Modern development of agricultural regions: driving forces, regional pattern changes and

land use conflicts

IGU Moscow Conference - August 2015

Alexey Naumov

Faculty of Geography

Lomonosov Moscow State University

alnaumov@mail.ru

Regionalization of the world agriculture: historical overview

• Since the end of XIX century, many geographers have attempted to produce schemes of regionalization of the world agriculture (E. Hahn, 1892; O. Baker,1920s; D. Whittlesey, 1936; D.Grigg, 1969, etc.)

• Some of these schemes were based on the agroecological approach (regionalization by potential agricultural use, based on physical-geographical characteristics)

• Most geographers preferred to study the proper phenomena of agriculture and have focused on characteristics of agriculture itself (social, economical, technical)

• Global schemes of regionalization of agriculture, produced until 1970s, were mainly based on observations/descriptions, regions were determined as areas of predominance of model types of agriculture

• These model types, sometimes thought as products of evolution of agricultural economy and techniques, had real regional prototypes (as the types of agricultural occupance of the land in: D.Wittlesey, 1936)

• Some scholars considered agricultural regions as complex territorial systems, ‘maturing’ with the development of market economy, and having specific role in local, regional and global division of labor (B. Knipovich, other Russian and Soviet geographers)

• Thus, specialization on production of certain kinds of agricultural raw materials became one of the main variables for regionalization of agriculture

Regionalization of the world agriculture: new opportunities

• Nowadays, there are powerful tools and precise data sources for regionalization of the world agriculture

• Statistical database: by 2006, 134 countries had carried out agricultural census, in 130 countries, concise data are available for large administrative units (states, provinces…), and in 59 countries – by smaller units (counties, municipalities…) (FAO)

• Remote sensing: is widely applied to determine land use pattern and areas under certain crops

• GIS technologies: create possibilities for cross statistical indicators with land use data

• FAO has recently started projects on global mapping of agriculture (Global livestock information system, Agro-maps, GLC2000…)

• The goal of FAO project on global mapping of agricultural production systems (Agro-maps) is to cover whole area of the globe with rectangle 20-50 km side size spots, characterized by predominance of certain crop, or combination of crops

• GIS-based matching of agricultural statistics with land use data is already used for yields monitoring (US NASS, Brazilian CONAB)

• This approach is very productive for mapping crops distribution by the Earth surface and geographical difference of crop yields (N. Ramankutty, A. Evan, C. Monfreda, J. Foley, 2008)

Source: Monfreda, Ramankutty and Foley, 2008

Geographic distribution of crop areas, yields, physiological types, and net primary production in the year 2000

Specialized agricultural regions of the world

(see the legend in separate printed file)

Source: Naumov, 2015

No Crop 5 leading countries, %10 leading

countries, %

20 leading

countries, %

Number of specialized

regions*

1. Wheat 53 71 86 22

2. Rice 70 85 94 21

3. Maize (corn) 68 79 87 22

4. Soybean 88 96 99 9

5. Rapeseed 71 87 96 7

6. Sunflower 63 81 95 11

7. Olive 72 91 98 8

8. Oil palm 91 95 99 9

9. Potato 56 67 80 17

10. Sugarcane 74 83 92 19

11. Sugar beet 58 79 93 12

12. Cotton (lint) 76 89 95 23

13. Flax (lint) 84 99 100 6

14. Tea 75 90 98 13

15. Coffee 65 81 92 18

16. Cocoa 82 94 98 5

17. Apples 64 75 87 16

18. Oranges 61 76 90 17

19. Banana 57 74 88 18

20. Coconut 82 90 96 15

21. Grape 49 70 87 17

22. Dates 67 90 99 5

Global

concentration of

agricultural

production:

share of leading

countries in

global

production, %,

and number of

regions

producing >1%

of the world

harvest (2012)

Note: * map on the

next page

Source:

FAOSTAT

Large-scale agricultural regions (commercial regions, industrial regions): grains and oilseeds, sugar crops, fiber crops, fruits, etc.

• Produce the main volume of food and agricultural raw materials, spread all over the world

• Develop in a similar natural conditions

• Specialization developed in industrial period, changes depend on demand for new products (e.g. biofuel)

• Mostly relay on machine plowing and harvesting, hired labour widely used

• Extend with the growing demand for food, new technology (high bred seeds, GMO, fertilizers, machinery…)

• Borders not stable, they move with oscillations of prices of commodities and means of production

• Spread from ‘optimal conditions’ core to marginal zones, the last ones vulnerable in terms of cost/benefit relation and may as extend, as shrink

• Economy is sustainable in case of state subsidies, overproduction control

Soybeans harvesting in the Brazilian Cerrado, West of the Bahia state (Naumov, 2007)

Localization index (IL) of the harvested area of grains and oilseeds in the USA, 2010

State* Crop

Winter wheat Summer wheat Wheat (total) Maize (corn) Sorghum Soybean

Idaho 1,6 –** 2,0 – – –

Iowa – – – 2,0 – 1,6

Arizona – 13,0 – – – –

Arkansas – – 4,0 – – 1,7

Wisconsin – – – 1,5 – –

Delaware – – – 1,5 – 1,6

Illinois – – – 2,1 – 1,6

Indiana – – – 1,8 – 1,7

California – 3,5 – – – –

Kansas 3,5 – 2,3 – 6,4 –

Colorado 3,7 – 2,5 – 1,7 –

Louisiana – – – – 1,5 1,2

Minnesota – – – 1,4 – 1,5

Missisippi – – – – – 1,9

Missouri – – – – – 1,6

Montana 2,1 7,2 3,8 – – –

Nebraska – – – 1,8 – –

New Mexico 3,1 – 2,1 – 4,8 –

Ohio – – – – 1,8 –

Oklahoma 4,3 – 2,9 – 1,8

Oregon 3,6 – 2,8 – – –

North Dakota – 10,2 2,6 – – –

North

Carolina

– – – – 1,4 –

Texas 1,9 – 4,3 – 5,6 –

South Dakota – – 1,1 – – –

Notes: * Only states with IL > 1; ** Hereafter: Harvested area of given crop insignificant, or does not exist. Source: Naumov, 2011

Crop 1924 2010

Share of the leading state

in the total harvested area

of given crop, 2010 (%)

Maize (corn)Iowa (4,5)*

Nebraska (3,7)

Iowa (5,0)

Illinois (3,6)

15,5%

SoybeanIowa (0,04)

Missouri (0,04)

Iowa (3,6)

Illinois (3,0)

11,8%

Wheat (all) North Dakota (4,2)

Kansas (1,6)**

North Dakota (3,2)

Kansas (2,1)

16,8%

SorghumTexas (0,7)

Kansas (0,6)

Kansas (0,8)

Texas (0,1)

35,2%

PotatoMinnesota (0,1),

New York (0,1)

Idaho (0,4)

Washington (0,1)

13,3%

States of the USA, ranking 1st and 2nd by harvested area of main commercial crops,

1924 and 2010.

Notes:* Hereafter in brackets – harvested area, million ha;** In 1926, Kansas was the 1st, and North Dakota – the 2nd with 3,5 and 1,5 million ha respectively.

Source: Naumov, 2012; data source: NASS/USDA

Localization index (IL) for seasonal crops by economic regions of France,2008

Region Sugar beet Summer wheat Winter wheat Rapeseed Maize (corn) Potato Sunflower Soybean

IL > 1 for four crops

Poitou-Charentes 0,0 1,1* 1,1 1,1 1,3 0,1 3,2 0,1

Champagne-Ardenne 3,3 0,0 1,1 1,9 0,5 1,6 0,2 0,0

Centre 0,6 1,7 2,0 1,9 0,7 0,6 1,0 0,1

Midi-Pirénées 0,0 3,1 0,7 0,4 1,2 0,0 3,5 4,8

IL > 1 for three crops

Aquitaine 0,0 0,0 0,0 0,2 3,9 0,3 1,7 4,0

Picardie 5,5 0,0 1,5 1,1 0,5 4,4 0,0 0,0

Alsace 1,2 0,0 0,1 0,2 6,1 0,7 0,0 3,1

IL > 1 for two crops

Bourgogne 0,1 0,0 0,9 2,1 0,5 0,1 0,8 2,0

Haute-Normandie 1,7 0,0 0,7 1,6 0,2 2,2 0,0 0,0

Languedoc-Roussilion 0,0 13,2 0,0 0,3 0,1 0,6 2,1 0,3

Nord-Pas-de-Calais 4,2 0,0 0,8 0,4 0,3 8,1 0,0 0,0

Rhône-Alpes 0,0 0,6 0,3 0,4 2,2 0,4 0,8 2,8

Franshe-Comté 0,0 0,1 0,2 1,1 1,2 0,1 0,7 4,7

IL > 1 for one crop

Pays-de-la-Loire 0,0 0,7 1,1 0,4 0,9 0,1 0,6 0,0

Ile-de-France 3,3 0,3 0,7 1,6 0,8 0,8 0,2 0,0

Lorraine 0,0 0,0 0,7 2,5 0,2 0,1 0,1 0,0

PACA 0,0 12,0 0,0 0,1 0,2 0,5 0,9 0,3

No IL > 1

Bretagne 0,0 0,0 0,8 0,3 0,9 0,8 0,0 0,0

Corse 0,0 0,0 0,0 0,0 0,8 0,2 0,1 0,0

Limouisin 0,0 0,0 0,1 0,1 0,2 0,1 0,3 0,0

Basse-Normandie 0,5 0,0 0,6 0,7 0,3 0,3 0,1 0,0

Auvergne 0,4 0,0 0,3 0,3 0,8 0,1 0,7 0,2Source: Naumov, 2011

Localization Index (IL) for main export crops in Brazil, 2002

Rondônia 0 1,5 0 1,9 0,1 0,4 0

Tocantins 0,1 0,1 0,1 0 0,1 0,1 0

Maranao 0,2 0,3 0,3 0 0,1 0,1 0

Piayi 0,1 0 0,1 0 0 1,3 0

Ceará 0,1 0 0 0 0,1 0,4 0

Riu Grande de Norte 1,3 0,1 0 0 0 2,1 0,1

Paraíba 1,3 0 0 0 0,1 1,4 0,1

Pernambuco 5,1 0 0 0 0,1 0,1 0

Alagoas 5,4 0,1 0 0 0,1 0,2 4,2

Sergipe 0,6 0 0 0 8,2 0,2 0,7

Bahia 0,2 0 0,5 11,7 0,5 2,1 0,4

Minas Gerais 0,7 3,5 0,5 0 0,6 0,7 0,1

Espírito Santo 0,6 4,9 0 1,7 0,2 0 0

Rio de Janeiro 5,7 14,7 0 0 1,2 0 0

São Paulo 4,2 1,2 0,3 0 6,4 1,2 0

Parana 0,4 0,2 1,6 0 0,1 1,8 0,8

Santa Catarina 0,2 0,4 0,5 0 0,3 0 8,5

Rio Grande do Sul 0,1 0 1,8 0 0,2 0 3

Goiás 0,4 0,1 1,8 0 0,1 2,1 0

Mato Grosso 0,4 0 2,6 0 0 0,8 0

Mato Grosso do Sul 0,5 0,1 2,2 0 0 2,2 0

DF 0,1 0 1,7 0 0,5 0 0

Source: Naumov, 2005

Source: Ferreira, Prado, Naumov et al (2009)

Part of Brazilian Cerrado, colonized after 1980s (SW of Goias state)

Specific small-scale agricultural regions (peasant regions, non-industrial regions): vegetables, fruit, cheese, wine production

• Unique physical-geographical conditions, contrasting with nearby territory

• Natural fertility guarantees high yields

• Agriculture based on labour-intensive technologies

• Specialization developed in pre-industrial period

• Small-scale family farming is predominant

• Borders of these regions match with natural barriers and are stable

• Economy is sustainable because of constant demographic pressure on land, overpopulation controlled by migration

• Specialization determined by demand of a nearby consumption market (city)

• Production is maintained because of fame of local ‘brands’ (AOP, DOP, etc.) and high qualification of local producers

Onions planting on the terraces at the shore of Atitlan lake, Guatemala (Naumov, 2009)

The Lassithi Plateau, Crete (Greece)

• Drainless hollow at 800 m asl, protected by mountain ranges

• Fertile alluvial soil used for wheat (in previous times), potato, vegetables and forage crops

production since the ancient Greece

• Old drainage system is still in use

• Land is divided by small plots (less than 1 ha), owned by peasants

• 2500 inhabitants live on agriculture, production is supplied to the Heraklion market

1 km

Source: Wikimapia Photo: A. Naumov, 2015

Conclusions

•GIS technologies and availability of statistical and remote sensing data create new opportunities for agricultural regionalization and studying of regional development of agriculture

•In modern agriculture coexist various social-economic models of production, i.e. large-scale commercial and small-scale peasant agriculture; these models are sustainable enough because of relaying on different driving forces (according to A. Chayanov theory)

•Large-scale commercial agriculture development is driven by market mechanisms (surplus value law)

•Small-scale traditional agriculture survives due to elasticity of peasant economy

•Modern agricultural regions represent spatial expression of both large-scale and small-scale economic models of agriculture

•Both types of regions create networks, which may overlap; these cases are areas of conflicts for land possession (land grabbing for commercial farming in peasant regions, landless peasants protests)

Thank you!

Cotton harvest in recently colonized part of Brazilian Cerrado, W of Bahia state (Naumov, 2005)