PassiveDetection andLocalization ofTransient Signals from Marine Mammals usingWidely SpacedBottom Mounted Hydrophonesin Open Ocean Environments

Susan 3arvis and David Moretti NavalUndersea Warfare Center Division NewportEngineering,Test and EvaluationDepartment 1'I 76 Howell St., Newport, R.l. 02841-1708

Abstract Oneobjective of the MarineMammal Monitoring on NavyRanges project is to useexisting Navy undersearange infrastructure to develop a toolset for passivedetection and localization of marine mammals.The Office of NavalResearch funded the M3Rproject as part of the Navy'seffort to deter- mine the effects of acoustic emissionson marine mammalsand threatened/ endangeredspecies. A necessaryfirst step in this effort is the creationof a baselineof behaviorwhich requires long-term monitoringof marinemammals. Such monitoring, in turn, requiresthe abilityto detectand localize the animals,This paper will present algorithms for passivedetection and localizationof transient signalsdeveloped as part of the M3Rtoolset. It wiII also present results of the application of these tools to detection and tracking of various toothed whales at the Atlantic UnderseaTest and Evaluation Center AUTEC!, Andros Island, Bahamas.

Introduction

Navy undersearanges such as the Atlantic UnderseaTest and EvaiuationCenter AUTEC!use arrays of widely spaced bottom mounted hydrophonesto acousticallytrack underseaand surfacevehicles. Traditionally,the vehiclesare equipped with acousticpingers that emit knownidentification signals at knownrepetition rates. Increasingly, range instrumentation infrastructure Figure 1! is being appliedto non-traditionaltracking problems, The Marine Mammal Monitoring on NavyUndersea Ranges M3R!program has developed a set of signal processingtools to detect and track marine mammalsusing Navy range facilities [11. Under the M3Rprogram, algorithms were developed to automatically detect and track two classes of whale vocalizations clicks and whisties. Both of these classesof signals are transient in nature. The tool set was recently tested at AUTECover a two- weekperiod. Over five hundredsquare nautical miles of oceanwere simultaneously monitored via 68 broad-bandhydrophones. Several species of toothedwhales where automatically detected and trackedin real-time.The positionalaccuracy of the M3Rtracking tools was confirmed by visual sightings by a surfacecraft and by manual analysisof the hydrophone data.

Proceedingsfrom the international workshop on the Applications of PassiveAcoustics to Fisheries 123 Discussion Visualsightings [2] and auralanalysis of hydrophonerecordings [3] indicatethat manyspecies of toothed whalesare presentat AUTEC.The mostcommonly seen and heardare spermwhales, dol- phinsand short finned pilot whales,all of whichare present nearly year round. Consequently,the M3Rtools weredeveloped to detect and trackthese common species. For purposes of algorithm development, the vocaiizations produced by the whales were characterizedas clicks and whistles. Clicksare, in general,any impulsive,broad-band signal. However, sperm whale clicks were of partic- ular interest.Sperm whale clicks are very distinct,have high sourcelevel, and occurin regularpat- terns [4] or "clicktrains" Figure2!, Whistles were more broadly defined as any narrowbandevent that sweepsin frequencyover time Figure3!.

Thereare three distinct partsto the whale localizationproblem. First the vocalizationsor whale callsmust be automaticallydetected. In orderto determinethe positionof the animalin three dimensions,a givencall mustbe detectedon a minimumof four hydrophones.The second part of the problemis the associationof the detectionsreceived on varioushydrophones with eachother. Thatis, one must be able to determinethat the call received on hydrophone A at time tA is the samesignal that wasreceived by hydrophone B attime tB. Finally, associated sets of arrivaltimes areinput into a multilaterationalgorithm to solvefor position.A three-dimensionalhyperbolic posi- tioning model [5] is usedto determinethe vocalizinganimal's location in X,Y, and Z aswell asthe time of emission of the call.

M3Remploys a real-timefrequency domain energy detector for whalecall detection. A spectrogram of the incomingacoustic data from each of thehydrophones isformed using 512-point fast Fourier transforms FFT! with a rectangularwindow and fifty percentoverlap. The resultant spectrogram hasa frequencyresolution of approximately51 Hzand a timeresolution of approximately9.8 ms. Eachtime-frequency bin of the spectrogramis comparedto a timevarying threshold, D f t!. The thresholdis set to be m dBabove the time! averagepower within frequencybin f.The output of the detector,Q~ t!,f for eachhydrophone, is a binaryvalued "detection spectrogram" which contains a 1 in eachtime-frequency bin that exceededD f t! anda 0everywhere else Figure4!. The detection spectrogramindicates, in real-time,the presenceof whalevocalizations as well asproviding infor- mationon their frequencycontent. As evidentin Figures2 and3, the signalstructure of sperm whale!clicks is very differentfrom the signalstructure of whistles.Therefore, separate detection associationalgorithms were developed for eachsignal type.

A seriesof clicks from a single sperm whale exhibits nearly the same inter-click interval on ail receiv- ing hydrophones.Calls from eachadditional animal exhibit their own uniquepattern. In fact,inter- clickinterval patterns were found to be an effectivemeans of both differentiatingbetween individ- ualwhales and associatingpatterns of detectionsamong hydrophones [6]. In the first stepof the M3Rclick association algorithm the time-frequencydetection spectra from all hydrophoneswere reduced to binary "click maps".Click maps contain a 1 for time indices where broad band events occurredin the detectionspectrum and 0 forall other times Figure 5!. Conceptually,the next step is to crosscorrelate the clickmaps from severalhydrophones with a masterhydrophone to Findthe difference in time of arrival between each hydrophone and the master. However,care must be

Proceedingsfrom the international Workshop on the Applications of PassiveAcovstics to Rsheries 124 taken in implementing the crosscorrelation in order to properly associateeach click detection amongthe hydrophones.Figure 6a showsan exampleof a clickmap from a singlehydrophone containingclicks from two individuals,Figure 6b showsthe clickmap from a secondhydrophone overthe sametime period.The question is which clicksin figure6b belongto whichindividual?

TheM3R click association algorithm uses the notionof a "scanningsieve" [7] to matchdetection pat- ternsbetween hydrophones. The sequence of cilickdetections i.e. click map! within the scanning sieveon the masterchannel is comparedto the clicksmaps from surroundinghydrophones "scanned"signals!. The scanning sieve time window always starts on a click detection, and is moved acrossthe scannedsignal one click detection at a time, That is,the resultant correlation valueat anytime delayrepresents the numberof matchesbetween the masterchannel pattern startinga specificclick and the scannedchannel pattern starting at a specificclick, The delay of the rnaxirnum correlation value represents the difference in time of arrival where the first clicks in the scanningsieve and the scannedsignal were best aligned. The output of the scanningsieve process are sets of time difference of arrival TDOA! for each click detection received on the master channe! Figure7!. TheTDOA data from eachhydrophone are then histogrammedto estimatethe number of separablesources Figure 8!, Onlydetections associated with significantpopulations are used Figure9!. Theseassociated TDOA sets are then sentto the AUTECmultilateration tracking algo- rithm which calculates3D position.

Whistle vocalizations do not typically follow known repetition patterns. An individual can emit a single short whistle or groups of sweepsthat last severalseconds or both. However,the time-fre- quency characteristicsof the calls in whatever sequencethey may occur remain the same on all receivinghydrophones. To determine the TDOAof signalsamong the hydrophones,the detection spectrogramsQ f t! of the availablehydrophones are cross-correlated against a masterchannel, M [8].The cross correlation C tg between the i-th channel and the masterchannel is calculatedover a time window of approximately6 to 10 seconds.That time windowis then advancedby onehalf its duration and Ci tg is updated,

Ci t,x!=ZZQ~ f,t!Qi f,t+~!

Thetime delayassociated with the peakof the correlationfunctions indicates the TDOAfor a signal relativeto the masterhydrophone Figure 10a!. If whistlesfrom multiplewhales are presentwithin a crosscorrelation time window,multiple correlation peaks will be evident Figure10b!. Note that if both clicksand whistlesare present at the sametime, sperm whale clicks will dominatethe detec- tion spectra.Correlation peaks due to whistlesignals will be obscured.Therefore, for practicalpur- poses,broad-band click events should be removedfrom the detectionspectra prior to crosscorrela- tion.

Whilecross correlation of detectionspectra indicates times of signalarrival and the presenceof multiplewhales, it doesnot associatethe time delaysof the correlationpeaks with an individual acrossthe hydrophonechannels. However, as mentionedearly, the sequenceof whistlesfrom an individualis the sameon all receivinghydrophones. Figure 11 shows the time differencesof arrival relative to a master hydrophone of the correlation peaksfor five hydrophones. Notice that there are

Proceedingsfrom the internationalWorkshop on the Appiicationsof PassiveAcoustics to Fisheries 125 two distinctpatterns of detectionsversus time along specific time delays. Matching these patterns alongtime delaysassociates the TDOA'samong the hydrophoneswith an individualwhale.

Associatedsets of TDOAcan then be the sentto the multilaterationtracking algorithm which calcu- lates 3D position.

Recent Results TheM3R toolset was demonstrated at AUTECas part of a jointexperiment with researchersfrom WoodsHole Oceanographic Institution WHOI!. The WHOI team was testing a newwhale tagging system[9]. TheM3R algorithms were used with sixty-eightof the AUTEChydrophones to monitor over500 sq. NMi. When marine mammals were localized, their positions were relayed to thetagging vessel,which then endeavoredto maneuverclose enough to placea tag.

Thedetection, association and tracking algorithms described in Section2.0 were implemented to runin real-timefor arrays of fiveto sevenhydrophones. Given that there were 68 hydrophones to monitor,other display tools were used to broadlylocate whales before applying the high resolution positioningalgorithm. The Circle display is a Matlabprogram that showsthe numberof detections on eachhydrophone by drawinga circlearound the respectivehydrophone. The number of detec- tions per minuteis mappedto the colorof the circle.Figure 12 showsan exampleof the Circledis- playwhile two groups of whaleswere on the range.The bright circles around Hydrophone 85 were causedby a singleclicking sperm whale. The bright circles around Hydrophone 53 were caused by a groupof pilot whalesjust off the range hydrophones47,48, 54 and55 werenot monitored!.The WHOIteam successfully tagged two of the pilot whalesshortly after this picturewas taken.

Thestrip chart program displays the detection spectrogram from a particularhydrophone in real- time. Theprogram reads the detectiondata from a serverprocess allowing the user to runmultiple chartson multiplecomputers simultaneously. During the AUTECtests this display was quite handy for monitoringphones over a widearea. At varioustimes, both broad sperm whales clicks, and pilot whale clicks and whistles were evident Figure 13!.

Boththe click association and whistle association algorithms worked well during the exercise. Vocalizingwhales were hearcf on rangealmost everyday, At differenttimes, individuals and/or groupsof spermwhales, short finned pilot whales,roughed toothed dolphins,melon headed whalesand even a beakedwhale were all detected and tracked by the M3R algorithms. The track positionsproduced by M3Rwere confirmed by GPSreadings and visual observations from the tag- gingvessel, as well as by manualmonitoring of the hydrophones.Figures 14a-b show an example of real-timeX-Y position and depth plots for a groupof two or threesperm whales. The depth plot indicatesthat thesewhales were likelyperforming deep feeding dives. On somedives monitored duringthe test, sperm whales were tracked at depthsof 1000to 1200m. Figure14c shows the depthtrack for a singlesperm whale that was performing shallow, near-surface dives. Figure 15 showsthe real-timeX-Y position plot for a groupof whistlers,which were later identified by WHOI team members as roughed toothed dolphins and melon headed whales.

Proceedingsfrom the international Workshopon the Applicationsof PassiveAcoustics to Fisheries 126 Summary TheM3R project has developed algorithms for the passivedetection and tracking of marinemam- malsusing widely spaced, bottom-mounted hydrophones characteristic of Navy undersea tracking ranges.While these algorithms have been implemented and testedfor deploymentat the AUTEC, theyare applicable to anyfixed or portablerange that usesrnultilateration tracking algorithms. Potentialranges with the hardware to supportthe M3Rsystem include the Pacific Missile Range Facility,the Southern California Offshore Acoustic Range, and any of theNavy's various portable sys- terns.

TheM3R algorithms have been designed to work in a highlychannelized multi-processor hardware environment,and the softwarearchitecture has been developed to be fully networkcompatible. Signaldetection, and detection-association algorithms for two primarytypes of whalecalls, whistles andclicks, have been developed. These algorithms are specifically designed to beused with widely spacedsensors, and assumethat the marinemammals vocalize repetitively with sufficientsource levelsto be detectedon multiple hydrophones.

TheM3R algorithms, for bothclicks and whistles, have been successfully demonstrated resulting in realtime 3Dtracking of severalspecies of toothed whalesincluding sperm whales, rough toothed dolphins,melon headed whales and pilot whales.The M3Rtool set allows automated collection of datapreviously unavailable for the long-termmonitoring of marinemammal bioacoustics within their naturalenvironment, This opportunity hasbeen created with minimalinvestment in infra- structureby providingNavy ranges as a dual-useasset. Research applications of the M3Rsystem include the ability to remotely estimate marine mammal abundance, assessmentof bioacoustic behavioralbaselines, and evaluationof the impactof anthropogenicnoise compared to thosebase- lines.

Acknowledgements

We would like to acknowledge our sponsor,Dr. Robert Gisiner,at the Office of NavalResearch, for fundingthis project. We would also like to thankthe AUTEC personnel, especially Thomas Szlyk, for accessto their considerableinfrastructure and ongoing support. In addition,we would liketo thank the NUWCDivision Newport ILIR program manager, Richard Philips, for supportingthe initiative to createa baselinesperm whale bioacoustic characterization in the Tongueof the Ocean TOTO!.

References [1] Moretti,D., eI al.,"MarineMammal Monitoring on NavyRanges M3R!", Proceedings of the UnderseaDefenseTechnology Hawaii 2001 Conference,October 2001,

[2] NavalUndersea Warfare Center Detachment AUTEC,"Final Environmental Review, Adoption of a RangeManagement Planfor the Atlantic UnderseaTest and Evaluation Center AUTEC!,Andros

Proceedingsfrom the lnlernationalWorkshop on the Applicationsof PassiveAcoustics to Fisheries 127 Island,Bahamas", p. 57,September 1997,

[3] Perkins,P.J,, "Bioacoustics at AUTEC, Bahamas: A Surveyand Guide",Naval Undersea Systems Center Technical Mernorandurn 87-2018, 1987,

[4] JaquetN., Dawson S., and Douglas L.,"Vocal behavior of malesperm whales; Why do theyclick?", Journalof the AcousticalSociety of America,Vol.109 S!,pp, 2254-2259, 2001.

[5] Vincent,H., "Models, Algorithms, and Measurements for UnderwaterAcoustic Positioning",Ph.D. Dissertation.University of Rhode Island,Kingston, R.I.,2001.

[6] WardJ.,"Sperm Whale Bioacoustic Characterization at the Tongueof the Ocean,Bahamas U!," NUWCDIVNPTTM-01-106, Naval Undersea Warfare Center, Division Newport, Rl, December 2001 Unclassified!.

[7] Hu,Jand H.Vincent,"A Real-Time Multi-Hydrophone Data Association Algorithm for Marine MammalTransient Signals" ,NUWCDIVNPT TM-01-107, Naval Undersea Warfare Center, Division Newport, Rl. December 2001 Unclassified!.

[8] Moretti,D., et al"OpenOcean Marine Mammal Monitoring Using Wideily Spaced Bottom Mounted Hydrophones U!",to appear in Journal of Underwater Acoustics,2002,

[9] Tyack,P., et al.,"Acoustic Response and Detectionof MarineMammals Using and Advanced DigitalAcoustic Recording Tag - C51188",www.serdp.org/reportong/reporting.html.

Proceedingsfrom t'he InternationalWorkshop on the AppIicationsof PassiveAcoustics to Fisheries 128 , ths!f'.Mj Figure1: A JTEChas sixty eight broadband bottom mounted hydrophones with a 2A%i baseline.

6'gure2: Spectrogramshowing sperm whale clicksfrom severalindividuals,

Figure3: Spectrogramshowing a sequenceof whistles probably from a shortfinned pilot whale

proceedings from the inter»ational Yrorkshopon the Application.. of passiveAcoustics to Fisheries 129 Figure4: Detectionspectra-gram, 0 f t!, of whistles.Threshold was set 6-d8 above the average spectrai power.

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Figure5: Clickmaps are formed by summing the detection spectrum above! along frequency then thresholding the sums.The red curveindicatesthe click map for this data.

Proceedingsfrom the internationalIrIrorkshop on the Apph'cationsof'Passive Acoustics to Fisheries 'l 30 tx«««neinal Ala!«Dca«ct«ann!«n. S n«a«an 'Sn««nac I«« .! 1' sinn«an1 ! [ ...... Oa«ncce I I O «11-

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Figure6: Clickmaps for two hydrophonescontaining clicks from twoindividuals. itis not evidentwhich clicks received by hydrophoneB areassociated with Source1 or Source2.

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-5 3820 3840 3860 3880 3900 3920 3940 3960 Time sec!

Figure7: Preliminary output of the M3Rclick associationalgorithm showing the estimated TDOAbetween the scan- ning sieve,hydrophone 61 1,and five additionalhydrophones

Proceedingsfrom the international Workshopon the Applications of PassiveAcoustics to Fisheries '1 31 Figure8: Aboveisthe output of theclick association algorithm for hydrophone6 12 indicated in purpieinfigure 7!, Twoseparate ti mesof arrivalare evidentindicating the presence of 2 whales.A histogramof theTDOA data shows two significantpopulations.

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0 3800 3820 3840 3860 3880 3900 3920 3940 3960 3980 4000 DetectionTime sec!

Figure9i Finaloutput of theclick association algorithm for calls from a singlesperm whole, The points indicate the TDOAat whichthe algorithm found the best matches between the scanning sieve and theclicks maps of hydrophones605, 603,604,612 and 606 relative to masterhydrophone,611, Notice the minimal scatter of theTDOA points.

Proceedingsfrom the International Workshopon the Applications of PassiveAcoustics to Fisheries 132 Figure 10:

a!Resultsof crosscorrelation indicating the TDOAof the signal from one whale.

b!Cross correlation results indicating the TDOA'sof signalsfrom two whales,

TvroW~

Figure1 1;TDOA data resulting from cross correlations of fivehydro phones against a masterhydrophone. Two indi- vidualwhales show two distinct patterns indicated by purple and green boxes! of detectionsversus time along spe- cific TDOA's.

Proceedingsfrom the internationalWorkshop on theApplications of PassiveAcoustics to Fisheries 333 Figure12: Circle detection count display, Maps color of thecircle around a hydrophoneto thenumber of detection per minute.

Figure13: Strip chart displays scroll horizontally todisplay detection spectra for a given hydrophone in realtime. Thetop rightand lowerleft chartsshow sperm whale clicks while the top left and lower right show whistles.

Proceedingsfram the internationalWorkshop an the Applicationsaf PassiveAcoustics ta Fisheries 134 b!

a!

Figure14: Examp!esof position and depth plots for spermwhales.a! Real-timeX-Ydisplay for agroupof2 « or 3individuals. b! Thedepth plot Forthat group. c! A depthplot showing the shallow divesof a singlesperm- whale.

Figure 15:Areal-time X-Y position plot for multiple whistlers.Theicon shapesindicatetheindividuals that the NR toolswere ab!e to identify.This group was observed by researchers aboard the O'HOi whale tagging vessel. The group consistedof more than twenty roughed tootheddolphins and melon headedwhales.

Proceedingsfrom the international Workshopon the Applications of PassiveAcoustics to Fisheries 135 ' Synchronized underwater audio-video recording

Phillip S. Lobel

Boston University Marine Program,Marine Biological Laboratory Woods Hole, MA 02543

Extracted from: Lobel P.S.2001 Fish bioacousticsand behavior:passive acoustic detection and the applicationof a closed-circuitrebreather for field study.Marine Technology Society Journal, 35;19-28

Introduction Oneadvanced technique used in undersearesearch to studyfish acousticbehavior is simplythe interdisciplinary application of established acoustic technology combined with new mini-video camerasand hydrophoneswhile diving with a UBArebreather. Rebreathers and hydrophoneshave beenaround for morethan 40 yearsbut it hasbeen only in the lastdecade that videocameras and hydrophoneshave become miniaturized. Most importantly, these video cameras are equipped with audioinput enablingsynchronous audio-video recording. Acoustic signal analysis is alsogreatly simplifiedby directconnections to advancedportable computers and new soundanalysis software. Evenso, the basicsituation is the samenow aswhen Steinberg and Koczy964! stated,"the prino- ple accomplishmentof the techniquesfor underwaterobservation is that of extendingman's senses of sight and hearing underwater".

Beingable to observeand recordthe sonicbehavior of marineanimals was recognized as an irnpor- tant scientific approach to understanding fish behavior ever since it was first revealedthat sounds wereintegral to behaviorin manyspecies Fish 1954, Griffin 1955, Moulton 1958,Tavolga 1960!. The approach that I usein recording bioacousticswas pioneered in the 1960'sat the LernerMarine Laboratoryin Bimini,Bahamas and during missionsof the underwaterhabitat, TEKTITE. In 1963, a televisionand hydrophonesystem was deployed in about20m depth and linkedby cableto the Lernerlab with a roomfull of electronicequipment for recording see figures in Kronengoldet al, 1964!.This system recorded a varietyof soundsbut the fixedcamera did not usuallycatch the iden- tity of the soundproducer Kumpf1964!. This early system did, however, clearly document several temporalpatterns of distinctivesound production by marineanimals Cummings et al,1964!.This systemwas also used for the playbackof soundsto determinethe effectivenessof pulsedlow fre- quencysounds for attractingsharks and other fishes Richard 1968, Myrberg et al.1969!.Duringthe TEKTITEmissions of 1969, divers used rebreathers from an underwater habitat to record fish sounds usinga Bmmfilm moviecamera and a tape-recorderwith hydrophoneoperated independently but simultaneously Bright 1972!. Bright clearly noted the benefitof the noiselessrebreather when

Proceedingsfrom the InternationalWorkshop on theApplications of PassiveAcoustics to Fisheries 136 recordingfish behavior.The two majoradvances today are 1!advanced video and hydrophonetech- nologyenabling truly synchronousaudio recording in a muchsmaller package! and 2! the increasedreliability of electronic rebreather systems.

Bubble Noise Bubblesnot only producenoisy sounds but alsonear-field vibrations in the water Fig.1,2!. This waterdisturbance is probablysimilar to the hydrodynamicdisturbances produced by fast moving predatorsto which mostfish areespecially sensitive by meansof their lateralline and sensorypore system.The common range of reeffish hearingis roughlybetween 20 and 1000Hz although some hearingspecialist species can hear in rangesup to 10 KHz.Oneherring species can hearat 180KHz Hawkins 1981,Mann et al.1997, Popper and Fay 1998!.However, it is fair to note that some fish apparentlyhabituate to boatand scubanoise, as is seenat somemarine protected areas or other sites with high diver activities.For example, I recently recorded a situation where scubaand exces- siveboat noisedid not affectthe matingactivity of the damselfish,Dascyllus reticulatus in a lagoon Lobel pers.obs., Saipan,July 2000!.

I started recording the acoustic behavior of free ranging fishes in 1988 using open circuit scubaand first generation8mm camcordersconnected to a hydrophone Label 1992!. Because of the scuba bubbles,I hadto spendmany hours per day in the waterto allowthe subjectfish to habituateto my presence,This required remaining motionless on the bottomfor long periodsand carefullycontrol- ling my breathingso that only a trickleof tiny bubbleswas slowly exhaled Figure3!.This somewhat avoided the louder noise caused by a big burst of bubbles from a singleexhalation, In order to obtain quality acoustic recordings without scuba bubble noise interference,acoustic measurements were edited in the lab from those portions of the video made between breaths. Thus, divers needed to be verydisciplined in their respiratorypace and activitywhiie recording.

We started using a rebreatherthree years ago and, without a doubt,it is the most successful methodfor obtainingfish behavioraland bioacousticdata Lobeland Kerr,pers. obs!. Beginning with myfirst field experiencewith the rebreather after31 yearsof scuba!,I wasgreatly impressed with howdifferently fish behavedwhen there wereno bubbles.The great advantage of the rebreatheris to allow usto approachanimals more closely. But this is alsoa bit morerisky for the same reason.I havefound that eels and grey reef sharksare more inquisitive and approach much closerwithout noisybubbles. On the other hand,the only time I experienceda schoolof juvenile parrotfishactually swim toward and over me,as if I wasjust a rock,was when usinga rebreather. Thisaspect of usingrebreathers will haveits mostsignificant impact on the practiceof conducting underwater transects for speciescensus and abundance surveys.We havefound that we see more individuals and a greater diversity,especially large fishes,while diving with the rebreather Lobel and Kerrpers. obs.!. Taking this one stepfurther, we haverecently acquired camouflage pattern wet- suits that are made to blend in with reef habitat. Thus,divers not only make no noise,but their sil- houettesare lessconspicuous and makethe diverappear less like a largepredator. Underwater photographerswere among the first to userebreathers routinely for the samereasons e.g. Cranston

Proceedingsfrom the international Workshop on the Applications of PassiveAcoustics to Fisheries 137 1993!.Any type of observationaldata that marinebiologists collect will clearlybenefit from using the rebreather.Examples include: 1! conductingtransects to determinespecies diversity and abun- dance,2!quantifying fish feedinghabits by observation,and 3! definingspecies habitat usage and behavior.Such field projectsrequire a toolthat providesthe greatestdegree of scientificaccuracy possibleand confidencein the results.The advantage of the rebreatheris that it allowsfor; 1! noise- lessoperations,2! the long bottom time necessaryto allowfish to acclimateto the observer'spres- ence overall,the useof a rebreathergreatly reduces the time neededto habituatefishes compared to opencircuit!, and 3! sufficientdive time to recordentire courtshipand spawningactivities. The unit only releasesa limited amount of bubbles when ascending due to expansionand overflow of gasesin the scrubber assembly,

Acknowledgernent Fundingfor the field and laboratorystudies is supportedby the ArmyResearch Office DAAG55-98- 1-0304and DAAD19-02-1-0218!.My participationin this meetingwas supported by the WoodsHole SEAGRANT office,

References LobelP.S. 2001 Fishbioacoustics and behavior:passive acoustic detection and the applicationof a closed-circuitrebreather for field study.Marine Technology Society Journal, 35:19-28

Proceedings rom the international Workshopon the Applications of PassiveAcoustics to Fisheries 138 Figure1. Recordingfishes undervvater using a videocamera and hydrophone.Photo by LisaKerr LobeL

Proceedingsfrom the international Workshopon the Applications of PassiveAcoustics to Fisheries 339 David A, Mann

Universityof SouthFlorida, College of MarineScience, 140 Seventh Avenue South, St. Petersburg, FL, 33701 USA. dmann@marine,usf.edu

Introduction Passiveacoustic detection of fish soundsrelies heavily on advancesin recordingand data process- ing technology. The recent explosion in fast, inexpensive personal computers and electronics has createdtremendous growth potentialin the field. Thispaper describes early efforts in developing passiveacoustic detection systems for fishesand morerecent efforts utilizing digital systems,The goalsof eachof thesesystems were to automaticallydetect and quantifysounds of interestin real- time, minimize false detections, and minimize the amount of data that needs to be stored to deter- rnine calling ratescontinuously over long periodsof time.

FirstGeneration Passive Acoustic Detection System Mostfish soundsare either simple pulsed broad-band sounds or tonal type sounds,where the pulse ratesor dominant frequency are species-specific e.g.Lobel and Mann, 1995;Mann and Lobel,1998; reviewed in Zelick et a!., 1999!. Fishsounds do not typically exhibit complex frequency modulations seen in many marine mammal vocalizations. This makes it possibie to describe most fish sounds with a fewmetrics, such as sound duration, peak frequency, and bandwidth.Timing between pulses can be recordedby storingthe time of onsetof eachpulse. By recording these simple metrics, a sys- tem canbe developedto automaticallydetect and processsounds of interestand greatly reduce the amount of data that would be acquired by simply recording continuously,

Earlyattempts at passiveacoustic detection involved developing a largelyanalog system that would detect soundsthat were above some background level and store the time of occurrenceand soundduration actualsound data were not stored! Mannand Lobel,1995! Fig.1!. Fromthese data,the rateof soundproduction of differentspecies'sounds could be determined.This system was employed to measuresound production rates of individual damselfish over periods of months, and revealeda strikingdawn chorus in sound productionand a tight link betweensound produc- tion and spawning cycles Mann and Lobel,1995!.

Proceedingsfrom the internationai Workshop on the Appiications of PassiveAcoustics to Fisheries 140 Real-TimeDigital SignalProcessing Systems Whilethe analogsystem was a robustdetector, continued increases in data storagecapacities and the emergenceof inexpensivedigital signalprocessing chips and the flexibility that theseprovide, promptedthe developmentof a programmabledigital system.This system is commerciallypro- ducedby Tucker-Davis Technologies Gainesville, FL! and consistsof a battery-powereddatalogger with two channelsof A/D,32MB of RAM,and a graphicalprogramming interface. The fiexibility of the dataloggeris that it canbe usedto processthe signalin real-timeincluding a widearray of fil- tering FlR,IIR! techniques and adaptive thresholding. The datalogger can be programmedto store whateverdata is desiredby the researcher,To demonstrateits flexibility,a devicewas programmed to detect the sounds produced by the toadfish Opsanusbeta, store the time of occurrenceof the soundand recorda 1000-pointsound sample Fig 2!.

The Future of Fisheries Bioacoustics Theprimary tools for the fish bioacoustician will remainthe PCand continuous digital recording systemsfor sometime. Topromote the emergenceof fisheriesbioacoustics requires more research intothe sounds made by different fish species and the developmentof newtechnologies that uti- lize these data.

Ultimatelyfisheries bioacoustics should move the wayof fisheriesacoustics where the signal output is not the actualsound data, but the locationsand intensityof fish spawning.

A usefulanalogy is the developmentof SONARsystems for fish quantification.These systems do not deliver raw sound data to the researcher.They return processeddata on fish location and abun- dance.One can envision the daywhen real-timefisheries bioacoustics systems will producemaps of the locationsof sound-producingfishes that can providemanagers with data on the temporal and spatial extent of spawning.

Acknowledgments My introductionand passionfor the field of passiveacoustic detection was driven by my Ph.D.advi- sor PhillipLobel. Support for the developmentof the digital dataloggerwas provided to TDTby an NIH grant to the author.

References Lobel,PS. and D,A,Mann. 1995. Spawning sounds of the damselfish,Dascyllus albisella Pomacentridae!,and relationshipto male size.Bioacoustics 6: 187-198.

Mann,D A.,and PS.Lobel,1995. Passive acoustic detection of soundsproduced by the damselfish, Dascyllus albisella Pomacentridae!. Bioacoustics 6: 199-213.

Proceedingsfrom the international Workshopon the Applications of PassiveAcoustics to Fisheries 141 Mann,D.A., and PS.Label. 1998. Acoustic behavior of the damselfishDascyllus albisella: behavioral and geographic variation. Environ,Biol. Fish. 51:421-428.

Zelick,R,, D.A. Mann, and A.N. Popper. 1999. Acoustic communication in fishesand frogs.ln: ComparativeHearing: Fish and Amphibians. Springer, New York. pp. 363-411.

Proceedingsfrom the internationalWorkshop on the Applicationsof PassiveAcovstics to Fisheries 142 Illustrationsand Diagrams

Ms@DBI4cloR

Figure1. Signalprocessing scheme for thedetectionofdamselfish Dascyllusalbisella! calls.

Figure2, Spectrogramof a seriesof automatically detectedtoadfish Opsanusbeta! callsplotted one after another. Thedominant frequencyof thesecalls is approximately250 Hz.

Proceedingsfrom the international Workshopon the Applications of PassiveAcoustics to Fisheries 143