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This document is the accepted manuscript version of the following article: Ladd, S. N., Maloney, A. E., Nelson, D. B., Prebble, M., Camperio, G., Sear, D. A., … Dubois, N. (2021). Leaf wax hydrogen isotopes as a hydroclimate proxy in the tropical pacific. Journal of Geophysical Research G: Biogeosciences, 126(3), e2020JG005891 (21 pp.). https://doi.org/10.1029/2020JG005891

Leaf Wax Hydrogen Isotopes as a Hydroclimate Proxy in the Tropical Pacific S. N. Ladd1,2*, A. E. Maloney3,4, D. B. Nelson5, M. Prebble6,7, G. Camperio1,2, D. A. Sear8, J. D. Hassall8, P. G. Langdon8, J. P. Sachs3, and N. Dubois1,2

1Swiss Federal Institute of Aquatic Science and Technology (EAWAG), Dept. of Surface Waters – Research and Management, Dübendorf, CH. 2Swiss Federal Institute of Technology (ETH-Zürich), Dept. of Earth Sciences, Zürich, CH. 3University of Washington, School of Oceanography, Seattle, USA. 4Princeton University, Dept. of Geosciences, Princeton, USA. 5University of Basel, Dept. of Environmental Sciences-Botany, Basel, CH. 6University of Canterbury, School of Earth and Environment, Christchurch, NZ. 7Australian National University, School of Culture, History and Languages, Canberra, AU. 8University of Southampton, School of Geography and Environmental Science, Southampton, UK.

Corresponding author: S. Nemiah Ladd ([email protected]) *Current address: University of Freiburg, Ecosystem Physiology, Freiburg, DE Article Key Points: ● Leaf wax 2H/1H ratios are correlated with mean annual precipitation 2H/1H ratios globally, but not in the tropical Pacific ● Deviations from the global relationship between precipitation leaf wax 2H/1H ratios cannot be predicted from palynological assemblages ● Small range and large uncertainties in estimates of tropical Pacific precipitation 2H/1H ratios likely account for poor correlations

Accepted line. Our results suggest that Ourthat line. results suggest of the small rangeof the small of correlations Rather, calibration poorobs line. the particularpollen betweenof typerelationshipany PalynologicalPacifrommodels.analyses these same values at some Pacific sites. However, tropical Pac However, at valuesPacific tropical some sites. Abstract Abstract Earth’s climate system. Geochemists reconstruct pas reconstructGeochemists Earth’sclimate system. mean annual precipitation ( meanannual precipitation and regression line are no greater than those observed regressiongreater those are than no line globalcalibration, the an range on based values of Plain Language SummaryPlain Language precipitation. sediments and soils. Globally, there is apo strong sediments is Globally, there and soils. global to anupdatedtropical 15coPacific islands correlated with estimated correlated with estimated to addto reconstructwe past Here, hydroclimate. this threshold exits exits in both improvedthreshold this understanding in the antropicalchanges Pacific in precipitation

Hydrogen isotope ratios of sedimentary leaf waxes ( of sedimentary Hydrogen leaf isotope waxes ratios Past precipitation patterns are difficult toreconsare patterns difficult Past precipitation 28 -acid(R 2 = 0.74, n = 242). Tropical 0.74,242). = = Pacific n δ 2 H P δ values relative to the typical residuals around th valuesresidualsaround relativethe typical to 2 δ H 2 δ H P 2 values from isoscapes or from isotope-enabled gene valuesorfrom isotope-enabled from isoscapes H P values) and the leaf waxes values)andwaxes the leaf Wax values are currently most suitable for use in detevalues most in use areforcurrentlysuitable δ 2 d elsewhere, but that ample room for roomimproving elsewhere, that ample but d erved in the tropical Pacificareatropical ervedfunction in the likely H sitive linearbetween correlationsitive mpilation of published data from mpilation surface data of published elsewhere,uncertainties despitein large d the largest residuals from the globalfromlargest the residuals the d distribution and deviations from the global deviations andfrom distribution the ific Wax of t precipitation by amountoftmeasuring precipitation by the fic sediment samples suggest no sediment ficsystematic suggest samples δ values from 19 lakes and fromfour values onswamps lakes 19 2 δ δ H truct, limiting our ability to understandlimiting to ability truct, our 2 2 H H variability in plants, asas wellin variability in plants, H Wax Wax δ n values fall within the predicted fall values within 2 -C H values in isolation values are not 29 Wax -alkane (R values) are increasingly used e globale calibration 2 = 0.74, n = = n0.74,665) = δ ral circulation ral 2 H values of H of values cting large large cting δ 2 H P

with much higher temporal resolution is thanpossib much resolution with temporal higher Lacustrine region.andyears s the past 600 in this Linsleyal.,DeL 2007; et Calvo 2004; et al., 2006; et al., Quinn 1993; et (Quinn al., 2014) coralsand havefrom paleohydrologicestablishedbeen records records (Hass highcontinuous producingresolution, which region,arein this because of limited partly andbe constrained valida Theseto need predictions Pacificet(Tan al., 2015; changetropical over the 1 Introduction Introduction 1 to understandtool smaller this to use in t changes i but past precipitation, can showin changes large the region. pr smallwithin range Atof variability constrained best attributed to poorly estimates of the withinregion.Plant typeexists distributions areglobal cal the within that althoughshow values in le Wemeasured hydrogen waterfarming.heavy and rainfalland most the home planet intense on the to st However,calibration nocloud movement. existing allowing to correlatedus with local precipitation, oceans.soils, andH lakes, mud that accumulates in incorporated heavy the waxy naturally into hydrogen

This article is protected by copyright. All rights reserved. ThisAllarticleis rights by copyright. reserved. protected Accepted Article As Earth warms, precipitation frequency, intensity,As Earthwarms, precipitation do not explain correlation,which the lackexplain not is do of learn about rainfall intensity, rainfall temperature, and intensity, about learn he tropical Pacific and elsewhere. elsewhere. he andtropical Pacific heavyleafwaxes from hydrogen ancient esent, therelativelyin localand rain heavy hydrogen Sharmila et al., 2018; Brown et al., Sharmila 2020).al.,Brown 2018; et et wamp sediments can provide longercan wamp records provide sediments a lack of proxies archives andforsuitable lack a proxies of al., 1998; Hendy et al, 2002; Linsley Hendyet et al., al., 1998; 2002; al, mproved process-level understanding is needed mproved process-levelis understanding ong et al., 2012), but are generallyare butlimitedto al., 2012),onget populations that rely that for rain populations drinking on ibration error, no precipitation relationship error,ibration precipitation no eavy hydrogen in leaf waxes is strongly is in leafwaxes hydrogen eavy ted by robust reconstructions of past changes,robust ted byreconstructions lemarine from accumulating slowly all 2017).high-resolution all Existing speleothems (Partin et al., 2013; Maupin al., et 2013; et speleothems (Partin coating of leaves, which is preserved in is which coatingleaves, of udies include sites from the tropical Pacific, sites frominclude udies the tropical af waxes from tropical Pacificandislands tropicalwaxes affrom and spatial distribution will likely andwill spatial distribution 2019). applied toreconstruct applied (McFarlin et al., 2019) and from soil and etand (McFarlinsediments al., 2019) al., 2012; Schwab et al, 2015) (Figure 1). c al,al., Schwab 2012; etRecent 2015) al.,al., Bai2010; 2011), et al., Aichner 2008; et Ea Douglas&Freeman,al.,2013),et Polissar 2010; 2018)extended etandNelson 2013; t al., have been began surfacein E soils. efforts These calibration calibrations empirical throughbeenhas established based on the hydrogen isotopic composition based of isotopic the leaf hydrogen on Sachs2017; et &Sachs,Richey al., Hassall, 2016; (Sachs al.,Smi 2009; higheret temporal resolution usedhavepast hydroclimat to reconstruct also been et Prebbleal., Gosling 2019; Wilmshurst,et 2009; & (Southern,HopePask, changes1986; in the region archivesarewell-established eco sediments, of and hydroclimate dynamics (Bowen et al., 2019). al., 2019).hydroclimateet dynamics (Bowen increasingaccuracy,reco systemsmaking with their geologbe both material preserved transferredon to with hydrogenmean with isotopes of precipitation annual 1) (Sachse et al., 2012; Koneckyet al., al., 2012; 1)Hass 2016; et(Sachse

This article is protected by copyright. All rights reserved. ThisAllarticleis rights by copyright. reserved. protected Accepted Article One hydroclimate proxy suitable swampforsuitable and lakeOne hydroclimate proxy As is typical for organic geochemical proxies, the typicalAs is organicproxies, geochemical for δ 2 H P values are related to specificvalues processes, physical are related to δ 2 H P values in diverse locations (Sachse et valuesal., 2012; in diverse locations and Africa (e.g., Peterse et al., 2009; Garcin Africaal., et Peterse 2009; et (e.g., and urope (e.g., Sachse et al., 2004; Leider Sachseal., 2004; etet (e.g., al., urope ompilations of ompilations all, 2017).all, ttenburg et al., 2011; ttenburgal.,Konecky2011; et al., 2016; et suchal., 2020).sediments More recently, ic timescales, as well as modeled in modern modeled in as well as timescales, ic logical, anthropogenic, and broadanthropogenic,and logical, climatic with surface sediments from with surfaceand lakes sediments 2018; Sear al., 2020). 2018; et s s (Liu 2019) placed these &An, local e change in the western tropical Pacific tropical e in at the western change waxes ( o the Americas (e.g., Hou et the oal., Americas 2008; Hou (e.g., st Asia and the Tibetan Plateau (e.g., Jia et (e.g., PlateauJia Asia the Tibetan and st nstructions useful forpast nstructions understanding ( 1998; Stevenson et al., 2001; Prebble2001; & al., Stevenson 1998;et δ 2 H relationship betweenrelationship P ) δ sediments in the tropical Pacific is in the tropical sediments

on a global scale and have globalbeenhave and ascale on 2 and are a chemical signal that can and that are can signal a chemical δ H 2 H Wax Wax δ = (= 2 H values arecorrelated highly 2 Wax H/ from surfacesediments 1 H) McFarlin et al., al., McFarlin et Wax δ 2 /( H 2 Wax H/ 1 and H) VSMOW δ 2 H P −

incorporated offer another potential incorporated calibration another potential ta offer calibration. Firstly, different vegetationFirstly,ca calibration. types different Pacific. Direct measurements of Pacific.measurements Direct assessed. assessed. salinity effects, mangroveeffects,salinity t of swamps,treesadapted consist shrubs andwhich oronformer regions lagoons Additionally, coastal man oncommunitiesPacificinclude islands tropical K Sachseal., 2010; (Feakins2012; Sessions, etand leafnot between which is waxes, precipitation and uncertainties for statistical interpolations of interpolations uncertaintiesstatistical for compare temporally(GNIP)and limited are spatially δ IsotopesCalculator in Precipitation (OI the Online tropical Pacific However, existing global calibrations in acontext. tropical Pacific that has not yet been explored. yet explored. tropical hasPacific that been not Convergence Zone (SPCZ) and from mangrove swampsConvergence from and Zone in (SPCZ) b surfacefromsediments lakes collected influenced However, the impact of mangrove contributions mangrove to se However, contributions the impact of nearbyprecipitation intensity as plants freshwater

AcceptedH Article P from general circulation models (GCMs) in which which pr models (GCMs) fromcirculation in general Secondly, there is large uncertainty associated wit Secondly, associated uncertainty is large there Heremeasuredwe Two considerations make it important makeittoincludeTwo considerations tro δ 2 H Wax values. δ 2 δ H values of values seven H 2 H Wax δ 2 values may have the opposite response to changesresponseopposite valuesin to the may have H P from the Global Network of Isotopes in Precipitati in NetworkIsotopes ofthe Global from δ 2 n H -alkane and fiveand -alkane P n influencen community net such as those used for isoscape products andasused products thosesuchisoscapefor rget forrget (Ladd & Sachs, 2012; He et al., 2017).&Sachs, et (LaddHe 2012; global compilations do not include anyinclude globalnot do compilations PC; Bowen & Revenaugh, 2003). Estimates &Revenaugh, 2003).of PC; Bowen these islands are often covered by mangrovethese are covered islands by often constant among plant types or amongenvironments constant types plant ahmen et al., 2013). The unique plant unique The ahmen al., 2013).et ySouth Pacificfrom the precipitation o brackish to hypersaline Due water. to to hypersaline brackisho y endemic species (Gillespie yet al., 2013). species endemic(Gillespie d to other regions,resulting to otherin large d dimentary h estimatesh of δ pical Pacific data in the global the pical in Pacific data ecipitation ecipitation isotopes been have 2 fluenced by the Intertropical the fluenced by H Wax n δ measurements in the modern -alkanoic acid homologues from -alkanoic acid homologues 2 H Wax δ values been not has 2 H P in the tropical 2 H/ 1 H fractionation

on inland edge inland to the coast. samplescollectedfro or five were surface sediment at swamps All were of Guam. located and Micronesia t within weremangrove located swamps from obtained covered the surfac horticulture. Aquatic vegetation regions, in forested were many located sites other Mangrove tr al., 2014).(Sichrowsky et saline water w Lake Lalolalo(Fiji)Dranoniveilomoand (Wallis), brackifor Most the except were systems, freshwater bodies m-deepvolc to an 88 ephemeralshallow water Onetahi Tetiaroa, (Rimatu’u, on and ponds Oroatera, mean with aboveelevations Table(Figuresea 1, 1), the influence of plant communities on tropical on communities Paci plant the influence of Finally, algorithmswesetmodels. and of polle use Convergence Zone (ITCZ). WeConvergence Zone (ITCZ). consistent with the globalbetween relationshipwith the consistent islands distributed throughout the tropical Pacific throughout the distributed islands values. Weassess values. whether 2.1 Site description and collection Site2.1 sample description Materials 2 and Methods compounds (

This article is protected by copyright. All rights reserved. ThisAllarticleis rights by copyright. reserved. protected Accepted Article Surface sediments were collected from 19 lakes on 1 wereonSurface19collected fromlakes sediments n -C 29 -alkane and

δ 2 H n Wax

-C addsediment new surface fromvalues andPacific laketropical sedime swamp 28 -acid) from 19 lakes and four mangrove swamps on -acid)lakes15 mangrove on swamps fromfour and 19 δ 2 to an updated global compilation of global anupdated compilation to H some impacted by human activity, byparticularly somehuman impacted e of some lakes (Table 1). Additional 1).samples Additional (Table e oflakes some n-based vegetation reconstructions to evaluaten-based reconstructions vegetation fic fic m each swamp along a transect from along the a m from transect swamp each Wax ees surrounded Lakewhile ees Dranoniveilomo, surrounded level from 760 m (Lanoto’o, Samoa) mmto 1 level(Lanoto’o, from 760 sh (salinity = 17) coastal Lakecoastal17) = (salinity sh hich has a freshwater surface lens above hich lens above ahas surface freshwater FrenchPolynesia). Lakesfrom varied anic crater lake (Lake Lalolalo, Wallis).Lalolalo,anic (Lake lake crater δ sea level and submerged at high tide. Fourhighsubmergedatand sea level tide. modeledand he ITCZ throughout the Federated the Stateshe ITCZ throughout 2 H Wax δ 1 islands across the SPCZ regionSPCZ across the islands 1 2 H values. Wax measurements of two of these measurements two of of δ 2 H P values fromvaluesa diverse δ nts are nts 2 H Wax

2.2 Leaf wax extraction Leafpurification and extraction 2.2 wax analysis. wells rainwhenavintegratorsand suchcisterns as fromwater wereadjace collectedAdditional samples into compoundgel columninto chromatog usingSi classes surfLipids from mangrove the fromsample Nopovois. Krents from chromatographyby Vesalea was described gelLipid extract column. silica ml6 hexanea from th gelcolumnand aminopropyldiethyl from ether an the acid-containing Forf allsediments, these lake processedSamples were Dranoniveilomo followin from forchromatographyexcep lake surface allsediments sediments in 2012. Samples wereWhfrozen in stored sediments in 2012. Samples was handmaterial. uppermost trowel Acm 2 of or 1 WI, s Fortof Analyses lake USA).(Nasco, Atkinson, the field cm1 at in cores subsampled intervals was tube. with equipped a polycarbonate cm 6.3 diameter perc a cored Vesalea with and in 2017 were Nopovois a Hope 6.6 ID, (Aquatic with USA) fitted Research, those from Lakefrom those

This article is protected by copyright. All rights reserved. ThisAllarticleis rights by copyright. reserved. protected Accepted Article Maloney et al. (2019) described lipid extraction, s extraction, Maloneyetlipid (2019)al. described Watera the collectedsurface lake of wasfrom each Maloney et al. (2019) described the collection of m of Maloneyet the collection (2019)al. described

Dranoniveilomo, which was cored in 2010 with with 2010a Univ in cored Dranoniveilomo, which was raction was eluted with 6 ml6 in raction eluted with acetic 4% wasacid ailable. Samples were Samples priorailable. stored atto °C 4 and stored frozen in Whirl-Pak stored and bags in frozen plastic ion, saponification, and columnsaponification, andion, cm diameter polycarbonate core cmtube. core polycarbonate diameter t Dranoniveilomo, Vesalea, and Nopovois. Vesalea,Nopovois. t and Dranoniveilomo, used to collect the upper 1 cm of mangrove used cm the1 of upper to collect e alkane-containing fraction alkane-containing wasfraction e eluted with Unconsolidated upper sedimentUnconsolidated from these upper nt streams and long-term precipitation streamsprecipitation and nt long-term urface sediment wererestricted urface sediment to the irl-Pak bags. bags. irl-Pak ussion corer (UWITEC, Mondsee,Austria) corer(UWITEC, ussion raphy as in Ladd and Sachs (2017). LaddSachs(2017). and as raphy in ace sediments were extracted andextracted ace divided were sediments cher et al. (2019), and was identical etfor cherand (2019), al. aponification, and column column andaponification, g Maloneyet (2019). of al. the protocol ost lake samples. New samples lake ost include samples. New nd stored in screw-cap glass ndvials. stored in screw-cap ersal Percussion CorerPercussion ersal 2.3 2.3 al.describedLaddet (2018). in alkane and over 0.5 goverof0.5AgNO iso methyl (FAMEs) saturatedesters were acid fatty wereH 5%methylated with acids from lake sediments urea wasfraction lakeadducted samples, the alkane 2017). u for which was methylation, addedcorrected during eluting 8 mL of 100% hexane overg of mL0.5 AgNOofeluting 100% 8 hexane composition (Shimmelmann, Indiana University) was IndianaUniversity)m composition (Shimmelmann, Ladd program referencing described in isotopic and s Lake(2017). described LaddSachs sediment and in GC conductedpr the same were GC-IRMSwith analyses also Vs with resolvedare areaspeak homologues >15 chromatography – isotope ratio spectrometrymass (G chromatography isotope – GC program and instrumentation described in Ladd an describedLadd program GC in and instrumentation flame–chromatographygassamples assessed were by from mangrove surface sediments. Purity concentandsediments.from mangrove surface of

Samples were dissolved in hexane at concentrations hexane concentrations at Samples were in dissolved For mangrove surface sediments,For mangrove surface 29 Wax -alkane or measurements measurements n -acid homologues were quantified using the same GC were using the -acid quantifiedsame homologues n 3 -C -impregnated Si gel -impregnatedSiAcid weight). fractions (10%by 28 -acid when those compounds were sufficiently -acid abunda were compounds sufficiently whenthose n -alkanes were purified from a Si gel hexane fractiogel purified Sifrom were ahexane -alkanes 3 -impregnated Si gel-impregnatedFor weight). (10% by Si to isolate unbranched compounds. Fattycompounds. unbranched to isolate lated by elution in 8 mL of 4:1 Hex/DCM bymLin 8 Hex/DCM oflated elution 4:1 et al. (2018). Phthalic acid of knownPhthalicisotopic al.acid ofet (2018). sing isotopic mass balance (Lee et sing (Leeal., isotopic balance mass amples were analyzed with the same with the GC amplesanalyzed were reported. For samples, sediment reported.mangrove C-IRMS). rationsof d Sachs (2017). For Sachs dsamples, (2017). lake Cl in methanol for 12 hours at 70 °C, and °C, hours70and inmethanol at Cl 12 for ionization detection (GC-FID) using the detection ionization ethylated to to determine ethylated ogram and isotopic and ogramreferencing isotopic suitable for hydrogen isotope analysesforsuitable hydrogen isotope n δ -alkanes from mangrovefrom -alkanes 2 H values of other baseline- H values program and instrumentation were analyzed not nt for gas nt for δ 2 H valuesHH of n - n by by n accommodate the proximity of a given location givenproximityto ne accommodatea theof location gridded data spatial set u from high-resolution the those pixels (“OIPC pixels mean annualextractedthose standards as in Newberry et al. et (2017). standardsNewberry as in Germa Scientific,(TC/EA-IRMS;ThermoFisher Bremen, – Analysis analyzed Conversion/Elemental Thermal by water fro samplesAdditional Maloneyet (2019).al. Li-2130i, th Santa Picarro, Clara,(CRDS; using CA) LakeDranoniveilomoanalyzed campaign from were and w lakeof streamand most composition The isotopic Wat(2019). al.Maloney analyzedetand by reported Estimates2.4 of 2.5 Water 2.5 products. G specifically (Yoshimuraet the ECHAM, al., 2008), cl all predictedfor calculated averaging values by obtained manually from the web interface (“OIPC mea (“OIPC webfrominterfaceobtained the manually (Sturmal. LMDZ, et modelsand HadAM, MIROC isoGSM, from (SWING2)Group Intercomparison IsotopeWater t moisotope-enabledclimate as asBowen, well 2020), (Bowen 3.2 Calculator Precipitation(OIPC) version produc ofeach Model elevationlongitude,and site.

δ 2 H and δ 2 H δ 18 δ P P 2 values values O analyses H P values were extracted from different model product modelwere fromextracteddifferent values

δ 2 H”). The multi-model meanannualThe H”).multi-model imate models that employed spectral nudgingimatemodels that spectral employed sing a bilinear smooth function to sing function asmooth bilinear ts included the Online Isotopesincluded the Online ts in m the 2017 Vanuatu field campaignmVanuatuwere field the 2017 & Ravenaugh, 2003; IAEA/WMO, 2015; &2003; Ravenaugh, ighboring pixels and ighboring the pixels er samples from the 2012 Micronesian2012 fromfield er the samples e same conditions and as standardsin and conditions e same del contributions to the second Stablethesecond to del contributions ISSLMDZ andisoGSM, (nudged), n annualn Isotope Ratio Mass Spectrometry Mass Isotope Ratio he CAM, ECHAM, GISS ModelE, GISS ECHAM, he CAM, by Cavity Ring Down Down Spectroscopyby Ring Cavity ny) using the same conditions andconditions the same using ny) ater samples were atersamplespreviously , 2010). OIPC estimated were values 2010). , OIPC δ 2 H”), and alsoby H”), and extraction s using latitude, susing latitude, δ 2 H from values δ 2 H P value was valuewas amount of mean annual amountprecipitation were mean annual dinosterol of palynomorphs held in the Australasian Pollen and Sp andPollen in the Australasian palynomorphs held reachingleas atuntil calculated.continued Counts Lycopodiumclavatum 199 KOH, al.acetolysis) and10% (Moore et hot HCl, differences among lakes. Eachamongcm1differences lakes. theupperof the sediment portionwithin to de core annual precipitation. An exception was annual An precipitation. 2). The only lipids with significant correlations w with significantcorrelations 2). only lipids The Climatolog Precipitation as the Global estimated by 3.1 3.1 Results 3 IslandPacific e fromsynthesis of a regional plant types identification.vegetation (primary, seco The and counts Pollen2.6 Maloneyet al., 2019), In almost all cases, correlation coefficientswere In almost correlation cases, all values that are negatively correlated with mean ann correlated that with valuesare negatively mean meanannual

This article is protected by copyright. All rights reserved. ThisAllarticleis rights by copyright. reserved. protected Accepted Article δ δ 2 2 H Core poforsamples (including palynomorph analyses H δ Wax P 2 values, and positive for the relationship between andrelationship for positive values, the H thevalues tropical Pacific in Wax δ 2 values Pacif fromin the tropical surface sediments H P P values as calculated by the OIPC, nor with with normeanann asby calculated the OIPC, values L. tablets to allow the palynomorph and charcoal c the L.palynomorph tablets to allow charcoaland n -C 16 -acid, and 3 sample was processed using standard procedures (10 wassample using processedstandard n n -C -C 18 17 -acid, and the only significant correlations with -acid,t correlations the with onlyand significant -alkane, which, similarly to dinosterol, -alkane,had which, similarlyto dinosterol, negative for the relationship betweenrelationship fornegative the cology (Mueller-Dombois &Fosberg 1998). cology (Mueller-Dombois ith ith t 100 terrestrial palynomorphs. Reference 100 terrestrial t palynomorphs. ndary, dryland herbs, etc.) were determined were determined etc.)ndary, dryland herbs, termine modern baseline vegetation moderntermine baseline ual precipitation amount (R = -0.95; p = p -0.95; = (R ual precipitation amount y(GPCP) Project et(Figure al., 2003) (Adler δ , ore Atlas (Atlas ore 1). Samples were spiked with exotic with exotic Samplesspiked1). were 2 n H -C P 18 values were dinosterol from(datawere values dinosterol δ 2 -acid, llen and spores) were taken from llen spores) andwere H Wax apsa.anu.edu.au/ ic were not correlated with notic correlated were values and amount valuesmean of and n -C 17 -alkane, and ual precipitation amount precipitationamount ual oncentrations tobeoncentrations ) assisted with assisted ) n -C δ 2 33 H δ -alkane. 2 % Wax H he he

were greater than this at 5 sites sites 5for were greater atthis than glob residuals tropicalfrom the Pacific locations, 3.2 Tropical3.2 Pacific tentative. oftheseassessmentcorrelations C values rangedfromvalues δ bas therange expected measuredwere waxes) in leaf much factors besides OIPC estimates of muchestimates OIPC besides factors al., 2018; Fengal., 201al., Goldsmith 2019; et al., 2018; et w al., McFarlin 2019, as et &fromand 2019Liu An, surfacesediment fromsoil values and all available correlated 0.049) positivelyand with Vanuatu). Vanuatu). at(L compounds two sites greater for20‰than both (Table 1; Figure 3). Adding these new measurementsFigure new(Table Adding these3). 1; between were previouslytheir calculatedvalues, published y-intercept,coefficients for slope, correlation or Luvanet der al., Struck2020; 2020; et al., 2020;

Accepted ArticleH -alkane was only abundant enough to measure its its -alkane to measure enoughabundant was only Wax Tropical Pacific To compare new measurements from the tropical Pacif from Tomeasurements the comparetropical new and δ 2 H

δ Wax Wax 2 H P and values estimated from the OIPC (Figure 3). Tropica 3).(Figure OIPC estimated from the values −

δ δ 2 2 177 to 177 H values in the global context valuesglobal H context in the δ H 2 P P H (excluding new tropical Pacific use data), whichwe (excludingnew tropical

values of values − 139‰, n -C n δ -C

while those whileof those 2 29 H 29 δ -alkane sites 6for and P 2 -alkanesand H values (R = 0.95; (Figure = p 0.051)= However, 2).(R values P and/or uncertainty in and/or the global linear regression (Figure global linear 3). regression the 9; Li et al., 2019; Wu Daniels2019; Li et al., al. 9; et et al., 2019; Veen et al., 2020) has minimal impact onminimal the Veen al., impact 2020) ethas al linear regression line were within ± line linear were al within regression but 20‰, sidual values from the global regression fromlinearvaluessidual the data sets in in non-marine (compilationsdata sets settings ed on the global regression between linear the ed on ake Tagamaucia in Fiji and WhiteFiji Lakeand in ake in Tagamaucia ell as data from Nelson, 2013; Bakkelund 2013; as etNelson, data ell from δ n to an updated global to anupdated compilation of 2 -C n H valuesH in four samples,makingany -C 28 -acid ranged from 28 -acidsmost (thecommonly ic to the relationship defined byto the relationship ic n -C 28 δ 2 -acid l Pacific l H P affect

(TableResiduals 1). − to to assesshow n δ 175 to to 175 -C 2 H 29 Wax -alkane . At most At . − 119‰ δ 2 δ H 2 n H Wax Wax - , annual values were positively correlated with werevalues positively correlation coefficientbetweencorrelation from the 17bycompiled values randomly subsampling the 32‰ the rangePacificran 32‰ inthe (smallesttropical Phase 2 (SWING 2) model comparison. Forallcomparison. Phasemodelmodels, (SWING 2) 2 modelStabfromvalues eachthe climate included in were most highly correlated with with correlated weremost highly acid) (Figure 4). acid) 4). (Figure Correlation coefficients were always positive and t wereand always Correlation positive coefficients global (100 iterations for each possible 35‰ range with ma range35‰ with (100forpossible iterations each 4). The correlation coefficients and the 4).rangeand correlation of The coefficients became greaterand increasing thanwasvalues 100‰, (Figure 4). None of these subsampled data sets had these subsampled(Figuresets had Noneof data 4). sets with a sets with compoundsmorethan both were deviatio standard one tr generated the randomvaluesHowever, bysubsets. 100‰ (1,000 iterations each for the highest, each(1,000lowest highest, 100‰foriterations the whi the compiled 118‰), datawe so again subsampled iterations for each possible 50‰ range with maximum range50‰ with iterations each forpossible lowest correlation was with lowest was correlation with

This article is protected by copyright. All rights reserved. ThisAllarticleis rights by copyright. reserved. protected Accepted Article In addition to theOIPC,severalIn addition to water-isotope-enab We also contextualized variability in the tropical We in the tropical variability also contextualized δ δ 2 2 H H Wax P δ 2 values. We extracted values. H values were most highly correlated with with values correlated were most highly P range between 30 and 35‰ (0.43 ± range (0.43 betweenand for 30 35‰ 0.28 δ 2 H δ P 2 values from HadAM (R = 0.57) (Figure 5). For fromvalues(Figure0.57) (R 5). = HadAM δ H δ 2 2 Wax H H P P values obtained manually from the OIPC from = obtained 0.86). values the(Rmanually δ and values for all sites with surface with all for values sites or soil sediment 2 H P For estimates 5).(Figure δ 2 H P to the range in δ 2 H gefor ypicallyrange of when the high (>0.5) , and, middle ranges in P le WaterIntercomparisonIsotope leGroup, ximum ximum opical Pacific correlation opical coefficients for Pacific correlation values in the tropical Pacific plotted within Pacificwithin valuesplottedtropical in the ly scattered below this threshold (Figure ly scattered below this

n belownofrandom the sample mean value δ δ data 4,000 times and comparingthe times and data 4,000 Pacific data relative to the global relativethesetPacific data data to le restricting the maximum rangemaximumle the restricting to global 2 2 n H H led GCMs provide estimates of meanof led GCMsestimates provide -C P P values shifted by 10‰), and 35‰byand 10‰), shifted values values fromextractedvalues CAM the δ 29 n δ 2 -C H -alkane 59‰, for = 2 n H δ P -C δ 29 2 values shifted by shifted values 5‰). P 2 H values that were as small aswereas small values that H -alkane;±0.22 for 0.41 29 P P -alkane and-alkane values from OIPC values the values), 50‰ (20050‰ values), n -C 29 -alkane, n n -C n -C -C δ 28 2 28 H 28 -acid -acid,

Wax δ -acid = 2 H δ values n 2 Wax The δ -C H 2 H P 28

- (Figure 6; Table 2). Three sites sites had(Figure Three 2).6;Table andfore were low primary concentrations fern spore and aquatic plants never contributedmorethanaquatic and 23% never plants TaLake Pond,lakes surface(Onetahithree water at we Table (FigureAlthough were 2).most6; abundant group,except anyplant palynomorph other than sum most abund was Whenvegetation not forest secondary types pollen ass vegetation, thedominant are from 3.3 spectraandPollen3.3 spore = was0.86) (R intermediate themanuallyOIPC from (Fi0.82)gridded = dataOIPC spatial (R resolution model (R = 0.91). The lowest correlation was with was correlationwith modellowest 0.91). (RThe = the global the recent pollen sample is 12from– histo recent11 butcm), is sample pollen #1LakeThe fromsecond,contributions Harai ferns. greater(Figure these that One were6). of 20‰ than (Figure 6, Table 2). Three sites sites hadTable(Figure Three 6, 2). wet abundance Each aof andhad ferns high of these less of than relationship whichtwo poll have −20‰, 6; Table 2). However, at the third site with ansite at 2). with 6; Table the third However, WhiteLake),were abund (Tagamaucia spores fern and

This article is protected by copyright. All rights reserved. ThisAllarticleis rights by copyright. reserved. protected Accepted Article Pollen data are only available dataPollenforfiv are only available of three the Palynomorphs from most sites were indicative of hum were sites most of indicative Palynomorphs from δ 2 H Wax vs. vs. δ 2 H P relationship were less than −20‰ (Figure 6). Intw (Figure were less relationship −20‰ than 6). n n -C -C 28 28 -acid residuals from-acid global residuals the -acid residuals from-acid global residuals the n -C 29 econdary 6; Tableforest(Figure 2).taxa rically had high contributions fromricallyferns high contributions had gurecoefficientobtainedcorrelation The 5). δ -alkanethan less residual gamucia,Pond), herbs Veseleaand wetland , WhiteLake, , high relatively had 2 en data (Tagamaucia and Dranoniveilomo). en data (Tagamauciaand st taxa palynomorphs were most taxa abundant werepalynomorphs st , does not have recent pollen data (the mostdata does(thepollenhave , not recent land plants (80% and 37%,(80% plants land respectively) and of the observed pollen. ofpollen. the observed H at Lake Hut, where primary forest taxa forestLake primarytaxa at where Hut, tland plants covered more than morethe50%plantstland of covered than among the different models (Figure 5). models different 5). (Figure among the ant, fern spores contributed more to the ant, contributed fern spores ant (59% and 39%, respectively) (Figurerespectively) ant 39%, (59% and P values from extracted the high- e sites where sites e an disturbance to the catchment to the an disturbance n -C δ δ 29 2 2 H H -alkane residuals-alkane from Wax Wax −20‰ (Lake Hut),−20‰ o of o these vs. vs. vs. δ δ 2 2 H H P P relations

have highwetland from– andcontributions plants ferns global(Fig relationship adhere more to the closely subsequent preservation varies as much within archi muchvaries within aspreservation subsequent historythat suggests compilations the transit of l Thecompound(Figure for similar 3c andeither 3d). catchment areas, there is no significantno catchmentdifference is there areas, might have sedimentsanand soils different sources surfaceand to Mc soils (in contrast both sediments (in marine cont bysedimentscompilations excluding glo to addingdata, published addition our recently compiled literature regressionfrom values surfa of values the tropicalfal in isolation, Pacific sites uncertainty in the y-axis (variabletheuncertainty in thegloballyexists and the regression line within C have palynological features havethat clearly features palynological distinguis is dominatedby sec Nopovois, (Table third, The 2). 4 Discussion 4 remains robust with the addition of tropical Pacifi with remains the addition robust

Accepted29 Article -alkane (n = -alkane665) (n and = δ The positive linear relationship betweenlinearThe positive relationship Although the relationship betweenAlthough the relationship 2 H Wax values close to the global close valuesto the (Figure relationship 6) n -C 28 -acid (n = -acid242) (n (Figure = s considerable 3). However, 2 H/ 1 H fractionation between leaf waxes and water betweenamong leaf waxes H fractionation δ 2 H Wax Wax

l within the globallinear aroundthe the scatter within l δ 2 and eaf waxes from plant to deposition and from to deposition plant eaf waxes H tropical Pacific. Large residuals are due to to both are Large Pacific.due tropical residuals in the relationship between therelationship in h it from it h where sites c samples, with Rc samples, with bal data set differs from two recent recent differs bal fromdata settwo Wax Wax ure 6; Table 2). Additionally, some sites with with ureAdditionally, sites 2).some 6; Table ce sediments and soils (FigureInand1). soils ce 3; Table sediments Farlin in etleaf waxes Although al., 2019). Harai Lake #3, Lanoto’o, and Lakeand– Lanoto’o, Lake Otas Harai #3, d represent different timescales and differentrepresentd timescales ondary forest vegetation (54%) and does not(54%) ondary andvegetation forest does

ve type as it does between them. doesthem. asve typeit between ity between the soil and sedimentand soil itybetween the δ rast to Liu to including rast andand 2019), An, 2 and H P

values lacks any correlation for the correlation any lacks values δ 2 H .

P values in the global compilationglobal in the values 2 2 values of 0.74 forof values 0.74 both n -C 28 -acid δ 2 H Wax δ catter around catter 2 H values and δ 2 H n plant plant - P

( in in metabolis changes in plant with &and2015), Sachs, al et can(Newberry waterseasonally waxes vary and et Additional al., relative 2015). (Tipple humidity and typesal., 2006),leaves other et (Liubetween hydrogen isotope fractionation between plant waxes between waxes plant hydrogenfractionation isotope 5), well-establisseveral precipitation (Figures 3, the water source used by plants, discussed in secti plants, discussed in the waterby source used types and environments, discussed in section 4.1) a 4.1)section discussed in types environments, and 4.1.1 Mangroves Mangroves 4.1.1 4.1 Variable hydrogen isotope fractionation during fractionation Variable4.1 isotope hydrogen anomalous changesweinferred in vegetation that demonstrate at each site with the residuals betweenresiduals at with each the site δ –whos plants, andgroupsmangroves, aquatic ferns – a single within factors plant, such occur that can to di that might relate wefactors examine can only al.,He2014; al.,et SachseEley et et al., 2012;

AcceptedH Article α Wax Wax-P 1 H)

Although globalAlthough andvalues. By info distributions comparing pollen Wax can also exist amonggrowing exist the can at also species plant /( δ 2 2 H/ H Wax 1 H) values in tropicalsediments. Pacific surface in values P )) (Sachse et al., 2012). Variations in ))al.,2012). (SachseVariations et δ 2 H Wax valueswith correlated are well δ 2 H Wax Wax values and the global calibration line (Figure line global the6),andvalues calibration 2020). With set Pacific data tropical current 2020). the hed variability factors contributein the net to hed as metabolic state. We plantmetabolicthreeexamine as state. ly, biosynthetic fractionation between ly,leaf fractionation biosynthetic organs (Gamarra & Kahmen, 2015), and&Kahmen, organs with (Gamarra 2015), on 4.2). on 4.2). fferences among types of plants, and not typesplants, fferences of among nd in the x-axis (mean annual in the x-axis nd leaf wax synthesis synthesis leaf wax from pollen cannot consistently explain explain cannotfrom consistently pollen m (Cormier et al., 2018). Largem al., 2018).et (Cormier differences and precipitation ( e contributions ecommunitymay contributions impact ., 2015), with environmental stresses with (Ladd environmental 2015),., stresses α rmation about surrounding vegetation vegetation aboutrmation surrounding Wax-P same site (Feakins & 2010; Sessions, site (Feakins same δ 2 H occur among plant functional functional among plant occur P values of mean valuesmean annual of α Wax-P Wax-P = = δ 2 H P values andvalues spatial spatial variabilityin global (Table linearwith the consistent regression δ (~15%; Figure 6; Table 2). InLake Otas, Figure(~15%;6; Table 2). o mangrove pollen ofamounts East) have the highest pollencoas (Table 2).areas for and Two leaf waxes whichmaydiffer reflectthewassediment, found in Dr mangroves(Table the abundant around Despite 1). lake gr mangroves and waterDranoniveilomo, brackish had have was observed i freshwaterrelationship plants. This calibration line. calibration line. 2012; He et al., 2017; Ladd & Sachs, 2017), they sh Ladd & et He2012; 2017),al., 2017; Sachs, they waxes are influence waxes anonimportant not indicat that pollen to the extent data suggest that signi (Tableexpected impact of to the opposite 1), WaérowaInEast 1).Lake global (Table relationship in the tropical Pacific could result in sedimentary result Pacific in the in could tropical 2014). Because mangroves discriminate more against against discriminatemore 2014).mangroves Because coastalmattersediment large ofamounts to organic

Accepted ArticleH P values (He et al., 2020). Significant contribution Significantal., 2020). (Heetvalues n δ Mangroves are woody plants that grow t in brackish that Mangroves plants are woody Several of the lakes in our calibration lo Severalset were in our of the lakes Likewise, MicronesianmangroveLikewise,sedime surface swamp -C 2 H 28 Wax -acid is significantly depleted relative to the glothesignificantly-acid is relative to depleted ~50‰values from lighter nearby freshwa than those δ 2 H Wax values mangrove individual throughoutswamp, each δ δ 2 H 2 H Wax Wax values in tropicalvalues Pacific lake sediments. es mangrove leaf waxes to sediment,mangrovewaxes es these to leaf values predicted are close the to the values by

δ 1; Figure little 1; was3).there Additionally, ficant mangrove leaf wax contributions. These wax contributions. mangrove ficantleaf n the Florida the n mangroves whereEverglades, 2 ent transport mechanisms mechanisms and ent transportcatchment s in the tropics and s in the subtropics tropics (Alongi, tal lakes in Vanuatu (Otas and Waérowa (Otas and Vanuatu tal lakes in H ould ould lowerhave , they, areexpected than higher slightly bserved in all examined allsurface sediments examined bserved in Wax s of mangrove leaf waxes in in coastal areass of mangrove leaf waxes anoniveilomo, minimal mangrovepollen minimal anoniveilomo, 2 cated in coastal areas, but onlycated one, butin coastal areas, H as salinityH&Sachs, (Ladd increases owing directly in its periphery. In periphery.directly owing in its this values that fall below the global values fallthe that below bal calibration, but calibration, bal o hypersaline water. They contribute water.hypersalineo They nts had had nts ter trees, equivalentdespite trees, ter δ 2 δ H 2 Wax H Wax values than nearby than values n values were that -C 29 with with 5‰ -alkanenot is have lower alkanehave lower S (Table aquatic 1).floatingcoveredvegetation by reasons why aquatic plants may relativelyaquaticreasons plants low have why 4.1.2 Aquatic 4.1.2 plants mangroveswamps. consistent with with the surface consistentsediment wita usingswamp watermangroves throughout in all et (Santini mangrovesobservedhas previously been relativelywater. opportunisticallyfresh taken up awater access with to thereforeroot networks had and varying with spatially rai andtides temporally waterSurfacetime at w collection. salinity the of w from locations collected even were samples though s awithin standardamong samplessingle deviations Cernusakal., 2016).et leaf waxes from aquatic plants couldse plantsalso reduce aquatic leaf from waxes al.,He2020; et GaoDion-Kirschner e et al., 2011; becoming enriched enriched becomingin lake water, and it may therefore maintain lake andtherefore mayawater, it or water vegetaticoveredsimilarlilies aquatic by between leaf water and waxes. However,existinginv waxes. andbetween leaf water

This article is protected by copyright. All rights reserved. ThisAllarticleis rights by copyright. reserved. protected Accepted Article Some of the lakes included in the tropical Pacific Somein the included of the lakes δ 2 H 2 Wax Second, aquatic plants may exhibit greater exhibit may biosynth Second, aquatic plants H due to transpiration, as for leaves exposed to ai exposed to transpiration, dueasleavesH for to values than nearby terrestrial plants (Chikaraishi plants values nearby terrestrial than δ 2 H Wax δ values Micronesian observed from in transects 2 H signal similar to that of precipitation, rather t signal to that H of similarprecipitation, Preferentialfresherwater of byuptake dynamic as surveys,swamp throughout these on, there is a physical barrier to evaporation of to evaporation atherebarrier physical is on, n events. Individual mangrove trees with with largeIndividual mangrove trees events. n t al., 2020), differing relative contributions of contributions al.,2020), t differing relative ince aquatic plants at diverse ince to ataquatictend sites plants wide range of salinities and may widehave and range salinities of dimentary δ wamp (Table 1). This This wamp(Tablehomogeneityoccurred 1). al., 2015; Reef et al., al., 2015), al., Reef2015; could and result et 2 estigations of ith ith surface water ranging salinity from 0-31 h similar salinity and isotopic composition, similarh salinity isotopic and H survey were partially or completelysurvey were partially or Wax values. First,mostly lake values. is when a δ 2 H Wax δ 2 values. Therearea few H Wax r (Kahmenet al., 2013; insubmergedvalues etic fractionation etic &Naraoka, 2003; han aquatic plants does not unequivocally result in in dec result doesaquaticunequivocally plants not et HeOverall, al., et Kirschner2020). al., 2020; thereforeof low tohave tendthese concentrations moistureneed desiccation b the for little have and soldanella have similar regression line had palynomorph spectra characteriz regressionspectra had line palynomorph of somethe sites with linear However, regression. similar onlyat high suggest aquaticis this plantslikely by mats of aquatic plants (primarilymats byaquaticplants of ForL plants. example, lakescoveredallby aquatic global(Table relative theline 1). calibration to minimal sedimentary influence on globalfromthelarge residuals calibratio or small aquatic andfromAdditionally, wetland pollen herbs 4.1.3 Ferns 4.1.3 sediments. Fiji, which is covered in floating(S Fiji, islandssedge in which is covered sedimentary contributions of leaf waxes fromoffernsleaf sedimentarywaxes contributions We (Gao magnoliids therefore and 2014). ethad al.,

This article is protected by copyright. All rights reserved. ThisAllarticleis rights by copyright. reserved. protected Accepted Article High contributions fromHighcouldaquatic plantsexplai contributions Assessments of α Wax-P ), yet), α values to other plants (Aichner et al, 2017). (Aichner plantsal, etother to values Wax-P δ 2 H values to many other plant taxa, including to manylycopod taxa, other plant values Wax δ 2 values from its sediment fell close to the global c close to the values fell its sediment from H Wax Wax values from ferns are limited, but previous studiesbut valuesprevious from are limited, ferns δ 2 Persicaria Persicaria H Wax values because submerged plants arevalues of at because not plants risk submerged However, this relationship wasconsistent notin relationship However, this cf salinity, while plants grown infreshwatergrown display while plants salinity, our results suggest that increased presence of suggest presence that increased results our n line (Figure 6). Aquatic plants(Figure Aquaticmay line have 6). n outhern et al., 1986), were veryet were outhern al., 1986), . attenuata. arrier provided by long-chain leaf waxes. Theyarrierleaf long-chain by waxes. provided reased compounds (Ficken et al., 2000; Dion- 2000; al., compounds et (Ficken the largest residuals relative to the globalthe relative the to largest residuals ake Veselea in Vanuatu is is completely covered ake Veselea in Vanuatu would diverge from the global would diverge from the no expectation that sites with large sites with no that expectation ed by large contributions of contributions fern This large ed by spores. plants is not consistently associated is with not plants δ n whyn 2 H , Wax Salvinia molestaSalvinia δ values in tropicalvaluesPacific lakein 2 H Wax s, gymnosperms, eudicots,gymnosperms, s, atvalues inTagamaucia alibration line line (Table alibration 1). , and show that fernsshow that 2 H-depleted H-depleted δ Calystegia Calystegia 2 H Wax - δ 2 H P

n IslaLakes and in the #1Harai SamoaSolomon and #3 Additionally, Lake Hut in New Caledonia had the lar LakeinNew Additionally,the had Hut Caledonia Fi to the contrast direct global regression fit, in et al., 2018).et Additionally, al., δ year,hasdifferent the water and from diff seasons rather than a change arather in change than may in a down-core abundance record of spores fern 4.2 Uncertainty4.2 in between largeaccounts poorly a for likely and constrained contributions of leaf waxes from ferns do not have dofernshave not fromof contributions leafwaxes manyhave(Fig notdata, did pollen but spores fern may differ considerably from the long-term mean. Fi mean. from maythe considerablylong-term differ years see al., 2019 Maloney etdecades; few to two The time captured varyperiod values interannually. didsporesuniversally low not correspond to Fiji’s FiguLakein (Table 1; extent Dranoniveilomo Fiji Lakean was Tagamaucia particularly at in true values. Nevertheless, a shift in values. Nevertheless,a shift δ

Accepted e by Hnot typically of values water is usedplants H Article 28 Wax -acid

Variabilityin and

δ 2 H δ δ 2 Wax 2 H valuesH muchLakesfromthan were higher the Harai H P and and (Figure 3). However, unlike most proxymost However,unlikethe 3). systems, (Figure δ 2 α H δ Wax-P 2 P H δ values values 2 P H contributes to uncertainty in the y-axis uncertainty y-axis in the re in the to contributes values in the tropical Pacific. Pacific. in the values tropical δ P 2 values. values. H P δ values from the OIPC represent climatological meansclimatological represent OIPC from values the 2 H Wax values that coincides with a change in therelativvaluescoincides in change with that a δ 2 jian lakes and WhiteFigure lakes 1; Lakeand6). jian (Table H Wax portion of the linear regression residuals portion of the regression linear erent residence times in soil, meaning that the soil, residenceerent times in ure 6). Overall, this suggeststhis relative ure Overall, that 6). d White Lake in Vanuatu, and to to aWhite dandlesser Vanuatu, Lake in predictable effects on effectssedimentary predictableon for sediment accumulation rates at most ratessites) at for accumulation sediment by a surface sediment sample (typically (typically aby sediment a sample surface qual to meanqual to annual values, for example at Lake values,Lanoto’ofor example at in re 6). However, high accumulation offernaccumulation high6). However, re nally, the robustness of meanannual robustness of nally, the gest indicate a change in organic matterchange a sources in organic indicate nds (Tables 1 and 3; Figure these,Of (Tablesand6). 3; 1 nds δ 2 H n -C P values are not constant arethroughoutconstant notvalues 29 -alkane for site residual anywith the predicted fromvaluesthethe predicted x-axis calibrationtarget is x-axis δ lationship betweenlationship 2 H P values (Brinkmann values , but but , δ 2 e H Wax δ 2 H

P the large uncertainties in OIPC the largederived in uncertainties estimates of al.,al.,20Conroy2010; etenabledet (Sturm GCMs densityof amo estimatesthe variesOIPC by spatially provided values from isotope-enabled GCMs (Figure 5). GCMs fromvalues 5). isotope-enabled (Figure for theG New Islands, Vanuatu, Solomon or in Caledonia southeastern portion of the region, since there are region,sincethereofsoutheastern the portion (Table uncertainties usingthelarge have OIPC 1). likely contributes to the lack of a regional correl regional likelyof ato the lack contributes studythis T in formed.waxes surfacesediment leaf meansdataClimatologicalfrom may calculated these a collected 1968 (Truk) between observations 72 has observationscollectedfrom Yap GNIP 65 has station from based aof GNIP on limited number observations may confid false add Micronesia, uncertainties OIPC and ~55‰ andfor whether scatter in the global relationship between relationship whetherglobal scatter in the range in

This article is protected by copyright. All rights reserved. ThisAllarticleis rights by copyright. reserved. protected Accepted Article δ 2 H Limited An alternative approach for estimating meanestimating An approachalternative annual for P values from sites in Vanuatu are as large as 76‰, c areasin Vanuatularge from values sites δ 2 δ H 2 P H δ 2 values (~30‰) and the range in measured (~30‰) the rangeand in values P δ H n observations (IAEA/WMO, 2015). (IAEA/WMO, 2015). observations 2 -C P H values have not typically been used in havein beentypically not valuesused P 28 data from some sites in the tropical Pacific themeant tropical from sites in some data -acid) in the Pacific (Table 1; Figure 3). ForFigure -acid) in the 3).Pacificothe (Table 1; δ 2 H P values from some western Pacific sites, we sites, assesse Pacific fromwesternvalues some ation betweenation no observations of δ This is especially in the This is sites problematic for 2 his uncertainty in in the uncertaintyhis independent variable H 13; Steen-Larsen et al., 2017). These Steen-Larsenal., 13; et ng geographic settings due to to the geographicunevendue ngsettings nd 1977 (IAEA/WMO, 2015). nd (IAEA/WMO, 1977 ence to predicted values, as these can values, beasence these to predicted can 1968 to 1976, and the station onstation Chuuk the 1976, and to 1968 not be representative of conditions when of representative conditions be not Wax several decades ago. For the decades ago. example, several NIP database. 95% confidence NIP database. intervals 95% δ δ 2 2 and and H δ H 2 onsiderably larger the thanoverall onsiderably larger Wax Wax H δ P δ 2 calibration studies. calibrationBecausestudies. of values is to use is valueswater-isotope- to values (~40‰ for(~40‰ values 2 H H P Wax Wax could be be reduced could using r sites, such asin those sites, r δ hat hat and 2 H P δ values from the δ 2 H 2 H P P P values calculatedvalues values (Figure 3). (Figurevalues 3). n- C 29 -alkane δ 2 H P

d each other. However, the leewardwesterneachHowever, the sites other.shou exclusively from North America (Figure 1). Sitesfr(Figure exclusively1).America from North sites that receive rain from moremarine that masses airreceiverain sites from considerable challenge for assessing thefidelity o assessing challenge considerablefor OIPCfrommodern the or estimates uncertainties in predicted Himalayas and Tibetan Plateau (Figure 1). Here, ste PlateauHere,Himalayas 1). (Figureand Tibetan globally i more and aredistributed, more numerous, by isotope-enabled GCMs than than by isotope-enabled GCMs does not suggest any structural limitations to usin anyto limitations doesstructural suggest not calibration. However, the calibration.limited However, the the distinct spatial distributions spatial of distributions the two calib the distinct processes may transport waxes between regions with with waxes between regions processesmay transport theresolut spatial smallerscaleson that than are OIPC predicts equivalent OIPCequivalent predicts Therefore,minimal availabl stations. data is local in the southeast locatedcorner is Pekoa at airport 2011). However, the the (Terry, onl thaneast coast in the rain shad sits from coast the east,west the Vanuatu Santoof 2000 island Espiritu are nearlyin prappropriate water calibration forisotope target GCMs,causing by the or either OIPC isotope-enabled

This article is protected by copyright. All rights reserved. ThisAllarticleis rights by copyright. reserved. protected Accepted Article Ingeneral, In particular, the orographic mountainou effects Inof orographic particular, the δ 2 H P values from water-isotope-enabled GCMs each on fromcoa valueswater-isotope-enabled δ 2 H Wax values from δ 2 H P values for sites on opposite Sacoastsopposite of Espiritu values foron sites δ 2 δ H 2 Wax H n P -C fromvalues measurements frommeasurements and Pacific resultin the tropical 28 -acid are better correlated with -acid correlatedarebetterwith ration data sets, with fatty acid fatty acid with data sets, ration ow of the mountains and is significantlymountains ow drier ofis and the ion of most models, mostaeolianandand of fluvial ion of the island, and there local of are noGNIP the there island, and oxies. For on the the highest peaks example, oxies. e to inform precipitation isotope models. informThe e to precipitation gtoestimate the OIPC f f y long-term weather station forySanto Espiritu weather long-termstation (Scholl et al., 1996, 2007). This (Schollexpectation et al., 1996, 2007). δ m above sea level. With windsprevailing m sea abovelevel. om whichom n ep elevation gradients makeepmay elevation nclude many from measurements the isotope-enabled GCMs remainsGCMsa isotope-enabled 2 ld lighter ld have -C H distinct distinct particular challenges determining particularchallenges the Wax 29 s islands may s islands benot captured adequately -alkane. This difference may-alkane. to be This difference due values in this region. values in this δ n 2 -alkane -alkane H P values.Overall,analysis our δ 2 H st are within a few within of ‰ st are P δ values thethaneastern values 2 δ H areavailablevalues δ 2 H 2 H P P values proxyforvalues values generated values δ nto, and and nto, 2 H almostvalues δ 2 H P vary g large leaf waxes, and the different controls on their onleafcontrols the different and waxes, sources. primarilyThese algal are typica compounds completely resolve sources of down-corevariability resolveof completely sources 4.3 Contrasts with with Contrasts 4.3 S2). Set coastwindward(Data east westthe leeward40–on ‰ which are 20 by depleted In addition to the longer chain to the longer In addition is supported is by the Pacific from higher plant waxes, we also measuredwe also fromwaxes, plant higher maritime regions where the amount effect plays a st playsamount effect amaritime the where regions δ between t correlation amount An inverse 2). (Figure al., 2004) and with (consistent Sachse inversely et 4.3.1 Algal 4.3.1 lipids compounds produc fromubiquitous andalgal sources, (Dansgaard, 1964; Rozanski et al., 1993; Kurita etal.,Rozanski (Dansgaard,1993; et 1964; (Cranwell et al., 1987; Meyers, 2003), werealsopo Meyers,(Cranwell et2003), al., 1987; (Volkman, (Volkman, 2003). The et which (Maloneyal., case 2019), dinosterol for i

AcceptedH Article P (andvalues therefore Unlike δ 2 H P values and mean annual precipitation amount (Figur meanannual andvalues precipitation δ 2 H Wax δ δ 2 2 H valueslipids ofnon-leaf wax H values of lake and stream waters andduring of lakecollected stream H values values, δ 2 H valuesH of δ 2 H values of lipids that trackH that of values lipids δ 2 H values of algal biomarkers are well correlated wi Hcorrelated are well ofvaluesalgal biomarkers n n -C -alkane and 17 -alkane, which is primarily derived from-alkane,algaeprimarily which is derived δ 2 δ H values from several compounds orof mixed from compounds several H values 2 H values offer the opportunity H to more offer values the opportunity correlated with mean annual precipitation correlated with mean annual s s primarily dinoflagellates by produced al.,2009). sitively correlated sitively with n- rongdetermining in role in he amount of mean annual precipitationmean he amountof and annual lly found in sedimentary records along llyrecords with sedimentary found in ern side of the island comparedernisland sideof to the the alkanoic acids that are primarily derived derived acidsalkanoic that are primarily ed by mostorganisms. ed by δ 2 H δ 2 Wax H P

) is expected ina low-latitude expected) is values. Here welipids discuss e 2). This is is particularly the eThis 2). our field campaigns, our δ 2 δ H 2 H P values P values values th th tropical waxes from higher plants growing reflec may fromonwaxes land plants higher waxes soon after setting new leaves, resulting in a newresultingleaves, soon after in waxes setting the tropical at40‰ can Pacivalues byto up differ values thanvalues 2003; Gao et al., 2014; Nelson et al., Nelson 2017; al.,GaoNelson 2003; 2014; et al., al., 2020). &(Bush aquatic2 terrestrialand McInerney, plants be transported long distances and have be have transportedand distances long s accumulating in leaf20% Additionally, of > waxes sizecatchment a catchment,of the relative and the their adjacentdepoc derivedto growing plants from overlayingthelakespacesediments or pond the of lipids that more that meanannuallipids closely track year,mayannu integratethroughout the they better Fr et (Tipple al., transferred 2013; waxes to their acetogenic acetogenic compounds, including manymi of 4.1, the leaf discussed in section waxes range sources morecomefromlimited aof potential contributions, whilealways the algal contributions, are compounds waxes re may Breethe leaf Therefore al., 2018).et different trends differentin their trends

This article is protected by copyright. All rights reserved. ThisAllarticleis rights by copyright. reserved. protected Accepted Article One reason why Another reason why algal biomarkers track may Anotherreason algal why Finally, the spatial variabilityFinally, by spatial each integrated the n δ -C 2 H 28 Wax -acid can also be partially derived from-acidmicroalgal can derived also be partially values might relate to the source water used by ea might valuesbywater relate used the source to δ δ 2 2 H H values from the algal biomarkers are better corre fromarebetter the Halgal biomarkers values Wax values. Algal lipids are produced within the relatiarethe values.Algal produced within lipids n -C 29 δ -alkane and 2 H values distinct from local vegetation (Conte et froma distinct localHvegetation values δ 2 H P values. values. eimuth et al., 2017). If etare algae eimuth al., 2017). productive theseasonal bias in fic sites. Higher primarilyleaf sites.ficplantsproduce rea can differ among water bodies. among water reacan differ et al., 2018). Leaf wax aerosols Leaffrom al., 2018).very wax et aerosols present variable aquatic and aquatic terrestrial present variable al precipitation, therefore resulting in algal resultingprecipitation, therefore alin in which they accumulate. Leafwhichcan accumulate.in waxesthey be d-chain and long-chained relativelyd-chain 013; Andrae et al., 2020; Andraeetal.,Dion-Kirschner 2020; et 013; n enter, but also from further afield in the inthe enter,further afield also from but . Infortherange of sources addition . plant to aquatically sourced. sourced. aquatically ediment can come from aerosols, whichedimentcan from aerosols, can come -C t a temporal bias, as monthlytemporal t OIPC a bias, 28 type of compound could explain theof compoundcould explain type δ -acid,of can bemix derived from a 2 H P better than leaf waxes is that that they waxes better is leafthan sources (Volkman, 1980; van (Volkman, 1980; sources ch type ofLeaf organism. ch type δ 2 H P signal that is lated with with lated vely confined confined vely δ 2 δ H 2 H l., l., P

P algae. Inalgae.either case, also vary could non-photoautotrophs, but to dif due acids acids that can have Lichemoautot Heterotrophic 2004; al.and et 2009). al are frequently attributed mostbutto organisms, This large This range in coincidence. Dinosterol and coincidence. Dinosterol and C microbial mats (Osburn et al., 2011), sedimentary al., microbial matset (Osburn Heinzelinsimilargrownet water al., (Zhang2009; hydroclimate, and their negative correlations with with andhydroclimate,correlationsnegative their 4.3.2 Generic 4.3.2 fatty acids mustgrea bewaxescarried non-localallwhere leaf of local leafcontribution the overallhand, waxes arelatively is contiguous area land smallerto con may sites lakemore havedistant impact on sediment factors between lake water factorsandlake water between Inet Zhangal., 2018). al., Heinzelmannet 2009; o fromvalues with fractionation factors p consistent and negatively correlated with with negativelyandcorrelated of the of algae (Zhang and Sachs, 2007; Zhangal.,2009 et2007; (ZhangSachs, of andalgae

Accepted Article16 and n In contrast to the algal specific biomarkers Indinost biomarkers specific contrast to the algal -C n -C 16 18 and

fatty acids were positively correlated with theamo with fattyacidswere positively correlated n -C α δ 18 2 Lipid-Water δ H values that differ by several hundred‰thos by from that several differ H values -acids in our dataour be -acidsinfluenced couldvaria in byset 2 H values of these compounds valuesreflectlikelycompounds of ecology these H n values is consistent observationsofis values consistent cultures with -C δ n 2 17 -C H -alkaneoforganisasmaller range fromare sourced P 16 (Figure 2). These shorter chain fatty acids are acids syn chain fatty 2). shorter(Figure These and n -C 18 -acids( tribute regional and local waxes. On regionalOn the waxes.other tribute local and may be significantly higher on small islands higher significantlymaysmall islands on be gal sources in aquatic sediments (Huang (Huang etgal sedimentsal., sources in aquatic hotoautotrophs in in culture (Liet hotoautotrophs 2009; al, n δ ur tropical Pacific data set, fractionationur tropical set, Pacific data mann et However, other mannin al., than 2015). fering contributions fromdifferentferingtypes contributions of t distances. distances.t -C 2 rophic microbes produce short-chain fatty microbesrophic short-chain produce ; 2015).Heinzelmann The al., ; et H s on islands than on continents, sincethan therecontinents,islands s on on 16 16 P α values in our set samplein our bevalues amay Lipid-Water and erol and erol n -C 18 ) ranged) to0.920. from 0.773 unt of meanannual ofprecipitation unt n fatty acids typically have -C 17 -alkane, ble contributions from contributions ble e of photoautotrophs of photoautotrophs e more than of different types δ 2 H of values δ ms the than thesized thesized by 2 H values n - values that that values influence (Figure 6). Rather, one of the largest (Figure of f challenges one Rather,6). robustly interpret proxies robustlyproxies interpret Konecky et (ConroyContin al., al., 2016; 2019). et elsewhere (Figure 3). Any calibration Anyof elsewhere(Figure calibration 3). are residuals that onresult fractionation) in the s and/or aquatic from leaves than from other organs other archives like speleothems. speleothems.other archives like tropical Pacific are uncertainties associated tropical Pacificwith are uncertainties has helped constrain the processes that control processescontrol the that helpedhas constrain availability modern limitedspatial temporal of and 4.4 Implications for paleoclimate reconstructions i reconstructions Implications4.4 paleoclimate for near ubiquitous nearubiquitous which which could make their indicated by palynological analyses)residuals and byindicated palynological suggest that are However, cle datathere ourdo not the poor correlations associated with with correlations the poor associated interpreting relatively small down-corechanges in interpreting relatively small relationshi in this (Figure residuals the large 3), values in the tropical Pacific, inthe values tropicalthe correlation and values (Maloney et al., 2019), suggest that that the unc et suggest (Maloneyal., values2019),

This article is protected by copyright. All rights reserved. ThisAllarticleis rights by copyright. reserved. protected Accepted Article The expected inverse correlation between correlationTheprecipitat expected inverse Although n -C δ 2 H 16 δ Wax Wax and 2 H δ values are strongly linearly correlated with correlated are with stronglyvalues linearly Wax 2 δ H valuesH more wat directly of related to those lake n 2 -C H (variations valuescatchment in seasonality,scale P 18 values,whether are derived from they -acids Meyers,(CranwellVolkmaet al., 1987; 2003; δ 2 H δ Wax Wax 2 H values (Figure 2). Rather, factors besides besides (Figure values factors Rather, 2). Wax δ order of ±25‰order of and Pacific in the tropical p indicate that caution should beforebe indicatep applied caution should that range valuesof a small spanningrelatively 2 s between these variables and algalbetween and lipid variables these s modern estimates ofmodernestimates H or interpretingsedimentaryor ertainty inertainty n Pacific the n tropical observations. Recent isotope modeling observations.work Recent isotope from the globalfrom the sourcear (as vegetation links between P δ ued effort in this regard is is uednecessaryregardthis effort in to ources, or changesources, inbiosynthetic or values in this dynamically important region dynamicallyin this valuesimportant 2 H Wax values as hydroclimate changes.values as hydroclimate ion amount and OIPC-derivedamountion and δ 2 H P values cannot solely cannot valuesexplain δ 2 δ H 2 δ δ H Wax 2 2 H H P values on a globala scale on values Wax P - values, given values, the δ 2 er. H values or from or values from δ s, contributions s, contributions 2 P H

relationship Wax values in the inthe values n, n, 2003), δ 2 H δ δ P 2

2 H δ H 2 P H

and biodiversity, all of which may impact may biodiversity,of andimpact which all precipitation, vulnerabilityse to tropical storms, mountainous atolls andincluded low-lyingrepresent continental-scaleeven km, studie ~8500 larger than a Pacific new the regiona exceed datatropical from δ calibration, make it unsurprising that that calibration,unsurprising make it generated by randomly subsampling the global thes generatedrandomly data subsampling by coefficientsfor Correlation variables (Figure 4). likely is (likestudied values here) the range 32‰ global calibration line. Together, these results su results line. global these Together, calibration global and the set,expected range on do data based constraining some variables that that scatcontributeconstraining to variables some elsewhere. lakeintropical values andPacific sediments swamp down-core changes as large as ~50‰ at any location ~50‰as any at as down-core location large changes constant, the threshold for detecting in the constant,threshold changes for vaInmany asite values. atsingle where practice, local estimates oflocal estimates correlation coefficient (Figure 4). coefficient(Figurecorrelation 4). moreof range,this towardsfall thebut low th end the tropical Pacific. However, it is encouraging th However, the is tropical it Pacific.

Accepted ArticleH Wax values (Garcin et al., 2012; Goldsmith et al., 2019 Goldsmithet al., al., (Garcin values2012; et The scatter in the global relationship between relationshipscatter global The in the Regional calibrations are expected to expectedto have are stronger Regional calibrations

δ 2 H P values, and small and small values, δ 2 H Wax δ δ 2 H 2 H values with arenot correlated P signal relative to the noise in the globalthe in relativethenoisesignal to Wax δ nsitivity to El Niño−Southern Oscillation events, Niño−Southern Oscillation El nsitivity to ggest determining that the processes the tropical Pacific are within the distribution thedistribution are tropicalwithin Pacific the 2 values. The diversity of sites, uncertainty values. The in of diversity sites, riables that contributeare that to scatter among sites riables atPacific tropical H to betweento havecorrelationpoor a the two an below the mean deviation standard1 ter in the global relationship between terglobal relationship in the not havenot the abnormally residuals from large l scale in manyspanningdistancescale ways,a l in of P s (e.g., Sachse et al., 2004). TheSachse 2004). s islands et(e.g., al., aredifferent fundamentally notthan values may bevalues smaller. significantly volcanoes. The sites differ in seasonality of inseasonalityvolcanoes. sites of differ The et while range etlimitingin the could be driven by factors otherbe couldfactors than bydriven δ 2 H ; However, theal., McFarlin 2019).et P than average correlations thanby average and and δ 2 H Wax δ 2 H (Figure that suggests 3) Wax values fall within the within fallvalues δ 2 H P values within within values δ 2 H δ 2 P H to 35‰, δ 2 Wax H δ P 2

and H P

C Pacific there is no between Pacificsignificant correlation is there et al., 2018). Continued refinement of a multi-prox of2018). etrefinement Continued al., of elementali composition thechanges 2008), in or changes Sachs et&Sachs, Richey al., 2018),2016; like(Smitten sourcedinosterol biomarkers specific the the large-scale calibration efforts. efforts. large-scale calibration most robust when supported by independent lines of mostwhenby lines robust independent supported 5 Conclusions 5 toconfidentlyreconstr offersvaluesthe bestpath morecons for etmayKirschneruseful al., 2020) be the catchments at studies Detailed processed-based this study, as deduced from pollen assemblages. deduced study,this assemblages. from as pollen to different vegetation bedata and ascribed cannot regionally is at least atregionally partlyunce to the large due is global calibration. The global globalThe calibration. δ compilation surface sediment measurements (Rcompilationsurface sediment the within ove Pacificthroughout thefall tropical

AcceptedH Article -acid (n = 242)), and the residuals around the glob the residualsaround -acid = 242)), the and(n δ P 2 are similar in the tropical Pacific and global are similardata Pacific global inthe andtropical H δ To a first order on a global To ascale, aon first order 2 Hydroclimate-driven interpretations of changes in s in of changes Hydroclimate-driven interpretations P H signal spanning the tropical Pacific remains small the remains tropical Pacificsignal spanning Wax values from surface sediments from 19 lakes and fromlakes fou valuesand surface 19sediments from δ 2 H Wax – δ δ 2 2 H H Wax P calibration remains limited by uncertainties remains limitedby in bo calibration values are clearly by influenced 2 rtainties in rtainties = 0.74 both for = ucting past hydrologic change. change. ucting past hydrologic rall range of values expected based on a global based rangea ofon expected values rall

δ sources in surrounding and within the lakes y sedimentary that includes toolbox berg et al., 2011; Nelson &berg al.,Sachs,Nelson 2011; et2016; 2 norganic sediments (Sear etHigley norganic(Searal sediments 2020; training sedimentary cale (Freimuth et al., 2019, 2020; Dion- cale2020; et al., (Freimuth 2019, in grain(Conroyal.,inet distributions size H proxyasevidence, such al regression betweenlinear sets. Nevertheless, within the tropical Nevertheless,within sets. Wax and relative to the noise in the relativecurrent to the noise edimentary δ 2

H δ 2 P H derivedvalues from reanalysis n P -C r swamps on 15 swamps r values. The lack of correlationlack ofThe values. 29 -alkane665) (n and = δ 2 δ H 2 Wax Wax H Wax Wax δ values will be will values 2 H valuesmoreH of δ than additional additional than 2 H

δ islands islands 2 P H values, but values, Wax δ 2 and and H Wax Wax n - th th Figure 1 captions Figure (doi: 10.3929/ethz-b-000412154). repository ma data theAllassociatedmanuscript. with on this ano andJamie McFarlin an Krentscheret (2019). al. collection, sampleas manyackno with helped others acknowledgedtothose samplein addition processing H Lake Nichola data Strandbergprovided frompollen and workforNLCarsten Schubert hosted laboratory Resea anand grant (NE/N00674/1), to DASAustralian grantFoundation Science a PP00P2_163782), National shows thelocations shows for be be paired with is the case for all paleoclimate proxies, interpretthecase all is paleoclimate proxies, for and Global amount is from Mean the precipitation annual Filledsymbols sign represent the tropical Pacific. Acknowledgments, Samples, and Data Samples, Acknowledgments,and Data context. multiproxy locations, large changes in largelocations, in changes the x- and y-axes, be improved andcould and the better x- by relative to variables otherthan growth conditions, and delivery of leaf waxes to to se deliveryand conditions, growthleaf waxes of Incon needstudies. interpretations to particular, Figure 2: Figure 2: continents. over spatial dataproduce 2020).sets not does OIPC &Ravenaugh,Calculator Precipitation(OIPC) (Bowen (242 sites). Background shading represents annual m Background (242annual represents shading sites). distinguish changes in water isotopes from changes from distinguishchanges water changesisotopes in waxes, with increasingly with likelywaxes, s terrestrial plant

This article is protected by copyright. All rights reserved. ThisAllarticleis rights by copyright. reserved. protected Accepted Article δ 2 Funding was provided by a Swiss National Science Fo aFunding Science Swiss wasNational provided by H P values are from the OIPC. Compounds are grouped are thebyOIPC. arefrom Compounds values Global distribution of leaf wax samplesof leaffrom Global distribution surfac wax Correlation coefficients of linear regressions of Correlation coefficients of regressions linear δ

2 H P δ values (blue circles) and amount of mean annual pre meancircles) of and (blue annual amount values 2 H

values of more source-specific compounds such as di compoundsof more suchsource-specific values δ 2 H n P -C , and could be improved by more catchment-scale, pr by andmorebe, improvedcatchment-scale, could δ 29 2 H -alkaneshows the location right panel sites); (665 Wax in sediments from tropical Pacific islands may in sediments be Pacificfrom islands tropical ations of ations sider the possible effects of changing of the possible source, effectssider ources associated with longer chainlengths).longer associated with ources ificant correlations at the 95% at confidence correlationslevel. the ificant diments. When diments.possible, nuscript is freely available in in the ETH freelynuscriptavailabledata is constraints onconstraints marine areas, therefore shading is limited to areas, therefore marine inother factorsthat affect nymous reviewer provided helpful feedbackhelpful provided nymous reviewer wledged by Maloney et (2019)al. Maloneyet and wledged by ean Precipitation Climatology (GPCP) Project by Maloney et al. (2019). Julie andJulie Richey (2019). Maloney et by al. provided necessary instrumentation. provided necessary instrumentation. ut. Christiane Krentscher Christiane helped ut. with rch Council grant (DP0985593).to MP rch Council to JPS (Grant No. 1502417), a JPS1502417), NERC (Grant No. to 2003; IAEA/WMO, 2015; Bowen,IAEA/WMO, 2015; 2003; δ δ 2 δ 2 H H 2 H undation grantND (Grant undationto Nr. P Wax e sediments and soils. Left soils. epanel sediments and values from the Online Isotopes in Online from values the

values of all analyzedcompounds of values all valuesrobust aremostin a source (algal, general, or plant (algal, source δ 2 H cipitation (pink cipitation diamonds) in P values. As in other values. nosterol, nosterol, whichcan help δ 2 H ocessed-based α s s for Wax-P Wax values should n values. As values. causedby -C 28 -acid not differlacustri andnot soils between significantly and new compile with Pacificwithout data. Globally the tropical averagePacific sites 5.2‰ foroutside errorbarsbycolor-codedarenot region. X-axis sh Circlesmarker typically are size. thansmaller the fr from measurements deviationreplicate samples of intervals 95%of represent values. OIPC confidence pl Micronesiaboth study), mangrove (this swamps in fromdiamonds are In lakes d).panels b, andred a Figure 3 S1 Set Individualareincluded measurements in Data Aichner, B., Hilt, S., Périllon, C., Gillefalk,C.,M., S.,Périllon, Aichner, Hilt, B., Adler R. F., Huffman, G. J., Chang, A., Ferraro, F., R. Chang,Adler J., G. Huffman,A., R. References values. with the same residual sites Figure 6 soils relativeto the soils Dinosterol Dinosterol alkane and (b)alkane and C restricted widths of the ellipses correspond to correlation correspond coof to widths the ellipses plotted relativeOIPC-derived plotted to samples plotted relative to glob residuals from the samples relative to plotted relativerange of to compilation surface sediment and soil of and (a) compilationsurface soil sediment Figure 5 comparison. for each andcontinent are plotted Aichner, B., Herzschuh, U., Wilkes,U., A., H., Aichner,Vieth, Herzschuh,B., Figure 4

Accepted Article28 -acid. Shading around linear regressions represents regressions linear -acid. Shading around https://doi.org/10.1016/j.orggeochem.2017.07.021 https://doi.org/10.1016/j.orggeochem.2010.05.010 Effect of groundwaterand Effectsalinity. discharge of fractionation duringsynthes isotopic lipid factors analysis (1979 -- Present). ofJournalHydrometeoro analysis--Present). (1979 in Climatology Precipitationversion-2 Proje Global application to a 16 ka record from Lake Koucha.Lakefrom kaapplication16 to a record andmacrophytes–A in Tibetan aquatic lake sediments Correlation plots of plots Correlation Correlation coefficients of random subsamples of of 1 random subsamples coefficients Correlation δ Pollen distributions from surface or near surface s fromPollen surface or near distributions δ 2 2 δ H H 2 H data is from Maloney et al. (2019), all Maloney etother lip H(2019), from al. data is

P values of (a, (a, c)of values ranges as described in the text. Correlation coeff Correlation describedthetext. ranges as in n -C 28 δ δ -acid. Square and triangle symbols areSquare dist andused symbols -acid. to triangle 2 2 H H P P values. Subsampled data were taken from the full d full were taken from values. data Subsampledthe values from various models (described in section 2 sectionmodels (described in from values various n δ -C 2 H valuesofHsurfaceglobal from compilation the sed δ 29 2 -alkaned) (b,and H P values, color-coded by region (a, b), and sampleandregionb), ty (a, bycolor-coded values, n -C & Sachse, D. (2017). Biosynthetic hydrogen&Sachse, Biosynthetic (2017). D. 29 ne sediments for either (c) (c) sediments either for ne global values compiled from global the literature, values efficients, R values, which are written *10are efficients,written R values, which . Regression statistics in (a)(b) and. statistics are shown Regression al -alkane (b)and own for previously published data points, anddata points, forown previously published the SPCZ region and green squaresaregreen and the regionSPCZ Böhner,& J. (2010). , Xie, P.-P., Janowiak, J., et al. et the (2003). , Janowiak, Xie, J., P.-P., Organic GeochemistryOrganic Y-axis error bars represent 1 standard1 error Y-axis represent bars δ om the same lake or swamp and orare swampsameomlake the d datad (including tropical do Pacific values) n . . otted with error error with otted X-axis bars. bars 2 -C 95% confidence intervals. confidence intervals. 95% H is in in submergedaquaticmacrophytes: is Organic GeochemistryOrganic

Wax 28 ct (GPCP) monthly precipitation monthly (GPCP)precipitation ct logy, 4(6), 1147-1167. logy, 1147-1167. 4(6), -acid from surface sediments and soils -acidsediments soils fromand surface – – ediments in tropical Pacificlaketropical ediments in surface sediment study study andsurface sediment 7 values from the globalthefrom values 7 δ id id 2 icients for the global the compilation icients for H δ P n 2 -C H datafromH study.this calibration line for (a)line calibration 28 inguish amongmultipleinguish -acid δ D values of valuesn-alkanes D , 113 n .4). Colors the andColors .4). ata set from and δ -C , 2 H plottedvalues 41 , 10-16. , 29 -alkane(d) or (8), 779-790. iments andiments pe (c, pe n -C 2 .. .. 29 n - - Bowen, G. J., Cai, Z., Fiorella, R. P., & Putman, A &Fiorella,R. Z., P., Putman,Cai, Bowen, J., G. Bai, Y., Fang, X., Gleixner, G., &Mügler,I.(2011 Fang, G., Y., Bai, Gleixner, X., Bakkelund, A., Porter, T. J., Froese,&Feak G., D.J., Bakkelund, A., Porter, T. Chikaraishi H.Y., Chikaraishi & Compound-speci (2003). Naraoka Brinkmann, N., Seeger, S., Weiler, N. M.,Seeger,Buchmann, S., Brinkmann,N., Alongi D. M. (2014). Carbon cycling and storage in in andcycling M.Carbon storage Alongi (2014). D. Andrae, J. W., McInerney, F.McInerney, W.,Sniderman, &Kale Andrae, A., J. Brown, J. R., Lengaigne, M., Lintner, B. R., Widlan Lengaigne,M., Lintner, R., R., Brown, J. B. Conroy, J. L., Cobb, K.Com (2013).D.& M., L.,Conroy,Noone, Cobb, J. Calvo, E., Marshall, J. F., F., Pelejero,Marshall, McCulloch C., J.Calvo, E., Conroy, J. L., Noone, D., Cobb, K. M., Moerman, J.Moerman, M.,K. Cobb, L.,Conroy, D., Noone, J. Bowen, G. J. (2020). The Online Isotopes in in Precipi Online Isotopes (2020). Bowen, J.G. The Cernusak, L. A., Barbour, M. M., Arndt, S. K.,M.M.,S.L. Arndt, Chee Cernusak,A.,Barbour, Bush, R. T., & Mcinerney, F. n-T.,Leaf &Mcinerney,R. wax Bush, (2013). A. Bowen, G. J., & Ravenaugh, J. (2003). Interpolating & Bowen, J., J.G. (2003). Ravenaugh,

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This article is protected by copyright. All rights reserved. ThisAllarticleis rights by copyright. reserved. protected Accepted Article scale and vegetation precipitation regional-scale (USA). Isotope Fractionation of Vascular Plant Leaf Waxes.LeafFractionationIsotopeVascularPlant of Geochimica et CosmochimicaGeochimica etActa https://doi.org/ in in Israel. and n-alkanoic acids in a temperateareand biased acids n-alkanoicin a bog (2020).sedimentof lake Contrasting sensitivity 015-3278-6 015-3278-6 Convergence Zone. University of Southampton. Convergence Southampton. Zone. University of Science, 295 surPacific sea(2002).tropical decrease Abrupt in temperate European grassland. grassland. temperateEuropean organs,andsignificantly species amonghabit plant https://doi.org/10.1016/j.gca.2019.08.026 https://doi.org/10.1016/j.gca.2017.02.027 paleorecords. 2 https://doi.org/10.1029/2019JG005149 and their Acta, 75Acta, species richness and endemism of tropical dry species fores dry andof tropical endemism richness δ aquatic macrophyte inputs ofaquatic macrophytemid-chain inputs 110 interpreting compound specific hydrogen isotopic re isotopic interpretinghydrogen compoundspecific Geochemistry duringHolocene. the ec McMichael, occupation and HumanH.N. C. (2020). Cosmochimica 79Acta, hydrology: insights from acalibrationacrtransect hydrology: insights from n lacustrine Hydrogensedimentary of ratios isotope 614. Distributions, 19Distributions, H/ 13 C in soils recordsoils hydrologicalin C in environmental and 1 , 1-12. H fractionationleafFloridaH n-alkanes in wax from https://doi.org/10.1111/jbi.13783 Geochimica et Cosmochimica Acta et Cosmochimica Geochimica (13), 3781-3791. (13), 3781-3791. Journal of Geophysical Research: Biogeosciences, Research:12 of Geophysical Journal δ 2 https://doi.org/10.1016/j.orggeochem.2017.04.007 H and (5559), 1511-1514. https://doi.org/10.1126/science. 1511-1514. (5559), , Geochimica et Cosmochimica Acta, 206Cosmochimica etActa, Geochimica 128 10.1371/journal.pone.0112610 (8), 896-906. δ , 94-107 , 94-107 13 C valuesalongC typicalplants in a terrestrial-coas Journal of of Biogeography, Journal , 106-126. , https://doi.org/10.1016/j.gca.2011.04.008 https://doi.org/10.1016/j.orggeochem.2019.01.006 https://doi.org/10.1111/ddi.12036 Oecologia, 178Oecologia, https://doi.org/10.1016/j.gca.2011.11.039 , , 281

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This article is protected by copyright. All rights reserved. ThisAllarticleis rights by copyright. reserved. protected Accepted Article Acta, 198Acta, communities. Nationa variabilityfrom Yellowstone acids in fatty abundances of leaf waxes in in aerosolsincentral abundancesofEur leaf waxes plant water-uptake studies usingstablewater-uptakeisotope plantana studies stalagmite geochemistry. stalagmitegeochemistry. South rainfall variabilityMultidecadal(2013).in Reviews,225 https://doi.org/10.1002/eco.1892 https://doi.org/10.1016/j.gca.2015.05.001 https://doi.org/10.1073/pnas.1516271113 https://doi.org/10.1016/j.gca.2011.05.038 Invasions, 11 as distributions toolslipid paleoelevationfor rec microalgal and mangrove biomarkermicroalgalmangrove and and paleohy Galapagos to reconstructing application Cosmochimica 222Acta, sedimentary 8824-8833. 8824-8833. Proceedings of the National Academyof Proceedings of Sciences of the National in marginalEarlyPacific subtr production tropical of Sciences of the United States ofAmerica,States of Sciences 113 of the United Oxford. and large-scale deposition andof recently large-scalesynthesized deposition species on island environments in Remote Oceania usspecies Oceania in Remote environmentsisland on reconstructions: a summary of examples from the Laufrom examplesreconstructions: the of a summary Damste, J. S. (2009). Assessment of soil Damste,Assessmentsoil S. of (2009). J. Springer, New York. Springer,York. New Salix viminalisSalix constant throughout th not isotope fractionation is Geochemistry, 34Geochemistry, , 299-314. https://doi.org/10.1073/pnas.1821732116 δ , 105978. , 105978. , 1529–1556. ,https://doi.org/10.1007/s10530-008-940 1529–1556. 2 Geochimica et Cosmochimica Acta, 75 etActa, Cosmochimica Geochimica . H plant wax-water relationships in Greenlandlakes. H relationships wax-water plant Geochimica et Cosmochimica Acta, 165CosmochimicaGeochimica etActa, (2), 261-289. (2),261-289. https://doi.org/10.1016/j.gca.2016.11.018 https://doi.org/10.1016/j.quascirev.2019.105978 , 599-617., Geology, Geology, 41 https://doi.org/10.1016/S0146-6380(02)00168-7

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This article is protected by copyright. All rights reserved. ThisAllarticleis rights by copyright. reserved. protected Accepted Article D19108. among lipids and species. among species. andlipids biomarkers during soil biomarkersstorage. during soil 1133-1143. 1133-1143. Fatty sedimentandI. acids hydrocarbons. – https://doi.org/10.1016/j.orggeochem.2006.12.004 https://doi.org/10.1016/j.orggeochem.2018.12.011 https://doi.org/10.1016/j.quascirev.2018.05.023 reanalysis atmospheric data. reanalysisdata. atmospheric https://doi.org/10.1016/j.gca.2020.09.014 https://doi.org/10.1016/j.gca.2020.09.014 of the Himalayan climatic gradient.climaticof the Himalayan United States of America, 106 of America, UnitedStates centralmetabolic pathways. Quaternary Science Reviews, 192 QuaternaryScienceReviews, Kenya/Tanzania):Impl equatiorial lake (LakeChala, partic composition of in suspended biomarkerslipid W.,inth etCrop, Seasonal (2018). variability al. 495–506. https://doi.org/10.1007/s00253-002-1172-8 495–506. https://doi.org/10.1007/s00253-002-1172-8 (2020). Validation and calibration of soil of soil calibration (2020). Validation and https://doi.org/10.1029/2008JD010074 https://doi.org/10.1016/0016-7037(80)90067-8 Organic Geochemistry, 38Organic Geochemistry, Proceedings of the National Academy theof National of Sciences of Proceedings Journal of Geophysical Research: Atmospheres Research: of Geophysical Journal (31), 12580-12586. Organic Geochemistry, 128Geochemistry, Organic , 208-224. Geochimica et Cosmochimica Acta Cosmochimica et Geochimica δ 2 H and brGDGTs along (E-W) and strike (N-S) and strikeand H brGDGTs along (E-W) Geochimica et Cosmochimica Acta, 44Acta, et Cosmochimica Geochimica . J., Middelburg, J. J., Negash, A. M. D., De M.D., A. Middelburg, J., Negash, J.,. J. , B., Bookhagen, B., France-Lanord,al. Bookhagen,etB., C., , B., opical soil profiles reveal of profileswaxopical soil plant the fate Applied Microbiology 60 and Microbiology Applied Biotechnology, G. J. (1980). Microbial lipids of an lipids Microbialintertidal (1980). J.G. rge D/H variations in bacterial lipids reflectbacterial in lipids rge variations D/H actionation in freshwater algae: 1. Variations 1. Variations algae: in freshwater actionation

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This article is protected by copyright. All rights reserved. ThisAllarticleis rights by copyright. reserved. protected Accepted annual precipitation Mean and longitu latitude for provided is precision Less Article # Site, Island, Country Lat. Lat. (°N) Site,Island, Country

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are site specific standard deviations of OIPC deviations standard specific site are uncertainty for compound specific specific compound for uncertainty sampl one only When deviation. standard 1 represent # 4 3 detection limit for for limit detection δ

This article is protected by copyright. All rights reserved. ThisAllarticleis rights by copyright. reserved. protected Lakes with greater than 50% vegetation cover 50% vegetation greater than with Lakes line calibration global from offsets are Residuals measurement sediment surface multiple value of Mean 2

Accepted Article a from available are samples multiple when values H δ 2 H measurements. “ H measurements. δ 2 H measurements is 4‰ is measurements H N.M. ” = not measured. not =measured. ” δ 2 H values, and are propagated with standard deviatio standard with propagated and are values, H of compiled leaf wax wax leaf compiled of e was analyzed no uncertainty is reported. Analytic reported. is uncertainty analyzed no e was site. site. s from same lake, relative to VSMOW. Uncertainties Uncertainties VSMOW. to relative lake, from same s . “N.A.”. = compound was not present or was below below was or present not was compound = δ 2 H values from the literature. Uncertainties Uncertainties literature. from the values H ns of leaf wax leaf of ns al al are presentedare for topthe bottomand depth. Table 2Table *Meanof2 samplesfromdifferent sites in thesela Goslingetal.(2020), Sear andet al. (2020) ranges$ Ageare provided fromwithsites existing Lakeswith # greater than 50% vegetation cover fullrangethe ofpossible agesboth for sites. Lac Lanutavake, Wallis, Wallis and Futuna 3-4 1990 1990 3-4 and Wallis,Lac Wallis Lanutavake, Futuna Harai Lake #1, Rendova, Solomon Islands 11-12 1716 1716 11-12 Harai Lake IslandsSolomon Rendova, #1, Harai Lake #3, Rendova, Solomon Islands 30-31 1871 1871 30-31 Harai Lake IslandsSolomon Rendova, #3, Lake Dranoniveilomo, Vanua Balavu, Fiji 2-3 2010 2010 ± 2-3 Vanua Dranoniveilomo, Lake FijiBalavu, ooosPn,Eprt at,Vnau - 21 N.A. 1996 5 ± 8-9 2017 Tavara,Lake Tetepare, Islands Solomon 0-1 Pond, Nopovois Santo, Espiritu Vanuatu Lac Lalolalo, Wallis, Wallis and Futuna* 1-3 2001 + 2001 1-3 Wallis, WallisLac Lalolalo, and Futuna* Vesalea Pond,Vesalea Espiritu VanuatuSanto, Lake Rano, Rendova, Solomon Islands 9-10 1969 1969 +17 - 9-10 Rendova, Rano,IslandsLake Solomon a u,GadTre e aeoi 01 .. .. 5 N.A. N.A. 0-1 Lac Hut, Terre, CaledoniaGrand New Waérowa East Lake, East Espiritu Waérowa Santo, Lake Lake Teveuni, Tagamaucia, Fiji mou ae ft,Vnau 1-2 Emaotul VanuatuLake, Efate, aeLnt',Uou ao 1-2 Samoa Lanoto'o, Upolu,Lake White Lake, Thion, Vanuatu 3-4 1997 +23 -14 1991 1991 +3 1997 +23 -14 3-4 White Lake, Vanuatu Thion, tsLk,Eae aut 23 .. .. . 5. 15. 52.1 4.7 N.A. N.A. 2-3 VanuatuLake,Otas Efate, Pollencounts fromnear surface sediments, reported Site, Island, Island, Site, Country Vanuatu # # # - 21 1- 20 1 1 65 62 1. 15 11 1.5 18.8 0 46.2 6.5 2005 -14 +10 2016 +1 -3 0-1 This article is protected by copyright. All rights reserved. ThisAllarticleis rights by copyright. reserved. protected Accepted Article

- 21 20 12 12 41 59 1. 14. 11.2 0 0 21.3 35.9 0.6 14.1 11.2 0 1.2 58.6 2009 3 ± 0 13.4 2010 3 ± 5.1 3-1 1978 ± 10 1989 7 ± 2-3 Depth of pollen sample (cm) kes. Age rangespresented represented themean age age models, the detailsofwhich providedare by Ma 2016 2013 2013

+99 -123 Bacon age at 2 6 18 2 8 1. 6. 0 . 0 . 46 2. 0 4.6 6.2 0 4.3 0 69.1 13.1 1983 -86 +26 +20 -64 ± 3.4 ± 3.4 ± 85 1866 +86 -84 3.1 5.2 0 91.8 0 0 0 0 0 0 0 0 0 0 91.8 0 5.2 3.1 1866 -84 +86 ± 85 1 19 4-9 03 71 1. 0 . 1. 0.8 13.4 0.4 0 16.4 0 57.1 10.3 + 1991 14 -19 8 -14 ± 1 ± top of interval 20 2. 3. 07 75 . 42 96 2.1 0 19.6 4.2 1.4 17.5 0.7 33.6 21.0 2009 3 ± 2 6 90+1-0 67 65 2. 0 44 . 1.8 0.9 4.4 0 0 29.8 0 46.5 16.7 1960 -20 +21 16

93±6 . 2. 63 47 16 . 0 0.1 0 7.8 1.6 0 54.7 6.3 23.4 6.3 1993 6 ± $

(year C.E.) asapercentage oftotal palynmorphs counted.For 1702 +103 - 2014 2002 2002 Bacon age at 120 120 bottom of . 49 58 1. 03 14 . 52 1.3 5.2 8.4 11.4 0.3 12.7 0 55.8 4.9 3.4 ± ± 1 3.0 24.6 0 62.8 0 2.7 6.9 0 0 0 0 6.9 2.7 0 62.8 0 24.6 3.0 1 ± 1 13 23 3. 0 . 1. 0 3.4 0 11.7 2.1 0 39.3 0 42.3 1.3 -19 0 63 35 1. 0 . 31 . 2.6 0.3 3.1 8.9 0 15.0 0 53.5 16.3 interval (year C.E.) $ . 1. 22 67 0 . 0 1.1 0 5.4 0 0 66.7 2.2 19.4 5.4 . 4. 0 . 0 09 3.1 0 0.9 0 0 4.8 0 41.1 0.1 Primary forest (%)

Secondary forest (%)

27 0 18 . 2.3 0.8 21.8 0 0 2.7 6 Mangroves (%) forthe andtop bottomof eachinterval, and loney(2019),etal. Krentscher et (2019), al.

Ferns (%) eachsediment sample, ageranges

Non-vascular plants (%)

Dryland herbs 4 . 46 4.3 4.6 6.8 .4 (%)

Wetland herbs 77 4.1 7.7 7 (%)

Aquatic plants 1.0 1.7 (%)

7 7 Unknown (%) lat − − 60 30 30 60 0 0 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● data.source ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 60 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● Lit n ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● lat ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 120 − ● ● ● ● − − ● C29 n 60 30 30 60 ● − ● 0 C29 alkane ● SPCZ n 0 180 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● data.source ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● − ● ● ● ● ● ● ● ● C29 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● Latitude (°N) Latitude (°N)lat − − -60 -60 -30

60 lat 240 30 60 − − −60 −30 30 60 60 30 ● 60 30 30 60 ● 30 60 ● 0 ● 0 ● 0 0 ● ● Mangrove n ● ● ● ● ● ● ● ● ● n n ● ● ● ● 0 ● ● 0 ● ● 0 -C 0 -C ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 29 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 29 ● ● ● ● ● ● ● ● ● ● Literature Literature ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● data.source ● ● ● ● data.source ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● -alkane ● ● ● ● ● ● ● ● ● -alkane ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● Lit n ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 60 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 60 ● ● ● ● ● ● ● ● ● 60 300 ● ● ● ● 60 ● ● ● ● ● ● ● ● ● ● ● ● 120 − − ● ● ● ● C29 ● C29 n

● ● ● ● ● ●

● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 120 ● ● − ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● Lit n−C29 ● ● ● ● ● ● ● ● ● ● ● ● ● Lit n ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● C29 alkane ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 120 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 120 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 120 − ● n−C29 alkane ● ● ● ● ● ● C29 n ● − ● C29 alkane lon ● Lit n SPCZ lakes SPCZ lakes

SPCZ n 180 180 180 180 − 0 C28 − ● ● ● ● ● ● ● ● C29

● ● ● ● ● ● ● 240300 ● ● ● ● ● ● ● − 240 240 C29 240 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● Mangrove n−C29 ● Mangrove n ● ● ● SPCZ n ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 300 ● 60 ● ● ● ● ● ● ● ● ● ● ● ● 300 Longitude (°E) Longitude ● ● ● ● ● 240 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 300 ● ● − ● ● ● ● C29 ● Longitude (°E) Longitude Micronesian mangroves mangroves Micronesian ● ● ● ● ● ● ● ● ● ● ● ● ● ● Mangrove n − ● ● ● C28 ● lon Lit n−C28 lon Lit n n ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0 ● ● ● ● ● ● 0 ● ● -C ● ● ● n ● − 0 0 C28 ● -C 28 ● ● ● ● ● ● ● ● ● n 120 ● ● ● ● ● ● ● ● ● ● 28 ● -acid ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● − ● ● -acid ● ● ● ● 300 ● C28 fatty acid

SPCZ n−C28 − d2H.OIPC.ann 60 60 60 C29 SPCZ n

60 ● ● ● ● ● ● ● ● ● ● ● ● ● −

120 C28 120 n−C28 fatty acid ● 120 180 n 120 d2H.OIPC.ann − lon C28 fatty acid d2H.OIPC.ann − Lit n 200 180 180 δ

● ● 180 ● −200 2 − ● ● ● − ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● H 180 ● ● 0 C28 150 P − ● 200 −150 ● ● (‰, VSMOW) ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

● ● ● ● − ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 240300 ● ● ● ● ● ● 240 − 150 −100 240 ● 240 ● ● ● ● ● ● ● ● ● 100 ● ● ● ● ● ● ● ● ● ● ● − 240 ● ● ● ● ● ● ● ● ● ● 100 ● ● ● ● ● −50 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● − ● ● ● ● ● ● ● − ● ● ● ● ● ● ● ● ● ● 50 ● 50 ● 0 SPCZ n ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 300 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 300 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 60 ● 0 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 300 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 300 ● ● ● ● ● ● ● ● ● ● −

C28 ● ● ● ● ●

● ● ● ● ● ● ● ● ● n 120 − C28 fatty acid d2H.OIPC.ann 180 − 200 ● ● ● ● ● ● − ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 150 ● ● ● ● ● ● ● ● ● ● ● ● ● − 240 ● ● ● ● ● ● ● ● 100 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● − ● ● ● ● ● ● 50 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 0 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● 300 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● n -C 2 2 16 R value δ Hlipid vs δ HOIPC acid (n = 19) -1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0 n -C 18 acid (n = 13) Generic Generic Dinosterol (n = 21)

n -C 17 alkane (n = 4)

n Aquatic -C 26 acid (n = 12) n

Compound -C 27 alkane (n = 8) n -C 28 n acid (n = 17) -C Plant waxes waxes Plant 29 alkane (n = 17)

n -C 30 n acid (n = 10) -C 31 alkane (n = 12) n -C 33 alkane (n = 12) Terrestrial -1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0

2 R value δ Hlipid vs mm/day (GPCP) c) a)

2 2 δ H n-C -alkane (‰, VSMOW) δ H n-C29-alkane (‰, VSMOW)

-300 -250 29 -200 -150 -100 -300 -250 -200 -150 -100 -50 -50 0 δ 0 -200 δ -200 2 2 H mean annual precip (‰, VSMOW) H meanannualprecip(‰,VSMOW) R m =0.902 R m =0.93 Pacific: Tropical Without R m =0.92 Pacific: Tropical With 2 2 2 =0.82;p<0.0001;n191 = 0.74;p<0.0001;n648 = 0.74;p<0.0001;n665 -150 -150 ± ± ± 0.02; b = -116 0.02;b=-116 0.02;b=-117 0.03; b = -114 0.03;b=-114 Lakes -100 -100 R m =0.976 2 Americas Africa Micronesia SPCZ =0.67;p<0.0001; n=474

This article is protected by copyright. All rights reserved. ThisAllarticleis rights by copyright. reserved. protected Accepted Article ± ± ± 2 2 -50 2 -50 ± 0.03; b = -115 0.03;b=-115 Soils 0 Europe Asia Australia 0 ± 2 50 50 d) b)

2 2 δ H n-C -acid (‰, VSMOW) δ H n-C28-acid (‰, VSMOW)

-300 -250 28-200 -150 -100 -300 -250 -200 -150 -100 -50 -50 0 0 δ δ -200 -200 2 2 H mean annual precip (‰, VSMOW) H meanannualprecip(‰,VSMOW) R m =0.74 Pacific: Tropical Without R m =0.73 Pacific: Tropical With R m =0.758 2 2 2 =0.75;p<0.0001;n224 = 0.73;p<0.0001;n225 = 0.74;p<0.0001;n242 -150 -150 ± ± 0.03; b = -113 0.03;b=-113 0.03;b=-114 ± 0.03; b = -113 0.03;b=-113 Lakes -100 -100 m =0.860 R 2 =0.98;p<0.0001; n=18 ± ± 3 3 ± N. America (>60 N. America (25-60 N. Switzerland America (<25 N. SPCZ -50 -50 3 ± 0.03;b=-102 Soils 0 0 ° ° N) N) ± ° 5 N) 50 50 b) a) R R -1.0 -0.5 -1.0 -0.5 1.0 1.0 0.0 0.5 0.0 0.5 0 0 n n -C -C 28 29 -acid -alkane

This article is protected by copyright. All rights reserved. ThisAllarticleis rights by copyright. reserved. protected Accepted Article 50 50 Range of Range of Tropical (n =665) Global (n =117) Africa Pacific (n=17) δ δ 2 2 100 100 H H P P Values (‰ Values Values (‰ Values Europe (n=22) Asia (n=383) (n =20) America S. (n =105) America N. (n =17) Tropical Pacific Global (n=242) (n =217) America North Europe (n=8) ) ) 150 150 Sampling range: Sampling range: All data 35‰ 50‰ 100‰ All data 35‰ 50‰ 100‰ 200 200 n−C29 alkane n -C (n = 665) (n = 665) 29 This article is protected by copyright. All rights reserved. ThisAllarticleis rights by copyright. reserved. protected n−C28 fatty acid Accepted Article -alkane n (n = 242) (n = 242) -C R 0.5 28 -acid -acid 74 n−C28 fatty acid 86 86 OIPC 0.6 82 84 OIPC−extracted n−C28fattyacid=242 91 64 CAM (free) n−C29 alkanen=665 87 67

0.7 ECHAM (nudged) 84 70 GISS (nudged) 86 69 GISS (free) 0.8 89 57 HadAM (free) 86 66 IsoGSM (nudged) 85 65 0.9 LMDZ (nudged) 89 67 MIROC (free) 88 70 SWING2 nudged mean 1 a)

Relative abundance (%) 100 20 40 60 80 0 -50 Secondary forest Primary forest -40 n -C -30 29 -alkane residual -20 Different shapes indicate different lakeswithsameresidualvalues shapesindicatedifferent Different -10 0 Non-vascular plants Mangroves

Relative abundance (%) 100 20 40 60 80 0 -50 Wetland herbs Dryland herbs -40 n -30 -C 28 -20 -acid residual -10 0 Ferns Aquatic plants 10 20 30