RESUMEN
Wastewater is treated by concerted actions of the microbial communities within bioreactors. Although protists (unicellular eukaryotes) are good bioindicators and important players influencing denitrification, nitrification, and flocculation, they are the least known organisms in WWTPs. The few recent environmental surveys of the protistan diversity in WWTPs show that the most abundant protistan sequences in WWTPs belong to Thecofilosea (Rhizaria). We re-investigated previously published environmental sequencing data and gathered strains from seven WWTPs to determine which species dominate WWTPs worldwide. We found that all highly abundant thecofilosean sequences represent a single species - Rhogostoma minus. Considering that Thecofilosea are frequent hosts for Legionellales, i.e. bacteria linked to waterborne diseases, we confirm that Rhogostoma minus functions as a host for Legionellales in WWTPs. Whether the highly abundant Rhogostoma minus also serves as a host for known human pathogenic Legionellales requires further attention.
Asunto(s)
Cercozoos , Rhizaria , Bacterias , Cercozoos/genética , Eucariontes , Humanos , Aguas ResidualesRESUMEN
During the transmission of acoustic signals, the spectral and temporal properties of the original signal are degraded, and with increasing distance more and more echo patterns are imposed. It is well known that these physical alterations provide useful cues to assess the distance of a sound source. Previous studies in birds have shown that birds employ the degree of degradation of a signal to estimate the distance of another singing male (referred to as ranging). Little is known about how acoustic masking by background noise interferes with ranging, and if the number of song elements and stimulus familiarity affect the ability to discriminate between degraded and undegraded signals. In this study we trained great tits (Parus major L.) to discriminate between signal variants in two background types, a silent condition and a condition consisting of a natural dawn chorus. We manipulated great tit song types to simulate patterns of reverberation and degradation equivalent to transmission distances of between 5 and 160â m. The birds' responses were significantly affected by the differences between the signal variants and by background type. In contrast, stimulus familiarity or their element number had no significant effect on signal discrimination. Although background type was a significant main effect with respect to the response latencies, the great tits' overall performance in the noisy dawn chorus was similar to the performance in silence.
Asunto(s)
Ruido , Passeriformes/fisiología , Localización de Sonidos , Vocalización Animal , Animales , Condicionamiento Operante , Señales (Psicología) , Discriminación en Psicología , Percepción de Distancia , Masculino , Enmascaramiento Perceptual , Espectrografía del SonidoRESUMEN
Our study estimates detection thresholds for tones of different durations and frequencies in Great Tits (Parus major) with operant procedures. We employ signals covering the duration and frequency range of communication signals of this species (40-1,010 ms; 2, 4, 6.3 kHz), and we measure threshold level-duration (TLD) function (relating threshold level to signal duration) in silence as well as under behaviorally relevant environmental noise conditions (urban noise, woodland noise). Detection thresholds decreased with increasing signal duration. Thresholds at any given duration were a function of signal frequency and were elevated in background noise, but the shape of Great Tit TLD functions was independent of signal frequency and background condition. To enable comparisons of our Great Tit data to those from other species, TLD functions were first fitted with a traditional leaky-integrator model. We then applied a probabilistic model to interpret the trade-off between signal amplitude and duration at threshold. Great Tit TLD functions exhibit features that are similar across species. The current results, however, cannot explain why Great Tits in noisy urban environments produce shorter song elements or faster songs than those in quieter woodland environments, as detection thresholds are lower for longer elements also under noisy conditions.