|Site specific probability of passive acoustic detection of humpback whale calls from single fixed hydrophones|Helble, T.A.; D'Spain, G.L.; Hildebrand, J.A.; Campbell, G.S.; Campbell, R.L.; Heaney, K.D. (2013). Site specific probability of passive acoustic detection of humpback whale calls from single fixed hydrophones. J. Acoust. Soc. Am. 134: 2556-2570. hdl.handle.net/10.1121/1.4816581
In: Journal of the Acoustical Society of America. American Institute of Physics: New York, etc.. ISSN 0001-4966, more
Acoustic sensing Plucked stringed instruments Acoustic noise Agroacoustics Acoustic modeling Speed of sound Oceans Acoustical properties Bathymetry Marine vehicle noise
|Authors|| || Top |
- Helble, T.A.
- D'Spain, G.L.
- Hildebrand, J.A.
- Campbell, G.S.
- Campbell, R.L.
- Heaney, K.D.
Passive acoustic monitoring of marine mammal calls is an increasingly important method for assessing population numbers, distribution, and behavior. A common mistake in the analysis of marine mammal acoustic data is formulating conclusions about these animals without first understanding how environmental properties such as bathymetry, sediment properties, water column sound speed, and ocean acoustic noise influence the detection and character of vocalizations in the acoustic data. The approach in this paper is to use Monte Carlo simulations with a full wave field acoustic propagation model to characterize the site specific probability of detection of six types of humpback whale calls at three passive acoustic monitoring locations off the California coast. Results show that the probability of detection can vary by factors greater than ten when comparing detections across locations, or comparing detections at the same location over time, due to environmental effects. Effects of uncertainties in the inputs to the propagation model are also quantified, and the model accuracy is assessed by comparing calling statistics amassed from 24?690 humpback units recorded in the month of October 2008. Under certain conditions, the probability of detection can be estimated with uncertainties sufficiently small to allow for accurate density estimates.