Franz J. Weissing

The relationship between facial expressions and facial shape is surprisingly understudied. We use facial videos and photographs, along with others’ judgements, to investigate the interplay among facial morphology, dynamics, and perception. Facial expressions were quantified through Action Units (AUs) using the Facial Action Coding System. Facial shape was analysed using geometric morphometrics. Analysis of the relationships between 14 AUs and 13 morphological parameters revealed that women display more intense facial movements, but men exhibit a tighter link between facial movements and facial structures. Next, we used Principal Component Analysis for a broader categorisation. The principal components (PCs) of the AU data corresponded to groups of AUs, revealing specific facial expressions. Three of the expressions thus identified were the same in both sexes, while the fourth was sex specific. The PCs of the morphometric data were more mosaic in composition; however, one male and one female PC largely agreed, reflecting a similar facial-shape phenotype. In both sexes, this facial shape dimension was associated with the tendency to produce a Duchenne smile. In turn, the expression of a Duchenne smile systematically affected how people in the videos were judged by an independent panel on various attributes (e.g., generosity, trustworthiness, happiness). In men, a male-specific PC of the morphometric data corresponded to facial masculinity, as determined by Linear Discriminant Analysis. Men with more masculine facial shapes were more likely to produce lower-face anger expression. We conclude that natural facial expressions are to a certain extent related to facial morphology, especially in men.

Empirical studies have demonstrated that mutation rates may change with individual condition, such as in the case of stress-induced mutagenesis. This has led to the hypothesis that condition-dependent (or “plastic”) mutation rates could be selectively favoured, as the increased production of new mutants in times of maladaptation enhances evolvability, the ability to undergo adaptive evolution. However, while empirical evidence for condition-dependent mutation rates is accumulating, theoretical models studying their evolution are lacking. Here, we employ an individual-based simulation approach to examine the evolution of condition-dependent mutation rates in a changing environment. We find that condition-dependent mutation rates consistently evolve when the environment changes at an intermediate pace. Furthermore, populations with condition-dependent mutation rates are substantially better adapted to their (changing) environment. Finally, the evolutionary dynamics of condition-dependent mutation rates are both accelerated and destabilised when the mutation rate is self-referential (i.e., when mutator loci affect their own mutation rate). We conclude that condition-dependent mutation rates (and thus evolvability) can readily evolve in changing environments. Significance statement: Mutation provides the raw material for evolution. Mutation rates thus tune evolvability, the ability to undergo adaptive evolution: if mutation rates are too low, evolution is impeded; if mutation rates are too high, adaptive traits cannot be maintained. Using a theoretical model, we explore the evolution of plastic mutation rates that systematically depend on the condition of the organism and its environment. An example is stress-induced mutagenesis in bacteria, which is implicated in the evolution of antibiotic resistance. We show that plastic mutation rates readily evolve, providing “well-timed” variation specifically when organisms are poorly adapted. Such plastic mutation rates thus facilitate better adaptation to changing environments, and their evolution provides an example of evolvability itself evolving.

Individual phenotypes strongly affect dispersal. Yet studying the relationship between dispersal tendencies and personality under ecologically relevant conditions is challenging, especially in fish. Laboratory studies lack environmental complexity and scale, while field-based approaches are often unfeasible. We here mimicked dispersal events in fish; encompassing all 3 phases of dispersal (departure, transience, settlement) in a large experimental mesocosm containing breeding sites. Using 3-spined sticklebacks (Gasterosteus aculeatus) tagged with ‘Passive Integrated Transponders’ (PIT tags), we remotely monitored proxies of dispersal of 2 cohorts, each consisting of 40 individuals of known activity and aggressiveness scores, continuously over 2 wk. We tested whether personality variation explained differences in departure timing, transience movements, settlement success and spatial distribution along the environmental gradient. We found that more active/aggressive individuals dispersed quicker in the mesocosm, spent more time on territories and collected more eggs. However, we did not detect strong phenotype-environment correlations. Our findings emphasize the potential role of personality-dependent dispersal in population dynamics, with specific behavioral types driving dispersal and settlement success. Our mesocosm setup provides unique insights into the dispersal dynamics in a system where detailed observations across all dispersal stages are rare and difficult to obtain. Despite limitations, behavioral experiments in mesocosms serve as a valuable bridge between laboratory and natural systems.

Parental cooperation is not self-evident, as conflicts often arise over individual contributions. Evolutionary game theory suggests this conflict may be resolved through negotiation, where parents adjust their care level based on their partner’s contribution. However, mathematical negotiation models typically predict low parental cooperation. As these models are not dynamically explicit and mostly neglect stochasticity, we employ individual-based simulations to investigate how parental negotiation strategies evolve and shape care patterns. Our results differ markedly from earlier analytical predictions. Parental negotiation strategies readily evolve, resulting in four alternative care patterns: uniparental care, sex-biased care and two types of egalitarian biparental care. Effective cooperation evolves regularly but, contrary to common expectations, always relies on a Tit-for-Tat strategy rather than parental compensation. Our study underscores that diverse cooperative patterns in animals can emerge from sex-specific negotiation strategies, even in the absence of initial sex roles and environmental variation.

Most sexual selection models assume that the evolution of female choosiness is driven by indirect (genetic) benefits, such as the production of more viable offspring or more attractive sons. There is ample empirical evidence that female choosiness can also provide direct (non-genetic) benefits, including access to good territories or paternal care. Yet, theoretical models of direct-benefits sexual selection are scarce. Here, we use individual-based evolutionary simulations to explore the joint evolution of female mating preferences and male ornamentation under sexual selection driven by direct benefits. We find that, within each generation, male ornamentation reliably indicates paternal quality (the direct benefit); females thus benefit from being choosy and readily evolve preferences for male ornamentation. Yet this in turn selects for males to invest resources in ornamentation at the expense of paternal care. Across generations, female selection for ornamented males (driven by the pursuit of direct benefits) thus erodes the very benefit it seeks, leading to population decline and potentially extinction. Our results highlight the complexity and non-intuitive nature of direct-benefits sexual selection.

Delayed offspring dispersal, the prolonged residence in the natal territory after reaching independence and before dispersing to breed elsewhere, is an important aspect of the evolution of cooperative breeding. By applying a path analysis approach to the long-term Seychelles warbler (Acrocephalus sechellensis) dataset, we studied whether and how delayed dispersal is affected by territory quality, the presence of helpers and non-helping subordinates, maternal breeding status, age and fecundity, and offspring sex ratio. We found that offspring are more likely to disperse when their genetic mothers are co-breeders, helpers are absent, and territory quality is high, highlighting that a complex interplay of ecological and social factors shapes dispersal decisions. In contrast to earlier findings, our analysis does not support the idea that the offspring sex ratio is affected by territory quality and helper presence. Collectively, this study underscores the importance of considering proximate factors in understanding cooperative breeding dynamics, and it shows that path analyses offer valuable insights into dissecting the intricate relationships influencing dispersal in wild populations.

Parental cooperation is not self-evident, as conflicts often arise over individual contributions. Evolutionary game theory suggests this conflict may be resolved through negotiation, where parents adjust their care level based on their partner’s contribution. However, mathematical negotiation models typically predict low parental cooperation. As these models are not dynamically explicit and mostly neglect stochasticity, we employ individual-based simulations to investigate how parental negotiation strategies evolve and shape care patterns. Our results differ markedly from earlier analytical predictions. Parental negotiation strategies readily evolve, producing four alternative care patterns: uniparental care, sex-biased care and two types of egalitarian biparental care, that occasionally emerge as transitional stages over evolutionary time. Effective cooperation evolved regularly but, contrary to common expectations, always relied on a Tit-for-Tat strategy rather than parental compensation. Our study underscores that diverse cooperative patterns in animals can emerge from sex-specific negotiation strategies, even in the absence of initial sex roles and environmental variation.

Learning from others is an important adaptation. However, the evolution of social learning and its role in the spread of socially transmitted information are not well understood. Few models of social learning account for the fact that socially transmitted information must be reconstructed by the learner, based on the learner’s previous knowledge and cognition. To represent the reconstructive nature of social learning, we present a modelling framework that incorporates the evolution of a neural network and a simple yet biologically realistic learning mechanism. The framework encompasses various forms of individual and social learning and allows the investigation of their interplay. Individual-based simulations reveal that an effective neural network structure rapidly evolves, leading to adaptive inborn behaviour in static environments, pure individual learning in highly variable environments, and a combination of individual and social learning in environments of intermediate stability. However, the evolutionary outcome depends strongly on the type of social learning (social guidance versus social instruction) and the order of individual and social learning. Moreover, the evolutionary dynamics of social learning can be surprisingly complex, with replicate simulations converging to alternative outcomes. We discuss the relevance of our modelling framework for cultural evolution and suggest future avenues of research.

Summary: Interference by tumor-associated macrophages may significantly reduce the efficacy of therapeutic viruses designed to infect cancer cells and activate antitumor T-cells. Using a computational model, we hypothesized that viruses encoding a T cell-stimulating signal, like IFN-γ, could overcome this barrier. We engineered an alphavirus-based replicon expressing IFN-γ and evaluated its effect in various human-derived tumor-immune coculture systems and an in vivo murine model. While alphavirus replicons do not replicate in macrophages, macrophages acted as a barrier, limiting tumor infection in a frequency-dependent but phenotype-independent manner. Nonetheless, T-cell activation occurred even when only a fraction of infected tumor cells expressed IFN-γ, regardless of macrophage presence, frequency, or phenotype. Additionally, viral stimulation drove macrophage-repolarization towards a pro-inflammatory phenotype favoring T-cell activation. These findings highlight a strategy for optimizing virotherapy in macrophage-rich tumors by designing viruses that stimulate T-cell activation, ensuring therapeutic efficacy.