Open Access
Article de recherche / Research Article
Issue
Cah. Agric.
Volume 29, 2020
Article Number 30
Number of page(s) 10
DOI https://doi.org/10.1051/cagri/2020028
Published online 29 October 2020
  • Abildtrup J, Audsley E, Fekete-Farkas M, Giupponi C, Gylling M, Rosato P, et al. 2006. Socio-economic scenario development for the assessment of climate change impacts on agricultural land use: a pairwise comparison approach. Environmental Science & Policy 9(2): 101–115. [Google Scholar]
  • ADEME. 2012. L’exercice de prospective de l’ADEME « Vision 2030–2050 ». Angers, France: ADEME. [Google Scholar]
  • Audsley E, Pearn KR, Simota C, Cojocaru G, Koutsidou E, Rounsevell MDA, et al. 2006. What can scenario modelling tell us about future European scale agricultural land use, and what not? Environmental Science & Policy 9(2):148–162. http://dx.doi.org/10.1016/j.envsci.2005.11.008. [Google Scholar]
  • Billen G, Le Noë J, Anglade J, Garnier J. 2019. Polyculture-élevage ou hyper-spécialisation territoriale ? Deux scénarios prospectifs du système agro-alimentaire français. Innovations Agronomiques 72: 31–44. https://hal.inrae.fr/hal-02627306. [Google Scholar]
  • Canfin P, Grandjean A, Mestrallet G. 2016. Propositions pour des prix du carbone alignés avec l’Accord de Paris. In : Rapport de la mission remis à Ségolène Royal, en sa qualité de présidente de la COP21. https://www.ecologique-solidaire.gouv.fr/sites/default/files/Rapport%20Canfin%20Grandjean%20Mestrallet.pdf. [Google Scholar]
  • Carpenter S, Pingali P. 2005. Millennium ecosystem assessment—scenarios assessment. Washington DC, USA: Island Press. [Google Scholar]
  • Cascailh A, Dubosc N, Longueval C, Nedellec J, Tizon A, Vandewalle A. 2015. Étude Climagri® région Midi-Pyrénées. Toulouse, France: Chambre Agriculture Midi-Pyrénées. [Google Scholar]
  • COMIFER. 2013. Calcul de la fertilisation azotée. p. 159. https://comifer.asso.fr/fr/publications/les-brochures.html (accès : août 2020). [Google Scholar]
  • European Commission. 2017. EU Agricultural Outlook for the agricultural markets and income 2017–2030. Bruxelles, Belgique: European Commission. [Google Scholar]
  • INRA. 2007. Alimentation des bovins, ovins et caprins : besoins des animaux-valeurs des aliments. Paris: Éditions Quae, 307 p. [Google Scholar]
  • Hirschler J, Stark F, Gourlaouen Y, Perrot C, Dubosc N, Ramonteu S. 2019. Évolution des systèmes de polyculture-élevage : une rétrospective statistique 2007–2014. Innovations Agronomiques 72: 193–209. https://doi.org/10.15454/HPTJH1. [Google Scholar]
  • Kremen C, Iles A, Bacon CM. 2012. Diversified farming systems: an agroecological, systems-based alternative to modern industrial agriculture. Ecology and Society 17(4): 44. https://doi.org/10.5751/ES-05103-170444. [Google Scholar]
  • Lemaire G, Franzluebbers A, Carvalho PCdF, Dedieu B. 2014. Integrated crop–livestock systems: strategies to achieve synergy between agricultural production and environmental quality. Agriculture, Ecosystems & Environment 190: 4–8. https://doi.org/10.1016/j.agee.2013.08.009. [Google Scholar]
  • Mazoyer M, Roudart L. 2002. Histoire des agricultures du monde : du néolithique à la crise contemporaine, Histoire. Paris: Éditions du Seuil. [Google Scholar]
  • Miller R. 2018. Transforming the future. Anticipation in the 21st century. Paris, France: UNESCO and Routledge, 301 p. [Google Scholar]
  • Mosnier C, Britz W, Julliere T, De Cara S, Jayet PA, Havlík P, et al. 2019. Greenhouse gas abatement strategies and costs in French dairy production. Journal of Cleaner Production 236: 117589. https://doi.org/10.1016/j.jclepro.2019.07.064. [Google Scholar]
  • Mosnier C, Duclos A, Agabriel J, Gac A. 2017a. Orfee: a bio-economic model to simulate integrated and intensive management of mixed crop-livestock farms and their greenhouse gas emissions. Agricultural Systems 157: 202–215. https://doi.org/10.1016/j.agsy.2017.07.005. [Google Scholar]
  • Mosnier C, Duclos A, Agabriel J, Gac A. 2017b. What prospective scenarios for 2035 will be compatible with reduced impact of French beef and dairy farm on climate change? Agricultural Systems 157: 193–201. https://doi.org/10.1016/j.agsy.2017.07.006. [Google Scholar]
  • Ryschawy J, Martin G, Moraine M, Duru M, Therond O. 2017. Designing crop-livestock integration at different levels: toward new agroecological models? Nutrient Cycling in Agroecosystems 108: 5–20. https://doi.org/10.1007/s10705-016-9815-9. [Google Scholar]
  • Searchinger TD, Wirsenius S, Beringer T, Dumas P. 2018. Assessing the efficiency of changes in land use for mitigating climate change. Nature 564(7735): 249–253. https://doi.org/10.1038/s41586-018-0757-z. [Google Scholar]
  • Seufert V, Ramankutty N. 2017. Many shades of gray—The context-dependent performance of organic agriculture. Science Advances 3(3): e1602638. https://doi.org/10.1126/sciadv.1602638. [CrossRef] [PubMed] [Google Scholar]
  • Steinmetz L, Mosnier C. 2019. Adaptation des systèmes de polyculture-élevage aux variations de prix et de taille de l’exploitation : simulation à partir du modèle bioéconomique Orfee. Innovations Agronomiques 72: 77–89. https://doi.org/10.15454/o65nf2. [Google Scholar]
  • Vert J, Portet F. 2010. Prospective agriculture énergie 2030. L’agriculture face aux défis énergétiques. Paris, France: Centre d’études et de prospective, SSP, ministère de l’Agriculture, de l’Alimentation, de la Pêche, de la Ruralité et de l’Aménagement du territoire. [Google Scholar]
  • Vidalenc E, Meunier L, Topper B. 2013. Visions Ademe 2030–2050. Revue de l’énergie (612): 85–94. [Google Scholar]
  • Van Zanten HHE, Herrero M, Van Hal O, Röös E, Muller A, Garnett T, et al. 2018. Defining a land boundary for sustainable livestock consumption. Global Change Biology 24(9): 4185–4194. https://doi.org/10.1111/gcb.14321. [CrossRef] [PubMed] [Google Scholar]

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