Xiaoyan Long

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.

Phenotypic traits rarely evolve in isolation. Instead, multiple traits typically interact to influence fitness, 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 thus predicting evolutionary trajectories and potential endpoints. Current theory focuses mainly on analysing how traits change in response to selection, which changes over time as traits evolve. However, the extent to which changes in each trait contribute to changes in the selection environment remains unquantified, leaving much of our understanding of trait coevolution reliant on verbal reasoning. To advance a more comprehensive and quantitative understanding of coevolutionary dynamics, we develop a general framework that examines how trait changes feedback to influence the selection environment. This framework enables a fine-grained and systematic investigation of coevolutionary feedback between traits and selection gradients by quantifying the pathways through which they 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.

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 summary: Most 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 drive’s 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.

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.

Competition over resources is often decided via aggressive interactions, which may or may not escalate to all-out fights. Weapons and body size play important roles in such interactions, as they often provide reliable cues of an individual’s fighting ability. In contrast, traits like nonfunctional display “weapons” may dishonestly exaggerate fighting ability in order to intimidate opponents into retreating. Signals used in the context of aggressive interactions potentially evolve via very different mechanisms than courtship signals, but have received far less theoretical attention. Here, we contrast the evolution of honest and dishonest signals of fighting ability using a game-theoretic model. Contests are assumed to consist of three discrete stages: display from a distance, low-intensity physical contact, and fighting. At each stage, contestants evaluate the fighting ability of their opponents in comparison to their own based on body size and an aggressive signal. After making this evaluation, contestants decide whether to escalate the interaction or cede to their opponent. Our model predicts that both honest and dishonest aggressive signals can exaggerate far beyond their ecological optima, but that exaggeration is more pronounced for honest signals. Equilibrium levels of aggressiveness—as measured by individuals’ propensity to escalate aggressive interactions to the next stage—are independent of the honesty of signals. We additionally develop a novel approach, based on causal inference theory, to understand how changes in underlying parameters shape the coevolution of multiple traits. We use this approach to study how aggression coevolves with body and signal size in response to changes in the cost of losing a fight.

The parental roles of males and females differ considerably between and within species. By means of individual-based evolutionary simulations, we strive to explain this diversity. We show that the conflict between the sexes creates a sex bias (towards maternal or paternal care), even if the two sexes are initially identical. When including sexual selection, there are two outcomes: either female mate choice and maternal care or no mate choice and paternal care. Interestingly, the care pattern drives sexual selection and not vice versa. Longer-term simulations exhibit rapid switches between alternative parental care patterns, even in constant environments. Hence, the evolutionary lability of sex roles observed in phylogenetic studies is not necessarily caused by external changes. Overall, our findings are in striking contrast to the predictions of mathematical models. We show that the discrepancies are caused by transient within-sex polymorphisms in parental strategies, a factor largely neglected in current sex-role theory.

Parental care is one of the most diverse social behaviours, and caring by the male, female or both parents is essential for successful reproduction of many organisms. Theoretical and empirical studies suggest that parental sex roles are associated with biased sex ratios. However, there is considerable debate on the causal relationship between parental sex roles and sex ratio biases and on the relative importance of the operational sex ratio (OSR), the adult sex ratio (ASR), and the maturation sex ratio (MSR). Here we use individual-based evolutionary simulations to investigate the joint evolution of sex-specific parental behaviour and the various sex ratios in several life history scenarios. We show that sex differences in maturation time or mortality rates at various life-history stages predict the evolution of parental sex roles relatively well: typically, but not always, parental care is biased toward the sex with the lower mortality or the faster maturation. The association of parental sex roles with the various sex ratios is more intricate. In our simulations, the operational sex ratio at evolutionary equilibrium was typically biased toward the less-caring sex. However, the direction and strength of OSR biases often changed drastically in the course of evolution, implying that, rather than being a driver of parental sex roles, OSR biases emerge as a consequence of sex-biases in parental care. When the MSR or the ASR is biased, this bias is generally associated with a bias in parental care: the overrepresented sex does most of the caring. However, the opposite pattern (that the underrepresented sex did most of the caring) also occurs in some scenarios. Moreover, pronounced parental sex roles may also evolve in the absence of an MSR or ASR bias. Taken together, we conclude that none of the sex ratios can be viewed as drivers of a parental care bias; they rather co-evolve with parental care bias in a subtle manner.