Monitoring soundscapes is essential for assessing environmental conditions for soniferous species, yet little is known about sound levels and contributors in Oregon coastal regions. From 2017 to ...2021, during June–September, two hydrophones were deployed near Newport, Oregon to sample 10–13,000 Hz underwater sound. One hydrophone was deployed near the Port of Newport in a high vessel activity area, and another 17 km north within a protected Marine Reserve. Vessel noise and whale vocalizations were detected at both sites, but whales were recorded on more days at the Marine Reserve. Median sound levels in frequencies related to noise from various vessel types and sizes (50 – 4,000 Hz) were up to 6 dB higher at the Port of Newport, with greater diel variability compared to the Marine Reserve. In addition to documenting summer season conditions in Oregon waters, these results exemplify how underwater soundscapes can differ over short distances depending on anthropogenic activity.
Passive acoustic data collection has grown exponentially over the past decade resulting in petabytes of data that document our ocean soundscapes. This effort has resulted in two big data challenges: ...(1) the curation, management, and global dissemination of passive acoustic datasets and (2) efficiently extracting critical information and comparing it to other datasets in the context of ecosystem-based research and management. To address the former, the NOAA National Centers for Environmental Information recently established an archive for passive acoustic data. This fast-growing archive currently contains over 100 TB of passive acoustic audio files mainly collected from stationary recorders throughout waters in the United States. These datasets are documented with standards-based metadata and are freely available to the public. To begin to address the latter, through standardized processing and centralized stewardship and access, we provide a previously unattainable comparison of first order sound level-patterns from archived data collected across three distinctly separate long-term passive acoustic monitoring (PAM) efforts conducted at regional and national scales: NOAA/National Park Service Ocean Noise Reference Station Network, the Atlantic Deepwater Ecosystem Observatory Network, and the Sanctuary Soundscape Monitoring Project. Nine sites were selected from these projects covering the Alaskan Arctic, Northeast and Central Pacific, Gulf of Mexico, Caribbean Sea, and Mid and Northwest Atlantic. Sites could generally be categorized into those strongly influenced by anthropogenic noise (e.g., vessel traffic) and those that were not. Higher sound levels, specifically for lower frequencies (<125 Hz), and proximity to densely populated coastal zones were common characteristics of sites influenced by anthropogenic noise. Conversely, sites with lower overall sound levels and away from dense populations resulted in soundscape patterns influenced by biological sources. Seasonal variability in sound levels across selected decidecade bands was apparent for most sites and often represented changes in the presence or behavior of sound-producing species. This first order examination of levels across projects highlights the utility of these initial metrics to identify patterns that can then be examined in more detail. Finally, to help the PAM community collectively and collaboratively move forward, we propose the next frontier for scalable data stewardship, access, and processing flow.
Passive acoustic sensors provide a cost-effective tool for monitoring marine environments. Documenting acoustic conditions among habitats can provide insights into temporal changes in ecosystem ...composition and anthropogenic impacts. Agencies tasked with safeguarding marine protected areas, such as the U.S. National Park Service and U.S. National Oceanic and Atmospheric Administration’s Office of National Marine Sanctuaries, are increasingly interested in using long-term monitoring of underwater sounds as a means of tracking species diversity and ecosystem health. In this study, low-frequency passive acoustic recordings were collected fall 2014 - spring 2018, using standardized instrumentation, from four marine protected areas across geographically disparate regions of the U.S. Economic Exclusive Zone: Northwest Atlantic, Northeast Pacific, South Pacific, and Caribbean. Recordings were analyzed for differences in seasonal conditions and to identify acoustic metrics useful for resource assessment across all sites. In addition to comparing ambient sound levels, a species common to all four sites, the humpback whale (Megaptera novaeangliae), was used to compare biological sound detection. Ambient sound levels varied across the sites and were driven by differences in animal vocalization rates, anthropogenic activity, and weather. The highest sound levels (dBRMS (50 Hz-1.5 kHz) re 1 μPa) were recorded in the Northwest Atlantic in Stellwagen Bank National Marine Sanctuary (Stellwagen) during the boreal winter-spring resulting from bioacoustic activity, vessel traffic, and high wind speeds. The lowest sound levels (dBRMS (50 Hz-1.5 kHz) re 1 μPa) were recorded in the Northeast Pacific adjacent to a vessel-restricted area of Glacier Bay National Park and Preserve (Glacier Bay) during the boreal summer. Humpback whales were detected seasonally in the southern latitude sites, and throughout the deployment periods in the northern latitude sites. Temporal trends in band and spectrum sound levels in Glacier Bay and the National Park of American Samoa were primarily driven by biological sound sources, while trends in Stellwagen and the Buck Island Reef National Monument were primarily driven by anthropogenic sources. These results highlight the variability of ambient sound conditions in marine protected areas in U.S. waters, and the utility of long-term soundscape monitoring for condition assessment in support of resource management.
Chronic low-frequency noise from commercial shipping is a worldwide threat to marine animals that rely on sound for essential life functions. Although the U.S. National Oceanic and Atmospheric ...Administration recognizes the potential negative impacts of shipping noise in marine environments, there are currently no standard metrics to monitor and quantify shipping noise in U.S. marine waters. However, one-third octave band acoustic measurements centered at 63 and 125 Hz are used as international (European Union Marine Strategy Framework Directive) indicators for underwater ambient noise levels driven by shipping activity. We apply these metrics to passive acoustic monitoring data collected over 20 months in 2016–2017 at five dispersed sites throughout the U.S. Exclusive Economic Zone: Alaskan Arctic, Hawaii, Gulf of Mexico, Northeast Canyons and Seamounts Marine National Monument (Northwest Atlantic), and Cordell Bank National Marine Sanctuary (Northeast Pacific). To verify the relationship between shipping activity and underwater sound levels, vessel movement data from the Automatic Identification System (AIS) were paired to each passive acoustic monitoring site. Daily average sound levels were consistently near to or higher than 100 dB re 1 μPa in both the 63 and 125 Hz one-third octave bands at sites with high levels of shipping traffic (Gulf of Mexico, Northeast Canyons and Seamounts, and Cordell Bank). Where cargo vessels were less common (the Arctic and Hawaii), daily average sound levels were comparatively lower. Specifically, sound levels were ∼20 dB lower year-round in Hawaii and ∼10-20 dB lower in the Alaskan Arctic, depending on the season. Although these band-level measurements can only generally facilitate differentiation of sound sources, these results demonstrate that international acoustic indicators of commercial shipping can be applied to data collected in U.S. waters as a unified metric to approximate the influence of shipping as a driver of ambient noise levels, provide critical information to managers and policy makers about the status of marine environments, and to identify places and times for more detailed investigation regarding environmental impacts.
Understanding animals’ responses to stressors is required to assess population consequences and inform management. We develop a flexible analytical approach to investigate the relationships between ...glucocorticoid concentrations in gray whale faeces and exposure to sound and vessels. Our results highlight that context (e.g., sex, body condition) modulates physiological disturbance responses.
Abstract
Understanding how individual animals respond to stressors behaviourally and physiologically is a critical step towards quantifying long-term population consequences and informing management efforts. Glucocorticoid (GC) metabolite accumulation in various matrices provides an integrated measure of adrenal activation in baleen whales and could thus be used to investigate physiological changes following exposure to stressors. In this study, we measured GC concentrations in faecal samples of Pacific Coast Feeding Group (PCFG) gray whales (Eschrichtius robustus) collected over seven consecutive years to assess the association between GC content and metrics of exposure to sound levels and vessel traffic at different temporal scales, while controlling for contextual variables such as sex, reproductive status, age, body condition, year, time of year and location. We develop a Bayesian Generalized Additive Modelling approach that accommodates the many complexities of these data, including non-linear variation in hormone concentrations, missing covariate values, repeated samples, sampling variability and some hormone concentrations below the limit of detection. Estimated relationships showed large variability, but emerging patterns indicate a strong context-dependency of physiological variation, depending on sex, body condition and proximity to a port. Our results highlight the need to control for baseline hormone variation related to context, which otherwise can obscure the functional relationship between faecal GCs and stressor exposure. Therefore, extensive data collection to determine sources of baseline variation in well-studied populations, such as PCFG gray whales, could shed light on cetacean stress physiology and be used to extend applicability to less-well-studied taxa. GC analyses may offer greatest utility when employed as part of a suite of markers that, in aggregate, provide a multivariate measure of physiological status, better informing estimates of individuals’ health and ultimately the consequences of anthropogenic stressors on populations.
The National Oceanic and Atmospheric Administration (NOAA)/National Park Service (NPS) Ocean Noise Reference Station (NRS) Network is an array of currently twelve calibrated autonomous passive ...acoustic recorders. The first NRS was deployed in June 2014, and eleven additional stations were added to the network during the following two years. The twelve stations record data that can be used to quantify baseline levels and multi-year trends in ocean ambient sound across the continental United States, Alaska, Hawaii, and island territories within and near to the United States Exclusive Economic Zone (U.S. EEZ). The network provides multi-year, continuous observations of low-frequency underwater sound between 10 Hz and 2000 Hz to capture anthropogenic, biological, and geophysical contributions to the marine soundscape at each location. Comparisons over time and among recording sites will provide information on the presence of calling animals and the prevalence of abiotic and anthropogenic activities that contribute to each soundscape. Implementation of the NRS Network advances broad-scale passive acoustic sensing capabilities within NOAA and the NPS and is an important tool for monitoring protected areas and marine species and assessing potential environmental impacts of anthropogenic noise sources. This analysis focuses on the first year of recordings and captures the wide variability of low-frequency sound levels among and within individual NRS sites over time. Continued data collection will provide information on long-term, low-frequency sound level trends within or near the U.S. EEZ and will be used to explore the value of using soundscape analysis to inform management and mitigation strategies.
•The NRS Network is 12 calibrated passive acoustic recorders deployed within and near the U.S. EEZ.•Recordings capture anthropogenic, biological, and environmental soundscape contributors.•Soundscape analysis is an important tool for monitoring protected areas and sensitive species.•Assessing potential impact of chronic noise sources informs management and mitigation strategies.
Abstract
Patterns of underwater human-generated noise events and durations of noise-free intervals (NFIs) are soundscape metrics that can potentially affect animal communication and behavior. Due to ...the arduous task of manual analysis, these metrics have not been described in Glacier Bay National Park and Preserve (GBNP). To surmount this challenge, we created a machine-learning (ML) model trained on 18 hr of labeled audio samples from a hydrophone operating in GBNP since 2000. The validated convolutional neural net transfer-learning model (GBNP-CNN) was used to classify several categories of sound sources in nearly 9,000 hours of data from the same hydrophone, enabling our study of vessel noise between 2017 and 2020. We focused on the occurrence and duration of NFI and the hourly proportion (HP) of vessel noise. As expected, shorter NFI and higher HP were found during daytime hours. The GBNP-CNN F1 score was 75%, largely due to the model’s confusion of vessel noise with harbor seal roars. Therefore, NFI lengths should be considered minimum estimates, but the errors do not qualitatively affect diurnal or seasonal patterns. In 2018, mean daytime NFI during peak tourism months (June–August) was less than half the duration compared to May and September (1.3 min vs. 2.9 min). In 2020, when large-vessel tourism was substantially reduced but small-craft activity continued, we found that HP decreased in June–August. In conjunction with other soundscape metrics, monitoring NFI trends using ML models such as GBNP-CNN will provide crucial information for management and conservation of acoustic habitats and sensitive species in GBNP.
The NOAA-NPS Ocean Noise Reference Station Network (NRS) is a passive acoustic monitoring effort to record the low-frequency (<2 kHz) sound field throughout the U.S. Exclusive Economic Zone. Data ...collection began in 2014 and spans 12 acoustic recording locations. To date, NRS datasets have been analyzed to understand spatial variation of large-scale sound levels, however, assessment of specific sound sources is an area where these datasets can provide additional insights. To understand seasonal patterns of blue whale,
Balaenoptera musculus
, and fin whale,
B. physalus
, sound production in the eastern North Pacific Ocean, this study explored data recorded between 2014 and 2020 from four NRS recording sites. A call index (CI) was used to quantify the intensity of blue whale B calls and fin whale 20 Hz pulses. Diel and seasonal patterns were then determined in the context of their migratory patterns. Most sites shared similar patterns in blue whale CI: persistent acoustic presence for 4–5 months starting by August and ending by February with a CI maximum in October or November. Fin whale patterns included persistent acoustic presence for 5–7 months starting by October and ending before April with a CI maximum between October and December. The diel patterning of blue whale song varied across the sites with the Gulf of Alaska, Olympic Coast, Cordell Bank, and Channel Islands (2014–2015) exhibiting a tendency towards nighttime song detection. However, this diel pattern was not observed at Channel Islands (2018–2020). Fin whale song detection was distributed evenly across day and night at most recording sites and months, however, a tendency toward nighttime song detection was observed in Cordell Bank during fall, and Gulf of Alaska and Olympic Coast during spring. Understanding call and migration patterns for blue and fin whales is essential for conservation efforts. By using passive acoustic monitoring and efficient detection methods, such as CI, it is possible to process large amounts of bioacoustic data and better understand the migratory behaviors of endangered marine species.
PDF
