02099nas a2200241 4500008004100000245013800041210006900179260001600248520131100264653001701575653002201592653001601614653002001630653001101650653002201661653002201683653002201705100002401727700002201751700001901773700002201792856004301814 2018 eng d00aAcoustic monitoring reveals the times and tides of harbor porpoise (Phocoena phocoena) distribution off central Oregon, U.S.A.0 aAcoustic monitoring reveals the times and tides of harbor porpoi cJan-10-20203 a

Harbor porpoises (Phocoena phocoena) are commonly observed in Oregon’s nearshore marine environment yet knowledge of their eco- system use and behavior remains limited, generating concerns for potential impacts on this species from future coastal development. Pas- sive acoustic monitoring was used to investigate spatial and temporal variations in the presence and foraging activity of harbor porpoises off the Oregon coast from May through October 2014. Digital monitoring devices (DMONs) were deployed to record acoustic data (320 kHz sam- ple rate) in two neighboring but bathymetrically different locations off the Oregon coast: (1) a site on the 30 m isobath in close proximity (<50 m) to a rocky reef, and (2) a site on the 60 m isobath in an open sandy environment. Data were analyzed with respect to two dynamic cyclic variables: diel and tidal phase. Porpoise presence at the rocky reef site was aligned with the ebb phase of the tidal forcing, while, har- bor porpoise presence and foraging at the offshore, sandy bottom site was associated with night-time foraging. The spatial and temporal pat- terns identified in this study suggest harbor porpoise habitat use is modulated by specific environmental conditions particular to each site that maximize foraging efficiency.

10adistribution10aforaging behavior10ahabitat use10aharbor porpoise10aOregon10apassive acoustics10aPhocoena phocoena10atemporal patterns1 aHoldman, Amanda, K.1 aHaxel, Joseph, H.1 aKlinck, Holger1 aTorres, Leigh, G. uhttp://doi.wiley.com/10.1111/mms.1253702070nas a2200313 4500008004100000022001400041245006000055210005600115260001600171300001600187490000800203520117800211100002001389700003001409700002401439700002101463700002501484700001901509700002201528700002501550700001901575700002101594700001701615700002101632700002001653700001301673700001901686856005101705 2018 eng d a0001-496600aThe use of context in machine learning for bioacoustics0 ause of context in machine learning for bioacoustics cJan-09-2018 a1728 - 17280 v1443 a

Biological acoustic signals are often produced in context. Contextual information includes things such as timing between calls, conspecific or interspecies cues, and physical environmental cues such as sunrise or sunset. We show how some forms of contextual information can be used to improve the results of detection and classification tasks for biological acoustic signals. We examine how context can be used to improve labeled data, resulting in more-accurate classification results, as well as how learners can exploit context directly. We demonstrate these improvements via two bioacoustic detection/classification tasks. The first algorithm detects odontocete echolocation clicks. We used a decision support system that allowed analysts to label echolocation clicks using between call timing cues as well as other measurements and found that deep learners trained with these high quality data are able to detect clicks in adverse environments. The second algorithm applies contextual information surrounding North Atlantic right whale upcalls to improve precision and recall. [This work was supported by ONR Grant Nos. N00014-17-1-2867 and N00014-15-1-2299.]

1 aRoch, Marie, A.1 aBaumann-Pickering, Simone1 aCholewiak, Danielle1 aFleishman, Erica1 aFrasier, Kaitlin, E.1 aGlotin, Hervé1 aHelble, Tyler, A.1 aHildebrand, John, A.1 aKlinck, Holger1 aLindeneau, Scott1 aLiu, Xiaobai1 aNosal, Eva-Marie1 aPalmer, Kaitlin1 aShiu, Yu1 aSingh, Gurisht uhttp://asa.scitation.org/doi/10.1121/1.506766501961nas a2200169 4500008004100000022001400041245016700055210006900222260001600291300001600307490000800323520134900331100001601680700002501696700001901721856005101740 2018 eng d a0001-496600aDiving behavior of Cuvier's beaked whales inferred from three-dimensional acoustic localization and tracking using a nested array of drifting hydrophone recorders0 aDiving behavior of Cuviers beaked whales inferred from threedime cJan-10-2018 a2030 - 20410 v1443 a

Echolocation pulses from Cuvier's beaked whales are used to track the whales' three-dimensional diving behavior in the Catalina Basin, California. In 2016, five 2-element vertical hydrophone arrays were suspended from the surface and drifted at ∼100-m depth. Cuvier's beaked whale pulses were identified, and vertical detection angles were estimated from time-differences-of-arrival of either direct-path signals received on two hydrophones or direct-path and surface-reflected signals received on the same hydrophone. A Bayesian state-space model is developed to track the diving behavior. The model is fit to these detection angle estimates from at least four of the drifting vertical arrays. Results show that the beaked whales were producing echolocation pulses and are presumed to be foraging at a mean depth of 967 m (standard deviation = 112 m), approximately 300 m above the bottom in this basin. Some whales spent at least some time at or near the bottom. Average swim speed was 1.2 m s−1, but swim direction varied during a dive. The average net horizontal speed was 0.6 m s−1. Results are similar to those obtained from previous tagging studies of this species. These methods may allow expansion of dive studies to other whale species that are difficult to tag.

1 aBarlow, Jay1 aGriffiths, Emily, T.1 aKlinck, Holger uhttp://asa.scitation.org/doi/10.1121/1.505521602236nas a2200253 4500008004100000245017200041210006900213260001600282300001400298490000700312520141300319653002101732653001001753653003201763653001801795653001301813100002101826700002001847700001601867700001501883700002201898700001901920856004301939 2018 eng d00aDescription and classification of Indian Ocean humpback dolphin ( Sousa plumbea ) whistles recorded off the Sindhudurg coast of Maharashtra, India0 aDescription and classification of Indian Ocean humpback dolphin  cJan-07-2018 a755 - 7760 v343 a

The Indian Ocean humpback dolphin (Sousa plumbea), a common cetacean species in India, has a diverse vocal repertoire, which to date has not been described in detail. This study focused on analyzing their whistle vocalizations. Humpback dolphins were recorded off the Sindhudurg coast of Maharashtra, India, and 2,260 whistles were analyzed for their acoustic characteristics. Whistles spanned a wide frequency range between 2.3 kHz and 33.0 kHz, with durations ranging from 0.01 s to 1.60 s. Whistles were categorized into seven contour classes based on their qualitative prop- erties. A classification and regression tree (CART) analysis was used to quantify vari- ability between the seven contour classes using the measured acoustic features. Based on the CART analysis, frequency gradient, minimum slope, maximum slope, begin- ning and ending slope accounted for most variability between whistle types. CART resulted in an overall classification accuracy of 89.5%. This study provides a detailed description of acoustic features and qualitative properties of humpback dolphin whis- tles from the northwestern coast of India. Further comparisons of acoustic data from Sousa populations along the Indian coast are necessary to determine possible geo- graphic variations in whistle characteristics and whether the variations are driven by environmental or genetic factors or a combination of both.

10ahumpback dolphin10aIndia10apassive acoustic monitoring10aSousa plumbea10awhistles1 aBopardikar, Isha1 aSutaria, Dipani1 aSule, Mihir1 aJog, Ketki1 aPatankar, Vardhan1 aKlinck, Holger uhttp://doi.wiley.com/10.1111/mms.v34.3