van Dijk Laura J A, Ehrlén Johan, Tack Ayco J M
Department of Ecology, Environment and Plant Sciences, Stockholm University, SE-106 91, Stockholm, Sweden.
New Phytol. 2022 Mar;233(6):2585-2598. doi: 10.1111/nph.17948. Epub 2022 Jan 22.
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.
植物病原体的特性,如传播方式和越冬策略,可能对传播和持久性产生重要影响,并推动疾病动态变化。然而,我们对生活史特征如何影响时空疾病动态仍缺乏深入了解。我们采用了多方面的方法,结合实验分析、理论和实地调查,来研究关于两种病原体生活史特征——感染力和越冬策略——的信息是否能够预测自然系统中病原体集合种群的动态变化。为此,我们聚焦于森林草本植物银莲花上的四种真菌病原体(两种锈菌、一种壶菌和一种黑粉菌)。主要通过孢子感染新植物的病原体(壶菌和黑粉菌)比主要引起系统感染并在根茎中越冬的病原体(两种锈菌)具有更高的斑块占据率和定殖率。尽管锈菌更常占据连接良好的植物斑块,但壶菌和黑粉菌在孤立斑块中同样常见或更为常见。宿主斑块大小与所有病原体的斑块占据率和定殖率呈正相关。预测疾病动态对于理解宿主 - 病原体相互作用的生态和进化动态以及预防疾病爆发至关重要。我们的研究表明,结合实验、理论和实地观察是预测疾病动态的一种有效方法。