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.

Summary:

In nature, hosts are exposed to a multitude of diseases and a wide range of food qualities and quantities. Hereby, hosts and diseases are in a constant co-evolutionary struggle, which might be influenced by the hosts‘ food intake. This could lead to non-linear responses in host-pathogen interactions. These host food intake dependent host-pathogen interactions on individual level could be translated to the dynamics in populations. Nevertheless, food and disease effects are usually studied independently. So far, prediction models from host individual to population level exist, which either predict food or disease effects, but not effects of both factors at the same time. To fill this gap, a new mathematical model was developed. Due to its characteristics, the model can additionally be used to inversely predict individual level host parameters from population parameters. The given predictions were then compared to the results of life history and population experiments. Therefore, we tested the crustacean model organism Daphnia magna, which offers a wide range of pathogens and foods. We concluded, that population parameters can be successfully predicted from single host parameters and vice versa, depending on specific host, disease and food properties.