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Local adaptation at higher trophic levels: contrasting hyperparasite–pathogen infection dynamics in the field and laboratory

Predicting and controlling infectious disease epidemics is a major challenge facing the management of agriculture, human and wildlife health. Co‐evolutionarily derived patterns of local adaptation among pathogen populations have the potential to generate variation in disease epidemiology; however, s...

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Detalles Bibliográficos
Autores principales: Parratt, Steven R., Barrès, Benoit, Penczykowski, Rachel M., Laine, Anna‐Liisa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5412677/
https://www.ncbi.nlm.nih.gov/pubmed/27859910
http://dx.doi.org/10.1111/mec.13928
Descripción
Sumario:Predicting and controlling infectious disease epidemics is a major challenge facing the management of agriculture, human and wildlife health. Co‐evolutionarily derived patterns of local adaptation among pathogen populations have the potential to generate variation in disease epidemiology; however, studies of local adaptation in disease systems have mostly focused on interactions between competing pathogens or pathogens and their hosts. In nature, parasites and pathogens are also subject to attack by hyperparasitic natural enemies that can severely impact upon their infection dynamics. However, few studies have investigated whether this interaction varies across combinations of pathogen–hyperparasite strains, and whether this influences hyperparasite incidence in natural pathogen populations. Here, we test whether the association between a hyperparasitic fungus, Ampelomyces, and a single powdery mildew host, Podosphaera plantaginis, varies among genotype combinations, and whether this drives hyperparasite incidence in nature. Laboratory inoculation studies reveal that genotype, genotype × genotype interactions and local adaptation affect hyperparasite infection. However, observations of a natural pathogen metapopulation reveal that spatial rather than genetic factors predict the risk of hyperparasite presence. Our results highlight how sensitive the outcome of biocontrol using hyperparasites is to selection of hyperparasite strains.