Listening to biodiversity under extreme weather

Climate change is one of the major threats to biodiversity. Besides increasing air temperatures, the magnitude and frequency of extreme weather events have been increasing, and are predicted to increase further in the future. To understand impacts of extreme weather on biodiversity, long-term and frequent data collections on the environment and biodiversity responses are needed. In this study, we used the environmental ultrasounds collected at eight sites across Taiwan to evaluate the usefulness of passive acoustic monitoring for accessing ecological impacts of heavy rains, which are one of the deadliest weather events. We separated acoustic signals of bats, insects and rains using a machine-learning tool we developed. We then investigated temporal changes in the intensity and frequency compositions of bat signals over a heavy rain event. We found significant impacts of the event on the acoustic signals produced by bats. Bat signals took a longer time to recover from the event at the places experiencing heavier and more temporally concentrated rains than at the places with lighter and more spread out rains. This study shows the potential of passive acoustic monitoring for improving our understanding of the responses of biodiversity to extreme weather events under climate change.Climate change is one of the major threats to biodiversity. Besides increasing air temperatures, the magnitude and frequency of extreme weather events have been increasing, and are predicted to increase further in the future. To understand impacts of extreme weather on biodiversity, long-term and frequent data collections on the environment and biodiversity responses are needed. In this study, we used the environmental ultrasounds collected at eight sites across Taiwan to evaluate the usefulness of passive acoustic monitoring for accessing ecological impacts of heavy rains, which are one of the deadliest weather events. We separated acoustic signals of bats, insects and rains using a machine-learning tool we developed. We then investigated temporal changes in the intensity and frequency compositions of bat signals over a heavy rain event. We found significant impacts of the event on the acoustic signals produced by bats. Bat signals took a longer time to recover from the event at the places experiencing h...