Host phenology regulates parasite–host demographic cycles and eco‐evolutionary feedbacks

Abstract

Parasite–host interactions can drive periodic population dynamics when parasites overexploit host populations. The timing of host seasonal activity, or host phenology, determines the frequency and demographic impact of parasite–host interactions, which may govern whether parasites sufficiently overexploit hosts to drive population cycles. We describe a mathematical model of a monocyclic, obligate‐killer parasite system with seasonal host activity to investigate the consequences of host phenology on host–parasite dynamics. The results suggest that parasites can reach the densities necessary to destabilize host dynamics and drive cycling as they adapt, but only in some phenological scenarios such as environments with short seasons and synchronous host emergence. Furthermore, only parasite lineages that are sufficiently adapted to phenological scenarios with short seasons and synchronous host emergence can achieve the densities necessary to overexploit hosts and produce population cycles. Host‐parasite cycles also generate an eco‐evolutionary feedback that slows parasite adaptation to the phenological environment as rare advantageous phenotypes can be driven extinct due to a population bottleneck depending on when they are introduced in the cycle. The results demonstrate that seasonal environments can drive population cycling in a restricted set of phenological patterns and provide further evidence that the rate of adaptive evolution depends on underlying ecological dynamics.

Parasite‐mediated selection on host phenology

“…That is, mutant invasion fitness is equivalent to that were produced in season by who successfully matured by the end of the season . Following the same approach as in previous analyses (MacDonald et al, 2022 ; MacDonald & Brisson, 2022a , 2022b ), the mutant host invades in a given host phenological scenario if is greater than or equal to the initial introduced at the start of season . Optimal phenological traits ( , ) are those that invade and replace populations with alternative trait values when rare and also prevent invasion, while at equilibrium, from mutants with different trait values.…”

“…That is, mutant invasion fitness is equivalent to $$$ {\hat{s}}_m\left(n+1\right) $$$ that were produced in season $$$ n $$$ by $$$ {s}_{n,m} $$$ who successfully matured by the end of the season $$$ {a}_{n,m}(T) $$$. Following the same approach as in previous analyses (MacDonald et al, 2022; MacDonald & Brisson, 2022a, 2022b), the mutant host invades in a given host phenological scenario if $$$ {\hat{s}}_m\left(n+1\right) $$$ is greater than or equal to the initial $$$ {\hat{s}}_m(n)={s}_{n,m}(0)=1 $$$ introduced at the start of season $$$ n $$$ $$$ \left({\hat{s}}_m\left(n+1\right)\ge 1\right) $$$. Optimal phenological traits ($$$ {t}_0^{\ast } $$$, $$$ {t}_l^{\ast } $$$) are those that invade and replace populations with alternative trait values when rare and also prevent invasion, while at equilibrium, from mutants with different trait values.…”

“…In previous work on a similar model, we derived an analytical expression for end‐of‐season host and parasite density ($$$ {a}_n(T) $$$, $$$ {v}_n(T) $$$, respectively) (MacDonald & Brisson, 2022a). However, we can only solve system (1) in the current framework analytically if $$$ \tau $$$ is long enough that parasites only complete one infection generation per season.…”

“…We have shown previously that host carryover can generate a feedback between parasite fitness and host demography that drives quasiperiodic dynamics for some parameter ranges (MacDonald & Brisson, 2022a , 2022b ). In this study, we found no evidence that host–parasite cycling occurs for the parameter ranges considered, that is, the dynamics always eventually settle to stable end‐of‐season densities.…”

Maintenance and evolution of individual differences in a prey defence trait examined with a dynamic predator-prey model

“…Through the calculation of invasion fitnesses, this method derives conditions for the occurrence of evolutionary stable strategies, or the occurrence of evolutionary branching. Adaptive dynamics has been pioneered by Abrams (2001), Dieckmann and Law (1996), Geritz et al (1998) and Metz et al (1995) for simple birth-death processes and has more recently been used in the predator-prey context, for example by Grunert et al (2021) andMacDonald andBrisson (2022).…”