Suchergebnisse

An institutional and socio-economic environment that fosters resilience is crucial for the future of EU farming systems. SURE-Farm has integrated much of its previous work into a set of 6 key principles for a resilience enabling environment. These are (1) to use resources to help the FS to deal with a shock only to buy time while working on structural solutions; (2) to devote enough resources to building anticipating and responsive capacities when shocks happen; (3) to detect long term trends and their potential impact on the FS; (4) to foster a diversity of potential options; (5) to develop a sufficient degree of ambidexterity; and (6) to do in-depth analysis of root causes of challenges and the FS's vulnerability to them. Implementing these principles into concrete actions and strategies requires social learning and concerted efforts by all actors involved. ; en; EU; contact: miranda.meuwissen@wur.nl

Die europäische Landwirtschaft, wie auch die Wirtschaft insgesamt, erwartet in den kommenden Jahrzehnten erhebliche demographische Veränderungen, die vor allem den Arbeitsmarkt betreffen. Die Generation der Babyboomer wird in den nächsten 10 bis 15 Jahren in den Ruhestand treten, während die nachfolgenden jüngeren Generationen zahlenmäßig wesentlich kleiner sind. Das gilt vor allem für ländliche, wirtschaftsschwache Regionen. Dementsprechend wird der Agrarsektor mit anderen Sektoren in ländlichen Regionen und städtischen Gebieten, die oft attraktivere Berufsaussichten bieten, in Konkurrenz um den relativ geringen Nachwuchs stehen. Vor diesem Hintergrund erarbeitet das SURE-Farm-Projekt Grundlagen zum besseren Verständnis der Nachhaltigkeit und Resilienz der europäischen Agrarsysteme. Besondere Beachtung finden dabei die Herausforderungen landwirtschaftlicher Betriebe im Zusammenhang mit demografischen Prozessen und der Frage, was dies für den Strukturwandel bedeutet. Dieser Policy Brief zielt darauf ab, die Erkenntnisse des SUREFarm Projekts zum Generationswechsel landwirtschaftlicher Betriebe mit politischen Optionen zu verknüpfen, die resiliente landwirtschaftliche Strukturen ermöglichen. ; EU; BE; DE; de; contact: miranda.meuwissen@wur.nl

Resilience of the agricultural sector is an important aim of the Common Agricultural Policy (CAP). Most often, resilience is focused on stimulating robustness, with policy and market instruments aimed at maintaining the stability of the farm business. However, a group of European scientists argues that this is too narrow a way of looking at resilience. They state that while robustness contributes to agricultural development, the current higher risk environment also requires other types of capacity in food and agribusiness: namely adaptability and transformability. ; EU; en; contact: miranda.meuwissen@wur.nl

International trade agreements and reforms of the European Common Agricultural Policy increase the importance of agricultural risk management as a means to stabilise farm incomes. 'Income stabilisation in European agriculture' addresses farm income and risk management issues from various perspectives. A cohesive work is brought together on historic income data, quantitative analyses of future policy scenarios, actual farmers' perceptions and an updated view on various risk management instruments. In-depth analyses focus on Germany, Hungary, the Netherlands, Poland and Spain. Overall findings are synthesised in policy recommendations for agricultural risk management in European agriculture. For academia, this publication brings together an interesting variety of quantitative and qualitative methods to understand and interpret risk management concepts in agriculture. For public and private stakeholders analyses and reflections can be used in debating the domain of policy reforms, risk exposure and risk management in European agriculture

BACKGROUND: Illegal use of fipronil as an insecticide in 2017 has caused substantial damage to Dutch laying hen farms. We assessed how the fipronil crisis has affected the financial performance of affected farms as well as unaffected farms. While affected farms faced culling their flocks and lost revenue, unaffected farms benefitted from temporary high egg prices. METHODS: A three-step normative modelling approach is taken using financial statements and a partial budget. The estimations are for a 50,000 laying hen farm facing the fipronil crisis for 5 months. First, a baseline is created by generating an income statement of this laying hen farm representing a 'normal year'. Second, incremental costs and revenue as a result of the fipronil crisis are estimated. Third, the baseline income statement is updated with the outcomes of the partial budget. This results in two additional income statements that report the net operating result of this farm being unaffected and affected by the fipronil crisis. RESULTS: While in a normal year this average-sized farm has a net operating result of around 18,000 euros, profitability was estimated to be − 369,000 euros and + 169,000 euros for the affected and unaffected farm due to the crisis respectively. For affected farms, impacts were especially high as there was no government compensation or insurance. CONCLUSIONS: As Dutch farms typically operate as independent family farms, there was also no compensation from other chain actors. The affected farms therefore likely have faced financial distress and have had to increase debt or use their financial reserves for household consumption and restarting the business. Outcomes contribute to discussions around liability claims and cost-benefit assessments of measures to improve the chain food safety and rapid alert systems. [Image: see text]

This report presents the results of a participatory sustainability and resilience assessment of 11 farming systems in the European Union (EU). The assessments focused on 1) ranking the importance of functions and selecting representative indicators for these functions, 2) scoring the current performance of the representative indicators, 3) sketching dynamics of main representative indicators of functions, 4) linking these dynamics to challenges and resilience enhancing strategies, 5) assessing level of implementation of identified strategies and their potential contribution to the robustness, adaptability and transformability of the farming system, and 6) assessing level of presence of resilience enhancing system characteristics (resilience attributes) and their potential contribution to the robustness, adaptability and transformability of the farming system. ; EU; en; contact: pytrik.reidsma@wur.nl

By 2020, Dutch dairy chains envisage to be self-sufficient with regard to energy used by dairy farms and dairy processors. This would require dairy farms to produce 25 PJ per year, possibly by a combination of wind, solar and biogas. This paper focuses on biogas. To evaluate the project's viability we estimated the expected technical and financial performance of 4 types of business models, i.e. "CHP-farm", "CHP-large", "green gas" and "central upgrading of green gas". Data stem from among others 23 biogas plants in the Netherlands. Anticipating that CHP-models and green gas models occur with a likelihood of 40% and 60% respectively, the total number of biogas plants would amount to 232 (1% of dairy farms), including a total of 5 million tons of manure per year (14% of all cattle manure in the Netherlands) and annual government subsidies of Euro 295 million. Aggregated annual profits are expected to be positive, but over the project's total life time there is an expected deficit of Euro 262. For this to change costs of feedstocks or digestate disposal costs would for instance have to go down. Also fully switching to green gas models dampens the deficit. Results are used in current stakeholders debates on the organization of an "energy neutral dairy chain" in the Netherlands. Further analyses incorporating uncertainty around key technical and economic parameters including financial impacts of CO2-reductions are underway.

Sustainable agricultural commodities should be favored in international trade negotiations to meet the growing demand for food in a context of environmental conservation, population growth, and globalization. There is a need for a metric that allows for the differentiation of traded agricultural commodities according to how sustainably they were produced. In this context, this paper develops two single metrics, based on a Total Factor Productivity indexing approach, for benchmarking products in terms of their sustainability performance. Both metrics are adjusted to internalize the social and environmental externalities of food production, and to account for the sustainability effects of stages along agri‐food supply chains. Key aspects such as data availability, the selection of variables, and the selection of sustainability standards and targets are discussed.

CONTEXT Enhancing farm resilience has become a key policy objective of the EU's Common Agricultural Policy (CAP) to help farmers deal with numerous interrelated economic, environmental, social, and institutional shocks and stresses. A central theme in resilience thinking is the role of the unknown, implying that knowledge is incomplete and that change, uncertainty, and surprise are inevitable. Important strategies to enhance resilience are exploiting social capital and learning as these contribute to improved knowledge to prepare farmers for change. OBJECTIVE This paper explores how social capital and learning relate to farm resilience along the dimensions of robustness, adaptation, and transformation. METHODS We study the resilience of Dutch arable farmers from the Veenkoloniën and Oldambt using a combination of four methods. Qualitative data from semi-structured farmer interviews, focus groups, and expert interviews are combined with quantitative data from farmer surveys. The qualitative data are analysed using thematic coding. Non-parametric tests are used to analyse the quantitative data. Based on methodological triangulation, we mostly find convergence in our qualitative and quantitative datasets increasing the validity of our findings. RESULTS AND CONCLUSIONS The results reveal that social capital and learning help farmers to adapt and are, in certain cases, also related to robustness and transformations. Robust farmers often learned by exploiting farmers' informal social networks, primarily relying on bonding social capital to acquire knowledge about agriculture or develop financial skills. Farmers undertaking adaptation are characterised by bonding and bridging social capital obtained by formal and informal networks, are early adopters of innovation, and have high self-efficacy. Combinations of bridging and linking social capital from formal networks could foster farmers to learn new ideas and critically reflect on current farm business models. These learning outcomes relate to farm transformations. ...

Greater resilience is needed for farms to deal with shocks and disturbances originating from economic, environmental, social and institutional challenges, with resilience achieved by adequate adaptive governance. This study focuses on the resilience capacity of farms in the context of multi-level adaptive governance. We define adaptive governance as adjustments in decision-making processes at farm level and policy level, through changes in management practices and policies in response to identified challenges and the delivery of desired functions (e.g. private and public goods) to be attained. The aim of the study is twofold. First, we investigate how adaptive governance processes at farm level and policy level influence the resilience capacity of farms in terms of robustness, adaptability and transformability. Second, we investigate the "fit" between the adaptive governance processes at farm level and policy level to enable resilience. We study primary egg and broiler production in Sweden taking into consideration economic, social and environmental challenges. We use semi-structured interviews with 17 farmers to explain the adaptive processes at farm level and an analysis of policy documents from the Common Agricultural Policy program 2014–2020, to explain the intervention actions taken by the Common Agricultural Policy. Results show that neither the farm level nor policy level adaptive processes on their own have the capacity to fully enable farms to be robust, adaptable and transformable. While farm level adaptive processes are mainly directed toward securing the robustness and adaptability of farms, policy level interventions are targeted at enabling adaptability. The farm- and the policy level adaptive processes do not "fit" for attaining robustness and transformability. ; Peer Reviewed

Greater resilience is needed for farms to deal with shocks and disturbances originating from economic, environmental, social and institutional challenges, with resilience achieved by adequate adaptive governance. This study focuses on the resilience capacity of farms in the context of multi-level adaptive governance. We define adaptive governance as adjustments in decision-making processes at farm level and policy level, through changes in management practices and policies in response to identified challenges and the delivery of desired functions (e.g. private and public goods) to be attained. The aim of the study is twofold. First, we investigate how adaptive governance processes at farm level and policy level influence the resilience capacity of farms in terms of robustness, adaptability and transformability. Second, we investigate the "fit" between the adaptive governance processes at farm level and policy level to enable resilience. We study primary egg and broiler production in Sweden taking into consideration economic, social and environmental challenges. We use semi-structured interviews with 17 farmers to explain the adaptive processes at farm level and an analysis of policy documents from the Common Agricultural Policy program 2014–2020, to explain the intervention actions taken by the Common Agricultural Policy. Results show that neither the farm level nor policy level adaptive processes on their own have the capacity to fully enable farms to be robust, adaptable and transformable. While farm level adaptive processes are mainly directed toward securing the robustness and adaptability of farms, policy level interventions are targeted at enabling adaptability. The farm- and the policy level adaptive processes do not "fit" for attaining robustness and transformability.