Browsing by Subject "uncertainty"
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(2020)Computing complex phenomena into models providing information of the causalities and future scenarios is a very topical way to present scientific information. Many claim models to be the best available tool to provide decision making with information about near-future scenarios and the action needed (Meah, 2019; Schirpke et al., 2020). This thesis studies global climate models based on objective data compared to local ecosystem services models combining ecological and societal data offer an extensive overview of modern environmental modelling. In addition to modelling, the science-policy boundary is important when analyzing the societal usefulness of models. Useful and societally-relevant modelling is analyzed with an integrative literature review (Whittemore & Knafl, 2005) on the topics of climate change, ecosystem services, modelling and science-policy boundary, n=58. Literature from various disciplines and viewpoints is included in the material. Since the aim is to create a comprehensive understanding of the multidisciplinary phenomenon of modelling, the focus is not on the technical aspects of it. Based on the literature, types of uncertainty in models and strategies to manage them are identified (e.g. van der Sluijs, 2005). Characteristics of useful models and other forms of scientific information are recognized (e.g. Saltelli et al., 2020). Usefulness can be achieved when models are fit for purpose, accessible and solution-oriented, and sufficient interaction and trust is established between the model users and developers. Climate change and ecosystem services are analyzed as case studies throughout the thesis. The relationship of science and policy is an important discussion especially important when solving the sustainability crisis. Because modelling is a boundary object (Duncan et al., 2020), the role of boundary work in managing and communicating the uncertainties and ensuring the usefulness of models is at the center of the analysis.
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