Page 44 - Acoustics Today

used to obtain a (left-right ambiguous) localization—this is then amenable to analysis using a different flavor of distance sampling called line transect analysis—see, e.g., Lewis et al. (2007).
There are many possible applications in the terrestrial environment, where animals are hard to see but easier to hear. Examples include forest elephants, gibbons and frogs.
Future directions
Currently, few surveys are designed with passive acoustic density estimation in mind. All of the above case studies made use of data originally gathered for other purposes. One example of a designed survey is the SAMBAH project7 where around 300 autonomous detectors have been deployed on a random grid of locations throughout the Baltic Sea with the goal of yielding an abundance estimate of the extremely low- density population of harbor porpoise resident there. Fixed passive acoustic methods are potentially highly cost-effective compared with other methods for long-term monitoring programs, because costs are relatively low after initial set up. Hence we expect to see increasing uptake where long-term monitoring is required, such as over the lifetime of oil pro- duction fields.
We have shown that the methods work best when a large number of sensors can be distributed through the survey area, and where at least a subset collect auxiliary information such as distances to detected sounds. There is great potential for the development of inexpensive commercial hardware and associated algorithms and software to facilitate this.
There are plenty of statistical developments left to pur- sue, including methods for combining different sources of information to estimate detectability better, methods for sen- sors that use adaptive duty-cycling to increase their longevi- ty and optimal survey design.
Lastly, improvements in our knowledge of the acoustic biology of animal species, coupled with advances in our abil- ity to detect, classify and localize sounds, will make passive acoustic density estimation ever more feasible in a wider variety of situations.AT
Endnotes
1 For example, our research group at St. Andrews develops free software, Distance, which can be used to design and analyze dis- tance sampling surveys. The program has acquired over 26,000 registered users covering all major taxa since the windows-based version was released 13 years ago—see http:// www.ruwpa.st- and.ac.uk/distance/
2 DECAF stands for Density Estimation for Cetaceans from Acoustic Fixed Sensors. The project ran from 2007–2011 and was funded under the National Oceanographic Partnership Program jointly by the Ocean Acoustics Program of the US National Marine Fisheries Service, Office of Protected Resources and the Joint Industry Program of the International Association of Oil and Gas Producers on Sound and Marine Life. In addition to the other team members, we also thank the project steering commit- tee for their assistance: Jay Barlow (National Marine Fisheries Service), Stephen Buckland (University of St. Andrews) and Walter Zimmer (NATO Undersea Research Center). All project outputs are available at http:// www.creem.st-and.ac.uk/decaf/. Our work in this area is also supported by the US Navy, Chief of
Naval Operations, Energy and Environmental Readiness
Division (Code N45).
3 We omit all details of the acoustic processing techniques
required to yield the raw materials for density estimation: the detected and classified (and in some cases associated and local- ized) vocalizations. Other articles in this issue describe some of the work in this area, as does an article from last year (Tiemann et al., 2011). Recent reference texts are Zimmer (2011) and Au and Hastings (2009).
4 The CV on a quantity that is the product of a set of independent random quantities can be calculated using the “delta method,” which just involves adding the squared CVs of each of the inde- pendent quantities—see e.g., Marques et al. (2009).
5 This is something of an over-simplification. DTAG data alone yields an imprecise “pseudotrack,” which needs to be combined with positions estimated from, e.g., acoustic localization to give a useable track—see Ward et al. (2008) and references therein for details.
6 The newer versions are called C-PODs; they are manufactured by Chelonia Limited (www.chelonia.co.uk).
7 Static Acoustic Monitoring of Baltic Sea Harbour Porpoise—see www.sambah.org.
References
Au, W. W. L., and Hastings, M. C. (2009). Principles of Marine Bioacoustics (Springer, New York).
Baggenstoss, P. M. (2011). “An algorithm for the localization of multiple interfering sperm whales using multi-sensor time dif- ference of arrival,” J. Acoust. Soc. Am. 130, 102–112.
Buckland, S. T., Anderson, D. R., Burnham, K. P., Laake, J. L., Borchers, D. L., and Thomas, L. (2001). Introduction to Distance sampling–Estimating Abundance of Biological Populations (Oxford University Press, Oxford).
Buckland, S. T., Burt, M. L., Rexstad, E. A., Mellor, M., Williams, A. E.. and Woodward, R. (2012). “Aerial surveys of seabirds: The advent of digital methods,” J. Appl. Ecol. 49, 960–967.
D’Amico, A., Gisiner, R. C., Ketten, D. R., Hammock, J. A., Johnson, C., Tyack P. L., and Mead, J. (2009). “Beaked whale strandings and naval exercises,” Aquatic Mammals 35, 452–472.
Küsel, E. T., Mellinger, D. K., Thomas, L., Marques, T. A., Moretti, D., and Ward, J. (2011). “Cetacean population density estimation from single fixed sensors using passive acoustics,” J. Acoust. Soc. Am. 129, 3610–3622.
Kyhn, L., Tougaard, J., Thomas, L., Duve, L., Steinback, J., Amundin, M., Desportes, G., and Teilmann, J. (2012). “From echolocation clicks to animal density–Acoustic sampling of har- bour porpoises with static dataloggers,” J. Acoust. Soc. Am. 131, 550–560.
Lewis, T., Gillespie, D., Lacey, C., Matthews, J., Danbolt, M., Leaper, R., McLanaghan, R., and Moscrop, A. (2007). “Sperm whale abundance estimates from acoustic surveys of the Ionian Sea and Straits of Sicily in 2003,” J. Marine Biol. Assn. of the UK 87, 353–357.
Marques, T. A., Munger, L., Thomas, L., Wiggins, S., and Hildebrand, J. A. (2011). “Estimating North Pacific right whale (Eubalaena japonica) density using passive acoustic cue count- ing,” Endangered Species Res. 13, 163–172.
Marques, T. A., Thomas, L., Ward, J., DiMarzio, N., and Tyack, P. L. (2009). “Estimating cetacean population density using fixed pas- sive acoustic sensors: An example with Blainville”s beaked whales,” J. Acoust. Soc. Am. 125, 1982–1994.
Martin, S. W., Marques, T. A., Thomas, L., Morrissey, R. P., Jarvis, S., DiMarzio, N., Moretti, D., and Mellinger, D. K. (in press, 2012). “Estimating minke whale (Balaenoptera acutorostrata) boing
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