Source levels of fin whale calls can be used to determine range to recorded vocalizations and to model maximum communication range between animals. In this study, source levels of fin whale calls were estimated using data collected on a network of eight ocean bottom seismometers in the Northeast Pacific Ocean. The acoustic pressure levels measured at the instruments were adjusted for the propagation path between the calling whales and the instruments using the call location and estimating losses along the acoustic travel path. A total of 1241 calls were used to estimate an average source level of 189 ± 5.8 dB re 1μPa at 1 m. This variability is largely attributed to uncertainties in the horizontal and vertical position of the fin whale at the time of each call and the effect of these uncertainties on subsequent calculations. Variability may also arise from station to station differences within the network. For call sequences produced by a single vocalizing whale, no consistent increase or decrease in source level was observed over the duration of a dive. Calls within these sequences that immediately followed gaps of 27 s or longer were classified as backbeat calls and were consistently lower in both frequency and amplitude.

Fin whale calls recorded from 2003 to 2004 by a seafloor seismic network on the Endeavour segment of the Juan de Fuca Ridge were analyzed to determine tracks and calling patterns. Over 150 tracks were obtained with a total duration of ~800 h and swimming speeds from 1 to 12 km/h. The dominant inter-pulse interval (IPI) is 24 s and the IPI patterns define 4 categories: a 25 s single IPI and 24/30 s dual IPI produced by single calling whales, a 24/13 s dual IPI interpreted as two calling whales, and an irregular IPI interpreted as groups of calling whales. There are also tracks in which the IPI switches between categories. Call rates vary seasonally with all the tracks between August and April. From August to October tracks are dominated by the irregular IPI and are predominantly headed to the northwest, suggesting that a portion of the fin whale population does not migrate south in the fall. The other IPI categories occur primarily from November to March. These tracks have slower swimming speeds, tend to meander, and are predominantly to the south. The distribution of fin whales around the network is non-random with more calls near the network and to the east and north.

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A model of crustal thickness and lower crustal velocities is obtained for crustal ages of 0.1–1.2 Ma on the Endeavour Segment of the Juan de Fuca Ridge by inverting travel times of crustal paths and non‐ridge‐crossing wide‐angle Moho reflections obtained from a three‐dimensional tomographic experiment. The crust is thicker by 0.5–1 km beneath a 200 m high plateau that extends across the segment center. This feature is consistent with the influence of the proposed Heckle melt anomaly on the spreading center. The history of ridge propagation on the Cobb overlapping spreading center may also have influenced the formation of the plateau. The sharp boundaries of the plateau and crustal thickness anomaly suggest that melt transport is predominantly upward in the crust. Lower crustal velocities are lower at the ends of the segment, likely due to increased hydrothermal alteration in regions influenced by overlapping spreading centers, and possibly increased magmatic differentiation.

Analysis and synthesis of large and complex datasets are increasingly important components of scientific research. To expose undergraduate students to these datasets and to develop valuable data analysis skills, a team of environmental scientists and education researchers created Project EDDIE (Environmental Data-Driven Inquiry and Exploration). Project EDDIE is a pedagogical collaborative that develops and assesses flexible modules that use publicly-available, large datasets that allow students to explore a range of concepts in the biological, earth, and environmental sciences. Modules have been implemented in a range of courses, class sizes, and institutions. We assessed six modules over eight courses, which were taught to total of 1,380 students. EDDIE modules led to significant improvements in students' competence using spreadsheet software and as well as their conceptual understanding of how to use large complex datasets to address scientific problems. Furthermore, students reported positive and informative experiences using large datasets to explore open-ended questions.

Ocean observing systems are well-recognized as platforms for long-term monitoring of near-shore and remote locations in the global ocean. High-quality observatory data is freely available and accessible to all members of the global oceanographic community—a democratization of data that is particularly useful for early career scientists (ECS), enabling ECS to conduct research independent of traditional funding models or access to laboratory and field equipment. The concurrent collection of distinct data types with relevance for oceanographic disciplines including physics, chemistry, biology, and geology yields a unique incubator for cutting-edge, timely, interdisciplinary research. These data are both an opportunity and an incentive for ECS to develop the computational skills and collaborative relationships necessary to interpret large data sets. Here, we use observatory data to demonstrate the potential for these interdisciplinary approaches by presenting a case study on the water-column response to anomalous atmospheric events (i.e., major storms) on the shelf of the Mid-Atlantic Bight southwest of Cape Cod, United States. Using data from the Ocean Observatories Initiative (OOI) Pioneer Array, we applied a simple data mining method to identify anomalous atmospheric events over a four-year period. Two closely occurring storm events in late 2018 were then selected to explore the dynamics of water-column response using mooring data from across the array. The comprehensive ECS knowledge base and computational skill sets allowed identification of data issues in the OOI data streams and technologically sound characterization of data from multiple sensor packages to broadly characterize ocean-atmosphere interactions. An ECS-driven approach that emphasizes collaborative and interdisciplinary working practices adds significant value to existing datasets and programs such as OOI and has the potential to produce meaningful scientific advances. Future success in utilizing ocean observatory data requires continued investment in ECS education, collaboration, and research; in turn, the ECS community provides feedback, develops knowledge, and builds new tools to enhance the value of ocean observing systems. These findings present an argument for building a community of practice to augment ECS ocean scientist skills and foster collaborations to extend the context, reach, and societal utility of ocean science.

A large number of fin whale calls have been observed in a 3-year ocean bottom seismometer dataset (2003–2006) over the Endeavor Ridge (48°N/129°W), a hydrothermally active area in the Northeast Pacific Ocean. Most of the vocalizations were detected during the winter months. Because zooplankton constitute an important part of fin whales’ diets, and enhanced populations of zooplankton have been observed at all depths above the Endeavor hydrothermal vents, it has been hypothesized that the fin whales could be near the vents specifically for feeding. As part of the analysis of the Endeavor vent field data set, algorithms have been developed, which utilize the absolute and relative spectral energy levels in the frequency band of the whale vocalizations. In order to test whether the concentrations of whale vocalizations are unusually high over the hydrothermally active area, the detection algorithm is being applied to data from individual ocean bottom seismometers at other nearby locations including the center of Explorer Plate (49.5°N, 129°W), and the base of the continental slope off Nootka Sound (49.3°N, 127.6°W).

Using authentic data from NSF's Ocean Observatories Initiative in undergraduate teaching: An invitation.