Abstract
Global climate change presents long-term risks to agriculture. In general, global climate change is expected to positively affect Russian agriculture. In high and middle latitudes, global warming would expand the growing season. Acreages of agricultural crops may expand toward the north, although yields would likely be lower due to less fertile soil. However, in the south there is a possibility of drier climate, which has a negative impact on crop yields and livestock productivity. In addition, climate change is expected to increase the scarcity of water resources and encourage weed and pest proliferation, and it is expected to increase the short-term risks associated with an increase in extreme weather events and natural disasters. This paper uses data on current conditions to simulate future scenarios and examine possible impacts on crop production in the Russian Federation. It also considers adaptive measures for agriculture in response to climate change.
References
Carpenter, S.R., P. Pingali, E.M. Bennett, and M. Zurek (eds) (2005). Ecosystems and Human Well-being: Scenarios. Washington, DC: Island Press.Search in Google Scholar
Center for International Earth Science Information Network Columbia University (2004). Global Rural-Urban Mapping Project (GRUMP), Alpha Version: Population Density Grids. Palisades, NY: Socioeconomic Data and Applications Center (SEDAC), Columbia University. http://sedac.ciesin.columbia.edu/gpwSearch in Google Scholar
Cline, S A, with T. Zhu (2008). International Model for Policy Analysis of Agricultural Commodities and Trade (IMPACT): Model Description. Washington, D.C.: International Food Policy Research Institute. http://www.ifpri.org/themes/impact/impactwater.pdfSearch in Google Scholar
FAO (2010). FAOSTAT. Online Database. http://faostat.fao.org/site/291/default.aspxSearch in Google Scholar
JRC (2000). Global Land Cover. http://bioval.jrc.ec.europa.eu/products/glc2000/glc2000.phpSearch in Google Scholar
Jones, J W, G Hoogenboom, C.H. Porter, K..J. Boote, W.D. Batchelor, L.A. Hunt, P.W. Wilkens, U. Singh, A.J. Gijsman, and J.T. Ritchie (2003). The DSSAT Cropping System Model. European Journal of Agronomy 18 (3–4): 235–265. http://www.sciencedirect.com/science/article/pii/S116103010200107710.1016/S1161-0301(02)00107-7Search in Google Scholar
Korshunov A.A., M.Z. Shaymardanov, and I.L. Shaymardanova (2010). Hydrometeorological Safety and Sustainable Development of Russia’s Economy for the Service of Consumers: Results of the Statistical Analysis of Dangerous Weather Conditions. Information Technologies of the State Fund of Data on a Condition of Surrounding Environment, Researches of Public Institution “All-Russian Research Institute of Hydrometeorological Information – the World Center of Data”, release 174, Obninsk.Search in Google Scholar
Lehner, B., and P. Döll (2004). Development and Validation of a Global Database of Lakes, Reservoirs and Wetlands. Journal of Hydrology 296 (1–4): 1–22.Search in Google Scholar
Le Treut, H., R. Somerville, U. Cubasch, Y. Ding, C. Mauritzen, A. Mokssit, T. Peterson, and M. Prather (2007). Historical Overview of Climate Change. In Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, ed. by S. Solomon, D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor, and H.L. Miller. Cambridge, UK and New York, NY, USA: Cambridge University Press.Search in Google Scholar
Margulis, S. (2010). Economics of Adaptation to Climate Change: Synthesis Report. Development. Washington, DC. http://climatechange.worldbank.org/sites/default/files/documents/EACCSynthesisReport.pdfSearch in Google Scholar
Nelson, G.C., M.W. Rosegrant, A. Palazzo, I. Gray, C. Ingersoll, R. Robertson, S.Tokgoz, et al. (2010). Food Security, Farming, and Climate Change to 2050: Scenarios, Results, Policy Options. Washington, DC: International Food Policy Research Institute.Search in Google Scholar
Raskin, P., F. Monks, T. Ribeiro, D. van Vuuren, and M. Zurek. (2005). Global Scenarios in Historical Perspective. In Ecosystems and Human Well-being: Scenarios, Volume 2, ed. S.R. Carpenter, P. Pingali, E.M. Bennett, and M. Zurek, 35–44. Washington, D.C. Island Press.Search in Google Scholar
StataCorp (2009). Stata. College Station, TX: StataCorp LP.Search in Google Scholar
Russian Federation Ministry of Agriculture (2011). The Russian Federation Report on the Status and Use of Agricultural Lands. http://www.mcx.ru/documents/document/show/17135.133.htmSearch in Google Scholar
Russian Federation State Statistics Service. ROSSTAT. Online database. http://www.gks.ru/wps/wcm/connect/rosstat_main/rosstat/en/main/Search in Google Scholar
The Russian Federation National Report for 1990–2009 on Anthropogenic Emissions by Sources and Absorption of Greenhouse Gases not Controlled by the Montreal Protocol (2011). http://unfccc.int/national_reports/annex_i_ghg_inventories/national_inventories_submissions/items/5888.phpSearch in Google Scholar
Tukey, J.W. (1977). Exploratory Data Analysis. Reading, MA: Addison-Wesley.Search in Google Scholar
UNEP (2009). World Database on Protected Areas (WDPA). Annual Release. http://www.wdpa.org/protectedplanet.aspx.Search in Google Scholar
United Nations (2008). World Population Prospects: The 2008 Revision. New York. http://www.un.org/esa/population/publications/wpp2008/wpp2008_highlights.pdf; http://esa.un.org/unpd/wpp/.Search in Google Scholar
Wood, S., G. Hyman, U. Deichmann, E. Barona, R. Tenorio, Z. Guo, S. Castano, O. Rivera, E. Diaz, and J. Marin (2010). Sub-national Poverty Maps for the Developing World Using International Poverty Lines: Preliminary Data Release. Harvest Choice, IFPRI. http://labs.harvestchoice.org/2010/08/poverty-maps/.Search in Google Scholar
World Bank (2009). World Development Indicators. Washington, DC: World Bank. http://data.worldbank.org/data-catalog/world-development-indicatorsSearch in Google Scholar
World Resource Institute (2011). Climate Analysis Indicators Tool (CAIT) Version 8.0. http://cait.wri.org/.Search in Google Scholar
You, L., and S. Wood (2006). An Entropy Approach to Spatial Disaggregation of Agricultural Production. Agricultural Systems 90 (1–3): 329–347.Search in Google Scholar
You, L., S. Wood, and U. Wood-Sichra (2009). Generating Plausible Crop Distribution and Performance Maps for Sub-Saharan Africa Using a Spatially Disaggregated Data Fusion and Optimization Approach. Agricultural Systems 99 (2–3): 126–140.Search in Google Scholar
© 2013 Sergey Kiselev et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
