Ecosystems around the world are increasingly exposed to multiple, often interacting human activities, leading to pressures and possibly environmental state changes. Decision support tools (DSTs) can assist environmental managers and policy makers to evaluate the current status of ecosystems (i.e. assessment tools) and the consequences of alternative policies or management scenarios (i.e. planning tools) to make the best possible decision based on prevailing knowledge and uncertainties. However, to be confident in DST outcomes it is imperative that known sources of uncertainty such as sampling and measurement error, model structure, and parameter use are quantified, documented, and addressed throughout the DST set-up, calibration, and validation processes. Here we provide a brief overview of the main sources of uncertainty and methods currently available to quantify uncertainty in DST input and output. We then review 42 existing DSTs that were designed to manage anthropogenic pressures in the Baltic Sea to summarise how and what sources of uncertainties were addressed within planning and assessment tools. Based on our findings, we recommend future DST development to adhere to good modelling practise principles, and to better document and communicate uncertainty among stakeholders.

世界各地的生态系统越来越多地暴露于多种经常相互作用的人类活动中，从而导致压力和可能的环境状态变化。决策支持工具 (DST) 可以帮助环境管理者和政策制定者评估生态系统的现状（即评估工具）以及替代政策或管理方案（即规划工具）的后果，从而根据流行的知识和不确定性。然而，为了对 DST 结果充满信心，必须在整个 DST 设置、校准和验证过程中量化、记录和解决已知的不确定性来源，例如采样和测量误差、模型结构和参数使用。在这里，我们简要概述了不确定性的主要来源以及目前可用于量化 DST 输入和输出中的不确定性的方法。然后，我们回顾了旨在管理波罗的海人为压力的 42 个现有 DST，以总结在规划和评估工具中如何以及哪些不确定性来源得到解决。根据我们的发现，我们建议未来的 DST 开发遵循良好的建模实践原则，并更好地记录和沟通利益相关者之间的不确定性。