LAUSR

ABSTRACT Birds are dominant creatures that produce abundant sounds in urban forest ecosystems, and birdsongs are a desired soundscape to reduce noise pollution in biophilic cities. The aim of this study was to explore the impact of soundscape drivers on perceived birdsongs and to model the associated drivers. Questionnaires and acoustic measurements of biophony and birdsongs were conducted at 41 observation sites in three urban forest locations in Vancouver, Canada. Pearson’s correlations were then used to analyze relationships between the soundscape drivers. Potential soundscape drivers were modeled using template matching (TM) and back propagation neural network (BP neural network). Findings suggest that there is an interaction between perceived birdsongs and the pleasantness of perceived birdsongs (PPB), eventfulness of perceived birdsongs (EPB), and number types of perceived birdsongs (NTP). Results also show that high frequency contents have an effect on perceived birdsongs in urban forests. We established a perceived birdsongs model (PBM) that effectively simulates the process from soundscape information to perceived birdsongs in urban forests, and the methodology developed in this study could be useful for conducting soundscape assessment and promoting soundscape conservation in other urban forests.