An acoustic detection dataset of birds (Aves) in montane forests using a deep learning approach.

ABSTRACT:

Background

Long-term monitoring is needed to understand the statuses and trends of wildlife communities in montane forests, such as those in Yushan National Park (YSNP), Taiwan. Integrating passive acoustic monitoring (PAM) with an automated sound identifier, a long-term biodiversity monitoring project containing six PAM stations, was launched in YSNP in January 2020 and is currently ongoing. SILIC, an automated wildlife sound identification model, was used to extract sounds and species information from the recordings collected. Animal vocal activity can reflect their breeding status, behaviour, population, movement and distribution, which may be affected by factors, such as habitat loss, climate change and human activity. This massive amount of wildlife vocalisation dataset can pr

SUBMITTER: Wu SH 

PROVIDER: S-EPMC10848598 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature