Estimativa de estoques de carbono da biomassa para áreas de Caatinga de Pernambuco

• Ano de defesa: 2021
• Autor(a) principal: Santos, Maiara Pedral dos
• Orientador(a): Pinto, Alexandre de Siqueira
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Programa de Pós-Graduação: Pós-Graduação em Ecologia e Conservação
• Palavras-chave em Português: Biomassa; Carbono; Caatinga; Sistemas de informação geográfica; Florestas Pernambuco
• Palavras-chave em Inglês: Dry forest; Century model; Semiarid
• Área do conhecimento CNPq: CIENCIAS BIOLOGICAS::ECOLOGIA
• Link de acesso: https://ri.ufs.br/jspui/handle/riufs/14828

The Caatinga is part of the Seasonally Dry Tropical Forests (SDTF) domain, which is of great importance due to the provision of essential ecosystem services and their socioeconomic role related to the subsistence of the northeast brazilian countryman. Estimates of carbon stocks in the Caatinga biomass can contribute to decision-making about remaining areas management and maintaining this ecosystem service. In this sense, an alternative is the use of environmental models associated with Geographic Information Systems (GIS). In recent years, Century model has been adjusted to make it an accurate tool for a better understanding of the functioning of the Caatinga. Given this context, the present work was divided into two chapters. The first chapter aimed to evaluate the performance of the Century model previously calibrated and validated for the Caatinga when simulating biomass carbon stocks on a regional scale. The input data referring to climatic conditions were obtained through the TerraClimate database. The soil texture information and reference of biomass C stocks come from samples in three mesoregions (Agreste, Sertão Leste, and Sertão Oeste) of Pernambuco. When analyzing mesoregion, the model showed better performance in simulating C stocks in the Sertão Oeste region. There was a correspondence between the C stocks in the total biomass modeled with those obtained in the field with environmental parameters such as precipitation, temperature, and soil classes. The second chapter aimed to spatialize the aboveground biomass carbon stocks for areas of Caatinga. Pixel-by-pixel C stock estimates in biomass were performed using local climate parameters, obtained from the TerraClimate database, and soil parameters from the SoilsGrids database for three municipalities (one in each mesoregion). The map of C stocks in biomass from the Institute of Forest and Agricultural Management and Certification (IMAFLORA) was used as a reference to assess the accuracy of the estimates obtained with the Century model. The model presented a satisfactory performance, as the differences of the modeled stocks with the reference were acceptable (less than ± 25%) in approximately 60% of the evaluated area. Therefore, the integration between ecosystem modeling and the geographic information system is a promising tool for evaluating C stocks in the Caatinga.