Plant population and community responses to environmental change

植物种群和群落对环境变化的反应

• 批准号: RGPIN-2022-03937
• 负责人: Vellend, Mark
• 金额: $ 4.74万
• 依托单位: Université de Sherbrooke
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=745033
• 关键词: Plant; population; community; responses; environmental

The timing of yearly events in a plant's life, such as the emergence of leaves or flowers, has important consequences for how those plants perform and how they interact with other populations and other species. Since the timing of such events ("phenology") is sensitive to climatic conditions, we expect potentially important ecological consequences of climate change acting through phenology. However, testing hypotheses involving year-to-year climate fluctuations climate requires long-term data, which is rare in ecology. My central objective is to test hypotheses concerning causal links between climate, phenology, plant fitness, and species interactions. Over the next 5 years, long-term monitoring plots for plant flowering and a network of automated cameras for vegetative phenology will be extended to durations of 15 and 10 years, respectively. Analyses of these data, along with targeted experiments manipulating hypothesized causal factors, will permit mechanistic understanding of the causes and consequences of plant phenology. The outcome will be major advances in fundamental ecological understanding, with benefits both to science and to Canada via an improved basis for forecasting the ecological consequences of climate change. The research takes place in Parc national du Mont Mégantic, Québec, where low-elevation temperature deciduous forest is dominated by sugar maple, and high-elevation boreal forest is dominated by balsam fir and red spruce. The focus is largely on understory plants that emerge in early spring and that take advantage of a 4 to 5-week period of high light, prior to the expansion of canopy tree leaves. There are 3 research themes. Theme 1 focuses on flowering phenology and will first test the hypotheses that (i) flowering time is most sensitive to snowmelt, (ii) climate warming will cause reduced potential for gene flow across populations at different elevations, and (iii) climate warming is associated with novel combinations of plant species that flower simultaneously. Subsequent experimental studies will test for potential consequences of altered phenology (e.g., for plant-pollinator interactions). Theme 2 focuses on vegetative (leaf) phenology and will first test the hypothesis that the duration of the high-light period for spring understory plants will increase with climate warming. Theme 3 will use manipulative experiments to test causal factors (e.g., snowmelt, temperature, day length) that potentially underlie patterns observed in the field for both flowering and vegetative phenology. The proposed research program involves production of a landmark long-term data on plant phenology, with a unique combination of high temporal resolution, detailed data on flower or plant numbers and sizes (rather than only presence), and coverage of a steep climatic (elevational) gradient. Combined with the targeted experimental studies, the results will permit major scientific advances.

植物生命中每年事件的时间，例如叶子或花朵的出现，对这些植物的表现以及它们如何与其他种群和其他物种相互作用具有重要影响。由于这些事件（“物候”）的时间是敏感的气候条件，我们预计通过物候作用的气候变化的潜在重要的生态后果。然而，检验涉及逐年气候波动的假设需要长期数据，这在生态学中是罕见的。我的中心目标是测试有关气候，物候，植物健身和物种之间的相互作用的因果关系的假设。在未来5年内，植物开花的长期监测地块和植物物候的自动相机网络将分别延长至15年和10年。这些数据的分析，沿着有针对性的实验操纵假设的因果因素，将允许植物物候的原因和后果的机械理解。其结果将是在基本生态认识方面取得重大进展，通过改善预测气候变化生态后果的基础，对科学和加拿大都有好处。这项研究在魁北克省梅甘蒂克山国家公园进行，那里的低海拔温度落叶林以糖枫为主，高海拔北方森林以香脂冷杉和红云杉为主。重点主要放在早春出现的林下植物上，这些植物在树冠树叶展开之前利用了4到5周的强光。有三个研究主题。主题1侧重于开花物候学，并将首先测试以下假设：（i）开花时间对融雪最敏感，（ii）气候变暖将导致不同海拔地区种群间基因流动的潜力降低，（iii）气候变暖与同时开花的植物物种的新组合有关。随后的实验研究将测试改变物候的潜在后果（例如，植物-传粉者相互作用）。主题2侧重于植物（叶）物候，并将首先测试的假设，即春季林下植物的高光期的持续时间将随着气候变暖而增加。主题3将使用操纵实验来测试因果因素（例如，融雪、温度、日长），这可能是在田间观察到的开花和营养物候模式的基础。拟议的研究计划涉及生产具有里程碑意义的植物物候长期数据，具有高时间分辨率，详细的花或植物数量和大小（而不仅仅是存在）的数据，以及陡峭的气候（海拔）梯度的覆盖范围的独特组合。结合有针对性的实验研究，结果将允许重大科学进步。