DISSERTATION RESEARCH: DETECTING SELECTION ACROSS SPATIAL SCALES AND ENVIRONMENTAL GRADIENTS

居住在北纬的物种预计在下个世纪将经历剧烈的气候变化，基础科学家和应用科学家都需要关于这些变化对生物自然资源的影响的信息。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地貌中生存的能力的重要信息。一名博士生将通过这项研究接受培训，并将结果传达给合作的公共土地机构，以便直接应用于定义管理单元，模拟未来野生动物种群的分布和数量，并规划潜在的物种范围转移。结果还将通过公共论坛广泛传播，包括受邀的演讲活动、专业会议、公共广播和学校演讲。当气候和景观格局变化超过生物体的生理阈值时，该种群持续生存的选择仅限于适应或迁徙。可靠地识别自然选择特征背后的基因是检测适应当地条件的空间尺度的必要组成部分，并为理解进化和种群复原力提供关键信息。然而，统计检验对检测选择的相对敏感度还没有得到严格的检验，对自然景观中的种群更是如此。这个项目调查了我们在较小的景观水平和更广泛的物种水平上检测自然种群局部适应的能力的准确性和精确度。计算机模拟和来自新的遗传技术的经验信息的结合将有助于研究环境变化、不同的种群规模和迁移率对北部高山野生绵羊整个范围内局部适应的影响。

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.