Obtaining and analysing sound data can be a tedious and lengthy process. We present sound data consisting of 20,485 1 min sound recordings obtained in three sites within a rainforest landscape in southeast Cameroon. The sites differ in anthropogenic disturbance. We also present meta data corresponding to these recordings with the identification of all animal vocalisations in each 1 min sound recording. Additionally, we provide a raw database with data on habitat, human activities, remoteness, accessibility, temperature, humidity, rainfall, moon phase, and mammal and bird observations in the area during the recording period. The data were used by Diepstraten & Willie (2021) to investigate the structure and drivers of biological sounds along a disturbance gradient. The data contribute to call libraries of tropical species and can also be used to build classifiers for automatic detection and classification of animal vocalisations.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8866143 | PMC |
http://dx.doi.org/10.1016/j.dib.2022.107930 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!