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Parasite Prevalence Corresponds to Host Life History in a Diverse Assemblage of Afrotropical Birds and Haemosporidian Parasites

Avian host life history traits have been hypothesized to predict rates of infection by haemosporidian parasites. Using molecular techniques, we tested this hypothesis for parasites from three haemosporidian genera (Plasmodium, Haemoproteus, and Leucocytozoon) collected from a diverse sampling of bir...

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Detalles Bibliográficos
Autores principales: Lutz, Holly L., Hochachka, Wesley M., Engel, Joshua I., Bell, Jeffrey A., Tkach, Vasyl V., Bates, John M., Hackett, Shannon J., Weckstein, Jason D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4390322/
https://www.ncbi.nlm.nih.gov/pubmed/25853491
http://dx.doi.org/10.1371/journal.pone.0121254
Descripción
Sumario:Avian host life history traits have been hypothesized to predict rates of infection by haemosporidian parasites. Using molecular techniques, we tested this hypothesis for parasites from three haemosporidian genera (Plasmodium, Haemoproteus, and Leucocytozoon) collected from a diverse sampling of birds in northern Malawi. We found that host life history traits were significantly associated with parasitism rates by all three parasite genera. Nest type and nest location predicted infection probability for all three parasite genera, whereas flocking behavior is an important predictor of Plasmodium and Haemoproteus infection and habitat is an important predictor of Leucocytozoon infection. Parasite prevalence was 79.1% across all individuals sampled, higher than that reported for comparable studies from any other region of the world. Parasite diversity was also exceptionally high, with 248 parasite cytochrome b lineages identified from 152 host species. A large proportion of Plasmodium, Haemoproteus, and Leucocytozoon parasite DNA sequences identified in this study represent new, previously undocumented lineages (n = 201; 81% of total identified) based on BLAST queries against the avian malaria database, MalAvi.