Editorial Type:
Article
Article Type:
Research Article

Associations between Grain Crop Yields in Central-Eastern Argentina and El Niño–Southern Oscillation

Guillermo P. Podestá Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, Florida

Search for other papers by Guillermo P. Podestá in
Current site
Google Scholar
PubMed Close
,
Carlos D. Messina Facultad de Agronomía, Universidad de Buenos Aires, Buenos Aires, Argentina

Search for other papers by Carlos D. Messina in
Current site
Google Scholar
PubMed Close
,
Martín O. Grondona Instituto de Clima y Agua, Instituto Nacional de Tecnología Agropecuaria, Castelar, Argentina

Search for other papers by Martín O. Grondona in
Current site
Google Scholar
PubMed Close
, and
Graciela O. Magrin Instituto de Clima y Agua, Instituto Nacional de Tecnología Agropecuaria, Castelar, Argentina

Search for other papers by Graciela O. Magrin in
Current site
Google Scholar
PubMed Close
Print Publication:
01 Oct 1999
DOI:
https://doi.org/10.1175/1520-0450(1999)038<1488:ABGCYI>2.0.CO;2
Page(s):
1488–1498
Restricted access

Abstract

Associations are investigated between yields of major crops in the Argentine Pampas (central-eastern Argentina) and El Niño–Southern Oscillation (ENSO) phase. For maize and sorghum, higher (lower) yield anomalies occur more frequently than expected by chance alone during warm (cold) ENSO events. For both crops, the depression of yields during cold events is, on average, larger and less variable than yield increases are during warm events. A yield decrease during cold events also is observed in soybean yields, although the effect of warm events is not statistically significant. There is a marginally significant tendency for low sunflower yields to occur less frequently than expected during cold events. Wheat, the only winter crop considered, did not show an association with ENSO. Precipitation anomalies during October–February (the period with strongest ENSO signal in the Pampas) are summarized through principal component analysis. Precipitation anomalies during November–January are significantly correlated with maize, sorghum, and soybean yield anomalies. In turn, those precipitation anomalies show a distinct ENSO signal. Late spring–early summer precipitation, then, appears to mediate associations between ENSO phase and yields of maize, sorghum, and soybean in the Pampas.

Corresponding author address: Dr. Guillermo P. Podestá, University of Miami, RSMAS/MPO, 4600 Rickenbacker Causeway, Miami, FL 33149-1098.

Abstract

Associations are investigated between yields of major crops in the Argentine Pampas (central-eastern Argentina) and El Niño–Southern Oscillation (ENSO) phase. For maize and sorghum, higher (lower) yield anomalies occur more frequently than expected by chance alone during warm (cold) ENSO events. For both crops, the depression of yields during cold events is, on average, larger and less variable than yield increases are during warm events. A yield decrease during cold events also is observed in soybean yields, although the effect of warm events is not statistically significant. There is a marginally significant tendency for low sunflower yields to occur less frequently than expected during cold events. Wheat, the only winter crop considered, did not show an association with ENSO. Precipitation anomalies during October–February (the period with strongest ENSO signal in the Pampas) are summarized through principal component analysis. Precipitation anomalies during November–January are significantly correlated with maize, sorghum, and soybean yield anomalies. In turn, those precipitation anomalies show a distinct ENSO signal. Late spring–early summer precipitation, then, appears to mediate associations between ENSO phase and yields of maize, sorghum, and soybean in the Pampas.

Corresponding author address: Dr. Guillermo P. Podestá, University of Miami, RSMAS/MPO, 4600 Rickenbacker Causeway, Miami, FL 33149-1098.

Save
Cover Journal of Applied Meteorology and Climatology
Journal of Applied Meteorology and Climatology

  • Adams, R. M., K. J. Bryant, B. A. McCarl, D. M. Legler, J. J. O’Brien, A. Solow, and R. Weiher, 1995: Value of improved long-range weather forecasts. Contemp. Econ. Policy,13, 10–19.

  • Barnston, A. G., and Coauthors, 1994: Long-lead seasonal forecasts—Where do we stand? Bull. Amer. Meteor. Soc.,75, 2097–2114.

  • Cane, M. A., G. Eshel, and R. W. Buckland, 1994: Forecasting Zimbabwean maize yield using eastern equatorial Pacific sea surface temperature. Nature,370, 204–205.

  • Cantagallo, J. E., C. A. Chimenti, and A. J. Hall, 1999: Number of seeds per unit area in sunflower correlates well with a photothermal quotient. Crop Sci., in press.

  • Carlson, R. E., D. P. Todey, and S. E. Taylor, 1996: Midwestern corn yield and weather in relation to extremes of the Southern Oscillation. J. Prod. Agric.,9, 347–352.

  • Chen, D., S. E. Zebiak, A. J. Busalacchi, and M. A. Cane, 1995: An improved procedure for El Niño forecasting: Implications for predictability. Science,269, 1699–1702.

  • Cleveland, R. B., W. S. Cleveland, J. E. McRae, and I. Terpenning, 1990: STL: A seasonal-trend decomposition procedure based on Loess. J. Off. Stat.,6, 3–73.

  • Cleveland, W. S., and S. J. Devlin, 1988: Locally-weighted regression:An approach to regression analysis by local fitting. J. Amer. Stat. Assoc.,83, 596–610.

  • Connor, D. J., and V. O. Sadras, 1992: Physiology of yield expression in sunflower. Field Crops Res.,30, 333–389.

  • Dai, A., I. Y. Fung, and A. D. Del Genio, 1997: Surface observed global land precipitation variations during 1900–88. J. Climate,10, 2943–2962.

  • Díaz, A. F., C. D. Studzinski, and C. R. Mechoso, 1998: Relationships between precipitation anomalies in Uruguay and southern Brazil and sea surface temperature in the Pacific and Atlantic Oceans. J. Climate,11, 251–271.

  • Díaz, R. A., 1995: Seeking practical applications for short climate predictions in the agriculture of Argentina. International Research Institute for Climate Prediction Rep. IRIP-TL-95/1, 40 pp. [Available from INTA, Instituto de Clima y Agua, 1712 Castelar, Prov. Buenos Aires, Argentina.].

  • Dilley, M., 1997: Climatic factors affecting annual maize yields in the Valley of Oaxaca, Mexico. Int. J. Climatol.,17, 1549–1557.

  • Garnett, E. R., and M. L. Khandekar, 1992: The impact of large-scale atmospheric circulations and anomalies on Indian monsoon droughts and floods and on world grain yields—A statistical analysis. Agric. For. Meteor.,61, 113–128.

  • Hall, A. J., J. H. Lemcoff, and M. Trápani, 1981: Water stress before and during flowering in maize and its effect on yields, its components and their determinants. Maydica,26, 19–38.

  • ——, C. M. Rebella, C. M. Ghersa, and J. P. Culot, 1992: Field-crop systems of the Pampas. Ecosystems of the World: Field Crop Ecosystems, C. J. Pearson, Ed., Elsevier, 413–449.

  • Hammer, G. L., D. P. Holzworth, and R. Stone, 1996: The value of skill in seasonal climate forecasting to wheat crop management in a region with high climatic variability. Aust. J. Agric. Res.,47, 717–737.

  • Handler, P., 1990: USA corn yields, the El Niño and agricultural drought: 1867–1988. Int. J. Climatol.,10, 819–828.

  • Hansen, J. W., and Coauthors, 1996: ENSO effects on yields and economic returns of wheat, corn, and soybean in Argentina. Actas del VII Congreso Argentino y VII Congreso Latinoamericano e Ibérico de Meteorología, Buenos Aires, Argentina, Centro Argentino de Meteorólogos and Federacíon Latinoamericana e Ibérica de Sociedades de Meteorología, 89–90.

  • Hoogenboom, G., J. W. Jones, and K. J. Boote, 1991: A decision support system for prediction of crop yield, evapotranspiration, and irrigation management. Proc. Irrigation and Drainage, Honolulu, HI, Irrigation Division, American Society of Civil Engineers, 198–204.

  • Lanzante, J. R., 1996: Resistant, robust and non-parametric techniques for the analysis of climate data: Theory and examples, including applications to historical radiosonde station data. Int. J. Climatol.,16, 1197–1226.

  • Legler, D. M., K. J. Bryant, and J. J. O’Brien, 1999: Impact of ENSO-related climate anomalies on crop yields in the U.S. Climatic Change, in press.

  • Manly, B. F. J., 1997: Randomization, Bootstrap and Monte Carlo Methods in Biology. Chapman and Hall, 399 pp.

  • Meinke, H., R. C. Stone, and G. L. Hammer, 1996: SOI phases and climatic risk to peanut production: A case study for northern Australia. Int. J. Climatol.,16, 783–789.

  • Messina, C., A. Beltrán, and A. Ravelo, 1996a: El fenómeno ENSO:Su relación con la productividad de maíz en la región pampeana argentina (The ENSO phenomenon: Its relationship with maize productivity in the Argentine Pampas). IV Congreso Colombiano de Meteorología, Santa Fe de Bogota, Colombia, Sociedad Colombiana de Meteorología, 236–241.

  • ——, ——, and ——, 1996b: La variabilidad interanual de los rendimientos de trigo en la región pampeana y su relación con el fenómeno ENSO (El Niño/Southern Oscillation) (Interannual variability of wheat yields in the Pampas, and their association with the ENSO phenomenon). Actas del VII Congreso Argentino y VII Congreso Latinoamericano e Ibérico de Meteorología, Buenos Aires, Argentina, Centro Argentino de Meteorólogos and Federacíon Latinoamericana e Ibérica de Sociedades de Meteorología, 55–56.

  • Meyers, S. D., J. J. O’Brien, and E. Thelin, 1999: Reconstruction of monthly SST in the tropical Pacific Ocean during 1868–1993 using adaptive climate basis functions. Mon. Wea. Rev.,127, 1599–1612.

  • Mjelde, J. W., T. N. Thompson, F. M. Hons, J. T. Cothren, and C. G. Coffman, 1997: Using Southern Oscillation information for determining corn and sorghum profit-maximizing input levels in east-central Texas. J. Prod. Agric.,10, 168–175.

  • Nicholls, N., 1985: Impact of the Southern Oscillation on Australian crops. J. Climatol.,5, 553–560.

  • Phillips, J. G., C. Rosenzweig, and M. Cane, 1996: Exploring the potential for using ENSO forecasts in the U.S. Corn Belt. Drought Network News,8, 6–10.

  • ——, M. A. Cane, and C. Rosenzweig, 1998: ENSO, seasonal rainfall patterns and simulated maize yield variability in Zimbabwe. Agric. For. Meteor.,90, 39–50.

  • Pisciottano, G., A. Díaz, G. Cazes, and C. R. Mechoso, 1994: El Niño–Southern Oscillation impact on rainfall in Uruguay. J. Climate,7, 1286–1302.

  • Rao, V. B., L. D. A. Sá, S. H. Franchito, and K. Hada, 1997: Interannual variations of rainfall and corn yields in Northeast Brazil. Agric. For. Meteor.,85, 63–74.

  • Rebella, C. M., R. Díaz, and L. A. Funston, 1984: Tendencias de lluvias y rendimientos de maíz en la región maicera típica argentina (Precipitation trends and maize yields in Argentina’s corn belt). Proc. III Congreso Nacional de Maíz, Pergamino, Argentina, Asociación Argentina de Ingenieros Agrónomos del Norte de Buenos Aires, 129–133.

  • Ropelewski, C. F., and M. S. Halpert, 1987: Global- and regional-scale patterns associated with the El Niño/Southern Oscillation. Mon. Wea. Rev.,115, 1606–1626.

  • ——, and ——, 1989: Precipitation patterns associated with the high index phase of the Southern Oscillation. J. Climate,2, 268–284.

  • ——, and ——, 1996: Quantifying Southern Oscillation–precipitation relationships. J. Climate,9, 1043–1059.

  • SAGPyA, 1994: Estadísticas agropecuarias y pesqueras 1994. Ministerio de Economía y Obras y Servicios Públicos, Secretaría de Agricultura, Ganadería, Pesca y Alimentación, Argentina, 459 pp.

  • Smit, B., R. Blain, and P. Keddie, 1997: Corn hybrid selection and climatic variability: Gambling with nature? Can. Geogr.,41, 429–438.

  • Sokal, R. R., and F. J. Rohlf, 1969: Biometry. W. H. Freeman, 776 pp.

  • Sonka, S. T., J. W. Mjelde, P. J. Lamb, S. E. Hollinger, and B. L. Dixon. 1987: Valuing climate forecast information. J. Climate Appl. Meteor.,26, 1080–1091.

  • Tanco, R., and G. J. Berri, 1996: Acerca del efecto del fenómeno El Niño sobre la precipitación en la Pampa húmeda argentina (On the effects of the ENSO phenomenon on precipitation in the Argentine Pampas). Actas del VII Congreso Argentino y VII Congreso Latinoamericano e Ibérico de Meteorología, Buenos Aires, Argentina, Centro Argentino de Meteorólogos and Federacíon Latinoamericana e Ibérica de Sociedades de Meteorología, 319–320.

  • Travasso, M. I., 1990: Evaluation des facteurs agroclimatiques limitant le rendement du ble dans le sud de Buenos Aires, Argentine. Essai de modelisation a l’echelle regionale (Assessment of agroclimatic factors limiting wheat yields in southeastern Buenos Aires, Argentina. A modelling test on regional scales). Ph.D. thesis, Universite de Paris, 96 pp. [Available from INTA, Instituto de Clima y Agua, 1712 Castelar, Prov. Buenos Aires, Argentina.].

  • Trenberth, K., 1996: El Niño–Southern Oscillation. Climate Change:Developing Southern Hemisphere Perspectives, T. W. Giambelluca and A. Henderson-Sellers, Eds., John Wiley and Sons, 145–173.

  • ——, 1997a: Short-term climate variations: Recent accomplishments and issues for future progress. Bull. Amer. Meteor. Soc.,78, 1081–1096.

  • ——, 1997b: The definition of El Niño. Bull. Amer. Meteor. Soc.,78, 2771–2777.

  • Whiteman, P. C., and G. L. Wilson, 1965: Effects of water stress on the reproduction development of Sorghum vulgare. Pers. University of Queensland, Paper 14. [Available from University of Queensland, Brisbane, Queensland 4072, Australia.].

  • Widmann, M., and C. Schär, 1997: A principal component and long-term trend analysis of daily precipitation in Switzerland. Int. J. Climatol.,17, 1333–1356.

  • Wilks, D. S., 1995: Statistical Methods in the Atmospheric Sciences. Academic Press, 467 pp.

All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 1701 856 77
PDF Downloads 630 143 18