Datasets for assessing the structure and drivers of biological sounds.

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.

Methods to measure biological sounds and assess their drivers in a tropical forest.

The study of soundscapes and biological sounds is becoming the focus of increasing scientific attention. Studying biological sounds involves the deployment of acoustic sensors to record sounds and the identification of animal species and other sources of sound in audio recordings. In addition, data extracted from audio recordings may be pooled together with ecological and human activity data to investigate the drivers of biological sounds. We provide a detailed method description of our study on biological sounds in a tropical forest and their drivers along a gradient of disturbance in Southeast Cameroon. We designed and implemented a research protocol to:•make large scale audio recordings and identify animal species detected;•collect ground-truth data on mammal and bird species;•collect climate, habitat, and human activity data and describe remoteness and accessibility.