A simple model to assess the sensitivity of grassland dairy systems to scenarios of seasonal biomass production variability
2013
Lurette, Amandine | Moulin, Charles-Henri | Aubron, Claire | Systèmes d'élevage méditerranéens et tropicaux (UMR SELMET) ; Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro) | Projet Climfourel, Conseil Régional of Rhône-Alpes, Languedoc-Roussillon et Midi-Pyrénées
In recent decades, dairy herds of the peri-Mediterranean area have coped with high climatic variability, which has contributed to weakening their economic equilibrium. Survey studies highlighted that climatic impact depends on the strategies of farmers, related to forage autonomy. To explain this observation precisely and assess the opportunity of changing forage strategy as an adaptation to cope with climatic variability over the long term, a simulator was developed to explore the impact of several biomass production variability scenarios on forage purchases. This approach was applied on dairy cattle farms in a mountain area in the South of France (Ardèche), with forage systems based on grass (hay and pasture), using several levels of forage autonomy. A computer application was developed through a partnership project between our research team and officers of an extension board. We then validated the ability of the simulator to account for the operation of special cases of farms after calibration and studied the model sensitivity to key parameter variations. Then we explored (i) how the simulator can be used to assess the sensitivity of six dairy farms to biomass production variability and (ii) the value of an adaptation strategy with advance forage stockpiling. The sensitivity analysis highlights that the purchase of forage was highly sensitive to production variation during March, April and May. The farms which used grazing the most, exhibited a lower standard deviation than the other farms. Variation obtained for the standard deviation of forage bought was not only explained by the forage autonomy but might depend on other characteristics such as time of turnout and surface allocation. The succession of disadvantageous years was tested. The decrease in the stock differed according to the forage autonomy of farms. Whereas farms which were only just autonomous bought forage as of the first disadvantageous year, farms with forage autonomy of 120% can resist repeated biomass production variability for 8 years with the constitution of remaining stocks of forage. The simulator developed here is simple enough both to explore the sensitivity of a dairy system and promote the debate on the results with farmers and advisers.
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