EAGER: Spillover of coffee diseases into forest ecosystems and consequences for forest plant communities

许多农地和受保护的自然区在物理上相互毗邻并相互作用，但很少有人研究农业和自然生态系统如何相互影响，以及这些相互作用对农业管理的有效性和自然土地的保护有何影响。外溢是疾病生态学中的一个术语，最近更广泛地用于描述生物体跨越生境边界时的运动和影响。该项目将增进人们对农业和自然生境之间溢出效应的重要性以及鸟类和风在植物相关真菌传播中的作用的认识。通过比较日照和遮荫两种咖啡管理方式的真菌和植物病害，这项研究将为决策提供决策依据，以确定这两种农业策略在咖啡真菌病害管理和减少溢出负面影响方面的相对好处。该项目将培训一名研究生和两名来自科学方面代表性不足群体的本科生，并向学生和社区群体提供外联服务。系统发育生态学领域为预测病原菌从一个宿主向另一个宿主的溢出模式和影响大小提供了一个清晰的框架，可用于病原体从农业系统向自然系统的溢出。这项研究将估计风和鸟类对真菌的移动，测量森林中的疾病发生率，并通过比较咖啡附近和远离咖啡的地块的林下植物的群落组成来评估咖啡对本地森林植物群落的影响。这个项目是高风险-高回报的，因为它应用了真菌溢出的系统发育框架，它测量了从农业到自然栖息地的双向移动和溢出，以及它对鸟类和风在植物相关真菌传播中的作用的研究。通过研究咖啡是引进物种但与许多林下植物物种密切相关的地点的咖啡林界面，该项目将检验系统发育群落生态学的两个完整假说：1)关系较近的寄主比远亲寄主共享更多病原体和疾病；2)关系较近的病原体与不太亲缘的病原体共享更多的寄主物种。测试用于预测疾病和植物群落组成的系统发育框架的效用，对于发展对农业和自然植物群落之间的生物相互作用的预测性理解非常重要。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Many agricultural lands and protected natural areas are physically adjacent to each other and interact with each other, yet there have been few studies of how agricultural and natural ecosystems influence each other and what the consequences of these interactions are for both the effectiveness of agricultural management and the conservation of natural lands. Spillover is a term from disease ecology recently applied more generally to describe the movement and effects of organisms as they cross habitat boundaries. This project will advance understanding of the importance of spillover between agriculture and natural habitats and of the role of birds as well as wind in the dispersal of plant-associated fungi. By comparing fungi and plant disease between two types of coffee management, sun and shade, this research will inform decisions on the relative benefits of these agricultural strategies for coffee fungal disease management and for minimizing negative effects of spillover. This project will train a graduate student and two undergraduate students from underrepresented groups in science as well as provide outreach to student and community groups. The field of phylogenetic ecology provides a clear framework for predicting patterns and effect size of pathogen spillover from one host to others that can be applied to the spillover of pathogens from agricultural to natural systems. This research will estimate fungal movement by wind and birds, measure disease incidence in the forest, and assess effects of coffee on native forest plant communities by comparing community composition of understory plants at plots near and away from coffee. This project is high risk-high reward in its application of a phylogenetic framework to the community ecology of fungal spillover, its measurement of bi-directional movement and spillover from agriculture to natural habitats, and its examination of the role of birds as well as wind in the dispersal of plant-associated fungi. By examining the coffee-forest interface at sites where coffee is an introduced species yet closely related to many understory plant species, this project will test two integral hypotheses of phylogenetic community ecology: 1) more closely related hosts share more pathogens and disease than distantly related hosts; and 2) more closely related pathogens share more host species than less closely related pathogens. Testing the utility of a phylogenetic framework for predicting disease and plant community composition is important for developing a predictive understanding of biotic interactions between agricultural and natural plant communities.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.