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Migration, the recurring movement of animals between habitats, can exert pressures on the pathogens they host. Properties of host populations can determine pathogen strategy (e.g. virulence) to increase pathogen fitness. To study the effect of adding a resistant compartment on virulence evolution, we developed an SIRS model and examined the winning pathogen strategy across different rates of recovery and of immunity loss. We find that when hosts spend a relatively long time in the resistant compartment, a more virulent pathogen evolves. These results have implications in conservation of migratory animal populations afflicted by disease. 

The spread of parasites and the emergence of disease are currently threatening global biodiversity and human welfare. To address this threat, we need to better understand those factors that determine parasite persistence and prevalence. It is known that dispersal is central to the spatial dynamics of host–parasite systems. Yet past studies have typically assumed that dispersal is a species-level constant, despite a growing body of empirical evidence that dispersal varies with ecological context, including the risk of infection and aspects of host state such as infection status (parasite-dependent dispersal; PDD). Here, we develop a metapopulation model to understand how different forms of PDD shape the prevalence of a directly transmitted parasite. We show that increasing host dispersal rate can increase, decrease or cause a non-monotonic change in regional parasite prevalence, depending on the type of PDD and characteristics of the host–parasite system (transmission rate, virulence, and dispersal mortality). This result contrasts with previous studies with parasite-independent dispersal which concluded that prevalence increases with host dispersal rate. We argue that accounting for host dispersal responses to parasites is necessary for a complete understanding of host–parasite dynamics and for predicting how parasite prevalence will respond to changes such as human alteration of landscape connectivity. This article is part of the theme issue ‘Diversity-dependence of dispersal: interspecific interactions determine spatial dynamics’. 

Abstract Changes to migration routes and phenology create novel contact patterns among hosts and pathogens. These novel contact patterns can lead to pathogens spilling over between resident and migrant populations. Predicting the consequences of such pathogen spillover events requires understanding how pathogen evolution depends on host movement behaviour. Following spillover, pathogens may evolve changes in their transmission rate and virulence phenotypes because different strategies are favoured by resident and migrant host populations. There is conflict in current theoretical predictions about what those differences might be. Some theory predicts lower pathogen virulence and transmission rates in migrant populations because migrants have lower tolerance to infection. Other theoretical work predicts higher pathogen virulence and transmission rates in migrants because migrants have more contacts with susceptible hosts.We aim to understand how differences in tolerance to infection and host pace of life act together to determine the direction of pathogen evolution following pathogen spillover from a resident to a migrant population.We constructed a spatially implicit model in which we investigate how pathogen strategy changes following the addition of a migrant population. We investigate how differences in tolerance to infection and pace of life between residents and migrants determine the effect of spillover on pathogen evolution and host population size.When the paces of life of the migrant and resident hosts are equal, larger costs of infection in the migrants lead to lower pathogen transmission rate and virulence following spillover. When the tolerance to infection in migrant and resident populations is equal, faster migrant paces of life lead to increased transmission rate and virulence following spillover. However, the opposite can also occur: when the migrant population has lower tolerance to infection, faster migrant paces of life can lead to decreases in transmission rate and virulence.Predicting the outcomes of pathogen spillover requires accounting for both differences in tolerance to infection and pace of life between populations. It is also important to consider how movement patterns of populations affect host contact opportunities for pathogens. These results have implications for wildlife conservation, agriculture and human health. 

Theory is a critical component of the biological research process, and complements observational and experimental approaches. However, most biologists receive little training on how to frame a theoretical question and, thus, how to evaluate when theory has successfully answered the research question. Here, we develop a guide with six verbal framings for theoretical models in biology. These correspond to different personas one might adopt as a theorist: ‘Advocate’, ‘Explainer’, ‘Instigator’, ‘Mediator’, ‘Semantician' and ‘Tinkerer’. These personas are drawn from combinations of two starting points (pattern or mechanism) and three foci (novelty, robustness or conflict). We illustrate each of these framings with examples of specific theoretical questions, by drawing on recent theoretical papers in the fields of ecology and evolutionary biology. We show how the same research topic can be approached from slightly different perspectives, using different framings. We show how clarifying a model’s framing can debunk common misconceptions of theory: that simplifying assumptions are bad, more detail is always better, models show anything you want and modelling requires substantial maths knowledge. Finally, we provide a roadmap that researchers new to theoretical research can use to identify a framing to serve as a blueprint for their own theoretical research projects. 

Abstract Spatial aggregation of environmental or trophically transmitted parasites has the potential to influence host–parasite interactions. The distribution of parasites on hosts is one result of those interactions, and the role of spatial aggregation is unclear. We use a spatially explicit agent‐based model to determine how spatial aggregation of parasites influences the distribution of parasite burdens across a range of parasite densities and host recovery rates. Our model simulates the random movement of hosts across landscapes with varying spatial configurations of areas occupied by environmental parasites, allowing hosts to acquire parasites they encounter and subsequently lose them. When parasites are more spatially aggregated in the environment, the aggregation of parasite burdens on hosts is higher (i.e., more hosts with few parasites, fewer hosts with many parasites), but the effect is less pronounced at high parasite density and fast host recovery rates. In addition, the correlation between individual hosts' final parasite burdens and their cumulative parasite burdens (including lost parasites) is greater at higher levels of spatial parasite aggregation. Our work suggests that fine‐scale spatial patterns of parasites can play a strong role in shaping how hosts are parasitized, particularly when parasite density is low‐to‐moderate and recovery rates are slow. 

Ongoing environmental changes alter how natural selection shapes animal migration. Understanding how these changes play out theoretically can be done using evolutionary game theoretic (EGT) approaches, such as looking for evolutionarily stable strategies. Here, we first describe historical patterns of how EGT models have explored different drivers of migration. We find that there are substantial gaps in both the taxa (mammals, amphibians, reptiles, insects) and mechanisms (mutualism, interspecific competition) included in past EGT models of migration. Although enemy interactions, including parasites, are increasingly considered in models of animal migration, they remain the least studied of factors for migration considered to date. Furthermore, few papers look at changes in migration in response to perturbations (e.g. climate change, new species interactions). To address this gap, we present a new EGT model to understand how infection with a novel parasite changes host migration. We find three possible outcomes when migrants encounter novel parasites: maintenance of migration (despite the added infection cost), loss of migration (evolutionary shift to residency) or population collapse, depending on the risk and cost of getting infected, and the cost currency. Our work demonstrates how emerging infection can alter animal behaviour such as migration. This article is part of the theme issue ‘Half a century of evolutionary games: a synthesis of theory, application and future directions’. 

Abstract Research has conclusively demonstrated the potential for dispersal evolution in range expansions and shifts, however the degree of dispersal evolution observed has varied substantially among organisms. Further, it is unknown how the factors influencing dispersal evolution might impact other ecological processes at play. We use an individual-based model to investigate the effects of the underlying genetics of dispersal and mode of reproduction in range expansions and shifts. Consistent with predictions from stationary populations, dispersal evolution increases with sexual reproduction and loci number. Contrary to our predictions, however, increased dispersal does not always improve a population’s ability to track changing conditions. The mate finding Allee effect inherent to sexual reproduction increases extinction risk during range shifts, counteracting the beneficial effect of increased dispersal evolution. Our results demonstrate the importance of considering both ecological and evolutionary processes for understanding range expansions and shifts.