Limits to the accurate and generalizable use of soundscapes to monitor biodiversity

Abstract

Although eco-acoustic monitoring has the potential to deliver biodiversity insight on vast scales, existing analytical approaches behave unpredictably across studies. We collated 8,023 audio recordings with paired manual avifaunal point counts to investigate whether soundscapes could be used to monitor biodiversity across diverse ecosystems. We found that neither univariate indices nor machine learning models were predictive of species richness across datasets but soundscape change was consistently indicative of community change. Our fndings indicate that there are no common features of biodiverse soundscapes and that soundscape monitoring should be used cautiously and in conjunction with more reliable in-person ecological surveys.