NEON RCN: The Ecological Forecasting Initiative RCN: Using NEON-enabled near-term forecasting to synthesize our understanding of predictability across ecological systems and scales

NEON RCN：生态预测计划 RCN：使用 NEON 支持的近期预测来综合我们对跨生态系统和规模的可预测性的理解

• 批准号: 1926388
• 负责人: Robert Thomas
• 金额: $ 50万
• 依托单位: Virginia Polytechnic Institute and State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-01-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1926388&HistoricalAwards=false
• 关键词: NEON; RCN; Ecological; Forecasting; Initiative

The 21st century is characterized by major environmental changes that alter the ecosystems society depends on for supplying clean water, storing carbon, and supporting plants and animals. Predicting and forecasting the future of these systems can help resource managers anticipate and respond to these changes. Ecological forecasts also advance scientific understanding by developing and testing models and testing alternative views of how ecological systems operate. To harness the power of forecasting, a community of practice is needed. This community will establish standards for developing and communicating forecasts. It will share best practices for generating forecasts with known uncertainties. The group will create tools and educational materials to enable ecologists to begin forecasting. The Ecological Forecasting Initiative Research Coordination Network award will build this community of practice around forecasting data from the continental-scale National Ecological Observatory Network (NEON). By focusing on data from NEON, the community will be challenged to develop and evaluate forecasts for a diversity of environments that exist across the United States. The award will train hundreds of early career researchers and graduate students in ecological forecasting.The Ecological Forecasting Initiative Research Coordination Network will use a set of network workshops, conferences, and collaborative software development events to address the following objectives: (1) develop best practices for archiving and sharing NEON-enabled ecological forecasts, (2) increase the number, diversity, and quality of NEON-enabled forecasts, (3) train the ecological community to produce NEON-enabled forecasts by developing open tutorials in ecological forecasting methods, (4) facilitate and support collaborative interactions dedicated to forecasting knowledge transfer among ecologists, (5) cultivate connections between the academic ecological forecasting community and mission-driven agencies that use forecasts to guide decision-making, and (6) synthesize existing forecasts and new NEON-enabled forecasts to evaluate limits to forecastability across ecological systems and scales. Overall, these objectives are focused on solving the grand challenge of understanding the predictability of nature.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

世纪的特征是重大的环境变化，这些变化改变了社会赖以提供清洁水、储存碳和支持动植物的生态系统。预测和预测这些系统的未来可以帮助资源管理人员预测和响应这些变化。生态预测还通过开发和测试模型以及测试生态系统如何运作的替代观点来促进科学理解。为了利用预测的力量，需要一个实践社区。该社区将建立发展和传播预报的标准。它将分享生成已知不确定性预测的最佳做法。该小组将创建工具和教育材料，使生态学家开始预测。生态预测倡议研究协调网络奖将围绕来自大陆规模的国家生态观测网络（氖）的预测数据建立这一实践社区。通过关注来自氖的数据，社区将面临开发和评估美国各地存在的各种环境的预测的挑战。该奖项将培训数百名早期职业研究人员和研究生在生态预测.生态预测倡议研究协调网络将使用一套网络研讨会，会议，和协作软件开发活动，以解决以下目标：（1）制定归档和共享NEON支持的生态预测的最佳实践，（2）增加NEON支持的生态预测的数量，多样性，和NEON启用预测的质量，（3）通过开发生态预测方法的开放式教程，培训生态社区制作NEON启用预测，（4）促进和支持致力于生态学家之间预测知识转移的协作互动，（5）在学术生态预测界和利用预测指导决策的使命驱动机构之间建立联系，以及（6）综合现有的预测和新的NEON启用的预测，以评估跨生态系统和尺度的可预测性的限制。总的来说，这些目标集中在解决理解自然的可预测性的巨大挑战。这个奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

项目成果

Going Virtual: What we Learned from the Ecological Forecasting Initiative Research Coordination Network Virtual Workshop

走向虚拟：我们从生态预测倡议研究协调网络虚拟研讨会中学到了什么

• DOI: 10.1002/bes2.1828
• 发表时间: 2021
• 期刊: The Bulletin of the Ecological Society of America
• 作者: Peters, Jody A.;Quinn Thomas, R.
• 通讯作者: Quinn Thomas, R.

Progress and opportunities in advancing near‐term forecasting of freshwater quality

• DOI: 10.1111/gcb.16590
• 发表时间: 2023-01
• 期刊: Global Change Biology
• 影响因子: 11.6
• 作者: M. Lofton;Dexter W. Howard;R. Q. Thomas;C. Carey

Assessing Ecosystem State Space Models: Identifiability and Estimation

• DOI: 10.1007/s13253-023-00531-8
• 发表时间: 2023-03-09
• 期刊: JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS
• 影响因子: 1.4
• 作者: Smith Jr，J. W.;Johnson，L. R.;Thomas，R. Q.
• 通讯作者: Thomas，R. Q.

A community convention for ecological forecasting: Output files and metadata version 1.0

生态预测社区公约：输出文件和元数据版本 1.0

• DOI: 10.1002/ecs2.4686
• 发表时间: 2023
• 期刊: Ecosphere
• 影响因子: 2.7
• 作者: Dietze, Michael C.;Thomas, R. Quinn;Peters, Jody;Boettiger, Carl;Koren, Gerbrand;Shiklomanov, Alexey N.;Ashander, Jaime
• 通讯作者: Ashander, Jaime

Virtual Growing Pains: Initial Lessons Learned from Organizing Virtual Workshops, Summits, Conferences, and Networking Events during a Global Pandemic

虚拟成长的烦恼：在全球大流行期间组织虚拟研讨会、峰会、会议和社交活动的初步经验教训

• DOI: 10.1002/lob.10431
• 发表时间: 2021
• 期刊: Limnology and Oceanography Bulletin
• 作者: Meyer, Michael F.;Ladwig, Robert;Dugan, Hilary A.;Anderson, Alyssa;Bah, Abdou R.;Boehrer, Bertram;Borre, Lisa;Chapina, Rosaura J.;Doyle, Chris;Favot, Elizbaeth J.
• 通讯作者: Favot, Elizbaeth J.