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1,26%
77,11%
21,62%
0,00%
0,00%
0,00%
38,2%
19,5%
39,6%
1,5%
0,1%
1,1%
100% Agriculture
100% Livestock
Agriculture-Livestock
Dairy
Forestall
Others
San Justo Land Use (superifice) San Justo 2002-2009
TS 2009 CNA 2002
50,93%
6,61%
42,43%
0,00%
0,00%
62,19%
1,72%
33,22%
2,74%
0,13%
100% Agriculture
100% Livestock
Mixed (Agriculture-livestock)
Dairy
Others/No data
Junn Land Use (Surface) 2002-2009
TS 2009 CNA 2002
72%
9%
9%
6%4%
Crops surface 2009-10 (San Justo)
Soybean
Sorghum
Sunflower
Corn
Wheat
54%17%
10%
15%
1%3%
Crops surface 2009-10 (Junn)
Soybean 1
Soybean 2
Corn
Wheat
Sunflower
Others
SUMMARY: This work analyses the relationship among climate factors, agricultural producers productive practices and their strategies to mitigate climate impacts. We will analyze climatic vulnerabilities and mitigation strategies of different kind of agriculture producers. The needs of expert knowledge on climate are related to the socio-productive profile and local context of each farmer. The ways in which this knowledge is integrated by producers in their mitigation strategies are also mediated by cognitive, material and symbolic factors. The emphasis will be placed on the conditions to elaborate mitigation strategies to reduce vulnerability and climate change adaptation plans which are able to integrate expert knowledge needs according to different kind of social actors.
INTRODUCTION: The way in which climate factor information is incorporated by farmers in their productive practices is a complex process, in which myriad factors take part on. From producers own features (place of residence, education level, local relations network, etc.) to environmental conditions (climate variability, soils, etc.), and structural conditions (macroeconomics, agricultural social structure, etc.) and contextual factors (infrastructure, presence/absence of public policies, articulation with local climate expert community, etc.) Due to this diversity , we have applied an anthropological approach that allows us to address this complexity from the ethnographic practice. Ethnographic fieldwork has been performed in two contrasting agro-ecological regions of La Plata Basin (Argentina): Junn, in Buenos Aires Province, and San Justo Department, in Santa Fe Province. These ethnographies extended from 2009 to 2011.
Climate and actors of agriculture production Florencia Fossa Riglos (UBA), Eugenia Muzi (UBA), Valeria Hernandez (IRD)
METODOLOGICAL APPROACH
We have applied the ethnographic method on two case studies, which allowed us to to reveal the point of view of each of the actors involved in the territories (agriculture producers, local politic authorities, and civil society) trough individual interviews and participant observation in local collective interaction spaces. In both cases we settled for a long stay of approximately 10 months (between 2009 and 2010) and in the main city of each productive zone selected. Then, during the rest of 2010 and 2011, we performed visits of variable lengths The cooperative relations with local actors were the result of a permanent interaction, based on the proposal of generating knowledge from and for the actors of these territories. We call this dynamic a Co-production of socially meaningfull knowledge, which envolves diverse genres of knowledge (scientific, productive, social, institutional, etc.), interests (economic, political, knowledge) and actors, all convoked to participate in the interaction space opened by means of the ethnography. Our unit of analysis was the urban zone and the adjacent agriculture zone, area which we call agrocity. The agriculture seasons of reference were mainly 2008/09 and 2009/10; and secondly 2010/11.
AGROECOLOGIAL AND CLIMATIC FEATURES OF EACH CASE STUDY:
Surface: 226,337 hectares. Population: 90305 inhabitants (CNPyV, 2010). Approximately 80% of Junns land allows agricultural activity, 14% extensive livestock, another 6% is composed of lagoons and 5% is only apt for livestock. Climate: Template, with a range of average temperatures between 19C and 23C. Rainfall: 900 mm. annual average with a higher incidence during the summer.
The charts above allow to observe the acceleration of agriculturalization process (more surface destined to agriculture) and the productive concentration by land tenants. Along with soybean expansion, livestock activities were abandoned or gradually displaced towards nearby departments with less aptitude for agriculture.
Surface: 557500 ha. Population: 40.904 inhabitants (CNPyV, 2010). Transitional space between two natural regions: the Pampas plains and lowland Chaco. Transitional climate zone: between zones with template climate and subtropical climate. Temperature: 19 C annual average. Approximately 44% of the land allows agricultural activities, 38% allows livestock activity, and 18% is integrated by lands with a very low productivity (lagoons, islands, etc). Rainfall: 1150 mm annual average, with extremes between 500 and 1800 mm/year.
Rainfall evolution and crops yields show that the combination of agroecological conditions and the kind of predominant production presents, in general, more vulnerability on dry periods than in events of hydric excess, though this last ones have been more frequent on XX century and XXI.
Climatic Events and mitigation strategies of the different socio-productive profiles: Main climatic events perceived: Material co-produced on focus groups.
Impact relativity: Agroecological, socio-structural and symbolic factors interacting within a productive unit:
Kind of farming techniques and kind of crops. Exploitation features: tenure, size, localization, kind of soil, etc.
Capitalization on infrastructure and machinery. Climatic information available. Representations, habits.
Family cycle and social capital.
Junn: Northwest of Buenos Aires
San Justo: North- center of Santa Fe Province Results of the quantitative territorial scan on land use and tenure performed with local actors. To evaluate the evolution of these variables we compared them with CNA 2002 data:
Knowledge role and new technological packages: Direct sowing technique (stubbles maintain soil's temperature), genetically modified seeds that adapt diverse environments, chemical fertilization, reference of national and international forecasts, local weather conditions monitoring through private devices , detailed analysis of each type of soil that will be sown on each season (moisture profile, composition, etc.), continuous monitoring of fields to prevent diseases and weeds, modeling of the agribusiness variables involved for each agricultural season (international price, agricultural inputs prices, services costs, average yield for each zone, climate forecast for the region , etc.) basing on specific software.
INTEGRATED STRATEGIES Complexity of actor's appropriation, which is central at the moment of
designing strategies to mitigate diverse climatic events impacts.
Mitigation Strategies: ethnographic material
CONCLUSIONS Extreme climatic events highlight structural social tensions inherent to modern agriculture productive model, which are not evident in times of high yields, economic benefits and in the absence of this climactic events. If, as forecasted, there is an accentuation on the occurrence of such events, then socio-economic gaps among the current rural world different productive profiles will express more vigorously , which will introduce a social conflict dynamics. In this context, State, trough the design of sectorial public policies that incorporate this complex analysis, integrating climatic, agro-ecological, social, economic, political and symbolic issues, could anticipate and regulate, these inherently controversial trend.
Climatic event ResponsesDrought 77,78%Flood 83,33%Hail 33,33%Extreme temperature 33,33%Late frost 16,67%Rainfall out of season 5,56%
Climatic factor (Junn)
Climatic event ResponsesDrought 100,00%Flood 100,00%Hail 0,00%Extreme temperature 36,36%Frost 0,00%Rainfall variability 100,00%"El Nio" efect 36,36%
Climatic factor (San Justo)
0200400600800100012001400160018002000
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
Yea
r19
6919
7019
7119
7219
7319
7419
7519
7619
7719
7819
7919
8019
8119
8219
8319
8419
8519
8619
8719
8819
8919
9019
9119
9219
9319
9419
9519
9619
9719
9819
9920
0020
0120
0220
0320
0420
0520
0620
0720
08
Mm rainfall
Kg/h
a
Rainfall and yiels by crop (San Justo)
Linen Wheat Corn Sunflower Soybean Sorghum Mm rainfall
0
200
400
600
800
1000
1200
1400
1600
1800
0
2000
4000
6000
8000
10000
12000
1969
/70
1970
/71
1971
/72
1972
/73
1973
/74
1974
/75
1975
/76
1976
/77
1977
/78
1978
/79
1979
/80
1980
/81
1981
/82
1982
/83
1983
/84
1984
/85
1985
/86
1986
/87
1987
/88
1988
/89
1989
/90
1990
/91
1991
/92
1992
/93
1993
/94
1994
/95
1995
/96
1996
/97
1997
/98
1998
/99
1999
/00
2000
/01
2001
/02
2002
/03
2003
/04
2004
/05
2005
/06
2006
/07
2007
/08
2008
/09
2009
/10
2010
/11
Mm rainfall
Kg/h
a
Agricultural season
Rainfall and yields by crop (Junn)
Soybean Corn Wheat Sunflower Mm rainfall
67,86%
21,08%
11,06%
0,00%
46,41%
39,52%
13,56%
0,51%
Surface produced by Owners
Surface produced by Tenants
Surface in mix exploitation
Others
San Justo Land Tenure (surface) 2002-2009
TS 2009 CNA 2002
51,87%
5,27%
42,80%
0,06%
51,06%
31,91%
16,75%
0,28%
Produced by owners
Produced by tenants
Produced in a mixed way
Others/No data
Junn Land Tenure (Surface) 2002-2009
TS 2009 CNA 2002
Climatic Event Agribuisness capitalized producers Traditional practices and/or low capitalization producersDraught (Impact according to productive diversification)
Productive diversification relying on cattle (more expensive and less profitable than soybean ) They didnt sow and waited for humidity accumulation on the ground
Livestock: animal migration, geographic diversification Scarce or nule geographical diversification "nothing else to do"
Agriculture: posibility of stocking wet grains on "grain-bags"Little capital to manouver technological investmentsPrivate channels construction, no territorial planification, differential appropiation of the territory
Vulnerability to private channels construction and the drainage of the water into their lands
Machinary Owner: flexibility of sowing schedule Machinery Owner: prioritize their engament with bigger producers over their own fileds labour scheduleMachinary Contractee: priority over contractors and small producers (due to profitability)
Machinary Contractee: conditioned by contractors schedule built according to profit possibilities.
Nio/Nia Cycles Access to private climatic information and advice in order to plan their agriculture season Little availability of appropiate information in order to plan the agriculture season. Traditional climatic indicators.
Floods (Impact according to land location and geographical diversification)
Frosts (Impact according to farming schedule flexibility)