The number of participants in the control group should be twice as many as that of the treatment group to ensure a higher number of matched samples. Consequently, the target number of study participants was 1152. Data from the DCP and the Department of Agriculture and Rural Development were used during the pilot testing of the interview schedule and the sampling of survey participants. As a result, 5 districts and 15 communes were selected from Kien Giang, Soc Trang, and Long An provinces, with three communes being selected from each district. The districts of each province were selected based on the data of the area planted before and after 15 November 2019 and on the ratio of salinity-affected area to total salinity area in the province. Thus, the selected districts have the following characteristics: they are more heavily damaged by salinity relative to other districts in terms of the proportion of affected areas to the total area, and they have farmers who adopt early planting. Within each district, the three most salinity-affected communes were chosen as study sites. Within each commune, the sampling distribution was determined by the proportion of salinity-affected areas to the total salinity-affected area. The sample households were chosen using a two-stage sampling strategy. The first stage involved dividing the households into two groups, namely, early planter households and non-early planter households. In the second stage, hydroponic grow table sample households from each group were selected by simple random sampling. The survey yielded slightly more study participants than the initial target: 412 early planters and 764 non-early planters.
The European Commission,when presenting its legislative proposals for the Common Agricultural Policy post-2020, emphasised the aim to better support the resilience of agricultural systems in the European Union . Phil Hogan, then Commissioner for Agriculture and Rural Development , declared that the CAP would deliver on “genuine subsidiarity for Member States; ensuring a more resilient agricultural sector in Europe; and increasing the environmental and climate ambition of the policy” . This strong emphasis on resilience is based on the concern that the agricultural sector should be supported in responding to current and future economic, societal, and environmental challenges and uncertainties. Building on Meuwissen et al. , we define the resilience of a farming system as its ability to manage change by responding and adjusting itself, while maintaining essential functions. Despite the resonance of the concept of resilience in agricultural policy making circles, less is known about its concrete implications for the designing of public policy. Previous research focused mainly on how to enable resilience at farm level: in individual farms or in farm management , or on individual farmers’ strategies to anticipate or respond to shocks or uncertainties . These studies acknowledge the role of public policies by describing how they, as part of a broader social context, affect e.g. production processes, decisions about diversification, and farmers’ possibilities to adapt strategies, and, therefore, a farm’s resilience. However, a conceptualisation of how policies enable or constrain resilience remains unspecified. The extent to which the CAP and its national implementations support resilience, or even constrain it, is currently unclear. For instance, the CAP relies heavily on various instruments to increase farmers’ income in the short term, but less is known about how these instruments affect resilience in the long term. In order to actually contribute to a resilient agricultural sector, a more comprehensive understanding is required about how the CAP affects the resilience of farming systems. The question of how to develop policies that enable a system’s ability to overcome current and future challenges is not specific to agriculture.As argued by Biesbroek et al. , much of the resilience literature tends to treat policy and governance as black box concepts; the actual causal relations through which policies enable or constrain a system’s resilience remain largely uncharted territory.
This knowledge gap resulted in various efforts to identify resilience-enhancing characteristics of policies . The literature, however, focuses mainly on how the policies themselves can become more resilient; an agreed-upon approach to systematically analyse how policies affect a system’s resilience is still lacking. Furthermore, these characteristics are not fine-tuned to farming systems. To address this research gap, this study analyses whether and how the CAP enables or constrains farming systems’ resilience. We address the research gap by proposing a new heuristic: the Resilience Assessment Tool . This heuristic consists of a set of indicators to assess the capability of a policy to support the resilience of a farming system. The tool was inspired by Gupta et al. ’s Adaptive Capacity Wheel, which allows users to assess the capability of governance institutions and policies to enable society to adapt to climate change. Subsequently, we apply the ResAT to examine the perceived effects of the CAP and its national implementation on the resilience of an intensive arable farming system in De Veenkoloni¨en, the Netherlands. Two focus groups with policymakers and stakeholders were organised to discuss and validate the findings of the ResAT analysis. Finally, we discuss several key reflections that emerge from our analysis. To analyse how policies affect the resilience of the agricultural sector, we chose a farming system as the level of analysis. A farming system is the system hierarchy level above the individual farm: it is a local network of comparable types of farms and other actors that interact formally and informally and are responsible for private and public goods in a specific regional context . Furthermore, farming systems are open systems and their activities are linked to social networks, economic processes, and the agro-ecological context in which the systems operate. Farming systems serve different essential functions for society through the provision of private goods and public goods . However, they may be subject to economic, social, institutional, and environmental challenges that confront the ability of these systems to maintain their functions. These challenges vary from sudden events or shocks to long-term stressors, which both can increase systemic vulnerabilities as well as provide opportunities.
As a next step, we conceptualise resilience in relation to these farming systems. The concept of resilience has become widespread in academic discussions and policy contexts across a diverse set of fields, such as ecology, disaster management, psychology, natural resource management, and agriculture and rural development . Resilience is understood in different ways within these fields. For instance, the understanding that resilience entails the capacity of a system to resist shocks or disturbances with the goal of rapidly returning to a perceived normal is particularly common in disaster management studies . In this respect, key aspects of resilience are a system’s resistance to perturbations and its ability to recover without experiencing change to existing functions afterwards . While this understanding links resilience to the ability to resist shocks and changes in the short-term, other studies, e.g. in the field of rural and agricultural studies, have suggested that resilience also consists of the capacity to adapt, or even transform, in response to external shocks or stresses . For example, Darnhofer highlights that managing a farm’s resilience also includes being capable of dealing with uncertainties through learning and adjusting responses to changing circumstances, and to fundamentally change components of farming systems when these prove dysfunctional. By including change as integral parts of resilience, resilience thinking offers a conceptual lens that accepts that change is omnipresent and often unpredictable in complex systems . Based on this broad understanding of resilience, we build on concepts rooted in social-ecological systems analysis to conceptualise farming system resilience as the system’s capacity to manage and respond to challenges, both foreseeable trends and unexpected events, while maintaining its essential functions of providing private and public goods. We also distinguish between three resilience dimensions , flood tray expressed in three different capacities: Robustness is the capacity of the system to resist external perturbations and to maintain previous levels of functionality, without major changes to internal elements and processes.
Adaptability is the capacity of the system to adjust internal elements and processes in response to changing external circumstances. The system can continue to develop along the original trajectory, while maintaining important functionalities.Transformability is the capacity of the system to change fundamentally, particularly when structural changes in the ecological, economic, or social environment make the existing system untenable to provide important functionalities.Conceptualising resilience through robustness, adaptability, and transformability extends the understanding of resilience beyond only maintaining equilibrium; adjustments and change are also integral to a system’s resilience. Public policies are sets of interrelated decisions that governmental actors take regarding an issue. We follow Howlett ’s conceptualisation of public policy outputs as consisting of goals and instruments. Policy output refers to the direct results of governmental actors’ decision-making processes, which take the form of policy programmes, laws, or regulations. Policy output consists of goals and instruments that are interrelated and operate at different levels of abstraction. Policy goals are the aims and expectations that a policy pursues, and policy instruments are the means or techniques used to achieve these goals . These policy components interact with one another, leading to synergies, conflicts, or trade-offs that result in complex policy configurations with often unclear means-ends relations. This also means that certain policy components can enable the resilience of the system in one area, while constraining it in another area . The challenge for policymakers is then to discover how policy components can generate synergies and avoid trade-offs to support a system’s resilience. The resilience literature has identified various ways in which policies may enable resilience, particularly in the areas of risk and crisis management, resource management, and city planning. B´en´e et al. , for example, showed with their systematic literature review on urban resilience that multilevel or polycentric governance is vital for enhancing resilience.
Huitema et al. and Pahl-Wostl also underline the desirability of polycentric governance and how it enhances knowledge exchange and potentially synergy-enabling adaptations. Other scholars have pointed to the importance of accommodating self-organisation and knowledge networks or the encouragement of learning and experimentation . The topic of resilience has also received attention in the policy literature through questions about how to design policies that are capable of dealing with uncertainties and can support systems to overcome current and future challenges. For instance, Howlett highlighted that agility, improvisation, and flexibility are important policy features to adapt and to deal with surprising or uncertain futures. Likewise, Swanson et al. identified specific characteristics for policies to function under complex, dynamic, and uncertain conditions, such as variation through multiple policies to address the same issue to increase the likelihood of achieving desired outcomes in uncertain times, regular policy review processes to evaluate effectiveness and continuous learning, and pilots to test assumptions relating to emerging issues. Moreover, Daedlow et al. discussed factors that determine the resilience of natural resource governance systems. For instance, they revealed in their case study that external processes of change and disturbances with high uncertainty may prevent decision makers from adapting or transforming the governance system. They showed that the position, influence, and motivation of key decision makers can very much determine the outcome of a reorganisation process of a governance system. Despite these valuable insights, to date, the policy literature concentrates primarily on how to increase the resilience of policies rather than on how policies can improve systems’ resilience. Consequently, a systematic approach to analyse how public policies enable or constrain the three dimensions of resilience of complex systems remains largely uncharted territory. Moreover, there is no specific conceptualisation of how policies enable or constrain the resilience of farming systems. The ResAT is not a classic assessment tool in the sense that it measures the policy’s impact on resilience; instead, it allows for a qualitative policy analysis. We systematically analyse and interpret the policy output and its relation to the indicators for robustness, adaptability, and transformability enabling policies in the case study context. The analysis is based on qualitative content analysis and expert judgement, which requires a clear methodological approach that is systematic and transparent .