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 … Show more
“…n = 300 , in the absence of parasites, t * l = 0.5 (minimum possible emergence period length), all other parameters are the same as in Table 1. results presented herein that host-parasite intensity is predicted to select for partial host migration (Balstad et al, 2021; Binning, 2016)-a prediction that is matched by empirical data on reindeer (Folstad et al, 1991) and fish migration (Poulin et al, 2012;Sikkel et al, 2017).…”
The timing of seasonal activity, or phenology, is an adaptive trait that maximizes individual fitness by timing key life events to coincide with favorable abiotic factors and biotic interactions. Studies on the biotic interactions that determine optimal phenology have focused on temporal overlaps among positively‐interacting species such as mutualisms. Less well understood is the extent that negative interactions such as parasitism impact the evolution of host phenology. Here, we present a mathematical model demonstrating the evolution of host phenological patterns in response to sterilizing parasites. Environments with parasites favor hosts with shortened activity periods or greater distributions in emergence timing, both of which reduce the temporal overlap between hosts and parasites and thus reduce infection risk. Although host populations with these altered phenological patterns are less likely to mature and reproduce, the fitness advantage of parasite avoidance can be greater than the cost of reduced reproduction. These results illustrate the impact of parasitism on the evolution of host phenology and suggest that shifts in host phenology could serve as a strategy to mitigate the risk of infection.
“…n = 300 , in the absence of parasites, t * l = 0.5 (minimum possible emergence period length), all other parameters are the same as in Table 1. results presented herein that host-parasite intensity is predicted to select for partial host migration (Balstad et al, 2021; Binning, 2016)-a prediction that is matched by empirical data on reindeer (Folstad et al, 1991) and fish migration (Poulin et al, 2012;Sikkel et al, 2017).…”
The timing of seasonal activity, or phenology, is an adaptive trait that maximizes individual fitness by timing key life events to coincide with favorable abiotic factors and biotic interactions. Studies on the biotic interactions that determine optimal phenology have focused on temporal overlaps among positively‐interacting species such as mutualisms. Less well understood is the extent that negative interactions such as parasitism impact the evolution of host phenology. Here, we present a mathematical model demonstrating the evolution of host phenological patterns in response to sterilizing parasites. Environments with parasites favor hosts with shortened activity periods or greater distributions in emergence timing, both of which reduce the temporal overlap between hosts and parasites and thus reduce infection risk. Although host populations with these altered phenological patterns are less likely to mature and reproduce, the fitness advantage of parasite avoidance can be greater than the cost of reduced reproduction. These results illustrate the impact of parasitism on the evolution of host phenology and suggest that shifts in host phenology could serve as a strategy to mitigate the risk of infection.
“…Third, the host population can go extinct, if both costs (infection, residency) are too high (figure 2, grey regions). Intriguingly, we never see an outcome of partial migration (0 < θ < 1), where only a subset of the population migrates each year (an outcome we have seen in many of our earlier models [61–64]). Figure 2Migration strategies.…”
Section: Migratory Loss In Response To An Emerging Infectionmentioning
confidence: 58%
“…For example, we never observed partial migration, but our past work suggests that a reduction in migration (i.e. shift from full migration to partial migration) should be a possible outcome when parasites have density-dependent transmission [62], when migration decisions depend on infection [63,64], and when recovery from infection is possible [61]. Our work is in line with the broader idea that parasites are critical, if overlooked, drivers of host behaviour and life history and that, 50 years on, EGT remains a topical and relevant way of studying patterns of animal behaviour, including migration.…”
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’.
“…cardiovascular, or respiratory function; Warnecke et al, 2013). More broadly, disease ecology models rarely consider intensity-dependent sublethal effects of the host fitness (Balstad et al, 2021;Joseph et al, 2013).…”
1. The progression of infectious disease depends on the intensity of and sensitivity to pathogen infection. Understanding commonalities in trait sensitivity to pathogen infection across studies through meta-analytic approaches could provide insight to the pathogenesis of infectious diseases. The globally devastating amphibian chytrid fungus, Batrachochytrium dendrobatidis (Bd), offers a good case system due to the widely available dataset on disruption to functional traits across species.2. Here, I systematically conducted a phylogenetically controlled meta-analysis to test how infection intensity affects different functional traits (e.g. behaviour, physiology, morphology, reproduction) and the survival in amphibians infected with Bd.3. There was a consistent effect of Bd infection on energy metabolism, while traits related to body condition, osmoregulation, and behaviour generally decreased with Bd infection. Skin integrity, hormone levels, and osmoregulation were most sensitive to Bd infection (minimum Bd load ln 2.5 zoospore equivalent), while higher minimum Bd loads were required to influence reproduction (ln 10.6 zoospore equivalent). Mortality differed between life stages, where juvenile mortality was dependent on infection intensity and exposure duration, while adult mortality was dependent on infection intensity only. Importantly, there were strong biases for studies on immune response, body condition and survival, while locomotor capacity, energy metabolism and cardiovascular traits were lacking.4. The influence of pathogen load on functional disruption can help inform pathogen thresholds before the onset of irreversible damage and mortality. Metaanalytic approaches can provide quantitative assessment across studies to reveal commonalities, differences and biases of panzootic diseases, especially for understanding the ecological relevance of disease impact.
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