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  1. Abstract

    Numerous theoretical models have demonstrated that migration, a seasonal animal movement behaviour, can minimize the risks and costs of parasite infection. Past work on migration–infection interactions assumes migration is the only strategy available to organisms for dealing with the parasite infection, that is they migrate to a different environment to recover or escape from infection. Thus, migration is similar to the non‐spatial strategy of resistance, where hosts prevent infection or kill parasites once infected. However, an alternative defence strategy is to tolerate the infection and experience a lower cost to the infection. To our knowledge, no studies have examined how migration can change based on combining two host strategies (migration and tolerance) for dealing with parasites.

    In this paper, we aim to understand how both parasite transmission and infection tolerance can influence the host's migratory behaviour.

    We constructed a model that incorporates two host strategies (migration and tolerance) to understand whether allowing for tolerance affects the proportion of the population that migrates at equilibrium in response to infection.

    We show that the benefits of tolerance can either decrease or increase the host's migration. Also, if the benefit of migration is great, then individuals are more likely to migrate regardless of the presence of tolerance. Finally, we find that the transmission rate of parasite infection can either decrease or increase the tolerant host's migration, depending on the cost of migration.

    These findings highlight that adopting two defence strategies is not always beneficial to the hosts. Instead, a single strategy is often better, depending on the costs and benefits of the strategies and infection pressures. Our work further suggests that multiple host‐defence strategies as a potential explanation for the evolution of migration to minimize the parasite infection. Moreover, migration can also affect the ecological and evolutionary dynamics of parasite–host interactions.

     
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  2. Abstract

    Migration can allow individuals to escape parasite infection, which can lead to a lower infection probability (prevalence) in a population and/or fewer parasites per individual (intensity). Because individuals with more parasites often have lower survival and/or fecundity, infection intensity shapes the life‐history trade‐offs determining when migration is favored as a strategy to escape infection. Yet, most theory relies on susceptible‐infected (SI) modeling frameworks, defining individuals as either healthy or infected, ignoring details of infection intensity. Here, we develop a novel modeling approach that captures infection intensity as a spectrum, and ask under what conditions migration evolves as function of how infection intensity changes over time. We show that relative timescales of migration and infection accumulation determine when migration is favored. We also find that population‐level heterogeneity in infection intensity can lead to partial migration, where less‐infected individuals migrate while more infected individuals remain resident. Our model is one of the first to consider how infection intensity can lead to migration. Our results frame migratory escape in light of infection intensity rather than prevalence, thus demonstrating that decreased infection intensity should be considered a benefit of migration, alongside other typical drivers of migration.

     
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  3. Abstract

    Pathogen and parasite infections are increasingly recognized as powerful drivers of animal movement, including migration. Yet, infection‐related migration benefits can result from a combination of environmental and/or social conditions, which can be difficult to disentangle.

    Here, we focus on two infection‐related mechanisms that can favour migration: moving to escape versus recover from infection. By directly comparing the evolution of migration in response to each mechanism, we can evaluate the likely importance of changing abiotic conditions (linked to migratory recovery) with changing social conditions (linked to migratory escape) in terms of infection‐driven migration.

    We built a mathematical model and analysed it using numerically simulated adaptive dynamics to determine when migration should evolve for each migratory recovery and social migratory escape.

    We found that a higher fraction of the population migrated under migratory recovery than under social migratory escape. We also found that two distinct migratory strategies (e.g. some individuals always migrate and others only occasionally migrate) sometimes coexisted within populations with social migratory escape, but never with migratory recovery.

    Our results suggest that migratory recovery is more likely to promote the evolution of migratory behaviour, rather than escape from infected conspecifics (social migratory escape).

     
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  4. Abstract

    Most studies on the evolution of migration focus on food, mates and/or climate as factors influencing these movements, whereas negative species interactions such as predators, parasites and pathogens are often ignored. Although infection and its associated costs clearly have the potential to influence migration, thoroughly studying these interactions is challenging without a solid theoretical framework from which to develop testable predictions in natural systems.

    Here, we aim to understand when parasites favour the evolution of migration.

    We develop a general model which enables us to explore a broad range of biological conditions and to capture population and infection dynamics over both ecological and evolutionary time‐scales.

    We show that when migration evolves depends on whether the costs of migration and infection are paid in reduced fecundity or survival. Also important are the parasite transmission mode and spatiotemporal dynamics of infection and recovery (if it occurs). Finally, we find that partial migration (where only a fraction of the population migrates) can evolve but only when parasite transmission is density‐dependent.

    Our results highlight the critical, if overlooked, role of parasites in shaping long‐distance movement patterns, and suggest that infection should be considered alongside more traditional drivers of migration in both empirical and theoretical studies.

     
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  5. Abstract

    Network analysis of infectious disease in wildlife can reveal traits or individuals critical to pathogen transmission and help inform disease management strategies. However, estimates of contact between animals are notoriously difficult to acquire. Researchers commonly use telemetry technologies to identify animal associations, but such data may have different sampling intervals and often captures a small subset of the population. The objectives of this study were to outline best practices for telemetry sampling in network studies of infectious disease by determining (a) the consequences of telemetry sampling on our ability to estimate network structure, (b) whether contact networks can be approximated using purely spatial contact definitions and (c) how wildlife spatial configurations may influence telemetry sampling requirements.

    We simulated individual movement trajectories for wildlife populations using a home range‐like movement model, creating full location datasets and corresponding ‘complete’ networks. To mimic telemetry data, we created ‘sample’ networks by subsampling the population (10%–100% of individuals) with a range of sampling intervals (every minute to every 3 days). We varied the definition of contact for sample networks, using either spatiotemporal or spatial overlap, and varied the spatial configuration of populations (random, lattice or clustered). To compare complete and sample networks, we calculated seven network metrics important for disease transmission and assessed mean ranked correlation coefficients and percent error between complete and sample network metrics.

    Telemetry sampling severely reduced our ability to calculate global node‐level network metrics, but had less impact on local and network‐level metrics. Even so, in populations with infrequent associations, high intensity telemetry sampling may still be necessary. Defining contact in terms of spatial overlap generally resulted in overly connected networks, but in some instances, could compensate for otherwise coarse telemetry data.

    By synthesizing movement and disease ecology with computational approaches, we characterized trade‐offs important for using wildlife telemetry data beyond ecological studies of individual movement, and found that careful use of telemetry data has the potential to inform network models. Thus, with informed application of telemetry data, we can make significant advances in leveraging its use for a better understanding and management of wildlife infectious disease.

     
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  6. Abstract

    Determining parameters that govern pathogen transmission (such as the force of infection, FOI), and pathogen impacts on morbidity and mortality, is exceptionally challenging for wildlife. Vital parameters can vary, for example across host populations, between sexes and within an individual's lifetime.

    Feline immunodeficiency virus (FIV) is a lentivirus affecting domestic and wild cat species, forming species‐specific viral–host associations. FIV infection is common in populations of puma (Puma concolor), yet uncertainty remains over transmission parameters and the significance of FIV infection for puma mortality. In this study, the age‐specific FOI of FIV in pumas was estimated from prevalence data, and the evidence for disease‐associated mortality was assessed.

    We fitted candidate models to FIV prevalence data and adopted a maximum likelihood method to estimate parameter values in each model. The models with the best fit were determined to infer the most likely FOI curves. We applied this strategy for female and male pumas from California, Colorado, and Florida.

    When splitting the data by sex and area, our FOI modeling revealed no evidence of disease‐associated mortality in any population. Both sex and location were found to influence the FOI, which was generally higher for male pumas than for females. For female pumas at all sites, and male pumas from California and Colorado, the FOI did not vary with puma age, implying FIV transmission can happen throughout life; this result supports the idea that transmission can occur from mothers to cubs and also throughout adult life. For Florida males, the FOI was a decreasing function of puma age, indicating an increased risk of infection in the early years, and a decreased risk at older ages.

    This research provides critical insight into pathogen transmission and impact in a secretive and solitary carnivore. Our findings shed light on the debate on whether FIV causes mortality in wild felids like puma, and our approach may be adopted for other diseases and species. The methodology we present can be used for identifying likely transmission routes of a pathogen and also estimating any disease‐associated mortality, both of which can be difficult to establish for wildlife diseases in particular.

     
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  7. 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’. 
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  8. null (Ed.)
    Pathogen management strategies in wildlife are typically accompanied by an array of uncertainties such as the efficacy of vaccines or potential unintended consequences of interventions. In the context of such uncertainties, models of disease transmission can provide critical insight for optimizing pathogen management, especially for species of conservation concern. The endangered Florida panther experienced an outbreak of feline leukaemia virus (FeLV) in 2002–2004, and continues to be affected by this deadly virus. Ongoing management efforts aim to mitigate the effects of FeLV on panthers, but with limited information about which strategies may be most effective and efficient. We used a simulation-based approach to determine optimal FeLV management strategies in panthers. We simulated the use of proactive FeLV management strategies (i.e. proactive vaccination) and several reactive strategies, including reactive vaccination and test-and-removal. Vaccination strategies accounted for imperfect vaccine-induced immunity, specifically partial immunity in which all vaccinates achieve partial pathogen protection. We compared the effectiveness of these different strategies in mitigating the number of FeLV mortalities and the duration of outbreaks. Results showed that inadequate proactive vaccination can paradoxically increase the number of disease-induced mortalities in FeLV outbreaks. These effects were most likely due to imperfect vaccine immunity causing vaccinates to serve as a semi-susceptible population, thereby allowing outbreaks to persist in circumstances otherwise conducive to fadeout. Combinations of proactive vaccination with reactive test-and-removal or vaccination, however, had a synergistic effect in reducing the impacts of FeLV outbreaks, highlighting the importance of using mixed strategies in pathogen management. Synthesis and applications. Management-informed disease simulations are an important tool for identifying unexpected negative consequences and synergies among pathogen management strategies. In particular, we find that imperfect vaccine-induced immunity necessitates further consideration to avoid unintentionally worsening epidemics in some conditions. However, mixing proactive and reactive interventions can improve pathogen control while mitigating uncertainties associated with imperfect interventions. 
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