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Whole-farm models to quantify greenhouse gas emissions and their potential use for linking climate change mitigation and adaptation in temperate grassland ruminant-based farming systems

Published online by Cambridge University Press:  06 June 2013

A. Del Prado ,
P. Crosson ,
J. E. Olesen  and
C. A. Rotz
A. Del Prado*
Affiliation:
Basque Centre for Climate Change (BC3), Alameda Urquijo, 4, 4°-1a /48008 Bilbao, Spain
P. Crosson
Affiliation:
Livestock Systems Research Department, Animal & Grassland Research and Innovation Centre, Teagasc, Grange, Dunsany, Co. Meath, Ireland
J. E. Olesen
Affiliation:
Department of Agroecology, Aarhus University, Blichers Allé 20, PO Box 50, DK-8830 Tjele, Denmark
C. A. Rotz
Affiliation:
USDA-ARS, Pasture Systems and Watershed Management Research Unit, University Park, 3702 Curtin Rd., PA 16802, USA
*
†E-mail: [email protected]
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Abstract

The farm level is the most appropriate scale for evaluating options for mitigating greenhouse gas (GHG) emissions, because the farm represents the unit at which management decisions in livestock production are made. To date, a number of whole farm modelling approaches have been developed to quantify GHG emissions and explore climate change mitigation strategies for livestock systems. This paper analyses the limitations and strengths of the different existing approaches for modelling GHG mitigation by considering basic model structures, approaches for simulating GHG emissions from various farm components and the sensitivity of GHG outputs and mitigation measures to different approaches. Potential challenges for linking existing models with the simulation of impacts and adaptation measures under climate change are explored along with a brief discussion of the effects on other ecosystem services.

Keywords

adaptationfarm-modelsgreenhouse gasesmitigationruminants
Type
Full Paper
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animal , Volume 7 , Issue s2: Greenhouse Gases & Animal Agriculture Conference (GGAA 2013), 23rd ‐ 26th June 2013, Dublin, Ireland , June 2013 , pp. 373 - 385
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Copyright © The Animal Consortium 2013 

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