Duffy Lab Research Research in the Duffy Lab lies at the interface of evolutionary, community and disease ecology,
and utilizes a combination of field, lab and theoretical studies. Most research focuses on the evolutionary and community
ecology of infectious diseases, particularly in natural populations of Daphnia. Some specific areas of research are described below: |
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Community Ecology of Parasitism We have looked at interactions between predators, parasites, and prey in a series of observational, theoretical, and experimental studies. Generally, Daphnia dentifera (formerly Daphnia galeata mendotae and Daphnia rosea) has been the focal host/prey species, with bluegill sunfish (Lepomis macrochirus) as predator and either the yeast Metschnikowia bicuspidata or the bacterium Spirobacillus cienkowskii as parasite. We have found that, in many cases, selective predation can reduce parasitism (see Duffy et al., 2005, Limnology and Oceanography, Hall et al., 2005, American Naturalist, Hall et al., 2006, Ecology, Duffy and Hall, 2008, American Naturalist). However, we have also found that predation can not necessarily be counted upon to reduce parasitism (Duffy, 2007, Oecologia) and some of our theoretical results suggest that, under some conditions, selective predation may actually increase the severity of epidemics (Duffy and Hall, 2008, American Naturalist). Interestingly, we have found parasite-driven trophic cascades (Duffy, 2007, Oecologia), suggesting that parasites can have food web-level effects. |
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Eco-Evolutionary Host-Parasite Dynamics |
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Effects of Parasitism on Host Diversity Ecologists and evolutionary biologists are intensely interested in the drivers of diversity in nature, and parasites are often invoked as causal agents. We have found that Metschnikowia epidemics can decrease host diversity (via directional selection; Duffy and Sivars-Becker, 2007, Ecology Letters), but that it can also increase host diversity (via disruptive selection; Duffy et al., 2008, BMC Evolutionary Biology). We plan on following up on this result to study the factors favoring different types of selection. Analyzing the data from the population that experienced disruptive selection required developing a novel method for measuring selection in natural populations. Code for this method (and data from our study) are available here. |
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| This research has been supported by funding from the National Science Foundation. | |
Collaborators Chad Brassil (University of Nebraska), Claes Becker (unaffiliated), Carla Cáceres (University of Illinois), Jeff Conner (Kellogg Biological Station/Michigan State), Dieter Ebert (Universitat Basel), Samantha Forde (University of California-Santa Cruz), Nicole Gerardo (Emory University), Spencer Hall (Indiana University), Marianne Huebner (Michigan State University), Tony Ives (University of Wisconsin-Madison), Chris Klausmeier (Kellogg Biological Station/Michigan State), Jorge Rodrigues (University of Texas-Arlington), Tom Schmidt (Michigan State University), Lena Sivars-Becker (unaffiliated), Alan Tessier (National Science Foundation) |
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