Dear MARMAM community, On behalf of my co-authors I am pleased to announce the following publication in JASA: Amorim, T.O.S., Castro, F.R., Ferreira, G.A., Neri, F.M., Duque, B.R., Mura, J.P., Andriolo, A. (2022). "Acoustic identification and classification of four dolphin species in the Brazilian marine area affected by the largest tailings dam failure disaster", The Journal of the Acoustical Society of America (Vol.152, Issue 6). You can find the article here: https://doi.org/10.1121/10.0016358 Abstract Passive acoustic monitoring (PAM) is an increasingly used technique to access the occurrence, distribution, and abundance of cetaceans that may be visually unavailable most of the time. The largest tailings dam failure disaster occurred on 5 November 2015, when the Fundão dam collapsed, releasing over 50 million cubic meters of tailings into the Doce River basin; 14 days later, the tailings plume reached the Atlantic Ocean. PAM was implemented in the concerned area and cetacean species were acoustically identified. Whistles and clicks of visual and acoustic matches were used to predict and classify exclusive acoustic records through random forest models. The identified species were Guiana, rough-toothed, and bottlenose dolphins. Additionally, the franciscana, the most threatened cetacean in the western South Atlantic Ocean, was also acoustically identified. The whistle classifier had 86.9% accuracy with final frequency, duration, and maximum frequency ranked as the most important parameters. The clicks classifier had 86.7% accuracy with peak frequency and 3 dB bandwidth as the most important parameters for classifying species. Considering the potential effect of the increase in turbidity on sound transmission, such as attenuation, the presented classifier should be continuously improved with novel data collected from long-term acoustic monitoring. Please feel free to email me at amorim@aqualie.org for a pdf copy. Kind regards, Thiago Amorim ***** Programa de Pós Graduação em Biodiversidade e Conservação da Natureza - Universidade Federal de Juiz de Fora. Laboratório de Bioacústica e Ecologia Comportamental - LABEC Instituto Aqualie http://www.aqualie.org.br