24 research outputs found
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 narratorsâ 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
Understanding farm generational renewal and its influencing factors in Europe
Understanding the complex process of generational renewal (GR) in agriculture is essential for supporting the continuation of farming. This paper demonstrates how multiple factors, simultaneously and through their mutual interactions, influence GR and related individual decision-making processes. Results originated from 155 in-depth interviews performed on 85 farms in eleven European regions, and were triangulated with the literature. Our analysis, combining inductive and deductive approaches, revealed three conceptual phases (successor identity formation, farm succession process, and farm development) and fourteen factors important to understand GR. We elaborate how these factors interact, hence exert their impact on (one of) the phases in a complex and variable way. Implications highlight potential pitfalls and opportunities for attracting people into agriculture. Although policy-makers should be aware of their limited ability to affect GR by targeting the first phase, we propose some ideas that would complement current existing measures acting on the third phase
Policies and Farming System Resilience
The EUâs Common Agricultural Policy appears essential for farming systemsâ resilience, but its resilience-enabling effects in practice remain underexplored. We assessed how farming system actors perceive the CAPâs effects on resilience. The CAP contains a robustness-oriented approach, which actors expect to buffer stress and shocks, while adaptation receives less support and transformation is neglected. Policies need to a take a broader, integrated approach towards farming systemsâ resilience
How do Stakeholders Perceive the Sustainability and Resilience of EU Farming Systems?
An increasing variety of stresses and shocks provides challenges and opportunities for EU farming systems. This article presents findings of a participatory assessment on the sustainability and resilience of eleven EU farming systems, to inform the design of adequate and relevant strategies and policies. According to stakeholders that participated in workshops, the main functions of farming systems are related to food production, economic viability and maintenance of natural resources. Performance of farming systems assessed with regard to these and five other functions was perceived to be moderate. Past strategies were often geared towards making the system more profitable, and to a lesser extent towards coupling production with local and natural resources, social selfâorganisation, enhancing functional diversity, and facilitating infrastructure for innovation. Overall, the resilience of the studied farming systems was perceived as low to moderate, with robustness and adaptability often dominant over transformability. To allow for transformability, being reasonably profitable and having access to infrastructure for innovation were viewed as essential. To improve sustainability and resilience of EU farming systems, responses to shortâterm processes should better consider longâterm processes. Technological innovation is required, but it should be accompanied with structural, social, agroâecological and institutional changes
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, farmersâ 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 Europeâs diverse farming systems. The
framework is designed to assess resilience to specific challenges (specified resilience) as well as a farming systemâs
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 farmersâ 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 systemsâ 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
Participatory assessment of sustainability and resilience of three specialized farming systems
There is a need for participatory methods that simultaneously assess agricultural sustainability and resilience at farming system level, as resilience is needed to deal with shocks and stresses on the pathways to more sustainable systems. We present the Framework of Participatory Impact Assessment for Sustainable and Resilient FARMing systems (FoPIA-SURE-Farm). FoPIA-SURE-Farm investigates farming system functioning, dynamics of main indicators, and specifies resilience for different resilience capacities, i.e., robustness, adaptability, and transformability. Three case studies with specialized farming systems serve as an example for the used methodology: starch potato production in Veenkoloniën, The Netherlands; dairy production in Flanders, Belgium; and hazelnut production in Lazio, Italy. In all three farming systems, functions that related to food production, economic viability, and maintaining natural resources were perceived as most important. Perceived overall performance of system functions suggest moderate sustainability of the studied farming systems. In the studied systems, robustness was perceived to be stronger than adaptability and transformability. This indicates that finding pathways to higher sustainability, which requires adaptability and transformability, will be a challenging process. General characteristics of farming systems that supposedly convey general resilience, the so-called resilience attributes, were indeed perceived to contribute positively to resilience. Profitability, having production coupled with local and natural resources, heterogeneity of farm types, social self-organization, and infrastructure for innovation were assessed as being important resilience attributes. The relative importance of some resilience attributes in the studied systems differed from case to case, e.g., heterogeneity of farm types. This indicates that the local context in general, and stakeholder perspectives in particular, are important when evaluating general resilience and policy options based on resilience attributes. Overall, FoPIA-SURE-Farm results seem a good starting point for raising awareness, further assessments, and eventually for developing a shared vision and action plan for improving sustainability and resilience of farming systems