Collaborative Proposal: MRA: Macroecology of microorganisms: Scaling fungal biodiversity from soil cores to the North American continent

土壤真菌大多是肉眼看不见的，但它们提供了广泛的生态系统功能：作为分解者，它们分解复杂的有机物质，作为植物的共生伙伴，它们帮助植物清除稀缺的营养物质，促进生长。由于这两种作用都涉及碳、氮和磷等关键元素的转移，因此这些真菌在全球营养收支中起着至关重要的作用。土壤真菌还可以作为植物和动物的病原体来调节生态系统。在某些情况下，病原真菌可能产生有害影响，如作物病害暴发，但更常见的是，它们通过防止任何单一物种主宰生态系统，在全球范围内促进生物多样性。尽管它们在调节这些关键的生态系统功能方面发挥着作用，但人们对是什么决定了整个北美大陆真菌群落的结构以及真菌群落结构的未来变化可能产生的后果知之甚少。实现这一研究目标的主要障碍之一是缺乏大规模、系统地取样和鉴定土壤真菌的努力。该研究项目将通过使用两个新的下一代DNA测序数据集来量化土壤真菌多样性模式来克服这一障碍，这些数据集表征了北美大陆的土壤真菌群落：国家生态观测站网络（NEON）和北美土壤真菌生物多样性维度项目（DoB-FUN）。通过利用最先进的建模技术，不仅考虑土壤真菌如何随环境变化，而且考虑这些变化如何依赖于它们邻近的植物群落，该项目将改变我们对土壤微生物多样性的理解。通过整合两个最广泛的土壤真菌群落数据集，采用几乎相同的采样设计、分子方法和空间范围，研究人员将有一个前所未有的机会来回答关于构成微生物地理范围和生物多样性的基本因素的两个关键问题。(1)什么是关键的环境变量，(2)真菌和植物之间的相互作用和关联如何影响它们？研究人员将利用这些信息，采用一种新颖的三管齐下的方法在社区层面对生物多样性进行建模：自上而下、自下而上和综合方法。这种方法克服了以往研究中的一个重大限制，即未能考虑到物种相互作用在控制微生物分布中的重要性。新的数据和模型将有助于解决从微生物到宏观系统的预测中的关键挑战。在快速环境变化的背景下，该项目可以在大陆尺度上对微生物多样性的变化和不确定性做出一些第一个强有力的预测。虽然初步结果已经强调了真菌群落组成和地理分布未来发生实质性变化的可能性，但自上而下，自下而上和集成建模方法的综合将使我们对真菌生物地理学的理解取得重大进展，并能够预测真菌对未来环境胁迫的反应。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Soil fungi are mostly invisible to the naked eye, but they provide a wide range of ecosystem functions: as decomposers, they break down complex organic materials, and as plant symbiotic partners, they help plants scavenge for scarce nutrients that improve growth. Because both these roles involve a transfer of critical elements, such as carbon, nitrogen, and phosphorus, these fungi play an essential part in global nutrient budgets. Soil fungi can also regulate ecosystems by acting as pathogens of plants and animals. In some cases, pathogenic fungi can have detrimental impacts such as crop disease outbreaks, but more commonly, they promote biodiversity on a global scale by preventing any single species from dominating the ecosystem. Despite their role in regulating these critical ecosystem functions, little is known about what determines the structure of fungal communities across the North American continent, and what consequences future changes in fungal community structure may have. One of the main barriers to this research goal is the lack of a large-scale, systematic effort to sample and identify soil fungi. This research project will overcome this barrier by quantifying patterns of soil fungal diversity using two new, next-generation DNA sequencing datasets that characterize soil fungal communities across the North American continent: the National Ecological Observatory Network (NEON) and the Dimensions of Biodiversity project on North American soil fungi (DoB-FUN). By leveraging state-of-the-art modeling techniques to consider not only how soil fungi change with the environment, but how those changes may depend on their neighboring plant communities, this project will transform our understanding of soil microbial diversity.By integrating two of the most extensive datasets on soil fungal communities with nearly identical sampling design, molecular methods, and spatial range, the investigators will have an unprecedented opportunity to answer two key questions about the fundamental factors that structure microbial geographic ranges and biodiversity. (1) What are the key environmental variables, and (2) how are they influenced by the interactions and associations between fungi and plants? The researchers will leverage this information with a novel three-pronged approach to modeling biodiversity at the community-level: top-down, bottom-up, and integrated methods. This approach overcomes a significant limitation in previous studies, which fail to account for the importance of species interactions in controlling microbial distributions. The novel data and models will help solve critical challenges in scaling predictions from microorganisms to macrosystems. In the context of rapid environmental change, this project can make some of the first robust predictions of change and uncertainty in microbial diversity at the continental scale. While preliminary results have already highlighted the possibility for substantial future changes in fungal community composition and geographic distribution, the synthesis of top-down, bottom-up, and integrated modeling approaches will lead to significant advances in our understanding of fungal biogeography and the ability to forecast the response of fungi to future environmental stressors.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.