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.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Carlson RE, Todey DP, Taylor SE (1996) Midwestern corn yields and weather in relation to extremes of the southern oscillation. J Prod Agric 9:347–352
Easterling WE, Chetri N, Niu X (2003) Improving the realism of modeling agronomic adaptation to climate change: simulating technological substitution. Clim Change 60(1–2):149–173
Fuhrer J (2003) Agroecosystem responses to combinations of elevated CO2, ozone, and global climate change. Agric Ecosyst Environ 97:1–20
Goudriaan J, Unsworth MH (1990) Implication of increasing carbon dioxide and climate change for agricultural productivity and water resources. In: Impact of carbon dioxide, trace gases and climate change on global agriculture. ASA Special Publication, vol 53. American Society of Agronomy, Crop Science Society of America, and Soil Science of America, Madison, WI, pp 111–130
IPCC (2001) Climate change 2001: impacts, adaptation, and vulnerability. Contribution of working group II to the third assessment report of the intergovernmental panel on climate change
Jones JW, Hoogenboom G, Porter CH, Boote KJ, Batchelor WD, Hunt LA, Wilkens PW, Singh U, Gijsman AJ, Ritchie JT (2003) The DSSAT cropping system model. Eur J Agron 18:235–265
Kaiser HM, Riha SJ, Wilks DS, Rossiter DG, Sampath R (1993) A farm-level analysis of economic and agronomic impacts of gradual climate warming. Am J Agric Econ 75(2):387–398
Mendelsohn R, Dinar A (1999) Climate change, agriculture, and developing countries: does adaptation matter? World Bank Res Obs 14(2):277–293
Meza FJ, Varas E (2000) Estimation of mean monthly solar global radiation as a function of temperature. Agric For Meteorol 100:231–241
Meza FJ, Silva D, Vigil H (2008) Climate change impacts on irrigated maize in Mediterranean climates. Evaluation of double cropping as an emerging adaptation alternative. Agric Syst 98:21–30
Parry ML (1990) Climate change and world agriculture. Earthscan, London
Parry ML, Rosenzweig C, Iglesias A, Livermore M, Fisher G (2004) Effects of climate change on global food production under SRES emissions and socio-economic scenarios. Glob Environ Change 14:53–67
Phillips JG, Cane MA, Rosenzweig C (1998) ENSO seasonal rainfall patterns, and simulated maize yield variability in Zimbabwe. Agric For Meteorol 90:39–50
Podestá GP, Messina CD, Grondona MO, Magrin GO (1999) Associations between grain crop yields in central-eastern Argentina and El Niño-Southern Oscillation. J Appl Meterol 38:1488–1498
Polsky C, Easterling E (2001) Adaptation to climate variability and change in the US Great Plains: a multi-scale analysis of Ricardian climate sensitivities. Agric Ecosyst Environ 85(1–3):133–144
Reilly J, Tubiello F, McCarl B, Abler D, Darwin R, Fuglie K, Hollinger S, Izaurralde C, Jagtap S, Jones J, Mearns L, Ojima D, Paul E, Paustian K, Riha S, Rosenberg N, Rosenzweig C (2003) U.S. agriculture and climate change: new results. Clim Change 57(1):43–69
Richardson CW (1981) Stochastic simulation of daily precipitation, temperature, and solar radiation. Water Resour Res 17:182–190
Riha SJ, Wilks DS, Simoens P (1996) Impact of temperature and precipitation variability on crop model predictions. Clim Change 32(3):293–311
Rosenzweig C, Parry ML (1994) Potential impact of climate change on world food supply. Nature 367:133–138
Rubas DJ, Hill HSJ, Mjelde JW (2006) Economics and climate applications: exploring the frontier. Clim Res 33:43–54
Schneider S, Easterling WE, Mearns LO (2000) Adaptation: sensitivity to natural variability, agent assumptions and dynamic climate changes. Clim Change 45(1):203–221
Tao F, Yokozawa M, Xu Y, Hayashi Y, Zhang Z (2006) Climate changes and trends in phenology and yields of field crops in China, 1981–2000. Agric For Meteorol 138:82–92
Tubiello FN, Donatelli M, Rosenzweig C, Stöckle CO (2000) Effects of climate change and elevated CO2 on cropping systems: model predictions at two Italian locations. Eur J Agron 13:179–189
Webb LB, Wheton PH, Barlow EWR (2008) Climate change and winegrape quality in Australia. Clim Res 36:99–111
Wilkens PW, Hoogenboom G, Porter CH, Jones JW, Uryasev O (2004) Decision support system for agrotechnology transfer version 4.0. volume 2. DSSAT v4: data management and analysis tools. University of Hawaii, Honolulu, HI
Wilks DS, Wilby RL (1999) The weather generation game: a review of stochastic weather models. Prog Phys Geogr 23(3):329–357
Wolf J, Van Diepen CA (1994) Effects of climate change on silage maize production potential in the European Community. Agric For Meteorol 71:33–60
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Meza, F.J., Silva, D. Dynamic adaptation of maize and wheat production to climate change. Climatic Change 94, 143–156 (2009). https://doi.org/10.1007/s10584-009-9544-z
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10584-009-9544-z