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ZENODO
Dataset . 2013
License: CC 0
Data sources: ZENODO
DRYAD
Dataset . 2013
License: CC 0
Data sources: Datacite
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Data from: Rapid change in parasite infection traits over the course of an epidemic in a wild host–parasite population

Authors: Auld, Stuart K. J. R.; Wilson, Philip J.; Little, Tom J.;

Data from: Rapid change in parasite infection traits over the course of an epidemic in a wild host–parasite population

Abstract

By combining a field study with controlled laboratory experimentation, we examined how infection traits of the sterilizing bacterium, Pasteuria ramosa, changed over the course of a growing season in a natural population of its crustacean host Daphnia magna. The number of parasite transmission spores per infected host increased ten-fold over the course of the season, concomitant with a decline in the density of infected hosts. Plausible explanations for this variation include changes in environmental conditions, changes in host quality, or that parasite migration or natural selection caused a genetic change in the parasite population. We sought to distinguish some of these possibilities in a laboratory experiment. Thus, we preserved field-collected parasite spores throughout the season, and later exposed a set of hosts to a fixed dose of these spores under controlled laboratory conditions. Parasites collected late in the season were more infectious and grew more rapidly than parasites collected early in the season. This result is compatible with the hypothesis that the observed increase in infectivity in the field was due to genetic change, i.e. evolution in the P. ramosa population.

AuldetalOikosField-collected data. Details in ReadMe file

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Keywords

host- parasite interactions, Daphnia magna, Pasteuria ramosa, epidemics

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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