Postdoctoral Research Fellowships in Biology for FY 2009

2009财年生物学博士后研究奖学金

• 批准号: 0905885
• 负责人: Daniel Sheldon
• 金额: $ 12.3万
• 依托单位: Sheldon Daniel R
• 依托单位国家: 美国
• 项目类别: Fellowship Award
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-01-01 至 2011-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0905885&HistoricalAwards=false
• 关键词: Postdoctoral; Research; Fellowships; Biology; FY

This action funds an NSF Postdoctoral Research Fellowship in Biology for FY 2009 under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). The fellowship supports a research and training plan entitled "Algorithms for changing species distributions: tracking the world's tree swallows" for Daniel Sheldon. The host institution for this research is Oregon State University, and the sponsoring scientist is Thomas Dietterich.Understanding the geographical distributions of species and how they change is critical to conservation, ecological science, and global climate change research. This research develops computational methods to quantify patterns of change in the distribution of the Tree Swallow (Tachycineta bicolor), a migratory songbird that forms dense communal roosts during its eight-month non-breeding season. The early-morning departure of birds from the roost creates a distinctive "roost ring" pattern that is visible in NEXRAD weather radar images. The project employs techniques from computer vision, machine learning and probabilistic modeling to automatically detect and extract roost rings from radar, assembles daily estimates of the distribution of Tree Swallows throughout the United States, and then infers the patterns of migration and other events that cause distribution changes over time, both short-term and long-term. One of the great assets of NEXRAD radar is the ability to look fifteen years into the past with archived data. This project addresses significant questions about the roosting biology and population trends of swallows, advances techniques in radar ornithology, and lays an algorithmic foundation for identifying patterns of change in species distributions.Training objectives include strengthening skills in computer vision, radar ornithology, and species distribution modeling. This research engages a broad audience of biologists, computer scientists, conservationists, and the general public by providing a complete and accurate model of songbird distribution on a large scale, with provisions to continuously monitor changes for the past fifteen years and into the future.

该行动为2009年的《 2009年美国回收与再投资法》（公法111-5）基金，为2009财年生物学的NSF博士后研究奖学金提供了资金。 该奖学金支持丹尼尔·谢尔顿（Daniel Sheldon）的研究和培训计划，名为“改变物种分布的算法：跟踪世界的燕子”。这项研究的主持机构是俄勒冈州立大学，赞助科学家是托马斯·迪特里奇（Thomas Dietterich）。理解物种的地理分布以及它们的变化方式对于保护，生态科学和全球气候变化研究至关重要。这项研究开发了计算方法，以量化树燕麦分布的变化模式（tachycineta bicolor），这是一种迁徙的鸣禽，在其八个月的非繁殖季节形成了密集的公共栖息地。鸟类远离栖息的早晨出发产生了独特的“栖息地环”图案，在Nexrad天气雷达图像中可见。该项目采用计算机视觉，机器学习和概率建模的技术来自动检测和提取雷达中的栖息环，每天估算整个美国树燕子的分布，然后渗透迁移的模式和其他导致分布的事件随时间变化，短期和长期变化。 Nexrad雷达的最大资产之一是能够通过存档数据来期待过去十五年。该项目解决了有关燕子的栖息生物学和人口趋势，雷达鸟类学技术的进步，并为识别物种分布的变化模式奠定了重大问题。培训目标包括增强计算机视觉，雷达鸟类学和物种分布模型的技能。这项研究吸引了广泛的生物学家，计算机科学家，保护主义者和公众，通过大规模提供完整而准确的鸣禽分布模型，并提供了在过去的十五年中不断监视变化的规定。