Conclusions : Promises and Challenges for Sustainable Agri-food Systems
| Autoři | |
|---|---|
| Rok publikování | 2017 |
| Druh | Kapitola v knize |
| Fakulta / Pracoviště MU | |
| Citace | |
| Přiložené soubory | |
| Popis | This chapter summarizes the main sustainability challenges (in terms of science and policy) of the current dominant agri-food system and presents insights derived from the cases in the volume. We return to the two main questions asked in the introductory chapter of the book. How useful is the socio-metabolic approach in studying the sustainability of local food systems (LFS)? To this, we identify three main methodological contributions: 1. That classic indicators (of material and energy flows) derived from the sociometabolic approach offers greater insights as well as lend power and rigour when combined with social, ecological, political and other dimensions; 2. Multi-dimensional and multi-scalar analyses can contribute not only to sustainability assessment of a particular LFS but also to broader theoretical and conceptual debates regarding sustainability and potential localisation of LFS; 3. Socio-metabolic studies on the local level provide detailed understanding of the particular LFS while revealing potential leverage points for intervention for improved system performance with respect to sustainability. Besides methodological insights, the chapter derives key lessons from the cases in the book, in particular the promising characteristics of both the historical and current local food system. We identify the following points as important: 1. A close proximity between the producers and consumers holds a very strong potential for systemic change of the current dominant agri-food system, but also the other way round, the growing distance obscures the sustainability challenges; 2. LFS proves better in closing nutrient cycles on local and regional levels. This issue is also related to the importance of the multifunctionality of land use, and livestock use, in both the historical and the current LFS. [...] |
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