Caracterização ecossistêmica e funcional das pastagens brasileiras

• Autor(a) principal: Santos, Claudinei Oliveira dos
• Data de Publicação: 2021
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: Repositório Institucional da UFG
• Texto Completo: http://repositorio.bc.ufg.br/tede/handle/tede/12653
• topic: Pastagens; Pastagens degradadas; Carbono; Sensoriamento remoto; Índice de vegetação; Pastures; Degraded pastures; Carbon; Remote sensing; Vegetation index; CIENCIAS BIOLOGICAS::ECOLOGIA::ECOLOGIA DE ECOSSISTEMAS

Livestock 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.