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Modeling the spatial and temporal distribution of planktonic foraminifera [Elektronische Ressource] / vorgelegt von Igaratza Fraile Ugalde

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Modeling the Spatial and TemporalDistribution of PlanktonicForaminiferaDissertation zur Erlangung desDoktorgrades der Naturwissenschaftenam Fachbereich Geowissenschaftender Universitat¨ Bremenvorgelegt vonIgaratza Fraile UgaldeSeptember 2008The question is not what you look at, but what you see- Henry David Thoreau -iContentsAcknowledgements viiAbstract viii1 Introduction 11.1 Planktonic foraminifera .......................... 11.2 as paleoproxy .................. 61.2.1 Foraminiferal abundance as a paleotemperature proxy . . . . 71.2.2 shell chemistry as ae proxy . . 91.2.3 Difficulties associated with foraminifera-based proxies . . . . 101.3 Seasonality of planktonic foraminifera 111.4 Scientific objectives ............................. 132 A dynamic global model for planktonic foraminifera 252.1 Introduction . . ............................... 252.2 Model setup . . 272.2.1 Ecosystem model .......................... 272.2.2 PLAFOM . 272.2.3 Standard model experiment: grid, forcing and boundary con-ditions ................................ 332.2.4 Comparison to core-top data ................... 352.2.5 to sediment-trap data ................ 352.2.6 Sensitivity analysis of the parameters .............. 362.3 Results .................................... 382.3.1 Spatial distribution patterns.................... 382.3.2 Temporal .................. 41iiiContents2.3.3 Spatio-temporal distribution pattern ............... 452.3.

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Published 01 January 2008
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emporalT

and

Spatial

the

Modeling

Planktonic

of

Distribution

Foraminifera

September

2008

von

gelegtvor

Igaratza

Fraile

Ugalde

der

emenBr

at¨Universit

am

GeowissenschafteneichFachber

des

Erlangung

zur

Dissertation

NaturwissenschaftendergradesDoktor

The

question

is

i

not

what

you

look

-

at,

but

Henry

what

David

you

see

eauThor

-

Acknowledgements

Abstract

Contents

Introduction1..........................foraminiferaPlanktonic1.11.2Planktonicforaminiferaaspaleoproxy..................
1.2.11.2.2ForaminiferalForaminiferalshellabundancechemistryasaasapaleotemperaturpaleotemperaturepreoxypr.oxy.....
1.2.3Difficultiesassociatedwithforaminifera-basedproxies....
1.3Seasonalityofplanktonicforaminifera..................
.............................objectivesScientific1.4

2Adynamicglobalmodelforplanktonicforaminifera
2.1Introduction.................................
2.2Modelsetup.................................
..........................modelEcosystem2.2.1..............................PLAFOM2.2.22.2.3Standardmodelexperiment:grid,forcingandboundarycon-
................................ditions2.2.4Comparisontocore-topdata...................
2.2.5Comparisontosediment-trapdata................
2.2.6Sensitivityanalysisoftheparameters..............
2.32.3.1ResultsSpatial....................................distributionpatterns....................
2.3.2Temporaldistributionpatterns..................

iii

vii

viii

11679101131

255272727233535363838314

Contents2.3.42.3.3SensitivitySpatio-temporalexperiment:distributionspatio-temporalpattern...............distributionpatterns45
withconstanttemperature.....................45
2.4Discussion..................................47
2.4.1Comparisonwithcore-topdata..................47
2.4.2Comparisonwithsediment-trapdata..............50
2.4.3Sensitivityanalysis.........................51
2.4.4Modelexperimentwithconstantmixed-layertemperature..51
2.5Summaryandconclusions.........................53
33.1SeasonalIntrbiasoductionin..Foraminifera-based...............................Proxyrecords6677
3.2DataandMethods.............................69
3.2.1Descriptionofthemodel......................69
3.2.2Sediment-trapdata.........................69
3.2.3Experimentaldesign........................71
17....................................Results3.33.3.1Influenceofseasonalityandtemperaturesensitivityontem-
peratureestimates.........................71
3.3.2Sensitivityanalysis.........................73
3.4Discussion..................................77
3.4.1Latitudinalspeciesdistribution..................77
3.4.2SensitivityofspeciestochangesinSST.............79
3.5Conclusions.................................80
4SeasonalityofplanktonicforaminiferaduringtheLastGlacialMaximum91
4.1Introduction.................................91
29...................................Methods4.24.2.1Foraminiferamodelandexperimentsetup...........92
4.2.2CCSM3ClimateModelsimulations...............93
4.2.3UVicEarthSystem-ClimateModelsimulations........95
4.2.4Sedimentaryfaunalassemblages.................97
4.2.5Flux-weightedtemperaturesignal................98
4.3Results....................................100
4.3.1RelativeabundancesofthespeciesduringtheLGM......100
4.3.2ForaminiferalseasonalityduringtheLGM...........102
4.44.4.1Discussion.Comparison..between...............................modeloutputandsedimentsamples..110404
4.4.2Influenceofseasonalityonproxyrecords............105
iv

Contents4.5Conclusions.................................109
5VerticaldistributionoflivingplanktonicforaminiferaintheAzoresFront119
5.1Introduction.................................119
5.2Materialandmethods...........................120
5.2.1Samplingandprocessing.....................120
5.2.2Oceanographicsetting.......................122
5.3Results....................................126
5.3.1Totalforaminiferalfauna.....................126
5.3.2Foraminiferalassemblagecomposition.............126
5.3.3Modelprediction..........................127
5.4Discussion..................................131
5.4.1Depthhabitatofthespecies....................131
5.4.2Comparisonbetweensamplesandmodelprediction.....132
5.5Conclusions.................................134
139Summary6141Conclusions77.1Outlook....................................142
AModelnotationandequations145
A.1A.2CouplingParametersforbetweentheecosystemforaminiferaandmodelforaminifera..................models........114465
A.2.1Variablesandinitialvalues....................146
A.2.3A.2.2SpeciesBiologicalspecificparametersbiologicalcommonparameterstoallspecies........................114476
A.3Modelequations...............................149
v

Acknowledgments

ThisworkwascarriedoutattheGeosciencesDepartmentofBremenUniversity,
andwasfundedbyDeutscheForschungsgemeinschaft(DFG)withintheEuropean
GraduateCollegue“ProxiesinEarthHistory”(EUROPROX).Theysupportedme
duringthreeyearsgivingtheopportunitytoparticipateinseveralinternationalcon-
ferencesandexchangeprograms.
IMulitza,wouldwhoseliketothoughtfulthanktomyadviseoftensupervisors,servedProf.togiveMichaelmeaSchulzsenseofanddirDr.ectionStephandur-
ingmyPhDstudies.Iwouldhavebeenlostwithoutthem.Thankyouforbelieving
inme,andforalwaysencouragingmetogobeyondmypastachievements.Ialso
liketoexpressmygratitudetoProf.MichalKucerawho,duringmystayinthe
UniversityofT¨ubingen,sharedwithmealotofhisexpertiseandresearchinsight.
IamindebtedtomymanycolleaguesandPhDstudentsatBremenUniversity
forprovidingastimulatingandfunenvironmentinwhichtolearnandgrow.Iam
especiallygratefultothe’palmod’group,whocreatedafriendlyworkingenviron-
ment.AndreasManschkewasparticularlyhelpfulincomputersupport,patiently
teachingmetoworkwithLinux.MathiasPrangehasbeenalwaysinterestedinmy
researchandIwouldliketothankhimforallhiscontributions.J¨orgFranke,who
spentplentyoftimefightingwithmycomputerproblemsandprovidedmeseveral
usefulpiecesofhiscode,turnedoutagreatofficemate.
IwishtothankeverybodywithwhomIhavesharedexperiencesinlife.From
thepeoplewhofirstpersuadedandgotmeinterestedinsciencetothosethathave
joinedmeinthediscoveryoflife.IwouldspeciallyliketothankCatalinaGonz´alez
andIlhamBoumetarhamwho,withthegiftoftheircompanyandunconditional
friendship,mademydaysinBremenmoreenjoyableandworthliving.
Finally,Iwouldliketothankmyfamilyfortheunderstanding.Theyhaveal-
wayssupportedandencouragedmetodomybestinallmattersoflife.TothemI
thesis.thisdedicate

vii

UgaldeFraileIgaratzaemenBrOctober200817,

Abstract

iments,Planktonicanddueforaminiferatotheircontributeexcellentprsubstantiallyeservationtointhesediments,fossilrecorthedoffossilmarineshellsarsed-e
ofnalgreatassemblagespaleoceanographicandgeochemicalsignificance.compositionTemporalofthevariationsindividualinfossilsedimentaryshellshavefau-
becomeimportantproxiesforpastoceanicconditions.Differentecologicalprefer-
encesbetweenspeciescausedistinctseasonalpatterns,andtheimprintofdiffering
seasonalproductionispreservedinthesedimentaryrecord.Accurateknowledgeof
foraminiferalecologyandseasonalsuccessionisindeedcrucialtocorrectlyinterpret
becorrsensitiveespondingtoprtemperaturoxy-basede,randeconstrtherefoructions.eclimatePlanktonicchangesmayforaminiferaalterartheeknownseasonalto
patternofspecies.Anychangeinthetimingofthelargestfluxtotheseafloorthat
mayhaveoccurredinthepastwillleadtoabiasinestimatedpaleotemperature.
Therefore,thisdissertationfocusesonthevariabilityofplanktonicforaminiferal
seasonalitythroughtime,anddiscussesitsimplicationsforpaleotemperaturere-
uctions.constr

Anumericalmodelsimulatingthepopulationdynamicsofplanktonicforamini-
ferawasdevelopedandcoupledtoanexistingmarineecosystemmodel.Thismodel
isforcedwithaglobalhydrographicdataset(e.g.,temperature,mixedlayerdepth)
andwithbiologicalinformationtakenfromtheecosystemmodeltopredictmonthly
concentrationofthefollowingforaminiferaspecies:Neogloboquadrinapachyderma
(dextralandsinistralvarieties),Globigerinabulloides,Globigerinoidesruber(whiteva-
riety)andGlobigerinoidessacculifer.Thesespeciesaresensitivetosea-surfacetemper-
ature,andduetotheirhighspatialcoverageandabundancearethemostcommon
planktonicforaminiferaspeciesusedinpaleoceanography.Themodelresultsfor
theglobaldistributionofplanktonicforaminiferaformodernconditionsarecom-
paredtoavailablecore-topandsediment-trapdata.IntheNorthAtlantic,model
predictioniscomparedtothelivingpopulationcollectedbyplankton-nets.

ix

Themodeledspatialdistributionofmostofthespeciescomparesfavorablywith
core-topdata.Themodelpredictionindicatesthatpolarregionsaredominatedby
N.pachyderma(sin.);N.pachyderma(dex.)andG.bulloidesarethemostcommon
speciesinhighproductivityzones;andtropical-subtropicalspecieslikeG.ruberand
G.sacculiferaremoreabundantinoligotrophicwaters.Thepredictedseasonalflux
patternscoincidedwithsediment-traprecordsinmostofthelocations,althoughthe
comparisonwashamperedbyinterannualvariabilitynotcapturedbythemodel.

Usingtheforaminiferamodel,wecarriedoutsensitivityexperimentstostudy
theimentresponseusingaofconstantforaminiferatemperaturtodiffereoentf12◦Cboundaryindicatedconditions.thatfoodAsensitivityavailabilityiexpersa-n
importantfactorcontrollingforaminiferaldistribution.

Anothersensitivityexperimentconsistedofdecreasingthetemperatureglob-
allyby2◦Cand6◦C,andassessingtheinfluenceofthistemperaturevariationon
therecordedsignal.Inmostoftheregionsatmidandhighlatitudes,duetothe
coolingandtemperaturesensitivityofthespecies,maximumproductionshifted
toawarmerseason.Thus,theforaminiferalpopulationasawholerecordedlittle
changeinthetemperature.Bycontrast,intropicalwaters,wheretemperaturecy-
clehasrelativelylowamplitude,therecordedsignalisclosetoannualmeanSST
regardlessofthetimingofmaximumproduction.Therefore,atlowlatitudesfora-
miniferarecordedtheentiretemperaturechange.Theseexperimentsemphasizethe
importanceofconsideringchangesinseasonalitythroughtime,astheycanmask
thetotaltemperaturevariation.

Finally,westudiedtheresponseofforaminiferatotheboundaryconditionsof
theLastGlacialMaximum.Weforcedtheforaminiferamodelusingthephysicaland
chemicalparameterspredictedbycoupledclimatemodels.Intropicalwatersvari-
ationsinforaminiferalseasonalitydidnotcausesignificantchangeintherecorded
temperature.Bycontrast,athighlatitudestheforaminiferalfluxtotheseafloor
hasapronouncedseasonalcycle,andtheamplitudeoftemperatureseasonalityis
alsohigh.Therefore,changesintheseasonalityofforaminiferahadlargeinfluence
ontheseasonalimprintofthefossilrecord.Theassessmentandquantificationof
seasonalbiasonaglobalscaleallowstheimprovementofforaminifera-basedproxy
calibrations.

Kurzfassung

PlanktischeForaminiferentragenwesentlichzumFossilieninhaltinmarinenSedi-
mentenbeiundsinddahervongrosserBedeutungf¨urdiePal¨aozeanografie.Zeitliche
Verfenheit¨anderihrerungenfossileninderSchalenfaunalensindzuZusammensetzungeinemwichtigenoderPrdieoxybeigeochemischederRekonstrBeschaf-uk-
tionmarinerPal¨aoumweltbedingungengeworden.Unterschiedeinder¨Okologie
dieimverschiedenerSedimentForaminiferaufgezeichnetenartenwerden.erzeugenEingenauesunterschiedlicheWissen¨jahruberdieeszeitliche¨OkologieMusterder,
f¨urdieForaminiferkorrenekteundihrInterpreretationsaisonalenvonprSukzessionoxy-basiertenistvonRekonstrentscheidenderuktionen.BedeutungPlanktis-
¨cheanderungenForaminiferjahrenreszeitlicheeagierenMustersensitivderaufTForaminiferenartenemperaturschwankungen,ver¨andernsok¨dassonnen.Klima-Jede
Ver¨anderungdesZeitpunktesdesmaximalenForaminiferen-FlusseszumMeeres-
bodendiesemGrkannundzubehandeltFehlernbeidiedervorliegendeAbsch¨atzungDissertationvonPal¨dieVeraotemperatur¨anderenungf¨uhrderen.Saison-Aus
alit¨atplanktischerForaminiferenimLaufederZeitsowiediedarausresultierenden
Implikationenf¨urPal¨aotemperatur-Rekonstruktionen.

EinnumerischesModellzurSimulationderPopulationsdynamikplanktischer
Foraminiferenwurdeentwickeltundaneinbereitsexistierendesmarines¨Okosystem-
modellgekoppelt.AngetriebenwirddasModellmiteinemglobalenhydrografis-
chenDatensatz(z.B.,f¨urTemperatur,Deckschichm¨achtigkeit)sowiemitbiologis-
chenInformationen,diedem¨Okosystemmodellentnommenwerden,umdiemonat-
licheKonzentrationfolgenderArtenzuberechnen:Neogloboquadrinapachyderma
(dextralundsinistral),Globigerinabulloides,Globigerinoidesruber(wei¨s)andGlobigeri-
noidessacculifer.DieseArtenreagierensensitivaufMeeresober߬achentemperaturen
undz¨ahlenaufgrundihrergrossenr¨aumlichenAbdeckungundH¨aufigkeitzuden

xi

wichtigstenplanktischenForaminiferenf¨urdiePal¨aozeanografie.DieModellergeb-
nissehinsichtlichderglobalenheutigenVerteilungderForaminiferenwerdenmit
verf¨ugbarenOberfl¨achenundSedimentfallendatenverglichen.

Diemodelliertenr¨aumlichenVerteilungsmusterdermeistenArtenstimmengut
mitdenDaten¨uberein.DieModellrechnungenergeben,dassdiepolarenRegionen
vonN.pachyderma(sin.)dominiertwerden,dassN.pachyderma(dex.)undG.bu-
subtrlloidesdieopischeh¨ArtenaufigstenwieArtenG.ruberinundHochprG.oduktivitsacculifer¨amatszonenh¨aufigstensindinundoligotrdasstrophenopisch-Ge-
bietenauftreten.DiesimuliertensaisonalenFlussmusterstimmenweitgehendmit
annuelleVSedimentfallendatenariabilit¨at,¨dieuberdasein,Modellwenngleichnichtdersimuliert,Modell-Daten-Verschwerterwirgleichd.durchinter-

MitHilfedesForaminiferen-ModellswerdenSensitivit¨atsexperimentedurchge-
fzu¨uhrt,umuntersuchen.denEinflussEinExperimentunterschiedlicherbeieinerkonstanteRandbedingungenTemperaturaufdievon12◦ArtenverteilungC,zeigt,
dassdieNahrungsverf¨ugbarkeiteinwichtigerKontrollfaktorist.

EinweiteresSensitivit¨atsexperimentbestehtdarin,dieTemperaturglobalum
2◦Cund6◦CzureduzierenunddenEinflussdieserTemperaturvariationaufdas
BreitenaufgezeichneteverschiebtSignalsichzudieberechnen.MaximalprIndenoduktionmeistenhinzuRegioneneinerw¨mittlerarmererenundJahrhohereszeit.
TInfolgedessenemperaturver¨anderzeichnetungdieauf.InPopulationtropischenvonN.Gebietenpachydermaalshingegen,Ganzeswonurjahreineeszeitlichegeringe
TneteSignalnaheemperaturschwankungenamWertdernurJahreineesmitte.kleineAmplitudehaben,liegtdasaufgezeich-

Dar¨uberhinauswurdedieReaktiondesForaminiferensignalsaufdieRandbe-
dingungendesLetztenGlazialenMaximumsuntersucht.DasModellwurdevon
chemischenundphysikalischenRandbedingungenangetrieben,diegekoppelten
Klimamodellenentnommenwurden.IndenTropen¨anderteeine¨Anderungder
Saisonalit¨atderForaminiferendasTemperatursignalimSedimentnurwenig.In
denhohenBreitenzeigtderForaminiferenfluxzumMeeresbodendagegendeut-
lichesaisonaleZyklenunddieAmplitudederTemperatur-Saisonalit¨atisthoch.
¨AnderungeninderSaisonalit¨atderForaminiferenhabendahereinendeutlichen
EinflussaufdensaisonalenCharakterderSedimentabfolge.DieBewertungund
QuantifizierungdesEinflussesdiesessaisonalenSignalsaufdasglobaleSignaler-
laubtdieVerbesserungderKalibrationvonForaminiferen-Proxies.

1Chapter

foraminiferaPlanktonic1.1

Introduction

lanktonicforaminiferaaresingle-cellmarinezooplanktonwhichliveevery-
Psea-icewherei(Dieckmanntheetopenal.,ocean.1991),butTheyarecannormallysurviveinabsentextrfremeomcoastalconditionswaters.likewithinMost
of(Murraythe,species1991).liveDuringinthetheirupperlifecyclewatertheycolumn,producewheraeathefoodmulti-chamberavailabilityedcalcarishigheous
toshell.theTheseafloorlife.ofThisforaminiferashellisendsnormallyafterrwelleprproduction,eservedinanditssediments,calcareousandshellthereforsinkse
thefossilsofplanktonicforaminiferaareextensivelyusedforpaleostudies.Dueto
themostglobalimportantspatialfossilcoverageusedinandgoodprpaleoceanographyeservation,.planktonicForaminiferareprforaminiferaesentaareminorthe
componentofthetotalzooplanktonbiomass(between2-10%,ArnoldandParker,
of1999)thebuttotaltheircarbonatecalcareoussequestratedshellsinaccumulatedthedeeponseathesea(Langerflooretal.,account1997).forBecauseabout20%the
carbonoceaniccycle,carbonatecarbonatesystemprisoductioncloselyoflinkedtoforaminiferabothholdsatmosphericgreatCOinter2estandforthepaleocli-global
matologists.

Dependingontheirspecificecologicalneeds,differentforaminiferaspeciesare
distributedlatitudinallyandverticallyinthewatercolumn.Murray(1897)wasthe
firsttonotethatthedeadshellsofforaminiferaspeciesweredistributedglobally
inhorizontalbelts,andconcludedthattemperaturemustbethemostimportant
controllingfactorinsuchdistribution.Later,plankton-tows(e.g.,B´e,1960)andlab-
oratoryculturestudiesconfirmedtheimportanceoftemperatureinthephysiology
offoraminifera(e.g.,Bijmaetal.,1990).Asaresult,planktonicforaminiferalassem-
blagesoccurinfivemajorfaunalprovinces:tropical,subtropical,transitional(or
temperate),subpolarandpolar(B´e,1977)(Fig.1.1,lowerpanel).Althoughthetem-
peraturelimitsofforaminiferaarenotsharplydefined,eachforaminiferalspecies
hasanoptimumtemperatureandarangeoftemperaturetolerance(Fig.1.1,upper

2

Figure1.1:

ThefivemajorfaunalovincesprofmodernplanktonicThedistributionreflectsthestrongrelationshipbetweenspecies

upperpanel,relativeabundanceofplanktonicforaminifera

samplesoftheAtlanticOceanisshown(Kucera,2007).

1.

foraminiferaoductionIntr

(lowerpanel).occurrenceandSST.inthe

species

in

surface

sediment-

foraminiferaPlanktonic1.1.

3

(a)(b)
Figure1.2:Alivingplanktonicforaminifera,(a)G.sacculifer(approx.300μm),oneofthe
twomostimportantspinosespeciesinwarmtropicalsurfacewaters.(b)G.truncatulinoides
(approx.500μm),anon-spinosespecies,livingpreferentiallyatthebaseofthethermocline.
Photo:C.deVargas,UniversityofAlaska.

panel).However,temperatureseemstobecriticalonlywhenitisatthelimitsofthe
tolerancerange(Ortizetal.,1995;˘Zari´cetal.,2005).Ataregionalscale,foodavail-
abilityisanimportantfactorcontrollingtheabundanceofforaminifera.Thedietof
foraminiferavariesbetweenspecies,butmostspeciescanconsumeawidevariety
ofpreys.Someforaminiferaspeciespossesspines(Fig.1.2),whichseemstobea
deviceforcapturingpreys(B´e,1977;Sextonetal.,2006),althoughthisisstillnot
clear.Mostforaminiferalspeciesareopportunistictosomeextent,butingeneral,
spinosespeciesdependonanimalprey,includingmetazoanssuchascopepodsor
pteropods(Anderson,1983;CaronandB´e,1984;Spindleretal.,1984).Non-spinose
specieshavemoreherbivorousbehavior,andfeedmainlyondiatomsanddinoflag-
ellates(Andersonetal.,1979;Spindleretal.,1984;Hemlebenetal.,1985).Spinose
speciesusuallybearsymbionts,commonlydinoflagellatesorchrysophycophytes
(e.g.,B´e,1977).Thepresenceofsymbiontsenablesforaminiferatosurviveinareas
wherenutrientsandfoodarescarcebutlightisabundant,inparticularsubtropical
andtropicaloceanicenvironments(Hemlebenetal.,1989;Murray,1991;Hallocket
al.,1991;Norris,1996).Algalsymbiontsarealsoimportantforthecalcificationpro-
cess,astheycanmodulatethechemicalmicroenvironmentaroundtheshell(Kucera,
2007).Species-specificecologicalneedsaresummarizedinTable1.1.

iesTherduringeartheearlastoundyears40-50haveshownplanktonicthatmanyforaminiferaofthesespecies.speciesareHowever,comprisedgeneticbystud-dif-

4

(a)

oductionIntr1.

(b)

(d)(c)Figure1.3:Planktonicforaminiferafossilspecimens:(a)G.bulloides(approx.200μm),(b)
G.ruber(approx.200μm),(c)G.sacculifer(approx.300μm)and(d)N.pachyderma(sin.)(ap-
prox.150μm).Photo:F.Peeters,FreeUniversityofAmsterdam.

ferentgenotypeswhicharemorphologicallyindistinguishable(Darlingetal.,1999;
KuceraandDarling,2002;Darlingetal.,2004,2006).Themainpartofthisdisserta-
tionfocusesonthefollowingforaminiferalspecies:N.pachyderma(sinistralanddex-
tralvarieties),G.bulloides,G.ruber(whitevariety)andG.sacculifer(Fig.1.3).These
fivespecies,whichhavedifferentgeographicalandecologicalcharacteristics,are
distributedworldwideandarewellstudied.Therefore,theyrepresentthebestsub-
setofforaminiferausedinpaleoceanography.

N.pachyderma(sinistralvariety)N.pachyderma(sin)isatypicalcold-water
speciesandisthedominantspeciesinpolarwatermasseswhereitcansurviveeven

foraminiferaPlanktonic1.1.

5

orwithinousdiet,seaicefeeding(Dieckmanmainlyetonal.,diatoms1991).Itisa(Hemlebennon-spinoseetal.,1989;species,Murrayand,has1991).anTherherbiv-e-
fore,maximumfluxesprimarilyoccurwhenprimaryproductivityishigh(˘Zari´cet
al.,2005).N.pachyderma(sin.)isnormallyassociatedwithweaklystratifiedwaters
andwithdeepmixed-layerdepth.Inpolarwatersitisfoundtoliveintheupper
100m(Volkmann,2000),whereasattemperateregionsitseemstopreferdeeperwa-
1991).,(Murrayters

N.pachyderma(dextralvariety)N.pachyderma(dex.)isasubpolarspecies,
typicallyoccurringathighlatitudesandupwellingregions.Ithasapreferencefor
warmertemperaturesthanthesinistralvariety,between∼8-22◦C(˘Zaric´etal.,2005).
Thefoodisthesameasthesinistralvariety,whichconsistsofphytoplankton(Hem-
lebenetal.,1989).N.pachyderma(dex.)livesatthethermocline,andisoftenassoci-
atedwithmaximumchlorophylllevels(Ortizetal.,1995).

G.bulloidesTemperaturedoesnotseemtostronglyaffecttheabundanceofG.
bulloides.Itcanbefoundfrompolartosubtropicalwatersandisrelatedtohigh
productivityareas(Schiebeletal.,1997).Therefore,itisoftenusedasanindicator
ofupwellingintensity.G.bulloidesisaspinosespecies,butdoesnotbearalgalsym-
bionts(e.g.,Murray,1991;Hemlebenetal.,1989).Itisconsideredanintermediate-
dwellingspecies,andhasapreferenceforweakly-stratifiedwatersascharacteristic
ofupwellingregions(Hemlebenetal.,1989;Murray,1991;PujolandGrazzini,1995).

G.ruber(whitevariety)G.ruber(white)isinsurface-dwellingspeciestypically
livingintropical-subtropicalwaters(Murray,1991).Itisaspinosespeciesfeeding
mainlyonzooplankton(copepodsandtintinids),althoughithaslesszooplankton
dependencethanotherspinosespecies(Hemlebenetal.,1989).Ithasapreference
forstratifiedwaters(PujolandGrazzini,1995),andisespeciallytoleranttovarying
sanities(Watkinsetal.,1996).

G.sacculiferG.sacculiferisatypicaltropicalspecies.Itpossessesspinesand
bearsdinoflagellatesymbionts(Hemlebenetal.,1989;Murray,1991;Watkinsetal.,
1996).Itsdietconsistsmainlyofcopepods,pteropods,tunicatesandotherzoo-
plankton.Itprefersshallow,stratifiedwatersandisabsentatlowtemperatures
(optimumtemperaturerangeis≥23◦C)(˘Zaric´etal.,2005).

6

Table1.1:Dietpreferencesofdifferentforaminiferalspecies.

oductionIntr1.

SourceSymbiontSpinesDietSpeciesN.pachyderma(sin.)herbivorenobarrenHemlebenetal.(1989)
N.pachyderma(dex.)herbivorenobarrenHemlebenetal.(1989)
G.bulloidesherbivore(moreopportunistic)yesbarrenHemlebenetal.(1989)
(1998)MixandatkinsW(1991)Murray(1991)AndersonandLeeG.ruber(white)mostlycarnivoreyesbearingSpindleretal.(1984)
WatkinsHemlebenandetal.Mix(1989)(1998)
G.sacculifermostlycarnivoreyesbearingSpindleretal.(1984)
WHemlebenatkinsandetal.Mix(1989)(1998)

asforaminiferaPlanktonic1.2paleoproxy

Reconstructionofpastenvironmentalconditionsispossiblebytheuseofproxies.
Theseproxiesallowthecomparisonandvalidationofclimate-modelsimulations,
therebyimprovingourabilitytopredictfutureclimatechange.Mostevidencefor
paleoclimateisbasedoninformationderivedfrombiologicalsourcespreserved
inthefossilrecord.Themineralizedshellsofplanktonicforaminiferapreserve
physico-chemicalinformationofthewaterinwhichtheygrew.Thus,theshellsof
foraminiferadepositedonthesea-floorareoneofthemostimportantfossilsusedin
paleoceanographystudies.Differentoceanicpropertiessuchaspaleoproductivity
(e.g.,Mulitzaetal.,1999),paleotemperature(e.g.,Malmgrenetal.,2001)orsurface-
waterstratification(e.g.,Mulitzaetal.,1997)canbederivedfromfossilshells.
Planktonicforaminiferacanbeusedtoreconstructpastoceanictemperatures
bydifferentmethods:(1)Speciesabundancescanbedirectlyrelatedtosea-surface
temperature(SST),asmostofthespeciesaresensitivetotemperature;(2)thechem-
icalcompositionofcalciticshellsisextensivelyusedtoderivethephysico-chemical
conditionsoftheenvironmentwhereforaminiferagrew;(3)morphologicalfeatures
oftheshellcanalsoberelatedtoSST.Someexamplesofproxiesbasedonmor-
phologyincludeshellsize(MalmgrenandKennet,1978;Hecht,1976;Schmidtet
al.,2003,2004),shape(Kennett,1968a,b;Spencer–CervatoandThierstein,1997),
porosity(Berger,1968;Frerichsetal.,1972;deVargasetal.,1999;Itouetal.,2001)
andcoilingdirection(Ericson,1959;KuceraandKennett,2002)inparticularspecies

1.2.Planktonicforaminiferaaspaleoproxy

7

Figure1.4:ChangesincoilingdirectionofNeogloboquadrinawithtemperature.Atlowtem-
peraturestheleft-coilingspecimensaredominant(N.pachyderma),andbetween6-10◦Cthe
leftcoilingshellsarereplacedbytheright-coilingshells(N.incompta)(Kucera,2007).

(Fig.1.4).However,shellformationisacomplexprocesswhichdependsonmany
morefactorsthantemperature.Therefore,theuseofmorphologyasapaleotemper-
atureproxyisconsideredlessreliable.Adetaileddescriptionofmorphology-based
proxiesisdescribedinthereviewpaperbyKucera(2007).Thefollowingsectionis
focusedonspeciesabundanceandchemicalcompositionaspaleotemperatureprox-
ies,asthesearethemethodsmostwidelyusedbypaleoceanographers.

1.2.1Foraminiferalabundanceasapaleotemperatureproxy

Mostforaminiferaspeciesaresensitivetotemperature.Murray(1897)wasthefirst
toSinceinferthen,thatmanytheforaminiferalinvestigationshavedistributiondemonstratedpatternwasthepotentialinfluencedusebyoftheforamini-climate.
arferaertoelativelystudyeasyclimateandchange.economicAstechniques,foraminiferathesecollectionmethodsandhavespeciesbeenidentificationextensively
struseductionsincanbepaleoceanographydoneby.twoUsingdifferspeciesentapprcompositionoaches,usingforindicatorpaleotemperaturspecieserorecon-as-
composition.semblage

8

Intr1.oduction

speciesIndicatorThisisthesimplesttechniqueforusingplanktonicforaminiferatotraceenviron-
mentalchanges.Itisbasedonvariationsintheabundanceofindividualspecies
whichareadaptedtospecificenvironmentalconditions.Forexample,G.bulloides
isspecieswhichisadaptedtohighproductivityregions.Therefore,thepresenceof
G.bulloidesinsedimentsisanindicatorofupwellingconditions(e.g.,Thiede,1975).
AnotherexampleistheabundanceofN.pachyderma(sin.),atypicalpolarspecies,
whichintemperatewatersasacoolingindicator.However,ecologicalknowledge
ofindividualspeciesisoftenlimited,andgroupingsimilarspeciesintoassemblages
mayprovideamorerobustproxy.

compositionAssemblageThecompositionofplanktonicforaminiferaassemblagescanbeusedtoestimate
pastSSTsviatransferfunctions.Transferfunctionsprovideamathematicalrela-
tionshiprelatingspeciesabundancetotheirlifehabitats,whichisappliedtothe
byfossilBergerfauna.(1969).ThemThisostsimpleequationrequationelatestothepredictoptimalpaleotemperaturtemperatureoefwaseachintrspeciesoducedto
itsrelativeabundancetoyieldanaverageestimateofSST.However,thisapproach
doesnotaccountforthecomplexinteractionsbetweentemperatureandotherpa-
transferrametersthatfunctionrinfluenceeconstructionsdistribution.wasAintrwelloducedknownbyimprImbrieovementandinKippthepr(1971).ecisionTheyof
appliedmultipleregressionstatisticaltechniquesandQ-modefactoranalysistore-
lateenvironmentalparameterswithspeciesabundancesincore-topsamples.This
methodwasthebasisoftheCLIMAPprojecttoreconstructtheSSTfieldsofthelast
1976).CLIMAP,(e.g.,periodglacial

Inmorerecenttimes,newstatisticalmethodshavebeendevelopedtoimprove
theaccuracyofpaleotemperaturereconstructions.Forexample,themodernanalog
technique(MAT)(Hutson,1980)searchestheentirecalibrationdatasettofindthe
mostsimilarassemblages,andusesaverageSSToftheselocations.Themodernana-
logtechniquewithsimilarityindex(SIMMAX)(Pflaumannetal.,1996)isalsobased
onthedegreeofsimilaritybetweenfossilandmodernassemblages.Thismethod
usesanewsimilarityindexandincorporatesgeographicinformationgivinghigher
weighttosamplesthatareclosertothefossilsample.Therevisedanalogmethod
(RAM)(Waelbroecketal.,1998)increasesthenumberandrangeofcalibrationsam-
plesandintroducesmorerigorouscriteriafortheselectionofthebestanalogsam-
ples.Artificialneuralnetwork(ANN)isacomputer-basedmethodwhich,using
artificialintelligencetechniques,hasthecapabilitytoautonomously“learn”there-

1.2.Planktonicforaminiferaaspaleoproxy

9

lationshipbetweenassemblagesofplanktonicforaminiferaandSST(Malmgrenand
1997).dlund,NorThetransferfunctionshaveyieldedverygoodtemperaturereconstructions,with
apredictionerrorofabout1◦C(Malmgrenetal.,2001).Thesimultaneousapplica-
tionofdifferenttransferfunctiontechniquesprovidesanobjectivetoolforassessing
thereliabilityoftheproxies,andcontributestominimizebiasassociatedwiththe
2005).al.,et(Kuceratechnique

1.2.2Foraminiferalshellchemistryasapaleotemperatureproxy
Shellsofforaminiferaarebuiltwithcalcite,buttheexactcompositionofthecalcite
dependsonthesurroundingenvironmentalconditions.Duringtheirlifecycle,fora-
miniferarecordachemicalsignatureintheirshell,thatreflectsthephysico-chemical
usedconditionstorofeconstrtheuctsurroundingpaleoceanographicwater.Theconditionschemical(e.g.,compositionRohlingofandtheshellCooke,is,1999).thus,
TheandMmostg/Caimportantratioofprtheoxiescalcite.forSSTarebasedontheoxygenisotopecomposition

shellsforaminiferalinisotopesStableOxygenhasthreenaturallyoccurringstableisotopes:16O(≥99%),17Oand18O.
Theabsoluteabundancesoftheisotopesaredifficulttodetermine,andtherefore
theratiosbetweenisotopesareoftenusedtoassesstheisotopiccomposition.The
termδ18Oisusedtodescribetheoxygenisotopecompositionofthecalcite,cor-
respondingtothepartsperthousanddifferencebetweenthe18O/16Oratioofthe
sampleandaknownexternalstandard(PDBstandard).The18O/16Ointheshell
dependsmainlyontwofactors:ononehand,itdependsontheisotopiccomposi-
tionofthesea-water,whichatthesametimedependsonglobalicevolume.On
theotherhand,theoxygenisotopefractionationincarbonateisalsoafunctionof
temperature.Therefore,byusinganindependentmethodtocalculateicevolume,
thetemperatureeffectintheisotopiccompositioncanbeisolatedandusedtore-
constructpaleotemperatures.TheearlyworkbyEmiliani(1955)hasbeenabasisfor
laterstudies.Althoughheinitiallyoverestimatedtheglacial-interglacialtempera-
turechangesbynotremovingtheicevolumeeffect,thispioneeringworkhasplayed
animportantroleinpaleoceanographyandbecomeoneofthemostimportanttech-
niquesinthereconstructionofpastclimates(RohlingandCooke,1999).Although
δ18Oofthecalciteisdirectlyrelatedtotemperature,duetothisdoublesignal,it
ismostcommonlyusedtoreconstructglobalicevolumebyremovingthetemper-
atureeffectderivedfromanindependentproxy(Shackleton,1967;Shackletonand
1973).Opdyke,

10

oductionIntr1.

Traceelementcompositioninforaminiferalshell
Theforaminiferalcalciteis99%CaCO3,withtheremaining1%correspondingto
traceelementselementscanalsosuchbeasusedMgto,rSr,econstrBaoructNapast(Lea,oceanic1999).conditions,Theratiosassomebetweenofthetraceel-
reviewementalpapersubstitutionbyRosenthaldepends(2007)onprenviresentsonmentaldetailedfactorsdescription(Benderofetpral.,oxies1975).basedTheon
trace-elements.Themostcommonlyusedpaleotemperatureproxyistheratiobe-
tweenMgandCa.ThesubstitutionofCabyMgisatemperature-dependentpro-
cess:athighertemperaturesmoreMgisincorporatedintothecalcite(Mucciand
Morse,temperatur1990).eforVariousseveralapprspeciesoachesofhaveplanktonicbeenmadetoforaminifera.calibrateTheseMg/Caincluderatiosmulti-and
forspeciesalimitedcore-topnumbercalibrationofspecies(e.g.,(e.g.,NElderfield¨urnberandgetal.,Ganssen,1996)and2000),cultursediment-trapecalibrationsbased
multi-speciescalibration(e.g.,Anandetal.,2003).Ingeneral,thereisgoodagree-
mentbecomebetweenoneofallthethesemostapprimportantoaches.prInroxiesecentforyears,SSTreconstrforaminiferaluctionsMg(e.g.,/CaCrratioonbladhas
1981).en,Malmgrand

1.2.3Difficultiesassociatedwithforaminifera-basedproxies
Althoughtheprecisionofforaminifera-basedproxieshasincreasedinrecentyears,
alltheseapproachesbearproblemsassociatedwithbothpre-depositionalandpost-
depositionalalteration.Post-depositionalalterationincludesprocessessuchasbio-
turbation,whichmixesdifferentagelayers(e.g.,B´e,1977;Be´andHutson,1977;
Boltovskoy,1994)oradvectionoftheshellsduringandaftersinking(e.g.,B´e,1977).
Whenusingassemblagecompositionforreconstructions,selectivedissolutionmay
alsoleadtoabiasinestimatedtemperaturebyremovingthemorefragileforami-
niferalspeciespreferentially(e.g.,Berger,1968;ThunellandHonjo,1981;Leand
Thunell,1996;DittertandHenrich,1999).

Thereareotherproblemsassociatedwithenvironmentaluncertaintiesduring
shellformation,oftenmakingtheinterpretationofproxyrecordsdifficult.Oneissue
istherelatedwatertocolumntheindepthorderhabitattoofsatisfythetheirspecies:ecologicalsomeneedsforaminiferal(B´e,1977).speciesThereformigratee,inthe
chemicalsignaturerecordedintheshellcorrespondstoanintegratedsignalover
thebetweenlifeofthespeciesandforaminiferaregionsatdifcausesferentdifdepths.ficultiesinDiftheferencesinterprinetationmigrationoftheprpatternsoxy
ds.ecorr

foraminiferaplanktonicofSeasonality1.3.

11

Anotherdifficultyisrelatedtodifferentialforaminiferalproductionoverthe
year:planktonicforaminiferahavearelativelyshortlifespan,typicallyontheorder
rofoneespondsmonthtothe(SautterenvirandonmentalThunell,conditions1991),andduringthethissignalmonth.recorThededprinoxyarshellecordcorin-
prsedimentsoduction.istherDependingeforeondominatedthebyspeciestheandconditionsecologicalduringcirthecumstances,seasonoftherecormaximumded
signalmayeitherrepresenttheannualaverageorasingleseasonoftheyear(Mix,
r1987).ecords,Astheseasonalmainpartofdistributionthisplaysdissertationanwillimportantberolefocusedinontheit.interpretationofproxy

1.3foraminiferaplanktonicofSeasonalityOneofthemostimportantaspectsofforaminiferalecologyistheirannualdistribu-
tionpattern,whichhasmajorimplicationsforpaleoceanography.Planktonicfora-
miniferahavelargeseasonalvariationsinabundancetiedcloselytosurfacewater
hydrography(B´e,1960;Deuseretal.,1981;ThunellandReynolds,1987;Sautterand
Thunell,1991).Suchseasonalityisanimportantissuewhenreconstructingpast
yearoceanicduringconditions,whichasthethecalciticsignalrshellecorwasdedinthedeposited.shellcorrMix(1987)espondstoshowedthetimeinaofverythe
simplifiedmodelthatthetemperaturerecordedbyatemperature-sensitiveforami-
niferalpopulationdependsontheannualtemperaturecycleandthetemperature
sensitivityofthespecies.Theoverallflux(SF(T))dependsontheannualSSTdistri-
butionatthesite(W(T))andthepreferredtemperatureofthespecies(F(T)).Thus,
theoretically,thetemperaturesensedbythemeanpopulationofaspecies(Tr)isthe
flux-weightedmeanofalltemperaturesatthesite:

Tr=SF(TSF)·(TW)(T)

(1.1)

Thisrelationshowshowtemperaturedistributionandspecies-specificecological
preferencescaninfluencetherecordedsignal.Theecologyofplanktonicforamini-
feraisthereforeanimportantissueinpaleoceanography,asthefluxpatterninflu-
encesthepaleotemperatureinterpretation.Oneoftheassumptionsinpaleoceanog-
raphyisthattheseasonalityofforaminiferahasremainedunchangedthroughtime,

12

oductionIntr1.

Figure1.5:TheoreticalannualvariationofSSTinthenorthernhemisphere(solidline)and
seasonalvariationofaforaminiferalspeciesatthesamesite(dashedline)forglacial(blue)
andinterglacials(red).Duringtheinterglacial,theoptimaltemperaturerangeofthespecies
(graybar)occursduringspring,thusthespeciesmainlyrecordsaspringsignal.During
glacials,theoptimaltemperatureoccursduringsummerandthespecieswillthenrecorda
signal.summer

andthereforethesedimentaryrecordsreflectthesameseasonasatpresentday.
ditionsHowever,nchangeoresear(e.g.,cherbyhasclimateshownchange),thisassumptionforaminiferatobemaytrrue.Ifespondenvirbyonmentalvaryingtheircon-
intheseasonalpastwilldistribution.thenleadAnytoshiftabiasinintheforaminiferalestimatedseasonalitypaleotemperaturthatmayehave(Fig.occurr1.5).edA
growingnumberofproxiesarederivedfromtrace-elementcompositionofforami-
nifera.niferalTheshells,aimandofaroureallworkafisfectedtobyassessthethisdifferbiasentialbystudyingseasonalprvariationsoductioninofforamini-forami-
time.oughthrseasonalityferal

objectivesScientific1.4.

13

objectivesScientific1.4Thegoalofthisstudyistocontributetoabetterknowledgeofforaminiferalseason-
ality.Amodelingapproachisusedforaglobalassessmentofthepotentialbiasof
foraminifera-basedproxyrecordsresultingfromchangesinseasonalityatglacial-
interglacialtimescales.Themainquestionsthatarisefromthisstudyare:

•Isitpossibletomodelplanktonicforaminiferaldistributionataglobalscale?
•Canwepredicttheseasonalpatternofeachforaminiferalspecies,andquan-
tifytheimprintofthedistinctseasonalpatternspreservedinthesedimentary
d?ecorr•Canweassesstheresponseofplanktonicforaminiferatodifferentboundary
conditions?•Didtheseasonaldistributionofplanktonicforaminiferavaryfromglacialtimes
day?esentprto•Whataretheimplicationsofshiftsinseasonalfluxesfortheinterpretationof
down-coreproxyrecords?

Thisworkattemptstoanswerthementionedquestionsbyusingamodelingap-
proach.Forthatpurpose,anumericalforaminiferaldistributionmodelhasbeende-
velopedandimplementedwithinanexistingecosystemmodel(Mooreetal.,2002).
Theplanktonicforaminiferamodelpredictstheabundanceoffivefrequentlyused
foraminiferalspecies:N.pachyderma(sinistralanddextralvarieties),G.bulloides,
G.ruber(whitevariety)andG.sacculifer(Fig.1.6).Afundamentalissueinsettingup
theforaminiferalmodelisthefoodrequirementforthedifferentspecies.Inaddition,
itisalsoimportanttoknowifaspecieshasalgalsymbionts.Physico-chemicalprop-
ertiesofthewaterarealsoimportantininfluencingforaminiferaldistribution,in
particularSST.Basedonclimatologicaldataandthespecificecologicalpreferences
ofthedifferentspecies,themodelpredictsmonthlyconcentrationsforeachspecies.
Boththeecosystemandforaminiferamodelareforcedwithphysicalandchemical
boundaryconditions.TheforcingincludesSST,solarradiation,mixed-layerdepth,
verticalvelocityandtheturbulentexchangerateatthebaseofthemixed-layer,sea-
icecoverageandatmosphericironflux.Ateachtimestep,thephytoplanktonand
zooplanktonconcentrationpredictedbytheecosystemmodelareusedbythefora-
miniferamodelasfoodavailability.Informationontemperaturesensitivity(opti-
mumtemperatureandtolerancerange)ofplanktonicforaminiferaisavailablefrom
aglobalsetofmooredsedimenttrapsfromthemainoceanicprovinces(˘Zaric´etal.,

14

Figure1.6:

GlobalModelStructure1.

oductionIntr

1.4.objectivesScientific

15

2005).Usingthisnonlineardynamicmodel,monthlyconcentrationsoftheprevi-
ouslymentionedspecieshavebeenpredictedonaglobalscale.Sediment-trapdata
hastheprbeenedictedusedtodistributioncalibratethewithmodelobservationalwithrespectdata.toThetemperaturspatiale,anddistributiontoofvalidatethe
1998;speciesPrellhasetbeenal.,1999).comparTheedtomodelcore-topsetup,dataequations(Pflaumannandetpral.,edicted1996;Martinezdistributionsetaral.,e
describedindetailinthefirstpaper(chapter1).Additionally,plankton-netsamples
frlivingomthepopulationNorthinAtlanticthehaveupperbeenwateranalyzedcolumnto(chaptercompar5).ethemodeloutputwiththe

Severalsensitivityexperimentshavebeencarriedouttostudytheresponseof
planktonicforaminiferatochangingenvironments(chapter3).Intheseexperi-
ments,wevariedtheboundaryconditionsoftemperature(decreasingSSTglobally
orincreasingtheamplitudeoftemperatureseasonality)andlookedattheresponse
offoraminiferatodifferentenvironmentalconditions.Temperatureestimatesde-
rivedusingaspecies-specificmethodologyarestronglyinfluencedbytheseasonal-
ityoftemperature-sensitivespecies.Weassessedtheimplicationsthatchangesin
foraminiferalseasonalitymayhaveintherecordedtemperaturesignalundervary-
conditions.boundarying

Chapter4presentsmodelresultsforthedistributionofplanktonicforaminifera
duringtheLGM.Themodeledspatialdistributionpatternsofthespecieshavebeen
comparedtoGLAMAPandMARGOdatasets(Pflaumannetal.,2003;Barrowsand
Juggins,2004;Kuceraetal.,2004a,b;Niebleretal.,2004;Kuceraetal.,2005).Thesea-
sonaldistributionofthespeciesduringtheLGMhasbeencomparedtopresentday
conditions.Thisstudyaimstodetectshiftsinforaminiferalseasonalitybetween
glacial-interglacialperiods,andtoquantifythisseasonalbiasduetointerspecies
differencesinseasonality.Thepresentedstudysuggeststhatforaminiferalseason-
alityhasvariedfromLGMtopresentdayconditions.Thesevariationshavetobe
takenintoaccountinordertoimprovetheaccuracyofglacialSSTreconstructions.A
globalassessmentofthepotentialbiasofforaminifera-basedtemperatureestimates
duetochangesinseasonalityatglacial-interglacialtimescalesisnowpossible.

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2002.539–542,30,,GeologyKucera,M.,Weinelt,M.,Kiefer,T.,Pflaumann,U.,Hayes,A.,Weinelt,M.,Chen,
M.T.,Mix,A.C,Barrows,T.,Cortijo,E.,Duprat,J.,Juggins,S.,Waelbroeck,C.:
CompilationofplankticForaminiferacensusdata,LGMandSSTsfromthePacific
doi:10.1594/POcean,2004.ANGAEA.227329,Kucera,M.,Weinelt,M.,Kiefer,T.,Pflaumann,U.,Hayes,A.,Weinelt,M.,Chen,
M.T.,Mix,A.C,Barrows,T.,Cortijo,E.,Duprat,J.,Juggins,S.,Waelbroeck,C.:
CompilationofplankticForaminiferacensusdata,LGMandSSTsfromthePacific
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Publishedplanktonicas:Fraile,foraminiferaI.,Schulz,usingaM.,dynamicMulitza,S.ecosystemandKucera,model.M.,2008.Biogeosciences,Predicting5,the891–911.globaldistributionof

2Chapter

thePredictingusingglobaladynamicdistributionofecosystemplanktonicmodelforaminifera

AbstractWepresentanewplanktonicforaminiferamodeldevelopedfortheglobaloceanmixed-
layer.Themainpurposeofthemodelistoexploretheresponseofplanktonicforaminifera
todifferentboundaryconditionsinthegeologicalpast,andtoquantifytheseasonalbias
inforaminifera-basedpaleoceanographicproxyrecords.
Thismodelisforcedwithhydrographicdataandwithbiologicalinformationtakenfrom
anecosystemmodeltopredictmonthlyconcentrationsofthemostcommonplanktonic
foraminiferaspeciesusedinpaleoceanography:N.pachyderma(sinistralanddextral
varieties),G.bulloides,G.ruber(whitevariety)andG.sacculifer.Thesensitivityof
eachspecieswithrespecttotemperature(optimaltemperatureandrangeoftolerance)is
derivedfromprevioussediment-trapstudies.
Overall,thespatialdistributionpatternsofmostofthespeciesareinagreementwith
core-topdata.N.pachyderma(sin.)islimitedtopolarregions,N.pachyderma(dex.)
andG.bulloidesarethemostcommonspeciesinhighproductivityzones,whileG.ruber
andG.sacculiferaremoreabundantintropicalandsubtropicaloligotrophicwaters.
ForN.pachyderma(sin)andN.pachyderma(dex.),theseasonofmaximumproduction
coincideswiththatobservedinsediment-traprecords.Modelandsediment-trapdata
forG.ruberandG.sacculifershow,ingeneral,lowerconcentrationsandlessseasonal
sites.allatvariabilityAsensitivityexperimentsuggestthat,withinthetemperature-tolerancerangeofaspecies,
foodavailabilitymaybethemainparametercontrollingitsabundance.

Introduction2.1lanktonicforaminiferaarewidelyusedforpaleoceanographicreconstructions.
PThespatialdistributionofplanktonicforaminiferaspeciesiscontrolledbyphys-
iologicalrequirements,feedingpreferencesandtemperature(e.g.,Be´andHamilton,

26

2.Adynamicglobalmodelforplanktonicforaminifera

1967;Be´andTolderlund,1971).Shellsofplanktonicforaminiferaextractedfromma-
rinesedimentsserveasanarchiveofchemicalandphysicalsignalsthatcanbeused
toquantifypastenvironmentalconditions,suchastemperature(e.g.,Pflaumannet
al.,1996;Malmgrenetal.,2001),oceanstratification(e.g.,Mulitzaetal.,1997),atmo-
sphericCO2concentration(PearsonandPalmer,2000)andbiologicalproductivity
(Kiefer,1998).Pastsea-surfacetemperaturescanbeestimatedbyeitherquantifying
differencesbetweenmodernandfossilspeciesassemblages(e.g.,CLIMAP,1976;
Pflaumannetal.,1996;Malmgrenetal.,2001),orbyanalyzingtheisotopicortrace-
elementcompositionofthecalciteintheshell(e.g.,RohlingandCooke,1999;Lea,
1999).Ingeneral,allestimationproceduresarebasedonacorrelationbetweenmod-
ernenvironmentalconditionandassemblagecompositionorshellchemistry.
Seasonalchangesinthefluxofplanktonicforaminiferaarestronglyinfluenced
byenvironmentalfactors,suchassea-surfacetemperature,thestratificationofthe
watercolumn,andfoodsupply(e.g.,Bijmaetal.,1990;Ortizetal.,1995;Watkins
etal.,1996;WatkinsandMix,1998;Eguchietal.,1999;Schnack-Schieletal.,2001;
KingandHoward,2003a;Moreyetal.,2005;˘Zaric´etal.,2005).Theseasonalityoffo-
raminiferalproductionisanimportantfactorwhichhastobetakenintoaccountin
paleoceanographicinterpretations(e.g.,DeuserandRoss,1989;Wefer,1989;Mulitza
etal.,1998;GanssenandKroon,2000;KingandHoward,2001;Pflaumannetal.,
2003;Waelbroecketal.,2005).Anychangeinthetimingoftheseasonalmaximum
offoraminiferalfluxmayleadtoabiasinestimatedpaleotemperature.Mulitza
etal.(1998)haveshownhowtemperaturesensitivitycanaltertheproxyrecordin
thesediment.Moreover,thisdifferencesinseasonalitymakereconstructedtem-
peraturesbasedonplanktonicforaminiferaassemblagesdifficulttocomparewith
thosederivedbyothersea-surfacetemperatureproxies.Forexample,Niebleret
al.(2003)suggestedthatdiscrepanciesbetweentemperaturereconstructionsbased
onforaminiferaandalkenonesmightbeduetodifferentecologicalandthussea-
sonalpreferencesofalkenoneproducingalgaeandplanktonicforaminifera.Climate
changecouldinducevariationsintheseasonalsuccessionoftheplanktonicforami-
niferaandsuchvariationsneedtobequantifiedtocorrectlyinterpretcorresponding
uctions.econstrroxy-basedprTostudytheseasonalvariationsofplanktonicforaminiferaspecieswehavede-
velopedanumericalmodelforplanktonicforaminiferaataspecieslevel.Previ-
ously,˘Zaric´etal.(2006)developedanstatisticalmodelbasedonhydrographicand
productivitydata.Incontrasttothemodelof˘Zaric´etal.(2006),wepresentady-
namicmodelwhich,consideringecologicalprocesses,calculatesthegrowthrateof
theforaminiferapopulationbetweensuccessivetimesteps.Thisstudyshowsmodel
predictionsforspatialandtemporaldistributionpatternsofthefivemostimportant
modernplanktonicforaminiferausedasSSTproxies.

setupModel2.2.

27

setupModel2.2Thegeographicaldistributionandpopulationdensityofeachplanktonicforamini-
feraspeciesdependonbiotic(e.g.,food,symbionts)andabioticfactors(e.g.,light,
temperature).Tosupplytheforaminiferamodelwithecologicalinformation,we
runtheforaminiferamodulewithinanecosystemmodel.

modelEcosystem2.2.1Theemployedmarineecosystemmodel(Mooreetal.,2002)isconfiguredforthe
globalmixed-layeroftheocean.Itpredictsthedistributionofzooplankton,di-
atoms,diazotrophsandagenericgroupofphytoplankton(so-called’smallphyto-
plankton’).Themodelconsiderssinkingandnon-sinkingdetritalpools,andcarries
nitrate,ammonium,phosphate,ironandsilicateasnutrients.
Theecosystemmodelisdrivenbyhydrographicdatathatarederivedfroma
generaloceancirculationmodelandfromclimatologies.Theforcingdatainclude
localprocessesofturbulentmixing,verticalvelocityatthebaseofthemixedlayer,
andseasonalmixed-layerentrainment/detrainment.Horizontaladvectionisnot
included;thus,thereisnolateralexchangebetweengridpoints.Sinceourmain
interestistheecosysteminthemixedlayer,processesbelowthesurfacelayerare
ed.ignorPreviously,thistwo-dimensionalmodelhasbeenvalidatedagainstadiverseset
offieldobservationsfromseveralJGOFS(JointGlobalOceanFluxStudy)andhistor-
icaltimeserieslocations(Mooreetal.,2002),satelliteobservations,andglobalnu-
trientclimatologies(Mooreetal.,2002b).Thefulllistofmodelterms,parametriza-
tions,resolution,equationsandbehaviorintheglobaldomainisdescribedindetail
inMooreetal.(2002,b)andthecodeisavailableat
.eadme.htmle/arhttp://usjgofs.whoi.edu/mzweb/jkmoor

PLAFOM2.2.2Theplanktonicforaminiferamodeldeterminestheglobaldistributionofthefollow-
ing5species:Neogloboquadrinapachyderma(sinistralanddextralcoilingvarieties),
Globigerinabulloides,Globigerinoidesruber(whitevariety)andGlobigerinoidessaccu-
lifer.Thesespecieshaveoftenbeenconsideredtobesensitivetosea-surfacetem-
perature,andthereforetheirassemblagecanbeusedtoestimatepastsea-surface
temperaturesbymeansoftransferfunctions.
Eachspecieshasadifferentfoodpreference(Hemlebenetal.,1989;Watkinset
al.,1996;Schiebeletal.,1997;WatkinsandMix,1998;ArnoldandParker,1999).In
general,spinosespeciespreferanimalpreysuchascopepods(Spindleretal.,1984;

28

2.Adynamicglobalmodelforplanktonicforaminifera

CaronandB´e,1984;Hemlebenetal.,1989)whilenon-spinosespeciesarelargelyher-
bivorous(Andersonetal.,1979;Spindleretal.,1984;Hemlebenetal.,1985,1989),
althoughinsomespecimensmuscletissuehasbeenfoundinfoodvacuoles(Ander-
sonetal.,1979;Hemlebenetal.,1989).Manyspeciesalsocontainalgalsymbionts
thatmayprovidenutrition(Caronetal.,1981;Gastrich,1987;Ortizetal.,1995).On
aseasonalscale,itisgenerallyassumedthatfoodisthepredominantfactoraffect-
ingthedistributionofplanktonicforaminiferaunderfavorabletemperatures(Ortiz
etal.,1995).Planktonicforaminiferaappeartorespondtotheredistributionofnu-
trientsandphytoplanktonveryquickly,increasinginnumberofindividualswithin
severaldays(Schiebeletal.,1995).Informationaboutfoodavailabilityisobtained
fromtheecosystemmodel.Inthemodel,thefoodsourcesmaybeeitherzooplank-
ton,smallphytoplankton,diatomsororganicdetritus.
Forcompatibilitywiththeecosystemmodel,theforaminiferamodelcalculates
foraminiferalabundanceofeachspeciesviacarbonbiomass,thesameastheecosys-
temmodel.Sinceourstudyisdirectedtopaleotemperaturereconstructions,our
maininterestisinspeciesrelativeabundancesratherthaninassessingtheabsolute
biomass.Accordingly,foreachspeciesthechangeinforaminiferaconcentrationiscalcu-
follows:aslateddF=(GGE·TG)−ML(2.1)
dtwhereFistheforaminiferacarbonconcentration,andGGE(grossgrowtheffi-
ciency)istheportionofgrazedmatterthatisincorporatedintoforaminiferabiomass,
whichweassumetobeconstantregardlessofthefoodsource.TGandMLrepre-
senttotalgrazingandmassloss,respectively.

)TG(GrowthThegrowthratesaredeterminedbyavailablefoodusingamodifiedformofMichaelis-
2.2),(Eq.kineticsMenton4Cn
TG=n=1pn·Gmaxn·α·F·(Cn+g)(2.2)
whereGmaxisthemaximumgrazingrate,gisthehalfsaturationconstantfor
grazing,αistherelativeefficiencyforgrazinginrelationtotemperature(calibrated
fromrelativeabundances),Cnrepresentstheconcentrationofeachtypeoffood(di-
atoms(D),smallphytoplankton(SP),zooplankton(Z)ordetritus(DR)),andpis
thepreferenceforthisfood(assumedtobeinvariantintime).Thevaluesandunits

setupModel2.2.

29

ofallparametersaresummarizedinTable2.1.Foodrequirementsvaryforthediffer-
entforaminiferaspecies.Manyspeciesofplanktonicforaminiferaconsumeawide
varietyofzooplanktonandphytoplanktonprey,andtheyarecapableofareason-
ablyflexibleadaptationtovaryingtrophicregimes.ThefoodofN.pachyderma(sinis-
tralanddextralvarieties)consistalmostexclusivelyphytoplankton,commonlydi-
atoms(Hemlebenetal.,1989).G.bulloidespresentsbiologicalcharacteristicsthat
placeitontheborderbetweenspinoseandnon-spinosespecies;whilemostspinose
speciescarryalgalsymbionts,G.bulloidesdoesnot(Gastrich,1987;Hemlebenetal.,
1989;Schiebeletal.,1997).Itisabundantinperiodsofhighphytoplanktonpro-
ductivity(PrellandCurry,1981;ReynoldsandThunell,1985;Hemlebenetal.,1989)
andfeedsonalgalprey(Leeetal.,1966).G.bulloidesiscommoninmid-latitude
andsubpolarwaters,butitisalsopresentinthesubtropicalwatersoftheIndian
Ocean.Itisgenerallymoreabundantineutrophicwaterswithhighphytoplankton
productivityandforthisreasonitiscommonlyusedasaproductivityproxy(Hem-
lebenetal.,1989;SautterandThunell,1989;Ortizetal.,1995;GupthaandMohan,
1996;WatkinsandMix,1998).G.ruberexhibitstwovarieties;apinkandawhite
form.ThepinkvarietyislimitedtotheAtlanticOcean,andwehavethereforeonly
modeledthewhitevariety.G.ruber(white)isaspinosespeciesgenerallyfound
intropicaltosubtropicalwatermasses.Ithostsdinoflagellateendosymbionts,and
feedsmostlyonzooplankton,althoughithaslowerzooplanktondependencethan
otherspinosespecies(Hemlebenetal.,1989).Thecharacteristicsofbearingspines,
utilizationofzooplanktonpreyandsymbioticassociationaretypicalofforamini-
feraadaptedtooligotrophicwaters.G.sacculiferisalsoaspinosespecieshosting
dinoflagellateendosymbionts.CultureexperimentswithG.sacculiferconfirmthat
itdependsonzooplanktonfood(Be´etal.,1981).Itisalsoadaptedtolowproduc-
tivityareas,mainlythecentersoftheoceanicgyres.Watkinsetal.(1996)suggested
thattheadaptationtooligotrophicwatersispossiblebecausetheseforaminiferaob-
tainnutritionfromtheirsymbionts.However,theseasonalmaximumabundance
occurswhenproductivityintheseregionsismaximal.Toaccountforadaptation
tolowproductivityregions,welimitedthegrowthofG.ruberandG.sacculiferto
regionsinwhichmaximumnutrientandchlorophyllconcentrationdoesnotexceed
athresholdvalue.Thisisdonemultiplying”totalgrazing”(Eq.2.2)byahyperbolic
tangentfunctionwhich,usingmaximumnitrateandchlorophyllconcentrationas
input,identifieslowproductivityzones.
Maximumgrazingratefortheforaminifera(Gmax)varieswiththefoodsource.
Zooplanktoncarbonconcentrationisgenerallymuchlowerthanphytoplanktoncar-
bonconcentration.Forthisreason,whenzooplanktonisthefoodsourceGmax,is
sethigherthanifphytoplanktonordetritusarethefoodsource.Thus,undertypical
foodavailabilityconditions,carnivorespeciescangrowasfastasherbivorespecies.

30

2.Adynamicglobalmodelforplanktonicforaminifera

Basedontheobservationthatmostplanktonicforaminiferadistributionpatterns
arelatitudinalandcorrelatewithtemperature,weassumethattemperatureisthe
mostimportantphysicalparametercontrollingthedistributionofplanktonicfora-
minifera.ThisissupportedbytheexperimentalworkofBijmaetal.(1990),which
showedevidencefordirecttemperaturecontrolovervitalprocesses.Theseauthors
demonstratedthatacorrelationexistsbetweeninvitrotemperaturetolerancelimits
andtheknownnaturallimitsofthespeciesusedintheirexperiments.Thetoler-
ancelimitsofmostspeciesaremostlikelyprogressivesinceadeparturefromop-
timalgrowthconditionscausesagradualreductionofvitalprocesses(Arnoldand
Parker,1999).˘Zaric´etal.(2005,2006)compiledplanktonicforaminiferalfluxesfrom
sediment-trapobservationsacrosstheWorldOcean.Theyanalyzedspeciessensi-
tivitytotemperaturebyrelatingfluxesandrelativeabundancesofsevenspeciesto
sea-surfacetemperature.Basedonthiswork,weapproximatethetemperaturerela-
tionwithanormaldistribution.ThereforeeachspeciesexhibitsanoptimalSSTand
anSSTtolerancerange.Thegrowthrate(Eq.2.1)islimitedbytemperaturethrough
2.3).(Eq.αparameterthe(k1)
α=n·exp−0.5·(Ts−Topt)2(2.3)
σTherelationshipwithtemperatureassumesthattheforaminiferaconcentration
atanysiteisnormallydistributed,withanoptimumtemperaturewheretherelative
abundanceishighest.Awayfromthisoptimumtemperaturetherelativeabundance
decreasesuntilacriticaltemperaturebeyondwhichthespeciesdoesnotoccur.This
pattern,withacentralpeakandsymmetricaltails,canbeapproximatedbyGaussian
distribution(Eq.2.3).Thevalueofαvariesbetween0(outoflimitoftolerance)and
e).temperatur(optimal1Theparameternisaarbitraryparameterthatscalesthevaluesofαbetween0
and1.ToptandTsaretheoptimumandactualtemperatures,respectively,andσ
isthetolerancerangeofaspecies.Specieswithsmallσaremoresensitivetotem-
perature.ThevaluesofallparametersforeachspeciesaresummarizedinTable2.1.
Ofthefivespecies,G.ruber(white)andG.sacculifer(bothtropicalspecies),together
withN.pachyderma(sin.)exhibitthenarrowestSSTtolerancerange.N.pachyderma
(sin.)isabsentabove23.7◦C(˘Zaric´etal.,2005).N.pachyderma(sin.)isapolarspecies
andsurvivesevenwithinseaice(Antarctic),whereitfeedsondiatoms(Dieckman
etal.,1991;Spindler,1996).N.pachyderma(dex.)andG.bulloidesarepresentalmost
throughouttheentireoceanicSSTrange;however,N.pachyderma(dex.)exhibits
aclearpreferenceforintermediatetemperatures.ForG.bulloides,temperaturedoes
notseemtobeacontrollingfactor.Itisgenerallymoreabundantineutrophicwaters
withhighphytoplanktonproductivity,andforthisreasonitiscommonlyusedas

setupModel2.2.

31

a1995;productivityGupthaandproxyMohan,(Hemleben1996;Wetaal.,tkins1989;andMix,Sautter1998).andItThunell,hasthe1989;secondOrtizlaretgestal.,
temperaturetolerance,afterN.pachyderma(dex.),anddoesnotshowaunimodal
distributionwhenfluxisplottedversustemperature(˘Zaric´etal.,2005).G.bulloides
comprisesatleastsixdifferentgenetictypesandexhibitsapolymodaldistribution
pattern(Darlingetal.,1999,2000;Stewartetal.,2001;KuceraandDarling,2002;
Darlingetal.,2003).˘Zaric´etal.(2005)showedthatinthetropicalIndianOcean,
G.bulloidesispresentathighertemperaturesthanintheAtlanticandPacificOcean.
Inthisregion,highestabundancesofG.bulloidesoccuratSSTsatwhichAtlanticas
wellasPacificsamplesshowreducedfluxes.Sinceourstudyisappliedataglobal
scale,thetemperaturecalibrationisbasedonthepreferredtemperaturesofG.bulloi-
desinthePacificandAtlanticOcean.InEq.2.5wemodifiedthenormaldistribution
forN.pachyderma(dex.)andG.bulloidestoacceptwiderlimitsunderhighfood
availabilitythroughtheparameterk(seeTable2.1).

)ML(lossMassThemassloss(mortality)equationcomprisesofthreetermsrepresentinglossesdue
tonaturaldeathrate(respirationloss),predationbyhighertrophiclevelsandcom-
4–8).(Eqs.petition

with

ML=predation+deathrate+competition
predation=pl·exp−4000·1−1·(Fp)2
TTmksk

(2.4)(2.5)

Fp=max((F−0.01),0)(2.6)
deathrate=rl·Fp(2.7)
competition=Fp·clij·Fi·d(2.8)
Fi·d+0.1
Sinceourmodeldoesnotincludelateraladvection,aminimumthresholdis
neededtopreservetheforaminiferapopulationoverthewinterathighlatitudesor
duringperiodswithinsufficientfoodsupplyinregionswithhighseasonalvariabil-
ity.Wesettheminimumforaminiferabiomassat0.01mmolC/m3.Whenthepopu-
lationsreachthisminimumlevelthemortalitytermissettozero(Eq.2.6).Predators
specializedonplanktonicforaminiferaarenotknown,andtherefore,themortality

322.Adynamicglobalmodelforplanktonicforaminifera
Table2.1:Modelparameters.
SpeciesN.pachyderma(sin.)N.pachyderma(dex.)G.bulloidesG.ruber(white)G.sacculifer
σ4.06.06.04.04.0
Topt3.815.012.023.528
k11.2SP1.25D11
p(SP)0.30.20.150.00.0
p(D)0.70.80.450.20.1
p(Z)0.00.00.150.60.7
p(DR)0.00.00.250.20.2
p(SP)–0.40.2–0.0
p(D)–0.60.8–0.3
p(Z)–0.00.0–0.6
p(DR)–0.00.0–0.1
Gmax(SP,D,DR)1.081.081.081.081.08
Gmax(Z)2.162.162.162.162.16
g0.660.660.660.660.66
clN.pachyderma(sin.),j–0.2000
clN.pachyderma(dex.),j––0.110
clG.bulloides–0.5–11
clG.ruber(white),j–0.80.5–0.8
clG.sacculifer,j–00.50.8–
d–0.050.511
45514plrl0.060.060.060.060.06
GGE0.30.30.30.30.3
σ=standarddeviationof◦optimaltemperature
Topt=optimaltemperature(C)
k=parameterfortherangeontemperaturedependingonthefoodavailability
p(SP)=preferenceforgrazingonsmallphytoplankton
p(D)=preferenceforgrazingondiatoms
p(Z)=preferenceforgrazingonzooplankton
p(DR)=preferenceforgrazingondetritus
p=preferenceforgrazingwhenmainfoodsourceismissing
Gmax(SP)=maximumgrazingratewhengrazingonsmallphytoplankton(perday)
Gmax(D)=maximumgrazingratewhengrazingondiatoms(perday)
Gmax(Z)=maximumgrazingratewhengrazingonzooplankton(perday)
Gmax(DR)=maximumgrazingratewhengrazingondetritus(perday)
g=half-saturationconstantforgrazing
GGE=portionofgrazedmatterthatisincorporatedintoforaminiferabiomass(GrossGrowthEfficiency)
pl=quadraticmortalityratecoefficient
rl=respirationloss(perday)
clij=effectofcompetitionofthespeciesiuponthespeciesj
d=e-foldingconstant,whichcontrolsthesteepnessofthe
Michaelis-Mentonequationforcompetition3C=foodtype(SP,D,ZorDR)
SP=smallphytoplankton3[mmolC/m]
][mmolC/mdiatoms=DZ=zooplankton[mmolC/m3]
DR=detritus[mmolC/m3]

2.2.setupModel

33

equationdoesnotexplicitlydependuponpredatorabundance.Torepresentpre-
dation,wechooseaquadraticformwhichdependsonforaminiferalbiomassitself
(Eq.2.5).Thismaybeinterpretedeitheraspredationbyahighertrophiclevelnot
beingexplicitlymodeled(SteeleandHenderson,1992;EdwardsandYool,2000).
Theparameterplrepresentsthequadraticmortality-ratecoefficient,whichisused
toscalemasslosstograzing.Fromabioenergeticperspective,predationisalso
temperaturedependent.Foodconsumptionratestypicallyincreasewithincreas-
ingtemperature;thereforehighertrophiclevelswillexertmorepredationpressure
withincreasingtemperature(M.Peck,personalcommunication).Theparameterb
isusedtoscalethetemperaturefunctionbetween0and1.NotethatTskrepresents
theabsoluteSST,andthemaximumSST(Tmk)assumedinthemodelcorrespondsto
303.15K(30◦C).Deathratereferstonaturalphysiologicalbiomasslosses,including
respiration(Eq.2.7).Itisalineartermof6%perday(rl),thesamevalueusedby
Mooreetal.(2002)forzooplankton.
Thepresenceandactivityofonespeciesinfluencesnegativelytheresourceavail-
abilityforanotherspecies,leadingtotheassumptionthatcompetitionoccursbe-
tweendifferentspeciesofforaminiferainhabitingthesameregions(Eq.2.8).Inthis
equation,Fiistheconcentrationoftheforaminiferalspeciesexertingcompetition,
clijrepresentsthemaximumcompetitionpressureofthespeciesiuponthespecies
j(varyingfrom0to1)anddisthee-foldingconstant,whichcontrolsthesteepness
equation.Michaelis-Menton-typetheof

2.2.3Standardmodelexperiment:grid,forcingandboundarycon-
ditionsTheforaminiferamodelisrunwithintheecosystemmodelfortheglobalsurface
◦tweenocean,1–with2◦,awithlongitudinalhigherrresolutionesolutionnearof3.6the,aequator),varyingandalatitudinaltemporalrresolutionesolution(be-of
onemonth.Thiscorrespondstotheresolutionoftheunderlyingecosystemmodel
(Mooreetal.,2002,b).
WeusedthesameforcingasMooreetal.(2002).Mixed-layertemperaturesare
takenfromtheWorldOceanAtlas1998(Conkrightetal.,1998),surfaceshortwave
radiationfromtheISCCPcloud-cover-correcteddataset(BishopandRossow,1991;
RossowandSchiffer,1991)andclimatologicalmixed-layerdepthsfromMonterey
andLevitus(1997).Theminimummixed-layerdepthissetat25m.Thevertical
velocityatthebaseofmixedlayerisderivedfromtheNCAR-3Doceanmodel(Gent
aetal.,constant1998).valueTheof0.15turbulentm/day.exchangeSea-icerateatcoveragethebasewasoftheobtainedmixedfromlayertheissetEOSDISto
NSIDCsatellitedata(Cavalierietal.,1990).Atmosphericironfluxwasobtained

34

2.Adynamicglobalmodelforplanktonicforaminifera

Figure2.1:Locationsofthesediment-trapstationsusedtocomparemeasuredandmodeled
foraminiferalfluxes.SeeTable2.2fordetails.

fromthedustdepositionmodelstudyofTegenandFung(1994,1995).Moredetails
abouttheforcingcanbefoundinMooreetal.(2002).

Bottomboundaryconditionsarethesameasforthezooplanktoncomponent
oftheecosystemmodel.Forallforaminiferaspeciesweassumedauniformdis-
tributioninsidethemixedlayer,whereasbelowthemixedlayertheconcentration
wascalculatedasafunctionofthesurfaceconcentrationandthemixed-layerdepth.
Whenthemixed-layeristhin,theforaminiferalconcentrationbelowthemixed-layer
issetto75%ofthesurfaceconcentration.Withincreasingmixed-layerdepth,the
concentrationbelowdecreaseslinearly,untilreachingthevalue0atamixedlayer
depthof100m.Thisisarealisticlimit,asthemaximumproductionofthespecies
inquestionoccurswithinthisdepthrange(B´e,1977;Duplessyetal.,1981;Murray,
1991;WatkinsandMix,1998).

setupModel2.2.

35

datacore-toptoComparison2.2.4Sinceourmaininterestistounderstandthedistributionofplanktonicforamini-
feraatgeologicaltimescales,weusedtheBrownUniversityForaminiferalDatabase
(Prelletal.,1999)tocompareourmodelresultswithsedimentaryfaunalassem-
blages.Thisdatabasecontainscore-topplanktonicforaminiferacountsfrom1264
coresacrosstheworldocean.WeextendedthisdatabasewiththedatasetbyPflau-
mannetal.(1996),whichcontainsplanktonicforaminiferacountsfor738surface
sedimentsamplesfromtheNorthandSouthAtlantic;andwithanother57core-
topsamplesfromtheeasternIndianOcean(Martinezetal.,1998).Forcomparison,
therelativeabundanceswererecalculatedusingonlythefiveforaminiferaspecies
underconsideration.Additionally,thenumberofindividualswastransformedto
biomass(mgC/m3)totakeintoaccountthesizedifferencesofeachspecies.For
thistransformation,wecalculatedthevolumeoccupiedbythecytoplasmapproxi-
matingtheshapeofallthespeciestoasphereandassumingthatallthevolumeis
occupiedbythecytoplasm.Forthemeansizeofeachspeciesweusedsediment-trap
datafromPeetersetal.(1999).Weassumedthecarboncontentofthecytoplasmis
0.089pgC/μm3(Michaelsetal.,1995),thesameinallspecies.
Toassessthedeviationbetweenobservedandmodeledspeciesdistributions,we
calculatedtherootmeansquarederror(RMSE).Forthis,thedatafromeacheach
core-topsamplewascomparedtothenearestmodelgridpoint.Noaveragingwas
appliedtothecore-topdata.Thisisjustifiedbecausetheobservationaldatabaseis
identicalforallspeciesandourinterestisonlytotestmodelperformanceforthe
species.five

datasediment-traptoComparison2.2.5Severalsediment-trapstudieswereusedtocomparemeasuredandmodeledfora-
miniferalfluxes(Table2.2).Sedimenttrapsshowahightemporalresolutionand
rspeedecordofthefluxforaminiferalcontinuouslyshells(150over–1300severalm/daymonthsordependingyears.ontheirBecauseweightoftheandsinkingsize;
TakahashiandB´e,1984),thesediment-trapsamplesarenotsignificantlyaffectedby
dissolution,lateraladvectionorbioturbation,andthereforecanberelateddirectly
tomodernsurfacehydrography(e.g.,TedescoandThunell,2003;Marchantetal.,
2004;Mohiuddinetal.,2004;˘Zaric´etal.,2005).However,duetotheshortduration
ofthecollectingperiodsthosedatamayrepresentlocalprocessesofaparticular
yearratherthanalongtermmean.Weusedtheglobaldatabasecompiledby˘Zaric´
etal.(2005,2006).Thisdatabasecontainsplanktonicforaminiferalfluxescalculated
fromvarioussediment-trapinvestigationsacrosstheworldocean.Tocomparethe
modeledandobservedannualdistributionofthedifferentplanktonicforaminifera

36

2.Adynamicglobalmodelforplanktonicforaminifera

speciesweusedthosedatasetswithaminimumcollectingperiodofoneyearand
atleastmonthlyresolution.Weextendedthedatabaseof˘Zaric´etal.(2005,2006)
byaddingtrapdatafromthenorthwestPacific(OdaandYamasaki,2005;Xuetal.,
2005),BeringSea(AsahiandTakahashi,2007),SouthChinaSea(Tianetal.,2005)
andArabianSea(Schulzetal.,2002).Table2.2summarizeslocations,detailsand
referencesofthesediment-trapstudiesusedinthisstudy.Fig.2.1illustratesloca-
traps.sedimenttheoftionssediment-trapstudiesyieldfluxesbasedonindividualshells[ind.m−2day−1]
whereasthemodelprovidesconcentrations[mmolC/m3].Tocomparemodelout-
putwithobservations,weassumethatthefluxthroughthewatercolumnispropor-
tionaltothesurfaceconcentration.Theobjectiveofourstudyistodetectrelative
changesintheseasonaldistribution,ratherthantoassessforaminiferalbiomass.

2.2.6Sensitivityanalysisoftheparameters

Todeterminevaluesforbiologicalparametersisdifficultas,unlikemanychemical
orphysicalparameters,theycannotstrictlyberegardedasconstants.Thefreepa-
rametershavebeentunedbasedonecologicalknowledgeaboutdifferentspecies
offoraminifera.Inanattempttoassessthesensitivityofthemodeltothechosen
values,wedevelopedasensitivityanalysisoftheparameters.Theprocedureused
wassimilartoothermarineplanktonmodels(e.g.,Fashametal.,1990).Wekeptthe
parametersthatarecommontotheecosystemmodelconstant,andmodifiedonly
thevalueschosenfortheforaminiferamodule.Werunthemodelwitheachparam-
eteralteredbyhalfandtwicethestandardvaluerespectivelytodeterminewhich
parametershavethemosteffect(Table2.3).Incaseoftheparameterp(preference
forthefoodtype),wedecreasedthemainfoodsourcewasdecreasedby50%,shar-
ingthispartbetweentheotherfoodsources(scaledrelativetotheoriginalpinone
experiment,a;andsharingequallybetweentheotherfoodsourcesduringtheex-
perimentb).Totesttheeffectofcompetitonwecarriedoutthreeexperiments:first,
reducingexperiencedcompetitionby50%,asecondexperimentswithchingitoff
completelyandthelastexperimentincreasingcompetitionby50%.Forparameter
choice,wecomparedmodelledannualmeanrealtiveabundancesandcore-topdata.
ThesensitivitywasquantifiedbycalculatingthechangeofRMSEbetweensensitiv-
ityexperimentandstandardrun.Sensitivitiesofthespeciestoeachparameterare
2.3.ableTingiven

setupModel2.2.

37

Table2.2:Locations,trapandwaterdepths,sievesizeanddatasourcesoftheplanktonic
foraminiferafaunas(˘Zaric´etal.(2005)andadditionaldata).

TrapLocationLatitude[◦N]Longitude[◦E]Trapdepth[m]Waterdepth[m]Sievesize[μm]References
OceanStationPapa50.00−145.0038004240≥125ReynoldsandThunell(1985)
WSautterongetal.and(1999)Thunell(1989)
Peru-ChileCurrent−30.01−73.1823184345≥150Marchantetal.(1998)
(2000)al.etHebbelnN’NorthAtlantic69.6972.38−0.487.71500;1000500;1000;230032542624≥≥125125PeinertJensenet(1998)al.(2001)
CapeBlanc21.1520.76−−20.6819.74732;3552219541033646≥≥150150FischerFischeretandal.W(1996)efer(1996)
˘Zaric´etal.(2005)
W’equatorialAtlantic−−4.007.52−−25.5728.04631;652;1232;4991503153305570≥≥150150FischerFischerand(unpubl.Weferdata)(1996)
˘Zaric´etal.(2005)
WAtlantic−11.57−28.53719;45155472≥150Fischer(unpubl.data)
˘Zaric´etal.(2005)
WalvisRidge−20.059.16599;16482202≥150˘FischerandWefer(1996)
−20.138.9617172263≥150Zaric´etal.(2005)
WeddellSea−62.44−34.768633880≥125DonnerandWefer(1994)
−64.91−2.55256;44565032≥125
ArabianSea16.3360.491028;30264016≥150Curryetal.(1992)
14.4964.76733;29093901≥150GupthaandMohan(1996)
24.6515.4865.8168.741401;590277511663774≥≥125125HaakeSchulzetetal.al.(1993)(2002)
BayofBengal17.4589.60967;1498;20292263≥150GupthaandMohan(1996)
13.1584.35950;22863259≥150Gupthaetal.(1997)
NorthwestPacific25.00136.99917;1388;4336;47585107≥125Mohiuddinetal.(2002)
39.01147.001371;1586;47875339≥125
NW’NorthPacific43.9750.02155.05165.032957326053705570≥≥125125Kuroyanagietal.(2002)
40.00165.0029865483≥125
SubantarcticZone−−51.0046.76142.07141.741060;3850308045403780≥≥150150TrKingulletandal.Howar(2001)d(2003a,b)
−53.75141.76830;15802280≥150
ChatmanRise−42.70178.63300;10001500≥150KingandHoward(2003a,b)
−44.62178.62300;10001500≥150NodderandNorthcote(2001)
CariacoBasin10.50−64.672751400≥125TedescoandThunell(2003)
JapanTrench34.16141.981174;36808942≥125OdaandYamasaki(2005)
34.17141.971174;37008941≥125
RyukyuIslands27.38126.7310001627≥125Xuetal.(2005)
25.07127.5830003771≥125
BeringSea53.30N−17731983788≥125AsahiandTakahashi(2007)
49−17448125406≥125
SouthChinaSea14.60115.1112084270≥125Tianetal.(2005)

entCurru-ChilePerAtlanticNorthN’BlancCapeAtlanticequatorialW’AtlanticWRidgealvisWSeaeddellWSeaArabianBengalofBayPacificNorthwestPacificNorthNW’ZonecticSubantarRiseChatmanBasinCariacoenchrTJapanIslandsyukyuRSeaBeringSeaChinaSouth

30.01−72.3869.6920.7621.154.00−7.52−11.57−20.05−20.13−62.44−64.91−16.3314.4915.4824.6517.4513.1525.0039.0150.0243.9740.0046.76−51.00−53.75−42.70−44.62−10.5034.1634.1727.3825.0753.30N4914.60

73.18−7.71−0.4819.74−20.68−25.57−28.04−28.53−9.168.9634.76−2.55−60.4964.7668.7465.8189.6084.35136.99147.00165.03155.05165.00142.07141.74141.76178.63178.6264.67−141.98141.97126.73127.58177−174−115.11

2318500;1000;2300500;10002195732;3552652;1232;49915031631;4515719;599;16481717863256;445630261028;2909733;27751401;59020291498;967;2286950;917;1388;4336;475847871586;1371;3260295729861060;385030801580830;300;1000300;10002751174;36801174;370010003000319848121208

434526243254364641035330557054722202226338805032401639013774116622633259510753395570537054834540378022801500150014008942894116273771378854064270

150≥125≥125≥150≥150≥150≥150≥150≥150≥150≥125≥125≥150≥150≥125≥125≥150≥150≥125≥125≥125≥125≥125≥150≥150≥150≥150≥150≥125≥125≥125≥125≥125≥125≥125≥125≥

38

2.Adynamicglobalmodelforplanktonicforaminifera

Table2.3:Sensitivityanalysistotheparametervalues:Reductionofparametervaluesand
resultingchangeofRMSEbetweenthemodelandcore-toprelativeabundances(RMSEsen-
sitivityexperimentminusRMSEstandardrun)
ExperimentParameterchangeN.pachyderma(sin.)N.pachyderma(dex.)G.bulloidesG.ruber(white)G.sacculifer
1pmain(−50%)–0.34.6–2.9–4.70.6
2pmain(−50%)–0.34.6–2.9–4.70.6
3d(−50%)–4.0–0.2–1.9–0.7
4d(−100%)–4.60.86.41.9
5d(+50%)–3.4–0.5–5.30.7
6Gmax(−50%)2.93.6–1.9–5.6–0.5
7Gmax(+50%)–0.04.10.7–6.20.6
8σ(−50%)1.12.14.1–7.1–1.0
9σ(+50%)7.45.2–0.1–4.01.3

Experiments:1=Reductionofmainfoodpreference,p(SP,D,ZOorDR),by50%;sharingthispart
betweentheotherfoodsources(scaledinrelationtooriginalp)
2=Reductionofmainfoodpreference,p(SP,D,ZOorDR),by50%;sharingthispartequally
betweentheotherfoodsources
3=Reductionofexperiencedcompetitionby50%
4=Suppressionofcompetition
5=Increaseofexperiencedcompetitionby50%6=Decreaseofmaximumgrazingrate,Gmax
50%by7=Increaseofmaximumgrazingrate,Gmaxby50%
8=Decreaseoftemperaturetolerancerange,σby50%
9=Increaseoftemperaturetolerancerange,σby50%

Results2.3patternsdistributionSpatial2.3.1Modeledglobaldistributionpatternsofthefiveforaminiferaspeciesareshownto-
getherwiththecorrespondingcore-topdatainFigs.2.2–2.6.Themodelresultsare
expressedasrelativeabundancesasderivedfromthebiomassdata.Relativeabun-
dancesforcore-topdataconsideronlythefivespeciesincludedinthemodel.The
globaldistributionofN.pachyderma(sin.)showsthelowestRMSE,around9%,while
fortheremainingthespeciestheerrorvariesbetween22%and25%.
N.pachyderma(sin.)isacold-waterspecies,anddominatesplanktonicforamini-

Results2.3.

39

feralassemblagesinpolarwaters(Pflaumannetal.,1996;Bauchetal.,2003;Kucera
etal.,2005).PreviousworkhasshownthatitcansurvivewithinAntarcticseaice
(Dieckmanetal.,1991;Spindler,1996;Schnack-Schieletal.,2001).Itisusuallyused
asaproxyforcoldwaterconditions(Bauchetal.,1997).Core-top,aswellasmod-
eledassemblages,showthehighestrelativeabundances(upto100%)inpolarwa-
2.2).(Fig.tersN.pachyderma(dex.)istypicalofsubpolartotransitionalwatermasses.In
thesurfacesedimentsamples,N.pachyderma(dex.)showsaveryhighrelative
abundanceintheNorthAtlanticOcean,theBenguelaupwellingsystem,partsof
theSouthernOceanandintheequatorialupwellingofthePacificOcean.Itis
alsopresent,althoughatlowerabundance,intheupwellingsystemsoffnorthwest
Africa.ThemodeloutputshowsveryhighconcentrationsinthePeru-Chilecur-
rentandtheeasternboundaryupwellingsystems,aswellassouthofIceland,and
moderateabundancesatmidlatitudes(Fig.2.3).
LikeN.pachyderma(dex.),G.bulloidestypicallyoccursinsubpolarandtransi-
tionalwatermasses(Bradshaw,1959;TolderlundandB´e,1971;B´e,1977),andisalso
foundinupwellingareas(Duplessyetal.,1981;ThunellandHonjo,1984;Hemleben
etal.,1989).Temperaturedoesnotseemtobeacontrollingfactorinthedistribution
ofthisspecies,althoughtheexactrelationshipbetweenenvironmentalparameters
andgeographicaldistributionofG.bulloidesmaybemaskedbythefactthatthis
speciesgroupcomprisesseveraldistinctgenotypes(Darlingetal.,1999,2000;Stew-
artetal.,2001;KuceraandDarling,2002;Darlingetal.,2003).Generally,theabun-
danceofG.bulloidesisrelatedtohighproductivityareas(PrellandCurry,1981;B´eet
al.,1985;Hemlebenetal.,1989;Giraudeau,1993;WatkinsandMix,1998;˘Zaric´etal.,
2005).G.bulloidesshowsahighrelativeabundanceinthesurfacesedimentsamples
oftheNorthAtlanticOcean,theupwellingsystemsoffnorthwestandsouthwest
Africa,theSouthernOcean,thenorthernIndianOcean,andtoalesserextent,the
upwellingregionoffBajaCalifornia.Themodelresultsshowhighconcentrations
ofG.bulloidesinthesubpolarwatersofbothhemispheres,intheeasternbound-
arycurrentsofthesouthernhemisphereandinsomelocationsoftheArabianSea
2.4).(Fig.TheseafloorrecordshowshighrelativeabundanceofG.ruber(white)inthe
centralNorthandSouthAtlanticaswellastheSouthPacificandlesspronounced
relativeabundanceintheSouthIndianOceanupto40◦S.Themodeloutputshows
asimilarpatternwithhighrelativeabundancesintropicalandsubtropicalwaters
oftheAtlantic,PacificandIndianOceans,andverylowrelativeabundancesinup-
2.5).(Fig.easarwellingG.sacculifershowsaclearpreferenceforhightemperatures(optimumof28◦C)
andisabsent(orinconcentrations≤10%)below23◦C(˘Zaric´etal.,2005).Core-top

40

2.Adynamicglobalmodelforplanktonicforaminifera

Figure2.2:N.pachyderma(sin.)relativeabundances(%)fromcore-top(left)foraminiferal
assemblages(Pflaumannetal.,1996;Martinezetal.,1998;Prelletal.,1999)andmodeloutput
(right).Relativeabundancesconsideronlythespeciesincludedinthemodel.RMSEis9%.

Figure2.3:N.pachyderma(dex.)relativeabundances(%)fromcore-top(left)foraminiferal
assemblages(Pflaumannetal.,1996;Martinezetal.,1998;Prelletal.,1999)andmodeloutput
(right).Relativeabundancesconsideronlythespeciesincludedinthemodel.RMSEis22%.

datashowthisspeciesislimitedtotropicalwaters,reflectingitsnarrowtemperature
tolerance(Fig.2.6).Thehighestabundancesoccurinsurfacesedimentsfromthe
corequatoriale-topdataPacificfromandthecentralupwellingIndianregionOcean.oftheTherArabianelativeSeaabundanceis10%.inThemostofannualthe
meandistributionpatternofG.sacculiferinthemodelislimitedtotropicalwaters,
withabsencehighestorlowconcentrationsconcentrationsinthe(10%)inequatorialeasternPacific.upwellingThemodelsystemscorrasectlywellasinsimulatesthe
upwellingareaoftheArabianSea.

Results2.3.

41

Figure2.4:G.bulloidesrelativeabundances(%)fromcore-top(left)foraminiferalassemblages
(Pflaumannetal.,1996;Martinezetal.,1998;Prelletal.,1999)andmodeloutput(right).
Relativeabundancesconsideronlythespeciesincludedinthemodel.RMSEis25%.

Figure2.5:G.ruber(white)relativeabundances(%)fromcore-top(left)foraminiferalas-
semblages(Pflaumannetal.,1996;Martinezetal.,1998;Prelletal.,1999)andmodeloutput
(right).Relativeabundancesconsideronlythespeciesincludedinthemodel.RMSEis25%.

patternsdistributionemporalT2.3.2Weusedseveralsediment-trapdatasetstoassessthemodeledseasonalvariations
inforaminiferaabundance.Welimitthefollowingcomparisonbetweenthemodel
outputandthesediment-trapdatatoafewexamples(Figs.2.7–2.11).
Inmostofthecases,thesediment-trapdataexhibitverypronouncedinterannual
averages),variability.Iandniscontrast,therefortheeunablemodeltoisrforeprcedoducewithinterannualclimatologicalvariabilitydata.(i.e.,Forthatlong-termrea-

42

2.Adynamicglobalmodelforplanktonicforaminifera

Figure2.6:G.sacculiferrelativeabundances(%)fromcore-top(left)foraminiferalassemblages
(Pflaumannetal.,1996;Martinezetal.,1998;Prelletal.,1999)andmodeloutput(right).
Relativeabundancesconsideronlythespeciesincludedinthemodel.RMSEis23%.

son,wefocusedontheseasonwithmaximumproduction.Inordertocompare
modeledandobservedtimeseries,wepickedtheseasonwhenmaximumforami-
niferalproductionoccurs(Table2.4).Whensediment-trapweredeployedformore
thanoneyearweconsideredtheseasoninwhichmostmaximaoccur.
InterannualvariabilityofN.pachyderma(sin.)inallthelocationsisveryhigh
(Fig.2.7),butthetimingofthesignalagreesbetweenobservedandpredicteddata.
ThefluxofN.pachyderma(dex.)increasesduringsummer(July-October)in
northernNorthAtlantic(Fig.2.8a).Theseasonalpatternofpredictedconcentrations
correspondswellwiththetraprecord.
Sediment-trapdatalocatedatSubantarcticZoneshowanincreaseoftheN.pa-
chyderma(dex.)populationduringthesummer(January-February).Inaccordance
withthesediment-trapdata,themodelresultsalsoshowthehighestconcentrations
2.8b).(Fig.summertheduringExamplesforG.bulloidesareshowninFig.2.9.
AtWalvisRidge,thesediment-trapdatarevealsastrongseasonality,wheremax-
imaoccursinfall(September-November)andinspring(May-June).Themodelsuc-
cessfullycapturesthisbimodalpattern,withthemainbloomoccurringinspring.
ThesecondexamplerepresentsastationnorthoftheKuroshiocurrentinthenorth-
westPacific(Fig.2.9b).Atthislocationthemodelpredictsasmallpeakduring
winter(December-January)andthemaximumduringearlysummer(May-June).
Thetime-seriesrecordalsopresentsthisbimodalpattern;nevertheless,modeland
sediment-trapshowbettercorrespondenceduringthesecondyear.
Ingeneral,G.ruber(white)show,lessvariabilityinthesediment-trapdata(Fig.2.10).

Results2.3.

(a)

43

(b)Figure2.7:ComparisonofmeasuredfluxesofN.pachyderma(sin.)insedimenttraps(orange
bars)vs.modeledabundances(bluelines).Notethedifferenceinunitsbetweensediment-
trapdata[ind.m−2day−1]andmodeloutput[mmolC/m3],whichdoesnothamperwiththe
assessmentoftheseasonofmaximumforaminiferalproduction.Greybarsindicategapsin
sediment-trapdata.(a)OceanStationPAPA,innorthwestPacific,50◦N145◦W(Reynolds
andThunell,1985;SautterandThunell,1989;Wongetal.,1999);(b)WeddellSea,64.91◦S
2.55◦W,intheSouthernOcean(DonnerandWefer,1994).

SeasonalvariationsinthefluxofG.ruber(white)offCapeBlanc,intheCanaryCur-
rent,areshownforaperiodoffouryears(Fig.2.10a).Thefirstthreeyearswerechar-
acterizedbyamaximuminG.ruberfluxduringfall(September-October).During
fallof1991,however,thepeakmostlikelyoccurredaftertheendofthesediment-
trapdeployment.Themodelpredictsalongerbloom(highconcentrationsfrom
JunetoDecember),butthemaximuminSeptembercoincideswithsediment-trap
data.Thedatarecordedbythesediment-traplocatedatthewesternequatorialAt-
lanticdoesnotshowaclearpattern(Fig.2.10b).Thefirstsamplingyearischarac-
terizedbyabimodalpattern,withhighfluxesintheaustralsummerandwinter,
whereasduringthesecondyearthewinterbloomwasmissing.Atthissite,the
modelpredictsaunimodalpatternwithhighestfluxesfromSeptembertoOctober.

44

2.Adynamicglobalmodelforplanktonicforaminifera

(a)

(b)Figure2.8:ComparisonofmeasuredfluxesofN.pachyderma(dex.)insedimenttraps(orange
bars)vs.modeledabundances(bluelines).Symbolsandlayoutofthegraphsarethesameas
inFig.2.7.(a)northernNorthAtlantic,69.69◦N0.48◦E(Jensen,1998);(b)SubantarcticZone,
46.76◦S142.07◦E(Trulletal.,2001;KingandHoward,2003a,b).

G.sacculifershowslowfluxesinallsediment-trapdatausedformodelvalida-
tion.Inmostofthesiteswheresedimenttrapsweredeployed,themodelpredicts
2.11).(Fig.concentrationslowveryWhenthemodelreachesthethresholdvaluesetfortheminimumpopulation
size(0.01mmolC/m3),thehydrographiccomponentofthemodelstartstodominate
overthepopulationdynamicitself.Therefore,inmostofthelocations,themodel
outputistoolowforcomparison.WepresentexamplesfromtheBayofBengaland
theArabianSea(Fig.2.11).Atbothsites,themodelpredictslittlevariabilityinthe
.sacculiferG.ofpopulation

Results2.3.

45

Table2.4:SeasonwithmaximumforaminiferalproductionateachsiteinFig.2.1.Emptycells
denoteifspeciesisabsenteitherinsediment-trapdataorthemodeloutput.
N.pachyderma(sin.)N.pachyderma(dex.)G.bulloidesG.ruber(white)G.sacculifer
TrapLocationModelsediment-trapModelsediment-trapModelsediment-trapModelsediment-trapModelsediment-trap
OceanStationPapaspringspringfallfallsummerspring----
Peru-ChileCurrent--fallspringspringsummer----
N’NorthAtlanticsummersummersummersummer------
CapeBlanc----winterspringfallfall--
W’equatorialAtlantic------springwinter/springfallfall/spring
WAtlantic------springwinterfallfall/winter
WalvisRidge--springspringspringfall/spring/winter----
WeddellSeasummersummer--------
ArabianSea----summersummer--fallsummer
BayofBengal------winterwintersummersummer
NorthwestPacific--fallsummerspringwinter/springspringsummer--
NW’NorthPacific--fallfallspringspring----
SubantarcticZonesummersummersummersummer------
ChatmanRise--summersummer------
CariacoBasin------springspring--
JapanTrench----springspringspringspring--
RyukyuIslands----springfall/winter----
BeringSeasummerfall--------
SouthChinaSea------winterwinter--

patterndistributionSpatio-temporal2.3.3WeanalyzedthemodelpredictionforthetemporalvariationofG.bulloidesinthe
NorthAtlantic.Fig.2.12showsthemodeloutputofG.bulloidesconcentrations
throughouttheyearintheNorthAtlantic.Themaximumconcentrationsoccur
around40◦Nduringspring(March-April)andaround60◦Nduringsummer(June-
July),followingthephytoplanktonbloominthemodel.

2.3.4Sensitivityexperiment:spatio-temporaldistributionpatterns
temperatureconstantwithWerantheforaminiferamodulewithaconstanttemperatureof12◦Ceverywhere
totestthesensitivityofG.bulloidestootherenvironmentalparameters(mainlyfood
availability).Thechosentemperaturecorrespondstotheoptimaltemperatureof

46

2.Adynamicglobalmodelforplanktonicforaminifera

(a)

(b)Figure2.9:ComparisonofmeasuredfluxesofG.bulloidesinsedimenttraps(orangebars)
vs.modeledabundances(bluelines).Symbolsandlayoutofthegraphsarethesameasin
Fig.2.7.(a)WalvisRidge,20.05◦S9.16◦E(FischerandWefer,1996;˘Zaric´etal.,2005);(b)
northwestPacific,39.01◦N147.00◦E(Mohiuddinetal.,2002).

thisspeciesinthemodel.Fig.2.13showsthespatio-temporaldistributionofG.bu-
lloidesintheNorthAtlanticforthisexperimentalrun.Ingeneral,absoluteconcen-
trationsofG.bulloidesarehigherthaninthestandardrun(Fig.2.12).However,sea-
sonalpatterndoesnotchangesubstantiallyfromthestandardrun:Duringspring
themodelpredictsthehighestconcentrationsinthesouthernregion(around40◦)
whileduringsummer,thebloomshiftstohigherlatitudes.

Discussion2.4.

(a)

47

(b)Figure2.10:ComparisonofmeasuredfluxesofG.ruber(white)insediment-traps(orange
bars)vs.modeledabundances(bluelines).Symbolsandlayoutofthegraphsarethesame
asinFig.2.7.(a)CapeBlanc,21.15◦N20.69◦W(FischerandWefer,1996;Fischeretal.,1996;
˘Zaric´etal.,2005);(b)westernequatorialAtlantic,7.51◦S28.03◦W(FischerandWefer,1996;
Fischeretal.,1996;˘Zaric´etal.,2005).

Discussion2.4

datacore-topwithComparison2.4.1

Inmodelgeneral,aretheverycloseglobaltothosedistributionexpectedpatternsfromofcore-topforaminiferadata.speciespredictedbythe
ourThemodelcorre-topeflectsdatathereflectsituationtheintheintegratedmixedfluxlayerthr.Asoughatheconsequence,watercolumn,someofwhilethe

48

2.Adynamicglobalmodelforplanktonicforaminifera

(a)Figure2.11:ComparisonofmeasuredfluxesofG.sacculiferinsediment-traps(orangebars)
vs.modeledabundances(bluelines).Symbolsandlayoutofthegraphsarethesameasin
Fig.2.7.(a)centralBayofBengal,13.15◦N89.35◦E(Gupthaetal.,1997).

discrepanciesbetweenmodelandcore-topdistributionscouldbeduetothediffer-
entdepthhabitatsofthespecies.However,thefivespeciessimulatedinourmodel
liveformostoftheirlifecycleintheupperpartofthewater-column,thusweex-
pectonlyasmallerrorataglobalscale.Inaddition,fossilfaunalassemblagesmay
bealteredbyselectivedissolution(Berger,1968;ThunellandHonjo,1981;Leand
Thunell,1996;DittertandHenrich,1999),andbydisplacementthroughsubsurface
currentsorbioturbationprocesses(B´e,1977;Be´andHutson,1977;Boltovskoy,1994).
Sincewecannottakeintoaccountanyofthesefactors,theseprocessesmayexplain
someofthediscrepanciesbetweencore-topdataandthemodelresults.
TheglobaldistributionpatternofN.pachyderma(sin.)isverysimilartothat
inthecore-topdata(Fig.2.2).DistinctN.pachyderma(sin.)genotypeswereiden-
tifiedbyDarlingetal.(2004)intheArcticandAntarcticpolar/subpolarwaters.
Thosecrypticspeciesseemtohavedifferentenvironmentalpreferences(Bauchet
al.,2003).Accordingly,thetemperaturetoleranceofthepopulationsinthesouthern
hemisphereislargerthanthatofNorthAtlanticpopulation(Darlingetal.,2006).
Forthecalibrationwedidnottakedifferentgenotypesintoaccount.Thiscausesa
discrepancyattheedgeofthedistributionintheNorthAtlantic,wherethetemper-
aturetolerancerangeisnarrower.Infact,themodeloutputagreesslightlybetter
withthecore-topdataintheSouthernOcean,wheretheRootMeanSquareErroris
8.7%comparedto9.3%inthenorthernhemisphere.Thisresultreflectsthefactthat
ourparametrizationismainlybasedonthetemperaturetoleranceofthesouthern
population.However,thedifferencebetweenhemispheresisnotlarge,andtreating
thedifferentgenotypesofN.pachyderma(sin.)asasingleecologicalgroupinthe

Discussion2.4.

49

justified.seemsmodelForN.pachyderma(dex.)themodelwasabletopredictthehighrelativeabun-
dances(upto90%)foundincore-topdatafromtheeasternequatorialPacificand
Benguelaupwellingsystems(Fig.2.3).Incontrast,intheupwellingsystemoffNW
Africa,themodelpredictstoohighrelativeabundancesofN.pachyderma(dex.),
whilethoseinNorthAtlantic(40◦-70◦N)wereunderestimated.Anoticeabledis-
crepancyarisesintheequatorialPacific,northoftheeasternboundaryupwelling
region,wherethemodelunderestimatestherelativeabundanceofN.pachyderma
(dex.).Inthisregion,thesurfacetemperatureinthemodelishigherthanthattyp-
icalforN.pachyderma(dex.)(minimumtemperaturesabove22◦C).Itistherefore
possiblethatN.pachyderma(dex.)fromthesecore-topsrepresentapopulationliv-
ingbelowthemixedlayer,ashasbeendescribedinpreviousstudies(Murray,1991;
PujolandGrazzini,1995;KuroyanagiandKawahata,2004),orthattheyareexpatri-
atedspecimensfromtheupwellingregion.
Themodel-generatedglobalpatternofG.bulloidesfortheAtlantic,Pacificand
SouthernOceansagreeswellwithcore-topdata(Fig.2.4).Themodel,however,
underestimatestheabundanceofG.bulloidesinthenorthernIndianOcean.This
underestimationcouldbeduetothedifferentG.bulloidesgenotypes.Thetwowarm
watertypesarefoundmainlyintropical/subtropicalregions,whereascoldwater
typesarefoundintransitionaltosubpolarwaters(KuceraandDarling,2002).˘Zaric´
etal.(2005)studiedthesensitivityofseveralplanktonicforaminiferaspeciestosea-
surfacetemperatureandconcludedthatthepopulationofG.bulloidespresentin
thetropicalIndianOceancomprisesmainlythewarm-watergenotype.Sincethe
parametrizationofthemodelisdoneataglobalscalewithoutspecificallyconsider-
ingthewarmwatertype,theincreasedrelativeabundanceofwarm-waterG.bulloi-
desinthetropicalIndianOceancannotbecapturedbythemodel.Thehighconcen-
trationssimulatedintheArabianSeaareduetoanunrealisticallyhighphytoplank-
tonconcentrationintheecosystemmodel.Inaddition,themodificationofthenor-
maldistributionbytheintroductionofthefood-dependentrelation(throughthepa-
rameterkinEq.2.3)allowsG.bulloidestogrowintropicalwaters.Themodelunder-
estimatesrelativeabundancesofG.bulloidesintheupwellingregionsoffnorthwest
Africa,Peru-ChileandBenguelaasaresultoftheoverestimationofN.pachyderma
(dex.)concentration.Thiscouldbeduetothehigherturnover-rateofG.bulloidesin
comparisontothatofN.pachyderma(dex.),whichisnotincludedinthismodel.
ThesimulatedglobaldistributionpatternofG.ruber(white)isingoodagree-
mentwiththecore-topdata.OnlyinthenorthernIndianOceanareabundances
somewhatoverestimated(Fig.2.5).ThismaybeduetotheunderestimationofG.bu-
lloidesinthemodelaswecomparerelativeabundances.
Bothcore-topdataandmodeloutputshowthatthedistributionofG.sacculifer

50

2.Adynamicglobalmodelforplanktonicforaminifera

islimitedtotropicalareas(Fig.2.6).Themodelfavorablycapturesthedistribution
patternsintheAtlanticandeasternPacificOceans.Thepredictedrelativeabun-
dancesofG.sacculiferintheIndianandwesternPacificOceansareunderestimated
inthemodel.Theobserveddistributionshowsawiderspatialrangethaninthe
model.ThiscouldbeduetocompetitionexertedbyG.ruber.Theabundanceof
thisspeciesisoverestimatedinthementionedregionsandthereforecompetitionis
exertingastrongerinfluenceontheotherspecies.

datasediment-trapwithComparison2.4.2Thecomparisonbetweenmodelpredictionsandsediment-traprecordsbearssev-
eraldifficulties.Mostoftimeseriesonlyrepresentshortsamplingperiods(single
orafewyears).Sedimenttrapsthatweredeployedformorethanoneyearshow
pronouncedinterannualvariabilitythatisnotcapturedbythemodelduetothecli-
matologicalforcing.Moreover,themajorityofsediment-trapshavebeendeployed
sionsclosetoarethemorecoastcomplex(Fig.2.1),thanwherinetheenviropenonmentalocean.Theconditionslackofandsediment-trapecologicaldatasucces-in
general,open-oceanthesettingsseasonalisanpatternoobstaclefspeciesforaglobalconcentrationsscaleinthecomparison.modelissimilarNevertheless,tothein
sediment-traprecords(Table2.4).
SimulatedvariationsofN.pachyderma(sin.)correlatewellwithsediment-trap
data.In80%ofthecases,thepreadictedseasonofmaximumproductioncoincides
withobservationaldata.InthemodelN.pachyderma(sin.)livesinpolar/subpolar
waters,andthemaximumproductionofthisspeciesoccursduringashortperiodin
summer,togetherwiththephytoplanktonbloom.ForN.pachyderma(dex.),thesea-
andsonofsediment-trapmaximumprdataoductioncoincidevariesinb75%etweenofthecaseslocations.(TableHowever2.4).,Formodeltheprstationsedictionin
Peru-ChilecurrentandnorthwestPacific,modelpredictionandsediment-trapdata
todifafersinglesubstantiallyyearand.theHoweverdata,inshowstheanformerirregularlocation,patternthewithoutsamplingaperioddistinctisseasonallimited
peak,whereasinthenorthwestPacifictheinterannualvariabilityinsediment-trap
dataisveryhigh.Itislikelythatattheseparticularlocationsthesedimenttrapsdo
notreflectthemeanlong-termfluxpattern.
Formostofthelocations,theseasonofmaximumproductionofG.bulloidessim-
ulatedbythemodeldoesnotcoincidewiththeobservations.AtOceanStation
PAPA(northeastPacific)themodeledseasonalpeaksaredelayedwithrespectto
occurssediment-traptooearly.data,AtthewherWeasalvisintheRidge,Percloseu-ChiletothecurrentcoastalandoffupwellingCapezone,Blanc,thethemodelpeak
predictssuccessfullythebimodalpattern(Fig.2.9a).However,whenconsidering

Discussion2.4.

51

theabsolutefluxmaximumineachyear,theseasonwhenitoccursvariesthrough-
outthesediment-traprecord.AtRyukyuIslands(northwestPacific)twosediment
trapsweredeployedduringthesameperiod,butmaximumproductionseasons
recordedinbothtrapsaredifferent.Thedifferencesobservedinthesediment-trap
datahighlightsdifficultiesincomparingmodelpredictionsandobservationaldata.
TheseasonofmaximumproductionofG.ruber(white)inthemodelcorresponds
totherecordeddatain6of8stations.However,inthewesternAtlantic,themodel
produceshighestconcentrationstooearlyintheyear(Table2.4).Ontheotherhand,
thevariationsinthesediment-trapdataareverysmallandseemtooccurrandomly.
OnlyveryfewdataareavailabletocompareseasonalvariationsofG.sacculifer.
Modelandsediment-trapdatashow,ingeneral,lowerconcentrationsthantheother
fourspeciesandlittleseasonalvariabilityinallsites.Thisisnotsurprisingconsid-
eringthatG.sacculiferislimitedtotropicalwaters,withsmallseasonaltemperature
range.

analysisSensitivity2.4.3Inanattempttoassessthesensitivityofthemodeltothechosenparametervalues,
weperformedasensitivityanalysisoftheparameters.Theprocedureusedwas
similarparameterstootherthataremarinecommonplanktontothemodelsecosystem(e.g.,modelFashametconstant,al.,and1990).Wmodifiedekeptonlythe
theeteraltervaluesedbychosenhalfforandthetwiceforaminiferathestandarmodule.dvalueWerruntheespectivelymodeltowithdetermineeachparam-which
parametershavethemosteffect(Table2.3).
ThesensitivitywasquantifiedbycalculatingthechangeofRMSEbetweenthe
sensitivityexperimentandthestandardrun.Theresults(Table2.3)indicatethat
benonemorofertheobustforparametersG.leadsacculifertothanuniformforotherchangesforspecies.allInspecies.severalThemodelexperiments,seemstheto
errorbetweenmodelandcore-topdatadecreases.Thisoccursbecausethestandard
parametrizationisbasedonecologicaldatacompiledfromliteratureratherthan
”tuned”toobtainabetterfit.Removingcompetitiongeneratesageneralincreaseof
RMSE.Notsurprisingly,thetemperaturetolerancerange(σ)seemstobethemost
.parametersensitive

2.4.4Modelexperimentwithconstantmixed-layertemperature
Whentheforaminiferamodelisrunwithaconstanttemperatureof12◦C,G.bulloi-
desintheNorthAtlanticstillshowedhighestconcentrationsatlowlatitudesduring
springandmaximumconcentrationsathigherlatitudesinJune,linkedtothesea-

52

2.Adynamicglobalmodelforplanktonicforaminifera

Figure2.12:ModeledmonthlyconcentrationsofG.bulloides
un.rddar

intheNorthAtlanticinthestan-sonalmigrationofthephytoplanktonbloom(Fig.2.13).Thisindicatesthattemper-
atureisnottheonlycontrollingfactor,butthatfoodsupplyplaysanimportantrole
inthetemporaldistributionpatternofthisspecies.Theexperimentconfirmsthe
resultsofGanssenandKroon(2000),whofromisotopicstudiesonNorthAtlantic
surfacesediments,concludedthatG.bulloidesreflectstemperaturesofanorthward
bloom.springmigrating

conclusionsandSummary2.5.

Figure2.13:Modeledmonthlyconcentrationsof
mixedlayertemperatureof12◦C.

bulloidesG.

2.5conclusionsandSummary

inanexperimentwith53

constantAglobalmodelhasbeendevelopedthatpredictsmonthlyplanktonicforaminifera
(white)concentrationsandG.forsacculiferN..Itipachydermasanonlinear(sin.),N.dynamicpachydermamodel(dex.),simulatingG.grbulloidesowth,G.rateruberof
foraminiferapopulationsusinginformationfromanunderlyingecosystemmodel

54

2.Adynamicglobalmodelforplanktonicforaminifera

(Mooreetal.,2002).
Themodelaimsatpredictingthedistributionofplanktonicforaminiferaatgeo-
logicaltimescales.Overall,theglobaldistributionpatternsofthepredictedspecies
aresimilartocore-topdata.
oftheModeledlocations,seasonalalthoughvariationstheoverallcomparisonagriseewithhamperedbysediment-trapinterannualrecordsforvariabilitymost
notcapturedbythemodel.
◦foodAavailabilitysensitivity(primaryexperimentprusingoductionainconstantthecaseoftemperaturG.eobulloidesf12)Cisanindicatesimportantthat
factorcontrollingthedistributionofsomespecies.
Ourmodelprovidesatoolthatwillcontributetobetterassessinghowchanging
environmentalconditionsinthegeologicalpastaffectedthedistributionofforami-
time.andspaceinniferaQuantitativedataandabetterknowledgeofecologicalprocessfromlaboratory
andmayfieldalsobestudiesimprarovedebyessentialincludingforfurtheradditionalimprovementinformation,ofthesuchcurrasentdiffermodel.entResultsclasses
ofzooplankton,orbyexplicitlyresolvingdepth.

AcknowledgmentsWeappreciatethecontributionsandhelpfulcommentsofR.Schiebel,
M.Peck,A.Beck,A.Bisset,and4refereeswhoimprovedthemanuscript.Thanks
alsotoM.PrangeandT.LaeppleforanalyticalassistanceandG.Fischerforprovid-
ingsediment-trapdata.SpecialthankstoA.Manschkeforcomputersupport.This
projectwassupportedbytheDFG(DeutscheForschungsgemeinschaft)aspartof
theEuropeanGraduateCollegue“ProxiesinEarthHistory”(EUROPROX).

Publishedplanktonicas:Fraile,foraminiferaI.,Schulz,usingaM.,dynamicMulitza,S.ecosystemandKucera,model.M.,2008.Biogeosciences,Predicting5,the891–911.globaldistributionof

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M.,

and

Mulitza,

ographyhydr

and

S.:

Global

oductivitypr

edictionpr

data,

of

BIBLIOGRAPHY

foraminiferalplanktic

Biogeosciences,

3,

187–207,

2006.

SubmittedtoMarineMicropaleontologyas:Fraile,I,Mulitza,S.andSchulz,M.–“Modelingplanktonic
foraminiferalseasonality:ImplicationsforSSTreconstructions”

3ChapterProxyForaminifera-basedinbiasSeasonalrecords

AbstractAglobalforaminiferalmodelwasusedtodeterminetheseasonalimprintofplanktonic
foraminiferaonthesedimentaryrecord.Themodelprovidesmonthlyconcentrationsof
fiveplanktonicforaminiferalspeciesusedinpaleoceanographicreconstructionsinclud-
ingN.pachyderma(sin.anddex.),G.bulloides,G.ruber(white)andG.sacculifer.The
temperatureimprintinforaminiferalshellsvariesaccordingtotheseasonofcalcification,
andthesedimentaryrecordsretainthisseasonalimprint.Proxyrecordsforaspecieswill
thereforebeweightedtowardsthevaluesduringtheseasonofmaximumproductionfor
thatspecies.Ourmodelpredictionrevealsthat,ingeneral,athighlatitudes,closeto
thegeographicallimitofoccurrenceofeachspecies,thesignalisbiasedtowardssum-
merconditions.Incontrast,atlowerlatitudesthesignalisbiasedtowardswinteror
annualmeanconditions.TemperaturesderivedfromG.ruber(white)andG.sacculifer
aremostsuitableforestimatingannualmeanSSTintropicalwaters,between20◦N/S,
whileG.ruber(white)whencollectedatmid-latitudes,nearto40◦latitude,reflects
conditions.summermainlyWecarriedoutsensitivityexperimentstostudytheresponseofplanktonicforaminiferal
seasonalitytochangesintemperature.Weforcedthemodeldecreasingthetemperature
globallyby2◦Cand6◦C.Inmostoftheregions,duetothecooling,theseasonofmax-
imumproductionshiftedtoawarmerseason.Thus,theforaminiferalpopulationasa
wholerecordedlittlechangeinthetemperature.Intropicalwaters,wheretemperature
seasonalityislow,foraminiferalpopulationrecordedtheentiretemperaturevariation.
Thesefindingshighlighttheimportanceofconsideringchangesinseasonalitythrough
time.

Introduction3.1lanktonicforaminiferaarethemostcommonsourceofpaleoceanographicprox-
Pies.Theirlonggeologicalhistory,goodpreservationinsedimentsandeasy
collectionmakeforaminiferaidealbio-indicatorsofmarineenvironmentalchanges
(e.g.,Barbierietal.,2006).Assemblagesoffossilplanktonicforaminifera,sizeand

68

3.SeasonalbiasinForaminifera-basedProxyrecords

isotopicratiosortrace-elementcompositionofforaminiferalcalciteareusedtoquan-
tifythesea-watertemperatureinwhichtheforaminiferagrew(e.g.,Schmidtetal.,
2004;RohlingandCooke,1999;Lea,1999).Theuseofplanktonicforaminiferaasa
basisforgeochemicalproxiesreliesupontheknowledgeoftheecologyofthesignal
carriers(e.g.,Rohlingetal.,2004).Sedimenttraps,planktontowsandlaboratory
cultureshavecontributedtotheunderstandingofplanktonicforaminiferalecol-
ogy,revealingthatforaminiferahavelargeseasonalvariationsinabundance,tied
closelytosurfacewaterhydrography(B´e,1960;Be´andTolderlund,1971;Deuseret
al.,1981;ThunellandReynolds,1987;SautterandThunell,1991).Becauseofthat,
therecordedtemperaturemayreflecttheintegrationofafluxpatternorashorttime
periodoftheyear(Mix,1987;Deuser,1987;Mulitzaetal.,1998).Thus,thetempera-
turesignaturefoundinthesedimentaryrecordliesbetweentheannualmeanwater
temperatureandthetemperaturepreferredbyaspecies.Sediment-trapstudieshave
shownthatdependingonspeciesandsamplinglocation,thatrecordedtemperature
signalcanbeassociatedtodifferentseasons.Forexample,Tedescoetal.(2007),
concludedthatintheCariacoBasinthesedimentδ18OrecordofG.ruber(pink)is
mostsuitableforestimatingpastvaluesofannualsea-surfacetemperature(SST),
whileG.bulloidesprovidesinformationonconditionsduringthespringupwelling.
G.ruber(white)isoftenconsideredtobeasummerspecies.However,Tianetal.
(2005)haveshownthatintheSouthChinaSeathehighestfluxofG.ruber(white)
occursduringwinter.Thedifferenceinisotopicsignaturebetweenspecieshasalso
beensuggestedasatoolfortheestimationofseasonality(DeuserandRoss,1989).
Niebleretal.(2003)pointedoutthatdiscrepanciesbetweentemperaturereconstruc-
tionsbasedonforaminiferaandalkenonesmightbeduetodifferentecologicaland
thusseasonalpreferencesofalkenoneproducingalgaeandplanktonicforaminifera.
Thegeographicaldistributionofaspeciesanditsabundancedependsonthe
physico-chemicalpropertiesofthewaterandthespecies-specificecologicaldemands
(e.g.,Be´andHamilton,1967;B´e,1977).Thefaunalbiogeographicalprovincesare
distributedalonglatitudinalzones,reflectingthestrongrelationshipbetweenSST
andspeciesabundances(e.g.,Murray,1897;Be´andTolderlund,1971;Bijmaetal.,
1990).Foraminiferamayrespondtoenvironmentalchangesintermsofreproduc-
tionrates,leadingtohighproductionofspecimensunderfavorableconditionsand
totheirdisappearanceunderstronglyunfavorableenvironmentalconditions(Bar-
bierietal.,2006;Kucera,2007).Theimprintofthisseasonalityispreservedinthe
sedimentaryrecord(Wefer,1989;GanssenandKroon,2000;KingandHoward,2005;
SchiebelandHemleben,2005).Theseasonalityofsomespeciesmaychangethrough
timeasclimatechanges,leadingtoabiasinestimatedpaleotemperature.Thisvari-
ationneedstobequantifiedinordertoreduceuncertaintiesofforaminifera-based
uctions.econstrrSST

3.2.MethodsandData

69

Inthisstudy,weusetheglobalplanktonicforaminiferalmodeltocomparethe
sensitivitytemperatureexperimentssignaturertoecortestdedtheinrfiveesponseofplanktonicplanktonicforaminiferaforaminiferaspecies.toWechangesconductin
.SST

MethodsandData3.2

modeltheofDescription3.2.1Tostudytheseasonalvariationsofplanktonicforaminiferaspeciesweusedady-
namicforaminiferalmodel(Fraileetal.,2008).Thismodelisforcedwithaglobal
hydrographicdataset(e.g.temperature,mixedlayerdepth)andwithbiologicalin-
formationtakenfromaecosystemmodel(Mooreetal.,2002)topredictthegrowth
rateoffiveforaminiferaspecies:N.pachyderma(sinistralanddextralvarieties),G.bu-
lloides,G.ruber(whitevariety)andG.sacculifer.Thesespeciesaremostlyfoundin
theeuphoticzone,andreflecttheseasurfaceenvironment(B´e,1982).Previously,
thismodelhasbeenvalidatedagainstadiversesetoffieldobservationsfromsev-
eralcore-topsandsedimenttraps.Thefulllistofmodelterms,parametrizations,
equationsandbehaviorintheglobaldomainisdescribedindetailinFraileetal.
(2008).

dataSediment-trap3.2.2Usingthemodelpredictionandinsituobservationsfromsedimenttrap,wecalcu-
latedthetheoreticalannualtemperaturesignalrecordedbythemeanpopulationof
aspecies(Tr).Weusedplanktonicforaminiferafluxdatafromaglobalsediment-
trapdataset(˘Zaric´etal.,2005)tocomparemodelresultswithobservationaldata.
Thedatasetcontainstimeseriesofplanktonicforaminiferalspeciesfluxfrom42dif-
fer69.69ent◦Nsites.0.48◦WWeandadded72.38two◦Nmor7.71e◦Wtime(Jensen,seriesfrom1998).theWenorthernonlyusedNorthsediment-trapAtlantic,at
dataexceededwithaoneyearminimum,thedatasamplingweresplitperiodtoofsingleoneyearsyear.andWhentheytheweresamplingusedasperiodinde-
pendenttime-seriesrecords.Trforsediment-trapdatawascalculatedusingSSTde-
rived(ReynoldsfromandtheSmith,Integrated1994),GlobalthesameOceanSSTasServices˘Zaric´etSystemal.Pr(2005)oductsfortheBulletinsediment-trap(IGOSS)
studies.Thelocationsandoriginaldatasourcesofthesedimenttrapsusedforthis
analysisarelistedinTable3.1.

70

3.SeasonalbiasinForaminifera-basedProxyrecords

Figure3.1:Difference
tem-dedecorrbetweenannualandeperatur(WOA98)SSTmean(Tr–Ta).Trisbased
concen-monthlytheonwithedictedprtrationsPLAFOM.(sin.),pachydermaN.(a)(dex.),pachydermaN.(b),bulloidesG.(c)(white),ruberG.(d).sacculiferG.(e)

Results3.3.

71

designExperimental3.2.3Wecarriedoutastandardandthreesensitivityexperimentstotesttheresponse
ofthefiveplanktonicforaminiferaspeciestochangesinSST:Inthestandardrun
weforcedthemodelwithclimatologicalSSTfromtheWorldOceanAtlasWOA98
(Conkrightetal.,1998).InthefirsttwosensitivityexperimentswedecreasedSST
globallyby2◦Cand6◦Crespectively.Inthethirdexperimentweraisedtheampli-
tudeoftemperatureseasonalityby25%,thatis,weincreasedsummertemperature
anddecreasedwintertemperature.Temperaturecanexertdirectinfluenceonfora-
minifera,orcanalsoentailchangesintheecosystemmodelandaffecttheforami-
niferaindirectly.Inordertodifferentiatebotheffects,theseimposedtemperature
changeshavebeenappliedseparatelytotheforaminiferaandecosystemmodels.

Results3.33.3.1Influenceofseasonalityandtemperaturesensitivityontem-
estimatesperatureForsignalboth,recordedobservationalbythemeanandmodeledpopulationdata,ofawespecies(calculatedTr),astheannualtemperature

(3.1)

12m=1(Cm×Tm)
CmTr=12(3.1)
=1mTmwherdenoteseCmSSTis.Atmonthlyeachsite,speciesTrrangesconcentrationbetween(orthefluxmeanforwatersediment-traptemperaturdata)eandand
meanpreferredtemperaturebythespecies(Mix,1987).Takingintoaccountmonthly
concentrationsofthespecies(modeledwithPLAFOM)andmonthlySSTfromthe
WOA98flux-weighted(Conkrightmeanetal.,temperatur1998),ewesignalestimatedfoundTinrthatsediments.correspondsInordertothetotheordetermineetical
theandefthefectrecorofdedseasonalitytemperatur,theedif(Tferr)isenceshownbetweeninFig.the3.1.annualPositivemeanvaluestemperaturindicatee(thatTa)
thespeciesliveduringthewarmseason,andtherefore,therecordedtemperature
isabovetheannualmean.Negativevaluesindicatethatthetemperaturesignalis
biasedtowardsthecoldseason.Dependingonthelatitudeoroceanicregion,the
samevariabilityspecies,acanstatisticalreflectdifsignificanceferentofseasonalthediffersignals.encesSincecannotthebemodelassessed.hasnointernal

72

:3.2Figure

modeland

ariationVof(right).edictionpr

Tr(right).

–TaPositive(right).

with3.SeasonalbiasinForaminifera-basedProxyrecords

latitudeomfrsediment-trapdata(left)(˘Zari´cetal.,2005)

andmodelprediction(right).Positivevalues:Trreflects”warm”conditions.Shadowing:Tr

coincideswithannualmeantemperaturewithin±1◦C.

coincideswithinetemperaturmeanannualwith

.

Results3.3.

73

Ourmodelsimulationindicatesthatthetemperaturedifferencesshowthatthe
summerflux-weightedtemperaturannualesathightemperatureslatitudes,derivedbutfrcanomalsoN.reflectpachydermatemperatur(sin.)corresofespondcolderto
G.seasonsbulloideswhenshowacollectedveryfrsimilaromlowerpattern:Atlatitudeshigh(Figlatitudes3.1).N.theyrecorpachydermadasummer(dex.)sig-and
◦warnal;dsarofound40◦40thelatitude,winterTrsignalisclosebecomestothemoreannualsignificant.meanFortemperaturbothe,andspecies,inequatorthe-
northernhemisphere,theeffectofseasonalityappearsmoreimportant.G.ruber,
intribution,general,arreoundcords40◦temperaturlatitude,eitsrecorclosedstothesummerannualtemperaturmean.Ates.theOurlimitmodelofritsesultsdis-
suggestthat◦theflux-weightedannualtemperaturesderivedfromG.sacculiferare
within±1CoftheannualmeanSST.
Forboth,modelandsediment-trapdata,theimprintofseasonalforaminiferal
productionvarieswithlatitude(Fig.3.2).
Forallspecies,exceptG.bulloides,thegeneraltrendshownbythesediment-trap
toisthethesame:annualatmeanlow(±1latitudes◦C),thewhileattemperaturhighelatitudessignalritecorisdedbiasedinthetowarshelldsissummerclose
es.temperaturAsimilarpatterncanbeobservedinthemodel-simulatedreconstructionsfor
mostofthespecies.OurmodelindicatesthatN.pachyderma(sin.)recordssummer
conditionsathighlatitudes(60◦–80◦N),butaround40◦Nitcanalsorecordwin-
tertemperatures.Bothsediment-trapdataandmodelsimulationsillustratethatthe
temperaturesignalderivedfr◦omN.pachyderma(dex.)isupto5–7◦Cabovethe
annualmeanbetween40–80latitude.Theflux-weightedannualtemperaturede-
rivedfromG.bulloidesdoesnotshowastrongchangerelatedtolatitude.Inthe
northernhemisphere,inparticular,itcanrecordtemperaturesaboveandbelowthe
Intrannualopicalmean.watersThe(20◦S–2latitudinal0◦N)efG.fectinruberthe(white)caseofrecorG.dsruberannualappearsmeanverySST,whileimportant:in
dictssubtrtheopicalG.waterssacculiferitprovidespopulationisinformationlimitedontotrsummeropicalwatersconditions.(20◦N–2The0◦S),modelwherpre-e
seasonalityhasnoeffectontherecordedtemperature.

analysisSensitivity3.3.2Sincetheseasonalityofforaminiferacouldhavebeendifferentduringforexample,
glacials,wecarriedoutsensitivityexperimentstotesttheresponseofplanktonic
foraminiferatochangesintemperature.Inthefirstexperimentwedecreasedtem-
peraturegloballyby2◦C.Thetemperaturechangewasonlyappliedtotheforamini-
feralmodule,thus,theunderlyingecosystemmodelwasforcedwithmodernSST.If

74

3.SeasonalbiasinForaminifera-basedProxyrecords

Table3.1:Locationsanddatasourcesoftheplanktonicforaminiferafaunas(modifiedfrom
˘Zaric´etal.,2005).
TrapLocationLatitude[◦N]Longitude[◦E]References
OceanStationPapa50.00−−145.00ReynoldsandThunell(1985)
(1986)ThunellandReynolds(1989)ThunellandSautter(1999)al.etongWPeru-ChileCurrent−−30.01−−73.18Marchantetal.(1998)
(2000)al.etHebbelnSargassoSea32.08−−64.25Deuseretal.(1981)
(1987)Deuser(1989)RossandDeuserN’NorthAtlanticNB–672.38−−7.71Jensen(1998)
NB–769.690.48Peinertetal.(2001)
CapeBlancCB–120.76−−19.74FischerandWefer(1996)
CB–2,3,421.15−−20.68˘Zaric´etal.(2005)
W’equatorialAtlanticWA–1−−4.00−−25.57FischerandWefer(1996)
WA–2,3−−7.52−−28.04˘Zaric´etal.(2005)
WAtlanticWAB–1−−11.57−−28.53Fischer(unpubl.data)
˘Zaric´etal.(2005)
WalvisRidgeWR–2,3−−20.059.16FischerandWefer(1996)
WR–4−−20.138.96˘Zaric´etal.(2005)
WeddellSeaWS–1−−62.44−−34.76DonnerandWefer(1994)
2.55−−64.91−−WS3,4ArabianSeaWAST16.3360.49Curryetal.(1992)
CAST14.4964.76GupthaandMohan(1996)
EAST15.4868.74Haakeetal.(1993)
BayofBengalNBBT17.4589.60GupthaandMohan(1996)
CBBT13.1584.35Gupthaetal.(1997)
NorthwestPacificWCT–125.00136.99Mohiuddinetal.(2002)
147.0039.01–2WCTNW’NorthPacific50N50.02165.03
KNOT43.97155.05Kuroyanagietal.(2002)
165.0040.0040NSubantarcticZoneSAZ–47−−46.76142.07KingandHoward(2003a,b)
SAZ–51−−51.00141.74Trulletal.(2001)
141.7653.75−−SAZ–54ChatmanRiseSCR−−44.62178.62KingandHoward(2001)
(2001)NorthcoteandNodder

thereisnochangeintheseasonalityofforaminifera,thentheexpectedtemperature
variationrecordedbyforaminiferawillbe2◦C.Inourexperiment,duetocooling,
themaximumproductionmonthformostspeciesshiftedtoawarmerseason,and
asaconsequencethetemperaturevariationretainedinthesedimentaryrecordwas
oftensignificantlyunderestimated(Table3.2).However,theestimatesderivedfrom
G.sacculifer,aswellasN.pachyderma(sin.anddex.)intheArcticOceanandin
polar/subpolarwaters,wereabletoreflecttheentiretemperaturevariationof2◦C.
G.ruberunderestimatedthevariationoftemperatureatalllatitudes,morenotable
inthesubtropicalthaninthetropicalpopulation(maximumbiasof0.4◦Cinsub-

Results3.3.

75

Table3.2:DifferenceofrecordedtemperatureforT=–2◦C.Meantemperaturedifference
(sensitivityexperimentminusstandardexperiment)recordedbythespeciesanditsstandard
deviation(σ).Emptycellsindicatethatthespeciesisnotlivinginthisregion.*denotes
thattemperaturevariationwassignificantlyunderestimated(t–testwith99%ofconfidance;
**95%ofconfidance).Tappliedonlytotheforaminiferamodel.

OceanregionsN.pachydermaN.pachydermaG.bulloidesG.ruberG.sacculifer
(white)(dex.)(sin.)meanσmeanσmeanσmeanσmeanσ
AtlanticPolar/Subpolar(60◦–90◦)–20.6–1.9∗∗0.3–1.7∗0.5——
Temperate(40◦–60◦)–1.9∗0.5–1.9∗0.2–1.8∗0.3———
Subtropic(20◦–40◦)—–1.9∗0.3–20.4–1.6∗0.5–2<0.1
Tropic(0◦–20◦)—–20.3–1.7∗0.6–1.8∗0.3–2<0.1
PacificPolar/Subpolar(60◦–90◦)–1.9∗∗0.4————
Temperate(40◦–60◦)–1.6∗0.7–1.8∗0.4–1.7∗0.3——
Subtropic(20◦–40◦)—–1.8∗0.3–20.5–1.7∗0.5–2<0.1
Tropic(0◦–20◦)—–1.9∗0.3–1.6∗0.7–1.9∗0.1–2<0.1
IndianPolar/Subpolar(60◦–90◦)–2.50.4————
Temperate(40◦–60◦)–1.9∗0.2–1.9∗0.2–1.9∗0.2——
Subtropic(20◦–40◦)—–1.8∗0.3–1.9∗0.3–1.8∗0.4–2<0.1
Tropic(0◦–20◦)——–1.9∗0.2–1.9∗0.2–2<0.1
Arctic(70◦–90◦N)–1.90.5–20.3–1.5∗0.5——

tropicscomparedto0.2◦Cinsubtropics).
Wecarriedoutanotherexperimentinwhichthe2◦Ctemperaturereductionwas
onlyappliedtotheecosystemmodel,whiletheforaminiferamodelusedmodern
SST.ExceptforG.bulloides,thevariationsintheecosystemmodelduetothetem-
peraturereductiondidnotinfluencetheseasonalityofforaminifera,andtherefore
thespecieswereabletorecordtheentiretemperaturevariation(Table3.3).Hence,
forthesubsequentanalysis,weonlyconsiderthedirecttemperaturecontrolonfo-
raminiferaandnottheindirecteffectviatheecosystem.
Inthesecondsensitivityexperiment,decreasingSSTgloballyby6◦C,N.pachy-
derma(sin.)disappearedfromthePacificandIndiansectorsoftheSouthernOcean
(Table3.4).N.pachyderma(dex.)recordedavariationof5.5–5.9◦C,andwasthe
speciesthat,afterG.sacculifer,bestdocumentedtheentiretemperaturechangeof
6◦C.◦G.bulloidesandG.ruberrecordedthewereclosertorecordtheentirevariation
of6Catlowlatitudesthanathighlatitudes.Thetemperaturechangereflectedby

76

3.SeasonalbiasinForaminifera-basedProxyrecords

Table3.3:DifferenceofrecordedtemperatureforT=–2◦C.Meantemperaturedifference
(sensitivityexperimentminusstandardexperiment)recordedbythespeciesanditsstandard
deviation(σ).Emptycellsindicatethatthespeciesisnotlivinginthisregion.*denotes
thattemperaturevariationwassignificantlyunderestimated(t–testwith99%ofconfidance;
**95%ofconfidance).Tappliedonlytotheecosystemmodel.

OceanregionsN.pachydermaN.pachydermaG.bulloidesG.ruberG.sacculifer
(white)(dex.)(sin.)meanσmeanσmeanσmeanσmeanσ
AtlanticPolar/Subpolar(60◦–90◦)–20.2–2.10.2–20.4——
Temperate(40◦–60◦)–20.2–20.2–1.9∗0.3——
Subtropic(20◦–40◦)—–20.3–1.90.4–20.3–2.1<0.1
Tropic(0◦–20◦)—–20.3–1.6∗0.5–1.9∗0.1–2<0.1
PacificPolar/Subpolar(60◦–90◦)–20.1————
Temperate(40◦–60◦)–20.1–20.2–1.9∗0.3——
Subtropic(20◦–40◦)—–20.3–20.5–20.3–2.1<0.1
Tropic(0◦–20◦)—–1.9∗0.3–1.4∗0.6–20.1–2<0.1
IndianPolar/Subpolar(60◦–90◦)–20.1————
Temperate(40◦–60◦)–20.2–20.2–1.9∗0.2——
Subtropic(20◦–40◦)—–1.9∗0.3–1.9∗0.4–2.10.2–2.1<0.1
Tropic(0◦–20◦)——–1.9∗∗0.2–1.9∗0.1–2<0.1
Arctic(70◦–90◦N)–1.90.4–20.3–2.10.5——

◦inG.thetrbulloidesopicswasandaroundsubtr5.2opics–5.7theCattemperaturepolar/subpolarchangewasand5.4–6temperate◦C.regions;while

G.ruber(white),inthesubtropics,underestimatedthevariationoftemperature
toagreater◦thaninthetropics(5.1–5.6◦Ccomparedto5.7–5.8◦Cinthetropics).
G.sacculiferreflectedaccuratelythetotaltemperaturechange.

Thelastsensitivityexperimentconsistsonincreasingtheseasonalityoftemper-
turatureebincry25%.eases.ThisTheimpliesvariationaofcoolingTrinofallwintercaseswastemperaturverye,small,whilelessthansummer0.2◦C,tempera-which
hasnotmeasurableeffectinpaleotemperatureestimations(Table3.5).

Discussion3.4.

77

Table3.4:DifferenceofrecordedtemperatureforT=–2◦C.Meantemperaturedifference
(sensitivityexperimentminusstandardexperiment)recordedbythespeciesanditsstandard
deviation(σ).Emptycellsindicatethatthespeciesisnotlivinginthisregion.*denotes
thattemperaturevariationwassignificantlyunderestimated(t–testwith99%ofconfidance;
**95%ofconfidance).Tappliedonlytotheforaminiferamodel.

OceanregionsN.pachydermaN.pachydermaG.bulloidesG.ruberG.sacculifer
(white)(dex.)(sin.)meanσmeanσmeanσmeanσmeanσ
AtlanticPolar/Subpolar(60◦–90◦)–5.3∗0.6–5.8∗0.5–5.3∗0.4——
Temperate(40◦–60◦)–5∗1.3–5.5∗0.5–5.4∗0.6——
Subtropic(20◦–40◦)—–5.6∗0.4–60.6–5.1∗0.9–6.1<0.1
Tropic(0◦–20◦)—–5.9∗0.3–5.7∗0.6–5.7∗0.3–6<0.1
PacificPolar/Subpolar(60◦–90◦)—————
Temperate(40◦–60◦)–4.3∗1.6–5.6∗1–5.2∗0.7——
Subtropic(20◦–40◦)—–5.5∗0.5–5.7∗0.7–5.3∗1–6<0.1
Tropic(0◦–20◦)—–5.8∗0.4–5.6∗0.6–5.8∗0.3–6<0.1
IndianPolar/Subpolar(60◦–90◦)—————
Temperate(40◦–60◦)–5.6∗0.4–5.8∗0.3–5.7∗0.3——
Subtropic(20◦–40◦)—–5.6∗0.3–5.7∗0.4–5.6∗0.9–6<0.1
Tropic(0◦–20◦)—–5.5∗0.4–5.9∗0.2–5.8∗0.2–6<0.1
Arctic(70◦–90◦N)–5.1∗0.9–5.9∗∗0.3–5.1∗0.5——

Discussion3.4

distributionspeciesLatitudinal3.4.1Ourstudysuggeststhatforallspecies,exceptG.sacculifer,therecordedtempera-
turesignalvariesdependingonthesamplinglocation.Ingeneral,athighlatitudes,
closetothegeographicallimitofoccurrenceofeachspecies,thesignalisbiasedto-
wardsummerconditions,whileatlowerlatitudesthesignalshiftstowardswinter
orannualmeantemperatures.G.ruber(white)recordstemperaturesclosetoan-
nualmeanwhencollectedintropicalwaters.However,near40◦,attheedgeofits
thermaldistributionrange,itreflectssummertemperatures.Themodelprediction
showsthattheflux-weightedreconstructedtemperaturesderivedfromG.sacculi-
ferareclosetotheannualmeanSST,indicatingthatshellsofG.sacculiferprovidea
goodproxytoestimateannualmeantemperatures.Theseisconsistentwithprevi-

78

3.SeasonalbiasinForaminifera-basedProxyrecords

Table3.5:Differenceofrecordedtemperatureforincreasedtemperatureseasonality.Mean
temperaturedifference(sensitivityexperimentminusstandardexperiment)recordedbythe
speciesanditsstandarddeviation(σ).Emptycellsindicatethatthespeciesisnotlivingin
thisregion.Tappliedonlytotheforaminiferamodel.
OceanregionsN.pachydermaN.pachydermaG.bulloidesG.ruberG.sacculifer
(white)(dex.)(sin.)meanσmeanσmeanσmeanσmeanσ
AtlanticPolar/Subpolar(60◦–90◦)0.040.110.010.060.020.24——
Temperate(40◦–60◦)–0.050.270.050.120.010.13——
Subtropic(20◦–40◦)—–0.050.08–0.190.320.020.160.010.00
Tropic(0◦–20◦)—–0.040.10–0.090.31–0.030.090.000.00
PacificPolar/Subpolar(60◦–90◦)0.020.08————
Temperate(40◦–60◦)–0.130.310.110.210.020.10——
Subtropic(20◦–40◦)—–0.060.10–0.160.340.010.220.010.00
Tropic(0◦–20◦)—–0.040.05–0.160.31–0.020.040.000.00
IndianPolar/Subpolar(60◦–90◦)0.070.04————
Temperate(40◦–60◦)–0.030.130.040.100.020.09——
Subtropic(20◦–40◦)—–0.030.10–0.090.130.020.150.010.00
Tropic(0◦–20◦)—–0.060.160.000.14–0.030.030.000.01
Arctic(70◦–90◦N)0.030.12–0.010.100.030.24——

ousworkofCurryetal.(1983),whoconcludedthatthefluxweightedδ18Ocompo-
sitionofsediment-trapsampleswasinagreementwithannualmeanhydrography
intheareaofPanamaBasin.Ontheotherhand,themodelpredictsthepopulation
ofG.sacculiferislimitedtotropicalwaters(20◦N–20◦S),whereannualtemperature
cculifervariationsshellsareuprtoelatively40◦N,small.wheretheInstead,effectofsediment-trapseasonalitydataincrshowseases.fluxesTheseofG.samplessa-
belongtothestationsinthenorthwesternPacific(WCT-2and40NinTable3.1).At
WCT-2,G.sacculifercontributedasmallpart(lessthan1%)ofthetotalforaminiferal
turfluxesupto(Mohiuddin24◦Cetduringal.,late2002).Atsummer40N,,whileKurouroyanagietal.climatological(2002)SSTmeasurhasaedmaximumtempera-
of20◦C.Thisdifferenceintemperaturecouldbethereasonwhythemodeldoesnot
predictG.sacculiferattheselatitudes.
Inanycase,usingthis◦foraminiferalmodel,wecannotsimulateseasonalvaria-
tionsofG.sacculiferabove20latitude.

3.4.Discussion

3.4.2SensitivityofspeciestochangesinSST

79

Withglobalcoolingof2◦Ctheforaminiferalmaximumproductioncanshiftto
warmerseasons;thusthemeanpopulationwouldrecordlittlechangeinisotopic
ortraceelementcomposition(Mix,1987).Ourexperimentsshowthat,inmostre-
gions,thespeciesarenotabletorecordtheentirecoolingof2◦Cand6◦C.The
foraminifera-basedsignalunderestimatesthetemperaturevariationupto0.5◦Cfor
the2◦Ccoolingandupto1.7◦Cforthe6◦Ccooling.Atpolar/subpolarwaters
thetemperaturedecreaseof2◦CisindeedrecordedbyN.pachyderma(sin.).In
theseregionstheforaminiferalseasonalmaximaoccursduringsummer;therefore
itcannotshifttowarmerconditions.Thereareafewlocationswhereforaminifera
overestimatedthevariationoftemperature;e.g.N.pachyderma(sin.)intheIndian
sectorontheSouthernOceanandG.sacculiferinsuptropicalwatersoftheAtlantic
Ocean.Attheselocationsforaminiferalmaximumproductionoccursinsummer.
Uponcooling,theseasonalmaximumdoesnotshiftinphase,buttheamplitudeof
thepeakdecreases;whilethepopulationsizeduringthewinterseasondoesnotdi-
minish(butremainsclosetothethresholdvaluesetinthemodeltokeepaminimum
populationovertheyear).Inthisway,therelativeweightofthewinterpopulation
increasesandthetemperaturesignalreflectscoolerconditions.Itishoweverpos-
siblethatthisisamodelartifactratherthanacircumstancethatcanbefoundin
e.natur

IntropicalwatersoftheAtlanticandPacificOceans,N.pachyderma(dex.)is
oflinkedthetoupwellingcoastalregion.upwellingSSTzones,decreaseandprfollowsoducesthelittleordynamicnoandchangeinseasonaltheseasonalitysuccession
species.thisof

ForG.bulloides,consideredasaproductivityproxy(Hemlebenetal.,1989;Saut-
terandThunell,1991;Prell,1993;WatkinsandMix,1998;Ortizetal.,1995),tem-
peraturedoesnotseemtobethecontrollingfactor(Deuseretal.,1981;Thunelland
Honjo,1984;˘Zaric´etal.,2005).Nevertheless,exceptinsubtropicalwaters,thetem-
peraturevariationrecordedbytheshellwasunderestimated.Intropicalwatersof
thePacificOcean,themodelpredictsG.bulloideslivingclosetothePeruupwelling
system.TheseasonalmaximumofG.bulloidesoccursduringNovember-December
withtheendofthestrongupwellingseason(Marchantetal.,1998).Theeffectof
decreasingSSTby2◦C,istobringtemperatureduringthesemonthsclosertothe
optimaltemperatureofG.bulloides,andthereforetheamplitudeoftheseasonal
peakincreases.Oursimulationdoesnotshowashiftoftheseasonalmaximum,
butduetoincreaseinabundanceduringthesemonths(beginningofaustralsum-

80

3.SeasonalbiasinForaminifera-basedProxyrecords

mer),therelativeweightofthesummersignalincreased,andTrunderestimated
theprescribedvariation.ThesamesituationarisesintropicalregionsoftheAtlantic
Ocean,whereG.bulloidesislinkedtotheupwellingsystemofBenguela.

Inbothexperiments,thetemperaturebiasinG.ruber(white)populationwas
strongerinthesubtropicsthaninthetropics.Intropicalwaters,adecreaseof2◦C
stillallowsG.rubertoliveduringcoldseasons.Incontrast,inthesubtropics,where
theseasonalityoftemperatureishigher,a2◦Cdecreaseinwintershiftsthemaxi-
mumproductiontothesummer.Withthe6◦Ccoolingtheseasonalpeakshiftsto
summermonthsinbothregions,butsincetheamplitudeoftemperatureseasonality
islargerinthesubtropics,theeffectontherecordedsignalisalsomorepronounced.
G.sacculifer,whenlivingintropicalwaters,canrecordatemperaturedecreaseof2◦C
and6◦C.Intropicalwaterstheseasonalityoftemperatureisnotverypronounced,
andthereforeshiftsinforaminiferalproductiondonotaffecttheannualproxysignal
sediments.infoundIncreasingtheamplitudeoftemperatureseasonalityby25%doesnotshowef-
fectsintherecordedtemperaturesignal.Thedifferencesbetweenthestandardand
sensitivityexperiment(0–0.16◦C),althoughinsomecasesstatisticallysignificant,
arenotmeasurableinproxyrecords.G.bulloidesistheonlyspeciesunderestimating
Trby0.2◦Cinsubtropicalandtropicalregions.Fortheremainingspecies,thedif-
ferencesarewithinthetypicalanalyticaluncertaintyof±1◦C(Anandetal.,2003;
Dekensetal.,2002;Shenetal.,2007).
Thisforaminiferalmodelallowstoprojectanyclimatechangetothetemperature
signatureofthepopulationofeachspeciesreachingtheseafloor.However,this
modelislimitedtotheglobaloceanmixed-layer,assumingthatitisbiologically
homogeneous.Therefore,theeffectsinthetemperaturesignatureduetothedepth
habitatcannotbeassessedwiththismodel.

Conclusions3.5

Theeffectofseasonalityatdifferentlatitudeshastobetakenintoaccountforthecal-
mayibrationoverprintandinterprthetrueetationclimaticofsignal.foraminifera-basedThegeneraltemperaturpatternsershoweconstrthatatuctions,lowaslati-it
turtudeses.Onthethetemperaturotherehand,signalatrhighecordedlatitudes,bythedueshellstotherfacteflectsthatannualthehighestmeantempera-seasonal
Forfluxalloccursspecies,duringtheimprintsummer,oftherseasonalityecordedinsignalthercorrecordedespondstotemperatursummeresignalisconditions.more
pronouncedinthenorthernhemispherethaninthesouthernhemisphere.

Conclusions3.5.

81

Ourexperimentsindicatethatinregionswhereforaminiferalmaximumproduc-
tionoccursduringthewarmestseason(e.g.N.pachyderma(sin.)inpolarwaters),
thespeciescanrecordacoolingof2◦C.G.sacculifer,whenlivingintropicalwaters,
reflectsvariationistemperaturfullyresecorcloseded.toForthetheannualremainingmean.Therspecies,eforethethetemperaturabsoluteesignaltemperaturree-
◦theflectedglobalbythetemperaturshellseunderisrestimateseducedbythe2◦C;temperaturandupe1.7◦variationCwhenbyuprtoeduced0.5Cby6when◦C.
analyticalNevertheless,theuncertaintyunder.Enhancingestimationtheisrelativelyamplitudeofsmallandtemperaturinmostecasesseasonalityiswithinby25%the
hasnomeasurableimpactintherecordedtemperature.
Ourmodelpredictionsuggestthatplanktonicforaminiferalseasonalityisstrongly
linkedtotemperature.Inthisstudy,weisolatedthedirectimpactoftemperatureon
foraminiferaanditsimplicationsontheannualflux-weightedtemperaturesignal.
Climaticchangesincludealterationsonbroad-scaleconditions,suchmixed-layer
pastdepth,iceclimaticcoverorconditionssolarenablesradiation.toquantifyApplyingthetheseasonalsamebiasinmethodologytoforaminifera-basedcontrolled
ds.ecorroxypr

AcknowledgmentsThisprojectwassupportedbytheDFG(DeutscheForschungs-
gemeinschaft)aspartoftheEuropeanGraduateCollegue“ProxiesinEarthHistory”
(EUROPROX).WeappreciatethecontributionsandhelpfulcommentsofA.Bisset
andM.Prange.WealsothankG.Fischerforprovidingsediment-trapdataand
support.computerforManschkeA.

SubmittedtoMarineMicropaleontologyas:Fraile,I,Mulitza,S.andSchulz,M.–“Modelingplanktonic
foraminiferalseasonality:ImplicationsforSSTreconstructions”

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–Submitted“ModelingtotheseasonalPaleoceanographydistributionas:ofFraile,planktonicI.,Schulz,foraminiferaM.,Mulitza,duringS.,theLastMerkel,GlacialU.,Prange,Maximum”M.andPaul,A.

4ChapterduringforaminiferaplanktonicofSeasonalityMaximumGlacialLastthe

AbstractWestudiedtheseasonalityofplanktonicforaminiferaduringtheLastGlacialMaximum
usingaforaminiferamodelcoupledtoanecosystemmodel.Themodelsuggeststhatthe
seasonalityofplanktonicforaminiferaduringtheLastGlacialMaximumwasdifferent
fromtoday.Thisfindingentailsimplicationsforforaminifera-basedpaleotemperature
reconstructions.Thechangeinthetimingofmaximumforaminiferalproductioncould
leadtoabiasinestimatedpaleotemperature,ifthechangeinseasonalityisnottakeninto
account.Intropicalwaters,wheretemperatureseasonalityhasarelativelysmallamplitude,the
estimatedsea-surfacetemperatureisclosetotheannualmean.Thus,variationsinfo-
raminiferalseasonalitydonotcauseasignificantchangeintherecordedtemperature.
Bycontrast,changesinseasonalityhavethelargestinfluenceonthetemperaturesignal
athighandmid-latitudes.Ourmodelpredictionsuggeststhatduetothetemperature
sensitivityoftheconsideredspecies,duringtheLastGlacialMaximum,thelargestpro-
ductionofforaminiferaoccurredduringawarmerseasonoftheyear.Insomeregions,
themaximumforaminiferalproductionmonthshiftedbyuptosixmonths.
Ourfindingsmayhelptoreconcilelowglacialplanktonicδ18Ovalueswithproxyevi-
dencefordeep-waterformationintheNordicSeas.

Introduction4.1oraminiferalstudiesprovideafundamentalcontributiontoourunderstanding
Fofpastandfutureoceanandclimatesystems.Manypaleotemperaturerecon-
structionsrelyontheanalysisofforaminiferaltestchemistryorassemblagecom-
position.However,temperatureestimatesderivedusingspecies-specificpaleotem-
peratureequationsarestronglyaffectedbytheseasonalityoftemperature-sensitive
species(Mulitzaetal.,1998;Tedescoetal.,2007).Inordertoaccuratelyinterpret
theforaminiferalfossilrecordpreservedwithindeep-seasediments,earlyworks
focusedonmodernforaminiferalecology(e.g.,Be´andHamilton,1967;Be´andTold-

92

4.SeasonalityofplanktonicforaminiferaduringtheLastGlacialMaximum

erlund,1971;Hemlebenetal.,1989).Thedevelopmentofautomatedtime-series
sedimenttraps(Honjoetal.,1980;HonjoandDoherty,1988)hasledtoabetterun-
derstandingofthefluxesofmodernplanktonicforaminifera,revealingthatthey
havelargeseasonalvariationsinabundancetiedcloselytosurfacewaterhydrogra-
phy(B´e,1960;Be´andTolderlund,1971;Deuseretal.,1981;ThunellandReynolds,
1987;SautterandThunell,1991).Differentforaminiferaspecieshavedistinctsea-
sonalpatterns,theimprintofwhichispreservedinthesedimentaryrecord(King
andHoward,2005;SchiebelandHemleben,2005).Thus,thetemperaturesignature
foundinthesedimentaryrecordliesbetweentheannualmeanwatertemperature
andthepreferredtemperatureofaparticularspecies(Mix,1987).
Theseasonaldistributionofsomeforaminiferalspeciescanchangethroughtime
asclimatechanges,leadingtoabiasinestimatedpaleotemperature.Thisvariation
needstobequantifiedinordertobetterconstraintheinterpretationofforaminifera-
basedsea-surfacetemperature(SST)reconstructions.Tostudytheseasonalvari-
ationsofplanktonicforaminiferaspeciesatglacial-interglacialtimescales,weuse
aforaminiferalnumericalmodel(Fraileetal.,2008).Thisplanktonicforaminife-
ralmodelpredictsmonthlyconcentrationsofthemostimportantspeciesusedas
sourceofpaleoceanographicproxies.Inordertotesttheresponseofplanktonicfo-
raminiferatoclimatechanges,themodelhasbeenrunformodernconditionsand
fortheLastGlacialMaximum(LGM).Thisstudyshowsmodelpredictionsforspa-
tialandtemporaldistributionsoffivemostfrequentlyusedforaminiferalspecies,
anddiscussestheimplicationsforpaleotemperaturereconstructions.

Methods4.2

4.2.1Foraminiferamodelandexperimentsetup
Themodelpredictsmonthlyconcentrationsofthefollowingplanktonicforamini-
feraspecies:N.pachyderma(sinistralanddextralvarieties),G.bulloides,G.ruber
(whitevariety)andG.sacculifer.Thesespeciesaremostlyfoundintheeuphotic
zone,andreflectthesea-surfaceenvironment(B´e,1982).Themodelisimplemented
intoanecosystemmodel(Mooreetal.,2002),fromwhichittakesinformationon
foodavailabilityfortheforaminifera.Theecosystem-foraminiferamodelisforced
withphysicalandchemicalboundaryconditions.Initially,themodelisintegrated
fortwoyears,toallowanequilibriumstatetobereached(Mooreetal.,2002).The
thirdyearisthensavedwithatemporalresolutionofonemonth.Inthemodelstan-
dardsetup,theforcingincludesSST(WorldOceanAtlas1998,Conkrightetal.,1998),
surfaceshortwaveradiation(BishopandRossow,1991;RossowandSchiffer,1991),
climatologicalmixed-layerdepths(MontereyandLevitus,1997),verticalvelocityat

Methods4.2.

93

thebaseofmixedlayer(Gentetal.,1998),turbulentexchangerateatthebaseof
themixedlayer(constantvalueof0.15m/day;Mooreetal.,2002),sea-icecoverage
(Cavalierietal.,1990)andatmosphericironflux(Mahowaldetal.,1999).Thefo-
raminiferamodelanditsbehaviorinaglobalsurfacemixed-layerisdescribedin
detailinFraileetal.(2008).

Tocomparetheforaminiferalresponsetoglacial-interglacialperiods,weused
theglobalcoupledCommunityClimateSystemModel-version3(CCSM3)(Collins
etal.,2006)toforcetheforaminiferamodel.Wecarriedoutexperimentsfortwo
differentenvironmentalconditions:inthestandardrunthemodelwasforcedwith
presentdayconditions(PD),usingthesameforcingasdescribedinFraileetal.
(2008),andinthesecondrunwithLastGlacialMaximumconditions(LGM).
onWealsoforaminiferalperformedpopulations.sensitivityWecarriedexperimentsoutantoevaluateexperimenttheincrinfluenceeasingofthenutrientsnutrient
creaserconcentrationsesultingfrbelowomathe120mmixedeustaticlayerbysea-level3.2%forloweringtheLGM,(Fairbanks,equivalent1989).totheFinallyin-,
weperformedanotherexperimentusingthenutrient(nitrateandphosphate)dis-
Systemtributions-ClimatebelowtheModelmixed(UViclayerESCM)asforsimulatedtheLGMbythe(WeaverUniversityetal.,ofV2001).ictoriaForEarththis
dustrialexperiment,andweLGMcalculatedconditionsthedifwithinfertheenceUVinic,nutrientandweappliedconcentrationthisanomalybetweentoprourein-
un.rLGMdstandar

simulationsModelClimateCCSM34.2.2TheNationalCenterforAtmosphericResearch(NCAR)CCSM3isastate-of-the-art
coupledclimatemodel.Theglobalmodeliscomposedoffourseparatecomponents
representingatmosphere,ocean,land,andseaice(Collinsetal.,2006).Here,we
usethelow-resolutionversionofCCSM3whichisdescribedindetailbyYeageret
al.(2006).Inthisversion,theresolutionoftheatmosphericcomponentisgiven
byT31(3.75◦by3.75◦transformgrid)spectraltruncationwith26layers,whilethe
oceanhasameanresolutionof3.6◦by1.6◦(likethesea-icemodel)with25levels.
Thelatitudinalresolution◦oftheoceanicmodelgridisvariable,withfinerresolution
neartheequator(≈0.9).
therWeesultshaveofwhichperformedweretwousedtocoupledforcetheclimateecosystemsimulationsand(prforaminiferaeindustrialandmodel.LGM),The
prizationeindustrialandfollowssimulationtheprusesotocolforcingestablishedappropriatebytheforPaleoclimateconditionsbeforeModellingindustrial-Inter-
comparisonProject,Phase2(PMIP–2;http://www–lsce.cea.fr/pmip2/)(Bracon-

94

4.SeasonalityofplanktonicforaminiferaduringtheLastGlacialMaximum

notetal.,2007).ThisforcingrepresentstheaverageconditionsofthelateHolocene
beforethesignificantimpactofhumans,ratherthanaspecificdate,anditincludes
concentrationsofgreenhousegases,changesinthespatialdistributionsofozone,
sulfate(onlydirecteffect),andcarbonaceousaerosols(Otto-Bliesneretal.,2006b).
Inadditiontotheseforcingfactors,changesinorbitalparameters,icesheetsand
areducedglobalsealevelaretakenintoaccountfortheLGM(21,000yearsbefore
present)simulationfollowingthePMIP-2protocol.Forcontinentalice-sheetextent
andtopography,theLGMICE-5Greconstruction(Peltier,2004)isused.Thecoast-
lineisalsotakenfromICE-5Gandcorrespondstoasea-levelloweringof≈120m
suchthatnewlandisexposed.

Bothclimatesimulationswereintegratedformorethan600yearssothatthesur-
faceclimatologiesreachedastatisticalequilibriumandcouldbeusedforecosystem-
modelforcing.Themeanofthelast100simulationyearsofthefollowingparam-
eterswasusedtoforcetheecosystemandforaminiferamodels:SST,mixed-layer
depth,icefraction,shortwaveradiationandverticalvelocityatthebaseofmixed-
layer.Theglacialcoolingofthetropicalsurfaceoceanisupto2◦C.Strongercooling
(>5◦C)takesplaceathighlatitudes.Thelargesttemperaturedropcanbefound
intheNorthAtlantic,whereglacialtemperaturesareupto10◦Ccolderthanpre-
industrialvalues(Fig.4.1).TheNorthAtlantictemperaturedropcanpartlybeex-
plainedbyareductionofthemeridionaloverturningcirculation.IntheLGMsimu-
lation,theoverturningweakensbynearlyonethirdfrom14Svinthepreindustrial
runtoabout10Sv(notshown).ThecoredepthofsouthwardflowingNorthAtlantic
DeepWater(i.e.theDeepWesternBoundaryCurrent)reducesfrom∼2500minthe
preindustrialsimulationto∼1500mintheglacialrun.Thepeaknorthwardheat
transportintheNorthAtlanticoceandecreasesbyabout20%intheLGM.Further
detailsofthemodelexperimentwillbepresentedelsewhere(Merkeletal.,inprep.).
Wecalculatedtheanomalyoftheforcingvariables(SST,mixed-layerdepth,icefrac-
tion,shortwaveradiationandverticalvelocityatthebaseofthemixed-layer)sim-
ulatedbyCCSM3betweenLGMandpreindustrialconditions,andweaddedthis
anomalytothestandardforcingdataasanLGMforcingfortheforaminiferalmodel.
Weusedthisapproachinordertoreducedeviationsinducedbytheclimatemodel
errors.Forexample,intheNorthAtlantic,theSSTssimulatedbyCCSM3forpresent
dayareupto7◦CtoolowcomparedtoWorldOceanAtlasdata(Prange,2008).
GlacialSSTanomaliescorrespondwellwithreconstructions(Fig.4.1).Inorderto
avoidpotentialinconsistenciesbetween◦sea-icefractionandSST,weseticefraction
tozerofortemperaturesabove-1.5C.

Methods4.2.

95

Figure4.1:AverageannualSSTanomalybetweenLastGlacialMaximumandmoderncondi-
tions(LGM–WOA)estimatedfromplanktonicforaminifera(MARGOdataset(left)(Weinelt
etal.,2004);andGLAMAP2000compilation(center)(Pflaumannetal.,2003)),andSST
anomaly(LGM–PI)simulatedbyCCSM3.0(right).

4.2.3UVicEarthSystem-ClimateModelsimulations

Foranexperimentonforaminiferalsensitivitytochangesinthenutrientdistribu-
tions,weusedtheoutputfromtheUVicESCM(version2.8).ComparedtoCCSM3,
theatmosphericcomponentissimplifiedandconsistsofaverticallyintegratedtwo-
dimensionalenergy-moisturebalancemodel(Weaveretal.,2001).Inadditiontothe
atmosphere,oceanandseaicecomponents,itcontainsalandsurfacescheme(Cox,
1999),adynamicglobalvegetationmodel(Coxetal.2001;Meissneretal.2003)and
amarinebiogeochemicalcomponent(Schmittneretal.,2005).
Thehorizontalresolutionofthemodelisconstantat3.6◦inthelongitudinal
and1.8◦inthelatitudinaldirectionandthuscomparabletoCCSM3.Intheocean
component,thereare19levelsintheverticaldirection.withathicknessrangingfrom
50mnearthesurfaceto590mnearthebottom.
Inboth(preindustrialandLGM)simulationscarriedoutwiththeUVicESCM,
themonthlywindstresstoforcetheoceanandmonthlywindsfortheadvection
ofheatandmoistureintheatmosphereareprescribedfromtheNCEPreanalysis
climatology(Kalnayetal.,1996).Themodelisdrivenbytheseasonalvariationof
insolation,appropriatetoeitherpreindustrialorLGMconditions.AsinCCSM3,
theICE-5Greconstruction(Peltier,2004)isusedtoprescribethecontinentalice-
sheetextentandtopographyfortheLGM.Becauseofthecomputationalefficiency

96

4.SeasonalityofplanktonicforaminiferaduringtheLastGlacialMaximum

Figure4.2:RelativeabundanceofN.pachyderma(sin.)formodernconditions(upperpanel)
andduringtheLGM(lowerpanel)inthesedimentaryrecord(left)andmodelprediction
(right).Relativeabundancesconsideronlythefivespeciesincludedinthemodel.Modern
sedimentaryfaunalassemblagedatafromPflaumannetal.(1996);Prelletal.(1999);Martinez
etal.(1998),andLGMdatafromMARGOandGLAMAPdatasets(BarrowsandJuggins,
2004;Kuceraetal.,2004a,b;Niebleretal.,2004;Kuceraetal.,2005;Pflaumannetal.,2003).

oftheUVicESCM,thesimulationscouldbeintegratedformorethan10,000years
theandrseaeachedsurfacebetweenquasi-equilibrium≈2◦Cintheconditionstropicsevenandin≈the10◦Cdeepintheocean,withhigh-latitudeacoolingNorthof
Atlantic.Forfurtherdetails,seePauletal.,inprep.

Methods4.2.

97

Figure4.3:RelativeabundanceofN.pachyderma(dex.)formodern(upperpanel)andduring
theLGM(lowerpanel)inthesedimentaryrecord(left)andmodelprediction(right).Symbols
andlayoutofthegraphsarethesameasinFig.4.2.

4.2.4assemblagesfaunalSedimentary

Tocompareourmodelpredictionofplanktonicforaminiferaldistributionduring
theLGMwithsedimentdata,weusedplanktonicforaminiferacensusdatafrom
theMARGO(BarrowsandJuggins,2004;Kuceraetal.,2004a,b;Niebleretal.,2004;
Kuceraetal.,2005)andGLAMAP(Pflaumannetal.,2003)datasets.Forpresentday
weusedcore-topdatafromtheBrownUniversityForaminiferalDatabase(Prellet
al.,1999),extendedwiththedatasetbyPflaumannetal.(1996)fortheAtlantic,and
withsamplesfromtheeasternIndianOcean(Martinezetal.,1998).Forcomparison,
therelativeabundanceswererecalculatedusingonlythefiveforaminiferaspecies
underconsideration.Thenumberofindividualswastransformedintobiomass
(mgC/m3)totakeintoaccountthesizedifferencesofeachspecies.Thetransfor-

98

4.SeasonalityofplanktonicforaminiferaduringtheLastGlacialMaximum

Figure4.4:RelativeabundanceofG.bulloidesformodern(upperpanel)andduringtheLGM
(lowerpanel)inthesedimentaryrecord(left)andmodelprediction(right).Symbolsand
layoutofthegraphsarethesameasinFig.4.2.

mationwasmadefollowingthesameprocedureasinFraileetal.(2008).

signaltemperatureFlux-weighted4.2.5

Seasonalvariationsintheabundanceofthespecieshavebeenstudiedtoevaluate
theirimplicationsforproxyrecords.Theisotopic(ortrace-element)compositionof
aforaminiferalpopulationinthesedimentistheflux-weightedmeanofallisotope
values.Thus,theoretically,thetemperaturesensedbythemeanpopulationofa
species(Tr)istheflux-weightedmeanofalltemperaturesatthesite.Wecalculated
thetheoreticalmeanSSTrecordedineachoftherespectivespecies(Tr):

Methods4.2.

99

Figure4.5:RelativeabundanceofG.ruber(white)formodern(upperpanel)andduringthe
LGM(lowerpanel)inthesedimentaryrecord(left)andmodelprediction(right).Symbols
andlayoutofthegraphsarethesameasinFig.4.2

(4.1)

12(Cm×Tm)
Tr=m=112(4.1)
Cm=1mwhereCmismonthlyspeciesconcentrationandTmdenotesSST.Ateachsite,
Trrangesbetweenthemeanwatertemperatureandmeanpreferredtemperature
bythespecies(Mix,1987).Theoretically,Trcorrespondstothesignalfoundinthe
d.ecorrsedimentary

100

4.SeasonalityofplanktonicforaminiferaduringtheLastGlacialMaximum

Figure4.6:RelativeabundanceofG.sacculiferformodern(upperpanel)andduringtheLGM
(lowerpanel)inthesedimentaryrecord(left)andmodelprediction(right).Symbolsand
layoutofthegraphsarethesameasinFig.4.2.

Results4.3

4.3.1RelativeabundancesofthespeciesduringtheLGM
Thesensitivityexperimentwithincreasednutrientconcentrationsbelowthemixed
layerby3.2%doesnotshowasignificanteffectinforaminiferalconcentration(to-
talbiomassvariation≤2%forallspecies).Usingthenutrientredistributionbelow
themixedlayersimulatedwithUVicESCMdoesnotleadtomajorchangeseither
(totalbiomassvariation≤3%forallspecies).Therefore,tocomparewithsediment
samples,nutrientconcentrationsbelowthemixedlayerwerekeptthesameasin
Mooreetal.(2002)forbothmodernandLGMruns.Figs.4.2–4.6illustrateannual
meanrelativeabundancespredictedbythemodelascomparedtothosemeasured

Results4.3.

101

Figure4.7:Temperaturesignalrecordedbythespecies(Tr)minusannualmeanSSTduring
LGMfor(a)N.pachyderma(sin.),(b)N.pachyderma(dex.),(c)G.bulloidesand(d)G.ruber
(white).Valuesaroundzero:TrcorrespondstoannualmeanSST.Negative/positivevalues:
Trdominatedbywinter/summerconditions.

insedimentsforthefivedifferentspecies.

theThemodelglobalprediction,abundanceyieldpatternhighestofrN.elativepachydermaabundances(sin.)in(uptosediments,100%)inaspolarwellaswa-in
ofters(Fig.dominance4.2,ofupperN.panels).pachydermaIn(sin.)comparisonduringthewithprglacialesent-dayperiodisconditions,wider.Inthepartic-area

102

4.SeasonalityofplanktonicforaminiferaduringtheLastGlacialMaximum

Figure4.8:MaximumproductionmonthofN.pachyderma(dex.)atpresentday(PD),Last
GlacialMaximum(LGM)andthedifferencebetweenboth(inmonths).Positivevaluesindi-
catethatduringtheLGM,themaximumproductionwaslaterintheyear.

ular,itsdistributionintheNorthAtlanticspreadssouthwardstolowerlatitudes.
ThelackofforaminiferalcensusdataintheSouthernOceanhampersmodelevalu-
ation(dex.)inandthisG.region.bulloidesBothoccurrmodeledinandsignificantsedimentarynumbersdataintheindicatemajorthatN.upwellingpachydermaareas
◦nance(Figs.of4.3–4.4G.rbulloidesespectivelyover,theupperotherpanels).fourspecies,Along40whichS,isthealsomodelreflectedpredictsbyathedomi-sed-
desimentsduringsouththeofLGMAustralia.alsoextendsThetowardistributiondslowerofN.latitudespachydermacompar(dex.)edtoprandesentG.bulloi-day.
tweenHowever20◦,Ntheandmodel20◦S,overwhere,estimatesawayfrtheiromrelativeupwellingrabundanceegions,theinrtrelativeopicalwaters,abundancesbe-
intweenthe20–sediments40%arduringe≤the10%.LGM.ByAscontrast,theconsequence,modeltheprpredictsedictedrelativerelativeabundancesabundancebe-
isofG.limitedrubertotr(white)opicalatthesewaters,butlatitudesitsistooabundancelowis(Fig.also4.5,underupperestimated,panels).G.moresacculiferpro-
nouncedintheAtlanticOceanthaninthePacificandIndianOceans(Fig.4.6,upper
panels).

4.3.2ForaminiferalseasonalityduringtheLGM
ThesignalrecordedbyN.pachyderma(sin.)andG.bulloidesduringtheLGMis
foundtobebiasedtowardssummerconditionsathighlatitudes(polar/subpolar

Results4.3.

103

watersforN.pachyderma(sin.),andbetween40–60◦N/SforG.bulloides),andto-
wardswinterbelow40◦latitude(Fig.4.7).Incontrast,forN.pachyderma(dex.)and
G.ruber,theseasonalimprintonTrbecomesonlydiscernibleattheedgeoftheir
distributions(polewardof40◦N/SforN.pachyderma(dex.)and35◦N/SforG.ru-
ber),wherethesignalisbiasedtowardssummerconditions.Atlowerlatitudesthe
recordedtemperaturesignalisclosetoannualmeanSST.Duetothefactthatthe
seasonalityoftemperatureinthetropicsisnotverypronounced,thetemperature
signalrecordedbyG.sacculiferintropicalwatersreflectsmostlyannualmeancon-
ditionsandisthereforenotshowninthefollowingfigures.

Figs.4.8–4.11illustratethemaximumproductionmonthofeachspeciespredicted
bythemodelforPDandLGM.Ithastobenotedthatinregionswheretheannual
distributionpatternhaslowvariability(e.g.inthetropicsoratregionswherethe
doesannualnotalwaysforaminiferalhaveacycleissignificanttypicallyimprintbimodal),onthertheecordedmaximumtemperaturpre.oductionInregionsmonth
iswithtakenawideintoseasonalaccount,rmaximumesultinginorawithnoisyadoublepattern.peakInoronlyderthetorabsoluteeducethismaximumnoise,
thegridpoints.originaldataDuringhavethebeenLGMthesmoothedmaximumusingpraboxcaroductionfiltermonthalongbothcoincidesaxesmorbyethroftenee
withsummermonthscomparedtomodernthesituation.Forexample,accordingto
ofthe60◦model,latitude,N.andpachydermaduring(sin.)springpresentlybetween40occurs–60◦duringlatitude.summerDuringmonthstheLGM,polewarthed
maximumproductionoccurredduringsummerabove30◦latitude,moreevidentin
theimumprsouthernoductionhemisphermonthe.frTheomrightLGMtopanelsprofesentFigs.conditions.4.8–4.11showThus,thepositiveshiftofvaluesmax-
indicatethatduringtheLGMmaximumproductionoccurredlaterintheyear.

Themodelsimulationsuggeststhatthemaximumproductionmonthcouldhave
shiftedconsiderablybetweenPDandLGMconditions,producingalargeseasonal
bias.Theresultsshowaveryvariableresponseforeachspecies:Maximumseasonal
biasforN.pachyderma(sin.)andG.bulloidesoccursinthesubantarcticfront,around
60◦Sand40◦Srespectively.IncaseofN.pachyderma(dex.)thelargestchangein
seasonalitytakesplacebetween30–40◦NintheNorthAtlanticOcean,wheremax-
imumproductionisshiftedbyupto6months.G.ruber(white)experiencesamax-
imumshiftofseasonalityintropicalwaters.Nevertheless,variationsinforamini-
feralseasonalityintropicalwatersdonotaffecttheisotopicsignalconsiderably,as
small.isseasonalityetemperatur

104

4.SeasonalityofplanktonicforaminiferaduringtheLastGlacialMaximum

Figure4.9:MaximumproductionmonthofN.pachyderma(dex.)atpresentday(PD),Last
GlacialMaximum(LGM)andthedifferencebetweenboth(inmonths).Positivevaluesindi-
catethatduringtheLGM,themaximumproductionwaslaterintheyear.

Discussion4.4

4.4.1Comparisonbetweenmodeloutputandsedimentsamples
ThedistributionpatternsofallspeciesduringtheLGMareshiftedtolowerlati-
tudesinresponsetotheglacialcooling.Accordingtoourmodelprediction,during
theLGM,N.pachyderma(sin.)extendeditsdistributiontolowerlatitudes(Fig.4.2),
inresponsetofavorablecoldtemperaturesfoundbetween40–50◦latitude.During
theLGM,thespatialdistributionwaswidercomparedtothatformoderncondi-
tions,especiallyinthesouthernhemisphere.Coredataandthemodelprediction
comparefavorably,althoughthelackofglacialsedimentsamplesinthesubantarc-
ticregionhamperstheevaluationinthisregion.
Maximumcoolingoccurredaround40–50◦Sandbetween30–50◦NintheNorth
Atlantic(morethan4◦Ccooling,Fig.4.1).Thiscoolingcausesthedistributionoffo-
raminiferainhabitingtheseregions(mainlyG.bulloidesandN.pachyderma(dex.))
tobeshiftedtowardswarmerwaters(Fig.4.3–4.4).Intropicalwaters,therelative
abundanceofthesespeciesduringtheLGMisoverestimatedincomparisonwith
sedimentsamples.CoredatasuggestthatduringtheLGMthepopulationofN.
pachyderma(dex.)wasdiminishedinresponsetounfavorablecoldconditions.In-
stead,accordingtoourpredictions,thepopulationwasshiftedtowarmerregions
ratherthanbeingreduced.InthecaseofG.bulloidesthesedimentaryrecordinthe

Discussion4.4.

105

Figure4.10:MaximumproductionmonthofG.bulloidesatpresentday(PD),LastGlacial
Maximum(LGM)andthedifferencebetweenboth(inmonths).Positivevaluesindicatethat
duringtheLGM,themaximumproductionwaslaterintheyear.

NorthAtlanticOceanshowsaclearshiftinitsdominancearea:atpresentdayit
occursmainlybetween40–50◦N,whereasduringtheLGM,northof40◦Nitsrel-
ativeabundancewasverylow(<10%).Thisshiftinthedominanceareafromlow
tohigherlatitudesfitswellwiththemodelprediction.TheoverestimationofG.
bulloidesandN.pachyderma(dex.)intropicalwatersbringsasconsequencetheun-
derestimationoftherelativeabundanceofG.ruber(white)(Fig.4.5).
Inthisecosystemmodel,nutrientconcentrationbelowthemixedlayerdoesnot
seemtoplayanimportantroleinthebiomassofphyto-andzooplankton.Inthe
waytheecosystemmodelisparametrized,thephyto-andzooplanktonreachan
equilibriumstateinwhichhighergrowthratetranslatesintohighermortality,keep-
ingtheconcentrationalmostunaltered.Thus,foraminiferalabundance,whichis
relatedtofoodavailability,isalsounaffected.

4.4.2Influenceofseasonalityonproxyrecords
Climatechangecaninducevariationsintheseasonalityofforaminifera.Changes
inthetimingofmaximumforaminiferalproductionmayinfluencetheproxysignal
andleadtoabiasinestimatedpaleotemperature.Fig.4.12illustratessomeexam-
pleswhere,accordingtoourmodelprediction,ashiftinseasonalityfromLGMto
prclearlyesentdayshifted(Fig.conditions4.12a,cwasandnoted.d),wherTheeasinmaximumsomeprotheroductioncasesthepeakisdoublesometimespeakis

106

4.SeasonalityofplanktonicforaminiferaduringtheLastGlacialMaximum

Figure4.11:MaximumproductionmonthofG.ruber(white)atpresentday(PD),LastGlacial
Maximum(LGM)andthedifferencebetweenboth(inmonths).Positivevaluesindicatethat
duringtheLGM,themaximumproductionwaslaterintheyear.

transformedintoasinglemaximum(Fig.4.12b).

ThelargestdifferencesbetweenpresentdayandLGMconditionsarefoundin
theSouthernOceanandintheNorthAtlantic(Figs.4.8–4.10).Inparticular,inthe
westernNorthAtlanticglacialcoolingisverypronounced,andasaconsequence
themaximumproductionmonthofN.pachyderma(sin.)andG.bulloidesoccurslater
intheyear,coincidingwiththewarmestseason.

Insomecasesmaximumproductionshiftedbyupto6months.Thisimpliesa
considerablevariationinrecordedtemperature.Forexample,ourexperimentwith
presentdayconditionssuggeststhat,around40◦NintheNorthAtlantic,theiso-
topicsignatureinG.bulloidesisbiasedtowardswintertemperatures,whereasdur-
ingtheLGM,itwasbiasedtowardssummerconditions.Asaconsequence,using
G.bulloidestoreconstructglacialSSTinthisregionwouldunderestimatetheentire
temperaturevariationbyupto2◦CintheeasternNorthAtlanticandupto6◦Cin
thewesternregion.Similarly,thechangeinseasonalityofN.pachyderma(sin.)in
thesubantarcticfront,between40–60◦S,influencestheinterpretationofthetem-
peraturesignal:DuringtheLGM,thedistributionofN.pachyderma(sin.)spreads
equatorwardsandmaximumproductionoccurredlaterintheyear;thus,themean
populationwouldrecordlittlechangeinthetemperaturesignal.

Discussion4.4.

107

Figure4.12:Examplesofmodelledannualbiomass[mmolC/m3]variationof(a)N.pachy-
derma(sin.)intheNorthAtlantic(52–56◦N,36–43◦W),(b)N.pachyderma(dex.)inthe
NorthPacific(36–39◦N,151–158◦E),(c)G.bulloidesintheNorthAtlantic(39–43◦N,47–
54◦W)and(d)G.ruber(white)intheSouthAtlantic(22–25◦S,22–30◦W)atPD(red)and
LGM(blue).Linesrepresentmeanvaluesanderrorbarsstandarddeviationsovertheregion.

Anotherinterestingfeatureofthemodeloutputisthedifferenceoftherecorded
signalbyN.pachyderma(sin.)inthewesternandeasternNorthAtlantic.Accord-
ingtotheLGMsimulation,inthewesternandeasternregionsoftheNorthAtlantic,
around40–50◦NN.pachyderma(sin.)recordsatemperaturesignalabovetheannual
mean,i.e.itlivesmostlyduringsummer,whereasinthecentralNorthAtlanticthe
recordedsignalisbiasedtowardswinter(Fig.4.7a).TheGLAMAPreconstructionat
NorthAtlanticsubpolarwatersbasedonplanktonicforaminifera,oneofthemajor
departuresfromtheCLIMAP(1981)pattern,wascharacterizedbyananticyclonic
gyreofwarmwatertransportedfromthewesternAtlanticmargin(summerSSTs
of5–7◦C),andacoldcurrentintheeasternNorthAtlantic,alongtheice-covered
BritishIslespenetratingintothecenterofthegyre(summerSSTsof3-4◦C)(Pflau-
mannetal.,2003).Thispatternwithacoldgyrecenterandawarmsurrounding
currentisdifficulttoexplainphysically,andtheauthorsalsodiscussthepossibil-

1084.SeasonalityofplanktonicforaminiferaduringtheLastGlacialMaximum

ityofanartifactresultingfromlateraladvectionofpolarfauna.Accordingtoour
themodelprtemperaturedictioneitsignalcouldcorrjustespondsbeduetoatothewinterfactsignal,thatinwhertheeasincentraltheNorthwesternAtlanticNorth
Atlanticforaminiferarecordasummersignal.

Inthesameway,Duplessyetal.(1991)usedtheisotopiccompositionofN.pa-
chyderma(sin.)andG.bulloidestoreconstructsurfacesalinityduringtheLGMin
theNorthAtlanticOcean,assumingthattheisotopiccompositionofforaminife-
ralsalineshellssurfaceislinearlywaterrwhichelatedtopenetratedsummertoSSTthe.TheycentralreconstrAtlanticuctedupato53tongue◦N,ofsouthhighlyof
18lowIceland.salinity)TheyinthealsofoundNorwegian-Granegativeeenlandanomalyseas,inδnortheastOofofseaIceland,waterand(interprconcludedetedas
ofthatfrthiseshwaterwasrduetoesultingbothfrothemlocalprdisappearanceecipitationoftheandNorthicemelting.AtlanticBaseddriftandonthisthepale-input
osalinitydistribution,Labeyrieetal.(1992)andSarntheinetal.(1994)suggestedthat
themajorsiteofglacialNorthAtlanticdeepwaterformationwasshiftedtothecen-
tralaccountsNorthformorAtlantic.ethanHowever98%of,ourthetotalmodelprforaminiferaedictionforN.assemblagepachyderma(Pflaumann(sin.),etwhichal.,
LGM1996),toprsuggestsesentthatday.theAtprseasonalityesentdayin,themaximumNorwegianproductionSeamayoccurshavefromshiftedAprilfromto
June,whereasaccordingtothemodel,itoccurredduringJuly-AugustattheLGM
(Fig.4.8).Theshiftofoneortwomonthsintheseasonalproductiontranslatesinto
achangeof1◦18Cintherecordedtemperaturesignal,whichcorresponds18toare-
ductionoftheδOanomalyofabout0.3.ThenegativeanomaliesinδOfound
byDuplessyetal.(1991)intheNorwegianSea(northeastofIceland)couldthere-
foryeare,beandduethertoefortheerfactecorthatdedanduringisotopictheLGMsignalN.corrpachydermaesponding(sin.)towarmercalcifiedlaterconditions.inthe
lowHence,salinitythe.Mornegativeeover,anomalybasedonwouldoxygenbeaisotopeconsequencerecorofds,Sarntheintemperatureetal.rather(1995)thande-of
finedtheLGMasaperiodofclimaticstabilityandminimummeltwaterflux.The
surfacewaterintheNorwegianSeawould,inthiscase,bedenseenoughfordeep-
waterformation,assuggestedbylaterstudies(Weineltetal.,1996;Sch¨afer-Neth
2001).Paul,andFortropicalspecies,shiftsinseasonalitydonotseemtohavemajorimplications
forpaleoceanographicreconstructions.Forexample,themonthofmaximumpro-
ductionofG.ruber(white)andG.sacculifershiftedconsiderablybetweenPDand
LGMconditionsbetween20◦S-20◦N.However,theflux-weightedtemperaturesig-
nalinsuggestingtropicalthelackwatersofawasseasonalfoundbiastoinbeinagrforaminifera-basedeementwithprtheoxyrannualecordsmean(Fig.4.7).SST,

Conclusions4.5.

109

Insubtropicalwaters,attheedgeofitsthermaldistributionG.ruber(white)records
summerconditionsduringtheLGM,similartothoseobservedundermoderncon-
ditions.

Conclusions4.5

Ourforaminiferamodelsimulationsuggeststhattheseasonalityofforaminiferahas
changedfromtheLGMtothepresentday.Thisvariationintheannualdistribution
patternvarieswiththespeciesandtheoceanicregion.Ingeneral,thechangesin
peraturseasonalityesareweratethegreatestloweratlimittheofedgetheirofthetolerancedistributionrange.ofDuringeachthespecies,LGM,whertheemax-tem-
imumproductionofsubtropicalandhigh-latitudeforaminiferagenerallyoccurred
atawarmerseasonoftheyear.

Changesinseasonalityofthespeciesrecordingaseasonalproxysignal,inpar-
ticularspecieslivingathighlatitudesassociatedwithhightemperatureseasonality,
haveimplicationsforpaleoceanographicreconstructions.Incontrast,forthespecies
livingintropicalwatersthechangeinseasonalitydidnotproduceanimportantbias
inestimatedtemperature,astheamplitudeoftheannualcycleofSSTisrelatively
low,andthereforetherecordedtemperatureisclosetotheannualmeanSST.

AcknowledgmentsTheCCSM3climatemodelrunswereperformedontheIBM
pSeries690SupercomputeroftheNorddeutscherVerbundf¨urHoch-undH¨ochstleis-
tungsrechnen(HLRN).ThisprojectwassupportedbytheDFG(DeutscheForschungs-
gemeinschaft)aspartoftheEuropeanGraduateCollege“ProxiesinEarthHistory”
(EUROPROX)andtheDFGResearchCenter/ExcellenceCluster“TheOceaninthe
System”.Earth

–Submitted“ModelingtotheseasonalPaleoceanographydistributionas:ofFraile,planktonicI.,Schulz,foraminiferaM.,Mulitza,duringS.,theLastMerkel,GlacialU.,Prange,Maximum”M.andPaul,A.

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5ChapterVerticaldistributionoflivingplanktonic
FrontAzorestheinforaminifera

Abstract

PlanktontowsfromintheAtlanticOceanallowanalysisofverticaldistributionofplank-
tonicforaminiferainthewatercolumn.TwositeshavebeenstudiedalongaN-Stransect
intheregionoftheAzoresFront(33-36◦N,20◦W)duringApril2006.Multinetsam-
pleswerecollectedbetweenthesurfaceand300m,inintervalsof20mand100m,and
foraminiferaspecieswereidentified.Livinganddeadspecimensweredistinguishedin
ordertorecognizethelivinghabitatofeachspecies.
ingMaximumspecimenstotalofG.foraminiferalfalconensis,abundanceG.wasglutinata,foundG.atthehumilisbase,G.ofrtheuber,mixedG.rlayer.ubescensLiv-
prandeferG.enceforsacculifersurfacewerewaters,limitedbuttowertheenotupperlimited60m.toG.it.Inbulloidescontrast,andG.G.scitulacalida,G.trshowedun-
catulinoidesandG.hirsutaoccurredmainlyindeeperwaters,butoccasionallywere
waters.shallowinfoundalsoTheTheassemblageforaminiferaofthemodelupperpredicted100mhighwasrcomparelativeedtoabundancetheoutputofG.ofabulloidesforaminiferalatthismodel.loca-
tions.ecologicalInstead,nicheinofG.oursamplesbulloideswewasfoundoccupiedverybylowotherspeciesconcentrations;notprincludedobablyinthebecausemodel.the

Introduction5.1

nthemodernocean,planktonicforaminiferalspeciespreferspecificecological
Ihabitats,andthereforetheverticaldistributionoftheindividualspeciesinthe
watercolumndependsonverticalvariationsinhydrographicparameterssuchas
temperature,salinity,foodavailability,chlorophyllconcentration,andlightlevel
(e.g.,Be´etal.,1985;Deuser,1987;Watkinsetal.,1996;Gupthaetal.,1997).Empty
shellofforaminiferaaccumulatedontheoceanfloorareusedtoreconstructpast
oceanicconditions.Thus,inordertoofferbetterconstrainsinpaleoceanographic
interpretations,itisimportanttounderstandtheirmodernverticalandhorizontal
distributionpatterns,andtheecologicalparametersthatcontroltheirlifecycle.To

1205.VerticaldistributionoflivingplanktonicforaminiferaintheAzoresFront

studythevariationsinthedistributionofplanktonicforaminifera,amathematical
model,whichsimulatesthepopulationdynamicsofthedifferentspecies,wasde-
veloped(Fraileetal.,2008).Thismodelpredictsthemonthlyconcentrationoffive
ofthemostimportantmodernplanktonicforaminiferausedinpaleoceanography
includingN.pachyderma(sin.),N.pachyderma(dex.)(followingtherecommendation
ofDarlingetal.(2006)herenamedN.incompta),G.bulloides,G.ruber(white)andG.
sacculifer.Themodelhasalreadybeenvalidatedusingsedimenttrapandcore-top
datasituatedallovertheworldforcomparison.However,themodelonlypredicts
thelivingpopulationinthemixedlayer,whereasthesedimenttrapandcore-top
datarepresenttheintegratedpopulationthroughoutthewatercolumn.Theobjec-
tiveofthisstudyistocomparethemodeloutputwithlivingpopulationcollected
withplanktonnetsinthewatercolumnandsurfacewatersoftheAzoresFront,in
Atlantic.Northeasternthe

methodsandMaterial5.2processingandSampling5.2.1ThesamplesweretakenbytheresearchgroupoftheMicropaleontologyDepart-
mentintheUniversityofT¨ubingeninthePoseidoncruise334,from15Marchto
3April2006betweenLasPalmasandMessina(Fig.5.1,lowerpanel).Amultiple
opening–closingnetcollectedsamplesofplanktonorganismbyverticalhauls(100-
μmmeshsize,50x50cm2opening)betweentheoceansurfacewaterand1000m
waterdepthacrossthehydrographicAzoresFrontintheeasternNorthAtlantic
(Fig.5.1,upperpanel).Ateachstation,themultinetwasdeployedtwicebetween
thesea–surfaceand1000m.Theupper100mweresampledin20mdepthintervals,
andbelow100m,at100–200–300–500–700–1000mwaterdepths.Theresultsshown
inthisstudycorrespondtotheupper300mofthestationPOS334–67(32◦59N
19◦59W)andupper100mofthestationPOS334–69(36◦59N19◦59W).Thesam-
pleswerepreservedinsolutionofsea-waterand4%offormalineandhexamethyle-
tramineuntilFebruary2007.Inthelaboratory,thesampleswerewashed,andthen
foraminiferawerepicked,driedandsievedthrougha63μmmeshbeforecount-
ing.Cytoplasm-bearingtests(livingspecimenswhencollected)werecountedsep-
aratelyfromemptytests(deadspecimens).Adetrendedcorrespondenceanalysis
(DCA,HillandGauch,1980)wasappliedtoplanktonicforaminiferalcensusdata.
DCAassumesthatspeciesabundancesaredistributedunimodallyalongsomeun-
derlyingecologicalgradient,andcorrelatesthemaingradients(axes)withgiven
variables.onmentalenvir

Rogersonomfr(Modifiedpanel)(upperAtlanticN.inculationcirsurfaceGeneral5.1FigurePOS334–69

stationstheear

ininvestigated.studythis

al.,et2004)

theofmapand

uisecrtheduringstations

POS334

(lower

panel).

POS334–67

and

:

5.2.

Material

and

methods

121

122

5.VerticaldistributionoflivingplanktonicforaminiferaintheAzoresFront

settingOceanographic5.2.2

Surface:5.2Figurecon-αophyll-chloresAzorincentrationchMarduringegionrearstationsBoth2006.theofsouthlocatedea.aroductivityprhighomfrimageSatelliteat(availableSeaWIFShttp://seadas.gsfc.nasa.gov).

Theareaofstudyischaracterizedbyasignificantmesoscaleactivity,confirmedby
theimportanceofeddiesinthebiologicalactivityoftheregion(Gonz´alezetal.,2001;
Huskinetal.,2001).TheAzoresFrontisprobablythemainmesoscalestructurein-
fluencingthedynamicsofthearea(FernandezandPingree,1996).TheAzoresFront
markstheboundarybetweentheEuropeansurfacewatermasses(coldandfresher)
andAfrican(warmerandsaltier)surfacewatermasses(Gould,1985;Schiebelet
al.,2002a),andextendsacrosstheAtlanticbetween30–40◦N.TheAzorescurrent,
whichcoincideswiththeAzoresFront,isthenorthernborderofthesubtropical
NorthAtlanticgyreandactsasacontinuouslinktothesouth-easternbranchof
GulfStreamtransportingsubtropicalwaterstowardstheIberianmargin(Kleinand
Siedler,1989;Alvesetal.,2002).Atwaterdepthsof100–500m,theNorthAtlantic
CentralWater(NACW)formsbasicallythepermanentthermocline.TheNACWst
isrelativelywarmandsaltybutpoorlyventilated.

TheAzoresFrontisthereforeanareaofstronghydrographictransition,interms
oftemperatureandwatercolumnstructure(Gould,1985;Fashametal,1985).Dur-
inghightheprsamplingoductivityarperiodea(Fig.(endof5.2).MarPrchevious2006)studiesbothrstationselatedwerechangeslocatedinthesouthplanktonofthe

methodsandMaterial5.2.

123

Figure5.3:Totalforaminferalconcentration(ind./m3)atstationsPOS334–67(32◦59N
19◦59W)andPOS334–69(36◦59N19◦59W).

assemblagesacrosstheAzoresFronttotheoverallproductivityandtothedepth
oftheDeepChlorophyllMaximum(DCM)(Fashametal,1985;Angel,1989;Fer-
nandezandPingree,1996;Schiebeletal.,2002a).Theecologicalsignatureofthe
AzoresCurrent/AzoresFrontinthesedimentaryrecordhasalreadybeenusedto
investigatethehistoryofthecurrentsystemoftheNorthAtlanticOceaninthepast
(Schiebeletal.,2002b;Rogersonetal.,2004).

124

Figure

:5.4

5.

erticalV

Relativedistribution

abundancesofof

living

planktonicplanktonic

foraminifera

foraminiferaspeciesinin

the

theesAzor

watersitePOS334–67,andrelationbetweenliving(black)anddead(gray)specimens.

ontFr

columnat

5.2.

Material

Figure5.5:

and

methods

RelativesiteandPOS334–69,

abundancesofplanktonicbetweenelationr

foraminiferadeadand(black)living

speciesinthewaterspecimens.(gray)

125

columnat

1265.VerticaldistributionoflivingplanktonicforaminiferaintheAzoresFront

Results5.3faunaforaminiferalotalT5.3.1Theverticaldistributionoftheoverallplanktonicforaminiferalabundancesvary
fromsitetosite.Inthesouthernmostsite(POS334–67)thestandingstocksoftotal
foraminiferavariedsubstantiallywithdepth.Anoverviewoftheverticaldistribu-
tionoftotalforaminiferaatbothstationsisgiveninFig.5.3.Foraminiferalstanding
stockwascomparativelylowbetween0–60m(maximumof28ind/m3),andinthe
samplingintervalof60–80mitincreasedupto120ind/m3.Below80mthecon-
centrationdecreasedagainrapidly.Incontrast,atstationPOS334–69,mostspeci-
mensweredwellingintheupper80m,wherethetotalforaminiferalconcentration
remainedrelativelyhighandunchanged,butdecreasedbelowthisdepth.

compositionassemblageForaminiferal5.3.2Theassemblagecompositionvariedwithdepth(Fig.5.4),mostnotableatthesouth-
ernsite(POS334–67).ThesouthernfaunawasdominatedbyG.calida,G.falconensis,
G.ruber,G.rubescensintheupper100m.Amongthedeep-dwellingspecies,G.hir-
sutaandG.scitulaweremostfrequent,andoccurredinhighnumbersbelow80m.
Theextraordinaryhighstandingstockof120ind/m3,at60–80mdepthatthesta-
tionPOS334–67wasduetohighnumbersjuvenilesofG.quinqueloba.Inaddition,
G.truncatulinoidesandN.pachydermaalsoincreasedtheirrelativeabundancebelow
80m.Somespecies,e.g.G.glutinatadidnotshowaclearpattern,maintainingthe
relativeabundancesrelativelyunchangedatdifferentdepths.Twomaximawere
foundforG.calidaandG.bulloides;oneatsurfaceandasecondmaximabetween
80–200mforG.calidaandbetween200–300mforG.bulloides.
Inthenorthernmostsite(POS334–69,36◦N)weonlyanalyzedthetop100m.The
foraminiferalassemblagewasmainlycomposedofthesamespeciesasinPOS334–
67,butmostofthespeciesdidnotshowabigvariabilitywithinthisdepth(Fig.5.5).
AtthisstationN.pachydermaoccurredatshallowerwaters,andtheconcentrationof
N.incomptawashighercomparedtothesouthernsite.
Inordertorecognizethedepthhabitatofeachspecies,livinganddeadspeci-
menswereidentified(Figs.5.4–5.5).Inthisway,deadspecimensthataresinking
andmayhaveadifferentdepthhabitatcanbeseparatedfromthelivingpopula-
tion.AtstationPOS334–67,livingspecimensofG.bulloidesandG.calidawerefound
atsurfaceandalsoatdeeperwaters(below100m).Incontrast,G.falconensis,G.
glutinata,G.humilis,G.ruber,G.rubescenssandG.sacculiferwererestrictedtothe
photiczone,betweensurfaceand100–130m(Huskinetal.,2004).Livingspecimens
ofG.scitula,G.truncatulinoidesandG.hirsutaweremainlyfoundbelow100min

Results5.3.

127

Figure5.6:RatiobetweenG.ruberandG.bulloidesintheannualmeanconcentrationpredicted
bytheforaminiferamodel(leftpanel)(Fraileetal.,2008)andofsurfacesediments(right
panel)(Pflaumannetal.,1996;Prelletal.,1999).Thestarsrepresentthetwostationsofthis
.study

deeperwaters,butsomelivingspecimenswerealsofoundbetweensurfaceand
m100depth.

Inthenorthernmoststation(POS334–69)livinganddeadspecimensofallspecies
werefoundateverydepth(Fig.5.5),althoughsomespeciesasG.rubescens,G.hu-
milis,G.calidaorG.falconensisdecreasedthenumberoflivingspecimenswithdepth.
Incontrast,thenumberoflivingspecimensofG.scitulaandG.hirsutaincreasedwith
depth.Ingeneral,thenorthernmoststationreflectslessvariabilityintheassemblage
depth.withcomposition

predictionModel5.3.3Wecomparedthemodelpredictionwiththelivingpopulationassemblageinorder
toidentifythephysico–chemicalconditionsinwhichtheforaminiferagrew.Due
tothefactthatweusedanon–lineardynamicmodel,inversemodelingwasnot
possible.identifiedtheInstead,siteswewheretheanalyzedmodeltheprmodeledictedaoutputsimilarformodernassemblageconditionscompositionandweto
POS334–67stationtheofthat

128

5.VerticaldistributionoflivingplanktonicforaminiferaintheAzoresFront

Foraminiferalstandingstocksoftheupper100mofoursampleswereintegrated
(approximatelycorrespondstothemixedlayerdepth),andtheratiobetweentwo
specieswascalculated.ThespeciespredictedbytheforaminiferamodelareN.pa-
chyderma(sin.),N.incompta(inthemodelnamedasN.pachyderma(dex.)),G.bulloi-
des,G.ruber(white)andG.sacculifer.InthesamplesN.incomptaandN.pachyderma
orwerderetoverycomparscarce,eandplanktonthenetmodelandsimulatesmodeldatatotalwelackfocusedofG.onthesacculiferthe.rTherelativeefore,abun-in
(33◦dancesN20◦W)betweenthetheratioremainingbetweenG.tworuberspecies:/G.G.bulloidesruberandfoundG.inourbulloides.samplesInwasPOS334–67∼4,
whereasthemodelpredictsG.ruber/G.bulloidesratioof0.4attheendofMarch(the
timewhenthesampleswerecollected)forthesamelocation.Thus,inthemodel
simulationtheabundanceofG.bulloides(andalsoofN.incompta,whichwasnearly
absentinthesamples)ishigherthanG.ruber,whereasintheplanktonnetdatawe
ruberfoundisalsohighervisibleconcentrationswhenofcomparingG.ruberthe.ThesimulatedmismatchannualbetweenmeanG.concentrationbulloidesandandG.
corbulloidese–topisdatadominant(Fig.5.6).overInG.therubermodelisshiftedsimulation,4–6◦thesouthwarborderdsofapprtheregionoximately.whereG.

Ourcenterofinterestistoanalyzewhicharethephysico–chemicalconditions
inwhichthemodelpredictstheassemblagecompositionfoundintheplankton–net
data.WeselectedthelocationswherethepredictedratebetweenG.ruberandG.
bulloidesismostsimilartothatobservedinthesample.Table5.1summarizesthe
locationswhereG.ruber/G.bulloidesratesiswithin10%oftheobservedvalue.It
alsoshowstheSSTfromWorldOceanAtlas2005(Locarnini,2006)andchlorophyll
concentrationsinthemixedlayerfromtheecosystemmodel(Mooreetal.,2002)at
thistimeoftheyear.Thetemperatureatalllocationswashigherthanatstation
POS334–67.InthoselocationswhereSSTwaswithin+2◦C(markedwith∗)ofthe
valueatPOS334–67,thechlorophyllconcentrationswaslow.Therefore,ingeneral,
themodelpredictsasimilarassemblagecompositionatwarmerand/orlowerpro-
eas.arductivity

Results5.3.

129

:5.1ableTrateLocationsasthewherobservedetheonemodelatprPOS334–67edictsa(33similar◦N2G.0◦W)ruberat/G.theendbulloidesof
march(markedwith∗:locations◦wherethetemperature
deviationdoesnotexceed+2C).

3.893

17.54

84.73

0.2295

Latitude[◦N]Longitude[◦E]G.rG.bulloidesuberTemperature[◦C]Mixed–layerdepth[m]Chl[mgChl/m3]
AprilinPOS334–67atConditions33-203.89317.5484.730.2295
outputModelJanuary23.3–21.63.5421.1189.850.27
–0.9–135.83.6425.9557.560.22
–2.6–904.0024.3025.000.16
–30–14.43.9324.1125.000.10
uaryFebr28.3-28.83.6520.19139.50.26
0–1443.8626.8841.510.120
–0.9–1443.7926.9441.610.20
–3.57.23.8828.1425.000.21
–31.9–147.63.6022.7225.000.12
chMar28.3–169.23.7918.96∗81.800.17
23.3–122.43.7119.07∗81.250.15
10.464.83.5527.9725.000.20
6.968.43.7828.8725.000.18
–3.57.23.7628.7425.000.21
–11.2–86.43.9926.3025.000.17
–20.5–903.7723.5639.100.15
–33.746.83.5123.2731.230.17
April28.3–176.43.6820.0530.510.09
6.968.43.5929.7125.000.20
–3.57.23.8128.3725.000.23
–11.2–86.43.5425.7826.840.16
–31.9363.8524.4035.560.23
May26.5–28.83.8421.5725.000.10
–4.3–79.23.9120.8625.002.81

–21.6–135.8–90–14.4-28.8–144–1447.2–147.6–169.2–122.464.868.47.2–86.4–9046.8–176.468.47.2–86.436–28.8–79.2

3.543.644.003.933.653.863.793.883.603.793.713.553.783.763.993.773.513.683.593.813.543.853.843.91

21.1125.9524.3024.1120.1926.8826.9428.1422.72∗18.96∗19.0727.9728.8728.7426.3023.5623.2720.0529.7128.3725.7824.4021.5720.86

89.8557.5625.0025.00139.541.5141.6125.0025.0081.8081.2525.0025.0025.0025.0039.1031.2330.5125.0025.0026.8435.5625.0025.00

0.270.220.160.100.260.1200.200.210.120.170.150.200.180.210.170.150.170.090.200.230.160.230.102.81pagenextonContinued

1305.VerticaldistributionoflivingplanktonicforaminiferaintheAzoresFront
Table5.1–continuedfrompreviouspage
Latitude[◦N]Longitude[◦E]G.rG.bulloidesuberTemperature[◦C]Mixed–layerdepth[m]Chl[mgChl/m3]
–6.9–79.23.6219.7025.002.23
–21.8–903.9621.9677.260.22
–31.9–39.63.5821.5061.350.26
–35.625.23.5719.7025.000.86
June–28.382.83.6220.4836.470.15
July23.3–25.23.5023.4740.360.17
–5.2–86.43.9122.0531.920.23
–10.4–86.43.8521.9743.890.23
–24.9–93.63.7020.5934.170.16
–28.303.9719.34∗25.000.14
August–0.9–1263.8824.9528.950.17
–6.986.43.9321.2837.790.22
–8.6–86.43.9121.2143.020.21
–11.203.9722.5448.810.27
–20.5–93.63.8820.9125.000.16
–28.3100.83.7118.7664.070.13
September19.2–183.5624.9025.001.03
0.9–1443.7326.0937.760.17
–13.9–93.63.6020.7086.150.21
–19.27.23.7117.71∗87.333.07
–28.3104.43.6018.81∗57.610.10
October30140.43.6025.7036.300.24
20.5–25.23.8125.4234.050.21
0–129.63.5524.0725.000.16
–0.9–97.23.6222.0825.000.17
–10.403.7521.8141.430.21
–28.3165.63.7720.9132.720.12
–28.3903.6919.20∗34.200.08
–30–1263.5620.2360.370.14
November28.3165.63.9324.8641.040.22
20.5–25.23.7324.7448.150.24
–1.7–1443.8226.3655.250.21
–5.2–903.6321.9225.000.17
–9.5–903.5121.7750.960.17
–28.3–100.83.9620.9842.270.12
pagenextonContinued

Discussion5.4.

131

Table5.1–continuedfrompreviouspage
Latitude[◦N]Longitude[◦E]G.rG.bulloidesuberTemperature[◦C]Mixed–layerdepth[m]Chl[mgChl/m3]

December30–133.23.6619.09∗
–8.6–9.5–903.63.973.8723.6322.92

74.1725.0026.86

Discussion5.45.4.1Depthhabitatofthespecies
Thetotalforaminiferalconcentrationsfoundinthisstudyaresimilartothosere-
portedbySchiebeletal.(2002b)inthesameregion.Themixedlayerdepthsduring
Aprilwere60mand85matthestationsPOS334–67andPOS334–69respectively
sity(Monterdiffereyenceandcriteria).Levitus,1997,Foraminiferalclimatologicalconcentrationmixed–layerseemstodepth,bestrbasedonglyonrtheelatedden-to
themixedlayerdepth.Atbothstations,maximumforaminiferalconcentrations
werefoundatthebaseofmixedlayer.However,thenorthernsitePOS334–69,
showedhigherforaminiferalstandingstockthroughthewatercolumn.Thiswas
probablycausedbytheproximityofthehighproductivityzoneassociatedtoAzores
Front,asreflectedbythehighchlorophyllconcentration(Fig.5.2).
DCArevealsthatthreemajorfaunalassemblagescanbeidentifiedatsitePOS334–
pr67eted(Fig.as5.7).aThegradientaxisof1,depthwhich(oraexplainsparmeteraroundwhich50%ofvariedthewithvariance,depth).canbeAccorinterd--
ingly,theshallow–waterassemblageiscomprisedbyG.tenella,G.sacculifer,G.si-
phoniphera,B.pumilio,G.inflata,T.quinqueloba,G.falconensis,G.ruber,G.rubescens
andT.humilis.Thefewlivingspecimenswefoundindeeperwatersprobablyrep-
resentsinkingindividuals.Thedeeper–dwellingassemblageincludesO.universa,
N.livepreferpachyderma,entiallyG.inscitula,deeperG.clarkeiwaters,,G.buthirsutaoccasionallyandG.theytruncatulinoidescanalso.liveTheseinshallowspecies
couldwaters.beThefewindividualslivingmigratingspecimenstoweshallowfoundinwaterstheforupperreprpartoduction.oftheThewaterthirdcolumnfau-
nalassemblageenclosesspecieswithaintermediatedepthhabitat:G.bulloides,G.
calida,N.incomptaandG.glutinata.Thesespeciesarenotrestrictedtothesurface
watersalthoughtheyhavepreferenceforit.TheDCAfromsitePOS334–69reflects
nomixedclearanddifferthereaentiationrenotinclearlyfaunalgrseparatedoups,ecologicalsuggestingthatnichesthe(Fig.upper5.8).100mHoweverare,wellthe

0.180.150.19

132

5.VerticaldistributionoflivingplanktonicforaminiferaintheAzoresFront

Figure5.7:DetrendedCorrespondenceAnalysis(DCA)atsitePOS334-67.Axis1(interpreted
asdepthexplains50%ofthevariance.Axis2corespondstootherfactorswhichalsoplaya
roleinexplainingthevariousgroups(11%ofthevariance).

analysisfromthissiteislimitedtotheupper100mandthereforethedeep–dwelling
absent.earspecies

5.4.2Comparisonbetweensamplesandmodelprediction
Atthesouthernmostsite,POS334–67(32◦59N),themodeldoesnotpredicttheob-
servedrelativeabundancesbetweenG.ruber,N.incomptaandG.bulloidesspecies.In
theplankton–netsamplestherelativeabundanceofG.ruberwashigherthanG.bu-
belloidesdueandtoaN.wrongincompta,whileparametrizationthemodeloftemperatursimulationereflectstolerancetheofG.contraryruber..ThisHowevercould,
thissituationoccursduetoquitelowconcentrationsofG.bulloidesandN.incompta

Discussion5.4.

:5.8Figure

endedDetrespondenceCorrAnalysis(DCA)atsitePOS334–69.133

ratherthanduetohighconcentrationsofG.ruber(14ind/m3intheupper100m).
Thereforeismorelikelythatthedifferencebetweenthemodeloutputandobserved
dataisduetothefactthattheecologicalnicheofG.bulloidesisoccupiedbyother
speciesnotincludedinthemodel,likeG.glutinataandG.falconensis.Thesamples
werecollectedattheendofMarch,thereforeitisprobablethathigherabundances
ofG.bulloidesoccurredlaterintheyear,sinceitgenerallyfollowsthespringalgal
bloomoftheNorthAtlantic(GanssenandKroon,2000).

1345.VerticaldistributionoflivingplanktonicforaminiferaintheAzoresFront

Conclusions5.5Plankton–netstudiesalongaN–StransectneartheAzoresFrontintheregionof
easternpositionNorthvarieswithAtlanticrdepth.evealedG.thatfalconensisliving,G.planktonicglutinata,G.humilisforaminifera,G.ruber,assemblageG.rubescenscom-
andandG.G.hirsutasacculiferprliveeferdeepmostlyinwatersthe(≥upper100m60m,depth).whileG.G.bulloidesscitula,G.andG.calidatruncatulinoideshave
preferenceforsurfacewaters,butcanalsoliveoccasionallyindeeperwaters.

Ingeneral,thesouthernmostsite(POS334–67)showsmorestratifiedstructurein
speciescomposition.DCAanalysisshowedthatatthissitethedepthcanexplain
50%ofthefaunalvariance.Incontrast,inthenorthernmostsite(POS334–69)we
foundamorehomogeneousspeciescompositionwithdepth,suggestingthatthe
frontalsystemcausesstrongmixingintheupper100m.

Mostofspeciessimulatedwithourforaminiferamodelwereabsentinthestud-
iedarea,andthestandingstocksofthosespeciesincludedinthemodelwerevery
tionlow.wasThernotefore,apossible.directItisprcomparisonobablethatbetweenspecieslikeplankton–netG.databulloidesandoccurrmodeledprlateredic-in
theyear,asthisspeciesislinktophytoplanktondynamics.Thedominantspecies
collectedextensioninofthesurfacecurrentwatermodelsamplesincludingwereG.morefalconensisspecies,G.inmayglutinataimprandoveG.thecalidamodel.An
esults.r

AcknowledgmentsIwouldliketothanktheMicropaleontologygroupintheUni-
versityofT¨ubingenforallthesupportandhelpreceivedduringmystaythere.In
particular,toProf.MichalKucera,whogavemeexcellentadvicesandmotivation
tofollowwithmywork.ThanksalsotothecrewmembersofPOSEIDON–334for
providingtheplanktonsamples.VeryspecialthanktoMargretBayerforallthe
timesheexpendedpatientlyteachingmetheidentificationofplanktonicforamini-
feraspecies.IalsowouldliketothankCatalinaGonzalez,fromtheUniversityof
Bremen,forallthehelpfulsuggestionsinmultivariateanalysis.Thisprojectwas
supportedbytheDFG(DeutscheForschungsgemeinschaft)aspartoftheEuropean
GraduateCollegue“ProxiesinEarthHistory”(EUROPROX).

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Huskin,I.,Viesca,L.andAnad´on,R.:ParticlefluxintheSubtropicalAtlanticnear
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OceanAtlas2005,Volume1:Temperature.S.Levitus,Ed.NOAAAtlasNESDIS
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Rogerson,M.,Rohling,E.J,Weaver,P.P.E.andMurray,J.W.:TheAzoresFrontsince
theLastGlacialMaximum,EarthPlanet.Sc.Lett.,222,779–789,2004.

Schiebel,R.,Waniek,J.,Zeltner,A.andAlves,M.:ImpactoftheAzoresFrontonthe
distributionofplankticforaminifers,shelledgastropodsandcoccolithophorids,
Deep–SeaRes.II,49,4035–4050,2002a.

Schiebel,R.,Schmuker,B,Alves,MandHemleben,C:TrackingtheRecentandlate
PleistoceneAzoresfrontbythedistributionofplankticforaminifers,J.Mar.Sys-
2002b.213–227,37,tems,

Watkins,J.M.,Mix,A.C.,andWilson,J.:Livingplankticforaminifera:tracersof
circulationandproductivityregimesinthecentralequatorialPacific,Deep–Sea
II,Res.1996.1257–1282,43,

6Chapter

Summary

numericalmodelforplanktonicforaminiferahasbeendesignedinorderto
Aimprovetheaccuracyofforaminifera-basedpaleotemperaturereconstruction
(chapter2).Thismodelisanon–lineardynamicmodelwhichconsideringecolog-
icalprocessescomputesthegrowthrateofthemostimportantplanktonicforami-
niferaspeciesusedinpaleoceanography:N.pachyderma(sin.anddex),G.bulloides,
G.ruber(white)andG.sacculifer.Thegrowthrateisintegratedoveraweek,and
ultimately,monthlyconcentrationofeachspeciesiscalculatedforonehypothet-
icalyear.Themodelisconstructedtoexamineforaminiferalvariabilityonlarge
spatial(global)andtemporal(monthly)timescale,anditsuseathightemporalres-
olutionisnotrecommended.Themodeldomainis,atpresent,alsorestrictedto
themixedlayer,includingonlythefirstorderparametersthatcontrolforamini-
feraldistribution(temperatureandfood).Fortheparametrization,weusedthe
climatologicaltemperaturesfromWOA98(Conkrightetal.,1998).Tosupplythe
foraminiferamodelwithecologicalinformation(foodavailability),werunthefora-
miniferamodulewithinanecosystemmodel(Mooreetal.,2002,b),whichpredicts
theabundanceofzooplanktonanddifferentgroupsofphytoplankton.Forcompat-
ibilitywiththeecosystemmodel,theforaminiferamodelcalculatesforaminiferal
abundanceofeachspeciesviacarbonbiomass.However,ourstudyisdirectedto
paleotemperaturereconstructions,andthereforeourmaininterestisinspeciesrela-
tiveabundancesandseasonalityratherthaninassessingtheabsolutebiomass.

Themodelresultshavebeencomparedtocore–top,sediment–trapandplankton–
netdata.Overall,modeledrelativeabundancepatternsaresimilartothecore–top
faunalrecord.Althoughthecomparisonbetweensimulatedannualseasonalcycle
andsediment–trapdatabearssomedifficulties(shortsamplingperiods,highinter-
annualvariabilityandlackofsediment–trapdatainopenocean),formostofthe
locationsthemodeledseasonalvariationsagreewithobservationaldata.Thecom-
parisonwithplankton–netdataintheNorthAtlantic(AzoresFront)wasnotpossi-
bleduetothefactthatthespeciesincludedinthemodelwereabsentatthistimeof
theyear(chapter5).Instead,G.calida,G.glutinataandG.falconensisweredominant
speciesatsurfacewaters.Anextensionofthecurrentmodelincludingthesespecies

140

Summary6.

mayimprovethequalityandthecapabilityofpredictionoftheforaminiferamodel.

Thismodelgivestheopportunitytoexploretheresponseofplankticforaminifer
todifferentboundaryconditions.Oneoftheproblemsthatremainsunsolvedinpa-
leoceanographyistheseasonalbiasassociatedtotheseasonalityoftheorganisms
hasusedformajorreconstrimplicationsuctions.forThisdifferpaleotemperaturentialerforaminiferaleconstrpructions.oductionProxythrroughecordstheforyeara
speciesareweightedtowardsthevaluesduringtheseasonofmaximumproduction
aforfluxthatpatterspecies.,orThemayreevencordrprepresenteservedonlyintheashortsedimenthigh–fluxmayreflectperiodtheoftheintegrationyear(e.g.of
seasonallyice–coveredregions).Usingthismodel,wedeterminedtheseasonalim-
printofplanktonicforaminiferaonthesedimentaryrecord.Theresultsrevealed
thattudes),closethetoprtheoxyuppersignalisgeographicalbiasedtowarlimitdsofsummeroccurrenceconditions;ofeachwhilespeciesat(highlowerlati-lat-
itudesthesignaloftenreflectsannualmeanconditionsorisevenbiasedtowards
.winter

Foraminiferaareknownbybeingsensitivetotemperature.Thus,iftheenvi-
ronmentalconditionsvary,foraminiferalproductioncanshiftinordertokeepin
therangeofoptimaltemperature.Oursensitivityexperimentssuggestthatundera
globalcoolingof2◦C,thegeochemicalsignalinmostofthespecieswillnotentirely
recordthetemperaturevariation,asthemonthofmaximumproductionshiftsto
awarmerseason.Thisphenomenonhasimplicationswhenreconstructingglacial
environments,asthebasicassumptionthattheseasonalityofforaminiferahasre-
mainedunchangedthroughtimemaynotbetrue.Forcingthemodelwithboundary
conditionsdifferentthanmodern,itispossibletoderiveancientseasonalities,and
isthusapowerfultooltoimproveproxycalibrations.Ofspecialinterestisthefora-
miniferaldistributionduringtheLastGlacialMaximum,whichwesimulatedusing
aglobalcoupledclimatemodel(chapter4).Ourfindingsshowthatforaminiferal
seasonalityduringtheLGMwasdifferentthanthatinmoderndays,andthatthe
maximumproductioncouldhaveshiftedbyuptosixmonths.Ithasmajorimpli-
cationsfortheinterpretationofforaminifera–basedtemperaturereconstructions,as
differencesintemperaturecouldjustbeanartifactresultingfromdifferencesinthe
calcificationseason.Theseasonalimprintintherecordedtemperatureismaximum
atmidandhighlatitudes.Instead,intropicalwaterschangesinforaminiferalcycle
donotsubstantiallyaffectthetemperaturesignal,astherecordedtemperaturerep-
conditions.meanannualesentsr

Chapter7

Conclusions

Thisstudyprovedthatmodelingplanktonicforaminiferaldistributionataglobal
scaleispossible.Usingthisforaminiferamodelweconcludethat:

•Thecorrprespondedictedwellrelativewithcore-abundancestopdata.oftheSeasonalspeciesforthevariationspresentoveralldayagreeconditionswith
sediment-traprecordsformostofthelocations,althoughthehighinterannual
variabilityinthesediment-trapdatahampersthecomparison.
•Theseasonalcycleofforaminiferahasstronginfluenceintheproxysignal
recordedintheirshells,inparticularatmiddleandhighlatitudes.Usingthis
model,theinfluenceofseasonalityintherecordedtemperature,whichcorre-
spondstotheflux-weightedannualmeantemperature,canbequantifiedat
point.grid-each•Thevaryingseasonalclimaticdistributionconditionsofoverprintingtemperature-thetrsensitiveueclimaticspeciescansignal.changeChangesunderin
seasonaldistributioninthetropicsdonotinfluencesubstantiallytheproxy
record,asthetemperaturesignalrecordedbytheshellsreflectsannualmean
es.temperatur•TheseasonalityofforaminiferahaschangedfromtheLGMtothepresentday.
DuringtheLGM,themaximumproductionofsubtropicalandhigh-latitude
foraminiferagenerallyoccurredatawarmerseasonoftheyear.Asaconse-
quence,assumingmodernseasonalityasastandardforglacialpaleotempera-
turereconstructionscouldleadtoabiasinforaminifera-basedpaleotempera-
estimates.etur•Usingthisforaminiferalmodeltopredictmaximumproductionmonthatglacial
ferentperiods,prweoxiescan(e.g.explainalkenonesdiscrvs.epanciesMg/Ca,asbetweenrsuggestedeconstrbyuctionsNiebleretbasedal.,on2003),dif-
aswellasdiscrepanciesabouttheNorthAtlanticDeepwaterformationdur-
ingtheLGMbasedonforaminiferalδ18Ovalues(Duplessyetal.,1991vs.
1995).al.,etSarnthein

142

Outlook7.1

Conclusions7.

Futureimprovementsmaybeachievedbyincludingmoreforaminiferalspecies,
asforexample,G.calida,G.glutinataandG.falconensis,whichconstituteanim-
terportantcolumnpartofofthetotalAzoresforaminiferalFrontduringfaunaMarandchwher2006.eWdominantiththeincurrtheentupperversionwa-
themodelpredictssomesituationswheretheabundancesofallfivespecies
Incrincludedeasinginthethenumbermodelarofeveryspecieslow,mayrsolveesultingthisinprdubiousoblem,randelativemayalsoabundances.mod-
ifytheresultsviainterspecificcompetition.

Dividingthespeciesindifferentgenotypescouldalsoimprovetheresults,as
differentgenotypesareoftenadaptedtodifferentenvironments.However,
somegenotypesoccurgloballywhereasothersarelimitedtospecificarea,
andtherefore,todifferentiategenotypesisnecessarytointroduceregional
parametrization.Moreover,thereareneitherclearindicationssofarwhichare
theecologicalpreferencesofeachgenotype,norisitknownwhichtypesdom-
inatewhere.Futureprogressionsinunderstandingtheadaptationsofgeno-
typesassociatedwitheachmorphospeciesarecrucialforpaleoceanography
andcouldleadtoamoreaccuratemodelprediction.

Anotherimportantissueforpaleoceanographyisthatforaminiferamigrate
verticallythroughthewatercolumnduringtheirlifecycle.Consequently
therecordedtemperaturebyshellsisconsideredtoreflectanintegrated(and
weighted)proxysignalovertheupperwatercolumndepthintervalinwhich
specimensliveandsecrettheircalcite.Thecurrentversionofthemodelis
two–dimensional,andneglectsalltheverticalstructureassumingthatthe
mixed–layerisbiologicallyhomogeneous.Extendingthecurrentmodelin
depthenablestoaccountfortheverticalstructureofthewatercolumnin-
cludingdepthhabitatofindividualspecies.Thisopensthepossibilitytostudy
themodificationofthecalcificationpatternbasedonhydrographicconditions.
Detailedinformationofdepthhabitatofthespeciesis,thus,necessaryinorder
tocontributetotheextensionofthecurrentmodel.

Bibliography

Conkright,M.,Levitus,S.,OBrien,T.,BoyerT.,Antonov,J.andStephens:
WorldOceanAtlas1998CD-ROMDataSetDocumentation,Tech.Rep.15,
NODCInternalReport,SilverSpring,MD,16pp.,1998.

Duplessy,J.C.,Labeyrie,L.,Juillet-Leclerc,A.,Maitre,F.,Duprat,J.andSarn-
thein,M.:SurfacesalinityreconstructionoftheNorthAtlanticOceanduring
theLastGlacialMaximum,OceanologicaActa,14,311-324,1991.

Moore,J.K.,Doney,S.C.,Kleypas,J.A.,Glover,D.M.,andFung,I.Y.:An
intermediatecomplexitymarineecosystemmodelfortheglobaldomain,
Deep-SeaRes.II,49,403–462,2002a.

Moore,J.K.,Doney,S.C.,Glover,D.M.,andFung,I.Y.:Ironcyclingand
nutrient-limitationpatternsinsurfacewatersoftheWorldOcean,Deep-Sea
2002b.463–507,49,II,Res.

Niebler,H.S.,Arz,H.W.,Donner,B.,Mulitza,S.,P¨atzold,J.,andWefer,
G.:duringSeathesurfacelastglacialtemperaturmaximumesinthe(23–19equatorialka),andPaleoceanographySouthAtlantic,18,Ocean1069,
2003.A000902,doi:1010.1029/2003P

Sarnthein,M.,Jansen,E.,Weinelt,M.,Arnold,M.,Duplessy,J.C.,Erlenkeuser,
L.,H.,FlatMaslin,φy,A.,M.,Johannessen,Pflaumann,U.G.,andJohannessen,Schulz,H.:T.,VJung,ariationsS.,Koc,inN.,AtlanticLabeyrie,sur-
faceyears,oceanPaleoceanographypaleoceanography,10,,50◦1063-1094,80◦N:a1995.time-slicerecordofthelast30,000

AAppendix

equationsandnotationModel

A.1Couplingbetweenecosystemandforaminifera
models

Theforaminiferamodelisincludedwithinanintermediatecomplexitymarine
ecosystemmodelfortheglobalmixedlayer(Mooreetal.,2002,b).Allcode
necessarytorunthemarineecosystemmodelandtheinputfilescanbedown-
loadedfromhttp://usjgofs.whoi.edu/mzweb/jkmoore/areadme.html.The
modeliscodedinFortran77,anditisstructuredinawaythatincludesthe
mainmoduleofglobalmixedlayergridcode,whichisthedrivingprogram
(bio−2dx3pV5.f),themainmoduleofmarineecosystemmodelcode(bio−subs−x3pV5.f)
andthenumericalcodeforimplementingthe4thorderRunge–Kuttadriver
withadaptivestepsizecontrol(numerics−subs.f).Themodelisintegrated
fortwoyearsasspinup,andthen,outputdatafromathirdyearat48equally
spacedweeklyintervalsiswrittentotheoutputfile.Attheend,monthlymean
iscalculatedandsavedasfinaloutputfile.Hightemporalresolutionisnotrec-
ommended,sincethemodelisconstructedtoexaminebiologicalvariabilityon
largespatial(non-eddyresolving)andtemporal(monthly)timescales.

Theforaminiferamodelisincludedinthebiologicalsubroutine(bio−2d−x3pV5.f),
whichcomputestimederivativesresultingfrombiologicalandphysicalpro-
cessesforasetofindependentmixedlayercellsonaglobalgrid.Forthe
parametrizationweusedthesameinputfiles,samecommonvariablesand
sameparametersasMooreetal.(2002)fortheglobalmixedlayerecosystem
model.Forthebottomboundaryconditions,effectofturbulentmixingatthe
baseofmixedlayer,entrainment–detrainmentandupwelling–downwelling
wefollowthesameprocedureastheecosystemmodel.Thus,whenverti-
calvelocityis≤0(downwellingoccurs)mixedlayerconcentrationsdonot
change,assumingthatlateraltransportofwaterwithidenticalconcentrations

146

equationsandnotationModelA.

replacesdownwelledwater.Upwellingreducesthetotalconcentrationsinthe
mixedcentration.layerTheasupwelledbehaviourofwaterbiologicalconcentrationvariablesisunderlowerthanphysicalmixedprocesseslayercon-and
thecorrespondingequationsaredescribedinbio−2d−x3pV5.f

A.2Parametersfortheforaminiferamodel

stepsizeInternallyat,theeachmodeltime–step),operatesratesappraretypicallyoximatelyinatdaily[1/day].resolution(itadjusts

A.2.1Variablesandinitialvalues
3pdCpsC0.01250.0125N.N.pachydermapachyderma(sin.)(dex.)carboncarbon[mmolC/m[mmolC/m3]]
3rubuCC0.01250.0125G.G.ruberbulloides(white)carboncarbon[mmolC/m[mmolC/m]3]
saC0.0625G.sacculifercarbon[mmolC/m3]
3lpspCC0.06250.0625LarSmallgeohytoplanktonphytoplanktoncarbon(diatom)carbon[mmolC/m][mmolC/m3]
3zodrCC0.06250.0625DetritusZooplanktoncarboncarbon[mmolC/m[mmolC/m3]]
3maxmax((CHNOL3))MaximumMaximumchlornutrientophyllconcentrationconcentration[mmolC/m[mmolC/m]3]
SSTSea–surfacetemperature[◦C]
◦minmax((SSTSST))AnnualAnnualmaximummaximumSSTSST[[◦C]C]

A.2.2Biologicalparameterscommontoallspecies

Gmax(SP)1.08Maximumforaminiferalgrowthratewhengrazingonsmallphytoplankton
Gmax(LP)1.08Maximumforaminiferalgrowthratewhengrazingonlargephytoplankton
GGmaxmax((ZDR))2.161.08MaximumMaximumforaminiferalforaminiferalgrgrowthowthrateratewhenwhengrazinggrazingonondetrituszooplankton
+grl0.060.66+halfforamlinearsaturationmortalityconstantrateforgrazing(%/day)
++GGEdenotesthe0.3samevalueportionasof(Mooregrazedetal.matter(2002a))addedtozooplanktonbiomass

.

A.2.Parametersfortheforaminiferamodel

parametersbiologicalspecificSpeciesA.2.3

147

(sin.)pachydermaN.Topt3.8optimaltemperature[◦C]
σ4.0standarddeviationofoptimaltemperature
max(SST)24maximumtoleratedtemperaturetolerated[◦C]
pl1.0∗foram.quadraticmortalityrate,tohighertrophiclevels
pspC0.3preferenceforgrazingonsmallphytoplankton[0–1]
plpC0.7preferenceforgrazingonlargephytoplankton[0–1]
pzoC0.0preferenceforgrazingonzooplankton[0–1]
pdrC0.0preferenceforgrazingondetritus[0–1]
pspC0.3preferenceforgrazingonsmallphytoplanktonwhenmainfoodsourceismissing[0–1]
plpC0.7preferenceforgrazingonlargephytoplanktonwhenmainfoodsourceismissing[0–1]
pzoC0.0preferenceforgrazingonzooplanktonwhenmainfoodsourceismissing[0–1]
pdrC0.0preferenceforgrazingondetrituswhenmainfoodsourceismissing[0–1]
clps0.0competitionexertedbyN.pachyderma(dex.)[0–1]
clbu0.0competitionexertedbyG.bulloides[0–1]
clru0.0competitionexertedbyG.ruber(white)[0–1]
clsa0.0competitionexertedbyG.sacculifer[0–1]
d0.0e–foldingconstant,whichcontrolsthesteepnessoftheMichaelis–Menton
competitionforequation(dex.)pachydermaN.Topt15.0optimaltemperature[◦C]
σ6.0standarddeviationofoptimaltemperature
max(SST)29maximumtoleratedtemperaturetolerated[◦C]
min(SST)-0.3maximumtoleratedtemperaturetolerated[◦C]
pl4.0∗foram.quadraticmortalityrate,tohighertrophiclevels
pspC0.2preferenceforgrazingonsmallphytoplankton[0–1]
plpC0.8preferenceforgrazingonlargephytoplankton[0–1]
pzoC0.0preferenceforgrazingonzooplankton[0–1]
pdrC0.0preferenceforgrazingondetritus[0–1]
pspC0.4preferenceforgrazingonsmallphytoplanktonwhenmainfoodsourceismissing[0–1]
plpC0.6preferenceforgrazingonlargephytoplanktonwhenmainfoodsourceismissing[0–1]
pzoC0.0preferenceforgrazingonzooplanktonwhenmainfoodsourceismissing[0–1]
pdrC0.0preferenceforgrazingondetrituswhenmainfoodsourceismissing[0–1]
clps0.2competitionexertedbyN.pachyderma(sin.)[0–1]
clbu0.5competitionexertedbyG.bulloides[0–1]
clru0.8competitionexertedbyG.ruber(white)[0–1]
clsa0.0competitionexertedbyG.sacculifer[0–1]
d0.05e–foldingconstant,whichcontrolsthesteepnessoftheMichaelis–Menton
competitionforequation

148

bulloidesG.12.0Topt6.0σmin(SST)-0.3∗
5.0pl0.15pspC0.45plpC0.15pCzo0.25pCdr0.2pspC0.8plpC0.0pCzo0.0pCdr0.0clps0.1clpd0.5clru0.5clsa0.5d(white)ruberG.23.5Topt4.0σmin(SST)5∗
5.0pl0.0pspC0.2plpC0.6pCzo0.2pCdr0.0pspCp0.2lpC0.6pCzo0.2pCdr0.0clps1.0clpd1.0clbu0.8clsa1.0d

equationsandnotationModelA.

optimaltemperature[◦C]
standarddeviationofoptimaltemperature
maximumtoleratedtemperaturetolerated[◦C]
foram.quadraticmortalityrate,tohighertrophiclevels
preferenceforgrazingonsmallphytoplankton[0–1]
preferenceforgrazingonlargephytoplankton[0–1]
preferenceforgrazingonzooplankton[0–1]
preferenceforgrazingondetritus[0–1]
preferenceforgrazingonsmallphytoplanktonwhenmainfoodsourceismissing[0–1]
preferenceforgrazingonlargephytoplanktonwhenmainfoodsourceismissing[0–1]
preferenceforgrazingonzooplanktonwhenmainfoodsourceismissing[0–1]
preferenceforgrazingondetrituswhenmainfoodsourceismissing[0–1]
competitionexertedbyN.pachyderma(sin.)[0–1]
competitionexertedbyN.pachyderma(dex.)[0–1]
competitionexertedbyG.ruber(white)[0–1]
competitionexertedbyG.sacculifer[0–1]
e–foldingconstant,whichcontrolsthesteepnessoftheMichaelis–Menton
competitionforequation

optimaltemperature[◦C]
standarddeviationofoptimaltemperature
maximumtoleratedtemperaturetolerated[◦C]
foram.quadraticmortalityrate,tohighertrophiclevels
preferenceforgrazingonsmallphytoplankton[0–1]
preferenceforgrazingonlargephytoplankton[0–1]
preferenceforgrazingonzooplankton[0–1]
preferenceforgrazingondetritus[0–1]
preferenceforgrazingonsmallphytoplanktonwhenmainfoodsourceismissing[0–1]
preferenceforgrazingonlargephytoplanktonwhenmainfoodsourceismissing[0–1]
preferenceforgrazingonzooplanktonwhenmainfoodsourceismissing[0–1]
preferenceforgrazingondetrituswhenmainfoodsourceismissing[0–1]
competitionexertedbyN.pachyderma(sin.)[0–1]
competitionexertedbyN.pachyderma(dex.)[0–1]
competitionexertedbyG.bulloides[0–1]
competitionexertedbyG.sacculifer[0–1]
e–foldingconstant,whichcontrolsthesteepnessoftheMichaelis–Mentonequation
competitionfor

equationsModelA.3.

149

sacculiferG.Topt28.0optimaltemperature[◦C]
σ4.0standarddeviationofoptimaltemperature
min(SST)15maximumtoleratedtemperaturetolerated[◦C]
pl4.0∗foram.quadraticmortalityrate,tohighertrophiclevels
pspC0.0preferenceforgrazingonsmallphytoplankton[0–1]
plpC0.1preferenceforgrazingonlargephytoplankton[0–1]
pzoC0.7preferenceforgrazingonzooplankton[0–1]
pdrC0.2preferenceforgrazingondetritus[0–1]
pspC0.0preferenceforgrazingonsmallphytoplanktoninexceptionallywarmwaters[0–1]
plpC0.3preferenceforgrazingonlargephytoplanktoninexceptionallywarmwaters[0–1]
pzoC0.6preferenceforgrazingonzooplanktoninexceptionallywarmwaters[0–1]
pdrC0.1preferenceforgrazingondetritusinexceptionallywarmwaters[0–1]
clps00.05competitionexertedbyN.pachyderma(sin.)[0–1]
clpd00.05competitionexertedbyN.pachyderma(dex.)[0–1]
clbu10.05competitionexertedbyG.bulloides[0–1]
clru0.8competitionexertedbyG.ruber(white)[0–1]
d1.0e–foldingconstant,whichcontrolsthesteepnessoftheMichaelis–Menton
competitionforequation∗denotesmaximumvaluewhichisreducedaccordingtothetemperaturefunctionT−func

equationsModelA.3

T−fucn=exp

pl=pl·T−func

−4000.0·

SST1.+0273.15−1.3030.15

(A.1)

(A.2)

.

150

(sin.)pachydermaN.

rate:owthGr

A.equationsandnotationModel

∂(∂tpsC)=(pspC·TGspC+plpC·TGlpC)·GGE−floss

equations:Mortality

psC=max((psC−0.01),0)

floss=pl·psC2+rl·psC

equations:Grazing

10SST−Topt2
α=σ·√2π·exp−0.5·σ
spCTGspC=Gmax(SP)·α·psC·spC+g

ClpTGlpC=Gmax(LP)·α·psC·lpC+g·0.81
CzoTGzoC=Gmax(Z)·α·psC·zoC+g·0.81
CdrTGdrC=Gmax(DR)·α·psC·drC+g·0.81

(A.3)

(A.4)

(A.5)

(A.6)(A.7)

(A.8)(A.9)(A.10)

equationsModelA.3.(dex.)pachydermaN.

rate:owthGr

∂(∂tpdC)=(pspC·TGspC+plpC·TGlpC)·GGE−floss
iflpC≤0.02:
)pdC(∂∂(t)=(pspC·TGspC+plpC·TGlpC)·GGE−floss

equations:Mortality

pdC=max((pdC−0.01),0)

151

(A.11)

(A.12)

(A.13)

floss=pl·pdC2+rl·pdC+pdC·d·clps·psC+pdC·d·clbu·buC+pdC·d·clru·ruC
psC·d+0.01buC·d+0.01ruC·d+0.01
(A.14)

equations:Grazing

21.21spC
α=15√·exp−0.5·SST−Topt
σπ2σ·spCTGspC=Gmax(SP)·α·pdC·
g+spC

ClpTGlpC=Gmax(LP)·α·pdC·lpC+g·0.81

(A.15)(A.16)

(A.17)

152

bulloidesG.

rate:owthGr

andnotationModelA.equations

Cu∂b∂t=(pspC·TGspC+plpC·TGlpC+pzoC·TGzoC+pdrC·TGdrC)·GGE−floss
(A.18)iflpC≤0.02:
)psC(∂∂(t)=(pspC·TGspC+plpC·TGlpC)·GGE−floss(A.19)

equations:Mortality

buC=max((buC−0.01),0)

(A.19)

(A.20)

floss=pl·buC2+rl·buC+buC·d·clpd·pdC+buC·d·clru·ruC+buC·d·clsa·saC
pdC·d+0.1ruC·d+0.1saC·d+0.1
(A.21)

equations:Grazing

21.251lpC
α=15√·exp−0.5·SST−Topt
σπ2σ·spCTGspC=Gmax(SP)·α·buC·
g+spC

ClpTGlpC=Gmax(LP)·α·buC·lpC+g·0.81

(A.22)(A.23)

(A.24)

A.3.equationsModel

CzoTGzoC=Gmax(Z)·α·buC·zoC+g·0.81

CdrTGdrC=Gmax(DR)·α·buC·drC+g·0.81

153

(A.25)

(A.26)

154

(white)ruberG.

owthGrrate:

equationsandnotationModelA.

)Cru(∂∂t=(plpC·TGlpC+pzoC·TGzoC+pdrC·TGdrC)·GGE·nutm·chlm−floss
(A.27)

equations:Mortality

ruC=max((ruC−0.01),0)

(A.28)

floss=pl·ruC2+rl·ruC+ruC·d·clpd·pdC+ruC·d·clbu·buC+ruC·d·clsa·saC
pdC·d+0.01buC·d+0.01saC·d+0.01
(A.29)

equations:Grazing

10SST−Topt2
α=σ·√2π·exp−0.5·σ
spCTGspC=Gmax(SP)·α·ruC·spC+g

ClpTGlpC=Gmax(LP)·α·ruC·lpC+g·0.81
CzoTGzoC=Gmax(Z)·α·ruC·zoC+g·0.81

(A.30)(A.31)

(A.32)(A.33)

equationsModelA.3.

CdrTGdrC=Gmax(DR)·α·ruC·drC+g·0.81

max(NO3)
nutm=3·0.5−0.25·tanh1.2−2·2+0.006

chlm=0.5−0.25·tanhmax(CHL)−1.7·2+0.006
37.0

sacculiferG.

rate:owthGr

155

(A.34)

(A.35)

(A.36)

)saC(∂∂t=(plpC·TGlpC+pzoC·TGzoC+pdrC·TGdrC)·GGE·chlm−floss(A.37)
ifmin(SST)≥26:
)psC(∂∂(t)=(plpC·TGlpC+pzoC·TGzoC+pdrC·TGdrC)·GGE−floss(A.38)

equations:Mortality

saC=max((saC−0.01),0)

(A.39)

floss=pl·saC2+rl·saC+saC·d·clbu·buC+saC·d·clru·ruC(A.40)
buC·d+0.01ruC·d+0.01

156

Grazingequations:

equationsandnotationModelA.

10TSSTopt−20.15
α=√·exp−0.5·
σσπ2·

TGspC=Gmax(SP)·α·saC·spCspC+g

ClpTGlpC=Gmax(LP)·α·saC·lpC+g·0.81

CzoTGzoC=Gmax(Z)·α·saC·zoC+g·0.81

CdrTGdrC=Gmax(DR)·α·saC·drC+g·0.81

chlm=0.5−0.25·tanhmax(CHL)−1.7·2+0.006
37.0

(A.41)

(A.42)

(A.43)

(A.44)

(A.45)

(A.46)

e,Moor

J.K.,Doney,S.C.,

Kleypas,

A.,J.

,Glover

Bibliography

D.M.,andFung,I.Y.:An

intermediatecomplexitymarineecosystemmodelfortheglobaldomain.

Deep–SeaRes.II,49,403–462,2002a.

Moore,J.K.,Doney,S.C.,Glover,D.M.,andFung,I.Y.:Ironcyclingand

nutrient-limitationpatternsinsurfacewatersoftheWorldOcean,Deep-Sea

2002b.463–507,49,II,Res.