Cetacean population density estimation from single fixed sensors using passive acoustics

Abstract

Passive acoustic methods are increasingly being used to estimate animal population density. Most density estimation methods are based on estimates of the probability of detecting calls as functions of distance. Typically these are obtained using receivers capable of localizing calls or from studies of tagged animals. However, both approaches are expensive to implement. The approach described here uses a MonteCarlo model to estimate the probability of detecting calls from single sensors. The passive sonar equation is used to predict signal-to-noise ratios (SNRs) of received clicks, which are then combined with a detector characterization that predicts probability of detection as a function of SNR. Input distributions for source level, beam pattern, and whale depth are obtained from the literature. Acoustic propagation modeling is used to estimate transmission loss. Other inputs for density estimation are call rate, obtained from the literature, and false positive rate, obtained from manual analysis of a data sample. The method is applied to estimate density of Blainville's beaked whales over a 6-day period around a single hydrophone located in the Tongue of the Ocean, Bahamas. Results are consistent with those from previous analyses, which use additional tag data.

A small long-life acoustic transmitter for studying the behavior of aquatic animals

“…Based on all of these and the passive sonar equation, the transmission loss can be related to the source level. According to the passive sonar equation, 21,22 the transmission loss can be expressed as…”

Application of Density Estimation Methods to Datasets from a Glider

“…The methodology employed in this study to estimate the population density of marine mammals off Newport, OR, will be based on the works of Zimmer et al (2008), Marques et al (2009), Küsel et al (2011), Ainslie (2013, and the results from the ONR-funded project "Cetacean density estimation from novel acoustic datasets by acoustic propagation modeling." In the latter, this study's PIs investigated the effects of call bandwidth, multipath arrivals, and the use of propagation models in population density estimation from single sensor datasets.…”

“…In the latter, this study's PIs investigated the effects of call bandwidth, multipath arrivals, and the use of propagation models in population density estimation from single sensor datasets. Required steps for a cue counting approach, where a cue has been defined as a clicking event (Küsel et al, 2011), to density estimation from data recorded by single, fixed sensors are summarized in Figure 1. Fitting the glider with two recording sensors, instead of one, provides the opportunity to investigate other density estimation modalities (Thomas and Marques, 2012), such as individual or group counting.…”

Marine mammal tracks from two-hydrophone acoustic recordings made with a glider

“…The works of Thomas and Marques (2012) and Marques et al (2013) provide good summaries of the current 274 E. T. Küsel et al: Marine mammal tracks from glider acoustics state of density estimation techniques from passive acoustics applied to different species of marine mammals. Küsel et al (2011) addressed density estimation from single fixed sensors in which no information on animal location is readily available from the data. In such cases, a modeling approach is used to estimate detection distances, which are then translated into a relationship expressing the probability of detection as a function of range -the detection function.…”