The 2nd Summer Institute: Uncertainty in Ecological Inference, Forecasting, and Decision ?Modern Statistical Computation

第二届暑期研修班：生态推理、预测与决策的不确定性？现代统计计算

• 批准号: 0527070
• 负责人: James Clark
• 金额: $ 12.6万
• 依托单位: Duke University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-09-01 至 2006-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0527070&HistoricalAwards=false
• 关键词: 2nd; Summer; Institute; Uncertainty; Ecological

A two-week Summer Institute for graduate and post-graduate students will be conducted to introduce environmental scientists to modern statistical techniques that have emerged over the last decade. Ecological inference and predictions are currently limited by the many sources of variability that operate at a range of scales. There are, however, powerful tools available for analyzing processes characterized by these sources of uncertainty and variation, including hierarchical Bayes and Markov chain Monte Carlo simulation. However, the widespread use of these techniques in ecology has been hindered due to limited training options. The 2nd Summer Institute will follow the format of the highly successful 1st Institute held in June 2004. Participants will include advanced graduate student and postdoctoral associates selected by an open application process. Leading statisticians and ecologists will provide day-long presentations and hands-on training with computational techniques. Students will participate in small working groups, with the aim of producing a published volume and lecture notes. The 2nd Summer Institute will take place in 2006, retaining aspects of the format that worked well in the 1st Institute, and incorporating modifications that will improve its effectiveness.By training a select group of quantitative environmental scientists who will in turn train others and use this training in their research, this 'summer school' will expedite the spread and use of modern statistical computation techniques. Adoption of these modern methods by ecologists and earth scientists will strengthen the field of ecological forecasting, enhance its reputation, and increase its usefulness to resource managers and policy makers. Many of the techniques that will be covered should directly enhance capacity to use network information available in distributed databases.

将为本科生和研究生举办为期两周的暑期学院，向环境科学家介绍过去十年出现的现代统计技术。生态推论和预测目前受到在不同尺度上运作的许多可变性来源的限制。然而，有强大的工具可用于分析以这些不确定性和变化源为特征的过程，包括分层贝叶斯和马尔可夫链蒙特卡罗模拟。然而，由于有限的培训选择，这些技术在生态学中的广泛使用受到了阻碍。第二届暑期班将采用2004年6月举行的非常成功的第一届暑期班的形式。参与者将包括通过开放申请程序挑选的高级研究生和博士后助理。领先的统计学家和生态学家将提供为期一天的演讲和计算机技术的实践培训。学生将参加小组讨论，目的是出版一本书和课堂讲稿。第二届暑期学院将于2006年举办，保留了第一届学院运作良好的模式的某些方面，并进行了修改，以提高其有效性。通过培训一批精选的定量环境科学家，这些科学家将反过来培训其他人，并在他们的研究中使用这种培训，这一“暑期班”将加快现代统计计算技术的传播和使用。生态学家和地球科学家采用这些现代方法将加强生态预测领域，提高其声誉，并增加其对资源管理者和政策制定者的有用性。将介绍的许多技术应直接增强使用分布式数据库中可用的网络信息的能力。