IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v277y2014icp57-67.html
   My bibliography  Save this article

Modelling the effects of climate variability on spring wheat productivity in the steppe zone of Russia and Kazakhstan

Author

Listed:
  • Pavlova, Vera N.
  • Varcheva, Svetlana E.
  • Bokusheva, Raushan
  • Calanca, Pierluigi

Abstract

Spring wheat is the principal crop in the steppe zone of Russia and Kazakhstan, but wheat productivity levels are currently low and susceptible to weather and climate anomalies. Water scarcity during the growing season represents a major stress factor and is expected to negatively affect wheat production in the future as well. In this paper we present a simple mechanistic model for assessing the impact of climate variability on spring wheat productivity in the steppe zone of Russia and Kazakhstan. The novel aspect of the model development is represented by the adoption of an adaptive approach for the formulation of growth partitioning. In spite of simplifying assumptions the model is shown to satisfactorily reproduce yield levels observed both at the local scale under controlled conditions as well as at the regional scale. The model is able to capture a significant percentage of the observed year-to-year variability of wheat yields. Results of the model application indicate that, for the steppe zone of Russia and Kazakhstan, seasonal water shortage is likely to cause yield deficits of 20–25%, with deficits of up to 40% in extreme years, and an increase in the coefficient of variation of yields.

Suggested Citation

  • Pavlova, Vera N. & Varcheva, Svetlana E. & Bokusheva, Raushan & Calanca, Pierluigi, 2014. "Modelling the effects of climate variability on spring wheat productivity in the steppe zone of Russia and Kazakhstan," Ecological Modelling, Elsevier, vol. 277(C), pages 57-67.
    • Handle: RePEc:eee:ecomod:v:277:y:2014:i:c:p:57-67
    DOI: 10.1016/j.ecolmodel.2014.01.014
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S030438001400057X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ecolmodel.2014.01.014?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Conradt, Sarah & Bokusheva, Raushan & Finger, Robert & Kussaiynov, Talgat, 2012. "Yield trend estimation in the presence of non-constant technological change and weather effects," 123rd Seminar, February 23-24, 2012, Dublin, Ireland 122541, European Association of Agricultural Economists.
    2. Just, Richard E. & Pope, Rulon D., 1978. "Stochastic specification of production functions and economic implications," Journal of Econometrics, Elsevier, vol. 7(1), pages 67-86, February.
    3. Carew, Richard & Smith, Elwin G. & Grant, Cynthia, 2009. "Factors Influencing Wheat Yield and Variability: Evidence from Manitoba, Canada," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 41(3), pages 1-15, December.
    4. Richard E. Just & Rulon D. Pope, 1979. "Production Function Estimation and Related Risk Considerations," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 61(2), pages 276-284.
    5. Carew, Richard & Smith, Elwin G. & Grant, Cynthia, 2009. "Factors Influencing Wheat Yield and Variability: Evidence from Manitoba, Canada," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 41(3), pages 625-639, December.
    6. Liefert, William M. & Liefert, Olga & Vocke, Gary & Allen, Edward W., 2010. "Former Soviet Union Region To Play Larger Role in Meeting World Wheat Needs," Amber Waves:The Economics of Food, Farming, Natural Resources, and Rural America, United States Department of Agriculture, Economic Research Service, pages 1-8.
    7. Bouman, B. A. M. & van Keulen, H. & van Laar, H. H. & Rabbinge, R., 1996. "The `School of de Wit' crop growth simulation models: A pedigree and historical overview," Agricultural Systems, Elsevier, vol. 52(2-3), pages 171-198.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Danmeng Wang & Guoxi Gao & Ruolan Li & Shynggys Toktarbek & Nueryia Jiakula & Yongzhong Feng, 2022. "Limiting Factors and Environmental Adaptability for Staple Crops in Kazakhstan," Sustainability, MDPI, vol. 14(16), pages 1-15, August.
    2. Prishchepov, Alexander V. & Ponkina, Elena & Sun, Zhanli & Müller, Daniel, 2019. "Revealing the determinants of wheat yields in the Siberian breadbasket of Russia with Bayesian networks," Land Use Policy, Elsevier, vol. 80(C), pages 21-31.
    3. Prishchepov, Alexander & Ponkina, Elena & Sun, Zhanli & Müller, Daniel, 2019. "Выявление Детерминант Урожайности Пшеницы В Западной Сибири С Использованием Байесовских Сетей [Revealing the Determinants of Wheat Yields in the Siberian Breadbasket of Russia with Bayesian Networ," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 15(1), pages 39-83.
    4. Li, Zhi & Fang, Gonghuan & Chen, Yaning & Duan, Weili & Mukanov, Yerbolat, 2020. "Agricultural water demands in Central Asia under 1.5 °C and 2.0 °C global warming," Agricultural Water Management, Elsevier, vol. 231(C).
    5. Belyaeva, Maria & Bokusheva, Raushan, 2017. "Will climate change benefit or hurt Russian grain production? A statistical evidence from a panel approach," IAMO Discussion Papers 253788, Institute of Agricultural Development in Transition Economies (IAMO).
    6. Djanibekov, Utkur & Finger, Robert, 2018. "Agricultural risks and farm land consolidation process in transition countries: The case of cotton production in Uzbekistan," Agricultural Systems, Elsevier, vol. 164(C), pages 223-235.
    7. Chandio, Abbas Ali & Dash, Devi Prasad & Nathaniel, Solomon Prince & Sargani, Ghulam Raza & Jiang, Yuansheng, 2023. "Mitigation pathways towards climate change: Modelling the impact of climatological factors on wheat production in top six regions of China," Ecological Modelling, Elsevier, vol. 481(C).
    8. Danmeng Wang & Ruolan Li & Guoxi Gao & Nueryia Jiakula & Shynggys Toktarbek & Shilin Li & Ping Ma & Yongzhong Feng, 2022. "Impact of Climate Change on Food Security in Kazakhstan," Agriculture, MDPI, vol. 12(8), pages 1-13, July.
    9. Belyaeva, Maria & Bokusheva, Raushan, 2017. "Will climate change benefit or hurt Russian grain production? A statistical evidence from a panel approach [Wird der Klimawandel der russischen Getreideproduktion nutzen oder schaden? Statistische ," IAMO Discussion Papers 161, Leibniz Institute of Agricultural Development in Transition Economies (IAMO).
    10. repec:zbw:iamodp:253788 is not listed on IDEAS
    11. Muratbek Baglan & Gershom Endelani Mwalupaso & Xue Zhou & Xianhui Geng, 2020. "Towards Cleaner Production: Certified Seed Adoption and Its Effect on Technical Efficiency," Sustainability, MDPI, vol. 12(4), pages 1-17, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ali D. Cagdas & Scott R. Jeffrey & Elwin G. Smith & Peter C. Boxall, 2016. "Environmental Stewardship and Technical Efficiency in Canadian Prairie Canola Production," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 64(3), pages 455-477, September.
    2. Cagdas, Ali D. & Jeffrey, Scott R. & Smith, Elwin G. & Boxall, Peter C., 2013. "Adoption of BMPs and technical inefficiency in Canadian canola production," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150200, Agricultural and Applied Economics Association.
    3. Tsegaye Ginbo, 2022. "Heterogeneous impacts of climate change on crop yields across altitudes in Ethiopia," Climatic Change, Springer, vol. 170(1), pages 1-21, January.
    4. Barnwal, Prabhat & Kotani, Koji, 2013. "Climatic impacts across agricultural crop yield distributions: An application of quantile regression on rice crops in Andhra Pradesh, India," Ecological Economics, Elsevier, vol. 87(C), pages 95-109.
    5. Lee, Heera & Bogner, Christina & Lee, Saem & Koellner, Thomas, 2016. "Crop selection under price and yield fluctuation: Analysis of agro-economic time series from South Korea," Agricultural Systems, Elsevier, vol. 148(C), pages 1-11.
    6. Samira Shayanmehr & Shida Rastegari Henneberry & Mahmood Sabouhi Sabouni & Naser Shahnoushi Foroushani, 2020. "Climate Change and Sustainability of Crop Yield in Dry Regions Food Insecurity," Sustainability, MDPI, vol. 12(23), pages 1-24, November.
    7. Rocha, Jr., Adauto B. & Fulginiti, Lilyan E. & Perrin, Richard K. & Walters, Cory G., 2022. "What is the value of crop insurance for Nebraskan farmers?," 2022 Annual Meeting, July 31-August 2, Anaheim, California 322529, Agricultural and Applied Economics Association.
    8. Zeytoon Nejad Moosavian, Seyyed Ali & Goodwin, Barry K., 2018. "GENERALIZING THE GENERAL: Generalizing the CES Production Function to Allow for the Flexibility of Input-Driven Output Risk and Viability of Input Thresholds," 2018 Annual Meeting, August 5-7, Washington, D.C. 274352, Agricultural and Applied Economics Association.
    9. Joshi, Niraj Prakash & Maharjan, Keshav Lall & Piya, Luni, 2011. "Effect of climate variables on yield of major food-crops in Nepal -A time-series analysis-," MPRA Paper 35379, University Library of Munich, Germany.
    10. Mitchell, Paul David, 1999. "The theory and practice of green insurance: insurance to encourage the adoption of corn rootworm IPM," ISU General Staff Papers 1999010108000013154, Iowa State University, Department of Economics.
    11. Hasibuan, Abdul Muis & Gregg, Daniel & Stringer, Randy, 2022. "Risk preferences, intra-household dynamics and spatial effects on chemical inputs use: Case of small-scale citrus farmers in Indonesia," Land Use Policy, Elsevier, vol. 122(C).
    12. Peter E. Rossi, 1984. "Stochastic Specification of Cost and Production Relationships," Discussion Papers 616, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
    13. Jutta Roosen & David A. Hennessy, 2003. "Tests for the Role of Risk Aversion on Input Use," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 85(1), pages 30-43.
    14. Finger, Robert & Buchmann, Nina, 2015. "An ecological economic assessment of risk-reducing effects of species diversity in managed grasslands," Ecological Economics, Elsevier, vol. 110(C), pages 89-97.
    15. Ashok K. Mishra & Mike G. Tsionas, 2020. "A Minimax Regret Approach to Decision Making Under Uncertainty," Journal of Agricultural Economics, Wiley Blackwell, vol. 71(3), pages 698-718, September.
    16. De Nova, Carolina Carbajal, 2021. "Synthetic data. A novel proposed method for applied risk management," 95th Annual Conference, March 29-30, 2021, Warwick, UK (Hybrid) 311085, Agricultural Economics Society - AES.
    17. Phoebe Koundouri, 2004. "Current Issues in the Economics of Groundwater Resource Management," Journal of Economic Surveys, Wiley Blackwell, vol. 18(5), pages 703-740, December.
    18. TSIBOE, Francis & ASEETE, Paul & DJOKOTO, Justice G., 2021. "Spatiotemporal Evaluation Of Dry Beans And Groundnut Production Technology And Inefficiency In Ghana," Review of Agricultural and Applied Economics (RAAE), Faculty of Economics and Management, Slovak Agricultural University in Nitra, vol. 24(1), March.
    19. Luigi Biagini & Simone Severini, 2022. "How Does the Farmer Strike a Balance between Income and Risk across Inputs? An Application in Italian Field Crop Farms," Sustainability, MDPI, vol. 14(23), pages 1-15, December.
    20. Zulfiqar, Farhad, 2010. "Estimation of Wheat Yield Response under different Economic, Location and Climatic Conditions in Punjab," MPRA Paper 26503, University Library of Munich, Germany.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecomod:v:277:y:2014:i:c:p:57-67. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/ecological-modelling .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.