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The aquaculture industry in Norway currently represents 60% (US$ 5.4 billion) of Norwegian seafood exports. Of these, farmed Atlantic Salmon (Salmo salar) represents over 80% (850,000 tons). These production levels are driven by a strong and growing demand for farmed fish, and has a stated political goal of increased growth by a factor of 5 by 2050 in Norway alone. However, growth is potentially more challenging without the public support and trust in the governance regime that regulates the industry. The theoretical framework of this paper rests on accountability theory, whereby the research team highlighted and tested the paradox between the ideal and the actual practices on a group of stakeholders representing the aquaculture industry and municipal, regional, and sector management in northern Norway relative to their interactions and need thereof—vs. the expectations of the public. The findings of a workshop were used to develop a conceptual model and test our theory on stakeholder driven future scenarios using a combination of systems thinking and fuzzy cognitive mapping. We found that stakeholders and management alike in a workshop setting valued flexibility of legislation and expert opinions highly, whereby regulatory standardization is not prioritized—in line with soft accountability. The industry acknowledged, though, that the public perception and negative media attention of the industry, in turn depended on hard accountability. ; publishedVersion

Climate change affects the marine environment at all levels of governance. At a global level, researchers expect the projected increase in sea surface temperature to facilitate large changes in the marine food web, which in turn will affect both global fisheries and aquaculture. At the local level, government and stakeholders want to know whether and how this affects their local communities and their adaptive capacity in light of this. Research suggests that risk communication of the effects of changes in the marine food web suffers from stakeholders' short-term mentality and narrow boundaries. This in turn can lead to an underestimation of the potential risks associated with climate change. We explore this theory by mapping the perceptions of marine stakeholders in the region of Troms, Norway. We first developed cognitive maps in a workshop setting, and then used system conceptualization to analyze the feedback mechanisms of the system qualitatively using fuzzy cognitive mapping. We examined the outcomes and compared them for different scenarios using a simple MatLab script. Results demonstrated that stakeholders did not underestimate their risks to climate change. They were aware of environmental changes, and they perceived that a changing climate was the cause of this change, and that it was indeed affecting their livelihoods—and would continue to do so in the future. ; publishedVersion

Climate change affects the marine environment at all levels of governance. At a global level, researchers expect the projected increase in sea surface temperature to facilitate large changes in the marine food web, which in turn will affect both global fisheries and aquaculture. At the local level, government and stakeholders want to know whether and how this affects their local communities and their adaptive capacity in light of this. Research suggests that risk communication of the effects of changes in the marine food web suffers from stakeholders' short-term mentality and narrow boundaries. This in turn can lead to an underestimation of the potential risks associated with climate change. We explore this theory by mapping the perceptions of marine stakeholders in the region of Troms, Norway. We first developed cognitive maps in a workshop setting, and then used system conceptualization to analyze the feedback mechanisms of the system qualitatively using fuzzy cognitive mapping. We examined the outcomes and compared them for different scenarios using a simple MatLab script. Results demonstrated that stakeholders did not underestimate their risks to climate change. They were aware of environmental changes, and they perceived that a changing climate was the cause of this change, and that it was indeed affecting their livelihoods—and would continue to do so in the future. ; publishedVersion ; © 2016 Tiller, De Kok, Vermeiren, Richards, Ardelan and Bailey. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

To reach the global aspiration of 17 ambitious SDGs, local realities must be integrated. Often, models are developed based on quantitative statistical data sources from databases on environmental indicators or economics to assess how a given SDG can be achieved. This process however removes the local realities from the equation. How can you best include stakeholders in this mathematical modelling processes distanced from their local realities, though, and ensure higher probability of future compliance with top-down global decisions that may have local consequences once implemented? When researching stakeholder involvement and their ability to form public policy, their opinions often get reported as a single assessment, like counting the fish in the ocean once and stating that as a permanent result. Too seldom do stakeholders get invited back and given the opportunity to validate results and allow researchers to adjust their models based on on-the-ground validation or change requests. We tested the full integration of stakeholders in the modelling process of environmental topics in six different case areas across Europe, with each area holding six sectoral and one inter-sectoral workshops. In these workshops, the scope of the issues relevant to the stakeholders was driven by first the sectoral priorities of the given sector, followed by a merging of issues. In this process, we were able to identify what the commonalities between different sectors were and where synergies lay in terms of governance paths. These results were then returned to the stakeholders in a mixed session where they were able to come with feedback and advice on the results researchers presented, so that the models reflected more closely the perceptions of the regional actors. We present these methods and reflect on the challenges and opportunities of using this deep-integration method to integrate qualitative data from stakeholder inclusion in a quantitative model ; The authors would like to acknowledge funding from the European Union's ...

To reach the global aspiration of 17 ambitious SDGs, local realities must be integrated. Often, models are developed based on quantitative statistical data sources from databases on environmental indicators or economics to assess how a given SDG can be achieved. This process however removes the local realities from the equation. How can you best include stakeholders in this mathematical modelling processes distanced from their local realities, though, and ensure higher probability of future compliance with top-down global decisions that may have local consequences once implemented? When researching stakeholder involvement and their ability to form public policy, their opinions often get reported as a single assessment, like counting the fish in the ocean once and stating that as a permanent result. Too seldom do stakeholders get invited back and given the opportunity to validate results and allow researchers to adjust their models based on on-the-ground validation or change requests. We tested the full integration of stakeholders in the modelling process of environmental topics in six different case areas across Europe, with each area holding six sectoral and one inter-sectoral workshops. In these workshops, the scope of the issues relevant to the stakeholders was driven by first the sectoral priorities of the given sector, followed by a merging of issues. In this process, we were able to identify what the commonalities between different sectors were and where synergies lay in terms of governance paths. These results were then returned to the stakeholders in a mixed session where they were able to come with feedback and advice on the results researchers presented, so that the models reflected more closely the perceptions of the regional actors. We present these methods and reflect on the challenges and opportunities of using this deep-integration method to integrate qualitative data from stakeholder inclusion in a quantitative model. ; publishedVersion