Abstract
Extensive livestock agroforestry systems in Mediterranean areas, characterized by seasonality and large use of available biomass, are important for the subsistence of the local population and the ecosystem services provided. However, they often show low production levels and poor efficiency in resource use, with low profitability and high environmental impact in terms of methane emissions. This work aimed to model a Sardinian cow-calf farm scenario, a typical agroforestry Mediterranean system, in order to dynamically predict, on monthly basis, its profitability and both methane and nitrogen emissions expressed as CO2 equivalents (CO2eq.). The model, built on Stella® using range Kutta integrations, was initially developed reproducing a stock and flow diagram of the bio-economic model of Hirooka et al., (1998, Animal Science 66: 607–621). The model was then adapted and calibrated to perform simulations on the extensive agroforestry Sardinian beef farms by using data from a local survey. Inputs included initial animal stocks, replacement rates, ages at weaning and slaughtering, fertility rates, mortality rates. As main outputs the model predicts the monthly pattern of the enteric methane emissions (Tier 2, IPCC guidelines), nitrogen excretion, methane and manure emissions and gross revenues from meat. In addition, it calculates herd dynamics (stocks of cows per year of age, calves, births, deaths, replacement heifers, sold beef, culled cows), weight curves of animal categories and meat production from each category. The enteric greenhouses gas emissions of the typical scenario resulted equal to 12.4 kg of CO2eq. per kg of meat. A higher replacement rates (+5%/yr) and a lower fertility rate (-10%/yr) reduce gross revenues by 2.3% and 5.9%, where as increase animal emissions by 2.1% and 9.1%, respectively.