Collaborative Research: SG: Effects of altered pollination environments on plant population dynamics in a stochastic world

合作研究：SG：随机世界中授粉环境改变对植物种群动态的影响

• 批准号: 2337426
• 负责人: Amy Iler
• 金额: $ 19.38万
• 依托单位: Rocky Mountain Biological Laboratory
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-04-01 至 2028-03-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2337426&HistoricalAwards=false
• 关键词: Collaborative; Research; SG; Effects; altered

A major challenge in biology is understanding how random fluctuations in the environment affect populations and their ability to persist. For plants, this is compounded by declines in pollinators, which have been documented across the world. There is concern that many flowering plant species will decline alongside their pollinators because almost 90% of flowering plants rely on animal pollination to make seeds, grow new plants, and prevent extinction. Short-term, year-to-year fluctuations in pollinators and other environmental factors (like precipitation) during a longer-term decline make the challenge of identifying a true plant decline even harder. Despite the strong dependence of plants on pollinators, pollinator declines may not immediately cause plant declines, and this can prevent us from detecting the warning signs of plant extinction. For example, plants may appear to do better immediately after a pollinator decline by reinvesting energy that would have been used to make seeds into improving their survival. This project will amplify natural variation in pollination for thousands of plants, follow their fates, and use mathematical models to understand how plants persist despite year-to-year changes in pollination and other environmental factors. This project will help scientists to understand why some plant species are more at risk from pollinator declines than other species. The project will leverage 9–11 years of field-based data on plant demography and pollinator abundance to measure and experimentally impose stochastic fluctuations in pollinator abundance. Individual-based population models (integral projection models) will be parameterized with data from a long-term, ongoing field experiment in which two species of perennial plants receive different pollination treatments: (i) increased pollination, (ii) reduced pollination, and (iii) an unmanipulated control. All plants are tagged with a unique identification number and their demographic status assessed annually. Projections of the population models will demonstrate the consequences of stochasticity in pollination services for plant population dynamics. Further analyses based on model-based population projections will reveal which demographic vital rates (survival, growth, reproduction) are responsible for changes in population dynamics when pollinator abundances fluctuate, in addition to how various components of stochasticity – the mean, variance, and autocorrelation of pollinator abundances – affect plant population dynamics. This project will shed new light on how species interactions shape population dynamics in a stochastic world.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.

生物学的一个主要挑战是了解环境中的随机波动如何影响人群及其持久能力。对于植物而言，这在世界范围内已记录的授粉媒介中的下降使它更加复杂。令人担忧的是，许多开花植物物种会随着授粉媒介而下降，因为几乎90％的开花植物依靠动物授粉来制造种子，种植新植物并防止延伸。在长期下降期间，授粉媒介和其他环境因素（例如降水）的短期，年复一年的波动使确定真正植物下降的挑战更加困难。尽管植物对授粉媒介的依赖性很强，但授粉媒介的下降可能不会立即导致植物下降，这可以阻止我们检测到植物扩展的警告信号。例如，在授粉媒介下降后，通过再投资可以使用的能量，植物可能会立即做得更好，该项目将扩大数千种植物的授粉自然变化，遵循其命运，并使用数学模型来了解植物如何在授粉中持续存在授粉的目的地变化和其他环境因素。该项目将帮助科学家了解为什么某些植物物种比其他物种更容易受到授粉的风险。该项目将利用9 - 11年的基于现场的植物解释学和传粉媒介丰度的数据，以测量和实验性地施加传粉媒介丰度的随机波动。基于个体的人群模型（积分投影模型）将通过长期，持续的现场实验的数据进行参数化，其中两种多年生植物植物会接受不同的授粉处理：（i）授粉的增加，（ii）减少授粉和（iii）无操纵的控制。所有植物均标有唯一的识别码及其每年评估的人口统计状态。人口模型的预测将证明授粉服务对植物种群动态的随机性后果。基于基于模型的人群预测的进一步分析将揭示哪些人口重要率（生存，增长，繁殖）负责授粉媒介抽象的波动，除了各种随机性（均值，方差和自相关的各种成分）如何影响植物的人群动力学。该项目将为物种相互作用如何影响随机世界中的种群动态提供新的启示。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响标准，被视为通过评估而被视为珍贵的支持。