Novel methodological approaches in loess research ...Fig. 3: Principle of bulk TC/EA-IRMS δD and...

170 E&G / Vol. 60 / No. 1 / 2011 / 170–187 / DOI 10.3285/eg.60.1.12 / © Authors / Creative Commons Attribution License

E&G Quaternary Science Journal Volume 60 / Number 1 / 2011 / 170–187 / DOI 10.3285/eg.60.1.12

www.quaternary-science.net

GEOZON SCIENCE MEDIA

ISSN 0424-7116

Novel methodological approaches in loess research – interrogating biomarkers and compound-specific stable isotopes

Michael Zech, Roland Zech, Björn Buggle, Ludwig Zöller

Abstract: Loess-paleosolsequencesareuniqueterrestrialarchivesforthereconstructionofQuaternarylandscapeandclimatehistory.Thedevelopmentofnovel,morequantitativepaleoclimateproxiesmayinitiateaneweraofloessresearchoverthenextdecade.Thisreviewpaperpresentstheprinciples,analyticalbackgrounds,andfirstapplicationsofsomeofthesenewproxiesthatarecurrentlybeingdeveloped.Wediscuss the potential of (i) n-alkanes as plant leafwax-derivedbiomarkers for reconstructingvegetationhistory,(ii)aminoacidracemizationandglyceroldialkylglyceroltetraether(GDGT)indicesasproxiesforreconstructingpaleo-temperatureand(iii)compound-specificδDandδ18Oanalyzesofplant-derivedn-alkanesandmonosaccharides,respectively,asproxiesforreconstructingpaleoclimate/-aridity.Whilewewanttoinspirethereadershipabouttheexcitingmethodologicalandanalyticaldevelopmentsandtheirpotentialforloessresearch,thecurrentlimitationsandshortcomingsofeachproxyshouldnotbeoverlooked.Degradationeffectsandpossiblepost-depositional’contamination’,forexample,needtobeconsideredwheninterpret-ingbiomarkerrecords,andthedeconvolutionofvaryingfactorsinfluencingtheisotopicsignalscanbechallenging.

[Neue methodische Ansätze in der Lössforschung – Biomarker- und substanzspezifische Stabilisotopen-Analytik]

Kurzfassung: Löss-PaläobodenSequenzensindwichtige terrestrischeArchive fürdieRekonstruktionderquartärenLandschafts-undKlima-geschichte.DieEntwicklungneuer,quantitativererPaläoklima-Proxieskönnte indenkommendenJahreneineneueÄra inderLössforschungeinleiten.DieserReview-ArtikelstelltdiePrinzipien,diezugrundeliegendeAnalytik,understeAnwendungsbei-spielefüreinigedieserProxiesvor,welchederzeitentwickeltwerden.WirdiskutierendasPotentialvon(i)pflanzenwachsbürtigenn-AlkanenalsBiomarkerfürdieRekonstruktionderVegetationsgeschichte,(ii)AminosäureRazemisierungundGlycerin-Dialkyl-Glycerin-Tetraether(GDGT)IndizesalsProxiesfürdieRekonstruktionderPaläotemperaturund(iii)substanzspezifischenδD and δ18O Analysenanpflanzenbürtigenn-Alkanenbzw.ZuckernfürdieEntwicklungvonProxieszurRekonstruktionvonPaläoklima/-aridität.Währendwirversuchen,dieLeserschaftfürdiemethodischenundanalytischenNeuentwicklungenundderenPotentialfürdieLössforschungzubegeistern,verweisenwirgleichzeitigauchaufdieLimitierungenundSchwächenderjeweiligenMethoden.SomüssenbeispielsweiseDegradationseffekteoderpostsedimentäre ‚Kontamination’beider InterpretationvonBiomarker-Re-kordsberücksichtigtundweiteruntersuchtwerden.DesWeiterenkönntesichdieQuantifizierungderunterschiedlichenEinfluss-faktorenaufDeuterium-und18O-Rekordsalsherausfordernderweisen.

Keywords: Loess, paleoenvironment, paleoclimate, biomarker, molecular fossil, n-alkane, glycerol dialkyl glycerol tetraether, amino acid ra-cemization, sugar, stable isotope, δD, δ18O

Addresses of authors: M. Zech*,#,L. Zöller,ChairofGeomorphology,UniversityofBayreuth,Universitätsstr.30,95440Bayreuth,Germany.E-Mail:[email protected];M. Zech, B. Buggle,DepartmentofSoilPhysics,UniversityofBayreuth,Universitätsstr.30,95440Bay-reuth,Germany.M. Zech, B. Buggle,DepartmentofTerrestrialBiogeochemistry,Martin-LutherUniversityHalle-Wittenberg,Weidenplan14,D-06120Halle,Germany. R. Zech#,GeologicalInstitute,BrownUniversity,324BrookStreet,ProvidenceRI02912,USA.R. Zechnowat:GeologicalInstitute,ETHZurich,Sonneggstr.5,8092Zurich,Switzerland.#these authors contributed equally to this manuscript. *corresponding author

1 Introduction

Oceansedimentsandpolaricecoreshaveprovidedinvalu-able insights into the climate system, its natural variabil-ity, forcings and mechanisms over the last few decades.However, it is the terrestrial, non-polar regions that pro-videmostoftheecosystemservicesthatwedependon.Inview of global warming and the anticipated negative ef-fects for ecosystems and economies, increasing scientificeffortsshouldfocusonreconstructingpastclimateanden-vironmental conditions on land.We need a profound un-derstanding of climate change-induced geomorphologicalprocessesandecologicalconsequences.

Loess-paleosolsequences(LPS)areuniqueterrestrialar-chivesforthispurpose.MostfamousfromtheChineseLoess

Plateau,LPShavealsoaccumulatedtenstohundredsofme-tersatplacesinEurope,Siberia,AlaskaandSouthAmerica(Markovicetal.2009;Zöller&Faust2009;Frechen2011).The typical successionof loess andpaleosols generally re-flectsglacialandinterglacialperiods,respectively,andthusthecharacteristicclimatevariabilityoftheQuaternary,thelast ~2.6Ma.The international‘Loessfest 2009’ (Markovic2011)inNoviSad,Serbia,recentlyprovidedaplatformforpresentingscientificresults,fordiscussingnewmethodolog-icaldevelopments,andstrengthening the international co-operationinloessresearch.Anoverviewovertheprogressesmadeduring the lastdecade isprovided inZöller (2010).Emphasis therein was mainly put on the developments ofthedatingmethods,aswellasonhigh-resolutionmagneticsusceptibility and grain-size measurements, because these

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171E&G / Vol. 60 / No. 1 / 2011 / 170–187 / DOI 10.3285/eg.60.1.12 / © Authors / Creative Commons Attribution License

allow detailed reconstructions of pedogenesis and windstrength.

The aim of this review is to elaborate further on themost recent proxy developments. Our motivation stemsfrom the anticipation that sophisticated analytical equip-ment, including HPLC (high performance liquid chroma-tography) and GC-IRMS (gas chromatography – isotoperatiomassspectrometry),willbecomemorewidelyavaila-bleandboostloessresearchoverthenextdecade.Thenewtools will provide valuable, complementary paleoclimateand paleoenvironmental proxies. In this review, we canonly give an overview over the principles of the proxiesthatwearecurrentlyworkingon,sobynomeansitshouldbeconsidered tocover the full rangeof interesting,prom-ising, new methods. The potential, as well as the currentlimitations of the presented methods will be illustrated inselectedcasestudies.

2 Biomarkers and compound-specific stable isotope analyzes (CSIA) – some basics

Biomarkersareorganicmoleculesthatareproducedbycer-tainorganismsorgroupsoforganismsandthushavemoreorlessspecificsources.Inmanycases,theyserveessentialbiophysiologicalfunctions,forexampleasmembranelipidsinsoil-thrivingbacteria,orasleafwaxesforplants.Provid-edthatthebiomarkersaresufficientlyresis-tanttodegrada-tionandmineralization,theyarepreservedinsoilsandcanbe extracted andanalyzed inpaleosols to reconstruct pastchanges in vegetation or bacterial communities. Biomark-erscanthusbeconsideredasmolecularfossils(Eganhouse1997;Eglinton&Eglinton2008).

Theanalyticaldeterminationofbiomarkersgenerallystartswith an (i) extraction or hydrolysis step. For example, li-pid biomarkers are extracted from soil/sediment sampleswith organic solvents traditionally using Soxhlet appara-tuses and biomarkers that form macromolecules such asaminoacids (inproteins)or sugars (inpolysaccharides)arehydrolyticallyreleasedusingacids. (ii)Subsequently,therecommonly followvariouspurificationstepse.g. to removeinterfering cations. (iii) Quantification of the individualmolecules is in many cases carried out via gas chromato-graphy(GC)coupledtoflameionisationdetectors(FID)ortomassspectrometers(MS).Frequently,moleculeshavetobe derivatised to be measurable via GC because they arelow-volatileornotvolatileatall.Forinstance,transforma-tion of hydroxyl groups into trimethylsilyl-(TMS-)deriva-tivesusinge.g.N,O-Bis(trimethysilyl)fluoroacetamid (BST-FA)increasesthevolatilenessofmoleculesbydisablinghy-drogen bonds. But as HPLC becomes more common andavailable,thisstepisnotnecessaryanymoreforthosebio-markersthatcanbemeasuredviaHPLC.

Concerning stable isotopes, d13C and d15N analyzes ofbulksamples,forinstanceofsoilorsedimentssamples,canbeaccomplishedrelativelyeasyviaelementalanalysis–iso-toperatiomassspectrometry(EA-IRMS).Carbonandnitro-genofsamplesaretherebytransformedintocarbondioxide(CO2)andnitrogen(N2),respectively,intheEA.Subsequent-ly, the abundance of heavy versus light isotopes (13C/12Cand 15N/14N, respectively) in these gases is directly deter-mined online in the coupled IRMS. Hence, these analyzesaremeanwhilewellestablishedinmanydifferentscientificcommunitiesandallow,forexample,reconstructingC3–C4vegetationchanges(Boutton1996;Liuetal.2005;Zechet

-40

-35

-30

-25

-20

-15-31 -29 -27 -25 -23 -21 -19 -17 -15

δ13CTOC (‰)

δ13C

alka

ne (‰

)

nC27nC33

Fig. 1: Correlation of compound-specific δ13C (shown here are nC27 and nC33) with bulk δ13C (on total organic carbon, TOC) in a sediment core from Ar-gentina (Zech et al. 2009b). The higher amplitude for δ13C of nC33 compared to δ13C of nC27 reflects the dominant origin of nC33 from C3- or C4-grasses, whereas nC27 primarily derives from C3 trees and shrubs.

Abb. 1: Korrelation von substanz-spezifischen Alkan-δ13C-Werten (dargestellt für nC27 und nC33) mit Gesamt-δ13C-Werten (Gesamt organischer Kohlen-stoff, TOC) für einen Sediment-Bohrkern aus Argentinien (Zech et al. 2009b). Die größere Amplitude von δ13C für nC33 verglichen mit δ13C von nC27 kann damit erklärt werden, dass nC33 überwiegend von C3- oder C4-Gräsern stammt, wohingegen nC27 hauptsächlich von C3 Bäumen und Sträuchern stammt.


TC/EA

bulk samplesoil/sediment/wood/water

cellulose,hemicellulose, lignin, lipids,

clay minerals, minerals,water, etc.

H2HD

C16OC18O

IRMS

m/z 2m/z 3

m/z 28m/z 30

al.2009b)andchangesinthenitrogen(N-)cycle(Zechetal.2007;Schatzetal.2010).

A more sophisticated analytical approach is the combi-nation of biomarker- and stable isotope analyzes. From atechnicalpointofview,thisismostlyaccomplishedbythecouplingofaGCtoanIRMSviaan‘online’combustionunit(GC-C-IRMS).Thus,theisotopiccompositionofindividualbiomarkers eluting successively from the GC-column canbe determined to provide more specific information thanbulk isotopeanalyzes (Glaser2005;Glaser&Zech2005;Amelungetal.2008).Zechetal.(2009b),forexample,haveshownforasedimentcorefromNE-Argentinathatthed13Cvalues of all individual plant leaf-wax derived n-alkanes

nC27, nC29, nC31 and nC33 correlate significantly with bulkd13C.However,theisotopicvariationsaremostpronouncedfornC31andnC33(Fig.1),whichcorroboratesthefactthatthe n-alkane biomarkers nC31 and nC33 derive primarilyfromgrassesandarethusverysensitiveforC3–C4chang-es,whereasnC27andnC29deriveprimarilyfromtreesandshrubs(C3vegetation).

Asthenaturalabundancesofdeuteriumand18Oinrain-fallmainlydependonclimaticfactors,namelytemperature(Fig.2)andtheamountofprecipitation(Craig1961;Dans-gaard1964;Gat1996;Araguas-Araguasetal.2000),dDandd18OrecordsfromLPSwouldbeofgreatvalue,too.Itis no surprise that various kinds of archives and chemical

Fig. 2: Correlation between δ18O of monthly precipitation and surface air temperature for the IAEA/WMO network stations situated between 40 °N and 60 °N (from Araguas-Araguas et al. 2000, Fig. 4a).

Abb. 2: Korrelation von δ18O im monatlichen Niederschlag mit Lufttemperatur für IAEA/WMO Klimastationen zwischen 40 °N und 60 °N (aus Araguas-Araguas et al. 2000, Abb. 4a).

Fig. 3: Principle of bulk TC/EA-IRMS δD and δ18O analyzes. All hydrogen/oxygen atoms of a sample are converted at high temperature into hydrogen (H2) / carbon monoxide (CO), for which δD and δ18O are determined ‘online’ via a coupled IRMS by detecting the masses m/z 2 and 3, and m/z 28 and 30, respectively.

Abb. 3: Prinzip von Gesamt TC/EA-IRMS δD und δ18O Analysen. Alle Wasserstoff-/Sauerstoff-Atome einer Probe werden bei hoher Temperatur in Wasser-stoff- (H2) / Kohlenmonoxid- (CO) Gas umgewandelt. Mittels eines ‚online’ gekoppelten IRMS werden für diese Gase die δD bzw. δ18O-Werte durch Detek-tion der Massen m/z 2 und 3 bzw. m/z 28 and 30 gemessen.


compoundsthatrecordthedeuteriumand18Osignaturesofprecipitationhavebeentargetedextensivelyinpaleoclimatestudies, including ice cores, speleothems, lacustrine andpedogeneticcarbonates,andplantcellulose(e.g.Sternberg1988;Mayer&Schwark1999;e.g.Danisetal.2006;Wangetal.2006;Gessleretal.2009).However,theseproxiesarehardlyappliedtoLPSssofar.

Fromananalyticalpointofview,dDandd18Oanaly-zesofbulksamplescanbecarriedoutviathermoconversion/el-ementalanalysis(TC/EA-)IRMS‘online’couplingonpyro-lyticallyproducedhydrogen(H2,HD)andcarbonmonoxide(C16O,C18O),respectively(Werneretal.1996;Kornexletal. 1999;Werner 2003) (Fig. 3).However, oxygen andhy-drogenoccurinmanydifferentorganicandinorganicpoolsinsoilsandsediments(crystalwater,aliphaticcompounds,aromaticcompounds,alcohols,plant-derivedorganicmate-rial,microbial-derivedorganicmaterial,etc.).Asthesepoolscanhavedistinctisotopicsignals,itisverydifficulttodisen-tanglearealpaleoclimaticsignalwhenchangesinpoolsizescannotbeexcluded.Anothermetho-dologicalshortcomingisthatmanyhydrogenandoxygenatomsarenotstronglyboundandthattheyarethereforepronetoexchangereac-tions(Schimmelmannetal.2006).ConsiderforexampleR-COOH (carboxyl-) groups, where the isotopes will equili-brate(post-depositionally)withtheambientsoilwater.Wewilldiscusswaystoovercometheseproblemsfurtherbelow.

3 Novel methodological approaches

3.1 Plant leaf-wax derived n-alkanes

n-Alkanes with 25 to 33 carbon atoms (nC25–nC33) and astrong odd-over-even predominance (OEP) are importantconstituents of cuticular plant leaf waxes (Eglington &Hamilton 1967; Kolattukudy 1976). With the litter-fallthey are deposited and stored in soils and sediments, forexample in aeolian sediments, where they are assumed tobe relatively resistant against biogeochemical degradation

(Cranwell1981;Lichtfouse1998;Lichtfouseetal.1998).Sincedifferentvegetationtypeshavedistinctn-alkanepat-ternsandhenceaso-called“chemicalfingerprint”,n-alkaneshavethepotentialtoserveasbiomarkers.Forinstance,theyareusedtodifferentiatebetweenautochthonous(lacustrine)andallochthonous (terrestrial)organicmatter in lakesedi-ments (Bourbonniereet al. 1997;Fickenet al. 2000;Mü-gleretal.2008;Zechetal.2009b),ortoreconstructvegeta-tionchanges,predominantlyintermsoftherelativepropor-tionsofgrassesandtrees(Cranwell1973;Schwarketal.2002;Zech2006).Thelatterisbasedonthefindingthatthen-alkanesnC27andnC29dominateinmostmoderntreesandshrubs,whereasnC31andnC33dominateingrasses.

n-Alkanescanbeeasilyextractedfromdriedandgrin-dedplant(~0.5g)orsedimentsamples(upto150g)withaccel-eratedsolventextraction(ASE)orSoxhletsystems(e.g.Wi-esenbergetal.2004).InthemethoddescribedforinstancebyZech&Glaser(2008),anazeotropicmethanol/toluenemixture(7/3)isusedassolventanddeuteratedn-tetracosane(d50-n-C24) as internal standard. The extracts are concen-tratedandco-elutedestersaresaponifiedwith0.5MKOHinmethanol.Purificationofthen-alkanefractionisperformedonaluminiumoxide/silicagelcolumns(both5%deactivated)withhexane/toluene(85:15)aseluent.Afterconcentrationofthehydrocarbonfractionusingrotaryevaporation,deuter-atedn-eicosane(d42-n-C20)isaddedasrecoverystandardandthen-alkanesarequantifiedbyinjectionintoanHP6890GCequippedwithaflameionizationdetector(FID).Fig.4illus-tratesexemplarilyaGC-FIDn-alkanechromatogramforaloesssamplefromthe‘Crvenka’LPS,Serbia.

Althoughthen-alkanebiomarkermethoditselfisknownalreadyformanydecades,itisappliedtoLPSonlyrelativelyrecently (Liu&Huang2005;Zhangetal.2006;Baietal.2009).Zechetal.(2008a)pointedoutthatthen-alkanepat-terns change over time and that a correction procedure isnecessarytoaccountforthisdegradationeffectandtoavoiddeceptive interpretations when reconstructing vege-tationchangesfromsedimentaryn-alkanes.Twocorrectionproce-

Fig. 4: GC-FID n-alkane chromatogram for a loess sample from Crvenka, Serbia. The highest abundance of nC31 indicates a former vegetation cover domi-nated by grasses; the relatively higher abundance of nC27, nC29, nC31 and nC33 compared to nC26, nC28, nC30 and nC32 is called odd-over-even predomi-nance (OEP) and indicates little degradation.

Abb. 4: GC-FID n-Alkan-Chromatogramm für eine Lössprobe aus dem Profil Crvenka, Serbia. Die Dominanz des Alkans nC31 belegt, dass die frühere Vegetation überwiegend aus Gräsern bestand; das stärkere Auftreten von nC27, nC29, nC31 und nC33 verglichen mit nC26, nC28, nC30 und nC32 bezeichnet man als odd-over-even predominance (OEP) und ist charakteristisch für wenig stark degradiertest pflanzliches Ausgangsmaterial.


dureshavemeanwhilebeen suggested,bothofwhichem-ploytheoddoverevenpredominance(OEP)asdegradationindex(Zechetal.2009a;Buggleetal.2010).

Case study: Vegetation reconstruction in the Carpathian BasinBasedonpollenfindingsitiswidelyassumedthattree-lesstundraexpandedvastareasofEuropeduringglacialperiods.FortheCarpathianBasin,thistraditionalparadigmoftree-less full glacial (stadial) paleoenvironments has first beencalledintoquestionbyfossilcharcoalandmalacologicalevi-dencefromHungarianLPSs(Willisetal.2000;Rudner&Sümegi2001).ThestudiesofSchatzetal.(2011)andZechetal.(2009a)wereinitiatedtocontributetothediscussionabout“treesornotrees?”(Willis&Andel2004)fromann-alkanebiomarkerperspective. Inorder toestimate thepercentagecontributionofn-alkanes(treesversusgrasses)totheCrven-kaLPSinNorthernSerbia,Zechetal.(2009a)proposedanendmembermodellingapproachbasedonmodernreferencesamples.Thisapproachisillustratedexemplarilyforthen-alkaneratio(nC31+nC33)/(nC27+nC29)inFig.5A.Theresults,takingdegradationeffectsintoaccount,allowedtheauthorstoinferthatgrassesalwaysdominatedduringthewholelastglacialcycle,butthatasmallcontributionoftreesislikelyduringtheglacialperiodsandtheHolocene.Notethattheaccuracyofthen-alkanebiomarkermethodislimitedbythescatteringofthemoderndatasetsforgrasslandsandforests(Fig.5A).Thislargeinterspecievariabilitycanbeattributed

for instance to leaf and needle aging (Prügel et al. 1994)or to environmental stress (Shepherd & Griffiths 2006).Fig.5Billustratesthatthiscanresultin‘negative’treecoverpercentages.Yetthemodellingresultsforseveralrelevantn-alkaneratios[(nC31+nC33)/(nC27+nC29),nC31/nC27,nC33/nC27,andnC31/nC29)]allrevealverysimilarandsystematicshifts,which increases the confidence that degradation-correctedn-alkane patterns can be used to reconstruct past changesin vegetation. Accordingly, the n-alkane biomarker resultsofbothSchatzetal.(2011)andZechetal.(2009a)provideadditionalevidencechallengingtheparadigmoftreelessfullglacialpaleoenvironments.

Thereliabilityofn-alkanesaswellasmostotherbiomar-kersasproxies in loess-paleosolsequencesdependsontheabsence of strong post-sedimentary overprinting of theoriginal organicmatter signal.Wehighly acknowledge ef-fortsaimingatquantifyingsucheffectsandpoint to stud-iespublishedbyGockeetal. (2010)forrhizolithsinloess.The authors found that the n-alkane patterns of rhizolithorganicmatter are dominatedbynC31 (Gocke et al. 2010,Fig.6),Althoughthisisnottypicalforabove-groundlipidsfrommosttreesandshrubsbutforgrasses,theauthorsfa-vorpost-sedimentaryincorporationofroot-derivedorga-nicmatterin loess.Furtherstudiesshouldthereforefirstlyad-dressn-alkaneconcentrations in rootsas the latterareas-sumedtobeverylowcomparedtoabove-groundlitter;sec-ondly,datasetsformodernreferencen-alkanepatternsfromroots,lackingsofar,shouldbeestablished.Andthirdly,we

Fig. 5: A) End member modelling approach for the n-alkane ratio (nC31+nC33)/(nC27+nC29). Based on modern plant and soil n-alkane ratios, degradation lines are calculated using the OEPs as degradation proxy. The percentage of trees and grasses contributing to a loess-paleosol sample is estimated by the quotients b/c and a/c, respectively. B) Pedostratigraphy of the Crvenka LPS in Northern Serbia and modelling results for the contribution of tress and grasses (adopted from Zech et al. 2009a).

Abb. 5: A) End Member Modell für das n-Alkanverhältnis (nC31+nC33)/(nC27+nC29). Basierend auf n-Alkanverhältnissen von rezenten Pflanzen und Bö-den werden Degradationslinien ermittelt. Die OEP-Werte dienen dabei als Proxy für den Degradationsgrad. Die Anteile von Baum- bzw. Gras-n-Alkanen zu einer LPS-Probe lassen sich anhand der Quotienten b/c bzw. a/c abschätzen. B) Pedostratigraphie der LPS Crvenka in Nordserbien und Modellierungs-Ergebnisse für die Anteile von Bäumen im Vergleich zu Gräsern (aus Zech et al. 2009a).


highlyencouragefurtherinvestigationsespeciallyapplyingcompound-specific14C-datingofdifferentbiomarkersinLPSfor which independent and high resolution luminescencedatingofthesedimentaryhistoryisavailable.

3.2 Amino acid racemization

Aminoacids,mainlyboundinproteins,constituteanimpor-tantN-poolinsoils(Amelung2003).Theyarenobio-markerssensu strictu,becausetheydonotoriginatefromspecificor-ganisms.However,theymayprovidevaluableinsightsintheagingofsoilorganicmatter(SOM)andpast temperatures.Aminoacids containachiralC-atom,and theycan there-foreoccureitherintheleft-handedform(L-enantiomer)orintheright-handedform(D-enantiomer).LivingorganismsprimarilyproduceL-aminoacids,buttheD-enantiomersarethenformedduringracemization–anabioticprocessthatismainlytime-,temperature-andpH-dependent(Bada1985)(Fig. 6). It has therefore been suggested thatD/L-ratios ofamino acids can be used for dating. Mahaney & Rutter(1989),forinstance,foundtheD/L-ratioofasparticacidtobeasuitablegeochronometerinburiedsoils.Forthelast15years,aminoacidgeochronologyinloessresearchwasmain-lybasedonmeasuringtheratioalloisoleucine/isoleucineinfossilgastropodshellsandwassuccessfullyusedtodistin-guish between loess from different glacial cycles (Zölleretal.1994;Oches&McCoy2001;Novothnyetal.2009).Principally,ofcourse,aminoacidracemizationcouldalsobeusedtoreconstructpaleotemperatures,butindependentagecontrolneedstobeavailable,andsuchapplicationsareveryraresofar(Kaufman2003).Mostgeochronologicalstudieshavefocussedonaminoacidsinfossilgastropodshells,basedonthenotionthattheselike-lyprovidethebest‘closedsystems’available,i.e.thatpost-depositional amino-acid losses or contaminationaremini-mal(Penkmanetal.2008).Amelung&Zhang(2001),how-ever, also proposed a method for determining amino acidenantiomersinbulksoilsamples.Samplepreparationcom-prisespre-extractionoffreeandwater-solubleaminoacids,

hydrolysisofprotein-boundaminoacids,purificationovercolumns(DowexWX8),andderivatization.QuantificationiscarriedoutusingGC-MS.AsracemizationisknowntobecatalysedbylowpHandhightemperatures,conditionsthatarealsoappliedduringhydrolysis,Amelung&Brodowski(2002)quantifiedthehydrolysis-inducedracemizationusingdeuteriumlabelling.Theyshowthatlessthan10%ofD-AspandD-Lyswereformedduringtheanalyticalprocedureinenvironmentalsamplesolderthan3000years.Hence,Ame-lung (2003) suggested that aspartic acid (asp) and lysine(lys)arethemostsuitableaminoacidsfordatingpurposesinsoils.

Case study: Temperature reconstruction in SiberiaZechetal.(2008b)appliedthemethodofAmelung&Zhang(2001)to10selectedsamplesfromaSiberianpermafrostLPS(‘Tumara’), which probably comprises the last two glacialcycles.Fordetailsconcerningthe(chrono-)stratigraphy,thegeochemical,theisotopicandthebiomarkercharacterizationofthissequencethereaderisreferredtoZechetal.(2007;2008b;2010a).Inbrief,darkorganic-richpaleosolsalternatewith brown and more intensively mineralised and weath-eredpaleosols(Fig.7).Basedonnumericdatingresultsandamulti-proxyapproach,thedarkunitsB,C2andDarecor-relatedwithglacialperiods,whereasthebrownunitsA,C1,C2 and E are correlated with interglacial/-stadial periods.The D/L ratios obtained for aspartic acid (asp) and lysine(lys)areplottedversusdepthinFig.7andcanberoughlyde-scribedbyexponentialfits.Inaddition,thebrownunitsaregenerallycharacterizedbyhigherratiosthanthedarkgreyunits.Nevertheless,D/L ratiosoverall increasewithdepthandrevealthattheapparentracemizationratesaresmallerforlysinethanforasparticacid(thelatterhavinghigherD/Lratios). This is in agreement with findings from Amelung(2003),who furthermore emphasised that lysine racemiza-tion ratesaremoreor less constant indifferent soil types.GiventhatthesoilpHrevealsonlyminorvariationsrangingfrom7to8throughoutthewholeprofile,temperatureandtimecanbeassumedtobethemainfactorscontrollingthe

1

CO2H

H2N C* H

Rtime- and temperature-dependent racemizationreaction

L-isomer

A) B)

CO2H

H C* NH2

R

D-isomer

* chiralic C-atom

(Living organisms)

Fig. 6: Principle of amino acid geochronology: A) Time- and temperature-dependent racemization reaction. B) Exponential functions describing the time-de-pendency of racemization; t1/2 = half-life time, L0 = initial amount of L-enantiomers, D/L = ratio of D- to L-enantiomers (from Wagner 1998, p. 342, Fig. 142).

Abb. 6: Prinzip der Aminosäure-Geochronology: A) Die zeit- und temperaturabhängige Gleichgewichtsreaktion der Razemisierung. B) Exponentielle Funk-tionen die die Zeitabhängigkeit der Razemisierung beschreiben; t1/2 = Halbwertszeit, L0 = Anfangsgehalt des L-Enantiomers, D/L = Verhältnis von D- zu L-Enantiomeren (aus Wagner 1998, Seite 342, Abb. 142).


aminoacidracemization.Consequently,Zechetal.(2008b)suggest that the higher D/L ratios that characterize thebrownUnitsA,C1andC3areprimarilytheresultofhighertemperaturesduringformationoftherespectivepaleosols.

Based on these results, we see high potential for theamino acid racemization method to provide a paleotem-perature proxy in LPS. A high sampling resolution mightalso help depicting sedimentary hiatuses, which shouldyieldabruptincreasesoftheD/Lratioswithdepth.Unfor-tunately, the described method is relatively laborious andwillrequiresomefurtheroptimisation,particularlyfortheapplication to organic-poor loess samples. An importantstepwouldprobablybealreadymadewhenusingaHPLCinstead of a GC system, because that will supersede thederivatizationstep.

Fig. 7: Stratigraphy and tentative chronostratigraphy of the Tumara LPS, NE-Siberia. D/L-ratios for Asp and Lys increase with depth, reflecting the time dependency of the racemization. Higher ratios in the brown units compared to lower ratios in the dark units are suggested to reflect the temperature de-pendency of amino acid racemization (from Zech et al. 2008b).

Abb. 7: Stratigraphie und Chronostratigraphie der LPS Tumara, NO-Sibirien. D/L-Verhältnisse für Asp and Lys werden mit zunehmender Tiefe weiter. Dies spiegelt die Zeitabhängigkeit der Razemisierung wider. Weitere Verhältnisse in den braunen Paläoböden verglichen mit den dunklen Paläoböden lassen sich mit der Temperaturabhängigkeit der Razemisierung erklären (aus Zech et al. 2008b).

3.3 GDGTs

Overthelastfewyears,severalnewproxieshavebeenpro-posedbasedonGDGTs(Fig.8),membranelipidsofArchaeaandBacteria.TheexactchemicalcompositionoftheGDGTsisthoughttoreflectadjustmentsofmembranepermeabilityandfluiditytoenvironmentalconditions(e.g.pHandtem-perature).Thus theanalyzesofGDGTsmayoffer interest-ing,newapproaches toquantitatively reconstructpast cli-mateandenvironmentalvariabilityfromvariousgeologicalarchives.TheTEX86,forexample,isanewpaleotemperatureproxy based on the cyclicity of isoprenoid GDGTs, whicharemainlyderivedfromArchaealivinginoceansandlakes(Schoutenetal.2002;Kimetal.2008;Powersetal.2010).Although it has meanwhile been found that isoprenoid


GDGTsalsooccurinsoils,anotherproxy,theBIT(branchedversusisoprenoidGDGTs),hasbeensuggestedtoallowthequantification of terrestrial versus autochthonous organicmatterinlacustrineandmarinesediments(Schoutenetal.2002). This index is further based on the original assump-tionthatbranchedGDGTsareonlyderivedfromsoil-thriv-ing bacteria. Meanwhile, however, it has been found thatbranched GDGTs are also produced within the water col-umnofoceansandlakes(Blagaetal.2009;Peterseetal.2009a;Bechteletal.2010;Tierneyetal.2010),whichwar-rantscautionwheninterpretingtheBITandTEX86indices.

ThebranchedGDGTs,whicharepresumablyderivedfromyetunknownanaerobic,heterotrophicsoilbacteria(Weijersetal.2010),maybepromisingbiomarkersforloess-paleosolsresearch.Anempiricalstudybasedon134soilsamplesfrom90 globally distributed locations has shown that branchedGDGTs vary in their degree of cyc-lisation and methyla-tion(expressedasCBTandMBT,i.e.cyclisationandmeth-ylationindexofbranchedtetraethers)dependingonsoilpH(R2=0.70)andmeanannualair temperature (MAAT,R2=0.82) (Weijers et al. 2007). Local calibration studies alongaltitudinal transectsatMt.Kilimanjaro,Tanzania, andMt.Gongga,China,havemeanwhilecorroboratedthesuggestedpH and temperature dependency of theCBT/MBT indices(Schoutenetal.2002;Peterseetal.2009b).TheanalysisofbranchedGDGTsinlakeandoceansedimentsmightthere-

foreprovideavaluable,newproxyforcatchment-widepHandMAATreconstructions,providedthattheyarederivedfromerodedsoilsonly.Asmentionedabove,however,thereis evidence that branchedGDGTsare alsoproducedauto-chthonously in lakes and oceans, which prevents robustinterpretation of the CBT and MBT indices in respectivestudiesthusfar.Surpri-singly,toourknowledge,nostudieshavebeenpublishedyetapplyingtheCBT/MBTindicesforpaleoenvironmentalreconstructionsinloess-paleosols.

The analysis of GDGTs comprises (i) lipid extractionfromtypicallyfreeze-driedsoilorsedimentsamples(5–50gdependingonabundance),(ii)separationintotheapolarandpolar(containingtheGDGTs)fractionoveraAl2O3col-umn using e.g. hexane:dichloromethane (DCM) (9:1) andDCM:Methanol (1:1), and (iii) filtering, prior to quantifi-cation of the variousGDGTs by HPLC/atmospheric pres-sure chemical ionization-mass spectrometry (APCI-MS).So-calledselectiveionmonitoringallowsdetectingspecificmolecularmasses,i.e.specificGDGTmolecules(Fig.8).

Case studies: Application of GDGT indices to the Tumara LPS, Siberia, and Crvenka LPS, SerbiaThe first case study presents GDGT results from theTu-mara LPS (Fig. 9). The BIT indices are generally high(>0.84), which is in agreement with the notion thatbranched GDGTs are mainly derived from soil-thriving

Fig. 8: Chemical structures of the branched GDGTs (left), and total and selective ion mass [M+H]+ chromatograms for a soil sample (modified after Weijers et al. 2007).

Abb. 8: Chemische Strukturen für verzweigte GDGTs (links), und Chromatogramme für die Gesamtmasse bzw. einzelner Massen [M+H]+ für eine Boden-probe (abgeändert nach Weijers et al. 2007).


bacteria. The MBT indices range from 0.08 to 0.32, andtheCBTranges from0.24 to0.95.This translates into re-constructed MAAT between -8.7 and 3.8°C, and soil pHbetween6.3and8.1.

Replicate measurements of a soil standard (“Yong-song’s garden”) throughout the course of the measure-ments indicate laboratory precision of 0.2°C for MAAT,and 0.01 for pH. However, much higher uncertaintiesregarding the accuracy of the reconstructed parametersmayariseforseveralreasons:(i)Thereconstructedtemperaturesfor theTumaraLPSarepartlywellbelow0°Candthusbeyondthelowestvaluesintheglobalcalibrationdata set.Althougha recent study inSvalbard indicates that mean annual air temperatures be-low0°Cmaybe successfully reconstructedusingbranchedGDGTs (Peterse et al. 2009a), comparison of our upper-most sample (-1.7°C)with estimatedMAATof ~-15°C sug-gestsasignificantpositivebias.Atthisstage,wecanonlyspeculate that the observed discrepancy might be due toseasonal (summer) growth of the soil bacteria, differencesbetween MAAT and soil temperatures, or other unknownmethodologicalshortcomings.

(ii) Analytical challenges regarding the new proxieshavebecomeevident,becauseoneofthetargetcompounds(m/z1050, III inFig.10a),whichisgenerallycharacterized

Fig. 9: Pedostratigraphy of the Tumara LPS, NE-Siberia, GDGT indices MBT, CBT and BIT, and reconstructed temperatures and soil pH. While the recon-structed relative interglacial-glacial temperature variability in the upper 7 m of the profile is in agreement with the expected temperature variability derived from the chronostratigraphy, reconstructed temperatures for the presumably penultimate glacial Unit D seem to be too high.

Abb. 9: Pedostratigraphie der LPS Tumara, NO-Sibirien, GDGT Kennzahlen MBT, CBT und BIT, sowie die rekonstruierten Temperaturen und Boden pH-Werte. Während die rekonstruierten relativen interglazial-glazial Temperaturschwankungen in den oberen 7 Metern des Profils der Chronostratigraphie übereinstimmen, scheinen die rekonstruierten Termperaturen im vorherigen, älteren Glazial zu hoch zu sein.

by a minor “contamination” shoulder on the right side,turnedouttobedominatedbythat“contamination”(com-poundIII,probablyan isomerof III (Weijersetal.2010)).Whencoupling twoHPLCcolumns toachievebetterpeakseparation, it is possible to quantify the two compoundsindividually(Fig.10b,Y.Huang,pers.comm.).However,nocalibrationstudiesareavailableyetthattaketheseparatedcompounds into account. Moreover, other target peaks al-so turnedout toconsistofmultiple,yetunidentifiedcom-pounds. Clearly, further research is necessary to improvecompoundseparationandidentification.

(iii) There are two other effects that might constrainthe applicability of GDGT-based reconstructions in loess-paleosols,whichwerefer tohereas“changingcommunityeffect” and“growth depth effect”: The first one addressesthepossibility thatchanges intheGDGT-producingbacte-rial communities could result in changes in the structuralcomposition of the membrane lipids without necessarilyreflecting changes in environmental conditions. In thatsense, as long as the GDGT-producing organisms are notidentified,culturedandtestedindividually,wehavetorelyon empirical calibration studies as they exist today evenif they do not fully capture all possible factor affectingGDGDdistributions.The“growthdepth effect”has todowith the fact thatwe

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A) B)

Fig. 10: Total ion chromatogram of one of the Siberian samples, illustrating the existence of two isomers III and III* for m/z 1050. A) Standard chromato-gram and B) chromatogram with improved peak separation.

Abb. 10: Beispiel für ein HPLC Chromatogramm der siberischen Proben. Es zeigt das Vorhandensein von zwei Isomeren mit der Massenzahl m/z 1050 (III und III*). A) Standardchromatogramm und B) Chromatogramm mit verbesserter Peak-Trennung.

still know very little about the soil bacteria’s ecology, in-cluding for example the soil depth at which the bacteriathrive and produce GDGTs. A non-negligible subsurfaceproduction ofGDGTs could thus result in an overprint of‘older’ paleo-environmental signals at depth. The growthdepth effect might limit the temporal resolution of recon-structions,mutethevariabilityof therealsignal,andren-der‘absolute’ reconstructions very challenging from loess-paleosolsLPS.

With these methodological limitations in mind, the in-terpretation of paleo-data should be very cautious. Ourfirst case study from Siberia shows that Unit A and C,whichweremostlikelydepositedduringtheHoloceneandthe Eemian, respectively, are characterized by higher re-constructed temperatures than the glacial Unit B (Fig. 9).AlthoughtheabsoluteMAATarelikelyoverestimatedsys-tematically, the glacial-interglacial temperature differenceof ~10°C is reasonable. One could also speculate that thelast glacial pattern is real, with coldest conditions duringMarine Isotope Stage (MIS) 2 and 4 and slightly warmerconditions during MIS3. Surprising features, however, are(i) relatively warm conditions during MIS2 compared toMIS4,(ii)UnitCnotdisplayingacommonlyexpectedtem-perature peak maximum for MIS5e (Unit C3, Fig. 9), and(iii)‘too warm’ reconstructed temperatures for the penul-timateglacialUnitD.Providedthatthepresentedchronos-tratigraphy of theTumara LPS is correct, our results sug-gest that the growth depth effect might have overprintedand muted the paleo-signals, i.e. warm conditions duringthe Holocene are now overprinting the cold MIS2 signal,andtheverywarmconditionsduringtheEemianhaveal-lowedGDGT-producingbacteriaatdepthtostronglyaffecttherecordbelow5mdepth.

In our second case study forGDGTs, unpublished datafrom theCrvenkaLPS (Fig. 11),pose similarchallenges toa robust interpretationofGDGT indices.Here, the topsoilsamples show reconstructed MAAT of ~15°C, which is inreasonable agreement with estimated MAAT of 11°C, al-thoughwithaslightbiastotoohightemperatures.Subsur-facesamplesreach20°Creconstructedtemperatures,whichmight indeed reflect warmer conditions during the mid-

Holocene optimum. However, reconstructed temperaturesremain very high in the underlying MIS2 loess (V L1L1).Asabove,wespeculatethatthismightreflectthatGDGTswere produced during the Holocene at depth and thusoverprinted the cold, glacial signal. While reconstructedtemperatures drop to values as low as ~4°C deeper in theprofile, which would be reasonable in terms of expectedglacial-interglacial temperature variability, reconstruc-ted lowest temperatures also characterize the interglacialEemian paleosolV S1, although the latter should be cha-racterizedbyhighesttemperatures.Isthisagainduetothegrowthdeptheffect?Ordoes this indicateothermethodo-logicalshortcomingsthatarenotyetfullyunderstood?In summary,we advise cautionwhen interpretingGDGT-derived proxies from LPS. GDGT analyzes are a promis-ingnewtoolforpaleoclimatereconstruction,buttherearemany yet unresolved questions that need to be addressedbefore robust conclusions can be inferred from respectiveproxies.

3.4 Compound-specific δD-analyzes of n-alkanes

Asdiscussedearlier,bothdDandd18Ohaveahighpotentialfor paleoclimatic reconstructions. Albeit with certain bio-synthetic fractionation factors, plant photosynthetic prod-uctsincorporatetheisotopicclimatesignalofprecipitation,becausetheirdDvaluesarerelatedtothesourcewaterdDvalues (Sternberg1988; Sessionset al. 1999; Saueret al.2001;Sachseetal.2004).Duringsoilorganicmatterforma-tion,thisclimatesignalisalsoinheritedbysoils.However,changing soil organic matter pool sizes (e.g. lipids, lignin,cellulose)andisotopicexchangereactionsinsoilsandsedi-mentshavepreventedthesimpleuseofbulkanalyzes(Bal-abane1983).Oneapproachtoovercomeatleastthelatterproblemistoequilibratebulksamplesinwaterwithknownisotopiccom-position,andthentocorrectfortheexchangereactionsaf-terbulkmeasurementsviaTC/EA-IRMS(Ruppenthaletal.2010).Yettechnicalimprovementsnowalsoallowamoreel-egantandmorespecificapproach,namelydeterminingtheisotopic compositionof individualbiomarkersbycoupling


injection

GC Pyrolysis reactor IRMSCxHyOz x-z C +y/2 H2

z CO

Fig. 12: Principle of compound-specific δD- and δ18O-analysis of biomarkers using GC-Py-IRMS. Biomarkers eluting successively from the GC-column are converted “online” in a pyrolysis reactor to hydrogen (H2) and carbon monoxide (CO) and the isotopic composition of these gases are determined directly in a coupled IRMS.

Abb. 12: Prinzip der substanz-spezifischen δD- und δ18O-Analytik von Biomarkern mittels GC-Py-IRMS. Die nacheinander von der GC-Säule eluierenden Biomarker werden im ‘online’ Verfahren in einem Pyrolysreaktor in Wasserstoff- (H2) und Kohlenmonoxid-Gas (CO) umgewandelt. Die Isotopenzusam-mensetzung dieser Gase wird in einem direkt gekoppelten IRMS gemessen.

Fig. 11: Pedostratigraphy of the Crvenka LPS in Northern Serbia, GDGT indices MBT, CBT and BIT, and reconstructed temperatures and soil pH. Similar to the Tumara LPS, reconstructed GDGT temperatures are not always in agreement with what can be expected from the chronostratigraphy, e.g. lowest reconstructed temperatures coincide with the presumably last interglacial Eemian soil V S1. Possibly, the “growth depth effect” prevents a simple interpre-tation of GDGT proxies in LPSs.

Abb. 11: Pedostratigraphie der LPS Crvenka in Nordserbien, GDGT Kennzahlen MBT, CBT und BIT, und rekonstruierte Temperaturen und Boden pH-Werte. Ähnlich wie bei der LPS Tumara, stimmen die rekonstruierten GDGT-Temperaturen nicht immer mit der Chronostratigraphie überein. Insbesonde-re überraschen die für den vermutlich letzt-interglazialen Eemboden V S1 rekonstruierten niedrigen Temperaturen. Eine einfache Interpretation der neuen Proxies in LPS ist möglicherweise durch das Wachstum von GDGT-produzierenden Archaebakterien in tieferen Bodenschichten erschwert.

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ofGCandIRMSviaan‘online’pyrolysisreactor(Py)(Bur-goyne&Hayes1998;Hilkertetal.1999)(Fig.12)

With this new tool at hand, compound-specificdD be-cameapopularpaleoclimateproxy(Liuetal.1999;Huangetal.2004;Sachseetal.2004;Xieetal.2004;Paganietal.2006;Mügleretal.2008).Plant-derivedn-alkanesareprob-ably the most useful biomarkers to target, because theyare well-preserved in sediments and soils (Lichtfouse etal. 1998), and because their alkyl hydrogen atoms are less

pronetoexchangereactionscomparedtootherbiomarkers(Sessionsetal.2004;Pedentchouketal.2006;Dawsonetal.2007).

Ofcourse,ultimately,onehas to take intoaccount thatevaporative enrichmentof soil andplantwater, aswell asbiosynthetic fractionation are also important factors con-trolling the isotopic signature of the targeted biomarker(Schmidtetal.2001;Liuetal.2006;Smith&Freeman2006;Barbour2007;Houetal.2007;Feakins&Sessions2010).


Two case studies: Paleoclimate reconstructions from Tu-mara and CrvenkaTo our knowledge, the first and only application of com-pound-specificdDanalyzesofn-alkanestoaLPSwascar-riedoutbyLiu&Huang(2005)ontheChineseLoessPla-teau.Wewillherepresenttwocasestudiesbasedonownda-tatoillustratethemethodologicalpotentialsandlimitations.Thefirstcasestudyaimedatmorequantitativetemperaturereconstruction for the Tumara LPS in Northeast Siberia(Zech et al. 2010b). ThedD records of all three n-alkanesthathadsufficientconcentrationforthedDmeasurements(nC27,29and31)showverysimilarpatternsalongthe~240kaprofile(Fig.13).Theauthorsthereforeconcludedthatveg-etationchanges,whichhavebeenreconstructedforTumaraemployingn-alkanepatternsandpollenanalyzes (Zechetal.2010a)didnotplayadominantrolefortheisotopicsignal.ThemeandDrecordcanthusbeinterpretedtoreflectpastchangesintheisotopiccompositionofsoilwater,whichinturndominantlyreflectstemperatureathighlatitudes.Morenegativevalues(-280‰)characterizetheorganic-richUnitsB,C2andD,whichconfirmsourearlierinterpretationthatthoseunitsweredepositedduring cold, glacial conditions.Morepositivevalues(>-250‰)characterizetheUnitsA,C1,

C3 and E, which is in agreement with deposition duringwarm,interglacialperiods.

Zechetal.(2010b)notethatacorrectioncouldbeappliedforthefactthattheglacialoceansandthusprecipitationbe-camemorepositive(~8‰,theglobalicevolumeeffect).Thiswouldincreasetheglacial-interglacialdifferencesinthein-vestigatedrecord,butwouldrequireamorerobustagecon-trolthantheonebeingathand.Anothercautionarynoteisthatchangingevaporationmightalsohaveaffectedthepre-sentedrecord.Zechetal.(2010b)suggestedthatevaporationeffectsareprobablyonlyofsecond-orderimportanceatthissitebecauseofthelowtemperatures.Assumingthatevapo-rationhadameasurableeffect,itshouldhaveledtoisotopicenrichmentduringthemorearidglacialperiods.Thismightinfactexplaintheslightlysmallerglacial-interglacialrangeindD(~30‰)comparedtorespectiverangesinicecorere-cords(upto50‰).

OursecondcasestudypresentsunpublisheddDdataforCrvenka. The n-alkanes C29 and 31 were most abundant inthesamplesandthereforetargetedforthedDmeasurements.Overall,thetworecordsmostlytrackeachotherreasonablywell(Fig.14),althoughthemeasurementprecisionof3.1and2.9‰ for the external standards nC27 and C29, respectively(run during the course of the whole measurement period),aswellasmeanstandarddeviationsof1.5and1.2‰forthetriplicatemeasurementsofthesamplesindicatethatsomeofthedifferencesbetweendDC29andC31maybereal.OnemayspeculatethatC29andC31deriveproportionallyfromdistinctplantspeciesbeingtoagreaterorlesserextentsensitivetoevaporativedDenrichment.However,forthepurposeofthisreview,wewilldiscussprimarilythebroad,commonpatterns(‘dDmean’inFig.14).Thefirstfeaturewewouldliketodrawtheattentiontoisthe~10‰dropindDfromtheHolocene(~-200‰)totheMIS2loessVL1L1.Asabove,correctionfortheglobalicevolumeeffectwouldincreasethisdifference,butstillthedifferenceismuchlessthanwhatonewouldexpectfromahightomid-latitude temperature signal alone. For compa-rison, thedDrecordfromVostok,Antarctica,isplottedinFig.14.Onepos-sibleexplanationmightbethatthesoilwaterwasisotopicallyenrichedduringglacialsduetomorearidconditions(ormoreprecisely a higher ratio of evaporation to precipitation). Infact,manyoxygen records from theMediterranean region,includinge.g.theSoreqandPiqiincavespeleothemsinIsrael(Bar-Matthewsetal.2003)showmoreenrichedvalues(Fig.14),whichwasoriginallyinterpretedtodocumentmorearidconditions(Robertsetal.2008).However,doubtsconcerningthis interpretation arose from lake level reconstructions ofLakeLisan,aglacialfreshwaterlakeoccupyingtheDeadSearegion(Liskeretal.2009).Asitturnedout,thespeleothemoxygen isotope recordsmainly followed the isotopic signaloftheMediterraneanSea,whichservesaswatersourceforregionalprecipitationand showsapronouncedenrichmentduringglacials (>3%) (Bar-Matthewsetal.2003;Almogi-Labinetal.2009).This‘sourceeffect’(translatinginto~25‰glacial-interglacialdifferenceindDofregionalprecipitation)islikelyresponsibleforoff-settingtheexpectedtemperaturesignalatCrvenkaatleasttosomedegree.Additionally,pastchangesinatmosphericcirculationpatternsandthuschang-ing moisture source areas might have affected our record,thoughthiseffectisdifficulttoquantify.

Fig. 13. Stratigraphy, organic carbon content (Corg) and δD measured on the n-alkanes nC27, nC29 and nC31 (in blue, red and green; the mean value is displayed in grey) from the Tumara LPS. More negative δD-values are interpreted to reflect colder paleotemperatures. Correlation with marine isotope stages (MIS) is shown to the right (Zech et al. 2010b).

Abb. 13. Stratigraphie, organischer Kohlenstoffgehalt (Corg) und ermittelte δD-Werte für die n-Alkane nC27, nC29 und nC31 (in blau, rot und grün; Mit-telwerte in grau) der LPS Tumara. Stärker negative δD-Werte lassen sich mit kälteren Paläotemperaturen erklären. Die Korrelation mit den Marinen Isotopen Stadien (MIS) ist rechts dargestellt (aus Zech et al. 2010b).


Fig. 14: Stratigraphy and δD of nC29 and nC31 from the Crvenka profile, compared to the δD record from Vostok and the δ18O record from the Soreq/Piqiin speleothems (scaled to reflect respective δD changes based on the meteoric water line). Many factors, such as temperature, changes in precipitation, atmos-pheric circulation patterns, source effects and evaporative isotopic enrichment, need to be considered for the interpretation of the LPS δD-values.

Abb. 14: Stratigraphie und δD-Werte der n-Alkane nC29 und nC31 der LPS Crvenka. Im Vergleich dazu die δD-Kurve des Vostok Eisbohrkerns und die δ18O-Kurve der Soreq/Piqiin Speläothemen (umgerechnet auf entsprechende δD-Werte anhand der Meteoric Mater Line). Zahlreiche Faktoren, z.B. Temperatur, Niederschlagsmenge, Veränderungen der atmoshärischen Zirkukation, Quell-Effekte und Isotopenanreicherung durch Verdunstung müssen bei der Inter-pretation der LPS δD-Ergebnisse berücksichtigt werden.

Itshouldbeacknowledgedatthispoint,thatadetailed,robustdeconvolutionofall these factors isnot trivial.Ne-vertheless, we would like to point to a second interestingfeatureof our record.The temperaturedifferencebetweenthe Holocene and the Eemian basically accounts alreadyfor the differences in alkane dD. This might indicate thatthe Mediterranean source water effect, from which onewould infer more positive isotope values during the Ho-locene,wasoffsetbyotherfactors,forexampledifferencesinaridity. Ifcorrect, thismightdocumentthattheEemianwas more arid than the Holocene, an interpretation thatwouldbeingoodagreementwiththealkanepatternsthathavebeenused(furtherabove)toinfermoregrassvegeta-tion(steppe)duringtheEemian.

WesummarizethatdDrecordsfromalkanesinLPSpro-videvaluableinformationaboutpastclimaticandenviron-mental changes, but that deconvolving the various factorsinfluencing dD can be challenging. Apart from tempera-ture,changes inprecipitation,atmospheric circulationpat-ternsandsourceeffectsshouldbetakenintoconsideration.

3.5 Compound-specific δ18O-analyzes of monosaccharides

Similartodeuterium,the18Oconcentrationinprecipitationdependson climatic factors and thereforehashighpoten-tialaspaleoclimateproxyinappropriatearchives.Likewise,however,bulksoilor sediment isotopeanalyzesusingTC/EA-IRMShave thedisadvantage thatmanydifferent inor-ganic (carbonates, water from clay minerals) and organicpools contribute to the pyrolytically produced CO, whichhence represents a mixed signal (see Fig. 3). Furthermore,notalloxygenpoolsinsoilshaveaclimatesignalincorpo-rated,asforinstanceoxygeninlignindoesnotderivefromwater,butfromtheatmosphere(Schmidtetal.2001).

Inloessresearch,attemptshavebeenmadetoobtaind18Orecords from pedogenetic carbonates, mollusc shells, andcrystalwaterinclayminerals(Kuleshov&Gavrilov2001;Pustovoytov &Terhorst 2004). However, in contrast tocarbonatesfromstalagmites,itismuchmoredifficulttogetwelldatedandcontinuousrecords,withpotentialrecrystal-


lisationpresentingamajorchallenge.Analternative,moreelegantapproachmightbetoemployagaincompound-spe-cificisotopemethods(Fig.15).

Itiswellknown,forexample,thathexoses(glucose,man-nose andgalactose), deoxyhexoses (fucose, rhamnose) andpentoses(xylose,arabinose)areplantandmicrobialbiomar-kers in soils (Gross &Glaser 2004; Sauheitl et al. 2005;Jiaetal.2008).Plant-derivedmonosaccharidescouldthusbemeasuredinsoilsandsedimentsviaGC-Py-IRMS(Fig.15).AlthoughtheinstrumentalcouplingofGC-Py-IRMSiscom-merciallyavailableforabout10years,thismethodhashard-lybeenadoptedbyresearchessofar(Heneretal.1998;Jungetal.2005; Jungetal.2007;Greuleetal.2008).We thinkthatthefollowingd18Omethodmaybemostpromisingforloessresearchinthenearfuture.MoredetailsaredescribedinZech&Glaser(2009):- hydrolytic extraction of cellulose- or hemicellulose-de-

rivedneutralsugars,suchasglucose,xylose,arabinose,fu-coseandrhamnosefromsoils/sediments

-purificationofthemonosaccharidesusingXAD-(remo-valof organic contaminants) and Dowex- (cation exchangeresins)-columns

- derivatization of the monosaccharides in order to makethemGC-amenable

- GC-separation of the individual monosaccharide-deriva-tives

-‘online’pyrolysisoftheGC-eluatesandquantitativecon-versionintocarbonmonoxide

-‘online’d18O-determinationfortheCOintheIRMS.

Asquality tests during themeasurements, the authors re-commend to regularly (i) co-analyze not only the massesm/z 28 and 30 (C16O and C18O, respectively), but also themassesm/z44and46(C16O2andC16O18O)inordertomini-mize isotope fractionation effects due to not quantitativeCO-production (ii) co-analyze n-alkanes in order to checkfor oxygen contamination in the system, because alkanescontainnooxygenatomsandmustnotproduceCOpeaksinthechromatograms(iii)runbatchesofexternalmonosac-charidestandardswithknownd18Osignaturesandvaryingconcentrations in order to check for amount-effects of thed18Omeasurementsand tostickascloseaspossible to the‘PrincipleofIdenticalTreatment’ofsamplesandstandards.Of course, when interpreting d18O records from LPS, oneshouldkeep inmind that theoxygen isotopiccompositioninplants(andpreservedsoilorganicmatter)doesnotonlydependond18Oinprecipitation/soilwater,butissimilartodDcontrolledbyevaporativeenrichmentandbiophysiologi-cal fractionations, too (Scheidegger et al. 2000; Barbour2007;Cuntzetal.2007).Nevertheless,ourproposedmethodmightprovidevaluablenewproxiesfromLPS,whichcouldbe directly correlated with otherd18O records derived forinstancefromice-cores,stalagmitesordeep-seasediments.Furthermore, the combination of dD- and d18O-analyzesmighthelptoassessthedeuteriumexcessfromLPSrecordsand thus help to deconvolve in future the varying factorsinfluencingtheisotopicrecords.Zech&Glaser(2009)high-light that the new d18O method could potentially help toevaluateandimprovepaleolimnologicaland-climaticstud-

Monosaccharidesglucose, arabinose, xylose

hydrolysis

purificationBulk soil/sediment/

wood sample

cellulose,hemicellulose, lignin,

clay minerals, minerals etc.

derivatisationderivatives

(1,2) = plant-derived sugars arabinose (1) and xylose (2)

21

injection

GC Py IRMSCO

Fig. 15: Principle of compound-specific δ18O analyzes of plant-derived monosaccharides in soils. Monosaccharides are released hydrolytically from a soil/sediment/wood sample and derivatised after purification. The sugar-derivatives eluting successively from the GC-column are converted online to carbon monoxide (CO) and the 18O/16O isotopic composition of the gas is measured via a coupled IRMS.

Abb. 15: Prinzip der substanz-spezifischen δ18O-Analytik pflanzenbürtiger Einzelzucker in Böden. Einzelzucker werden hydrolytisch aus Boden/Sediment/Holz-Proben gewonnen und nach Aufreinigung derivatisiert. Die nacheinander von der GC-Säule eluierenden Zucker-Derivate werden im ‚online‘ Verfah-ren in Kohlenmonoxid-Gas (CO) umgewandelt und dessen 18O/16O Isotopenzusammensetzung in einem gekoppelten IRMS gemessen.


ies targeting lake cellulose ford18Oanalyzes (Wolfeet al.2001;Wolfe et al. 2007;Wissel et al. 2008). Replacing theTC/EA-IRMSmeasurementsontheextractedcellulosewithGC-Py-IRMSmeasurementsonthehydrolysedsugarmono-mers can overcome the common challenges of the currentmethods,namelypurityafterextractionandhygroscopicityofthecellulose.

Case study: Oxygen isotopic fractionation/exchange ef-fects during litter decomposition? Inafirstapplicationof theabovedescribedmethod,Zechetal.(2011)used5differentlitterspecies(maple,beech,ash,pineandspruce),whichweredegradedina27monthsfieldlitterbagexperimentinordertoevaluateisotopicde-grada-tioneffectsduringlitterdecomposition.Whilethebulkd18Ovaluesbecamesystematicallymorenegativeduetorelativemassincreaseoflignin(rangingfrom145%inbeechto235%inpinelitter)andrelativemassdecreaseof(hemi-)cellulose(rangingfrom31%inmapleto67%inash),thecompound-specificd18Ovaluesofthemonosaccharidesrevealednosys-

tematictrendovertime(Fig.16).Thiscorroboratesthegen-eralnotionthatisotopicsignalsofindividualcompoundsareonly negligibly affected during mineralisation, and it alsoindicates that oxygen exchange reactionsof thehydroxyl-oxygenatomsdonotoccur.

Havingdemonstratedtheabsenceofdegradationeffectson the 18O-(hemi-) cellulose proxy, ongoing work focuseson(i)eliminatingtheoxygenatominC1position,whichispronetoexchangereactionduringanalyticalprocedureandcorrected mathematically, so far, (ii) calibrating the proxywithappropriatesamplesetsfromclimatechamberexperi-mentsandnaturalclimatetransectsandon(iii)applyingtheproxytopromisingLPS.

4 Concluding remarks

Giventhemeanwhileextremelywiderangeofverydifferentanalyticaltoolsbeingemployedinloessresearch,includingnumerical dating, micromorphology, mineralogy, elemen-talanalysis,environmentalandpaleomagnetism,grainsizeanalysis,andbiomarkerandisotopeanalyzes,weconcludethatmulti-disciplinaryandmulti-proxyapproachesaremostpromising.

Wehope thatour review illustrated the fascinatingpo-tentialoftheselectednovelmethodsinloessresearch,andalso provided an overview over the current shortcomingsand limitations.Ongoing joint research is required to fur-therdevelopandapplythenewmethods.

Acknowledgements

The authors gratefully acknowledge the support providedby the many cooperation partners world-wide during thelast few years. M. Zech and B. Buggle thank all membersof the Soil Physics Department, University of Bayreuth,for the familial working atmosphere, A. Mergner and KJeschke for laboratory assistance, PD Dr. M. Fuchs, Dr. U.Hambach and Dr. G.Wiesenberg for valuable discussionsand Prof. B. Glaser, Prof. G. Gebauer, Prof. B. Huwe andProf. S. Markovic for logistic support. B. Buggle appreci-ates the financial support given by the German ResearchFoundation(DFGGL327/8–2)andM.Zechexpressesgrati-tude for thefinancial supportgivenby theAlexandervonHumboldt-Foundation and the German Research Founda-tion (DFGZE844/1–1).R.ZechwassupportedbyanSNFfellowship, and gratefully acknowledges the supervisionandtrainingbyProf.Y.HuangandhisteamattheBrownUniversityoverthe last twoyears.WealsothankProf.M.Frechenfortheeditorialhandlingandproof-readingofourmanuscriptandananonymousreviewerforvaluablecom-mentsandsuggestions.

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Novel methodological approaches in loess research ...Fig. 3: Principle of bulk TC/EA-IRMS δD and...

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