Trusting is good? Hints from an exploratory survey on trust in agri-food professions

Trust is considered a fundamental requisite for markets to work properly. In 2014, GFK Verein published a study that measured the trust of ordinary people from 25 countries of the world towards over 30 professions. In almost all the countries surveyed farmers are among the professions in which people trust more. Moving from this evidence, the paper presents a preliminary exploration on the level of trust for different professions of the agricultural and food chains in Italy. An explorative analysis has been carried out through a questionnaire submitted to a group of university students. The people interviewed confirmed that professions involved at different stages in the agri-food chains receive a high degree of trust: among these: farmers (83%) are the most trusted in, followed by chefs (78%), wine producers (75%), organic farmers (72%), and butchers (70%). Results are commented and possible practical implications are discussed in the final section

D2.2 Report on analysis of biographical narratives exploring short- and long-term adaptive behaviour of farmers under various challenges

The Horizon 2020 project Towards Sustainable and Resilient EU Farming Systems (SURE-Farm) defines resilience as maintaining the essential functions of EU farming systems in the face of increasingly complex and volatile economic, social, ecological and institutional risks: Meuwissen (2018) suggests that resilience over time is achieved across the increasingly fundamental attributes of robustness, adaptability and transformability, representing system responses to short, medium and long-term external drivers, respectively. Maxwell (1986) also recognised that external drivers vary significantly in time and space and distinguished four different types of perturbations: noise, shocks, cycles and trends. Analysis of narratives (Rosenthal, 2004; Riessmann, 2008) can be used to enable researchers to gain indepth understanding of the rationale surrounding farmer decision making when faced with drivers of change (e.g. MacDonald et al., 2014), and how farmers manage critical decision points in their farming businesses. This understanding is crucial for developing the tools and policy measures needed to support the sustainability and resilience of European agriculture. We have used personal histories of family farms, and business histories of corporate farms, to identify phases in the separate production, demographic and policy adaptive cycles (and consequences of interactions between them) as they have impacted on the individuals concerned and their business enterprises. Biographical stories were collected from nine to ten narrators (early-, mid- and late-career), in each of five case studies chosen to represent a range of regions and farming systems in Europe. These included large scale family and corporate arable farms in Northeast Bulgaria (BG) and the East of England (UK); dairy farms in Flanders (BE); small-scale perennial crop (hazelnut) farms in central Italy (IT) and high value egg and broiler systems in Southern Sweden (SE). A single question was used to initiate the narrators’ stories, without qualification beforehand, supported only with expressions of interest and encouragement in the first part of the interview, with subsequent exploratory questions devoted to clarifying the internal structure of the narrative. Narratives were transcribed and analysed to identify the drivers and responses to critical decision-making points in the stories. Comparisons across the five regional farming system cases have also been made to generate wider insights into how the narrators responded to different challenges. The drivers leading up to critical decision points in the narratives were grouped according to themes which followed a spectrum ranging from internal (those arising from within the farm system), to external (those acting on the farm system). Internal drivers included health, relationships, intergenerational change, retirement, redundancy. The more intermediate drivers included financial pressures, skills, labour, disasters, land issues, water. External drivers included supply chain factors, markets, technology, policy and regulation. Some drivers and responses were observed to relate to the farmer whilst others related to the farming system. Key findings from cross-narrative analysis distinguished inertia as the predominant response to system challenges, and that incremental changes (or creeping change, as we have termed it) in the system over a long-time frame rather than a definable critical decision point, is widely evident in the narratives. Climate change was not identified as being a driver and was only mentioned at all in two of the 45 narratives. Farmer identity ranged broadly across the narratives with the extremes being represented by those who farmed because it was their vocation, to those who perceived themselves first and foremost as business operators. To an extent, these identities reflected the degree of attachment to land, with the more vocational farmers having a strong attachment to their farmed land (particularly in the Flemish case) and the more business-minded (particularly in Northeast Bulgaria and the East of England) having less attachment. The long-term nature of the hazelnut crop in Central Italy meant that attachment to the land was strong, regardless of farmer identity. Family support, whether perceived as positive or negative by the narrator, was found to influence decision-making, and changing work/life balance expectations, particularly amongst early-career farmers with young families, was also influential. The narratives revealed different approaches to risk alleviation, both within and across case studies. In instances where land availability was not restricted (for example, Northeast Bulgaria, and to some extent, East Anglia), scale enlargement was predominant, but where land was restricted, diversification was the predominant response (for example, in the Flemish narratives). There were strong similarities and distinctive differences across the narrative contexts. Similarities included the dominance of internal drivers, intergenerational change as a major critical decision point, the perception of many external drivers as noise, and more frustration with policy drivers compared with weather events. There were few mentions of insurance by the narrators. The findings indicate that robustness is demonstrated in response to many drivers classified as cycles and shocks, whilst prolonged trends result primarily in adaptation. Transformations were relatively infrequent in the narratives and those identified were not radical in nature. The main policy related conclusions from the study suggest that farming systems are ill-equipped for a rapid move from direct payments to income insurance. They also appear to be unprepared for climate change. Long-term, coherent strategies required for dealing with intergenerational change were not apparent, confirming parallel literature that suggests that legal, social welfare and policy obstacles to farm succession need to be addressed

Constrained Sustainability and Resilience of Agricultural Practices from Multiple Lock-In Factors and Possible Pathways to Tackle Them

5.2 Aim of This Chapter While other chapters focus more upon economic and production factors and their contribution to resilience, this chapter focuses on environmental sustainability and its inherent importance to resilience. Using Therond et al.’s farming system classification framework and the theory of lock-in in agricultural systems, we assess the environmental sustainability and therefore resilience of three case studies within Europe. We demonstrate how the challenges they face lock them in to their current systems, despite EU policies geared towards agrienvironment schemes. With multi-stakeholder input, we then show how tackling these lock-in factors can create more sustainable and resilient systems

D5.6 Impacts of improved strategies and policy options on the resilience of farming systems across the EU

Resilience is the ability to deal with shocks and stresses, including the unknown and previously unimaginable, such as the Covid19 crisis. The aim of this paper is to assess responses of farming systems (FS) to this crisis and to assess them from the perspective of resilience thinking. We build on a resilience framework developed in the SURE‐Farm project and on ongoing resilience assessments in 11 FS across Europe through which we have an in‐depth understanding of the ‘pre‐Covid19 situation’ in each FS. This includes insights whether an FS has an enabling (or constraining) environment, who are the relevant system actors beyond farms, and what are the social, economic and ecological functions to be delivered by the system. The analysis allows us to understand which resilience resources and strategies were mobilised in different FS and thereby to explain differences in the ability of FS to cope with and respond to the crisis. Furthermore, the approach enables us to put crisis responses in a broader resilience perspective and to assess whether responses might enhance (or constrain) future resilience. Thus, our analysis allows to draw policy and industry relevant conclusions how to increase resilience of farming systems

A framework to assess the resilience of farming systems

Agricultural systems in Europe face accumulating economic, ecological and societal challenges, raising concerns about their resilience to shocks and stresses. These resilience issues need to be addressed with a focus on the regional context in which farming systems operate because farms, farmers’ organizations, service suppliers and supply chain actors are embedded in local environments and functions of agriculture. We define resilience of a farming system as its ability to ensure the provision of the system functions in the face of increasingly complex and accumulating economic, social, environmental and institutional shocks and stresses, through capacities of robustness, adaptability and transformability. We (i) develop a framework to assess the resilience of farming systems, and (ii) present a methodology to operationalize the framework with a view to Europe’s diverse farming systems. The framework is designed to assess resilience to specific challenges (specified resilience) as well as a farming system’s capacity to deal with the unknown, uncertainty and surprise (general resilience). The framework provides a heuristic to analyze system properties, challenges (shocks, long-term stresses), indicators to measure the performance of system functions, resilience capacities and resilience-enhancing attributes. Capacities and attributes refer to adaptive cycle processes of agricultural practices, farm demographics, governance and risk management. The novelty of the framework pertains to the focal scale of analysis, i.e. the farming system level, the consideration of accumulating challenges and various agricultural processes, and the consideration that farming systems provide multiple functions that can change over time. Furthermore, the distinction between three resilience capacities (robustness, adaptability, transformability) ensures that the framework goes beyond narrow definitions that limit resilience to robustness. The methodology deploys a mixed-methods approach: quantitative methods, such as statistics, econometrics and modelling, are used to identify underlying patterns, causal explanations and likely contributing factors; while qualitative methods, such as interviews, participatory approaches and stakeholder workshops, access experiential and contextual knowledge and provide more nuanced insights. More specifically, analysis along the framework explores multiple nested levels of farming systems (e.g. farm, farm household, supply chain, farming system) over a time horizon of 1-2 generations, thereby enabling reflection on potential temporal and scalar trade-offs across resilience attributes. The richness of the framework is illustrated for the arable farming system in Veenkoloniën, the Netherlands. The analysis reveals a relatively low capacity of this farming system to transform and farmers feeling distressed about transformation, while other members of their households have experienced many examples of transformation

D5.3 Resilience assessment of current farming systems across the European Union

For improving sustainability and resilience of EU farming system, the current state needs to be assessed, before being able to move on to future scenarios. Assessing sustainability and resilience of farming systems is a multi-faceted research challenge in terms of the scientific domains and scales of integration (farm, household, farming system level) that need to be covered. Hence, in SURE-Farm, multiple approaches are used to evaluate current sustainability and resilience and its underlying structures and drivers. To maintain consistency across the different approaches, all approaches are connected to a resilience framework which was developed for the unique purposes of SURE-Farm. The resilience framework follows five steps: 1) the farming system (resilience of what?), 2) challenges (resilience to what?), 3) functions (resilience for what purpose?), 4) resilience capacities, 5) resilience attributes (what enhances resilience?). The framework was operationalized in 11 case studies across the EU. Applied approaches differ in disciplinary orientation and the farming system process they focus on. Three approaches focus on risk management: 1) a farm survey with a main focus on risk management and risk management strategies, 2) interviews on farmers’ learning capacity and networks of influence, and 3) Focus Groups on risk management. Two approaches address farm demographics: 4) interviews on farm demographics, and 5) AgriPoliS Focus Group workshops on structural change of farming systems from a (farm) demographics perspective. One approach applied so far addresses governance: 6) the Resilience Assessment Tool that evaluates how policies and legislation support resilience of farming systems. Two methods address agricultural production and delivery of public and private goods: 7) the Framework of Participatory Impact Assessment for sustainable and resilient farming systems (FoPIA-SURE-Farm), aiming to integrate multiple perspectives at farming system level, and 8) the Ecosystem Services assessment that evaluates the delivery of public and private goods. In a few case studies, additional methods were applied. Specifically, in the Italian case study, additional statistical approaches were used to increase the support for risk management options (Appendix A and Appendix B). Results of the different methods were compared and synthesized per step of the resilience framework. Synthesized results were used to determine the position of the farming system in the adaptive cycle, i.e. in the exploitation, conservation, release, or reorganization phase. Dependent on the current phase of the farming system, strategies for improving sustainability and resilience were developed. Results were synthesized around the three aspects characterizing the SURE-Farm framework, i.e. (i) it studies resilience at the farming system level, (ii) considers three resilience capacities, and (iii) assesses resilience in the context of the (changing) functions of the system. (i) Many actors are part of the farming system. However, resilience-enhancing strategies are mostly defined at the farm level. In each farming system multiple actors are considered to be part of the system, such as consultants, neighbors, local selling networks and nature organizations. The number of different farming system actors beyond the focal farmers varies between 4 (in French beef and Italian hazelnut systems) and 14 (large-scale arable systems in the UK). These large numbers of actors illustrate the relevance of looking at farming system level rather than at farm level. It also suggests that discussions about resilience and future strategies need to embrace all of these actors. (ii) At system level there is a low perceived capacity to transform. Yet, most systems appear to be at the start of a period in which (incremental) transformation is required. At system level, the capacity to transform is perceived to be relatively low, except in the Romanian mixed farming system. The latter may reflect a combination of ample room to grow and a relatively stable environment (especially when compared to the past 30 to 50 years). The relatively low capacity to transform in the majority of systems is not in line with the suggestion that most systems are at the start of (incremental) transformation, or, at least, reached a situation in which they can no longer grow. Further growth is only deemed possible in the Belgium dairy, Italian hazelnut, Polish fruit and Romanian mixed farming systems. (iii) System functions score well with regard to the delivery of high-quality and safe food but face problems with quality of rural life and protecting biodiversity. Resilience capacities can only be understood in the context of the functions to be delivered by a farming system. We find that across all systems required functions are a mix of private and public goods. With regard to the capacity to deliver private goods, all systems perform well with respect to high-quality and safe food. Viability of farm income is regarded moderate or low in the livestock systems in Belgium (dairy), France (beef) and Sweden (broilers), and the fruit farming system in Poland. Across all functions, attention is especially needed for the delivery of public goods. More specifically the quality of rural life and infrastructure are frequently classified as being important, but currently performing bad. Despite the concerns about the delivery of public goods, many future strategies still focus on improving the delivery of private goods. Suggestions in the area of public goods include among others the implementation of conservation farming in the UK arable system, improved water management in the Italian hazelnut system, and introduction of technologies which reduce the use of herbicides in Polish fruit systems. It is questionable whether these are sufficient to address the need to improve the maintenance of natural resources, biodiversity and attractiveness of rural areas. With regard to the changing of functions over time, we did not find evidence for this in our farming systems

Impact of COVID-19 on farming systems in Europe through the lens of resilience thinking

CONTEXT Resilience is the ability to deal with shocks and stresses, including the unknown and previously unimaginable, such as the Covid-19 crisis. OBJECTIVE This paper assesses (i) how different farming systems were exposed to the crisis, (ii) which resilience capacities were revealed and (iii) how resilience was enabled or constrained by the farming systems’ social and institutional environment. METHODS The 11 farming systems included have been analysed since 2017. This allows a comparison of pre-Covid-19 findings and the Covid-19 crisis. Pre-Covid findings are from the SURE-Farm systematic sustainability and resilience assessment. For Covid-19 a special data collection was carried out during the early stage of lockdowns. RESULTS AND CONCLUSIONS Our case studies found limited impact of Covid-19 on the production and delivery of food and other agricultural products. This was due to either little exposure or the agile activation of robustness capacities of the farming systems in combination with an enabling institutional environment. Revealed capacities were mainly based on already existing connectedness among farmers and more broadly in value chains. Across cases, the experience of the crisis triggered reflexivity about the operation of the farming systems. Recurring topics were the need for shorter chains, more fairness towards farmers, and less dependence on migrant workers. However, actors in the farming systems and the enabling environment generally focused on the immediate issues and gave little real consideration to long-term implications and challenges. Hence, adaptive or transformative capacities were much less on display than coping capacities. The comparison with pre-Covid findings mostly showed similarities. If challenges, such as shortage of labour, already played before the crisis, they persisted during the crisis. Also, the eminent role of resilience attributes was confirmed. In cases with high connectedness and diversity we found that these system characteristics importantly contributed to dealing with the crisis. Also the focus on coping capacities was already visible before the crisis. We are not sure yet whether the focus on short-term robustness just reflects the higher visibility and urgency of shocks compared to slow processes that undermine or threaten important system functions, or whether they betray an imbalance in resilience capacities at the expense of adaptability and transformability. SIGNIFICANCE Our analysis indicates that if transformations are required, e.g. to respond to concerns about transnational value chains and future pandemics from zoonosis, the transformative capacity of many farming systems needs to be actively enhanced through an enabling environment