Biology subjects

Henshaw, J. M.

Publications and source records attributed to Henshaw, J. M..

6 recordsLinked to original sources

bioRxiv2026

Partitioning covariance into causal and spurious components

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.

evolutionary biology↗

bioRxiv2025

Mate choice against gene drives leads to evolutionary rescue

Artificial gene drives offer a promising approach for controlling populations of agricultural pests, invasive species and disease vectors, such as malaria-carrying mosquitoes. Gene-drive alleles induce a transmission bias, meaning there is a greater than 50% probability that they will be inherited by offspring, facilitating their rapid propagation through populations. When these alleles induce high fitness costs, their spread can lead to the eradication of target populations. While gene drives hold great potential, there are various barriers that can hinder their effectiveness. One such barrier, precopulatory mate choice, has been suggested to impact the spread of gene drives, yet it remains underexplored. Here, we use individual-based simulations to investigate the spread of gene drives while allowing female mating preferences to evolve. In our model, gene-drive alleles exhibit transmission bias but also incur survival costs. Crucially, females are assumed to be able to distinguish between drive carriers and wild-type males based on drive-associated phenotypic differences. Consequently, females can evolve to prefer wild- type or drive-carrying males as mates. Our simulations show that under certain parameter settings, mating preferences against drive carriers can evolve during the spread of a gene drive. This can result in the eradication of the drive alleles and the evolutionary rescue of the population. The impact of mate choice was most pronounced when the gene drive spread relatively slowly, as this allowed more time for preferences against drives to evolve. In addition, evolutionary rescue occurred less frequently for recessive drives than for dominant ones. Our results demonstrate that mate choice can indeed impair the effectives of gene drive as a mechanism of population control and should therefore be seen as a potential risk. We further consider the implications for scientists developing gene drives as a population control technology. Lay summaryMost genes exist in multiple versions called alleles, with each having a 50% chance of being passed on by parents during sexual reproduction. However, some alleles, known as gene drives, manipulate inheritance to spread more widely across populations, even if they reduce the fitness of individuals carrying them. Gene drives occur naturally but can also be engineered in the laboratory. Recent technological advancements have led scientists to explore gene drives as a promising tool for controlling pests, invasive species, and disease vectors like malaria-carrying mosquitoes. However, before releasing any gene drives into the wild, it is crucial to assess their feasibility and potential risks. Here, we used computer simulations to explore how artificial gene drives spread when mate choice is allowed to evolve, assuming females can differentiate between males carrying gene drives and those without them. While gene drives have a transmission advantage, they also reduce the survival of carriers. Our results show that evolution can act rapidly after a gene drive is released. Females evolve to discriminate against drive-carrying males, which can sometimes result in the eradication of the gene drive. When gene drives have high survival costs, this evolutionary response can prevent population extinction, potentially undermining the drives purpose. The impact of mate choice is greatest when gene drives spread slowly, giving more time for evolution to act. These findings highlight the importance of considering mate choice dynamics when developing gene drives for population control.

evolutionary biology↗

bioRxiv2025

Quantifying feedback among traits in coevolutionary models

Phenotypic traits rarely evolve in isolation. Instead, multiple traits typically interact, resulting in complex coevolutionary dynamics. Such dynamics can be predicted using mathematical frameworks such as adaptive dynamics and quantitative genetics. Selection gradients play a crucial role in these frameworks, describing the direction and strength of selection and predicting evolutionary trajectories and potential endpoints. Current theory focuses mainly on analysing how traits change in response to selection. However, selection gradients also change over time as traits evolve. For a complete understanding of coevolutionary dynamics, it is consequently essential to examine how trait changes feed back to influence the selection environment. Here, we develop a general framework for investigating coevolutionary feedback between traits and selection gradients. Rather than relying on verbal interpretation of causal relationships, our approach explicitly quantifies the various pathways by which traits and selection gradients influence one another. Our framework can be applied both to adaptive-dynamic models and to quantitative-genetic models under the weak selection limit. We illustrate our approach with three examples that showcase its potential to deepen our understanding of established models.

evolutionary biology↗

bioRxiv2024

Simulations provide a mechanistic interpretation of Bateman gradients

The Bateman gradient (BG or ) is a fundamental metric of sexual selection, and is often interpreted as the fitness advantage individuals can gain by increasing their number of mates. However, researchers commonly misconceive the relationship between mating success (MS) and reproductive success (RS) as always being causal, leading to a misinterpretation of the BG. The BG is phenomenological and therefore uninformative about the mechanisms leading to correlations between MS and RS. Here, we simulate sequential matings in males from biological systems with varying levels of anisogamy and sperm competition, to better understand the underlying processes that modulate male BGs. We show that the BG does not solely reflect the causal influence of MS on RS as is typically interpreted, but is also a consequence of covariances between male MS and male ejaculate traits, female fecundity, or female post-mating decisions. For example, we show that the BG is substantially shallower when the ejaculate size of males negatively co-varies with their MS, such as in species with alternative male reproductive tactics. Such covariances can lead to a misinterpretation of the measured BG, because here, it does not merely represent the strength of selection on intra-sexual competition for mates. We suggest how such covariances can be visually assessed, and accounted for using partial Bateman gradients, to better interpret the influence of MS on RS, thus the strength of pre-copulatory sexual selection. Among other simplifications, our simulations have a male-only focus, but they provide insights into the mechanisms driving inter- and intra-specific variation in the BG, clarify its meaning, and improve our understand of sexual selection.

evolutionary biology↗

bioRxiv2022

Phenotypic selection analysis and confounding environmental variables

When environmental variation contributes to relationships between traits and fitness, it can confound analyses of phenotypic selection and, ultimately, bias predictions of adaptive evolution. To date, discussions of how to combat this problem emphasise complex statistical analyses aimed at estimating the genetic basis of the relationship between traits and fitness (e.g., the secondary theorem of selection). This article presents a path analysisbased description of the environmental confounding problem, which clarifies the issue and motivates simpler analyses as potential solutions. We show how standard selection analyses can be expanded to explicitly include environmental variables that may confound trait-fitness relationships, potentially leading to dramatically improved predictions of the evolutionary response to selection relative to classical phenotype-based estimates. We provide both univariate and multivariate treatments of the decomposition of the selection differential into components that may cause evolution via direct and indirect selection and components representing evolutionarily inert, environmentally-induced covariance. The multivariate treatment also yields expressions for the decomposition of the selection differential based on extended selection gradients, which may be of wide general interest beyond the environmental problem. Our approach to the environmental confounding problem makes more plausible demands on data than previous, more involved, quantitative genetic approaches, and addresses the issue of environmental confounding in a more biologically informative way.

evolutionary biology↗

bioRxiv2020

Selection of lamb size and early pregnancy in Soay sheep (Ovies aries)

The paradox of stasis - the unexpectedly slow evolution of heritable traits under direct selection - has been widely documented in the last few decades. This paradox is often particularly acute for body size, which is often heritable and where positive associations of size and fitness are frequently identified, but constraints to the evolution of larger body sizes are often not obvious. Here, we identify a trade-off between survival and size-dependent reproduction in Soay sheep (Ovis aries), contributes to selection against large body size. Using recently developed theory on non-linear developmental systems, then decompose total selection of ewe lamb mass along different causal paths to fitness. Larger lambs are more likely to become pregnant, which has a large viability cost. After controlling for this pathway, however, the association between lamb mass and subsequent lifetime fitness is positive. Thus this trade-off does not fully explain stasis of size in tis population, but it does substantially reduce the strength of positive directional selection of size that would otherwise occur. While selection currently favours reduced probability of early pregnancy, largely irrespective of body size, it is likely that the occurrence of early pregnancy could result from adaptation to conditions during a recent period during which population density was much lower.

evolutionary biology↗