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

RII Track-1：将基因组与表型组联系起来以预测生物体对不断变化的景观的适应性反应

• 批准号: 1757324
• 负责人: Andrew Kliskey
• 金额: $ 2000万
• 依托单位: Regents of the University of Idaho
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-10-01 至 2024-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1757324&HistoricalAwards=false
• 关键词: RII; Track; Linking; Genome; Phenome

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.

植物和动物生活在一个脆弱的平衡中，可能会被人类的土地使用决定所破坏。该项目旨在帮助爱达荷州的土地所有者、州立公园规划者、城市规划者和美洲原住民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，以及土地所有者和美洲原住民部落的调查结果。这些工具将提供土地利用的备选办法，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。通过这一计划，爱达荷州将参与公众，培养下一代科学家，并开发令人兴奋的新工具，将提供新的方法，科学知情的土地使用decision.Technical Description这一研究基础设施改善（RII）轨道-1项目从爱达荷州将研究两个关键物种（红带鳟鱼和山艾树）在美国西部的生态系统。该项目将利用现有的环境遗留数据为基于代理的模型（ABM）提供信息，以预测这两个物种的适应能力。该项目团队将通过实验确定基因组和表型之间的联系，使用温度作为关键变量，以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，以进一步了解我们对遗传能力的理解。最后，项目参与方将通过社会和经济科学的方法，根据生物、非生物和各种人为影响等其他影响的环境结果以及当地知识绘制物种基因组图谱，为反弹道导弹模型提供信息。该模型将用于预测各种土地使用情景的结果，并将提交给利益攸关方咨询小组，他们将根据模拟结果进行讨论并作出决定。利益相关者群体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利用决策的变革工具。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年和4年制的初级本科院校（PUI），采用垂直整合项目方法，鼓励机构的所有学术水平共同努力。包括不同类型的高等教育机构在爱达荷州将解决和回答国家？该奖项反映了NSF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。

项目成果

How does extreme point sampling affect non-extreme simulation in geographical random forest?

极值点采样如何影响地理随机森林中的非极值模拟？

• DOI: 10.1007/s12145-024-01268-9
• 发表时间: 2024
• 期刊: Earth Science Informatics
• 影响因子: 2.8
• 作者: Wang, Hui;Chen, Meixu;Wang, Zhe;Huang, Li;Caudill, Christopher C.;Qu, Shijin;Que, Xiang
• 通讯作者: Que, Xiang

Using Decision Analysis to Determine the Feasibility of a Conservation Translocation

使用决策分析确定保护易位的可行性

• DOI: 10.1287/deca.2023.0472
• 发表时间: 2023
• 期刊: Decision Analysis
• 影响因子: 1.9
• 作者: Keating, Laura M.;Randall, Lea;Stanton, Rebecca;McCormack, Casey;Lucid, Michael;Seaborn, Travis;Converse, Sarah J.;Canessa, Stefano;Moehrenschlager, Axel
• 通讯作者: Moehrenschlager, Axel

Unifying community detection across scales from genomes to landscapes

• DOI: 10.1111/oik.08393
• 发表时间: 2021-04
• 期刊: Oikos
• 影响因子: 3.4
• 作者: Stephanie F. Hudon;A. Zaiats;Anna V. Roser;A. Roopsind;Cristina Barber;B. Robb;Britt Pendleton;Meghan J. Camp;Patrick E. Clark;Merry M. Davidson;Jonas Frankel‐Bricker;Marcella R. Fremgen-Tarantino;J. Forbey;Eric J. Hayden;Lora A. Richards;Olivia K. Rodríguez;T. T. Caughlin-T.

Genomic Analyses of Phenotypic Differences Between Native and Invasive Populations of Diffuse Knapweed (Centaurea diffusa)

• DOI: 10.3389/fevo.2020.577635
• 发表时间: 2021-01-08
• 期刊: FRONTIERS IN ECOLOGY AND EVOLUTION
• 影响因子: 3
• 作者: Turner，Kathryn G.;Ostevik，Kate L.;Rieseberg，Loren H.
• 通讯作者: Rieseberg，Loren H.

Simulated Indigenous fire stewardship increases the population growth rate of an understorey herb

• DOI: 10.1111/1365-2745.13542
• 发表时间: 2020-11-29
• 期刊: JOURNAL OF ECOLOGY
• 影响因子: 5.5
• 作者: Hart-Fredeluces, G. M.;Ticktin, Tamara;Lake, Frank K.
• 通讯作者: Lake, Frank K.