In Brasil ranching has played a fundamental role in the occupation of rural land. This process results in a series of environmental impacts, such as the erosion and compaction of the soil, and the emission of greenhouse gases, in addition to the intensive use of the soil and water resources. In part of the properties, inadequate management resulted in pastures with degradation levels. The literature points out the importance of intensifying technology as a way to guarantee sustainable pastures. The present study aims to identify and analyze the relationships between the technological level level of cattle production and the degradation of pastures in the Vermelho River basin in Goiás, central Brazil. This area is considered to be representative of livestock in the Brazilian Cerrado. The sample consisted of 60 cattle ranches, selected from each of the three sectors of the Vermelho River basin. The data were analyzed using a Multiple Correspondence Analysis, cluster analysis, and Beta regression to obtain Pasture Degradation Indice (PDI). Bivariate associations were found between the Technological Index (TI) and three variables – the manager’s income, topographic relief, and the size of the property. It was possible to verify the use of a higher technological level in the largest properties as well as in flatter areas. It was also found that the higher technological level provides higher remuneration to managers. However, there was no relationship between the technology used in the establishments and the cattle density, which can reduces profitability economic and animal welfare. There was also no association between TI and PDI, suggesting pasture degradation, even when using more intensive technologies in cattle production.
ARMENTERAS, D., et al. Landscape Dynamics in Northwestern Amazonia: An Assessment of Pastures, Fire and Illicit Crops as Drivers of Tropical Deforestation. PLoS ONE, v.8, January, 2013. https://doi.org/10.1371/journal.pone.0054310
BOWMAN, M., et al. Persistence of Cattle Ranching in the Brazilian Amazon: A Spatial Analysis of the Rationale for Beef Production. Land Use Policy, v. 29, p.558-568, 2012. https://doi.org/10.1016/j.landusepol.2011.09.009
CARO, D., et al. Greenhouse Gas Emissions Due to Meat Production in the Last Fifty Years. In: Ahmed M., Stockle C. (eds) Quantification of Climate Variability, Adaptation and Mitigation for Agricultural Sustainability. Springer, Cham, 2017. https://doi.org/10.1007/978-3-319-32059-5_2
DIAS, L.C.P., et al. Patterns of land use, extensification, and intensification of Brazilian agriculture. Global change biology, v.22, n. 8, p.2887-2903, 2016. https://doi.org/10.1111/gcb.13314
GIBBS, H. K., et al. Tropical forests were the primary sources of new agricultural land in the 1980s and 1990s. Proceedings of the National Academy of Sciences, v. 107, n.38, p.16732-16737, 2010. https://doi.org/10.1073/pnas.0910275107
GOENER, A., GLOAGUEN, R., MAKESCHIN, F. Monitoring of the Ecuadorian mountain rainforest with remote sensing. Journal of Applied Remote Sensing, v.1, n. 1, p.013527-013527-12, 2007. https://doi.org/10.1117/1.2784111
GREENACRE, M.. Correspondence Analysis in Practice. Barcelona, Chapman and Hall/CRC, 2007. https://doi.org/10.1201/9781420011234
GRIFFITH, D. C. Migration, Labor Scarcity, and Deforestation in Honduran Cattle Country. Journal of Ecological Anthropology, v. 18, n. 1, p.3, 2016. https://doi.org/10.5038/2162-45188.8.131.52
GUEDES, T. A., et al. Seleção de variáveis categóricas, utilizando análise de correspondência e análise procrustes. Acta Scientiarum. Technology, v.21, p.861-868, 2008. https://doi.org/10.4025/actascitechnol.v21i0.3084
HAIR JR., J.F., et al. Análise multivariada de dados. Trad. Adonai Schlup Sant’Anna e Anselmo Chaves Neto. 5 ed. Porto Alegre: Bookman, 2009.
IBGE - Instituto Brasileiro de Geografia e Estatística. Base Cartográfica Contínua do Brasil ao milionésimo. Ver 3. Rio de Janeiro. 2017. Available in: < https://bit.ly/2EROYLT>. Acessed: february, 12, 2018.
_____ Economia. Censo agropecuário, 2006. Available in: <https://bit.ly/3d0SazL>. Acessed: july, 05, 2017.
KLINK, C.A., MACHADO, R.B. A conservação do Cerrado brasileiro. Megadiversidade, v.1, n. 01, p.147-155, 2005. Available in: < https://bit.ly/3g9rUFa>. Acessed: August 26, 2018.
LIMA, S. S., et al. Relação entre a presença de cupinzeiros e a degradação de pastagens. Pesquisa Agropecuária Brasileira, v.46, n.12, p.1699-1706, 2012. https://doi.org/10.1590/S0100-204X2011001200016
LIMA, V. M. A., CALDARELLI, C. E., CAMARA, M. R. G. Análise do desenvolvimento municipal paranaense: uma abordagem espacial para a década de 2000. Economia e Desenvolvimento, v. 26, n. 1, p. 1-19, 2014. https://doi.org/10.5902/1414650911030
MACHADO, L.E.G., LIMA, C.V.L. Compartimentação geomorfológica da bacia hidrográfica do Rio Vermelho (GO), utilizando imagens ASTER. In: Simpósio Brasileiro de Sensoriamento Remoto – SBSR, Curitiba. Anais... São Paulo, Instituto Nacional de Pesquisa Espacial, p.8231, 2011. Available in: < https://bit.ly/2NDPOwj>. Acessed: August 26, 2018.
MARGULIS, S. Causas do Desmatamento da Amazônia Brasileira. Banco Mundial Brasília DF, 2003. Available in: < https://bit.ly/3d0SSNr >. Acessed: August 26, 2018.
MCMANUS, C., et al. Dynamics of Cattle Production in Brazil. Plos One, January 27, 2016. https://doi.org/10.1371/journal.pone.0147138
OECD-FAO – Organization for Economic Cooperation and Development, Food and Agriculture Organization of the United Nations, 2015. OECD-FAO Agricultural Outlook 2015 – Chapter 2. Paris. http://dx.doi.org/10.1787/agr_outlook-2015-4-pt
OLIVEIRA, E. R., et al. Development of a technological index for the assessment of the beef production systems of the Vermelho River Basin in Goiás, Brazil. Revista Pesquisa Operacional, v.38, n.1, p.117-134, 2018. https://doi.org/10.1590/0101-7438.2018.038.01.0117
PAGÈS, J. Multiple Factor Analysis by example using R. Chapman and Hall, CRC Press, 2014.
PERON, A.J.; EVANGELISTA, A.R. Degradação de pastagens em regiões de cerrado. [Degradation of pasture in the Brazilian Cerrado]. Revista Ciência e Agrotecnologia, Lavras, MG, v. 28, n. 30, p.655-661, 2004. https://doi.org/10.1590/S1413-70542004000300023
PINHEIRO, T. F. et al. Forest degradation associated with logging frontier expansion in the Amazon: the BR-163 region in Southwestern Pará, Brazil. Earth Interactions, v.20, n. 17, p.1-26, 2016. https://doi.org/10.1175/EI-D-15-0016.1
ROSA, A. N. et al. Peso adulto de matrizes em rebanhos de seleção da raça Nelore no Brasil. Revista Brasileira de Zootecnia, v.30, n.30, p. 1027-1036, 2001. https://doi.org/10.1016/j.rsase.2020.100288
SHIRVANI, Z., et al. Analyzing spatial and statistical dependencies of deforestation affected by residential growth: Gorganrood basin, Northeast Iran. Land Degradation & Development, 18 april, 2017. https://doi.org/10.1002/ldr.2744
WARD JR., J.H. Hierarchical grouping to optimize an objective function. Journal of the American statistical association, v.58, n.301, p.236-244, 1963. https://doi.org/10.1080/01621459.1963.10500845
Authors hold the Copyright for articles published in this journal, and the journal holds the right for first publication. Because they appear in a public access journal, articles are licensed under Creative Commons Attribution (BY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.