Towards automated long-term acoustic monitoring of endangered river dolphins: a case study in the Brazilian Amazon floodplains.

ABSTRACT: Using passive acoustic monitoring (PAM) and convolutional neural networks (CNN), we monitored the movements of the two endangered Amazon River dolphin species, the boto (Inia geoffrensis) and the tucuxi (Sotalia fluviatilis) from main rivers to floodplain habitats (várzea) in the Mamirauá Reserve (Amazonas, Brazil). We detected dolphin presence in four main areas based on the classification of their echolocation clicks. Using the same method, we automatically detected boat passages to estimate a possible interaction between boat and dolphin presence. Performance of the CNN classifier was high with an average precision of 0.95 and 0.92 for echolocation clicks and boats, respectively. Peaks of acoustic activity were detected synchronously at the river entrance and channel, corresponding to d

SUBMITTER: Erbs F 

PROVIDER: S-EPMC10374533 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature