Estimating animal population density using passive acoustics

By Tiago A. Marques, L. Thomas, S. Martin, David K. Mellinger, J. Ward, D. Moretti, Danielle V Harris, P. Tyack. Biological Reviews of The Cambridge Philosophical Society, 2012

668 citations recorded by the source corpus.

Reliable estimation of the size or density of wild animal populations is very important for effective wildlife management, conservation and ecology. Currently, the most widely used methods for obtaining such estimates involve either sighting animals from transect lines or some form of capture‐recapture on marked or uniquely identifiable individuals. However, many species are difficult to sight, and cannot be easily marked or recaptured. Some of these species produce readily identifiable sounds, providing an opportunity to use passive acoustic data to estimate animal density. In addition, even for species for which other visually based methods are feasible, passive acoustic methods offer the potential for greater detection ranges in some environments (e.g. underwater or in dense forest), and hence potentially better precision. Automated data collection means that surveys can take place at times and in places where it would be too expensive or dangerous to send human observers.

Subfields: Developmental Biology, Ecology

View Paper: https://www.semanticscholar.org/paper/ae70793fc397fad1aa76019e7a64bca00db8026f

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Citations in the corpus

Automatic acoustic detection of birds through deep learning: The first Bird Audio Detection challenge (2018, background): “Also via statistical ecology methods relative abundances may still be inferred from the distribution of positive detections (Marques et al., 2012).”
Estimating bird density using passive acoustic monitoring: a review of methods and suggestions for further research (2021, background): “…the number of cues recorded using ARUs (e.g. number of bird songs per unit area per unit time of recording) by an estimate of the average rate at which individuals of the target species vocalize (average number of bird songs per unit time, in this example) (Hiby & Ward 1986, Marques et al .”
Emerging opportunities and challenges for passive acoustics in ecological assessment and monitoring (2018, background): “Such approaches generally assume consistent detection between individuals and over time, even though the relationship between detection rates and relative abundance may vary widely between species and habitats (Marques et al., 2013).”
Computational bioacoustics with deep learning: a review and roadmap (2021, background): “Bioacoustics—the study of animal sound—offers a fascinating window into animal behaviour, and also a valuable evidence source for monitoring biodiversity (Marler and Slabbekoorn, 2004; Laiolo, 2010; Marques et al., 2012; Brown and Riede, 2017).”
Sound production and associated behavior of tagged fin whales (Balaenoptera physalus) in the Southern California Bight (2015, neutral): “[14] review new approaches to solve this problem, which generally rely upon estimates of call rates of individuals and of the probability of detecting a call as a function of range from the receiver.”
Applications for deep learning in ecology (2018, methodology): “For instance, population size can be estimated by counting individuals 20 , or by using estimation methods such as distance sampling 40 .”
Real-time bioacoustics monitoring and automated species identification (2013, positive): “…of bats (Herr, Klomp & Atkinson, 1997; Walters et al., 2012; Parsons & Jones, 2000), whales (Murray, Mercado & Roitblat, 1998; Brandes, 2008; Marques et al., 2012; Mellinger & Clark, 2000; Moore et al., 2006), dolphins (Oswald, Barlow & Norris, 2003), insects (Chesmore, 2004; Chesmore &…”
Drones count wildlife more accurately and precisely than humans (2017, positive): “Camera traps and acoustic recorders have become established tools for determining whether a species is present at a site, and estimating population density (Marques et al., 2013; Rowcliffe & Carbone, 2008).”
Assessing the performance of a semi‐automated acoustic monitoring system for primates (2015, background): “It has been widely applied for monitoring marine mammals (Mellinger et al. 2007) and fish (Gannon 2008), since acoustic signals propagate efficiently in water and visual surveys are problematic or expensive (Marques et al. 2013).”
Acoustic monitoring for conservation in tropical forests: examples from forest elephants (2017, background): “…for example, nocturnal species (e.g. De Solla et al. 2006; Djossa, Zachee & Sinsin 2012; Barros, Pessoa &Rui 2014; Digby et al. 2014; Zwart et al. 2014), marine mammals (e.g. Marques et al. 2013; Rogers et al. 2013), and forest elephants (Thompson, Schwager & Payne 2009a; Wrege et al. 2010, 2012).”
Robust sound event detection in bioacoustic sensor networks (2019, background): “In this context, one emerging application is the species-specific inventory of vocalizing animals [12], such as birds [13], primates [14], and marine mammals [15], whose occurrence in time and space reflects the magnitude of population movements [16], and can be correlated with other environmental v”