bioRxivEcology
Parasite-driven cascades or hydra effects: susceptibility and foraging depression shape parasite-host-resource interactions
Abstract
O_LIWhen epidemics kill hosts and increase their resources, should the density of hosts decrease (with a resource increase, this constitutes a trophic cascade) or increase (a hydra effect)? Seeking answers, we integrate trait measurements, a resource-host-parasite model, and experimental epidemics with plankton. This combination reveals how a spectrum from cascades to hydra effects can arise. It reflects tension between parasite-driven mortality (a density-mediated effect) and foraging depression upon contact with parasite propagules (a trait-mediated one). C_LIO_LIIn the model, mortality rises when higher susceptibility to infection increases infection prevalence. Epidemics release resources while suppressing hosts (creating a cascade). In contrast, when hosts are less susceptible and parasites depress their foraging, a resource feedback can elevate host density during epidemics (creating a hydra effect), particularly at higher carrying capacity of resources. This combination elevates primary production relative to per-host consumption of resources (two key determinants of host density). C_LIO_LIWe test these predictions of the qualitative effects of host traits and resource carrying capacity with trait measurements and a mesocosm experiment. Trait measurements show clonal lines of zooplankton hosts differ in their foraging depression and susceptibility. We seeded resource-host-parasite mesocosms with different host genotypes and provided different nutrient supplies to test model predictions. Hydra effects and trophic cascades arose under different conditions, as predicted by the model. C_LIO_LIHence, tension between trait-mediated and density-mediated effects of parasites governs the fate of host density during epidemics - from cascades to hydra effects - via feedbacks with resources. C_LI
- organism: non-human primate
- research focus: host-pathogen & immune response
- approach: statistical model
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