Comparing how land use change impacts soil microbial catabolic respiration in Southwestern Amazon

• Autor(a) principal: Mazzetto,Andre Mancebo
• Data de Publicação: 2016
• Outros Autores: Feigl,Brigitte Josefine, Cerri,Carlos Eduardo Pellegrino, Cerri,Carlos Clemente
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Brazilian Journal of Microbiology
• Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1517-83822016000100063
• topic: Amazon region; Land use change; Catabolic profile; Microbial communities

Abstract Land use changes strongly impact soil functions, particularly microbial biomass diversity and activity. We hypothesized that the catabolic respiration response of the microbial biomass would differ depending on land use and that these differences would be consistent at the landscape scale. In the present study, we analyzed the catabolic response profile of the soil microbial biomass through substrate-induced respiration in different land uses over a wide geographical range in Mato Grosso and Rondônia state (Southwest Amazon region). We analyzed the differences among native areas, pastures and crop areas and within each land use and examined only native areas (Forest, Dense Cerrado and Cerrado), pastures (Nominal, Degraded and Improved) and crop areas (Perennial, No-Tillage, Conventional Tillage). The metabolic profile of the microbial biomass was accessed using substrate-induced respiration. Pasture soils showed significant responses to amino acids and carboxylic acids, whereas native areas showed higher responses to malonic acid, malic acid and succinic acid. Within each land use category, the catabolic responses showed similar patterns in both large general comparisons (native area, pasture and crop areas) and more specific comparisons (biomes, pastures and crop types). The results showed that the catabolic responses of the microbial biomass are highly correlated with land use, independent of soil type or climate. The substrate induced respiration approach is useful to discriminate microbial communities, even on a large scale.