Impact of climate changes on existing crop-livestock farming systems

Ghahramani, Afshin and Moore, Andrew D. (2016) Impact of climate changes on existing crop-livestock farming systems. Agricultural Systems, 146. pp. 142-155. ISSN 0308-521X

Abstract

The state of Western Australia is a major producer and exporter of crops and livestock. Mixed farming systems are typical agricultural enterprises in the Western Australian wheatbelt where climate drives the productivity and profitability of these farms and therefore the effects of likely climate change on their performance need to be understood. Here the effects of climate change projected at 2030 were evaluated compared to a baseline period (1980–1999) on mixed farming systems at paddock, enterprise and whole farm scales using the coupled APSIM and GRAZPLAN biophysical simulation models. The yield of different crops, livestock production and gross margins were assessed under current and projected climates using current farming technology and management practices. Representative mixed-farm systems were selected along a climate transect. Modelling analysis suggests that current production levels and gross margins of mixed farm systems in Western Australia will not be sustained in 2030 climate conditions except in areas of moderately high-rainfall. Whole farm gross margin declined at all site × potential climate scenarios between 1% and 22% except in moderately high rainfall where gross margin increased by up to 4% under a ‘hot and moderate change in rainfall’ climate. Projected crop yields declined for most of the crop × site × potential climate combinations, with greatest declines under a hot and dry climate (at driest margin of transect) in which wheat, barley, canola, and lupin yield declined up to 16%, 15%, 21%, and 27%, respectively. Increase in yield was predicted for wheat and barley at some of the site × potential climate s. Wheat yield increased only under moderately high rainfall region by 6% while barley increased by 1%. Simulated cropping gross margin was also shown to decline by between > 1% and 23%, except for the moderately high-rainfall site where cropping gross margins were projected to increase by up to 3%. Changes in simulated livestock production were smaller and less variable than for crop production. The change in weight of livestock sold across sites × potential climate combinations ranged between − 3% and + 3%. Livestock gross margin varied between − 11% and + 6%. Modelling results indicated a greater fertilisation effect of the elevated CO2 on pasture production than on crop yield and biomass particularly in drier sites. But however, this could not offset negative impact of climate change under hot potential climates. The main negative environmental impacts from the projected climate change were declines in annual net primary production (ANPP), ground cover and water use efficiency mostly at drier sites. Whole farm N2O emission declined significantly for the majority of site × potential climate combinations, while smaller decreases in ruminant CH4 emission were predicted. In 2030, returns from livestock enterprises are predicted to be smaller, but less variable than from cropping and with increasing probability of success in drier regions. Reduced variability in financial return is important from the perspective of whole farm risk management. Shifts in enterprise mix in dryland mixed-farming systems towards increased livestock may be a helpful strategy in adapting to climate change and managing the associated financial risks.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: Permanent restricted access to Published version, in accordance with the copyright policy oft he publisher.
Faculty / Department / School: Current - Institute for Agriculture and the Environment
Date Deposited: 24 Oct 2016 06:34
Last Modified: 02 Nov 2016 01:05
Uncontrolled Keywords: mixed farm systems; complex system; modelling; APSIM; GRAZPLAN; AusFarm; CO2
Fields of Research : 07 Agricultural and Veterinary Sciences > 0701 Agriculture, Land and Farm Management > 070105 Agricultural Systems Analysis and Modelling
Identification Number or DOI: 10.1016/j.agsy.2016.05.011
URI: http://eprints.usq.edu.au/id/eprint/29869

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