Minimizing direct greenhouse gas emissions in livestock production: The need for a metabolic theory

Gonçalo M. Marques, Carlos M.G.L. Teixeira, Tânia Sousa, Tiago G. Morais, Ricardo F.M. Teixeira and Tiago Domingos

Ecological Modelling, 2020, vol. 434, issue C

Abstract: Livestock production is one of the main contributors to global greenhouse gas (GHG) emissions. The tools provided by the Intergovernmental Panel on Climate Change to estimate GHG emissions (Tier 1 and Tier 2) cannot be used as a tool for advising farmers or national policy on how to minimize GHG emissions because these estimates are not explicitly related to any metabolic properties. For that, we need a metabolic model that obeys mass and energy balances and that models the trade-offs between different allocations of energy in the organism, throughout the life-cycle, as a function of environmental variables such as temperature and the amount and type of food. The Dynamic Energy Budget (DEB) Theory ensures mass conservation and models the transformations of state variable and product formation, allowing for explicit GHG emissions estimates. Therefore, we used this theory to build models for four bovine breeds – Alentejana, Angus, Charolais and Limousin. The goodness-of-fit of DEB models to data is good for all breeds. Differences in DEB breed specific parameters, such as the maximum reserve density and the maximum specific assimilation rate, explain differences in GHG emissions, ultimate lengths and weights and von Bertalanffy growth rates. Accumulated methane and nitrogen production ranges between 0.2 and 2, and 0.1 and 0.7 kg per kg of body weight, respectively. In terms of accumulated direct GHG emissions, there is a strong dependence on breed and age.

Keywords: Climate change; Livestock; Beef; Dynamic energy budget; Metabolism; Enteric fermentation; Animal growth; Bovine excretion; Industrial ecology (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:434:y:2020:i:c:s030438002030329x

DOI: 10.1016/j.ecolmodel.2020.109259

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