DISSERTATION RESEARCH: DETECTING SELECTION ACROSS SPATIAL SCALES AND ENVIRONMENTAL GRADIENTS

论文研究：检测跨空间尺度和环境梯度的选择

• 批准号: 1407300
• 负责人: Gordon Luikart
• 金额: $ 1.84万
• 依托单位: University of Montana
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-06-01 至 2016-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1407300&HistoricalAwards=false
• 关键词: DISSERTATION; RESEARCH; DETECTING; SELECTION; ACROSS

Species that inhabit Northern latitudes are expected to experience dramatic climate changes in the coming century, and both basic and applied scientists need information about the effect of these changes on living natural resources. This project will produce useful statistical tools and baseline data for long-term population monitoring and management, and deliver important information regarding the ability of wildlife to persist in a changing landscape. One PhD student will be trained through this research, and will communicate results to collaborating public lands agencies for direct application to defining management units, modeling future distribution and abundance of wildlife populations, and planning for potential species range shifts. Results will also be broadly disseminated through public forums including invited speaking events, professional meetings, public radio, and school presentations.When climate and landscape patterns change beyond an organism's physiological threshold, the options for persistence of that population are limited to adaptation or migration. Reliable identification of genes underlying signatures of natural selection is a necessary component of detecting the spatial scale at which adaptation to local conditions occurs, and provides critical information for understanding evolution and population resilience. However, the relative sensitivity of statistical tests to detect selection has not been rigorously examined, even less so for populations in natural landscapes. This project investigates the accuracy and precision of our ability detect local adaptation in naturally occurring populations at both smaller, landscape level scales, and broader, species-level scales. A combination of computer simulations and empirical information from novel genetic techniques will facilitate investigation of the influence of environmental variation, different population sizes, and migration rates on local adaptation of a northern alpine wild sheep throughout its range.

居住在北方纬度的物种预计将在未来世纪经历剧烈的气候变化，基础科学家和应用科学家都需要有关这些变化对生物自然资源影响的信息。 该项目将为长期种群监测和管理提供有用的统计工具和基线数据，并提供有关野生动物在不断变化的景观中持续生存能力的重要信息。一名博士生将通过这项研究进行培训，并将结果传达给合作的公共土地机构，以直接应用于定义管理单位，模拟未来野生动物种群的分布和丰度，并规划潜在的物种范围变化。 研究结果还将通过公共论坛广泛传播，包括邀请演讲活动、专业会议、公共广播和学校报告。当气候和景观模式的变化超出生物体的生理阈值时，该种群的持续性选择仅限于适应或迁移。 可靠的识别基因的自然选择的签名是一个必要的组成部分，检测的空间尺度，适应当地条件发生，并提供了重要的信息，了解进化和人口弹性。 然而，相对敏感的统计测试，以检测选择还没有严格审查，更不用说在自然景观的人口。 该项目调查了我们在较小的景观水平尺度和更广泛的物种水平尺度上检测自然发生的种群的局部适应能力的准确性和精确性。 结合计算机模拟和经验信息，从新的遗传技术，将有利于调查的影响，环境变化，不同的人口规模和迁移率的本地适应的北方高山野生绵羊在其整个范围。