Qualidade do solo em áreas restauradas no estado de São Paulo

• Ano de defesa: 2015
• Autor(a) principal: Sanglade, Lucas Dias
• Orientador(a): Casagrande, José Carlos
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de São Carlos; Câmpus Araras
• Programa de Pós-Graduação: Programa de Pós-Graduação em Agricultura e Ambiente - PPGAA-Ar
• Palavras-chave em Português: Qualidade do solo; Modelo aditivo ponderado; Monitoramento de projetos de restauração florestal
• Palavras-chave em Inglês: Soil quality; Weighted additive model; Monitoring of forest restoration projects
• Área do conhecimento CNPq: CIENCIAS AGRARIAS
• Link de acesso: https://repositorio.ufscar.br/handle/20.500.14289/7388

Ecological restoration is an emerging field of restoration ecology, and is widely used as an important tool for biodiversity conservation. However, appropriate indicative allocations of soil quality for the assessment and monitoring of forest restoration projects are still scarce. The objective of this study was to evaluate soil quality of four restored forests of different ages, a forest remnant and their agricultural surroundings in the State of São Paulo through chemical, physical and microbiological soil parameters by categorization by the weighted additive model. To measure the discrimination of soils due to the different locations and types of land use, the weighted additive model, along with a soil quality index (SQI) and principal component analysis (PCA) were used. The PCA differentiated the forests of their agricultural environments and locations with a prevalence of physical and chemical parameters in the distinction between the matrices. The parameters soil organic matter, total cation exchange capacity, phosphorus, soil bulk density, porosity, microbial biomass carbon and microbial activity had higher averages in the forests matrices, being higher in older forests. There was differentiation in soil quality of the studied forests, where the highest rates were obtained in the remaining forest soils and older restored forests. All forest areas showed higher rates compared to their respective agricultural environments. Finally, the SQI used were efficient for the identification of the areas, having potential as a tool to support decision-making on environmental issues.