Passive acoustic monitoring for the estimation of density of the singing lemur ( Indri indri )

Passive acoustic monitoring (PAM) has emerged as a valuable tool for estimating animal density and abundance, particularly in challenging environments where traditional methods face limitations. In this study, we applied PAM techniques to study the indri ( Indri indri ) in the Maromizaha New Protected Area, a tropical forest in Eastern Madagascar. Leveraging advancements in acoustic monitoring methodologies, we aimed to assess the efficacy of PAM in estimating indri density and its implications for conservation efforts. We tested a method originally developed for marine environments to estimate density using PAM in a terrestrial forest setting. By deploying a network of Autonomous Recording Units (ARUs) across the forest landscape, we captured indri vocalizations and evaluated their detectability using Generalized Linear Mixed Models (GLMMs). We included directional information and environmental covariates to account for the complexities of tropical forest acoustics. This allowed us to calculate the detection probability within the range of action of the ARUs. We then used this value to estimate indri density in an area where we knew the actual density. Our calculated density estimates were 5.55 groups/km 2 , closely matching the known density in the monitored area (6.17 groups/km 2 ). These findings underscore PAM's potential as a powerful tool for monitoring elusive species in challenging habitats. These results have important implications for conservation strategies in tropical forest ecosystems, highlighting the efficacy of PAM in informing evidence‐based management decisions and targeted conservation efforts.