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Recent climate variability and its impacts on soybean yields in Southern Brazil

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Abstract

Recent climate variability in rainfall, temperatures (maximum and minimum), and the diurnal temperature range is studied with emphasis on its influence over soybean yields in southern Brazil, during 1969 to 2002. The results showed that the soybean (Glycine max L. Merril) yields are more affected by changes in temperature during summer, while changes in rainfall are more important during the beginning of plantation and at its peak of development. Furthermore, soybean yields in Paraná are more sensitive to rainfall variations, while soybean yields in the Rio Grande do Sul are more sensitive to variations in temperature. Effects of interannual climatic variability on soybean yields are evaluated through three agro-meteorological models: additive Stewart, multiplicative Rao, and multiplicative Jensen. The Jensen model is able to reproduce the interannual behavior of soybean yield reasonably well.

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References

  • Alexander LV, Zhang X, Peterson TC, Caesar J, Gleason B, Klein Tank AMG, Haylock M, Collins D, Trewin B, Rahim F, Tagipour A, Kumar Kolli R, Revadekar JV, Griffiths G, Vincent L, Stephenson DB, Burn J, Aguilar E, Brunet M, Taylor M, New M, Zhai P, Rusticucci M, Luis Vazquez Aguirre J (2006) Global observed changes in daily climate extremes of temperature and precipitation. J Geophys Res 111:D05109. doi:10.1029/2005JD006290

    Article  Google Scholar 

  • Barros V, Doyle M (1996) Precipitation trends in Southern South America to the east of the Andes. Center for Ocean-Land-Atmosphere Studies. Report N° 26. Editors J. l. Kinter III and E. K. Schneider. pp 76-80

  • Bendat JS, Pearson AG (1986) Radom data—analysis and measurement procedures, 2nd edn. Wiley, New York, p 525

    Google Scholar 

  • Berlato MA, Farenzena H, Fontana DC (2005) Association between El Niño Southern Oscillation and corn yield in Rio Grande do Sul State. Pesq agropec bras 40:423-432 http://www.scielo.br/pdf/%0D/pab/v40n5/24422.pdf

  • Brevedan RE, Egli DB (2003) Short periods of water stress during seed filling, leaf senescence, and yield of soybean. Crop Sci 43:2083–2088

    Article  Google Scholar 

  • Doorenbos J, Kassam AH (1979) Yield Response to Water. Food and Agriculture Organization, Irrigation and Drainage Paper, 33. Rome, Italy.

  • Embrapa Soybean (2008) Brazilian Agricultural Research Corporation's. Production Technology of Soybean over Central Region of Brazil 2009/2010. http://www.cnpso.embrapa.br/download/Tecnol2009.pdf. Accessed 14 July 2009, 262 pp

  • Fedorov AV, Philander SGH (2000) Is El Niño changing? Science 288:1997–2002

    Article  Google Scholar 

  • Fraisse CW, Cabrera VE, Breuer NE, Baez J, Quispe J, Matos E (2008) El Niño – Southern Oscillation influences on soybean yields in eastern Paraguay. Int J Climatol 28:1399–1407

    Article  Google Scholar 

  • Grimm AM, Ferraz SET, Gomes J (1998) Precipitation anomalies in Southern Brazil associated with El Niño and La Niña events. J Climate 11:2863–2880

    Article  Google Scholar 

  • Hulme M, Sheard N (1999) Climate Change Scenarios for Brazil. Norwich. Climatic Research Unit, 6 pp

  • Huntingford C, Lambert FH, Gash JHC, Taylor CM, Challinor AJ (2005) Aspects of climate change prediction relevant to crop productivity. Phil Trans R Soc B 360:1999–2009

    Article  Google Scholar 

  • IBGE - Brazilian Institute Geography and Statistics (2009) Database Clusters (SIDRA in Portuguese). http://www.sidra.ibge.gov.br. Accessed 28 January 2009

  • IPCC - Intergovernmental Panel on Climate Change (2001) The Scientific Basis. In: Houghton JT, Ding Y, Griggs DJ, Noguer M, Van Der Linden PJ, Dai X, Maskell K, Johnson CA (eds) Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge Univ. Press, Cambridge, p 881

    Google Scholar 

  • IPCC - Intergovernmental Panel on Climate Change (2007) Observations: Surface and atmospheric climate change. In: Hoskins BJ, Karl TR, Jallow B (eds) Climate Change 2007: The Physical Science Basis, Working Group I Contribution to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, pp 235–336

    Google Scholar 

  • Jensen ME (1968) Water consumption by agricultural plants. Academic, New York, pp 1–22, 2

    Google Scholar 

  • Karl TR, Knight RW, Gallo KP et al (1993) Asymmetric trends of daily maximum and minimum temperature. Bull Amer Meteor Soc 74:1007–1023

    Article  Google Scholar 

  • Lobell DB (2007) Changes in diurnal temperature range and national cereal yields. Agri For Meteorol 145:229–238

    Article  Google Scholar 

  • Magrin G, Gay C, Cruz D, Giménez JC, Moreno AR, Nagy GJ, Nobre C, Villamizar A (2007) Latin America. In: Parry ML, Canziani OF, Palutikof JP, Van der Linden PJ, Hanson C (eds) Climate Change 2007. Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, pp 581–615

    Google Scholar 

  • Mitchell TD, Jones PD (2005) An improved method of constructing a database of monthly climate observations and associated high-resolution grids. Int J Climatol 25:693–712

    Article  Google Scholar 

  • Nicholls N (1997) Increased Australian wheat yield due to recent climate trends. Nature 387:484–485

    Article  Google Scholar 

  • Nuñez MN, Ciapessoni HH, Rolla A, Kalnay E, Cai M (2008) Impact of land use and precipitation changes on surface temperature trends in Argentina. J Geophys Res 113:D06111. doi:10.1029/2007JD008638

    Article  Google Scholar 

  • Pascale AJ (1969) Tipos agroclimáticos para el cultivo de la soya en la Argentina. Revista de la Facultad de Agronomía e Veterinaria. B Aires 17:31–38

    Google Scholar 

  • Peterson TC (2003) Assessment of urban versus rural in situ surface temperatures in the contiguous United States: No difference found. J Climate 16:2941–2959

    Article  Google Scholar 

  • Podestá G, Letson D, Messina C, Royce F, Ferreyra RA, Jones J, Hansen J, Llovet I, Grondona M, O’brien JJ (2002) Use of ENSO-related climate information in agricultural decision making in Argentina: A pilot experience (2002). Agric Syst 74:371–392

    Article  Google Scholar 

  • Rao NH, Sarma PBS, Chander S (1988) A simple dated water-production function for use in irrigated agriculture. Agric Water Manage 13:25–32

    Article  Google Scholar 

  • Rao VB, Cavalcanti IFA, Hada K (1996) Annual variation of rainfall over Brazil and water vapor characteristics over South America. J Geophys Res 101:26539–26551

    Article  Google Scholar 

  • Rusticucci M, Barrucand M (2001) Climatología de temperaturas extremas en la Argentina. Consistencia de datos. Relación entre la temperatura media estacional y la ocurrencia de extremos. Meteorologica 26:69–84

    Google Scholar 

  • Schnepf RD, Dohlman E, Bolling C (2001) Agriculture in Brazil and Argentina: Developments and Prospects for Major Field Crops. Market and Trade Economics Division, Economic Research Service, U.S. Department of Agriculture, Agriculture and Trade Report, WRS-01-03

  • Seager R, Ting M, Davis M, Cane MA, Naik N, Nakamura J, Li C, Cook E, Stahle DW (2009) Mexican drought. An observational, modeling and tree ring study of variability and climate change. Atmósfera 22:1–31

    Google Scholar 

  • Slingo JM, Challinor AJ, Hoskins BJ, Wheeler TR (2005) Introduction: food crops in a changing climate. Phil Trans R Soc B 360:1983–1989. doi:10.1098/rstb.2005.1755

    Article  Google Scholar 

  • Stewart JI, Hagan RM, Pruitt W (1976) Production functions and predicted irrigation programmes for principal crops as required for water resources planning and increased water use efficiency. Final report. Washington. U.S. Department of Interior, 80 pp

  • Thornthwaite CW, Mather RJ (1955) The water Balance. Laboratory of Climatology, New Jersey, p 104, 8

    Google Scholar 

  • Tiku ML (1971) Power function of the F-test under non-normality Situation. J Am Statistic Assoc 66:913–916

    Article  Google Scholar 

  • Venegas SA, Mysak LA, Straub DN (1998) Atmosphere-ocean coupled variability in the south Atlantic. J Climate 10:2904–2920

    Article  Google Scholar 

  • Vincent LA, Petterson TC, Barros VR, Marino MB, Rusticucci M, Carrasco G, Ramirez E, Alves LM, Ambrizzi T, Berlato MA, Grimm AM, Marengo JA, Molion LC, Moncunill DF, Rebello E, Anunciação YMT, Quintana-Gomes J, Santos JL, Baez J, Coronel G, Garcia J, Trebejo I, Bidegain M, Haylock MR, Karoly D (2005) Observed trends in indices of daily temperature extremes in South America 1960–2000. J Climate 18:5011–5023

    Google Scholar 

  • Wilks DS (1995) Statistical Methods in the Atmospheric Sciences: An Introduction. Academic, New York, 467 pp

    Google Scholar 

  • World Bank (2009) Country Note on Climate Change Aspects in Agriculture. http://siteresources.worldbank.org/INTLAC/Resources/Climate_BrazilWeb.pdf. Accessed 20 December 2009, 16 pp

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Acknowledgments

This paper is part of the first author’s Ph.D. thesis at the National Institute for Space Research (Brazil). The authors thank the National Institute of Meteorology (Brazil), especially Luiz André R. dos Santos and Andrea M. Ramos for their helpful guidance on the statistical techniques. The data used in this study were provided by the University of East Anglia and the Brazilian Institute of Geography and Statistics, which records, manages, and distributes this dataset.

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  1. Danielle Barros Ferreira

    Present address: Coordenação de Desenvolvimento e Pesquisa (CDP), Instituto Nacional de Meteorologia, Eixo Monumental Via S1, Sudoeste, Brasília, DF, 70680-900, Brazil

Authors and Affiliations

  1. Instituto Nacional de Pesquisas Espaciais (INPE), São José dos Campos, 12227-010, SP, Brazil

    Danielle Barros Ferreira & V. Brahmananda Rao

  2. Instituto Nacional de Meteorologia (INMET), Brasília, 70680-900, DF, Brazil

    Danielle Barros Ferreira

Authors
  1. Danielle Barros Ferreira
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  2. V. Brahmananda Rao
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Correspondence to Danielle Barros Ferreira.

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Ferreira, D.B., Rao, V.B. Recent climate variability and its impacts on soybean yields in Southern Brazil. Theor Appl Climatol 105, 83–97 (2011). https://doi.org/10.1007/s00704-010-0358-8

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