The relationship between acoustic indices, vegetation, and topographic characteristics is spatially dependent in a tropical forest in southwestern China

Abstract

The soundscape of different habitats can be discriminated by multiple acoustic indices as they have previously been related to vegetation characteristics. However, the relationship between acoustic indices and topography still needs to be thoroughly evaluated, as well as the variance in the relationship at different spatial scales within the same research system. Networks of forest dynamics plots constructed under the same protocol provide an ideal research platform for addressing the above issue. Our study investigated the relationship between acoustic indices, vegetation, and topographic characteristics at two spatial scales. We recorded soundscapes using autonomous recorders across a tropical forest dynamics plot network consisting of 22 plots in Xishuangbanna, Yunnan Province, southwest China. To exclude recordings with geophony and with biotic sounds from non-avian species, especially from cicadas and frogs, the recordings were previewed aurally and visually, with 9110 min of “clear” bird acoustic recordings chosen for final analysis. We assessed the relative importance of tree species richness, six vegetation characteristics, and three topographic characteristics for five acoustic signal complexity indices, and three statistical indices which describe the properties of frequency spectrum, at 25 m and 50 m spatial scales. We found that topographic complexity was the most significant factor influencing acoustic indices. The variation explained by topographic complexity ranged from 13.2 % to 47.2 % for the seven best-fitted models at both spatial scales. Horizontal vegetation characteristics, including tree density and basal area, were also important variables related to acoustic indices. The Acoustic Diversity Index (ADI) and Bioacoustic Index (BIO) were not associated with vegetation or topographic characteristics at either spatial scale. Three out of seven significant relationships between acoustic indices and vegetation or topographic characteristics disappeared as the spatial scale increased from 25 m to 50 m. In contrast, the significant relationship between Acoustic entropy (H), the centroid (CENT) and skewness (SKEW) and topographic complexity remained stable. Our results suggest that both acoustic signal complexity indices and acoustic statistical indices showed a different relationship to vegetation and topographic characteristics in tropical forests, and the strength of these relationship was scale-dependent. This study revealed that topographic complexity might be an effective predictive variable for further ecoacoustic research.