Page 249 - Climate Change and Food Systems

chapter 7: grain rain production trends in russia, ukraine and kazakhstan in the context of climate change and international trade
Federation: the “Virgin Lands” campaign (end of 1950s); Kosygin-Liberman initiatives (late 1960s); Brezhnev’s stagnation era (late 1970s-early 1980s); Gorbachev’s “Perestrojka” (1985-1991); and land privatization and price liberalization (1990s). They found a long-term trend of ~1.15 percent yield increase annually, which they attributed to long- term technological change.
To estimate future climate-related yield changes in the region of interest, we used a dynamic yield model by Alcamo et al. (2007) and a statistical model by Dronin and Kirilenko (2013). Both
models were limited in coverage to the Russian Federation territory; for this reason, we estimated corresponding changes in Ukraine and Kazakhstan by computing the changes in yields in the adjacent agricultural zones of the Russian Federation. For Kazakhstan, this zone included Chelyabinskaya, Kurganskaya, Omskaya, and Tumenskaya Oblasts, and for Ukraine, Belgorodskaya, Kurskskaya, Lipetskskaya, Rostovskaya, and Voronezhskaya Oblasts and Stavropolsky Kray. For the territory of the Russian Federation, the dynamic and statistical models both show similar patterns in yield change, generally with a small reduction or an increase
in yield for the Russian Federation and Ukraine
and larger reductions for Kazakhstan (Table 7). Since the statistical model may poorly represent the yield outside the range of the historical
climatic envelope, in the next section we base our assessments on the results of the dynamic model (Alcamo et al., 2007), while assuming the historical long-term technology-related trends in yields found by Dronin and Kirilenko (2013).
5. Outlooks for grain production and export
The outlooks for grain production and export
are typically based on analyses of the recent agricultural trends, agricultural and economic policies, and assumptions about improvements of technology, infrastructure, and management techniques. They do not usually take into account climate change scenarios. The Federal Program of Agricultural Development and Regulation of Markets for Agricultural Produce, Raw Materials, and Food for 2013-2020 (Gosudarstvennaya programma razvitiya..., 2012) set new targets for the agriculture sector of the Russian Federation focusing on: (1) increased export potential; and
table 7
Estimated wheat yield change from 1980s to 2020s (percentage) attributable to temperature and precipitation shift alone, as simulated by dynamic (D, see Alcamo et al., 2007) and statistical (S, see Dronin and Kirilenko, 2013) yield models. Notice that for this time period the pattern of climate change is similar for A1FI and A2 scenarios
A1FI S 78.9 91.6 97.3
D---
A2 S 75.9 90.1 97.1
D 96.8 94.0 78.5
B1 S 80.4 90.8 98.0
D---
B2 S - - -
D 73.8 90.3 86.4
Sources: ERBD, 2008 ; IKAR, 2009 ; Liefert et al., 2013 ; Rau, 2012 ; FAOSTAT, 2013 ; Babkin, 2013, Schierhorn et al., 2012
Scenario
Model
Kazakhstan
Russia
Ukraine
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