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This chapter assessed sustainability and resilience of eleven farming systems in their current situation, as well as in hypothetical future systems, using qualitative and quantitative methods. The assessment shows that current farming systems address sustainability dimensions in an unbalanced way and are characterized by poor resilience. Future resilient systems are imagined to promote environmental and social functions in the long term.

This chapter aims to formulate principles and recommendations for an enabling environment that fosters resilience of farming systems. Principles have been derived from archetypical patterns identified in the various case studies on how actions in the enabling environment tend to constrain the resilience of farming systems.

The Welfare Quality® consortium has developed and proposed standard protocols for monitoring farm animal welfare. The uptake of the dairy cattle protocol has been below expectation, however, and it has been criticized for the variable quality of the welfare measures and for a limited number of measures having a disproportionally large effect on the integrated welfare categorization. Aiming for a wide uptake by the milk industry, we revised and simplified the Welfare Quality® protocol into a user-friendly tool for cost- and time-efficient on-farm monitoring of dairy cattle welfare with a minimal number of key animal-based measures that are aggregated into a continuous (and thus discriminative) welfare index (WI). The inevitable subjective decisions were based upon expert opinion, as considerable expertise about cattle welfare issues and about the interpretation, importance, and validity of the welfare measures was deemed essential. The WI is calculated as the sum of the severity score (i.e., how severely a welfare problem affects cow welfare) multiplied with the herd prevalence for each measure. The selection of measures (lameness, leanness, mortality, hairless patches, lesions/swellings, somatic cell count) and their severity scores were based on expert surveys (14-17 trained users of the Welfare Quality® cattle protocol). The prevalence of these welfare measures was assessed in 491 European herds. Experts allocated a welfare score (from 0 to 100) to 12 focus herds for which the prevalence of each welfare measure was benchmarked against all 491 herds. Quadratic models indicated a high correspondence between these subjective scores and the WI (R 2 = 0.91). The WI allows both numerical (0-100) as a qualitative ("not classified" to "excellent") evaluation of welfare. Although it is sensitive to those welfare issues that most adversely affect cattle welfare (as identified by EFSA), the WI should be accompanied with a disclaimer that lists adverse or favorable effects

The Flemish beef sector faces growing economic uncertainty and societal criticisms. Agroecology is regularly proposed as an alternative development pathway, yet what this exactly means in this context is largely unexplored. This doctoral research aimed at investigating the relevance of agroecology to beef farming in Flanders. By gathering and analyzing data from a diverse group of Flemish beef farmers with both qualitative and quantitative methods, this dissertation renders agroecology as a practice more concrete conceptually in this context. The analysis of these farmers accounts also served to lay bare important ambiguities and inadequacies within agroecological thought with regard to the transformative potential of these agroecological practices, farmers, and the systems they construct. Out of this dialogue between agroecology and farmers thus emerged a more general societal reflection that advances contemporary ideas and practices to transform food systems, (AGRO - Sciences agronomiques et ingénierie biologique) -- UCL, 2021

In this paper we reflect on the effectiveness of cognitive mapping (CMing) as a method to study farm functioning in its complexity and its diverse forms in the framework of our own experiment with a diverse group of Flemish beef farmers. With a structured direct elicitation method we gathered 30 CMs. We analyzed the content of these maps both qualitatively and quantitatively. The central role of the concept “Income” in most maps indicated a shared concern for economic security. Further, the CMs indicated that farmers dealt with this shared social reality differently, as the relationships included in their maps referred to different functional processes relating to revenue streams, marketing strategies, investment decisions, dependence on production inputs, on-farm resource management, and personal well-being. With a clustering algorithm we grouped farmers based on the relationships in their maps, which allowed us to trace some of the broader patterns within the data, such as the existence of more business- and investment-minded farmers, in contrast to farmers focused on their quality of life, and animal production-oriented in contrast to marketing-oriented farmers. Taking into account farmers’ comments, we find that the applied methods had limited capability to classify farmers based on their perspectives on farming. Still, the system presentations proved useful to study what aspects farmers were working on or towards, and how these aspects may actually fit together as a whole. CMing was therefore mostly effective in exploring farm functioning in its complexity, and less so in exploring farm functioning in its diversity.

Agroecology is increasingly recognized as a valuable perspective to face the sustainability challenges of contemporary foods systems. Yet case-comparisons based on a holistic assessment of actual farmer practices have been lacking. In this paper, we seek to identify the different farming models underlying the sets of practices of Flemish beef farmers (Belgium). For this, we rely on 37 accounts of a diverse group of Flemish beef farmers. Their practices were gathered through semi-structured interviews. These practices were categorized along 36 Pathways of Action to pursue 13 agroecological principles, identified in research published earlier. To compare how and to what extent each farmer is pursuing these principles, we turned this qualitative information into sets of indicator scores. With Archetypal Analysis, we identified three farming models underlying their diverse pursuits of agroecological principles: one farming model represents seven conventional farmers who name a bare minimum of practices contributing to agroecology, and two models representing farmers that do integrate elements of agroecology. Conceptually, the second farming model, which represents nine direct selling farmers, eight of them organic, corresponds with a low-input, low-capital, but knowledge intensive model, embedded within alternative commercial and social networks, which actively seeks to become independent from regime institutions. The third farming model represents five mostly whole-selling conventional beef farmers that find advantages within the mainstream market environment. It overlaps with a number of practices related to the techno-productive dimension of agroecology with the second model, as far as these maintain or increase productivity, and are compatible with the expectations of value-chain actors. These results provide an empirical basis for concepts such as “peasant farming” and “sustainable intensification” to understand the diverging translation of agroecological principle

Dataset used as input to the model by Pinsard et al (2021) and results published in D5.5 of the SURE-Farm project.

The Welfare Quality® consortium has developed and proposed standard protocols for monitoring farm animal welfare. The uptake of the dairy cattle protocol has been below expectation, however, and it has been criticized for the variable quality of the welfare measures and for a limited number of measures having a disproportionally large effect on the integrated welfare categorization. Aiming for a wide uptake by the milk industry, we revised and simplified the Welfare Quality® protocol into a user-friendly tool for cost- and time-efficient on-farm monitoring of dairy cattle welfare with a minimal number of key animal-based measures that are aggregated into a continuous (and thus discriminative) welfare index (WI). The inevitable subjective decisions were based upon expert opinion, as considerable expertise about cattle welfare issues and about the interpretation, importance, and validity of the welfare measures was deemed essential. The WI is calculated as the sum of the severity score (i.e., how severely a welfare problem affects cow welfare) multiplied with the herd prevalence for each measure. The selection of measures (lameness, leanness, mortality, hairless patches, lesions/swellings, somatic cell count) and their severity scores were based on expert surveys (14–17 trained users of the Welfare Quality® cattle protocol). The prevalence of these welfare measures was assessed in 491 European herds. Experts allocated a welfare score (from 0 to 100) to 12 focus herds for which the prevalence of each welfare measure was benchmarked against all 491 herds. Quadratic models indicated a high correspondence between these subjective scores and the WI (R2 = 0.91). The WI allows both numerical (0–100) as a qualitative (“not classified” to “excellent”) evaluation of welfare. Although it is sensitive to those welfare issues that most adversely affect cattle welfare (as identified by EFSA), the WI should be accompanied with a disclaimer that lists adverse or favorab

Farming systems in Europe are experiencing multiple stresses and shocks that may push systems beyond critical thresholds after which system change is expected to occur. These critical thresholds may lie in the economic, environmental, social and institutional domain. In this paper we take a participatory approach with involvement of farming system stakeholders to assess the presence of critical thresholds in 11 European farming systems, and the potential consequence of surpassing those with regard to system sustainability and resilience. First, critical thresholds of the main challenges, key system variables and their interactions in the studied farming systems were assessed. Second, participants assessed the potential developments of the key system variables in case critical thresholds for main system challenges would be exceeded. All studied systems were perceived to be close, at or beyond at least one identified critical threshold. Stakeholders were particularly worried about economic viability and food production levels. Moreover, critical thresholds were perceived to interact across system levels (field, farm, farming system) and domains (social, economic, environmental), with low economic viability leading to lower attractiveness of the farming system, and in some farming systems making it hard to maintain natural resources and biodiversity. Overall, a decline in performance of all key system variables was expected by workshop participants in case critical thresholds would be exceeded. For instance, a decline in the attractiveness of the area and a lower maintenance of natural resources and biodiversity. Our research shows that concern for exceeding critical thresholds is justified and that thresholds need to be studied while considering system variables at field, farm and farming system level across the social, economic and environmental domains. For instance, economic variables at farm level (e.g. income) seem important to detect whether a system is approach

The challenges faced by agricultural systems call for an advance in risk management (RM) assessments. This research identifies and discusses potential improvements to RM across 11 European Union (EU) farming systems (FS). The paper proposes a comprehensive, participatory approach that accounts for multi-stakeholder perspectives relying on 11 focus groups for brainstorming and gathering suggestions to improve RM. Data analysis is based on content analysis and coding of suggested improvements, and their assessment through the lenses of main challenges faced, farms’ flexibility, and dependence on subsidies. First, the results show that necessary improvements differ depending on whether they have their origin in sudden shocks or long-term pressures. Second, farm dependence on direct payments determines a stronger need to improve financial instruments, whereas farm flexibility suggests a need for more accessible and tailored tools for low-flexibility FS, and increased know-what and know-how for high-flexibility FS. Third, our findings indicate a potential for extending stakeholder involvement in RM to new or unconventional roles. Underlying specific improvements, the paper suggests and discusses three main avenues to improve RM as a whole: i) a developed learning and knowledge network; ii) new forms of collaboration; and iii) integrated financial and policy instruments.

In the face of longstanding social and technological trends, the application of agroecological insights at beef farms in Flanders may at first seem a curious proposition. We found, however, that beef farmers pursue agroecological principles through an impressive diversity of practices in this context. In 37 semi-structured interviews, we asked farmers how they put into practice a set of principles which covers many themes addressed in agroecological literature. Inspired by a grounded theory approach, but also based on literature and consultation of fellow researchers, we conceptualized for each principle distinctive pathways of action to categorize relevant practices. By documenting farmers’ practices, we show that an agronomic interpretation of agroecology as a practice obfuscates the many ways farmers can contribute to the social dimensions of agroecology too, which also problematizes those food systems approaches that undervalue the farmers’ agency in changing their social context themselves. This grounded conceptual framework may be used to further assess how each beef farmer addresses these different principles together in practice. Given these results and perspectives, we contend that empirical inquiries such as these are instrumental in maintaining the connection between agroecological theory and practice, allowing both to move dialectically forward.

everal authors propose agroecology as a more sustainable development path for livestock systems in temperate regions, yet the relevance of agroecology to the Flemish beefsector remains largely unexplored. In order to identify what actions are taken to pursue agroecological principles by what kind of farmers and on what kind of farms and to explain why this is so, we have developed a mixed methods research approach. We collectmental models of farm functioning through direct elicitation of cognitive maps with individual farmers. We seek to complement these with quantitative measures based onan accompanying structured farm questionnaireand characterizehow and to what extent agroecological principles are pursued at the farm levelin semi-structured interviews. From the more complete but still empirical account of reality generated by this triple approach, we identify patterns to corroboratea grounded theory on what sustains or limits the implementation of agroecological principles at Flemish beef farms. We extensively discuss the advantages and limits of this method of data gathering, processing and analysis from a critical realist perspective