LiT: Life History Responses to Genetic and Environmental Perturbations in Arabidopsis thaliana

为了在有利的条件下开花，植物利用来自多种环境信号的信息，如白天的长度、温度和冬季的寒冷程度。然而，全球变暖不仅会改变温度，还会改变生长季节的时间和长度，因此可能会造成以前准确的线索与这些事件的实际时间之间的不匹配。例如，温暖的冬天可能没有足够的寒冷来触发开花，导致开花延迟，尽管春天早些时候变暖。因此，该项目将探索季节时间对遗传和环境变化的敏感性。这项研究将利用遗传模式物种拟南芥的现有信息和工具，拟南芥是油菜、卷心菜、西兰花、芜菁和芥菜等作物的一年生近亲。它将预测数学模型与现场和控制室实验相结合。研究将会问：1。在自然的季节环境中，冬季冷却需求的遗传变异如何影响开花时间？2. 在自然环境中，自然选择是如何作用于这种变化的？3. 全球变暖情景预测的更高温度将如何影响开花的季节时间？该模式的预测将在受控的室内环境中进行实验测试，模拟21世纪末预测的变暖温度的影响。如果这个模型是准确的，那么变暖的气温和冬季寒冷的减少将改变季节时间和不同基因变异的相对时间。植物季节性事件（如叶片出芽、开花、结果和衰老）的准确时间对作物和林业产量以及野生物种在气候变化面前的生存至关重要。因此，这项研究的结果对于预测农作物、杂草、森林树木和野生植物群落将如何应对全球变暖具有重要意义。该建模方法将是传统作物模型的重大进步，并可能提高其通用性和预测能力。本项目将为两名女性科学家提供就业机会和培训：一名博士后研究员和一名博士研究员在职业中断后重返工作岗位。它还将为一些本科生提供研究机会，并将支持为罗德岛高中教师开发一个关于植物对气候变化的反应的课堂模块。

In order to flower during favorable conditions, plants use information from multiple environmental signals, such as day length, temperature, and winter chilling. However, global warming will alter not only temperatures, but also the timing and length of the growing season, and may thus create a mismatch between formerly accurate cues and the actual timing of those events. For example, warmer winters may not allow sufficient chilling to trigger flowering, resulting in delayed flowering despite earlier spring warming. This project will therefore explore the sensitivity of seasonal timing to genetic and environmental change. The study will take advantage of information and tools available for the genetic model species Arabidopsis thaliana, a weedy annual relative of crops such as canola, cabbage, broccoli, turnips, and mustard. It will combine a predictive mathematical model with field and controlled chamber experiments. The research will ask: 1. How does genetic variation in winter chilling requirements affect flowering time in natural seasonal environments? 2. How does natural selection act upon this variation in natural environments? 3. How will higher temperatures predicted by global warming scenarios affect seasonal timing of flowering? Predictions of the model will be tested experimentally in controlled chamber environments simulating effects of warming temperatures predicted for the end of the 21st century. If the model is accurate, warming temperatures and reduced winter chilling will alter seasonal timing and the relative timing of different genetic variants. Accurate timing of plant seasonal events - such as leaf emergence, flowering, fruiting and senescence - is critical for crop and forestry yields, as well as for the survival of wild species in the face of climate change. The results of this study will therefore be important for predicting how crops, weeds, forest trees, and wild plant communities will respond to global warming. The modeling approach will be a significant advance from traditional crop models and may improve their generality and predictive ability. This project will provide career opportunities and training for two female scientists: a postdoctoral researcher and a Ph.D researcher returning to the workforce after a career interruption. It will also provide research opportunities to several undergraduates, and will support development of a classroom module on plant responses to climate change for Rhode Island high school teachers.