No abstract

Phytoplankton and environmental variables were studied during a year in a shallow eutrophic lake and its inflow in the 'depressed Pampa' of Argentina. The taxa were classified according to the competitors, stress tolerators, ruderals and intermediate categories (CSR) model and were allocated to morphofunctional groups (MFG). As was expected according to the trophic state, scarce transparency and mixing condition, the R-strategists (several cyanobacteria and pennate diatoms) dominated almost all of the study period. C-strategists were more scarce and favoured by short periods of transparency, whereas only three species were attributed to the S-strategist category. Each MFG was represented by a single species at a time, resulting in a high functional miscellany in this shallow lake. Thus, we can assume that the CSR approach is a useful tool to explain the success of the different species of phytoplankton in this shallow lake.

No abstract

Kramers-Kronig (KK) equations allow us to obtain the real or imaginary part of linear, causal and time constant functions, starting from the imaginary or real part respectively. They are normally applied on different practical applications as a control method. A common problem in measurements is the lack of data in a wide-range frequency, due to some of the inherent limitations of experiments or practical limitations of the used technology. Different solutions to this problem were proved, such as several methods for extrapolation, some of which based on piecewise polynomial fit or the approach based on the expected asymptotical behavior. In this work, we propose an approach based on the symmetric extrapolation method to generate data in missing frequency ranges, to minimize the estimated error of the KK equations. The results show that with data from impedance measurements of an electrode-electrolyte interface, the adjustment error of the transformed functions can be drastically reduced to below 1%.