How have the studies been undertaken? Are they written by experts alone or do they involve relevant stakeholders? What methods and tools have been applied? Studies concerning the future of the Arctic are diverse in both scope and methodological approach. They can be characterised in different ways, based on whether or not they make explicit images of the future, how many or what kind of future images they make, how they study driving forces, whether or not they include wildcards and so on. In this section we will shed light on the methodological aspects of the studies we have reviewed.
Participation
Most of the studies are expert-based in the sense that they have been performed by consultants or researchers. This is typical for all the four categories mentioned in section 4. The main exemptions are the assessments commissioned by the Arctic Council, which have involved a comprehensive set of authors, peer reviewers and government agencies in the Arctic states. In the development of the Arctic Climate Impact Assessment (Arctic Council 2004a), indigenous groups took part, and the Arctic Maritime Shipping Assessment (Arctic Council 2009) were partly based on two scenario workshops and town hall meetings.
In two of the studies, the future images that were developed clearly rested on dialogue-based tools and a process involving a number of participants (Olsen & Iversen 2009; Ducharme & Brightman 2011). Similarly, reference groups, workshops and seminars also made up an important part of other projects (i.e. Brunstad et al. 2004; Brunstad 2007; Barlindhaug 2006; Arbo et al. 2007; Lian 2010; Ecologic Institute 2010).
Sources of information
Anticipating the course of the future requires information about past developments and the current state of affairs. Future studies usually employ several and quite different sources of information. Many of them rely on available statistics from national and international agencies. In the Norwegian studies, data from Statistics Norway, the Norwegian Petroleum Directorate, the Directorate of Fisheries, the Norwegian Coastal Administration and other public agencies are frequently used. Other important sources are the reports from the Intergovernmental Panel on Climate Change (IPCC) and the Arctic Climate Impact Assessment, as well as figures from the International Energy Agency (IEA), the U.S. Geological Survey and the International Monetary Fund (IMF). With the Arctic Marine Shipping Assessment as the main exception, very few collect their own data. Scientific publications are referred to in several studies, but press releases, newspaper articles, consulting reports and interviews seem to be more common sources.
Methodology
While all the studies have a view to the future of the Arctic, there is a huge variation in how the ideas about the future are spelled out and how they are arrived at.
Implicit futures
Many of the studies concentrate on major trends that will shape the future and do not present explicit images of the future (e.g. Arctic Council 2007; Fairhall 2010; Seidler 2009; Smith 2011). That is, they leave it to the readers to draw the implications and to envisage what lies ahead. Still, many of them have a clear implicit message or convey facts and thought-provoking reflections that give hints about the future and choices to be made. The weakness of such studies is that uncertainties are often downplayed, leaving little scope for developing a preparedness for dealing with unexpected events.
The rest of the studies we have reviewed provide explicit images pertaining to the future of the Arctic. This is done in a more or less disciplined and rigorous way, and by introducing different levels of uncertainty. Five slightly overlapping approaches can be discerned.
Visions
While most future studies contain two or more future images, some only present one in the form of a vision (e.g. Barlindhaug 2005; ECON 2006; Blakkisrud el al. 2008). The visions depict what might come true under a certain set of conditions – either as a desired outcome or as an outcome that must be avoided. Typical for these studies is that they have the future as their fixed place and have a retrospective look on how this future state was reached. In most cases they are stories about how it would look like if everything went right, according to the hopes of the relevant audience.
The main purpose of visions is normally to create consensus among decision-makers about goals and the strategies and measures that must be taken in order to realise these goals. Discontinuities and radical shifts may be part of the story, but there is only one final outcome.
High probability scenarios
Scenarios typically seek to identify driving forces, trends and critical uncertainties, and to explore how these might unfold and determine future conditions, opportunities, threats and obstacles. The high probability scenarios concentrate on one or more trends that are considered major and likely to have a high impact. In these studies it is assumed that the most important drivers for future development are known. What are under scrutiny, are their strength, interaction and perceived outcomes. This seems to be the most common approach. Many of the scenarios are based on high or low values for some key parameters (Barlindhaug 2006; Slotfeldt-Ellingsen & Sandvik 2009; Olsen & Iversen 2009; Lian 2010; Faggruppa 2005; IISS 2008; Billyard et al. 2010). As one of the alternatives is usually preferred, this means that a positive development is contrasted with a negative or no-growth alternative.
In some cases the two extremes are supplemented by a “middle way” scenario, where the one in the middle stands out as the most realistic one, even though, in fact, it is no more reasonable or reliable than the others (cf. Rabinowitz 2009). In the EU Arctic Footprint and Policy Assessment Report (Ecologic Institute 2010) the scenarios were built around given combinations of four main drivers. By attributing different levels of change to each of the four variables, three scenarios were constructed implying high, medium and low EU footprints in the Arctic.
Simulations
Scenarios can also be developed on the basis of complex formal models which require substantial amounts of data. The Arctic Climate Impact Assessment (Arctic Council 2004a) and the NorACIA programme (Øseth 2010) are comprehensive studies of this kind. They build on climate models which simulate the interactions of the atmosphere, oceans, land surface, and ice. Similar to the high probability scenarios, these studies rest on the assumption that the most important variables and their relationships are known and can be specified, but formal models can better demonstrate the interactions, and the outcomes of alternative causation and feedback mechanisms can be simulated.
In our sample, simulations are also applied in some of the studies on Arctic shipping (Niini 2006, Mejlænder-Larsen & Espeland 2009; DNV 2010). These are basically feasibility studies, testing out under which conditions new shipping routes or technological solutions are viable and their sensitivity to different factors. Peters et al. (2011) combine several types of models and assess future petroleum and shipping activities and their resulting emissions to air, while Valsson & Ulfarsson (2011) provide rough estimates of future activity structures.
Qualitatively different scenarios
Another approach is to emphasise trends and driving forces that might have a high impact, but which are also associated with high uncertainty. Here, the scenarios are built around the main aspects of uncertainty rather than the most probable trends, which are included with slight variation in all the scenarios anyhow. In these studies a number of qualitatively different scenarios are presented. The studies also investigate the series of actions, events and circumstances that are generating the alternative futures. In our review, Arbo et al. (2007), Brunstad et al. (2004), Brunstad (2007), Brigham (2007), Brigham (2008), and Arctic Council (2009) are among the studies adopting such an approach.
Games
A well-known but not frequently used method for studying the future is games. Games are well suited when interaction among key actors may take the course of development in different directions. Games are primarily employed in a military context (Billyard et al. 2010; Ducharme & Brightman 2011). In the Strategic War Game (Billyard et al. 2010), the main sources of uncertainty are introduced by the actions of the three players: the Air Force, the Canadian government, and adversaries that challenge the Canadian territorial boundaries. Their assumed mutually dependent actions determine the multiple outcomes of the games. By running several games under various contextual conditions, the study summarises the outcomes in two scenarios, a worst and a best case. In this respect, even though the study starts from an entirely different methodological standpoint, it resembles the high/low scenarios mentioned earlier.