Assessing the structure and drivers of biological sounds along a disturbance gradient

Abstract

Studying soundscapes to improve knowledge about an environment with limited visibility is gaining popularity. However, the structure and drivers of biological sounds remain poorly understood although this information can improve understanding of landscape dynamics. To describe biological sounds and provide a better understanding of their drivers, we conducted a study aiming at detecting and identifying individual vocalising animal species, determining the abundance, diversity, and composition of vocalisations, and assessing how ecological and anthropogenic factors affect these sounds. Sounds were recorded from February through May 2020 in southeast Cameroon, using passive acoustic monitoring, in three study sites representing a gradient of disturbance. Local experts listened to 20,485 1-min files of recorded sounds to identify vocalising species. These identifications, in combination with anthropogenic and ecological data from the field, were used to assess abundance, diversity, and composition of vocalisations. Fifteen vocalising mammal species and 37 vocalising bird species were identified. Overall, insects and, to a lesser extent, birds were the most dominant animal classes in the soundscape. Furthermore, vocalisation abundance and the diversity of vocalising mammals did not vary along the disturbance gradient, whereas vocalisation abundance of birds was lowest in the site where anthropogenic disturbance was least present. Moreover, both mammal and bird vocal activity were negatively impacted by rainfall. Human activity and the amount of swamp habitat reduced the vocal activity of mammals, but these factors did not affect bird vocalisations. For birds, on the other hand, the diversity of vocalisations was positively affected by bird abundance and negatively affected by higher temperatures. Our results indicate that animal classes do not have the same number of acoustically active species and produce differing amounts of sound, thus highlighting that sources of sound differ in their relative contributions to the soundscape and furthering knowledge of soundscape structure. They also show that the effects of anthropogenic and ecological factors on biological sounds vary depending on the sound source, which suggests that soundscape components are affected by soundscape drivers differently. Additionally, our study provides baseline acoustic information on vocalising species in African tropical rainforests. This acoustic information may be used for automated detections of vocalisations in the future. Together, an understanding of soundscape drivers and information on vocalising species can contribute to the development of applications that will monitor soundscapes and detect important changes in landscapes. This will help guide future decision making and landscape conservation planning.