On the uncertainty and confidence in decision support tools (DSTs) with insights from the Baltic Sea ecosystem
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REVIEW
On the uncertainty and confidence in decision support tools (DSTs) with insights from the Baltic Sea ecosystem Floris M. van Beest Jacob Carstensen
, Henrik Nyga˚rd, Vivi Fleming,
Received: 1 February 2020 / Revised: 12 August 2020 / Accepted: 13 August 2020
Abstract 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. Keywords Baltic Sea Confidence Decision support tools Uncertainty
Electronic supplementary material The online version of this article (doi:https://doi.org/10.1007/s13280-020-01385-x) contains supplementary material, which is available to authorized users.
INTRODUCTION Most ecosystems on Earth are affected by multiple pressures originating from anthropogenic activities, often with negative environmental and socio-economic consequences (Halpern et al. 2015; Steffen et al. 2015). To effectively manage human activities affecting environmental systems, policy makers frequently rely on decision support tools (DSTs) to guide the decision-making process (MilnerGulland and Shea 2017). In the broadest sense, a DST can be defined as any guidance, procedure, or analysis tool that can be used to help support a decision (Sullivan 2002). The optimal DST should provide a structured process in which all assumptions, model parameters, and predicted outcomes are tested, reviewed, and documented. This allows environmental managers to make the best possible decision based on prevailing knowledge and uncertainties. Uncertainty is unavoidable and all scientists and policymakers are familiar with it. Nonetheless, many people working with DSTs shy away from quantifying, documenting, and communicating the uncertainty within the tool, the output, and the decision-making process. Our main aim was to evaluate how uncertainty has been handled in DSTs that have been developed specificall
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