RESUMO
Maintenance work on the harbor of Setúbal, in Portugal, required the removal of a 14-m deep rocky outcrop at the ship maneuver area, using about 35 kg of Gelamonite, a nitroglycerin-based high-explosive. This important harbor is located in the Sado estuary, a biologically rich environment and an important feeding area for a resident community of bottlenose dolphins. Using different safe range calculation models, a mitigation and monitoring plan was developed that minimized the risks of these underwater explosions for the dolphins. At our monitoring station, at 2 km from the demolition site, acoustic pressure levels in excess of 170 dB re 1 µPa (root-mean-square) were measured. Samples of dead fish collected at the site were indicative of shock trauma from the blasts.
Assuntos
Comportamento Animal , Golfinho Nariz-de-Garrafa/fisiologia , Ecossistema , Monitoramento Ambiental , Explosões , Ruído/efeitos adversos , Animais , Monitoramento Ambiental/métodos , Portugal , Pressão , Medição de Risco , Água do Mar , Fatores de TempoRESUMO
Common bottlenose dolphins (Tursiops truncatus), produce a wide variety of vocal emissions for communication and echolocation, of which the pulsed repertoire has been the most difficult to categorize. Packets of high repetition, broadband pulses are still largely reported under a general designation of burst-pulses, and traditional attempts to classify these emissions rely mainly in their aural characteristics and in graphical aspects of spectrograms. Here, we present a quantitative analysis of pulsed signals emitted by wild bottlenose dolphins, in the Sado estuary, Portugal (2011-2014), and test the reliability of a traditional classification approach. Acoustic parameters (minimum frequency, maximum frequency, peak frequency, duration, repetition rate and inter-click-interval) were extracted from 930 pulsed signals, previously categorized using a traditional approach. Discriminant function analysis revealed a high reliability of the traditional classification approach (93.5% of pulsed signals were consistently assigned to their aurally based categories). According to the discriminant function analysis (Wilk's Λ = 0.11, F3, 2.41 = 282.75, P < 0.001), repetition rate is the feature that best enables the discrimination of different pulsed signals (structure coefficient = 0.98). Classification using hierarchical cluster analysis led to a similar categorization pattern: two main signal types with distinct magnitudes of repetition rate were clustered into five groups. The pulsed signals, here described, present significant differences in their time-frequency features, especially repetition rate (P < 0.001), inter-click-interval (P < 0.001) and duration (P < 0.001). We document the occurrence of a distinct signal type-short burst-pulses, and highlight the existence of a diverse repertoire of pulsed vocalizations emitted in graded sequences. The use of quantitative analysis of pulsed signals is essential to improve classifications and to better assess the contexts of emission, geographic variation and the functional significance of pulsed signals.