Climatic Change (2009) 94:143���156 DOI 10.1007/s10584-009-9544-z Dynamic adaptation of maize and wheat production to climate change Francisco J. Meza �� Daniel Silva Received: 22 February 2008 / Accepted: 30 December 2008 / Published online: 4 February 2009 �� Springer Science + Business Media B.V. 2009 Abstract Agriculture represents the main source of livelihood for small scale farm- ers, and a significant fraction of the gross domestic product in the case of intensive commercial agriculture. Because crop performance at the end of a growing season is strongly linked to the observed meteorological conditions, agricultural systems have been one of the main subjects of analysis to understand the impacts of both climatic variability and climatic change. As climate scientists make progress understanding the key elements of the atmosphere and provide with better projections of climate change scenarios, more effort is devoted to impact assessment and the evaluation of adaptation strategies to reduce vulnerability of crops and farmers. The objective of this work was to document the impacts of climate change on maize and wheat yields in Chile as well as to describe the dynamics of adaptation (i.e. changes in management decisions over time) that will take place, considering that farmers can ���learn��� from previous crop yield outcomes. Yield outcomes were obtained using a crop simulation model run under climate change scenarios based on HadCM3 projections. A simple decision model for a risk neutral farmer was used to investigate changes in optimum management decisions over time. Maize showed yield reduc- tions in the order of 5% to 10%. Under irrigation, the best alternative for adaptation corresponded to adjustments in sowing dates. In the case of winter wheat significant yield reductions were observed for the no adaptation case. Because this crop showed positive responses to the increase of carbon dioxide, adaptation strategies were very effective counterbalancing the impacts of a warmer and drier environment. Dynamic adaptation was referred here to the introduction of small adjustments in management based on previous observed changes in productivity. This type of adaptation strategy F. J. Meza (B) �� D. Silva Facultad de Agronom��a e Ingenier��a Forestal, Pontificia Universidad Cat��lica de Chile, Casilla, 306-22 Santiago, Chile e-mail: fmeza@uc.cl F. J. Meza Centro Interdisciplinario de Cambio Global, Pontificia Universidad Cat��lica de Chile, Santiago, Chile

144 Climatic Change (2009) 94:143���156 outperformed prescriptive decisions based on historical or projected climate change scenarios, since it was sufficiently flexible to maintain near optimum economic per- formance over time, as climate varied from baseline to projected future conditions. 1 Introduction Agriculture is one of the most susceptible systems to climate change since me- teorological variables determine resource availability (i.e. solar radiation, water, carbon dioxide) and control fundamental processes involved in crop growth and development. Literature shows a wide variety of examples where researchers have addressed the effects of climate variability on crops (Carlson et al. 1996 Phillips et al. 1998 Podest�� et al. 1999 Rubas et al. 2006) as well as the impacts of climate change on crop yields and resource capture (Kaiser et al. 1993 Rosenzweig and Parry 1994 Riha et al. 1996 Reilly et al. 2003 Parry et al. 2004). These studies have contributed to understand the degree of vulnerability of crops under variable climatic conditions. Even though agricultural responses to climate change tend to be crop and location specific, there is ample evidence that most agricultural systems will be reshaped. In some cases, projected changes in productivity will force farmers to adopt different management practices, while in others the impacts of climate change will imply that current varieties (species) will no longer be a feasible economic alternative. Although there is still considerable uncertainty regarding to the magnitude of future climatic changes, it is necessary to assess the impacts that can be expected on agricultural production and evaluate alternatives of adaptation, for both scientific and policy making reasons. As new insights about the relationship between climate change and crop produc- tivity are generated, more attention is given to the identification of specific changes in current management practices to either reduce negative consequences or take advantage of future favorable conditions. Agricultural adaptation, defined as ���the adjustment in agricultural systems in response to actual or expected climatic stimuli or their effects, to moderate harm or exploit beneficial opportunities��� (IPCC 2001) becomes a key element in climate change policy that must be studied in depth. Researchers have performed impact assessments and alternatives evaluation fol- lowing a wide variety of methodologies. Some examples are historical analogs, Ri- cardian analysis and empirical relationships (Tao et al. 2006 Mendelsohn and Dinar 1999 Polsky and Easterling 2001 Webb et al. 2008). However, the most common approach corresponds to the use of crop simulation models to estimate the potential impacts of projected climatic conditions on agricultural systems. In this framework, daily meteorological variables consistent with current climatic conditions and climate change projections are generated. Then these time series, in conjunction with soil parameters, are used as input variables for crop simulation models that represent the dynamics of plant growth and development. Finally the results of these simulations (i.e. yields, length of the growing period, total water and nutrient uptake, etc.) for both, current and future climatic conditions are compared. Impacts of climate change are then expressed as absolute or relative changes in crop productivity and resource use. Because crop models allow the representation of different agricultural management practices, adaptation strategies are explored simulating the results of a set of alternatives and cultivars, choosing the ones that would maximize productivity or any other economic index under projected climatic conditions.