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</script>doi: 10.1086/653002
pmid: 20465424
Understanding the coevolution of hosts and parasites is one of the key challenges for evolutionary biology. In particular, it is important to understand the processes that generate and maintain variation. Here, we examine a coevolutionary model of hosts and parasites where infection does not depend on absolute rates of transmission and defense but is approximately all-or-nothing, depending on the relative levels of defense and infectivity of the host and the parasite. We show that considerable diversity can be generated and maintained because of epidemiological feedbacks, with strains differing in the range of host and parasite types they can respectively infect or resist. Parasites with broad and narrow ranges therefore coexist, as do broadly and narrowly resistant hosts, but this diversity occurs without the assumption of highly specific gene interactions. In contrast to gene-for-gene models, cycling in strain types is found only under a restrictive set of circumstances. The generation of diversity in both hosts and parasites is dependent on the shape of the trade-off relationships but is more likely in long-lived hosts and chronic disease with long infectious periods. Overall, our model shows that significant diversity in infectivity and resistance range can evolve and be maintained from initially monomorphic populations.
Infection range, Parasitic Diseases, Animal, Adaptation, Biological, Genetic Variation, Biodiversity, Biological Evolution, Models, Biological, Host-Parasite Interactions, Species Specificity, Animals, Computer Simulation, Genetic variation, Adaptive dynamics, Coevolution
Infection range, Parasitic Diseases, Animal, Adaptation, Biological, Genetic Variation, Biodiversity, Biological Evolution, Models, Biological, Host-Parasite Interactions, Species Specificity, Animals, Computer Simulation, Genetic variation, Adaptive dynamics, Coevolution
| citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 69 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
