Adaptation of maize to climate change impacts in Iran
- 411 Downloads
Adaptation is a key factor for reducing the future vulnerability of climate change impacts on crop production. The objectives of this study were to simulate the climate change effects on growth and grain yield of maize (Zea mays L.) and to evaluate the possibilities of employing various cultivar of maize in three classes (long, medium and short maturity) as an adaptation option for mitigating the climate change impacts on maize production in Khorasan Razavi province of Iran. For this purpose, we employed two types of General Circulation Models (GCMs) and three scenarios (A1B, A2 and B1). Daily climatic parameters as one stochastic growing season for each projection period were generated by Long Ashton Research Station-Weather Generator (LARS−WG). Also, crop growth under projected climate conditions was simulated based on the Cropping System Model (CSM)-CERES-Maize. LARS-WG had appropriate prediction for climatic parameters. The predicted results showed that the day to anthesis (DTA) and anthesis period (AP) of various cultivars of maize were shortened in response to climate change impacts in all scenarios and GCMs models; ranging between 0.5 % to 17.5 % for DTA and 5 % to 33 % for AP. The simulated grain yields of different cultivars was gradually decreased across all the scenarios by 6.4 % to 42.15 % during the future 100 years compared to the present climate conditions. The short and medium season cultivars were faced with the lowest and highest reduction of the traits, respectively. It means that for the short maturing cultivars, the impacts of high temperature stress could be much less compared with medium and long maturity cultivars. Based on our findings, it can be concluded that cultivation of early maturing cultivars of maize can be considered as the effective approach to mitigate the adverse effects of climate.
KeywordsMitigation DSSAT GCM HadCM3 IPCM4
The authors acknowledge the financial support of the project by Ferdowsi University of Mashhad, Iran.
- Anonymous (2013) http://en.wikipedia.org/wiki/Iran
- Boote KJ (2011) Improving soybean cultivars for adaptation to climate change and climate variability. In: Yadav SS, Redden RJ, Hatfield JL, Lotze-Campen H, Hall AE (eds) Crop adaptation to climate change. Wiley-Blackwell press, Oxford, ch26Google Scholar
- Conover WJ (1980) Practical nonparametric statistics, second ed. Wiley, New YorkGoogle Scholar
- Huang Y, Yu Y, Zhang W et al (2009) Agro-C: A biogeophysical model for simulating the carbon budget of agroecosystems. Agr Forest Meteorl 149:106–129Google Scholar
- IPCC (2000) Special Report on Emissions Scenarios (SRES): A special report of working group III of the intergovernmental panel on climate change. Cambridge University Press, CambridgeGoogle Scholar
- IPCC (Intergovernmental Panel on Climate Change) (2007) The physical science basis. Contribution of working group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, p 996, New York, NY, USAGoogle Scholar
- Jones CA, Kiniry JR (1986) CERES-Maize: A simulation model for maize growth and development. Texas A&M University Press, College StationGoogle Scholar
- Jones JW, Hoogenboom G, Porter CH et al (2003) The DSSAT cropping system model. Europ J Agronomy 18:235–265Google Scholar
- MAJ (Ministry of Agriculture of the I.R. of Iran) (2012) Planning and Economics Department, Statistics Bank of Iranian Agriculture, <http://www.maj.ir/english/Statistic/Default.asp?p=statistic>
- Nielsen, R. L. 2010. Silk development and emergence in corn. Purdue University. Available at http://www.agry.purdue.edu/ext/corn/news/timeless/silks.html. (accessed at February 2013)
- Winters P, Murgai R, Janvry A et al (1999) Climate change and agriculture: Effects on developing countries. In: Frisvold G, Kuhn B (eds) Global environmental change and agriculture. Edward Elgar Publishers, CheltenhamGoogle Scholar