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A pattern-oriented model for assessing effects of weather and freshwater discharge on black coral (Antipathes fiordensis) distribution in a fjord

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A pattern-oriented model for assessing effects of weather and freshwater discharge on black coral (Antipathes fiordensis) distribution in a fjord
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  EcologicalModelling304(2015)59–68 ContentslistsavailableatScienceDirect Ecological   Modelling  journalh   omepage:www.elsevier.com/locate/ecolmodel A   pattern-oriented   model   for   assessing   effects   of    weather   andfreshwater   discharge   on   black   coral   (  Antipathes    fiordensis )   distributionin   a   fjord Weimin    Jiang ∗ ,Chris   Cornelisen,   Ben   Knight,   Mark   Gibbs 1 CawthronInstitute,98HalifaxStreetEast,Nelson7042,NewZealand a   r   ti   c   l   e   i   nf   o  Articlehistory: Received3November2014Receivedinrevisedform24February2015Accepted27February2015 Keywords: Blackcoral  Antipathesfiordensis Pattern-orientedmodelSalinitytoleranceLowsalinitylayerFjord a   b   st   ra   ct Doubtful   Soundand   other   NewZealand   fjordsare   unique   in   that   they   provide   suitable   habitatfor   ablackcoralspecies   (  Antipathesfiordensis )   at   depthsasshallowas   4m.Researchsuggeststhe   upper   depthlimit   atwhich   black   corals   cansurviveinDoubtful   Soundiscontrolled   by   gradients   insalinity(asopposed   tolightlevels)within   buoyant   low-salinity   layers(LSL).   Thethickness   of    the   LSLinDoubtful   Soundvaries   alongthe   fjord   and   fluctuates   as   a   functionof    rain,wind   and   freshwater   tailrace   discharge   from   the   ManapouriHydroelectric   Power   Station.   A   pattern-orientedsurvivorship   model   was   developedtopredict   mortalityand   upper-depth   distribution   of    blackcorals   inDoubtful   Soundinresponse   tochangesin   theLSL.   Modelparameters   were   estimated   usingobserved   patternsof    black   coraldistributionand   time-series   salinitymeasurements   overarange   of    depths.   Predicted   upper   depth   limits   inDoubtful   Soundand   a   referencefjord   (Milford   Sound)were   validated   againstfieldobservations   of    black   coraldepth   distributions   ontheadjacent   rockwalls.Themodel   accurately   forecasteddepths   of    corals   inmidtoouter   regions   of    DoubtfulSound,butunderestimatedupperdepth   limitsin   the   inner   region   of    both   fjords.   Thediscrepanciesininner   fjord   locationssuggest   thatother   factors,   suchassedimentation,   arealso   limiting   establishment   of long-lived   corals   insome   locations.Data   fromhydrodynamic   simulations   of    the   LSLinDoubtful   Soundwere   fed   intothe   survivorship   modeltoinvestigate   black   coraldistributions   under   varyingrain,windand   tailrace   discharge   scenarios.Results   indicate   that   weather,rather   than   tailracedischarge,driveslong-termpatterns   intheverticaldistributionof    black   coralsinDoubtfulSound.©2015   ElsevierB.V.   All   rights   reserved. 1.Introduction Fiordlandis   theonlyknownplaceintheworldwherea   speciesofblackcoral(  Antipathesfiordensis )   canbefoundin   depthsasshal-lowas4m(Fig.1;KregtingandGibbs,2006).Approximately7.5 millionblackcoralcoloniesliewithinthetop35mof    thewatercolumnacrosstheregion’sfourteenfjords(Grange,1985).Suit- ablehabitatconditionsforblackcoralslocatedelsewherein   theworldoccurprimarilybelow100m(Boetal.,   2011;Wagneretal.,2011).Theuniqueoccurrenceof    blackcoralsatshallowdepthsinNewZealand’sfjordshasbeenattributedtoa   reductioninwaveactionwithintheprotectedconfinesof    thesurroundingsteepter-rain,andalowlightenvironmentasa   resultof    topographicshading ∗ Correspondingauthorat:98   HalifaxStreetEastNelson,7010Nelson,NewZealand.Tel.:+6435482319. E-mailaddress: weimin.jiang@cawthron.org.nz(W.    Jiang). 1 Presentaddress:AECOM,540WickhamTerrace,FortitudeValley,Queensland,Australia. and   thepresenceof    buoyantlow-salinitylayers(LSLs)thatcontainhighlevelsoftanninsthatattenuatelightwithinsurfacewaters(Grange,1986,1990;Grangeetal.,   1991;Davies-Colleyetal.,1992).However,lowsalinityexposureassociatedwithperiodicdeep-eningof    theLSLhasmorerecentlybeenfoundtobethefactorultimatelylimitingtheirshallowwaterdistribution(KregtingandGibbs,2006).ThepresenceofanLSLisadefiningfeatureofallthefjords;however,inDoubtfulSoundaconstantfreshwaterinflowfromLakeManapouriintoDeepCovethroughtheManapouriHydro-electricPowerStation(MHPS)tailraceactstomaintaina   shallowLSL( ∼ 1–3min   thickness)throughoutmuchoftheSound(Gibbs,2001).Thecombinationofup-fjordwindsandepisodicrainfallhasbeendeterminedtobetheprimarydriverof    LSLdeepeningeventsthatoccurin   NewZealandfjords(Gibbsetal.,   2000;Gibbs,2001;GoodwinandCornelisen,2012).However,thereis   littlepublishedinformationon   thepotentialinfluenceof    thetailracedischargedur-ingweather-driveneventsandtheextenttowhichincreasesindischargewouldfurtherdeepentheLSL,andin   turnimpactcoralslivingattheirupperdepthlimit. http://dx.doi.org/10.1016/j.ecolmodel.2015.02.0200304-3800/©2015ElsevierB.V.Allrightsreserved.  60 W.Jiangetal./    EcologicalModelling304(2015)59–68 Fig.1. Ablackcoral(  Antipathesfiordensis )alongthe   rock   wallof    DoubtfulSound.PhotocreditCawthronInstitute. Inordertoevaluatethepotentialeffectofweatherandthetail-racedischargeontheLSL,andinturnthedistributionofblackcorals,wedevelopedandvalidateda   pattern-orientedmodelforpredictingtheupperdepthlimitof    coralsthroughtheuseof existingsalinitydataandobservationsof    existingblackcoraldistri-bution.Thisapproachutilizedtheobservedpattern(e.g.time   seriesorspatialpattern)whichaccountsforsite-history,characteristicsandecologicalprocessovertimeandspace(Wiegandetal.,   2003).Wethenuseddataoutputsfromnumericalsimulationsof    theLSL underdifferentweatherandtailracedischargeconditionstodrivethemodelandinturnforecastpotentialeffectsofincreasingtherateoftailracedischargeandto   understandtheinfluenceof    rainandwindontheupperdepthlimitofblackcorals.TheoutcomesareintendedtoinformdecisionsaroundthemanagementoftheMHPSandalsoprovideinsightintothepotentialimplicationsof climate-relatedweatherchangesonfuturedistributionsof    blackcorals. 2.Methods  2.1.Studysite TheDoubtful-Thompson–BradshawSoundcomplex(hereinreferredtoasDoubtfulSound)isoneof    14glaciallycarvedfjordslocatedonthesouth-westerncoastof    theSouthIslandof    NewZealand(Fig.2).DoubtfulSoundis   37kmlongandgenerallylessthan1kmwide.Thefjordis   surroundedbymountainousterrain;hencethewallsof    thefjordboth   aboveandbelowthewatersur-facearesteep,andthewaterdepthwithinDoubtfulSoundis   greaterthan400minplaces.DoubtfulSound,aswithotherNewZealandfjords,issubjecttohighlevelsofannualrainfall( ∼ 5–7m),   whichrunsoffthesteepcatchmentsandentersthesystemrapidlyduringepisodicevents.Duringthese   events,thesteeptopographysteersstrongcoastalwindsupintothefjordandretardstheoutwardflowoftheLSL,whichin   turncausestheLSLtodeepentodepthsof  ∼ 10–18mintheinnerSounds(Gibbs,2001).Ourstudyutilized dataonblackcoraldistributioncollectedat14establishedlong-termmonitoringsitesvisitedannuallyandhourlysalinitydatafrominstrumentsmooredatfourlocationsinDoubtfulSoundandonelocationin   MilfordSound.  2.2.Blackcoraldepthdistribution Formodeldevelopmentandvalidation,theupperdepth(shal-lowestdepth)distributionsofblackcoralswerefirstdeterminedatelevensitesin   DoubtfulSoundandthreesitesinMilfordSound(seeFig.   2).Theobservedupperdepthsthatblackcoralscolonizeonthesteeprockwallswererecordedbydiversatestablishedlong-term  W.Jiangetal./    EcologicalModelling304(2015)59–68 61 Fig.2. Milford(topright)andDoubtful(bottom)Sounds.LocationsofoceanographicmooringsM1–M5,andmonitoringsiteswhereblackcoralupperdepthlimitswererecorded   (1–11inDoubtful-Thompson–BradshawSounds,andMIL1–MIL3inMilfordSound).Alsoshownare   locationsof    meteorologicalstationsatDeepCove(DC),SecretaryIsland(SI),andMilfordSound(MS)andthelocationof    theMHPStailrace. monitoringsitesin   DoubtfulandMilfordSounds.As   partof    envi-ronmentalmonitoringfortheManapouriPowerStation,dataoncoraldepthsateachmonitoringsitewerecollectedbetween25 Januaryand15Februaryeachyearbetween2006and2011andagainin2013.Duringvisitstoeachsite,thedepthsofthreetofivecoralsgreaterthan0.3minsizeandnearestthewatersurface(i.e.shal-lowestcorals)wererecordedbydiversusinga   digitaldepthgaugeofthesamemakeandmodelplacedatthemidpointof    eachcolony(SuuntuVyper;0.1mresolution,1%accuracyorbetteroffullrangeto80m).   Coralsweretypicallythosethatwereclosesttofourper-manentlymarkedverticaltransectsspacedapproximately5–7malongtherockwall.Intheabsenceofverticalreferencepoints,diversrecordedcoralsalonga ∼ 30–40msectionof    therockwall.Typicallyvisibilityisverygood(beyond10m)   andtheupperdepthatwhichcoralscolonizedwasclearlydelineated,thereforereduc-ingthelikelihoodthatcoralswerepresentabovethedepthsof thoserecorded.Onthepasttwosamplingoccasions(2011and2013),particularlyatsitesintheinnerSounds,we   observedsmallercorals(about0.05–0.10minlength)atdepthsshallowerthanthelarger,longer-livedcorals.Depthsofthesejuvenilecorals,whenobservedto   beshallowerthanthedepthsof    thelargercorals,werealsorecorded.  2.3.Collectionofsalinitydata Two   setsofsalinitydatacollectedaspartofon-goingphysicalmonitoringrequiredfortheconsentedoperationof    theMHPSwereavailableforthisstudy.Thefirstdatasetincludeddatacollectedatfourmooringlocations(M2–M5)inDoubtfulSoundbetween1997andDecember2000(Fig.2).Forthisdataset,datawascollectedhourlyusingconductivity-temperature(CT)loggers(FalmouthSci-entificInstruments)deployedat2mintervalsbetweendepthsof1and21m.ThemooringswereinspectedandcleanedonamonthlybasisandquarterlyCTD(conductivity,temperatureanddepth)sur-veyswereusedto   calibratethemooredinstrumentation.Additionalcalibrationandservicingwasperformedannually(Gibbs,2001).For modeldevelopmentandvalidation,weuseddataforthe1998year,whichrepresentedthehighestqualitydataandalsotheyearthatexperiencedthehighestdegreeofrainfall.Thedepthofthelow  62 W.Jiangetal./    EcologicalModelling304(2015)59–68 Fig.3. Conceptualdiagramof    modellingapproachandsteps. salinitylayerisheavilyinfluencedbyrainandwind(Gibbsetal.,2000),andbyusingdatafroma   wetyearwewereabletoaccountforthe‘worst-case-scenario’forblackcoralsurvivorship.TheseconddatasetincludedsalinitydatacollectedoveraneightyearperiodfromMarch2005toMarch2012attheM1mooringneartheheadofMilfordSoundandtheM4mooringalongthemainchannelofDoubtfulSound(Fig.2).Theseconddatasetwasbasedonrecordingsevery15min   usingCTloggers(RBRXR-420CT;accuracy ± 0.003mS/cmat35psu15 ◦ C,resolution1  S/cm)deployedat0.5,1.0,1.5,2.0,3.0,5.0,7.0,9.0,11.0and19.0m.   TheM1andM4   mooringsare   maintainedeverythreemonthsandgothrougha   pre-processingandcalibrationpro-ceduretoensuredatausedwasofhighqualityandthatperiodof instrumentationfailureor   driftassociatedwithfoulingwasomit-ted.Piece-wiselinearinterpolationbetweenadjacentsensorsontheoceanographicmooringswasconductedtoconstructsalinityandtemperatureprofilesatafinerspatialscale.Theseconddatasethasasamplingfrequencyof15min;datawereintegratedinto1hfrequencyforusein   thecoralsurvivorshipmodelbytakingthemedianvaluewithineachhour.Inaveryfewcases,oceanographicdatawereinterpolatedifthereweredatagaps(spatialor   temporal)duetoinstrumentationmalfunction.In   additionto   thetwo   pri-marydatasets,salinitydatawascollectedaspartofanotherstudyattheM5   mooringinDeepCovebetween16Julyand15August2007;thisdatasetwasusedtoillustratethebehaviourof    theLSLinDeepCovefollowinga   largerainfalleventandalsotovalidatethehydrodynamicmodelusedinsimulations(seeSection2.5).Theprimaryaimof    themooredinstrumentationis   tomon-itorthebehaviouroftheLSL.Themooringsweredesignedsothattheinstrumentationis   mooredbeneathabuoythatfloatsat   theseasurface,therebyensuringthatthetrueLSLdepthisalwaysmeasured.Blackcoralsarefixedtotherockwall;hencesalinitydatawereconvertedtodepthsrelativetotides(http://www.niwa.co.nz/services/online-services/tide-forecaster)tobetterrepresentthesalinitythat   thecoralsactuallyexperiencealongtherockwalls.  2.4.Modeldevelopmentandparameterization Amodelforforecastingcoraldistributioninresponsetoachangingsalinityregimewasdevelopedusingsurvivorshipmodelstraditionallyappliedinfisheriesscience,togetherwithtime-seriessalinitydatacollectedattheM4   mooringandobserva-tionsofblackcoraldepthsalongtheadjacentrockwall(Site6inFig.1).Themodellingapproachassumesthat   salinityistheprimarydriverofblackcoralsurvivorshipin   shallowwaters,asopposedtoother   factorssuchaspredation,orphysicaldisturbancefromwaveactionorsedimentation.AconceptualdiagramofthemodellingapproachandstepsusedinthestudyisdepictedinFig.3.Theexponentialdecaymodel,oftenusedin   fisherysciencetoestimatesurvival,was   appliedtoestimatesurvivorshipofblackcorals.Themodelexpressesthenumberofindividualsatanytime t  by: n t   =   n t  − 1 e −  f    ( s ) (1)Infisheries,  f    includesnaturalmortalitywhichiscausedbyoldage,diseaseandpredation,andfishingmortalitythroughhumancatch.  f  is   oftenassumedtobeconstantovera   year.Ratherthanconsideringthemortalityrateasconstant,werelatedtheinstanta-neousmortalityrateasa   functionofsalinity.Blackcoralsexposedtolowsalinity(<32psu)showevidenceofosmoticstresswithinanhour,anddie   after5–6hcontinuousexposureto   lowsalinity(withinrangeof    20–30psu;KregtingandGibbs,2006).However, experimentsbyKregtingandGibbs(2006)haveshownthattheycansurviveexposureto   lowsalinitywateraslongascoralsareperiodicallyflushedbywaterwithsalinityabove32psu.KregtingandGibbs(2006)providedimportantinformationoncoralsurvivorshipinresponseto   salinitystressbut   did   notquantifytherelationshipbetweensurvivalandsalinity.Topredictimpactof salinityonthesurvival,aquantitativerelationshipwasconstructed.A   logisticfunctionwaschosento   describethisrelationship,whichassumesthat   atsomesalinityvalue,50%of    thecoralwoulddiewithinanhour,witha   decreasingprobabilityofdyingassalin-ityincreases.Mathematically,theprobabilityofmortalitycanbeexpressedas: m t   = e ˛ ( s c  − s t  ) 1 +   e ˛ ( s c  − s t  )  (2)where s t   isthesalinityattime t  ,   s c   isparameterwhichcontrolshowfarto   theleftorrightthecurvelieswiththeinflectionpointrepresentingthesalinityatwhichtheprobabilityof    mortalityis0.5. ˛ isa   parameterthatcontrolshowsteeplythecurvemovesbetweenitstwoasymptotesandrepresentstherateofchangeinmortalitywithsalinity.Theinstantaneousmortality  f  isdefinedas:  f  t  ( s ) =−   log(1 −   m t  )(3)where  f  hastheunitof    h − 1 .Anexampleofpossibleprofilesof    theprobabilityof    mortalityinrelationtosalinityis   shownin   Fig.4withdifferentparametervalues.Thesurvivalratebytheendofthetimeperiodis   calculatedas: s r   = n t  n  (4)Inthismodel,recruitmentis   assumedto   equalthenaturalmor-talityandblackcoralcolonieswouldstabilizein   theabsenceof adverseeffects.  W.Jiangetal./    EcologicalModelling304(2015)59–68 63 Fig.4. Possibleprofilesofprobabilityof    mortalityrateinrelationtosalinity.Upper: s c   =5andlower: s c   =   10withtwo   valuesofparameter ˛ . Aninitialnumberof    10,000individualswereusedforbothparameterizationandprediction.Asvaluesfor s c   and ˛ arenotavailable,aMonteCarlofilteringmethodwasusedto   deriveandtestmodelparameters(Roseetal.,1991).   Thismethodinvolvesrandomlysamplingthepairsof    parameterswithina   rangeof    val-uestoproducemodeloutputs(i.e.themodelledpattern).Theseoutputswerethencomparedwithfielddata(i.e.theobservedpat-tern)andifoutputis   withinthecriterion,thesetof    parametersareconsideredtobeacceptable.The1998M4datawereusedfortheMonteCarlosimulation.Asnopreviousknowledgeontheparameterswasavailable,a   widerangeofvalues(0–30psu)for s c   wereusedintherandomization.Parameter ˛ describestherateof    probabilityof    mortalitywithsalinity;ahighervalueof    ˛ correspondswithasharperchangeoftheprobability(Fig.4).Anarbitraryvaluefortheupperboundof parameter ˛ wassetto4.   Valuesgreaterthan4werenotconsid-eredtobebiologicallymeaningful.When ˛ becomeslargerthan4,thesurvivalprobabilityapproacheseither1(salinitygreaterthan s c  )or0(salinitylessthan s c  )andcontradictsobservationsof    blackcoralsrecoveringfromperiodicexposuretolowsalinity(KregtingandGibbs,2006).Pairsof    parameterswerethenrandomlysampledfromthepredefinedrangesandusedtoestimatetheupperdepthlimit.Runningthesimulationmanytimes( n   =   5000)producessetsofacceptableparametervalues.Themedianof    s c  andcorresponding ˛ valueswereusedasthefinalestimates.  2.5.Predictionandvalidation Aftertheparametersweredetermined,themodelwas   usedtopredictblackcoralsurvivalatsiteswheretimeseriesdataonsalin-itywereavailable.PredictionsweremadeforallfourmooringsitesinDoubtfulSoundusingdatafrom1998to2000,andfortheM1andM4   mooringsusingtheadditionaldatacollectedatthesetwo   loca-tionsbetween2005and2012.Theupperdepthlimitof    blackcoralsatagivenlocationwasdefinedastheminimumdepthatwhichthesurvivalrateisgreaterthan95%attheendofa   yearduetotheirlong-livednature.Predictedupperdepthlimitsbasedondatafromthemooringswerecomparedto   upperdepthlimitsof    blackcoralsobservedatthenearestrockwalllocations(asdescribedabove;seeFig.2).Themodelledupperdepthlimitsforblackcoralswerecomparedtomeasuredupperdepthlimitsusingtwocommonlyemployedmetrics,therootmeansquareerrorandmeanabsoluteerror(RMSEandMAE,ChaiandDraxler,2014).RMSEandMAE   wereusedto Fig.5. Meanupperdepthlimits( ± 1SE)forblackcoralsobservedbydiversalongver-tical   transects( n =4)atlong-termmonitoringsitesinDoubtfulandMilfordSounds.Data   shownarebasedon   themean   of    samplemeansforsixsamplingoccasionsbetween2007and2013.Depthsareaccordingtomeansea   level. assessthemodelperformanceatallmooringlocationsunderdif-ferentcombinationsof  s c   and ˛   parameters.A   sensitivityanalysiswasalsoconductedusingsalinitydatafromtheM4mooringasanexample.Themodelsensitivitywasevaluatedbyvaryingeachof theinputparameters( s c   or ˛ )instepsof    10%from − 50%to   50%whilsttheotherparameterremainedunchanged.  2.6.Simulationsandforecasting  In   ordertoevaluatepotentialresponseof    blackcoraltochangesin   theLSL,we   usedthehydrodynamicnumericalmodelSINMODtosimulatethephysicalconditionsacrossthefjordundervary-ingweatherandtailracedischargescenarios.TheSINMODmodelhasa   longhistoryof    validationagainstobservedmeasurementsintheBarentsSea(e.g.Slagstadetal.,1989;SlagstadandMcClimans,2005),andasuccessfulside-by-sidecomparisonwithanothercommonlyusedoceanmodel,thePrincetonOceanModel–POM(HackettandRøed,1994).TheSINMODmodelwasparameterizedforuseinassessingtheeffectsof    weatherandthetailracedischargeonLSLbehaviourin   DoubtfulSoundaspartof    a   consentingprocessforamendingtherateof    dischargefromtheMHPS.Briefly,themodelwasdefinedfortheentireDoubtful-ThompsonSoundcomplexasfarastheentrancesof    thefjordata   constanthorizontalresolutionof100min   theeastandnorthdirections.Theverticalresolutionofthemodelwassetto   25layersofvaryingthickness;thesurfacelayersweremodelledata   muchhigherresolutionto   accountforchangesinthesalinitystructure.Thefjordis   thusrepresentedby‘cells’,or   blocksof    water,eachcellbeing100m 2 inthehorizontalplane,andbetween0.5   and150mthickin   thevertical,whichtogetherapproximatelyfillthesamespaceasof    theactualfjord.SyntheticsalinitydatasetsweregeneratedusingtheSINMODmodelunderdifferentscenariosforthemaindriversknowntoinfluencetheLSL:rainfall,windandtailracedischarge.Duringsim-ulations,eachdriverwasvariedwhiletheothertwodriverswereheldattheactuallevelmeasuredduringtheperiod.Dataforrain-fall   andwindsusedinthemodelrunswerefromtheSecretaryIslandandDeepCoveweatherstations(seeFig.2).Atotalof    104riversweredefinedwithinthemodeldomainbasedonknownriverlocations;flowsfromtheseriverswerecalculatedtorepre-sentthefreshwaterenteringthefjordbasedonatotalcatchmentareaof    1069km 2 .Thistotalvolumeofwaterwasthendividedbetweentheriversbasedontheproportionalareaof    theirrespec-tivecatchments.Windswereresolvedintofjordperpendicularprimarydirections(Gibbs,2001).Weathervariableswerechangedinthemodelbyproportionalincreasesanddecreasesinrain(a20%
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