The problem of mediocre generalists: population genetics and eco-evolutionary perspectives on host breadth evolution in pathogens.

OF THE DISSERTATION In order to predict how species will respond to global climate change, scientists must understand the relationships between traits, fitness, environments and distributions. Niche theory provides a useful framework. Niche breadth describes the range of environmental conditions necessary for population growth. Among these conditions, climate is especially important. Climate niche breadth in turn may reflect a confluence of different forces. This dissertation presents a series of projects that assess the relative roles of historical, geographic and population processes that contribute to climate niche breadth in temperate plants. The first project evaluates the predictive power of a classical hypothesis. If gene flow slows divergent adaptation, then range fragmentation should promote niche breadth. By quantifying the relationships between environmental difference, geographic distance and genetic isolation among European plants, I show that the effect of allopatry on niche breadth depends on the role of the geographic distance among populations. The remaining projects focus in increasingly finer detail on the evolution of niche breadth in a taxonomically complex group. Dodecatheon sect. Dodecatheon grow in diverse habitats across North America. They have confounded taxonomists with polyploidy, hybridization and convergent adaptation. Currently recognized species are either widespread or rare microclimate specialists. First, with multilocus phylogenetics, I show that the difference in niche breadth among rare and widespread species is not simply due to differences in environmental tolerance. In eastern North America, geographic heterogeneity and paleoclimate history strongly contribute to taxonomic rarity. The next project focuses on this group. Both rare eastern species are considered

Several theoretical studies of niche breadth evolution have shown that niche breadth expansion can only occur under a limited set of conditions. These studies have assumed that mating pairs form at random within spatial subpopulations. I show here that nonrandom mating within spatial subpopulations can greatly alter niche breadth evolution. Niche breadth expansion is restricted by assortative mating but is permitted by sexual selection. When new populations are formed by a single pulse of immigrants, the ability to persist in novel but similar environments is enhanced by sexual selection. When new populations receive a constant stream of immigrants, sexual selection allows the evolution of increased niche breadth even when the novel environment is very different from the ancestral environment. These results suggest that species lineages that exhibit sexual selection will have broader niches than species lineages that mate randomly or assortatively.

Macroevolutionary and microevolutionary studies provide complementary explanations of the processes shaping the evolution of niche breadth. Macroevolutionary approaches scrutinize factors such as the temporal and spatial environmental heterogeneities that drive differentiation among species. Microevolutionary studies, in contrast, focus on the processes that affect intraspecific variability. We combine these perspectives by using macroevolutionary models in a comparative study of intraspecific variability. We address potential differences in rates of evolution of niche breadth and position in annual and perennial plants of the Eriogonoideae subfamily of the Polygonaceae. We anticipated higher rates of evolution in annuals than in perennials owing to differences in generation time that are paralleled by rates of molecular evolution. Instead, we found that perennial eriogonoid species present greater environmental tolerance (wider climate niche) than annual species. Niche breadth of perennial species has evolved two to four times faster than in annuals, while niche optimum has diversified more rapidly among annual species than among perennials. Niche breadth and average elevation of species are correlated. Moreover, niche breadth increases more rapidly with mean species elevation in perennials than in annuals. Our results suggest that both environmental gradients and life-history strategy influence rates and patterns of niche breadth evolution.

Bacteria exhibit varying niche breadths, with generalists thriving in diverse environments and specialists confined to specific habitats. Although genes for cooperative traits have been suggested to influence niche breadth evolution, their precise role remains unclear. We used a combination of phylogeny-based comparative methods to test causal hypotheses about the directionality of the relationship between genes for cooperation and bacterial niche breadth evolution across 25,785 species. Our results revealed 1) a positive correlation between the proportion of genes for cooperation and niche breadth; 2) genes for cooperation influenced niche breadth evolution, with a decreased proportion of such genes promoting niche contraction as the predominant evolutionary direction; and 3) genes for cooperation experience more frequent gain and loss within species rather than across species. These findings suggest a role of bacterial cooperation in influencing niche breadth evolution and maintaining the ecological versatility of bacteria. While our results are consistent with a simple relationship under the hypotheses tested, more complex causal scenarios are possible, including the role of factors that influence both cooperation and niche breadth.

Ecologists have long studied the evolution of niche breadth, including how variability in environments can drive the evolution of specialism and generalism. This concept is of particular interest in viruses, where niche breadth evolution may explain viral disease emergence, or underlie the potential for therapeutic measures like phage therapy. Despite the significance and potential applications of virus–host interactions, the genetic determinants of niche breadth evolution remain underexplored in many bacteriophages. In this study, we present the results of an evolution experiment with a model bacteriophage system, Escherichia virus T4, in several host environments: exposure to Escherichia coli C, exposure to E. coli K‐12, and exposure to both E. coli C and E. coli K‐12. This experimental framework allowed us to investigate the phenotypic and molecular manifestations of niche breadth evolution. First, we show that selection on different hosts led to measurable changes in phage productivity in all experimental populations. Second, whole—genome sequencing of experimental populations revealed signatures of selection. Finally, clear and consistent patterns emerged across the host environments, especially the presence of new mutations in phage structural genes—genes encoding proteins that provide morphological and biophysical integrity to a virus. A comparison of mutations found across functional gene categories revealed that structural genes acquired significantly more mutations than other categories. Our findings suggest that structural genes are central determinants in bacteriophage niche breadth.

Several theoretical studies of niche breadth evolution have shown that niche breadth expansion can only occur under a limited set of conditions. These studies have assumed that mating pairs form at random within spatial subpopulations. I show here that nonrandom mating within spatial subpopulations can greatly alter niche breadth evolution. Niche breadth expansion is restricted by assortative mating but is permitted by sexual selection. When new populations are formed by a single pulse of immigrants, the ability to persist in novel but similar environments is enhanced by sexual selection. When new populations receive a constant stream of immigrants, sexual selection allows the evolution of increased niche breadth even when the novel environment is very different from the ancestral environment. These results suggest that species lineages that exhibit sexual selection will have broader niches than species lineages that mate randomly or assortatively.

P opulation genetics relies heavily on mathematical modeling to make quantitative predictions about the behavior of genes in populations. These models are based on the principles of classic Mendelian gene inheritance; the Hardy-Weinberg equilibrium law, which predicts the gene frequency in a population; and Darwin's theory of natural selection. PopGene version 1 is a simulation program that explores the parameters that affect the behavior of alternative forms of a gene (alleles) in a population. The program window is composed of three smaller windows specifying the parameters used, the calculated allele frequencies through each generation, and the graphical output of the calculations. PopGene provides simulations for both basic and more advanced models in population genetics. The simplest model demonstrates the principles of the Hardy-Weinberg equilibrium law for the case of a single gene with two alleles. Increasingly complex examples based on the assumptions of the Hardy-Weinberg equilibrium law demonstrate the effect of multiple alleles of a gene and multiple gene loci on the genotype of all the individuals in a population. Default parameters for each model are built into the program, but users may also enter their own values. The simulation results, parameters, and graphs may be saved or printed. Up to 15 simulations may be run for a particular model with the results plotted on a single graph for easy comparison. Natural selection and inbreeding can be studied with the program. Natural selection of a gene with two alleles occurs when the fitness of each genotype is not equal. The program permits users to examine the outcomes of several scenarios—selection of an allele that exhibits dominance over another, alleles that combine to produce an intermediate (semidominant) phenotype, an allele that is recessive to another, or selection against a recessive allele because of its lethality. The model for inbreeding explores the consequence of nonrandom mating between individuals on the genotype frequencies of that population. Mating pairings are included to demonstrate self-fertilization (the most extreme form of nonrandom mating), as well as matings between parent and offspring; matings between siblings, first cousins, and second cousins; and random mating. PopGene also provides simulations for genetic drift, mutation, and migration—factors that contribute to evolutionary changes in a population that have long-term effects and are more difficult to study. In summary, PopGene is a valuable tool to use in conjunction with traditional textbook-based teaching of an introductory population genetics course. It provides students with illustrations of the principles they have learned. The program is straightforward, easy to use, and is available for Macintosh and Windows platforms. No preprinted manual is available for PopGene; however, a concise and well-written one is supplied as a PDF file that is readable with Adobe Acrobat. It covers the specifics of using the program and provides a step-by-step tutorial. A brief summary of population genetics, mathematical modeling, and the value and limitations of computer simulations is also discussed. The system requires a PC with a 486 or Pentium processor that uses Windows 3.1, 95, 98, or NT with 8 MB RAM or any Macintosh with 4 MB RAM, a 1.4-MB disk drive, and a hard drive. PopGene Trinity Software, Inc. Plymouth, NH. $95.00; $39.95, college students. 800-352-1282

Infectious disease dynamics result from the complex interplay of epidemiological, ecological and evolutionary (epi-eco-evo) processes. Accurately modelling these coupled processes is crucial for understanding pathogen spread and informing public health strategies. However, existing genomic epidemiology simulators typically assume conditional independence among these processes: generating transmission trees independently of pathogen evolution, and then superimposing neutral mutations onto fixed genealogies without ecological feedback. This simplification fails to capture how pathogen evolution dynamically reshapes epidemic trajectories.We introduce e3SIM, an open-source, agent-based, forward-time simulator for macOS and Linux that explicitly integrates pathogen transmission dynamics, molecular evolution and environmental factors. e3SIM incorporates configurable compartmental models, user-defined host contact networks, customizable pathogen genetic architectures and optional eco-evolutionary features (e.g. within-host dynamics, multi-strain infections). This integration enables realistic modelling of pathogen spread and evolution. Key features include modularity, flexible epidemiological and population-genetic modelling, time-varying environmental factors and a user-friendly graphical interface.We demonstrated e3SIM’s capabilities by simulating SARS-CoV-2 and Mycobacterium tuberculosis outbreaks. e3SIM captured the emergence and spread of drug-resistant variants under sequential treatments, highlighting how pathogen evolution and environmental variations dynamically reshape epidemic trajectories. We also illustrated how interactions between pathogen transmissibility and host population structures, particularly those involving socially active “superspreaders”, strongly influence pathogen lineage expansion and transmission clusters. Runtime profiling demonstrated computational efficiency and scalability.e3SIM provides a powerful tool for simulating infectious disease dynamics through the explicit integration of epi-eco-evo processes, substantially enhancing realism and predictive accuracy in genomic epidemiology. Its modular, user-friendly design supports broad applications across diverse host-pathogen systems, enabling rigorous exploration of scenarios critical to public health.

Hardy–Weinberg Law

In this chapter, I elaborate the population genetics perspective introduced in chapter 1 and adopted in the subsequent chapters. I submit more justification here for the position that there are indeed heuristic advantages in approaching language evolution on the model of population genetics, assuming that a language is a species but not an organism. However, I also argue that the linguistic species need not be a clone of any biological species, despite the fact that it shares several properties with the parasitic species. In fact, the proposed population genetics of language evolution is more than an analog of population genetics, although its heuristics has been very much inspired by the latter. A linguistic species must be defined on its own independent terms and its evolutionary properties hypothesized according to its own combination of ontological characteristics. These account for both the similarities and differences which it displays with its closest kin in biological evolution. The basic assumption is that there are general evolutionary principles which apply similarly to the linguistic and biological species. However, there are species-specific principles which distinguish them from each other, based in part on whether a species is of the Darwinian or Lamarckian kind, on whether traits are transmitted sexually or asexually, horizontally and/or vertically, on whether the default quality of copying in trait inheritance is with or without modification, etc. One cluster of factors that plays an important role in any theory of evolution is “ecology.”

Let $\{X_n\}$ be a Markov chain on a bounded set in $R^d$ with $E_x(X_1) = f_N(x) = x + \beta_N h_N(x)$, where $x_0$ is a stable fixed point of $f_N(x) = x$, and $\operatorname{Cov}_x(X_1) \approx \sigma^2(x)/N$ in various senses. Let $D$ be an open set containing $x_0$, and assume $h_N(x) \rightarrow h(x)$ uniformly in $D$ and either $\beta_N \equiv 1$ or $\beta_N \rightarrow 0, \beta_N \gg \sqrt{\log N/N}$. Then, assuming various regularity conditions and $X_0 \in D$, the time the process takes to exit from $D$ is logarithmically equivalent in probability to $e^{VN\beta_N}$, where $V > 0$ is the solution of a variational problem of Freidlin-Wentzell type $\lbrack \text{if} \beta_N \rightarrow 0 \text{and} d = 1, V = \inf\{2 \int^y_{x_0}\sigma^{-2}(u)|h(u) du|: y \in \partial D\} \rbrack$. These results apply to the Wright-Fisher model in population genetics, where $\{X_n\}$ represent gene frequencies and the average effect of forces such as selection and mutation are much stronger than effects due to finite population size.

This paper considers a semilinear elliptic equation which arises in a selection-migration model in population genetics, involving two alleles $A_1$ and $A_2$ such that $A_1$ is at an advantage over $A_2$ in certain subregions and at a disadvantage in others. The system is studied on all of $R^n$ and is assumed to possess radial symmetry. Existence and asymptotic properties of solutions of the corresponding ordinary differential equation are investigated and, by using shooting method type arguments, results are obtained on the bifurcation of solutions from the trivial solutions corresponding to the cases where $A_1$ or $A_2$ is extinct. The nature of the results obtained varies according to whether $A_1$ or $A_2$ has an overall advantage.

The evolutionary dynamics of quantitative traits in a species depends on demographic structure (e.g. age‐ and size‐dependent vital rates, migration across subpopulations, mate preferences, and the presence or absence of overlapping generations), which in turn can depend on interspecific interactions with other evolving species. Furthermore, biologists increasingly appreciate that evolutionary change in a single species can substantively affect broader ecological processes, such as community assembly and ecosystem functioning. Models integrating insights from classical population and quantitative genetics, on the one hand, and community ecology theory, on the other, are therefore critical to elucidating the interplay between ecological and evolutionary processes. However, few modelling approaches integrate ecological and genetic details into a comprehensive framework. Such models are needed to account for the reciprocal feedback between evolutionary change and ecological dynamics, and develop effective responses to anthropogenic disturbances on natural communities, improve agricultural practices and manage global health risks such as emerging pathogens. Here we introduce an open‐source, multi‐species forward‐time population genetics simulator and framework for rapidly simulating eco‐evolutionary dynamics. Our approach permits building models that can account for alternative genetic architectures, non‐standard population dynamics and demographic structures, including those driven by interspecific interactions with other evolving species and the spatial dynamics of metacommunities. By integrating these processes into a common framework, we aim to facilitate the development of models that can further elucidate eco‐evolutionary dynamics. While multi‐species, forward‐time population genetic models can be computationally expensive, we show how our framework leverages relatively economical graphics cards installed in modern desktops. We illustrate the versatility and general applicability of our approach for two very different case studies: antagonistic coevolution in space, and the evolution of life‐history traits in response to resource dynamics in physiologically structured populations. We find that our analyses can run up to c. 200 times faster on a single commodity graphics card than on a single CPU core, comparable to the performance gains on small‐to‐medium sized computer clusters. Our approach therefore substantively reduces implementation difficulties to integrating ecological and evolutionary theory.

A general exchangeable model is introduced to study gene survival in populations whose size changes without density dependence. Necessary and sufficient conditions for the occurrence of fixation (that is the proportion of one of the types tending to 1 with probability 1) are obtained. These are then applied to the Wright–Fisher model, the Moran model, and conditioned branching-process models. For the Wright–Fisher model it is shown that certain fixation is equivalent to certain extinction of one of the types, but that this is not the case for the Moran model.

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