MARU data were used to characterize temporal and spatial variation in sanctuary sound levels
24 hour spectrogram of sound at five locations near the shipping lane. Note peaks in noise associated with ships transiting the sanctuary, with noise dominating low frequency bandwidths (<1000 Hz) used by baleen whales.
Acoustic data from MARUs were also used to detect vocalizing whales (identified by the species-specific characteristics of their vocalizations) and calculate distributions and acoustic densities for different species in sanctuary waters throughout the year. These results were integrated to begin to quantify the areas and time periods over which whale vocalizations may be “masked” by ambient or background noise within sanctuary waters.
Temporal variation in the distribution of North Atlantic right whale “up-calls” within the sanctuary.
To begin to estimate the noise contributions made by different source types to the sanctuary, acoustic data were integrated with data from the US Coast Guard’s Automated Identification System (AIS). The AIS is a ship tracking system that provides information as often as every 2 seconds on the location, speed and identity of large commercial or ocean-going traffic. Through collaboration with the US Coast Guard’s Research and Development Center and the University of New Hampshire’s Center for Coastal and Ocean Mapping, data from all AIS-transmitting vessels in greater sanctuary waters were archived and used to analyze the distributions of vessels in the sanctuary.
Density of two months of large commercial vessel traffic in the sanctuary, with peak densities seen in the shipping lanes.
AIS and MARU data were integrated both to match recorded acoustic signatures with vessel sources and to examine the relationships between shipping traffic patterns and variability in the sanctuary’s underwater noise budget.
The kriged acoustic footprint of a container ship at its closest point of approach (CPA) to an Marine Autonomous Recording Unit (MARU) in the array (labeled dots). The color scale, from blue (low) to red (high), represents interpolated received levels in the 71 to 141 Hz bandwidth at each location (dB re 1 µPa), based on an average of three received level estimates taken at each MARU location (1-s peak, 10-s peak, and 5-min root mean square). The blue rectangle represents the Boston Traffic Separation Scheme in 2006, and the pink circles represent the track of the vessel through the sampling region.
This study found the SBNMS to be a dynamic acoustic landscape with significant peaks and troughs in the relative intensity of sound within frequency bandwidths important to the communication capabilities of resident species. Received level estimates were found to be within the range of those reported for areas where increasing commercial shipping has been invoked as a possible determinant of rising ocean low-frequency noise and were significantly, positively related to the number of AIS-tracked vessels closely approaching the recording units. Initial estimates found tankers to contribute the most noise to the sanctuary’s annual low-frequency noise budget, though relative contributions varied both spatially and temporally. Financial support for this research was provided by NOAA NOS’s National Marine Sanctuary Program, NOAA Fisheries’ Northeast Fisheries Science Center and Northeast Regional Office, the National Marine Sanctuary Foundation, the International Fund for Animal Welfare and the Massachusetts Environmental Trust.
For more information on this study see
Hatch, L.T., Clark, C.W., Merrick, R., Van Parijs, S., Ponirakis, D., Schwehr, K., Thompson, M. & Wiley, D. (2008). Characterizing the relative contributions of large vessels to total ocean noise fields: a case study using the Gerry E. Studds Stellwagen Bank National Marine Sanctuary. Environmental Management. Click here.
Hatch, L. T., C. W. Clark, R. Merrick, S. M. Van Parijs, D. Ponirakis, K. Schwehr, M. Thompson, and D. Wiley. 2009. Erratum to: characterizing the relative contributions of large vessels to total ocean noise fields: a case study using the Gerry E. Studds Stellwagen Bank National Marine Sanctuary. Environmental Management 44:998-999. Click here