Accommodating false positives within acoustic spatial capture–recapture, with variable source levels, noisy bearings and an inhomogeneous spatial density

Funding: Tiago Marques was partly supported by CEAUL (funded by FCT - Fundação para a Ciência e a Tecnologia, Portugal, through the project UIDB/00006/2020).Passive acoustic monitoring is a promising method for surveying wildlife populations that are easier to detect acoustically than visually. When animal vocalisations can be uniquely identified on an array of sensors, the potential exists to estimate population density through acoustic spatial capture–recapture (ASCR). However, sound classification is imperfect, and in some situations, a high proportion of sounds detected on just a single sensor (‘singletons’) are not from the target species. We present a case study of bowhead whale calls (Baleana mysticetus) collected in the Beaufort Sea in 2010 containing such false positives. We propose a novel extension of ASCR that is robust to false positives by truncating singletons and conditioning on calls being detected by at least two sensors. We allow for individual-level detection heterogeneity through modelling a variable sound source level, model inhomogeneous call spatial density, and include bearings with varying measurement error. We show via simulation that the method produces near-unbiased estimates when correctly specified. Ignoring source-level variation resulted in a strong negative bias, while ignoring inhomogeneous density resulted in severe positive bias. The case study analysis indicated a band of higher call density approximately 30 km from shore; 59.8% of singletons were estimated to have been false positives.Publisher PDFPeer reviewe

A comparison of three methods for estimating call densities of migrating bowhead whales using passive acoustic monitoring

TAM thanks partial support by Centro de Estatistica e Aplicações, Universidade de Lisboa (funded by FCT—Fundação para a Ciência e a Tecnologia, Portugal, through the project UID/MAT/00006/2013).Various methods for estimating animal density from visual data, including distance sampling (DS) and spatially explicit capture-recapture (SECR), have recently been adapted for estimating call density using passive acoustic monitoring (PAM) data, e.g., recordings of animal calls. Here we summarize three methods available for passive acoustic density estimation: plot sampling, DS, and SECR. The first two require distances from the sensors to calling animals (which are obtained by triangulating calls matched among sensors), but SECR only requires matching (not localizing) calls among sensors. We compare via simulation what biases can arise when assumptions underlying these methods are violated. We use insights gleaned from the simulation to compare the performance of the methods when applied to a case study: bowhead whale call data collected from arrays of directional acoustic sensors at five sites in the Beaufort Sea during the fall migration 2007–2014. Call detections were manually extracted from the recordings by human observers simultaneously scanning spectrograms of recordings from a given site. The large discrepancies between estimates derived using SECR and the other two methods were likely caused primarily by the manual detection procedure leading to non-independent detections among sensors, while errors in estimated distances between detected calls and sensors also contributed to the observed patterns. Our study is among the first to provide a direct comparison of the three methods applied to PAM data and highlights the importance that all assumptions of an analysis method need to be met for correct inference.Publisher PDFPeer reviewe

Using line acceleration to measure false killer whale (Pseudorca crassidens) click and whistle source levels during pelagic longline depredation

False killer whales (Pseudorca crassidens) depredate pelagic longlines in offshore Hawaiian waters. On January 28, 2015 a depredation event was recorded 14m from an integrated GoPro camera, hydrophone, and accelerometer, revealing that false killer whales depredate bait and generate clicks and whistles under good visibility conditions. The act of plucking bait off a hook generated a distinctive 15 Hz line vibration. Two similar line vibrations detected at earlier times permitted the animal’s range and thus signal source levels to be estimated over a 25-min window. Peak power spectral density source levels for whistles (4–8 kHz) were estimated to be between 115 and 130 dB re 1 lPa2/Hz @ 1 m. Echolocation click source levels over 17–32 kHz bandwidth reached 205 dB re 1lPa @ 1 m pk-pk, or 190 dB re 1lPa @ 1 m (root-meansquare). Predicted detection ranges of the most intense whistles are 10 to 25 km at respective sea states of 4 and 1, with click detection ranges being 5 times smaller than whistles. These detection range analyses provide insight into how passive acoustic monitoring might be used to both quantify and avoid depredation encounters.The authors are indebted to Captain Jerry Ray and the rest of the F/V Katy Mary crew for permitting the camera gear to be deployed during their longline fishing trip. Robert Glatts designed the custom GoPro circuit board, and Will Cerf assisted with video footage analysis. This research was sponsored by Derek Orner under the Bycatch Reduction Engineering Program (BREP) at the National Oceanic and Atmospheric Administration (NOAA).Ye

Experimental demonstration of time warping to invert for array tilt and mode shape on a vertical array in a shallow arctic environment

International audienceVertical arrays provide the most convenientgeometry for many underwater passive acoustic applications thatrequire the identification and isolating of propagating normalmodes. Unfortunately, practical deployments of vertical arraysface several practical issues, including the need to compensate forvertical array inclination, and incomplete coverage of the watercolumn that makes the use of Sturm-Liouville orthogonalityproblematic. Here bowhead whale signals collected in the ArcticOcean are used to demonstrate how the use of non-linearsampling (called “warping”) in the time domain can be used todirectly invert for array tilt, as well as yield mode shapes,without resort to the orthogonality relations

Northeasternmost record of a North Pacific fin whale (Balaenoptera physalus) in the Alaskan Chukchi Sea

International audienceFin whales (Balaenoptera physalus) in the North Pacific consistently range as far north as the Bering Sea. While occasional sightings of fin whales occur north of the Bering Strait, they are rarely documented north of 67°N. However, a recent increase in passive acoustic monitoring has shown that fin whales are more prevalent in the Chukchi Sea than previously thought. During a 2012 field survey in the Alaskan Chukchi Sea, fin whale calls were detected on a DiFAR sonobuoy deployed at 71.575°N, 157.823°W, 50 km off Barrow near the mouth of Barrow Canyon. On August 27, 2012, approximately 30 fin whale downsweep calls were detected over an hour and a half, at bearings of approximately 270–290° from the sonobuoy. Since only one sonobuoy was deployed, in situ localization of the calls was not possible. Post hoc range estimates using a combination of modal dispersion techniques, nonlinear time-domain warping, and geoacoustic inversion resulted in a source range estimate of less than 5 km. This location is approximately 280 and 365 km northeast of the previous closest acoustic detection and confirmed visual sighting of a fin whale, respectively. These results represent the farthest northeast record of fin whale calls in the Alaskan Arctic and illustrate the importance of continued passive acoustic monitoring in a rapidly changing environment