project no.: 022793 forescene development of a
DESCRIPTION
Development of a Forecasting Framework and Scenarios to Support the EU Sustainable De- velopment Strategy Thematic Priority 8.1: Policy-oriented research, scientific support to policies, integrating and strengthening the European Research AreaTRANSCRIPT
Project no.: 022793
FORESCENE
Development of a Forecasting Framework and Scenarios to Support the EU Sustainable De-
velopment Strategy
Instrument: STREP
Thematic Priority 8.1: Policy-oriented research, scientific support to policies, integrating and
strengthening the European Research Area
D.3.2 – Technical report
Possibilities for modelling sustainability scenarios
Submission date: November 2008
Start date of project: 1/12/2005 Duration: 30 months
Organisation name of lead contractor for this deliverable:
Lund University, Centre for Sustainability Studies
Revision: final
Project co-funded by the European Commission within the Sixth Framework Programme (2002-2006)
Dissemination Level
PU Public X
PP Restricted to other programme participants (including the Commission Services)
RE Restricted to a group specified by the consortium (including the Commission Services)
CO Confidential, only for members of the consortium (including the Commission Services)
Possibilities for modelling sustainability
scenarios
Technical Report of Work Package 3
Mats G E Svensson, Stefan Anderberg
Roy Haines-Young, Allison Rollett Stefan Bringezu, Mathieu Saurat
Lund University, Centre for Sustainability Studies
University of Nottingham, Centre for Environmental Management Wuppertal Institute for Climate, Environment and Energy
FORESCENE D.3.2 – Technical report
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Table of Contents
EXECUTIVE SUMMARY...............................................................................................3
1. INTRODUCTION ....................................................................................................4
2. SCENARIO ELEMENT SYSTEMATICS IN FORESCENE .....................................5
2.1. Cross-cutting driving forces: economic activities and underlying factors .............. 9
2.2. Desirable sustainability goal references....................................................................... 11
2.3. Key sustainability strategies...........................................................................................15
3. PRELIMINARY NARRATIVES IN FORESCENE..................................................18
4. REVIEW OF RELEVANT SCENARIO STUDIES AND SIMULATION
MODELS IN COMPARISON WITH FORESCENE ......................................................23
4.1. Global and regional scenario studies of particular relevance to FORESCENE..... 23
4.1.1. Millennium Ecosystem assessment scenarios.........................................................24
4.1.2. The Global Scenario Group.......................................................................................25
4.1.3. ATEAM and EURURALIS projects ...........................................................................26
4.2. Studies related to the FORESCENE topic areas..........................................................27
4.2.1. Material and energy flow models ..............................................................................27
4.2.2. Land use and biodiversity models.............................................................................30
4.2.3. Water use models ...................................................................................................... 32
4.3. Summing-up.......................................................................................................................33
5. SCENARIO MODELLING IN FORESCENE .........................................................35
5.1. Need for a framework or ‘meta-model’ ..........................................................................35
5.2. Short presentation of Bayesian Networks.................................................................... 35
5.3. Preliminary model structure for FORESCENE.............................................................37
5.3.1. Problem fields/environmental pressures .................................................................. 37
5.3.2. Activities......................................................................................................................38
5.3.3. Cross-cutting driving forces .......................................................................................38
5.3.4. Goals ...........................................................................................................................38
5.3.5. Key strategies.............................................................................................................38
5.3.6. Submodeliing systems...............................................................................................38
5.4. Uncertainties ......................................................................................................................40
6. CONCLUSIONS ...................................................................................................41
7. REFERENCES .....................................................................................................42
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List of Figures
Figure 1: Scenario elements systematics in FORESCENE’s scenario construction.. 5
Figure 2: Overview of the approach in WP1 and WP2.............................................. 6
Figure 3: Mapping of the cross-sectoral and multi-beneficial sustainability strategies
17
List of Tables
Table 1: Overview of the three levels of underlying factors ..................................... 8
Table 2: Analysis of underlying drivers for the three environmental topics (resource
use and waste, water and water use, and landscape, biodiversity and soils) ....... 10
Table 3: Sustainable goal references for the FORESCENE project....................... 13
Table 4: Sustainable goal references for the three topic areas at different scale
levels 14
Table 5: Summary of scenario models and their relation to FORESCENE ............ 34
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E X E C U T I V E S U M M A R Y
This technical report of Work package (WP) 3 in the FORESCENE project describes
the basis for the scenario construction and modelling in the project. FORESCENE aims
to develop an analytical framework for consistent environmental sustainability scenario
building. Preceding WP 1 and 2 had identified cross-cutting key driving forces for the
environmental problem areas “biodiversity, soil and landscape”, “water” and “resources
and waste”, and have described goals and sustainable strategies for relevant activity
fields (agriculture, land use/infrastructure, industry/economy). The aim of WP 3 is to
analyse the options for parameterization and simulation/modelling. It takes up the key
sustainability elements from earlier WPs, and combines them to preliminary narratives
which can be further integrated to comprehensive scenarios. A literature review is per-
formed to describe earlier scenario and modelling work relevant for the FORESCENE
scenario framework. As existing models use to have a more narrow scope, it is con-
cluded that there is a need for a meta-model which allows to model the broader per-
spective of FORESCENE while allowing to include knowledge and data derived from
specific models. This technical report presents the development of the FORESCENE
model framework describing the main elements and outlining the structure of the major
submodules.
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1 . I n t r o d u c t i o n
This technical report of Work Package 3 in the FORESCENE project describes the
basis for the modelling and scenario construction in the project. FORESCENE aims to
develop an analytical framework for consistent environmental sustainability scenario
building. The project seeks to identify elements of a desirable future and it uses back-
casting techniques in order to contribute to the identification of strategies needed to
reach different sustainability goals.
In Work Package 1, FORESCENE reviewed past and ongoing research projects and
policy frameworks with regard to the three particularly focused areas ‘water’, ‘biodiver-
sity, soil and landscape’, and ‘resource use and waste’. Key drivers behind environ-
mental problems in these areas were identified, with a particular focus on cross-cutting
drivers that influence several problem areas. In Work Package 2, the focus was put on
the concerned activity fields (economic sectors, policy fields): agriculture, infrastruc-
ture/land use, and industry/economy. The aim was to define essential elements of sus-
tainable development for these activity fields through answering what the desired future
should look like. In a backcasting fashion, FORESCENE then aimed at finding which
cross-sectoral measures could be expected to exert a multi-beneficial impact over the
environmental fields considered, in the perspective of reaching the previously defined
sustainability goals.
The objective of Work Package 3 is to consistently combine and expand selected sce-
nario elements (i.e. driving forces and environmental pressures from WP1, and
sustainability strategies and goals from WP2) into preliminary scenario narratives.
Those preliminary narratives are also scenario elements, but of a higher level of inte-
gration than the single 'puzzle pieces' of specified key elements delineated in WP1 and
WP2. The next step, which will occur in WP4 and WP5, aims to further develop, com-
bine and quantitatively parameterize the preliminary narratives in order to develop
business-as-usual and alternative scenarios, using existing models or additional mod-
elling frameworks developed in FORESCENE. It is expected, in the end, to give insight
into effective integrated approaches towards sustainability.
The present report has therefore two goals. First, in chapter 2, the key scenario ele-
ments from WP1 and WP2 are filtered out in order to select and thoroughly define con-
sistent clusters of drivers, pressures, strategies and goals. Based on this selection,
more integrated scenario elements are developed in the form of preliminary narratives
in chapter 3.
Second, a review of existing models and scenarios relevant to FORESCENE's topics is
undertaken in chapter 4. The criteria for the review shall allow a comparison between
existing modelling and scenario frameworks and FORESCENE's broad coverage of
environmental issues. The basis for the comparison, in terms of the driving forces, en-
vironmental issues, and sustainability strategies and goals to be modelled, is described
in chapter 2 and 3. Chapter 5 draws the consequences from the review in the preced-
ing chapter for the development of FORESCENE's modelling framework. That is to
which extent existing models can be used for FORESCENE's purposes or there is a
need to develop additional modelling frameworks in FORESCENE.
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2 . S c e n a r i o E l e m e n t S y s t e m a t i c s i n F O R E S C E N E
In WP1 and WP2, a participative process of stakeholder involvement (1st and 2nd inte-
gration workshops) and expert assessment (three targeted workshops) has resulted in
the delineation of the cross-cutting drivers influencing the three environmental topics at
stake, and the elicitation of sustainability goals and possible strategies to reach them.
Figure 1 shows the scenario element systematics adopted in FORESCENE for sce-
nario construction. The results from WP1 and WP2 represent single key scenario ele-
ments derived from a systemic perspective. In this chapter some of these elements will
be selected for their potential in scenario construction and further modelling. They will
be refined with the objective to combine them in the next chapter into preliminary narra-
tives, which represent certain combinations of those scenario elements.
Figure 1: Scenario elements systematics in FORESCENE’s scenario construction
Before that, the research process undertaken in WP1 and WP2 shall be briefly re-
minded. Figure 2 depicts in a nutshell the path followed in WP1 and WP2. A combina-
tion of the concept of socio-industrial metabolism and the EEA’s DPSIR framework
Single key combined scencario elements scenario elements
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provided a framework for the analysis of the three topic areas: ‘resource use and waste
generation’, ‘water and water use’, and ‘landscape, biodiversity and soils’. The combi-
nation of these approaches resulted in a comprehensive systems analysis tool, which
allowed quantification of the interaction between the anthroposphere and the environ-
ment (socio-industrial metabolism), as well as a qualitative evaluation of the results of
this interaction (DPSIR).
Figure 2: Overview of the approach in WP1 and WP2
In WP1, the relevance of the influence of a number of underlying factors on each of the
three environmental themes has been assessed in the context of eleven economic
activities. The relevance analysis is based on stakeholders' and experts’ views, pub-
lished data and literature. The results of the relevance study was compiled in a matrix
form, with each couple 'underlying factor'—‘activity’ classified as very relevant, relevant
or not relevant, depending whether, respectively, a direct, indirect or no link between
one underlying factor and the pressures related to a given activity was assessed. A
systematic ‘scoring’ method was then conducted in order to assess the relative impor-
tance of the activities and underlying factors. A score was assigned to each couple
‘underlying factor’— ‘activity’ according to its relevance classification and its cross-
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cutting character over the three environmental topics. Finally, adding the scores of the
‘underlying factor’— ‘activity’ couples row and column wise gave insight into the overall
relevance of a given underlying factor regarding all activities and environmental
themes, and into the overall importance of a given activity regarding all underlying fac-
tors and environmental themes, respectively. The scoring results were given colour
codes to ease the interpretation of the results of the relevance and cross-cutting analy-
sis.
In WP2, the expert workshops followed by the 2nd Integration Workshop delivered a
number of items for the core elements of sustainability scenarios ‘sustainable goal ref-
erences’ and ‘sustainability strategies’. In the backcasting approach adopted at this
stage of FORESCENE, the latter shall enable our society to proceed on the way to-
ward the former. The goals, which remained at this stage quite broadly formulated,
were divided into environmental and socio-economic objectives. Twenty-five sustain-
ability strategies were defined and grouped into seven sets. With regard to their poten-
tial role for a sustainable future, the strategies are expected to have cross-sectoral and
multi-beneficial characteristics. The former refers to elements which can be related to
the three activity fields delineated for WP2 (agriculture, industry/economy, infrastruc-
ture/land use). The latter corresponds to strategies which foster improvement towards
several of the sustainable goal references. Based on the descriptions provided by the
workshops, the strategies are further classified with regard to the level of specification
(low, medium, high) which determines the probability for direct operationalisation, as
the inverse of the effort expected for it (a low level of specification will require more
detailed information before the strategy can be translated into effective measures). The
second dimension in the classification reflects the state of the consensus with regard to
the proposed strategies, from more controversial to more or less undisputed ap-
proaches. It should be noted that there was an agreement in the workshops that all
strategies listed are important, but for some a common understanding was hampered
through lacking degree of concreteness, which indicates that level of specification and
status of consensus are not independent.
The workshops not only contributed to identification of cross-sectoral sustainability elements but also sought to determine measurable indicators for each of the sustain-ability elements identified. The indicators were viewed as Level 3 in the identification of underlying factors. This identification of indicators is in FORESCENE viewed as the first step in developing scenarios; the indicators can be used as parameters in the models. Table 1 presents an overview of the results of the analysis of underlying with various indicators for level 2 connected to the problem areas. The indicators are listed for the problem areas landscape, biodiversity and soils, resource use and waste, and water and water use. The indicators have then been further classified according to the DPSIR framework since they may play different roles in constructing and operationalising a potential scenario.
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Table 1: Overview of the three levels of underlying factors
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2.1. Cross-cutting driving forces: economic activities and underly-
ing factors
A major aim of WP1 was to determine cross-cutting drivers that together influence the
three problem areas) for the use of the subsequent work packages. Table 2 presents e.g. the results of the relevance analysis. ‘XX’ means that a Level 2 underlying factor has been classified as very relevant, and has a direct effect on the pressures and the resulting impacts due to a given activity on a given environmental topic. According to
these results from the evaluation of relevance of the participative stakeholder work-
shop, energy supply, agriculture, water supply and construction appeared to be the
activities most susceptible to cause pressures and impacts on the three environmental
themes. Transport, forestry, chemicals, basic metals, and food products were also ac-
tivities or product groups potentially important to consider.
The underlying factors were sorted into five categories: economic development, pro-
duction patterns, consumption patterns, demography and natural system. The catego-
ries ‘production patterns’ and ‘economic development’ were the groupings of underly-
ing factors that achieved the highest scores in the evaluation. The factors under pro-
duction patterns (‘material intensity’, ‘composition of material input’, ‘innovation’ and
‘recycling’) are all among the most powerful underlying factors. They all have a strong,
direct and cross-cutting influence on the most important activities in relation to the
three topic areas. ‘Globalisation’, ‘economic growth’ and ‘investment patterns’ have
also considerable influence, but only cross-cutting environmental effects within a more
limited number of activities.
The underlying factor categories ‘natural system’ and ‘consumption patterns’ follow
‘production patterns’ and ‘economic development’ in the ranking. For 'natural system',
‘depletion of resources’ and ‘climate change’ were the most relevant underlying factors,
and ‘food and drink’ and ‘transport and communication’ were the most important under
'consumption patterns'. ‘Natural system’ and ‘consumption patterns’ are more indirect
drivers in nature but according to the relevance analysis they are important and should
not be neglected, particularly in connection with agriculture, construction, energy and
water supply, and transport. In relation to these activities, these underlying factors have
a considerable cross-cutting influence.
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Table 2: Analysis of underlying drivers for the three environmental topics (resource use and
waste, water and water use, and landscape, biodiversity and soils)
The preliminary narratives which will be presented in this report are mostly based upon
drivers connected to “production patterns” and “consumption patterns”, but they are
also strongly based on economic development factors that set frames, have to be mo-
bilized and may be strongly effected by described developments. Economic growth is
central for setting frames for all kinds of societal development.
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Three narratives are based in changes of production patterns toward higher resource
productivity, changed agricultural production patterns and radically increased use of
renewable energy, respectively. Higher resource productivity is connected to all groups
of factors under “production factors”, including material intensity, composition of mate-
rials, recycling and innovation. This narrative is also closely related to economic devel-
opment factors such as investment patterns and have implications for globalization.
The other two have mostly connection with land use, agriculture and forestry.
The remaining two narratives are based upon changes in consumption patterns toward
increased service demand and vegetable diet, respectively. They have connections
with production patterns, particularly related to food and agriculture and the service
sector, and economic developments such as investment patterns and international
trade of goods and services.
One narrative is based on climate change mitigation and development of renewable
energy, which has strong implications for landscape and nature. Otherwise the narra-
tives do not take a direct starting point in demography or natural system and these are
only addressed indirectly in the narratives. Demographic factors such as age and
population patterns may be of great relevance for consumption developments. Differ-
ent responses to ageing and population development problems would have a possible
and perhaps interesting option for a narrative, but it was considered difficult to connect
to the resource related themes of FORESCENE.
2.2. Desirable sustainability goal references
In the European context, EU’s key objectives for sustainable development, which are
summarized below constitute the main guidance and these objectives also provide the
major goals for FORESCENE. The fundamental objectives constitute:
1. Environmental protection
Safeguard the earth's capacity to support life in all its diversity, respect the limits of
the planet's natural resources and ensure a high level of protection and improve-
ment of the quality of the environment. Prevent and reduce environmental pollution
and promote sustainable consumption and production to break the link between
economic growth and environmental degradation.
2. Social equity and cohesion
Promote a democratic, socially inclusive, cohesive, healthy, safe and just society
with respect for fundamental rights and cultural diversity that creates equal oppor-
tunities and combats discrimination in all its forms.
3. High living standard
Promote a prosperous, innovative, knowledge-rich, competitive and eco-efficient
economy which provides high living standards and high,high-quality and meaningful
employment throughout the European Union.
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4. Meeting EU’s international responsibilities
Encourage the establishment and defend the stability of democratic institutions
across the world, based on peace, security and freedom. Actively promote sustain-
able development worldwide and ensure that the European Union’s internal and ex-
ternal policies are consistent with global sustainable development and its interna-
tional commitments.
EU’s specific strategic sustainability objectives constitute:
1. Climate change and clean technology
To limit climate change and its costs and negative effects to society and the envi-
ronment. Kyoto Protocol commitments of the EU-15 and most EU-25 to targets for
reducing greenhouse gas emissions by 2008 – 2012, whereby the EU-15 target is
for an 8% reduction in emissions compared to 1990 levels. Aiming for a global sur-
face average temperature not to rise by more than 2ºC compared to the pre-
industrial level.
2. Sustainable transport
To ensure that our transport systems meet society’s economic, social and environ-
mental needs whilst minimising their undesirable impacts on the economy, society
and the environment. Thus, decoupling economic growth and the demand for
transport with the aim of reducing environmental impacts.
3. Sustainable consumption and production
To promote sustainable consumption and production patterns. Promoting sustain-
able consumption and production by addressing social and economic development
within the carrying capacity of ecosystems and decoupling economic growth from
environmental degradation.
4. Conservation and management of natural resources
To improve management and avoid overexploitation of natural resources, recogniz-
ing the value of ecosystem services. Improving resource efficiency to reduce the
overall use of non renewable natural resources and the related environmental im-
pacts of raw materials use, thereby using renewable natural resources at a rate that
does not exceed their regeneration capacity. Improving management and avoiding
overexploitation of renewable natural resources such as fisheries, biodiversity, wa-
ter, air, soil and atmosphere, restoring degraded marine ecosystems by 2015 in line
with the Johannesburg Plan (2002) including achievement of the Maximum Yield in
Fisheries by 2015. Halting the loss of biodiversity and contributing to a significant
reduction in the worldwide rate of biodiversity loss by 2010.
5. Public Health
To promote good public health on equal conditions and improve protection against
health threats.
6. Global poverty and sustainable development challenges
To actively promote sustainable development worldwide and ensure that the Euro-
pean Union’s internal and external policies are consistent with global sustainable
development and its international commitments.
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7. Social inclusion, demography and migration
To create a socially inclusive society by taking into account solidarity between and
within generations and to secure and increase the quality of life of citizens as a
precondition for lasting individual well-being.
These EU objectives formed the basic starting point for the definition of goal references
within FORESCENE. The EU objectives are sometimes not very well-defined. Their
priority and balance is not always clear and they have to be translated to more con-
crete terms, strategies and actions.
Table 3: Sustainable goal references for the FORESCENE project
Table 3 presents an overview of the sustainable goal references condensed from the outcome of the workshops. In this general formulation, the goals listed are relevant for a large span of economic activities and environmental problem fields. These goal refer-
ences were further elaborated and separated in three levels. Table 4 summarizes this
concretization of the goal references.
The preliminary narratives are linked to many of the goals above. The production effi-
ciency and changed consumption toward services are closely related to many of the
resource and material flows, while the other narratives; changed diet, liberalisation of
agriculture and climate change mitigation have closer connection to agricultural and
landscape development goals. The Climate change mitigation narrative is based upon
the global climate goal of minimizing temperature but through the emphasized mitiga-
tion strategies the sketched development may challenge land use and water goals
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Table 4: Sustainable goal references for the three topic areas at different scale levels
Level Resource use and Ma-terial flows
Land use and biodiversity Water management
Global - No increase of global
temperatures by more than 2°C (mean annual tem-
perature) by the year 2050 compared to today’s level => requiring a reduction of
greenhouse gas emissions by industrialised countries of up to 80%
- Prevent further loss of biodiver-sity
- Balance of demand and supply of water
- Maintain and enhance
regulation services; water quality and quantity
EU - Absolute decoupling of
resource use and GDP - Maximal individual happi-
ness/well-being
- Resource extensive life-styles, production and con-sumption patterns
- Resource self-sufficiency of Europe
- Low impact per consump-
tion unit - Transport culture based on
proximity, slowness and suf-
ficiency - Reduce use of non-
renewable resources
- Welfare more in the sense of happiness, reduction of social deprivation, and edu-
cation - Competitiveness
- Shift from non-renewable resources to renewable
ones while not increasing use of biomass
- Zero emissions of hazard-
ous substances - reduce pollution below critical loads
- Prevent further loss of biodiver-
sity - Maintain or restore eco-system
services
- Large and growing biodiversity within agro- and urban ecosys-tems
- Preserved natural and semi-natural ecosystem enclaves
- Optimal multifunctionality of
land use - Overall low volume of transport - Minimise urban sprawl by using
brownfield resource - Multifunctionality - Inter- and intraregional Diversity
- Minimise nutrient losses - Food production of good quality
- Balance of demand and
supply of water - Maintain and enhance
regulation services; water
quality and quantity
Regional - Overall low volume of trans-
port - Transport culture based on
proximity, slowness and suf-
ficiency - Minimize urban sprawl by
using brownfield resource
- Prevent further loss of biodiver-
sity - Maintain or restore eco-system
services
- Large and growing biodiversity within agro- and urban ecosys-tems
- Preserved natural and semi-natural ecosystem enclaves
- Optimal multifunctionality of
land use - Minimize urban sprawl by using
brownfield resource
- Balance of demand and
supply of water - Maintain and enhance
regulation services; water
quality and quantity
It will not be possible to model all of the goals listed above in the context of FORES-
CENE. For example, the goal of competitiveness for the EU can of course be used in
scenario narratives but it will not be modelled quantitatively. It would require the use of
econometric models which exceed the scope of FORESCENE. The modelling of hap-
piness and well-being will similarly remain at the qualitative level allowed by scenario
narratives.
On the other hand, some targets mentioned above are already quantitatively set. In
connection with climate change mitigation, the emissions of GHG which according
IPCC studies should be cut by 80% in 2050 in the industrial countries. Some other tar-
get values have also been suggested (e.g. the EU is committed to reducing its overall
emissions to at least 20% below 1990 levels by 2020, and is ready to scale up this re-
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duction to as much as 30% under a new global climate change agreement when other
developed countries make comparable efforts. It has also set itself the target of in-
creasing the share of renewables in energy use to 20% by 2020.) which could alterna-
tively be used for assessing the progress of the EU towards sustainability.
Some goals related to resource use and waste generation can be translated in con-
crete and quantitative terms using existing material flow indicators, such as total mate-
rial requirement (TMR). An ambitious target for TMR could be a 80% reduction by
2050. Because TMR is a very good indicator for the physical basis of a society, such a
change would certify that the EU has adopted a resource extensive way-of-life. Setting
targets to the different components of the TMR would also cover a number of the goals
listed in the first column of table 4. For example, the ratio TMR non renewables to bio-
mass should not increase. The ratio TMR foreign to domestic should not increase ei-
ther if the issue of problem shifting is to be efficiently addressed.
2.3. Key sustainability strategies
The FORESCENE workshops also resulted in sets of overall sustainability strategies
expected to have cross-sectoral and multi-beneficial characteristics. As a result of the discussions at the 2nd Integration Workshop, the defined twenty-five sustainability strategies were grouped into seven sets as derived from:
• Improving orientation and target setting
• Improving information and decision processes
• Improved planning
• Changing use of capital
• Changing environmental performance of production and consumption
• Improvement of product management and procurement
• Improving state finance and social security systems.
The environmental goals in Tables 3 and 4 are connected to the strategy set. Figure 3 presents a mapping of the strategies with reference to level of consensus and specifi-cation. Most of the strategies from the set "Changing environmental performance of production and consumption", which is closely related to the goals in Tables 3 and 4 are found in the top right corner, which translates to high levels of both consensus and specification. The general strategies must however be operationalized through more specific ones. Energy/resource efficiency through innovation can be, for example, be promoted via an ecological tax reform shifting labour taxes to energy and natural re-sources. This can be further targeted to discourage consumption related to greenhouse emissions or encourage use of renewable energy. Strategies in the lower parts of the figure are characterized by important disagreements and often address sensitive as-pects of the socio-economic sustainability. Food production within the EU may reduce transport and contribute to the security of food supply, but may also deprive less devel-oped countries of an opportunity to develop through international trade. A similar case is arising in connection with bioenergy.
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The preliminary narratives started with strategies that are characterized by high levels
of consensus. Today, for instance, there is growing support for increasing resource
productivity, and the use of renewable energy. However, there may be important dis-
agreements concerning the appropriate measures under these strategies, for instance
about the relation of intra vs. intersectoral change, and the potential contribution of
biomass to the renewables. This leads to the consideration of narratives which are
more controversial, involve higher risks of trade-offs and problem shifting, and could be
used to model worse case development compared to the baseline and more sustain-
able alternatives. Such a preliminary narrative concerns the opening up the European
food market for foreign producers with decreasing production subsidies which con-
fronts the strategy of localising markets and could have side effects in the EU and be-
yond.
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Figure 3: Mapping of the cross-sectoral and multi-beneficial sustainability strategies
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3 . P r e l i m i n a r y n a r r a t i v e s i n F O R E S C E N E
The identified scenario elements form the basis for the scenario construction and mod-eling activities in FORESCENE. Scenarios are stories or `snapshots' of what might be. Decision makers use them to evaluate what to do now, and what the options are, based on different possible futures. The options for the future reflect either an extrapolation of current trends or introduced changes, such as policies and management plans. Model-ling is the activity where a model is formulated, which is a way of creating a simplified and workable representation of a real-world problem. A model is designed for a specific purpose. A model can never be totally ‘right’ – it is an indicative instrument only. How-ever it should be plausible and rigorous enough to give decision support. Scenarios generally have a qualitative component - the narrative - and a quantitative component - the numbers that illustrate and support the story. Different scenario analyses will re-quire different balances between narrative and number.
In the FORESCENE project the aim is to develop a framework for scenario modelling purposes as a decision support tool. The constructed scenarios must be scientifically sound and quantitative and meet the practical needs of policy makers. All scenarios will
have a defined temporal scale. The major time frames consist of middle-term (2015-
2030) and long-term (2050). The spatial scale for the FORESCENE scenarios are in-
tended to mainly focus at the EU level and EU’s exchange with the surrounding world,
but will be broken down to subregions of the EU as well.
In the previous chapter, the key scenario elements from WP1 and WP2 have been
picked up and further described in the perspective of using them for scenario construc-
tion and modelling in FORESCENE. In the present chapter, these 'puzzle pieces' will
be assembled in several preliminary scenario narratives. Basically, the procedure is as
follows: one selects one key sustainability strategy deemed relevant in the previous
chapter and describes, in qualitative terms, its expected influence on the cross-cutting
drivers, which in turn will impact the pressures on the three environmental topics in a
way that may or may not be satisfactory with regard to the sustainable goals. The
qualitative narratives should also give hints regarding the parameters and indicators
that may be used in later work packages to translate them into quantitatively observ-
able terms.
Though these narratives are of a higher level of integration than the elements pre-
sented in the previous chapter (see figure 1), they are not yet fully fletched scenarios.
But they are built around a “what if?” kind of question which gives room to further inte-
grate the narratives with one another in order to develop consistent scenarios. This,
and the quantitative modelling part, is the task of WP4 and WP5.
Preliminary narrative 1: Increased resource productivity
A both high consensus and high specification key strategy (see section 2.3) is that of
increasing material, energy and water efficiency. The production system would be the
target of this strategy that may be fostered through economic instruments such as an
economic tax reform, increased R&D investment, material efficiency programmes for
manufacturing etc. Such instruments have been identified as important underlying fac-
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tors in WP1 (see section 2.1). They are deemed necessary to consider for their poten-
tial influence on economic activities and their associated environmental pressures. The
quantitative modelling, however, would require the adequate use of econometric mod-
els. Unless such models are accessible and can be integrated in the FORESCENE
framework, the unfolding of the economic instrumentarium will have to remain at the
narrative level.
The outcome of these strategically applied measures would be an overall increase in
material productivity in the production of goods. The amount of nonrenewable re-
sources, such as metals, industrial minerals and construction minerals, mobilised per
monetary unit of final demand (whether domestic or for exports) would decrease. This
would possibly also have a positive effect on the energy and water productivity. The
more efficient use of materials in goods production can be expected to lead to an in-
crease in energy and water productivity as well.
At the end of the causal chain, the consequences of a resource productivity increase
would have a positive influence for the sustainable goals related to the use of non re-
newables (minerals and fossil fuels), which would in turn reduce waste generation and
greenhouse gases emissions. A water productivity increase would as well be expected
to improve the water balance. FORESCENE should be capable to mode those effects,
and it should also be possible to estimate the changes in the total material requirement
of Europe, and whether its domestic and foreign components remain balanced.
Preliminary narrative 2: Changed consumption pattern towards service economy
The habits of European consumers could be modified in the direction of more service demand, while overall consumption volume in terms of available income spent grows unchanged with the trend of GDP. The overall European economy could actually move towards a service economy, which would imply that the EU would export a higher share of services. While there is a high consensus concerning the goal of strengthening the development of the service economy, there may be important ideological conflicts on many of possible means for bringing about consumption changes.
The hypothesis is that services show a higher resource productivity than goods. A higher share of services in the final demand would therefore lead to a – at least rela-tively – lower resource demand. The expected consequences for the environmental pressures would be similar in qualitative terms as those mentioned in the first prelimi-nary narrative. The use of non-renewables, waste generation, TMR, greenhouse gases emissions, water-balance etc. are likely to evolve in quantitative terms towards the sus-tainable goals. Comparing the modeling results of the preliminary narrative 2 to those of the preliminary narrative 1 would give insight into the respective potentials of the strate-gies around which they are respectively built. By preserving the level of consumption while decreasing the environmental impacts associated with resource use, one could also assume that within the wealthy EU the population would experience higher levels of happiness. It is however most probably not possible to model this aspect quantitatively in the ongoing project. Instead, the FORESCENE modelling may concentrate on model-ling the effects of higher share of service consumption on the environmental pressures quantified.
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Preliminary narrative 3: Changed diet
Changing the average European diet toward a more vegetable based food consump-
tion is also about changing consumption patterns. To change food consumption via
direct state intervention is probably very controversial, even if such a change may
seem very desirable from a resource consumption point-of-view since animal produc-
tion demands much higher inputs of energy, nutrients and land resources. Many stud-
ies on food and nutrient flows in industrial societies argue for a changed diet as the
perhaps most obvious option for an important decrease of resource consumption and
losses of nutrients in all steps of the food flows. The effects of a more vegetarian diet
depends on where the vegetables come from and how they were grown. However,
such a change may reduce natural land conversion for feed production, and the need
of long-distance imports of animal feed, and mitigate the GHG emissions of cattle
breeding, thus considerably decreasing the ecological foot-print of European food con-
sumption. Such a change could be achieved by a combination of economic instruments
bringing a changed price relationship between vegetable and animal products, and
changed attitude toward putting higher value on vegetable diets. The latter can be sup-
ported by health arguments and may be inspired by low animal diets in e.g. Asia or
Latin America. The modelling in FORESCENE would have to reflect relevant changes
with regard to changes of environmental pressure to the intra EU environment due to
changes of the structures of agricultural production in Europe as well as the impacts of
changed agricultural imports on extra EU land use and resulting pressures.
Preliminary narrative 4: Climate change mitigation: increased use of biofuels
Responding to the threat of global climate change is one of greatest challenges for
Europe in the coming decades. In the few last years consensus has developed that the
EU needs to take the lead for making it possible for the world to stabilize and later re-
duce emissions of greenhouse gases. An ambitious European response will focus on
both reducing fossil energy consumption through efficiency increase (preliminary narra-
tive 1) and increased use of alternative energy fuels. Two key targets have already
been set by the European Council for the year 2020: 20% reduction of greenhouse gas
emissions and a 20% share of renewable energy (from 8,5% in 2007). These targets
are likely to be a first step toward at 50% reduction and perhaps 50% renewable en-
ergy by 2050, which can be considered a minimum of necessary European efforts for
the realization of the temperature goal of not exceeding 2o warming by 2050.
Biofuels may contribute a certain share to GHG mitigation. However, additional land
requirements, particularly for the provision of growing imports, may result in counter-
productive effects, i.e. increased GHG emissions and pressures on biodiversity through
the conversion of tropical forests and savannahs. The global land use requirements of
the EU to supply the demand for agricultural goods are determined by the the intensity
and productivity of cultivation within and outside the EU. The FORESCENE modelling
should reflect the implementation of the currently invisaged biofuel quota for the EU
(10% in 2020), and the resulting implications on domestic environmental pressures and
impacts on the foreign environment.
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Preliminary narrative 5: Liberalisation of commercial agriculture
The Common Agricultural Policy (CAP) was traditionally based on production support,
which resulted in overproduction of many agricultural in Europe, which was delivered to
the world with support of export subsidies. An abolition of production subsidies to the
agricultural sector has been discussed intensively for the past two decades and CAP
has been gradually transformed towards an emphasis on other types of support, par-
ticularly toward landscape conservation and rural development. However, production
support is still important, although it has changed in many ways, e.g. from production to
areal support. With increasing global pressures on EU, e.g. in connection with negotia-
tions for a new international trade treaty, to abolish agricultural subsidies and allow
products from other regions to compete on equal terms on the European market, one
potential development route may foresee that EU will continue to reduce production
support. However, since many large member countries are opposed to this develop-
ment, it can hardly be described as a consensus strategy, also before the background
of social development of rural regions.
A profound liberalisation of commercial agriculture with maintained support for land-
scape conservation in marginal areas would have important many-sided structural ef-
fects on European agriculture and landscape development. This would lead to in-
creased concentration of agricultural production to regions that are able to compete on
a globalizing market. In such competitive regions, farming will be more specialized,
industrialized and intensified putting extra pressure on scarce water resources and
biodiversity. In major parts of Europe, however, agriculture is likely to become extensi-
fied and depend on support on landscape conservation. The future of the European
agriculture would increasingly depend on the development of the world market. How
agriculture will develop in various individual regions may depend on both traditional
specialization, organization and competitiveness of local agriculture and food industry.
Depending on the input from agro-economic models, an advanced modelling effort may
be able to identify production areas that will be most affected by abolition of subsidies
and show some of the effects on land use and water by intensification or extensifica-
tion. However, because of the complex uncertainties surrounding the development of
the global market for agricultural market, the development of individual products and
agricultural regions quantitative modelling will be difficult..
A possible way for a structured move from the preliminary narratives developed above
towards the final alternative scenarios (to come in WP4 and WP5) is to introduce a
similar procedure that was used in the model “Limits to growths - A 30 year update” In
that model, the scenario starts with one main element and new elements are succes-
sively added,. In the case of FORESCENE, the elements to be combined are the pre-
liminary narratives. For example :
Scenario 1.1: Increase resource productivity
Scenario 1.2: Increase resource productivity and changed consumption pattern
Scenario 1.3 Increase resource productivity and changed consumption pattern and diet
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Scenario 1.4 Increase resource productivity, changed consumption pattern and diet,
and increase of biofuels
Scenario 1.5 Increase resource productivity, changed consumption pattern and diet,
and increase of biofuels and liberalisation of commercial agriculture
The last scenario would be the closest to a final integrated alternative scenario. It
would have to specify the conditions under which certain elements such as the in-
crease of bioenergy and liberalization of agriculture markets would be beneficial, thus
probably describing the features of a “balanced” increase of biofuels and the degree of
liberalization which seems appropriate.
The final scenarios might in the end contain less elements than the sum of the prelimi-
nary narratives because of the impossibility to model them all. But it should also allow a
more detailed description of the interactions between the scenario elements.
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4 . R e v i e w o f r e l e v a n t s c e n a r i o s t u d i e s a n d s i m u l a -
t i o n m o d e l s i n c o m p a r i s o n w i t h F O R E S C E N E
The following section is a review of selected scenario modelling studies with relevance
for the FORESCENE scenario construction. It mostly includes scenario-based studies
with similar thematic aims and scope as FORESCENE. The review primarily assesses
how selected scenario studies and models deal with the three environmental topics of
FORESCENE, but also what problem area, cross-cutting drivers, scope and time hori-
zon have been used in these studies. Most existing models have been developed to
deal with rather specific aspects of sustainability, whereas FORESCENE adopts a
much broader perspective, where the aim is to integrate environmental problems and
activities which have been treated separately so far, and with an extended spatial and
temporal perspective.
4.1. Global and regional scenario studies of particular relevance to
FORESCENE
A number of large scenario projects have during the last decade been conducted at the
global level aimed at unravelling the impacts of human activities on natural systems.
The most well-known examples include the IPCC Assessments (IPCC, 1990, 1995,
2001, 2007), Global Environment Outlook (UNEP, 2002, 2007), Millennium Ecosystem
Assessment (MEA, 2005), and OECD Environment Outlook to 2030 (OECD, 2008)
These global assessments provide in general too little detail at the regional level for
making concrete contributions to a regional analysis. Global land use change assess-
ment are largely inadequate since most processes influencing global change are the
result of decisions and changes at the local scale that most often are poorly repre-
sented in global scale assessments (Houghton, 2003; Ellis, 2004). Thus, global studies
have therefore often limited direct relevance to support national or European policy and
planning. Regional scenario assessments at the EU level have more direct relevance
for FORESCENE. However, global thematic scenarios may still be valuable for provid-
ing an international context of future development within the EU, and are thus of some
relevance for the scope of FORESCENE. For FORESCENE, the scenario construction
by Millennium Ecosystem Assessment at the global level and Global Scenario Group
with both global and regional scenarios have provided valuable inspiration. Among
recent European studies, the ATEAM and EURURALIS projects have been particularly
valuable, and the MOSUS and Prelude projects in terms of land use approaches.
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Box 1. Examples of recent important global and regional scenario studies
Box 2. Scenario links
4.1.1. Millennium Ecosystem assessment scenarios
This project developed its first global scenarios in 1996-97, which have later been up-
dated. The project has the developing world as the primary focus and the scenarios
include both exploratory and normative approaches. Exploratory stands for adding
quantitative rigor to scenarios through the use of global models and other systematic
numerical approaches, and thus possible future pathways. The Millennium Ecosystem
Assessment Scenarios include the following set of four scenarios
(http://www.millenniumassessment.org/en/Scenarios.aspx):
• The World Futures Studies Federation • The Global Business Network (GBN), • The Millennium Project at the American Council for the United Na-
tions University. • The scenario page at Royal Dutch/Shell. • Le Laboratoire d’Investigation en Prospective, Strategie et
Organisation (LIPSOR). • The International Institute for Applied Systems Analysis (IIASA). • The Futures Group, • The EU’s information portal for environmental scenarios and pro-
spective studies. • The Society for International Development (SID)’s Future Searches
programme. • Global Multi-Thematic Scenarios • Barry Hughes’ International Futures (IFs) • The Millennium Institute’s Threshold 21 • UNEP’s Global Environment Outlook • The Global Scenario Group and the PoleStar Project • The Great Transition Initiative • RIVM’s IMAGE model
Global Thematic Scenarios
• The IPCC’s Special Report on Emissions Scenarios
• The FAO’s World Agriculture: Toward 2015/2030. An FAO Perspec-
tive
• The FAO’s Global Fibre Supply Study and other forestry outlook
studies
• Long-Term Scenarios of Livestock-Crop-Land Use Interactions in
Developing Countries, prepared for the FAO by A.F. Bouwman
Regional Multi-Thematic Scenarios
• African Futures - National Long Term Perspectives Studies
• NIES’s Asian-Pacific Integrated Model (AIM)
• Five Scenarios for Europe (Europe 2010) by the Forward Studies
Unit of the European Commission
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Global Orchestration - This scenario depicts a globally connected society that
focuses on global trade and economic liberalization and takes a reactive ap-
proach to ecosystem problems but that also takes strong steps to reduce pov-
erty and inequality and to invest in public goods such as infrastructure and edu-
cation. Economic growth in this scenario is the highest of the four scenarios,
while it is assumed to have the lowest population in 2050;
Order from Strength – This scenario represents a regionalized and fragmented
world, concerned with security and protection, emphasizing primarily regional
markets, paying little attention to public goods, and taking a reactive approach
to ecosystem problems. Economic growth rates are the lowest of the scenarios
(particularly low in developing countries) and decrease with time, while popula-
tion growth is the highest
Adapting Mosaic – In this scenario, regional watershed-scale ecosystems are
the focus of political and economic activity. Local institutions are strengthened
and local ecosystem management strategies are common; societies develop a
strongly proactive approach to the management of ecosystems. Economic
growth rates are somewhat low initially but increase with time, and population in
2050 is nearly as high as in Order from Strength.
TechnoGarden – This scenario depicts a globally connected world relying
strongly on environmentally sound technology, using highly managed, often en-
gineered, ecosystems to deliver ecosystem services, and taking a proactive ap-
proach to the management of ecosystems in an effort to avoid problems. Eco-
nomic growth is relatively high and accelerates, while population in 2050 is in
the mid-range of the scenarios.
All these scenarios point at the importance of maintaining ecosystem services.
FORESCENE is emphasizing biodiversity, which may be used as a proxy for ecosys-
tem services, but differs in terms of trade-offs between gains in provisioning services
and the potential losses of other services or functions. The MEA also points at 2050 as
a point of reference, which will be the same in the FORESCENE project. From the
MEA project one may also conclude that it is important to relate the EU perspective to
the surrounding world.
4.1.2. The Global Scenario Group
The Global Scenario Group developed during the 1990s a set of global and regional
scenarios. It consisted of six global scenarios; three main scenario types in two vari-
ants:
• Conventional Worlds (Policy Reform and Market Forces),
• Barbarization (Fortress world and Breakdown)
• Great Transitions (Eco-communalism and New sustainability paradigm).
These scenarios were compared to a reference scenario for the period 1995-2050, the
same end year that has been chosen for the FORESCENE scenarios. Global popula-
tion, food requirements, agricultural output, agricultural, forest, cropland and pasture-
land areas, requirements for energy, water and resource requirements including re-
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source use efficiency were focused by the scenarios. Global carbon dioxide emissions
were used as a proxy for global climate change. The issue of water sufficiency and
quality were also given special attention, similar to the FORESCENE focus on water.
The GSG project also developed some alternative scenarios:
• Market forces – a scenario, which is mainly supply-demand-based, which
may be analogous with a “business-as-usual” scenario. The “free market”
corrects for inefficiency and thus mitigates the environmental crisis;
• Policy reform – a scenario that maintains the essential assumptions of the
reference scenario paradigm. Remaining is the steady march of economic
globalization, the gradual convergence of all regions toward the evolving
model of development in industrial regions, and progressive homogenization
of global culture around the values of materialism and individualism. This
puts emphasis on the role of the global market and the world outside EU,
which should be considered in the FORESCENE scenarios.
4.1.3. ATEAM and EURURALIS projects
Global scenarios can give valuable inputs and inspiration for alternative development
pathways in the world and its dynamics. Regional scenarios may have more direct con-
tributions to the analysis of the particular European development, but can also provide
methodological inspiration. Two recent European scenario projects - ATEAM and EU-
RURALIS - focussed on ecosystems and rural areas, respectively. These two projects
followed a similar conceptual approach, but used different models and tools. The first
step of both studies involved the definition of the scenarios and the elaboration of the
narrative storylines.
The ATEAM project (Advanced Ecosystem Analysis and Modelling) was conducted
2001–2004 by a consortium of European universities and research institutes with fund-
ing from the EU commission (Ewert et al., 2005; Rounsevell et al., 2006). Ecosystem
development was in focus, and the project used the land use/land cover classes urban,
cropland, grassland and forest land as well as introducing new land use classes such
as bioenergy crops. This gives an indication of which land use classes that the
FORESCENE landscape submodel may use.
EURURALIS was undertaken in 2004-2005 by a consortium of Dutch universities and
research institutes funded by the Dutch Ministry of Agriculture, Nature and Food Qual-
ity (Klijn et al., 2005), and recently (December 2007) Eururalis 2.0 was released. This
project focuses on processes of change in Europe’s rural areas with the aim of provid-
ing an overview of threats and opportunities to inform and encourage policy discussion.
This objective is implemented through a scenario-based modelling approach to land
use change and impacts on the environmental, social and economic domains. Strate-
gic scenarios were elaborated, built on a 2x2 matrix, where the axes represent the
most critical uncertainties. The four scenarios were structured along two axes: (1) rang-
ing from increasing globalisation to a world of regional economic and cultural blocks
and (2) ranging from a future of lean governments to a future with ambitious govern-
ment regulation. This way of constructing and combining strategic scenario elements is
a useful way for the scenario construction and has been used by FORESCENE as well
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(WP2). The storylines were inspired by earlier work such as the emission scenarios of
the Intergovernmental Panel on Climate Change (SRES), the GEO-3 scenarios and
scenarios of the Netherlands Bureau for Economic Policy Analysis (CPB).
A recent scenario study of EURURALIS (van Meijl et al, 2006; Eickhout et al, 2007)
has the aim of making an assessment of land-use intensity and the related biodiversity
in agricultural landscapes in EU-25 for the year 2000 (reflecting the current situation),
and explore future trends, based on the four EURURALIS scenarios up to 2030, which
corresponds with suggested mid-term time perspective for the FORESCENE scenar-
ios. The scenarios are quantified with a chain of models, ranging from global models to
a spatially explicit model, which simulated land use on a 1kmx1km grid for the whole
EU. Data from the Farm Accountancy Data Network (FADN) were used to classify farm
types in 100 regions of the EU15, according to agricultural intensity. For the ten New
Member States (EU10), which are not yet considered by the FADN, country level data
were used to obtain similar farm types, which also limit the resolution for the FORES-
CENE modelling efforts with an EU-25 scale. Three processes were considered for the
assessment of future trends in agricultural land-use intensity: (1) land-use change, (2)
conversion into organic farming, and (3) changes in productivity of crop and grassland
production. Scenario results show that for the Global economy scenario, the highest
loss in ecosystem quality will take place in all regions in croplands and grasslands. The
Regional communities scenario provides the best opportunities to improve ecosystem
quality of agricultural landscapes. In most scenarios, agricultural land is decreasing,
while the remaining agricultural areas tend to be used more intensively. The negative
impact of intensification on biodiversity is partly set off by (active or spontaneous) na-
ture development on abandoned agricultural areas, but the overall trend seems to be
generally negative (Reidsma et al. 2006). The very ambitious data set of the EU-
RURALIS project may be out of reach for the FORESCENE modelling efforts, but the
strategic scenario constructing is of high relevance for the FORESCENE scenarios.
4.2. Studies related to the FORESCENE topic areas
Here follows a short overview of some inspiring studies for the scenario making in rela-
tion to the three topic areas of FORESCENE.
4.2.1. Material and energy flow models
There are numerous material and energy flow models from several scientific fields (for
a review covering ecology and economy, see Suh, 2005). Below are two selected pro-
jects with particular relevance described which have followed a more comprehensive
approach; and three recent papers are mentioned, which focus on selected aspects of
potential relevance for the FORECENE meta-modelling work.
The MOSUS project was funded by the 5th framework programme (sub-programme
energy, environment and sustainable development) of the European Union. The MO-
SUS project aimed at integrating the three policy themes; Sustainable development;
Competitiveness and social cohesion in the knowledge-based society and; Globalisa-
tion and international trade, within a macroeconomic, multi-sectoral framework. The
framework was based on an existing macro-economic model. The first application of
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IO analysis of material flows using an international IO model system was being re-
alised in the project MOSUS. The four major key objectives and targets of this project
were: 1. Assessing and quantifying the European use of resources (scale), including
“ecological rucksacks” induced by international trade; 2. Formulating and evaluating
sustainability scenarios, linking economic performance with resource use and environ-
mental deterioration; 3. Refining environmental indicators to assess resource produc-
tivities, material and energy intensities and labour intensities of resource use for the
EU; 4. Elaborating policy strategies and actions that reconcile long-term economic de-
velopment, international trade and environmental protection.
Scenarios of the economic and social/distributional impacts of key environmental policy
measures wer made with a time horizon to 2020. The baseline scenario projects further trends observed between 1980 and 2003. The weak sustainability scenario reflects sustainability policy goals and measures derived from strategic documents of the Euro-pean Community. The strong sustainability scenario defines policy goals and instru-ments, which are more ambitious from the point of view of sustainable development compared to those, included in the EU documents. The major cross-cutting drivers
were economic developments, energy consumption as the two interrelated major drivers.
The policy recommendations derived from the project were the following;
Environmental policy measures primarily geared towards decoupling economic activity
from material and energy throughput can be positive for economic growth, contrary to
the popular assumption that such policies will mainly raise costs for enterprises, de-
crease competitiveness and thus have an opportunity cost in terms of reduced eco-
nomic performance.
The TransSustScan project (Scanning Policy Scenarios for the Transition to Sustain-
able. Economic Structures, http://www.transust.org/transust.scan.htm) is mainly focus-
ing at economic modelling, targeted to support policies that aim at the transition to sus-
tainable economic structures. The models used within the project will therefore be able
to deal with; Competitiveness; Economic development; Security; The preparations for
Beyond-Kyoto policies; The interaction between technological change and the use of
natural resources on the EU scale. TranSuctScan scenario building work will involve;
forecasting of future states given the implementation of currently know policies; simula-
tion of deviations from business-as-usual strategies; backcasting the policy patterns
needed for achieving certain policy targets, with a time horizon: 2015-2030 The major
drivers derived by the preceding project TransScan are of three major kinds: techno-
logical change, economic development and natural resources use. This project’s aims
are in common with the FORESCENE’s project, but differ in the modelling approach
and will mainly make use of already existing economic models, but may be contribu-
tory.
Holz et al (2008) is presenting a model for the future supply of gas in Europe. The
natural gas market in the European Union is undergoing considerable changes. Three
main challenges for the next decades can be identified: the liberalization of the industry
initiated by the European Union, the increasing demand for natural gas and, simulta-
neously, an increasing import dependency on gas supplied from outside the European
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Union. Analyzing oligopolistic energy markets with large-scale simulation models, in
terms of data input, regional disaggregation, etc. is challenging and these models work
with the underlying assumption of perfect competition as well, which makes them less
appropriate for the studying the European market. This paper (and the following two
below) stresses out increasing global demand for energy as an important driver for the
FORESCENE models.
Hirsch (2006) presents in his article Mitigation of maximum world oil production: Short-
age scenarios, future scenarios that depicts development paths with a shortage of en-
ergy resources. A framework is developed for planning mitigation of the oil shortages
that will be caused by world oil production reaching a maximum and going into decline.
To estimate potential economic impacts, a reasonable relationship between percent
decline in world oil supply and percent decline in world GDP was determined to be
roughly 1:1. As a limiting case for decline rates, giant fields were examined. Actual oil
production from Europe and North America indicated significant periods of relatively flat
oil production (plateaus). However, before entering its plateau period, North American
oil production went through a sharp peak and steep decline. Examination of a number
of future world oil production forecasts showed multi-year rollover/roll-down periods,
which represent pseudoplateaus. Consideration of resource nationalism posits an Oil
Exporter Withholding Scenario, which could potentially overwhelm all other considera-
tions. Three scenarios for mitigation planning resulted from this analysis: (1) A Best
Case, where maximum world oil production is followed by a multi-year plateau before
the onset of a monatomic decline rate of 2-5% per year; (2) A Middling Case, where
world oil production reaches a maximum, after which it drops into a long-term, 2-5%
monotonic annual decline; and finally (3) A Worst Case, where the sharp peak of the
Middling Case is degraded by oil exporter withholding, leading to world oil shortages
growing potentially more rapidly than 2-5% per year, creating the most dire world eco-
nomic impacts. As energy demand, and the shift from non-renewables to renewables is
considered as one of the more important drivers in the resource use, this study is em-
phasising this, and also points out the importance of plateaus. The implications for the
FORESCENE scenarios is the importance to identify major cross-cutting drivers,
whereof the energy demand situation is one, which is further illustrated in the two stud-
ies below.
Smeets et al. (2007) used a model for estimating bioenergy production potentials in
2050 on a global level, called the Quickscan model. The Quickscan model uses a bot-
tom-up approach and its development is based on an evaluation of data and studies on
relevant factors such as population growth, per capita food consumption and the effi-
ciency of food production. Three types of biomass energy sources are included: dedi-
cated bioenergy crops, agricultural and forestry residues and waste, and forest growth.
The bioenergy potential in a region is limited by various factors, such as the demand
for food, industrial roundwood, traditional fuelwood, and the need to maintain existing
forests for the protection of biodiversity. Only the surplus area of agricultural land is
included as a source for bioenergy crop production. The model results indicate that the
application of very efficient agricultural systems combined with the geographic optimi-
zation of land use patterns could reduce the area of land needed to cover the global
food demand in 2050 by as much as 72% of the present area. A key factor was the
area of land suitable for crop production, but that is presently used for permanent graz-
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ing. Another key factor is the efficiency of the production of animal products. The global
potential of bioenergy production from agricultural and forestry residues and wastes
was calculated to be 76-96EJyr-1 in the year 2050. The paper is indicating the impor-
tance and the potential of the shift from non-renewables to renewables in the FORES-
CENE scenarios and what biomass sources that may be considered and included.
4.2.2. Land use and biodiversity models
Scenario development has become a popular tool for the assessment of land use
change and a large number of studies using scenario approaches have been published
during recent years (Rabbinge & van Diepen., 2000; Rotmans et al., 2000; de Nijs et
al., 2004; Ewert et al., 2005), whereof many are or relevance for the FORESCENE
Land use modelling. From ecosystem functioning and biodiversity to water resources
and greenhouse gas emissions, land use is central. In Europe, the most important land
uses are agriculture and forestry, which cover about 45% and 36% of the total land
area, respectively (FAO, 2003). A range of models has been developed to better un-
derstand, assess and project changes in land use and land cover (Veldkamp and Ver-
burg, 2004, Rounsewell, 2006).
In the paper by Rounsewell et al. 2006, a coherent set of future land use change sce-
narios for Europe was made. The paper presents a range of future, spatially explicit,
land use change scenarios for the EU15, Norway and Switzerland based on an inter-
pretation of the global storylines of the Intergovernmental Panel on Climate Change
(IPCC,2001) that are presented in the special report on emissions scenarios (SRES).
The methodology is based on a qualitative interpretation of the SRES storylines for the
European region, an estimation of the aggregate totals of land use change using vari-
ous land use change models and the allocation of these aggregate quantities in space
using spatially explicit rules. The scenarios include the major land use/land cover
classes urban, cropland, grassland and forest land as well as introducing new land use
classes such as bio-energy crops and abandoned land and set-asides, which is indicat-
ing the appropriate land use classes for FORESCENE as aforementioned The ap-
proach to estimate new protected areas is based in part on the use of models of spe-
cies distribution and richness. All scenarios assume some increases in the area of bio-
energy crops with some scenarios assuming a major development of this new land
use, which is also indicating for the FORESCENE modelling how sub-models for re-
source use and land use may be interconnected.
The project ALARM - Assessing Large-scale Risks for biodiversity with tested Meth-
ods, an integrated project within EU sixth framework programme, has a research focus
on assessment and forecast of changes in biodiversity and in structure, function, and
dynamics of ecosystems to 2050. This relates to ecosystem services and includes the
relationship between society, economy and biodiversity. In particular, risks arising from
climate change, environmental chemicals, biological invasions and pollinator loss in the
context of current and future European land-use patterns are assessed. The objectives
of the project are the following: To develop an integrated large scale risk assessment
for biodiversity; To focus on risks consequent on climate change, environmental
chemicals, rates and extent of loss of pollinators and biological invasions; To establish
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31
socio-economic risk indicators related to the drivers of biodiversity; and finally, to pro-
vide a contribution to objective based politics, to policy integration and to derive out-
come-oriented policy measures in the field of biodiversity. ALARM provides scenarios
of socio-economic, climate, land use and other biodiversity-related trends and use
these framework for analysing biodiversity pressures. Three basic scenarios: BAMBU
(Business-as-usual), SEDG (Sustainable European Development Goals) and GRAS
(Growth Applied Strategy), are explored and some alternative developments related to
environmentally-related shocks (high energy price, contagious disease and cooling
climate) are also analysed in connection with these scenarios. The scenarios are
viewed as instruments for communicating biodiversity-related risks to end users, and
the analysis will indicate policy options to mitigate such risks.
PRELUDE (PRospective Environmental analysis of Land Use Development in Europe),
an European Environmental Agency project, initiated in 2006, explores what European
landscapes may look like 30 years from now and beyond. Instead of making predic-
tions, it tackles the vast uncertainties of the distant future by analysing a range of plau-
sible developments. Prelude has used an innovative Story-and-simulation approach to
scenario development, integrating qualitative and quantitative aspects in scenarios,
including uncertainties and underlying driving forces, and how these might influence
land use.
Five contrasting futures are depicted in a set of coherent scenarios. The five PREL-
UDE scenarios are: 1. Great Escape - Europe of contrast; 2. Evolved Society - Europe
of harmony; 3. Clustered Networks - Europe of structure; 4. Lettuce Surprise U -
Europe of innovation; 5. Big Crisis - Europe of cohesion
Great Escape: This scenario is driven by globalisation, decreasing solidarity and pas-
sive government. Societal tension builds up as relatively poor immigrants move to ur-
ban city centres. Climate change affects the growing conditions for agriculture. The
agricultural market is liberalised and only large-scale farms with intensive manage-
ment survive the pressure from the world market.
Evolved Society: Main ingredients in this scenario are an energy crisis, growing envi-
ronmental awareness and active rural development. Serious flooding occurs and peo-
ple leave the most vulnerable areas. They rediscover the countryside where small-
scale organic farming, supported by strong policy measures, increases.
Clustered Networks: This scenario is all about optimization of land use and strong spa-
tial planning in response to an ageing of society and a declining agricultural sector.
Climate change is a less prominent driver in this scenario.
Lettuce Surprise U: The essential drivers here are growing environmental awareness,
technological innovation and decentralization. Agriculture revolutionizes, facilitated by
open source mentality and propagation of knowledge. Production becomes small scale
and less intensive.
Big Crisis: In this scenario climate change related disasters and increasing solidarity
are all-important. Floods and droughts affect many people and trigger strong European
policy interventions, aimed at a balanced regional development.
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The scenarios cover a wide spectrum of possible developments of drivers of change in
society, economy, governance, environment and technological invention. A full descrip-
tion can be found in EEA 2007. All scenarios except one assumes a net migration from
current urban centres towards the periphery, Another dominant feature is the loss of
agricultural land,
The PRELUDE project has an extensive list of driving forces behind the changes in
land use patterns in Europe, whereof subsidiarity, human population development and
settlement, immigration, economic and technological growth, climate change, energy
supply self-sufficiency, agriculture, health, social equity and quality of life, are the most
prominent ones. The identified 20 driving forces were further aggregated into 5 major
categories; Environmental concern, Solidarity and equity, Governance and interven-
tion, Agricultural optimisation, technology and innovation, with various weighing of
these. This list is of particular importance for the FORESCENE scenarios, as are the
five scenarios of PRELUDE.
4.2.3. Water use models
Scenario models for water use has a long history within hydrological dynamic model-
ling at various levels, from global down to local. With the Water Framework Directive
(WFD, Directive/2000/60/EC), EU established an environmental policy which aims at
achieving a good status of surface water and groundwater, which called for new tools
and approaches. The Water framework directive (WFD), adopted in October 2000, is a
major document that will guide the management of aquatic environments in Europe
during the coming decades. The document shifts from a water-management policy
based on usage, e.g. fishing, crop irrigation or electrical production, to a policy focusing
on aquatic life to avoid damage to ecosystems. Hydrological modelling has a long his-
tory within the engineering sciences, with models such as:
- TopModel (http://www.es.lancs.ac.uk/hfdg/topmodel.html), and EU-projects such as
- Rebecca (http://www.rbm-toolbox.net/rebecca/),
- BMW (http://www.environment.fi/default.asp?contentid=116046&lan=EN ),
- DaNubs (http://www.icpdr.org/icpdr-pages/danubs.htm ) and
- Harmoni-CA (http://www.harmoni-ca.info/Catchment_Modelling_projects/The_EC_
CatchMod_Cluster.php).
However, this rather technical approach may not always be suitable for policy testing
and cross-disciplinary approaches.
Bayesian Belief Network models are emerging as a valid approach for modelling and
policy testing and supporting decision-making in the field of water resource manage-
ment (Casteletti & Soncini-Sessa, 2007), which may also be a tentative modelling
pathway for the FORESCENE modelling efforts. In the water resource context they
have been used by Batchelor and Cain (1998) in irrigated and rainfed farming system
modelling, by Varis and Kuikka (1997) to investigate the effect of climate change on
surface waters and by Borsuk et al. (2001, 2004) in studying the eutrophication of river
estuaries. In the paper by Casteletti and Soncini-Sessa (2007) a comparison of Baye-
sian networks, mechanistic models, empirical models, and Markov chains is made.
They use a list of criteria, such as; Ease of identification, integration potential, dynam-
ics and parsimoniousness. They conclude that Bayesian models do not always meet all
FORESCENE D.3.2 – Technical report
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33
these criteria. A Bayesian network is a type of model that provides a simplified seman-
tics that is useful when knowledge about the system to be modelled is poor or unstruc-
tured, and mainly empirical in nature, but that Bayesian networks lose some of their
potential when the system being considered is dynamic, and includes recursive deci-
sions and feedbacks. For the FORESCENE Bayesian network model this may be con-
sidered, but the main objective for FORESCENE is to combine and cross over do-
mains, but with somewhat restricted capability of capturing dynamics of systems.
4.3. Summing-up
Global scenario studies may give important inspiration for general alternative trends.
But they have seldom sufficient detail for more concrete contributions for an analysis at
the regional European level. Regional scenarios as well as those related to the particu-
lar focus topics of FORESCENE provide more direct and concrete contribution.
Most existing models have been developed to deal with rather specific aspects of
sustainability, either within one discipline or a geographical area, whereas FORES-
CENE adopts a much broader perspective, trying to integrate sustainability problems
and activities, which mostly have been treated separately so far. FORESCENE also
has the ambition to introduce a more extended spatial and temporal perspective. There
are many studies that can provide inspiration both on scenario narratives and concrete
analysis of various topics, but the most concrete and direct contributions are given by
studies such as EURURALIS, which have similarities with the focus and ambitions of
FORESCENE. It also becomes clear that existing models cannot cover FORESCENE’s
scope and that another modelling framework is needed. Such a framework should al-
low to combine the various aspects so far often treated separately and to model the
basic links between the environmental problems, key drivers, and sustainability strate-
gies from an overview perspective, with an option to supply the meta-model with data
from more detailed and specific models.
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Table 5: Summary of scenario models and their relation to FORESCENE
Relation to FORESCENE
Temporal scope Most models deal with a -25-30
year time horizon, whereof eco-
nomic models usually have a
shorter time horizon.
FORESCENE will ad here to
the time horizon to 2050,
which is the same as of IPCC
scenarios.
Spatial scope Most models deal with parts of EU FORESCENE aim at EU-25-
level
Problem field(s) Usually mono-disciplinary in their
problem field approach
FORESCENE aim at combin-
ing several problem fields
Cross-cutting drivers Economic growth, competitiveness
and climate change are the domi-
nating cross-cutting drivers
FORESCENE will use these
cross-cutting drivers as well
as various others.
Key strategies Decoupling between economic
growth and environmental impact;
Curbing climate change by limiting
carbon emissions; adapt to water
shortages by improved technology;
These key strategies will be
used by the FORESCENE
meta-model, but also com-
bined with others.
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5 . S c e n a r i o m o d e l l i n g i n F O R E S C E N E
5.1. Need for a framework or ‘meta-model’
When the scope of FORESCENE project is considered, in the light of the Sustainability
Scenario Elements that was identified as a result from the FORESCENE Work pack-
ages 1 & 2 and the short review conducted above, it was decided to develop a specific
meta-model. The term “meta-model” stands for a model at an aggregate level and in a
simplified way of the highly complex interactions between the socio-industrial system
(especially the activity / policy fields agriculture, infrastructure / built environment, and
industry / economy) and the three environmental fields ‘resource use / waste’, ‘land-
scape / biodiversity / soils’ and ‘water / water use’. The meta-model should help testing
the preliminary narratives (i.e. combinations of SSEs, see section 3) in relation to Busi-
ness-As-Usual scenarios (developed in WP4) and refine them towards integrated al-
ternative scenarios (in WP5).
Several pertinent questions were arising from the previous workshops, considering
how to choose a modelling approach for the emerging scenarios (Jörgensen, 2008):
Can we model a system that has only uncertain observations/ data? The forcing func-
tions and several ecological processes are stochastic. How to account for that? How to
develop models if the databases are very heterogeneous, i.e. based on observations
and data from many different system types? How to develop models of systems, when
our knowledge is mainly based on a number of rules/properties/ propositions?
There were two major alternative approaches in consideration for constructing such a
meta-model; a system dynamic approach or Bayesian Network approach. Both have
their strengths and weaknesses (Varis, 1997). System dynamic models have generally
a larger data need, while Bayesian networks can be used to build a decision support
system, especially when working under uncertain conditions (Castelletti & Soncini-
Sessa, 2007). The latter is therefore better adapted to the situation, where the aim is to
connect different areas, as a meta-model approach. Bayesian Belief Networks can be
used to build a decision support system, especially when working under uncertain con-
ditions.
5.2. Short presentation of Bayesian Networks
In the area of environmental and resource management, the applications of Bayesian
analysis have been largely dominated by classical Bayesian inference (i.e. parameter
estimation and uncertainties). In decision theory, the idea of considering the entire
model as a construct subject to uncertainty and subjectivity stem from the game theory
of the 1930s and '40s (Shafer, 1990) and decision trees were developed. The basic
theory was developed into more applicable level towards the late 1960s (Raiffa, 1968).
For a long time, one of the bottlenecks to practical applications of Bayesian ap-
proaches has been the high amount of computation required. Powerful numerical tech-
niques have not been available until mid-1980s, and today most personal computers
are powerful enough to run such models. This has proliferated an expansion and use
of this approach and has resulted into several methodologies - known as belief net-
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works, causal networks, Bayesian nets, qualitative Markov networks, or constraint net-
works - this division is difficult or impossible to distinguish. Characteristic of these tech-
niques is the principle of networking nodes representing conditional, locally updated
probabilities. The local-updating principle allows construction of large and densely cou-
pled networks without excessive growth in computation (Varis, 1997).
Bayesian belief networks (BBNs) are useful tools for modelling complex situations and
aiding in management and decision-making (Jensen, 2001; Marcot et al. 2001). BBNs
also serve well as part of a risk-management Framework by explicitly displaying the
‘causal web’ of interacting factors and the probabilities of multiple states of predictor
and response variables. Development of a BBN model, however, does not follow a
standard process in the making. The first step is often done in discussion with expert
and/or stakeholders, and after an initial review of the literature. From a mathematical
point of view, the basic property of Bayesian networks is the chain rule: a Bayesian
network is a compact representation of the joint probability table over its universe.
From a knowledge engineering point of view, a Bayesian network is a type of graphical
model. The structure of the network is formulated in a graphical communication lan-
guage for which the language features have very simple semantics, namely causality.
The graphical specification also specifies the requirements for the quantitative part of
the model, the conditional probabilities. The graphical representation is for humans to
read, and it helps to focus attention, when working in a group jointly developing a
model. The graphical model has to be well-defined, to ensure it can be communicated
to a computer. The Bayesian network is a sufficiently well-defined language, and be-
hind the graphical specification in the user interface of Bayesian network software,
there is an alpha-numeric specification language. Bayesian network models are
acyclic, that is, there are not any feedback loops, which separate them from dynamic
models. Tractability may be considered, by using algorithms for probability updating of
the Bayesian network.
Bayesian networks has a long history in statistics, and in the first half of the 1980s they
were introduced to the field of expert systems through work by Pearl (1982) and
Spiegelhalte et al. (1993). Characteristic of these techniques is the principle of net-
working nodes representing conditional, locally updated probabilities. The local-
updating principle allows construction of large and densely coupled networks without
excessive growth in computation. Furthermore, networks can easily be constructed to
operate interactively and on-line. As is usual in such techniques, the entire model - the
hypothesis space – is subjected to Bayesian analysis, not only the parameter space. In
recent years, they have spread quickly to many application areas, including fault diag-
nosis, reliability theory, medicine, pattern recognition, and decision analysis (Varis,
1997). In historical perspective, the roots of decision trees are even older than those of
modern Bayesian decision theory. The basic idea is that the events, both controllable
(decision) and uncontrollable (chance) ones, are set up in procedural order. Each set
of outcomes from a node, be they decision alternatives or possible outcomes of a
chance, define a new branch in the tree. Influence diagrams have gained increasing
popularity within decision analysis, originally extended from decision trees. An influ-
ence diagram is an acyclic network of nodes connected with one-directional links. The
nodes represent probabilistic variables, deterministic variables, or decisions. Like a
decision tree, the diagram describes causality or the flow of information and probabilis-
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tic dependencies in a system. The influence diagram notation provides the analyst with
some attractive and useful properties. One of them is the straight way to perform the
value of information analysis. The network has n nodes that can arbitrarily be intercon-
nected. The prior probabilities assigned to the outcomes are updated with the informa-
tion linked from other parts of the network, yielding the posterior probability distribution.
Generalized belief networks can include models from many methodological families
that have conventionally been considered as being distant, e.g. pragmatic, linguistic,
mechanistic, and metric models can be used together in a hybrid model or in a meta-
model (Varis 1994).
The Bayesian network approach to modelling is not without its shortcomings (Borsuk et
al. 2004). Perhaps the most profound is the inability to explicitly represent system
feedbacks. Bayesian networks are defined as being directed acyclic graphs, so rela-
tionships must represent either one-way causal influences at a particular instant in time
or net influences on eventual steady-state conditions. An alternative is to construct a
dynamic Bayesian network (Jensen, 2001) in which a down-arrow variable in one time
step can influence an up-arrow variable in the next. Such a model requires significantly
more information to quantify the time dynamics. However, insufficiently representing
dynamic aspects of system behaviour can lead to unexpected consequences that are
not adequately captured by the probabilistic predictions (Jorgensen, 1999). An alterna-
tive way can be to let one network outcome influence the next network run, as in adap-
tive management, which is a structured, iterative process of decision making in the
face of uncertainty, evaluating results and adjusting actions over time via system
monitoring (Peterman et al. 1998).
5.3. Preliminary model structure for FORESCENE
Here follows a brief description of the structure of the meta-model in relation to chap-
ters 2 and 3, giving and overview of the FORESCENE meta model.
5.3.1. Problem fields/environmental pressures
The current EU environmental policy context is determined by the four priorities of the
6th EAP on climate change, nature and biodiversity, environment and health and qual-
ity of life, and on natural resources and waste, which is also indicating the most impor-
tant problem fields. These priorities have been translated into seven Thematic Strate-
gies that are being developed according to a common approach independently of the
specific content requirements relating to their subject matter:
Soil protection; Protection and conservation of the marine environment; Sustainable
use of pesticides; Air pollution; Urban environment; Sustainable use and management
of resources; Waste recycling. FORESCENE’s central hypothesis that the production
and consumption patterns have essential influence on the interaction between industry
and society on the one hand and the environment on the other hand, is also guiding
the integration between the problem fields. A key methodological approach will be the
analysis of the material flows between and within those spheres, and the transforma-
tion links between one material flow to another one.
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5.3.2. Activities
The economically defined activities energy supply, agriculture, water supply and con-
struction appear to be most relevant with regard to pressure-causing factors and im-
pacts on the environment. Transport, forestry, chemicals, basic metals, and food prod-
ucts are also activities or product groups potentially important that will be considered in
the FORESCENE meta-model.
5.3.3. Cross-cutting driving forces
Five major cross-cutting factors were identified during the workshops (see description
in Chapter 2 & 3 above), in particular Production patterns & Economic development;
Consumption patterns; and natural system dynamics (incl. climate change, and deple-
tion of natural resources). These factors are also related to each other, but will be used
separately as driving forces.
5.3.4. Goals
Based on WP2, and before the background of maximised well-being as an over-
arching goal for the EU sustainable development, the sustainable goal references
shown in Table 3 and 4 will be taken as starting point.
5.3.5. Key strategies
The twenty-five sustainability strategies that were defined and grouped during WP2,
and that were related to three major activity fields (agriculture, industry/economy, and
infrastructure/land use), are the basis for the development of narratives as well as for
further modelling. This relates especially to those strategies which can be operational-
ized by indicators and other quantified parameters (Fig. 2). The meta-model of
FORESCENE should therefore be made in such a way so optional key strategies could
be tested.
5.3.6. Submodeliing systems
To be able to study the impact of the identified cross-cutting driving forces and their
related activities on the problem fields, the FORESCENE modelling system is sug-
gested to contain a minimum set of three submodelling systems; Materials and waste
flow, Land use and biodiversity, and Water use. There are two major issues that differ-
entiate between the three submodelling systems; in the Material and waste production
submodel, also the extra EU dimension of the system will be considered, as minerals
can be imported, while in the Biodiversity and landscape submodel will focus on the
intra EU impacts while trying to cover also impacts of land use change outside the EU
due to increased biofuels imports; whereas in the water submodel, commodities out-
side of EU will not be considered, but a regional breakdown within the EU should be
implemented according to varying water availability in European regions.
Another aspect that will differentiate the submodels are that the Material and waste
production submodel is assumed to be driven amongst other factors by economic
growth, while the other two are indirectly connected to economic growth through the
demand for mineral and biomass materials and water. In this model it is therefore as-
FORESCENE D.3.2 – Technical report
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39
sumed that GDP is a driver, not an output. Moreover, biodiversity (but also some as-
pects of Water use) is a parameter that also includes qualitative aspects (as well as
ethical) which will have to be considered when interpreting the uncertainties for this
parameter. A common denominator for all three submodels is Population. The various
indicators that are identified in the submodels, respectively, are not shown in the sim-
plified views below. The structural model can also be seen as a synthesis of the work-
shops performed previously in the FORESCENE project.
Below is a simplified view of the Material and waste production submodel.
Below is a simplified view of the Landscape and Biodiversity submodel. It relates to the
other two submodelling systems through Agriculture and Forest in terms of water ab-
straction, and to the Material and waste submodelling system through the biofuel de-
mand and biomass production.
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Below is a simplified view of the Water use submodel. This submodel differs also from
the other two as it is more spatially explicit, as the future water situation is assumed to
be very different in different parts of Europe, especially between North and South.
5.4. Uncertainties
Bayesian networks offer a pragmatic and scientifically credible approach to modelling
complex ecological systems, where substantial uncertainties exist (Polino et al. 2007).
Bayesian networks are being used to model diverse problems of high complexity
(Laskey and Mahoney, 2000 and Korb and Nicholson, 2004), including environmental
applications (Borsuk et al., 2004, Bromley et al., 2005, Ticehurst et al., 2007 and Varis
and Fraboulet-Jussila, 2002). In many Bayesian networks, variables have been pa-
rameterized using either knowledge or data (Borsuk et al., 2004, Bromley et al., 2005,
Rieman et al., 2001 and Ticehurst et al., 2005), but rarely have both these information
sources be combined in order to parameterize one variable. Straightforward sensitivity
and uncertainty analysis of a belief network is thus highly time-consuming and difficult,
and often the knowledge of experts is incomplete (Morgan and Henrion, 1990). Con-
versely, often significant data gaps exist for parameterizing variables with data.
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6 . C o n c l u s i o n s
In this paper, based on the preceeding work in the project, we have delineated prelimi-
nary narratives for the scenarios to be developed in the FORESCENE project. We
have reviewed relevant existing work on sustainability scenarios and modelling, and
shown that there is the need for a meta-model which combines the different problems
and activities fields covered by FORESCENE. The Bayesian belief networks method-
ology seems a promising tool to establish such kind of meta-model for which we have
described the essential elements and outlined the basic structure of the main sub-
models..
Further work will have to develop the meta-model. For that purpose, it will need to be
filled with data and quantitative descriptions of functional relations of the various nodes
including probabilities. The sub-models will need to be checked for their own working
capacity and then combined to test the meta-model to look at the trade-offs between
different possible future pathways.
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