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.

中文翻译：

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使用 PoPS 迭代预测生物入侵以及我们朋友的一点帮助

生态预测具有巨大的潜力，可以通过跨管理相关的时间尺度和地点的重复、可测试的预测来支持环境决策。然而，资源经理很少使用共同设计的预测系统或将它们嵌入到决策中。尽管预测计划管理结果对于生物入侵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尚未公开共享、迭代更新或交互以促进管理行动的探索。我们描述了一个与物种无关的开源框架——称为害虫或病原体传播 (PoPS) 预测平台——用于共同设计生物入侵的近期迭代预测。提供了两个案例研究来证明迭代校准比仅使用最早的可用数据来预测未来传播具有更高的预测技巧。PoPS 框架是生态预测系统的一个主要示例，通过管理利益相关者的持续参与和使用，该系统已针对现实世界的决策进行了科学改进和优化。