Produção de serapilheira e devolução de macronutrientes em um povoamento de Eucalyptus saligna (F. Muell)

Litterfall is the mainly route of plant nutrients transfer to the soil in forest ecosystems. Therefore the study of the litterfall is very important fundamental to understanding the functioning of these ecosystems. Given this importance, this study aimed to estimate litter production in Eucalyptus saligna stand, São Gabriel – RS. Were installed 4 plots of 23 m x 26 m in each of these plots, 4 litter collectors. For branches with a diameter bigger than 0.5 cm, in each plot were demarcated aboveground three plots of 3 m x 2 m, bounded by an average diameter tree. Samples were collected fortnightly, sorted into thick branches, twigs (diameter of less than 0.5), leaves and miscellaneous, then were oven dried, weighty, and sent to the chemical analysis where it was determinate the content of macronutrients. During the twelve month period, litter production was 9,93 Mg ha-1, 54.0% of leaves, 24.7% thick branches, 11.2% of miscellaneous and 10.1% of twigs. The overall contribution of macronutrients was 71,56 kg ha-1mof Ca, 45,15 kg ha-1 of N, 38,93 kg ha-1 of K, 17,54 kg ha-1 of Mg, 6,19 kg ha-1 of S and 2,81 kg ha-1 of P.A serapilheira é a principal via de transferência de nutrientes das plantas para o solo em ecossistemas florestais, assim o estudo da produção de serapilheira é fundamental para compreender o funcionamento destes ecossistemas. O presente estudo objetivou avaliar a produção de serapilheira e a devolução de macronutrientes em um povoamento de Eucalyptus saligna (F. Muell) em função das variáveis climáticas, no município de São Gabriel – Rio Grande do Sul. Foram instaladas 4 parcelas de 23 m x 26 m e em cada uma destas parcelas foram distribuídos 4 coletores com 0,5 m2 de área. Para a quantificação de galhos grossos (diâmetro > 0,5 cm), em cada parcela foram demarcadas três subparcelas de 3 m x 2 m, sobre o solo, delimitadas por uma árvore de diâmetro médio. As amostras foram coletadas quinzenalmente, separadas em galhos grossos, galhos finos, folhas e miscelânea, após foram secas em estufa, pesadas, moídas e encaminhadas para análise química, onde foram determinados os teores dos macronutrientes. A produção anual de serapilheira foi de 9,93 Mg ha-1, sendo 54,0% folhas, 24,7% galhos grossos, 11,2% miscelânea e 10,1% galhos finos. O aporte total de macronutrientes foi de 71,56 kg ha-1 para o Ca, 45,15 kg ha-1 de N, 38,93 kg ha-1 de K, 17,54 kg ha-1 de Mg, 6,19 kg ha-1 de S e 2,81 kg ha-1 de P

INFLUENTIAL FACTORS IN SURFACE WATER QUALITY IN CATCHMENTS WITHIN THE PAMPA BIOME WITH DIFFERENT LAND USE1

The aim of this study was to identify, by multivariate statistical technique, the physic, chemical and biological variables that best characterize the quality of surface waters in two small rural catchments with different land uses (eucalyptus silviculture (SC) vs. pasture and extensive livestock (LC)) located in Rosário do Sul, RS - Brazil. Monitoring was conducted during the months of August 2011 to August 2012 and the following parameters were analyzed: Ca2+, Mg2+, K+, SO42-, Cl-, pH, electrical conductivity, turbidity, alkalinity, suspended and dissolved solids, biochemical oxygen demand , total coliforms, Escherichia coli and temperature, flow and rainfall. Through the use of FA/PCA, it was found that the model best fit to express water quality of in LC that was composed of five factors which account for 83.5% of the total variance, while for SC, four factors accounted for 85.12% of the variance. In LC, the five main factors were, respectively, soluble salts, diffuse pollution, solid, and both anthropogenic and organic factors. In SC, the four factors were namely: soluble salts, mineral, nutritional and diffuse pollution factors. The results of this study showed that by replacing the traditional soil usage (pasture and livestock) with planted forest, diffuse pollution was attenuated but, however, it did not result in major changes in the physical-chemical and biological characteristics of the water. Another point to note is that factorial analysis did not result in a large reduction in the number of variables, once the best model fit occurred with the addition of 15 of 18 analyzed variables (LC) and 17 of 18 analyzed variables (SC)