Linking global to regional scenarios in foresight

Futures 44 (2012) 847–859

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Linking global to regional scenarios in foresight Anastasia Stratigea *, Maria Giaoutzi Dept. of Geography and Regional Planning, School of Rural and Surveying Engineering, National Technical University of Athens, Greece

A R T I C L E I N F O

A B S T R A C T

Article history: Available online 9 October 2012

Scenarios have proven useful tools for dealing with future uncertainty in an integrated and cohesive way. A key issue in scenario approaches, still under development, is the linking of scenarios at different spatial scales, in order to be better understood the interaction of processes across scales. The paper presents the AG2020 experience on linking EU-wide backcasting policy scenarios, exploring strategic policy directions for the EU agriculture in 2020 to regional policy scenarios in different EU rural contexts. This may lead to an in depth exploration of region-specific characteristics in different EU rural contexts that need to be effectively dealt within the European backcasting policy scenario framework; but also to a systematic assessment of the upcoming impacts of the EU-level scenarios to the local scale, i.e. down-scaling of the EU top-down scenarios and checking how they affect regions and rural localities in the EU. ß 2012 Elsevier Ltd. All rights reserved.

Keywords: Foresight Multi-scale scenarios Backcasting scenarios Linking global/EU with regional scenarios

1. Introduction Complexity and uncertainty are key issues in exploring future developments. Moreover, although the future cannot be predicted, it is clear that certain decisions/actions today can orient the future towards desired directions. Therefore, planners are challenged to focus on the development of tools and approaches, dealing with complexity and uncertainty in order to effectively support policy makers in making knowledgeable decisions towards desirable futures. In modern policy analysis, scenarios are considered as powerful tools for decision making in complex environments and are widely used in both private and public domains [1]. They serve a range of purposes, such as: strategic planning and decision support in situations marked by long-term and largely unpredictable uncertainty, where visioning of future developments is requested for guiding the policy agenda; scientific or research purposes, for exploring and understanding the dynamics of a system by gaining insight into the interactions and linkages among key drivers of its external and internal environment; ‘learning’ and ‘communication’ purposes, as tools that stimulate creative thinking and communicate, in a coherent and structured way, different perceptions on alternative future developments in order to motivate or influence behavioural changes in society, etc. Based on the goal and objectives of a scenario study and the approach adopted, different spatial scales for scenario development are involved, ranging from the global to the local level. The scale of the proposed scenarios may vary so that a certain study may involve simultaneously scenarios at various spatial levels such as global, national, regional and local, and the challenge is to conclude with scenarios consistent at all levels [2]. The integration of multiple geographical scales in the scenario approach is a quite intriguing issue and still subject to methodological development. It actually involves the integration of information at different spatial scales, e.g. global and

* Corresponding author at: Heroon Polytechniou Str. 9, Zographou Campus, 157 80 Athens, Greece. Tel.: +30 210 7722672; fax: +30 210 7722750. E-mail address: [email protected] (A. Stratigea). 0016-3287/$ – see front matter ß 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.futures.2012.09.003

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regional, to the benefit of both global and regional scenario studies. Applications of such an approach can be found, e.g. in the VISIONS [3] and GEO-4 [4] scenario studies, where global developments served as an input to regional scenarios, while regional developments were used to enrich and refine scenarios at a higher scale level. A similar effort is undertaken in the context of the AG20201 Project that focuses on building strategic policy scenarios for the EU agriculture in 2020. In this context, certain interplay was carried out between the EU-wide backcasting policy scenarios and the regional policy scenarios, for the exploration of regional future developments of certain EU rural contexts. These were used to enrich both the content of the backcasting scenarios structured, but also the policy framework used for reaching the targets in agriculture at the EU level in 2020. Regional scenarios developed were framed by the global/EU developments in both market and non-market key drivers of change, explored in the process of building EU backcasting policy scenarios. The focus of the present paper is on linking EU-wide backcasting policy scenarios in agriculture for the year 2020 to exploratory regional policy scenarios for representative EU rural areas (regional scale). So Section 2 elaborates on the approaches used for linking scenarios at different spatial scales; in Section 3 is presented the AG2020 approach for building strategic policy scenarios for sustainable EU agriculture in 2020; in Section 4 are presented the four AG2020 case studies and the methodological approach developed for building and assessing regional scenarios; Section 5 presents the AG2020 approach for linking the EU-wide to regional scenarios. Finally, in Section 6, some conclusions are drawn, pointing out limitations met throughout the whole exercise. 2. Approaches for linking scenarios across different geographical scales The spatial scale addressed to a scenario study may vary from global to national or even regional/local. As empirical work shows, global scenarios are usually long term exercises that aim at exploring critical future uncertainties and provide plausible future outcomes in support of decision making and policy analysis. So far they tend to be rather science or research-oriented and seem to heavily rely on quantitative methods (e.g. global scenarios for climate change, water resources, etc.). Regional/local scenarios, on the other hand, are mostly considered as vision building mechanisms, that aim at reaching consensus and provide community-driven policy recommendations. They are often participatory-oriented (regional stakeholders involved) and mostly based on qualitative methods. A key difference between global and regional/local scenarios is on the focus of the scenario study, where global scenarios focus rather on the outcome of a study, based mostly on experts’ knowledge, while regional scenarios focus on the scenario building process, based on a spectrum of participatory approaches. In recent years, a number of scenario studies involve the development of a set of ‘‘multi-scale’’ scenarios [5]. Linking global to regional/local scenarios is of importance for a number of reasons, such as: - The interdependence of processes appearing at different spatial scales. For example, climate change, as a global phenomenon, affects biophysical processes across the world regions, while socio-economic developments are governing, to a large extent, future climate changes. In this respect, the development of multi-scale scenarios is of importance for a better understanding of cross-scale interactions [6–9]. - The nature of the problems studied, e.g. in environmental problems, the global level is equally important as the regional, which is imperative to place regional scenarios in a global context [9]. - The type of processes and level of impacts observed: certain social, economic, political and ecological processes can often be more readily observed or have stronger impacts at some spatial scales [10], which implies that certain type of impacts will not be observed unless respective spatial levels are taken into consideration. - Global scenarios are involving developments for a number of critical issues or driving forces in the external environment of a region, which are framing decisions at the regional level [9]. - Global scenarios are a rich source of interdisciplinary information and knowledge, which can be of great support to decision makers at lower geographical scales. - Linking global to regional/local scenarios creates a communication platform among a wider variety of researchers, stakeholders and decision makers from different geographical settings, enriching thus the understanding or concerns of the various stakeholders’ [11] on the problem at hand, the process and the final outcome. - Finally, multi-scale scenarios enable to study more easily the impacts of the mismatches between the scale of occurrence of processes and the scale at which management occurs [12,13]. As an example can be mentioned the mismatch between scientific models and policy needs [14]. Formal approaches for linking scenarios across multiple geographical scales are not yet well developed or tested [15]. Based on empirical evidence from scenario studies carried out so far, Biggs et al. [15] distinguish two kinds of approaches for linking multi-scale scenarios:

1 AG2020 Project, Foresight analysis for world agricultural markets (2020) and Europe, PRIORITY AREA 1: Sustainable management of Europe’s natural resources, Contract no.: 44280-AG2020, STREP, 2007–09.

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- in the first, links are established up front and are maintained iteratively throughout the exercise; while - in the second, links are established either up front or after the development of scenarios. Based on this distinction, Biggs et al. [15] claim that linking scenarios across multiple spatial scales may range, based on the aim of the whole exercise, from ‘tightly coupled’ cross-scale scenarios to ‘loosely linked’ multi-scale scenarios. In tightly coupled cross-scale scenarios, storylines may be developed in a tightly coupled, iterative fashion, so that they are consistent across scales and incorporate cross-scale feedbacks. Links are usually established up front and are reinforced by an iterative process of down-scaling and up-scaling, with down-scaling implying the ‘‘translation’’ of broader scale scenarios to finer-scale situations and up-scaling referring to the reverse situation. As Rotmans et al. [16,17] notice, most tightly coupled cross-scale scenario exercises have been primarily top-down exercises, placing emphasis on down-scaling than up-scaling. This reflects, on the one hand the difficulties involved in the effort to incorporate diverse and inconsistent elements from lower scales into the larger-scale storylines; and on the other hand, the emphasis placed by both the policy-makers and the research community on how top-down institutional and economic drivers affect regions and localities, rather than the effect of bottom-up factors [15]. The approach of tightly coupled cross-scale scenarios seems to work best when the main objective of the scenario exercise is to deepen our understanding of cross-scale processes/interactions and potential responses or to assess trade-offs between scales. In loosely linked multi-scale scenarios, storylines at different spatial scales may develop independently and be only loosely linked. Links may be established either up front or after the scenario development exercise [15]. In this type of scenarios, perspectives, uncertainties and drivers from each scale aim to partially inform or frame scenario exercises at other (lower) scales. For example, by establishing links up front, global scenarios can set the boundary conditions for the development of scenarios at lower spatial scales, by down-scaling global storylines. Such down-scaling can be accomplished with varying degrees of flexibility, by means of quantitative vs qualitative down-scaling, with the later leaving more space for flexible approaches [15]. When independent scenarios are developed at different spatial scales, links are established usually by categorizing the drivers and outcomes in the different scenarios and grouping similar scenarios at different scales [15,18]. The approach of loosely linking multi-scale scenarios appears more appropriate when the primary aim is to engage in an exploratory dialogue with stakeholders, as it tends to allow more freedom to the stakeholders at each spatial scale to explore the issues of their concern [15]. In Table 1 are presented the key attributes of single, loosely linked multi-scale scenarios and tightly coupled cross-scale scenarios. The linking of scenarios across different geographical scales can be accomplished, according to Zurek and Henrichs [9], through the: scenario development process; and scenario elements or outcomes; where, in both cases, links can be either loose or tight.

Table 1 Key attributes of various scenario linking approaches. Approach Attribute

Single scale

Loosely linked multi-scale scenarios

Tightly coupled cross-scale scenarios

Number of focal scales Consistency of storylines across scales

1 Not relevant

At least 2 Storylines usually differ and are inconsistent across scales

Consideration of drivers at other scales

Exogenous drivers from other scales included, based on their relevance

Consideration of feedbacks between scales Main advantages

Not considered

Exogenous drivers and constraints from higher and lower scales are included. Scenarios usually constructed by use of a common broad conceptual framework, incorporating similar types of drivers at different scales May or may not be considered

At least 2 Storylines have a high level of consistency across scales – explicit focus on down-scaling and/or up-scaling Exogenous drivers and constraints from higher and lower scales are included via down-scaling and up-scaling iterative procedures

Simple, no distraction by concerns at other scales

Allows stakeholders at each scale to frame the issues that are important to them

Main disadvantages

Important feedbacks between scales may be missed or important externalities at other scales may be overlooked

Scenario outcomes at different scales or different places are not directly comparable

Source: [15].

Multi-scale

Explicit linkages between scales and incorporation of feedbacks Consideration of feedbacks between scales -evaluation of how an issue plays out at different scales Very costly; may lose credibility because stakeholders at, especially, lower scales may not have much latitude to define the issues to be considered

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The first case – linking the scenario development processes – involves a number of approaches, ranging from having the same team of scenario developers that is used to create the scenarios at each single scale to running parallel scenario development processes, in which scenarios are built using the same methods [15]. By this approach, various levels of consistency can be achieved, based on the selected process for scenario building. The second case – linking scenario elements or outcomes – provides a variety of linking options that may range from a complete translation of focal questions, assumptions, drivers, and outcomes across scales to sets of scenarios that merely address similar broad issues at different scales [15]. 3. Building strategic policy scenarios at the EU level: the AG2020 approach In this section is shortly presented the methodological approach developed in AG2020 for building backcasting policy scenarios [19], serving the sustainable development of the EU agriculture in 2020 (Fig. 1) [20,21]. Key elements of this approach are: - Objectives referring to aims pursued towards 2020 [22]. - Targets defined as ‘explicit endpoints of public policy, expressed in terms of relevant indicators, to be pursued within a given time span, with a systematic monitoring of progress towards their achievement’ [22]. - External elements: driving forces of the external environment (market or non-market oriented) that may have an impact on the future development of the EU agriculture, e.g. WTO policies, environment policy. - Internal elements: driving forces of the EU agricultural system, e.g. CAP developments. - Strategic elements: the most influential drivers of the agricultural system, upon which solutions within the different policy making environments (Images) are pursued. As such were considered technology and decoupling. Based on the above elements are built the Images of the Future, which, based on different sets of hypothesis, describe different states (developments) of the society in general and the EU agriculture in particular at the year 2020 (the EU spatial scale), within which the targets are pursued (see [23–25]). Three Images of the Future are considered in AG2020 [21], namely: - IMAGE I – ‘High-tech Europe: Global Cooperation for Sustainable Agriculture’, where science and technology is of utmost importance, together with a focus on ‘‘top-down’’ initiatives. - IMAGE II – ‘In search of Balance: Accord on Sustainability’, corresponding to a ‘‘combined approach’’ (top-down and bottom-up), where the focus is on economy and energy. - Image III – ‘Active Regions and Reflexive Lifestyles’, where the emphasis is placed on behavioural change, involving strong public participation and prevalence of green values (‘‘bottom-up approach’’). Next is developed the policy framework that should be enforced in order to reach the targets within the different Images of the Future [24]. This consists of policy measures, packages and paths. Policy measures are selected on the basis of their potential, among others, to contribute to the achievement of the AG2020 targets and were validated by experts and stakeholders. Policy packages are developed by combining sets of policy measures that are likely to work well together (i.e. create synergies) in the context of the Images. Finally, policy paths are made up of both policy packages and policy measures.

Fig. 1. The AG2020 backcasting policy scenario approach. Source: [20,21].

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The construction of policy packages and policy paths is an iterative process, which can go on over many cycles and is based on experts’ and stakeholders’ participation. Policy making in agriculture is an EU-driven task (Common Agricultural Policy – CAP). Nevertheless, as the agricultural sector in the EU territory may follow completely diversified development patterns, it is of importance to link (down-scale) each of the EU AG2020 backcasting policy scenarios with the regional level and explore potential developments of rural regions, under the three different backcasting policy scenarios for the future of agriculture in the EU 2020. In this respect, the role of case studies (the regional level – Fig. 1) is to shed light on the local specificities/challenges of a variety of rural contexts of the European territory in order to enrich the knowledge on the diversification of the EU agricultural system across the European territory. It also aims to provide information on community-driven policy recommendations that reflect the view, values and perspectives of regional stakeholders as to the future development of the agricultural sector, but also other sectors as well in different EU rural communities. This knowledge will provide input for improving the policy framework, by indicating region-specific and scenario-specific policy measures for coping with the challenges emerging across the EU rural regions. Moreover, case studies can provide a useful input for revealing specific policy packages (directions) that may be of relevance in the AG2020 policy framework. 4. Building regional scenarios for the AG2020 case studies In AG2020, four representative regional case studies were selected, namely the: Rhodopes region in Bulgaria (CS1), Kastelli region in Herakleion-Crete (CS2), Central Denmark Region – CDR in Denmark (CS3) and Tuscany region in Italy (CS4) (Fig. 2), based on the: -

Challenges posed in each specific case study rural environment; Presence of factors that are expected to strongly impact agricultural development; Presence of factors that are identified as most challenging and influential at the regional level; Balanced geographical representation to ensure a variety of EU rural contexts in the study.

In the following are shortly presented the most outstanding characteristics, but also challenges and threats faced by each of the four case studies as well as the methodological approach developed for building regional scenarios, framed by the AG2020 approach. 4.1. The case studies The Rhodope Mountainous region-Bulgaria (CS1) has as most outstanding feature the rich biodiversity and the high value forest ecosystems. The agricultural sector is declining during the past decades, mainly due to the low level of efficiency and

Fig. 2. The AG2020 regional case studies.

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modernization, the rough morphology, but also the political priorities set in the past. Other important issues, framing the development of the agricultural sector so far, are the small scale of land ownership, the limited accessibility, the low qualification and productivity of labour resources, etc. The region today is facing new challenges for driving successfully sustainable rural development. As main comparative advantages can be considered the: qualitative agri-food production, alternative tourism, but also the energy production, based on biomass management. The Kastelli region – Greece (Herakleion Crete) (CS2) is a rural region in the island of Crete, facing a number of upcoming challenges, due to the location of a new airport infrastructure that intends to occupy a large part of the most fertile land of the region. The study focus is on the development of an integrated sustainable development plan for the study region, which promotes multifunctionality of the agricultural land in the area and may attract new investments in the region, for increasing local employment and income opportunities. In the Central Denmark Region – Denmark (CS3), the agri-food sector is traditionally a highly innovative, industrially oriented sector, strongly dominated by large multinationals food businesses, which place emphasis on efficiency aspects and hold a strong export orientation. The main threats that the region is facing nowadays relate to the intensive use of local resources (land, water, etc.); the industrially based agriculture, placing a lot of pressure on the environmental resources (e.g. landscape, soil); the lack of diversified production; etc. On the advantages can be countered the gains in competitiveness of the agri-food sector in a global context. Finally, the Tuscany region – Italy (CS4) is a region rich in natural and cultural resources, where the revitalization and integration of the agricultural sector to the local economic structure is at the core of the local policy efforts. A high level of multifunctionality is pursued, with the agricultural sector forming the basis for qualitative food production, safeguard of the natural resources, hosting of alternative tourist activity, production of renewable energy, etc. The landscape protection and conservation constitute key concerns for the Tuscany area, as the most important resource for the local population and a main attraction for visitors in the region. 4.2. The methodological approach For each case study, regional scenarios were structured and validated by local stakeholders. The steps of the methodological approach, adopted in each specific case study, have as follows [26] (see Fig. 3):  Step 1: Description of frames and objectives, involving the following stages: - Regionalization stage: aiming at the spatial delimitation of the study system. - Regional analysis stage: involving the study of the present situation as to the environmental, social and economic characteristics, cultural aspects, infrastructure, etc. - Identification/prioritization of problems: aiming at the exploration of problems in respect to both the internal (study system [26]) and the external environment. - Setting of objectives: where the objectives are selected, following the six AG2020 objectives, properly adjusted/prioritized to fit each specific regional context.  Step 2: Development/assessment of regional scenarios At this stage are built regional scenarios, taking into account the: regional characteristics; objectives set at the previous stage; and developments of the external environment (driving forces at the global and EU level), provided by AG2020. The scenario building process follows the subsequent steps [27]: - A set of hypotheses is structured, based on the key drivers of the internal environment of the region, as these are identified by the regional analysis, already carried out, but also the key drivers of the external environment, as identified by AG2020, e.g. technology, food preferences; - For each hypothesis, different possible future outcomes are drawn, based on local expert opinions; - Regional development scenarios are structured, placing at the core the agricultural sector. Each of them presents the future outcomes of the different combination of the hypotheses considered, that are coherent and consistent. Key drivers in the scenario building process are also technology and decoupling, the strategic elements of the AG2020 backcasting policy approach; - Assessment of regional scenarios by experts: qualitative assessment tools (SWOT analysis) and multicriteria evaluation tools (MULTIPOL model) are used to carry out scenario assessment for each case study, where it is assessed the performance of each scenario in respect to the region-specific set of objectives.  Step 3: Stakeholders’ validation of the scenarios Each regional scenario was validated by local stakeholders. As tools were used: - The microsimulation approach, studying the willingness of farmers to adopt/use technology for the production of high quality agri-food products and develop alternative activities at the farm level (for Central Denmark, Tuscany and Rhodopes regions) [28–30];

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Fig. 3. Methodological steps of the approach adopted in the AG2020 case studies. Source: [27].

- Stakeholders’ workshops at the local level for validating regional scenarios (for Central Denmark, Tuscany and Rhodopes regions) [28–30]; and - Focus groups methodology integrating the ‘future workshops’ participatory approach that aims at the structured discussion/ validation of regional scenarios (for the Kastelli region) [27].  Step 4: Region-specific policy measures The outcome of the previous steps is a set of region-specific (Rhodopes, Kastelli, Central Denmark and Tuscany regions) and scenario-specific policy measures, which may feed the pool of AG2020 policy measures, reflecting thus region-specific policy directions towards fulfilling the objectives. 5. Linking scenarios across different geographical scales: the AG2020 approach Based on the preceding discussion on the approaches for linking multi-scale scenarios (see Section 2), the linkage of the AG2020 EU-wide backcasting policy scenarios and the regional scenarios through the scenario building process presented certain limitations, as these followed different approaches. Therefore, a ‘loosely linking approach’ was adopted, linking the scenario elements of the multi-scale scenarios, i.e. linking focal questions, objectives, key drivers of the external environment and strategic elements between EU and regional scenarios, all serving the goal of sustainable agricultural development. In the following is presented the approach adopted in AG2020 for linking the EU-wide backcasting policy scenarios for agricultural development and the regional scenarios, developed in the four case studies (see Fig. 4).

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Fig. 4. Linking policy scenarios at the EU and the regional level – the AG2020 approach.

5.1. Setting the objectives in the AG2020 case studies The first element used for linking the EU-wide and the regional scenarios is the objectives pursued by these scenarios (link 1 in Fig. 4). From the point of view of AG2020, sustainability in the EU agricultural sector is encompassing the following objectives [31,24,25]: - Environmental aspects: preserving ecological balance of physical and biological systems. - Economic efficiency aspects: ‘‘. . . attaining the maximum flow of income, while at least maintaining the non-renewable stocks or assets that yield these benefits’’ ([32], p. 40). - Regional development: that aims at reducing disparities, providing thus equal access to employment, services, etc. - Social cohesion aspects: that aspire to maintain stability in social and cultural systems, by pursuing a healthy and productive life, in harmony with the environment. - Food quality and safety aspects: that promote food safety and trust in agricultural qualitative products for consumers. - Energy production aspects: that contribute to the EU climate change target of reducing 20% GHG emissions compared to 1990, upon which the EU has planned its long term energy policy up to 2020 (biofuels’ production). The objectives set in the AG2020 case studies are following the above set of objectives, properly adjusted to reflect the specificities but also the priorities set by the local community in each specific rural context (see Table 2). 5.2. Key drivers of change and strategic elements In AG2020, as key drivers of change are considered both the ‘external’ and ‘internal’ elements to the EU agricultural system, that may have an impact on the future development of the sector in EU. Knowledge of the key drivers of the external environment is critical for exploring the future states and constructing the main hypotheses for building the AG2020 Images of the Future. Knowledge of the key drivers of the internal environment supports the choice of those strategic elements that are considered as the most influential drivers of the agricultural system, i.e. a change in these key drivers is largely expected to influence the rest of the system. As key drivers, which are expected to have an impact on the EU agricultural system in the long run, were considered [21]: - Elements of the ‘‘external environment’’: these were further subdivided into ‘‘non-market’’ related elements and ‘‘marketrelated’’ elements. As ‘‘non-market’’ related elements were considered: globalization, international trade and division of

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Table 2 Specialization of AG2020 objectives in each specific rural context. The Rhodopes region

Set of objectives for the Rhodopes region Environmental protection: protection of biodiversity and landscape quality, as the region possesses outstanding natural attributes and rich/unique biodiversity. Economic efficiency: increase competitiveness – suspend state support. Regional development: increase in employment, accessibility of rural regions and a shift towards more value-adding agricultural production. Social cohesion: decreasing inequalities within the region. Food quality and safety: production of high quality and safe products, gourmet, organic and labelled products, etc. Energy: improvement of energy efficiency in the agri-food production sector.

The Kastelli region

Set of objectives for the Kastelli region Environmental protection: rational exploitation of resources, with emphasis on the protection of natural and cultural environment. Economic efficiency: emphasis on innovation diffusion and entrepreneurship in all economic sectors. Regional development: broadening the range of activities to support employment and income opportunities with emphasis on the multifunctional role of rural land. Social cohesion: ensuring equal access of local population to opportunities. Food safety and quality: increasing competitiveness of the agri-food sector based on qualitative agricultural production. Energy: enhancing renewable energy production (biomass, solar and wind energy).

The CDR region

Set of objectives for the Central Denmark region (CDR) Environmental protection: protection of water and natural resources, development of eco-efficient agriculture. Economic efficiency: placing emphasis on the promotion of innovation and entrepreneurship; and the strengthening of cooperation among agri-food businesses and R&D firms. Regional development: focusing on the upgrading of human potential, export activity, network infrastructure and built environment. Social cohesion: decreasing inequalities within the region. Food quality and safety: pursuing the diversification in food production, with emphasis on ‘clever everyday food’ and ‘cultural food’. Energy: focusing on full exploitation of renewable energy based on technology.

The Tuscany region

Set of objectives for the Tuscany region Environmental protection: protection of natural and cultural environment, heritage and landscape. Economic efficiency: pursued mainly by improvement of the production processes and promotion of entrepreneurship. Regional development: triggering the competitive advantages of the region and encouraging diversification of activities and innovation. Social cohesion: targeting removal of spatially related and group-related social inequalities. Food quality and safety: promotion of organic farming, innovations in the agri-food sector, etc. Energy: promoting renewable energy production and rational use of energy.

Source: [27–30].

labour, GDP and economic growth, environmental trends, demographic developments, quality of life and social welfare, global energy demand and supply, consumption patterns, societal values, environmental awareness, oil prices, R&D policies and technological breakthroughs, etc. As ‘‘market-related’’ elements were considered the WTO/World agricultural markets, other agricultural systems outside the EU, etc. - Elements of the ‘‘internal environment’’ (EU agricultural sector): EU enlargement, supply versus demand in agriculture, efficiency issues, local versus global consumption, taste variety, environmental policies, CAP, bioenergy production, land use patterns/conflicts, environmental awareness, availability of skilled labour in agriculture, etc. The above key drivers are used as ‘input’ to the regional level in order to inform the regional scenario building process on global developments (link 2 in Fig. 4). These forces are setting the frame for decision making at this level, although they are out of the control of the region.

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As strategic elements in AG2020, are considered technology and decoupling. Technological developments are important for supporting sustainable development in the European agriculture, facing challenges like globalization, energy shortage and climate change [33,34]. Moreover, they are also important for Europe’s farming, agri-food and forestry sectors, which, by means of technological innovations, can further develop high quality and value added products that meet the diverse and growing demand of European consumers and world markets. Strategic elements at the EU level (technology and decoupling) are also used to deal with future challenges of the agricultural sector at the regional level. Decoupling, on the other hand, can take a number of different forms, depending on the study focus, as for example [24,25]: - decoupling of agricultural production from intensive use of resources (land, water, energy, etc.), supporting a less resourceintensive or more environmentally friendly pattern of agri-food production; - decoupling of agricultural production from environmental degradation (e.g. organic farming); - decoupling of rural development from the agricultural sector; - decoupling of integration into agri-food markets from subsidies; - decoupling of agri-food production from biofuels’ production (coping with land competition issues); - decoupling of bio-energy production from environmental harm; etc. It is important to note that consistent ‘transformation’ of the above elements (drivers of change and strategic elements) at the regional scale, in order to frame the scenario development process at this level, is assured by the fact that the researchers involved in the development of the regional scenarios were also members of the AG2020 consortium and had participated in the AG2020 scenario building exercise. This has contributed to the widening of their knowledge and understanding of the variety of issues involved in the global-EU context. This, together with their good knowledge of the study region, had positive impacts on both the framing and the development of the regional scenarios, i.e. possible future outcomes under different developments of the global/EU drivers of change. 5.3. Building regional scenarios framed by the AG2020 context In AG2020, three Images of the Future were constructed (see Section 3), representing the desired futures of agricultural development meeting the targets in the EU 2020 [24,25]. As building blocks were used the: targets, contextual elements (external/internal elements) and strategic elements. Regional scenarios, on the other hand, were built on the basis of two types of information, namely (link 3 in Fig. 4): a. Information on the past and present developments, based on the regional analysis of each specific rural system at hand; and b. Information on the: - objectives, set in each case study, which reflect each specific rural context and are in line with the AG2020 objectives; - key drivers of change of the external environment (global and EU), both market-related and non-market related, provided by the AG2020 framework (Images of the Future); - strategic elements (technology and decoupling) as defined in AG2020; and - key elements of the agricultural sector, as defined in the building process of the AG2020 Images of the Future, namely: agritechnology and food technology, food quality and safety, energy production, integration into global agri-food markets, regulated factor markets (land labour, water), and rural development aspects; but also of the society in general, e.g. green values in the society, environmental awareness, participation, adoption/use of technology and ICTs, provided by the AG2020 framework. The information included above in part (b), setting the framework for the development of the Images of the Future (EUwide scale), is down-scaled to the regional level, where, combined also with the objectives set in each case study, sets the frame for the identification of a number of key domains and respective hypotheses considered in the scenario development process for each regional case. Based on the different combinations of hypotheses in the key domains, regional scenarios were developed and assessed by means of participatory approaches (stakeholders’ scenario workshops) (see Fig. 3). Out of this process, several plausible, distinct, but also coherent scenarios were constructed for each study region, which are shortly presented in Table 3. 5.4. Policy framework At this stage, takes place a certain linking between the two levels (top-down EU-wide and bottom-up regional spatial scale) in the policy context, which takes the form of a two way interaction (see link 4 in Fig. 4). In this respect, the EU level is used to inform the regional context on the type of global challenges that will frame the development of the agricultural sector in various EU local rural environments and the policy measures that could be of relevance in order to cope with challenges, by framing the policy framework at the regional level.

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Table 3 Regional scenarios in AG2020. The Rhodopes region Scenario 1: High-tech Rhodopes region

Scenario 2: Sustainable Rhodopes region

Scenario 3: Business as usual

Specialization in high-tech agri-production; high rate of adoption/use of technology – focus on technologies supporting regional specialization/export; less labour-intensive/ more efficient agricultural activities; education and training of labour force.

Focus on local identity and traditional high quality products/product certification; environmentally friendly agriculture and food processing; high level of multifunctionality; medium rate of adoption/use of technology; labour-intensive agri-food production; qualitative ‘green’ products.

Local production and consumption pattern; limited export orientation; labour-intensive farming model; region is self-sufficient in basic life-supporting goods (food and energy); local community more resilient to external shocks, e.g. energy supply disruptions.

The Kastelli region Scenario 1: Scenario ‘‘with new airport’’

Scenario 2: Scenario ‘‘without new airport’’

Considerable loss of agricultural and residential land; new concentrated settlement pattern; high rate of diffusion of agritechnology serving efficiency goals; strong multifunctionality (alternative tourism, processing of agri-products, RE production); high rate of ICTs adoption/use – new network opportunities, e.g. tourist marketing, e-commerce; new economic activities attracted by the new airport; improvement of the regional infrastructure networks.

Pattern of settlements/population distribution remains unchanged; high adoption/use of technology and innovation for rational use of resources; high quality products (organic agriculture); alternative tourism; energy production (biofuels) – processing of agri-biomass and energy crops; high quality and traditional products, export orientation; high rate of adoption/use of ICTs – networking; small scale investments around eco-activities; environmental culture prevails; RE. The CDR region

Scenario 1: ‘‘High tech agri-food sector’’

Scenario 2: ‘‘Nature matters’’

Scenario 3: ‘‘Revitalization of the Central Denmark rural region’’

Population distribution unchanged; technology for efficiency, environmentally friendly and of high quality production; industrialized agri-food sector; clustering of manufacturing firms; export orientation; cooperation of R&D institutions and agri-food industry; branding landscape values; medium rate of adoption/ use of ICTs; medium share of RE – energy efficiency.

Population distribution patterns unchanged; industrially based high tech agriculture, focus on efficiency and less environmental harm; management of natural resources; clustering of manufacturing firms, export orientation; agro-eco tourist activities, coastal and urban tourism; high rate of diffusion of agri-food technologies and ICTs; high share of RE; energy efficiency.

Dispersed pattern of population distribution; improved accessibility to transport and ICTs, educational and cultural activities; development of niche, innovation-based, export-oriented agri-food production; agro-eco tourist activities, integrated with coastal and urban tourism; high rate of adoption/use of ICTs; high share of RE; energy efficiency.

The Tuscany region Scenario 1: ‘‘High tech Tuscany’’

Scenario 2: ‘‘Business as usual’’

Scenario 3: ‘‘Revitalization of the region’’

Concentrated pattern of population distribution; emphasis on efficient agri-food production, food quality and safety as well as export orientation; low/medium level of multifunctionality; high rate of technology and ICTs adoption/diffusion; high share of RE; energy efficiency.

Concentrated pattern of population distribution; specialization on environmentally friendly agriculture – qualitative organic production; low/medium level of multifunctionality; low/medium rate of adoption/use of agri-food technology and ICTs; low share of renewable energy.

Deconcentrated pattern of population distribution; qualitative organic products, PDO, PGI, TSG, mountain products; product certification; alternative tourism; low/ medium rate of adoption of agri-food technology; medium rate of ICTs adoption and use; high share of RE; energy efficiency.

Source: [27–30].

On the other hand, the regional level is used to inform the EU-level on the various types of issues faced by the EU rural regions and the respective policy measures that could be of help in this respect. This may enrich the pool of policies at the EU level and may conclude with a pool of policy measures that may cope effectively with the different EU rural profiles. Out of this process it is created a pool of 257 policy measures in AG2020, accompanied by the strategy they are serving, their impact on the AG2020 targets, the agricultural sector and the critical issues that need to be dealt with by the agricultural sector, as well as the time and scale effects of these measures (see [24,25]). This could be of great help in support of policy makers in various EU regional environments, based on the direction of developments at the EU level. 5.5. Linkages of regional scenarios to the AG2020 images of the future Based on the previous discussion, in Table 4 are presented the linkages that are drawn between the Images of the Future designed in AG2020 (EU-wide spatial scale) and the regional scenarios developed in the four case studies (see link 5 in Fig. 4):The information presented above indicates the importance of multi-scale studies not only for better understanding of the interactions between processes across scales, but also in terms of assessing the impact of political decisions at a higher scale and the policy frameworks that need to be enforced in the various regions in order to successfully cope with challenges imposed by top-down political decisions.

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Table 4 Linkages of regional scenarios to the AG2020 Images of the Future. AG2020 Images of the Future

Regional scenarios Rhodopes region

Kastelli region

Central Denmark Region

Tuscany region

Image I ‘‘High-tech Europe: Global Cooperation for Sustainable Agriculture’’ Image II ‘‘In search of Balance: Accord on Sustainability’’

S1: ‘High-tech Rhodopes region’ – links to Image I

S1: Scenario ‘with new airport’ – links to Image I

S1: ‘High tech agri-food sector’ – links to Image I

S1: ‘High tech Tuscany’ – links to Image I

S3: ‘Business as usual’ – links to Image II

–

S2: ‘Business as usual’ – links to Image II

Image III ‘‘Active Regions and Reflexive Lifestyles’’

S2: ‘Sustainable Rhodopes region’ – links to Image III

S2: Scenario ‘without new airport’ – links to Image III

S3: ‘Revitalization of the Central Denmark rural region’ – links to Image II S2: ‘Nature matters’ – links to Image III

S3: ‘Revitalization of the region’ – links to Image III

6. Conclusions In the present paper, is carried out an effort to link scenarios at multiple geographical scales, involving EU-wide and regional geographical scales. The scenario studies in both the EU and the regional level were carried out in the context of the AG2020 Project, aiming at the sustainable development of the EU agriculture in 2020. For building strategic policy scenarios at the EU level, the backcasting approach was used, while regional scenario studies were based on a variety of tools and approaches. Participatory approaches were of key importance in both geographical scales, by providing experts’ and stakeholders’ inputs at each stage of the scenario building process and validating the results obtained out of the scenario exercises. The approach of loosely linking scenarios at different scales is adopted, as serving more effectively the goal of engaging stakeholders in an exploratory dialogue, allowing more freedom to cope with the issues of concern to the stakeholders at each scale [16]. More specifically, EU-wide and regional scenarios are linked through the scenario elements of the two geographical scales involved. A complete ‘translation’ of focal questions, assumptions, drivers, and objectives across the scales is carried out in this respect. The scope of the exercise is two-fold: on the one hand it aims at using the EU-level to inform/frame developments at the regional level, while on the other hand, it aims at using the regional level for broadening the scope of the EU level in order to cope more effectively with different EU rural profiles. The experience gained through this exercise shows that there are a number of limitations that need to be properly addressed for a successful outcome. These relate to the: - Identification/understanding the large variety of issues and interactions involved between the global-EU and the local level; - Data availability, mainly at the regional level; - Knowledge/skills on proper tools for scenario building, especially at the regional level; - Knowledge/skills level on participatory tools necessary for involving public and stakeholders at all geographical scales; - Consistent ‘transformation’ of the elements (drivers of change and strategic elements) at the regional scale – Important: experience/skills of researchers in charge at the regional level; - Willingness of local population to engage in participatory exercises – time/cost-consuming processes; - Difficulties in communication either among experts or among local stakeholders due to lack of common knowledge base/ interests; - Lack of cooperation and interaction among different geographical scales in the planning efforts. The adoption of loosely linking scenarios at the different scales involved (EU and regional scale), adopted in the present study appears to have certain advantages, as: - it assures the gathering of scale-specific stakeholders’ input that further enhances credibility and relevance of the output (scenarios) produced; - it facilitates the broadening of perspectives, processes and issues addressed at both scales; - it integrates experts’ and local stakeholders’ knowledge, which may result to a more effective set of options available; and - it creates a platform for the communication of a wider variety of researchers, stakeholders and policy makers, widening thus the range of views to the benefit of the problem, the process and the outcome of the whole exercise.

References [1] P. van Notten, J. Rotmans, M.B.A. van Asselt, D.S. Rothman, An updated scenario typology, Futures 35 (3) (2003) 425–443. [2] J. Jaeger, D. Rothman, C. Anastasi, S. Kartha, P. van Notten, GEO resource book – a training manual on integrated environmental assessment and reporting – training module 6 – scenario development and analysis, UNEP (2006). [3] J.W. Cosgrove, R.F. Rijsberman, World Water VISION. World Water Council, Earthscan Publications Ltd., 2000. ISBN: 1 85383 730 X.

A. Stratigea, M. Giaoutzi / Futures 44 (2012) 847–859

859

[4] J. Potting, J. Bakkes (Eds.), The GEO-3 scenarios 2002–2032 – quantification and analysis of environmental impacts., United Nations Environment Programme (UNEP) and National Institute for Public Health and the Environment (RIVM), Netherlands, 2004. [5] K. Kok, R. Biggs, M. Zurek, Multiscale narratives from an IA perspective. Part II. Participatory local scenario development, Futures 38 (2006) 285–311. [6] T.J. Wilbanks, R.W. Kates, Global change in local places: how scale matters, Climatic Change 43 (1999) 601–628. [7] F. Berkes, Cross-scale institutional linkages: perspectives from the bottom up, in: E. Ostrom, T. Dietz, N. Dolsak, P.C. Stern, A.S. Stonich, E.U. Weber (Eds.), The Drama of the Commons, National Academy Press, Washington, DC, USA, 2002, pp. 293–322. [8] L. Gunderson, C.S. Holling (Eds.), Panarchy: Understanding Transformations in Human and Natural Systems, Island Press, Washington, DC, USA, 2003. [9] M. Zurek, T. Henrichs, Linking scenarios across geographical scales in international environmental assessments, Technological Forecasting & Social Change 74 (2007) 1282–1295. [10] MEA – Millennium Ecosystem Assessment, Ecosystems and human well being: a framework for assessment. Report of the Conceptual Framework Working Group of the Millennium Ecosystem Assessment, Island Press, Washington, DC, 2003. [11] E. Wollenberg, D. Edmunds, L. Buck, Using scenarios to make decisions about the future: anticipatory learning for the adaptive co-management of community forests, Landscape and Urban Planning 47 (2000) 65–77. [12] C. Folke, L.J. Pritchard, F. Berkes, J. Colding, U. Svedin, The problem of fit between ecosystems and institutions. IHDP Working paper No 2. International Human Dimensions Programme on Global Environmental Change, Bonn, Germany, 1998. [13] K. Brown, Integrating conservation and development: a case of institutional misfit, Frontiers in Ecology and the Environment 1 (2003) 479–487. [14] C.E. van Daalen, W.A.H. Thissen, M.M. Berk, The Delft process: experiences with a dialogue between policy makers and global modelers, in: J. Alcamo, R. Leemans, G.J.J. Kreileman (Eds.), Global Change Scenarios of the 21st Century: Results from the IMAGE 2.1 Model, Elsevier Science, London, UK, 1998, pp. 267–285. [15] R. Biggs, C. Raudsepp-Hearne, C. Atkinson-Palombo, E. Bohensky, E. Boyd, G. Cundill, H. Fox, S. Ingram, K. Kok, S. Spehar, M. Tengo¨, D. Timmer, M. Zurek, Linking futures across scales: a dialog on multi-scale scenarios, Ecology and Society 12 (1) (2007) 17, http://www.ecologyandsociety.org/vol12/iss1/art17/. [16] J. Rotmans, M. van Asselt, C. Anastasi, S.C.H. Greeuw, J. Mellors, S. Peters, D.S. Rothman, N. Rijkens-Klomp, Visions for a sustainable Europe, Futures 32 (2000) 809–831. [17] J. Rotmans, M. van Asselt, D. Rothman, Scenario Innovation: Experiences from a European Experimental Garden, Taylor & Francis, London, UK, 2005. [18] K. Kok, R. Biggs, M. Zurek, Methods for developing multi-scale participatory scenarios: insights from Southern Africa and Europe, Ecology and Society 12 (1) (2007) 8, http://www/ecologyandsociety.org/vol12/iss1/art8/. [19] K.H. Dreborg, Essence of backcasting, Futures 28 (9) (1996) 813–828. [20] M. Giaoutzi, A. Stratigea, The rationale for building images of the future: the AG2020 approach. Paper Presented at the Copenhagen Consortium and Stakeholders’ Workshop, 7–9 May (Working paper No 1), 2007. [21] M. Giaoutzi, A. Stratigea, P. Nijkamp, E. van Leeuven, M. Banse, Definition of policy scenarios. D5.3, AG2020 Project – Foresight analysis for world agricultural markets (2020) and Europe, Contract no.: 44280-AG2020, STREP, 2007–09, 2008. [22] M. Giaoutzi, A. Stratigea, P. Nijkamp, E. van Leeuven, Policy targets in the context of AG2020. Working paper No 4. AG2020 Project – Foresight analysis for world agricultural markets (2020) and Europe, Contract no.: 44280-AG2020, STREP, 2007–09, 2007. [23] M. Giaoutzi, A. Stratigea, P. Nijkamp, E. van Leeuwen, Scenario design process in AG2020. AG2020 Project, Working paper No 6, 2008. [24] M. Giaoutzi, A. Stratigea, Assessment of alternative policy scenarios on a global level. D5.5. AG2020 Project – Foresight analysis for world agricultural markets (2020) and Europe, Contract no.: 44280-AG2020, STREP, 2007–09, 2009. [25] M. Giaoutzi, A. Stratigea, General assessment of alternative policy scenarios. D5.6 – Final Report. AG2020 Project – Foresight analysis for world agricultural markets (2020) and Europe, Contract no.: 44280-AG2020, STREP, 2007–09, 2010. [26] D. Orrell, P. McSharry, A systems approach to forecasting. Foresight, The International Journal of Applied Forecasting 14 (Summer) (2009) 25–30. [27] A. Stratigea, M. Giaoutzi, Ch. Papadopoulou, The AG2020 case studies – Report on the Kastelli – Herakleion case study. D6.4. AG2020 Project – Foresight analysis for world agricultural markets (2020) and Europe, Contract no.: 44280-AG2020, STREP, 2007–09, 2009. [28] J.G. Hansen, K. Borch, G. Trombi, A. Stratigea, The AG2020 case studies – Report on the Central Denmark Region case study. D6.4. AG2020 Project – Foresight analysis for world agricultural markets (2020) and Europe, Contract no.: 44280-AG2020, STREP, 2007–09, 2009. [29] G. Trombi, M. Bindi, G. Brandani, L. Orioli, A. Stratigea, M. Giaoutzi, K. Georgieva, K. Borch, The AG2020 case studies – Report on the Tuscany case study. D6.4. AG2020 Project – Foresight analysis for world agricultural markets (2020) and Europe, Contract no.: 44280-AG2020, STREP, 2007–09, 2009. [30] A. Atanassov, K. Georgieva, The AG2020 case studies – Report on the Rhodope case study. D6.4. AG2020 Project – Foresight analysis for world agricultural markets (2020) and Europe, Contract no.: 44280-AG2020, STREP, 2007–09, 2009. [31] M. Giaoutzi, A. Stratigea, Defining objectives and targets in AG2020. Paper prepared for the AG2020 Workshop. Copenhagen, 7–9 May (Working paper No 2), 2007. [32] R. Stimson, R. Stough, B. Roberts, Regional Economic Development: Analysis and Planning Strategy, second ed., Springer Verlag, Berlin, 2006. [33] K. Borch, H. Østergaard, S. Christense, M. Petzoldt, K. Menrad, Report on expected time frame of future technological developments and impact. AG2020 Project, Contract no.: 44280-AG2020, 2008. [34] L.R. Pearson, Forecasting future technology. Foresight, The International Journal of Applied Forecasting 20 (Winter) (2011) 24–28.

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