Lee Benjamin W, Oeller Liesl C, Crowder David W
Department of Entomology and Nematology, University of California-Davis, Davis, CA 95616, USA.
Department of Entomology, Washington State University, Pullman, WA 99163, USA.
Plants (Basel). 2023 Jun 15;12(12):2335. doi: 10.3390/plants12122335.
Vector-borne plant viruses are a diverse and dynamic threat to agriculture with hundreds of economically damaging viruses and insect vector species. Mathematical models have greatly increased our understanding of how alterations of vector life history and host-vector-pathogen interactions can affect virus transmission. However, insect vectors also interact with species such as predators and competitors in food webs, and these interactions affect vector population size and behaviors in ways that mediate virus transmission. Studies assessing how species' interactions affect vector-borne pathogen transmission are limited in both number and scale, hampering the development of models that appropriately capture community-level effects on virus prevalence. Here, we review vector traits and community factors that affect virus transmission, explore the existing models of vector-borne virus transmission and areas where the principles of community ecology could improve the models and management, and finally evaluate virus transmission in agricultural systems. We conclude that models have expanded our understanding of disease dynamics through simulations of transmission but are limited in their ability to reflect the complexity of ecological interactions in real systems. We also document a need for experiments in agroecosystems, where the high availability of historical and remote-sensing data could serve to validate and improve vector-borne virus transmission models.
媒介传播的植物病毒对农业构成了多样且动态的威胁，存在数百种具有经济破坏力的病毒和昆虫媒介物种。数学模型极大地增进了我们对媒介生物生活史的改变以及宿主 - 媒介 - 病原体相互作用如何影响病毒传播的理解。然而，昆虫媒介还会与食物网中的捕食者和竞争者等物种相互作用，而这些相互作用会以调节病毒传播的方式影响媒介种群规模和行为。评估物种间相互作用如何影响媒介传播病原体传播的研究在数量和规模上都很有限，这阻碍了能够恰当捕捉群落水平对病毒流行率影响的模型的开发。在此，我们回顾影响病毒传播的媒介特征和群落因素，探讨现有的媒介传播病毒传播模型以及群落生态学原理可改进模型和管理的领域，最后评估农业系统中的病毒传播。我们得出结论，模型通过传播模拟扩展了我们对疾病动态的理解，但在反映真实系统中生态相互作用的复杂性方面能力有限。我们还证明了在农业生态系统中进行实验的必要性，在那里历史数据和遥感数据的高可用性可用于验证和改进媒介传播病毒传播模型。
