Bioinformatics Starter Grant: Species-Specific Traits Controlling Forest and Woodland Dynamics Revealed by Bayesian Melding of Diverse Data and Process Models

生物信息学入门资助：通过贝叶斯融合不同数据和过程模型揭示控制森林和林地动态的物种特异性特征

• 批准号: 0630119
• 负责人: Kiona Ogle
• 金额: $ 5万
• 依托单位: University of Wyoming
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-09-01 至 2008-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0630119&HistoricalAwards=false
• 关键词: Bioinformatics; Starter; Grant; Species; Specific

The University of Wyoming is awarded a grant to supplement startup research funds for Dr. Kiona Ogle to develop a modeling and scaling framework that links physiological and structural traits at the individual and species level to the community and ecosystem level. This work integrates process models of tree growth and canopy interactions with empirical datasets. The project builds on work completed under a postdoctoral fellowship by implementing a hierarchical Bayesian melding method to couple process-based models of individual tree growth with field observation data. This approach will then be applied to a new context of water-limited woodland ecosystems.

怀俄明州的大学被授予补助金，以补充启动研究基金博士. Kiona Ogle开发一个建模和缩放框架，连接在个人和物种水平的生理和结构特征的社区和生态系统水平. 这项工作将树木生长和冠层相互作用的过程模型与经验数据集相结合。 该项目的基础上完成的博士后奖学金的工作，通过实施分层贝叶斯融合方法耦合基于过程的模型与现场观测数据的个别树木的生长。这种方法将被应用到一个新的背景下，水有限的林地生态系统。