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Beyond prediction—radical ocean futures—a science fiction prototyping approach to imagining the future oceans
Merrie, A. (2019). Beyond prediction—radical ocean futures—a science fiction prototyping approach to imagining the future oceans, in: Cisneros-Montemayor, A.M. et al. Predicting future oceans: Sustainability of ocean and human systems amidst global environmental change. pp. 519-527. https://dx.doi.org/10.1016/b978-0-12-817945-1.00047-2
In: Cisneros-Montemayor, A.M.; Cheung, W.W.L.; Ota, Y. (Ed.) (2019). Predicting future oceans: Sustainability of ocean and human systems amidst global environmental change. Elsevier: Amsterdam. ISBN 978-0-12-817945-1. xxvii, 554 pp. https://dx.doi.org/10.1016/c2018-0-02416-0, more

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    Marine/Coastal

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  • Merrie, A.

Abstract
    This chapter will first introduce the concept of scenarios and salient critiques of prevailing approaches before making an argument that storytelling and narrative has an important complementary role to play in “predicting the future ocean.” This chapter, building on the scientific findings that make up this book, will argue for why our changing oceans require a more, radical, imaginative approach to complement existing quantitative models and analytical scenarios for painting a full picture of the future ocean and present a specific tool that can be used by scientists, policy makers and others to apply imagination-led approaches to creating narrative scenarios. We used an empirically informed background on existing and emerging trends in marine natural resource use and dynamics to develop four “radical ocean futures,” incorporating and extrapolating from existing environmental, technological, social, and economic trends. We argue that the distinctive method as applied here can complement existing scenario methodologies and assist scientists in developing a holistic understanding of complex systems dynamics. The specific approach of Science Fiction prototyping will be described in detail as it was applied in the Radical Ocean Futures project and then the chapter will conclude with key learnings and takeaways from the approach.

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