Marine Research Centre, Finnish Environment Institute, Helsinki, Finland.
Department of Bioscience, Aarhus University, Roskilde, Denmark.
Environ Manage. 2020 Dec;66(6):1024-1038. doi: 10.1007/s00267-020-01356-8. Epub 2020 Sep 10.
Decision-support tools (DSTs) synthesize complex information to assist environmental managers in the decision-making process. Here, we review DSTs applied in the Baltic Sea area, to investigate how well the ecosystem approach is reflected in them, how different environmental problems are covered, and how well the tools meet the needs of the end users. The DSTs were evaluated based on (i) a set of performance criteria, (ii) information on end user preferences, (iii) how end users had been involved in tool development, and (iv) what experiences developers/hosts had on the use of the tools. We found that DSTs frequently addressed management needs related to eutrophication, biodiversity loss, or contaminant pollution. The majority of the DSTs addressed human activities, their pressures, or environmental status changes, but they seldom provided solutions for a complete ecosystem approach. In general, the DSTs were scientifically documented and transparent, but confidence in the outputs was poorly communicated. End user preferences were, apart from the shortcomings in communicating uncertainty, well accounted for in the DSTs. Although end users were commonly consulted during the DST development phase, they were not usually part of the development team. Answers from developers/hosts indicate that DSTs are not applied to their full potential. Deeper involvement of end users in the development phase could potentially increase the value and impact of DSTs. As a way forward, we propose streamlining the outputs of specific DSTs, so that they can be combined to a holistic insight of the consequences of management actions and serve the ecosystem approach in a better manner.
决策支持工具 (DST) 综合复杂信息，以协助环境管理者进行决策过程。在这里，我们回顾了应用于波罗的海地区的 DST，以调查生态系统方法在其中的体现程度、涵盖的不同环境问题以及工具满足最终用户需求的程度。DST 是根据以下四个方面进行评估的：(i) 一套绩效标准，(ii) 最终用户偏好信息，(iii) 最终用户如何参与工具开发，以及 (iv) 开发人员/主机在使用工具方面的经验。我们发现，DST 经常针对与富营养化、生物多样性丧失或污染物污染有关的管理需求。大多数 DST 都针对人类活动、其压力或环境状况变化进行了处理，但很少提供完整生态系统方法的解决方案。总的来说，DST 在科学上有文件记录并且透明，但输出的置信度传达得很差。除了在传达不确定性方面的缺点之外，最终用户的偏好也在 DST 中得到了很好的考虑。尽管在 DST 开发阶段通常会咨询最终用户，但他们通常不是开发团队的一部分。开发人员/主机的回答表明，DST 没有被充分利用。最终用户在开发阶段的更深入参与有可能增加 DST 的价值和影响力。为此，我们提出简化特定 DST 的输出，以便可以将它们组合成管理行动后果的整体见解，并以更好的方式服务于生态系统方法。
