Habitat degradation homogenizes ecological responses to typhoons across a subtropical island

Abstract

Climate change is increasing the frequency, intensity, and duration of extreme weather events across the globe. Understanding the capacity for ecological communities to withstand and recover from such events is critical. Typhoons are extreme weather events that are expected to broadly homogenise ecosystems through structural damage to vegetation and longer-term effects of salinization. Given their unpredictable nature, monitoring ecological responses to typhoons is challenging, particularly for mobile animals such as birds. Here, we report spatially variable ecological responses to typhoons across terrestrial landscapes. Using a high temporal resolution passive acoustic monitoring network across 24 sites on the subtropical island of Okinawa, Japan, we found that typhoons elicit divergent ecological responses among Okinawa’s pristine forests, as indicated by increased spatial variability of biological sound production (biophony) among forested sites. However, no such post-typhoon shift in variability was observed among developed urban or agricultural sites. This indicates that natural forests have a diversity of pathways through which communities can respond to typhoons, whereas land use development produces communities more constrained in their disturbance responses. That is, spatial insurance effects among forest communities may provide resilience to typhoons at the landscape scale, but this spatial insurance was diminished by habitat degradation through land use development. Though site-level typhoon impacts on soundscapes and bird detections were not particularly strong, we nevertheless revealed spatial heterogeneity in typhoon responses, owing to the data resolution afforded to us by monitoring at scale (high temporal resolution, broad spatial extent). Our findings underscore the importance of natural forests in insuring ecosystems against disturbance, and demonstrate the potential of landscape-scale acoustic sensor networks for documenting the understudied ecological impacts of unpredictable extreme weather events.