Abstracts (first author)

Poster 

Within-species genetic variation for resistance in a P-limited environment: the Daphnia-parasite system as a case-study

Author(s): Reyserhove L, Van Colen W, Muylaert K, Decaestecker E

Summary:

These last decades, there has been a strong plea to merge biochemical and ecological insights into a field called ecological stoichiometry. Here, ecological interactions are depicted as a flow of essential elements from one level to another. One established principle is that Daphnia suffer reduced growth and survival when fed on P-deprived algae. Moreover, Frost et al. 2008 demonstrated that parasites can intensify this negative effect by increasing their virulence in a P-limited host. As this study considered only one Daphnia clone, it remains to be seen how this environment – host – parasite interaction can be generalized to multiple genotypes. In this laboratory experiment, we selected two sets of six Daphnia magna clones and experimentally manipulated (i) food P-availability and (ii) presence of the microparasite White Bacterial Disease (WBD). Both clonal sets were originally hatched from the same sediment core, differing in their depth of isolation. As the selected depth range corresponds to a time span of about 40 years, we expected these sets to differ genetically as a result of historical adaptation towards differences in P-availabiltiy. Our results show a significant three-way GH x GP x E interaction. An increasing N:P ratio positively correlated with Daphnia mortality. For old clones, the negative impact of WBD was independent of food quality. On the contrary, recent clones suffered more under reduced P-availability when parasites were present. We conclude that the effect of parasites on Daphnia depends on the level of P-limitation and the identity of the considered population.



Contacts

Chairman: Octávio S. Paulo
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Address

XIV Congress of the European Society for Evolutionary Biology

Organization Team
Department of Animal Biology (DBA)
Faculty of Sciences of the University of Lisbon
P-1749-016 Lisbon
Portugal

Website

Computational Biology & Population Genomics Group 
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