Uncovering the secrets they keep – the role of parasites in food web ecology

Abstract

Interactions involving parasites often account for large proportions of links within aquatic food webs, yet few studies integrate parasites into their food web analyses. This analysis compares three sets of highly resolved food webs that differ in taxa composition, space, and time for a subarctic lake system. Key topological food web metrics, including connectance, linkage density, and mean generality and vulnerability, were calculated to explore the impact parasites have on food web structure and functioning. Incorporating parasites into this lacustrine food web was shown to increase connectance, linkage density, and mean vulnerability, a result of unique properties of parasites and the links they participate in. Parasites in the total food web were involved in a large proportion of concomitant predation interactions with their free-living counterparts and numerous trematodes also participated in intra-guild predation, leading to the observed changes in key metrics. Additionally, the division of the total food web into its benthic and pelagic compartments further illustrated that parasites have different impacts in these two highly contrasting habitats, as very different values were reported for most key metrics measured. However, connectance was nearly identical in the two compartments. The higher-than-expected connectance in the benthic compartment was due to the life history strategies of the benthic compartment’s parasite taxa. Finally, this analysis explored the impact of a series of fish introductions and the consequences of their ten hitchhiking parasites on the key topological metrics measured. These additional nodes increased linkage density and mean vulnerability but had very little effect on the other measured metrics. This analysis highlights the importance of incorporating parasites, especially trophically-transmitted parasites, into food webs as they significantly alter key topological metrics and are therefore essential for understanding a system’s structure and functioning.