Estimating bird density using passive acoustic monitoring: a review of methods and suggestions for further research

Abstract

Passive acoustic monitoring is a non-invasive tool for automated wildlife monitoring. This technique has several advantages and addresses many of the biases related to traditional field surveys. However, locating animal sounds using autonomous recording units (ARUs) can be technically challenging and therefore ARUs have traditionally been little employed to estimate animal density. Nonetheless, several approaches have been proposed in recent years to carry out acoustic-based bird density estimations. We conducted a literature review of studies that used ARUs for estimating bird densities or bird abundances in order to describe the applications and improve future monitoring programmes. We detected a growing interest in the use of ARUs for estimating bird density in the last 6 years , with a total of 31 articles assessing the topic. The most common approach was to estimate the relationship between the number of vocalizations per recording time with bird density or bird abundance estimated in the field (61%). In 26 studies (79%), bird estimates obtained by human surveyors agreed with those obtained using ARUs. Some approaches have proven able to reduce biases in acoustic surveys, such as considering imperfect detection (spatially explicit capture-recapture, using microphone arrays), applying paired acoustic sampling to control for different sampling radius between humans and ARUs, or including relative sound level measurements that allow researchers to estimate bird distance to recorder. However, several studies did not include any covariates to reduce existing biases and some did not estimate the sampling radius of the recorder, which may hamper future comparisons between human and ARU surveys. Future studies should include a measurement of the sampling radius of the recorder employed to be able to obtain density estimations using ARUs. Finally, we provide some guidelines to improve the applicability of ARUs to infer bird population estimates in future studies.

Acoustic monitoring shows invasive beavers Castor canadensis increase patch‐level avian diversity in Tierra del Fuego

“…Of the proliferating studies comparing PAM results to classical measures of abundance and diversity (e.g. Darras et al., 2018; Depraetere et al., 2012; Fuller et al., 2015; Pérez‐Granados & Traba, 2021; Zhao et al., 2019), our correlations are most comparable in terms of methods and statistics with those reported by Eldridge et al. (2018) and Mammides et al.…”

“…We employed PAM to: (a) reduce researcher‐induced bias and error, (b) enable long‐term, synchronous, high‐temporal resolution data collection (Gasc et al., 2017; Sueur & Farina, 2015) and (c) further test PAM’s utility as a scalable biodiversity proxy through comparison against count‐derived metrics of avian abundance, species diversity and functional diversity (e.g. Buxton et al., 2018; Darras et al., 2018; Depraetere et al., 2012; Gasc et al., 2015; Pérez‐Granados & Traba, 2021; Zhao et al., 2019). Located in the acoustic research gap of southern South America (Sugai et al., 2019), IGDTDF is an auspicious locale for field‐based comparison between classical diversity metrics and PAM due to its lack of potentially confounding non‐avian sounds (Rozzi & Jiménez, 2014).…”

Seasonal Climate Impacts on Vocal Activity in Two Neotropical Nonpasserines

“…The daily vocal activity of both focal species varied among some of the acoustic monitoring stations. That variation is likely related to different number of individuals vocalizing around recorders, since it is expected to find a positive association between the number of calls detected in sound recordings and the number of individuals vocalizing around recorders (see review in Pérez-Granados and Traba) [55]. Although we were unable to include the number of individuals vocalizing around recorders as a covariate in the analyses, it should not have influenced our results.…”

Acoustic censusing and individual identification of birds in the wild

“…Our approach allows accurate individual identification, and it is a true estimator of the number of individuals present in a set of recordings. This significantly differs from most current acousticbased methodologies for population monitoring, which primarily focus on determining presence/absence and call rates (25,26), or use indices based on the distribution of energy in the acoustic spectrum (27)(28)(29).…”