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Recent grain production boom in Russia in historical context

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Abstract

In recent years, Russia has established itself as the leading worldwide supplier of grain and continues to make ambitious plans for raising its grain production in the long term. Within the context of Russian agricultural history, the recent high growth in grain production is exceptional. This growth however is not fully replicated by the “weather-yield” crop models, which project only moderate yield increase in the twenty-first century and fail to predict the most recent record growth in grain yields. The difference between the projected climate-dependent yields and observations is especially high in two of the most important agricultural regions, the Central Black Earth and Northern Caucasus regions while the remaining agricultural zones show good agreement with the regression models. Similar differences were observed in the late 1960s, which we interpret in terms of the rapid changes in agricultural technology during the Union of Soviet Socialist Republic (USSR) agricultural reforms followed by periods of reversal. We also interpret the current period of high differentiation between weather-yield model results and collected yields as evidence of a higher than usual contribution of agricultural reforms in yield improvements, which, however, primarily benefit the large-scale producers located in the most productive areas of Russia.

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Notes

  1. In this publication, we use the terms “region” for 12 Economic regions of the Russian Federation (Fig. 2S in the Supplement) and “province” for its “federal subject” administrative units (such as Oblast, Autonomous Republic, and others). Our analysis is complete for provinces, but results are discussed in terms of the regions, which are larger units. For consistency, we used the administrative division of year 2008.

  2. Online Supplement is available at the following URL: https://www.researchgate.net/publication/358357637

  3. Black-box models have internal implementation, which is hard or impossible to inspect (is “black” for a researcher). Many (but not all) machine learning algorithms are black-box systems.

  4. Note that this data reflects only winter wheat, while Lobell et al. (2011) data are for winter and spring wheat.

  5. RosStat recognizes four categories of agricultural units: (1) agricultural enterprises; (2) individual entrepreneurs and private farms; (3) households in rural and urban settlements owning plots for subsistence farming; and (4) horticultural, kitchen-garden, livestock growing or gardening non-profit associations.

  6. Note that projections of massive increase of agriculture production in Russia in future climate such as published in The New York Times (https://www.nytimes.com/interactive/2020/12/16/magazine/russia-climate-migration-crisis.html) do not account for availability of fertile land suitable for agriculture.

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This article belongs to the topical collection "Climate Change in Russia – history, science and politics in global perspectives", edited by Benjamin Beuerle, Katja Doose, and Marianna Poberezhskaya

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Kirilenko, A., Dronin, N. Recent grain production boom in Russia in historical context. Climatic Change 171, 22 (2022). https://doi.org/10.1007/s10584-022-03332-z

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