Data from: Dispersal in a patchy landscape reveals contrasting determinants of infection in a wild avian malaria system
Knowles, Sarah C. L., University of Oxford
Wood, Matthew J., University of Gloucestershire, University of Oxford
Alves, Ricardo, University of Oxford
Sheldon, Ben C., University of Oxford
Published Oct 28, 2014 on Dryad.
Cite this dataset
Knowles, Sarah C. L.; Wood, Matthew J.; Alves, Ricardo; Sheldon, Ben C. (2014). Data from: Dispersal in a patchy landscape reveals contrasting determinants of infection in a wild avian malaria system [Dataset]. Dryad. https://doi.org/10.5061/dryad.cd423
1. Understanding exactly when, where and how hosts become infected with parasites is critical to understanding host-parasite coevolution. However, for host-parasite systems in which hosts or parasites are mobile (for example vector-borne diseases), the spatial location of infection, and the relative importance of parasite exposure at successive host life-history stages, are often uncertain. 2. Here, using a six-year longitudinal dataset from a spatially referenced population of blue tits, we test the extent to which infection by avian malaria parasites is determined by conditions experienced at natal or breeding sites, as well as by postnatal dispersal between the two. 3. We show that the location and timing of infection differs markedly between two sympatric malaria parasite species. For one species (P. circumflexum), our analyses indicate that infection occurs after birds have settled on breeding territories, and because the distribution of this parasite is temporally stable, hosts could in principle alter their exposure and potentially avoid infection through postnatal dispersal. Conversely, the spatial distribution of another parasite species (P. relictum) is unpredictable, and infection probability is positively associated with postnatal dispersal distance, potentially indicating that infection occurs during this major dispersal event. 4. These findings suggest that hosts in this population may be subject to divergent selection pressures from these two parasites, potentially acting at different life-history stages. Because this implies parasite species-specific predictions for many coevolutionary processes, they also illustrate the complexity of predicting such processes in multi-parasite systems.
Datafile for statistical analysis
This file contains all data required for statistical analyses in this paper. it contains one row per individual, from 447 locally born blue tit recruits, captured and tested for malaria parasites while breeding in the same population. See README csv file for a key to the column headings.