understanding the population consequences of...

Ecology and Evolution 20181ndash13 emsp|emsp1wwwecolevolorg

Received31May2018emsp |emsp Revised12July2018emsp |emsp Accepted14July2018DOI101002ece34458

R E V I E W

Understanding the population consequences of disturbance

Enrico Pirotta12 emsp|emspCormac G Booth3emsp|emspDaniel P Costa4emsp|emspErica Fleishman56emsp|emsp Scott D Kraus7emsp|emspDavid Lusseau8emsp|emspDavid Moretti9emsp|emspLeslie F New1emsp|emsp Robert S Schick1011emsp|emspLisa K Schwarz12emsp|emspSamantha E Simmons13emsp|emsp Len Thomas11emsp|emspPeter L Tyack14emsp|emspMichael J Weise15emsp|emspRandall S Wells16emsp|emsp John Harwood11

1DepartmentofMathematicsandStatisticsWashingtonStateUniversityVancouverWashington2SchoolofBiologicalEarthandEnvironmentalSciencesUniversityCollegeCorkCorkIreland3SMRUConsultingNewTechnologyCentreStAndrewsUK4DepartmentofEcologyandEvolutionaryBiologyUniversityofCaliforniaSantaCruzCalifornia5DepartmentofEnvironmentalScienceandPolicyUniversityofCaliforniaDavisCalifornia6DepartmentofFishWildlifeandConservationBiologyColoradoStateUniversityFortCollinsColorado7Anderson-CabotCenterforOceanLifeNewEnglandAquariumBostonMassachusetts8SchoolofBiologicalSciencesUniversityofAberdeenAberdeenUK9NavalUnderseaWarfareCenterNewportRhodeIsland10DukeUniversityDurhamNorthCarolina11CentreforResearchintoEcologicalandEnvironmentalModellingUniversityofStAndrewsStAndrewsUK12InstituteofMarineSciencesUniversityofCaliforniaSantaCruzCalifornia13MarineMammalCommissionBethesdaMaryland14SeaMammalResearchUnitScottishOceansInstituteSchoolofBiologyUniversityofStAndrewsStAndrewsUK15OfficeofNavalResearchMarineMammalampBiologyProgramArlingtonVirginia16ChicagoZoologicalSocietyrsquosSarasotaDolphinResearchProgramcoMoteMarineLaboratorySarasotaFlorida

ThisisanopenaccessarticleunderthetermsoftheCreativeCommonsAttributionLicensewhichpermitsusedistributionandreproductioninanymediumprovidedtheoriginalworkisproperlycitedcopy2018TheAuthorsEcology and EvolutionpublishedbyJohnWileyampSonsLtd

CorrespondenceEnricoPirottaDepartmentofMathematicsandStatisticsWashingtonStateUniversityVancouverWAEmailpirottaenricogmailcom

Funding information ThisreviewwassupportedbyOfficeofNavalResearchgrantN00014-16-1-2858ldquoPCoD+Developingwidely-applicablemodelsofthepopulationconsequencesofdisturbancerdquoTheworkbenefitedfromdiscussionswithparticipantsinaworkinggroupsupportedbyOfficeofNavalResearch(ONR)grantsN00014-09-1-0896totheUniversityofCaliforniaSantaBarbaraandN00014-12-1-0274totheUniversityofCaliforniaDavisItalsobenefitedfromdiscussionsandanalysesfundedbytheEampPSoundandMarineLifeJointIndustryProject

AbstractManaging thenonlethal effectsofdisturbanceonwildlifepopulationshasbeenalong-term goal for decisionmakers managers and ecologists and assessment oftheseeffectsiscurrentlyrequiredbyEuropeanUnionandUnitedStateslegislationHowever robust assessment of these effects is challenging Themanagement ofhumanactivities thathavenonlethal effectsonwildlife is a specific exampleof afundamental ecological problem how to understand the population-level conse-quences of changes in the behavior or physiology of individual animals that arecausedbyexternalstressorsInthisstudywereviewrecentapplicationsofacon-ceptual framework for assessing and predicting these consequences for marinemammalpopulationsWeexploretherangeofmodelsthatcanbeusedtoformalizetheapproachandweidentifycriticalresearchgapsWealsoprovideadecisiontreethatcanbeusedtoselectthemostappropriatemodelstructuregiventheavailable

2emsp |emsp emspensp PIROTTA eT Al

1emsp |emspINTRODUC TION

Thenonlethaleffectsofdisturbancewhichwedefineasadeviationinananimalrsquosphysiologyorbehaviorfrompatternsoccurringintheabsenceofpredatorsorhumans(FridampDill2002)canstronglyaf-fectwildlifepopulations(Lima1998)Understandingthepopulation-level repercussions of these changes in individual behavior andphysiologyispartofamorecomprehensiveecologicalchallengethequantificationoftrait-mediated indirecteffects (WernerampPeacor2003)alsoreferredtoasnonconsumptiveeffects(Peckarskyetal2008)onecologicalinteractionsUnderthisparadigmapredatororotherstressorcanaffectaspeciesdirectlyviatheremovalofindivid-ualsandalterationofpopulationdensity(theconsumptiveorlethaleffects)andindirectlybyinducingchangesinmorphologyphysiol-ogybehaviororlifehistory(iethespeciesrsquotraits)thatreducetheriskofpredation(SchmitzKrivanampOvadia2004)Trait-mediatedindirectinteractionscaninturnleadtocascadingeffectsonothercomponents of the ecological community (Peckarsky etal 2008RippleampBeschta2012)Characterizingtheseprocessesrequiresanintegrativeapproachthatcanscaletheresponsesofindividualani-malstodemographiceffectsinthecontextoftheirenergybalanceandthespeciesrsquolifehistory(Middletonetal2013)

Becausetheresponsesofanimalstomanyanthropogenicstimuliare similar to their responses topredation risk (BealeampMonaghan2004FridampDill2002) theevaluationandmanagementofhumanactivitiesthathavenonlethaleffectsonwildlifecanbeframedinthiswidercontextAssessingthepopulationconsequencesofdisturbance(PCoD) has been a long-term goal for ecologists decision makersandmanagersand iscurrentlya requirement formostenvironmen-tal impact assessments under European Union (European HabitatsDirective9243EEC)andUnitedStates(MarineMammalProtectionAct16USCsectsect1361et seq)legislation(Kingetal2015)Howevercomprehensiveassessmentsoftheeffectsofdisturbancearerarelyundertakenbecauseofalackofrelevantdataandbecausepermitand

policydecisionsaboutdisturbancemustbemadewithinstricttime-linesInadditiontotheseconstraintsthetheoreticalunderstandingand theempirical andanalyticalmethodsneeded toevaluate theselong-term consequences are often not available As a result man-agementdecisionshavebeengenerallybasedonevidenceofbehav-ioralresponsestodisturbancealthoughsuchresponsesmayhavenopopulation-level effect (Christiansen amp Lusseau 2015) Converselytheabsenceof anobviousbehavioral responsedoesnot ruleout apopulation-leveleffect(GillNorrisampSutherland2001)Giventhein-creasingexpansionofactivitiesthatcandisturbwildlifequantitativelylinking disturbance to population dynamics is amajor objective formodernconservation(Gilletal2001)Amechanisticunderstandingoftheprocessesbywhichdisturbanceaffectspopulationsisespeciallyuseful for long-livedwide-rangingspecies forwhichempiricaldataareoften collectedover relatively small spatial and temporal scales(NationalResearchCouncil2005)

GroupsestablishedbytheNationalResearchCouncilof theUSNationalAcademiesand theUSOfficeofNavalResearchhavead-dressedwaysofmodelingthepopulation-leveleffectsofdisturbanceonmarinemammals (NationalAcademies 2017NationalResearchCouncil 2005New etal 2014) Their efforts led to the develop-ment of a conceptual framework that summarizes the functionallinks among processes (Figure1) The underlying concept is thatdisturbance-induced changes in behavior or physiology affect fit-nessthroughindividualsrsquohealthandvitalrates(survivalreproductivesuccessandgrowthrate the latteraffectingageat firstbreeding)The population-level consequences of changes in individual fitnessdependonwhatproportionof thepopulation is affectedwhich inturndeterminesthedistributionoffitness-relatedtraits inthepop-ulationTheframeworkprovidesawaytoquantifyfourphenomena(a)thephysiologicalandbehavioralchangesthatoccurastheresultofexposuretoaparticularstressor(b)theacuteeffectsofthesephys-iologicalandbehavioralresponsesonindividualvitalratesandtheirchroniceffectsviaindividualhealthdefinedbyNewetal(2014)as

oftheInternationalAssociationofOilandGasProducersPLTandDLacknowledgesupportfromtheMASTSpoolinginitiative(MarineAllianceforScienceandTechnologyforScotlandsupportedbytheScottishFundingCouncilgrantreferenceHR09011andcontributinginstitutions)andPLTacknowledgessupportfromONRgrantN00014-15-1-2553

dataSynthesis and applicationsTheimplementationofthisframeworkhasmovedthefocusofdiscussionofthemanagementofnonlethaldisturbancesonmarinemammalpopulationsawayfromarhetoricaldebateaboutdefiningnegligibleimpactandto-ward a quantitative understanding of long-termpopulation-level effectsHerewedemonstrate the frameworkrsquos general applicability to othermarine and terrestrialsystemsandshowhowitcansupportintegratedmodelingoftheproximateandulti-mate mechanisms that regulate trait-mediated indirect interactions in ecologicalcommunitiesthatisthenonconsumptiveeffectsofapredatororstressoronaspe-ciesrsquobehaviorphysiologyorlifehistory

K E Y W O R D S

anthropogenicdisturbanceenvironmentalimpactassessmentsmarinemammalsnonconsumptiveeffectspopulationconsequencestrait-mediatedindirectinteractionsuncertainty

emspensp emsp | emsp3PIROTTA eT Al

all internal factorsthataffect fitnessorhomeostasis (c) theway inwhichchangesinhealthmayaffectindividualsrsquovitalratesand(d)howchangesinindividualvitalratesmayaffectpopulationdynamics

Thirteen years after the first published formalization of thisframework (NationalResearchCouncil 2005)we review its ap-plicationstomarinemammalpopulationsWefirstdiscusstheas-sessmentoftheexposurelevelsofindividualsinapopulationandthen review theapproaches thathavebeenused tomodeleachofthefunctionallinksintheframework(Figure2)Oursynthesiswillhelpreconcilethemarinemammal literaturewithstudiesonothertaxathathavequantifiedtheeffectsofanthropogenicdis-turbanceonvitalratesandpopulationdynamics(egBroekhuis2018CoetzeeampChown2016GreenJohnson-UlrichCouraudamp Holekamp 2018 Kight amp Swaddle 2007 McClung SeddonMassaro amp Setiawan 2004 Wood Stillman amp Goss-Custard2015)WealsoprovideadecisiontreethatcanguidetheselectionofthemostapplicablePCoDmodelingapproachgiventheinfor-mationavailable

2emsp |emspESTIMATING LE VEL S OF E XPOSURE IN THE POPUL ATION

Estimating the population-level consequences of individualsrsquo responsestodisturbancerequires informationontheproportionofthepopulationthatisexposedtothestressorandtheaggregate

exposureofeachindividual(iethetotaldurationandintensityofexposuretothestressorduringagivenperiod)InthiscontextthestressorcorrespondstoananthropogenicsourceofdisturbanceThe spatial and temporal overlap between the stressor and thefocalanimalsdeterminestheprobabilityofexposureThisoverlapisinfluencedbythepatternsbywhichthestressorisproducedatthe source and propagates through the environment (MerchantFaulknerampMartinez2018)andtheanimalsrsquoresidencetimeintheareawhereexposuremayoccur (CostaHuumlckstaumldt etal 2016)Residence time is determined inter alia by the size of individualhomerangesthemotivationunderlyingtheuseoftheareaofin-terest(egwhethertheareacontainsforagingpatchesorisusedsolely for transit) and any migratory behavior In some casesthese factorsmay result in the lackof anygeographicalor tem-poraloverlapbetweenapopulationandastressorobviatingtheneedtoassesspopulationeffects

Webelievethatevaluatingthespatialandtemporaloverlapbe-tweenapopulationrsquosrangeandthedistributionofstressorsonthebasisofdensitymapsderivedfromtheresultsofdedicatedorhis-torical surveys (Ellison etal 2016Hammond etal 2002) shouldbe a routine component of environmental impact assessmentsTelemetry data can provide information on the patterns of re-peatedexposureforspecificindividuals(Costaetal2003Falconeetal2017Jonesetal2017Madsenetal2006PirottaNewampMarcoux2018)andphotographicidentification(egCalambokidisBarlowFordChandlerampDouglas2009)canbeusedtoestimate

F IGURE 1emspThePopulationConsequencesofDisturbance(PCoD)conceptualframeworkmodifiedfromNationalAcademies(2017)TheboxeswithinthedashedgrayboundarylinerepresenttheeffectsofexposuretoastressorandarangeofecologicaldriversonthevitalratesofanindividualanimalTheeffectsarethenintegratedacrossallindividualsinthepopulationtoprojecttheireffectsonthepopulationrsquosdynamics


exposure risks for regularly monitored populations (ChristiansenBertulliRasmussenampLusseau2015PirottaThompsonCheneyDonovanampLusseau2015) Inalternativesomestudiesexaminedtheconsequencesofexposingallindividualsinapopulationtothesameamountofdisturbance(BraithwaiteMeeuwigampHipsey2015Newetal2014Villegas-AmtmannSchwarzGaileySychenkoampCosta2017Villegas-AmtmannSchwarzSumichampCosta2015)

3emsp |emspEFFEC T OF E XPOSURE ON PHYSIOLOGY AND BEHAVIOR

TheinitialstepinimplementingthePCoDframework(Figure1)isthe quantification of the physiological and behavioral responsesof individuals to a knownorpotential stressorControlledexpo-sureexperiments(Harrisetal2018)haveusedelectronicloggers

to assess changes in themovement and vocalizations ofmarinemammalsexposedtomilitarysonarandairgunsusedforseismicsurveys(Dunlopetal2013Wensveenetal2017)Loggershavealso been applied to monitor marine mammal responses to ac-tual disturbance events for example of Cuvierrsquos beakedwhales(Ziphius cavirostris)tosonarexercises(Falconeetal2017)aswellasofharborseals(Phoca vitulina)topiledrivingforwindfarmcon-struction (Russell etal 2016) and to pedestrian and vessel ap-proachesat theirhaul-outs (AndersenTeilmannDietzSchmidtampMiller 2014) Visual observations have been used to quantifyactivitybudgetsandestimatechanges inbehaviorssuchas rest-ing or foraging in the presence of other human activities suchas whale watching (eg Christiansen Rasmussen amp Lusseau2013 Lusseau 2003New etal 2015Williams Trites amp Bain2002) Visual studies on pinnipeds have alsomonitored flushingresponse and return to haul-out sites (eg Cowling Kirkwood

F IGURE 2emspStudiesinvestigatingthePopulationConsequencesofDisturbance(PCoD)onmarinemammalsupdatedfromNowacekChristiansenBejderGoldbogenandFriedlaender(2016)Thearrowsindicatethefunctionalstepsoftheframework(simplifiedontop)thatwereincludedineachstudyWhitegapsinthearrowsindicatestudiesthatevaluatedthelinkbetweenbehaviorandvitalratesdirectlywithoutestimatinghealth


Boren Sutherland amp Scarpaci 2015Osterrieder Salgado KentampRobinson2017)PassiveacousticmonitoringtechniquesofferamorecontinuousalternativetovisualsamplingforcollectingsuchdataoncetaceansTheyhavebeenusedtoassesstheresponsesof harbor porpoises (Phocoena phocoena) to wind farm develop-ments (Brandt Diederichs Betke ampNehls 2011Nabe-NielsenSiblyTougaardTeilmannampSveegaard2014Nabe-Nielsenetal2018) of Blainvillersquos beaked whales (Mesoplodon densirostris) tosonar (Morettietal2014Tyacketal2011) andofbottlenosedolphins (Tursiops truncatus) toboatpresence (PirottaMerchantThompsonBartonampLusseau2015)Intheabsenceofempiricaldata behavioral responses have been extrapolated from better-studied species or assumed often in terms of the number oflost foraging days (King etal 2015 New etal 2014 Villegas-Amtmannetal20152017)Moststudies(egWilliamsLusseauamp Hammond 2006) have evaluated the decrease in energy in-take due to the observed behavioral responses However therehave been efforts to quantify the change in energy expenditureassociated with avoidance responses (Braithwaite etal 2015Christiansen Rasmussen amp Lusseau 2014 Miller etal 2009Williams Blackwell Richter Sinding amp Heide-Joslashrgensen 2017WilliamsKendalletal2017)Measuringphysiologicalresponsestodisturbance ismorechallengingthanmeasuringbehavioralre-sponses and may require the analysis of tissue exhalations orfeces fromwild animals (Hogg etal 2009 Rolland etal 2012)dedicated physiological tags (Karpovich Skinner Mondragon ampBlundell2015WilliamsBlackwelletal2017WilsonWikelskiWilsonampCooke2015)orexperiments incaptivity (KvadsheimSevaldsen Folkow amp Blix 2010 Miksis etal 2001 ThomasKasteleinampAwbrey1990)Duetotheselimitationsmostapplica-tionsofthePCoDframeworkhavenotmodeledthephysiologicalconsequencesofdisturbanceexplicitly

4emsp |emspEFFEC T OF BEHAVIOR AL AND PHYSIOLOGIC AL CHANGES ON HE ALTH

Somebehavioralorphysiologicalchangescanhaveacuteeffectson individualsrsquovital rates forexamplebychanging theirpreda-tion risk or because injury directly affects their survival prob-ability (Hooker etal 2012) However such changes can alsoaffect vital rates indirectly by impairing an individualrsquos healthModeling health explicitly provides themechanistic link scalingindividual responses todemographiceffects that is required fortheassessmentoftrait-mediatedindirectinteractions(Middletonetal 2013)Although an individualrsquos health encompassesmanyaspectsofitsphysiology(forexampleimmunestatusstresslev-elsandcontaminantandparasite loadPettisetal2017)mostPCoDapplicationshaveused an individualrsquos energy stores (thatisitsbodycondition)asthemeasureofhealthForexampleNewetal (2014)andSchickNewetal (2013)examinedtherelationbetween foraging activity and energy stores (estimated fromchangesinbuoyancy)offemalesouthernelephantseals(Mirounga

leonina)overthecourseofaforagingtripOtherapplicationshaveinferredchangesinenergystoresfrommodelsofforagingactivitythateither treatenergyexplicitlyusingabioenergeticapproach(Beltran Testa amp Burns 2017 Christiansen amp Lusseau 2015Farmer Noren FougegraveresMachernis amp Baker 2018McHuronCostaSchwarzampMangel2017McHuronMangelSchwarzampCosta2017Noren2011PirottaMangeletal2018Villegas-Amtmann etal 2015 2017) or use an arbitrarily scaled energymetric that represents an underlying motivational state (Nabe-Nielsen etal 2014 2018 New Harwood etal 2013 PirottaHarwoodetal2015PirottaNewHarwoodampLusseau2014)Althoughtechnologiesthatcanmeasurethemorphometricsofin-dividualsremotelymaymakeiteasiertoestimatechangesinbodycondition directly (eg Christiansen Dujon Sprogis ArnouldampBejder 2016Miller Best Perryman Baumgartner ampMoore2012) extensive health assessment in cetaceans will probablyremain limited to a few closely monitored coastal populationsduetologisticalconstraints(Wellsetal2004)Incontrastsomepinniped populations can be regularly accessed tomeasure thevariation in body condition and health among individuals (egMcDonaldCrockerBurnsampCosta2008McMahonHarcourtBurton Daniel amp Hindell 2017 Shero Krotz Costa Avery ampBurns 2015 Wheatley Bradshaw Davis Harcourt amp Hindell2006) However evenwhen such assessments are possible es-tablishingthecauseofobservedchangesinhealthischallenging

5emsp |emspEFFEC T OF VARIATIONS IN HE ALTH ON VITAL R ATES

Formostspeciesfewempiricaldataareavailabletoquantifytherelation between an individualrsquos health and its vital rates Newetal(2014)andCostaSchwarzetal(2016)usedempiricaldataontherelationbetweenafemaleelephantsealrsquosenergystoresatthestartoflactationandtheweaningmassofherpupwhichaf-fectsthepuprsquossurvivalprobability (McMahonBurtonampBester20002003)asthebasisfortherelationbetweenhealthandre-productivesuccessSchickKrausetal (2013)andRollandetal(2016) used state-space models linking the health of individualNorth Atlantic right whales (Eubalaena glacialis) obtained fromtheintegrationofmultiplephotographicassessmentstotheirsur-vivalandfertilitySchwackeetal (2017)usedarespiratorymet-ric of health to quantify the effect of theDeepwater Horizon oil spillonvitalratesofbottlenosedolphinsintheGulfofMexicoIntheabsenceofadirectestimateofcalfsurvivalChristiansenandLusseau(2015)usedthefetallengthofminkewhales(Balaenoptera acutorostrata) as a proxy and investigated how fetal lengthwasassociatedwithfemalebodycondition(ChristiansenViacutekingssonRasmussenamp Lusseau2014)All otherPCoD studiesofmarinemammals have assumed a simple relationship between varioushealthmetricsandvitalrates(McHuronCostaetal2017Nabe-Nielsenetal20142018PirottaMangeletal2018Villegas-Amtmannetal20152017)


6emsp |emspA DIREC T LINK BET WEEN E XPOSURE AND VITAL R ATES

Fewmonitoringprogramscollectinformationonthechangesinin-dividual health and vital rates thatmay result frombehavioral re-sponsestodisturbanceInsituationswhereamanagementdecisionisneededandthisinformationisnotavailableapragmaticalterna-tiveistouseasinglefunctiontolinkbehavioralresponsesdirectlytovitalratesThishasbeenreferredtoasaninterimPCoDapproach(Kingetal2015)becausethisfunctionshouldbereplacedwithonebasedonempiricallyderivedvaluesassoonastheybecomeavail-able In someof these cases structured elicitation of informationfrommultipleexperts(knownasexpertelicitation)canprovidebothestimatesoftheappropriateparametersandameasureoftheasso-ciateduncertainty(Kingetal2015Martinetal2012OedekovenFleishmanHamiltonClarkampSchick2015)Inalternativethemeas-uredeffectof changes inprey availability canbeusedas aproxyfor the relation between energy intake and vital rates (WilliamsThomas Ashe Clark ampHammond 2016) The latter requires theassumptionthatareductioninforagingtimeresultingfromdistur-banceisequivalenttoareductionintheavailabilityofprey

7emsp |emspMODELING THE EFFEC T OF VITAL R ATES ON POPUL ATION DYNAMIC S

ThefinalstepinthePCoDconceptualmodelisthepropagationofchangesinindividualsrsquovitalratestothepopulationItisbeyondthescope of this study to review methods for modeling the dynam-icsofwildlifepopulationsHerewedescribethetypesofpopula-tionmodelsthathavebeenusedorcouldbeusedtoestimatethepopulation-leveleffectsofdisturbanceTheyliealongacontinuumfromtreatingallanimalsinapopulationasidenticaltoconsideringallanimalsasuniqueindividualsthatarefollowedfrombirthtodeath(ieindividual-oragent-basedmodels[IBMs])

Because traditional matrix models (Caswell 2001) are formu-lated indiscrete time theygenerally have abirth-pulse structureInthisstructureallbirthsanddeathsareassumedtooccuratthesamemoment intimewhichusuallycorrespondstothetransitionfromoneageclasstothenextandallindividualswithinaclassaretreatedasidenticalHoweverclassesmaybesubdividedtoreflectthedifferentvitalratesofdisturbedandundisturbedanimals(Kingetal2015)MostPCoDapplicationshaveusedasimpleLesliema-trixtopredictthetrajectoryofapopulationunderdifferentscenar-iosofanthropogenicdisturbance(Kingetal2015Newetal2014Schwackeetal2017)Matrixmodelshistoricallyassumedthatvitalratesaresimplyafunctionofanindividualrsquosageorstagebutintegralprojectionmodels(IPMs)accountfortheadditionaleffectsofcon-tinuouslyvaryingtraits (suchasphysicalsize)onvital rates (EllnerampRees2006) Inprincipleacontinuousmeasureofhealthortheamount of disturbance experienced by different individuals couldbemodeledasafitness-relatedtrait(Coulson2012)Howeverbe-causeIPMsdonotassigntraitstospecificindividualsindividualsare

stillnotconsistentlyfollowedovertimeandmodelsareformulatedindiscretetime

In reality survival and reproduction are affected by an indi-vidualrsquos physiological status and behavior in a complex manner(Houston amp McNamara 1999) and changes induced by distur-bancecanaffectvitalratesfromthemomentatwhichdisturbanceoccursContinuous-timelife-historymodels(DeRoos2008)couldthereforebemoreappropriateforestimatingthepopulation-leveleffects of disturbance Although continuous-time life-historymodelsalsoassume individualsare identical theycanreadilybestructured intomultipleclasses (DeRoosGalicampHeesterbeek2009)

IBMsfollowsimulatedindividualsthroughouttheirlifeallowingforexplicitmodelingofindividualheterogeneityandenvironmentalstochasticity in quasi-continuous time (GrimmampRailsback 2013)SomePCoDapplicationsdevelopedIBMsthatsimulate individualsmovingaccessingpreyandaccumulatingenergystorestosustainsurvival and reproduction (New Harwood etal 2013 PirottaHarwoodetal2015Pirottaetal2014Villegas-Amtmannetal2015)Howeveronlythreestudies(Nabe-Nielsenetal20142018Villegas-Amtmannetal 2017) haveused IBMs topredict thedy-namics of a population over time Although IBMs require consid-erabledatatheyareextremelyflexibleInadditionsimplemodelswith sufficient realismcanoftenbeconstructedon thebasisof arelativelysmallamountofempirical informationUnknownparam-etersmay as an interimmeasure be extrapolated from a specieswith a comparable life history (Sibly etal 2013) as long as theirinfluence on the modelrsquos outcome is explicitly quantified and ac-knowledged forexampleusingsensitivityanalysisModelparam-eters then can be optimizedwith standard calibration techniques(GrimmampRailsback2013)orfittedtodatawithBayesianinference(KattwinkelampReichert 2017) IBMs can also be implemented viastochasticdynamicprogramming (MangelampClark1988)andusedtoestimateoptimalbehaviorgivenestimatesofstatevariablesovertimeTheabilityofthisapproachtoforecastpopulation-leveleffectsofdisturbancewasdemonstratedforpinnipedsbyMcHuronCostaetal(2017)andforEasternNorthPacificbluewhales(Balaenoptera musculus)byPirottaMangeletal(2018)whereasKlaassenBauerMadsenandTombre(2006)usedstochasticdynamicprogrammingto quantify the effects of disturbanceon the survival of Svalbardpink-footedgeese(Anser brachyrhynchus)

8emsp |emspCHOOSING A MODEL STRUC TURE

Inmost situations selection of amodel structure to forecast thepopulation-leveleffectsofdisturbanceislikelytobedrivenbydataavailability(Figure3)NoPCoDmodeltodatehasbeenfullyparam-eterizedwithempiricaldataEvenmodelsthatencompassthechainfrom exposure to population dynamics (King etal 2015 Nabe-Nielsenetal20142018Newetal2014Villegas-Amtmannetal2017Williamsetal2016)haveuseddataextrapolatedfromotherspeciesexpertjudgmentsproxyrelationsorinformedassumptions


Thefirststepinchoosingamodelistoevaluatetheavailabilityofestimatesofbasicdemographicparameters suchasvital ratespopulationgrowthrateorageatfirstbreedingormaturityPreciseestimatesoftheseparametersarenotessentialandmissingvaluescanbeinferredifreliableestimatesofotherdemographicattributesareavailableIfnodemographicinformationisavailableforthetar-getpopulationorarelatedspeciesPCoDmodelingisnotpossible(outcome1inFigure3)but insights intoapopulationrsquospropensityforPCoDcanbeobtainedfromfirstprinciplesusingprospectiveap-proaches(NattrassampLusseau2016)Althoughsomedemographicparameters are emergent properties of bioenergetic models (seebelow)estimatesof theseparametersareneededtocalibrate themodelsandvalidatetheirpredictions

Thesecondstepistoassessevidenceofempiricalrelationsbe-tweenmeasuresofindividualhealthandfitnessForexampleNewetal (2014) estimated a relation between pup survival and totalbody lipidof adult female elephant seals If no empirical informa-tionisavailableasimpletheoreticalrelationbetweenanindividualrsquos

healthanditssubsequentsurvivalfecundityorgrowthcanbeas-sumed(NewMorettiHookerCostaampSimmons2013)Typicallysuchrelationsarehyperbolic(Nabe-Nielsenetal2014)orsigmoidal(McHuronCostaetal2017)

ThethirdstepistoinvestigatewhetherthereareempiricaldataontherelationbetweenbehavioralchangeandindividualhealthIfsuchinformationisunavailablebioenergeticmodelscanbeusedtoexaminethepotentialeffectsoflostforagingopportunitiesonanin-dividualrsquoshealthasmeasuredbyitsenergystores(McHuronCostaetal2017Nabe-Nielsenetal20142018PirottaMangeletal2018 Villegas-Amtmann etal 2015 2017) This allows construc-tionofafullPCoDmodelforthepopulation(outcome3inFigure3)asinNewetal(2014)Thebasicdatarequiredtoconstructsuchbio-energeticmodelsaredurationofgestationandlactationagrowthcurvetopredictmassatdifferentagesandanestimateoffieldmet-abolicrate(CostaampMaresh2017Villegas-Amtmannetal2015)Ideally these data should be collected from the target species orpopulation but they can be derived theoretically or from related

F IGURE 3emspDecisiontreetoguideselectionofthemostsuitablePopulationConsequencesofDisturbance(PCoD)modelforagivenpopulationgivendataavailabilityDecisionpointsarerepresentedbydiamondsandpossibleoutcomesbyrectangles


species The resultingmodels can be calibrated using informationonthedemographyofthepopulationsuchastheratioofcalvestomature femalesExpertelicitationcanbeusedto fill someknowl-edgegapsforexampletoestimatethelevelofenergystoresbelowwhichstarvationmortalitymayoccuror toestablishwhether therateofmilktransferisdeterminedbytheoffspringorthemother

If there is insufficient information to develop a bioenergeticmodel expertelicitationcanbeused toestimateadirect relationbetweenbehavioral changeandvital ratesThis is representedbyoutcome2ofthedecisiontree(Figure3)theuseofaninterimPCoDapproach(Kingetal2015)

9emsp |emspINCORPOR ATING UNCERTAINT Y

Whichevermodelischosenitisnecessarytoquantifyuncertaintyatallstagesofmodeling(HarwoodampStokes2003Milner-Gullandamp Shea 2017) Uncertainty arises through the precise choice ofmodel parameterization the specification of input parameter val-ues environmental stochasticity and variation among individualsIncorporation and propagation of these uncertainties vary amongthemodelingapproachesdescribedaboveForexampleinIBMsitispossibletosimulatefromdistributionsoninputparametersandto include environmental stochasticity and variation among indi-vidualsinthesimulation(GrimmampRailsback2013)Toincorporatemodeluncertaintysimulationscansamplefromalternativeparam-eterizationsalthoughthisrarelyisdoneinpracticeBycontrastlife-historymodelsareintrinsicallydeterministicalthoughitispossibletorepeatthemodelingwithdifferentinputsInallcaseswhereun-certaintyisnotexplicitlyincorporatedintothemodelingwesuggestthatasensitivityanalysisbeperformedposthoctodeterminetherobustnessof conclusions toplausibleviolationofmodel assump-tionsandvariationintheinputsUncertaintyintheestimatedpopu-lationconsequenceultimatelycanbereportedasadistributionofpotentialoutcomesThiswillallowtheprecautionaryprincipletobeappliediftheresultsareusedtomakemanagementdecisions

10emsp |emspAPPLIC ATIONS OF PCOD MODEL S

Since itsformulation(NationalResearchCouncil2005)thePCoDconceptualmodelhasservedasacommonframeworkforexamin-ingthepotentialeffectsofnonlethalhumandisturbanceonmarinemammal populations accounting for the uncertainties associatedwitheach step in theprocessUseof thismodelhaschanged thefocus of the scientific discussion from establishing subjectivethresholds of acceptable behavioral change to quantifying long-termpopulation-leveleffects(NationalAcademies2017)

Real-worldapplicationsofthePCoDframework inthe lastde-cade used a range of modeling approaches to translate the con-ceptual model into a mathematical structure and highlightedchallengesanddatagaps (Figure2)Theeffectsofdisturbanceonpopulationsizepredictedinthesestudiesweregenerallytoosmall

forshort-termdetectionwithconventionalmethodsofabundanceestimation(TaylorMartinezGerrodetteBarlowampHrovat2007)Yet these effects could have substantial medium-term effects onpopulationstatus

To remain tractable most PCoD models to date consideredonedisturbancesourceorscenario in isolationHowevermultiplesources of disturbance are likely to occur in an area at any giventime together with other concurrent environmental and ecolog-ical processes Attributing causation to a single stressor and de-veloping mitigation measures therefore is challenging in practiceAccordinglythePCoDframeworkrecentlywasexpandedtoincor-porate the cumulative effects ofmultiple stressors andecologicaldrivers(NationalAcademies2017)

Although models of the population consequences of anthropo-genicdisturbancehavebeendeveloped toassess theeffectsofex-pandinghumanactivitiesintheoceanonmarinemammalpopulationsthePCoDframeworkisrelevantforothermarineandterrestrialtaxaTheliteratureontheeffectsofhumandisturbanceonwildlifebehaviorisextensive(egBlumsteinFernaacutendez-JuricicZollnerampGarity2005Stankowich 2008)Moreovermany studies have linked changes inbehaviorderivingfrominteractionswithhumanstothesurvivalandreproductive success of individuals (eg Broekhuis 2018DussaultPinardOuelletCourtoisampFortin2012EllenbergMatternSeddonamp Jorquera 2006 Giese 1996 Gosselin Zedrosser Swenson ampPelletier2014Kerleyetal2002KightampSwaddle2007McClungetal 2004 Rodriguez-Prietoamp Fernandez-Juricic 2005) and somehave quantified the long-term effects on population dynamics (egCoetzeeampChown2016Greenetal2018IversonConverseSmithamp Valiulis 2006Wood etal 2015) These studies could be incor-porated intotheunifyingframeworkwedescribeheretomodelthe effectsofmanyformsofnonlethalanthropogenicdisturbance

There is interest in integratingproximate (mechanismsand func-tions)andultimate(adaptationandfitnessvalue)aspectsofbehaviorintoconservation(Cookeetal2014Sutherland1998)Knowledgeofthephysiologicalmechanismsofananimalrsquosinteractionwithitsenvi-ronmentisalsorelevanttoconservation(WikelskiampCooke2006)ThePCoDapproachprovidesameans for investigating thephysiologicalandthebehavioraldriversofanindividualrsquosresponsetohumandistur-banceandthereforeapopulationrsquosviability(Cookeetal2014)Linkingbehavioral and physiological changes to demography also facilitatespredictionoftheeffectsofclimatechangeonwildlifepopulations(egDesprezJenouvrierBarbraudDelordampWeimerskirch2018Paganoetal2018Weimerskirch2018)Moregenerallythenonlethaleffectsofhumandisturbanceandenvironmentalchangeandtheirrepercus-sionsatapopulationlevelcanbeviewedasexamplesofthefundamen-talprocessesregulatingtrait-mediatedindirectecologicalinteractions(RippleampBeschta2012WernerampPeacor2003)Disentanglingcon-sumptive and nonconsumptive effects requires an understanding oftheinteractionsamongtheindividualpopulationandcommunitylev-els(Schmitzetal2004)andintegrativeapproachesarenecessarytolinkindividualbehaviorenergybalanceandlifehistoryandtoinvesti-gatedemographiceffects(Middletonetal2013)ThePCoDapproachthereforecouldofferaformalframeworkfortheinvestigationofthe


proximatemechanismsoftheseandotherecologicalphenomenathatoperateviachangesattheindividuallevelExperiencealreadygainedfromapplicationofPCoDmodelstomarinemammalpopulationspro-vides practical guidance formodel development and data collection(Fleishmanetal2016)

ACKNOWLEDG MENTS

ThisreviewwassupportedbyOfficeofNavalResearchgrantN00014-16-1-2858 ldquoPCoD+ Developing widely-applicable models of thepopulation consequences of disturbancerdquo Thework benefited fromdiscussionswithparticipantsinaworkinggroupsupportedbyOfficeofNavalResearch(ONR)grantsN00014-09-1-0896totheUniversityofCaliforniaSantaBarbaraandN00014-12-1-0274totheUniversityof California Davis It also benefited from discussions and analysesfundedby theEampPSoundandMarineLife Joint IndustryProjectofthe InternationalAssociationofOil andGasProducers PLT andDLacknowledge support from the MASTS pooling initiative (MarineAlliance for Science andTechnology for Scotland supported by theScottishFundingCouncilgrantreferenceHR09011andcontributinginstitutions)andPLTacknowledgessupportfromONRgrantN00014- 15-1-2553Wethanktwoanonymousreviewers for theircommentsonthemanuscript

CONFLIC T OF INTERE S T

Nonedeclared

AUTHORSrsquo CONTRIBUTIONS

AllauthorscontributedtodiscussionsthatsupportedthedevelopmentoftheframeworkandledtothepresentreviewofitsapplicationsEPandJHledthewritingofthemanuscriptAllauthorscontributedcriti-callytothedraftsandgavefinalapprovalforpublication

DATA ACCE SSIBILIT Y

Nodataareassociatedwiththismanuscript

ORCID

Enrico Pirotta httporcidorg0000-0003-3541-3676

R E FE R E N C E S

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Beale C M amp Monaghan P (2004) Human disturbance People aspredation-free predators Journal of Applied Ecology41 335ndash343httpsdoiorg101111j0021-8901200400900x

BeltranRSTestaJWampBurnsJM(2017)Anagent-basedbioen-ergeticsmodel forpredicting impactsof environmental changeon

a topmarine predator theWeddell sealEcological Modelling35136ndash50httpsdoiorg101016jecolmodel201702002

Blumstein D T Fernaacutendez-Juricic E Zollner P A amp Garity S C(2005) Inter-specific variation in avian responses to human dis-turbance Journal of Applied Ecology 42 943ndash953 httpsdoiorg101111j1365-2664200501071x

BraithwaiteJEMeeuwigJJampHipseyMR(2015)Optimalmigra-tionenergeticsofhumpbackwhalesandtheimplicationsofdistur-banceConservation Physiology31ndash15

BrandtMDiederichsABetkeKampNehlsG (2011)ResponsesofharbourporpoisestopiledrivingattheHornsRevIIoffshorewindfarm in theDanishNorth SeaMarine Ecology Progress Series421205ndash216httpsdoiorg103354meps08888

BroekhuisF (2018)Naturalandanthropogenicdriversofcubrecruit-ment in a large carnivore Ecology and Evolution 8 6748ndash6755httpsdoiorg101002ece34180

CalambokidisJBarlowJFordJKBChandlerTEampDouglasAB (2009) Insights into the population structure of bluewhales inthe EasternNorth Pacific from recent sightings and photographicidentification Marine Mammal Science 25 816ndash832 httpsdoiorg101111j1748-7692200900298x

Caswell H (2001)Matrix population models Sunderland MA SinauerAssociates

ChristiansenFBertulliCGRasmussenMHampLusseauD(2015)Estimating cumulative exposure of wildlife to non-lethal distur-banceusingspatiallyexplicitcapturendashrecapturemodelsThe Journal of Wildlife Management 79 311ndash324 httpsdoiorg101002jwmg836

ChristiansenFDujonAMSprogisKRArnouldJPYampBejderL(2016)Non-invasiveunmannedaerialvehicleprovidesestimatesoftheenergeticcostofreproductioninhumpbackwhalesEcosphere7e01468httpsdoiorg101002ecs21468

Christiansen F amp Lusseau D (2015) Linking behaviour to vitalrates to measure the effects of non-lethal disturbance on wild-life Conservation Letters 8 424ndash431 httpsdoiorg101111conl12166

Christiansen F Rasmussen M amp Lusseau D (2013) Whale watch-ing disrupts feeding activities of minke whales on a feedinggroundMarine Ecology Progress Series 478 239ndash251 httpsdoiorg103354meps10163

ChristiansenFRasmussenMHampLusseauD(2014)InferringenergyexpenditurefromrespirationratesinminkewhalestomeasuretheeffectsofwhalewatchingboatinteractionsJournal of Experimental Marine Biology and Ecology459 96ndash104 httpsdoiorg101016jjembe201405014

Christiansen F Viacutekingsson G A Rasmussen M H amp Lusseau D(2014) Female body condition affects foetal growth in a capitalbreeding mysticete Functional Ecology 28 579ndash588 httpsdoiorg1011111365-243512200

CoetzeeBWTampChownSL(2016)Ameta-analysisofhumandis-turbance impactsonAntarcticwildlifeBiological Reviews91578ndash596httpsdoiorg101111brv12184

CookeSJBlumsteinDTBuchholzRCaroTFernaacutendez-JuricicEFranklinCEhellipWikelskiM (2014)PhysiologybehaviorandconservationPhysiological and Biochemical Zoology871ndash14httpsdoiorg101086671165

Costa D P Crocker D E Gedamke JWebb PM Houser D SBlackwell S B hellip Le Boeuf B J (2003) The effect of a low-frequencysoundsource(acousticthermometryoftheoceanclimate)onthedivingbehaviorofjuvenilenorthernelephantsealsMirounga angustirostris Journal of the Acoustical Society of America1131155ndash1165httpsdoiorg10112111538248

CostaDPHuumlckstaumldtLASchwarzLKFriedlaenderASMateBRZerbiniANhellipGalesNJ(2016)Assessingtheexposureofanimals to acoustic disturbance Towards an understanding of the


populationconsequencesofdisturbanceProceedings of Meetings on Acoustics27010027httpsdoiorg10112120000298

CostaDPampMaresh J L (2017) Energetics InBWuumlrsig JGMThewissenampKKovacs(Eds)Encyclopedia of marine mammals(pp329ndash335)SanDiegoCAAcademicPress

CostaDPSchwarzLRobinsonPSchickRSMorrisPAConditRhellipKilpatrickAM(2016)Abioenergeticsapproachtounderstand-ingthepopulationconsequencesofdisturbanceElephantsealsasamodelsystemInANPopperampAHawkins(Eds)Effects of noise on aquatic life II(pp161ndash169)NewYorkNYSpringerScience+BusinessMediahttpsdoiorg101007978-1-4939-2981-8

CoulsonT (2012) Integralprojectionsmodels their constructionanduseinposinghypothesesinecologyOikos1211337ndash1350httpsdoiorg101111j1600-0706201200035x

Cowling M Kirkwood R Boren L Sutherland D amp Scarpaci C(2015) The effects of vessel approaches on theNewZealand furseal(Arctocephalus forsteri)inthebayofplentyNewZealandMarine Mammal Science31501ndash519httpsdoiorg101111mms12171

DeRoosAM (2008)Demographic analysis of continuous-time life-historymodelsEcology Letters111ndash15

De Roos A M Galic N amp Heesterbeek H (2009) How resourcecompetition shapes individual life history for nonplastic growthUngulates in seasonal food environments Ecology 90 945ndash960httpsdoiorg10189007-11531

DesprezMJenouvrierSBarbraudCDelordKampWeimerskirchH(2018)Linkingoceanographicconditionsmigratoryschedulesandforagingbehaviourduringthenon-breedingseasontoreproductiveperformance in a long-lived seabirdFunctional Ecology32 2040ndash2053httpsdoiorg1011111365-243513117

DunlopRANoadMJCatoDHKniestEMillerPJOSmithJ N amp StokesM D (2013)Multivariate analysis of behaviouralresponse experiments in humpback whales (Megaptera novaean-gliae) Journal of Experimental Biology 216 759ndash770 httpsdoiorg101242jeb071498

DussaultCPinardVOuelletJ-PCourtoisRampFortinD (2012)AvoidanceofroadsandselectionforrecentcutoversbythreatenedcaribouFitness-rewardingormaladaptivebehaviourProceedings of the Royal Society of London Series B Biological Sciences2794481ndash4488httpsdoiorg101098rspb20121700

Ellenberg U Mattern T Seddon P J amp Jorquera G L (2006)Physiological and reproductive consequences of human distur-bance in Humboldt penguins The need for species-specific visi-tor management Biological Conservation 133 95ndash106 httpsdoiorg101016jbiocon200605019

EllisonWTRaccaRClarkCWStreeverBFrankelASFleishmanEhellipThomasL(2016)Modelingtheaggregatedexposureandre-sponsesofbowheadwhalesBalaena mysticetustomultiplesourcesofanthropogenicunderwatersoundEndangered Species Research3095ndash108httpsdoiorg103354esr00727

Ellner S PampReesM (2006) Integral projectionmodels for specieswith complex demographyThe American Naturalist167 410ndash428httpsdoiorg101086499438

Falcone E A Schorr G SWatwood S L Deruiter S L ZerbiniANAndrewsRDhellipMorettiDJ(2017)DivingbehaviourofCuvierrsquos beaked whales exposed to two types of military sonarRoyal Society Open Science 4 170629 httpsdoiorg101098rsos170629

FarmerNANorenDPFougegraveresEMMachernisAampBakerK(2018)Resilienceof theendangered spermwhalePhyseter macro-cephalustoforagingdisturbanceintheGulfofMexicoUSAAbio-energetic approachMarine Ecology Progress Series 589 241ndash261httpsdoiorg103354meps12457

FleishmanECostaDPHarwoodJKrausSMorettiDNewLFhellipWells R S (2016)Monitoringpopulation-level responsesof

marinemammals to human activitiesMarine Mammal Science 321004ndash1021httpsdoiorg101111mms12310

FridAampDillL(2002)Human-causeddisturbancestimuliasaformofpredationriskConservation Ecology611httpsdoiorg105751ES-00404-060111

GieseM(1996)EffectsofhumanactivityonadeliepenguinPygoscelis adeliae breeding success Biological Conservation 75 157ndash164httpsdoiorg1010160006-3207(95)00060-7

Gill J ANorris K amp SutherlandW J (2001)Why behavioural re-sponses may not reflect the population consequences of humandisturbance Biological Conservation 97 265ndash268 httpsdoiorg101016S0006-3207(00)00002-1

GosselinJZedrosserASwensonJEampPelletierF(2014)Therel-ative importance of direct and indirect effects of huntingmortal-ity on thepopulationdynamicsof brownbearsProceedings of the Royal Society of London Series B Biological Sciences28220141840httpsdoiorg101098rspb20141840

GreenDSJohnson-UlrichLCouraudHEampHolekampKE(2018)Anthropogenic disturbance induces opposing population trends inspottedhyenasandAfrican lionsBiodiversity and Conservation27871ndash889httpsdoiorg101007s10531-017-1469-7

GrimmVampRailsbackSF(2013)Individual-based modeling and ecology PrincetonNJPrincetonUniversityPress

Hammond P S Berggren P Benke H Borchers D L Collet AHeide-Joslashrgensen M P hellip Oslashien N (2002) Abundance of har-bour porpoise and other cetaceans in the North Sea and adja-cent waters Journal of Applied Ecology 39 361ndash376 httpsdoiorg101046j1365-2664200200713x

Harris C M Thomas L Falcone E A Hildebrand J Houser DKvadsheimPHhellipJanikVM(2018)MarinemammalsandsonarDose-responsestudiestherisk-disturbancehypothesisandtheroleofexposurecontextJournal of Applied Ecology55396ndash404httpsdoiorg1011111365-266412955

Harwood J amp Stokes K (2003) Copingwith uncertainty in ecologi-caladviceLessonsfromfisheriesTrends in Ecology amp Evolution18617ndash622httpsdoiorg101016jtree200308001

Hogg C J Rogers T L Shorter A Barton K Miller P J O ampNowacek D (2009) Determination of steroid hormones inwhaleblowItispossibleMarine Mammal Science25605ndash618httpsdoiorg101111j1748-7692200800277x

HookerSKFahlmanAMooreMJAguilardeSotoNBernaldodeQuirosYBrubakkAOhellipTyackPL (2012)DeadlydivingPhysiologicalandbehaviouralmanagementofdecompressionstressin diving mammals Proceedings of the Royal Society B Biological Sciences2791041ndash1050httpsdoiorg101098rspb20112088

HoustonAIampMcNamaraJM(1999)Models of adaptive behavior An approach based on stateCambridgeUKCambridgeUniversityPress

Iverson J B Converse S J Smith G R amp Valiulis J M (2006)Long-term trends in the demography of the Allen Cays RockIguana (Cyclura cychlura inornata)Humandisturbanceanddensity-dependent effectsBiological Conservation 132 300ndash310 httpsdoiorg101016jbiocon200604022

Jones E L Hastie G D Smout S Onoufriou J Merchant ND Brookes K L amp Thompson D (2017) Seals and shippingQuantifying population risk and individual exposure to ves-sel noise Journal of Applied Ecology 54 1930ndash1940 httpsdoiorg1011111365-266412911

KarpovichSASkinnerJPMondragonJEampBlundellGM(2015)Combinedphysiological andbehavioral observations to assess theinfluence of vessel encounters on harbor seals in glacial fjords ofsoutheastAlaskaJournal of Experimental Marine Biology and Ecology473110ndash120httpsdoiorg101016jjembe201507016

KattwinkelMampReichertP(2017)Bayesianparameterinferenceforindividual-basedmodelsusingaParticleMarkovChainMonteCarlo


methodEnvironmental Modelling and Software87110ndash119httpsdoiorg101016jenvsoft201611001

KerleyLLGoodrichJMMiquelleDGSmirnovENQuigleyHBampHornockerMG (2002)Effectsof roadsandhumandistur-banceonAmurtigersConservation Biology1697ndash108httpsdoiorg101046j1523-1739200299290x

KightCRampSwaddleJP(2007)Associationsofanthropogenicactiv-ityanddisturbancewithfitnessmetricsofeasternbluebirds(Sialia si-alis)Biological Conservation138189ndash197httpsdoiorg101016jbiocon200704014

KingSLSchickRSDonovanCBoothCGBurgmanMThomasL ampHarwood J (2015) An interim framework for assessing thepopulation consequences of disturbance Methods in Ecology and Evolution61150ndash1158httpsdoiorg1011112041-210X12411

KlaassenMBauerSMadsenJampTombre I (2006)Modellingbe-haviouralandfitnessconsequencesofdisturbanceforgeesealongtheirspringflywayJournal of Applied Ecology4392ndash100

Kvadsheim PH Sevaldsen EM Folkow L P amp Blix A S (2010)Behaviouralandphysiologicalresponsesofhoodedseals(Cystophora cristata)to1to7kHzsonarsignalsAquatic Mammals36239ndash247httpsdoiorg101578AM3632010239

LimaS(1998)Nonlethaleffectsintheecologyofpredatorndashpreyinter-actionsBioScience4825ndash34httpsdoiorg1023071313225

Lusseau D (2003) Effects of tour boats on the behavior of bot-tlenose dolphins Using Markov chains to model anthropo-genic impacts Conservation Biology 17 1785ndash1793 httpsdoiorg101111j1523-1739200300054x

MadsenPTJohnsonMMillerPJOAguilarSotoNLynchJampTyackP (2006)Quantitativemeasuresofair-gunpulses recordedonspermwhales(Physeter macrocephalus)usingacoustictagsduringcontrolledexposureexperimentsThe Journal of the Acoustical Society of America1202366ndash2379httpsdoiorg10112112229287

MangelMampClarkCW(1988)Dynamic modeling in behavioral ecology PrincetonNJPrincetonUniversityPress

MartinTGBurgmanMAFidlerFKuhnertPM Low-ChoySMcBrideMampMengersenK(2012)Elicitingexpertknowledgeinconservation science Conservation Biology 26 29ndash38 httpsdoiorg101111j1523-1739201101806x

McClungMR SeddonP JMassaroMampSetiawanAN (2004)Nature-basedtourismimpactsonyellow-eyedpenguinsMegadyptes antipodesDoesunregulatedvisitoraccessaffectfledgingweightandjuvenilesurvivalBiological Conservation119279ndash285httpsdoiorg101016jbiocon200311012

McDonald B I Crocker D E Burns J M amp Costa D P (2008)Bodyconditionasan indexofwinterforagingsuccess incrabeaterseals (Lobodon carcinophaga) Deep- Sea Research Part II Topical Studies in Oceanography 55 515ndash522 httpsdoiorg101016jdsr2200711002

McHuronECostaDSchwarzLampMangelM(2017)Abehavioralframeworkforassessingthepopulationconsequencesofanthropo-genicdisturbanceonpinnipedsMethods in Ecology and Evolution8552ndash560httpsdoiorg1011112041-210X12701

McHuronEAMangelMSchwarzLKampCostaDP(2017)Energyand prey requirements ofCalifornia sea lions under variable envi-ronmentalconditionsMarine Ecology Progress Series567235ndash247httpsdoiorg103354meps12041

McMahonCRBurtonHRampBesterMN (2000)WeaningmassandthefuturesurvivalofjuvenilesouthernelephantsealsMirounga leoninaatMacquarieIslandAntarctic Science12149ndash153

McMahon C R Burton H R amp Bester M N (2003) A de-mographic comparison of two southern elephant seal pop-ulations Journal of Animal Ecology 72 61ndash74 httpsdoiorg101046j1365-2656200300685x

McMahonCRHarcourtRGBurtonHRDanielOampHindellMA(2017)Sealmothersexpendmoreonoffspringunderfavourable

conditions and less when resources are limited Journal of Animal Ecology86359ndash370httpsdoiorg1011111365-265612611

MerchantNDFaulknerRCampMartinezR(2018)Marinenoisebud-getsinpracticeConservation Letters11e12420

MiddletonADKauffmanMJMcwhirterDEJimenezMDCookR C Cook J G hellipWhite P J (2013) Linking anti-predator be-haviourtopreydemographyrevealslimitedriskeffectsofanactivelyhuntinglargecarnivoreEcology Letters161023ndash1030httpsdoiorg101111ele12133

Miksis J Grund M Nowacek D Solow A Connor R amp TyackP (2001) Cardiac responses to acoustic playback experi-ments in the captive bottlenose dolphin (Tursiops truncatus)Journal of Comparative Phsychology 115 227ndash232 httpsdoiorg1010370735-70361153227

MillerCBestPPerrymanWBaumgartnerMampMooreM(2012)Bodyshapechangesassociatedwith reproductive statusnutritiveconditionandgrowthinrightwhalesEubalaena glacialisandE aus-tralis Marine Ecology Progress Series 459 135ndash156 httpsdoiorg103354meps09675

Miller P JO JohnsonM PMadsen P T BiassoniNQueroMampTyackPL(2009)Usingat-seaexperimentstostudytheeffectsofairgunsontheforagingbehaviorofspermwhales intheGulfofMexicoDeep- Sea Research Part I Oceanographic Research Papers561168ndash1181httpsdoiorg101016jdsr200902008

Milner-Gulland E J amp Shea K (2017) Embracing uncertainty in ap-pliedecologyJournal of Applied Ecology542063ndash2068httpsdoiorg1011111365-266412887

Moretti D Thomas L Marques T Harwood J Dilley A NealesB hellip Morrissey R (2014) A risk function for behavioral disrup-tion of Blainvillersquos beaked whales (Mesoplodon densirostris) frommid-frequency active sonar PLoS ONE 9 e85064 httpsdoiorg101371journalpone0085064

Nabe-Nielsen J Sibly RM Tougaard J Teilmann J amp SveegaardS (2014) Effects of noise and by-catch on aDanish harbour por-poise population Ecological Modelling 272 242ndash251 httpsdoiorg101016jecolmodel201309025

Nabe-Nielsen J vanBeestFMGrimmV SiblyRTeilmann JampThompson PM (2018) Predicting the impacts of anthropogenicdisturbancesonmarinepopulationsConservation Letters

NationalAcademies (2017)Approaches to understanding the cumulative effects of stressors on marine mammalsWashingtonDCTheNationalAcademiesPress

NationalResearchCouncil(2005)Marine mammal populations and ocean noise Determining when noise causes biologically significant effects WashingtonDCTheNationalAcademiesPress

NattrassSampLusseauD(2016)UsingresiliencetopredicttheeffectsofdisturbanceScientific Reports625539httpsdoiorg101038srep25539

NewLFClarkJSCostaDPFleishmanEHindellMAKlanjščekThellipHarwoodJ(2014)Usingshort-termmeasuresofbehaviourtoestimatelong-termfitnessofsouthernelephantsealsMarine Ecology Progress Series49699ndash108httpsdoiorg103354meps10547

New L F Hall A J Harcourt R Kaufman G Parsons E C MPearsonHChellipSchickRS(2015)Themodellingandassessmentof whale-watching impacts Ocean and Coastal Management 11510ndash16httpsdoiorg101016jocecoaman201504006

New L F Harwood J Thomas L Donovan C Clark J S HastieG hellip Lusseau D (2013) Modeling the biological significanceof behavioral change in coastal bottlenose dolphins in responseto disturbance Functional Ecology 27 314ndash322 httpsdoiorg1011111365-243512052

NewLFMorettiD JHookerSKCostaDPampSimmonsSE(2013)Usingenergeticmodelstoinvestigatethesurvivalandrepro-duction of beakedwhales (familyZiphiidae)PLoS ONE8 e68725httpsdoiorg101371journalpone0068725


NorenD P (2011) Estimated fieldmetabolic rates andprey require-mentsofresidentkillerwhalesMarine Mammal Science2760ndash77httpsdoiorg101111j1748-7692201000386x

Nowacek D P Christiansen F Bejder L Goldbogen J A ampFriedlaender A S (2016) Studying cetacean behaviour Newtechnological approaches and conservation applicationsAnimal Behaviour 120 235ndash244 httpsdoiorg101016janbehav201607019

OedekovenCFleishmanEHamiltonPClarkJampSchickR(2015)Expert elicitation of seasonal abundance of North Atlantic rightwhales Eubalaena glacialis in the mid-Atlantic Endangered Species Research2951ndash58httpsdoiorg103354esr00699

OsterriederSKSalgadoKentCampRobinsonRW(2017)Responsesof Australian sea lionsNeophoca cinerea to anthropogenic activ-ities in the Perth metropolitan area Western Australia Aquatic Conservation Marine and Freshwater Ecosystems 27 414ndash435httpsdoiorg101002aqc2668

PaganoAMDurnerGMRodeKDAtwoodTCAtkinsonSNPeacockEhellipWilliamsTM(2018)High-energyhigh-fatlife-stylechallengesanArcticapexpredatorthepolarbearScience359568ndash572httpsdoiorg101126scienceaan8677

PeckarskyBLAbramsPABolnickD IDill LMGrabowski JH Luttbeg B hellip Trussell G C (2008) Revisiting the classicsConsidering nonconsumptive effects in textbook examples ofpredatorndashprey interactions Ecology 89 2416ndash2425 httpsdoiorg10189007-11311

PettisHMRollandRMHamiltonPKKnowltonARBurgessEAampKrausSD (2017)Bodyconditionchangesarisingfromnat-ural factorsand fishinggearentanglements inNorthAtlantic rightwhalesEubalaena glacialis Endangered Species Research32237ndash249httpsdoiorg103354esr00800

PirottaEHarwoodJThompsonPMNewLCheneyBArsoMhellipLusseauD (2015)Predictingtheeffectsofhumandevel-opments on individual dolphins to understand potential long-term population consequences Proceedings of the Royal Society B Biological Sciences 282 20152109 httpsdoiorg101098rspb20152109

PirottaEMangelMCostaDPMateBGoldbogenJPalaciosDMhellipNewL(2018)Adynamicstatemodelofmigratorybehaviorandphysiology toassess theconsequencesofenvironmentalvari-ation and anthropogenic disturbance on marine vertebrates The American Naturalist191E40ndashE56httpsdoiorg101086695135

PirottaEMerchantNDThompsonPMBartonTRampLusseauD(2015)QuantifyingtheeffectofboatdisturbanceonbottlenosedolphinforagingactivityBiological Conservation18182ndash89httpsdoiorg101016jbiocon201411003

PirottaENewLHarwoodJampLusseauD(2014)Activitiesmoti-vationsanddisturbanceAnagent-basedmodelofbottlenosedol-phinbehavioraldynamicsandinteractionswithtourisminDoubtfulSoundNewZealandEcological Modelling282 44ndash58 httpsdoiorg101016jecolmodel201403009

PirottaENewLampMarcouxM(2018)Modellingbelugahabitatuseand baseline exposure to shipping traffic to design effective pro-tectionagainstprospectiveindustrializationintheCanadianArcticAquatic Conservation Marine and Freshwater Ecosystems 28 713ndash722httpsdoiorg101002aqc2892

PirottaEThompsonPMCheneyBDonovanCRampLusseauD(2015)Estimatingspatialtemporalandindividualvariabilityindol-phincumulativeexposuretoboattrafficusingspatiallyexplicitcap-turendashrecapture methods Animal Conservation 18 20ndash31 httpsdoiorg101111acv12132

RippleWJampBeschtaRL(2012)TrophiccascadesinYellowstoneThefirst15yearsafterwolfreintroductionBiological Conservation145205ndash213httpsdoiorg101016jbiocon201111005

Rodriguez-Prieto I amp Fernandez-Juricic E (2005) Effects of directhuman disturbance on the endemic Iberian frog at individual andpopulation levels Biological Conservation 123 1ndash9 httpsdoiorg101016jbiocon200410003

RollandRMParksSEHuntKECastelloteMCorkeronP JNowacekDPhellipKrausSD (2012)Evidencethatshipnoise in-creases stress in right whales Proceedings of the Royal Society B Biological Sciences 279 2363ndash2368 httpsdoiorg101098rspb20112429

RollandRMSchickRSPettisHMKnowltonARHamiltonPKClarkJSampKrausSD(2016)HealthofNorthAtlanticrightwhales Eubalaena glacialis over three decades From individualhealthtodemographicandpopulationhealthtrendsMarine Ecology Progress Series542265ndash282httpsdoiorg103354meps11547

RussellDJFHastieGDThompsonDJanikVMHammondPSScott-HaywardLAShellipVotierS(2016)AvoidanceofwindfarmsbyharboursealsislimitedtopiledrivingactivitiesJournal of Applied Ecology531642ndash1652httpsdoiorg1011111365-266412678

SchickRSKrausSDRollandRMKnowltonARHamiltonPK PettisHMhellipClark J S (2013)Using hierarchical Bayes tounderstandmovementhealthandsurvivalintheendangerednorthAtlanticrightwhalePLoS ONE8e64166httpsdoiorg101371journalpone0064166

SchickRSNewLFThomasLCostaDPHindellMAMcMahonCRhellipClarkJS(2013)Estimatingresourceacquisitionandat-seabodyconditionofamarinepredator Journal of Animal Ecology821300ndash1315httpsdoiorg1011111365-265612102

SchmitzO J Krivan V ampOvadiaO (2004) Trophic cascades Theprimacy of trait-mediated indirect interactions Ecology Letters 7153ndash163httpsdoiorg101111j1461-0248200300560x

Schwacke L H Thomas LWells R SMcFeeW E Hohn A AMullinKDhellipSchwackeJH(2017)Quantifyinginjurytocommonbottlenosedolphins from theDeepwaterHorizonoil spill usinganage-sex-andclass-structuredpopulationmodelEndangered Species Research33265ndash279httpsdoiorg103354esr00777

SheroMRKrotzRTCostaDPAveryJPampBurnsJM(2015)HowdooverwinterchangesinbodyconditionandhormoneprofilesinfluenceWeddellsealreproductivesuccessFunctional Ecology291278ndash1291httpsdoiorg1011111365-243512434

SiblyRMGrimmVMartinBTJohnstonASAKulakowskaKToppingC JhellipDeangelisDL (2013)Representing theacquisi-tionanduseofenergybyindividualsinagent-basedmodelsofanimalpopulationsMethods in Ecology and Evolution4 151ndash161 httpsdoiorg1011112041-210x12002

StankowichT(2008)UngulateflightresponsestohumandisturbanceAreviewandmeta-analysisBiological Conservation1412159ndash2173httpsdoiorg101016jbiocon200806026

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Taylor B L Martinez M Gerrodette T Barlow J amp Hrovat YN (2007) Lessons from monitoring trends in abundance of ma-rine mammals Marine Mammal Science 23 157ndash175 httpsdoiorg101111j1748-7692200600092x

Thomas J A Kastelein R A amp Awbrey F T (1990) Behavior andbloodcatecholaminesofcaptivebelugasduringplaybacksofnoisefrom an oil drilling platform Zoo Biology 9 393ndash402 httpsdoiorg101002(ISSN)1098-2361

TyackPLZimmerWMXMorettiDSouthallBLClaridgeDE Durban JW hellip Boyd I L (2011) Beakedwhales respond tosimulatedandactualnavysonarPLoS ONE6e17009httpsdoiorg101371journalpone0017009

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1emsp |emspINTRODUC TION

Thenonlethaleffectsofdisturbancewhichwedefineasadeviationinananimalrsquosphysiologyorbehaviorfrompatternsoccurringintheabsenceofpredatorsorhumans(FridampDill2002)canstronglyaf-fectwildlifepopulations(Lima1998)Understandingthepopulation-level repercussions of these changes in individual behavior andphysiologyispartofamorecomprehensiveecologicalchallengethequantificationoftrait-mediated indirecteffects (WernerampPeacor2003)alsoreferredtoasnonconsumptiveeffects(Peckarskyetal2008)onecologicalinteractionsUnderthisparadigmapredatororotherstressorcanaffectaspeciesdirectlyviatheremovalofindivid-ualsandalterationofpopulationdensity(theconsumptiveorlethaleffects)andindirectlybyinducingchangesinmorphologyphysiol-ogybehaviororlifehistory(iethespeciesrsquotraits)thatreducetheriskofpredation(SchmitzKrivanampOvadia2004)Trait-mediatedindirectinteractionscaninturnleadtocascadingeffectsonothercomponents of the ecological community (Peckarsky etal 2008RippleampBeschta2012)Characterizingtheseprocessesrequiresanintegrativeapproachthatcanscaletheresponsesofindividualani-malstodemographiceffectsinthecontextoftheirenergybalanceandthespeciesrsquolifehistory(Middletonetal2013)

Becausetheresponsesofanimalstomanyanthropogenicstimuliare similar to their responses topredation risk (BealeampMonaghan2004FridampDill2002) theevaluationandmanagementofhumanactivitiesthathavenonlethaleffectsonwildlifecanbeframedinthiswidercontextAssessingthepopulationconsequencesofdisturbance(PCoD) has been a long-term goal for ecologists decision makersandmanagersand iscurrentlya requirement formostenvironmen-tal impact assessments under European Union (European HabitatsDirective9243EEC)andUnitedStates(MarineMammalProtectionAct16USCsectsect1361et seq)legislation(Kingetal2015)Howevercomprehensiveassessmentsoftheeffectsofdisturbancearerarelyundertakenbecauseofalackofrelevantdataandbecausepermitand

policydecisionsaboutdisturbancemustbemadewithinstricttime-linesInadditiontotheseconstraintsthetheoreticalunderstandingand theempirical andanalyticalmethodsneeded toevaluate theselong-term consequences are often not available As a result man-agementdecisionshavebeengenerallybasedonevidenceofbehav-ioralresponsestodisturbancealthoughsuchresponsesmayhavenopopulation-level effect (Christiansen amp Lusseau 2015) Converselytheabsenceof anobviousbehavioral responsedoesnot ruleout apopulation-leveleffect(GillNorrisampSutherland2001)Giventhein-creasingexpansionofactivitiesthatcandisturbwildlifequantitativelylinking disturbance to population dynamics is amajor objective formodernconservation(Gilletal2001)Amechanisticunderstandingoftheprocessesbywhichdisturbanceaffectspopulationsisespeciallyuseful for long-livedwide-rangingspecies forwhichempiricaldataareoften collectedover relatively small spatial and temporal scales(NationalResearchCouncil2005)

GroupsestablishedbytheNationalResearchCouncilof theUSNationalAcademiesand theUSOfficeofNavalResearchhavead-dressedwaysofmodelingthepopulation-leveleffectsofdisturbanceonmarinemammals (NationalAcademies 2017NationalResearchCouncil 2005New etal 2014) Their efforts led to the develop-ment of a conceptual framework that summarizes the functionallinks among processes (Figure1) The underlying concept is thatdisturbance-induced changes in behavior or physiology affect fit-nessthroughindividualsrsquohealthandvitalrates(survivalreproductivesuccessandgrowthrate the latteraffectingageat firstbreeding)The population-level consequences of changes in individual fitnessdependonwhatproportionof thepopulation is affectedwhich inturndeterminesthedistributionoffitness-relatedtraits inthepop-ulationTheframeworkprovidesawaytoquantifyfourphenomena(a)thephysiologicalandbehavioralchangesthatoccurastheresultofexposuretoaparticularstressor(b)theacuteeffectsofthesephys-iologicalandbehavioralresponsesonindividualvitalratesandtheirchroniceffectsviaindividualhealthdefinedbyNewetal(2014)as

oftheInternationalAssociationofOilandGasProducersPLTandDLacknowledgesupportfromtheMASTSpoolinginitiative(MarineAllianceforScienceandTechnologyforScotlandsupportedbytheScottishFundingCouncilgrantreferenceHR09011andcontributinginstitutions)andPLTacknowledgessupportfromONRgrantN00014-15-1-2553

dataSynthesis and applicationsTheimplementationofthisframeworkhasmovedthefocusofdiscussionofthemanagementofnonlethaldisturbancesonmarinemammalpopulationsawayfromarhetoricaldebateaboutdefiningnegligibleimpactandto-ward a quantitative understanding of long-termpopulation-level effectsHerewedemonstrate the frameworkrsquos general applicability to othermarine and terrestrialsystemsandshowhowitcansupportintegratedmodelingoftheproximateandulti-mate mechanisms that regulate trait-mediated indirect interactions in ecologicalcommunitiesthatisthenonconsumptiveeffectsofapredatororstressoronaspe-ciesrsquobehaviorphysiologyorlifehistory

K E Y W O R D S

anthropogenicdisturbanceenvironmentalimpactassessmentsmarinemammalsnonconsumptiveeffectspopulationconsequencestrait-mediatedindirectinteractionsuncertainty





















































ACKNOWLEDG MENTS



Nonedeclared





ORCID


R E FE R E N C E S































































































































































































ACKNOWLEDG MENTS



Nonedeclared





ORCID


R E FE R E N C E S











































































































































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