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

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: adaptation, farm-models, greenhouse gases, mitigation, ruminants ImplicationsWhole-farm models are valuable tools to study the feedback and feedforward interactions between mitigation of greenhouse gas (GHG) emissions and adaptation to climate change for ruminant-based production systems. All of the processes affecting GHG emissions and farm productivity involve the cycling of C and N within the farm, most of which will be affected by climate change. However, not all farm models include such responses to climatic drivers, and there is a need for further development and testing of the models under diverse climatic conditions. Modelling of the complex interactions between farm components and the environment, including the socio-economic aspects, is instrumental for providing strategic direction to the development of climate and food-related policies. Despite the contribution of nontemperate livestock systems to total global GHG emissions, there is a dearth of specific farm models to assess GHG emissions from these regions. Modelling of soil carbon (C) fluxes is still largely absent or very simplified in many studies even though soil C has the potential to be the largest source or sink of C for grassland-based livestock systems. IntroductionAccording to The Food and Agriculture Organization (FAO) (Steinfeld et al., 2006) livestock production systems contribute about 18% of global anthropogenic greenhouse gas (GHG) emissions. Livestock is also currently one of the fastest growing agricultural subsectors in developing countries (Thornton, 2010), with projections indicating that by 2050 worldwide animal production is expected to increase by 80% compared with 2005 (Alexandratos andBruinsma, 2012). Although demand for non-ruminant meat has been increasing more rapidly than that for ruminant meats and, consequently, the importance of grasslands in livestock production and trade has been declining, increased milk and beef demand, potentially produced via grassland-based systems, is expected to increase (Fiala, 2008;Thornton, 2010). It is thus projected that the global annual growth rate of beef until 2050 will be 1.2%, clos...

Optimizing diet and pasture management to improve sustainability of U.S. beef production

“…Many studies exploring the effects of grazing on sequestration find that responsible grazing management (not over-grazing) can help to improve carbon sequestered in the soil (McSherry and Ritchie, 2013;Ostle et al, 2009;Schuman et al, 1999). Soil C-sequestration has the potential to be a substantial source or sink of carbon for grassbased livestock production systems (Del Prado et al, 2013). If carbon sequestration was included in this study, the GHG emissions baseline figures may be lower and the impacts of differing pasture management strategies may improve.…”

“…Whole-farm models have been used as tools to identify management effects on environmental impact with and without concurrent assessment of economic viability (Beauchemin et al, 2011;Capper and Hayes, 2012;Clarke et al, 2013;Foley et al, 2011;Nguyen et al, 2013;O'Brien et al, 2013;Rotz et al, 2013;Stackhouse-Lawson et al, 2012;Veysset et al, 2010;. These whole-farm assessments have been extensively reviewed Del Prado et al, 2013;Schils et al, 2007). Although the incorporation of economic http://dx.doi.org/10.1016/j.agsy.2014.06.004 0308-521X/Ó 2014 Elsevier Ltd. All rights reserved.…”

“…Increased climate variability is expected over the next century (IPCC, 2007), and since forage quality is partially dependent on temperature, humidity and rainfall (Porter and Semenov, 2005); the opportunities to improve forage quality in the face of altered weather conditions may limit the effectiveness of management changes to enhance sustainability. Whole-farm models have been used to assess the implications of climate change on livestock production and profitability (Bell et al, 2012a;Cullen and Eckard, 2011;Del Prado et al, 2013); however, social acceptability assessments are also missing from this body of literature.…”

Manure management for greenhouse gas mitigation

“…For manure management, it is important that the nutrient feedback loops are simulated; manure N applied to soil influences the productivity where feed is grown, and is itself an output from the animal feed intake. Del Prado et al (2013) discuss in more detail the requirements of whole-farm models for simulating GHG mitigation in ruminant systems. …”

“…If CP reduction is achieved by replacing grass for maize (or another arable crop), there is, however, concern that soil carbon may be lost as CO 2 owing to ploughing of existing grassland (Vellinga and Hoving, 2011). Some authors have proposed the use of mechanistic models of rumen function (Dijkstra et al, 2011), but generally they are too complex for integration in a farm scale model (Del Prado et al, 2013).Whole-farm model simulations have shown that mitigation measures that do not involve changes in manure management practices may still have implications for manure-derived GHG emissions. For example, Schils et al (2007), evaluating several models, predicted that a reduction in the length of the grazing period would give a modest decrease in GHG emissions because of a decrease in N 2 O emissions from N deposited during grazing, and because of a decrease in CH 4 from enteric fermentation as a result of better feed quality, although there is also an increase in CH 4 emissions from manure stores and a reduction in potential soil C storage.…”