Phylogenetic Disease Ecology of Plants

这项研究从一个简单的想法探索了三个预测：病原体通常可以攻击多个物种，当两个宿主物种彼此关系密切时，它们更有可能共享一个病原体。第一个预测是，通过考虑不同病原体物种和它们感染的不同宿主物种之间的关系，我们将提高我们预测自然界中哪些植物会受到哪些病原体的影响的能力。这一预测将在各种植物及其病原体上得到验证。第二个预测是，当一种新的植物物种（例如一种作物）被引入一个地区时，感染已经在那里生长的近亲的病原体将最有可能“溢出”并影响新的作物。最后一个预测是，由于病原体不太可能在不密切相关的物种之间传播，因此可以设计作物物种的混合物来减少农业中由于疾病引起的问题。在测试这些预测的过程中，研究人员将开发新的分析工具来研究植物病害。这项工作将有助于制定保护作物免受疾病侵害的新战略，以及保护其他宝贵的植物资源。这个项目的主要训练部分将包括高中班级、大学班级、毕业论文学生和博士生。这些学生将学习许多具有基础科学和经济重要性的领域的技能，包括森林生态学、生态监测、农业系统生态学、生态园艺学和生物信息学。这个项目将测试关于宿主系统发育亲缘关系和感染它们的病原体宿主范围之间关系的预测。对于该项目的三个组成部分中的每一个，研究人员将利用先前开发和验证的定量模型，该模型预测病原体寄主范围如何受到寄主植物之间进化关系的限制。在网络理论的新应用中，研究人员将把系统发育结构纳入植物-病原体相互作用的网络模型中。他们将使用宏基因组学方法（通过提取和测序其DNA来识别植物内部生长的所有真菌物种）来表征三个植物群落的植物-病原体网络，并将根据经验网络测试预测。新寄主将在田间进行移栽试验和在实验室进行接种试验，以测量哪些本地真菌在新寄主上定殖，以及本地植物-真菌网络的系统发育结构如何影响真菌对新寄主的溢出。最后，pi将与一家经过认证的有机研究农场合作，测试系统发育多样性的覆盖作物是否减少了疾病压力（一种被称为“稀释效应”的假设），以及间作物种之间更大的系统发育距离是否抑制了疾病。

This research explores three predictions that follow from a simple idea: that pathogens can often attack multiple species, and two host species are more likely to share a pathogen when they are closely related to each other. The first prediction is that by taking the relationships among different pathogen species and different hosts species that they infect into account, we will improve our ability to predict which plants can be affected by which pathogens in nature. This prediction will be tested with a variety of plants and their pathogens. The second prediction is that when a new plant species (such as a crop) is introduced into an area, pathogens that infect close relatives already growing there will be most likely to 'spill over' and affect the new crop. The last prediction is that because pathogens are less likely to spread between species that are not closely related, mixtures of crop species could be designed to reduce problems due to diseases in agriculture. In the process of testing these predictions, the researchers will develop new analytical tools for the study of plant disease. This work will aid in developing new strategies for protecting crop plants from disease, and for protecting other valuable plant resources. The large training component of this project will include high school classes, college classes, senior thesis students, and PhD students. These students will learn skills from many fields that have both basic science and economic importance, including forest ecology, ecological monitoring, ecology of agricultural systems, ecological horticulture and bioinformatics.This project will test predictions regarding the relationship between phylogenetic relatedness of hosts and the host ranges of the pathogens that infect them. For each of the three components of the project, the researchers will take advantage of a previously developed and validated quantitative model that predicts how pathogen host ranges are constrained by the evolutionary relationships among host plants. In a novel application of network theory, the researchers will incorporate phylogenetic structure into network models for plant-pathogen interactions. They will use a metagenomics approach (identifying all fungal species growing inside plants by extracting and sequencing their DNA) to characterize the plant-pathogen networks of three plant communities, and will test predictions against the empirical networks. Novel hosts will be used in a transplant experiment in the field and an inoculation experiment in the laboratory to measure which local fungi colonize novel hosts, and how the phylogenetic structure of local plant-fungus networks affects fungal spillover to novel hosts. Finally, collaborating with a certified organic research farm, the PIs will test whether phylogenetically diverse cover crops have reduced disease pressure, a hypothesis called the "Dilution Effect", and whether greater phylogenetic distance among intercropped species suppresses disease.