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Abstract The Llanquihue lake is included in the called Araucanian or Nord Patagonian lakes located between 38-41° S. These lakes are characterized by their oligo-mesotrophic status due to human intervention which takes to the increase in nutrients inputs from industries and towns. Effects on zooplankton assemblages are observed with marked increase of daphnids abundance. The aim of the present study is to analyze the trophic status and zooplankton relative abundance in different bays of Llanquihue lake. It was found direct associations between chlorophyll a with daphnids percentage, total dissolved nitrogen with reactive soluble phosphorus nitrogen/phosphorus molar radio with cyclopoids percentage, and an inverse relation between daphnids and calanoids percentages. The occurrence of three kinds of microcrustacean assemblages and environmental conditions was evidenced: the first one with high calanoids percentage, low species number and low chlorophyll and nutrients concentration, a second with moderate chlorophyll and nutrients concentration and moderate daphnids percentage; high species number and a third site with high chlorophyll and nutrients concentration, high daphnids percentage and high species number. Daphnids increase under mesotrophic status, agree with similar results observed for southern Argentinean and New Zealand lakes.

Electric power losses have a significant impact on the total costs of distribution networks. The use of renewable energy sources is a major alternative to improve power losses and costs, although other important issues are also enhanced such as voltage magnitudes and network congestion. However, determining the best location and size of renewable energy generators can be sometimes a challenging task due to a large number of possible combinations in the search space. Furthermore, the multiobjective functions increase the complexity of the problem and metaheuristics are preferred to find solutions in a relatively short time. This paper evaluates the performance of the cuckoo search (CS), harmony search (HS), and bat-inspired (BA) algorithms for the location and size of renewable distributed generation (RDG) in radial distribution networks using a multiobjective function defined as minimizing the energy losses and the RDG costs. The metaheuristic algorithms were programmed in Matlab and tested using the 33-node radial distribution network. The three algorithms obtained similar results for the two objectives evaluated, finding points close to the best solutions in the Pareto front. Comparisons showed that the CS obtained the minimum results for most points evaluated, but the BA and the HS were close to the best solution.