Abstract
Understanding what processes drive community structure is fundamental to ecology. Many wild animals are simultaneously infected by multiple parasite species, so host–parasite communities can be valuable tools for investigating connections between community structures at multiple scales, as each host can be considered a replicate parasite community. Like free‐living communities, within‐host–parasite communities are hierarchical; ecological interactions between hosts and parasites can occur at multiple scales (e.g., host community, host population, parasite community within the host), therefore, both extrinsic and intrinsic processes can determine parasite community structure. We combine analyses of community structure and assembly at both the host population and individual scales using extensive datasets on wild wood mice (Apodemus sylvaticus) and their parasite community. An analysis of parasite community nestedness at the host population scale provided predictions about the order of infection at the individual scale, which were then tested using parasite community assembly data from individual hosts from the same populations. Nestedness analyses revealed parasite communities were significantly more structured than random. However, observed nestedness did not differ from null models in which parasite species abundance was kept constant. We did not find consistency between observed community structure at the host population scale and within‐host order of infection. Multi‐state Markov models of parasite community assembly showed that a host's likelihood of infection with one parasite did not consistently follow previous infection by a different parasite species, suggesting there is not a deterministic order of infection among the species we investigated in wild wood mice. Our results demonstrate that patterns at one scale (i.e., host population) do not reliably predict processes at another scale (i.e., individual host), and that neutral or stochastic processes may be driving the patterns of nestedness observed in these communities. We suggest that experimental approaches that manipulate parasite communities are needed to better link processes at multiple ecological scales.
Highlights
Ecological systems are fundamentally hierarchical, from individuals, to populations, communities, and the broader ecosystem
If the order of community assembly at the individual scale matches the predictions based on community structure at the population scale, we can conclude that patterns of nestedness at one scale predict the process of community assembly order at the other
By combining analyses across scales, from host population to individual, we show (a) that there is clear nonrandom structure to the parasite communities of wild wood mice, (b) this nonrandomness is not related to systematic differences between hosts, and (c) this observed structure does not translate to predicting within-host– parasite community assembly over time
Summary
Ecological systems are fundamentally hierarchical, from individuals, to populations, communities, and the broader ecosystem. To investigate the relationship between the structure of within-host–parasite communities and their assembly patterns over time, we used wild wood mice, Apodemus sylvaticus, and their species-rich endoparasite community These datasets comprised longitudinal data (capture–mark–recapture) on individually tagged mice, where infection with over 30 taxonomically diverse parasite species was measured through time. It is well known that there is likely to be a strong link between a parasite's R0, its population-level prevalence, and the average age at which hosts first become infected with that parasite (Anderson & May, 1991) This is similar to the pattern predicted by variation in the dispersal ability of species in their ability to move to new habitat patches in free-living systems (Leibold et al, 2004). If the order of community assembly at the individual scale matches the predictions based on community structure at the population scale, we can conclude that patterns of nestedness at one scale predict the process of community assembly order at the other
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