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Ecology directs host-parasite coevolutionary trajectories across Daphnia-microparasite populations

Citation

Auld, Stuart; Paplauskas, Sam (2020), Ecology directs host-parasite coevolutionary trajectories across Daphnia-microparasite populations, Dryad, Dataset, https://doi.org/10.5061/dryad.qv9s4mwd6

Abstract

Host-parasite interactions often fuel coevolutionary change. However, parasitism is one of a myriad of possible ecological interactions in nature. Biotic (e.g., predation) and abiotic (e.g., temperature) variation can amplify or dilute parasitism as a selective force on hosts and parasites, driving population variation in (co)evolutionary trajectories. We dissected the relationships between wider ecology and coevolutionary trajectory using 16 ecologically complex Daphnia magna-Pasteuria ramosa ponds seeded with an identical starting host (Daphnia) and parasite (Pasteuria) population. We show, using a time-shift experiment and outdoor population data, how multivariate biotic and abiotic ecological differences between ponds caused coevolutionary divergence. Wider ecology drove variation in host evolution of resistance, but not parasite infectivity; parasites subsequently coevolved in response to the changing complement of host genotypes, such that parasites adapted to historically resistant host genotypes. Parasitism was a stronger interaction for the parasite than for its host, likely because the host is the principal environment and selective force, whereas for hosts, parasite-mediated selection is one of many sources of selection. Our findings reveal the mechanisms through which wider ecology creates coevolutionary hotspots and coldspots in biologically realistic arenas of host-parasite interaction, and sheds light on how the ecological theatre can affect the (co)evolutionary play.

Methods

This Excel file comprises four datasets:

1. Population data 

On the listed dates, various environmental variables, Daphnia counts and Daphnia predator (Charobarus larvae) counts were made from 16 experimental populations.

2. Time Shift Experiment data 

These data resulted from a laboratory infection experiment where twelve Daphnia genotypes were exposed to a fixed dose of Pasteuria spores from one of 17 possible parasite isolates. Sixteen of the isolates were collected from one of the the sixteen experimental ponds, and the seventeenth isolate was the ancestral parasite used to seed each of the ponds. There were three replicates per parasite isolate and thus a ouoal of 612 experimental unit. Each experimental unit comprosed of a single jar containing eight Daphnia. 

This dataset also contains the final frequency of each Daphnia genotype within each population at the time when the parasite isolates were sampled (all Daphnia genotypes were at frequency = 0.833 at the beginning of the field experiment, when the ancestral parasite isolate wqas placed in each pond).

3. Pairwise Eco Coevo data

Using the population data (1, above) we calculated the average for each of the environmental variables described in the manuscript (except for temperature, where the variance was also determined) between Julian Days 106 and 200. A Principal Components Analysis was then conducted and the pairwise Mahalanobian distances was determined between each population in twrms of multivariate ecological space. We then calculated the pairwise Malanobian distances in terms of coevolutionary space also, using the Coevo data (3, above).

The companion R code uses these datasets.

Usage Notes

The four datasets listed above are sufficient to recreate all analyses conducted within the manuscript.

1. Population data 

To determine the desities of adult Daphnia, the raw counts need to be divided by the number of net sweeps x the volume of each sweep. U denotes unmixed ponds and M denotes mixed ponds.

4. Pairwise Eco Coevo data

This was calulated using the companion R code.

Funding

Natural Environment Research Council, Award: NE/L011549/1