Suppr超能文献

利用PoPS并在我们朋友的些许帮助下迭代预测生物入侵。

Iteratively forecasting biological invasions with PoPS and a little help from our friends.

作者信息

Jones Chris M, Jones Shannon, Petrasova Anna, Petras Vaclav, Gaydos Devon, Skrip Megan M, Takeuchi Yu, Bigsby Kevin, Meentemeyer Ross K

机构信息

Center for Geospatial Analytics North Carolina State University Raleigh NC.

Animal and Plant Health Inspection Service (APHIS) US Department of Agriculture (USDA) Riverdale MD.

出版信息

Front Ecol Environ. 2021 Sep;19(7):411-418. doi: 10.1002/fee.2357. Epub 2021 Jun 3.

Abstract

Ecological forecasting has vast potential to support environmental decision making with repeated, testable predictions across management-relevant timescales and locations. Yet resource managers rarely use co-designed forecasting systems or embed them in decision making. Although prediction of planned management outcomes is particularly important for biological invasions to optimize when and where resources should be allocated, spatial-temporal models of spread typically have not been openly shared, iteratively updated, or interactive to facilitate exploration of management actions. We describe a species-agnostic, open-source framework - called the Pest or Pathogen Spread (PoPS) Forecasting Platform - for co-designing near-term iterative forecasts of biological invasions. Two case studies are presented to demonstrate that iterative calibration yields higher forecast skill than using only the earliest-available data to predict future spread. The PoPS framework is a primary example of an ecological forecasting system that has been both scientifically improved and optimized for real-world decision making through sustained participation and use by management stakeholders.

摘要

生态预测在跨管理相关时间尺度和地点进行反复、可检验的预测以支持环境决策方面具有巨大潜力。然而,资源管理者很少使用共同设计的预测系统或将其嵌入决策过程。尽管对于生物入侵而言,预测计划管理结果对于优化资源分配的时间和地点尤为重要,但传播的时空模型通常并未公开共享、迭代更新或具备交互性以促进对管理行动的探索。我们描述了一个物种无关的开源框架——称为有害生物或病原体传播(PoPS)预测平台——用于共同设计生物入侵的近期迭代预测。通过两个案例研究表明,与仅使用最早可得数据预测未来传播相比,迭代校准可产生更高的预测技能。PoPS框架是一个生态预测系统的主要范例,该系统通过管理利益相关者的持续参与和使用,在科学上得到改进并针对实际决策进行了优化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c5d1/8453564/2ceb014686bc/FEE-19-411-g001.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验