01990nas a2200193 4500008004100000245011100041210006900152520132100221653002101542653001701563653001801580653002301598653001601621100002101637700002101658700002601679700002501705856006601730 2019 eng d00aAcoustic crypsis in communication by North Atlantic right whale mother–calf pairs on the calving grounds0 aAcoustic crypsis in communication by North Atlantic right whale 3 a

Mammals with dependent young often rely on cryptic behaviour to avoid detection by potential predators. In the mysticetes, large baleen whales, young calves are known to be vulnerable to direct predation from both shark and orca predators; therefore, it is possible that mother–calf pairs may show cryptic behaviours to avoid the attention of predators. Baleen whales primarily communicate through low-frequency acoustic signals, which can travel over long ranges. In this study, we explore the potential for acoustic crypsis, a form of cryptic behaviour to avoid predator detection, in North Atlantic right whale mother–calf pairs. We predicted that mother– calf pairs would either show reduced calling rates, reduced call amplitude or a combination of these behavioural modifications when compared with other demographic groups in the same habitat. Our results show that right whale mother–calf pairs have a strong shift in repertoire usage, significantly reducing the number of higher amplitude, long-distance communication signals they produced when compared with juvenile and pregnant whales in the same habitat. These observations show that right whale mother–calf pairs rely upon acoustic crypsis, potentially to minimize the risk of acoustic eavesdropping by predators.

10aacoustic crypsis10abaleen whale10aeavesdropping10apredator avoidance10aright whale1 aParks, Susan, E.1 aCusano, Dana, A.1 aVan Parijs, Sofie, M.1 aNowacek, Douglas, P. uhttps://royalsocietypublishing.org/doi/10.1098/rsbl.2019.048502320nas a2200217 4500008004100000245013200041210006900173520157600242653002001818653002401838653001301862653001801875653003001893653003201923653002101955100001901976700001901995700002602014700001802040856004402058 2018 eng d00aImplementing conservation measures for the North Atlantic right whale: considering the behavioral ontogeny of mother-calf pairs0 aImplementing conservation measures for the North Atlantic right 3 a

Understanding the behavioral ecology of a species is fundamental to effective conservation and management efforts. This study quantifies the behavioral ontogeny of North Atlantic right whale mother‐calf pairs from birth to weaning spanning three critical habitat areas off the eastern coast of the United States and Canada. Data from 55 focal follows of 34 mother‐calf pairs were collected from 2011 to 2015. Resting behaviors dominated the activity budgets for both mother and calf during the first 5 months, putting them at increased risk of vessel collisions. There was an increase in the proportion of active behaviors (travel, foraging, social activity) in both mother and calf as the calf matured. Importantly, the type of active behaviors, in particular surface skim feeding and surface active social behavior, meant that the risk of vessel collision to the pair did not decrease as the calf matured. Mother‐calf right whale pairs showed very low calling rates on the calving grounds, suggesting that passive acoustic monitoring may not be an effective mitigation tool during the early months. However, calling rates increase once the pair leave the calving areas with both calf age and activity levels increasing, at which point passive acoustic monitoring becomes valuable. Protective measures need to take these rapid developmental changes throughout calf growth into account to improve the efficacy of protection measures for the endangered North Atlantic right whale and other species where behavioral ecology changes rapidly during maturation.

10aactivity budget10abehavioral ontogeny10acallrate10amarine mammal10aNorthAtlantic right whale10apassive acoustic monitoring10avessel collision1 aCusano, D., A.1 aConger, L., A.1 aVan Parijs, Sofie, M.1 aParks, S., E. uhttps://bio.acousti.ca/pt-pt/node/5325402372nas a2200181 4500008004100000022001400041245016100055210006900216260001600285490000800301520173600309100002102045700001902066700001602085700001602101700001802117856005502135 2018 eng d a0025-316200aSeen or heard? A comparison of visual and acoustic autonomous monitoring methods for investigating temporal variation in occurrence of southern right whales0 aSeen or heard A comparison of visual and acoustic autonomous mon cJan-01-20180 v1653 aPassive acoustic detectors are widely used for monitoring distribution of cetaceans. Autonomous visual methods are less frequently employed; they are limited to detections during daylight and good weather, but offer potential advantages due to certainty of species’ identification and longevity of deployment. To compare performance of acoustic and visual methods, temporal changes in distribution of southern right whales, Eubalaena australis, were monitored in the remote sub-Antarctic Auckland Islands (50°31′S, 166°16′E). A time-lapse camera was deployed for 2 years from August 2010, taking an image every 70 min. The presence of whales was scored for each image taken during daylight (n = 8295). A passive acoustic recorder was deployed in August 2011, recording for 3.75 min every hour until battery life expired after 10 months. Each recording (n = 6978) was aurally reviewed. Both methods revealed a similar seasonal distribution; maximum detection rates were in the austral winter and no whales were detected in January or February. However, at the peak of right whale occurrence, the proportion of samples with whales detected was much higher for the acoustic recorder (93.9% in August) than the time-lapse camera (14.8%). A generalised additive model fitted to the visual data revealed significant effects of sea state and visibility. Acoustic detection rates were higher, probably because detection range is greater, and less affected by weather. The solar-powered time-lapse camera system, however, functioned effectively for much longer. We discuss the relative merits of visual and acoustic detectors and attempt to draw conclusions about their efficacy for different focal species and monitoring locations.1 aRayment, William1 aWebster, Trudi1 aBrough, Tom1 aJowett, Tim1 aDawson, Steve uhttp://link.springer.com/10.1007/s00227-017-3264-002069nas a2200217 4500008004100000022001400041245010400055210006900159260001600228300001600244490000800260520139900268100001701667700001901684700002101703700001801724700002101742700001701763700002001780856005101800 2017 eng d a0001-496600aUsing nonlinear time warping to estimate North Pacific right whale calling depths in the Bering Sea0 aUsing nonlinear time warping to estimate North Pacific right wha cJan-05-2017 a3059 - 30690 v1413 a

Calling depth distributions are estimated for two types of calls produced by critically endangered eastern North Pacific right whales (NPRWs) in the Bering Sea, using passive acoustic data collected with bottom-mounted hydrophone recorders. Nonlinear time resampling of 12 NPRW “upcalls” and 20 “gunshots” recorded in a critical NPRW habitat isolated individual normal mode arrivals from each call. The relative modal arrival times permitted range estimates between 1 and 40 km, while the relative modal amplitudes permitted call depth estimates, provided that environmental inversions were obtained from high signal-to-noise ratio calls. Gunshot sounds were generally only produced at a few meters depth, while upcall depths clustered between 10 and 25 m, consistent with previously published bioacoustic tagging results from North Atlantic right whales. A Wilcoxon rank sum test rejected the null hypothesis that the mean calling depths of the two call types were the same (p = 2.9 × 10−5); the null hypothesis was still rejected if the sample set was restricted to one call per acoustic encounter (p = 0.02). Propagation modeling demonstrates that deeper depths enhance acoustic propagation and that source depth estimates impact both NPRW upcall source level and detection range estimates.

1 aThode, Aaron1 aBonnel, Julien1 aThieury, Margaux1 aFagan, Aileen1 aVerlinden, Chris1 aWright, Dana1 aCrance, Jessica uhttp://asa.scitation.org/doi/10.1121/1.498220000584nas a2200145 4500008004100000245014600041210006900187260001600256100002800272700002100300700002200321700002500343700002700368856004300395 2017 eng d00aUpcall production by southern right whale ( Eubalaena australis) mother-calf pairs may be independent of diel period in a nursery area0 aUpcall production by southern right whale iEubalaena australisi  cJan-02-20171 aDombroski, Julia, R. G.1 aParks, Susan, E.1 aGroch, Karina, R.1 aFlores, Paulo, A. C.1 aSousa-lima, Renata, S. uhttp://doi.wiley.com/10.1111/mms.1238201892nas a2200181 4500008004100000022001300041245012200054210006900176260001600245300001400261490000800275520128200283100002201565700001801587700002101605700001801626856006601644 2017 eng d a0003682X00aTwo-stage detection of north Atlantic right whale upcalls using local binary patterns and machine learning algorithms0 aTwostage detection of north Atlantic right whale upcalls using l cJan-05-2017 a158 - 1660 v1203 a

In this paper, we investigate the effectiveness of two-stage classification strategies in detecting north Atlantic right whale upcalls. Time-frequency measurements of data from passive acoustic monitoring devices are evaluated as images. Vocalization spectrograms are preprocessed for noise reduction and tone removal. First stage of the algorithm eliminates non-upcalls by an energy detection algorithm. In the second stage, two sets of features are extracted from the remaining signals using contour-based and texture based methods. The former is based on extraction of time–frequency features from upcall contours, and the latter employs a Local Binary Pattern operator to extract distinguishing texture features of the upcalls. Subsequently evaluation phase is carried out by using several classifiers to assess the effectiveness of both the contour-based and texture-based features for upcall detection. Comparing ROC curves of machine learning algorithms obtained from Cornell University’s dataset reveals that LBP features improved performance accuracy up to 43% over time–frequency features. Classifiers such as the Linear Discriminant Analysis, Support Vector Machine, and TreeBagger achieve highest upcall detection rates with LBP features.

1 aEsfahanian, Mahdi1 aErdol, Nurgun1 aGerstein, Edmund1 aZhuang, Hanqi uhttp://linkinghub.elsevier.com/retrieve/pii/S0003682X17300774