Biology subjects

MacPherson, A.

Publications and source records attributed to MacPherson, A..

16 recordsLinked to original sources

bioRxiv2026

Cyclic pathogen epidemics favour the evolution of delayed germination

Delayed germination is classically explained as a bet-hedging strategy against environmental variability: by withholding a fraction of seeds from germination, plants spread establishment risk across years that vary in temperature, precipitation, and other conditions governing seedling survival. Whether biotic interactions can generate analogous selective pressure has received comparatively little theoretical attention. Here we examine the evolution of germination timing in a host-pathogen model in which a saturating (Holling Type II) transmission function couples seed bank dynamics to epidemic cycles. The model produces three qualitatively distinct ecological regimes: a pathogen-free equilibrium, a stable endemic equilibrium, and an oscillatory endemic regime arising through a bifurcation, a transition from stable to oscillatory endemic dynamics. Using adaptive dynamics, namely invasion analysis, we show that the evolutionarily stable germination rate depends critically on which regime the resident population occupies. When pathogen dynamics settle to an equilibrium, selection favours ever-faster germination with no finite optimum, regardless of pathogen presence. When dynamics are limit cycles, periodic epidemic peaks create recurrent windows of high establishment mortality that function as biotic analogues of abiotic interactions (environmental), and selection drives the germination rate toward the bifurcation boundary. The evolutionary attractor thus coincides with an ecological bifurcation point. Trait substitution sequence simulations confirm convergence to this attractor, and multi-trait eco-evolutionary simulations provide evidence that the attractor is evolutionarily stable, consistent with a continuously stable strategy (CSS).These results extend classical bet-hedging theory to biotic drivers and suggest that pathogens capable of sustaining population cycles may be an underappreciated selective force on germination timing and, more broadly, on the pace of life-history evolution.

evolutionary biology↗

bioRxiv2026

An ecological model of masting reproduction matches empirical dynamics

Masting, characterized by highly variable, synchronized, and intermittent seed or fruit production, represents a common reproductive strategy among perennial plants and has profound ecological consequences. Resource provisioning and pollen limitation have long been viewed as central physiological mechanisms underlying this strategy, recent empirical evidence also highlights the role of weather cues in initiating and synchronizing reproductive effort. Drawing on mechanisms that drive periodicity in disease dynamics, this study proposes an alternative proximate mechanism for masting. We develop and analyze a stage-structured population growth model in which developmental delays create population-level cycles, and demographic stochasticity adds individual-level variation; together, yielding masting-like patterns. We compare the behaviour of this novel model with that of the widely used resource budget model and empirically observed patterns of masting in perennial plants. To quantify and compare model outputs and empirical observations, we employ three continuous metrics of masting that capture volatility, synchrony, and periodicity. Our study provides an alternative proximate mechanism for masting. Comparison of this novel mechanism and the established resource-budget model to empirical time-series reveals that both represent realistic yet distinct forms of masting reproduction. Together, these models provide a foundation for further exploration of the conditions under which this reproductive strategy can evolve. Beyond masting, our results highlight the general importance of life-history timing and demographic stochasticity in shaping population ecology.

ecology↗

bioRxiv2026

Repeatability of adaptation in interacting species

In many evolving systems, mutations have background-dependent fitness effects due to genetic interactions between loci within a genome (intragenomic epistasis). In coevolving species, genetic interactions can span across genomes, which has been described as intergenomic epistasis. It is known that intragenomic epistasis can make adaptation more repeatable by constraining accessible mutational paths from a specific starting genotype, generating path repeatability. Here, we investigate how endpoint repeatability, how often adaptation from different starting genotypes reaches the same states in the genotype and fitness space, is influenced by the interplay of intra- and intergenomic epistasis. To this end, we model a two-species community in which the fitness of each depends on the combination of genotypes in both species. We implement this system by constructing and simulating adaptation on coevolutionary fitness landscapes using an NKC(S) model, an extension of Kauffmans NK model of evolution that includes genetic interactions between loci across species. On these fitness landscapes, we simulate adaptive walks that alternate between mutation in a focal and a partner species. To quantify the repeatability of adaptation, we track the endpoints of adaptive walks and record the fitness of both species at the evolutionary endpoints. We find that intergenomic epistasis causes high endpoint repeatability within a given landscape but highly varying fitness outcomes across different coevolutionary landscapes. Thus, patterns of repeatability deviate from expectations based on single-species adaptation in the presence of intragenomic epistasis due to varying fitness trade-offs between species, which can lead to cycling and large coevolutionary fitness loads.

evolutionary biology↗

bioRxiv2025

From Field to FASTA: Onsite DNA Barcoding the Mushrooms of the 2024 NAMA Foray

Mushroom forays present unparalleled opportunities to record macrofungal biodiversity in a place and time. The 2024 NAMA annual foray at the Cispus Center near Randle, Washington was the first mass barcoding activity performed by the NAMA DNA Sequencing Committee (DNAMA). The workflows and methods utilized are presented along with planned improvements. Ultimately, 803 ITS barcodes were generated (83.7% of those attempted) for 513 unique taxa belonging to 209 Genera. Of these, 18 novel putative species-level operational taxonomic units (OTUs) were discovered as well as 28 new distribution reports at state level or above. Methods and suggestions for replicating and improving mass barcoding at forays are discussed.

genetics↗

bioRxiv2025

Sampling Aware Ancestral State Inference

In phylogeography, ancestral state inference methods are used to identify the geographic or host species origin of viral or bacterial lineages and reconstruct their transmission histories over time. However, differences in sampling among states can bias these inference methods. We introduce sampling-aware ancestral state inference (SAASI), a method that accounts for sampling differences. Here, we apply SAASI to the multi-host spread of the H5N1 virus in the United States in 2024 and find that the key transmission event from wild birds to cattle is estimated to occur later under lower sampling in wild birds (compared to other species) than when sampling is not accounted for. Using simulation, we find that SAASI infers past viral locations/host species considerably more accurately than standard methods when sampling bias exists, is computationally feasible for large datasets and scales to trees with 100,000 tips.

evolutionary biology↗

bioRxiv2025

Local Adaptation of Life-History Traits in a Seasonal Environment

Populations are often spread across a spatially heterogeneous landscape, connected by migration. Consequently, the question arises whether divergent selective forces created by spatial heterogeneity can overcome the homogenising force of migration and loss of diversity through genetic drift to favour different traits across space. Such spatial heterogeneity in the population due to divergent selection is known as local adaptation. While local adaptation has been studied in a variety of settings, it remains unclear whether local adaptation of certain life-history traits can arise. Life-history traits, such as those determining an organisms fecundity (the parameter r) and ability to compete for resources (the parameter K) demonstrate unique eco-evolutionary feedback loops due to their direct relationship to individual fitness. Classic theory holds that in a constant environment, evolution maximises the populations competitive ability. Divergent selective pressures on life-history traits requires complex environmental differences, such as heterogeneous patterns of seasonality. We consider life-history evolution in a Lotka-Volterra model with three types of seasonal perturbations: repeated, sudden crashes in population size, fluctuating death rates, and fluctuating resource levels. We show that fluctuating resources cannot change the evolutionary outcome, but that sufficiently harsh population crashes or fluctuating death rates favour increased fecundity over competitive ability. Finally, we apply deterministic and stochastic modelling to study local adaptation of an island population to periodic population crashes in an island-mainland model. We find that local adaptation favouring r-selected individuals again arises when conditions are sufficiently harsh, but not so harsh that the island population cannot be sustained in the absence of migration.

evolutionary biology↗

bioRxiv2024

The distribution of clade size in a coalescent diversification model

Characterizing the patterns and determinants of biological diversity is a central aim of evolutionary biology. Doing so requires developing expectations for clade size, the relationship between the number of species in a clade and its age, for standard diversification models, such as the coalescent or birth-death process. These expectations are necessary for identifying diversity outliers, specious or depauperate clades in the macroevolutionary context or transmission clusters of particular or little public health concern in the epidemiological context, and for testing alternative diversification hypotheses. Here, we derive a closed-form expression for the distribution of clade sizes under the widely used Kingman coalescent diversification model and extend the results to allow the number of niches (the effective population size) to vary through time. This result complements analogous results for the birth-death model in that it provides expectations for the joint distribution of clade sizes for a case where diversification is strongly density-dependent.

genetics↗

bioRxiv2024

The Untapped Potential of Tree Size in Reconstructing Evolutionary and Epidemiological Dynamics

A phylogenetic tree has three types of attributes: size, shape (topology), and branch lengths. Phylody-namic studies are often motivated by questions regarding the size of clades, nevertheless, nearly all of the inference methods only make use of the other two attributes. In this paper, we ask whether there is additional information if we consider tree size more explicitly in phylodynamic inference methods. To address this question, we first needed to be able to compute the expected tree size distribution under a specified phylodynamic model; perhaps surprisingly, there is not a general method for doing so -- it is known what this is under a Yule or constant rate birth-death model but not for the more complicated scenarios researchers are often interested in. We present three different solutions to this problem: using i) the deterministic limit; ii) master equations; and iii) an ensemble moment approximation. Using simulations, we evaluate the accuracy of these three approaches under a variety of scenarios and alternative measures of tree size (i.e., sampling through time or only at the present; sampling ancestors or not). We then use the most accurate measures for the situation, to investigate the added informational content of tree size. We find that for two critical phylodynamic questions -- i) is diversification diversity dependent? and, ii) can we distinguish between alternative diversification scenarios? -- knowing the expected tree size distribution under the specified scenario provides insights that could not be gleaned from considering the expected shape and branch lengths alone. The contribution of this paper is both a novel set of methods for computing tree size distributions and a path forward for richer phylodynamic inference into the evolutionary and epidemiological processes that shape lineage trees.

evolutionary biology↗

bioRxiv2022

Density-dependent selection during range expansion affects expansion load in life-history traits

Models of range expansion have independently explored fitness consequences of life-history trait evolution and increased rates of genetic drift--or "allele surfing"--during spatial spread, but no previous model has examined the interactions between these two processes. Here, we explore an ecologically complex range expansion scenario that combines density-dependent selection with allele surfing, using spatially explicit simulations to asses the genetic and fitness consequences of density-dependent selection on the evolution of life-history traits. We demonstrate that density-dependent selection on the range edge acts differently depending on the life-history trait and can either diminish or enhance allele surfing. Specifically, we show that selection on the range edge is always weaker at sites affecting competitive ability (K-selected traits) than intrinsic growth rate ((r-selected traits). We then link differences in the frequency of deleterious mutations to differences in the efficacy of selection and rate of mutation accumulation across distinct life-history traits. Finally, we demonstrate the fitness consequences of accumulated deleterious mutations for different life-history traits are related to the population density in which they are expressed. Our work highlights the complex relationship between ecology and expressed genetic load, which will be important to consider when interpreting both experimental and field studies of range expansion.

evolutionary biology↗

bioRxiv2021

Neo-sex chromosome evolution shapes sex-dependent asymmetrical introgression barrier

It is increasingly recognized that sex chromosomes are not only the "battlegrounds" between sexes, but also the "Great Walls" fencing-off introgression between diverging lineages. Here we describe conflicting roles of nascent sex chromosomes on patterns of introgression in an experimental hybrid swarm. Drosophila nasuta and D. albomicans are recently diverged, fully fertile sister species that have different sex chromosome systems. The fusion between an autosome (Muller CD) with the ancestral X and Y gave rise to neo-sex chromosomes in D. albomicans, while Muller CDs remains unfused in D. nasuta. We found that a large block containing overlapping inversions on the neo-sex chromosome stood out as the strongest barrier to introgression. Intriguingly, the neo-sex chromosome introgression barrier is asymmetrical in a sex-dependent manner. Female hybrids showed significant D. albomicans biased introgression on Muller CD (neo-X excess), while males showed heterosis with excessive (neo-X, D. nasuta Muller CD) genotypes. While the neo-Y is a more compatible pairing partner of the neo-X, it also shows moderate levels of degeneration and may thus be selectively disfavored, and sex ratio assay revealed heterospecific meiotic drive. We used a population genetic model to dissect the interplay of sex chromosome drive, heterospecific pairing incompatibility between the neo-sex chromosomes and unfused Muller CD, neo-Y disadvantage, and neo-X advantage in generating the observed neo-X excess in females and heterozygous (neo-X, D. nasuta Muller CD) genotypes in males. We show that moderate neo-Y disadvantage and D. albomicans specific meiotic drive are required to counteract the effect of heterospecific meiotic drive observed in our cross, in concert with pairing incompatibility and neo-X advantage to explain observed genotype frequencies. Together, this hybrid swarm between a young species pair shed light onto the dual roles of neo-sex chromosome evolution in creating a sex-dependent asymmetrical introgression barrier at species boundary.

evolutionary biology↗

bioRxiv2021

Fundamental identifiability limits in molecular epidemiology

Viral phylogenies provide crucial information on the spread of infectious diseases, and many studies fit mathematical models to phylogenetic data to estimate epidemiological parameters such as the effective reproduction ratio (Re) over time. Such phylodynamic inferences often complement or even substitute for conventional surveillance data, particularly when sampling is poor or delayed. It remains generally unknown, however, how robust phylodynamic epidemiological inferences are, especially when there is uncertainty regarding pathogen prevalence and sampling intensity. Here we use recently developed mathematical techniques to fully characterize the information that can possibly be extracted from serially collected viral phylogenetic data, in the context of the commonly used birth-death-sampling model. We show that for any candidate epidemiological scenario, there exist a myriad of alternative, markedly different and yet plausible "congruent" scenarios that cannot be distinguished using phylogenetic data alone, no matter how large the dataset. In the absence of strong constraints or rate priors across the entire study period, neither maximum-likelihood fitting nor Bayesian inference can reliably reconstruct the true epidemiological dynamics from phylogenetic data alone; rather, estimators can only converge to the "congruence class" of the true dynamics. We propose concrete and feasible strategies for making more robust epidemiological inferences from viral phylogenetic data.

evolutionary biology↗

bioRxiv2020

A General Birth-Death-Sampling Model for Epidemiology and Macroevolution

Birth-death stochastic processes are the foundation of many phylogenetic models and are widely used to make inferences about epidemiological and macroevolutionary dynamics. There are a large number of birth-death model variants that have been developed; these impose different assumptions about the temporal dynamics of the parameters and about the sampling process. As each of these variants was individually derived, it has been difficult to understand the relationships between them as well as their precise biological and mathematical assumptions. Without a common mathematical foundation, deriving new models is non-trivial. Here we unify these models into a single framework, prove that many previously developed epidemiological and macroevolutionary models are all special cases of a more general model, and illustrate the connections between these variants. This framework centers around a technique for deriving likelihood functions for arbitrarily complex birth-death(-sampling) models that will allow researchers to explore a wider array of scenarios than was previously possible. We then use this frame-work to derive general model likelihoods for both the "single-type" case in which all lineages diversify according to the same process and the "multi-type" case, where there is variation in the process among lineages. By re-deriving existing single-type birth-death sampling models we clarify and synthesize the range of explicit and implicit assumptions made by these models.

evolutionary biology↗

bioRxiv2020

Parental population range expansion before secondary contact promotes heterosis

Population genomic analysis of hybrid zones is instrumental to our understanding of the evolution of reproductive isolation. Many temperate hybrid zones are formed by the secondary contact between two parental populations that have undergone post-glacial range expansion. Here we show that explicitly accounting for historical parental isolation followed by range expansion prior to secondary contact is fundamental for explaining genetic and fitness patterns in these hybrid zones. Specifically, ancestral population expansion can result in allele surfing where neutral or slightly deleterious mutations drift to high frequency at the expansion front. If these surfed deleterious alleles are recessive, they can contribute to substantial heterosis in hybrids produced at secondary contact, counteracting negative effects of Bateson-Dobzhansky-Muller incompatibilities (BDMIs) hence weakening reproductive isolation. When BDMIs are linked to such recessive deleterious alleles the fitness benefit of introgression at these loci can facilitate introgression at the BDMIs. The extent to which this occurs depends on the strength of selection against the linked deleterious alleles and the distribution of recombination across the chromosome. Finally, surfing of neutral loci can alter the expected pattern of population ancestry, thus accounting for historical population expansion is necessary to develop accurate null genomic models of secondary-contact hybrid zones.

evolutionary biology↗

bioRxiv2020

Feedback Between Coevolution and Epidemiology Can Help or Hinder the Maintenance of Genetic Variation in Host-Parasite Models

Understanding if and when coevolution helps maintains genetic variation in hosts of a directly-transmissible pathogen is fundamental to quantifying the prevalence and impact of coevolution on disease epidemiology. Here, we extend our previous work on the maintenance of genetic variation in a classic matching-alleles coevolutionary model by exploring the effects of ecological and epidemiological feedbacks, where both allele frequencies and population sizes are allowed to vary over time. In general, we find that coevolution rarely maintains more host genetic variation than expected under neutral genetic drift alone. When and if coevolution maintains or depletes genetic variation relative to neutral drift is determined, predominantly, by two factors: the deterministic stability of the Red Queen allele frequency cycles and the frequency at which pathogen fixation occurs, as this results in directional selection and the depletion of genetic variation in the host. Compared to purely coevolutionary models with constant host and pathogen population sizes, ecological and epidemiological feedbacks stabilize Red Queen cycles deterministically, but population fluctuations in the pathogen increase the rate of pathogen fixation, especially in epidemiological models. Taken together our results illustrate the importance of considering the ecological and epidemiological context in which coevolution occurs when examining the impact of Red Queen cycles on genetic variation.

evolutionary biology↗

bioRxiv2020

Coevolution does not slow the rate of loss of heterozygosity in a stochastic host-parasite model with constant population size

Coevolutionary negative frequency dependent selection has been hypothesized to maintain genetic variation in host and parasites. Despite the extensive literature pertaining to host-parasite coevolution, the effect of matching-alleles (MAM) coevolution on the maintenance of genetic variation has not been explicitly modelled in a finite population. The dynamics of the MAM in an infinite population, in fact, suggests that genetic variation in these coevolving populations behaves neutrally. We find that while this is largely true in finite populations two additional phenomena arise. The first of these effects is that of coevolutionary natural selection on stochastic perturbations in host and pathogen allele frequencies. While this may increase or decrease genetic variation, depending on the parameter conditions, the net effect is small relative to that of the second phenomena. Following fixation in the pathogen, the MAM becomes one of directional selection, which in turn rapidly erodes genetic variation in the host. Hence, rather than maintain it, we find that, on average, matching-alleles coevolution depletes genetic variation.

evolutionary biology↗

bioRxiv2018

TACAN is an essential component of the mechanosensitive ion channel responsible for pain sensing

Mechanotransduction, the conversion of mechanical stimuli into electrical signals, is a fundamental process underlying several physiological functions such as touch and pain sensing, hearing and proprioception. This process is carried out by specialized mechanosensitive ion channels whose identities have been discovered for most functions except pain sensing. Here we report the identification of TACAN (Tmem120A), an essential subunit of the mechanosensitive ion channel responsible for sensing mechanical pain. TACAN is expressed in a subset of nociceptors, and its heterologous expression increases mechanically-evoked currents in cell lines. Purification and reconstitution of TACAN in synthetic lipids generates a functional ion channel. Finally, knocking down TACAN decreases the mechanosensitivity of nociceptors and reduces behavioral responses to mechanical but not to thermal pain stimuli, without affecting the sensitivity to touch stimuli. We propose that TACAN is a pore-forming subunit of the mechanosensitive ion channel responsible for sensing mechanical pain.

neuroscience↗