DRIVERS OF DEGRADATION OF PASTURES IN THE CERRADO NORTH OF MINAS GERAIS - BR
Resumo
The Brazilian Cerrado Biome is a strategic region for livestock, with a high concentration of pastures and cattle. Approximately 30% of these pastures have some degree of degradation, especially in semi-arid regions. The northern region of the state of Minas Gerais portrays this context well. Therefore, identifying the degradation vectors is a fundamental step in agro-environmental planning. This study aims to develop a model to evaluate the vectors of degradation of pastures in Cerrado north of Minas Gerais. The methodological structure was based on i) mapping of the pasture degradation index (PDI) using remote sensing techniques, ii) setting up a database with predictive variables representing socioeconomic, relief and climatic aspects, and iii) elaboration of a model to evaluate the vectors of pasture degradation with multiple linear regression. The PDI mapping showed that the pastures in all municipalities present some degree of degradation. Eighteen municipalities (21%) have moderately degraded pastures and 66 municipalities (79%) predominantly have pastures with mild degradation levels. According to the statistical model, the degradation of pastures is explained by climatic vectors, specifically by air temperature, seasonality of precipitation and annual precipitation (R² = 0.50, p-value < 0.001). The management of pastures in the region must consider these environmental factors, aiming at a more sustainable livestock in the Cerrado of northern Minas Gerais.
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AGUIAR, D. A.; MELLO, M. P.; NOGUEIRA, S. F.; GONÇALVES, F. G.; ADAMI, M.; RUDORFF, B. F. T. MODIS time
series to detect anthropogenic interventions and degradation processes in tropical pasture. Remote Sensing, v. 9, n. 1, p. 73, 2017. https://doi.org/10.3390/rs9010073.
AKAIKE, H. A new look at the statistical model identification. IEEE Transactionson Automatic Control, v.19, n. 6, p. 716–723, 1974. https://doi.org/10.1109/TAC.1974.1100705.
ALIN, A. Multicollinearity. Wiley interdisciplinary reviews: computational statistics, v. 2, n. 3, p. 370–374, 2010. https://doi.org/10.1002/wics.84.
ANDRADE, R. G.; RODRIGUES, C. A. G.; SANCHES, I. D. A.; TORRESAN, F. E.; QUARTAROLI, C. F. Uso de técnicas
de sensoriamento remoto na detecção de processos de degradação de pastagens. Revista Engenharia na Agricultura-Reveng, v. 21, n. 3, p. 234–243, 2013. https://doi.org/10.13083/1414-3984.v21n03a02.
ANDRADE, R. G.; TEIXEIRA, A. H. D. C.; LEIVAS, J. F.; NOGUEIRA, S. F. Analysis of evapotranspiration and biomass in pastures with degradation indicatives in the Upper Tocantins River Basin, in Brazilian Savanna. Revista Ceres, v. 63, n.6, p. 754–760, 2016. https://doi.org/10.1590/0034-737x201663060002.
BRAZ, S. P.; URQUIAGA, S.; ALVES, B. J.; JANTALIA, C. P.; GUIMARÃES, A. P.; SANTOS, C. A.; BODDEY, R. M. Soil
carbon stocks under productive and degraded Brachiaria pastures in the Brazilian Cerrado. Soil Science Society of America Journal, v. 77, n. 3, p. 914–928, 2013. https://doi.org/10.2136/sssaj2012.0269.
CLEMENTINI, C.; POMENTE, A.; LATINI, D.; KANAMARU, H.; VUOLO, M. R.; HEUREUX, A.; DEL FRATE, F. Long-
term grass biomass estimation of pastures from satellite data. Remote Sensing, v. 12, n. 13, p. 2160, 2020. https://doi.org/10.3390/rs12132160.
COSTA, L. R. F. Considerations about the geomorphological macrounities of the state of Minas Gerais–Brazil. William Morris Davis–Revista de Geomorfologia, v. 2, n. 1, p. 1–9, 2021. https://doi.org/10.48025/ISSN2675- 6900.v2n1.2021.109.
DIDAN, K. MOD13Q1: MODIS/Terra vegetation indices 16-day L3 global 250m grid SIN V006. NASA EOSDIS Land Processes DAAC, v. 10, n. 1, 2015.
ESPINDOLA, G. M.; SILVA FIGUEREDO, E.; PICANÇO JÚNIOR, P.; REIS FILHO, A. A. Cropland expansion as a driver
of land-use change: the case of Cerrado-Caatinga transition zone in Brazil. Environment, Development and Sustainability, v.23, p. 1-15, 2021. https://doi.org/10.1007/s10668-021-01387-z.
FERNANDES, F. H. S.; SANO, E. E.; FERREIRA, L. G.; MELLO BAPTISTA, G. M.; CASTRO VICTORIA, D.; FASSONI-
ANDRADE, A. C. Degradation trends based on MODIS-derived estimates of productivity and water use efficiency:
A case study for the cultivated pastures in the Brazilian Cerrado. Remote Sensing Applications: Society and Environment, v. 11, p. 30–40, 2018. https://doi.org/10.1016/j.rsase.2018.04.014.
FERREIRA, G.H. C. Atlas da questão agrária Norte Mineira. 1.ed.São Paulo: Entremares, 2020.
FERREIRA, L. G.; SANO, E. E.; FERNANDEZ, L. E.; ARAÚJO, F. M. Biophysical characteristics and fire occurrence of cultivated pastures in the Brazilian savanna observed by moderate resolution satellite data. International Journal of Remote Sensing, v. 34, n. 1, p. 154-167, 2013. https://doi.org/10.1080/01431161.2012.712223.
FICK, S. E.; HIJMANS, R. J. WorldClim 2: new 1‐km spatial resolution climate surfaces for global land areas. International journal of climatology, v. 37, n. 12, p. 4302-4315, 2017. https://doi.org/10.1002/joc.5086.
GALDINO, S.; SANO, E. E.; ANDRADE, R. G.; GREGO, C. R.; NOGUEIRA, S. F.; BRAGANTINI, C.; FLOSI, A. H. Large‐
scale Modeling of Soil Erosion with RUSLE for Conservationist Planning of Degraded Cultivated Brazilian Pastures. Land Degradation & Development, v. 27, n. 3, p. 773–784, 2016. https://doi.org/10.1002/ldr.2414.
HABERMANN, E.; DIAS DE OLIVEIRA, E. A.; CONTIN, D. R.; DELVECCHIO, G.; VICIEDO, D. O.; DE MORAES, M. A.;
MARTINEZ, C. A. Warming and water deficit impact leaf photosynthesis and decrease forage quality and digestibility of a C4 tropical grass. Physiologia Plantarum, v. 165, n. 2, p. 383–402, 2019. https://doi.org/10.1111/ppl.12891.
IBGE. Instituto Brasileiro de Geografia e Estatística. Censo Demográfico, 2010. Disponível em: https://censo2010.ibge.gov.br/resultados.html. Acesso em: 15 de jan. 2020.
LAPIG. Laboratório de Processamento Digital de Imagens. Atlas das Pastagens, 2019. Disponível em: https://atlasdaspastagens.ufg.br/map. Acesso em: 05 de jan. 2020.
LEITE, M. E.; SOUZA, C. M. P.; SILVA, L. A. P. Dinâmica de uso da terra no Norte de Minas – Sudeste do Brasil. In: Ferreira, G. H. C.; COSTA, L. R. F. (orgs.). A Geografia do Norte de Minas Gerais: reflexões e proposições. 1. ed. São Paulo: Entremares, 2022. p. 165-177.
OLIVEIRA, E. R. D.; SILVA, J. R.; BAUMANN, L. R. F.; MIZIARA, F.; FERREIRA, L. G.; MERELLES, L. R. D. O. Tecnologia e degradação de pastagens na pecuária no Cerrado brasileiro. Sociedade & Natureza, v. 32, p. 626–638, 2020. https://doi.org/10.14393/SN-v32-2020-55795.
OLIVEIRA, W.F.; LEITE, M.E. Perda de Solo por Erosão Hídrica em Bacia Hidrográfica: o caso da área de drenagem da barragem do Rio Juramento, no Norte do estado de Minas Gerais. Caminhos de Geografia. V. 19, n. 67, p.16- 37, 2018. http://dx.doi.org/10.14393/RCG196702.
PARENTE, L.; MESQUITA, V.; MIZIARA, F.; BAUMANN, L.; FERREIRA, L. Assessing the pasturelands and livestock dynamics in Brazil, from 1985 to 2017: A novel approach based on high spatial resolution imagery and Google Earth Engine cloud computing. Remote Sensing of Environment, v. 232, p. 111301, 2019. https://doi.org/10.1016/j.rse.2019.111301.
PEREIRA, O. J. R.; FERREIRA, L. G.; PINTO, F.; BAUMGARTEN, L. Assessing Pasture Degradation in the Brazilian Cerrado Based on the Analysis of MODIS NDVI Time-Series. Remote Sensing, v. 10, n. 11, p. 1761, 2018. https://doi.org/10.3390/rs10111761.
PFEIFFER, M.; LANGAN, L.; LINSTÄDTER, A.; MARTENS, C.; GAILLARD, C.; RUPPERT, J. C.; SCHEITER, S. Grazing
and aridity reduce perennial grass abundance in semi-arid rangelands–Insights from a trait-based dynamic vegetation model. Ecological Modelling, v. 395, p. 11–22, 2019.
https://doi.org/10.1016/j.ecolmodel.2018.12.013.
R Core Team (2022). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
RIGHI, C. A.; OLIVEIRA RISANTE, A. P.; PACKER, A. P.; DO COUTO, H. T. Z. Biodiversity and biomass relationships in a cerrado stricto sensu in Southeastern Brazil. Environmental Monitoring and Assessment, v. 195, n. 4, p. 492, 2023. https://doi.org/10.1007/s10661-023-11051-w.
RIPLEY, B. et al. Package ‘mass’. Cran r, v. 538, p. 113–120, 2013.
ROSA, R; SANO, E. E; ROSENDO, J. S. Estoque de carbono em solos sob pastagens cultivadas na bacia hidrográfica do rio Paranaíba. Sociedade & Natureza, v. 26, n.2, p. 333-351, 2014. https://doi.org/10.1590/1982- 451320140210.
SÁ JÚNIOR, A.; CARVALHO, L. G.; SILVA, F. F.; CARVALHO ALVES, M. Application of the Köppen classification for climatic zoning in the state of Minas Gerais, Brazil. Theoretical and Applied Climatology, v. 108, n. 1, p. 1–7, 2012. https://doi.org/10.1007/s00704-011-0507-8.
SALIS, H. H. C.; EVANGELISTA, L. P.; DA COSTA, A. M.; HORTA, I. D. M. F. Diagnóstico da disponibilidade hídrica na bacia hidrográfica do rio Manso-MG. Caminhos de Geografia, Uberlândia, v. 18, n. 64, p. 91–102, 2017.
SAMPAIO, G.; NOBRE, C.; COSTA, M. H.; SATYAMURTY, P.; SOARES‐FILHO, B. S.; CARDOSO, M. Regional climate
change over eastern Amazonia caused by pasture and soybean cropland expansion. Geophysical Research Letters, v. 34, n. 17, 2007. https://doi.org/10.1029/2007gl030612.
SANTANA SANTOS, P.; GUIMARÃES FERREIRA, L. Análise descritiva dos aspectos biofísicos associados aos padrões de cobertura e uso da terra na bacia hidrográfica do Rio Vermelho, bioma Cerrado. GeoFocus Revista Internacional de Ciencia y Tecnología de la Información Geográfica, v. 20, p. 3–28, 2017. https://doi.org/10.21138/GF.395.
SANTOS, C. O. D.; MESQUITA, V. V.; PARENTE, L. L.; PINTO, A. D. S.; FERREIRA JR, L. G. Assessing the Wall-to-Wall
Spatial and Qualitative Dynamics of the Brazilian Pasturelands 2010–2018, Based on the Analysis of the Landsat Data Archive. Remote Sensing, v. 14, n. 4, p. 1024, 2022. https://doi.org/10.3390/rs14041024.
SIDRA. Sistema IBGE de recuperação automática. Produto Interno Bruto dos municípios, 2018. Disponível em: https://sidra.ibge.gov.br/pesquisa/munic/tabelas. Acesso em: 20 de jan. 2020.
SILVA, Márcio L. Mapeamento de superfícies aplainadas no norte de Minas Gerais. Revista Brasileira de Geografia Física, v. 9, n. 02, p. 526-545, 2016. https://doi.org/10.26848/rbgf.v9.2.p526-545.
SILVA, L. A. P.; BOLFE, E.; FERREIRA, M. E.; VELOSO, G. A.; LAURENTINO, C. M. M. Modelling the Pastureland
productivity in areas of Savanna in Northern Minas Gerais. Caminhos de Geografia, v. 23, n. 87, p. 124–134, 2022. https://doi.org/10.14393/RCG238759046.
SOUZA, C. M. P.; FRANCELINO, M. R.; COSTA, L. M. D.; FERNANDES, E. I. Pastures Degradation and the Relation with Pedo-Geomorphological Attributes in Watershed. Floresta e Ambiente, v. 26, n. 4, p. e20170616, 2019. https://doi.org/10.1590/2179-8087.061617.
SPERANDIO, H. V.; CECÍLIO, R. A.; CAMPANHARO, W. A.; DEL CARO, C. F.; HOLLANDA, M. P. Semina: Ciências
Agrárias, v. 33, n. 4, p. 1411-1418, 2012. https://doi.org/10.5433/1679-0359.2012v33n4p1411.
STANIMIROVA, R.; ARÉVALO, P.; KAUFMANN, R. K.; MAUS, V.; LESIV, M.; HAVLÍK, P.; FRIEDL, M. A. Sensitivity of
global pasturelands to climate variation. Earth’s Future, v. 7, n. 12, p. 1353–1366, 2019. https://doi.org/10.1029/2019EF001316.
VELOSO, G. A.; FERREIRA, M. E.; JÚNIOR, L. G. F.; SILVA, B. B. Modelling gross primary productivity in tropical savanna pasturelands for livestock intensification in Brazil. Remote Sensing Applications: Society and Environment, v. 17, p. 100288, 2020. https://doi.org/10.1016/j.rsase.2020.100288.
ZALLES, V.; HANSEN, M. C.; POTAPOV, P. V.; PARKER, D.; STEHMAN, S. V.; PICKENS, A. H.; KOMMAREDDY, I. Rapid expansion of human impact on natural land in South America since 1985. Science Advances, v. 7, n. 14, p. eabg1620, 2021. https://doi.org/10.1126/sciadv.abg1620.
DOI: http://dx.doi.org/10.5380/raega.v57i0.92339
