Climate change adaptation-mitigation tradeoffs in the southern Australian livestock industry: GHG emissions

Ghahramani, A. and Moore, A. D. (2013) Climate change adaptation-mitigation tradeoffs in the southern Australian livestock industry: GHG emissions. In: 20th International Congress on Modelling and Simulation (MODSIM 2013): Adapting to Change: The Multiple Roles of Modelling , 1-6 Dec 2013, Adelaide, Australia.

Text (Published Abstract)

Download (18Kb) | Preview


The trade-offs between farm system production and profitability, adaptation to climate change
and mitigation of greenhouse gas (GHG) emissions are associated with complex interactions. The GHG
mitigation consequences of effective adaptations should be taken into account when including them in
mitigation policies. In this paper, we present the results of 2 modelling studies of climate change adaptation x
mitigation interactions in southern Australian broadacre livestock production: (a) case studies of adapting to
climate change by increasing soil fertility at 2 locations that examine the effects on farm-level GHG
balances, and (b) an examination how systematic combinations of adaptations (grassland management and
animal genetic improvement) might affect future methane (CH4) emissions across the whole of southern
Australia (33.25 Mha). We used the AusFarm model to simulate the effects of climate change under the
SRES A2 scenario in 2030.
Merino ewe grazing systems were modelled at 2 locations (Lake Grace, WA and Wellington, NSW) under
historical climate and climates projected for 2030. The effects of adapting to climate change by increasing
soil fertility by adding phosphorus (P) on system productivity, profitability, N2O emissions, enteric CH4
emissions, and changes in soil carbon stocks were estimated. The negative impacts of climate change on
productivity were reduced by achieving higher soil fertility, so increasing profitability at 2030. CH4
emissions declined under 2030 climate owing to lower sustainable stocking rates, but the reduction was
smaller when soil fertility was increased. Soil C stocks were predicted to decrease under 2030 climate due to
a decrease in net primary productivity of the pasture. Increasing soil fertility was predicted to cause little
change in soil carbon stocks, because its main effect was to increase NPP consumed by livestock instead of
NPP left to be incorporated into the soil. An increase in N2O emissions under 2030 climate can be related to
changes in rainfall regime. Increased soil fertility by P could slightly reduce this increase. Higher soil P
fertility decreased N2O emissions compared with no adaptation by 7% at Lake Grace and 25% at Wellington.
CH4 is the second most important anthropogenic GHG. Ruminants (2.4 Gt CO2-eq yr-1) are the largest source
of CH4 emissions. By modelling 5 livestock enterprises at 25 representative locations, we estimated an areaaverage
ruminant CH4 emission rate of 70 kg ha-1 yr-1 during the historical period, which is consistent with
previous estimates. By decreasing optimal sustainable stocking rates (OSSR), climate change impacts were
projected to decrease ruminant CH4 emissions to 55, 51, and 42 kg ha-1 yr-1 in 2030, 2050, and 2070,
respectively. Ruminant CH4 emissions under the most profitable systemic adaptation were estimated to vary
among sites, depending mainly on OSSR. If the most profitable adaptations were fully adopted, average
ruminant CH4 emissions were estimated to increase to 84 kg ha-1 yr-1 in 2030, 83 kg ha-1 yr-1 in 2050, and 75
kg ha-1 yr-1 in 2070.
Across regions and averaging among enterprises, a linear relationship was found between CH4 emissions (kg
ha-1) and profit (A$ ha-1). A linear relationship was predicted between CH4 emission and meat production. In
2050, the most profitable combination of adaptations will result in CH4 emission changes that range between
factors of -0.82 and +1.08 relative to the reference period. In addition, CH4 emissions will reach an intensity
of 0.26 kg ha-1 yr-1 (6.5 CO2-eq kg ha-1 yr-1) for each A$1 of profit and 0.99 kg ha-1 yr-1 (24.9 CO2-eq kg ha-1
yr-1) for 1 kg of meat production. Across regions and averaging among enterprises, changes in the CH4
emissions for the most profitable combinations had a logarithmic relationship with changes in profitability
(e.g. for 2050: ΔCH4= 0.207ln (Δprofit)-0.326, R2=0.63).
Ruminant CH4 emissions will depend on animal numbers (i.e. stocking rates) that, in turn, will be controlled
by adaptation intensity. Greater intensification and ruminant CH4 emission are likely to occur, because
increasing demand of meat has been projected for the future and there is capacity for higher and profitable
production to respond this demand. Future food market projections have shown such a great demand even
under price effects.

Statistics for USQ ePrint 29987
Statistics for this ePrint Item
Item Type: Conference or Workshop Item (Commonwealth Reporting Category E) (Speech)
Refereed: Yes
Item Status: Live Archive
Additional Information: Oral presentation - Abstract only published in Conference Proceedings.
Faculty / Department / School: Current - Institute for Agriculture and the Environment
Date Deposited: 14 Nov 2016 07:43
Last Modified: 20 Jun 2017 01:12
Uncontrolled Keywords: grazing systems, climate change, nitrous oxide, methane, soil carbon
Fields of Research : 07 Agricultural and Veterinary Sciences > 0701 Agriculture, Land and Farm Management > 070103 Agricultural Production Systems Simulation
07 Agricultural and Veterinary Sciences > 0701 Agriculture, Land and Farm Management > 070105 Agricultural Systems Analysis and Modelling

Actions (login required)

View Item Archive Repository Staff Only