Influência da precipitação pluviométrica no conteúdo de nutrientes na serapilheira em sistemas florestais e agroflorestais no nordeste paraense

Abstract

This work had as main objectives: to assess the dynamics of nutrient contents in different forest ecosystems and agroforestry in the district of Bragança, Benjamin Constant in the community, in northeastern Pará. Litter were collected in two periods: dry season (November) and rainy (March), in 2009. For the collection of litter samples was used collectors measuring (0.25 x 0.25 m2) were placed directly on the soil surface. The collected material was stored in paper bags and taken to the Chemical Analysis Laboratory of the Brazilian Agricultural Research Corporation (EMBRAPA), where it was determined the analysis of macronutrients (N, P, K, Ca, Mg, Na) and micronutrients (Fe, Co, Mn, Zn). The highest concentrations of nutrients were found in the N to agroforestry systems with slash and burn, in the periods (wet and dry), and the forest at 40 and 10years in the treatments without desbate (SD), with partial desbate (SD) desbate and total (DP). All the nutrients showed the influence of seasonality, which was verified by the wide variation in nutritional behavior. The decreasing concentration of nutrients presented was N> Ca> Mg> Na> K> P (SAFCQ), all with maximum values of nutrients during the rainy season, and N, P, K, Ca, Na in highest concentrations in the ( SAFSQ), and only Mg showed maximum value in (SAFCQ). The statistical differences were shown (Tukey, p <0.05) mainly between (SAFCQ) for the elements phosphorus, potassium, magnesium and sodium, because they showed differences in the same treatment during different periods Among the micronutrients studied, higher concentrations agroforestry systems with slash and burn, and the forest at 40 and 10 years (SD) (DP) (DT) was the element iron. The decreasing concentration of nutrients was presented Fe> Mn> Zn> Cu. Seasonality significantly influenced nutrient concentrations of litter in most elements. Statistically significant variation between treatments and time periods systems.