Programa de Pós-graduação em Ciências Ambientais
URI Permanente desta comunidade
Navegar
Navegando Programa de Pós-graduação em Ciências Ambientais por Por Orientador "Ferreira, Laerte Guimarães"
Agora exibindo 1 - 2 de 2
Resultados por página
Opções de Ordenação
Item Práticas de manejo pecuário na microrregião de São Miguel do Araguaia, Goiás: uma análise a partir de dados de campo e de sensoriamento remoto(Universidade Federal de Goiás, 2017-02-03) Aguado, Oscar Ivan De Oro; Araújo, Fernando Moreira de; http://lattes.cnpq.br/8681719274269970; Ferreira, Laerte Guimarães; http://lattes.cnpq.br/8647270006257055; Miziara, Fausto; Couto, Victor Rezende MoreiraPasture degradation is a process in the tropical region and in Brazil, it is estimated that there are approximately 100 million hectares under poor conservation and management conditions. This work aims to understand, in an exploratory way, the quality of the Brachiaria Brizantha and Andropogon Gayanus species, evaluating the seasonal and trend characteristics in relation to the conditioning factors of the degradation in the microregion of São Miguel do Araguaia. The methodology consisted in the selection of pastures in three levels of degradation for the species mentioned above; historical management for the last 15 years; and estimated vegetative vigor analysis using satellite images from the MODIS sensor, i.e. product MOD13Q1 - NDVI, for the period 2000 to 2015. The time series was analyzed using seasonal metrics and the algorithms Breaks For Additive Season and Trend (BFAST) for trend analysis and identification of the degradation factors for the three levels of degradation of both species. The results demonstrated the differentiation between the three categories of pasture management (optimal, reasonable and poor) for the two grass species using data collected in the field and orbital. According to the seasonal metrics, statistically, the species presented differentiated vegetative vigor behaviors (t = 2,083, gl = 375, p <0.001), and the discrimination is higher using the amplitude and maximum metrics of the NDVI index. The optimal pastures (t = 2.876, gl = 375, p <0.001) and poor (t = 4,142, gl = 375, p <0.001) differed according to seasonal behavior, while reasonable pastures did not (t = 0.745; = 375, p> 0.05). The optimal and reasonable pastures of B. Brizantha presented similar behaviors over the analysis period, whereas the poor pasture presented differentiated behaviors for the amplitude and average metrics. However, the optimal, reasonable and poor pastures of the A. Gayanus species, despite having differentiated qualities and management in the field, the NDVI values throughout the temporal series presented similar behaviors for both qualities. The Trends analysis showed that the high temperatures of 2007 and 2010 generated negative breaks points for both species, while the years of 2009 and 2013 were points of positive breaks due to the increase in rainfall records. As a conclusion, moderate resolution orbital data, particularly NDVI, allow the differentiation of pasture species and their respective qualities through the analysis of time series and, on the other hand, trend analysis showed that both species of grass showed high Sensitivity to the climatic factors, as El Niño and La Niña, in relation to the management used.Item Caracterização ecossistêmica e funcional das pastagens brasileiras(Universidade Federal de Goiás, 2021-07-08) Santos, Claudinei Oliveira dos; Pinto, Alexandre de Siqueira; http://lattes.cnpq.br/6624723278135170; Ferreira, Laerte Guimarães; http://lattes.cnpq.br/8647270006257055; Ferreira, Laerte Guimarães; Costa Junior, Ciniro; Assad, Eduardo Delgado; Ramos Neto, Mario Barroso; Bustamante, Mercedes Maria da CunhaLivestock activity occupies ~67% of the global area used for agricultural activity, being directly related to important issues for humanity such as food security and the need to mitigate greenhouse gas emissions - GHG. In Brazil, the sixth largest emitter of GHG, land use and land cover activity is the main source of emissions. Considering that most of the pastures in Brazil present some level of degradation, in these areas there is a great opportunity to mitigate GHG emissions. In this study, three important aspects of this land use class are analyzed: The influence of climatic seasonality on biomass and on the spectral response of pasture areas at different spatial scales; The potential of the Normalized Difference Vegetation Index (NDVI), obtained by remote sensing for the mapping of pasture quality, and analysis of spatial patterns in national scale; And estimates of carbon stock in soil and aboveground biomass of pastures in the Cerrado biome, using models based on ecosystem processes. We observed that annual mean and variation of biomass stocks varied with spatial scale, and there were no significant differences in these stocks during the dry and rainy seasons due to grazing management strategies. The NDVI had low potential to predict the biomass stock of pastures in the evaluated areas, on the other hand, the potential as an pasture vigor indicator was high, showing a significant linear relation with the living/dead biomass ratio, especially in non-degraded pastures. The temporal pattern of the NDVI varied depending on the quality of the pasture and the spatial scale analyzed, indicating that it is not possible to establish single thresholds to map the condition of pastures in large areas like the Brazilian territory. From the mapping of pasture quality, it was possible to analyze their spatiotemporal dynamics. In this analysis, we identified an improvement in the brazilian pasture quality, with the area of gain quality being 2.7 times larger than the area of lost quality. The results correspond to the patterns observed in the literature and to the incentives for the recovery of pastures through programs such as the ABC Plan. The modeling of the dynamics and estimates of carbon stocks in the pasture areas of the Cerrado biome using the Century model, with the parameters adjusted to simulate the conventional pasture management in the biome, confirmed the versatility and robustness of the model, being effective in estimate carbon stocks in this areas, adequately reproducing the characteristic spatial patterns of seasonal influence in the Cerrado biome. In this sense, we believe that the results achieved through this study can contribute to a better characterization and understanding of pastures in Brazil.