"Resistance Is Futile": Weaker Selection for Resistance by Abundant Parasites Increases Prevalence and Depresses Host Density

AMERICAN NATURALIST(2023)

引用 1|浏览2
暂无评分
摘要
Theory often predicts that host populations should evolve greater resistance when parasites become abundant. Furthermore, that evolutionary response could ameliorate declines in host populations during epidemics. Here, we argue for an update: when all host genotypes become sufficiently infected, higher parasite abundance can select for lower resistance because its cost exceeds its benefit. We illustrate such a "resistance is futile" outcome with mathematical and empirical approaches. First, we analyzed an eco-evolutionary model of parasites, hosts, and hosts' resources. We determined eco-evolutionary outcomes for prevalence, host density, and resistance (mathematically, "transmission rate") along ecological and trait gradients that alter parasite abundance. With high enough parasite abundance, hosts evolve lower resistance, amplifying infection prevalence and decreasing host density. In support of these results, a higher supply of nutrients drove larger epidemics of survival-reducing fungal parasites in a mesocosm experiment. In two-genotype treatments, zooplankton hosts evolved less resistance under high-nutrient conditions than under low-nutrient conditions. Less resistance, in turn, was associated with higher infection prevalence and lower host density. Finally, in an analysis of naturally occurring epidemics, we found a broad, bimodal distribution of epidemic sizes consistent with the resistance is futile prediction of the eco-evolutionary model. Together, the model and experiment, supplemented by the field pattern, support predictions that drivers of high parasite abundance can lead to the evolution of lower resistance. Hence, under certain conditions, the most fit strategy for individual hosts exacerbates prevalence and depresses host populations.
更多
查看译文
关键词
host evolution, infectious disease, eco-evolutionary feedbacks, experimental evolution
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要