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Chapter Sixteen - Healthy herds or predator spreaders? Insights from the plankton into how predators suppress and spread disease

from Part III - Understanding wildlife disease ecology at the community and landscape level

Published online by Cambridge University Press:  28 October 2019

By
Meghan A. Duffy ,
Carla E. Cáceres  and
Spencer R. Hall
Edited by
Kenneth Wilson ,
Andy Fenton  and
Dan Tompkins
Kenneth Wilson
Affiliation:
Lancaster University
Andy Fenton
Affiliation:
University of Liverpool
Dan Tompkins
Affiliation:
Predator Free 2050 Ltd
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Summary

How and why do predators sometimes fuel disease outbreaks but other times thwart them? Answering this could help explain spatial and temporal variation in disease and could explain why attempts to control disease by manipulating predators sometimes fail. We give eight mechanisms by which predators can suppress/spread disease in prey populations, exploring each generally and reviewing evidence from the study system that has been the focus of much of our research. This system focuses on Daphnia dentifera, a dominant herbivore in lake food webs in the Midwestern United States. D. dentifera is prey to bluegill sunfish and phantom midge larvae, as well as host to a virulent fungal pathogen. We review evidence for bluegill sunfish as ‘healthy herds’ predators that reduce disease, and for midge larvae as ‘predator spreaders’ that fuel disease outbreaks. We find that both predators can impact disease via multiple mechanisms. Bluegill feed selectively on infected hosts and also depress disease in Daphnia by reducing the density of midge larvae which spread disease. They also increase the abundance of Ceriodaphnia, which reduce disease. Midge larvae increase disease in their hosts, in part by releasing spores into the water column where they can be consumed by additional hosts.

Keywords

predationpredatorstrophic cascadesselective cullinghost densityhost demographyclass structurecommunity compositiontrait-mediated indirect effects (TMIEs)size structure
Type
Chapter
Information
Wildlife Disease Ecology
Linking Theory to Data and Application
 , pp. 458 - 479
Publisher: Cambridge University Press
Print publication year: 2019

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