RII Track-1: Linking Genome to Phenome to Predict Adaptive Responses of Organisms to Changing Landscapes

植物和动物生活在一种脆弱的平衡中，这种平衡可能会被人类的土地利用决定所破坏。该项目旨在帮助土地所有者、州立公园规划者、城市规划者和爱达荷州的印第安部落在土地使用方面做出明智的决定，以最大限度地减少对当地野生动物的影响。为了做到这一点，来自全州几所学院和大学的研究人员将创建工具，这些工具将使用来自各种来源的数据，包括先进的遗传学、生态和地理数据库，以及来自土地所有者和美洲土著部落的调查结果。这些工具将为土地使用提供各种选择，鼓励最有效地利用土地，同时尽量减少对本地动植物物种的影响。通过这个项目，爱达荷州将吸引公众参与，培训下一代科学家，并开发令人兴奋的新工具，为科学的土地使用决策提供新方法。技术描述这项来自爱达荷州的研究基础设施改善（RII） Track-1项目将研究美国西部生态系统中的两个关键物种（红带鳟鱼和山艾树）。该项目将利用现有的环境遗产数据为基于主体的模型（ABM）提供信息，以预测这两个物种的适应能力。项目团队将通过实验确定基因组和现象之间的联系，以温度为关键变量，确定这些物种适应能力的基因组反应，并通过ABM迭代地将它们联系起来，以进一步了解遗传能力。最后，项目参与者将通过来自社会和经济科学的方法，通过其他影响（包括生物、非生物和各种人为影响）的环境结果和当地知识，绘制物种基因组图谱，为ABM模型提供信息。该模型将用于预测各种土地使用情景的结果，并将提交给利益相关者咨询小组，他们将根据模拟结果进行讨论并做出决策。涉众组所做的决定将进一步为模型提供信息。预计这种迭代反馈模型将成为爱达荷州及其他地区土地使用决策的变革性工具。此外，强大的劳动力发展计划将吸引爱达荷州三所研究型大学的教师、博士后、研究生和本科生，以及2年制和4年制本科院校（PUIs）的纵向整合项目方法，鼓励该机构的所有学术水平共同努力。在爱达荷州纳入不同类型的高等教育机构将解决和回答国家？it’我们需要在STEM领域训练有素的劳动力。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。

Non-technical DescriptionPlants and animals live in a fragile balance that can be upset by human land use decisions. This project aims to help landowners, state park planners, city planners, and Native American tribes in Idaho make informed decisions on land use that will minimize the effects on native wildlife. To do this, researchers from several colleges and universities across the state will create tools that will use data from a wide variety of sources including advanced genetics, ecological and geographical databases, and survey results from landowners and Native American tribes. These tools will provide options for land use that will encourage the most effective use of land while minimizing the impacts on native plant and animal species. Through this program, Idaho will engage the public, train the next generation of scientists, and develop exciting new tools that will provide new methods for scientifically informed land use decisions.Technical DescriptionThis Research Infrastructure Improvement (RII) Track-1 project from Idaho will study two keystone species (redband trout and sagebrush) in ecosystems of the American West. The project will use existing environmental legacy data to inform agent-based models (ABM) to predict adaptive capacity of these two species. The project team will determine the links between genomes and phenomes via experiments using temperature as the key variable to identify genomic responses of the adaptive capacity of these species and iteratively link them through the ABM to further inform our understanding of genetic capacity. Finally, the project participants will map species' genomes by environmental outcomes across additional impacts including biotic, abiotic, and various anthropogenic effects and local knowledge through methodologies originating from the social and economic sciences to inform the ABM model. The model will be used to predict the outcomes of various land use scenarios, and will be presented to stakeholder advisory groups who will discuss and make decisions based on the results from simulations. Decisions made by the stakeholder groups will further inform the model. It is expected that this iterative feedback model will be a transformative tool for land use decisions in Idaho and beyond. Additionally, strong workforce development plans will engage faculty, postdocs, graduate, and undergraduate students of the three research universities in Idaho, as well as 2- and 4-year Primarily Undergraduate Institutions (PUIs) in a Vertically Integrated Project approach that encourages all academic levels of the institution to work together. The inclusion of different types of higher educational institutions across Idaho will address and answer the state?s need for a well-trained workforce in STEM fields.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.