EAGER: Advancing Biological Interpretations of Radar Data

EAGER：推进雷达数据的生物学解释

• 批准号: 1340921
• 负责人: Jeffrey Kelly
• 金额: $ 29.95万
• 依托单位: University of Oklahoma Norman Campus
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-08-15 至 2017-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1340921&HistoricalAwards=false
• 关键词: EAGER; Advancing; Biological; Interpretations; Radar

Earth's seasonality produces a flow of energy, information, and biodiversity between tropical and temperate regions. Much of this flow occurs through the aerosphere is a broad diversity of migratory animals. Long distance migration and dispersal is an important contributor to the rapid seasonal redistribution of productivity, spread of disease, and shifts in biodiversity across and among continents. Visualizing and modeling the collective behaviors of the diversity of animals that use the aerosphere for foraging, dispersal, and migration is pivotal to understanding and forecasting continental macroecological dynamics; and will be a core focus of this project. This EAGER award will focus on a high-risk approach building a mechanistic understanding of macroecological dynamics in the aerosphere based on the NEXRAD network of weather surveillance radars. The combination of recent and ongoing advances in radar technology, computation capabilities and data processing workflows, primarily in meteorology, have brought researchers to the edge of a revolution in the capacity to use weather radars as a biological sensors system. However, outside of meteorology, this resource is vastly under-used due to a general lack of analysis tools and data sets tailored to biologists. This EAGER award will focus on improved infrastructure and validation on providing radar-based metrics of distribution, density, and diversity of animals in the aerosphere. This project will include an integrated series of observational, experimental, and modeling studies that will result in a set of tools, products, and applications that enable transformative science in aeroecology.The broader impacts of this award will increase the availability and interpretability of radar data for investigations in environmental biology and building an interdisciplinary training environment at the interface of ecology, spatial modeling, computer science and meteorology. The radar tools and products that are developed will be widely distributed and make major contributions to basic understanding of aeroecology, which will be useful in (1) minimizing the impact of wind power development; (2) aviation safety; and (3) evaluation of ecosystem services. This project will lead a growing culture of interdisciplinary research by supporting a post-doc and student in an interdisciplinary group project with co-advisors and committee members from different disciplines (i.e. biology, computer science, and meteorology).

地球的季节性在热带和温带地区之间产生了能量、信息和生物多样性的流动。这种流动的大部分是通过大气层发生的，是一种广泛多样的迁徙动物。长距离迁移和扩散是生产力季节性快速重新分配、疾病传播和各大洲之间生物多样性变化的重要因素。可视化和模拟利用大气层觅食，扩散和迁移的动物多样性的集体行为是理解和预测大陆宏观生态动态的关键;并将成为该项目的核心重点。EAGER奖将重点关注一种高风险方法，基于NEXRAD天气监视雷达网络，建立对大气层宏观生态动力学的机械理解。雷达技术、计算能力和数据处理工作流程（主要是气象学领域）的最新和持续进步，使研究人员处于将气象雷达用作生物传感器系统的能力革命的边缘。然而，在气象学之外，由于普遍缺乏为生物学家量身定制的分析工具和数据集，这一资源的利用率极低。EAGER奖将专注于改进基础设施和验证，以提供基于雷达的大气层动物分布，密度和多样性指标。该项目将包括一系列综合的观测、实验和建模研究，这些研究将产生一系列工具、产品和应用，从而实现航空生态学的变革性科学。该奖项的更广泛影响将提高雷达数据的可用性和可解释性，用于环境生物学研究，并在生态学、空间建模、计算机科学和气象学。所开发的雷达工具和产品将广泛分发，并为基本了解航空生态学做出重大贡献，这将有助于（1）最大限度地减少风力发电的影响;（2）航空安全;（3）评估生态系统服务。该项目将通过支持博士后和学生与来自不同学科（即生物学，计算机科学和气象学）的共同顾问和委员会成员的跨学科小组项目，引领跨学科研究的文化。