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Evolution in an acidifying ocean Jennifer M. Sunday 1,2 , Piero Calosi 3 , Sam Dupont 4 , Philip L. Munday 5,6 , Jonathon H. Stillman 7,8 , and Thorsten B.H. Reusch 9 1 Department of Biological Sciences, Simon Fraser University, Burnaby, British Columbia, V5A 1S6, Canada 2 Biodiversity Research Centre, University of British Columbia, Vancouver, British Columbia, V6T 1Z4, Canada 3 Marine Biology and Ecology Research Centre, School of Marine Science and Engine
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  Evolution   inanacidifying   ocean JenniferM.Sunday 1,2 ,PieroCalosi 3 ,SamDupont 4 ,PhilipL.Munday 5,6 ,JonathonH.Stillman 7,8 ,andThorstenB.H.Reusch 9 1 Department   of    Biological   Sciences,   Simon   Fraser   University,   Burnaby,   British   Columbia,   V5A   1S6,   Canada 2 Biodiversity   Research   Centre,   University   of    British   Columbia,   Vancouver,   British   Columbia,   V6T   1Z4,   Canada 3 Marine   Biology   and   Ecology   Research   Centre,   School   of    Marine   Science   and   Engineering,   Plymouth   University,   Drake   Circus,Plymouth   PL4   8AA,   UK 4 Department   of    Biological   and   Environmental   Sciences,   University   of    Gothenburg,   The   Sven   Love´n   Centre   for   Marine   Sciences,Kristineberg,   45178,   Fiskeba ¨ckskil,   Sweden 5 ARC   Centre   of    Excellence   for   Coral   Reef    Studies,   James   Cook   University,   Townsville,   Queensland   4811,   Australia 6 School   of    Marine   and   Tropical   Biology,   James   Cook   University,   Townsville,   Queensland   4811,   Australia 7 Romberg   Tiburon   Center   and   Department   of    Biology,   San   Francisco   State   University,   Tiburon,   CA   94920,   USA 8 Department   of    Integrative   Biology,   University   of    California   Berkeley,   Valley   Life   Sciences   Building,   Berkeley,   CA   94720,   USA 9 GEOMAR   Helmholtz   Centre   for   Ocean   Research   Kiel,   Evolutionary   Ecology   of    Marine   Fishes,   Du ¨sternbrooker   Weg   20,   D-24105Kiel,Germany Ocean   acidification   poses   a   global   threat   to   biodiversity,yet   species   might   have   the   capacity   to   adapt   throughevolutionary   change.   Here   we   summarize   tools   availabletodetermine   species’   capacity   for   evolutionary   adapta-tion   to   future   ocean   change   and   review   the   progressmade   to   date   with   respect   to   ocean   acidification.   Wefocus   on   two   key   approaches:   measuring   standing   ge-netic   variation   within   populations   and   experimentalevolution.   We   highlight   benefits   and   challenges   of   eachapproach   and   recommend   future   research   directions   forunderstanding   the   modulating   role   of   evolution   in   achanging   ocean.Bringing   evolution   into   the   forecast   of   an   acidifiedocean Theocean   environmentis   changingrapidly,   with   surfacewaterschangingintemperatureandacidityatgeologi-callyunprecedentedrates   [1].   Projecting    thefate   of    ma-rinebiodiversity    requires   notonlyunderstanding    howthese   changes   willaffectpopulations,   butalso   how   popu-lations   willrespond    viaacclimationand   adaptive   evolu-tion   (Box1).    A    globalresearcheffortis   underwaytounderstandthepotentialimpactsof    globalchange   onspecies’   physiologyandoverall   fitness   andto   considerthebroaderimpactsfor   biodiversity,ecosystem   function,andecosystemservices,including    food   security    [2].    Yetmost   experiments   assessphenotypicresponses   inrela-tivelyshort-term,single-generation,   experimentsunderfutureoceanconditionsprojected   to   occur   within100–200years,   andfallshort   ofconsidering    thepotential   forevolutionaryadaptation[3].Ocean   acidification–   the   increasein   partial   pressure   of CO 2  (    p CO 2 )andreduction   in   pH   associated   withuptakeof fossil   fuel-derived   CO 2  fromtheatmosphere   –   profoundly alters   theinorganicconditions   of    theoceans.    Althoughincreased  p CO 2  canenhancephotosynthesis   andgrowthofphotoautotrophic   organisms,ocean   acidificationis   astressor   for   many    organisms(i.e.,decreasesfitness,reviewedin   [4]).   Because   spatial   gradients   in    p CO 2  arerelativelylow   and   unstructured   relative   to   thetemporalchange   predicted   [5],   species   arelesslikelyto   find   refugethroughmigration   (ashasbeen   observedacrossthermalgradients   [6]).   Evolutionary    adaptation   couldhence   be   aparticularlyimportant   response   to   thiswidespread   change. Although   the   possibility    for   evolutionary    adaptation   toocean   acidification   is   increasingly    recognized   [7–9],thefield   is   at   a   nascent   stage.   Here   we   summarize   approachesthat   can   be   used   to   address   the   potential   for   evolutionary adaptation   in   order   to   guide   future   work    with   an   evolu-tionary    focus.    Although   we   use   ocean   acidification   as   a   casestudy,   the   methods   reviewed   are   equally    applicable   toother   aspects   of    ocean   change   and   we   highlight   the   utility ofconsidering    multiple   drivers   simultaneously    (see   [10]and[11]   for   reviews   that   focus   on   broader   aspects   of    oceanchange).   We   first   review   two   key    methodologies   for   asses-sing    the   potential   for   future   adaptation:   measuring    stand-inggenetic    variation   inclimate-sensitive   traits   andconducting    evolution   experiments   in   real   time.   We   nextconsider   how   past   adaptation   can   be   inferred   from   com-parisons   across   space   and   time.   We   discuss   the   limitationsof    these   methodologies,   consider   how   these   data   will   beuseful   for   understanding    the   fate   of    marine   biodiversity andthe   potential   emergent   changes   in   ecosystem   function,and   highlight   the   most   promising    paths   toward   that   un-derstanding. Measuring   standing   genetic   diversity   in   response   traits Using    quantitative    genetics  Present-day    populations   might   harbour   phenotypic    varia-tion   in   responses   to   ocean   acidification.   The   extent   to   whichthis    variation   has   a   heritable,   genetic   basis   can   indicate Review 0169-5347/$–seefrontmatter  2013ElsevierLtd.Allrightsreserved.http://dx.doi.org/10.1016/j.tree.2013.11.001 Correspondingauthor: Sunday,J.M.(sunday@zoology.ubc.ca).  Keywords: oceanacidification;climatechange;evolutionarypotential;adaptation;quantitativegenetics;experimentalevolution. TrendsinEcology&Evolution,February2014,Vol.29,No.2 117  the   potential   for   an   evolutionary    response   [12].Quantita-tive   genetics   approaches   use   comparisons   among    relativeswith   known   genetic   relatedness   to   partition   observed   phe-notypic    variance   into   their   environmental   and   geneticcomponents   [13].The   advantage   of    these   methods   is   thatthey    can   be   applied   to   a   range   of    organisms   withoutrequiring    prior   molecular   genetic   information   and   they can   focus   directly    on   fitness   traits   with   no   need   to   identify the   specific   genes   involved.Quantitativegeneticsapproacheshave   beenused   in   ahandfulof    oceanacidificationstudies.   These   focuseitheron variationinacidification-sensitive   phenotypes   in   theelevat-ed    p CO 2  condition   or   on    variationinreactionnorms   of phenotypes   across   present   and   futureocean   conditions(identifying    a   genotype-by-environment   interaction,seeFigure   1 A).The   use   of    clonalorganismsprovides   thesim-plest   study    design.   Becauseall    variationwithinclonedindividuals   is   assumed   tobe   environmental,heritability  Box   1.   Acclimation   or   adaptation? Organismsmightbeabletomaintaintheirperformanceinafutureacidifiedoceanthroughacclimationoradaptation.Acclimation(heremeaningbothnaturalacclimatizationandlaboratory-basedacclima-tion sensu  [71])   involvesphenotypicallyplasticresponsesinphysiol-ogy,morphology,orbehaviourthatcanhelpmaintainfitnessinanewenvironment.Bycontrast,adaptationinvolvesselectionongeneticvariationthatshiftstheaveragephenotypetowardthefitnesspeak.Underacclimation,wemightobservenodifferenceinatraitresponseofinterestbetweenenvironmentsbecauseofplasticityinunderlyingprocesses,called‘phenotypicbuffering’[72,73].   Forexample,anorganismmightmaintainasimilargrowthrateinacidifiedconditionscomparedwithcurrent-daycontrolsbecauseofplasticityinmetabolicprocessesthat   supportgrowth(FigureI).Acclimationiscategorizedintothreetypes:reversible,develop-mental,andtransgenerational(FigureIB).Reversibleacclimationoccursoverdaystomonths,oftenwithinalifestage[71],suchasphysiologicaladjustmenttoseasonalchange[74].Developmentalacclimationoccurswhenexposuretoanovelenvironmentearlyinlifeenhancesperformanceinthatenvironmentlaterinlife[75].Transge-nerationalacclimationoccurswhentheenvironmentexperiencedbyparentsinfluencestheperformanceofoffspringinthesameenviron-mentthroughnutritional,somatic,cytoplasmic,orepigenetictransferbetweengenerations[76].Thiscanprimeoffspringforimprovedperformanceinastressfulenvironment[77](FigureIC).   Consequently,itmighttaketwogenerationsforthefullextentofenvironmentalacclimationtobeexpressed.Allforms   ofacclimationcaninteractwithgeneticadaptation.Acclimationcanbufferpopulationsagainstimmediateimpactsof oceanacidificationandprovidetimefor   adaptationtocatchup[20],whichcouldbeespecially   importantfororganismswith   longgenerationtimes.However,acclimationcouldalsoretardgeneticadaptationbyshiftingthemeanphenotypeclosertothefitnesspeak,weakeningtheselectiongradient,withoutchangingallelicfrequen-cies.Acclimationcanalsocomeatacost.Forexample,maintenanceofionbalanceinacidifiedconditionscandivertenergyfromotheractivities[78,79].   Suchacostcaninfluenceadaptiveresponsesinanenvironment-specificmanner(e.g.,energeticcostsmightnotmatterif foodavailabilityishigh).Finally,acclimationmightenhancegeneticadaptationifthenewphenotypeisfavourablyselected(geneticassimilation[80]),althoughtheoccurrenceofthisprocessremainshighlyuncertain.Bothacclimationandadaptationcanhelporganismspersistinthefaceofenvironmentalchangeandunderstandingthelinksbetweentheseprocesseswillbecriticalforpredictingevolu-tionaryresponsestooceanacidification. 8.08.28.48.68.89.09.29.4low   low   mod   highlow   high   mod   highParent environment:Offspring environment:Reversible Transgeneraonal Developmental    T   r   a   i   t   v   a    l   u   e Phenotypic bufferingSelecon in a populaon    M   e   a   n   t   r   a   i   t   v   a    l   u   e Observedfunconalphenotype Underlyingmechanism    G   e   n   e   e   x   p   r   e   s   s   i   o   n    l   e   v   e    l ,   m   o   r   p    h   o    l   o   g   i   c   a    l   c    h   a   n   g   e ,   e   n   e   r   g   y   a    l    l   o   c   a      o   n  p CO 2  p CO 2  p CO 2    p CO 2    F   r   e   q   u   e   n   c   y   o    f      p    C   O    2   -   t   o   l   e   r   a   n   t   i   n   d   i   v   i   d   u   a   l   s 2 (A)    O    ff   s   p   r   i   n   g    l   e   n   g   t    h    (   m   m    ) (C)(B) TRENDS in Ecology & Evolution FigureI .( A )TwoprocessesbywhichafunctionalphenotypemightbesimilaracrosspartialpressureofCO 2  (   p  CO 2 )treatmentsdespiteunderlyingmechanisticchanges.Left:ifphenotypicplasticityexists,wemightobservenochangeina   functionalphenotypeofinterestdespiteunderlyingchangesingeneexpression,morphologicalchange,orenergyallocation.Right:inexperimentsusingpopulationsofindividuals,mortalityselectionremoving p  CO 2 -intolerantphenotypesathigh p  CO 2  treatmentscanleadtonomeanfunctionaltraitresponsedespiteunderlyingchangesinphenotypicfrequencies(e.g.,[26]).   ( B )Threecategoriesofacclimation.( C )Theeffectofparentalenvironmentonstandardlengthofjuvenileanemonefishexposedtolow,medium,andhigh p  CO 2  [77].   Thenegativeeffectof  p  CO 2  onoffspringlengthwaserasedwhenbothparentsandoffspringwererearedathigher p  CO 2  levels,showingtransgenerationalacclimation. Review  Trends    in    Ecology    &   Evolution    February   2014,   Vol.   29,   No.   2 118  in   thebroadsense   (  H  2 ,   see   below)canbe   estimated   by partitioningvariancewithin   and   between   clones[13].   Inthe   bryozoan Celleporella   hyalina ,theresponse   ofcolony growth   rate,   reproductive   investment,   andcolony    conditiontoelevated  p CO 2  and   temperature   differedacrossclones,demonstrating    that   heritablevariationexists   in   fitness-related   traitsinfluencedby    oceanacidification,oceanwarm-ing,   and   theirinteraction[14].   Clonal   strains   ofthecocco-lithophore  Emiliania   huxleyi   [15]collectedfromdifferentregions   and   grown   in   a   common   environment   differedintheirgrowth   rateand   carboncontentresponses   to   elevated  p CO 2 .   Likewise,   fitness,photosynthesis,   carboncontent,andsize   responses   differedamong    isolated   ecotypesofthepico-plankton   Ostreococcustauri   [16].   These   clonalstudiesdem-onstrate   theexistence   of    heritabilityfor  p CO 2 -relatedtraits,but   onlyin   thebroadsense,meaning    theyincludeheritableplastic,   epigenetic,   or   geneticcomponentsof     variationin  p CO 2  responses.Neverthelesstheysuggest   that   lineageswith   less   adverse   responses   (orgreaterpositive   responses)will   increaseinfrequency,at   leastin   theshortterm   [16].In   non-clonal   organisms,   single-generation   breeding designs   and   parent–offspring    comparisons   can   be   usedto   estimate   additive   genetic    variance   ( h  2 ),   the    variancecomponent   that   can   readily    respond   to   selection   (variancedue   to   heritable,   genetic    variation   that   is   additive   innature)   [13].Factorial   breeding    designs   are   particularly useful   for   broadcast-spawning    species   in   which   both   maleand   female   gametes   can   be   isolated   (Figure1)and   allowadditive   genetic    variance,   maternal   effects,   and   narrow-sense   heritability    (i.e.,   the   proportion   of    phenotypic    vari-ance   that   is   additive   genetic,   denoted   h 2 )to   be   estimated[13].Using    factorial   breeding    designs,   the   size   of    early pluteus   larvae   in   sea   urchins   at   elevated    p CO 2  was   shownto   have   high   heritability    in    Strongylocentrotus    purpuratus ( h 2 =   0.5   [17]),but   lower   heritability    in    Strongylocentrotus franciscanus   ( h 2 =   0.09   [18]).Interestingly,   there   weresimilar   levels   of    additive   genetic    variation   for   larval   lengthin   these   two   studies   (350   and   248   m m,   respectively),   indi-catingthat   differences   in   the   heritability    estimates   werepossibly    driven   by    differences   in   phenotypic    variance,   afeature   that   can   differ   according    to   experimental   condi-tions   [17].By    contrast,   inlarvae   ofthe   mussel    Mytilustrossulus ,   there   was   additive   genetic    variance   for   larvalsize   at   low    p CO 2 ,   but   none   detected   at   high    p CO 2 and   henceadiminishing    scope   for   an   evolutionary    response   [18]. Although   the   sea   urchin   Centrostephanus   rodgersii   didnot   show   significant   genetic    variation   for   gastrulationsuccess   with    varying     p CO 2  treatments,   there   was   genetic variation   at    varying    temperatures   and   a   significant   geneticcorrelation   between   the   two   responses,   indicating    a   poten-tial   for   correlated   responses   to   selection   imposed   by    thetwo   stressors   [19]   (Box2).In   all   ofthese   examples,   much   of the   observed    variation   was   attributed   to   maternal   effectsat   high-   and   low-  p CO 2  conditions,   indicating    differencesin   maternal   provisioning    that   are   expected   at   early    em-bryonic   stages. Control  p CO 2 Future  p CO 2 Meanfitnessby sire (A) (B) Test for adaptaonCorrelated responseAncestralpopulaonPopulaonsizeReplicaonSeleconenvironmentControlenvironment n  generaons of experimental evoluon Assayexperiment 1Assay experiment 2... m    F   i   t   n   e   s   s CorrelatedresponseTest foradaptaon TRENDS in Ecology & Evolution Figure1 .   ( A )Illustrationofafactorialfertilizationcrosswithablockeddesigntoestimatestandinggeneticvariationusingninedamsandsires.Insetshowsidealizeddatashowingmeanresponsesbyindividualsire.PhenotypicvariationinexperimentalpartialpressureofCO 2  (   p  CO 2 )   conditions(heightofpointsingreybox)orvariationinphenotypereactionnormsbetweencontrolandexperimental p  CO 2  conditions(slopeofresponsecurvesininset)canbeattributedtosireeffects,dameffects,sire  daminteractioneffects,andcultureeffects.Usingthesiremodel[13],additivegeneticvariationisderivedfromthesireeffectsandmaternaleffectsarederivedfromthedifferencebetweensireanddameffects.( B )Importantelementsofanexperimentalevolutionexperiment.Criticalstepsarethechoiceoftheancestralorbasepopulationwithitsinitialgeneticdiversity,thenumberandpopulationsizeoftheindependentlyevolvingpopulationreplicates,thenumberofgenerationsofexperimentalevolution,andthechoiceoftheselectiontreatment,alwayscomparedwitha   laboratoryselectioncontrol.Thecriticaltestforadaptationisconductedviaareciprocalassayexperimentinwhichselectionandcontroltreatmentsareexposedtobothconditionsafterappropriateacclimation.Thefull-factorialassayexperimentshavetoberepeatedoverthecourseoftheexperiment.Thehypotheticalbardiagramindicatestheevolutionaryadaptationoftheadaptedpopulationsaswellasadeclineoffitnessduetotrade-offswhenexposingadaptedlinesbacktotheancestralconditions. Review  Trends    in    Ecology    &   Evolution    February   2014,   Vol.   29,   No.   2 119   Although   these   studies   demonstrate   the   advantage   of using    breeding    designs   to   estimate   heritable    variation,theyeach   focused   on   growth   during    early    development,thefitness   consequences   of    which   are   difficult   to   ascertain.Estimating    evolutionary    potential   requires   knowledge   of genetic    variance   as   well   as   the   strength   of    selection   towarda   fitness   optimum   [20].Future   work    must   focus   on   surviv-al,reproduction,   or   other   ecologically    important   traitsaffecting    population   growth   to   improve   the   utility    of    quan-titative   genetics   studies,   so   that   selection   responses   can   bebetter   estimated. Using    genomics    to    identify    pCO  2  -responsive    loci  Recent   advances   in   next-generation   DNA    sequencing    havemade   it   possible   and   cost-effective   to   develop   genome-scaledata   that   can   be   useful   toward   identifying    standing    genetic variation   at   multiple   loci   responsive   to    p CO 2  change.Transcriptomics   profiles   have   been   useful   for   identifying genes   that    vary    in   gene   expression   levels   in   future   oceanenvironments,   indicating    a   plastic   response   at   a   cellularlevel   (e.g.,   [21,22]).However,   to   show   a   potential   for   evolu-tionary    adaptation,   heritable    variation   in   expression   levelresponses   or   allelic    variation   in   the   coding    genes   them-selves   must   be   demonstrated   [23].Oncesuch   lociareidentified,   itwillbecritical   to   relategenetic    variation   directlyto   fitness   [24,25].This   wasrecentlyachieved   ina   studyof     S.purpuratus   urchinlarvaeinwhichallelefrequencieschangeddifferentially over7   daysina   high-versuslow-  p CO 2 regime,   suggesting allele-specific   survival[26].   Thechanges   inthehigh-  p CO 2 treatmentoccurred   atlociof    known   functional   proteinclasses.   Furthermore,   amongthose   genes   related   tobiomineralization,lipidmetabolism,   andion   homeostasis,survivingalleles   hadgreater-than-expecteddifferences   ataminoacid-changingnucleotide   sites   compared   withthesrcinalpool,supportingtheinterpretation   that   selectionactedonfunctional   proteins.   These   underlying    allelicchanges   occurred   despite   little   changeindevelopmentandmorphology    betweenthe   high   andlow   treatments,suggesting    thattheunderlyingpopulationgeneticchangewas   responsiblefor   thepopulationresilienceobserved(Box   1). Althoughsequencing    projects   remainsimplest   in   mod-el   organisms   withexistinggenomicdata(Box3),recentbioinformaticsadvancesarefacilitatingtheuseof    next-generation   sequencinginnon-modelorganisms,opening use   of    thistechnology    for   a   broaderscope   of    organisms[27]. Box   2.   Correlated   traits   and   fitness   trade-offs Genetic   correlations   amongtraitsmightincrease[81]ordecrease[82,83]therateofadaptiveevolution,dependingonwhethertheyarepositivelyor   negativelycorrelated   withrespect   to   thefitnesslandscape(FigureIIA,B).Thebasisfor   suchcorrelationscan   begenetic   pleiotropy(singlegenes   conferringmultipletraits)   orlinkagedisequilibrium(non-randomassociationofalleles   atdifferentloci)[84,85],suchthatselectionononetraitwill   elicit   aresponseinanother   inthedirection   of    thecorrelation   (e.g.,   [86]).Ifthecorrelationexistsbecause   ofgene   linkage,it   canbebrokenupbyrecombination[87].IntheSydneyrockoyster,tenyearsofartificialselectionforfastergrowthanddiseaseresistanceinadvertentlyresultedinincreasedresilienceto p  CO 2  stress[88].Thissuggestsapositivegeneticcorrelationbetweengrowthordiseaseresistanceunderambientconditionsandgrowthrateresponsesto p  CO 2  [88].Likewise,indevelopingseaurchinlarvae,genotypesthatperformedwellinhightemperaturesalsoperformedwellatlowpH[89],whichshouldacceleratetherateofevolution(FigureIIB).Theadaptive   landscape   itselfmightleadtounexpectedresponses   toselectionbecauseoffitnesstrade-offs.For   example,   greater   survivalunder   ocean   acidificationmightoccur   atacost   toreproductive   output,toperformanceofother   life-historystages,ortofitnesswhenmultipledriversareconsidered   (e.g.,warming,anoxia,predation,competition;FigureIIC).   Recentevidenceshowingthat   p  CO 2  resilienceincalcifierscomesat   ametaboliccost   [19,90]suggestsenergyallocation   trade-offsbetween p  CO 2  resilienceand   otherenergeticallymaintainedfitnesstraits.Manytaxa(butnot   all)alsoshownegativesynergistic   responsestoacidificationand   warming(reviewedin[50,51]).Thissuggestsacommon,nonlinearphysiologicalmechanism   linkingan   organism’sresponsetoeither   anenvironmentaldriver,   such   asmutualeffectsonaerobicscope[85,91],orapreviousfitness   trade-off    intoleratingbothvariables,such   thatfewindividualshave   cotolerance   [92].   There   isalsoevidencethat   greaterresilienceto p  CO 2  comesatacompetitivecost.Intwospeciesofmarinemicroalga,slow-growingstrainshadgreaterresilienceto p  CO 2  thanfast-growingstrains[93],suggesting   thatselectionforfast   growth,andhence   competitiveabilityinphytoplank-ton,mightcounterselectionfor   p  CO 2  resilience(FigureIIC).   Wherepossible,understanding   the   physiologicalmechanisms   of  p  CO 2 responseswillhelpinanticipatinggeneticcorrelationsandfitnesstrade-offs. +  p CO 2  tolerance    T   e   m   p   e   r   a   t   u   r   e   t   o    l   e   r   a   n   c   e +  p CO 2  tolerance    T   e   m   p   e   r   a   t   u   r   e   t   o    l   e   r   a   n   c   e    p CO 2  tolerance +    C   o   m   p   e         v   e   a    b   i    l   i   t   y (A)   (B)   (C) TRENDS in Ecology & Evolution FigureII .Geneticvarianceandfitnesslandscapesacrosstwophenotypicdimensions.Colouredlinesshowisoplethsinthefitnesslandscapeleadinguptoalocalmaximum(+),blackdotsandgreyregionsshowmeanandvariationin2Dphenotypebeforeselection,arrowsshowdirectionofselection,andbrokenlinesshowdirectionofmaximalgeneticvariance.Apositivegeneticcorrelationbetweentwotraits[e.g.,partialpressureofCO 2  ( p  CO 2 )   toleranceandtemperaturetolerance]willaccelerateadaptiveevolution( A ),whereasanegativegeneticcorrelationwillslowadaptiveevolution( B ).Evenwithoutgeneticcorrelations,fitnesstrade-offs,suchasbetween p  CO 2  toleranceandcompetitiveability,canconstrainevolutionalongamaximalfitnessridge( C ). Review  Trends    in    Ecology    &   Evolution    February   2014,   Vol.   29,   No.   2 120
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