Fauna edáfica e sua relação com variáveis ambientais em sistemas de manejo do solo

• Autor(a) principal: Baretta, Dilmar
• Data de Publicação: 2014
• Outros Autores: Bartz, Marie Luise Carolina, Fachini, Ivandro, Anselmi, Rafael, Zortéa, Talyta, Baretta, Carolina Riviera Duarte Maluche
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Repositório Institucional da Universidade Federal do Ceará (UFC)
• dARK ID: ark:/83112/001300001mk49
• Texto Completo: http://www.repositorio.ufc.br/handle/riufc/14985
• topic: Sustentabilidade; Indicadores de qualidade do solo; Plantio direto; Plantio convencional

The present study aims to generate knowledge about the soil fauna, its relation to other explanatory environmental variables, and, besides it, to select edaphic indicators that more contribute to separate the land use systems (LUS). Five different LUS were chosen: conventional tillage with crop rotation (CTCR); no-tillage with crop rotation (NTCR); conventional tillage with crop succession (CTCS); no-tillage with crop succession (NTCS) and minimum tillage with crop succession (MTCS). The samples were made in the counties Chapecó, Xanxerê and Ouro Verde located in the state of Santa Catarina, Brazil, and were considered the true replicates of the LUS. In each site, nine points were sampled in a sampling grid of 3 x 3. At the same points, soil was sampled for the physical, chemical and biological attributes (environmental variables). Pitfall traps were used to evaluate the soil fauna. Data were analyzed using principal component analysis (PCA) and canonical discriminant analysis (CDA). The soil fauna presented potential to be used as indictors of soil quality, since some groups proved to be sensible to changes of the environmental variables and to soil management and tillage. The soil management using crop rotation (NTCR and CTCR) presented higher diversity, compared to the systems using crop succession (NTCS, MTCS and NTCS), evidencing the importance of the soil tillage, independent of the season (summer or winter). The variable that better contributed to explain these changes were the chemical variables (potassium, pH, calcium, organic matter, available phosphorus, potential acidity), and biological variables (Shannon diversity index, Collembola, Pielou equitability index and microbial biomass carbon), respectively