Multi-Scaled Data in Ecology: Scale Dependent Patterns in the Environment

康奈尔大学获得了一笔赠款，用于在线提供有关鸟类的新信息，并将其传播给广泛而多样化的受众。目标是继续扩大鸟类知识网络（AKN）（http：//www.example.com）提供的资源和分析工具。www.avianknowledge.net将添加恒定努力捕获方法（CECM）社区的数据资源。这些数据是由北美1000多个野外观测站在20年的时间里收集的，提供了详细的鸟类人口统计信息。将这一数据资源带到AKN将创造最全面的环境监测和保护生物学资源。这些数据将通过鸟类环志数据交换方案纳入AKN。该模式基于达尔文核心标准，并与AKN的观测数据模式兼容。其目标是扩大现有的鸟类监测数据交换模式，以包括鸟类人口统计数据，特别是修改模式，以处理收集的信息（年龄，性别，大小，重量）对个别鸟类。持续努力捕获数据将使用DiGIR协议进行联合。数据仓库结构将对这些数据进行存档，并使其普遍可用。最后，将开发一个基于因特网的多尺度分析应用程序，并向广大用户公开发布。跨学科的方法将把统计和计算专家与人口生物学家聚集在一起，开发新的和广泛适用的技术，以创造新的方法，跟踪长期的环境模式在一系列尺度。为了能够在互联网上快速浏览这些数据，将探索数据可视化的新战略。该项目将向广大新受众展示新的数据资源和统计分析的进展：从生物学家，保护机构和土地使用规划者到学校教室和参与环境监测的数千名公民。该项目将开辟新的科学、保护和教育机会，通过积极传播数据可视化和探索应用程序，它将使研究人员以及北美数百万观看和欣赏野生鸟类的人能够访问以鸟类种群为重点的大量资源。

Cornell University is awarded a grant to bring new information on birds online and disseminate these to a wide and diverse audience. The goal is to continue to expand the resources and analysis tools available at the Avian Knowledge Network (AKN) (http://www.avianknowledge.net). The data resources of the Constant Effort Capture Method (CECM) community will be added. These data, which have been gathered over a 20-year period by more than 1000 field stations across North America, provide detailed avian demographic information. Bringing this data resource to the AKN will create the most comprehensive source of environmental monitoring and conservation biology available. The data will be integrated into the AKN via a bird banding data exchange schema. This schema is based on the Darwin Core standard and is compatible with AKN's observational data schema. The goal is to expand the existing bird monitoring data exchange schema to include bird demographic data, and, specifically, to modify the schema to handle information gathered (age, sex, size, weight) on individual birds. The constant effort capture data will be federated using the DiGIR protocol. A data warehouse structure will archive these data and make them generally available. Finally, an Internet-based multi-scale analysis application will be developed and publicly released to a broad spectrum of users. The interdisciplinary approach will bring statistical and computational specialists together with population biologists to develop new and broadly applicable technologies to create new methodologies that track long-term environmental patterns at a range of scales. To allow rapid browsing of these data over the Internet, new strategies in data visualizations will be explored. This project will expose new data resources and advances in statistical analysis to vast new audiences: from biologists, conservation agencies, and land-use planners to school classrooms and thousands of citizens who participate in environmental monitoring. The project will open new scientific, conservation, and educational opportunities, and by actively disseminating data visualization and exploration applications it will enable researchers as well as literally millions of people across North America who watch and appreciate wild birds to access a vast resource focused on bird populations.