Evolution

Assortative mating for a trait under selection can increase the rate of adaptive evolution and limit introgression of detrimental alleles. We therefore hypothesized that assortative mating facilitated the rapid evolution of flowering phenology observed in the self-incompatible perennial Lythrum salicaria (purple loosestrife) as it invaded eastern North America. We characterized flowering schedules of 600 individuals representing 20 populations sampled along a latitudinal gradient of 10 degrees and grown in a common garden at mid-latitude. Consistent with our hypothesis, we found that flowering schedules were less synchronous in the mixed population of the common garden (s = 0.50) relative to the 20 locally adapted populations comprising it (s = 0.56 to 0.86), and flowering synchrony decreased towards higher latitudes of origin. Despite high synchrony, assortment potential ({rho}) by growth and phenology varied by population ({rho} = 0.03 to 0.61), but the predicted negative correlation between s and {rho} was masked by among-individual fitness variation in the common garden. We show how fitness variation and asynchrony associated with locally adapted phenology can reduce the fitness impacts of maladaptive gene flow and accelerate the rate of adaptive evolution during invasion.

Species interactions shape ecological dynamics, but adaptation to one interaction can trade off with others. Experiments that measure such evolved fitness changes across multiple interactions remain rare. We used experimental evolution to test whether recent selection under one ecological interaction changes fitness under other interactions in a fly-parasitoid system. We evolved a genetically diverse Drosophila melanogaster population for 15-17 generations under three regimes: benign conditions (control), high intraspecific competition, and infection by the parasitoid wasp Leptopilina boulardi. We then measured fly fitness (egg-to-adult survival and subsequent reproduction) under benign conditions, high intraspecific competition, and infection by three other parasitoid species and an additional conspecific L. boulardi strain. Selection history strongly influenced fitness across interactions. Populations maintained under high larval density showed reduced survival under infection by L. boulardi and L. victoriae, indicating a trade-off between past selection for competition and defence against some parasitoids. Populations evolved under parasitoid infection by L. boulardi showed increased resistance to a conspecific strain but reduced fitness when infected by another species, L. heterotoma. Our results show that rapid evolution in response to a single interaction can reshape multiple ecological interactions through fitness trade-offs, highlighting how recent evolutionary history may influence community dynamics and invasion susceptibility.

Dominance is an important and evolvable property of the genotype-phenotype map. A longstanding debate in evolutionary genetics concerns whether dominance is determined primarily by intrinsic properties of alleles at the focal locus or by modifiers elsewhere in the genome. Theoretical models show that second-site modifiers of dominance can evolve under some conditions. However, direct empirical tests of these models are rare because they require holding the focal heterozygous genotype constant while changing the rest of the genome. In the Drosophila montium species subgroup, female pigmentation is a Mendelian trait controlled by a single gene, POU domain motif 3 (pdm3), but the dominance relationships between pdm3 alleles differ among species. Using reciprocal introgressions among three closely related species, we compared females carrying the same Light/Dark pdm3 allele combinations in different homozygous or heterozygous genomic backgrounds and across different temperatures. In both species-pair comparisons, changing genomic background significantly altered the phenotype of identical pdm3 heterozygotes, demonstrating the existence of second-site modifiers of dominance. The effects of dominance modifiers depend on the particular pair of pdm3 alleles and on rearing temperature. These results show that dominance in this system is a genotype-by-genotype-by-environment trait, rather than a fixed attribute of individual alleles. The finding that second-site modifiers can alter dominance by reshaping reaction norms provides a developmental mechanism that links the evolution of dominance to phenotypic plasticity.

Populations that have detectable additive genetic variance for fitness (VA(W)) have the capacity for increase in their mean fitness through natural selection. The extent to which the magnitude of VA(W) in wild populations is predictive of the rate of adaptation is not well known, because few empirical field-based studies have been designed to address this question. Here, we report a two-year field experiment with pedigreed seeds embedded in four natural populations of the annual wildflower Baby Blue Eyes (Nemophila menziesii H. & A.), a species native to western North America. We first estimated VA(W) in a parental generation and then evaluated whether that estimate accurately predicted the adaptive response observed in the subsequent offspring generation grown under natural field conditions. We achieved this by directly comparing the mean fitnesses of the parental generation and their progeny grown under the same environmental conditions. We detected VA(W) and evidence of adaptation in all populations despite inter-annual differences in environmental conditions that directly affected fitness. Genotype-by-year interactions in fitness indicate that the fitness ranking of families differed between years, implying that the selective environment shifted over time. Additionally, although the environment in the second year reduced population mean fitness in three sites, the offspring generation maintained mean fitness at or above replacement, suggesting that adaptive evolution may have buffered the effects of environmental change. Overall, our results suggest that the four populations harbored sufficient VA(W) for adaptation through natural selection to the environmental conditions observed during the two years of this study.

Animal behaviour is both innately constrained and shaped by learning. This mosaic organization has evolved in response to species-specific ecological demands and may differ between sensory modalities. Flower-visiting animals are a particularly useful system for investigating the relationship between sensory ecology and learning because they rely on multiple floral cues, particularly odour and colour, to locate food sources. However, it remains largely unexplored whether specialization on floral resources entails divergence in learning abilities across sensory modalities. Drosophila elegans is a flower-feeding species that depends heavily on floral resources throughout its life; adults spend much of their time on flowers and larvae develop on fallen flower leaves. Here, we compared odour-reward and colour-reward associative learning between the flower-feeding D. elegans and the fruit-feeding D. melanogaster. We found that, under conditions of equilibrated motivation, odour- and colour-preference, and using the same sugar reward, D. elegans exhibited poorer odour-reward learning performance but better colour-reward learning performance than D. melanogaster. These results suggest that the modality-specific eligibility of sensory information to enter into associations, known as the 'Garcia-effect' in experimental psychology, can evolve oppositely between species. This highlights the relationship between ecological specialization and mnemonic processing, and shows that biological 'intelligence' is not general.

Statistical associations between two variables can arise via various causal mechanisms. For example, one variable may influence the other, or they may share common causes. Surprisingly little attention has been devoted to quantifying how such causal pathways contribute to the overall association between variables. Here, I present two methods for partitioning a covariance between variables X and Z into a causal component arising from the effect of X and Z and a spurious component arising via other pathways. Both methods rely on averaging causal decompositions over the distributions of the variables, but the decomposition and averaging are performed in different ways. The 'gradient' definition decomposes causal effects in the neighbourhood of naturally occurring values, making it relatively straightforward to estimate. It assumes that the cause variable X is normally distributed. In contrast, the 'two step' definition decomposes large ('step-wise') changes in values and makes no distributional assumptions. I describe applications of these methods to analysing natural selection and illustrate them using the covariance between body size and the number of eggs carried by pregnant male dusky pipefish, Syngnathus floridae. I partition this total covariance into a causal component due to the effect of body size on egg number and a spurious component arising from variation in body size and egg number among collection sites.

Trade-offs are commonly assumed when the statistical parameters used to define biological traits are negatively correlated. However, parameter correlations can emerge from the geometry of the model, rather than underlying biological signal. We characterize this phenomenon generally, and develop a framework to parse biological signal from statistical artifact in parameter correlations. Using the widely reported trade-off between thermal sensitivity and static upper critical thermal limit as a case study, we show that an extreme correlation between these parameters is expected even in the absence of a real trade-off. However, our method reveals that there is, in fact, a biological correlation underneath this spurious artifact. We confirm this finding, as independent genome-wide association analysis reveals genetic variation among trade-off phenotypes, but none corresponding to net thermal tolerance, suggesting that adaptive capacity to a warming climate may be severely limited. This particular trade-off is therefore biologically supported, illustrating how biological signal can be obscured by estimation artifact, thus evading correlation-based detection. We broaden our analysis, showing that artifact is present across biological systems and model types, although its manifestation may vary. Analytical results and simulations reveal how sampling design, model choice and parameterization govern the artifact, providing practical guidance for experimental planning. Our findings identify both a problem and a solution: correlations among model parameters cannot be interpreted biologically without first accounting for the structure imposed by the model and data, but genuine biological relationships can still be recovered when that structure is explicitly modeled.

Understanding how specialized herbivores track divergence among their hosts is central to evolutionary biology. Congruent genetic structure between hosts and herbivores is often interpreted as evidence of long-term codivergence, but similar patterns may also arise when herbivores rapidly adapt to pre-existing host differentiation. Here, we integrate population genomics, host volatile profiling, and behavioral assays to examine host-associated divergence in the obligate seed-feeding wasp Megastigmus daduheensis and its conifer host Cupressus chengiana across three river valleys on the eastern Qinghai-Tibet Plateau. Despite strong phylogeographic congruence between each of the three wasp and host lineages, calibrated demographic analyses indicate that wasp divergence occurred during the early Holocene, substantially later than the Pliocene-Pleistocene divergence of host lineages. This temporal mismatch is inconsistent with strict long-term codivergence and instead supports rapid host tracking in a topographic complex region. Host lineages differed in volatile organic compound profiles, and behavioral assays showed that wasps were preferentially attracted to volatiles from their local host lineages. These results identify olfactory-mediated host recognition as a plausible mechanism promoting host fidelity and reinforcing host-associated genomic and behavioral differentiation. Our findings show that apparently concordant host-herbivore divergence can emerge over compressed evolutionary timescales through rapid local adaptation, highlighting how ecological differentiation can accumulate within species through host tracking.

Male and female animals often differ remarkably in their reproductive behaviours, typified by competing males and caring females. One influential explanation traces sex-role divergence to anisogamy: sex differences in gamete size. This explanation remains controversial, because existing models have not fully resolved how anisogamy leads to secondary sex-role divergence, and exceptions to typical patterns are empirically well-documented. Here, we develop mathematical models linking anisogamy to secondary sex-role evolution, showing that anisogamy drives sex-role divergence along contrasting evolutionary trajectories depending on ecological context. When the sexes differ only in gamete size, male-biased mating competition and offspring care evolve under scramble competition, whereas uncertain paternity shifts the population towards typical patterns. By contrast, anisogamy generally drives typical sex roles under contest competition, although sex-role reversal can emerge as an alternative stable state when care must be apportioned among offspring. Anisogamy can thus explain the striking diversity of sex differences across taxa.

The repeated evolution of similar phenotypes in response to shared ecological pressures provides striking examples of natural selection and raises broader questions about the predictability of evolution. Evolutionary constraint may shape this predictability, while the apparent extent of parallelism may also depend on the biological scale at which it is measured. When are adaptive solutions channeled along the same route? We addressed this question using three sympatric benthic-limnetic ecotype pairs of threespine stickleback (Gasterosteus aculeatus), characterizing gene expression in gill and liver from wild-caught fish. We tested whether proxies of pleiotropic and coding-sequence constraint predicted the repeatability of transcriptional divergence across lakes. At the gene level, differential expression was strongly biased toward parallel rather than antiparallel responses. At the functional level, numerous pathways showed parallel enrichment, but the conservation of their underlying member-gene responses varied substantially, indicating that similar functional outcomes can arise with differing degrees of gene-level concordance. Most importantly, several proxies of evolutionary constraint predicted transcriptional repeatability, particularly in gill: broadly expressed, highly connected, and more slowly evolving genes showed more stable expression responses across lakes, with similar relationships evident for repeated use of genes within functionally parallel pathways. Together, these results show that both gene-level constraint and biological scale contribute to variation in molecular repeatability and suggest that the predictability of repeated adaptation may reflect an interaction between genetic architecture, population-genetic context, and the level of biological organization at which parallelism emerges.

Evolution in fluctuating environments depends critically on epistatic interactions between mutations and the pleiotropic effects these mutations have on fitness across multiple conditions. However, while these effects of epistasis and pleiotropy have been extensively studied individually, the interactions between them are less well understood. In this study, we analyze how genetic background shapes the effects of mutations across multiple environmental conditions in generic models of complex traits. We show that when epistasis is widespread and random, systematic patterns of cross-environment pleiotropy can emerge naturally. Specifically we outline two regimes, widespread random epistasis (WRE) and structured pleiotropy (SP), in which patterns of global epistasis in one environment can be predicted from those in other conditions. We outline these predictions in several classes of generic null models, and test these predictions in laboratory budding yeast by measuring the fitness effects of a large set of mutations across many genetic backgrounds in several growth environments. We find that only a subset of mutations fall within the WRE and SP regimes, but that in these cases two of our models provide accurate fits to the data. Finally, we use this framework to show how modular, pleiotropic architectures shape long-term evolutionary steady states in fluctuating environments, revealing how tradeoffs between environments can develop from the geometry of shared latent interaction structure.

Many pathogenic and microbial species undergo complex life cycles wherein they experience drastic bottlenecks during invasion into a host and rapid growth within hosts. The effects of such a complex population history on patterns of genetic variation is not currently understood. We model a pathogen population as a metapopulation where each deme represents a host and incorporate transmission dynamics as well as the effects of transmission bottlenecks. We employ a coalescent framework, obtaining analytical expressions for pairwise times to coalescence and genetic differentiation within and between hosts. We find that recurrent bottlenecks rescale the coalescent process within hosts to the size of the bottleneck, reducing within-host variation. In addition, the pairwise distribution of time to coalescence under our model deviates substantially from the Wright-Fisher process when the number of hosts (d) is of similar order to the size of the bottleneck (k), i.e., k [~] d and when m <<1/(2k) +1/(2d), where m is the migration rate. Otherwise, the pairwise process under our model converges in distribution to the Wright-Fisher process. Coalescent simulations show that under the same conditions the site frequency spectrum (SFS) under our model deviates from that under the Kingman coalescent and is drastically skewed towards singletons. Our results suggest that the inference of selection or demographic history from pathogen population genetics data may be systematically biased by the mechanics of pathogen reproduction, indicating a need for further theoretical work that can inform inference.

Evolutionary rescue occurs when genetic adaptation prevents extinction of a declining population. Mutation and recombination generate adaptive variation, but when their rates at adaptive loci are too low, rescue may require evolution toward higher rates of genetic change. Here, we derive and compare analytical approximations for the probability of rescue through two alternative routes: mutation-rate and recombination-rate evolution. Our model comprises two resident genotypes from which the same adaptive haplotype can arise along either route, with rescue requiring the appearance of an unlinked modifier allele that increases mutation at, or recombination between, two fitness-determining loci. We show that resident genotype composition determines the relative success of the two routes. Mutation-rate evolution yields a higher rescue probability when one resident genotype is sufficiently more common because mutation can act on either genotype whereas recombination requires both. Otherwise, the two routes yield similar rescue probabilities. Even when either route makes rescue appreciably likely, however, the modifier alleles facilitating rescue are often lost before rescue is complete. This loss is driven by multiple factors: segregation can separate the modifier from the adaptive haplotype; the fitness cost of modifier expression raises extinction risk for modifier-bearing lineages; and continued modifier-induced mutation disrupts the adaptive haplotype after it forms. The latter effect can make recombination-rate modifiers more likely to persist even when mutation-rate evolution yields a higher rescue probability. Overall, these results show that both mutation- and recombination-rate evolution can induce rescue, but successful rescue need not entail persistence of the modifier allele that facilitated it.

Genotype-environment association (GEA) approaches identify genetic variants that likely contribute to adaptation along environmental gradients. These associations can inform predictive models of maladaptation risk and evolutionary rescue in future climates. However, because population structure and climate parameters often co-vary, tradeoffs arise between accounting for population structure to reduce false positive associations and removing true positives. Here, we examine whether conducting GEA analyses at multiple spatial scales provides more informative associations by mitigating confounds between population structure and environment, and we evaluate what factors influence how congruent GEA results are across regions. We performed GEA analyses for climate parameters on genome resequencing data obtained for 110 annual populations of the common monkeyflower, Mimulus guttatus. We find that more genetic variation was specifically attributable to environmental variation in regional GEA models compared to a full-range model, and that agents of selection differ considerably in importance among regions and range-wide. Few genetic targets of selection shared across regions were detected, yet all regions possess ample standing genetic variation for most environment-associated variants, suggesting that regional differences in climate breadth may be a primary cause of this incongruence. In combination with a genome-wide association study for several climate-associated phenotypes, we also find that regulators of flowering repressors in the FLC/MAF gene family often harbor adaptive variation in this species. Together, our results suggest that GEA analyses of widespread species considerably benefit from examining both range-wide and regional trends to more fully capture and understand the agents and targets of climate adaptation.

Artificial light at night (ALAN) disrupts the natural light-dark cycle, which is the most important cue for synchronizing circadian clocks. If populations most exposed to ALAN adapt to get less disturbed by it, we expect forest and city populations to differ genetically. We tested this prediction in a common garden experiment using a songbird, the great tit (Parus major), originating from forest and city populations. We simulated ALAN exposure during the breeding season by keeping the birds in pairs under ALAN or dark nights for three months and then repeated the experiment in the following year with the same pairs under the opposite treatment. The advancement of daily onset under ALAN disappeared over time for city birds, but not for their forest counterparts. For these same birds, we measured their onset of daily activity under constant dim light and shift in activity in response to light pulses and showed that the city/forest difference in behavioural response was not reflected in any clock property measured. This indicates that city and forest birds differ genetically in the downstream behavioural response to ALAN, and not in the circadian clock. Thus, urbanization is unlikely to select for divergence in circadian clock properties in songbirds.

Flowering plants vary in sex allocation (resource division between male and female function) and in selfing rate. These traits should evolve together: selfing changes fitness returns from pollen and ovules, whereas sex allocation changes the pollen available for selfing and export. Yet most models allow only one trait to evolve, leaving their evolutionary feedback unresolved. Here we model the joint evolution of sex allocation, pollen export and maternal control of competition between self- and cross-pollen. We show that selfing and sex allocation strongly influence one another, as selection favours associations between sex allocation and mating-system traits. When maternal control is fixed to recover classical mass-action, evolution can lead to the stable coexistence of selfing hermaphrodites and males specialised in pollen export. This androdioecy persists because hermaphrodites cannot prevent fertilisation by males. When maternal control of pollen competition also evolves, we find that where a mixed-mating equilibrium exists, selection again favours the emergence of androdioecy. As hermaphrodites evolve to favour their own pollen, however, they progressively exclude pollen from males, driving them extinct. The population may then return to mixed mating and repeat the process, or evolve complete selfing. We discuss these results with reference to known variation in the mating and sexual systems of plants.

The Yampolsky-Stoltzfus (YS) model provided the first formal demonstration that a bias in the introduction of new mutations can shape the direction of adaptive evolution, even when mutation rates are small relative to selection coefficients. Despite its foundational role, the model has been characterized almost entirely by simulation and closed-form solutions for its central quantity, the probability PA that a mutationally favored but less-fit genotype fixes ahead of a rarer, fitter alternative, have been available only in the limiting regimes of vanishing mutation supply and infinite population size. Here we derive closed-form approximations for PA across the intermediate regime of finite population size and appreciable mutation supply that lies between these two limits. Under strong selection between the competing mutants, we combine an establishment-probability argument with clonal interference theory to obtain an explicit expression for PA that accounts for both the ongoing input of the mutationally favored mutation and the frequency-dependent establishment probability of its competitor. Under weak selection between competing mutants, we derive a complementary expression based on the fixation of a mixed population under Kimura's classical formula. Both expressions agree closely with direct simulation of the underlying Wright-Fisher process, recover the known limiting cases, and remain consistent with one another over a substantial intermediate range of parameters. These results are expected to provide a basis for assessing how the strength of mutation bias affects adaptation in empirical data.

Haldane's principle relates equilibrium mutation load to deleterious mutational input rather than to selection strength. We study this balance in a homeostatically regulated, damage-structured population where mutation occurs during reproduction, repair restores individuals toward lower-damage states, and nonlinear demographic feedback maintains constant population size. An exact demographic identity shows that load at every time equals excess reproductive effort weighted by mean relative fecundity. Without repair, the equilibrium branch with positive pristine-class frequency is exactly solvable, and along it the load is exactly the mutation probability times the realized per-capita reproductive turnover rate; when the terminal cap is removed, this is precisely the realized deleterious input, for every mutation probability below one. For rare mutation it reduces to the mutation probability times the pristine turnover rate, with the local fitness contrast canceling at leading order. With a finite terminal class the branch instead reaches a closure-dependent boundary collision. Repair modifies the rare-mutation balance by partitioning first-order removal from the first damaged class between selection and restoration, multiplying the leading load by the selective share of that removal. An exact binary solution extends these results to finite mutation pressure: the unrepaired interior equilibrium collides nonhyperbolically with the fully damaged boundary and converges algebraically at the threshold, whereas any positive repair rate restores a unique interior equilibrium for positive mutation; at the no-repair threshold, its displacement from the boundary scales as the square root of the repair rate as repair vanishes. These results separate the familiar competing-transition structure of mutation--selection balance from the specifically homeostatic effects of turnover-dependent mutation input and nonlinear demographic feedback.

How natural populations maintain genetic variation for fitness remains a central problem in evolutionary biology. Theory predicts that opposing selective pressures across environments can preserve fitness-associated polymorphism, but how interactions among species contribute to this process remains poorly understood. Here we show that host diversity preserves standing genetic variation within sexual populations of the leafmining fly Scaptomyza flava. We evolved twelve populations for ten generations on either of two naturally co-occurring host plants or on both, pooling survivors from the two hosts before mating. Single-host populations evolved reciprocal fitness trade-offs, whereas two-host populations maintained relatively even performance across hosts. Whole-genome time series dynamics identified a linked region in which alleles increased on one host and decreased on the other, while showing little net change under two-host conditions. Wild flies reared from the two hosts showed corresponding allele-frequency differences within this region. Across the genome, two-host populations retained more rare variants than populations evolving on either host alone. These findings show that selection imposed by different host species in sympatry can maintain standing genetic diversity within an herbivore population.

Global warming will impact natural selection on plant traits and their plasticity by influencing phenotypes, biotic interactions, and fitness. Because warming affects biotic interactions, community composition may influence how warming affects selection on plants, but this is little studied. We grew full-sibling pairs of Brassica rapa plants in an ambient and hot temperature environment and exposed them to visitation by a pollinator (Bombus terrestris), a pollinating herbivore (Pieris rapae), or their combination. We recorded plant phenotypes, insect visitation, herbivory, and plant fitness. We used these to calculated phenotypic selection on plant traits and their plasticity, including additive and nonadditive effects. Elevated temperature changed selection on traits related to pollinator attraction, such as flower number, nectar production, and floral scent emission. We found both positive and negative selection on temperature-mediated trait plasticity depending on the biotic treatment. Elevated temperature changed patterns of additive and non-additive selection on a variety of traits including flower morphology and scent. This study shows that elevated temperatures can reshape patterns of phenotypic selection, including nonadditive effects, and plastic trait expression. Effects of elevated temperature on phenotypic selection depended on the biotic interactors, highlighting the importance of community context for the effects of warming on natural selection.