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ispartof: EUROCHOICES vol:21 issue:3 pages:21-26 status: published

This deliverable D7.6 of the LIFT project is the final scientific deliverable of the project that was carried out during four years from May 2018 till April 2022. The deliverable summarises the methodologies used and the key results for the main research activities that were carried out in LIFT: definition of ecological agriculture; adoption of ecological approaches; farm performance of ecological agriculture; territorial sustainability of ecological agriculture; trade-offs and synergies across sustainability dimensions and scales; impact of policies; role of stakeholders. Recommendations in terms of policies, data and research needs, are then provided.

This Deliverable 5.2 of the LIFT project presents a territorial level sustainability assessment of alternative scenarios for the adoption of ecological farming approaches for 16 case study areas across Europe. Given that there are many approaches to sustainability assessment depending on the theoretical framework, the assessment’s aims, and data used, this deliverable begins with a review of the sustainability assessment literature in relation to agriculture and territorial scale issues, to identify the most appropriate methodology for this deliverable. The limited availability of landscape-scale data, the use of scenarios, and the need to rapidly apply a straightforward methodology across diverse case study areas, favoured a qualitative assessment of each adoption scenario in terms of their impacts against a set of regionally-specific sustainability objectives. Moreover, because territorial impacts can reflect many interacting cause-effect relationships, network analysis formed an optional extension to the assessment, to explore the patterns of influence underpinning scenario performance. In order to define the sustainability objectives for assessment, an initial long list of possible objectives was created through a review of the academic literature and relevant regional policy documents, followed by a round of stakeholder consultation to produce a final short list of objectives for each case study area. Performance against these objectives was assessed for four ecological farming adoption scenarios that differed in terms of the rate (either high or low) and distribution (clustered or dispersed) of adoption in 10 years’ time. The ecological practices being adopted in these scenarios were identified based on the output of Delphi exercises with stakeholder panels for each case study area, conducted as part of previous research in LIFT. Drawing on results from LIFT, local literature, and expert knowledge, each scenario was described as the product of a set of drivers of change. The drivers of change were tabulated against the objectives to produce an assessment matrix for each scenario. Groups of experts and stakeholders completed these matrices by deciding whether the state of each driver in each scenario had a positive or negative, strong or weak, impact on each objective. The different driver impacts on each objective were aggregated to show the scenario’s overall performance against each objective. For the High Weald case study area in England, the assessment matrices were also used to create network graphs to show the interacting cause-effect relationships between drivers and impacts, and network analysis was used to identify features of the system that were especially influential in determining overall sustainability performance. Based on this qualitative mapping of impacts against sustainability objectives, across case study areas, territorial sustainability performance was assessed to be strongest when the ecological farming adoption rate was high, and when adoption occurred in a clustered distribution (although the impact of adoption distribution was typically smaller than the impact of adoption rate). The same overall pattern was also reported when considering only the environmental and social dimensions of sustainability, but economic sustainability performance was only impacted by the rate, and typically not the distribution, of adoption. These results suggest that the practices identified by stakeholders as relevant to future ecological adoption scenarios for a given case study area tend to be appropriate for achieving the area’s specific sustainability objectives, and that the spread of ecological farming approaches, at least in some areas, has the potential to deliver ‘win-win-win’ outcomes that reconcile performance across different sustainability dimensions. However, no one scenario was best for every objective in a case study area, so even if high clustered adoption of ecological farming makes an overall positive contribution to sustainability at the territorial level, realising this scenario in practice will still involve navigating some trade-offs between objectives. By extending the methodology to include network analysis, the sustainability assessment for the High Weald highlighted pathways and barriers that could be important in accounting for differences in scenario performance. In particular, information exchange among farmers on the benefits of ecological practices (facilitated by strong organisational and advisory support, and the use of technology) was a key contributor to the strong territorial sustainability performance of a high clustered adoption scenario. The network graphs produced for the High Weald also provided some indication as to how the territorial sustainability performance of ecological farming is due to a combination of farm-level and landscape-level processes, and suggested areas of interaction between these farm and landscape-level processes. As an example, strong interpersonal relationships among farmers could enhance information exchange that promotes ecological practice uptake on individual farms, but also encourage greater coordination of land management and collaboration between farmers. While the combination of scenario analysis, qualitative impact mapping and network analysis has been used for sustainability assessment before, in this case scenario development was built around alternative outcomes for the spread of agricultural land management practices, rather than starting with particular philosophies about the direction of society or policy. A key challenge, and priority area for further innovation, could be to reconcile the approach presented here with farm-level sustainability assessments, helping to identify areas of alignment or disconnect between farm and territorial level performance.

In light of the ambitions of the European Union (EU) to achieve an ecological transition of its agricultural sector it is crucial to assess and continuously monitor (i) the uptake of main ecological approaches by farms and (ii) associated effects on farm performance, considering all sustainability dimensions (economic, environmental, social) jointly. Given these needs, in the present deliverable D5.1 of the LIFT project, we develop a novel indicator system, which combines the LIFT farm typology and farm performance data, covering all sustainability dimensions. The approach compares performance of farms in five ecological groups (referred to as ecological farming approaches or ecological farming systems) from the LIFT farm typology (Conservation Agriculture, Low-Input farming, Integrated/Circular farming, Organic farming, Agroecology) as well as possible combinations of these groups with a less ecological group, referred to as Standard farming. This allows us to depict whether ecological farms perform differently or have different trade-offs and synergies than standard farms. Based on this system, we carry out a farm sustainability performance assessment with the two main data sources in the LIFT project, namely Farm Accountancy Data Network (FADN) data and data from the LIFT large-scale farmer survey, covering main farm types present in the European Union (EU) in several case study regions/countries. Additionally, we present in-depth analyses of further specific aspects, namely (i) the extension of the developed indicator framework to bio-economic models, (ii) the integration of the consumption and provision of ecosystem services into the developed indicator system through composite agri-environmental performance (AEP) indicators, derived from the body of secondary literature and region-specific stakeholder input, and (iii) working conditions and employment on farms in the context of an ecological transition. Overall, our results show the importance of considering trade-offs and synergies both within and between farm sustainability dimensions, in the assessment of farm level sustainability performance of ecological farming approaches. Our results also highlight that in many cases the effects of an increasing uptake of ecological approaches are heterogenous and need to be investigated further. We clearly point out the assumptions associated with our approach as well as its limitations. Given these limitations, the LIFT farm sustainability performance assessment developed here is nevertheless well suited for large-scale and long-term monitoring. This is based on readily available FADN data and, in the near future, could be based on Farm Sustainability Data Network (FSDN) data, providing an in-depth exploratory view for policy makers and researchers regarding farm level sustainability performance of ecological approaches in the EU farming sector. We outline several possible avenues for further research, namely (i) the inclusion of other data sources, (ii) the usage of econometric methods to facilitate causal inference, (iii) the broader usage of the developed composite AEP indicators, and (iv) further in-depth studies regarding the social sustainability dimension. Finally, in terms of policy recommendations we point out the importance of (i) flexible policy measures, able to properly address region-specific needs of farms, (ii) sound data as a basis for evidence-based policy, and (iii) investigating the ecological transition of the EU farming sector in more detail also at regional level, e.g. via living labs.

In the present deliverable, D4.3 of the LIFT project we provide insights on the environmental impact, which is termed here more precisely the agri-environmental impact (AEI), of ecological farm management practices using the ecosystem service concept at territorial level through a two-pronged approach. First, we present an indicator framework which uses one the one hand, evidence derived from an extensive systematic literature review quantifying the potential supply of 17 ecosystem services from 26 different (ecological) farm management practices, and on the other hand local, stakeholder-derived ecosystem service weights (which reflect relative ecosystem service demand) to obtain an overall AEI indicator for a given ecological farm management practice. The indicator framework is then applied to three case study regions across Belgium (Hageland-Haspengouw) and England (North Kent and the High Weald) to demonstrate the context-specific territorial-level AEI of ecological farm management practices. We demonstrate that at territorial level, though there is quite some variation in AEI of ecological farm management practices based on local contexts, semi-natural habitats, extensive livestock systems and cover crops have a high AEI across the three considered case study regions. Second we present results from a discrete choice experiment (DCE) in which we quantify preferences for the aesthetic value of integrating ecological farm management practices into an agricultural landscape in Flanders (Belgium), England and Hungary. From this DCE, we find that, similarly to the findings from the AEI indicators, ecological management practices which target increasing (bio)diversity and maintaining green corridors within a landscape, such as semi-natural habitats and cover crops, illicit strong positive preferences from the general public. Our findings illustrate that considering local context and demand is important when evaluating AEI of farm management practices based on ecosystem services.

The deliverable D6.1 of the LIFT project explores what types of discourses are used in six European Union (EU) member states’ Rural Development Programs (RDP) and other agricultural policy documents and how they incorporate ecological approaches acrossthree Common Agricultural Policy (CAP) periods. This multiple case study highlights similarities and differences in the dominant discourses as emerging from national policy documents in the following selected EU member states: France, Germany (Bavaria), Hungary, Poland, Romania and Sweden. It also demonstrates how discourse analysis can be used to gain understanding about the dominant discourses expressed in these documents in relation to how ecological approaches are defined, the policy rationale for encouraging ecological approaches and the expected consequences of doing so. Conceptually, we focused on two types of discourses identified from the literature: 1) the three CAP discourses: i) neomercantilism; ii) neoliberalism and iii) multifunctionality, and 2) the five socio-political discourses of Rural Development (RD): iv) agri-ruralist, v) hedonist, vi) utilitarian, vii) nature conservation and viii) community sustainability. These types of discourses were together integrated in a model, where each policy discourse depicts agriculture as accomplishing a specific function. The theoretical framework is grounded within a political economy perspective. This means that policy develops because of confrontation between different concerned agents with different interest, pushing for different objectives. The state acts as an intermediary between these agents and aims at ensuring consensus and maintenance of agreement. Policy documents are therefore often the result of competing discourses and contradicting policy objectives. Across EU member states, the results show that ecological approaches are mainly depicted with the multifunctionality discourse with two dominating sub-discourses of nature conservation and agri-ruralism. Nevertheless, we observe an increase in the use of the neomercantilist discourse in the last CAP period. This parallels what the previous literature finds in Commissioners’ speeches: a reappearance of the traditional neomercantilist discourse in the CAP agenda 2014-2020. Farming systems (with farming practices) related to agroecology, biodiversity-based and organic farming are among the most commonly mentioned farming systems.

The enlargement of the European Union (EU) led to an increase in regional development differences, challenging the EU structural policy. Whilst there are a wealth of papers discussing international and across EU development convergence, the issue seems under-researched at national level, especially when small territorial units are considered. This paper aims to partially fill this gap, by using low aggregation (Local Administrative Unit 1, LAU1) territorial data between 2002 and 2013 - a period that comprises Hungary’s EU accession and also the years of the recent global financial crisis. We employ a novel approach to circumvent the lack of income, productivity or competitiveness data at LAU1 level by deriving two Regional Development Indices (RDI) resting on the estimation of an internal migration functions. Once the RDIs are estimated, we proceed to a test sigma, beta and unit root convergence. Further, we assess the probabilities of LAU1 region specific RDIs of changing their positions within distributional quartiles. Results regional divergence and low mobility of regions with rather bleak consequences for Hungarian and indeed European cohesion aims.

This paper analyses the efficiency of EU internal dairy markets between 2000 and 2014 from spatial price integration perspective, employing a cross-methodological approach in three steps. First, we analyse the spatial integration of raw milk markets, which is often used to test the efficiency of agricultural markets. National monthly raw milk price data are tested for integration and whether the Law of One Price (LOP) holds. Second, we assess integration results in a binary choice setting, employing gravity model variables. Finally, in order to partly overcome the often cited drawback of price transmission analysis (i.e. that by employing price variables (only), there is no connection with real trade flows), bidirectional network analysis models are designed using export variables. Country specific network centrality measures were contrasted with the frequency of LOP fulfilment. Results suggest that besides the milk volume traded, the position occupied in the trade network structure should be also considered when market integration is analysed.

JEL classification : P52; Q12; Technical efficiency has long been analysed as a measure of farm performance, however most studies are restricted to a single country case. This paper presents a comparative analysis of field crop and dairy farm performance across eight EU countries, including two New Member States (NMS), focusing on long run stability and mobility patterns. The main research question is how relative performance of farms fluctuates over time, i.e. whether poorly performing farms remain always inefficient whilst some farms are always very efficient. Results show that on average 60% of farms maintain their efficiency ranking in two consecutive years, whilst 20% improve and 20% worsen their positions, for all countries. Due to the unstable economic conditions, farms in NMS are more mobile than those in EU15.

The main purpose of this deliverable is to use technical efficiency scores obtained with three distinct methods, Stochastic Frontier Analysis (SFA), Data Envelopment Analysis (DEA), Operational Competitiveness Ranking Analysis (OCRA), based on national Farm Accountancy Data Network (FADN) data, in order to analyse the impact of European Union (EU) accession and the influence of farm classification, more precisely farm type, upon the performance on field crop and dairy farms in three New Member States (NMS), Bulgaria, Estonia and Hungary We provide theoretical and empirical evidence that farm classification is subject for empirical analysis, because using FADN and conceptual (e.g.Hill type) typology may result in considerably different farm structures. The main outcome of this research is that individual farms are not equivalent to family farms as usually assumed in previous research. We find that average size of individual farms is considerably higher than of family farms.

This document presents the results of Task 3.2 (farm technical-economic performance) in workpackage (WP) 3 (farm performance of ecological agriculture) of the LIFT project. The overall aim of Task 3.2 is to assess and compare technical-economic farm performance across the European Union (EU) depending on the degree of ecological approaches adopted by farms and analyse drivers, affecting their performance. This requires an approach, which allows to consider regional specifics, while still allowing comparisons between different regions and countries. The deliverable thus consists of several academic papers, focussing on a range of different case studies, applying a wide range of methods, which can most generally be divided into empirical econometric approaches and bio-economic models. At the same time, all case studies follow a similar structure and include some common elements in terms of the applied methods, in particular a set of common indicators of technical-economic farm performance was implemented in several papers. Various approaches to differentiate farms according to the degree of ecological approaches adopted were explored, including the LIFT farm typology developed in WP1 and other strategies. Overall, our results show that the wide variety of farm types and biophysical, socio-economic and political framework conditions present in the EU matter: results of comparing technical-economic farm performance depending on the degree of ecological approaches adopted, as well as with respect to drivers of farm technical-economic performance, are heterogenous and vary between the different analyses. Therefore, this heterogeneity needs to be considered by policy makers and can most likely best be addressed by providing a policy framework, which provides the necessary flexibility to adjust measures to region-specific framework conditions in order to foster economic viability of farms in the context of an ecological transition of EU agriculture. Building on the results of this deliverable and the other deliverables within WP3, Task 5.1 will in a next step undertake an integrative assessment of all performance dimensions jointly (technical-economic, environmental and private-social performance as well as employment effects at the farm level), uncovering associated trade-offs and synergies of an increasing uptake of ecological approaches in the EU farming sector, while WP6, in particular Task 6.2 and Task 6.3, will further investigate the role of policies in the development of ecological agriculture.

The deliverable D6.1 of the LIFT project explores what types of discourses are used in six European Union (EU) member states’ Rural Development Programs (RDP) and other agricultural policy documents and how they incorporate ecological approaches across three Common Agricultural Policy (CAP) periods. This multiple case study highlights similarities and differences in the dominant discourses as emerging from national policy documents in the following selected EU member states: France, Germany (Bavaria), Hungary, Poland, Romania and Sweden. It also demonstrates how discourse analysis can be used to gain understanding about the dominant discourses expressed in these documents in relation to how ecological approaches are defined, the policy rationale for encouraging ecological approaches and the expected consequences of doing so. Conceptually, we focused on two types of discourses identified from the literature: 1) the three CAP discourses: i) neomercantilism; ii) neoliberalism and iii) multifunctionality, and 2) the five socio-political discourses of Rural Development (RD): iv) agri-ruralist, v) hedonist, vi) utilitarian, vii) nature conservation and viii) community sustainability. These types of discourses were together integrated in a model, where each policy discourse depicts agriculture as accomplishing a specific function. The theoretical framework is grounded within a political economy perspective. This means that policy develops because of confrontation between different concerned agents with different interest, pushing for different objectives. The state acts as an intermediary between these agents and aims at ensuring consensus and maintenance of agreement. Policy documents are therefore often the result of competing discourses and contradicting policy objectives. Across EU member states, the results show that ecological approaches are mainly depicted with the multifunctionality discourse with two dominating sub-discourses of nature conservation and agri-ruralism. Nevertheless, we observe an increase in the use of the neomercantilist discourse in the last CAP period. This parallels what the previous literature finds in Commissioners’ speeches: a reappearance of the traditional neomercantilist discourse in the CAP agenda 2014-2020. Farming systems (with farming practices) related to agroecology, biodiversity-based and organic farming are among the most commonly mentioned farming systems.

This deliverable investigates the employment effects of ecological farming by analysing both the differences in the intensity of labour use and rewards to skills. It contributes to one of the main outcomes/achievements of the LIFT project, i.e. to “identify the sources of performance and sustainability differences between farms of different types, size and output complexity as observed in the landscape of the European Union (EU)”. It is based on collaborative research on Task 3.5 ‘Employment effects of ecological farming at the farm level’ of LIFT between UNIKENT (England) (Task Leader), INRAE (France), DEMETER (Greece), MTA KRTK (Hungary) and IRWiR PAN (Poland). The analyses reported consider the differences between farms on a scale from the most conventional farming systems to the most ecological as measured by the intensities of use of external inputs and labour, the receipt of agri-environmental payments (AEP), capital and involvement in organic production. This approach was used since, at the time of working on the deliverable the LIFT typology protocol on how to classify farms according to the different degrees of adoption of ecological approaches to farming has not been completed. The approach nevertheless makes use of the LIFT conceptual typology in Deliverable 1.1 (Rega et al., 2018). In the analysis, intensity of labour use is studied as a function of farming inputs (fuel, fertiliser, crop protection chemicals), capital and AEP. Dependent and independent variables have been standardised by dividing them by the output value and the resulting ratios named intensities of use. The standardisation by dividing by the overall output value was done to remove the effect of different farm sizes and to focus the discussion on the way output is produced, rather than how land is used. In order to reduce the impact of quality differences in the inputs, we make use of monetary value of input used to take account of quality differences that would be reflected in price differentials. Five EU Member States (MSs) are analysed in this deliverable, i.e. those involved in Task 3.5 – Greece, France, Hungary, Poland and England or the United Kingdom (all data collected refer to when the UK was a MS). Two types of data are employed in the deliverable - secondary, i.e. data from the Farm Accountancy Data Network (FADN) for the period 2004-2015 and primary, i.e. data from the LIFT cross-sectional large-scale farmer survey carried out in 2019-2020 and referring to the year 2018. The literature review is a summary of LIFT Milestone 16 (Davidova et al., 2019), which included a structured literature review as part of Task 3.5, expanded by additional sources. This deliverable also uses a qualitative method, the Delphi exercise, to give further insights and supplement the literature. This approach is also related to Task 3.2 ‘Assessment of farm technical-economic performance’. Labour use is analysed relative to productivity and profitability within the intensities. A lower intensity of input use relative to output indicates an ecologically less intensive farm, but it is also a farm that is potentially more productive and profitable. The analysis of the impact on the labour share of output shows a consistent picture across analysed EU MSs. Low intensities of external inputs and capital, which proxies farms employing ecological approaches, increases the intensity of labour use when external input and capital input intensities decrease. As farms become less intensive in their use of purchased inputs, the intensity of total labour (or labour’s share of output) falls and this is primarily driven by a lower intensity in the use of family labour. However, after a certain threshold of input and capital intensities there is a switch to a substitution effect. Therefore, conventional farming, not defined here as non-organic or any other defined system of farming but characterised here by intensive use of externally purchased inputs and highly capitalised farms, drops in labour intensity as the intensity of purchased inputs increase. Returns to skills in ecological farming have been estimated based on the data from the LIFT large-scale farmer survey and this analysis has only covered LIFT case study areas. The explorative picture based on the survey data has been expanded by a common econometric analysis of the case study areas in France and England. The comparative study raised questions about the educational systems in the two countries which could influence the innovative capacity to employ new farming technologies. The data sources did not allow for a systematic analysis of gender effects through adoption of ecological farming approaches, but some insights were taken from the literature review and Delphi exercise. Gender becomes more and more important from the point of view of employment, division of labour within the farm households and pay. However, the studies are on developing countries where customary traditions and norms are much stronger. This literature review shows that the impacts of introducing ecological practices in agriculture in developing countries does not have a clear-cut gendered effect on labour. The effect depends on on-farm labour division and on intra-household time allocation. Several conclusions and policy implications have been formulated on the basis of the deliverable: There is no theory that can guide researchers to a priori expectations about the effect of different farming practices on labour demand in quantitative terms and qualitative ones (skills). Farms which use ecological farming practices may decrease their intensity of labour use as their intensity of use of purchased inputs and capital is lower. Therefore, policies which support the adoption of ecological farming approaches may have as a by-product increased (maintained) farm, and consequently, rural employment. AEP and the increased complexity of output, proxied by the number of enterprises (activities) on a farm, which is expected to be present in the farms using ecological farming practices, also result in higher labour intensity. Ecological approaches to farming will mainly increase the use of hired labour strengthening the existing trend of substitution of hired to family labour. Cost minimising farmers might be reluctant to adopt ecological farming practices trying to minimise labour costs. Policy incentives might be necessary to stimulate the adoption of ecological farming practices, e.g. agroecology, since the latter has a high potential to provide important environmental and social non-product benefits. Government policies, concerning labour market, should be re-orientated towards a decrease of transaction costs for a farmer hiring/firing farm labour to allow more flexible adjustments of hired labour in view of wider adoption of ecological farming practices. Agricultural education should provide a broad skill set necessary for the implementation of ecological approaches to farming, thus encouraging a successful adoption of ecological technologies and a positive economic return from their adoption. Further research should focus on a comparative study of best practice in the EU: i) in the area of employment law concerning agriculture to provide policy insights on how to build more flexibility in the market for hired farm labour and ii) in the area of agricultural education and practical training.

This document presents the results of Task 3.2 (farm technical-economic performance) in workpackage (WP) 3 (farm performance of ecological agriculture) of the LIFT project. The overall aim of Task 3.2 is to assess and compare technical-economic farm performance across the European Union (EU) depending on the degree of ecological approaches adopted by farms and analyse drivers, affecting their performance. This requires an approach, which allows to consider regional specifics, while still allowing comparisons between different regions and countries. The deliverable thus consists of several academic papers, focussing on a range of different case studies, applying a wide range of methods, which can most generally be divided into empirical econometric approaches and bio-economic models. At the same time, all case studies follow a similar structure and include some common elements in terms of the applied methods, in particular a set of common indicators of technical-economic farm performance was implemented in several papers. Various approaches to differentiate farms according to the degree of ecological approaches adopted were explored, including the LIFT farm typology developed in WP1 and other strategies. Overall, our results show that the wide variety of farm types and biophysical, socio-economic and political framework conditions present in the EU matter: results of comparing technical-economic farm performance depending on the degree of ecological approaches adopted, as well as with respect to drivers of farm technical-economic performance, are heterogenous and vary between the different analyses. Therefore, this heterogeneity needs to be considered by policy makers and can most likely best be addressed by providing a policy framework, which provides the necessary flexibility to adjust measures to region-specific framework conditions in order to foster economic viability of farms in the context of an ecological transition of EU agriculture. Building on the results of this deliverable and the other deliverables within WP3, Task 5.1 will in a next step undertake an integrative assessment of all performance dimensions jointly (technical-economic, environmental and private-social performance as well as employment effects at the farm level), uncovering associated trade-offs and synergies of an increasing uptake of ecological approaches in the EU farming sector, while WP6, in particular Task 6.2 and Task 6.3, will further investigate the role of policies in the development of ecological agriculture.

This deliverable investigates the socio-economic effects of ecological approaches to farming through implementing two participatory approaches, namely Delphi exercise and Q-method, at the level of a case study area (CSA). The focus is on how people and other productive assets are employed and remunerated by ecological approaches to agriculture, particularly those aspects that can influence employment, and drive the prosperity and vitality of local communities and some rural businesses. It is based on the collaborative research on Task 4.2 ‘Socio-economic impact of ecological agriculture at the territorial level’ of the LIFT project between UNIKENT (United Kingdom-UK) (Task Leader), BOKU (Austria), INRAE (France), VetAgro Sup (France), DEMETER (Greece), MTA KRTK (Hungary), UNIBO (Italy), IRWiR PAN (Poland), IAE-AR (Romania), SLU (Sweden), SRUC (UK). Beginning with the Delphi exercise, this deliverable presents qualitative information extracted from stakeholders in the following four steps. First, the researchers build a presentation of differences between ecological and conventional farming approaches in each CSA. Second, stakeholders elaborate on how they understand ecological farming approaches to exist in each CSA. Third, stakeholders develop a scenario of adoption of ecological approaches to farming depending on two factors: pattern (ecological farms forming clusters or randomly spread within the territory) and rate of adoption 10 years in the future. After establishing this scenario across two rounds, the stakeholders explore the socio-economic effects of their adoption scenario. The Q-methodology then presents a Q-set of statements that the Delphi has developed and, through factor analysis, studies the key stakeholder perspectives of the socio-economic effects of the perceived adoption of ecological practices in 10 years in the future. Four key results can be derived from the Delphi exercise and the Q-methodology. First, a higher adoption of ecological farming approaches, especially so at a 50% adoption rate, is mostly thought by stakeholders in the Delphi Exercise to lead to an increase in skill level and quality of life in on-farm employment. This is as a result of an increased diversity of farming enterprises on farms using ecological farming approaches, the interest generated from this, the knowledge of natural processes and biology required, engagement with nature and change in machinery that is coming into the industry. Strongly related to this need for skills is a predicted increase in the number of advisers and civil servants to deal with more complicated farms and incentives as well as monitoring of ecological effects on farm. An increase in required skill level is repeated across all Q-studies. Second, especially where farms are clustered together, Delphi Exercise respondents predict an increase in the trade of inputs such as manure and compost replacing synthetic fertiliser, as well as more sharing of capital and labour. Q-methodology highlights that these clusters may support a stronger social movement, more consumers buying local food and increase collaboration between farmers. Supply chains are expected to become shorter as farmers sell more directly and there are fewer intermediaries upstream of the farming sector. As farmers collaborate more with each other on environmental objectives, trading inputs and sharing best practices, farmer relationships should improve in rural communities. Third, Delphi exercise finds that contracting, machinery purchasers, and machinery traders and dealers could increase, decrease or display no change – the anticipated effects are mixed. Stakeholders are in no doubt that machinery use will change and therefore new skills will need to be learnt, but the wider effect on machinery purchase is uncertain. However, stakeholders conclude that a greater specialisation in machinery will occur leading to changes in farm management as well as the suppliers of this machinery. Q-methodology highlights that ecological practices will not mean the end of machinery and a lot more labour – often machinery will be useful in weeding and reducing physical labour as technology has significantly improved and skills are improving too in order to use these technologies. Fourth, Delphi respondents argued that although rural populations might be little affected by ecological farming, a shift in people moving from urban to rural settlements, and thereby a higher rural population density, seeking a more attractive rural environment, might contribute to higher local consumer demand. The Q-methodology highlights that where there is high adoption, rural areas are expected to become more attractive, as landscapes will have a much greater variety of crops instead of fields of monocrops. This variety of crops may include agroforestry (farmers interested in ecological approaches to farming may also be interested in agroforestry as a way of boosting their yields and protecting crops and livestock from the elements) as well as intercropping.

This deliverable investigates the socio-economic effects of ecological approaches to farming through implementing two participatory approaches, namely Delphi exercise and Q-method, at the level of a case study area (CSA). The focus is on how people and other productive assets are employed and remunerated by ecological approaches to agriculture, particularly those aspects that can influence employment, and drive the prosperity and vitality of local communities and some rural businesses. It is based on the collaborative research on Task 4.2 ‘Socio-economic impact of ecological agriculture at the territorial level’ of the LIFT project between UNIKENT (United Kingdom-UK) (Task Leader), BOKU (Austria), INRAE (France), VetAgro Sup (France), DEMETER (Greece), MTA KRTK (Hungary), UNIBO (Italy), IRWiR PAN (Poland), IAE-AR (Romania), SLU (Sweden), SRUC (UK). Beginning with the Delphi exercise, this deliverable presents qualitative information extracted from stakeholders in the following four steps. First, the researchers build a presentation of differences between ecological and conventional farming approaches in each CSA. Second, stakeholders elaborate on how they understand ecological farming approaches to exist in each CSA. Third, stakeholders develop a scenario of adoption of ecological approaches to farming depending on two factors: pattern (ecological farms forming clusters or randomly spread within the territory) and rate of adoption 10 years in the future. After establishing this scenario across two rounds, the stakeholders explore the socio-economic effects of their adoption scenario. The Q-methodology then presents a Q-set of statements that the Delphi has developed and, through factor analysis, studies the key stakeholder perspectives of the socio-economic effects of the perceived adoption of ecological practices in 10 years in the future. Four key results can be derived from the Delphi exercise and the Q-methodology. First, a higher adoption of ecological farming approaches, especially so at a 50% adoption rate, is mostly thought by stakeholders in the Delphi Exercise to lead to an increase in skill level and quality of life in on-farm employment. This is as a result of an increased diversity of farming enterprises on farms using ecological farming approaches, the interest generated from this, the knowledge of natural processes and biology required, engagement with nature and change in machinery that is coming into the industry. Strongly related to this need for skills is a predicted increase in the number of advisers and civil servants to deal with more complicated farms and incentives as well as monitoring of ecological effects on farm. An increase in required skill level is repeated across all Q-studies. Second, especially where farms are clustered together, Delphi Exercise respondents predict an increase in the trade of inputs such as manure and compost replacing synthetic fertiliser, as well as more sharing of capital and labour. Q-methodology highlights that these clusters may support a stronger social movement, more consumers buying local food and increase collaboration between farmers. Supply chains are expected to become shorter as farmers sell more directly and there are fewer intermediaries upstream of the farming sector. As farmers collaborate more with each other on environmental objectives, trading inputs and sharing best practices, farmer relationships should improve in rural communities. Third, Delphi exercise finds that contracting, machinery purchasers, and machinery traders and dealers could increase, decrease or display no change – the anticipated effects are mixed. Stakeholders are in no doubt that machinery use will change and therefore new skills will need to be learnt, but the wider effect on machinery purchase is uncertain. However, stakeholders conclude that a greater specialisation in machinery will occur leading to changes in farm management as well as the suppliers of this machinery. Q-methodology highlights that ecological practices will not mean the end of machinery and a lot more labour – often machinery will be useful in weeding and reducing physical labour as technology has significantly improved and skills are improving too in order to use these technologies. Fourth, Delphi respondents argued that although rural populations might be little affected by ecological farming, a shift in people moving from urban to rural settlements, and thereby a higher rural population density, seeking a more attractive rural environment, might contribute to higher local consumer demand. The Q-methodology highlights that where there is high adoption, rural areas are expected to become more attractive, as landscapes will have a much greater variety of crops instead of fields of monocrops. This variety of crops may include agroforestry (farmers interested in ecological approaches to farming may also be interested in agroforestry as a way of boosting their yields and protecting crops and livestock from the elements) as well as intercropping.