Long-term passive acoustic recordings track the changing distribution of North Atlantic right whales (Eubalaena glacialis) from 2004 to 2014

Abstract

Given new distribution patterns of the endangered North Atlantic right whale (NARW; Eubalaena glacialis) population in recent years, an improved understanding of spatio-temporal movements are imperative for the conservation of this species. While so far visual data have provided most information on NARW movements, passive acoustic monitoring (PAM) was used in this study in order to better capture year-round NARW presence. This project used PAM data from 2004 to 2014 collected by 19 organizations throughout the western North Atlantic Ocean. Overall, data from 324 recorders (35,600 days) were processed and analyzed using a classification and detection system. Results highlight almost year-round habitat use of the western North Atlantic Ocean, with a decrease in detections in waters off Cape Hatteras, North Carolina in summer and fall. Data collected post 2010 showed an increased NARW presence in the mid-Atlantic region and a simultaneous decrease in the northern Gulf of Maine. In addition, NARWs were widely distributed across most regions throughout winter months. This study demonstrates that a large-scale analysis of PAM data provides significant value to understanding and tracking shifts in large whale movements over long time scales.

Emerging opportunities and challenges for passive acoustics in ecological assessment and monitoring

“…These include sensor calibration guidelines (Merchant et al., ), metadata standards (Roch et al., ), assessing the efficacy of sampling designs (Braun de Torrez et al., ; Froidevaux, Zellweger, Bollmann, & Obrist, ; Van Parijs et al., ), quantifying sensitivity differences between sensor models and over time due to environmental degradation (Adams et al., ; Merchant et al., ), and quantifying effects of sensor proximity to habitat features (e.g., vegetation, water surface, topography) on sound detection (Darras, Pütz, Fahrurrozi, Rembold, & Tscharntke, ; Farcas et al., ). Ultimately, these efforts should facilitate more robust, data‐driven approaches to analysing large, multisensor acoustic datasets, which currently tend to assume constant species detectability over space and time (e.g., Davis et al., ; Newson et al., ).…”

“…Crucially, recording and storing audio at sufficient quality (Figure c), alongside detailed metadata on surveys, sensor type and recording parameters, also provides opportunities to address additional questions. For example, a recent study collated multiyear hydrophone data to estimate the distribution of the critically endangered North Atlantic right whale Eubalaena glacialis (Davis et al., ). Leveraging decades of PAM survey data will require collaborative development and maintenance of web infrastructure for the collation and public archiving of massive (multi‐gigabyte to petabyte) environmental audio datasets (e.g., https://ngdc.noaa.gov/mgg/pad/).…”

“…However, low‐cost sensors have pushed the bottlenecks into the analysis and management stages, and as we have emphasised, addressing these logistical and analytical barriers now increasingly requires collaborative, community‐led efforts. Marine research remains a source of key innovations, including auto‐ID software development (Baumgartner & Mussoline, ; Gillespie et al., ), acoustic sensor tags (Johnson & Tyack, ), density estimation methods (Marques et al., ), real‐time reporting (Baumgartner et al., ; http://dcs.whoi.edu/), and collation of multisource datasets (Davis et al., ). Increased integration between marine and terrestrial PAM communities would be beneficial to jointly addressing pressing challenges, such as standardisation of survey protocols, establishment of publically archived audio datasets and sound libraries, development of an improved theoretical and analytical framework for measuring vocalising animal communities, and research around operationalising PAM data for conservation.…”

“…Detections derived from sensor networks can provide highly spatially and temporally detailed data on wildlife activity (e.g., London's Nature‐Smart Cities bat monitoring network: https://naturesmartcities.com). Real‐time data feeds could, for instance, be applied to adjust urban lighting regimes to reduce impacts on bat activity, mitigate human‐wildlife conflict, adaptively reroute shipping traffic to avoid threatened cetacean populations (Davis et al., ; Van Parijs et al., ), or report on illegal logging or hunting (Astaras et al., , Rainforest Connection https://rfcx.org). Beyond the institutional and political barriers, developing such an infrastructure would still face substantial technical difficulties, especially since the ultimate goal of developing comprehensive suites of robust auto‐ID tools is likely many years or even decades away.…”

Phenological changes in North Atlantic right whale habitat use in Massachusetts Bay

“…Right whales feed almost exclusively on dense aggregations of calanoid copepods, primarily Calanus finmarchicus (Baumgartner & Mate, ; Baumgartner, Mayo, & Kenney, ; Mayo & Marx, ). Up until 2011, right whale occurrence in these feeding areas followed a relatively consistent phenology (Brillant, Vanderlaan, Rangeley, & Taggart, ; Cole et al, ; Davis et al, ; Hayes et al, ). In late winter and spring, right whales congregated in CCB, where densities typically peaked in April (Hamilton & Mayo, ; Mayo & Marx, ; Nichols, Kenney, & Brown, ; Pendleton et al, ).…”