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.

居住在北部纬度的物种预计将在未来世纪经历巨大的气候变化，而基本和应用的科学家都需要有关这些变化对生活自然资源的影响的信息。 该项目将生成有用的统计工具和基线数据，以用于长期人口监测和管理，并提供有关野生动植物在不断变化的景观中持续存在的能力的重要信息。一名博士生将通过这项研究进行培训，并将将结果传达给公共土地机构，以直接应用到定义管理单位，建模未来的分配和野生动植物种群的丰富度以及为潜在物种范围转移的计划。 结果还将通过公共论坛广泛传播，包括被邀请的演讲活动，专业会议，公共广播和学校演讲。气候和景观模式在生物体的生理阈值之外发生变化时，该人群的持久性选择仅限于适应或移民。 对自然选择的基因的可靠鉴定是检测适应当地条件的空间量表的必要组成部分，并提供了关键的信息，以理解进化和种群的弹性。 然而，尚未严格检查统计检测选择的相对灵敏度，对于自然景观中的种群而言，统计测试的相对敏感性甚至较少。 该项目调查了我们能力的准确性和精度检测在较小的景观水平尺度和更广泛的物种水平尺度下自然存在的人群中的局部适应性。 来自新型遗传技术的计算机模拟和经验信息的结合将有助于研究环境变化，不同的人口规模以及迁移率对整个范围内北山野生绵羊的局部适应的影响。