Policies and Farming System Resilience

Although Indonesia has recorded good performance in its national economic development, especially in the agriculture sector during the Covid-19 pandemic, the impact of the pandemic on farming and food systems has not been evaluated yet. This study has evaluated the resilience of the two dominant existing farming systems in West Timor, i.e. (i) wetland farming system and (ii) dryland farming system. This research aims to understand the resilience of farming after the Covid-19 pandemic and to develop strategic policies that could be adopted to increase the resilience of the farming system in West Timor. A quantitative analysis using the Structural Equation Modelling (SEM) was employed to evaluate the relationship and impact of the following seven generic aspects: labour movement, sustainability, economy, socio- culture, output markets, input markets, farming system resilience, and 27 reflective indicators. The analysis shows that dryland farming systems are more resilient than wetland farming systems. It might be understood from the size of the regression coefficient, as the impact of exogenous construct variables of the environment, socioculture, input, and output on the resilience of dryland farming systems is more significant than on wetlands. Economic performance rather than labour movement factors will create better resilience of farming systems for wetland or dryland after the Covid-19 pandemic. Finally, the economic recovery process and the ongoing input supply mechanism after the Covid-19 pandemic have increased the resilience of the dryland food system more than the resilience of the wetland farming system.

For improving the sustainability and resilience of EU farming systems, it is important to assess their likely responses to future challenges under future scenarios. In the SURE-Farm project, a five-steps framework was developed to assess the resilience of farming systems. The steps are the following: 1) characterizing the farming system (resilience of what?), 2) identifying the challenges (resilience to what?), 3) identifying the desired functions (resilience for which purpose?), 4) assessing resilience capacities, and 5) assessing resilience attributes. For assessing the resilience of future farming systems, we took the same approach as for current farming systems, with the addition that future challenges were placed in the context of a set of possible future scenarios, (i.e., Eur-Agri-SSP scenarios). We evaluated future resilience in 11 case studies across the EU, using a soft coupling of different qualitative and quantitative approaches. The qualitative approach was FoPIA-SUREFarm 2, a participatory approach in which stakeholders identified critical thresholds for current systems, evaluated expected system performance when these thresholds would be exceeded, envisaged alternative future states of the systems (and their impact on indicators and resilience attributes), as well as strategies to get there. Quantitative approaches included models simulating the behavior of the systems under some specific challenges and scenarios. The models differed in assumptions and aspects of the farming systems described: Ecosystem Service modelling focused on the biophysical level (considering land cover and nitrogen fluxes), AgriPoliS considered, with an agent-based approach, socio-economic processes and interactions within the farming system, and System Dynamics, taking a holistic approach, explored some of the feedback loops mechanisms influencing the systems resilience from both a qualitative and quantitative approach. Each method highlighted different aspects of the farming systems. For each case study, results coming from different methods were discussed and compared. The FoPIA-SURE-Farm 2 assessment highlighted that most farming systems are close to critical thresholds, primarily for system challenges, but also for system indicators and resilience attributes. System indicators related to food production and economic viability were often considered to be close to critical thresholds. The alternative systems proposed by stakeholders are mostly adaptations of the current system and not transformations. In most case studies, both the current and alternative systems are moderately compatible with 'Eur-Agri-SSP1 – Agriculture on sustainable paths’, but little with other Eur-Agri-SSPs’. From the point of view of ecosystem services and nitrogen fluxes, the more resilient case studies are those able to provide multiple services at the same time (e.g., hazelnut cultivations in Italy and vegetable and fruit cultivation in Poland, able to provide good levels of both food production and carbon storage) and those well connected with other neighbouring farming systems (e.g., the Dutch case study receiving manure by the livestock sectors). The System Dynamic simulation (applied quantitatively for the Dutch and French case study) highlighted the need to develop resources that can increase farmers’ flexibility (e.g., access to cheap credit, local research and development, and local market). It also showed that innovation, networks, and cooperation contribute to building resilience against economic disturbances while highlighting the challenges for building resilience to environmental threats. From the application of AgriPoliS to the German case study it was concluded that changes in direct payment schemes not only affect the farm size structure, but also the functions of the farming system itself and therefore its resilience. The report showed complementarity between different methods and, above all, between quantitative and qualitative approaches. Qualitative approaches are needed for interaction with stakeholders, understand perceptions of stakeholders, consider available knowledge on all aspects of the farming system, including social dimensions, and perform a good basis for developing and parameterizing quantitative models. Quantitative methods allow quantifying the consequences of mental models, operationalizing the impact of stresses and strategies to tackle them and help to unveil unintended consequences, but are limited in their reach. Both are needed to assess resilience of farming systems and suggest strategies for improvement and to help stakeholders to wider their views regarding potential challenges and ways to tackle them.

Increased global agricultural output since the 1990s has been largely driven by innovations that raised the efficiency of use of labour, land, capital and other inputs—referred to as total factor productivity (TFP) growth. Yet debates over the future of farming still weigh heavily on models of agricultural land use and socioecological trade-offs along traditional (partial factor productivity) growth paths of ‘intensification’ or ‘extensification’. Overlooking the role of TFP in the evolution of global agriculture not only obscures the changing drivers of productivity growth but also misses vital linkages with agricultural sustainability and farming system resilience. We describe two pathways for growth—technology-based and ecosystem-based—and link these in a heuristic framework that emphasizes sustainability and resilience outcomes in farming systems. Interdisciplinary research is urgently needed to empirically examine the dynamic interplay of TFP growth, farming system sustainability and resilience. Such insights will help to transform TFP growth as metric into actionable efforts on farms and beyond. Since the 1990s, global agricultural output has been driven largely by innovations that raised the efficiency of using labour, land and other inputs, together called total factor productivity (TFP). This Perspective discusses this reality and suggests two pathways for future growth: technology-based and ecosystem-based. Future research on farm-system sustainability and resilience should leverage these options.

Finding pathways to more sustainability and resilience of farming systems requires the avoidance of exceeding critical thresholds and the timely identification of viable alternative system configurations. To serve this purpose, the objective of this paper is to present a participatory, integrated and indicator-based methodology that leads researchers and farming system actors in six steps to a multi-dimensional understanding of sustainability and resilience of farming systems in the future. The methodology includes an assessment of current performance (Step 1), identification of critical thresholds whose exceedance can lead to large and permanent system change (Step 2), impact assessment when critical thresholds are exceeded (Step 3), identification of desired alternative systems and their expected improved performance of sustainability and resilience (Step 4), identification of strategies to realize those alternative systems (Step 5), and an assessment on the compatibility of alternative systems with the developments of exogenous factors as projected in different future scenarios (Step 6). The method is applied in 11 EU farming systems, and the application to extensive sheep production in Huesca, Spain, is presented here, as its problematic situation provides insights for other farming systems. Participants in the participatory workshop indicated that their farming system is very close to a decline or even a collapse. Approaching and exceeding critical thresholds in the social, economic and environmental domain are currently causing a vicious circle that includes low economic returns, low attractiveness of the farming system and abandonment of pasture lands. More sustainable and resilient alternative systems to counteract the current negative system dynamics were proposed by participants: a semi-intensive system primarily aimed at improving production and a high-tech extensive system primarily aimed at providing public goods. Both alternatives place a strong emphasis on the role of technology, but differ in their approach towards grazing, which is reflected in the different strategies that are foreseen to realize those alternatives. Although the high-tech extensive system seems most compatible with a future in which sustainable food production is very important, the semi-intensive system seems a less risky bet as it has on average the best compatibility with multiple future scenarios. Overall, the methodology can be regarded as relatively quick, interactive and interdisciplinary, providing ample information on critical thresholds, current system dynamics and future possibilities. As such, the method enables stakeholders to think and talk about the future of their system, paving the way for improved sustainability and resilience.

SummaryOne of the aims of the post‐2020 Common Agricultural Policy (CAP) is to improve the resilience of Europe's farming systems. The CAP of the budget period 2014–2020, however, has insufficiently supported the resilience of farming systems. The ongoing CAP reform process offers an appropriate opportunity to integrate a broader perspective on resilience in the CAP. We therefore propose a set of policy recommendations on how to improve the capability of the CAP to support more fully the resilience (i.e. robustness, adaptability and transformability) of farming systems in the EU. The policy recommendations are based on a comparative analysis of six national co‐design workshops with stakeholders and a final EU‐level workshop with Brussels‐based experts. We concluded three key lessons about the CAP's influence on resilience: (1) resilience challenges, needs and policy effects are context‐specific; (2) resilience capacities are complementary, but trade‐offs between robustness, adaptability and transformability occur at the level of policies and due to budget competition; (3) there is a need for a coordinated long‐term vision for Europe's agriculture, which is difficult to achieve through the bargaining processes associated with a CAP reform. We propose specific policy recommendations that could contribute to a better balance between policies that support robustness, adaptability and transformability of Europe's farming systems.

The Mediterranean region is expected to be a hotspot for climate change, making the resilience of farming systems a major challenge. Some studies have used quantitative models at the farm scale to analyze the resilience of farming systems but with little involvement of stakeholders. We used a participatory approach with local actors on the Sais plain of Morocco to design possible future states and qualitatively assess the resilience of typical farm types (FTs) experiencing major change. Our approach combined individual interviews of farmers and local actors, mainly public, with participatory collective meetings to identify representative FTs and their performance, project their evolutions and future performance in the face of change, and evaluate their resilience. Performance, defined according to literature, interviews and meetings, included different types of capital, income, yields, markets, support of public policies, and water access. Four FTs were considered: highly irrigated horticulture (FT1), rainfed cereals (FT2), partly irrigated cereal-legumes (FT3), and mostly irrigated fruit-tree/horticulture (FT4). The primary driver for FT2 and FT3 was climate change; for FT1 and FT4, it was limiting access to water resources. Participants designed more diversified systems for all FTs in relation to those changes. Rankings of FT performance did not change between current and future states. Performance did not evolve significantly, but FT4 was seen as the most resilient and FT2 the least. These qualitative results differ somewhat from other studies mobilizing quantitative approaches, but they highlight the potential of local adaptation to limit the impacts of global change on vulnerable agriculture.

State support for financial risk management schemes has been introduced in numerous agricultural policies to enhance farming system resilience in response to increased income fluctuations and partially reduced producer support levels in the agricultural sector. In order to better understand how financialisation of risks can contribute to an actual improvement of specific farming systems’ resilience, this study investigates its effects with regards to dairy farming. Based on an in-depth case study of a dairy system in Northwest Germany, multilayered challenges faced by the farm system are identified, resilience strategies investigated and the role of financial risk management evaluated. In doing so, the resilience assessment framework developed by Meuwissen et al. (2019) is applied in order to analyse the systems’ capacity to resist, adapt or transform in response to external challenges threatening the provision of system’ functions. The results indicate a high relevance of insurances and savings with regards to the system’s robustness against short-term shocks. However, to address the various long-term pressures, resilience-enhancing attributes that increase the system’s capacity to adapt and transform would need to be strengthened. In particular, more cooperation and knowledge transfer beyond system boundaries could contribute to a holistic risk management allowing for improved farming system resilience.

A framework to assess the resilience of farming systems

The agricultural sector plays a strategic role in the Tunisian economy, particularly in rural areas. Resilience and adaptation to climate change are the main challenges facing this sector. This paper aims to analyze climate change resilience of agricultural production systems in Tunisian semi-arid areas and to propose options for policy interventions. A path Structural Equation Model (SEM) was used to predict the resilience of these systems using the partial least squares method (PLS). Results show that farming systems in Tunisian semi-arid areas remain threatened against negative impact of climate change since 80% of farms in the sample have shown low resilience levels. The most important determinants of agricultural systems' resilience are farmers' income and access to food, adaptive capacity, and access to productive and non-productive assets. Results indicate also that integrated systems, income diversification, along with cooperation and collective action are the key options to enhance resilience of rural households and farming systems. It is recommended to raise awareness of stakeholders and decision-makers about climate change challenges and to develop integrated approaches to better engaging with local stakeholders and institutions in adaptation programs and strategies development.

Actors and their roles for improving resilience of farming systems in Europe

This Special Issue showcases findings from the SURE-Farm research project which aims to assess the resilience and sustainability of farming systems in Europe. The call for greater resilience responds to the accumulating economic, environmental, institutional and social challenges facing Europe's agriculture. Since the Covid-19 pandemic, the need for enhanced re-silience has become an overarching guiding principle of EU policymaking. But what exactly is resilience and how can it be enhanced? How can farming systems prepare for different and often simultaneous types of shocks and stresses, for unexpected and even unknown events? The articles in this Special Issue distinguish three resilience capacities: for some shocks and systems robustness (‘bouncing back’) is adequate, but other circumstances require adaptability and transformability (anticipation, quick learning and change). Putting these capacities central, each article addresses key questions such as: whether current capacities match the resilience needs; which characteristics of a system can enhance resilience; how an enabling environment affects resilience; whether current governance systems constrain resilience; and which actors can actually influence and build resilience capacities. Promisingly, the contributions identify various pathways to enhance resilience. However, many of our suggestions require substantial change compared to current practices and policies. Meuwissen et al. conclude that resilience strategies tend to focus on the farm level, while farming systems include many other actors that also need to actively engage. Reidsma et al. find that resilience strategies in the past were often geared too much towards increasing the profitability of farming systems, and tended to neglect the coupling of agricultural production with local institutions, natural resources, and a facilitating infrastructure for innovation. Spiegel et al. demonstrate the importance of learning as part of resilience-enhancing strategies. Several articles derive specific recommendations to change public policies towards resilience – probably resonating with farmers’ perception that current policies are inadequate (Nicolas-Davies et al.). Buitenhuis et al. recommend policies that could contribute to a better balance between support for robustness, adaptability and transformability of Europe's farming systems. In the ‘Point de Vue’ article Mathijs and Wauters argue similarly that public policies play key roles in determining the resilience of farming systems and should invest more in foresight and resilience structures. Current policies towards addressing the ‘young farmer problem’ are considered to be inadequate. Coopmans et al. propose that more attention is devoted to the stages preceding farm take-over, during which possible entrants develop a ‘successor identity’. On a similar theme, Pitson et al. call for greater focus on increasing the human capital base of the agricultural sector through training, trans-sectoral and trans-regional mobility – including the provision of adequate infrastructure in rural areas to attract a young skilled labour force. The importance of attracting ‘young potential’ is visualised by Slijper in the Parlons Graphiques which illustrates the predominance of negative net migration rates from rural areas in Europe. Vroege et al. stress that the policy environment should more fully enable agricultural insurance innovations to underpin risk management in a rapidly changing global environment. If all of the above issues are capable of being addressed, can resilience of agricultural systems really be enhanced? Or will the prevailing governance systems facilitate unsustainable exploitation of socio-economic and ecological systems that fundamentally undermine their resilience? There are reasons for optimism. Firstly, our research found much spirit for change – and calls for more long-term vision and courage (see for example ‘frequent question’ Q4, Meuwissen et al.). Secondly, the systematic analysis of the multiple components contributing to resilience has enabled us to develop a better understanding of processes of change in agri-food systems, the need to develop greater resilience in Europe's farming systems and the priority areas to be addressed. We record our thanks for the comments of external reviewers of all articles in this Special Issue and to the editorial team for their expert guidance and recommendations. We wish you an inspiring read. The ‘Science talks’ video about this special issue is available at: www.wur.nl/en/project/Resilient-Farming-Systems.html. “Resilience is more than robustness; learning and change are essential.” “La résilience est davantage que la robustesse; l'apprentissage et le changement sont essentiels.” “Resilienz bedeutet mehr als nur Stabilität, denn Lernen und Veränderung sind in diesem Zusammenhang von wesentlicher Bedeutung.” This research was funded by the European Union's Horizon 2020 research and innovation programme. The content of this issue does not necessarily reflect the official opinion of the European Union. Responsibility for the information and views expressed herein lies entirely with the authors. Miranda Meuwissen Peter H. Feindt

The European Commission has emphasised that a more resilient farming sector is required to better respond to current and future economic, societal, and environmental challenges. Consequently, supporting resilience has become an important aim of the proposals of the Common Agricultural Policy (CAP) post-2020. However, interactions between public policies and resilience outcomes have hardly been researched in-depth. This study analyses whether and how the CAP and its national implementations enable or constrain the resilience of farming systems. For this purpose, we introduce the Resilience Assessment Tool (ResAT): a heuristic that conceptualises how policy outputs enable or constrain farming systems’ resilience. The tool consists of three dimensions (robustness, adaptability, and transformability) with four indicators each. The ResAT is applied to a Dutch case study: the intensive arable farming system in De Veenkoloniën. We conclude that the CAP and its national implementation strongly support the robustness of this farming system, but that the policy enables adaptability much less and rather constrains transformability. The article ends with a reflection on how the application of the ResAT allows for new insights into how EU agricultural policies influence the resilience of farming systems.

With the concept of resilience being increasingly applied in farming systems research, there is general agreement that the resilience theory should be supported by sound assessment methodologies. Yet, in the extant literature, definitions and measures of resilience as a system outcome, a system capability or a process are often conflated, causing conceptual and methodological ambiguities. To overcome these limitations, here we systematically review the literature on assessing the resilience of farming systems and identify patterns, including similarities and differences in underpinning theories and in methodologies. We analyzed 123 papers on how the resilience of farming systems is conceptualized and assessed. From these papers, we identified four theoretical positions (“lenses”): traditional, vulnerability, capacities, and agroecology. These lenses differ and complement each other in terms of the outcome definition of resilience (stability, transformation, and reduced vulnerability), the prominent components of resilience (capacities, practices, and resources), and the perturbations that farming systems are exposed to (shocks, exposure, and sensitivity). Collectively, these lenses offer a novel causality framework with a complementary set of causal links between perturbations, components, and outcomes. This paper suggests for the first time that resilience assessment methodologies can be further developed by drawing from the strengths and complementarities of the different perspectives. Hence, this paper identifies five design choices that need to be made in order to rigorously assess the resilience of farming systems. These concern the choice of system traits, of perturbations, of type of resilience, of contributing factors, and of resilience outcomes that will be considered.

Climate change poses a profound risk to farming activities, threatening agricultural productivity and livelihoods through increasing temperatures, erratic rainfall patterns, and frequent extreme weather events. These challenges raise critical questions about the resilience of farming systems, particularly under diverse socio-economic and environmental pressures. Resilience must be understood in terms of both system-level dynamics and individual actors, whose decision-making processes exhibit significant heterogeneity. Farmers’ unique preferences, perceptions, and strategies necessitate well-defined policies that consider individual behaviors to enhance resilience. Agent-based modeling (ABM) offers a robust framework to address these challenges by explicitly representing the diversity of actors and their behaviors while simulating the impacts of climate threats and policy interventions on farming systems.This study adopts a novel agent-based framework, ABNexus, designed to analyze the resilience of the Adda River farming system in northern Italy. ABNexus integrates an ABM with a distributed-parameter water balance crop yield model, IdrAgra, to provide high spatial resolution and behavioral flexibility. The model uses survey data collected from 460 local farms to calibrate farmer profiles, capturing the diversity of decision-making processes based on farm characteristics, climate change awareness, perceived impacts, and adaptation strategies. Farmers were categorized into three distinct clusters—risk-averse, risk-neutral, and risk-taker— reflecting behavioral traits that influence their decision-making criteria within the ABM framework. We also implemented different behavioral modes, ranging from profit maximization under perfect foresight to differentiated risk aversion under uncertainty, and assessed their alignment with observed decisions over the past 20 years.Building upon this validated framework, we assessed the resilience of the Adda River basin farming system under various climate change scenarios, such as an increased frequency of severe drought years. We further explored the impact of targeted policy interventions, such as subsidies for the adoption of water-efficient irrigation technologies.Our results highlight the importance of incorporating behavioral heterogeneity in agricultural modeling. Historical analysis revealed that behavioral assumptions significantly influence the alignment of simulated decisions with real-world observations, underscoring the need for detailed behavioral representations. Preliminary findings from scenario testing indicate that targeted subsidies for irrigation technology adoption can enhance system resilience. However, the magnitude and distribution of these benefits vary across different behavioral assumptions, reflecting farmers’ diverse responses to policy interventions. This research provides valuable insights into the complex interplay between human behavior, climate change, and agricultural system resilience. The ABNexus framework offers a valuable tool for exploring the potential impacts of various climate change scenarios and evaluating the effectiveness of policy interventions.

According to stakeholders, many European farming systems are close to critical thresholds regarding the challenges they face (e.g., droughts, price declines), functions they deliver (e.g., economic viability, biodiversity and habitat) and attributes required for resilience (e.g., social self-organization). To accelerate a transition process towards sustainable and resilient agriculture, this study aimed to identify actor-supported alternative systems across 10 European farming systems, and to identify associated future strategies that contribute to strengthening resilience attributes, using a backcasting approach. This paper synthesizes 1) the participatory identification of desired alternative systems and their expected performance on sustainability and resilience, 2) the participatory identification of strategies to realize those alternative systems, 3) the contribution of identified past and future strategies to 22 resilience attributes, and 4) the compatibility of the status quo and alternative systems with different future scenarios, the Eur-Agri-SSPs. Many identified alternative systems emphasized technology, diversification and organic and/or nature friendly farming, while in some farming systems also a focus on intensification, specialization, better product valorization, collaboration, or creating an attractive countryside could increase sustainability and resilience. Low economic viability limited farming system actors to pay attention to environmental and social functions. Further, most alternative systems were adaptations rather than transformations. Many stakeholders had difficulty to envisage systems without the main products (e.g., starch potato in NL-Arable, sheep in ES-Sheep and hazelnut in IT-Hazelnut), but in few cases transformative systems were designed (e.g. local organic farming in PL-Horticulture and RO-Mixed). Sustainability and resilience can be enhanced when alternative systems and strategies are combined, thereby improving multiple functions and attributes at once. In particular, production and legislation need to be coupled to local and natural capital. Identified alternative systems seem only compatible with Eur-Agri-SSP1 ‘agriculture on sustainable paths’. This requires policies at EU-level that stimulate macro-level social, institutional, economic, and technological developments that strengthen this scenario. We conclude that to get stakeholders along, incremental adaptation rather than radical transformation should be sought. The identification of alternative systems is only a start for the transition process. Their analysis, along with the strategies identified, need to trigger the involvement of farmers and other ‘enabling actors’ inside and outside the farming systems to make a change, and where needed, systems can evolve into more transformative systems.