetic comparative R packages compute ancestral states via inefficient tree rerooting and full tree traversals at each tree node, making ancestral state reconstruction extremely time‐consuming for large phylogenies. Here, a computationally efficient method for fast maximum likelihood ancestral state reconstruction of continuous characters is described. The algorithm has linear complexity relative to the number of species and outperforms the fastest existing R implementations by several orders of magnitude. The described algorithm is capable of performing ancestral state reconstruction on a 1,000,000‐species phylogeny in fewer than 2 s using a standard laptop, whereas the next fastest R implementation would take several days to complete. The method is generalizable to more complex evolutionary models, such as phylogenetic regression, within‐species variation, non‐Brownian evolutionary models, and multivariate trait evolution. Because this method enables fast repeated computations on phylogenies of virtually any size, implementation of the described algorithm can drastically alleviate the computational burden of many otherwise prohibitively time‐consuming tasks requiring reconstruction of ancestral states, such as phylogenetic imputation of missing data, bootstrapping procedures, Expectation‐Maximization algorithms, and Bayesian estimation. The described ancestral state reconstruction algorithm is implemented in the Rphylopars functions anc.recon and phylopars.     

gen3sis: A general engine for eco-evolutionary simulations of the processes that shape Earth’s biodiversity

Understanding the origins of biodiversity has been an aspiration since the days of early naturalists. The immense complexity of ecological, evolutionary, and spatial processes, however, has made this goal elusive to this day. Computer models serve progress in many scientific fields, but in the fields of macroecology and macroevolution, eco-evolutionary models are comparatively less developed. We present a general, spatially explicit, eco-evolutionary engine with a modular implementation that enables the modeling of multiple macroecological and macroevolutionary processes and feedbacks across representative spatiotemporally dynamic landscapes. Modeled processes can include species’ abiotic tolerances, biotic interactions, dispersal, speciation, and evolution of ecological traits. Commonly observed biodiversity patterns, such as α, β, and γ diversity, species ranges, ecological traits, and phylogenies, emerge as simulations proceed. As an illustration, we examine alternative hypotheses expected to have shaped the latitudinal diversity gradient (LDG) during the Earth’s Cenozoic era. Our exploratory simulations simultaneously produce multiple realistic biodiversity patterns, such as the LDG, current species richness, and range size frequencies, as well as phylogenetic metrics. The model engine is open source and available as an R package, enabling future exploration of various landscapes and biological processes, while outputs can be linked with a variety of empirical biodiversity patterns. This work represents a key toward a numeric, interdisciplinary, and mechanistic understanding of the physical and biological processes that shape Earth’s biodiversity.

This study describes a novel mechanistic engine that predicts a realistic global latitudinal diversity gradient, species richness distribution and phylogenies. This approach is a step towards the interdisciplinary numeric understanding of the physical and biological processes that have shaped Earth’s biodiversity.     

Rates of phenotypic evolution of ecological characters and sexual traits during the Tanganyikan cichlid adaptive radiation

Theory suggests that sexual traits evolve faster than ecological characters. However, characteristics of a species niche may also influence evolution of sexual traits. Hence, a pending question is whether ecological characters and sexual traits present similar tempo and mode of evolution during periods of rapid ecological divergence, such as adaptive radiation. Here, we use recently developed phylogenetic comparative methods to analyse the temporal dynamics of evolution for ecological and sexual traits in Tanganyikan cichlids. Our results indicate that whereas disparity in ecological characters was concentrated early in the radiation, disparity in sexual traits remained high throughout the radiation. Thus, closely related Tanganyikan cichlids presented higher disparity in sexual traits than ecological characters. Sexual traits were also under stronger selection than ecological characters. In sum, our results suggest that ecological characters and sexual traits present distinct evolutionary patterns, and that sexual traits can evolve faster than ecological characters, even during adaptive radiation.     

Alternative forms for genomic clines

Understanding factors regulating hybrid fitness and gene exchange is a major research challenge for evolutionary biology. Genomic cline analysis has been used to evaluate alternative patterns of introgression, but only two models have been used widely and the approach has generally lacked a hypothesis testing framework for distinguishing effects of selection and drift. I propose two alternative cline models, implement multivariate outlier detection to identify markers associated with hybrid fitness, and simulate hybrid zone dynamics to evaluate the signatures of different modes of selection. Analysis of simulated data shows that previous approaches are prone to false positives (multinomial regression) or relatively insensitive to outlier loci affected by selection (Barton's concordance). The new, theory‐based logit‐logistic cline model is generally best at detecting loci affecting hybrid fitness. Although some generalizations can be made about different modes of selection, there is no one‐to‐one correspondence between pattern and process. These new methods will enhance our ability to extract important information about the genetics of reproductive isolation and hybrid fitness. However, much remains to be done to relate statistical patterns to particular evolutionary processes. The methods described here are implemented in a freely available package “HIest” for the R statistical software (CRAN; http://cran.r-project.org/ ).     

EVOLUTIONARY CHARACTER ANALYSIS: TRACING CHARACTER CHANGE ON A CLADOGRAM

Abstract— There has been little formal discussion concerning character analysis in cladistics, even though characters and their character state trees are central to phylogenetic analyses. We refer to this field as Evolutionary Character Analysis. This paper defines the components of evolutionary character analysis: character state trees, transmodal characters, cladogram characters, attribute and character phylogenies; and the use of these components in phylogenetic inference and evolutionary studies. Character state trees and their effect on cladogram construction are discussed. A new method for numerically coding complex character state trees is described that further reduces the number of variables required to describe them. This method, ordinal coding, reduces the size of data matrices, and facilitates retrieval of state codes. This paper advocates the use of both biological evidence and evidence internal to the cladogram itself to construct character state trees (CSTs). We discuss general models of character evolution (morphocline analysis, Fitch minimum mutation model, etc.) and their role in forming CSTs. Character state trees formed with theories of character evolution are referred to as transmodal characters. These transmodal characters are contrasted with cladogram characters (Mickevich, 1982), and the place of each in a phylogenetic analysis is discussed. The method for determining cladogram characters is detailed with more complicated examples than found in previous publications. We advocate testing transmodal characters by comparing them with the resultant cladogram characters. This comparison involves transformation series analysis (TSA; Mickevich, 1982) which is viewed as an extension of reciprocal illumination. The TSA procedure and its place in hypothesis testing are reviewed. Tracing the evolution of characters interests both systematists and non-systematists alike. When character state trees (transmodal characters) are optimized on pre-existing phylogenies, character phylogenies and attribute phylogenies result. Attributes are defined as a feature that may or may not be homologous (i.e., ecological categories, plant hosts, etc.). We provide two illustrations of this approach, one involving the evolution of the anuran ear and another involving the coevolution of the butterfly Heliconius and its hostplants. Finally, the components of phylogenetic character analysis can be used to test more general evolutionary theories such as the biogenetic law and vicariance biogeography.     

Impact of temperature shifts on the joint evolution of seed dormancy and size

Seed dormancy and size are two important life‐history traits that interplay as adaptation to varying environmental settings. As evolution of both traits involves correlated selective pressures, it is of interest to comparatively investigate the evolution of the two traits jointly as well as independently. We explore evolutionary trajectories of seed dormancy and size using adaptive dynamics in scenarios of deterministic or stochastic temperature variations. Ecological dynamics usually result in unbalanced population structures, and temperature shifts or fluctuations of high magnitude give rise to more balanced ecological structures. When only seed dormancy evolves, it is counter‐selected and temperature shifts hasten this evolution. Evolution of seed size results in the fixation of a given strategy and evolved seed size decreases when seed dormancy is lowered. When coevolution is allowed, evolutionary variations are reduced while the speed of evolution becomes faster given temperature shifts. Such coevolution scenarios systematically result in reduced seed dormancy and size and similar unbalanced population structures. We discuss how this may be linked to the system stability. Dormancy is counter‐selected because population dynamics lead to stable equilibrium, while small seeds are selected as the outcome of size‐number trade‐offs. Our results suggest that unlike random temperature variation between generations, temperature shifts with high magnitude can considerably alter population structures and accelerate life‐history evolution. This study increases our understanding of plant evolution and persistence in the context of climate changes.     

Neighbor GWAS: incorporating neighbor genotypic identity into genome-wide association studies of field herbivory

An increasing number of field studies have shown that the phenotype of an individual plant depends not only on its genotype but also on those of neighboring plants; however, this fact is not taken into consideration in genome-wide association studies (GWAS). Based on the Ising model of ferromagnetism, we incorporated neighbor genotypic identity into a regression model, named “Neighbor GWAS”. Our simulations showed that the effective range of neighbor effects could be estimated using an observed phenotype when the proportion of phenotypic variation explained (PVE) by neighbor effects peaked. The spatial scale of the first nearest neighbors gave the maximum power to detect the causal variants responsible for neighbor effects, unless their effective range was too broad. However, if the effective range of the neighbor effects was broad and minor allele frequencies were low, there was collinearity between the self and neighbor effects. To suppress the false positive detection of neighbor effects, the fixed effect and variance components involved in the neighbor effects should be tested in comparison with a standard GWAS model. We applied neighbor GWAS to field herbivory data from 199 accessions of Arabidopsis thaliana and found that neighbor effects explained 8% more of the PVE of the observed damage than standard GWAS. The neighbor GWAS method provides a novel tool that could facilitate the analysis of complex traits in spatially structured environments and is available as an R package at CRAN (https://cran.rproject.org/package=rNeighborGWAS).Subject terms: Quantitative trait, Plant ecology, Ecological genetics     

Assessing among‐lineage variability in phylogenetic imputation of functional trait datasets

Phylogenetic imputation has recently emerged as a potentially powerful tool for predicting missing data in functional traits datasets. As such, understanding the limitations of phylogenetic modelling in predicting trait values is critical if we are to use them in subsequent analyses. Previous studies have focused on the relationship between phylogenetic signal and clade‐level prediction accuracy, yet variability in prediction accuracy among individual tips of phylogenies remains largely unexplored. Here, we used simulations of trait evolution along the branches of phylogenetic trees to show how the accuracy of phylogenetic imputations is influenced by the combined effects of 1) the amount of phylogenetic signal in the traits and 2) the branch length of the tips to be imputed. Specifically, we conducted cross‐validation trials to estimate the variability in prediction accuracy among individual tips on the phylogenies (hereafter ‘tip‐level accuracy’). We found that under a Brownian motion model of evolution (BM, Pagel't λ = 1), tip‐level accuracy rapidly decreased with increasing tip branch‐lengths, and only tips of approximately 10% or less of the total height of the trees showed consistently accurate predictions (i.e. cross‐validation R‐squared >0.75). When phylogenetic signal was weak, the effect of tip branch‐length was reduced, becoming negligible for traits simulated with λ < 0.7, where accuracy was in any case low. Our study shows that variability in prediction accuracy among individual tips of the phylogeny should be considered when evaluating the reliability of phylogenetically imputed trait values. To address this challenge, we describe a Monte Carlo‐based method that allows one to estimate the expected tip‐level accuracy of phylogenetic predictions for continuous traits. Our approach identifies gaps in functional trait datasets for which phylogenetic imputation performs poorly, and will help ecologists to design more efficient trait collection campaigns by focusing resources on lineages whose trait values are more uncertain.     

Phylogenetic analyses of mode of larval development

Phylogenies based on morphological or molecular characters have been used to provide an evolutionary context for analysis of larval evolution. Studies of gastropods, bivalves, tunicates, sea stars, sea urchins, and polychaetes have revealed massive parallel evolution of similar larval forms. Some of these studies were designed to test, and have rejected, the species selection hypothesis for evolutionary trends in the frequency of derived larvae or life history traits. However, the lack of well supported models of larval character evolution leave some doubt about the quality of inferences of larval evolution from phylogenies of living taxa. Better models based on maximum likelihood methods and known prior probabilities of larval character state changes will improve our understanding of the history of larval evolution.     

Inferring speciation modes in a clade of Iberian chafers from rates of morphological evolution in different character systems

Background  

Studies of speciation mode based on phylogenies usually test the predicted effect on diversification patterns or on geographical distribution of closely related species. Here we outline an approach to infer the prevalent speciation mode in Iberian Hymenoplia chafers through the comparison of the evolutionary rates of morphological character systems likely to be related to sexual or ecological selection. Assuming that mitochondrial evolution is neutral and not related to measured phenotypic differences among the species, we contrast hypothetic outcomes of three speciation modes: 1) geographic isolation with subsequent random morphological divergence, resulting in overall change proportional to the mtDNA rate; 2) sexual selection on size and shape of the male intromittent organs, resulting in an evolutionary rate decoupled to that of the mtDNA; and 3) ecological segregation, reflected in character systems presumably related to ecological or biological adaptations, with rates decoupled from that of the mtDNA.     

Inferring evolutionary processes from phylogenies

Evolutionary processes shape the regular trends of evolution and are responsible for the diversity and distribution of contemporary species. They include correlated evolutionary change and trajectories of trait evolution, convergent and parallel evolution, differential rates of evolution, speciation and extinction, the order and direction of change in characters, and the nature of the evolutionary process itself—does change accumulate gradually, episodically, or in punctuational bursts. Phylogenies, in combination with information on species, contain the imprint of these historical evolutionary processes. By applying comparative methods based upon statistical models of evolution to well resolved phylogenies, it is possible to infer the historical evolutionary processes that must have existed in the past, given the patterns of diversity seen in the present. I describe a set of maximum likelihood statistical methods for inferring such processes. The methods estimate parameters of statistical models for inferring correlated evolutionary change in continuously varying characters, for detecting correlated evolution in discrete characters, for estimating rates of evolution, and for investigating the nature of the evolutionary process itself. They also anticipate the wealth of information becoming available to biological scientists from genetic studies that pin down relationships among organisms with unprecedented accuracy.     

Positive correlation between diversification rates and phenotypic evolvability can mimic punctuated equilibrium on molecular phylogenies

The hypothesis of punctuated equilibrium proposes that most phenotypic evolution occurs in rapid bursts associated with speciation events. Several methods have been developed that can infer punctuated equilibrium from molecular phylogenies in the absence of paleontological data. These methods essentially test whether the variance in phenotypes among extant species is better explained by evolutionary time since common ancestry or by the number of estimated speciation events separating taxa. However, apparent "punctuational" trait change can be recovered on molecular phylogenies if the rate of phenotypic evolution is correlated with the rate of speciation. Strong support for punctuational models can arise even if the underlying mode of trait evolution is strictly gradual, so long as rates of speciation and trait evolution covary across the branches of phylogenetic trees, and provided that lineages vary in their rate of speciation. Species selection for accelerated rates of ecological or phenotypic divergence can potentially lead to the perception that most trait divergence occurs in association with speciation events.     

Phylogenetic estimates of diversification rate are affected by molecular rate variation

Molecular phylogenies are increasingly being used to investigate the patterns and mechanisms of macroevolution. In particular, node heights in a phylogeny can be used to detect changes in rates of diversification over time. Such analyses rest on the assumption that node heights in a phylogeny represent the timing of diversification events, which in turn rests on the assumption that evolutionary time can be accurately predicted from DNA sequence divergence. But there are many influences on the rate of molecular evolution, which might also influence node heights in molecular phylogenies, and thus affect estimates of diversification rate. In particular, a growing number of studies have revealed an association between the net diversification rate estimated from phylogenies and the rate of molecular evolution. Such an association might, by influencing the relative position of node heights, systematically bias estimates of diversification time. We simulated the evolution of DNA sequences under several scenarios where rates of diversification and molecular evolution vary through time, including models where diversification and molecular evolutionary rates are linked. We show that commonly used methods, including metric‐based, likelihood and Bayesian approaches, can have a low power to identify changes in diversification rate when molecular substitution rates vary. Furthermore, the association between the rates of speciation and molecular evolution rate can cause the signature of a slowdown or speedup in speciation rates to be lost or misidentified. These results suggest that the multiple sources of variation in molecular evolutionary rates need to be considered when inferring macroevolutionary processes from phylogenies.