| In the section | Articles |
| Title of the article | Revealing the Determinants of Wheat Yields in the Siberian Breadbasket of Russia with Bayesian Networks |
| Pages | 39-83 |
| Author 1 | Alexander V. Prishchepov PhD, Associate Professor Department of Geosciences and Natural Resource Management, University of Copenhagen; Institute of Steppe of the UB RAS; Institute of Environmental Sciences, Kazan Federal University Oster Voldgade 10, Kobenhavn K, 1350, Denmark; 11 Pionerskaya Street, Orenburg, Russia, 460000; 5 Tovarisheskaya Street, Kazan, Russia, 420097 This email address is being protected from spambots. You need JavaScript enabled to view it. , This email address is being protected from spambots. You need JavaScript enabled to view it. ORCID: 0000-0003-2375-1651 |
| Author 2 | Elena V. Ponkina Candidate of Technical Sciences, Associate Professor Faculty of Mathematics and Information Technology, Altai State University Lenin Avenue, 61, Barnaul, Russia, 656049 This email address is being protected from spambots. You need JavaScript enabled to view it. ORCID: 0000-0001-7604-6337 |
| Author 3 | Zhanli Sun PhD, Senior Research Fellow Leibniz Institute of Agricultural Development in Transition Economies (IAMO) Theodor-Lieser-Strasse 2, 06120 Halle (Saale), Germany This email address is being protected from spambots. You need JavaScript enabled to view it. ORCID: 0000-0001-6204-4533 |
| Author 4 | Daniel Müller PhD, Senior Research Fellow Leibniz Institute of Agricultural Development in Transition Economies (IAMO); Geography Department, Humboldt Universitat zu Berlin; Integrative Research Institute on Transformations of Human-Environment Systems (IRI THESys), Humboldt Universitat zu Berlin Theodor-Lieser-Strasse 2, Halle (Saale), 06120, Germany; Unter den Linden 6, Berlin, 10099, Germany This email address is being protected from spambots. You need JavaScript enabled to view it. |
| Abstract | Higher crop yields are critical to satisfy the rising global food demand. Russia holds untapped potential for increasing agricultural production because current grain yields are often far below the potentially attainable yields. Western Siberia is an important breadbasket in Russia, where wheat yields fall particularly short of their potential. Our goal was to assess the determinants of yield variations among farmers in the province of Altai Krai in Western Siberia. We conducted 67 structured in-person interviews with corporate farm managers and individual farmers about the potential determinants of wheat yields and complemented these data with 149 additional observations obtained from the provincial agricultural extension service. We used Bayesian networks (BNs) to represent the relationships between the explanatory parameters and contemporary wheat yields and to examine qualitative future scenarios of future yields. The results revealed higher yields on larger farms than on medium and small farms. Our results corroborated that the application of fertilizers and herbicides and the implementation of new equipment had large positive impacts on the yields. The scenario of higher future production costs and lower precipitation resulted in a yield reduction from 7.6 dt/ha to 5.3. Overall, our results suggest that policies aimed at increasing wheat yields should concentrate on the education of farmers and encourage higher input applications, particularly for small-scale farms. Additionally, policies should address concurrent challenges, such as a higher drought frequency, through the application of new equipment, seed material and tillage practices |
| Code | 519.1+631.1+332.1 |
| JEL | C12, Q12, Q18 |
| DOI | 10.14530/se.2019.1.039-083 |
| Keywords | Bayesian belief network ♦ food security ♦ land-use intensity ♦ scenario analysis ♦ wheat production ♦ yield gap ♦ Russia |
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| For citation | Prishchepov A.V., Ponkina E.V., Sun Z., Muller D. Revealing the Determinants of Wheat Yields in the Siberian Breadbasket of Russia with Bayesian Networks. Prostranstvennaya Ekonomika = Spatial Economics, 2019, vol. 15, no. 1, pp. 39–83. DOI: 10.14530/se.2019.1.039-083. (In Russian). |
| References | 1. Adhikari C., Adhikary B., Rajbhandari N.P., Hooper M., Upreti H.K., Gyawali B.K., Rajbhandari N.K., Hobbs P.R. Wheat and Rice in the Mid-Hills of Nepal: A Benchmark Report on Farm Resources and Production Practices in Kavre District. Kathmandu: NARC; CIMMYT, 1999, 26 p. Available at: https://repository.cimmyt.org/xmlui/bitstream/handle/10883/3937/68337.pdf (accessed November 2017). 2. Agriculture. Canada Year Book 2011. Statistics Canada, 2011. Available at: https://www150.statcan.gc.ca/n1/pub/11-402-x/2011000/chap/ag/ag-eng.htm (accessed November 2017). 3. Aguilera P.A., Fernandez A., Fernandez R., Rumi R., Salmeron A. Bayesian Networks in Environmental Modelling. Environmental Modelling and Software, 2011, vol. 26, issue 12, pp. 1376–1388. DOI: 10.1016/j.envsoft.2011.06.004 4. Alcamo J. Scenarios as Tools for International Environmental Assessments. European Environment Agency. Environmental Issue Report No. 24, 2001, 31 p. Available at: https://www.eea.europa.eu/publications/environmental_issue_report_2001_24/file (accessed November 2017). 5. Ali M. Quantifying the Socio-Economic Determinants of Sustainable Crop Production: An Application to Wheat Cultivation in the Tarai of Nepal. Agricultural Economics, 1996, vol. 14, issue 1, pp. 45–60. DOI: 10.1016/0169-5150(95)01161-7 6. Banerjee H., Goswami R., Chakraborty S., Dutta S., Majumdar K., Satyanarayana T., Jat M.L., Zingore S. Understanding Biophysical and Socio-Economic Determinants of Maize (Zea mays L.) Yield Variability in Eastern India. Wageningen Journal of Life Sciences, 2014, vol. 70–71, pp. 79–93. DOI: 10.1016/j.njas.2014.08.001 7. Bavorova M., Imamverdiyev N., Ponkina E. Farm-Level Economics of Innovative Tillage Technologies: The Case of No-Till in the Altai Krai in Russian Siberia. Environmental Science and Pollution Research, 2018, vol. 25, issue 2, pp. 1016–1032. DOI: 10.1007/s11356-017-9268-y 8. Bednarikova Z., Bavorova M., Ponkina E.V. Migration Motivation of Agriculturally Educated Rural Youth: The Case of Russian Siberia. Journal of Rural Studies, 2016, vol. 45, pp. 99–111. DOI: 10.1016/j.jrurstud.2016.03.006 9. Bischoff N., Mikutta R., Shibistova O., Puzanov A., Reichert E., Silanteva M., Grebennikova A., Schaarschmidt F., Heinicke S., Guggenberger G. Land-Use Change Under Different Climatic Conditions: Consequences for Organic Matter and Microbial Communities in Siberian Steppe Soils. Agriculture Ecosystems & Environment, 2016, vol. 235, pp. 253–264. DOI: 10.1016/j.agee.2016.10.022 10. Blanc E., Lepine A., Strobl E. Determinants of Crop Yield and Profit of Family Farms: Evidence From the Senegal River Valley. Department of Research, IPAG Business School. Working Papers 2014-596, 2014. 11. Bloch P., Melmed-Sanjak J., Hanson R. The Debate over Agrarian Structure in Macedonia: Implications for Land Management. Transactions in International Land Management. Edited by R.W. Dixon-Gough, R. Mansberger. London – New York: Routledge, 2000, pp. 1–26. 12. Bogoviz A.V., Lobova S.V., Oskorbin N.M., Ponkina E.V., Manicheva A.S. Problems of Increasing the Profitability of Grain Production in the Altai Territory. Barnaul, 2011, 275 p. (In Russian). 13. Bokusheva R., Hockmann H. Production Risk and Technical Inefficiency in Russian Agriculture. European Review of Agricultural Economics, 2006, vol. 33, issue 1, pp. 93–118. DOI: 10.1093/erae/jbi036 14. Bokusheva R., Hockmann H., Kumbhakar S.C. Dynamics of Productivity and Technical Efficiency in Russian Agriculture. European Review of Agricultural Economics, 2012, vol. 39, pp. 611–637. DOI: 10.1093/erae/jbr059 15. Boogaard H., Wolf J., Supit I., Niemeyer S., van Ittersum M. A Regional Implementation of WOFOST for Calculating Yield Gaps of Autumn-Sown Wheat Across the European Union. Field Crops Research, 2013, vol. 143, pp. 130–142. DOI: 10.1016/j.fcr.2012.11.005 16. Bryan B.A., King D., Zhao G. Influence of Management and Environment on Australian Wheat: Information for Sustainable Intensification and Closing Yield Gaps. Environmental Research Letters, 2014, vol. 9, no. 4. DOI: 10.1088/1748-9326/9/4/044005 17. Carpenter S.R., DeFries R., Dietz T., Mooney H.A., Polasky S., Reid W.V., Scholes R.J. Millennium Ecosystem Assessment: Research Needs. Science, 2006, vol. 314, issue 5797, pp. 257–258. DOI: 10.1126/science.1131946 18. Central Base of Statistical Data. Federal State Statistics Service, 2016. Available at: http://www.gks.ru/dbscripts/cbsd/dbinet.cgi (accessed November 2017). (In Russian). 19. Climate Change and Terrestrial Carbon Sequestration in Central Asia. Edited by R. Lal, M. Suleimenov, B.A. Stewart, D.O. Hansen, P. Doraiswamy. London: Taylor & Francis Group, 2007, 494 p. 20. Climate Doctrine of the Russian Federation. 2009, December 17. Available at: http://en.kremlin.ru/supplement/4822 (accessed November 2017). 21. Dronin N.M. Climate Change and Food Security in Russia: Historical Analysis and Model Forecasts. Moscow, 2014, 303 p. (In Russian). 22. Dronin N.M., Bellinger E.G. Climate Dependence and Food Problems in Russia, 1900–1990: The Interaction of Climate and Agricultural Policy and Their Effect on Food Problems. Budapest: Central European University Press, 2005, 366 p. 23. Economics and Land Use Planning. Edited by A.W. Evans. Oxford: Blackwell Publishing Ltd., 2004, 224 p. 24. Ennew C.T. A Model of Import Demand for Grain in the Soviet Union. Food Policy, 1987, vol. 12, issue 2, pp. 106–115. DOI: 10.1016/0306-9192(87)90027-3 25. Eremin А.А., Bykov N.I. Demographic Situation in the Altai Territory at the Present Stage (1990–2010). Altai State University. Barnaul, 2011, 272 p. (In Russian). 26. Fischer G., Nachtergaele F.O., Prieler S., Teixeira E., Toth G., van Velthuizen H., Verelst L., Wiberg D. Global Agro-Ecological Zones (GAEZ v. 3.0). International Institute for Applied Systems Analysis (IIASA), 2012. Laxenburg, Austria, FAO, Rome, Italy. 27. Fischer J. Land Sparing Versus Land Sharing: New Evidence. Ideas for Sustainability, 2013. Available at: http://ideas4sustainability.wordpress.com/2013/04/03/land-sparing-versus-land-sharing-new-evidence/ (accessed November 2017). 28. Foley J.A. Global Consequences of Land Use. Science, 2005, vol. 309, issue 5734, pp. 570–574. DOI: 10.1126/science.1111772 29. Garrett R.D., Lambin E.F., Naylor R.L. Land Institutions and Supply Chain Configurations as Determinants of Soybean Planted Area and Yields in Brazil. Land Use Policy, 2013, vol. 31, pp. 385–396. DOI: 10.1016/j.landusepol.2012.08.002 30. Gooding M.J., Davies W.P. Wheat Production and Utilization: Systems, Quality and the Environment. New York: CABI Publishing, 1997, 352 p. 31. Gotz L., Glauben T., Brummer B. Wheat Export Restrictions and Domestic Market Effects in Russia and Ukraine During the Food Crisis. Food Policy, 2013, vol. 38, pp. 214–226. DOI: 10.1016/j.foodpol.2012.12.001 32. Hamilton S.H., Pollino C.A., Jakeman A.J. Habitat Suitability Modelling of Rare Species Using Bayesian Networks: Model Evaluation under Limited Data. Ecological Modelling, 2015, vol. 299, pp. 64–78. DOI: 10.1016/j.ecolmodel.2014.12.004 33. Hassan I., Chattha M.B., Chattha T.H., Ali M.A. Factor Affecting Wheat Yield: A Case Study of Mixed Cropping Zone of Punjab. Journal of Agricultural Research, 2010, vol. 48, issue 3, pp. 403–408. 34. Heckerman D., Geiger D., Chickering D. Learning Bayesian Networks: The Combination of Knowledge and Statistical Data. Machine Learning September, 1995a, vol. 20, issue 3, pp. 197–243. DOI: 10.1007/BF00994016 35. Heckerman D., Mamdani A., Wellman M.P. Real-World Applications of Bayesian Networks. Communications of the ACM, 1995b, vol. 38, issue 3, pp. 24–26. 36. Interactive Agricultural Ecological Atlas of Russia and Neighboring Countries. Edited by A.N. Afonin, S.L. Greene, N.I. Dzyubenko, A.N. Frolov. Economic Plants and Their Diseases, Pests and Weeds, 2008. Available at: http://www.agroatlas.ru/ru/index.html (accessed November 2017). 37. IPCC, 2000. Special Report on Emissions Scenarios. Cambridge University Press, Cambridge. Special Report on Emissions Scenarios. Intergovenmiental Panel on Climate Change. Cambridge: Cambridge University Press, 2000, 608 p. Available at: https://www.ipcc.ch/report/emissions-scenarios/(accessed November 2018). 38. Jensen F.V., Nielsen T.D. Bayesian Networks and Decision Graphs. New York: Springer-Verlag, 2007, 448 p. DOI: 10.1007/978-0-387-68282-2 39. Josephson P., Dronin N., Mnatsakanian R., Cherp A., Efremenko D., Larin V. An Environmental History of Russia. Cambridge; New York: Cambridge University Press, 2013, 352 p. 40. Kamp J. Land Management: Weighing Up Reuse of Soviet Croplands. Nature, 2014, vol. 505, issue 7484, pp. 483. DOI: 10.1038/505483d 41. Kherad M., Ahani H., Kousari M.R., Beyraghdar Kashkooli A., Karampour M.A. Evaluation of Education and Water Resource Types on Some Wheat Land Features, Using Fars Comprehensive Agricultural Database (Case Study; Pasargad, Iran). Environment, Development and Sustainability August, 2013, vol. 15, issue 4, pp. 1129–1142. DOI: 10.1007/s10668-012-9428-7 42. Kogan F., Guo W. Early Twenty-First-Century Droughts During the Warmest Climate. Geomatics, Natural Hazards and Risk, 2016, vol. 7, issue 1, pp. 127–137. DOI: 10.1080/19475705.2013.878399 43. Lambin E.F., Meyfroidt P. Global Land Use Change, Economic Globalization, and the Looming Land Scarcity. Proceedings of the National Academy of Sciences, 2011, vol. 108, issue 9, pp. 3465–3472. DOI: 10.1073/pnas.1100480108 44. Licker R., Johnston M., Foley J.A., Barford C., Kucharik C.J., Monfreda C., Ramankutty N. Mind the Gap: How do Climate and Agricultural Management Explain the ‘Yield Gap’ of Croplands Around the World? Global Ecology and Biogeography, 2010, vol. 19, issue 6, pp. 769–782. DOI: 10.1111/j.1466-8238.2010.00563.x 45. Liefert W., Liefert O. Changing Crop Area in the Former Soviet Union Region (A Report from the Economic Research Service). FDS17b-01, USDA, Washington, D.C., 2017. Available at: https://www.ers.usda.gov/webdocs/publications/82573/fds-17b-01.pdf?v=0 (accessed November 2017). 46. Liefert W.M., Liefert O. Russian Agriculture during Transition: Performance, Global Impact, and Outlook. Applied Economic Perspectives and Policy, 2012, vol. 34, issue 1, pp. 37–75. DOI: 10.1093/aepp/ppr046 47. Lioubimtseva E., Henebry G.M. Grain Production Trends in Russia, Ukraine and Kazakhstan: New Opportunities in an Increasingly Unstable World? Frontiers of Earth Science, 2012, vol. 6, issue 2, pp. 157–166. DOI: 10.1007/s11707-012-0318-y 48. Lobell D.B., Cassman K.G., Field C.B., Crop Yield Gaps: Their Importance, Magnitudes, and Causes. Annual Review of Environment and Resources, 2009, vol. 34, pp. 179–204. DOI: 10.1146/annurev.environ.041008.093740 49. Madsen A.L., Jensen F., Kj?Rulff U.B., Lang M. The HUGIN tool for Probabilistic Graphical Models. International Journal on Artificial Intelligence Tools, 2005, vol. 14, no. 3, pp. 507–543. DOI: 10.1142/S0218213005002235 50. Mallampalli V.R., Mavrommati G., Thompson J., Duveneck M., Meyer S., Ligmann-Zielinska A., Druschke C.G., Hychka K., Kenney M.A., Kok K., Borsuk M.E. Methods for Translating Narrative Scenarios Into Quantitative Assessments of Land Use Change. Environmental Modelling & Software, 2016, vol. 82, pp. 7–20. DOI: 10.1016/j.envsoft.2016.04.011 51. Mann M.L., Warner J.M. Ethiopian Wheat Yield and Yield Gap Estimation: A Spatially Explicit Small Area Integrated Data Approach. Field Crops Research, 2017, vol. 201, pp. 60–74. DOI: 10.1016/j.fcr.2016.10.014 52. McCauley M. Khrushchev and the Development of Soviet Agriculture: The Virgin Land Programme, 1953–1964. New York: Holmes & Meier Pub., 1977, 232 p. 53. Mendelsohn R., Nordhaus W.D., Shaw D. The Impact of Global Warming on Agriculture: A Ricardian Analysis. The American Economic Review, 1994, vol. 84, no. 4, pp. 753–771. 54. Menne M.J., Durre I., Korzeniewski B., McNeal S., Thomas K., Yin X., Anthony S., Ray R., Vose R.S., Gleason B.E., Houston T.G. Global Historical Climatology Network-Daily (GHCN-Daily), Version 3. National Centers for Environmental Information; National Climatic Data Center, 2012. Available at: https://data.nodc.noaa.gov/cgi-bin/iso?id=gov.noaa.ncdc:C00861 (accessed November 2017). 55. Mueller N.D., Gerber J.S., Johnston M., Ray D.K., Ramankutty N., Foley J.A. Closing Yield Gaps Through Nutrient and Water Management. Nature, 2012, vol. 490, pp. 254–257. DOI: 10.1038/nature11420 56. Nefedova T.G. Russian Agricultural Resources and the Geography of Their Use in Import-Substitution Conditions. Regional Research of Russia, October 2016, vol. 6, issue 4, pp. 292–303. DOI: 10.1134/S2079970516040122 57. Netica Version 5.18. Norsys Software Corporation, 2015. Available at: https://www.norsys.com/ (accessed November 2017). 58. On the Statement of the Order of Providing from the Regional Budget of Subsidies for Rendering Incoherent Support of Agricultural Producers in the Field of Plant Growing: the Resolution of Administration of Altai Krai of February 21, 2014 No. 70 (Changed on July 8, 2015, the resolution No. 26). Available at: https://www.altairegion22.ru/upload/iblock/ef3/70_14.pdf (accessed November 2017). (In Russian). 59. Osborne S., Trueblood M.A. An Examination of Economic Efficiency of Russian Grop Production in the Reform Period. Agricultural Economics, 2006, vol. 34, issue 1, pp. 25–38. DOI: 10.1111/j.1574-0862.2006.00100.x 60. Paramonov E.G., Ishutin Ya.N., Simonenko A.P. Kulunda Steppe: Problem of Desertification. Edited by L.I. Bazina. Barnaul, 2003, 137 p. (In Russian). 61. Pavlova V.N., Varcheva S.E., Bokusheva R., Calanca P. Modelling the Effects of Climate Variability on Spring Wheat Productivity in the Steppe Zone of Russia and Kazakhstan. Ecological Modelling, 2014, vol. 277, pp. 57–67. DOI: 10.1016/j.ecolmodel.2014.01.014 62. Pearl J. Causality: Models, Reasoning, and Inference. Cambridge University Press, 2009, 484 p. 63. Peterson G.D., Cumming G.S., Carpenter S.R. Scenario Planning: A Tool for Conservation in an Uncertain World. Conservation Biology, 2003, vol. 17, issue 2, pp. 358–366. DOI: 10.1046/j.1523-1739.2003.01491x 64. Ponkina E., Bavorova M., Prishchepov A.V., Kovaleva I. Positive Quantitative Analysis of Farms Regarding Natural Conditions, Structure, Production Program, Factor Endowment, Productivity, Economic Success and Income. Technical Report. Working Paper. Subproject 8, 66 p. 65. Ponkina E., Belyaev V., Bovarova M., Prishchepov A., Maynel T., Bugay Yu., Kovaleva I., Kozhanov N., Kazardzhyan M., Fryuauf M. Economic, Environmental, Technological Factors and Results of Agricultural Enterprises in the Kulunda Steppe. Barnaul, 2014, 140 p. (In Russian). 66. Prishchepov A.V., Schierhorn F., Dronin N., Ponkina E., Muller D. 800 Years of Agricultural Land-Use Change in Asian (Eastern) Russia // Edited by M. Fruhauf, G. Guggenberger, T. Meinel, I. Theesfeld, S. Lentz. KULUNDA: Climate Smart Agriculture. South Siberian Agro-Steppe as Pioneering Region for Sustainable Land Use. Cham: Springer International Publishing, 2020. 67. Regions of Russia. Socio-Economic Indicators. 2013: Statistical Compendium. Federal State Statistics Service, 2013. Available at: http://www.gks.ru/wps/wcm/connect/rosstat_main/rosstat/ru/statistics/publications/catalog/doc_1138623506156 (accessed November 2017). (In Russian). 68. Russian Federation: Analysis of the Agribusiness Sector in Southern Russia. Report Series No. 13. FAO, FAO Investment Centre; EBRD Cooperation Programme, 2009, 109 p. Available at: (accessed November 2017). 69. Rylko D., Jolly R.W. Russia’s New Agricultural Operators: Their Emergence, Growth and Impact. Comparative Economic Studies, 2005, vol. 47, pp. 115–126. DOI: 10.1057/palgrave.ces.8100087 70. Schierhorn F., Faramarzi M., Prishchepov A.V., Koch F.J., Muller D. Quantifying Yield Gaps in Wheat Production in Russia. Environmental Research Letters, 2014, vol. 9,no. 8, 12 p. DOI: 10.1088/1748-9326/9/8/084017 71. Second Roshydromet Assessment Report on Climate Change and Its Consequences in Russian Federation. General Summary. Federal Service for Hydrometeorology and Environmental Monitoring. Moscow: Roshydromet, 2014, 56 p. Available at: (accessed November 2017). 72. Simulation Growth Model WOFOST Crop Plants and its Use for the Analysis of Land Productivity of Russia. Edited by I.Yu. Savin, V.S. Stolbovoi, K. van Diepen. V.V. Dokuchaev Soil Science Institute. Moscow: RAAS, 2001, 216 p. (In Russian). 73. State Program for the Development of Agriculture and Regulation of Markets of Agricultural Products, Raw Materials and Food for 2013–2020: Approved by the Government of the Russian Federation on July 14, 2012 No. 717. Ministry of Agriculture of the Russian Federation, 2013. (In Russian). 74. Sun Z., Muller D. A Framework for Modeling Payments for Ecosystem Services with Agent-Based Models, Bayesian Belief Networks and Opinion Dynamics Models. Environmental Modelling and Software, 2013, vol. 45, pp. 15–28. DOI: 10.1016/j.envsoft.2012.06.007 75. Swinnen J., Burkitbayeva S., Schierhorn F., Prishchepov A.V., Muller D. Production Potential in the ‘Bread Baskets’ of Eastern Europe and Central Asia. Global Food Security, 2017, vol. 14, pp. 38–53. DOI: 10.1016/j.gfs.2017.03.005 76. System of Agriculture in the Altai Region. Altai Research Institute of Agriculture. Novosibirsk, 1981, 326 p. (In Russian). 77. The Oxford Handbook of Land Economics, Oxford Handbooks in Economics. Edited by J.M. Duke, J.J. Wu. Oxford University Press, 2014, 768 p. 78. Theesfeld I., Jelinek L. A Misfit in Policy to Protect Russia’s Black Soil Region. An Institutional Analytical Lens Applied to the ban on Burning of Crop Residues. Land Use Policy, 2017, vol. 67, pp. 517–526. DOI: 10.1016/j.landusepol.2017.06.018 79. Tittonell P., Vanlauwe B., Leffelaar P.A., Rowe E.C., Giller K.E. Exploring Diversity in Soil Fertility Management of Smallholder Farms in Western Kenya. Agriculture, Ecosystems and Environment Agric, 2005, vol. 110, pp. 149–165. DOI: 10.1016/j.agee.2005.04.001 80. Trueblood M.A., Arnade C. Crop Yield Convergence: How Russia’s Yield Performance Has Compared to Global Yield Leaders. Comparative Economic Studies, 2001, vol. 43, issue 2, pp. 59–81. DOI: 10.1057/ces.2001.8 81. Uusitalo L. Advantages and Challenges of Bayesian Networks in Environmental Modelling. Ecological Modelling, 2007, vol. 203, pp. 312–318. DOI: 10.1016/j.ecolmodel.2006.11.033 82. Van Ittersum M.K., Cassman K.G., Grassini P., Wolf J., Tittonell P., Hochman Z., Yield Gap Analysis with Local to Global Relevance: A Review. Field Crops Research, 2013, vol. 143, pp. 4–17. DOI: 10.1016/j.fcr.2012.09.009 83. Visser O., Mamonova N., Spoor M. Oligarchs, Megafarms and Land Reserves: Understanding Land Grabbing in Russia. The Journal of Peasant Studies, 2012, vol. 39, issue 3–4, pp. 899–931. DOI: 10.1080/03066150.2012.675574 84. Visser O., Spoor M., Mamonova N. Is Russia the Emerging Global ‘Breadbasket’? Re-Cultivation, Agroholdings and Grain Production. Europe-Asia Studies, 2014, vol. 66, issue 10, pp. 1589–1610. DOI: 10.1080/09668136.2014.967569 85. Yastrebova O. Nonpayments, Bankruptcy and Government Support in Russian Agriculture. Comparative Economic Studies, 2005, vol. 47, issue 1, pp. 167-180. DOI: 10.1057/palgrave.ces.8100088 |
| Financing | This research was funded by the German Federal Ministry of Education and Research (BMBF, grant No. 01LL0905J) within the funding measure ‘Sustainable Land Management’, KULUNDA project. The work is performed according to the Russian Government Program of Competitive Growth of Kazan Federal University |