Optimal parasite infection strategies: a state-dependent approach.

Many macroparasites spend a crucial phase of their life-cycle as free-living infective stages. Despite their importance, however, little theoretical work has considered how evolution may shape the behaviour of these stages. Here, we develop what we believe to be the first stochastic dynamic programming model of parasite life-history strategies to investigate how a trade-off between resource depletion and host encounter rate may shape the optimal infection strategy of a macroparasite. The optimal strategy depends strongly on the probability of host contact and, depending on the relative costs and benefits, macroparasites should adopt either a passive 'ambushing' (sit-and-wait) strategy, an active 'cruising' strategy or a mixed strategy with an initial cruising phase, followed by a switch to ambushing when energy reserves fall to a threshold level. Under no circumstances does the model predict ambush-then-cruise. We use our model to help interpret previously published data on entomopathogenic nematode foraging behaviour, showing how this framework could facilitate our understanding of macroparasite behaviour during this key stage of the life-cycle.