DCLDE Workshops are intended for exchanging information that advances our understanding of acoustic methods to detect, classify, locate, track, count, and monitor marine mammals in their natural environment. The goal is to encourage interdisciplinary approaches to solve real-world problems related to the study of marine mammals and the effects of human activities. The DCLDE 2015 dataset consists of data from multiple deployments of high-frequency acoustic recording packages deployed in the Southern California Bight. Separate sets of development data are provided for mysticetes and odontocetes. The mysticete data have been decimated to 1 and 1.6 kHz bandwidth and the odontocete data bandwidth consists of data with 100 and 160 kHz of bandwidth. Data were selected to cover all four seasons and from multiple locations. High-frequency datasets consist of annotated data from multiple odontocete species. Included is Baird’s beaked whale (Berardius bairdii), Cuvier’s beaked whale (Ziphius cavirostris), Sperm whale (Physeter macrorhynchus), Pacific white-sided dolphin (Lagenorhynchus obliquidens), Risso’s dolphin (Grampus griseus), unspecified porpoise (Phocoenidae), and odontocete other than those described above (Odontoceti). The goal for this dataset is to identify acoustic encounters of a species during times when animals were echolocating. Low-frequency datasets consist of annotated data for specific calls from two mysticete species, blue whale (Balaenoptera musculus) D calls and fin whale (Balaenoptera physalus) 40 Hz calls. The goal for this dataset is to identify specific blue whale D and fin whale 40 Hz calls.

DCLDE Workshops are intended for exchanging information that advances our understanding of acoustic methods to detect, classify, locate, track, count, and monitor marine mammals in their natural environment. The goal is to encourage interdisciplinary approaches to solve real-world problems related to the study of marine mammals and the effects of human activities. These DCLDE 2018 workshop datasets were provided by the Scripps Institution of Oceanography. They consist of acoustic recordings from multiple deployments of high-frequency acoustic recording packages deployed in the Western North Atlantic (US EEZ) and Gulf of Mexico. Separate sets of development data are provided for mysticetes and odontocetes. The mysticete data have been decimated to 1 kHz bandwidth (2 kHz sample rate) and the odontocete data have 100 kHz of bandwidth (200 kHz sample rate). Data were selected to cover multiple seasons and locations while providing high species diversity and call counts.

This dataset is a compilation of 1 week of acoustic data, collected in the Stellwagen Bank National Marine Sanctuary within the Western North Atlantic Ocean. The dataset was manually annotated for the presence of North Atlantic right whale upcalls and was originally part of the 2013 DCLDE (Detection, Classification, Localization, and Density Estimation) conference datasets, and was recently re-analyzed so all log files were from the same site (site 10, corresponds to channel 10 in multichannel data files) for the entire week of data. Each day of data was manually browsed in Raven 1.5, and all North Atlantic right whale upcalls were logged (for multichannel data, only one channel was analyzed and logged: the channel logged is indicated in the corresponding csv file). In the "Detection_Confidence" field, a definite upcall is marked as "Detected"; Possible or unknown detections ( i.e. a call could not be definitely attributed to a North Atlantic right whale), is marked as "Possibly_Detected". Acoustic data and analysis provided by NOAA Northeast Fisheries Science Center's Passive Acoustic Research group; upcall logs annotated by Nicole Pegg.

The DCLDE Oahu dataset consists of a subset of passive acoustic data collected using a multi-channeltowed hydrophone array during the Hawaiian Islands Cetacean and Ecosystem Assessment Survey(HICEAS) in 2017. HICEAS was a visual and passive acoustic survey using line-transect methods. Thesurvey took place from July through November of 2017 using two research vessels that systematicallysurveyed the entire Hawaiian Exclusive Economic Zone (EEZ).

The project collected three years of baseline data 12 - 60 km offshore of Maryland prior to construction and operation of an offshore wind energy facility. Two main types of sound recording devices that encompassed a range of frequencies were used to detect vocalizations from baleen whales (low frequencies) and toothed whales (high frequencies): the Marine Autonomous Recording Unit (MARU, or pop-up) sampling at 2 kHz and the C-POD (cetacean click detector), which monitors the 20 - 160 kHz frequency range. These were supplemented by additional acoustic recorders during select periods of the study at five sites to provide further information on mid-frequency sounds, such as dolphin whistling behavior. The use of a grid array design for the acoustic detection devices within the Maryland WEA facilitated localization of vocalizing whales to further understand spatial patterns of habitat usage. RESULTS: There is substantial overlap between marine mammals and the Maryland WEA, but this varies seasonally. While the risk to endangered whales is lowest during the summer, the risk to bottlenose dolphins may be highest at this time, as they are most abundant in the summer time. The year-round occurrence of marine mammals offshore of Maryland will require decision-makers to consider the trade-off of the potential impacts

Passive acoustic monitoring recorders were deployed off the coast of Virginia to collect two years of acoustic data from 2015 - 2017 to determine the acoustic presence of four focal whale species: North Atlantic right whale (Eubalaena glacialis), minke whale (Balaenoptera acutorostrata), fin whale (Balaenoptera physalus) and humpback whale (Megaptera novaeangliae). Previously collected acoustic data from 2012, 2013 and 2015 supplemented the dataset and both seasonal and annual trends in temporal and spatial distribution were found for all four species of baleen whales. Baseline ambient noise measurements were analyzed to provide context for potential risks to whales associated with the construction and development in the offshore wind energy area. In addition, spatial and temporal trends in odontocete presence were analyzed. Offshore wind energy development in coastal Virginia waters may pose risks to marine mammals that use the habitat, both through acute risks of ship-strikes or construction-related activities such as pile driving, and chronic risks from increased exposure to noise. Passive acoustic monitoring can provide insight into the spatial and temporal distribution of whale species in the study area and can characterize the baseline ambient noise of the environment to assess potential risks to marine mammals.

Passive acoustic monitoring recorders were deployed off the coast of Virginia to collect two years of acoustic data from 2015 - 2017 to determine the acoustic presence of four focal whale species: North Atlantic right whale (Eubalaena glacialis), minke whale (Balaenoptera acutorostrata), fin whale (Balaenoptera physalus) and humpback whale (Megaptera novaeangliae). Previously collected acoustic data from 2012, 2013 and 2015 supplemented the dataset and both seasonal and annual trends in temporal and spatial distribution were found for all four species of baleen whales. Baseline ambient noise measurements were analyzed to provide context for potential risks to whales associated with the construction and development in the offshore wind energy area. In addition, spatial and temporal trends in odontocete presence were analyzed. Offshore wind energy development in coastal Virginia waters may pose risks to marine mammals that use the habitat, both through acute risks of ship-strikes or construction-related activities such as pile driving, and chronic risks from increased exposure to noise. Passive acoustic monitoring can provide insight into the spatial and temporal distribution of whale species in the study area and can characterize the baseline ambient noise of the environment to assess potential risks to marine mammals.

The North Carolina Renewable Ocean Energy Program (NCROEP) is evaluating the feasibility of extracting energy from the Gulf Stream off the coast of Cape Hatteras, North Carolina, USA. Characterizing the soundscape in this region is one of the environmental and ecological assessment goals of the program. To accomplish this, the UNC Coastal Studies Institute deploys a mooring on the continental slope off Cape Hatteras. The mooring is equipped with a hydrophone, a CTD, and an Acoustic Doppler Current Profiler (ADCP). To request ancillary data (CTD, ADCP), contact Dr. Lindsay Dubbs.

To understand natural and anthropogenic sound in the ocean, and to compare underwater soundscapes globally, standard methods of analysis must be applied to passive acoustic monitoring (PAM) data. Methods that balance constrained volume and adequate resolution of acoustic spectra have recently been published (Martin et al., 2021a,b). A community effort supported by NOAA, BOEM, U.S. Navy, and ONR was initiated to apply these methods to PAM datasets from around the world. These records are hybrid millidecade (HMD) spectra of sound levels derived from calibrated passive acoustic data. Daily HMD at 1 minute resolution were created using standalone MANTA software (v9.6.12) from audio data recorded at BOEM-Cornell sites.

To understand natural and anthropogenic sound in the ocean, and to compare underwater soundscapes globally, standard methods of analysis must be applied to passive acoustic monitoring (PAM) data. Methods that balance constrained volume and adequate resolution of acoustic spectra have recently been published (Martin et al., 2021a,b). A community effort supported by NOAA, BOEM, U.S. Navy, and ONR was initiated to apply these methods to PAM datasets from around the world. These data are hybrid millidecade (HMD) spectra of sound levels derived from calibrated passive acoustic data. Daily HMD at 1 minute resolution were created using standalone MANTA software (v9.6.13) from audio data recorded by the SanctSound monitoring project at various sites.