6 research outputs found
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Sustainability assessment of goat and sheep farms: a comparison between European countries
European sheep and goat farming faces diverse challenges at global or local scales and constitutes an important sector for many countries, playing important sociocultural, economic and environmental roles. A closer examination of the overall sustainability of the sector is necessary to assess the performance of different farm types in various geographical settings. This comparative study evaluates the use of a common sustainability assessment (SA) tool for the major European countries in the sheep and goat sector. In particular, the study reports the results of a SA using the Public Goods (PG) Tool, adapted within the Innovation for Sustainable Sheep and Goat Production in Europe (iSAGE) Horizon 2020 project, which includes questions accounting for 13 dimensions of a sheep and goat farm sustainability. In total, 206 farmers from Greece, Italy, Spain, Finland, United Kingdom, France and Turkey were interviewed, all of which were typical of specific types of a pan-European sheep and goat farm typologies elaborated within iSAGE. The study resulted in composite indicators of performance in each dimension for each country. Finland, Italy and the United Kingdom performed better than other countries, while Turkey and Greece performed below average in most categories. The results highlight challenges for each country but also at the European level, the latter mainly relating to generational renewal and an unwillingness to invest in the adoption of a more sustainable approach with long-term results.</jats:p
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Leverage points for the uptake of organic food production and consumption in the United Kingdom
Organic food systems are recognised as an important component in meeting United Nations’ (UN) Sustainable Development Goals. A leverage points perspective can help to identify approaches which have the potential to facilitate transformative systemic change towards organic and sustainable farming. Using fuzzy cognitive maps developed from expert stakeholder opinions, we modelled a system of drivers of organic food production and consumption in the United Kingdom, according to the UN Sustainability Assessment of Food and Agriculture systems framework. The most influential concepts in the uptake of organic systems were related to system norms and values and social structures, such as short-term economic thinking, landowner engagement, and relationships with certification bodies. However, in a scenario analysis, organic stakeholders identified relatively shallower leverage points as more likely to change under a sustainable future, resulting in limited systemic change. This demonstrates the need for policies targeting system norms, values and social structures relating to food systems to facilitate the transition to organic and sustainable farming
Incorporating ecosystem services in evaluating the sustainability of innovative organic farming systems using the Public Goods tool
In earlier studies, a tool was developed to assess the sustainability of farming systems – the Public Goods Tool (PG-tool). This tool was developed predominantly for use in food farming and in the current study it will be adapted for innovative examples in organic farming. To achieve this, new
indicators were identified in addition to those already in the PG-Tool. Special attention was given to incorporating indicators which could capture provisioning of ecosystem services by farming systems, in particular those with a focus on biodiversity, human nutrition and social well-being - areas that are also currently underrepresented in the PG Tool
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The design and application of the public goods tool: an evaluation framework for the development of sustainable farming systems
Sustainability Assessment of Goat and Sheep Farms: A Comparison between European Countries
European sheep and goat farming faces diverse challenges at global or local scales and constitutes an important sector for many countries, playing important sociocultural, economic and environmental roles. A closer examination of the overall sustainability of the sector is necessary to assess the performance of different farm types in various geographical settings. This comparative study evaluates the use of a common sustainability assessment (SA) tool for the major European countries in the sheep and goat sector. In particular, the study reports the results of a SA using the Public Goods (PG) Tool, adapted within the Innovation for Sustainable Sheep and Goat Production in Europe (iSAGE) Horizon 2020 project, which includes questions accounting for 13 dimensions of a sheep and goat farm sustainability. In total, 206 farmers from Greece, Italy, Spain, Finland, United Kingdom, France and Turkey were interviewed, all of which were typical of specific types of a pan-European sheep and goat farm typologies elaborated within iSAGE. The study resulted in composite indicators of performance in each dimension for each country. Finland, Italy and the United Kingdom performed better than other countries, while Turkey and Greece performed below average in most categories. The results highlight challenges for each country but also at the European level, the latter mainly relating to generational renewal and an unwillingness to invest in the adoption of a more sustainable approach with long-term results
Results of a workshop identifying the main factors that could affect the uptake of organic food production and consumption in 2050 within the UK
The accompanying file ‘FCM_Workshop.csv’ contains results of an online workshop that brought together 18 expert stakeholders in organic food systems in the UK. The workshop was hosted by University of Reading and held in March 2023, as described further in the above paper. This is the input file for the R script used to develop the Fuzzy Cognitive Map described in the paper.Each row or column is a factor identified by workshop participants that 'could affect the uptake of organic food production and consumption in 2050 within the UK'. The numeric values represent the effect of the row factor on the column factor, identified by the participants, where:-0.7: strong negative interaction-0.5: medium negative interaction-0.2: weak negative interaction0.2: weak positive interaction0.5: medium positive interaction0.7: strong positive interaction0: no interaction identified</p