Structural Equation Model of Successful Territorial Cooperation

Presented study was a part of ESPON TERCO project (European Territorial Cooperation as a Factor of Growth, Jobs and Quality of Life) and was aimed at verifying the hypothesis that territorial cooperation underpins socio-economic development. Based on the literature review a conceptual model of successful territorial cooperation was proposed, where this kind of cooperation was defined as bringing the highest joint socio-economic development to the cooperating territorial units. That theoretical model was verified empirically by structural equation modeling, based on data collected via electronic questionnaires (CAWIs) in 9 cross-border case studies. The results of the SEM analysis positively verified the main hypothesis and provided information about the role of particular ‘determinants and factors’ in achieving successful TC measured by several ‘impact’ indicators. It was also possible to access the extent to which particular ‘determinants and factors’ contributed to the successful TC as a whole and its particular ‘impacts’. The probability of success of territorial cooperation was the highest when TC projects were initiated by NGOs, local or regional government, funding came from own or EU sources, cooperation was based on simple forms of collaboration, and related to culture, economy, tourism, natural environment or physical infrastructure

Structural Equation Model of Successful Territorial Cooperation

Presented study was a part of ESPON TERCO project (European Territorial Cooperation as a Factor of Growth, Jobs and Quality of Life) and was aimed at verifying the hypothesis that territorial cooperation underpins socio-economic development. Based on the literature review a conceptual model of successful territorial cooperation was proposed, where this kind of cooperation was defined as bringing the highest joint socio-economic development to the cooperating territorial units. That theoretical model was verified empirically by structural equation modeling, based on data collected via electronic questionnaires (CAWIs) in 9 cross-border case studies. The results of the SEM analysis positively verified the main hypothesis and provided information about the role of particular ‘determinants and factors’ in achieving successful TC measured by several ‘impact’ indicators. It was also possible to access the extent to which particular ‘determinants and factors’ contributed to the successful TC as a whole and its particular ‘impacts’. The probability of success of territorial cooperation was the highest when TC projects were initiated by NGOs, local or regional government, funding came from own or EU sources, cooperation was based on simple forms of collaboration, and related to culture, economy, tourism, natural environment or physical infrastructure

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

Advancing the contributions of European stakeholders in farming systems to transitions to agroecology

The concept of a ‘just transition’ is gaining traction in international policy discourses. It has particular significance in relation to achieving net zero greenhouse gas emissions and the need for ensuring rights and responsibilities of all actors in transitions to agroecological farming systems. Research plays an important role in accompanying this transformation. It explores pathways for more sustainable and fair food systems, barriers to them being achieved, and where and what risks arise for communities of interest and of place. Researchers and practitioners across levels and sectors were brought together in H2020 projects LIFT and UNISECO using processes of stakeholder engagement. Both projects analysed the perceptions of actors towards agroecological farming, and their active involvement in the transitions required. This article summarises lessons learnt regarding multi‐actor engagement in different participatory settings in both projects, including a Multi‐Actor Platform approach, Q method, DELPHI and Hybrid forum workshops. The interactions involved several hundred actors from 18 countries across Europe. The article reflects on implications of the Covid‐19 pandemic on the processes and effectiveness of multi‐actor engagement, and assessments of the impacts on the empowerment of the actors. The findings are contextualised by contemporary European Union and national policy objectives of tackling climate change, the loss of biodiversity, and inequalities

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