The evolution of juvenile susceptibility to infectious disease

Abstract

Infection prior to reproduction usually carries greater fitness costs for hosts than infection later in life, suggesting selection should tend to favour juvenile resistance. Yet, juveniles are generally more susceptible than adults across a wide spectrum of host taxa. While physiological constraints and a lack of prior exposure can explain some of this pattern, studies in plants and insects suggest that hosts may trade off juvenile susceptibility against other life-history traits. However, it is unclear precisely how trade-offs shape the evolution of juvenile susceptibility. Here, we theoretically explore the evolution of juvenile susceptibility subject to trade-offs with maturation or reproduction, which could realistically occur due to resource allocation during development (e.g. prioritizing growth over immune defence). We show how host lifespan, the probability of maturation (i.e. of reaching the adult stage) and transmission mode affect the results. Our key finding is that elevated juvenile susceptibility is expected to evolve over a wide range of conditions, but should be lowest when hosts have moderate lifespans and an intermediate probability of reaching the adult stage. Our results elucidate how interactions between trade-offs and the epidemiological-demographic structure of the population can lead to the evolution of elevated juvenile susceptibility.

Keywords: age structure; development; eco-evolutionary theory; host–parasite; susceptibility; trade-off.

Figure 1.

Qualitative outcomes for the evolution of juvenile susceptibility when the trade-off is against (a) adult fecundity and (b) maturation. (a,b) Trade-off spaces where the following outcomes occur: minimum susceptibility (i.e. β_J = β_A; MN); maximum susceptibility (i.e. β_J = dβ_A; MX); intermediate susceptibility (i.e. β_A < β_J < dβ_A; CSS); repeller (RE); branching point (BR); repeller and a branching point (RE + BR). (c–f) Evolutionary simulations demonstrating some of these outcomes, with dashed lines indicating the singular strategies: (c) CSS; (d) RE; (e) BR; (f) RE + BR. Transmission is density-dependent. Fixed parameters: a₀ = 2, b = 0.1, d = 3, f = 0.75, g₀ = 0.25, q = 0.001, α = 0.5, β_A = 2q/3, γ = 0.5.

Figure 2.

Evolution of juvenile susceptibility when the host experiences a diminishing trade-off with adult fecundity. (a(i),b(i),c(i)) Effects of host lifespan (1/b) for different maturation rates (g₀). (a(ii),b(ii),c(ii)) Effects of the maturation probability (g₀/(b + g₀)) for different host lifespans. (a) Evolved level of juvenile susceptibility relative to the adult population. (b) Evolved (black) and initial (i.e. with β_J = β_A; grey) levels of disease prevalence. (c) Evolved (black) and initial (β_J = β_A; grey) proportion of the population that is juvenile. The solid, dashed and dotted lines in rows (b) and (c) correspond to those in row (a). The filled (evolved) and unfilled (initial) symbols indicate points at which the lines terminate because the host population is no longer viable. Transmission is density-dependent and parameters are as described in figure 1 with a₀ = 5, , and β_A = 2q.

Figure 3.

(a–c) Evolution of juvenile susceptibility when the host experiences a diminishing trade-off in terms of the maturation rate. Plots as described in figure 2. Transmission is density-dependent and parameters are as described in figure 1 with a₀ = 5, , and β_A = 2.

Figure 4.

Evolution of juvenile susceptibility when transmission is frequency-dependent and the host experiences a diminishing trade-off in terms of the (a,b) reproduction rate or (c,d) maturation rate. Filled symbols indicate points at which evolved host population is driven extinct by the disease, and the vertical grey lines show the point at which the host population is initially viable (i.e. when β_J = β_A). The gap between the black and grey lines indicates where the host exhibits evolutionary suicide. Parameters as described in figure 1 with a₀ = 5, (in a,b), , (in c,d), , and β_A adjusted so that the age structure and disease structure of the population matches that when transmission is density-dependent.