BU Acoustic Recording Analysis Protocol-V10...

AcousticRecordingAnalysisProtocolBioacousticUnitNovember2015

www.bioacoustic.abmi.ca 2

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TableofContents

1 OVERVIEW.............................................................................................................................................3

2 MATERIALS,SOFTWAREANDBASICDATAORGANIZATION..................................................................4

2.1 RequiredEquipment......................................................................................................................4

2.2 ConvertingRecordings...................................................................................................................4

2.2.1 UsingKaleidoscopeSoftware..................................................................................................4

2.3 FileOrganization............................................................................................................................6

2.4 ListeningSoftware..........................................................................................................................7

3 HOWTORECORDDATA........................................................................................................................8

3.1 NavigatingtotheCorrectRecord...................................................................................................8

3.2 FillingOutPrimaryFields................................................................................................................9

3.3 EnteringSpeciesData...................................................................................................................12

3.3.1 ResourcestoAssistSpeciesIdentification.............................................................................13

3.3.2 EnteringSpeciesData............................................................................................................14

3.3.3 AbundanceMeasurements(TMTC)......................................................................................17

3.4 HOWTOCLASSIFYUNKNOWNS...................................................................................................19

3.5 SampleTracks...............................................................................................................................20

4 ASSESSINGABIOTICNOISE..................................................................................................................22

4.1 AbioticCodesandDescriptions....................................................................................................22

4.2 AssessingAbioticNoiseonaRecording.......................................................................................24

5 HEADPHONEVOLUMECALIBRATION..................................................................................................27

5.1 HearingSafety..............................................................................................................................27

5.2 VolumeandDetection.................................................................................................................29

5.3 ComputerandHeadphoneCalibration........................................................................................29

APPENDIX1–HEADPHONECALIBRATIONDATASHEET............................................................................32

APPENDIX2–HOWTOADJUSTAUDIOSOFTWARE..................................................................................33

CalibratingspectraldisplaysinAdobeAudition....................................................................................33

CalibratingspectraldisplaysinAudacity................................................................................................37

APPENDIX3–SUMMARYTABLES..............................................................................................................42


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1 OVERVIEWTheBioacousticUnit(BU)isapartnershipbetweentheAlbertaBiodiversityMonitoringInstitute(ABMI)andtheUniversityofAlberta.TheBUisafull-serviceorganizationthatprovideseverythingaclientrequiresforwildlifeacousticstudies.Weprovideadvice,supplystandardizedprotocols,provideequipment,conductfieldwork,processaudiorecordings,andreportontheresults.Ourteamisactivelyconductingleading-edgeresearchtoimprovemethodsandtounderstandacousticwildlifecommunitiesbetter.

TherecordingequipmenttypicallyusedforBUstudiesaremanufacturedeitherbyWildlifeAcoustics(SongMetersSM2+orSM3,www.wildlifeacoustics.com)orRiverForks(www.riverforks.com).Clientsregularlycollaboratewithustoassistwiththeirwildlifemonitoringneeds.Ourinvolvementvariesfromclienttoclientandspansthefullrangeofservicesfromsimplyprovidinginformationtoconductingafullresearchprojectontheirbehalf.ThisprotocoldescribeshowtheBUprocessesacousticdataintotabulardata,howtomanageacousticdata,andhowtoenterthedataintoadatabase.ThisprotocolisintendedtoaccompanyaMicrosoftAccessdatabasefile(BU_Database_FrontEnd)thatyoumayusetoenteryourdata.NotethatwhileBUstafffollowthisprotocolandusethesamedatabasestructure,therewillbeminordetailsinthisprotocolthatapplyonlytoBUstaff.SuggestedCitation:Lankau,H.E.,MacPhail,A.,Knaggs,M.andBayne,E.2015.AcousticRecordingAnalysisProtocol.BioacousticUnit,UniversityofAlbertaandAlbertaBiodiversityMonitoringInstitute.Edmonton,Alberta.Formoreinformation,pleasecontact:AlexMacPhail,BUDataProcessingCoordinator([email protected])

• Listeningmethods,listenertraining,birdidentificationresources,dataprocessingHedwigLankau,BUInformationCoordinator([email protected])

• Databaseaccessprotocols,datamanagement


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2 MATERIALS,SOFTWAREANDBASICDATAORGANIZATION

2.1 RequiredEquipmentThefollowingequipmentandsoftwareisrequiredforprocessingacousticdata.BothMacandWindowsoperatingsystemsaresuitablebutyouwillneedtoinstallapartitionthatrunsWindowsprogramsifyouuseaMacinordertouseMicrosoftAccess(thedatabaseprogram).• Computer• Soundeditingsoftware(SeeSections2.2and2.4;Appendix2)• MicrosoftAccess• CopyofAccessDatabasefile(BU_Database_FrontEnd)• Birdidentificationresources(Section3.3.1)• Headphoneswiththefollowingspecifications

o Stereoo Circumaural(fullyenclosingtheear)o Frequencyrange:5-30,000Hzo Nobassboost;headphonesshouldhaveaflatfrequencyresponseo Makesuretoreadspecificationsbeforepurchasingheadphones.Ourpreferred

headphonemakeandmodelareSONYMDR-V61

2.2 ConvertingRecordingsTodate,allBUrecordingsarerecordedinWAC,aproprietarycompressedfileformatthatcannotbelistenedtodirectlyusingstandardaudiosoftware.TheymustfirstbeconvertedtoaWAVfileformatusingWildlifeAcoustics’software,Kaleidoscope2.

2.2.1 UsingKaleidoscopeSoftwareRefertoSection2.3(FileOrganization)forappropriatedirectorystructure.Openingtheprogrambringsyoutothemainscreen(seeFigures2.1and2.2)

• PlaceallWACrecordingstobeconvertedintoonefolder.Selectthisfolderin‘InputDirectory’.

• ChecktheWACfilesbox–onlyincludesubdirectoriesifWACfilesarestoredwithinmultiplefolders.

1https://en.wikipedia.org/wiki/Sony_MDR-V62http://wildlifeacoustics.com/products/kaleidoscope-software


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• Selecttheoutputdirectory(i.e.,folderwheretheWAVrecordingswillbestored).Notethatyoucannotselectthesameinputandoutputdirectoriesandtheoutputdirectorycannotbenestedwithinaninputdirectory.

• ChecktheWAVfilesboxanduncheckthesplitchannelsboxonthe‘Outputs’sideofthewindow.

• Click‘Processfiles’

Figure2.1–KaleidoscopeExample1.SettingsforconvertingWACtoWAV.Remembertouncheckthesplitchannelsboxsothatyoudonotseparatetherightandleftchannelsofastereorecording.Theconversionprocesscantakeafewminutesdependingonhowmanyrecordingsarebeingconverted.ItisalsoimportanttonotethatWAVfilesareuncompressedandareapproximatelydoublethevolumeoftheirWACcounterparts,therefore,besureyourcomputerorharddrivehasenoughfreespacebeforeconverting.


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Figure2.2–KaleidoscopeExample2.Uncheckthe‘Filternoisefiles’box.Thisisnotapplicabletoregularacousticrecordings.

2.3 FileOrganization

Createalocalfolderonyourcomputerorharddrivelabelled[YourName]_AudioWorkSpace.Withinthismainfolder,createfoursubfolders:• WACfiles–forWACfilesdownloadedfromtheserver• WAVfiles–forWAVfilesoncetheyareconverted(seeSection2.2)–alsocreate2

subfolderslabelled“Listened”and“NotListened”toseparateworkyouhavedonefromunprocessedfiles


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• [YourName]_Unknowns–forunknownbirdcalls(seeSection3.4)• [YourName]_Examples–forexamplesofparticularlyclearbirdrecordings,multiple

individuals,uniquedialects,mammalsounds,abioticsoundsoranythingyoumightfindinterestingorhelpful

• Youshoulddividefoldersfurtherbylisteningassignmentstokeeptrackoffiles.Thisfolderiswhereyoushouldstoreallaudiofilesrelatedtolisteningwork.Itisimportanttokeepalocalcopyoftheserecordingssothatyoucangobacktothemeasilyandsharethemwithotherlisteners.Organizeyourselfaheadoftime.Ifyouhaveaspecificblockofrecordingstocompleteandtheyarestoredonlineoronaremoteserver,firstdownloadthemfromtheserver(ifnecessary)andconvertthemfromWACtoWAVfiles(seeSection2.2).Therecordingscontainalargevolumeofdataandcantakealongtimetodownload,especiallyifyouhaveaslowinternetconnection.Havingrecordingsstoredlocallyandintheproperformatwillalsopreventlosttimeiftheservergoesoffline,whichoccasionallyhappens.Alternatively,youmaybegivenasetoffilesbytheDataProcessingCoordinatororcopythemoffalocalharddriveinsteadofaserver.Inthesesituations,itisalsogoodtogetenoughfilesforafewdaysofworkatatimesothatyouspendlesstimeonfileconversion.

2.4 ListeningSoftwareThemainsoftwareweuseisAdobeAudition3andAudacity5.OtherprogramssuchasRavenPro6,orSongScope4maybeusedforspecifictasksbutwillnotbeyourstandardlisteningsoftware.Audacityisavailablefreeonline;however,thedefaultsettingsarenotgoodforlistening.PleaserefertoAppendix3forinformationonhowtoadjustsettingsforbothAdobeAuditionandAudacity.Alltheaboveprogramsuseaspectrogram.Aspectrogramisavisualrepresentationofsoundfrequenciesovertime.Ratherthanonlylisteningtotherecordings,spectrogramsfacilitatethevisualinterpretationofthesoundsignature.Themainpropertiesofaspectrogramarethefrequencyandamplitude,which,whencombinedwithsound,createsauniquesignature.Individualsofthesamespeciescanhavetheirownuniquevariationsofsongthatevenakeenearcannotdistinguishbutthataredetectableonaspectrogram.Audition,RavenPro,AudacityandSongScopealldisplaythisinformationinsimilarwayswithparametersthatcanbeadjustedtooptimizespectrogramvisualization(seeAppendix2).Itisvitaltouseboththeauditoryandvisualsignalswhenlisteningasthisgreatlyimprovesone’sabilitytoaccuratelyidentifyspecies.3https://creative.adobe.com/products/audition5http://audacityteam.org/4http://wildlifeacoustics.com/products/song-scope-overview


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3 HOWTORECORDDATAAlldataentrytakesplacewithintheListeningtaboftheNavigationForm.TheListeningdataentryformisaninterfacetoenterdataintothetablesintheSQLdatabase.Thesetablescanthenbequeriedtoextractthedataforanalysis.Therearesomebasicrulesthatapplytoallforms:• Alwaysenterand/orselectfromthetopdownsothattherelationshipsamongtablesare

properlymaintained• Alwayschecktoensurethattherecordyouaretryingtocreatedoesnotalreadyexistin

thedatabase.Duplicatesmustbeavoided.• Mostfieldsinthedatabasearerequiredandyouwillgetanerrormessageifyoumoveon

tothenextsectionwithoutfillingthemin.• Alwaysaskquestionsifyouarenotsurehowsomethingworksorhowtoenteracertain

kindofinformation.• Donotrush:incorrectdataentryresultsinincorrectdataandsomeerrorsareverytime

consuminganddifficulttocorrect.

BEFOREBEGINNINGANYRECORDINGS,YOUMUSTCOMPLETESECTION5OFTHEPROTOCOLFORHEADPHONEANDCOMPUTERCALIBRATION

3.1 NavigatingtotheCorrectRecordUsersnavigatetothecorrectrecordbychoosing,inthisorder:

• ProjectID:Thisisa1-to-4lettercodeidentifyingtheprojectyouarelisteningforandshouldcorrespondtotheprojectidinthefilenameoftherecordingyouareanalyzing

• Cluster-Site:Forsomeprojects,thereisnoClusternumber.Inthesecases,dropdownshows“99999”andthesitenumber.Inallothercases,therewillbeatwonumbercombinationwithnumbersseparatedbyadash(e.g.03-223).

• Station:Selectthecorrectstationnumberorlettertocorrespondtothestationinthefileprefixoftherecordingyouareanalyzing.

• Year-Round:Thisletsyouselectthecorrectyearfordata.Thisisparticularlyimportantforstationsthathavebeensampledmultipletimeseitherbetweenorwithinyears.Roundreferstowithinyearresamplingofalocation.

Thesefieldsserveasyourprimarynavigationtoolinordertoselecttheappropriatelocationtoenteryourdata.Oncetheseoptionsareselected,theRecordingDate,RecordingTimeand


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Detectiondataentryformsloadontothescreen.Remembertodouble-checkthattheaudiofilenamecorrespondstothedatethatyouhaveselected.Formostdatasets,theidentifyinginformationwillbecontainedinthefileprefixoftheacousticrecordingyouareworkingon.Forexample,inthefilename“OW-01-001-SW_20150316_000000”theprojectIDis“OW”,theclusteris“01,thesiteis“001”,thestationis“SW”,thedateis2015March16andthetimeis12:00:00AM(midnight).

3.2 FillingOutPrimaryFieldsThenexttwosub-formsrequireyoutoenterdatamanually.Otherusersmaybeenteringdataforthesamedate,therefore,makesurethattheDATERECORDEDorTIMERECORDEDdonotalreadyexistfortheparticularentryyouareabouttocreatesothatyoudonotcreateunwantedduplicaterecordsinthedatabase.

Figure3.1–Exampleofafilled-inform• RECDATE(DATERECORDED)

o EitherENTERorSELECTthecorrectdatethatcorrespondstothedateinthefilename.Usethedropdownmenuinthe‘GOTO’fieldtocheckifarecordingdatehasalreadybeenaddedforastation.Ifthedateyouneedisalreadyinthedropdown,clickonthatdateinthedropdowntoloaditintothe‘RECDATE’field.Ifthedateyouneeddoesnotexist,clickonthe‘NEWDAY’buttontoaddanewrecord.Thenenterthedateinthe‘RECDATE’field.


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• R.TIME(TIMERECORDED)o Thisisthesecondfieldyouwillfilloutonthedata-entryform(seeFigure3.1).It

correspondstothetimeinthenameofthefileyouareanalyzing.AswiththeDATERECORDEDfield,youmayencounterthatcertaintimesalreadyexist.Usethedropdowninthe‘GOTO’fieldjustaboutthe‘R.TIME’fieldtocheckifthetimeyouaregoingtoenteralreadyexists.Ifyoufindthetime,thentherecordinghasalreadybeenanalyzed.Donotmakeanotherentryforthesametimeunlessyourassignmentistolistentoasetforrecordingsforasecondtime.Onceyouhaveensuredthatthetimeyouareenteringdoesnotalreadyexist,youcanclickonthe‘NEWTIME’buttontoopenablankrecordfortheSITE,STATION,DATEDEPLOYED,andDATERECORDEDconditionyouhaveselected.

• REP.(REPLICATE)

o Next,filloutthereplicatebox.Thereplicatereferstothenumberoftimesthesamerecordinghasbeenprocessed.Ifyouarethefirstpersontotheprocesstherecording,thereplicateis‘1’,thesecondperson,thereplicateis‘2’andsoon.Ifyouareprocessingthesamerecordingforthesecondtime,thereplicateisalso‘2’.

• OBSERVER

o Thisreferstothepersonwhodidthelisteningandisadrop-downboxwhereyouselectyourname.Ifyournameisnotlisted,pleaseinformtheDatabaseManagersotheycanaddyoutothelist

§ Ifyouarethesecondobserveranalyzingthesamerecord,scrolltoaspecificSITE,STATION,DATEDEPLOYED,DATERECORDEDandRECORDINGTIME.ThenaddanewrecordforRECORDINGTIME,re-entertherecordingtime,enterthereplicateas‘2’(or‘3’dependingonhowmanytimestherecordinghasalreadybeenanalyzedandaddyourselfastheobserver.Thiswillcorrectlycreatetworecordswiththesametimebutdifferentobservers.

• FILENAME

o CopythefilenameoftheoriginalWACrecordingintothefilenamefield.EnsurethisiscopiedcorrectlyfromtheoriginalWACrecording.NotethatwhenKaleidoscopeconvertsthefilestoWAV,ittacksonthreezeros.Donotincludetheseinthefilenamefield.

• DATECREATED

o Thiscorrespondstothedatetherecordingwaslistenedto.Thisisautomaticallyfilledinbythedatabasewhenanewrecordiscreated.

• INDUSTRY,RAIN,WINDandNOISE

o SeeSection4–ASSESSINGABIOTICNOISE


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• MICROPHONEo Everyrecordingcontainsacertainlevelofbackgroundstaticduetothepre-

amplifiers;however,problems,suchas,electrostaticdischargeonthemicrophones,faultywiring,poorlyinstalledmicrophonesand/ormissingmicrophonescanoccurcausingexcessstaticor‘dead’channels.Usethecodesbelowtoentersuchproblemsinthedatabase.Usethecommentssectiontodescribethefrequencyorseverityofthemicrophoneissuesaswell.

§ 0–Nomicrophonerelatedissues§ 1–Leftmicrophonecutsoutintermittently§ 2–Rightmicrophonecutsoutintermittently§ 3–Bothmicrophonescutoutintermittently§ 4--LeftChannelFailed§ 5–RightChannelFailed§ 6–BothChannelsFailed§ 7–LeftSideExtraStatic§ 8–RightSideExtraStatic§ 9–BothSidesExtraStatic§ 10--OtherIssues§ 11–UnbalancedChannels§ -9–Notassessed

• VOLUME

o Thisisthevolumesettingonyourcomputer(seeSection5:HEADPHONEVOLUMECALIBRATION)

• PROCESSINGMETHOD

o Thisprojectusesvarioustypesoflisteningmethodstofocusoncertainspeciesortobeabletocomparedifferentdataprocessingmethods.Theprocessingmethodfieldissettoadefaultvalueof‘-9’.Changethisvaluetoreflectthecorrectprocessingmethodbelowunlessyoudidnotprocesstherecording.Herearebriefdescriptionsoftheotherprocessingmethods.Alwaysmakesureyouareusingthecorrectone:

§ 0–Standard:Afull10-minuterecordingisprocessed,withallspeciesandindividualsidentified

§ 1–Presence/absenceofspeciesbyfirstdetection§ 2–Presence/absenceofspeciesbyminute-intervaldetection§ 3–Presence/absenceofindividualandspeciesbyfirstdetection§ 4–Recordinganalyzedforowls(listenernottrainedtoidentifyother

species)§ 5–Recordinganalyzedforamphibians§ 6–Recordingvisuallyscannedforyellowrail§ 7–Recordinganalyzedfornoisereduction


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§ 8–3minfullanalysisfollowedby7minvisualscanforselectedspecies.Onlythefirst3minutesofarecordingisprocessedwithallspeciesandindividualsbeingidentified.thelast7minarescannedvisuallyforspeciesatrisk(SAR):BTNW,BRCR,BBWA,CMWA,CAWA,OSFL,CONI,RUBL….Theremayalsobeprojectspecificspeciesofinterest(SOI).CheckthesewiththeDataProcessingCoordinator.Ifaspeciesisdetectedvisually,recorditinthedatabasethesameasanormaldetection.IfaSARisdetectedinthefirstthreeminutes,continuerecordingdetectionsinthelastseven.

§ 9–MP3filetype,useforMP3versusWAVexperiment.§ 10–CallRateAnalysis:usedbyundergraduateprojectsin2013/14§ 11--3minfullanalysis,samemethodas8butno7minvisualscanforSAR§ 12–1minfullanalysisnovisualscan§ 13–1minutefullanalysiswithfixed-time§ 14–3minutefullanalysiswithfixed-time§ -9–recordingnotprocessed§ -8–recordingincompletelyprocessed

• PROCESSINGTIME

o Beforebeginningtothelistentotherecording,notethestarttime(ahelpfulhintistomarkthetimeinthecommentssection).Markthetimeittookinminutestocompletetherecording,includingthetimetoentermetadata(site,dates,etc.)andthespeciesidentifications.Thisdoesnotincludethetimetakentomakeclips,samplesandidentifyunknownspecies.

• COMBO(HEADPHONE-COMPUTERCOMBINATION)

o Thiscorrespondstothecombinationofheadphonesandcomputerthateachpersonusesforlistening(seeSection5:HEADPHONEVOLUMECALIBRATION)

• COMMENTS

o Usethisfieldliberallytomakeanycommentsabouttheentirerecording(notethatthereisa255charactermaximumforthisfield).

3.3 EnteringSpeciesDataOnceyoustartlisteningtotherecording,youwillusethedetectiontable.Thefinaltableisaspreadsheet-styleformwhereyouwillenterthespeciesandabioticdataforarecording.Notethattheseinstructionsareforastandard10-minuterecording(processingmethod‘0’).Youwillenterdataforspecies,numberofindividuals,minute-by-minutedetectiontimes,vocalizationtype(VT),abundance(TMTC–toomanytocount),confidenceofidentification(TBC–tobechecked)andcomments(whennecessary).Section3clarifiestheuseofTBCandSection4for


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abioticdata.Youcannotenterspeciesdatauntilallfieldsintherecordingtablearecompleted.Ifforwhateverreason,youneedtoabortorcannotstartarecording,fillinthemethodas‘-8’andmakeanoteinthecomments.

TheSPECIEScolumnhasadrop-downboxincludingbirds,mammals,amphibians,aswellasabioticnoisecodes(seeSection4.1:AbioticCodesandDescriptions).Selectthespecies/noiseyouhearbyusingdrop-downortypingthe4-letterAOUcode.ThecompletelistofspeciesandAOUcodesisalsoavailableintheLook-UpTablessectionofthedatabase.Notallsoundsareidentifiable(Section3.4clarifiesunknownobservations).Ifnospeciesaredetectedthroughouttherecording,fillinaspeciescodeboxwith‘NONE’(hereitisnotnecessarytofilloutminute-intervals).Usethiscodeforrecordingswithnospeciestoflagthattherecordingwasprocessed.Enteringwhichrecordingshavenospeciesisessentialfordataanalysis.

3.3.1 ResourcestoAssistSpeciesIdentification

Usethefollowingsourcestohelpyouidentifybirdaswellassomeamphibianandmammalspecies:• EnvironmentCanada’sDendroica(http://www.natureinstruct.org/dendroica/)• AllAboutBirdsfromCornellUniversity(http://www.allaboutbirds.org/guide/search)• Thayer’sBirdingSoftware(http://www.thayerbirding.com/)• BarbBeck’sBirdCallCollection(SeeDatabaseManagerforAccess)• Xeno-Canto(http://www.xeno-canto.org)• BioacousticUnitListener’sWebsite(https://sites.google.com/site/birdsoundsab/)• BioacousticUnitSoundLibrary

Beawarethatsomeoftheselibrariesdonothaveexamplesofwesternbirds;therearedialectdifferencesbetweendifferentpartsofthecountry.TheBarbBeckCollection,DendroicaandXeno-Cantoarethereferencesofchoice.Importingbirdsongandcallsdirectlytoyouraudiosoftwareallowsyoutoflipquicklybackandforththroughspectrographsforcomparison.

• Xeno-Canto:mp3sandspectrogramsofbirdsongandcallsfromallovertheworld.Thissiteisincrediblyusefulwithdozensofexamplesofmostspecies.

• Dendroica:Agreatresourceforlearningbirdgroups.The‘ManageLists’buttonallowstheusertoselectbirdsfromacertaingeographicalregionaswellastheoptiontoshowrareandmigratorybirds.

• BioacousticUnitListener’sWebsite:anongoingdevelopmentofteachingandtrainingmaterialsforactivelisteners


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3.3.2 EnteringSpeciesDataThisisthelastpartoftheformthatyouneedtofillout.Enterthisinformationasyougothrougheachrecordingandidentifythespecies.Makesureyouunderstandhowtoenterspeciesdataforthedifferentmethodslistedabove.PleaserefertoAppendix3:SummaryTables.• INDIV_ID(IndividualNumber)

o Thedefaultvalueforthisfieldis‘1’.Itcorrespondstouniquelyidentifiedindividualsofaspeciesontherecording.Inotherwords,ifyouheartwoOvenbirdsintherecording,youwouldhaveonerowwith‘OVEN1’andsecondrowwith‘OVEN2’.Asmanyindividualsasyoucanidentifycanbeadded.Evidenceformultipleindividualsneedstobestrong(seeTMTCbelowandSection3.3.3).Fillinthefieldwith‘0’ifthespeciesis‘NONE’.

• 0–9MIN(Minute-intervalcolumns)

o Enterthesecondwheneachindividualwasdetectedwithineachminute.Inotherwords,everyboxshouldeitherbeempty,signifyingthatindividualwasnotheardduringthatminuteorhaveavaluebetween1and59.Detectionsmadewithinthefirst1second(e.g.<1)arelabeledas‘1’.Eachaudioprogramcontainsadigitaltimertohelppinpointthesecondthespecieswasheard.

• TMTC(TooManytoCount)

o TheTMTCcolumnisusedtostoreabundanceinformationforeachdetection;eitherTMTCis‘1’for1individualor‘2’formanyindividuals.SeeSection3.3.3forfurtherdetailsonabundancemeasurements.WeusetwodifferentTMTCmeasurements:oneforbirdsandmammalsandoneforamphibians.

DistinguishingTMTCforBirdsandMammals

Whenbirds(ormammals)becomeTMTC,theobserverisindicatingan“uncountable”abundanceofaparticularspecies.Mostoften,thisoccurswithflockingspecies,suchasCanadaGeeseandWhite-wingedCrossbillsorgregariousspecies,suchasBlack-cappedChickadeesorGrayJays.Ineithercase,thenumberofcallingorsingingindividualsmustbelargeenoughthattheobservercannotpinpointwhichindividualiscallingduringeachminute-interval.A‘2’isenteredintheTMTCcolumn.

DistinguishingTMTCforAmphibians


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Amphibiansarerankedbycallintensityratherthanbydistinguishingindividuals.Usethefollowingcallintensitycodes.SeeSection3.3.3formoredetailedinformationonhowtoassigncallintensitycode

Table3.1–AmphibianTMTCcodesandtheirdescriptors.TMTC Description3 CI1:Individualamphibianscanbecounted;thereisnooverlappingofcalls4 CI2:individualscanbedistinguishedbutthereissomeoverlappingofcalls5 CI3:Fullamphibianchorus,callsareconstant,continuousandoverlapping• VT(VocalizationType)

o Thisfielddescribesthetypeofvocalizationeachdetectedspecies/individualmade:Table3.2–Vocalizationtypecodesandtheirdescriptions.VocalizationType DescriptionCALL Usethisforcallnotes,alarmcallsandnon-passerinevocalizationsSC(SingleCall) Usethisforcallnotesfrompasserinesandnon-passerinesthatoccuronly

oncefortheentirelisteningtimeSONG UsethisforterritorialormatingsongsSS(SingleSong) UsethisforsongsthatoccuronlyoncefortheentirelisteningtimeNV(Non-vocal) Non-vocalsounds(seebelow)madefromtails,feathersorotherbody

parts*SingleCallsandSingleSongshavealowerchanceofbeingidentifiedcorrectly,especiallyiftheyarefaint,becausethereisnotchanceoflookingataclearercallorsonglaterintherecording.*Forpasserines,songsorotherprimaryvocalizations,takepriorityovercallsifbothoccuronarecordingbecausesongsareusedforterritorialbehaviourandmateattraction.*ForCommonNighthawk(CONI),WilsonSnipe(WISN)andRoughedGrouse(RUGR),NVsoundtakepriorityovercallsifbothoccurinarecordingbecausenon-vocalsounds(wingbooms)indicateterritorialitymorethancalls.

DifferentiatingVocalizationTypesHereisalistofspeciesdifferentiatedintocalls,songsandnon-vocalsounds:

Table3.3–Vocalizationtypecodesorganizedbytaxa.VocalizationType Species


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SONG(orSS) Malepasserinematingandterritorialvocalizations,allamphibiansandowlprimaryvocalizations

CALL(orSC) Passerinecallnotes,mammals;andnon-passerineprimaryvocalizationsfromthefollowingfamilies:Anseriformes(ducks),Apodiformes(swifts,hummingbirds),Caprimulgiformes(nighthawks),Charadriiformes(shorebirds,gulls,terns),Ciconiiformes(herons),Columbiformes(doves),Accipitriformes/Falconiformes(hawks,eagles,falcons),Coraciiformes(kingfisher),Cuculiformes(cuckoos),Piciformes(woodpeckers),Galliformes(pheasants),Gruiformes(cranes,rails),Gaviiformes(loons),Pelecaniformes(pelicans,cormorants),Podicipediformes(grebes)

NV WinnowingofaWilson’sSnipe(WISN),woodpeckerdrumming,CommonNighthawkflightdisplay(‘boom’),wingbeatsofallduckspecies(indicateUNDUandflyoverinthecomments),RuffedGrousedrumming,CRCH(“crunch”-noisemadebyapproachingmammals)

• TBC(ToBeChecked)

o Thiscolumnisforkeepingtrackofsongsorcallsthatyouwantotherobserverstocheck.Asetofnumericalcodeswillcorrespondtothecheckedstatusofthesongorcall.UsethiscolumninaccordancewiththeguidelinessetoutinSection3.4.

§ 0 – Default value – The observer is confident with the speciesidentificationprovided

§ 1 – To be checked – Use this for any sound or vocalizationwhere youcannot identify the species; always create a sound clip for TBC1 (seeSection3.4)

§ 2 –Species Confirmed – Sound has been checked and second observeragreeswithfirstobserver

§ 3–ChangedtoUnknown–Soundhasbeencheckedandsecondobserverdisagrees with first observer, changed to unknown and both guessesenteredinthecommentsfieldwithobservernames

§ 4–UnknownConfirmed–Soundhasbeencheckedbutneitherobservercanidentifyit

§ 5–UnknownFar–Soundisrecordedbut is likelytoofaintordegradedforanyonetoidentify.Asoundclipdoesnothavetomade.

§ -9–Notassessed. This is thedefault valueandmustbechangedwhenneededtothecorrectvalue.

• VB(VerifiedBy)


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o The second person who assesses a species’ identification. This will always be anequallyormoreexperiencedlistener.

• COMMENTS

o Usethiscolumn liberally tomakenotesaboutanyof thesongsorcalls relating tothespeciesinquestion,especiallyinthecaseofunknowns.

FIGURE3.2–Exampleofacompleteddetectiontable;herewehaveBorealChorusFrogs(BCFR)singingatanintensityof4,meaningtheirsongsareoverlappingbuthavedistinguishableindividuals.ACommonNighthawk(CONI)vocalizesirregularlywithbothtypesofsignalsindicatedbytheobserverintheCommentssection.‘Booms’aretheprimarynon-vocalsoundoftheCONIwhichsupersedesthe‘peent’callvocalization,thereforeVT=NV.AWilson’sSnipe(WISN)callsandwinnows(NV)frequentlythroughouttherecordingandhasdetectionsineveryminuteinterval.TherearetwoRed-neckedGrebesontherecordingthatcallinthe1,6and7minintervals,withonlythe1stindividualcallinginthe9mininterval.Sincebothsexesvocalizethesame,theyreceivetheVT‘call’.AGreaterYellowlegs(GRYE)alsocallsthroughouttherecordingatvarioustimes.ACommonLoon(COLO)isheardonlyoncethroughouttherecordingsoitreceivesthe‘singlecall’orSCvocalizationtype.ARing-neckedDuck(RNDU)isalsobrieflyheardinthemiddleoftherecordingonlyinthe3minand4minintervals.Finally,theobserverdetectedabioticnoiseinthe5minand7minintervalsdescribingthenatureofthenoiseinthecomments.NotetheINDIV_IDcodeannotatedas‘0’,andtheTMTCandVTfieldsas‘-9’.TheobserverwasconfidentofalltheiridentificationssoallTBCfieldsreceive‘0’.Note,thattimeoffirstdetectionforeachminuteintervalisindicated–eveniftheindividualvocalizesmultipletimes.

3.3.3 AbundanceMeasurements(TMTC)Individualsshouldbedifferentiatedwhereverpossible,andtheTMTC=2designationshouldonlybeusedwhenyouaresureyoucannottellindividualsapart,especiallyforterritorialspecieswhereyoumostlyhaveonly2to3individualsbutlesscommonlyupto5or6.Ifyouareunsureofhowmanyindividualsyoucantellapart,usethemoreconservativenumber.Thereisnohardandfastrulefordoingthisbutthefollowingtipswillhelp.Onceyouaretryingtotell


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morethanthreebirdsapart,youneedtomakesurethatyoucanconsistentlyusethesemethodstotelltheindividualapartthroughoutthecourseoftherecording.Itiscommontohavemorethanoneindividualofthesamespeciesonarecording.Whetherornotitispossibletotellhowmanytherearedependsonseveralfactors.Wecanidentifymultipleindividualsofthesamespeciesby:

• Timingo Overlapbetweencallsorsongsoro Spacingbetweenvocalizations

§ Evenspacing=morelikelytobesameindividual§ Oddspacing=morelikelytobemorethanon

• Variationin:Directionality:whichsideofARUissingingfrom,

o Intensity:howclosethebirdistotheARU,oro Song:differencesinpitch,length,syllablesandstructureareallindicators

Thenumberofindividualsthatareidentifiableisoftendependentonthespeciesandtheirbehaviour.Underthefollowingcircumstances,itwillbedifficulttodistinguishindividuals.

• Flocking-vocalizeandmovetogethero Crossbills,waxwings,PISI,swallows,chickadees,GRAJ,CANG,gullsandterns

• Rapidlychanginglocationo CONI,WISN,CORA,AMCR,ducks,shorebirds,woodpeckers

• Haveshort,invariablesongso LEFL,YBFL

• Jumbledor,disjointedsongso AMRO,RBGR,vireos

Typically,multiplefactorscomeintoplaytoproperlydiscern>2individualsonarecording.Estimatingindividuals(1to5+)ispossiblewhenbirdsare:

• Territorial-areseparatedspatiallyfromeachothero OVEN,TEWA,SWTH,LCSP

• Sedentary-tendtosingfromonegenerallocationo OSFLo Havevariablesongsbetweenindividuals-Warblers,sparrows,wrens,kinglets

Foramphibianscallsfromdifferentindividualscannotbedistinguishedfromeachotherusingthesamemethodsasforbirds.Insteadtheyarequaltifiedusingcallinintensitybyassessingthespacebetweencalls.The system we use was adapted from the North AmericanAmphibianMonitoringProgram(NAAMP)AmphibianCallingIndex(ACI)(2005):


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Callintensity1(CI1):callsdonotoverlap.Asinglecallcanbeseenonthespectrograph,andnoothercallsoccurwithinthedurationofthatcall.Callintensity2(CI2):callsoverlap,butcanbedistinguishedCallintensity2(CI3):overlappingcallsareconstantandcannotbedistinguished.Afullchorusofcallsmaynotappeardistinguishablevisuallyonthespectrograph.Theimagewillmostoftenlooklikeacontinuouslineofnoise.

3.4 HOWTOCLASSIFYUNKNOWNSThereisadegreeofuncertaintyinidentifyingspeciesonarecording,becausebirdsmakeavarietyofdifferentsoundsandtheabilityofanobservertoidentify~300borealbirds,amphibiansandmammalsbyvocalizationsislearnedoverlongexpansesoftime.Soundsthatcannotbeidentifiedareenteredasunknownsinthedatabase.Therearevariousreasonswhyunknownsoccur:• Thevocalizationisclearbuttheobserverisunabletoidentifyit• Thevocalizationistoodegradedorfaint,ormaskedtoidentify• Thevocalizationisashortcallnoteoralarmcall• Thevocalizationissomeothersound(i.e.abiotic)

Toaididentificationoftheseunknowns,trytoplacethecall/songtothebestofyourabilityintooneoftheunknowncategoriesinTable3inAppendix3.Otherthanprimarysongs,passerinesalsohavealarmcalls,flightcallsandcallnotes.Usingtheseasspeciesidentifiersisdifficultandunreliable.Therefore,weareavoidingclippingandattemptingtoidentifysongbirdsbasedoncalls.Ifatanypoint,thebirdsings,andyoucannotidentifyit,makeaclip.Generally,youshouldonlymakeclipsoftheunknownonlyiftheindividualcallsmorethanonce–inmostcasesasinglecalldoesnotprovideenoughinformation.UsetheTBCcolumntoindicatewhethertheentryneedstobeverifiedbyanotherobserverandwriteinthecommentssectionadetailedaccountofthesound(SeeTable3.4).Table3.4–Howtoenterunknownspeciescodesandtheiraccordingvocalizationtype,TBCstatusandcomments.

Soundtype SpeciesCode VT TBC CommentsUnknownpasserinecall UNPA SC/Call 0 Unknownpasserinesong UNPA SS/Song 1 0150-UNPA1.Short


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description.Unknownnon-passerinecall:SCorveryshort

UNKN SC 0

Unknownnon-passerinecall:

UNKN Call 1 0345-UNKN1.Shortdescription.

HereisafulllistoftheUNKNcodesinthedatabase:

• UnknownAccipiter(UNAC)• Unknownblackbird(UNBL)• UnknownButeo(UNBU)• Unknowncorvid(UNCV)• Unknownduck(UNDU)• Unknownflycatcher(UNFL)• Unknowngull(UNGU)• Unknown(UNKN)*usedifyoucan'tnarrowdowntoanyothergroup• Unknownowl(UNOW)• Unknownpasserine(UNPA)• Unknownshorebird(UNSH)• Unknownsparrow(UNSP)• Unknownswallow(UNSW)• Unknowntern(UNTE)• Unknownthrush(UNTH)• Unknowntriller(UNTRLL)• Unknownvireo(UNVI)• Unknownwarbler(UNWA)• Unknownwoodpecker(UNWO)• Unknownyellowlegs(UNYE)

Somesoundsaresofaintordegradedthattheyarelikelyunidentifiablebyanyone.Thesesoundslabelled5intheTBCcolumn,whichmeansthatclipsdonothavetobemade,andtherewillbenofurtherattempttoidentifythesound.Thethresholdbetweenidentifiableandlikelyunidentifiablesoundsisbasedonhowdegraded,faintofmaskedthesoundis,whattypeofsounditisandtheskillofthelistener.TogetanideawhentousetheTBC5code,refertoTBC5samplesintheBUSoundLibrary.

3.5 SampleTracksWearecontinuallyupdatingtheBUcallandsoundreferencelibrary.Todothis,weneedtosetasideexamplesofuniqueand/orveryclearvocalizationsandsounds.Wealsoneedsamplesofsongvariations,multipleindividualsandfaintcalls.Youmighthavearecordingthathasaveryclearspectrogramoftwocounter-singingmaleOvenbirdsoryougetaveryclearBarredOwl


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duet.YoumightfindaconfusingcallthatturnsouttobeyetanothervariationofaYellow-rumpedWarblerorAmericanRedstart.Afewexamplesofoddabioticsoundwillbeusefulaswell.Whenyougetasampleyoufeelmightbeusefulforyoulaterortoshare,takea20secondorlongersamplefromthemainrecordingandsaveitasanewsoundfile.ThenewfileshouldbeinWAVformat,16bit,stereo,andasamplerateof44100Hz.Labelthefilewiththeoriginalfilenameinadditiontothetimeintherecordingandthespeciesonthetrack.Forexample,ifyoufoundagoodYellow-rumpedWarblercallonatrackat1:35atSite6,StationFI6onJune25th,2012at6:00AM,youwouldlabelitasfollows:06-FI6-20120625_060000_0135_YRWA.StorecopiesofallyoursamplesintheBU_ExamplesfolderinyourBU_AudioWorkSpace.Tocreateacliporsample:• Findasectionoftherecordingwheretheunknownissinging/calling,ideallywithout

interferencefromotherspeciesorabioticnoise• Highlightthesong/callonthespectrographincorporatingacouplesecondsbeforeand

aftertoprovidecontext• Right-clickthehighlightedsectionandclick“SaveRecordingAs…”• Inthesubsequentwindow,savetheclipusingthefollowingconventions:

o ProjectID-Cluster-Site-Station_Date_Timeofrecording_Timeofclip_Speciescode_NumberofIndividuals.wav

§ Example:Y-01-200-CT_20130528_040000_0322_UNKN_3.wavo WAVformat,16-bit,stereoandasamplerateof44100Hzo SaveinUnknownsfolderwithinAudioWorkspacefolder.

• Besuretoincludethetimeandspeciescodeinformationofthefilenameinthecommentsforthespeciesyouareclippingforeasyreference(i.e.put0322_UNKNasthefirstpartofthecommentsforthatdetection.

• Onesongisoftennotenoughinformationtoidentifyanunknown.Anunknownrecordingwillhaveagreaterchanceofbeingidentifiediftherearemultipleexamples.Toquicklymakeaclipwithmultipleexamples:Selecttheareaofonesongandsaveitasanewfileusingthenamingconvention.Thenrepeatforatleasttwomoreexamplesorenoughthatanyvariationiscapturedandaddthemtotheendofthefirstsample.


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4 ASSESSINGABIOTICNOISETherecordingunitspickupallnoise,includingweather-relatedandanthropogenicnoise.Weneedtoassessbackgroundnoisebecauseitaffectsspeciesdetection.Noiseonrecordingsoriginatesfromdifferentsources.Certainrecorderswereplacedveryclosetofeaturessuchascompressorstationsorindustrialsiteswherenoiseisalmostconstantthroughouttheentirerecording(i.e.motors,fans,enginesrunning24/7).Otherswerelocatednearbusyroadswherenoiseisvariablethroughoutarecording(passingcarsandtrucks).Windandrainalsocreateanidentifiablenoisesignature.Allthesesourcesofnoisehavetheirownsoundsignatureandareidentifiablebothbyearandbyviewingthespectrogram.Weusefour-lettercodes(similartothebirdspeciescodes)torecordrain,wind,industrialandbackgroundnoiseinthedata-entryform.Generally,constantindustrialnoise,suchascompressorstations,occursbelow500kHzbutloudernoisecancoveragreaterfrequencyrange(upto1000kHzforlightnoise,upto1500kHzformoderateindustrialnoise(MONO)andupto2000kHzforheavyindustrialnoise.Low-intensitywindblowingagainstthemicrophonesalsocreatesnoisethatisgenerallybelow2000kHzbutcanmuffleallfrequencies.Raintendstocreatebroad-spectrumnoisefrom0to>10,000kHz.Therearefourcategories:wind,rain,industrialnoiseandotherbackgroundnoise.RefertoTable2inAppendix3:SummaryTablesforahandyreferenceofwhatgoesineachcategory.ARUsproduceaboutacertainamountofstaticfromtheunititself(30dBformostrecordings–newrecordingdevicesmayhavelowerbackgroundnoise).Donotrecordthisstaticasnoise

becauseitoccursonallrecordings!

4.1 AbioticCodesandDescriptions RAIN

• 0–Norainpresentontrack.(Nocodesincethereisnorain)• 1–Lightrainpresentontrack-affectstheabilitytoheardistant/faintspecies,drops

seldomhitmicrophones.(Code:LIRA)• 2–Moderaterainpresentontrack-affectstheabilitytohearnearbyspecies,dropsoften

hitmicrophones.(Code:MORA)• 3–Heavyrainpresentontrack-significantlyaffectstheabilitytodetectspecies,drops

veryfrequentlyhitmicrophones.(Code:HERA)


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Figure4.1–Exampleofheavyindustrialnoise(HENO)asseenonaspectrograminAdobeAudition.

Figure4.2–Exampleoflightindustrialnoise(LINO)asseenonaspectrograminAdobeAudition.


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WIND• 0–Nowindpresentontrack.(Nocodesincethereisnowind)• 1–Lightwindpresentontrack-usuallyhearrustlingleaves/treescreaking(background

noise),affectsabilitytodetectdistant/faintspecies.(Code:LIWI)• 2–Moderatewindpresentontrack-beginstomufflemicrophones(frequencyand

decibelratesbegintospike),occasionallyaffectsabilitytodetectnearbyspecies.(Code:MOWI)

• 3–Heavywindpresentontrack-alwaysmufflesmicrophones,frequencyanddecibelgraphsspikeconstantly(sometimescutsoutduetonoisethreshold).(Code:HEWI)

INDUSTRIALNOISE• 0–Noindustrialnoisepresentontrack.(Nocodesincethereisnonoise)• 1–Faintindustrialnoisepresentontrack(adistanttruck,alowhumfromaprocessing

plant)–affectsdistant/faintspeciesdetection.(Code:LINO)• 2–Moderateindustrialnoisepresentontrack(apump-jackwhirringnearby,significant

noisefromprocessingplants)–beginstoaffectspeciesdetection.(Code:MONO)• 3–Heavyindustrialnoisepresent(trucksdrivingbytherecorder,loudprocessingplants,

planeflyingoverhead)–significantlyaffectsabilitytodetectclose-rangespecies.(Code:HENO)

• BACKGROUNDNOISE• 0–Nobackgroundnoisedetected• 1–Faintbackgroundnoisepresent(e.g.runningwaternotclosetorecorder;distant

thunderrumble)–affectsdetectionofdistant/faintspecies.(Code:LIBA)• 2–Moderatebackgroundnoisepresentontrack(e.g.moderatelyloudwater)–beginsto

affectdetectionofcloserspecies.(Code:MOBA)• 3–Heavybackgroundnoisepresent(e.g.runningwaterorrapidsveryclosetorecorder;

mosquitosittingontopofthemicrophone)–speciesdifficulttodetectevenifpresent.(Code:HEBA)

4.2 AssessingAbioticNoiseonaRecording Assessingthenoiseonarecordinginvolvestwosteps.Firstly,enternoisecodesaccordingtotheirminute-–by-minutedetectiononarecording,justasyouwouldforbirds,amphibiansandmammals.Ateach1-minuteintervalwhereatypeofbackgroundnoiseispresent,thecodemustbere-enteredthesameasforspeciesdata.Ifabackgroundnoiseispresentatthesamelevelthroughouttheentirerecordings,enteravaluea“1”ineveryminuteboxtoindicatethattheeventoccurredfirstwithinthefirstsecondofeachminute.Forexample,ifthereislightwindthroughouttherecordings,youwouldenter1foreachofthe10minuteintervals.Thereisnoneedtoassessavocalizationtypeornumberofindividuals–INDIVID=0.TheVTandTMTCfieldscanbeleftattheirdefaultvalueof“-9”;but,ifyouwouldlikeanotherobservertoassess


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yourabilitytoquantifynoiselevel,youmaychangeTBCto“1”forreview–donotforgettoindicateaclipnoteinthecommentsandproperlystoreitinyourunknownsfolder.Insomecases,suchasforgustsofwindorvehiclespassingtherecorder,therewillbemorethanoneintensityofbackgroundnoisewithinoneminute.Forexample,ifthereislowlevelindustrialnoisethroughouttherecording,butacardrivesbyat1:20,thesecondminuteintervalwouldhaveLINOenteredas1(beginningoftheminute)andHENOenteredas20tocorrespondwiththecarpassingat1min20sintotherecording.InFigure4.3,trafficpassesveryclosetoarecorder;notethatamplitudeandfrequencywillspikewhiletrafficpasses(upto10kHz).Rain,windandnoisearenotmutuallyexclusive:theywilloftenoccurduringthesamerecording,mostoftenwithrainandwind(i.e.,astorm).Doyoubesttorateeachbackgroundnoiseonarecordingindependentlyoftheother.Secondly,createanaveragebasedonthenoisethroughoutthewholerecording.Fillintheseaveragesattheendoftherecordinginthefieldsabovethecommentssection.Processtheentirerecordingandthencreatetheaveragesintheappropriatenoisefields(industry,rain,wind,noise)aftertherecordingisfinished.Howmanyminutesyoucreatetheaveragesoverdependsontheanalysismethod.Forexample,forMethod0,theaverageisbasedonall10minutes.ForMethod11,theaverageisbasedononlythefirst3minutes.Ifthereisvariabilityinintensityforonekindofbackgroundnoise,onlychangetheaverageifthedifferentintensityispresentatleast1/3ofthetime.Forexample,ifthereislightwind(LIWI)anditonlyincreasestobeingheavywind(HEWI)foronlyoneminute,therecordingaverageshouldstillbeLIWI.HoweverifyouhaveLIWIin5ofthe10minutes,MOWIin1minuteandHEWIintheother4minutes,youmightputanaverageofMOWIfortheentirerecording.Rainintensitiesrarelychangeduringrecordings(chancesarethattherainwillnotpickuporsettledownwith10minutes),nevertheless,noteanyrainintensitychangesiftheydooccur.

Figure4.3–ExampleofacomplexsetofabioticnoiseeventsasseenonaspectrograminAdobeAudition.Notethevariabletrafficnoises(HENO),heavyrain(HERA)andlightwind(LIWI)occurring.


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Figure4.4–Exampleofaverynoisyrecording.Note“NONE”isstillenteredtoindicatenospeciesweredetected.

Figure4.5–Exampleofrecordingwithvariationinbothtypeofnoiseandintensityofnoise.Aswind,rainandindustryincreaseinintensity,bioticsoundsarehardertodetect.Withcertainlisteningassignments,youwillbeaskedavoidrecordingswhereabioticnoiseisaboveacertainlevel(usuallymoderate).Forexample,youmightbeinstructedtolistenonlytotrackswithRAIN,WIND,INDUSTRYand/orNOISEof“0”to“1”.IfyouopenarecordingandfindthatithasaNoiseratingof2or3ANDyouarenotsupposedtolistentorecordingswiththismuchnoise,thenfillinthedate,time,replicateandobserverotherrecordingrelatedinformationBUTleavetheDetectionfromBLANK.Fillintheprocessingmethoda-9(recordingnotprocessed).Itisimportanttoleavethespeciestableblanktodifferentiatefromrecordingswheretherewerenospeciesdetected(refertosectiononNONEbirds).Onlydothisifyouarespecificallyinstructedtodoso.Checkwiththelisteningco-ordinatorwhat,ifany,backgroundnoisecut-offsareapplicabletoyourassignments.


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5 HEADPHONEVOLUMECALIBRATION

5.1 HearingSafety Thevolumeinheadphonescanreachlevelsthataredamagingtohumanhearing.Technicianslistentorecordingsfor4to8hoursaday,therefore,weneedtoensurethatvolumelevelsdonotexceedamplitudesthatwouldincurhearingdamage.Occupationalhealthandsafetyrequiresthathearingprotectionbewornifworkplacenoiseexceed85dB(A-weighted)overthecourseoftheday.A-weightedsoundlevelsareartificiallyadjustedtomatchthebiasedhearingspectrumofthehumanear.Thechallengeistomeasurethevolumelevelattheeardrum,becausethehumanearamplifiesdifferentfrequenciesofsounddifferently.Figure5.1showsagraphfortheTransferFunctionoftheOpenEar(TFOE),whichillustrateshowmid-rangefrequenciesmaybeamplifiedbyupto15dBAbetweentheoutsideoftheearandtheeardrum.Largeamphibianchoruses,suchasexistonanumberofthewetlandrecordings,areveryloudandcomposedofmidrangefrequencies.Therefore,theseareofthegreatestconcerninregardstohearingsafety.Heavywindandindustrialnoisecanalsoreachhighvolumes.Agoodsystemistoalwaysstartlisteningtoarecordingatalowervolumeandturnitupasneeded.

Figure5.1–TransferFunctionoftheOpenEar


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Table5.1–NoiseExposureLimitsat85dB(A)

*http://www.ccohs.ca/oshanswers/phys_agents/exposure_can.html

Thefollowingreferencesgivemoreinformationonoccupationalhealthandsafetystandardsandonlisteninghealthforheadphoneusers.Pleasetakethetimetoreadthem:

• Noise-OccupationsExposureLimitsinCanadao http://www.ccohs.ca/oshanswers/phys_agents/exposure_can.html

• Berger,E.H.,S.C.megerson,andM.E.Sterger.August11,2009.PersonalMusicPlayers:AreWeMeasuringtheSoundLevelsCorrectly?TheAshaLeader

o http://www.asha.org/Publications/leader/2009/090811/f090811b.htm• Articleaboutheadphones

o http://www.headwize.com/articles/hearing_art.htm• ResearchersRecommendSafeListeningLevelsforAppleiPod

o http://phys.org/news80304823.html

Table1B*NoiseExposureLimitswhenCriterionLevel=85dB(A)

3dB(A)ExchangeRate MaximumPermittedDailyDuration(hours)

5dB(A)ExchangeRate

AllowableLeveldB(A) AllowableLeveldB(A)

85 8 85

88 4 90

91 2 95

94 1 100

97 0.5 105

100 0.25 110


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5.2 VolumeandDetection Thevolumeatwhichrecordingsarelistenedtomayaffectthenumberofspeciesandindividualsthataredetected.Theplaybackvolumethateachpersonchoosesontheirownwillbeaffectedbothbythegain(loudness)oftherecordingandthecomfortlevelofthelistener.Somepeoplehaveatoleranceforlouderheadphonevolumethanothers.Toaccountforthisdifferencebetweenobservers,weneedtoplayrecordingsatconstantvolumesthataresafeandcomfortableforalllisteners.Atthesametime,recordingshavedifferentgainlevelsduespeciesandnoiseproximity.Forexample,anamphibianchorusrightbesidetherecorderwillresultinalouderrecordingthaniftheamphibianchoruswas200maway.Owlshaveverylowfrequencycallsandaredetectedovergreatdistances.Theyaredetectableonveryquietrecordingsonlyifthecomputervolumeisturneduphigh.Usingidenticalvolumelevelsforloudamphibianchoruseswillbedetrimentaltohearing.

5.3 ComputerandHeadphoneCalibration

Figure5.2–Placementofsoundpenduringheadphonecalibration.

Wewillcalibratethecomputer/headphonecombinationthateachobserverisusingcodestoindicateatwhichvolumelevelarecordingisprocessedsothatwecanaccountfordifferencesbetweenobserversandequipmentandreproducethevolumesatwhichrecordingsarelistenedto.Usethefollowingprotocoltocalibrateyourcomputer/headphonecombination:

IMPORTANT:DONOTPLACEHEADPHONESONEARSFORTHISEXERCISE!


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Instructions• Playtesttone.Thisisacomputergeneratedtoneof3000Hzand-25dBfs(Theisavailable

onintheListenerInfofolderontheSharePointsiteorcanbesenttoyoudirectly)• UseSoundLevelPentomeasureoutputvolume(dBA)fromheadphones.Placecupsof

headphonesagainsteachother(seephoto)andplaceSoundLevelPeninbetween(putthepenin3differentpositionsforthethreerepeatedmeasurements:insertfrombottom,sideandtop.Makesurethatthesoundlevelpendoesnotmoveduringeachcalibrationrun.Usearubberbandtoholdthetwoheadphonestogether.Dothiscalibrationinaquietroom,preferablywiththesoundmeterreading45dBAorless.Trytoplacethesoundpensothatthetipisinthemiddleofthespacebetweentheheadphones.

• Playthetesttoneatavolumethatgivesyouanoutputascloseto50dBAaspossible.Notewhatthevolumesettingonyourcomputerisatthispoint(lookatthenumberonthevolumescrollbar(e.g.youmightbeat10%oftotalvolume).Enterthevalueinthevolumecalibrationchartunder“ComputerVolume”.Also,entertheexactdBAofthetoneatthiscomputervolume.ThisisVolumeLevel1.NOTEFORMACUSERS:Thereisnofunctionforvolumepercentagebecausethecomputersusedvolumeincrementsfrom1to16.Indicatevolumeonascaleof1-16.

• IncreasethevolumeuntiltheSoundLevelPenisregistering55dBA.ThisisVolumeLevel2.Notewhatthepositiononthecomputervolumeadjusteris.

• Dothisforincrementsof5dBAuntilyouareatthemaximumvolumethatthecomputercanproducethroughthoseheadphones.

Afteryoucompleteyourcalibration,pleaseentertheinformationintotheCalibrationfrominthedatabase.Usethe“New”buttontocreateanewrecordandfillinallinformationexcepttheCombinationnumber.TheDatabaseManagerwillprovideyouaCombinationtoenterwhenyoulistentorecordings.Whenyougetanewcomputer-headphonecombination,youwillneedtore-calibrateandhaveanewcombinationnumberassigned.


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Table5.2–Exampleofaheadphonevolumecalibrationtest.Computermakeandmodel: AcerAspire5560Headphonemakeandmodel: SonyMDR-V6ObserverName: JoeBlowSoundLevelPenSerialNumber: 051448TestToneUsed: 3000Hz,-25dBfs

Test1(bottom) Test2(side) Test3(top)VolumeLevel

TargetdBA*

AverageComputervolume

Computervolume

ActualdBA

Computervolume

ActualdBA

Computervolume

ActualdBA

1 50(65) 1 1 50.5 1 50.7 1 49.22 55(70) 3 3 54.7 3 56.4 3 543 60(75) 6 6 61.4 6 60.3 6 60.84 65(80) 8 8 65.7 9 65.4 8 64.55 70(85) 12 12 70.4 13 70.8 12 69.76 75(90) 18 16 75 18 75 18 75.77 80(95) 25 24 80.3 26 80.4 25 80.18 85(100) 35 33 85.6 37 85.8 36 85.49 90(105) 44 42 90.3 45 90.7 44 90.510 95(110) 58 58 95.5 59 94.9 58 95.311 100(115) 77 78 100.1 75 100.7 78 100.412 105(120) 100 100 103.2 100 102.9 100 103.4

*ThetargetdBAindicationwhattheSoundLevelPenshoulddisplay.ThevalueinbracketsindicatesthevolumeattheeardrumafteraddingtheTFOE:thevolumeattheeardrummaybeasmuchas15dBAgreaterthanmeasuredbythesoundmeter.Underlinedvaluesshowninredareinrangeofvolumethatisdangeroustolistentoformorethanafewminutes.IMPORTANT:Donotlistentoanyfiles,evenquietnight-timerecordings,overvolumelevel8.Level8issufficienttodetectmostbirds,evenfar-awayowls.Inaddition,asyouincreasethevolume,boththecallswillplaylouderandthebackgroundstaticandnoisebecomelouderand,afteracertainpoint,anincreaseinvolumewillnothelpindifferentiatingvocalizationsfrombackgroundnoise.


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APPENDIX1–HEADPHONECALIBRATIONDATASHEETComputermakeandmodel:Headphonemakeandmodel:ObserverName:SoundLevelPenSerialNumber:TestToneUsed:3000Hz,-25dBfs Test1(bottom) Test2(side) Test3(top)VolumeLevel

TargetdBA*

AverageComputervolume

Computervolume

ActualdBA

Computervolume

ActualdBA

Computervolume

ActualdBA

1 50(65) 2 55(70) 3 60(75) 4 65(80) 5 70(85) 6 75(90) 7 80(95) 8 85(100) 9 90(105) 10 95(110) 11 100

(115)

12 105(120)

*ThetargetdBAindicationwhattheSoundLevelPenshoulddisplay.ThevalueinbracketsindicatesthevolumeattheeardrumafteraddingtheTFOE:thevolumeattheeardrummaybeasmuchas15dBAgreaterthanmeasuredbythesoundmeter.Underlinedvaluesshowninredareinrangeofvolumethatisdangeroustolistentoformorethanafewminutes.DONOTLISTENTOTHETESTTONEATTHISVOLUME:ONLYUSETHESOUNDMETERNote:YoucanenterthisinformationdirectlyintotheCalibrationformifyouhaveaccesstotheBU_Database_FrontEnd..


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APPENDIX2–HOWTOADJUSTAUDIOSOFTWARE

Twodifferentprogramsareatourdisposaltovisualizerecordings:AdobeAuditionandAudacity.Thelatterisfreeopen-sourcesoftwarethatisavailableacrossalloperatingsystems.Withanever-increasingnumberofnewlistenersworkingwiththeEMCLA,AudacityissoftwarethatwillsavemoneyandallowuserstoprocessrecordingsinthesamewaytheywouldwithAudition.Audacityoffersanintuitivelayout,easytomanipulatesettingsandgrayscalespectraldisplayswhicharethesameasreferencerecordingsfromresourceslikeDendroicaandXeno-Canto.Spectraldisplaysaremostusefulwhentheyarepersonallyadjustedforeachuser.Aspectrographdisplaysaudiofilesinfrequency(kHz)overtime(seconds/minutes).Principally,settingsareadjustedtoaccommodatescreenresolution,screensizeandstudygoals.Ideally,eachuserwouldsetuptheirspectraldisplaysotheycanhavetheclearestpictureofbirdsongand/oramphibiancalls.Ourgoalistosetthefrequency,timeandspectralresolutionsettingstohavethemostdetailedimageofabirdsongwithoutcomprisingtheefficiencyofinterpretingandannotatingarecording.

CalibratingspectraldisplaysinAdobeAuditionCertaincomponentsofAdobeAuditionneedtobeadjustedinordertoeffectivelyusespectraldisplaysforwildlifelisteningpurposes.Calibrationisnotspecificallystandardizedasfactorssuchasscreensizeandscreenresolutionaredifferentfromusertouser.However,certainguidelinesshouldbefollowedtoensureusingAuditionaslisteningsoftware.Threesettingsmustbecalibratedappropriately:frequencyrange,timeframeandspectralresolution.Theexamplesbelowillustrateswhensettingsfavoursongbirdandamphibiandetections(seeTable8forotherstudyspecies).

InAuditionthefrequencypanelcanbemanuallyadjustedtoalogarithmicorlinearscale;bothscaleshavetheiradvantagesanddisadvantagestodisplayingspectralsignatures.Byright-clickingonthefrequencyscaleontherightsideofthespectraldisplay,ausercanadjustthelog-to-linearscaleuntilthespectraldisplayresemblestheonelikeinFigureA2.1.Theidealrangeistohavefrequenciesbelow1kHzandabove10kHzascompressedaspossiblebecausebirdsandamphibiansrarelyvocalizeintheseranges.Themajorityofthefrequencyinformationshouldbecentralizedbetween1kHzand8kHz(seecorrespondingfiguresbelowforimpracticaldisplays).


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FigureA2.1–Idealsettingsforspectraldisplay.Thisisastandardformost15-17inchscreens.Importantsettingsaretimeframe(35s),frequency(scaledmanuallyherewithmostlylinearbutsomelogtoeliminatehighfrequenciesofstatic)andspectralresolution(Blackmann-Harris,FFT2048,Range132dB).

FigureA2.2–Spectraldisplayfrequencyrangeadjustedtoafulllinearscale.Herethelowerfrequenciesandbirdsongsarecompressedandhalfofthescreenisdedicatedtoinherentstatic,notideal


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FigureA2.3–Spectraldisplayfrequencyrangeadjustedtoafulllogarithmicscale.Here,thelowindustrialnoisetakesovermostofthedisplaywiththeimportancebirdsongsignaturesbecomingcompressedintheupperpartsofthespectrograph.Thesecondsettingisthetimedisplay:dependingonthewidthofacomputerscreen,ashorterorlongertimeframemaybemoreappropriatefordisplayingspectralsignatures.Generally,mostscreensusedarebetween15”-17”andthereforeatimeframebetween15-45secondsisthescalebestfitforthesescreensizes(seecorrespondingfiguresbelowforinappropriatetimeframes).Naturally,thewideryourscreen,thelongeryoucandisplayaspectrogramwithoutcompromisingquality(i.e.ona27”screen,35-50secondscanbeused).Timecanbeadjustedbyusingthe“ZoomIn”and“ZoomOut”iconsaswellassimplyscrollingwiththemousewheel.

FigureA2.4–Spectraldisplaywithalongtimeframe.Thebirdsongherearelaterallyhighlycompressedanddifficulttoidentifyvisually.Ambiguousandfainterbirdsmaybevisuallyobscuredbythesesettings.


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FigureA2.5–Spectraldisplaywithashorttimeframe.Thebirdsongsherearestillvisible,however,arelackinggeneralcontext.Somesongsmaybetruncatedandresolutionissacrificedmakingthewholedisplaymuchcoarser.Thelastsettingisthespectralresolutionofthedisplay.Theresolutionreferstotwocomponents:FFT(Fast-FourierTransform)functionandeffectivespectralresolution.Together,thesetwofunctionswilldifferentiallydisplayacousticinformation.Thefollowingpathcanmodifyspectralresolutionsettings:EDITàPREFERENCESàSPECTRALDISPLAYSAswithtimeframe,spectralresolutioncanbeadjustedtomeettheneedsoftheuser’sscreenresolution,suchas,ahigherresolutioncanfavouradeeperresolutionscreen(e.g.4096fora1920x1080screen).

FigureA2.6–Inthisexample,thespectralresolutionwasincreasedtoanFFTsizeof16384.Birdsthatdidnotcarryenoughspectralinformationbegintofadeoutandevenbirdsclosetotherecordingbeginto“fizzle”duetothehighrefiningofthedisplay.


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FigureA2.7–Inthisexample,weadjustedthespectralresolutionofthedisplay.ThiswasdonebyusingacoarserFFTsizeof128.Wecanseethatthedisplayishighlypixelatedandthatsignaturesaredifficulttoidentify.TableA2.1-SpectraldisplaysettingsinAuditionforvariousstudyspeciesStudy Size WindowType Scale DecibelRange(dB) LengthMin

(s)LengthMax(s)

Owls 4096 Blackmann-Harris Logarithmic;+3linear

126 30 90

Songbirds/Amphibs

2048 Blackmann-HarrisORHann

Logarithmic;+6-7linear

132 15 30-45

Bats 2048 Blackmann-Harris FullLinear 132 15 30-45

CalibratingspectraldisplaysinAudacityUnlikeAudition,thefrequencyaxisinAudacityismanuallyadjustableandthuscanbetailoredtofocusonaspecificfrequencyrange.Itisalsopossibletozoomin“live”evenfurtherondesiredsectionsofrecordings.TimeframesettingsarethesameasAudition–simplybyzoominginandout,ausercanrestrictorexpandtheamountoftherecordingtheyarelookingatinthewindow.Spectralresolutionssettingsarealsosimilar,allowingtheuseofvariousFFTsizesandmanipulations.ThelinksprovidedbyXeno-Canto(seebelow)illustratestheidealsettingswhileusingAudacity–experiencedobservershavebeenfoundthatareessentialidenticalwithAuditionsettingsandemulatewhatusersneedtointerpretacousticdata.Theendofthedocumentprovidesadetailedlistofthespectraldisplaysettingscalibratedspeciallyfordifferentfocusspecies.https://dl.dropboxusercontent.com/u/62295188/audacity/usingaudacity.pdfhttp://www.xeno-canto.org/forum/topic/3042


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FigureA2.8–IdealsettingsforspectraldisplaysinAudacityforsongbirds.Thisisastandardformost15-17”laptopscreens.Importantsettingsaretimeframe(20s),frequencyrange(100-12000Hz)andspectralresolution(Blackmann-Harris;FFT2048).

FigureA2.9–Herethefrequencyrangehasbeenmodified(100-6000Hz)andzoomintocutthebottomsectionofthefrequencyrange(100-3500Hzeliminated).Thebirdsongsaredistortedandsectionsaremissingbecausetheyfallintofrequenciesthatwereexcludedfromthedisplay.


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FigureA2.10–Herethefrequencyrangehasbeenmodifiedtobetoobroad(100-22000Hz).Atleasthalfofthespectraldisplayisstatic–wecanimprovethedisplayofthebirdsongbyeliminatingthesefrequencies(~10000-22000Hz).

FigureA2.11–Herewehavemodifiedonlythetimeframe.Withalongertimeframe,wecanstillseethespectralsignaturesbutthebirdsongsarelaterallycompressedandtheirvisualcharacteristicsarenotasapparent.

FigureA2.12–Amodifiedtimeframethatistooshortwillsurelyeliminatesectionsofthebirdsongandoverlyexpandtheirspectralsignatures.


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FigureA2.13–Inthisexample,weadjustedthespectralresolutionofthedisplay.ThiswasdonebyusingacoarserFFTsizeof128.Wecanseethatthedisplayishighlypixelatedandthatsignaturesaredifficulttoidentify.

FigureA2.14–Inthisexample,thespectralresolutionwasincreasedtoanFFTsizeof16384.Birdsthatdidnotcarryenoughspectralinformationbegintofadeoutandevenbirdsclosetotherecordingbeginto“fizzle”duetothehighrefiningofthedisplay.EDITàPREFERENCES

PLAYBACK:LengthofPreview:20secondsQUALITY:SampleRate:44100Hz,Bitrate:32-bitfloatINTERFACE:ShowtracknameinwaveformdisplayTRACKS:Updatedisplaywhileplaying

AutomaticallyfitframesverticallyzoomedDefaultViewMode:Spectrogram


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TableA2.2–SpectraldisplaysettingsinAudacityforvariousstudyspeciesStudy Size WindowType MinFreq

(Hz)MaxFreq(Hz)

Gain(dB)

Range(dB)

FreqGain(dB/dec)

LengthMin(s)

LengthMax(s)

Owls 4096

Blackmann-HarrisORGaussian(α=4.5)

0 8000 15(or1)*

80(or126)*

15(or0)*

30 90

Songbirds/Amphibs

2048

Blackmann-HarrisORGaussian(α=4.5)

100 12000 15(or1)*

80(or126)*

15(or0)*

15 30-45

Bats 2048

Blackmann-Harris

6000 22000 15 80 15 15 30-45

*Ifsettinggainandrange,mustfollow15-80-15ruleor1-126-0foroptimaldisplay


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APPENDIX3–SUMMARYTABLESTable1–Listofpossiblespeciesdataentryscenarios

Situation Details SpeciesID

INDIV_ID Detections/min(onlyfirst3minshown)

TMTC(toomanytocount)

VT(vocalizationtype)

TBC(Tobechecked)

Comments

1 2 3SingleIndividualknown

sings>1/recording LCSP 1 30 5 1 Song 0 singsonce LCSP 1 30 1 SS 0 calls>1/recording LCSP 1 7 1 Call 0 callsonce LCSP 1 8 1 SC 0 Non-vocalsound–1ormanytimes*NVisrecordedwhentherearebothcallsandNV,exceptforCONI

WISN 1 10 1 NV

0 Alsocalled*noteiftheindividualalsocalled

Detectedin1stsecofminute

LCSP 1 1 5 1 Song 0

SpeciesUnknown

Clearsound UNKN 1 45 5 1 Song 1 0230_unkn.Squeakycall.Faint/brief/maskedsound

UNKN 1 50 5 8 1 Song 5 Fainttrillonlyheardonce

Multipleindividualsofsamespecies

Second(orthird,etc)individual

LCSP 2 5 9 1 Song 0

Toomanytocountaccurately

LCSP 1 1 5 1 2 Song 0 Atleast4or5

Amphibiansdetected

Callsdonotoverlap BCFR 1 3 3 Song 0 Callsoverlapbuthaveperiodsofnocalls

BCFR 1 1 4 Song 0

Constantcalloverlap BCFR 1 1 5 Song 0 Abioticdetection Abiotic 1 36 -9 -9 0(or1if

unsure)

Nobioticdetectionsinlisteningperiod NONE 0 Leaveblank -9 -9 0(or1ifunsure)


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Table2-AbioticsoundsRain LIRA 1 affectstheabilitytoheardistant/faintspecies,dropsseldomhitmicrophones

MORA 2 affectstheabilitytohearnearbyspecies,dropsoftenhitmicrophonesHERA 3 significantlyaffectstheabilitytodetectspecies,dropsalmostalwayshit

microphonesWind LIWI 1 rustlingleaves/treescreaking(backgroundnoise),affectsabilitytodetect

distant/faintspeciesMOWI 2 beginstomufflemicrophones(frequencyanddecibelratesbegintospike),

occasionallyaffectsabilitytodetectnearbyspeciesHEWI 3 alwaysmufflesmicrophones,frequencyanddecibelgraphsspikeconstantly

(sometimescutsoutduetonoisethreshold)Industrialnoise compressornoise,vehiclespassing,

constructionsounds,cannons,airplanes,trains,anythingelsewithanengine

LINO 1 affectsdistant/faintspeciesdetection(generally<500Hz)MONO 2 beginstoaffectspeciesdetection(generallybetween500-2000Hz)HENO 3 significantlyaffectsabilitytodetectclose-rangespecies(generally>2000Hzbegins

toaffectspeciesdetection)Backgroundnoise

flowingwater,mosquitos,peoplemakingnoises

LIBA 1 (e.g.runningwaternotclosetorecorder)–affectsdetectionofdistant/faintspecies

MOBA 2 (e.g.moderatelyloudwater)–beginstoaffectdetectionofcloserspeciesHEBA 3 (e.g.runningwaterorrapidsveryclosetorecorder)–speciesdifficulttodetect

evenifpresent

Table3-UnknownCategories.Speciescodesareinbrackets.Unknown(UNKN)

Unknownbird Unknownpasserine(UNPA) Corvid(UNCR),Flycatcher(UNFL),Sparrow(UNSP),Swallow(UNSW),Thrush(UNTH),passerinetrill(UNTRLL),Vireo(UNVI),Warbler(UNWA)

Other Accipiter(UNAC),Buteo(UNBUTEO),Duck(UNDU),Gull(UNGU),Owl(UNOW),Black-backedorThree-toedwoodpecker(UNTTBB),Shorebird(UNSH),Tern(UNTERN),Woodpecker(UNWO),Yellowlegs(UNYE),domesticduck(DUCC)

Otherunknown Mammal(UNMA)

Amphibian(UNFR)

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