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Identification of beef production farms in the Pampas and Campos area that stand out in economic and environmental performance

Modernel Pablo, Dogliotti Santiago, Alvarez Stéphanie, Corbeels Marc, Picasso Valentin, Tittonell Pablo, Rossing Walter A.H.. 2018. Identification of beef production farms in the Pampas and Campos area that stand out in economic and environmental performance. Ecological Indicators, 89 : 755-770.

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Résumé : Worldwide, native grasslands are being converted to non-native pastures and cropland. This process threatens local grassland biomes as well as the livelihoods of farm families that utilize these grasslands. In the Río de la Plata grasslands region meat production and multispecies native grasslands have coexisted for more than 400 years. Low levels of meat productivity and farm income, however, trigger replacement of native grasslands by crops and leys and threaten the survival of local beef farming systems. We studied the economic and environmental performance of beef farming in the region based on interviews and field measurements on 280 case study farms with the following aims: (a) to identify the multi-functional economic and environmental performance of beef farms across the Rio de la Plata grasslands biome; (b) to identify farms with 'outstanding' multi-functional performance; (c) to compare performance levels with those found in other regions; and (d) to discuss the implications of the outstanding farms for the development of new systems of meat production. The representativeness of the case study farms was ascertained by comparing them with a farm typology constructed from survey data of 15,448 beef farms situated predominantly on native grasslands in Argentina, Brazil and Uruguay. We identified seven farm types on the basis of farm size, labour, farm specialization, land use and stocking rate. We identified positive deviant farms based on Pareto-ranking and compared these with a classification based on threshold values provided by experts. Out of the 280 farms, 41 were ranked as Pareto-optimal, i.e. outperformed other farms in one or more indicators without being outperformed in other indicators. Out of these, 5 were positive deviants, achieving on average 192 kg LW ha−1 yr−1 of livestock productivity and 201 US$ ha−1 year−1 farm income, having most favourable values for fossil energy consumption, phosphorus balance, carbon footprint and having over 95% of their land under native grassland as a proxy for biodiversity conservation value. Four of these farms belonged to farm types that together represented 55% of the population, suggesting scope for widescale improvement. Compared to the values reported for the OECD countries the beef farming systems of the Río de la Plata grasslands region consume less energy and positive deviant farms demonstrated approximately average livestock productivity and carbon footprint. Increasing livestock productivity in the Rio de la Plata grasslands region resulted in a stronger decline of the carbon footprint without compromising the current negligible levels of fossil fuel energy use. Further elucidation of management practices that lead to positive deviant performance will require modelling of the interaction of pasture and herd dynamics at farm level and is needed to support targeted policy support for sustainable natural grassland-based beef production in the region.

Mots-clés Agrovoc : Pastoralisme, Bovin, Bovin de boucherie

Mots-clés géographiques Agrovoc : Argentine, Brésil, Uruguay

Classification Agris : L01 - Elevage - Considérations générales

Axe stratégique Cirad : Axe 1 (2014-2018) - Agriculture écologiquement intensive

Auteurs et affiliations

  • Modernel Pablo, Wageningen University (NLD) - auteur correspondant
  • Dogliotti Santiago, Universidad de la Republica (URY)
  • Alvarez Stéphanie, Wageningen University (NLD)
  • Corbeels Marc, CIRAD-PERSYST-UPR AIDA (KEN)
  • Picasso Valentin, Universidad de la Republica (URY)
  • Tittonell Pablo, Wageningen University (NLD)
  • Rossing Walter A.H., Wageningen University (NLD)

Source : Cirad-Agritrop (https://agritrop.cirad.fr/587544/)

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