BRC-BIO: Using analysis of historical and contemporary samples to elucidate mechanisms of altitudinal range expansion by plants

物种分布随时间和空间而变化，通常与环境条件有关。由于气候变化，环境正在迅速而剧烈地变化。这些变化对植物产生了影响。环境变化的幅度和植物应对这种变化的能力将决定它们的长期命运。植物应对气候变化的一种方式是向更适合的环境迁移。因此，当环境发生变化时，范围转移可能是植物种群的重要应对机制。本项目利用模式物种拟南芥的非本地种群来了解海拔范围扩张背后的进化机制。非本地物种是理想的、无计划的实验，有助于理解对新环境的反应。这项工作将利用保存在植物标本馆的历史样本，直接探索随时间的变化。历史样本也将与当代人群的样本相结合。这些样本将共同用于探索沿海拔梯度的适应模式。与这项研究相结合的是加州州立大学圣贝纳迪诺（CSUSB）植物标本馆的一个长期社区外展项目。这个项目针对的是在校学生、他们的家庭和K-12学生。该项目旨在展示当地植物群落的丰富性和生态相关性。植物标本室还努力提高人们对植物文化相关性的认识。最后，研究数据将被纳入基于课程的本科研究经验（CURE），为学生提供实践研究经验。通常，对过去生态进化事件的推断是基于现有种群的。不幸的是，这只提供了长期过程的一个快照。历史上的植物标本可以直接观察时间和空间的变化。本项目利用历史和当代样本，研究了拟南芥150多年来在加利福尼亚海拔移动的生态进化机制。植物标本室记录的数据显示，拟南芥在低海拔地区生活了大约40年。随后，在接下来的60年里，拟南芥扩展到海拔2000米以上的地区。这些运动模式，以及它作为模式生物的地位，使得拟南芥非常适合研究各种问题。包括，有多少向上的海拔变化是由于适应？哪些特质是重要的？将使用两种互补的方法来回答这些问题。首先，对历史拟南芥样本的调查将确定其分布的时间变化。跨海拔梯度的当代种群平行研究将探索当地适应模式。植物标本和当代标本的全基因组测序数据将探索跨越时间和空间发生的遗传变化。此外，这些数据将用于测试适应的特征。基因组数据也将为基因组关联研究提供信息。健康相关性状的数据将确定不同时间（历史样本）和空间（当代样本）的形态变化，并测试它们是否表明海拔适应。定量数据将与基因组数据相结合。总之，这些数据将用于研究适应性，并确定多少表型可塑性是由环境和遗传控制的。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。

Species distributions changes over time and space, often in association with environmental conditions. Due to climate change, environments are rapidly and dramatically changing. These changes have consequences for plants. The magnitude of the environmental change and the ability of plants to respond to such changes will determine their long-term fate. One way plants may respond to climate change is moving to better suited environments. Thus, range-shifts may be an important coping mechanism for plant populations when environments change. This project uses non-native populations of the model species Arabidopsis thaliana to understand the evolutionary mechanisms behind altitudinal range expansion. Non-native species are ideal, non-planned experiments useful in understanding responses to new environments. This work will leverage historical samples stored in herbaria, to directly explore changes over time. Historical samples will also be combined with samples from contemporary populations. Together, these samples will be used to explore adaptation patterns along altitudinal gradients. Integrated with the research is a long-term community outreach program at the California State University, San Bernardino (CSUSB) herbarium. This program targets campus students, their families, and K-12 students. The program aims to showcase the richness and ecological relevance of the local plant community. The herbarium also strives to bring awareness of the cultural relevance of plants. Finally, the research data will be incorporated in a Course-based Undergraduate Research Experience (CURE) to provide students with hands-on research experience. Typically, inferences about past eco-evolutionary events are based on existing populations. Unfortunately, this offers only a snapshot of long-term processes. Historical herbaria samples allow direct observation of changes over time and space. This project uses historical and contemporary samples to study the eco-evolutionary mechanisms over ~150 years of altitudinal movement in California by Arabidopsis thaliana. Data from herbaria records show that A. thaliana stayed at low altitudes for approximately 40 years. Subsequently, in the next 60 years, A. thaliana spread to elevations above 2,000m. These movement patterns, along with its status as model organism, makes A. thaliana great to investigate various questions. Including, how much of the upward elevational shift is due to adaptation? And, which traits were important? Two complementary approaches will be used to answer these questions. First, investigation of historical A. thaliana samples will identify temporal changes in distribution. Parallel study of contemporary populations across altitudinal gradients will explore patterns of local adaptation. Whole genome sequencing data of both herbaria and contemporary samples will explore what genetic changes occurred across time and space. Further, the data will be used to test for signatures of adaptation. Genomic data will also inform genome association studies. Data on fitness-related traits will identify morphological changes across time (historical samples) and space (contemporary samples) and test if they are indicative of altitude adaptation. Quantitative data will be combined with genomic data. Together, these data will be used to investigate adaptation and determine how much phenotypic plasticity is environmentally vs. genetically controlled.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.