Recurring topics were the need for shorter value chains, more fairness towards farmers, and less dependence on migrant workers. However, we observed limited adaptive and no transformative responses. This might betray a general orientation towards robustness and attempts to avoid larger changes to the modes of operation. Similar to the results of other studies , our case studies found limited impact 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. While this constitutes a significant achievement, considerations during the crisis were almost exclusively limited to the productive functions of the system.Moreover, actors in the farming systems and the enabling environment generally focused on the immediate issues and gave little consideration to long-term implications and challenges. Hence, adaptive or transformative capacities were much less on display than coping capacities. The comparison of pre-Covid findings and the Covid-19 crisis mostly showed similarities. For instance, if challenges already loomed before the crisis, they persisted during the crisis, sometimes even to a larger extent.
Also, the focus on coping capacities was already visible before the crisis. In addition, led grow lights the comparison confirmed the eminent role of resilience attributes. For instance, in cases with high connectedness and diversity we found that these system characteristics contributed significantly to the ability to deal with the crisis. However, the findings during the crisis did not entirely reproduce pre-Covid findings, i.e. some cases experienced other challenges, were able to mobilise more responsive capacities than expected, or showed that already existing connectedness did not lead to adequate actions during the crisis. This illustrates the latent, multi-faceted and dynamic nature of resilience. The data only capture short-term responses to the immediate shock of the first wave of the pandemic and the ensuing restrictions. For instance, we did not assess whether online platforms were sustained. Experiences from later lockdowns during the second and third wave of the Covid-19 pandemic indicate that ‘many had to invent the wheel again’. This resonates with the observation that despite a long list of discussed topics, farming system actors did not use the crisis as a window to trigger more structural change. The only exception in our sample – the prohibition of subcontracting in German slaughterhouses – was forced upon the industry by the Ministry of Labour Affairs, which enabled a change that most observers felt was long due. More than one year into the crisis it becomes clear that the short-term shock evolves into long-term stresses, in particular at the macro-economic level of unemployment, public and private debt and reduced purchasing power. Sectors that are particularly affected also lose valuable resources, from skilled labour to missing investments and interrupted social and economic network connections.
It is plausible that the experience of labour shortages and the importance of digital platforms in developing coping strategies will accelerate trends towards automation and digitalization in the food and agricultural sector as in the general economy. The findings have important implications for policy making. First, the analysis demonstrates a need to strengthen anticipatory capacities at all levels, in particular the ability to recognise signals of impending threats, whether they are short-term or long-term . Second, the actors’ reflections in our case studies mostly betrayed a questioning of transnational value chains. Policy makers need to discuss openly whether regional and short value chains are indeed generally more resilient and should therefore become a policy priority. Third, the importance of resilience attributes iterates that system design matters and, thus, that being impacted by a crisis is not ‘just a matter of bad luck’. It needs to be discussed how resilience attributes, such as connectedness in value chains and diversity, can become a more integral part of policy design. Fourth, the convergence of pre-Covid and crisis findings demonstrates that the systematic resilience assessment of farming systems points at system vulnerabilities. This knowledge can directly feed into stress tests of food systems. Fifth, the Covid-19 crisis is likely to reinforce concerns about future pandemics from zoonosis and to raise awareness of the interdependence of animal, plant, environmental and human health. From a resilience perspective, such public health issues create system vulnerabilities that might require a transformation, in particular of animal-based farming systems. At the same time, our analysis indicates that the transformative capacity of many farming systems needs to be actively enhanced and stimulated through an enabling environment. This includes the provision of specific resources for a desired transition and formal and informal institutional arrangements that provide a clear sense of direction and that enable rather than impede transformations that are necessary to maintain public goods and services.
An important question for future research is 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. Another task for research is the development of a systematic understanding how short-term crisis interventions to secure the provision of private goods can synergetically support transformations that are needed to address the broad range of challenges to public goods . Intensive farming practices produce cheap food, but are also criticised for impairing animal welfare, and for contributing to climate change, biodiversity loss, poor air quality, soil degradation, stench and the risk of zoonoses . Policy makers and citizens call for alternative, demand-oriented, and less intensive farming strategies, which generate a higher income for farmers and decrease the negative externalities of production . Farmers’ strategic decisions are done with regards to market integration, e.g., enlarge to stay competitive in the international market, or produce for smaller demand-oriented markets like organic. Yet, there has often been a mismatch between, on the one hand, societal and political preferences towards alternative farming strategies1 like organic, and on the other hand, observed farmer behaviour. In the past, implemented policies had unintended consequences. In the Dutch pork sector, for example, a governmental subsidy for pig farmers to convert to the organic market introduced around the year 2000 resulted in a higher increase in organic supply than the anticipated increase in demand for organic pork meat.
Excess supply resulted in dropped farm gate prices, pressure on organic farmers’ income, and a damaged reputation of organic farming as a good alternative to conventional among conventional pig farmers . In addition, while organic farming is generally seen by citizens and policy-makers as a viable alternative to conventional farming, farmers feel peer pressure to remain conventional or to defend their choice for alternative farming strategies like organic towards their peers . This shows a friction between societal preferences and farmer dynamics. In order to design an effective support strategy for alternative farming strategies, better understanding of the diffusion of alternative farming strategies is needed, in particular effects of market price dynamics and social interaction among farmers. Pig farmer decision-making is related to many factors, which can roughly be grouped into personal, contextual, and social factors . Personal factors that are associated with a higher chance to invest in stables in general are younger age and having a successor.Personal factors that are associated with investments in higher animal welfare or more sustainable stables are a positive attitude towards the alternative , higher innovativeness , and an idealistic farming style . Some of these factors are relatively static, i.e. a pig farmer’s innovativeness and a farmer’s farming style , while other factors are dynamic, i.e. age and attitudes.Contextual factors that influence pig farmers’ decision-making are the farmers’ investment rhythm and farm size. Farmers’ investment rhythm is determined by the useful life of an asset, such as the time that it takes for a stable to be depreciated, and the farmer’s opportunity rhythm to make a long-term change on his farm determined partly by the availability of a successor.
Farmers take into account their farm size as follows: the larger the size the more additional supply from the farm would affect the elastic organic market price; and therefore farmers with a large farm do not see organic as a viable alternative . Finally, social factors that influence investment decisions are norms, i.e. the behaviour and opinions of peers that can influence behaviour, and the status of farmers within reference groups. In a game environment, social interactions have shown to influence farmers’ strategic investments through opinion leadership . Also, in a study on the adoption of an alternative housing systems for sows, i.e. group housing instead of individual crates, those farmers who did not yet convert felt less peer pressure . The Social Identity Approach relates social interaction to behaviour change, through the social dimension of a person’s self-concept. The main idea behind the Social Identity Approach is that humans have a universal drive to evaluate their opinions and attitudes to increase their self-esteem and/or confidence and status as a group member . Individuals within a group are motivated to act according to the norms associated with being a member of the group,vertical grow system and disagreement in opinion or attitude between in-group members can result in attempts to reduce the disagreement through social influence . The Social Identity Approach states that the level of influence is based on similarity between self and other, i.e. whether they are in-group or out-group members; the similarity of the situational context between self and other; the status of oneself and the other within the group, i.e. the direction of influence; and the level of identification with the in-group . To understand and model influence between farmers, it is, therefore, important to know about similarity in person, situational context, and what gives status within a certain reference group. To identify Dutch pig farmers’ reference groups in the context of organic market conversion, we looked at previous findings and distinguish four reference groups. As shown above, pig farmers take into account their farm size when considering conversion to an added-value market . Therefore, the first reference group consists of farmers who are similar in farm size. Second, organic and conventional farmers opposed each other’s’ practices in the past . Therefore, the second reference group consists of farmers producing for the same market. Third, previous research identified three farming styles that have been relatively stable over time in the Dutch pig farmer population: idealists, craftsmen and entrepreneurs.
They differ in their definition of ‘being a good farmer’ and in status symbols, those factors that give farmers a high status within their farming style reference group . Idealists see pig farming as a way to earn a living instead of a way to maximise profits, and they like to keep investments low . In addition, they value farming methods that incorporate the intrinsic needs of animals into farm design and management. They oppose conventional farming methods that are harmful to animal welfare and think that behaviour of conventional farmers contributes to current societal criticism regarding the Dutch pig sector . Both craftsmen and entrepreneurs opt for maximising profits instead of maintaining a livelihood . Craftsmen gain profits through high productivity, e.g. intensification through increasing litter size and/or daily growth, while entrepreneurs optimise farm management, farm scale and market integration . The latter two oppose the idealistic worldview. Therefore, the third reference group consists of farmers with a similar farming style. Finally, innovative farmers, as opposed to conservative farmers, are more open to new ideas and alternative investments as described above. We, therefore, assume in the remainder of this article that farmers who are more innovative have a different reference group than their conservative colleagues: conservative farmers’ reference groups are similar farmers , while innovative farmers’ reference group are farmers who are higher in status . Therefore, the fourth reference group consists of farmers who are higher in status according to one’s own farming style. For example, the reference group of innovative farmers with an entrepreneurial farming style are all farmers who earn a higher income than themselves regardless of farming style, farm size or market. This will be further outlined under ‘interaction mechanism’ below.