Dynamic adaptation of maize and wheat production to climate change

Abstract

Agriculture represents the main source of livelihood for small scale farmers, 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 reductions 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 outperformed prescriptive decisions based on historical or projected climate change scenarios, since it was sufficiently flexible to maintain near optimum economic performance over time, as climate varied from baseline to projected future conditions. © 2009 Springer Science+Business Media B.V.