VEIR

Marla M. Holt, D. Noren, V. Veirs, C. Emmons, Scott R. Veirs

Scott R. Veirs, V. Veirs, J. Wood

Combining calibrated hydrophone measurements with vessel location data from the Automatic Identification System, we estimate underwater sound pressure levels for 1,582 unique ships that transited the core critical habitat of the endangered Southern Resident killer whales during 28 months between March, 2011, and October, 2013. Median received spectrum levels of noise from 2,809 isolated transits are elevated relative to median background levels not only at low frequencies (20–30 dB re 1 µPa2/Hz from 100 to 1,000 Hz), but also at high frequencies (5–13 dB from 10,000 to 96,000 Hz). Thus, noise received from ships at ranges less than 3 km extends to frequencies used by odontocetes. Broadband received levels (11.5–40,000 Hz) near the shoreline in Haro Strait (WA, USA) for the entire ship population were 110 ± 7 dB re 1 µPa on average. Assuming near-spherical spreading based on a transmission loss experiment we compute mean broadband source levels for the ship population of 173 ± 7 dB re 1 µPa 1 m without accounting for frequency-dependent absorption. Mean ship speed was 7.3 ± 2.0 m/s (14.1 ± 3.9 knots). Most ship classes show a linear relationship between source level and speed with a slope near +2 dB per m/s (+1 dB/knot). Spectrum, 1/12-octave, and 1/3-octave source levels for the whole population have median values that are comparable to previous measurements and models at most frequencies, but for select studies may be relatively low below 200 Hz and high above 20,000 Hz. Median source spectrum levels peak near 50 Hz for all 12 ship classes, have a maximum of 159 dB re 1 µPa2/Hz @ 1 m for container ships, and vary between classes. Below 200 Hz, the class-specific median spectrum levels bifurcate with large commercial ships grouping as higher power noise sources. Within all ship classes spectrum levels vary more at low frequencies than at high frequencies, and the degree of variability is almost halved for classes that have smaller speed standard deviations. This is the first study to present source spectra for populations of different ship classes operating in coastal habitats, including at higher frequencies used by killer whales for both communication and echolocation.

Ke Yang, Qi Han, Dujuan Yang, Bauke de Veirs

K. J. Palmer, E. Cummings, Michael G. Dowd, Kait Frasier, F. Frazão, A. Harris, April Houweling, Jasper Kanes, O. Kirsebom, Holger Klinck, Holly T. LeBlond, Lauren Laturnus, C. Matkin, Olivia Murphy, Hannah J. Myers, D. Olsen, Caitlin O’Neill, B. Padovese, James Pilkington, Lucy S. Quayle, Amalis Riera Vuibert, Krista Trounce, S. Vagle, Scott R. Veirs, V. Veirs, Jen Wladichuk, Jason Wood, T. Yack, H. Yurk, Ruth Joy

Killer whales (Orcinus orca) exhibit significant ecological and genetic diversity, with three primary sympatric populations in the Northeast Pacific: Resident, Bigg’s (Transient), and Offshore. Each population is characterized by distinct foraging habits, social structures, and vocal repertoires, which complicate accurate monitoring and conservation efforts. This dataset, compiled from diverse sources, provides a comprehensive resource for the detection and classification of killer whale vocalizations. The dataset includes annotated acoustic recordings spanning 11 years from various locations in Alaska, British Columbia, and Washington, collected using multiple hydrophone systems. It addresses the challenge of differentiating killer whale calls from other marine species and environmental noise, including specific instances of confounding signals that may help enhance model robustness. Detailed annotations capture a diverse suite of vocalizations and their associated metadata, facilitating the development of advanced machine learning models for ecological monitoring. This curated dataset aims to improve the accuracy of killer whale detection algorithms, support conservation efforts, and advance our understanding of killer whale acoustic communication across different populations.

Ran Yuan, Yikun Qiu, Tonggui Liu, Yin Cheng, Chaolie Ning, Dariusz Wanatowski, Yi He

ABSTRACT Although anisotropy in spatial correlations of intensity measures (IMs) has been acknowledged, few models specifically address the anisotropy, and consider cross-correlations of IMs. This study introduces anisotropic spatial cross-correlation models for 16 IMs: PGA, PGV, Ia, CAV, Ds5–75, Tm, spectral VEIr, and SA at periods of 0.05s, 0.2, 0.5s, 1s and 2s. The models can predict for four anisotropy directions, which are angled (i.e. 0°, 45°, 90°, and 135°) relative to the fault direction. Finally, the proposed model was utilized for the regional seismic landslide hazard assessment to show a practical application.