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Local adaptation drives thermal tolerance among parasite populations: a common garden experiment
Author(s) -
Elise MazéGuilmo,
Simon Blanchet,
Olivier Rey,
Nicolas Canto,
Géraldine Loot
Publication year - 2016
Publication title -
proceedings of the royal society b biological sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.342
H-Index - 253
eISSN - 1471-2954
pISSN - 0962-8452
DOI - 10.1098/rspb.2016.0587
Subject(s) - biology , adaptation (eye) , experimental evolution , natural selection , local adaptation , ecology , selection (genetic algorithm) , climate change , population , evolutionary ecology , evolutionary biology , genetics , host (biology) , demography , gene , neuroscience , artificial intelligence , sociology , computer science
Understanding the evolutionary responses of organisms to thermal regimes is of prime importance to better predict their ability to cope with ongoing climate change. Although this question has attracted interest in free-living organisms, whether or not infectious diseases have evolved heterogeneous responses to climate is still an open question. Here, we ran a common garden experiment using the fish ectoparasite Tracheliastes polycolpus, (i) to test whether parasites living in thermally heterogeneous rivers respond differently to an experimental thermal gradient and (ii) to determine the evolutionary processes (natural selection or genetic drift) underlying these responses. We demonstrated that the reaction norms involving the survival rate of the parasite larvae (i.e. the infective stage) across a temperature gradient significantly varied among six parasite populations. Using a Qst/Fst approach and phenotype-environment associations, we further showed that the evolution of survival rate partly depended upon temperature regimes experienced in situ, and was mostly underlined by diversifying selection, but also-to some extent-by stabilizing selection and genetic drift. This evolutionary response led to population divergences in thermal tolerance across the landscape, which has implications for predicting the effects of future climate change.

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