The relationship between pathogen life-history traits and metapopulation dynamics.
Autor: | van Dijk LJA; Department of Ecology, Environment and Plant Sciences, Stockholm University, SE-106 91, Stockholm, Sweden., Ehrlén J; Department of Ecology, Environment and Plant Sciences, Stockholm University, SE-106 91, Stockholm, Sweden., Tack AJM; Department of Ecology, Environment and Plant Sciences, Stockholm University, SE-106 91, Stockholm, Sweden. |
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Jazyk: | angličtina |
Zdroj: | The New phytologist [New Phytol] 2022 Mar; Vol. 233 (6), pp. 2585-2598. Date of Electronic Publication: 2022 Jan 22. |
DOI: | 10.1111/nph.17948 |
Abstrakt: | Plant pathogen traits, such as transmission mode and overwintering strategy, may have important effects on dispersal and persistence, and drive disease dynamics. Still, we lack insights into how life-history traits influence spatiotemporal disease dynamics. We adopted a multifaceted approach, combining experimental assays, theory and field surveys, to investigate whether information about two pathogen life-history traits - infectivity and overwintering strategy - can predict pathogen metapopulation dynamics in natural systems. For this, we focused on four fungal pathogens (two rust fungi, one chytrid fungus and one smut fungus) on the forest herb Anemone nemorosa. Pathogens infecting new plants mostly via spores (the chytrid and smut fungi) had higher patch occupancies and colonization rates than pathogens causing mainly systemic infections and overwintering in the rhizomes (the two rust fungi). Although the rust fungi more often occupied well-connected plant patches, the chytrid and smut fungi were equally or more common in isolated patches. Host patch size was positively related to patch occupancy and colonization rates for all pathogens. Predicting disease dynamics is crucial for understanding the ecological and evolutionary dynamics of host-pathogen interactions, and to prevent disease outbreaks. Our study shows that combining experiments, theory and field observations is a useful way to predict disease dynamics. (© 2022 The Authors. New Phytologist © 2022 New Phytologist Foundation.) |
Databáze: | MEDLINE |
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