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Geospatial analysis of ecological vulnerability of coffee agroecosystems in Brazil

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Abstract

Geographical information systems and statistics were used to characterize the climatic vulnerability of coffee agroecosystems in Brazil. Average annual mean air temperature, mean air temperature of the coldest month, and moisture index were used to characterize climatic vulnerability for Coffea arabica and Coffea canephora species cultivation based on high-resolution interpolated climate surfaces from the average of the period of 1950 to 2000 and the A2 2080 climate change scenario. Soil vulnerability for coffee cultivation was derived from soil classes 1:5,000,000 scale and slope estimated from SRTM digital elevation model at 90 m spatial resolution. Coffee tree production at municipal district level from 1990 to 2006 was used to validate the obtained results of the vulnerability of coffee agroecosystems. A coffee tree index was developed using the principal components technique, based on variables related to coffee yield, coffee harvested and coffee cultivated areas. The coffee tree fraction index explained 87.0 % of coffee tree fraction and was classified in five levels inside the municipal district boundaries using natural breaks method. Based on the adopted methodology, it was possible to observe relationship between coffee tree cultivation areas and coffee climatic vulnerability in Brazil for the scenario of 1950 to 2000. Considering A2 2080 scenario of climate change, suitable areas for coffee cultivation were moved to the states of the south and southeast of Brazil.

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References

  • Agrianual (2008) Anuário da Agricultura Brasileira. Instituto FNP, São Paulo

    Google Scholar 

  • Allen RG, Pereira LS, Raes D, Smith M (1998) Crop evapotranspiration—guidelines for computing crop water requirements. In: Food and Agriculture Organization of the United Nations-FAO. Irrigation and Drainage Paper, Rome, p 56

    Google Scholar 

  • Alves MC, Carvalho LG, Pozza EA, Alves LS, Maia JCS (2011) Ecological zoning of soybean rust, coffee rust and banana black sigatoka based on Brazilian climate changes. Procedia Environ Sci 6:35–49

    Article  Google Scholar 

  • Anuário (2002) Statistic coffee yearbook 2001/2002. Coffee business, Rio de Janeiro

    Google Scholar 

  • Assad ED, Evangelista BA, Silva FAM, Cunha SAR, Alves ER, Lopes TSS, Pinto HS, Zullo J Jr (2001) Agroclimatic zoning for Coffee (Coffea arabica L.) in the state of Goiás and southeastern state of Bahia, Brazil. Rev Bras Agrometeorol 9:510–518

    Google Scholar 

  • Assad ED, Pinto HS, Zullo J Jr, Ávila AMH (2004) Climatic changes impact in agroclimatic zonning of coffee in Brazil. Pesq Agropec Bras 39:1057–1064

    Article  Google Scholar 

  • Brasil (1992) Ministério da Agricultura e Reforma Agrária, Secretaria Nacional de Irrigação, Departamento Nacional de Meteorologia. Normais climatológicas (1961–1990), Brasília

  • Camargo AP (1977) Zoneamento da aptidão climática para a cafeicultura de arábica e robusta no Brasil. Fundação IBGE, Recursos meio ambiente e poluição

  • Camargo AP, Pereira AR (1994) Agrometeorology of the coffee crop. Agricultural Meteorology Cam Report No. 58. World Meteorological Organization, Geneva

  • Caramori PH, Caviglione JH, Wrege MS, Gonçalves SL, Faria RT, Androcioli Filho A, Sera T, Chaves JCD, Koguishi MS (2001) Climatic risk zoning for coffee (Coffea arabica L.) in Paraná state, Brazil. Rev Bras Agrometeorol 9:486–494

    Google Scholar 

  • Carvalho LG, Sediyama GC, Cecon PR, Alves HMR (2004) A regression model to predict coffee productivity in Southern Minas Gerais, Brazil. Rev Bras Eng Agríc Ambient 8:204–211

    Article  Google Scholar 

  • Carvalho LG, Mello CR, Alves MC, Curi N, Marques AFSM, Marques JJ (2008) Zoneamento da cana-de-açúcar e do eucalipto:aspectos geofísicos e bióticos. In: Scolforo JRS, Oliveira AD, Carvalho LMT (eds) Zoneamento Ecológico-Econômico do Estado de Minas Gerais: Zoneamento e Cenários Exploratórios, vol 1. Editora UFLA, Lavras, pp 53–60

    Google Scholar 

  • CGIAR (2009) Consortium for spatial information (CGIAR-CSI). Available from http://srtm.csi.cgiar.org/

  • Crepani E, Medeiros JS, Palmeira AF, Silva EF (2008) Zoneamento ecológico-econômico. In: Florenzano TG (ed) Geomorfologia: Conceitos e Tecnologias Atuais. Oficina de Textos, São Paulo

    Google Scholar 

  • Downing TE (1992) Climate Change and Vulnerable places: Global Food Security and country studies in Zimbawe, Kenya, Senegal and Chile. Research Report 1, Environmental Change Unit. University of Oxford, United Kingdom

    Google Scholar 

  • EMBRAPA (1999) Sistema Brasileiro de Classificação de Solos. Centro Nacional de Pesquisa de Solos, Rio de Janeiro

    Google Scholar 

  • Evangelista AWP, Carvalho LG, Sediyama GC (2002) Climatic zoning associated to the productive potential of coffee crop in Minas Gerais State, Brazil. Rev Bras Eng Agríc Ambient 6:445–452

    Article  Google Scholar 

  • Evenson RE (1999) Global and local implications of biotechnology and climate change for future food supplies. Proc Natl Acad Sci USA 96:5921–5928

    Article  Google Scholar 

  • FAO (1998) World Reference base for soil resources. FAO, ISRIC, ISSS, Rome

    Google Scholar 

  • Flato GM, Boer GJ, Lee WG, McFarlane NA, Ramsden D, Reader MC, Weaver AJ (2000) The Canadian centre for climate modelling and analysis global coupled model and its climate. Clim Dynam 16:451–467, 2000

    Article  Google Scholar 

  • Hansen JW (2002) Realizing the potential benefits of climate prediction to agriculture: issues, approaches, challenges. Agric Syst 74:309–330

    Article  Google Scholar 

  • Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A (2005) Very high resolution interpolated climate surfaces for global land areas. Int J Climatol 25:1965–1978

    Article  Google Scholar 

  • IBGE (2008) Produção agrícola municipal. Available from http://www.sidra.ibge.gov.br/

  • IBGE (2009) Mapas interativos. Available from http://mapas.ibge.gov.br/solos/viewer.htm

  • IPCC (2007) Summary for Policymakers. In: Parry ML, Canziani OF, Palutikof JP, Van Der Linden PJ, Hanson CE (eds) Climate Change 2007: impacts, adaptation and vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK

    Google Scholar 

  • Jenks GF (1967) The data model concept in statistical mapping. Int Yearb Cartogr 7:186–190

    Google Scholar 

  • Krug CA (1959) World coffee survey. FAO, Rome

    Google Scholar 

  • Mitchell N, Espie P, Hankin R (2004) Rational landscape decision-making: the use of meso-scale climatic analysis to promote sustainable land management. Land Urb Plan 64:131–140

    Article  Google Scholar 

  • Motha RP (2007) Development of an agricultural weather policy. Agric For Meteorol 142:303–313

    Article  Google Scholar 

  • Murray AT, Shyy TK (2000) Integrating attribute and space characteristics in choropleth display and spatial data mining. Int J Geogr Inf Sci 14:649–667

    Article  Google Scholar 

  • Parry ML, Porter JH, Carter TR (1990) Agriculture: climate change and its implications. Trends Ecol Evol 5:318–322

    Article  Google Scholar 

  • Pinto HS, Zullo J Jr, Assad ED, Brunini O, Alfonsi RR, Coral G (2001) Climatic risc zoning for coffee trees in the state of São Paulo, Brazil. Rev Bras Agrometeorol 9:495–500

    Google Scholar 

  • Salinger MJ, Stigter CJ, Das HP (2000) Agrometeorological adaptations strategies to increasing climate variability and climate change. Agric For Meteorol 103:167–184

    Article  Google Scholar 

  • Salinger MJ, Sivakumar MVK, Motha R (2005) Reducing vulnerability of agriculture and forestry to climate variability and change: workshop summary and recommendations. Clim Chang 70:341–362

    Article  Google Scholar 

  • Santos MA, Camargo MBP (2006) Calibration of an agrometeorological model for predicting coffee (Coffea arabica L.) productivity in Sao Paulo state, Brazil. Bragantia 65:173–183

    Article  Google Scholar 

  • Sediyama GC, Melo Junior JCF, Santos AR, Ribeiro A, Costa MH, Hamakawa PJ, Costa JMN, Costa LC (2001) Climatologial zoning for arabic coffee (Coffea arabica L.) in the state of Minas Gerais, Brazil. Rev Bras de Agrometeorol 9:501–509

    Google Scholar 

  • Sivakumar MVK, Gommes R, Baier W (2000) Agrometeorology and sustainable agriculture. Agric For Meteorol 103:11–26

    Article  Google Scholar 

  • Slocum TA, Mcmaster RB, Kessler FC, Howard HH (2009) Thematic cartography and visualization. Prentice-Hall, Upper Saddle River

    Google Scholar 

  • Thornthwaite CW, Mather JR (1955) The water balance. Publications in climatology, vol VIII. Laboratory of Climatology, Drexel Institute of Technology, Centerton, NJ

    Google Scholar 

  • Vianello RL, Alves AR (1991) Meteorologia básica e aplicações. Imprensa Universitária/UFV, Viçosa

    Google Scholar 

  • Wackernagel H (2003) Multivariate geostatistics. Springer, Berlin

    Book  Google Scholar 

Download references

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Authors and Affiliations

  1. Department of Soil and Rural Engineering, Federal University of Mato Grosso, Faculty of Agronomy and Veterinary Medicine, Av. Fernando Correa da Costa 2367, Boa Esperança, 78060-900, Cuiabá, Brazil

    Marcelo de Carvalho Alves

  2. Engineering Department, Federal University of Lavras, P.O. Box 3037, 37200-000, Lavras, Minas Gerais, Brazil

    Fábio Moreira da Silva & Luiz Gonsaga de Carvalho

  3. Department of Environmental and Sanitary Engineering, Federal University of Mato Grosso, Faculty of Agronomy and Veterinary Medicine, Av. Fernando Correa da Costa 2367, Boa Esperança, 78060-900, Cuiabá, Brazil

    Luciana Sanches

  4. Engineering Department, Rural Federal University of Rio de Janeiro, BR-465, Km 7, Seropédica, Rio de Janeiro, 23890-000, Brazil

    Gabriel Araújo e Silva Ferraz

Authors
  1. Marcelo de Carvalho Alves
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  2. Fábio Moreira da Silva
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  3. Luciana Sanches
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  4. Luiz Gonsaga de Carvalho
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  5. Gabriel Araújo e Silva Ferraz
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Correspondence to Marcelo de Carvalho Alves.

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de Carvalho Alves, M., da Silva, F.M., Sanches, L. et al. Geospatial analysis of ecological vulnerability of coffee agroecosystems in Brazil. Appl Geomat 5, 87–97 (2013). https://doi.org/10.1007/s12518-013-0101-0

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  • DOI: https://doi.org/10.1007/s12518-013-0101-0

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