Biology subjects

Hulse, S. V.

Publications and source records attributed to Hulse, S. V..

4 recordsLinked to original sources

bioRxiv2026

When should a pathogen strike? Navigating the landscape of birth pulses and mating season

Susceptibility to pathogens often differs across host life stages, which in turn depends on seasonal host phenology. For many species, juveniles are highly susceptible relative to adults, which given constrained birth periods can lead to seasonal variation in the average host susceptibility. Similarly, for pathogens with complex lifecycles, or seasonally dependent development, peak transmission may be temporally constrained. Maximum pathogen transmission may therefore coincide with a greater abundance of either juvenile or adult hosts. For instance, the birthing season presents a highly susceptible pool of hosts while the mating season presents a higher rate of contact between potentially less susceptible hosts. When these two transmission opportunities are separated in time, it is unclear whether pathogens should evolve a single, intermediate transmission timing or undergo disruptive selection to exploit different host life stages. To investigate how pathogens might navigate this complex landscape, we developed an age-structured model that allows us to test the impacts of host life history on pathogen prevalence and evolution, inspired by a fungal plant pathogen. Parameterizing the model for Silene latifolia, we find that disease prevalence is highest when seed germination coincides with flowering, and that separating the two reduces disease. Using invasion analysis, we find that at the estimated S. latifolia parameters, a single evolutionarily stable transmission timing closely tracks germination time, with infectious flowering centered about seven weeks after the median germination day. When juveniles mature faster or are much more susceptible than adults, or under parameters for Dianthus pavonius, a pathogen genotype that transmits to spring-germinating juveniles and one that transmits later in the year can instead each invade the other and coexist as a polymorphic population when germination is split between spring and summer cohorts. Our model may help explain observed phenological differences seen in wild populations of infected plants.

evolutionary biology↗

bioRxiv2025

Pathogens pull hardest in the coevolutionary arms-race to determine age-specific transmission biases

Juveniles across a wide range of species are more susceptible to pathogenic infection than their adult conspecifics, often driving epidemic spread. While high juvenile susceptibility can be related to developmental timing, recent theoretical studies have found that hosts often evolve high juvenile susceptibility given a trade-off with other host traits. However, most research on age-specific infection has focused solely on host evolutionary dynamics, and the effect of pathogen evolution or coevolution on juvenile infection rates remains unknown. Here, we developed a coevolutionary adaptive dynamics model to investigate age-specific infectivity and contrast the outcome of coevolution with host evolution and pathogen evolution alone. We found strong differences in the evolutionary dynamics of hosts and pathogens in the absence of coevolution. While host evolution often favoured genotypes with intermediate levels of juvenile and adult resistance, pathogen evolution selected for extreme specialists. When hosts and pathogens were allowed to coevolve, the dynamics more closely resembled the pathogen dynamics; pathogens rapidly evolved to specialize on infecting a specific age class and this drove reciprocal specialization in host resistance. Our results illustrate that coevolution has the potential to shape age-specific patterns of infection that impact disease spread.

evolutionary biology↗

bioRxiv2024

The Emergence of Non-Linear Evolutionary Trade-offs and the Maintenance of Genetic Polymorphisms

Evolutionary models of quantitative traits often assume trade-offs between beneficial and detrimental traits, requiring modelers to specify a function linking costs to benefits. The choice of trade-off function is often consequential; functions that assume diminishing returns (accelerating costs) typically lead to single equilibrium genotypes, while decelerating costs often lead to evolutionary branching. Despite their importance, we still lack a strong theoretical foundation to base the choice of trade-off function. To address this gap, we explore how trade-off functions can emerge from the genetic architecture of a quantitative trait. We developed a multi-locus model of disease resistance, assuming each locus had random antagonistic pleiotropic effects on resistance and fecundity. We used this model to generate genotype landscapes and explored how additive versus epistatic genetic architectures influenced the shape of the trade-off function. Regardless of epistasis, our model consistently led to accelerating costs. We then used our genotype landscapes to build an evolutionary model of disease resistance. Unlike other models with accelerating costs, our approach often led to genetic polymorphisms at equilibrium. Our results suggest that accelerating costs are a strong null model for evolutionary trade-offs and that the eco-evolutionary conditions required for polymorphism may be more nuanced than previously believed.

evolutionary biology↗

bioRxiv2019

Sexual signals of fish species mimic the spatial statistics of their habitat: evidence for processing bias in animal signal evolution

The diversity of animal visual displays has intrigued scientists for centuries. Sexual selection theory has explained some of this diversity, yet most of this effort has focused on simple aspects of signal design, such as color. The evolution of complex patterns that characterize many sexual displays remains largely unexplained. The field of empirical aesthetics, a subdiscipline of cognitive psychology, has shown that humans are attracted to visual images that match the spatial statistics of natural scenes. We investigated whether applying this result to animals could help explain the diversification of complex sexual signaling patterns. We used Fourier analysis to compare the spatial statistics of body patterning in ten species of darters (Etheostoma spp.), a group of freshwater fishes with striking male visual displays, with those of their respective habitats. We found a significant correlation between the spatial statistics of darter patterns and those of their habitats for males, but not for females. Our results suggest that visual characteristics of natural environments can influence the evolution of complex patterns in sexual signals.

evolutionary biology↗