NSF Postdoctoral Fellowship in Biology FY 2021: Tracing coral reef energy fluxes from genes to ecosystems in a changing climate

2021 财年 NSF 生物学博士后奖学金：追踪气候变化中从基因到生态系统的珊瑚礁能量通量

• 批准号: 2109411
• 负责人: Jennifer Bigman
• 金额: $ 13.8万
• 依托单位: Bigman, Jennifer
• 依托单位国家: 美国
• 项目类别: Fellowship Award
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-06-01 至 2024-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2109411&HistoricalAwards=false
• 关键词: NSF; Postdoctoral; Fellowship; Biology; FY

This action funds an NSF Postdoctoral Research Fellowship in Biology for FY 2021, Integrative Research Investigating the Rules of Life Governing Interactions Between Genomes, Environment and Phenotypes. The fellowship supports research and training of the fellow that will contribute to the area of Rules of Life in innovative ways. Understanding and measuring aspects of the biology of species and the communities in which they live is crucial to predicting how they will respond to a changing climate. Metabolic rate, or the rate at which organisms acquire and allocate energy to life-sustaining processes such as growth and reproduction, links species to their environments. Thus, metabolic rate may be a useful tool to understand the structure and dynamics of species and their ecosystems, as well as provide an opportunity to predict the effects of climate change. This is especially important for ecosystems that are sensitive to climate change such as coral reefs, which are globally in decline due to climate change, overfishing, pollution, and other human-induced threats. Thus, this project will use coral reef ecosystems as a model to test whether the metabolic rate of individual fish species can be used to explain and predict the dynamics of ecosystems now and in the future. The project supports education and outreach for other scientists, local communities, and students and other members of the public through a variety of methods. The project aims to empirically test ecological theory that posits that metabolic rate governs biological processes at all scales of organization and as such, can be used to predict current and future ecosystem dynamics that are traditionally difficult-to-estimate. The Fellow will use cryptobenthic fishes in the gobiid genus Eviota as a model system to test the validity of using metabolic rate to understand and predict these processes. Specifically, the Fellow will couple field-based collections, molecular ecology, and physiological trials alongside a novel theoretical modeling framework to (1) validate the use of metabolic rate to explain and predict the demography and life history of cryptobenthic fishes, (2) assess whether metabolic rate governs ecosystem functioning through its influence on life history, demography, and interspecific interactions, (3) quantify the cascading effects of increasing temperature on ecosystem functioning through its effects on individual metabolism, and (4) explore the eco-evolutionary determinants of metabolic rate through a population genomic framework. Through this project, the Fellow will become broadly trained in diverse and cutting-edge methodologies and contribute to other broader impacts including engagement with other researchers via working groups, outreach with local communities, no-cost quantitative ecology workshops for under-represented groups in science, and opportunities for student participation in metabolic theory and coral reef ecology.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.

该行动资助了2021财年的NSF生物学博士后研究奖学金，即调查基因组，环境和表型之间相互作用的生命规则的综合研究。该研究金支持研究员的研究和培训，以创新的方式为生活规则领域做出贡献。了解和测量物种的生物学和它们所生活的社区的各个方面对于预测它们将如何应对气候变化至关重要。代谢率，或生物体获取和分配能量以维持生命过程（如生长和繁殖）的速率，将物种与环境联系起来。因此，代谢率可能是了解物种及其生态系统的结构和动态的有用工具，并为预测气候变化的影响提供了机会。这对于对气候变化敏感的生态系统尤其重要，例如珊瑚礁，由于气候变化，过度捕捞，污染和其他人为威胁，全球珊瑚礁正在下降。因此，该项目将以珊瑚礁生态系统为模型，测试单个鱼类物种的代谢率是否可用于解释和预测生态系统现在和未来的动态。该项目通过各种方法支持对其他科学家、当地社区、学生和其他公众成员的教育和宣传。该项目旨在实证检验生态理论，该理论认为代谢率在所有组织尺度上都控制着生物过程，因此可以用来预测传统上难以估计的当前和未来生态系统动态。该研究员将使用隐底鱼类在戈比科属Eviota作为一个模型系统，以测试使用代谢率来理解和预测这些过程的有效性。具体而言，研究员将结合实地收集，分子生态学和生理学试验以及一个新的理论建模框架，以（1）验证代谢率的使用来解释和预测隐底鱼类的人口统计学和生活史，（2）评估代谢率是否通过其对生活史，人口统计学和种间相互作用的影响来控制生态系统功能，（3）通过对个体代谢的影响来量化温度升高对生态系统功能的级联效应;（4）通过种群基因组框架探索代谢率的生态进化决定因素。通过这个项目，研究员将在多样化和尖端方法方面得到广泛的培训，并为其他更广泛的影响做出贡献，包括通过工作组与其他研究人员接触，与当地社区进行外联，为科学界代表性不足的群体举办免费的定量生态学研讨会，以及学生参与代谢理论和珊瑚礁生态学的机会。该奖项反映了NSF的法定使命，并已被视为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，