Características limnológicas e estrutura trófica das comunidades de peixes de alguns lagos naturais e artificiais do Rio Grande do Norte

Artificial lakes must differ from natural lakes in important structural and functional aspects that need to be understood so that these ecosystems can be properly managed. The aim of this work was to test the hypothesis that the artificial lakes (impoundments) in the semi-arid region of the Rio Grande do Norte State are more eutrophic and turbid and have different trophic structure when compared to the natural coastal lakes that occur in the humid eastern coast of the State. To test this hypothesis, 10 natural lakes and 8 artificial lakes with about 100 ha were sampled between September and November 2005 for the determination of some limnological variables and the abundance of the main fish species, which were grouped in three trophic guilds: facultative piscivores, facultative planktivores and omnivores. The results show that the artificial lakes had significantly higher concentrations of total nitrogen, total phosphorus, chlorophyll a , total and volatile suspended solids than the natural lakes. Results also show that the values of pH, total alkalinity, electric conductivity, turbidity as well as the coefficient of vertical attenuation of light were significantly higher in the artificial lakes than in the natural lakes. In the artificial lakes, the abundance of facultative planktivores was significantly higher, while the abundance of facultative piscivores significantly lower than in the natural lakes. There was no significant difference in the abundance of omnivorous fish between the two types of lakes. These results suggest that the increase in turbidity together with the other changes in the water quality of the artificial lakes, modifies the trophic structure of the fish communities reducing the importance of piscivores and the length of the food chains

Um sistema para a inferência de variáveis usando redes neurais artificiais

This work aims to obtain a low-cost virtual sensor to estimate the quality of LPG. For the acquisition of data from a distillation tower, software HYSYS ® was used to simulate chemical processes. These data will be used for training and validation of an Artificial Neural Network (ANN). This network will aim to estimate from available simulated variables such as temperature, pressure and discharge flow of a distillation tower, the mole fraction of pentane present in LPG. Thus, allowing a better control of product quality