Collaborative Research: ABI Development: A toolbox for analysis of long-term ecological dynamics using the Kepler Workflow System

合作研究：ABI 开发：使用开普勒工作流程系统分析长期生态动态的工具箱

• 批准号: 1262377
• 负责人: Scott Collins
• 金额: $ 27.22万
• 依托单位: University of New Mexico
• 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: 2013-04-01 至 2018-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1262377&HistoricalAwards=false
• 关键词: Collaborative; Research; ABI; Development; toolbox

The University of Wisconsin Madison, The University of New Mexico, and the University of California Santa Barbara are awarded grants to develop a toolbox for automating the process of analyzing community change. Long-term data sets will be used to demonstrate data and system accessibility and functionality, and through implementation of new metrics we will gain insights into what drives change in ecological communities on a continental scale. Data will be accessed via the DataONE portal and the LTER Network Information System using the Ecological Metadata Language, and analyzed with R statistical routines within the Kepler Scientific Workflow Environment. The species makeup of ecological communities varies over time in response to changes in the environment. Analysis of this variability has a long history in ecology, yet because of the lack of long term data, ecological change in different localities has been studied in a so-called ?place for time? approach. That is, environmental conditions in one locality are considered to be comparable to the future conditions in another place. Although, this approach allows some insight into general trends it does not provide much information about rates and patterns of change. NSF programs like LTER and LTREB have generated long term observations of different ecological communities to allow for more realistic measures of how ecological communities change over time. This record will grow as automated observing platforms like NEON and GLEON contribute significantly to the long-term record. Along with the increasing availability of long-term datasets in on-line repositories, new methods for community change analysis are being developed. This open access toolbox will make community analysis more accessible and in turn expose a variety of indices to wider use, thorough testing, and improvement for measuring and visualizing ecological dynamics. Existing workflows will help reduce effort in data preparation and foster unprecedented potential for collaboration. Value added data products of community change indices across habitats are particularly valuable for education and outreach, and in broader synthetic activities related to environmental health, management, and dynamics at larger scales. Through the LTER Schoolyard program these data and understanding of environmental change will reach a large number and diversity of schoolchildren. For further information about the project and its software products, visit http://lter.limnology.wisc.edu/research/community-analysis-toolbox.

威斯康星大学麦迪逊分校、新墨西哥大学和加州大学圣巴巴拉分校获得拨款，用于开发一个工具箱，用于自动化分析社区变化的过程。长期数据集将用于展示数据和系统的可访问性和功能，通过实施新指标，我们将深入了解推动大陆范围内生态社区变化的因素。数据将使用生态元数据语言通过 DataONE 门户和 LTER 网络信息系统进行访问，并在开普勒科学工作流程环境中使用 R 统计例程进行分析。生态群落的物种组成随着时间的推移而变化，以响应环境的变化。对这种变异性的分析在生态学中有着悠久的历史，但由于缺乏长期数据，不同地区的生态变化一直是在所谓的“时间地点”中进行研究。方法。也就是说，一个地方的环境条件被认为与另一地方的未来条件具有可比性。尽管这种方法可以洞察总体趋势，但它并没有提供太多有关变化率和模式的信息。 LTER 和 LTREB 等 NSF 项目已经对不同生态群落进行了长期观察，以便对生态群落随时间的变化进行更现实的衡量。随着 NEON 和 GLEON 等自动观测平台对长期记录做出重大贡献，这一记录将会不断增长。随着在线存储库中长期数据集的可用性不断增加，社区变化分析的新方法正在开发中。这个开放获取工具箱将使社区分析变得更加容易，进而使各种指数得到更广泛的使用、彻底的测试以及对生态动态的测量和可视化的改进。现有的工作流程将有助于减少数据准备工作并激发前所未有的协作潜力。跨栖息地的社区变化指数的增值数据产品对于教育和推广以及与更大规模的环境健康、管理和动态相关的更广泛的综合活动特别有价值。通过 LTER Schoolyard 计划，这些数据和对环境变化的了解将惠及大量、多样化的学童。有关该项目及其软件产品的更多信息，请访问 http://lter.limnology.wisc.edu/research/community-analysis-toolbox。