Document 12132758

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ESILIENCE IN

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Feasibility study

Report to the World Food System Center

Birgit Kopainsky; Flury&Giuliani GmbH

Quang Bao Le, Andy Spörri; Chair for Environmental Sciences, Natural and Social Science Interface,

ETH Zürich

Zürich, December 2013

Executive summary

Improving the outcomes and resilience of the world food system requires new systems approach-‐ es that account for complex feedbacks and interactions within and between the food value chains forming the food system. Food value chains are crucial subsets of the world food system, as they are not only constitutional components, but also management units for understanding and im-‐ proving the food system’s outcomes and resilience. New systems approaches require a better ana-‐ lytical framework relating food value chains to food system outcomes such as food and nutritional security, and environmental and social welfare, as well as suitable tools for decision-‐makers to implement this framework.

Discussions are currently under way between the World Food System Center and several members of its partnership council regarding a potential innovative and visionary research program. The project would aim to develop a comprehensive methodology to conduct systems based analyses of food value chains. Due to the complex nature of this program, a feasibility study was undertak-‐ en. This study included an analysis of the state of the art in research in the field. The major out-‐ comes of the feasibility study are a pilot version of the resilience and food system assessment tool as well as recommendations regarding the best approach to design, structure and execute the research program. An immediate next step following the feasibility study is the publication of its outcomes. An article is currently under preparation and will be submitted to Environmental Sci-‐ ence and Technology, a journal that has published some of the most influential articles on food systems approaches.

The assessment tool consists of a series of checklists and guidelines that help uncovering and mapping the complex relationships among food system drivers, activities and outcomes, and esti-‐ mating the probable impacts of different interventions in food value chains. Table 1 provides an overview of the individual steps in the assessment process, the checklists and guidelines support-‐ ing these steps as well as the need for further research to consolidate the assessment.

Table 1: Pilot version of the assessment tool: Summary of activities, guidelines and research gaps

Assessment stage

Activities and out-‐ comes

Guidelines and checklists Research gap

Analysis of the food system

Defining the system: Resili-‐ ence/ vulnera-‐ bility of what

Identify relevant food system outcomes

Identify and prioritize the food value chains contributing to the relevant food system outcomes

Map the selected food value chain and estimate the relative importance of the different channels

List of food system outcomes for which indicators and data need to be found

Framework of key segments, nodes and possible channels in a food value chain

Food system map that explicitly links the mul-‐ tiple dimensions of food systems

Estimating flows of products (& product transformations), in-‐ formation, finance, including inputs, waste i

Identifying driv-‐ ers of change:

Resilience/ vul-‐ nerability to what

Select and map the most pertinent chan-‐ nel within this food value chain

Identify and analyze stakeholders and networks within this channel

Identify and prioritize drivers of change

Framework of key segments and assignment of segments and nodes to spatial levels for the selected channel

List of stakeholders and their char-‐ acteristics

Examples of drivers on different spatial and temporal levels relevant for agricultural production

Generic list of drivers that need to be adjusted to a specific food sys-‐ tem. Exposure of the food system to drivers of change for prioritiza-‐ tion of drivers

Framework of drivers interacting with the food system activities and stakeholders

List of stakeholders and their char-‐ acteristics and losses

Guidelines for stake-‐ holder and network analysis in food value chains

Food system map that depicts the causal pathways between drivers and food sys-‐ tem activities and out-‐ comes

Assessment

Designing interventions

Evaluating interventions

Design interventions that increase the resili-‐ ence of the food sys-‐ tem and improve out-‐ comes

Formulate scenarios of drivers, interventions and goals

Estimate impact on food system outcomes

List of generic value chain devel-‐ opment strategies

List of resilience criteria that help designing interventions

List of food system outcomes

Framework of interactions between drivers, activities and stakeholders as well as outcomes

Framework for impact assessment at several points in time

Establishing feedback relations between food system drivers, activi-‐ ties and outcomes

Guidelines for forma-‐ tive scenario analysis in food value chains

(Partial) quantification of feedback relations between food system drivers, activities and outcomes

Further developments of the tool will combine various quantitative system modeling approaches with transdisciplinary processes to incorporate the interests of different stakeholders. It will be developed and tested based on case studies in developed as well as developing nations using available data aggregated at the national level. The products of this research will include the tool itself, and, through its empirical application in different contexts, an iterative generation and im-‐ provement of knowledge on the world food system and intervention design, thus ultimately con-‐ tributing to the improvement of food system resilience and outcomes. ii

Table of contents

Executive summary ...................................................................................................................... i

Table of contents ........................................................................................................................ iii

List of figures .............................................................................................................................. iv

List of tables ............................................................................................................................... iv

1 Introduction .......................................................................................................................... 1

2 State of the art ...................................................................................................................... 3

2.1

Conceptual frameworks ............................................................................................................................................. 3

2.1.1

Food system approach .................................................................................................................................... 3

2.1.2

Resilience thinking in social-‐ecological systems ............................................................................................. 5

2.2

Methodological frameworks ...................................................................................................................................... 7

2.2.1

Material flow analysis and life cycle assessment ............................................................................................ 7

2.2.2

Systems analysis and modeling ....................................................................................................................... 7

2.2.3

Food system scenario analysis ........................................................................................................................ 8

2.2.4

Transdisciplinarity in food system research .................................................................................................... 8

2.3

Resilience assessments .............................................................................................................................................. 9

3 Proposed approach .............................................................................................................. 10

4 Pilot version of the resilience and food system assessment tool .......................................... 13

4.1

Identification of relevant food system outcomes .................................................................................................... 14

4.2

Identification and prioritization of food value chains contributing to the relevant food system outcomes ........... 15

4.3

Mapping of the selected food value chain and estimation of the relative importance of the different channels ................................................................................................................................................................... 16

4.4

Selection and mapping of the most pertinent channel ............................................................................................ 17

4.5

Identification and analysis of relevant stakeholders ................................................................................................ 18

4.6

Identification and prioritization of drivers of change .............................................................................................. 20

4.7

Design of interventions based on resilience and food system criteria .................................................................... 23

4.8

Formulation of scenarios ......................................................................................................................................... 26

4.9

Estimation of impact on food system outcomes ...................................................................................................... 27

4.10

Iteration of assessment ............................................................................................................................................ 29

5 Next steps ............................................................................................................................ 31

5.1

Research questions .................................................................................................................................................. 31

5.2

Ongoing applications ................................................................................................................................................ 32

5.2.1

Coop call for proposals November 1 st , 2013 ................................................................................................. 32

5.2.2

Forum for Sustainable Food Systems ............................................................................................................ 34

5.3

Links to education .................................................................................................................................................... 34 iii

5.4

Requirements for implementation beyond ongoing applications ........................................................................... 35

5.4.1

Short term ..................................................................................................................................................... 35

5.4.2

Longer term .................................................................................................................................................. 35

5.5

Concluding remarks ................................................................................................................................................. 36

6 References ........................................................................................................................... 37

List of figures

Figure 1: A simplified representation of a food supply chain (Hawkes & Ruel, 2011: 4) .................................................... 4

Figure 2: Food systems, their drivers and feedback (a); components of food systems (b) (Ingram, et al., 2010: 28) ........ 5

Figure 3: Proposed approach to design resilient interventions and assess their food system outcomes in national food value chains ............................................................................................................................................................. 11

Figure 4: Framework of key segments, nodes and possible channels .............................................................................. 17

Figure 5: Framework of key segments and spatial levels for the selected channel ......................................................... 18

Figure 6: Framework of drivers interacting with the selected food value chain channel ................................................ 23

Figure 7: Framework of interactions between drivers, activities and stakeholders as well as outcomes for the selected food value chain channel ........................................................................................................................................ 28

Figure 8: Dynamic estimation of impact on food system outcomes ................................................................................ 29

Figure 9: Iterative design and analysis of interventions to reduce the vulnerability of the food system, increase resilience and improve food system outcomes ...................................................................................................... 30

List of tables

Table 1: Pilot version of the assessment tool: Summary of activities, guidelines and research gaps ................................. i

Table 2: Stages in resilience assessment ............................................................................................................................ 9

Table 3: Activities for implementing the proposed approach .......................................................................................... 12

Table 4: Pilot version of the assessment tool: Summary of activities, guidelines and research gaps .............................. 13

Table 5: Food system outcomes for which indicators and data need to be found .......................................................... 15

Table 6: Value chain stakeholders and their characteristics ............................................................................................ 18

Table 7: Examples of drivers on different spatial and temporal levels relevant for the agricultural production segment

................................................................................................................................................................................ 21

Table 8: Exposure to drivers of change ............................................................................................................................ 22

Table 9: System-‐wide stakeholders and their characteristics .......................................................................................... 22

Table 10: Generic value chain development strategies .................................................................................................... 24

Table 11: Resilience criteria that help designing interventions ........................................................................................ 25

Table 12: Research questions that can be answered with resilience and food system assessment processes and tools 31

Table 13: Detailed research plan Coop proposal .............................................................................................................. 33

Table 14: Possible master theses for short term improvement of the assessment tool .................................................. 35 iv

1 Introduction

Improving the outcomes and resilience of food systems requires targeted and effective interven-‐ tions that account for the complex feedbacks that can occur. In this context, a food systems ap-‐ proach that links the activities of producing, processing, retailing and consuming food with the outcomes of these activities for food security and other societal and environmental goals (Ingram,

Ericksen, & Liverman, 2010) has great potential for decision-‐makers such as farmers, food proces-‐ sors, retailers, consumers, civil society organizations, and policy-‐makers. A food systems approach helps them identify where interventions in the food system can be most effective, and determin-‐ ing how these interventions could affect the outcomes of food systems such as food and nutrition security, and environmental and social welfare. To exploit this potential, however, better analyti-‐ cal frameworks and tools are required, which relate the interventions to food system outcomes

(Ericksen, Bohle, & Stewart, 2010; Ericksen, Ingram, & Liverman, 2009) and can effectively be used by decision-‐makers. Indeed, the complexity of food systems poses considerable conceptual chal-‐ lenges for research, and makes them difficult to manage. In particular, any analytical framework must take into account three important characteristics of food systems:

• Food systems are dynamic, adapting continuously to changing social, economic and environ-‐ mental conditions. The goal for policy must be to guide and support such adaptations so as to improve food and nutrition security (Hammond & Dubé, 2012) and make food systems more resilient (Adger, Arnell, & Tompkins, 2005).

•

The various activities of food systems play out across social, economic, political and environ-‐ mental processes and dimensions (referred to as scales; Cash et al., 2006) and at several ag-‐ gregation levels within each scale (e.g. local to global; Cash, et al., 2006), making them inher-‐ ently cross-‐level and cross-‐scale (Carpenter et al., 2009; Ericksen, et al., 2009; Holling, 2001;

Thompson & Scoones, 2009). Adaptation therefore cannot be treated as an isolated change in one part of the food system, such as agronomic technology or local practices only (Ingram, et al., 2010). However, efforts to achieve food security usually focus on food production (Ingram, et al., 2010), neglecting other parts of the system.

• Constituents of food systems are highly interconnected, so that changes at one level may be offset by adaptive responses elsewhere in the system (Hammond & Dubé, 2012). Solutions to problems with food system outcomes therefore cannot lie in the advocacy of particular food lifestyles without due consideration of the consequences of such proposals for other stake-‐ holders in the food system (Pinstrup-‐Andersen & Watson II, 2011). Diverse options associated with different impact pathways are necessary (Thompson & Scoones, 2009). This requires an analysis of the objectives and outputs of a food system, and the understanding of the distinct rationales and interests of its stakeholders, and the respective trade-‐offs and potential con-‐ flicts, both now and in the future.

Discussions are currently under way between the World Food System Center and several members of its partnership council regarding a potential innovative and visionary research project (or pro-‐ gram). The project would aim to develop a comprehensive methodology to conduct systems based analyses of food value chains based on the above listed characteristics of food systems that an analytical framework needs to take into account. The final result of the project will be a tool that supports with:

• Decision making and adaptive management

• Developing options for sustainable policy or institutional interventions

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• Scenario analysis and back casting

• Identifying bottlenecks and inefficiencies and facilitate corrective action

• Pin pointing technology and innovation needs

Due to the complex nature of this project, a feasibility study was undertaken. This study included an analysis of the state of the art in research in the field (section 2) and an identification of the key organizations and individuals working on relevant topics. For this purpose, literature review was combined with selected expert interviews and workshops with the steering committee of the fea-‐ sibility study. The steering committee consisted of representatives from ETH and the private sec-‐ tor (Bühler and Syngenta). The major outcomes of the feasibility study are a pilot version of the resilience and food system assessment tool (section 3 and 4) as well as recommendations regard-‐ ing the best approach to design, structure and execute the research program (section 5).

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2 State of the art

Food systems, covering a chain from production (the field) to consumption (the table), are increas-‐ ingly analyzed in the context of coupled social-‐ecological systems frameworks (Binder, Feola, &

Steinberger, 2010; Ericksen, 2008a; Hammond & Dubé, 2012; Liu et al., 2007; Rossing et al., 2007), and analyzed using the concepts and methods of resilience theory. Food value chains are crucial subsets of food systems, as they are not only constitutional components, but also management units for understanding and improving food systems' outcomes and resilience (Ingram, et al.,

2010). Understanding how food systems deliver food security, environmental and social welfare requires knowing what, where and to whom value is added across food supply chains (Ericksen, et al., 2009; Thompson & Scoones, 2009). Improving food security and social welfare requires im-‐ proving entire food value chains and their outcomes in the food system, and increasing stakehold-‐ ers' incentives for sustainable food supply (Pinstrup-‐Andersen & Watson II, 2011).

The review of the state of the art differentiates between conceptual (section 2.1) and methodo-‐ logical frameworks (section 2.2) to study resilience and food system outcomes. Section 2.2.4 summarizes the steps performed in existing resilience assessments.

2.1

Conceptual frameworks

2.1.1

Food system approach

Social-‐ecological systems are based on the assumption that ecological and social systems co-‐ evolve through multiple feedbacks that result in complex and adaptive systems (Folke, 2006). The analytical framework of social-‐ecological systems (SES) is useful for food systems because the agri-‐ cultural production process as well as food processing and distribution are inherently character-‐ ized by complex interactions of people and natural components (Ericksen, 2008a; Liu, et al., 2007).

SES frameworks specifically focus on an evaluation and assessment of policy making (Folke, Hahn,

Olsson, & Norberg, 2005).

The basic structure of food systems is captured in the food value chain approach. Food value chains can be regarded as subsets of food systems. For a single food or commodity product, a val-‐ ue chain comprises the processes and stakeholders that take a food from its production on the farm, including the inputs into that production, to the consumer and to its disposal as waste. A value chain also describes what and where value is added by these activities and stakeholders

(Hawkes & Ruel, 2011). Figure 1 illustrates some of these activities and the stakeholders involved in their execution in a simplified manner.

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Figure 1: A simplified representation of a food supply chain (Hawkes & Ruel, 2011: 4)

While food chain analyses including lifecycle assessments (e.g. Stoessel, Juraske, Pfister, &

Hellweg, 2012) or material flow analyses (e.g. Risku-‐Norja & Mäenpää, 2007) provide important information with respect to production and the corresponding environmental impacts, they pro-‐ vide limited potential to explain complex challenges such as the vulnerability of the food system to global change (Ericksen, 2008b) or food and nutrition security issues (Hammond & Dubé, 2012). To address these issues, a food system framework should consider (Ericksen, 2008a; FAO, 2008; cf

Figure 2):

• The complex interactions between environmental and social components that drive food sys-‐ tem activities including dynamics and feedback effects (food system drivers).

•

The activities along the food chain (food system activities).

•

The outcomes of these activities in terms of food security, environmental security and social welfare (food system outcomes).

The most influential definition of the food system framework emerged from the GECAFS (Global

Environmental Change and Food Systems) project, which focused on food security and global envi-‐ ronmental change (Ingram, et al., 2010). This framework emphasizes the importance of a dynamic and holistic approach as well as the socio-‐economic and environmental feedbacks and feedback loops from the food system activities and the food system outcomes within the social-‐ecological system. Finally, the framework highlights the synergies and trade-‐offs between different outcomes of the food system as well as trade-‐offs between outcomes and social as well as environmental concerns such as the potential degradation of ecosystem services.

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From a research perspective, the framework has three implications (Ericksen, 2008a):

• First, to analyze food systems, not only the component parts and stakeholders have to be de-‐ scribed but also the interactions and feedbacks that determine the food system outcomes.

• Second, food systems are inherently cross-‐scale and cross-‐level (Ericksen, et al., 2009;;

Thompson & Scoones, 2009). The challenges emerging from a holistic social-‐ecological systems perspective are that food systems include multiple stakeholders interacting with a broad array of environmental resources on multiple temporal and spatial scales (e.g., Cumming, Cumming,

& Redman, 2006, Carpenter, et al., 2009; Holling, 2001) as well as the involvement of multiple levels of governance and policy processes (e.g., Cash, et al., 2006; Kok & Veldkamp, 2011).

•

Third, institutional arrangements, i.e. the governance of the food system, play a key role in mediating expected interactions between social and ecological processes.

Figure 2: Food systems, their drivers and feedback (a); components of food systems (b) (Ingram, et al., 2010: 28)

2.1.2

Resilience thinking in social-‐ecological systems

Resilience thinking is a generic approach to understanding social-‐ecological systems (Folke et al.,

2010). It has its origin in ecology (Holling, 1973) but has since been expanded to social-‐ecological systems (Adger, 2000; Adger, et al., 2005; Carpenter, Walker, Anderies, & Abel, 2001; Folke, 2006).

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Social-‐ecological resilience is still seen as an approach to study social-‐ecological systems or way of thinking used by various scientific disciplines rather than a theory (Anderies, Folke, Walker, &

Ostrom, 2013; Anderies, Walker, & Kinzig, 2006; Kinzig, 2012).

The multidisciplinary research network “Resilience Alliance” defines resilience as the ‘capacity of a system to experience shocks while retaining essentially the same function, structure, feedbacks, and therefore identity’ (Walker, Anderies, Kinzig, & Ryan, 2006). Resilience is alternatively used to describe the disturbance that can be absorbed before a change in state (e.g., Holling, 1996) or the rate of recovery from perturbation (e.g., Adger, 2000).

Resilience thinking is characterized by five underlying concepts:

• Alternate stability regimes and thresholds imply that complex systems have a certain latitude

(Folke et al., 2004). The notion of latitude describes the maximum amount of change a system can endure before crossing a threshold from which recovery is difficult or impossible (Walker,

Holling, Carpenter, & Kinzig, 2004).

• Adaptive cycles imply that social-‐ecological systems exhibit dynamic cyclic development that allows them to adapt to changing environmental conditions (Holling, 2001).

•

The existence of feedbacks and cross-‐level interactions, referred to as panarchy , implies that resilience of a system at a particular level will depend on influences at levels above and below

(Holling, 2001).

•

Adaptability or adaptive capacity refers to the potential to determine the state of the system and to influence resilience (Folke, et al., 2010).

• Transformability implies that a system can be moved from an undesirable to a desirable state by transforming it into a new kind of system or a different panarchy (Walker, et al., 2004).

Resilience is not an either-‐or attribute. A system can be more or less resilient to specific disturb-‐ ances (Kinzig, 2012). Thus, the question is not whether a social-‐ecological system is resilient or not but how resilient is it. This refers to Carpenter et al. (2001) who argued that one should always ask the question of resilience of what to what. At the same time, this aspect of specific resilience im-‐ plies that increasing resilience of some aspect may result in reduced resilience of other aspects of that system to new or other disturbances (Kinzig, 2012).

A range of studies has looked at food systems or at components of a food system from a resilience perspective. These refer to agricultural production or other stages in the food value chain

(Anderies, et al., 2006; Walker, et al., 2006), study adaptability and transformability (Walker, Abel,

Anderies, & Ryan, 2009), cascading effects in regime shifts (Kinzig et al., 2006), adaptive capacity of farmers markets (Milestad, Westberg, Geber, & Björklund, 2010) and panarchy, e.g. in dairy farming (Van Apeldoorn, Kok, Sonneveld, & Veldkamp, 2011) or alpine grasslands cultivation

(Soane, Scolozzi, Gretter, & Hubacek, 2012). They also incorporate the ideas of adaptability and transformation to address the sustainability of farming systems (Darnhofer, Bellon, Dedieu, &

Milestad, 2010; Darnhofer, Fairweather, & Moller, 2010), food production systems (Naylor, 2009) or food security in emergency situations (Pingali, Alinovi, & Sutton, 2005).

Despite the growing literature, several important gaps remain in our understanding of resilience in food systems and food value chains:

•

Resilience studies often refer to local or regional natural resources (Anderies, et al., 2006;

Plieninger & Bieling, 2012) and they generally study selected scales and levels in a food system.

Thus, an important next step in resilience studies will be to apply these approaches to complex national, regional and global contexts such as entire food value chains.

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• Most studies have evaluated resilience ex-‐post and in a descriptive way on a case study basis.

It is thus important to develop analytical tools that allow for ex-‐ante analyses of interventions in food value chains.

• There has been a tendency to use the concept of resilience subjectively, as an argument for protecting local interests or supporting the status quo (Betsy et al. 2012; Kirchhoff, Brand, &

Hoheisel, 2012; Kirchhoff, Brand, Hoheisel, & Grimm, 2010). There is thus a need for more ob-‐ jective, evidence-‐based evaluations of food value chains across multiple scales and levels.

•

The concepts of adaptive cycles and the corresponding ideas of adaptability, transformability and buffering capacity are less prominent in the food system approach than in resilience think-‐ ing. In addition, thresholds and non-‐linearities resulting in regime shifts are not discussed in the context of the food systems approach even though there may be important boundaries to agricultural intensification (Rockström et al., 2009).

2.2

Methodological frameworks

A systems approach first requires the comprehensive mapping of system components and flows.

For food systems, this can be achieved with approaches such as material flow analysis and life cy-‐ cle assessment, which can provide an extensive basis of data concerning the physical elements of a system. However, complex interactions and connections between interrelated sub-‐systems across disciplinary boundaries cannot be reflected satisfyingly using only such methods. Analysis of feedback effects, time delays and counterintuitive system behavior for example requires innova-‐ tive methodological strategies such as modeling techniques drawn from complexity science. Of particular interest for a systems approach to food and nutrition security are system dynamics and agent-‐based modeling (Hammond & Dubé, 2012).

2.2.1

Material flow analysis and life cycle assessment

Material flows and the environmental impact of agricultural and food products have extensively been analyzed in life cycle assessment and material flow analysis studies (Stoessel, et al., 2012

Carlsson-‐Kanyama & Gonzalez, 2009; Corson & van der Werf, 2012; Jungbluth, 2000; Nemecek &

Gaillard, 2008; Xue & Landis, 2011). Results are highly product specific, but some tendencies seem to become apparent. Generally, animal-‐based food seems to be environmentally more harmful than plant-‐based food (Baroni, Cenci, Tettamanti, & Berati, 2007; Virtanen et al., 2011). The most important life cycle phases are agriculture and food processing (Vermeulen, Campbell, & Ingram,

2012). Environmental impacts from transport (with the exception of air transport) and packaging are less relevant on average but can be important for specific food products. The level of food waste in the various life cycle phases and the related environmental impacts have been shown to be considerable (Beretta, Stoessel, Baier, & Hellweg, 2013; Gunders, 2012; Moomaw, Griffin,

Kurczak, & Lomax, 2012). Relevant environmental impact categories are land use and loss of biodi-‐ versity, water use, energy use, air emissions, acidification and eutrophication.

These findings allow for the identification of improvement options in the different life cycle phases

(Baroni, et al., 2007; Jungbluth, 2000; Risku-‐Norja, Kurppa, & Helenius, 2009; Xue & Landis, 2011

Virtanen, et al., 2011).

2.2.2

Systems analysis and modeling

A growing body of literature studies transformation processes in the agri-‐food system resulting from different policy interventions and the interaction of different stakeholders following a system dynamics approach (Belcher, Boehm, & Fulton, 2004; Georgiadis, Vlachos, & Iakovou, 2005; A.

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Jones, Seville, & Meadows, 2002; Kopainsky, Tröger, Derwisch, & Ulli-‐Beer, 2012; Saysel & Barlas,

2001; Saysel, Barlas, & Yenigün, 2002; Shi & Gill, 2005). This modeling approach can provide a sys-‐ tematic understanding of food systems behavior, by studying the dynamics generated by exoge-‐ nous drivers in interaction with feedback loops. These loops span across scales, and temporal dy-‐ namics and effects such as accumulation and non-‐linearities can be captured. The main limitation of this approach is the difficulty of portraying cross-‐level interactions in fine-‐grained ways.

Agent based modeling approaches are widely used to model social-‐ecological systems (Heckbert,

Baynes, & Reeson, 2010; Huber et al., 2013; Le, Park, & Vlek, 2010; Le, Park, Vlek, & Cremers,

2008; Le, Seidl, & Scholz, 2012; Li, 2011; Miller & Page, 2007; Schlüter et al., 2012; Tesfatsion &

Judd, 2006). By representing flexible feedback loop structures (built on emerging interactions ra-‐ ther than fixed cause-‐effect relationships) across levels, the approach is valuable for explaining structural/organizational adaptation to changes in system drivers. Though the technique can theo-‐ retically address cross-‐scale interactions, it is still challenging to do so due to excessive data re-‐ quirements.

Detailed, parameter-‐rich simulation models that represent the complex cross-‐scale and cross-‐level dynamics of food systems are very difficult to develop and calibrate. A possible alternative consists in the identification and calibration of generic structures (or simplified simulation models) for se-‐ lected components of the food system (Bennett, Cumming, & Peterson, 2005; Carpenter, Brock, &

Hanson, 1999). Such models can be connected with each other through indicators that explicitly identify links among the multiple dimensions of food system performance such as food security indicators (e.g., von Grebmer et al., 2013), economic costs, distributional equity, environmental impacts, energy use, health and safety (Gómez et al., 2011).

2.2.3

Food system scenario analysis

Complex social-‐ecological systems such as food systems are unpredictable, especially to long-‐term horizons. In order to manage this uncertainty, scenario analysis, in conjunction with food system modeling, can be used to explore plausible future outcomes (Reilly & Willenbockel, 2010). Scenar-‐ io analysis copes with uncertainty by presenting a range of plausible futures without claiming to predict the future (e.g., Chaumet et al., 2009; Millennium Ecosystem Assessment, 2005; Parry,

Rosenzweig, Iglesias, Livermore, & Fischer, 2004; van der Heijden, 2005). Stakeholder participation is crucial in scenario analysis (van der Heijden, 2005; Lang et al., 2012; Stauffacher, Flüeler, Krütli,

& Scholz, 2008) as knowledge co-‐production my be impeded if scenario analysis is not sufficiently participatory or if the modeling/assessment process used to underpin the scenario narratives is not accessible.

Formative scenario analysis (Brand, Seidl, Le, Brändle, & Scholz, 2013; Scholz & Tietje, 2002), for example, allows linking simulation models with future trends and policy alternatives. Formative scenario analysis is a transparent method for integrating qualitative and quantitative knowledge and generating a set of consistent and plausible scenarios for future development (Brand, et al.,

2013; Spörri, Lang, Binder, & Scholz, 2009). The process is implemented in four steps: System and goal definition; definition of context scenarios; system analysis and projection phase; scenario selection and interpretation phase.

2.2.4

Transdisciplinarity in food system research

For the analysis of complexity, feedbacks and trade-‐offs across scales and levels, transdisciplinary approaches are important and represent a critical factor in the context of environmental and agri-‐ cultural policy analysis (Buizer, Arts, & Kok, 2011; Binder, et al., 2010; Carpenter, et al., 2009; Lang,

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et al., 2012; Ostrom, 2009; Hammond & Dubé, 2012; Rosenzweig et al., 2012). Inter-‐ and transdis-‐ ciplinary research is generally seen as key to overcoming fundamental problems in the analysis of complex systems (Carpenter, et al., 2009; Ostrom, 2009). Resilience thinking, similar to the food system approach, identifies the governance of the social-‐ecological systems as the key factor in achieving corresponding goals (Ericksen, 2008a; Folke, et al., 2005).

There are various intensity levels in the involvement of stakeholders such as information, consul-‐ tation, cooperation, or collaboration (Stauffacher, et al., 2008). Simulation models are increasingly developed and/or used within participatory or transdisciplinary approaches (Etienne, 2011; van de

Fliert, Hermann, & Olsson, 2011). The integration of simulation models in transdisciplinary pro-‐ cesses requires hybrid frameworks where multiple qualitative and quantitative methodologies are applied, making use of a combination of existing quantitative sources, case studies, and stake-‐ holder input for example (Engle, Bremond, Malone, & Moss, 2013).

2.3

Resilience assessments

Table 2 lists the stages necessary for assessing resilience in food systems. The first four columns summarize the stages described in selected resilience assessment studies. The last column (with text in italics ) integrates them into four generic stages.

Table 2: Stages in resilience assessment

Riisgaard et al., 2010 Walker et al.,

2002

Overall research design choices (major issues, value chain, geographical focus), identification and engage-‐ ment of target group (set-‐ ting boundaries)

Address poverty, gender, labor and environmental issues

Conduct value-‐chain analysis

Choice of upgrading strategy

Resilience of what (description of system)

Resilience to what (external shocks, plausible policies, visions)

Evaluation and implementa-‐ tion of research and action

(support activities); adjust-‐ ment (or exit)

Resilience analy-‐ sis and manage-‐ ment

Engle, et al., 2013

Identification and elaboration of cat-‐ egories of indica-‐ tors describing the system

Identification of exposure and vari-‐ ability in the con-‐ text of multiple stresses

Calibration of indi-‐ cators

Verification of indi-‐ cators

Cumming et al.,

2005

Defining the system

Measuring driv-‐ ers of change

(defining possi-‐ ble future sys-‐ tems)

Clarifying change trajectories

Identifying mechanisms and leverages of change

Generic stages

Defining the sys-‐ tem and out-‐ comes: “Resili-‐ ence of what”

Identifying driv-‐ ers of change:

“Resilience to what”

Designing inter-‐ ventions

Evaluating and implementing interventions

9

3 Proposed approach

Section 1 stated that the eventual objective of the research program is to develop a comprehen-‐ sive methodology to conduct systems based analyses of food value chains to assess food system outcomes from a resilience perspective. The review of the state of the art in section 2 has a series of implications for the design of such methodology:

• Any methodology needs to follow a food system approach and integrate the principles of resil-‐ ience thinking, i.e., it needs to keep track of food system outcomes, activities and their drivers as well as the multiple interactions and feedback loops across scales and levels.

• The objective of interventions in food systems such as food value chains must be to increase the resilience of the system while at the same time improving food system outcomes. This im-‐ plies that often, transformations towards higher levels of resilience (or a different panarchy) are needed. Food systems can be resilient, i.e., they can have the capacity to experience shocks while retaining the same identify, but at the same time perform poorly in terms of food system outcomes.

•

The overview of the resilience assessment process in Table 2 (section 2.2.4) indicated that no single method can accomplish the required integrated, cross-‐scale and cross-‐level assessment.

Instead, a hybrid framework is necessary (Gómez, et al., 2011), borrowing from a range of dis-‐ ciplines such as economics, environmental science, soil science, sociology, political science and geography.

For such a hybrid approach to be feasible it needs to have the following characteristics:

• The resilience and food system assessment tool needs to combine standard, state of the art methodologies in innovative ways with the aim of facilitating intervention analysis and design for public and private sector decision makers. For example, it has to enable comparative as well as trade-‐off analyses of food value chains as subsets of food systems.

•

Starting from these state of the art methodologies, it is important to develop standardized procedures that allow stakeholders to apply these methods in simplified and yet sufficiently exhaustive ways.

•

The resilience and food system assessment tool needs to be practical with an emphasis on empirical work. This implies that initially, qualitative analyses will prevail. Over time, theories and formal simulation models will emerge from these empirical applications.

Case studies play an important role in the implementation of resilience and food system assess-‐ ment. Hybrid approaches offer a learning component by building an understanding of those at-‐ tributes that are most strongly associated with resilience and other desirable food system out-‐ comes (Engle, et al., 2013; Gómez, et al., 2011). Quantitative as well as qualitative data about so-‐ cial-‐ecological systems such as food systems across different cases are needed to enable scholars to build and test theoretical models and design improved interventions (Ostrom, 2009).

Based on these principles and considerations, we propose an approach to designing resilient inter-‐ ventions and assessing their food system outcomes in national food value chains that follows the four stages identified in Table 2. The approach is illustrated in Figure 3 which positions the activi-‐ ties necessary for implementing the proposed approach in the food system framework introduced in Figure 2.

10

The resilience and food system assessment tool focuses on food value chains at a national level

(being the level where decision-‐making of stakeholders is most relevant), but will per definition include interactions and feedbacks with other levels.

Figure 3: Proposed approach to design resilient interventions and assess their food system out-‐ comes in national food value chains

7"

2"

3"

4"

5"

6"

8"

1"

9"

1+5"

6"

7+8"

Deﬁning"the"system:"vulnerability/resilience"of"what"

IdenEfying"drivers"of"change:"vulnerability/resilience"to"what"

Designing"intervenEons"

9" EvaluaEng"intervenEons"

Table 3 provides a more detailed description the activities for implementing the proposed ap-‐ proach to design resilient interventions and assess their food system outcomes. The activities de-‐ scribe a stepwise procedure that uses multiple methods and that allows the consistent collection and integration of qualitative as well as quantitative data about food systems. The data provide a holistic perspective on a national food value chain, including its activities and stakeholders at mul-‐ tiple scales and levels, as well as links to drivers and outcomes. Synergies and trade-‐offs in food system outcomes can be tracked within and across scales and levels.

In contrast to Figure 3, Table 3 lists a tenth activity, the design of appropriate governance systems for the implementation of resilient interventions that improve food system outcomes. This activity is listed for reasons of completeness and will not be further pursued in the remainder of this re-‐ port. The implementation stage is left for applications of the assessment tool in later stages of the research program.

11

Table 3: Activities for implementing the proposed approach

Stage in food system assess-‐ ment


Activities and outcomes

Defining the system:

Resilience/vulnerability of what


Identify and prioritize the food value chains contributing to the relevant food sys-‐ tem outcomes

Map the food value chain and estimate the relative importance of the different channels

Select and map the most pertinent channel within this food value chain


Identify and prioritize drivers of change Identifying drivers of change:

Resilience/vulnerability to what

Assessment



Implementation

Implementing interventions

Design interventions that increase the resilience of the food system and improve outcomes

Formulate scenarios


Design appropriate governance systems

12

4 Pilot version of the resilience and food system assessment tool

This section describes the pilot version of the assessment tool. This pilot version consists of a se-‐ ries of guidelines and checklists that guide through the activities for implementing the proposed approach to design resilient interventions and assess their food system outcomes. Table 4 summa-‐ rizes the guidelines and checklists developed in the pilot version of the assessment tool as well as the remaining research gaps that need to be addressed in the full research program (section 5).

Table 4: Pilot version of the assessment tool: Summary of activities, guidelines and research gaps

Assessment stage

Activities and out-‐ comes

Guidelines and checklists Research gap


Defining the system: Resili-‐ ence/ vulnera-‐ bility of what


Identify and prioritize the food value chains contributing to the relevant food system outcomes

Map the selected food value chain and estimate the relative importance of the different channels

Identifying driv-‐ ers of change:

Resilience/ vul-‐ nerability to what

Select and map the most pertinent chan-‐ nel within this food value chain


Identify and prioritize drivers of change

List of food system outcomes for which indicators and data need to be found

Framework of key segments, nodes and possible channels in a food value chain

Framework of key segments and assignment of segments and nodes to spatial levels for the selected channel


Examples of drivers on different spatial and temporal levels relevant for agricultural production

Generic list of drivers that need to be adjusted to a specific food sys-‐ tem. Exposure of the food system to drivers of change for prioritiza-‐ tion of drivers

Framework of drivers interacting with the food system activities and

Food system map that explicitly links the mul-‐ tiple dimensions of food systems

Estimating flows of products (& product transformations), in-‐ formation, finance, including inputs, waste and losses

Guidelines for stake-‐ holder and network analysis in food value chains

Food system map that depicts the causal pathways between drivers and food sys-‐ tem activities and out-‐ comes

13

stakeholders


Assessment



Design potential inter-‐ ventions that would increase the resilience of the food system and improve outcomes

Formulate scenarios combining drivers, in-‐ terventions and goals


List of generic value chain devel-‐ opment strategies

List of resilience criteria that help designing interventions

List of food system outcomes


Framework for impact assessment at several points in time

Establishing feedback relations between food system drivers, activi-‐ ties and outcomes

Guidelines for forma-‐ tive scenario analysis in food value chains

(Partial) quantification of feedback relations between food system drivers, activities and outcomes

4.1

Identification of relevant food system outcomes

This step performs an initial assessment of the situation in terms of food system outcomes in a country, that is, in terms of food security, environmental welfare and social welfare.

The literature documents a great variety especially of food security indicators and indices (e.g.,

Ericksen et al., 2011; FAO/IFAD/WFP food security indicators (FAO, IFAD, & WFP, 2013); the Global

Food Security Index (The Economist, 2013); the Global Hunger Index (von Grebmer, et al., 2013) etc.). Different proxy indicators for measuring food security can paint different pictures of the food security situation e.g. in a country (Barrett, 2010; Coates, ). The choice of specific food securi-‐ ty indicators thus depends on the objective of measuring food security and on the available re-‐ sources for doing so (Jones, Ngure, Pelto, & Young, 2013). The checklist developed for this step in the assessment process therefore only contains a list of indicator concepts for measuring food system outcomes without detailing the specific indicators for operationalizing these concepts.

In addition to food security, this step in the assessment process also contains an initial assessment of the social and environmental welfare outcomes of food system activities in a country (Bolwig,

Ponte, Du Toit, Riisgaard, & Halberg, 2010; Engle, et al., 2013; Ericksen, 2008a; FAO, 2012;

Millennium Ecosystem Assessment, 2005). As in the case of the food security outcomes, no uni-‐ versally agreed upon indicators exist for operationalizing these categories. The specific choice of indicator will again depend on the specific objectives and on the available resources.

Guidelines and checklists

• List of indicator concepts for measuring food system outcomes (Table 5).

• Basis: food system framework, see section 2.1.1.

14

Data sources

• International statistical data, e.g., FAOStat, World Health Organization, World Development

Indicators, Ecosystem Service Indicators Database.

•

National statistical data, e.g., national agricultural, economic, poverty and environmental sta-‐ tistics, survey data (e.g., living conditions, food expenditure and dietary diversity, post harvest production).

•

Potentially useful project: Maryland Food System Map, http://mdfoodsystemmap.org/

Table 5: Food system outcomes for which indicators and data need to be found

Category Dimension Indicator concept

Food security

Environmental welfare

Social welfare

Food availability Production

Distribution

Food access

Exchange

Affordability

Food utilization

Allocation

Preference

Nutritional value

Social value

Food safety

Ecosystem stocks, ecosystem flows

Ecosystem services

Access to natural capital

Income

Employment

Wealth

Social and political capital

Human capital

Source: Ericksen, 2008a

4.2

Identification and prioritization of food value chains contributing to the relevant food system outcomes

The second step in the assessment process identifies the main food value chains that contribute to the relevant food system outcomes in a country and prioritizes them in terms of their relevance and/or potential for improving food system outcomes.


•

(not necessary)

Data sources

•

Similar to the data sources in step 1, differentiated for the main commodities.

15

4.3

Mapping of the selected food value chain and estimation of the relative importance of the different channels

Value chain analysis typically explores four dimensions (Gereffi & Fernandez-‐Stark, 2011):

•

An input-‐output structure, which describes the process of transforming raw materials into final products (this section 4.3 on mapping the food value chain).

• A geographical consideration (section 4.4 on selecting and mapping the most pertinent value chain channel).

• A governance structure, which explains how the value chain is controlled (section 4.5 on stakeholder analysis).

•

An institutional context in which the value chain is embedded (section 4.6 on drivers of change).

As entire value chains consist of activities in different channels performed by a great variety of stakeholders, we split the analysis of a specific food value chain in several steps. A first step pro-‐ vides a rough overview of the different segments, nodes and channels in a value chain. Based on this overview, the most pertinent channel in terms of food system outcomes is selected (section

4.4) and analyzed in more detail regarding the flows of material and value as well as regarding the most important stakeholders, their power and networks (section 4.5).

Establishing the input-‐output structure of the food value chain requires mapping the process of transforming raw materials into final products. This process consists of different activities that add value to the products (segments in a food value chain) and which are linked through nodes. The same original raw material can result in different products. These different transformations occur in separate channels (e.g., processing commodity for human consumption domestically/in export markets; processing commodity for livestock feed/biofuels).


•

Framework of key segments, nodes and possible channels (Figure 4).

•

Segments: production inputs; agricultural production; primary food storage; transportation and primary processing; transportation and secondary processing; distribution; retailing; consumption.

•

Nodes: flows of information, materials, goods and services from one segment to another.

In Figure 4, black arrows indicate the flows between segments and red diamonds highlight places where market-‐transactions take place.

• Channels: Individual, competing production and marketing systems within the same value chain.

• Basis: principles from material flow analysis/life cycle analysis, see section 2.2.1.

Data sources

• Government data on food prices and labor markets.

•

Industry data.

•

Interviews.

16

Figure 4: Framework of key segments, nodes and possible channels a: generic frame-‐ work with seg-‐ ments, nodes and channels

Production inputs

...

Agricultural production

Primary food storage

Transportation and primary processing

Transportation and secondary processing

Subsistence*households

Distribution Retailing

Unprocessed*for*domes4c*human*consump4on

Consumption

Processed*for*domes4c*human*consump4on

Processed*for*export*human*consump4on

Livestock*feed

Biofuels

Industrial*purposes b: channels in the cassava value chain in Zambia

(based on

Chitundu,

Droppelmann, &

Haggblade, 2009:

594)


...





Subsistence*households

Distribution Retailing Consumption

Fresh*cassava*for*domes5c*human*consump5on

Processed*cassava*for*domes5c*human*consump5on

Livestock*feed

Industrial*starches*(beer)

4.4

Selection and mapping of the most pertinent channel

The overview of the entire value chain in the previous step provides the basis for selecting the most pertinent channel in light of the food system outcomes in the country. Once this channel is selected, it is analyzed in more detail. For this purpose, the geographical or spatial scale is included and the flow of information, materials, goods and services from one segment to another plus the origin of the various inputs to the activities in each segment are entered on the relevant spatial level (e.g., differentiation between inputs that are sourced locally versus inputs that are imported from abroad). In addition, waste and losses are traced explicitly.


• Framework of key segments and assignment of segments and nodes to spatial levels (Figure 5).

• Basis: principles from material flow analysis/life cycle analysis, see section 2.2.1.

Data sources

•

Similar to the data sources in step 3, differentiated for the main spatial levels.

17

Figure 5: Framework of key segments and spatial levels for the selected channel

Spatial scale Production inputs





Distribution Retailing Consumption

Local

Regional

National

Continental

Global

Waste

4.5

Identification and analysis of relevant stakeholders

This step in the assessment process identifies and characterizes the stakeholders involved in the activities within the chose value chain channel. In this step, only stakeholders that are directly in-‐ volved in the activities are considered. System-‐wide stakeholders such as the government, non-‐ governmental and civil society organizations or donor and aid agencies become relevant in the next steps (identification of risks and potential interventions; sections 4.6 and 4.7).


• List of stakeholders and their characteristics (Table 6).

• Based on stakeholder list: Stakeholder influence diagrams that indicate how stakeholders influence one another.

• Basis: principles from stakeholder and network analysis (Bryson, 2004; Downing & Franklin,

2004).

Data sources

•

Interviews.

Table 6: Value chain stakeholders and their characteristics

Segment Stakeholders Number Market power

Political power

Characteristics

Inter-‐ ests

Free-‐ dom to operate

Produc-‐ tion in-‐ puts

Crop breeders

Extension offic-‐ ers

Seed companies

Agrochemical companies

Re-‐ sources

Legal struc-‐ ture

18

Agricul-‐ tural produc-‐ tion

Farm machinery companies

Farmers

Agricultural la-‐ borers

Commodity pro-‐ ducers

Primary food storage

Trans-‐ portation and pri-‐ mary pro-‐ cessing

Trans-‐ portation and sec-‐ ondary pro-‐ cessing

Retailing

Farmers

Local collection points

Seed companies

Agrochemical companies

Transporters

Packers

Millers

Crushers

Refiners

Transporters

Processed food manufactures

Traders

Wholesalers

Informal retail-‐ ers

Supermarket chains

Restaurants

Fast food com-‐ panies

Consump sump-‐ tion

Subsistence households

Rural house-‐ holds

Urban house-‐ holds

Consumers abroad

Notes:

Freedom to operate – how constrained they are in their activities

Number/market power/political power/freedom to operate/resources: can be high, medium, low

19

4.6

Identification and prioritization of drivers of change

The assessment process so far defines the food system for which improvements are sought. The next step is now to identify the ways in which the food system is vulnerable to current and future environmental, socioeconomic and political stressors or drivers of change. This step links food sys-‐ tem activities and outcomes to processes that drive or create vulnerability across spatial and tem-‐ poral levels.

The feedbacks and cross-‐scale interactions between food system activities and drivers of change can create trade-‐offs among food system outcomes. For decision-‐making and policy impact, it is important to have analytical clarity about such impacts and trade-‐offs.

Vulnerability is a function of exposure, sensitivity as well as coping and adaptive capacity (Ericksen,

2008b). The guidelines and checklists for this step in the assessment process focus on the expo-‐ sure aspect of vulnerability. We provide an example of the specific drivers relevant on different spatial and temporal levels for the agricultural production segment. A more generic list of drivers illustrates how hot spots of exposure can be identified in a food system. For each food system ac-‐ tivity (segment in the value chain), the exposure of this activity to a driver is estimated. Filling in the entire matrix of drivers and food system activities reveals those activities that are particularly exposed to the various drivers and thus helps prioritize drivers to which exposure will be lessened through the design and implementation of interventions.

When identifying the drivers of change it is important to also identify and characterize the system-‐ wide stakeholders, that is, the stakeholders representing these drivers, such as the government, non-‐governmental and civil society organizations or donor and aid agencies.


•

Examples of drivers on different spatial and temporal levels relevant for the agricultural pro-‐ duction segment (Table 7).

•

Generic list of drivers that need to be adjusted to a specific food system. Exposure of the food system to drivers of change for prioritization of drivers (Table 8).

• Framework of drivers interacting with the selected food value chain channel, that is, with the food system activities and stakeholders (Figure 6).

•

List of stakeholders and their characteristics (Table 9).

•

Based on stakeholder list: Stakeholder influence diagrams that indicate how stakeholders influence one another.

• Basis: food system framework, see section 2.1.1; global environmental change literature

(Darnhofer, Fairweather, et al., 2010; Downing & Franklin, 2004; Ericksen, 2008b); principles from stakeholder and network analysis (Bryson, 2004; Downing & Franklin, 2004).

Data sources

•

Literature (mainly for identification of drivers).

•

Interviews, stakeholder workshops (mainly for the prioritization of drivers).

20

Table 7: Examples of drivers on different spatial and temporal levels relevant for the agricultural production segment

Source: Darnhofer, Fairweather, et al., 2010: 191

21

Table 8: Exposure to drivers of change

Segment Spa-‐ tial level

Tem po-‐ ral level

Global Environmental Change driv-‐ ers: Changes in

Socio-‐economic drivers: Changes in

Production inputs

Agricultural production

Primary food storage

Transporta-‐ tion and pri-‐ mary pro-‐ cessing

Transporta-‐ tion and sec-‐ ondary pro-‐ cessing

Retailing

Consumption

Notes:

Relevant spatial level: local, regional/national, international/global

Relevant temporal level: short term, medium term, long term

Exposure: 2 – strong exposure of food system activity to driver; 1 – intermediate exposure; 0 – no exposure

Table 9: System-‐wide stakeholders and their characteristics

Stakeholders

Relevant segment

Rele-‐ vant spatial level

Num-‐ ber

Mar-‐ ket power

Politi-‐ cal power

Characteristics

Inter-‐ ests

Free-‐ dom to oper-‐ ate

Governments

Standard-‐ setting bod-‐ ies

Research

Re-‐ sourc es

Legal struc-‐ ture

22

institutions

Donors, aid agencies

NGOs

Civil society organizations

Notes:

Segments: agricultural inputs, agricultural production, primary food storage, transportation and primary processing, transporta-‐ tion and secondary processing, retailing, consumption

Relevant spatial level: local, regional/national, international/global

Freedom to operate – how constrained they are in their activities

Number/market power/political power/freedom to operate/resources: can be high, medium, low

Figure 6: Framework of drivers interacting with the selected food value chain channel

4.7

Design of interventions based on resilience and food system criteria

This step in the assessment process designs interventions that, given the vulnerabilities of the sys-‐ tem, improve the food system outcomes in the selected food value chain channel. The interven-‐ tions that aim at improving food system outcomes need to do so by augmenting the resilience of the food system.

The design of intervention also needs to be informed by the relevant stakeholders in this specific food system. Interventions need to take into account the characteristics of the stakeholders to

23

increase the likelihood that interventions can successfully be implemented and to reduce una-‐ voidable trade-‐offs.


• List of generic value chain development strategies (Table 10).

• List of resilience criteria that help designing interventions (Table 11).

• Basis: resilience characteristics, see section 2.1.2; generic value chain development strategies; stakeholders and their characteristics from the previous assessment steps.

Data sources

• Interviews, stakeholder workshops.

Table 10: Generic value chain development strategies

Relevant value chain segment

Strategy Comments

Same seg-‐ ment/food sys-‐ tem activity

Several seg-‐ ments and nodes

Improve value chain coordina-‐ tion

Improve process Improving efficiency or reducing negative externalities; this includes deliv-‐ ering on delivery schedules, invoicing, improving client management, re-‐ ducing wastage, etc.

Improve product Moving into more ‘sophisticated’ products with increased unit value, through complying with buyer requirements for physical quality, certifica-‐ tion, food safety standards, traceability, packaging, etc. Alternatively, shift-‐ ing from producing for high-‐value markets to bulk-‐commodity markets based on economies of scale could also increase rewards or reduce risks.

Improve volume Increasing the amount of product sold, through increases in yield or area.

Functional up-‐ grading

Functional downgrading

Vertical contrac-‐ tualization

Functional upgrading refers to a situation when producers take on a new function in the value chain, either by performing downstream activities (for example, grading, processing, bulking up, transporting or advertising), or by engaging in upstream functions such as the provision of services, inputs or finance. Functional upgrading normally leads to vertical integration (when a stakeholder performs more than one value-‐chain function), except when the producer decides to abandon primary production in order to focus on the new function.

Functional downgrading is where the producer moves one node down the chain (for example, from processing his product to focus back on produc-‐ tion because of the low profitability of processing).

Vertical contractualization (two stakeholders, different segments, e.g., farmers and wholesalers, co-‐op and retailer, etc.) means ‘getting a better deal’ through closer and longer-‐term business ties with buyers. It repre-‐ sents a move away from spot or repeated market-‐type transactions to an increasing use of contracts between producers and other chain stakehold-‐ ers. It often involves ‘learning from buyers’ (about market requirements rather than prices) and ‘interlocking contracts’ where sales contracts in-‐ clude embedded services from the buyer (extension, credit, fertilizers, ice boxes, etc.). The benefits of contracts may include reduced price risks, ac-‐ cess to price premiums, improved access to market information, inputs and

24

Horizontal con-‐ tractualization finance or reduced marketing costs. But contracts also involve higher per-‐ formance requirements, for example in respect of quality, volume, and certification, which can be difficult and costly to meet.

Horizontal contractualization (same stakeholders, same segment – for ex-‐ ample, farmer groups, co-‐ops) describes agreements among producers to co-‐operate over input provision, marketing (for example, bulking produce for sale, identification of buyers), certification, and crop insurance in order to reduce costs, increase revenues or mitigate individual risks. Such collec-‐ tive action is often a precondition for increasing contractualization vis-‐à-‐vis buyers and can also strengthen producers’ bargaining power.

Sources: Bolwig, et al., 2010; Riisgaard, et al., 2010

Table 11: Resilience criteria that help designing interventions

Resilience criteria

Criterion Most rele-‐ vant value chain seg-‐ ments

Most rele-‐ vant stake-‐ holders

Comments

Self-‐ regulation

Socially self-‐ organized

Every segment

Farmers, consumers

Diversity

Ecologically self-‐regulated

Spatially and temporally heterogeneous

Functionally diverse



Every segment

Farmers

Farmers, regional planners, policy makers

Ability to organize into grassroots networks and institutions (e.g., co-‐operative, farmer’s markets, sustainability-‐related community associations, advisory networks) in re-‐ sponse to new demands and desires.

Resource use efficiency, including capture, conversion and recycling efficiencies.

Patchiness on the farm and across the land-‐ scape.

Mosaic pattern of managed and unman-‐ aged land.

Diverse cultivation practices, crop rotations.

Farm heterogeneity.

Diversity of farming inputs, outputs, food markets, pest controls, etc.

Diversity of livelihood activities.

System coupling

Appropriately connected

Every segment

Suppliers of farming in-‐ puts, farm-‐ ers, food traders, re-‐ gional plan-‐ ners, policy makers

Suppliers of farming in-‐ puts, farm-‐ ers, food traders, re-‐ gional plan-‐ ners, policy

Connectivity within agricultural production

(e.g. crop composition and pattern, crop-‐ livestock-‐forest connection, inter-‐regional links).

Connectivity across the food value chain.

Connectivity between different food value chains or value chain channels.

25

Coupled with local natural capital

Agricultural production makers

Scientists,

R&D organi-‐ zation, con-‐ sumers, poli-‐ cy makers

All segments All stake-‐ holders

Positive soil nutrient and carbon balance.

Recharged water.

Reduced waste export.

Capital building

Combines strong horizon-‐ tal with vertical linkages

Builds physical, human and social capital

Reasonably profitable



Existence and performance of extension and advisory services for farmers.

Collaboration between universities, re-‐ search centers, consumers and farmers.

Cooperation and knowledge sharing be-‐ tween value chain stakeholders.

Existence and performance of monitoring and evaluation routines.

Degree of re-‐investment in infrastructure and institutions for the education of chil-‐ dren and adults.

Support for social events in farming com-‐ munities.

Programs for preservation of local knowledge

Stakeholders performing food system activi-‐ ties earn a livable wage.

Food system activities do not rely on distor-‐ tionary subsidies

Sources: Cabell & Oelofse, 2012; Darnhofer, Bellon, et al., 2010; Darnhofer, Fairweather, et al., 2010; Engle, et al., 2013.

4.8

Formulation of scenarios

Scenarios are a coherent and consistent combination of drivers of change, interventions and vi-‐ sions for the future development of the system (Walker, et al., 2002.). This step thus integrates the previous steps about the identification and prioritization of drivers and the design of interven-‐ tions. To these, it adds the formulation of goals or visions for the future development of the food system. Visions about preferred directions will on the one hand depend on the interventions de-‐ signed in the previous step. On the other hand, they will also differ among stakeholder groups.

The actual development pattern that the food system will follow in the future will be the outcome of stakeholder interactions and drivers of change.

The first step in scenario formulation is thus to establish a range of possible trajectories, at least a business-‐as-‐usual one plus, for example, a more conservative one and a more developmental or growth-‐oriented one (Walker, et al., 2002). These visions are built into the scenarios used to exam-‐ ine resilience and food system outcomes.

26


• (none possible)

• Basis: scenario analysis, see section 2.2.3.

Data sources

•

Interviews, stakeholder workshops.

4.9

Estimation of impact on food system outcomes

After the design of interventions and formulation of scenarios, this step in the assessment process estimates the system-‐wide, short-‐ and long-‐term impacts of the scenarios. This allows identifying the synergies and trade-‐offs between food system outcomes across scales and levels and thus de-‐ riving leverage points for interventions in the food system.

Integrated impact assessment requires a procedural understanding of the impact pathways of drivers and interventions through food system activities and food system outcomes. This under-‐ standing needs to be supported by a combination of qualitative and quantitative methodologies.

Where possible and available, systems simulation models (section 2.2.2) support the quantitative assessment of direct and indirect consequences of interventions and changes in food system driv-‐ ers. In the absence of quantitative simulation models, causal maps need to be constructed that illustrate the multiple impact pathways of interventions and changes in food system drivers. Such qualitative, conceptual models need to be constructed in a multi-‐stakeholder process. They can contain quantitative and measurable as well as qualitative variables. The connections between variables indicate causal relationships that either work in the same or in opposite directions. The connections give rise to reinforcing and balancing feedback loops. The construction and analysis of such maps cannot be comprehensive but they facilitate the development of sophisticated and in-‐ tegrated policy approaches (Finegood, Merth, & Rutter, 2010; King & Thomas, 2007).

The guidelines and checklists developed for this step in the assessment process cover the ele-‐ ments necessary for constructing causal maps such as the specific food system outcomes that need to be improved, an overview of the relevant system elements (drivers on different spatial levels, activities and stakeholders on multiple spatial levels, outcomes on different scales and spa-‐ tial levels) that need to be integrated into a causal map as well as a reminder that impact assess-‐ ments should cover multiple points in time, that is, take into account short-‐term as well as long-‐ term consequences of interventions and changes in food system drivers.


•

List of indicator concepts for measuring food system outcomes (Table 5).

•


(Figure 7).

• Framework for impact assessment at several points in time (short, medium, and long-‐term;

Figure 8).

•

Basis: food system framework, see section 2.1.1; systems analysis and modeling, see section

2.2.2.

27

Data sources

• Literature (impact of similar interventions in related fields).

• Simulation models.

• Interviews, stakeholder workshops.

Figure 7: Framework of interactions between drivers, activities and stakeholders as well as out-‐ comes for the selected food value chain channel

Environment (e.g. temperature, rainfall patterns, drought, flooding, climate change<

Economy (e.g. energy prices, fertilizer prices, crop prices, market size)

Politics (e.g. trade agreements, subsidies and taxes)

Society (e.g. lifestyle, diets)

Spatial scale

Local






Distribution

Regional

National

Continental

Global

Retailing Consumption

Waste

Social welfare


Food & nutrition security

Cross cutting issues

28

Figure 8: Dynamic estimation of impact on food system outcomes

Environment (e.g. temperature, rainfall patterns, drought, flooding, climate change<

Economy (e.g. energy prices, fertilizer prices, crop prices, market size)

Politics (e.g. trade agreements, subsidies and taxes)

Society (e.g. lifestyle, diets)

Spatial scale

Local






Distribution

Regional

National

Continental

Global

Retailing

Temporal scale

Consumption t

Waste

Social welfare


Food & nutrition security

Cross cutting issues

4.10

Iteration of assessment

An important element of the assessment process is checking how the interventions modify the overall vulnerability of the food system, that is, whether the interventions reduce the vulnerability of the system to some drivers of change but increase it to others, thus creating trade-‐offs. The assessment thus goes into iterations and continues with a re-‐examination of the vulnerability to drivers (section 4.6). Figure 9 visualizes this iterative procedure that eventually develops food sys-‐ tem development strategies that consist in combinations of different interventions.

An important aspect of iterations in the assessment process is the use of systems simulation mod-‐ els and transdisciplinary approaches in addition to qualitative assessment methods. Stakeholders can re-‐define and re-‐prioritize food value chains after careful reflections on the ex-‐ante evaluation of the impact of interventions on food system outcomes.

The iterative design and analysis of interventions in a specific food system might well result in the finding that the overall food system outcomes can only be improved above a certain level if inter-‐ ventions increase the diversity of the overall food system, that is, if interventions target other food value chains or other value chain channels than the one originally selected.

29

Figure 9: Iterative design and analysis of interventions to reduce the vulnerability of the food sys-‐ tem, increase resilience and improve food system outcomes

Iden%fy(relevant(food(system(outcomes((

Iden%fy(and(priori%ze(the(food(value(chains( contribu%ng(to(the(relevant(food(system(outcomes((

Map(the(selected(food(value(chain(and(es%mate(the( rela%ve(importance(of(the(diﬀerent(channels((

Select(and(map(the(most(per%nent(channel(within( this(food(value(chain((

Iden%fy(and(analyze(stakeholders(and(networks( within(this(channel((

Assess(vulnerability:(Iden%fy(and( priori%ze(drivers(of(change((

Design(interven%ons(that(increase( the(resilience(of(the(food(system( and(improve(outcomes(and( formulate(scenarios(

Es%mate(impact(on(food( system(outcomes((

30

5 Next steps

The guidelines and framework presented in section 4 were tested with a group of 24 students

(MSc and PhD level) during the 2013 summer school organized by the World Food System Center.

The students were split into four groups working part time on different case studies during a week. Debriefing showed that the guidelines are useful to identify key issues in a specific food val-‐ ue chain and to structure the process of designing and evaluating interventions for improving its outcomes and resilience. To make the guidelines more widely applicable, a series of next steps are necessary and will be addressed in this section. Some of these next steps are already formalized in ongoing applications (section 5.2) or activities of the World Food System Center (section Links to education) while others go beyond these currently available options (section 5.4). An immediate next step is the ongoing preparation of a journal article on the outcomes of the feasibility study.

The target journal is Environmental Science and Technology as this journal has published a number of papers resulting from the Global Environmental Change and Food Security (GECAFS) project and would thus offer the opportunity to make the results of the feasibility study accessible to a rele-‐ vant audience in food systems research.

5.1

Research questions

The goals of assessing food value chains from a food systems and resilience perspective are:

1.

To find ways of integrating food system drivers, activities as well as outcomes (food and nutrition security, environmental and social welfare) into a comprehensive and policy-‐relevant framework.

2.

To further develop tools to conduct systems-‐based analyses of food value chains, in order to assess food and nutrition security, social and environmental welfare. The tools provide decision support for evaluating, designing, calibrating, coordinating and timing interventions that increase the resilience of and improve food system outcomes in food systems.

3.

To enable public and private sector decision makers to analyze the likely impacts of existing or proposed interventions: are these interventions likely to achieve their stated aims?, what are possible unexpected and undesired outcomes?, how robust are these measures to future uncertainties? The tools and assessments also assist the scientific community in identifying research needs and knowledge gaps.

The application of the assessment process and tools will allow answering research questions such as those listed in Table 12.

Table 12: Research questions that can be answered with resilience and food system assessment processes and tools

Category Research question Clarifying remarks

Intervention-‐ related research questions

What are the impacts of proposed interventions/investments

On the stakeholders and their activities in a food value chain?

On the outcomes of these activities, that is, on food and nutrition security, social and environmental wel-‐ fare?

In the short-‐ and in the long run?

How are they shaped by and how do they shape the drivers/framework conditions of a food value chain?

31

What are the information needs of decision makers and stakeholders in a food value chain?

E.g. outcomes relevant for local level stakeholders versus outcomes relevant for stakeholders on na-‐ tional/regional/global levels

E.g. outcomes in the short-‐term versus long-‐term

Theoretical re-‐ search questions

Methodological research questions

What are the trade-‐offs in food sys-‐ tem outcomes across different scales?

Which governance systems/models are able to manage such trade-‐offs?

Which criteria and indicators can represent preconditions for system transitions to higher levels of resili-‐ ence and towards improvements of food system outcomes?

What kind of computer-‐based simu-‐ lation tools can support the re-‐ search questions?

5.2

Ongoing applications

5.2.1

Coop call for proposals November 1

st

, 2013

Building on the results of the feasibility study and the identified next steps, the proposal for the

Coop Research Program suggests developing a decision-‐making oriented tool to assess food sys-‐ tem resilience and the impacts of different interventions. The tool will support transdisciplinary processes designed to take account of the interests of different stakeholders, and will make use of data available in the public domain. It will focus on food value chains at a national level (being the level where decision-‐making of stakeholders is most relevant), but will per definition include inter-‐ actions and feedbacks with other levels.

To develop this tool we will assemble and analyze data relating to selected food commodities ag-‐ gregated at the national level. The exact choice of commodities and countries will depend upon the quantity and quality of data available, and will be the first task once the project starts. It is likely to include sugar in Switzerland and maize in sub-‐Saharan Africa. Indeed, data is readily avail-‐ able for the case study in Switzerland (Beretta, et al., 2013; Spörri, Bening, & Scholz, 2011) , allow-‐ ing a systematical study of data requirements for a valid analysis of the main activities, challenges and outcomes of food value chains. Maize in sub-‐Saharan Africa will provide a case for which to establish the most important causal links between drivers, food system activities and food system outcomes, and explore to which degree cross-‐scale and cross-‐level interactions can be captured.

In developing the assessment tool, the proposed project addresses the following research ques-‐ tions:

• What are the main causal links between food system activities, drivers and outcomes?

• What are the main stakeholders’ roles and interests?

• How do stakeholders’ decisions determine food system activities and outcomes?

32

• How can these links and stakeholders’ decision-‐making be integrated into a comprehensive framework relevant for intervention design?

•

What are the relevant data sources and procedures for quantifying food system activities and estimating their impact on food system outcomes?

The study will be organized into the following four work packages (WP, see details in Table 13):

•

WP1: Inventory: Developing an aggregated, multi-‐scale and multi-‐level framework of food sys-‐ tem drivers, activities and outcomes

• WP2: Food systems analysis: determining resilience of what to what

• WP3: Resilience assessment: determining impacts and food system outcomes of value chains and interventions

•

WP4: Integrating WP1-‐3 outcomes into the food system resilience assessment tool

A problem framing process in the very beginning (organized by the USYS TdLab) will serve for the goal orientation of all participants (and in particular of postdocs 1 & 2), later enabling optimized integration in WP 4.

The case studies will serve to validate the assessment process in work packages two and three, thus providing a learning component by building an understanding of those attributes most strongly associated with resilience and other desirable outcomes (Engle, et al., 2013; Gómez, et al.,

2011).

We will recruit a panel of stakeholders to participate in assessment workshops. These stakehold-‐ ers will include researchers, policy-‐makers, private sector representatives, extension services, farmers as well as civil society organizations.

Table 13: Detailed research plan Coop proposal

WP Objectives Approach/methods

1

2

3

Develop a holistic, multi-‐scale & multi-‐ level causal integrated analysis framework of food system drivers, activities & outcomes

Develop guidelines for applying the frame-‐ work, part I: analysis of the food system

Develop guidelines for applying the frame-‐ work, part II: analysis of resilience impacts and food system out-‐ comes

Literature review.

Stakeholder workshop 1.

WFSC summer school.

Delphi technique.

Standardize material flow analysis and stakeholder analysis.

Work with existing datasets for food value chains to test the relationship between data quality and complete-‐ ness and the quality of the resulting analysis.

Stakeholder-‐specific causal mapping.

Identify generic/archetypal structures appearing repeatedly in many sys-‐ tems.

Model generic/archetypal structures quantitatively.

Expected outputs/outcomes

Indicators that explicitly link the multi-‐ ple dimensions of food systems.

Food system map/sub-‐system diagram.

Analytical framework for the proposed project.

Toolbox containing standardized indi-‐ vidual tools and checklists that allow for rigorous yet resource-‐efficient anal-‐ yses of the system.

Guidelines for mapping of food value chains.

Refined food system map that visual-‐ izes how food system drivers, activities and outcomes are related, how they create synergies and trade-‐offs be-‐ tween the different outcomes and how they are affected by different actors’ decision making.

33

4 Integrating WP1-‐3 outcomes into the food system resilience assessment tool

Apply to selected cases: e.g., maize in sub Saharan Africa.

Stakeholder workshop 2.

WFSC summer school.

Technical implementation & integra-‐ tion of toolbox and systems models.

Archetypes and generic model struc-‐ tures allowing multidimensional and dynamic impact of interventions to be estimated.

Resilience assessment tool.

Guidelines for its application in educa-‐ tional and policy-‐related settings (e.g.

Forum for Sustainable Food Systems).

The outputs of this project will be:

• A holistic, multi-‐scale and multi-‐level causal description framework of food system drivers, activities and outcomes.

• Guidelines for analyzing food systems.

• Guidelines for designing resilient interventions improving food system outcomes.

• A tool for assessing food system resilience and designing interventions to improve outcomes, based upon these guidelines.

5.2.2

Forum for Sustainable Food Systems

The Forum for Sustainable Food Systems will be launched in 2015 by the World Food System Cen-‐ ter and its Partnership Council, together with the proposed ETH Zurich Institute for Science Tech-‐ nology and Policy. It aims at providing a multi-‐stakeholder platform for designing solutions and informing decision in complex food systems. The Forum is foreseen as a primary user of the as-‐ sessment tool developed in this feasibility study and subsequent research projects.

In the Forum for Sustainable Food Systems, key food system stakeholders will apply the tool in national contexts to develop regional scenarios, identify priorities and create national road maps for action. These outcomes will also provide an input to global world food summits that form a further part of the Forum for Sustainable Food Systems initiative. These activities will not only en-‐ sure wide dissemination of findings, but also provide the opportunity to improve and institutional-‐ ize the tool at a global level. In this way, it is envisaged that the tool will contribute to research strategy development, agenda setting and policy formulation regarding the world food system, and thus provide an effective bridge between academia and practice.

5.3

Links to education

The assessment tool resulting from the feasibility study and subsequent research projects will be applied in the various summer school programs run by the World Food System Center. These pro-‐ grams bring together Masters and PhD students from around the globe to learn about the chal-‐ lenges of the world food system. The tool will form the basis of the case study work conducted by the students at the end of the programs, supporting them in learning about problem framing, sys-‐ tem analysis and intervention design.

34

5.4

Requirements for implementation beyond ongoing applications

The further theoretical and methodological development as well as empirical application of the assessment tool from the feasibility study requires efforts that go beyond the activities sketched in the previous sections. Here, we distinguish between short-‐term activities (section 5.4.1), that is, activities that can be implemented in the scope e.g., of a master thesis, and long-‐term activities

(section 0) that require more substantial time and effort.

5.4.1

Short term

Table 14: Possible master theses for short term improvement of the assessment tool

Objective Description

Programming of checklists and guidelines

Improvement of individual steps in the assessment pro-‐ cess

Technical implementation of the checklists such that the full range of options (e.g., food system outcomes; stakeholders; drivers of change) is available from a drop down list and that the checked options will appear in a case-‐specific table.

The technical implementation needs to take into account that the full range of options is easily modifiable based on further developments of the assessment process.

Development of methodological guidelines for the implementation of each as-‐ sessment step, e.g., simplified material flow/lifecycle analysis; stakeholder and network analysis; system diagrams; impact assessment.

The development of methodological guidelines should be based on empirical data, that is, work with existing datasets or cases.

Application of selected steps in the assessment process, e.g., vulnerability of what; vulnerability to what; impact assessment.

Implementation of selected steps in the assessment pro-‐ cess for specific cases

Implementation of the as-‐ sessment process for select-‐ ed parts of a food system

Application of the assessment process e.g. for a case in the agricultural production segment.

The application of the assessment process for a specific case will start accumulat-‐ ing empirical data that helps improving the assessment tool and illustrating the range of application areas.

5.4.2

Longer term

Further developments of the assessment tool in the longer term are extensions of the activities described in the Coop proposal (section 5.2.1) and a synthesis of the activities and outcomes of the Forum for Sustainable Food Systems (section 5.2.2). Further developments thus aim at:

•

Methodological improvements: Formalization of the vulnerability analyses (vulnerability of what to what) and formalization of impact assessments. A rough estimation of personnel re-‐ quirements for this work would be two postdoctoral researchers working for three years each with one postdoctoral researcher focusing on vulnerability analyses and one on the formaliza-‐ tion of impact assessments.

•

Collection of empirical data: In addition to the technical tool development, the assessment tool needs to be applied to a variety of case studies focusing on different value chains and channels and on different countries. A variety of activities in this direction are foreseen by the

World Food System Center (cf., Forum for Sustainable Food Systems, section 5.2.2; and also

35

section 5.3). Rather than the execution of as many case studies as possible, a postdoctoral re-‐ searcher responsible for the collection of empirical data should accompany already ongoing data collection efforts and complement them where necessary. A rough estimate of personnel requirements for the collection of empirical data would thus be one postdoctoral researcher for the duration of three years. It is conceivable that this part of the research starts a bit later than the methodological improvements.

• Theory and model building from empirical applications: The empirical data collected in the course of various case studies will accumulate a body of evidence that gradually allows for the identification of patterns emerging from data. Such patterns are relevant for understanding the exact criteria that define improved food system outcomes in national food systems, that allow for a dynamic understanding of the transition processes in food value chains and that in-‐ dicate leverage points for interventions. Such patterns can gradually be formalized in systems simulation models. Initial models should focus on selected aspects (scales, levels) of a food sys-‐ tem and only be extended based on solid empirical foundations. Theory and model building from empirical applications requires the engagement of a senior researcher for a period of at least five years.

5.5

Concluding remarks

Adaptive capacity is a function of access to assets and capital (Adger, 1999). There is an inherent tension or an inherent trade-‐off between adaptive capacity and efficiency (Darnhofer, Bellon, et al., 2010; Darnhofer, Fairweather, et al., 2010).

In addition, adaptive capacity is insufficient to ensure successful management of change or suc-‐ cessful reduction of vulnerability. Societies in the past have collapsed not because people were unwise or lacked sufficient foresight but because it was in the interest of those with power to con-‐ tinue to push the social-‐ecological systems in the direction of more vulnerable system states

(Kinzig 2012). Thus, adaptive capacity is often not realized since adaptive management is con-‐ strained by competing interests on various levels such as consumers in the north versus local re-‐ source use in the south. Successful long-‐term adaptation requires broader level enabling institu-‐ tions that address the politics of distribution and management (Adger et al., 2007).

The feasibility study and any future research program support the transition towards more resili-‐ ent and sustainable food systems by providing sound methodological and empirical decision sup-‐ port and by facilitating as inclusive assessment processes as possible. However, the tools, theories and processes can inform decision making but they cannot enforce it.

36

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Document 12132758

ESILIENCE IN

OOD

ALUE

HAINS

Executive summary

Table of contents

List of figures

List of tables

1 Introduction

2 State of the art

2.1

Conceptual frameworks

2.1.1

Food system approach

2.1.2

Resilience thinking in social-­‐ecological systems

2.2

Methodological frameworks

2.2.1

Material flow analysis and life cycle assessment

2.2.2

Systems analysis and modeling

2.2.3

Food system scenario analysis

2.2.4

Transdisciplinarity in food system research

2.3

Resilience assessments

3 Proposed approach

4 Pilot version of the resilience and food system assessment tool

4.1

Identification of relevant food system outcomes

4.2

Identification and prioritization of food value chains contributing to the relevant food system outcomes

4.3

Mapping of the selected food value chain and estimation of the relative importance of the different channels

4.4

Selection and mapping of the most pertinent channel

4.5

Identification and analysis of relevant stakeholders

4.6

Identification and prioritization of drivers of change

4.7

Design of interventions based on resilience and food system criteria

4.8

Formulation of scenarios

4.9

Estimation of impact on food system outcomes

4.10

Iteration of assessment

5 Next steps

5.1

Research questions

5.2

Ongoing applications

5.2.1

Coop call for proposals November 1

, 2013

5.2.2

Forum for Sustainable Food Systems

5.3

Links to education

5.4

Requirements for implementation beyond ongoing applications

5.4.1

Short term

5.4.2

Longer term

5.5

Concluding remarks

6 References

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