<mods:mods version="3.3" xsi:schemaLocation="http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-3.xsd" xmlns:mods="http://www.loc.gov/mods/v3" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><mods:titleInfo><mods:title>Modelling to evaluate agricultural adaptation to climate&#13;
change in southern Australia</mods:title></mods:titleInfo><mods:name type="personal"><mods:namePart type="given">R</mods:namePart><mods:namePart type="family">Farquharson</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:name type="personal"><mods:namePart type="given">A</mods:namePart><mods:namePart type="family">Abadi</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:name type="personal"><mods:namePart type="given">J</mods:namePart><mods:namePart type="family">Finlayson</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:name type="personal"><mods:namePart type="given">T</mods:namePart><mods:namePart type="family">Ramilan</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:name type="personal"><mods:namePart type="given">D L</mods:namePart><mods:namePart type="family">Liu</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:name type="personal"><mods:namePart type="given">M</mods:namePart><mods:namePart type="family">Anwar</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:name type="personal"><mods:namePart type="given">S</mods:namePart><mods:namePart type="family">Clark</mods:namePart><mods:role><mods:roleTerm type="text">author</mods:roleTerm></mods:role></mods:name><mods:abstract>An important issue for Australian agriculture is the capacity to adapt to predicted climate change.&#13;
The International Panel on Climate Change (IPCC) (2009) refers to adaptation as ‘adjustment in natural and&#13;
human systems in response to actual or expected climate stimuli or their effects, which moderates harm or&#13;
exploits beneficial opportunities’. Conceptualizing and evaluating adaptation options in agricultural&#13;
industries should be conducted at the farming systems level (Rickards et al. (2012), Hayman et al. (2012))&#13;
because it is at this level that management decisions are made and financial as well as natural resource&#13;
impacts will be felt. In particular whole-farm analysis can represent purposeful, goal-seeking systems (Dillon&#13;
1976) to assess farmers’ profitability and the system’s sensitivity to risks such as climate variability and&#13;
change. The potential of Australian dryland agricultural systems to adapt to climate change with perennial&#13;
plants was assessed by Farquharson et al. (2013). Perennial plants have deeper rooting systems with&#13;
improved access to soil moisture, making them better suited to warmer and drier climates. Climate data were&#13;
generated using Global Circulation Models (GCMs) downscaled to specific locations and corrected for bias&#13;
(Liu and Zuo 2012). The climate data were used to estimate growth and yield of grain crops, pastures, and an&#13;
energy-tree crop using process models such as APSIM (McCown et al. (1996)) and GrassGro (Moore et al.&#13;
(1997). Plant yield and production estimates and economic data (prices of inputs and commodities) were used&#13;
in bio-economic models (MIDAS (Kingwell and Pannell 1987) and IMAGINE (Abadi and Cooper 2004)) to&#13;
identify the most profitable land use and the cash flow of options available to growers.</mods:abstract><mods:classification authority="lcc">Climate Change</mods:classification><mods:originInfo><mods:dateIssued encoding="iso8061">2013</mods:dateIssued></mods:originInfo><mods:genre>Conference or Workshop Item</mods:genre></mods:mods>