Infection and invasion: study cases from aquatic communities

Melanie Hatcher, Jaimie Dick, Jamie Bojko, Grant Stentiford, Paul Stebbing, Alison Dunn

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Invasive species drive biodiversity loss and lead to changes in parasite–host associations. Parasites are linked to invasions and can mediate invasion success and outcomes. We review theoretical and empirical research into parasites in biological invasions, focusing on a freshwater invertebrate study system. We focus on the effects of parasitic infection on host traits (behaviour and life history) that can mediate native/invader trophic interactions. We review evidence from the field and laboratory of parasite-driven changes in predation, intraguild predation and cannibalism. Theoretical work shows that the trait-mediated effects of parasites can be as strong as classical density effects and their impact on the host’s trophic interactions merits more consideration. We also report on evidence of broader cascading effects warranting deeper study. Biological invasion can lead to altered parasite–host associations. Focusing on amphipod invasions, we find patterns of parasite introduction and loss that mirror host invasion pathways, but also highlight the risks of introducing invasive parasites. Horizon scanning and impact predictions are vital in identifying future disease risks, potential pathways of introduction and suitable management measures for mitigation.
Original languageEnglish
Title of host publicationWildlife Disease Ecology
Subtitle of host publicationLinking Theory to Data and Application
EditorsKenneth Wilson, Andy Fenton, Dan Tompkins
PublisherCambridge University Press
Pages262-295
ISBN (Print)9781136201900
DOIs
Publication statusPublished - 2019

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    Hatcher, M., Dick, J., Bojko, J., Stentiford, G., Stebbing, P., & Dunn, A. (2019). Infection and invasion: study cases from aquatic communities. In K. Wilson, A. Fenton, & D. Tompkins (Eds.), Wildlife Disease Ecology: Linking Theory to Data and Application (pp. 262-295). Cambridge University Press. https://doi.org/10.1017/9781316479964.009