Quaternary Science ReviewsMulu National Park, northern Borneo (4.1 N, 114.9 E; Fig. 1), Whiterock Cave (WR) and Lang's Cave (LC). The Mulu caves are well-known for some of the largest

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Glacialeinterglacial temperature change in the tropical West Pacific:A comparison of stalagmite-based paleo-thermometers

A. Nele Meckler a, *, St�ephane Affolter b, c, Yuri V. Dublyansky d, Yves Krüger e, c,Nadia Vogel f, g, Stefano M. Bernasconi a, Martin Frenz e, Rolf Kipfer f, g,Markus Leuenberger b, c, Christoph Sp€otl d, Stacy Carolin h, Kim M. Cobb h,Jessica Moerman h, Jess F. Adkins i, Dominik Fleitmann c, j

a Geological Institute, ETH Zürich, Switzerlandb Physics Institute, University of Bern, Switzerlandc Oeschger Centre for Climate Change Research, University of Bern, Switzerlandd Institute of Geology, University of Innsbruck, Austriae Institute of Applied Physics, University of Bern, Switzerlandf EAWAG, Swiss Federal Institute of Aquatic Science and Technology, Switzerlandg Institute of Geochemistry and Petrology, ETH Zürich, Switzerlandh Department of Earth and Atmospheric Sciences, Georgia Institute of Technology, USAi Division of Geological and Planetary Sciences, California Institute of Technology, USAj Department of Archaeology, Centre for Past Climate Change, School of Archaeology, Geography and Environmental Science, University of Reading,United Kingdom

a r t i c l e i n f o

Article history:Received 23 January 2015Received in revised form12 June 2015Accepted 16 June 2015Available online xxx

Keywords:SpeleothemsQuaternaryTropicsClimateNoble gasesClumped isotopesFluid inclusions

* Corresponding author. Present address: DepartBjerknes Centre for Climate Research, University of B

E-mail address: [email protected] (A.N

http://dx.doi.org/10.1016/j.quascirev.2015.06.0150277-3791/© 2015 Elsevier Ltd. All rights reserved.

Please cite this article in press as: Meckler,stalagmite-based paleo-thermometers, Qua

a b s t r a c t

In the tropics, geochemical records from stalagmites have so far mainly been used to qualitativelyreconstruct changes in precipitation, but several new methods to reconstruct past temperatures fromstalagmite material have emerged recently: i) liquidevapor homogenization of fluid inclusion water ii)noble gas concentrations in fluid inclusion water, iii) the partitioning of oxygen isotopes between fluidinclusion water and calcite, and iv) the abundance of the 13C18O16O (‘clumped’) isotopologue in calcite.We present, for the first time, a direct comparison of these four paleo-thermometers by applying them toa fossil stalagmite covering nearly two glacialeinterglacial cycles (Marine Isotope Stages (MIS) 12e9) andto two modern stalagmites, all from northern Borneo. The temperature estimates from the differentmethods agree in most cases within errors for both the old and recent samples; reconstructed formationtemperatures of the recent samples match within 2-sigma errors with measured cave temperatures.However, slight but systematic deviations are observed between noble gas and liquidevapor homoge-nization temperatures. Whereas the temperature sensitivity of fluid inclusion d18O and clumped isotopesis currently debated, we find that the calibration of Tremaine et al. (2011) for fluid inclusion d18O and asynthetic calcite-based clumped isotope calibration (Ziegler et al., in prep.) yield temperature estimatesconsistent with the other methods. All methods (with the potential exception of clumped isotopes) showexcellent agreement on the amplitude of glacialeinterglacial temperature change, indicating tempera-ture shifts of 4e5 �C. This amplitude is similar to the amplitude of Mg/Ca-based regional sea surfacetemperature records, when correcting for sea level driven changes in cave elevation. Our reconstructionof tropical temperature evolution over the time period from 440 to 320 thousand years ago (ka) addssupport to the view that climate sensitivity to varying greenhouse forcing is substantial also in the deeptropics.

© 2015 Elsevier Ltd. All rights reserved.

ment of Earth Science andergen, Norway.. Meckler).

A.N., et al., Glacialeinterglacial temperature change in the tropical West Pacific: A comparison ofternary Science Reviews (2015), http://dx.doi.org/10.1016/j.quascirev.2015.06.015

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A.N. Meckler et al. / Quaternary Science Reviews xxx (2015) 1e272

1. Introduction

1.1. Approaches and archives for temperature reconstruction

Quantitative reconstructions of past temperatures providevaluable constraints for benchmarking climate models and can bedirectly used to investigate the sensitivity of global or regionaltemperatures to varying levels of atmospheric CO2 concentration.However, at low latitudes currently available reconstructions ofHolocene and Pleistocene temperatures are strongly biased to-wards the ocean, where sea surface temperature (SST) estimateshave been derived from marine sediments using various proxies(e.g., plankton species assemblages, alkenone unsaturation, Mg/Caratios in carbonate shells, or TEX86). The few methods available inthe tropics to reconstruct temperature from terrestrial material arebased on either the determination of changes in the elevation of theglacier equilibrium-line (Porter, 2001) or on various proxies in lakesediments, such as pollen assemblages (Farrera et al., 1999), TEX86(e.g., Tierney et al., 2008), and most recently the difference in d18Oof lake carbonate and gypsum hydrationwater (Hodell et al., 2012).For a few low-latitude locations, noble gas concentrations inancient groundwaters have been used to infer temperatures of theLast Glacial Maximum (LGM; Edmunds et al., 1999; Stute et al.,1995; Weyhenmeyer et al., 2000). These terrestrial archives sufferfrom limited temporal coverage (most can only be used as far backas the LGM), poor age constraints, or both.

In recent decades, speleothems, and particularly stalagmites,have emerged as valuable terrestrial climate archives. Stalagmitescan be precisely dated back to around 600 ka using the UeThmethod (and beyond by UePb). Since the oxygen isotopic compo-sition of the stalagmite calcite (d18Occ) is closely related to theisotopic composition of the rainwater, the d18Occ signal containsinformation about the climate at the time of stalagmite growth. Athigh latitudes, d18Occ values predominantly reflect temperaturevariations, whereas at low latitudes, the dominant control on var-iations in d18Occ are changes in hydroclimate (precipitation and/ormoisture transport; Dansgaard, 1964). Although stalagmite d18Occrecords are therefore of great value for understanding tropicalhydroclimate, their interpretation is bound to remain qualitativedue to the complexity of the multiple influencing factors thatcontrol d18Occ.

Paleo-temperatures can be also obtained from speleothemcalcite by clumped isotope thermometry (Affek et al., 2008; Eiler,2007; Wainer et al., 2011). However, this proxy appears to bevery sensitive to kinetic effects during calcite precipitation (e.g.,due to rapid CO2 degassing) and thus usually yields temperaturesthat are too high (Affek et al., 2008, 2014; Wainer et al., 2011).

Stalagmites contain fluid inclusions, which preserve relicts ofthe former calcite-precipitating drip water, and thus represent acomplementary source of climate information. Several newmethods make use of these fluid inclusions to estimate the tem-peratures at which the calcite fabric of the growing stalagmiteenclosed the fluid inclusion. These novel methods are based on: i)the density of the water determined from liquidevapor homoge-nization (Krüger et al., 2011), ii) the concentrations of noble gasesdissolved in the water (e.g., Kluge et al., 2008; Scheidegger et al.,2011), and iii) the fractionation of oxygen isotopes between fluidinclusion water and the surrounding calcite host (e.g., vanBreukelen et al., 2008; Wainer et al., 2011). Fluid inclusion waterisotopes can be measured using different analytical approaches(Affolter et al., 2014; Arienzo et al., 2013; Dublyansky and Sp€otl,2009; Vonhof et al., 2006). To date, most of these methods havebeen applied independently. In the present study, all of these newmethods, including clumped isotope thermometry, were for thefirst time applied to the same stalagmite samples from northern

Please cite this article in press as: Meckler, A.N., et al., Glacialeinterglacistalagmite-based paleo-thermometers, Quaternary Science Reviews (201

Borneo. This multi-proxy approach allows us to assess the accuracyand precision of paleo-temperature estimates derived from thedifferent analytical methods, and to robustly reconstruct pasttemperature variations during the period between 440 and 320 ka.

1.2. Previous temperature reconstructions for the tropical WestPacific

Borneo is located in the Indo-Pacific Warm Pool, which harborsthe warmest surface water in the ocean. Reconstructions of tropicaltemperatures during the LGM indicate colder conditions duringglacial times, but estimates of the magnitude of this temperaturedecrease differ widely, ranging between 1 and 5 �C cooling (Porter,2001; Waelbroeck et al., 2009). Available data are mostly restrictedto the last glacial cycle, and are strongly biased towards SSTs, whichcan be additionally influenced by changes in ocean circulation. Itremains therefore uncertain whether SSTs and land temperaturesvaried in concert. Furthermore, different SST proxies disagree onthe extent of glacial cooling, with estimates ranging from 1 �C to4 �C cooling (CLIMAP_Project_Members, 1976; de Garidel-Thoronet al., 2007; Waelbroeck et al., 2009). Thereby, SST re-constructions based on Mg/Ca suggest larger cooling (especiallywhen corrected for salinity changes; Mathien-Blard and Bassinot,2009) compared to estimates based on changes in the planktonspecies assemblage. A recent study using clumped isotope ther-mometry on marine carbonate shells yielded 4e5 �C cooler SSTduring the LGM (Tripati et al., 2014) compared to the Holocene.Only few SST records from the Warm Pool region extend overseveral glacialeinterglacial cycles (see locations indicated in Fig. 1).These Mg/Ca based data suggest that glacial-to-interglacial SSTchanges varied between 3 and 5 �C during the last 500 kyrs (deGaridel-Thoron et al., 2005; Medina-Elizalde and Lea, 2005;Tachikawa et al., 2014).

Terrestrial temperature estimates for the LGM in the tropics alsospan a wide range, like SST reconstructions. Pollen data from theWarm Pool region indicate 1e2 �C cooler-than-present tempera-tures on land when normalized to present-day sea level, which isless than estimated for other tropical regions (Farrera et al., 1999),but similar to some of the Warm Pool SST reconstructions based onspecies assemblage changes (e.g., Waelbroeck et al., 2009). Incontrast, estimates of ancient snowlines in tropical regionsincluding Indonesia and northern Borneo suggest around 5 �Ccooler glacial temperatures at sea level, but include large un-certainties due to unconstrained additional influences such asvariations in precipitation (Porter, 2001). These estimates are closeto the 4 �C amplitude in SST estimates derived from clumped iso-topes (Tripati et al., 2014) and salinity-corrected Mg/Ca ratios(Mathien-Blard and Bassinot, 2009). Further afield, noble gas con-centrations in glacial-age groundwater in Brazil, Nigeria and Nigeralso suggest 5.0e6.5 �C cooler temperatures compared to today(Edmunds et al., 1999; Stute et al., 1995).

The controversy about glacial temperatures in the tropics hassignificant implications for predictions of future climate change.Given that glacial CO2 levels were around 80e90 ppm lower thanpre-industrial Holocene concentrations (Barnola et al., 1987;Schmitt et al., 2012), the reconstructed temperature bears directlyon estimates of the equilibrium climate sensitivity in tropical re-gions to greenhouse forcing. By reconstructing temperature fluc-tuations in the tropical West Pacific over several glacial andinterglacial periods, after evaluating the data by cross-comparisonof four different methods, we aim to clarify the amplitude ofterrestrial glacialeinterglacial temperature change in the tropicalWest Pacific and extend the temperature reconstructions back intime.

al temperature change in the tropical West Pacific: A comparison of5), http://dx.doi.org/10.1016/j.quascirev.2015.06.015

A.N. Meckler et al. / Quaternary Science Reviews xxx (2015) 1e27 3

2. Materials and methods

2.1. Samples

The stalagmites used in this study were collected in two caves inMulu National Park, northern Borneo (4.1�N, 114.9�E; Fig. 1),Whiterock Cave (WR) and Lang's Cave (LC). The Mulu caves arewell-known for some of the largest cave passages in the world,leading to generally good ventilation of the caves. In general, spe-leothem growth is comparatively slow, which could be related toCO2 enrichment of entraining waters being limited by the thintopsoil cover in this tropical rainforest, and rapid entrainment ofwater due to large precipitation amounts. For the present study weanalyzed a 19 cm-long section of stalagmite WR5 covering the timeinterval between 460 ka and 330 ka (Meckler et al., 2012) andcomprising almost two glacialeinterglacial cycles (MIS 12 to thebeginning of MIS 9; Fig. A.1). The fossil stalagmite WR5 wascollected in 2008 about 350m from the cave entrance ofWhiterockCave (~200 m a.s.l.). The d18Occ variations of WR5 and two other

Fig. 1. Map of the sample location in northern Borneo (4�N, 115�E), modified from MecklerWarm Pool surrounding Borneo and the locations of three sediment cores from which longwere averaged for the time series in Fig. 2. b) Relief map showing a close-up of northernplotted in Fig. 2. c) Locations of caves in Mulu National Park from which samples were usereader is referred to the web version of this article.)


Mulu stalagmites covering the same time interval mainly reflectchanges in regional precipitation (Meckler et al., 2012). Glacial-to-interglacial variations in d18Occ are not clearly apparent in WR5,but glacial terminations are characterized by distinct maxima ind18Occ, interpreted as dry phases.

In addition toWR5, the top 1.5e2 cm of two drill-cores collectedin 2008 (WR-MC2 and LC-1a), covering approximately the last1000e2000 years, were analyzed to obtain more recent tempera-ture data for a comparison with modern cave temperatures. WR-MC2 was drilled in Whiterock Cave from an actively growing sta-lagmite around 250 m from the cave entrance. LC-1a was drilled inLang's Cave (28 m a.s.l.), a tourist cave, from a stalagmite located inthe innermost part of the cave around 100m from the entrance. Thetemperatures determined from sample LC-1a can be comparedwith cave monitoring data (see Section 2.2). Unfortunately, no cavemonitoring data are available for Whiterock Cave. The comparisonof the results from WR-MC2 and WR5, however, allows us tocompare results from old and recent samples from the same cave,in order to assess whether or not systematic changes of the

et al. (2012). a) Present-day sea surface temperatures (SSTs) showing the Indo-PacificSST records are available. The red stippled line indicates the area over which SST dataBorneo and the locations of meteorological stations from which temperature data ared in this study. (For interpretation of the references to color in this figure legend, the


Table 1Temperatures measured inside and outside Mulu caves (see Fig. 1 for cave locations). Time series data from temperature loggers are considered more reliable than surveymeasurements with hand-held devices.

Cave Elevation Time series coverage Time seriesaverage (�C)

Range in timeseries (�C)

Range in survey08/2008 (�C)

Range in survey02/2010 (�C)

Back of Lang's Cave 28 m a.s.l. 08/2008e03/2010 24.1 23.9e24.2 24.1e24.9 (N ¼ 4) 23.9e24.5 (N ¼ 2)Secret Cave (in Clearwater Cave) 75 m a.s.l. (estimated) 08/2008e07/2009 23.7 23.6e23.8 23.2e23.9 (N ¼ 5) 23.5e24.0 (N ¼ 2)Clearwater connection varying around 70 m a.s.l. 23.8e24.7 (N ¼ 11) 23.8e24.8 (N ¼ 3)Entrance of Lang's Cave 28 m a.s.l. 24.1e24.4 (N ¼ 3)Tourist entrance Clearwater Cave 53 m a.s.l. 23.3e25.6 (N ¼ 3)


properties of the fluid inclusion water occurred over time, whichcould affect the results of the temperature estimates.

2.2. Setting: present-day temperature

Cave monitoring programs performed in 2008e2010 in theinterior of Lang's Cave (28 m a.s.l.; at the sampling location of LC-1a) and Secret Cave (~75 m a.s.l.) in the Clearwater Cave systemprovided continuous temperature records over 1.5 and 1 years,respectively. The measured temperatures were 23.9e24.2 �C forLang's Cave and 23.6e23.8 �C for Secret Cave, indicating verystable temperature conditions throughout the year (Table 1,Fig. 2). Similar results were obtained during single ‘spot’ mea-surements using hand-held devices (Table 1), although thescatter of these data was slightly greater. Limited spot tempera-ture measurements at both cave entrances suggest temperaturesto be similar to temperatures inside the caves, although morevariable (Table 1).

The temperature in Lang's Cave is 4.8 �C lower than the averageSSTs of 28.9 �C measured for the same time period in the WarmPool area surrounding Borneo (Fig. 2b). Accounting for the ~30 maltitude difference reduces the offset only by around 0.3 �C(assuming a moist adiabatic lapse rate of ~1 �C/100 m; Tripati et

1860 1880 1900 1920 1940 1960 1980 2000Year

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Yearly average temperaturesSST HadleySandakan WMOKota Kinabalu WMO

Bintulu WMODanum ValleyMulu Park HQ

13 m

5 m

3 m 75 m

24 m

a

Fig. 2. Compilation of instrumental temperature records from northern Borneo and the surrlocations see Fig. 1) compared to Warm Pool SST (averaged over 110e122�E and 0e8�N fromHeadquarters in 2007. Data were obtained with the Climate Explorer (www.climexp.knmi.nthe Danum Valley Field Centre climatic station run by the Royal Society SE Asia Rainforestgiven in meters above sea level. b) Monthly average temperatures for the time period 2005ecaves are also plotted in panel (b).


al., 2014 and pers. comm.). Part of this temperature offset canalready be observed in Mulu Park itself. At the Park headquarters(HQ), located at 24 m a.s.l. in an open patch in the rainforest,monthly average temperatures measured over two years in2006e2008 and during seven months in 2010 ranged from 25.5 to27.4 �C. The mean annual temperature in 2007 was 26.3 �C, andthus 2.2 �C warmer than the temperature in Lang's Cave. Evenhigher temperatures were measured at other meteorological sta-tions in northern Borneo (Fig. 2), for example at Danum Valley innortheastern Borneo (at 75 m a.s.l., Fig. 1; data obtained from TheRoyal Society SE Asia Rainforest Research Programme: www.searrp.org). There, the average temperature for the period2008e2010 was 27.2 �C (Fig. 2), and thus 3.1 �C higher than inLang's Cave, although the station is at 50 m higher elevation thanthe cave. Compared to Warm Pool SSTs, however, Danum Valleytemperatures are still ~1.5 �C lower even accounting for the alti-tude difference. Similar to Danum Valley, all land-based stationsmeasure systematically lower temperatures than concurrent SSTs,which is also observed in long-term instrumental records(1880e1990) from stations near sealevel in Sandakan, Kota Kin-abalu, and Bintulu (Figs. 1 and 2a; data obtained from ClimateExplorer: www.climexp.knmi.nl). The observed differences inpresent-day temperatures between SST, meteorological stations,

20201/1/05 1/1/06 1/1/07 1/1/08 1/1/09 1/1/10 1/1/11 1/1/12

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Monthly temperaturesSSTDanum ValleyMulu Park HQLang's CaveSecret Cave

b

ounding Warm Pool. a) Annual average temperatures from meteorological stations (forthe Hadley Center SST data set) and the average temperature measured at Mulu Park

l) from WMO (Sandakan, Bintulu, Kota Kinabalu) and the Hadley Center (SST) and fromResearch Programme (www.searrp.org). Elevations for the meteorological stations are2011 (gray band in panel a; note the expanded scale). Measured temperatures in Mulu


http://www.searrp.org


http://www.climexp.knmi.nl

http://www.climexp.knmi.nl



and the caves are likely related to radiation shielding by thevegetation and evaporative cooling in the rainforest and the cavesand will be further discussed in Section 5.2.

2.3. Sample preparation

Each of the methods to determine cave temperatures fromstalagmite samples employed in this study has distinct re-quirements in terms of sample preparation and amount of samplematerial. Polished sections of ~200 mm thickness are used topetrographically assess the abundance, distribution, and nature ofthe fluid inclusions (see Section 3.1 and Fig. 3). Fluid inclusionisotope and noble gas measurements are bulk analyses requiringcalcite blocks cut along growth layers. The liquidevapor homoge-nization method requires small pieces of ~300 mm thick unpolishedsections. Clumped isotope analyses are conducted on powderedstalagmite samples.

To meet these different requirements, the samples were takenfrom different pieces of the stalagmites, paying attention to samplethe same growth layers for all methods (Fig. A.1).

For stalagmite WR5, the samples are labeled by their averagedepth on the stable isotope (d18O and d13C) transect as used inprevious studies (inmm from the top ofWR5). Samples for noble gasanalyses as well as most clumped isotope samples and a few sam-ples for fluid inclusion isotope measurements were taken from a1.5 cm thick center slab, which had previously been used for stableisotope profiles and Uranium series dating (Meckler et al., 2012).Sample blocks were cut out with diamondwire- and band-saws andclumped isotope samples were milled from the slab. All othersamples as well as the sections for petrography and homogenizationtemperatures were taken from a part of WR5 immediately adjacentto the slab. This piece was cut into ~20 mm wide blocks (seeFig. A.2a) which were then glued onto glass plates to cut off fourslices with a low-speed circular saw. The first slice of ~3 mmthickness was kept as archivematerial for the center surface ofWR5.The thick sections for fluid-inclusion petrography were cut off nextand polished on one side, and a third slice was cut for homogeni-zation temperature measurements. After cutting, this section wasremoved from the glass substrate in an acetone bath and subse-quently broken into smaller pieces (Fig. A.2b). Note that these sec-tions were not polished in order to minimize the mechanical stresson the calcite host (Krüger et al., 2011). Finally, a fourth 5 mm-thickslice was used to cut out samples for fluid inclusion isotope mea-surements along growth layers (Fig. A.2c and d). In some cases, partof this sample material was used for additional clumped isotopemeasurements. All powders remaining after fluid inclusion isotopeanalyses were subsequently analyzed for d18Occ.

A similar sampling approach was taken for the recent samplesWR-MC2 and LC-1a. The cores were cut in half and a section wasprepared for homogenization temperature measurements andpetrographic inspection, which was performed prior to removingthe section from the carrier glass. The remaining material wassplit into aliquots for measuring fluid inclusion water isotopesand noble gas concentrations as well as clumped isotopes andd18Occ.

2.4. Methodology

2.4.1. Fluid inclusion petrographyAny analyses of fluid inclusions must be preceded by careful

observations of the fluid inclusion petrography, in order to i) studythe fabric of the calcite host and the distribution of the fluid in-clusions (e.g., inter- or intracrystalline) therein, ii) to estimate thewater content of the stalagmite sample based on the abundanceand size of these inclusions, iii) to confirm the primary origin of the


inclusions, and iv) to evaluate whether or not the fluid inclusionscan be regarded as closed systems (Fig. 3). Stalagmite sections werestudied with 2.5� to 40� magnification using an Olympus BX51microscope. Additionally, a slide-duplicator (Elinchrom) equippedwith a camera (Canon EOS D30) and polarization filters was used totake images of the entire stalagmite thick sections.

2.4.2. Liquidevapor homogenization of fluid inclusionsUnderlying principle and assumptions. The density of waterencapsulated within fluid inclusions depends on the cave tem-perature at the time the inclusion sealed off from the cave envi-ronment. Assuming that the volume and composition of the fluidinclusion water is preserved over hundreds of thousands of years,the density of the trapped water can be used to calculate theformation temperature of the inclusion and thus of the sur-rounding stalagmite host (Krüger et al., 2011). The water densitycan be determined by microthermometric measurement of theliquidevapor homogenization temperature Th, i.e., the tempera-ture at which a vapor bubble vanishes upon heating and the in-clusion homogenizes to the liquid phase. In speleothems, a vaporbubble needs to be stimulated by means of femtosecond laserpulses after initial cooling of the sample (Krüger et al., 2007). Theinterpretation of the measured Th values in terms of fluid den-sities and stalagmite formation temperatures relies on a ther-modynamic model (Marti et al., 2012) that accounts for surfacetension effects.

Analytical procedures. For a detailed description of themethodologywe refer to Krüger et al. (2011). The Th measurements are performedon a microscope heating/freezing stage (Linkam TMHSG 600). Afemtosecond laser system (Coherent) provides single amplifiedultra-short laser pulses to stimulate vapor bubble nucleation in themetastable liquid state of the water at 5.1 �C, i.e., the temperature atwhich the generated vapor bubbles havemaximum size (Marti et al.,2009). Upon subsequent heating, the liquid water expands at theexpense of the vapor bubble and the inclusion homogenizes againinto the liquid phase. The observed homogenization temperatureTh(obs) does not only depend on the density of the trapped water, butalso on the volume of the inclusion. Based on Th(obs) and an addi-tional measurement of the vapor bubble radius at a known tem-perature, the inclusion volume and the homogenizationtemperature of a hypothetical, infinitely large inclusion, denoted asTh∞, is calculated using the thermodynamic model proposed byMarti et al. (2012). The deviation of Th(obs) from Th∞ is due to theeffect of surface tension at the liquidegas interface of the vaporbubble that forces the bubble to collapse below Th∞. In the case ofstalagmites, Th∞ is equal to the formation temperature, providedthat the inclusions have preserved their original fluid density.

Study-specific details and errors of the measurements. For eachsample, 17e47 individual inclusions were analyzed, each in dupli-cate. All inclusions were initially monophase liquid. In order tominimize mechanical stress, the stalagmite sections were not pol-ished but instead, immersion oil was used to make the sectionstransparent for microscopic observation. Furthermore, the sampleswere not heated above 27 �C, to avoid irreversible volume changesof the inclusions due to high internal fluid overpressure.

The temperature accuracy of the heating/freezing stage is±0.1 �C based on calibrations using synthetic H2O and H2OeCO2fluid inclusion standards. The overall precision of the individual Th∞values ranges between±0.2 and ±0.6 �C (1 SD, with larger errors forsmaller inclusions) and includes the errors of the temperaturemeasurement (Th(obs)) and the determination of the vapor bubbleradius (Spadin et al., 2015). The reproducibility of Th(obs), based onthe duplicate measurements, is ±0.05 �C. The formation



temperature reported for each sample represents the average andthe standard deviation of the Th∞ values determined from the in-dividual inclusions.We note that the population of homogenizationtemperatures measured for each sample should not be regarded asreplicate measurements of the same temperature. Rather, thestandard deviation contains useful information about the vari-ability of formation temperatures within the analyzed speleothemsample.

2.4.3. Noble gas concentrations in fluid inclusion waterUnderlying principle and assumptions. Noble gas temperature (NGT)determination is based on the fact that the equilibrium concen-trations of dissolved atmospheric noble gases in water are a func-tion of temperature, pressure, and salinity (e.g., Brennwald et al.,2013; Kipfer et al., 2002). Since the salinity of cave drip water istypically very low, and the pressure is given by the elevation of thesampling site (e.g. altitude of the cave), the formation temperatureof a stalagmite can be deduced from the dissolved atmosphericnoble gas concentrations in the fluid inclusionwater, assuming thatthe inclusion has preserved its original noble gas content. Thisapproach is complicated by the fact that often some inclusions trapcave air. Such air-filled inclusions contain atmospheric noble gasesthat do not carry temperature information and often overwhelmthe small amounts of noble gases dissolved in fluid inclusion water(e.g., Kluge et al., 2008; Scheidegger et al., 2010, 2009). Noble gascontributions from air therefore need to be minimized andaccounted for.

Analytical procedures. The noble gas method depends on accuratedetermination of noble gas and water contents of fluid inclusions.Both are released from stalagmite samples by thermal extractionunder vacuum. Because air-filled inclusions tend to be larger thanwater inclusions (Scheidegger et al., 2010), it is possible to reducethe air content of a sample by crushing it to a grain size at whichwater inclusions are largely preserved within the grains, whereasair inclusions are cracked open and their content can be pumpedoff. In order to avoid adsorption of atmospheric noble gases on thefreshly produced grain surfaces, sample processing is performedunder vacuum by using the combined vacuum crushing and sieving(CVCS) system developed by Vogel et al. (2013). A disadvantage ofthe CVCS approach is the loss of part of the inclusion water duringpre-crushing, which implies that sufficiently large samples areneeded to obtain adequate amounts of water and noble gases forfinal analyses.

The extracted water amounts are determined manometrically(Scheidegger et al., 2010; Vogel et al., 2013), and noble gases (22Ne,36,40Ar, 86Kr, 136Xe) are analyzed by static mass spectrometry. Forthis study, we used a noncommercial all-metal 90� sector fieldmassspectrometer at ETH Zürich, which is equipped with a highly linearBauereSigner ion source (described, e.g., in Beyerle et al., 2000).Details of water and noble gas analyses as well as gas purificationprocedures and spectrometer settings are described in Vogel et al.(2013). For the manometric determination of the amounts of wa-ter extracted from the samples it is important to correct for afraction of the water (3e15 %) that adsorbs onto the metal surfacesof the line. Therefore, water loss curves need to be determined byadmitting known amounts of water into the line and observing therespective pressure reductions over time.

Despite the reduction of the air-related noble gas fraction byapplication of the CVCS technique, the measured noble gases stillrepresent binary mixtures of air and air-saturated water (ASW),which need to be separated mathematically.

Study-specific details and errors of the measurements. For ourmeasurements, stalagmite pieces of 0.7e1.5 g were loaded (one


sample at a time) into the CVCS system, which was then evacuatedand pumped for at least 24 h before crushing. Furthermore, theglass sample fingers in which later the pre-crushed grains areheated-up for final gas and water determination were baked to350 �C to reduce atmospheric noble gas backgrounds in thesystem.

Due to the relatively large size of water inclusions in speleothemWR5, the samples were rather coarsely crushed (maximum graindiameter of 1.5 mm), sieved into three size fractions, and funneledinto the pre-heated glass sample fingers without breaking thevacuum.

Water and noble gases were extracted from the largest grainsize fractions (>500 mm, unless otherwise noted) by heating thesamples (1 h, 260 �C). Blank contributions to sample gas amountswere on average 9% (22Ne), 4% (40Ar, 86Kr), and 6% (136Xe). Air andASW-derived noble gases were mathematically separated by aleast squares regression procedure, which is similar to the one ofAeschbach-Hertig et al. (1999), except for the fact that the usedroutine fits the water and noble gas amounts as independent pa-rameters instead of fitting the noble gas concentrations in thewater. This approach avoids correlation of errors associated withthe determination of the water amounts, which influences thefitting procedure in cases where the water amounts are small andassociated with uncertainties in the % range. From the ASWcomponent, equilibrium temperatures were calculated using noblegas solubility data (Kipfer et al., 2002). A c2-test was used to sta-tistically assess whether or not the measured data are adequatelydescribed by a binary mixture of air- and ASW-related noble gases.

Errors of the noble gas concentrations are presented at the 1slevel and account for the error in ion counting, the uncertaintiespropagated from interference and the blank corrections, and alsouncertainties related to absolute noble gas calibration and deter-mination of the extracted water amounts (e.g. the determination ofthe water loss curves). The errors of the noble gas concentrationwere then propagated into the NGT errors.

2.4.4. Fluid inclusion water isotopesUnderlying principle and assumptions. This method to determinecave temperatures exploits the temperature dependence of theoxygen isotope fractionation during calcite precipitation, which canbe determined by measuring the isotopic compositions of the hostcalcite and of the water trapped in fluid inclusions (d18Ow). Themethod assumes that fluid inclusions and surrounding calcite arecoeval and that the speleothem calcite precipitated in isotopicequilibriumwith the dripwater, or that the extent of disequilibriumis known. The calculation of the formation temperature requiresknowledge about the relationship between temperature and frac-tionation of oxygen isotopes, for example derived from calibrationsbased on natural or synthetic calcites grown at differenttemperatures.

Analytical procedures. The isotopic composition of the calcite ismeasured by gas-source isotope ratio mass spectrometry (IRMS)following acid digestion. The d18Ow as well as the hydrogen isotopiccomposition of the fluid inclusion water (dDw) can be measureddirectly in the water released by crushing the calcite. Two differentanalytical approaches have been used and compared in this study:i) thermal combustion/elemental analysis (TC/EA) IRMS(Dublyansky and Sp€otl, 2009), and ii) cavity ring-down spectros-copy (CRDS; Affolter et al., 2014).

In the TC/EA IRMS setup at the University of Innsbruckemployed here, fluid inclusion water is extracted with a crushingcell heated to 120 �C (Dublyansky, 2012). The released water is thenentrained in a He flow and, after cryogenic focusing, admitted intothe high-temperature reactor of a TC/EA unit (ThermoFisher



Scientific), where H2O is converted into H2 and CO. The gas transferline is held at 120 �C to minimize water adsorption. The generatedgases are analyzed using a ThermoFisher Scientific Delta VAdvantage mass spectrometer. Precise analysis with the TC/EA-IRMS method requires at least 0.1e0.2 mL of water.

The CRDS method recently developed at the University of Bernallows simultaneous determination of both dDw and d18Ow of thereleased water vapor by measuring its isotope-specific opticalabsorbance and does not require any treatment of the water priorto analysis (Affolter et al., 2014). The setup is as follows: A spe-leothem sample is placed into a copper tube and attached to themeasuring line. The entire line including the sample is kept at140 �C and flushed with a nitrogen/standard-water mixtureproviding a constant background signal. To release the water, thesample in the copper tube is crushed using a hydraulic press andthe vaporized water is flushed directly to the analyzer (PicarroL1102-i). The continuous addition of standard water with well-known isotopic composition minimizes fractionation of thereleased sample water due to adsorption on the surfaces of the line.Further, the adjusted water flow allows the measurements to beperformed close to the optimal water vapor concentration range forthe instrument (17,000e23,000 ppmv).

Study-specific details and errors of the measurements. For TC/EAIRMS, 70e100 mg of stalagmite calcite were used for stalagmiteWR5, releasing 0.4e0.8 mL of water. For the recent samples,300e500mg of calcite were used, yielding ca. 0.5 mL and 0.2e0.9 mLfor WR-MC2 and LC-1a, respectively. All samples were analyzed atleast in duplicate. For the CRDS analyses, three replicates of eachWR5 sample (100e240 mg each) were crushed releasing wateramounts between 0.4 and 2.3 mL. For the recent sample LC-1a, al-iquots around 600mgwere used, releasing ~0.5 mL of water, and forWR-MC2 between 220 and 600 mg aliquots were used for wateramounts between 0.3 and 0.8 mL.

With the TC/EA IRMS method, measurements of d18Ow often donot reproduce well and/or yield improbable values, which is alsoobserved in this study. For this reason, following the approach ofHarmon and Schwarcz (1981), we calculated d18Ow from measureddDw, using the relationship between d18Ow and dDw determinedfrom local drip water samples obtained over 5 years in variousMulu caves (Moerman et al., 2014). This local drip water line isslightly offset towards more negative d18Ow (by ~0.3‰) relative tothe Local Meteoric Water Line of the same location (LMWL;Moerman et al., 2013), which is nearly identical to the GlobalMeteoric Water Line (Fig. A.4). Such an offset has also beenobserved in other locations, and has been related to watercondensation on cave walls (Genty et al., 2014). The drip waterrelationship and the LMWL may vary over geological times (e.g.,Gat, 1980), and in some cases may be dependent on the prevailingsources of moisture supply (Weyhenmeyer et al., 2000). Theseadditional uncertainties have to be taken into account wheninterpreting d18Ow values calculated from dDw.

The analytical uncertainty of the TC/EA IRMS setup in Innsbruckis 1.5‰ for dD (1 SD; Dublyansky and Sp€otl, 2009), translating to anuncertainty of ~0.9 �C for water conforming to the meteoric waterline relationship. Analytical uncertainties with CRDS in Bern arebetter than 1.5‰ for dDw and 0.4‰ for d18Ow (1 SD; Affolter et al.,2014). Due to the limited number of replicate measurements forboth methods, we use these estimates of long-term precision asmeasurement uncertainty whenever observed standard deviationswere smaller.

Aliquots of the carbonate powders remaining after analyseswith the two methods were analyzed for d18Occ, after homogeni-zation of the crushed powders with mortar and pestle. The mea-surements were performed by continuous-flow IRMS at ETH Zürich


using a GasBench II carbonate preparation device coupled to a DeltaV Plus mass spectrometer (both from ThermoFisher Scientific) withthe method described by Breitenbach and Bernasconi (2011).

The temperature dependence of the equilibrium fractionationfactor between d18Ow and d18Occ has been determined by variousstudies, resulting in multiple equations for calculating temperature(e.g., Coplen, 2007; Craig,1965; Friedman and O'Neil, 1977; Kim andO'Neil, 1997; Tremaine et al., 2011). Here we calculated tempera-tures using the equation of Tremaine et al. (2011), which was ob-tained from in situ growth experiments in a cave, combined with alarge number of published speleothem data from different loca-tions, as well as with the synthetic calcite calibration of Kim andO'Neil (1997).

2.4.5. Clumped isotope thermometry

Underlying principle and assumptions. The carbonate clumpedisotope thermometer is based on the ordering (‘clumping’) of iso-topes in carbonate ions, and more specifically on the abundance ofcarbonate ions containing both rare isotopes, 18O and 13C (Eiler,2007). The bond between these two heavy isotopes is favored un-der colder conditions, allowing reconstruction of the formationtemperature of the carbonate mineral from its ordering state(Schauble et al., 2006). The low abundance of clumped moleculesmakes the measurement analytically challenging and prone to avariety of mass spectrometer-induced artifacts, which have to becorrected for. The method relies on the assumption that isotopicequilibrium has been achieved between dissolved inorganic car-bonate (DIC) and water, or that the degree of disequilibrium isknown. The calculation of temperatures relies on empirical ortheoretical calibrations of the temperature-dependence of theabundance of 18Oe13C bonds.

Analytical procedures. Details of the analytical method have beendescribed by Meckler et al. (2014). In brief, the abundance of18Oe13C bonds in CO2 released from the sample (i.e., cardinal mass47) is measured with a gas source IRMS, together with the overallabundance of each isotope (d13C and d18O). By calculating the offsetof the measured mass 47 abundance from the concentration ex-pected if the distribution of all isotopes were stochastic (D47), onecan derive a temperature estimate using empirical calibrations.

The measurements for this study were performed at ETH Zürichwith a MAT 253 mass spectrometer coupled to a Kiel IV carbonatepreparation device (both from ThermoFisher Scientific). Wedistinguish between the terms “measurement” and “analysis”:Each measurement consists of 8e12 analyses within the samesample run of sample aliquots of 150e200 mg each (i.e., 1.2e2.0 mgcalcite are used per measurement). The carbonate powders areindependently converted to CO2 by phosphoric acid digestion at70 �C. After removal of water, the released CO2 is purified in aPorapak column, before being analyzed on the IRMS in micro-volume mode. The data are corrected for pressure-dependentbaseline signals. Several carbonate standards are measuredfrequently, and the results are used to correct the sample data. Alldata are reported in the absolute reference frame (Dennis et al.,2011) and are corrected for the difference in acid digestion frac-tionation at 70 �C compared to 25 �C by adding 0.064‰ to D47

(Meckler et al., 2014).

Study-specific details and errors of the measurements. In this study,4e7 replicate measurements (with 8e12 aliquots each) were per-formed on the same homogenized powder over the course ofseveral months. As the results from multiple replicate measure-ments typically display a normal distribution and the error of theirmean follows counting statistics laws (Meckler et al., 2014), we



report the uncertainty of the clumped isotope temperatures as thestandard errors of the mean (1 SE) of the replicate measurements.

Similar to the oxygen isotope fractionation between calcite andwater, several temperature calibrations for D47 have been proposed(e.g., Defliese et al., 2015; Dennis and Schrag, 2010; Ghosh et al.,2006; Zaarur et al., 2013). We used four different calibrations forour calculations: Two synthetic calcite calibrations obtained at YaleUniversity using different calcite precipitation methods (Affek andZaarur, 2014; Zaarur et al., 2013), and two calibrations obtained atETH Zürich with the same analytical setup used for this study,based on synthetic calcites and natural travertines, respectively. Inorder to use the Yale calibrations, we tentatively adjusted our D47

results for observed inter-laboratory differences by adding 0.025‰,the average offset observed in four standards measured repeatedlyin both laboratories (see Supplementary information). However,due to the large uncertainty associated with this approach (forexample, it is not yet clear whether this offset varies withcomposition), we currently prefer to mainly rely on the syntheticcarbonate calibration derived at ETH Zürich.

For this calibration, which will be published elsewhere, thetemperature dependence of D47 was assessed with synthetic calciteproduced at the University of Leeds at different temperatures be-tween 3.5 and 70 �C. The calcite was precipitated slowly during twodays on glass beads by constant addition (2 ml/h) of 0.1 M CaCl2 and0.1 M NaHCO3 to a parent solution in an N2 atmosphere, using asystem similar to those described by Bots et al. (2011) and Tesorieroand Pankow (1996). pH measured before and after the experimentsranged from 6.6 to 8.2. The calibration yielded the robust relation-ship D47 ¼ (0.044 ± 0.006 � 106)/T2 þ (0.179 ± 0.071), and a tem-perature dependence of the oxygen isotope fractionation similar tothose found by Kim and O'Neil (1997) and Zaarur et al. (2013). Thetravertine calibration from ETH Zürich (Kele et al., in press), whichwe use for comparison, covers a temperature range of 5e95 �C. Thetravertines cover a wide range of environmental parameters like pH,temperature, and saturation state. Nonetheless, the calibration lineis well defined as D47 ¼ (0.044 ± 0.005 � 106)/T2 þ (0.205 ± 0.050),with the same slope of D47 against T�2 as the constant additionsynthetic calcite calibration, but a different intercept.

3. Results and evaluation of individual methods

3.1. Fluid inclusion petrography

Stalagmite WR5 displays marked changes in color (Figs. 3a andA.1) that correlatewith glacial (gray) and interglacial (ochre yellow)periods and are a subject for further investigations. The stalagmitehas a columnar calcite fabric, with mm-to cm-scale alternations ofporous, inclusion-rich and dense, almost inclusion-free layers(Fig. 3b). These variations in porosity occur within the samecolumnar macro-crystals and can be traced laterally across crystalboundaries. Additionally, several growth hiatuses were identified(see Fig 3e for an example), but their duration could not be resolvedby U-series dating. The agemodel proposed byMeckler et al. (2012)yields a mean growth rate of approximately 1.5 mm/year, suggestingthat individual porous and dense calcite intervals can cover severalhundreds to thousands of years.

Fluid inclusions are abundant in stalagmite WR5 and are ar-ranged along former growth surfaces. Their largest extension isparallel to the main growth direction of the calcite crystals, indi-cating that they were formed during crystal growth and thus, are ofprimary origin. Secondary inclusions, in contrast, would haveformed along healed cracks, but were not observed in our samples.

In spite of their abundance, the fluid inclusions are well sepa-rated from each other. The inclusions are typically monophaseliquid (i.e., they do not contain a vapor phase), and the volume of


individual inclusions is up to 106 mm3, with large variations amongdifferent porous layers. Fig. 3c and d show two examples of fluidinclusion assemblages, one with large inclusions of elongatespindle-like shape and the other one with rather small, more iso-metric inclusions. Fig. 3f displays some typical inclusion shapes thatall seal off in a characteristic thorn-shaped tip at the upper end.

Fig. 3c and d also show some dark, air-filled inclusions, whichcan complicate the noble gas measurements (see Section 2.4.3).Most of these air-filled inclusions, however, were located very closeto the surface of the thick sections, suggesting that they may haveresulted from leakage of initially water-filled inclusions caused bysample preparation. Still, as we cannot unambiguously distinguishbetween originally air-filled inclusions and inclusions that haveleaked after sample preparation, we cannot exclude the presence ofprimary air-filled inclusions.

Based on our petrographic observations, we conclude that thefluid inclusions in stalagmite WR5 can be regarded as closed sys-tems that preserved the original properties of the encapsulateddrip water. Potential small alterations, particularly changes of thewater density, are likely to have resulted from mechanical stressduring sample preparation (see Section 3.2).

The two recent samples (LC-1a and WR-MC2) also show acolumnar calcite fabric with partly irregular crystal boundaries(Fig. 3g and l). Both samples exhibit several growth hiatuses(Fig. 3g, h, i, and l) that are sometimes followed by a layer of smallcalcite crystals with random orientation. The shapes of the fluidinclusions in the two recent samples differ from those in WR5, asthey have more irregular shapes, and are thin and strongly elongate(aspect ratios >20; Fig. 3k and m through p). The boundaries of theinclusions often appear obscure, due to their irregular shapes andcapillary tails, which made a visual discrimination between sepa-rated and interconnected inclusions difficult. As for WR5, all in-clusions appear to be of primary origin.

3.2. Liquidevapor homogenization temperatures

The stalagmite formation temperatures estimated from liq-uidevapor homogenization are shown in Figs. 4 and A.3 and re-ported in Table A.1. Raw data used to determine Th∞ (i.e., Th(obs)and bubble radii) and calculated inclusion volumes are reportedas Supplementary information. Assuming that the inclusionspreserved their original water density, each Th∞ value representsthe formation temperature of the respective inclusion at the timeit was sealed off from the environment. In some of the inclusions,however, the water densities appear to have decreased after for-mation, resulting in Th∞ values significantly higher than the ma-jority of inclusions in the same layer. The density alterations inthese inclusions were likely caused by mechanical stress inducedby cutting the stalagmite sections, leading to cracks along thecalcite cleavage planes and leakage of tiny amounts of water.These effects result in a decrease of the water density and thus inan increase of Th(obs) and Th∞. An increase of the inclusion volumeby only 0.05%, for instance, would increase Th(obs) by more than2 �C. Since the samples were not heated above 27 �C, large fluidoverpressure in the inclusions during analysis can be excluded asa potential reason for artificially induced volume changes. Densityalterations are most obvious in inclusions with Th(obs) > 27 �C (i.e.,where no homogenization was observed until 27 �C). Th∞ values ofthese inclusions would plot clearly above the temperaturesdetermined for the other inclusions, which show a nearly normaldistribution (Figs. 4 and A.3). The distribution of the Th∞ valueswas also used as a criterion to identify a few more inclusions thatlikely changed density during sample preparation, but still ho-mogenized below 27 �C. Temperatures obtained from these in-clusions are plotted in gray in Figs. 4 and A.3 and marked by



asterisks in Table A.1, and were not considered in further statis-tical treatment of the data. In a few cases (e.g., two inclusions withTh∞ between 25 and 26 �C in LC-1a), the distinction betweenintact and altered inclusions is less obvious. However, incorpo-rating the respective inclusions into calculations would only havea small effect on average temperature estimates (e.g., an increaseof 0.2 �C in the case of LC-1a).

Artificially low Th∞ values are less likely. Unlike fluid inclusionsin gypsum (Krüger et al., 2013), we could not find evidence of post-entrapment volume decreases of inclusions in stalagmites that

Fig. 3. Petrography and fluid inclusions of the part of stalagmite WR5 used for this study anda) Cut face parallel to the growth axis of stalagmite WR5 displaying distinct color zoning. Locviewed under cross-polarized light. The image shows a columnar calcite fabric with large, 5eover the whole section length. Dense and porous calcite layers intersect the boundaries ospindle-like shape; note isolated dark, air-filled inclusions. d) Assemblage of very small fluidminor calcite dissolution (black arrows). f) Examples of typical inclusion shapes. All inclusgrowth. g) and l) Sections of the recent samples (LC-1a and WR-MC2) under cross-polarizedbars on the left indicate the intervals analyzed for this study. h) through k) typical appearantypical appearance of fluid inclusions in sample WR-MC2. Inclusions in both recent samplesinclusions is often obscure. (For interpretation of the references to color in this figure lege


would result in a decrease of Th∞. In the case of gypsum the volumedecrease results from plastic deformation of the inclusionwalls dueto tensile stress occurring in the metastable liquid state of the in-clusions, leading to a clear correlation of Th∞ values with the vol-ume of inclusions, which cannot be observed in Fig. 4. Themaximum tensile stress acting on the inclusion walls in the sta-lagmite samples was obviously too low. Since we do not have otherconvincing arguments to exclude Th∞ values on the low-temperature side, we consider all as potential formation tempera-tures of the stalagmite.

the two recent samples, at different scales. White arrows indicate the growth direction.ations of images shown in panels bee are indicated. b) 300 mm-thick stalagmite section7 mmwide calcite domains of slightly differing crystallographic orientation extendingf the calcite domains. c) Assemblage of large monophase fluid inclusions of elongateinclusions. e) Growth hiatus (type E surface (Railsback et al., 2013)) showing evidence ofions are monophase liquid and display thorn-shaped terminations in the direction oflight. Both samples feature columnar calcite fabric and several growth hiatuses. Whitece of fluid inclusion assemblages and growth hiatuses in sample LC-1a. m) through p)have significantly higher aspect ratios compared to those in WR5 and the outline of thend, the reader is referred to the web version of this article.)



Within samples, the spread among the individual Th∞ valuesthat were considered reliable (N ¼ 14e42; Table A.1) ranges from1.6 �C (sample LC-1a) to 4.3 �C (WR5-302), with a typical spread ofaround 3 �C. As the sample fragments used for the measurementshave a length of 3e5 mm in growth direction of the stalagmite, theanalyzed fluid inclusion assemblages may cover time intervals ofseveral thousand years. In the present study we did not analyze theinclusions at a higher spatial, i.e., temporal, resolution in order tomake the average temperatures directly comparable to those fromthe other methods, which are bulk measurements. In Fig. 4 we have

Fig. 4. Liquidevapor homogenization temperatures (Th∞) plotted against inclusion volumesstandard deviations of the data considered to have been derived from unaltered inclusionsterations of the inclusions induced by sample preparation and thus, were not considered f


indicated the mean stalagmite formation temperature (dashedlines) and the variability of temperatures (±1 SD; gray bands) foreach sample.

Considering the long time intervals covered by the sampleshosting the individual inclusions and the fact that each inclusionrepresents a snap-shot of temperature at the time it sealed off fromthe environment, the observed spread among the individual Th∞values may reflect real fluctuations in cave temperature. A com-parison between old and recent samples from Whiterock Caveshows similar spreads among individual Th∞ values, suggesting

for all measured stalagmite samples. Stippled lines indicate averages and gray bands the(black symbols). Data points plotted with light symbols likely result from density al-

or statistical analysis.


quationof

Trem

aineet

al.(20

11)an

dclumped

isotop

etempe

raturesareba

sedon

the

resentedin

Table3,

areindicated

.Theco

mbined

temperature

reco

rdco

nsistsof

error-

raturesba

sedon

mea

suredd1

8Owwereusedforthis

averag

ing.

reHom

ogen

izationtemperature

Nob

lega

stemperature

Com

bined

reco

rd

Ave

rage

SDSD

SD

22.7

0.9

ee

23.8

0.8

23.4

0.5

ee

23.0

1.9

22.8

1.0

ee

22.6

1.1

22.1

0.7

23.8

2.1

22.1

0.9

ee

22.7

1.0

20.1

0.8

18.7

0.7

ee

19.0

0.6

23.1

1.7

20.3

0.8

21.9

0.9

25.5

1.8

22.5

0.8

23.4

1.0

ee

24.6

1.0

ee

25.3

1.5

23.3

0.7

ee

25.5

1.2

ee

23.0

0.6

ee

22.7

0.8

21.5

0.8

19.1

3.3

21.1

1.7

19.0

0.9

ee

20.0

0.6

19.0

0.7

ee

19.3

0.4

ee

21.1

0.9

ee


that the relatively large temperature variations observed in theWR5 samples do not result from alterations of the inclusion den-sities over time. The spread of Th∞ values in LC-1a (1.6 �C) issmaller than that in WR-MC2 (3.6 �C), suggesting higher temper-ature variations in Whiterock Cave than in Lang's Cave. However,given the limited temporal and spatial coverage of temperaturemonitoring data and lack of high-resolution temperature re-constructions from the caves, we cannot ascertain at this pointwhether such a range in cave air temperature is realistic for the last1000e2000 years.

The mean formation temperature of stalagmite sample LC-1awas determined at 23.4 ± 0.6 e close to, but slightly lower than,the measured present-day cave temperature in Lang's Cave of24.1 �C (Table 1, Fig. 2). Compared to other samples, LC-1a con-tained more damaged inclusions yielding Th(obs) > 27 �C (Fig. A.3).The formation temperature derived for the second recent sample,WR-MC2, is 22.7 ± 0.9 �C. Formation temperatures determined forstalagmite WR5 display a clear glacialeinterglacial temperaturepattern with an amplitude of approximately 4.5 �C, and similarabsolute values for the two glacial and interglacial periods,respectively (Table 3, Fig. 8). The temperature maximum duringMIS 11 is 23.4 ± 1.0 �C, whereas temperature minima during theglacial periods MIS 10 and 12 were at around 19.0 �C. Standarddeviations (1 SD) of the formation temperatures determined forWR5 range from 0.5 to 1.0 �C (Table 2).

Table

2Com

parison

oftemperature

estimates

(in

� C)from

thedifferentproxies.F

luid

inclusion

isotop

etemperatureswerecalculatedwiththee

calib

ration

withsynthetic

calcites

ofZieg

leret

al.(in

prep.).Th

eresu

ltsthat

wereusedforav

erag

eglaciala

ndinterglacial

temperatures,p

weigh

tedav

erag

esof

thedifferenttempe

rature

estimates

forea

chsample

dep

th(excep

tforW

R5-34

6,seeSe

ction5.2).F

orCRDS,

tempe

Ave

ragingintervals

forTa

ble3

Sample

(*clumped

isotop

esamples)

Age

(ka)

Fluidinclusion

isotop

etemperature

Clumped

isotop

etemperatu

CRDS

from

d18O

SDCRDS

from

dDSD

IRMSfrom

dDSD

Ave

rage

SE

WR-M

C2

24.8

2.1

24.5

0.9

23.4

0.9

26.3

2.1

LC-1a

27.1

7.2

24.1

0.9

22.5

0.9

21.9

1.2

239

333

23.3

1.7

20.3

0.9

21.0

2.5

ee

WR5-24

6*/247

336

22.2

1.3

20.0

1.5

20.3

1.6

22.7

3.0

MIS10

WR5-25

5*/258

350

19.2

0.9

16.1

1.1

ee

16.9

1.9

MIS10

WR5-26

336

220

.30.9

17.2

0.9

17.7

1.5

ee

WR5-27

737

219

.92.0

16.8

0.9

16.6

1.6

21.6

1.4

WR5-30

239

622

.72.0

19.4

0.9

20.5

0.9

24.9

2.3

MIS11

WR5-31

840

927

.81.5

21.7

0.9

22.3

1.3

27.4

3.2

MIS11

WR5-32

041

123

.80.9

21.2

0.9

21.7

0.9

ee

MIS11

WR5-32

0repea

t41

1e

ee

ee

ee

e

WR5-33

141

921

.91.4

17.8

0.9

ee

ee

WR5-34

6/34

7*43

118

.51.9

12.6

1.4

12.2

1.7

24.2

2.0

MIS12

WR5-36

3/36

4*43

821

.31.0

18.2

0.9

e19

.71.2

MIS12

WR5-38

7*/388

447

19.5

0.9

16.9

0.9

17.5

0.9

19.7

1.5

MIS12

WR5-39

845

1e

ee

ee

ee

e
3.3. Noble gas temperatures
Before estimating NGTs, we investigated whether the measurednoble gas amounts (Table A.2) are adequately described as binarymixture of air and air-saturated water (ASW). In the three-elementplots shown in Fig. 5, any such mixture will fall on a straight lineconnecting the two end-member compositions. Only for such mix-tures, the fitting exercise will provide robust temperature estimates.

In the Ne/Kr vs. Xe/Kr plot (Fig. 5a), most of the WR5 samplesplot on the mixing line within 1-sigma uncertainties. In the Ar/Krvs. Xe/Kr plot (Fig. 5b), these samples show a small but systematicoffset to the right of the mixing line, and overlap within 2-sigmauncertainties only, indicating small excesses of Ar (in the percentrange) in the sample gas. These small Ar excesses most likelyoriginate from the getter pellets in the extraction and purificationline, which were produced in an Ar protective atmosphere, and,despite thorough baking, still release residual Ar whenever a sig-nificant amount of sample gas is admitted to the getters. Therefore,we only used Ne, Kr, and Xe data for fitting the temperatures,although using all four noble gas concentrations still leads to sta-tistically robust NGTs.

NGTs derived from fitting Ne, Kr, and Xe concentrations areshown in Tables 2 and A.2 and in Fig. 8. NGTs determined for twoaliquots of sample WR5-320 with different sample weights andthus different amounts of extracted water were nearly identical(25.3 ± 1.5 �C and 25.5 ± 1.2 �C, Table A.2), excluding a potentialinfluence of the sample weight or the amount of extracted water onthe temperature estimates. NGTs in WR5 vary between 19.1 �C(WR5-346; Termination V) and 25.5 �C (WR5-302 and WR5-320;MIS 11). The temperature estimate for Termination V is associatedwith the largest error, due to a large contribution of noble gasesfrom air-filled inclusions (the data point is closest to the air end-member in Fig. 5 and also shows a high Ne concentration,Table A.2). The temperature estimates for the glacial periods aremore reliable and slightly higher than for Termination V (around21.1 �C for MIS 12 and around 22.7 �C for MIS 10; Table 2). Overall,the NGTs suggest glacialeinterglacial temperature differences ofaround 4.3 and 2.7 �C for MIS 12e11 and MIS 11e10, respectively

Please cite this article in press as: Meckler, A.N., et al., Glacialeinterglacial temperature change in the tropical West Pacific: A comparison ofstalagmite-based paleo-thermometers, Quaternary Science Reviews (2015), http://dx.doi.org/10.1016/j.quascirev.2015.06.015


(Table 3). Uncertainties of the NGTs range between 0.9 and 3.3 �C (1SD; Table 2).

In contrast to the WR5 samples, the recent samples fromWhiterock Cave and Lang's Cave plot either close to the end-member composition of air, or far off the binary mixing lines(Fig. 5), indicating strongly fractionated noble gas composition.Measurement of a third recent sample (GC04) from a different caveclose to Mulu (Green Cathedral Cave at 160 m a.s.l.; Fig. 1) led to thesame conclusion (Fig. 5). Using the medium grain size fraction(300e500 mm, labeled “m” in Fig. 5) for WR-MC2 and GC04 yieldednoble gas ratios even further off the mixing line. In addition, thewater amounts extracted per gram of calcite from the recentsamples were considerably lower (on average 0.2 mL/g) than for theold samples (on average 1 mL/g). Whereas petrographic inspectionsuggested somewhat lower water contents in the recent samples(see Section 3.1), this large difference points to an additional waterloss during processing of the recent samples in the CVCS system.The strongly elongated shape of fluid inclusions in the recentsamples (Fig. 3 and Section 3.1) makes them likelymore prone to bedamaged during pre-crushing in the CVCS system. Knowing thatthe temperature of the recent samples should be close to 24 �C, andusing the measured NeeXe amounts, we roughly estimate that the

Fig. 5. Three-element plots Ne/Kr vs. Xe/Kr (a) and Ar/Kr vs. Xe/Kr (b). Filled symbolsrepresent WR5 samples, open symbols represent recent samples. Replicate measure-ments are indicated by “a” and “b” in brackets, and different grain size fractions areindicated by c (coarse) and m (medium). Element ratios are calculated from noble gasamounts given in Table A.2 and error bars are 1 SD. The gray dashed line represents themixing line between the end-member compositions of air and air-saturated water(ASW). ASW compositions (blue stars) are calculated for temperatures of 20 and 26 �C,taking into account the present day elevation of Whiterock Cave of 200 m a.s.l. andusing noble gas solubility data (Kipfer et al., 2002). (For interpretation of the referencesto color in this figure legend, the reader is referred to the web version of this article.)


water amounts originally associated with these samples were 2e4times higher than the measured water yields.

In addition to water loss, the noble gas ratios in the recentsamples point to fractionation of the noble gases: It can be hy-pothesized that water molecules and the small (light) noble gasespreferentially leave an inclusion at an earlier stage or faster duringcrushing under vacuum than the larger and “stickier” heavy noblegas atoms (e.g., through tiny cracks opening during pre-crushing).Thus, it is possible that inclusions in recent to sub-recent (<2000years old) speleothem calcite are not yet sufficiently sealed towithstand crushing under vacuum in the CVCS system, causingnoble gas fractionation. We speculate that the better performanceof ‘older’ stalagmite samples with regard to noble gas analysis couldbe caused by slow recrystallization (redistribution) of the calcitesurrounding the inclusions over time, which leads to better fluidinclusion protection.

It is possible that the large number of damaged inclusionsobserved in LC-1a during liquidevapor homogenization measure-ments (see Section 3.2) is also indicative of fragile inclusionwalls inyoung speleothem calcite. The recent samples WR-MC2 and LC-1awere drilled, which probably caused high mechanical stress on thecalcite host and could have altered inclusions in these samples.However, this cannot be the main reason for our observation, asnoble gas fractionation was also observed in the recent stalagmitesample from Green Cathedral Cave, which was not drilled. The ef-fects of stalagmite aging on fluid inclusion conservation shouldbecome subject of further investigations.

3.4. Fluid inclusion water isotope temperatures

The d18Ow and dDw of fluid inclusion water of 11 stalagmitesamples was determined by both the TC/EA IRMS and the CRDSmethods. A comparison of the measured water concentrations canserve as a test for the efficiency of the two different crushing sys-tems, though it has to be kept in mind that heterogeneous distri-bution of fluid inclusions can lead to different fluid inclusionabundance in different subsamples. In some samples, the wateryields with the different crushing systems differed significantly.Higher yields were obtained with the CRDS system in most cases(Table A.3), potentially related to larger calcite sample amountsused in this setup (100e240 mg) compared to the TC/EA IRMSsystem (70e100 mg for WR5). In both systems, the recent samplesreleased significantly smaller amounts of water compared to theold WR5 samples, but unlike for noble gases still yielded mean-ingful temperature estimates.

The fluid inclusion isotopic compositions are shown in Fig. 6 incomparison with the present-day drip water line (Moerman et al.,2014), the GMWL, and the LMWL (Moerman et al., 2013). Thed18Ow values determined by TC/EA IRMS deviate from the MWLstowards lower d18Ow to a varying degree. Taken at face value, theywould suggest unrealistically high deuterium excess in paleowater (~20‰) and are therefore considered to be unreliable. d18Owvalues obtained with CRDS, in contrast, are somewhat offset fromthe drip water line towards higher d18Ow. The reason for thepositive offset of d18Ow values from CRDS is not clear. Samplesfrom different climatic stages (e.g., glacial versus interglacialversus deglacial dry episodes) do not show a consistent extent ofdivergence from the MWLs, suggesting that the offset is notdirectly related to large-scale climatic boundary conditions. As wehave no independent evidence for analytical artifacts in the CRDSsystem at this stage, we consider both measured and calculatedd18Ow values for the CRDS method in this study. The recentsample LC-1a did not reproduce well in d18Ow, leading to a largeerror in the calculated temperature when it is based on measuredd18Ow.



In contrast to d18Ow, very good agreement is observed for dDwbetween the two methods (Fig. 6, Table A.3). The only exception issample WR5-302, where dDw measured by TC/EA IRMS is signifi-cantly lower than the value obtained by CRDS. However, thissample is also the only sample where d18Occ values of the crushedpowders differ significantly (Table A.3, Fig. 7a). The discrepancy istherefore likely due to biases in sampling, which is confirmed bythe good reproducibility of the calculated temperatures for thissample when comparing dDw-based results (Table 2, Fig. 7a).

To circumvent the uncertainties related to d18Ow in the com-parison of the two different analytical techniques, we reportCRDS temperatures based on calculated d18Ow from dD (Table 2,Fig. 7a), in addition to the results based on measured d18Ow,which are used for all other comparisons. Fig. 7a furthermoreshows the effects of choosing different water lines for calculatingd18Ow from dD, and the effect of choosing different temperaturecalibrations. Temperatures derived from measured d18Ow (onlyfor CRDS) are systematically higher than those using calculatedd18Ow, owing to the fact that the measured d18Ow plot to the rightof the drip water line. The difference in the temperature esti-mates based on measured versus calculated d18Ow typically rangebetween 2.2 and 3.3 �C, with the exception of WR-MC2 (0.3 �C)and the samples that were most offset from the LMWL: WR5-318(6.1 �C), WR5-346 (5.9 �C), and WR5-331 (4.1 �C) (Table A.3,Fig. 7a).

When temperatures are based on dD, the results from CRDS andTC/EA IRMS are in excellent agreement for all samples, with de-viations of typically less than 1 �C. A slight exception is sample LC-1a that shows a temperature difference of 1.6 �C. When calculatingd18Ow from dD, choosing the LMWL over the drip water line yields

Fig. 6. Isotopic composition of fluid inclusion water in comparison to the global and local mIRMS are plotted as open triangles, and those from CRDS as filled circles, with colors denperformed with TC/EA IRMS and CRDS (see also Table A.3), whereas IRMS results are offset treferences to color in this figure legend, the reader is referred to the web version of this ar


higher temperatures (1.1e1.5 �C for IRMS measurements; Fig. 7a),due the offset between the different water lines (Fig. 6).

The mean stalagmite formation temperatures derived fromIRMS for the recent samples are 23.4 ± 0.9 and 22.5 ± 0.9 �C forWR-MC2 and LC-1a, respectively, slightly lower that the present-daytemperature range of 24.1 ± 0.1 �C in Lang's Cave. Using theLMWL for calculating d18Ow would yield temperatures more closelymatching themeasured cave temperature (24.9 �C forWR-MC2 and23.9 �C for LC-1a). Nonetheless, we use the drip water line resultsfor further comparisons, as this line is expected to be most repre-sentative for the relationship between d18O and dD at the site ofstalagmite formation. Whatever process causes the isotopic dif-ference between rainwater and drip water should also be ‘felt’ bythe stalagmite fluid inclusions, which are relicts of ancient dripwater. The drip water line was derived fromMulu cave samples andincludes many samples from the caves where the stalagmites forthis study were obtained (Fig. A.4). The temperatures derived forthe recent samples from CRDS measurements (from measuredd18Ow) are associated with large errors which encompass themeasured cave temperature: 24.8 ± 2.1 �C for WR-MC2 and27.1 ± 7.2 �C for LC-1a. Calculating d18Ow from dD would bringtemperatures even closer to measured Lang's Cave temperature,yielding 24.5 ± 0.9 �C for WR-MC2 and 24.1 ± 0.9 �C for LC-1a. Wenonetheless use measured d18Ow for further comparisons, becauseat this point we have no clear indication for measurement biases.

Using the Kim and O'Neil (1997) equation instead of the cali-bration of Tremaine et al. (2011) decreases calculated temperaturesby around 5 �C (Table A.3, Fig. 7a), resulting in temperature esti-mates for the recent samples much lower than the measured cavetemperature. For both IRMS and CRDS, we therefore use the

eteoric water lines (GMWL, LMWL) and the cave drip water line. Results from TC/EAoting different samples. Note the good reproducibility in dD between measurementsoward more negative d18O values (see Sections 2.4.4 and 3.4). (For interpretation of theticle.)


Fig. 7. Fluid inclusion isotope- and clumped isotope-based temperature estimates from the recent samples and stalagmite WR5. a) Temperatures derived from the difference ind18Ow and d18Occ, in comparison with the continuous d18Occ record from WR5 (Meckler et al., 2012). d18Occ from the samples analyzed for fluid inclusions are also plotted forreference (blue circles and triangles). The temperature estimates were derived with two different analytical techniques (CRDS and TC/EA IRMS). For CRDS, temperatures frommeasured d18Ow (filled red circles) are shown as well as those obtained when d18Ow was calculated from dDw and the drip water line (open red circles). IRMS-based results werealways calculated from dDw, with either the drip water line (closed triangles) or the LMWL (open triangles). Two different calibrations were used for comparison: Tremaine et al.(2011; yellow triangles) as for CRDS, and Kim and O'Neil (1997; yellow crosses). b) Clumped isotope temperatures. All replicate measurements are shown in light color together withthe averages and their standard errors for the constant addition synthetic calcite calibration obtained at ETH (closed diamonds; Ziegler et al., in prep.). Temperatures wereadditionally calculated with a travertine calibration (open diamonds; Kele et al., in press) and with two calibrations obtained with a different analytical setup, after tentativecorrection for inter-laboratory differences. These calibrations are based on calcite precipitated at the solution surface (purple crosses; Affek and Zaarur, 2014) and in a bulk solution(purple circles; Zaarur et al., 2013). Dark gray lines depict the present-day temperature in Lang's Cave. Marine isotope stages (MIS) and glacial terminations (T-) are indicated at thetop. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)


equation of Tremaine et al. (2011) from here on. When comparingthe fluid inclusion isotope results to other methods, however, onehas to keep in mind that the reported temperatures systematicallydepend on the choice of calibration.

The formation temperatures obtained for WR5 from CRDS withmeasured d18Ow and the Tremaine et al. (2011) equation variedbetween 18.5 �C (WR5-346, or Termination V) and 27.8 �C (WR5-318, or MIS 11). For IRMS (d18Ow calculated from the drip waterline), the same samples yielded 12.2 �C and 22.3 �C, respectively. Ifthe extremely low IRMS-derived temperature estimate for Termi-nation V was real, it could indicate disequilibrium effects, whichwill be discussed in Section 4.3. The high temperature derived from


CRDS forWR5-318 is not supported by another sample fromMIS 11,WR5-320, which partly encompasses the same layers as WR5-318(Fig. A.1) and yielded 23.8 �C. Calculating d18Ow for CRDS resultsin consistent temperatures for the MIS 11 samples and a similarlylow temperature for Termination V as that obtained from IRMS.Apart from these few cases in which the choice of parameters hasan unusually large influence on the results, the remaining samplesyielded coherent results, with glacial temperatures around19e21 �C for both MIS 12 and 10 when based on measured d18Ow,and around 17e18 �C with calculated d18Ow for both analyticalsetups. Results from both methods suggest a glacialeinterglacialtemperature variation of around 4e5 �C.



3.5. Clumped isotope temperatures

The temperature estimates from all individual clumped isotopemeasurements are plotted in Fig. 7b. The standard errors of themean values vary between 1.2 and 3.2 �C (when using the constantaddition synthetic calcite calibration; Table A.4).

The determined temperature values systematically depend onthe choice of the calibration curve. The travertine calibration yieldson average 5 �C higher temperatures compared to the calibrationbased on the constant addition synthetic calcitee a reflection of thedifferent intercepts of the two calibration lines. The offset of thetwo calibrations is subject to further study, and could be related toprecipitation mechanisms, pH, saturation state, and/or precipita-tion rate. Travertine formation could be regarded as similar tospeleothem growth, as both form from solutions becoming super-saturated by degassing of CO2. However, travertines tend to pre-cipitate more rapidly and over longer distances, which might resultin different degree and expression of disequilibrium compared tospeleothems (Kele et al., in press).

Temperatures calculated with a synthetic calibration from Yalebased onbulk solutionprecipitation experiments (Zaarur et al., 2013)are similar (þ0.4 �C to þ2.5 �C) to those obtained with the constantaddition calibration from ETH (Fig. 7b), after tentatively adding0.025‰ to measured D47 to correct for inter-laboratory differences(see Section 2.4.5). We note that the reduced glacialeinterglacialamplitudewhenusing this calibrationreflects the steeperslope in theD47 � 1/T2 relationship compared to the ETH calibrations.

Discrepancies among calibrations obtained with differentanalytical setups are commonly observed, but not yet understood.They could be related to differences in the temperature of aciddigestion, sample and acid amounts, or duration of contact be-tween CO2 and acid (Defliese et al., 2015; Fernandez et al., 2014;Wacker et al., 2013). In addition, different conditions for carbon-ate formationwith different precipitation mechanisms could play arole. Speleothems seem to be special cases in that clumped isotopetemperatures calculated with calibrations from classical bulk so-lution precipitation have been found to be unrealistically high,which has been interpreted as a sign of kinetic fractionation effects(Affek et al., 2008; Wainer et al., 2011). Affek and Zaarur (2014)recently produced a calibration that is supposed to reflect this ki-netic fractionation effect, being based on synthetic calcite precipi-tated at the solution surface. For our samples, this calibration yieldsmuch colder temperatures (�7.5 �C, Fig. 7b).

At this point, we consider the constant addition synthetic calcitecalibration from ETH to be most appropriate, as it was derived withthe same analytical system used for our analyses and is based onslow calcite precipitation under controlled conditions. With thiscalibration, temperatures for the recent samples were 21.9 ± 1.2 �Cfor LC-1a and 26.3 ± 2.1 �C for WR-MC2. The temperature estimatefor LC-1a is lower than the measured temperature in Lang's Cave(24.1 ± 0.1 �C), however agreeing within 2 SE, whereas the tem-perature for WR-MC2 is higher than the temperatures measured inthe other caves. For stalagmite WR5, temperatures varied between16.9 �C (WR5-246; MIS 10) and 27.4 �C (WR5-318; MIS 11). Thelatter temperature, however, was associatedwith the largest scatteramong replicates and is therefore less reliable. Glacial temperaturesduring MIS 12 reconstructed from clumped isotopes were around20 �C.

4. Comparison of the different methods

4.1. Recent samples

Only three methods yielded formation temperatures for the tworecent stalagmites, as these samples were found not to be suitable


for noble gas thermometry (see Section 3.3). Average formationtemperatures for stalagmite LC-1a from Lang's Cave are close to thepresent-day cave temperature of 24.1 �C (Fig. 8). However, apartfrom the highly uncertain estimate from fluid inclusion isotopesfrom CRDS based on measured d18Ow, all results from LC-1a arelower than the measured temperature and do not agree within 1-sigma error. We note that sample LC-1a represents the last1000e2000 years and might therefore have grown at an averagetemperature being slightly different from that of the present-daycave.

For Whiterock Cave (sample WR-MC2), no cave air tempera-ture measurements are available. Considering the higher altitudeof Whiterock Cave (200 m a.s.l.), cave temperature could be up to2 �C lower compared to Lang's Cave (28 m a.s.l.), assuming amoist adiabatic lapse rate of ~1 �C/100 m, estimated for thisspecific region and altitude range (Tripati et al., 2014 and pers.comm.). However, the altitude effect could be offset by a differentdegree of evaporative cooling in or around the two caves,limiting our ability to estimate the present-day cave temperaturein Whiterock Cave. Liquidevapor homogenization yielded for-mation temperatures for WR-MC2 that are 0.7 �C lower thantemperatures determined for sample LC-1a. Temperaturesderived from IRMS-derived fluid inclusion dD values, in contrast,were slightly higher compared to sample LC-1a, and clumpedisotopes yielded the highest temperature of all three methods forWR-MC2.

4.2. Sample WR5

For stalagmite WR5, temperature estimates obtained from allfour methods agree in most cases within their uncertainties(Fig. 8). Nonetheless, subtle and possibly systematic differences indifferent temperature estimates are observed. While NGTs tend tobe on the high side of the range of reconstructed temperatures(except for sample WR5-346), liquidevapor homogenizationtemperatures tend to be lower. In most cases the errors of the twomethods still overlap, implying that any bias in the methods isdifficult to resolve at this stage. For the fluid inclusion isotope andclumped isotope methods, the absolute values of the temperaturesdepend strongly on the calibration applied. The fluid inclusionisotope temperature estimates calculated using the equation ofTremaine et al. (2011) agree well with the homogenization tem-peratures (in most cases within ±1 �C), using the measured d18Ow.Clumped isotope temperatures, when calculated with the syn-thetic calibration from ETH (Ziegler et al., in prep.), often fall in thecenter of all other estimates, but in two cases yielded the lowest(WR5-255) and highest (WR5-318) temperatures of all fourmethods.

Apart from possible systematic biases in the absolute tem-perature estimates, which will be further discussed below, theresults from almost all methods e except the results of theclumped isotopes e agree on the amplitude of glacial-to-interglacial temperature change of 4e5 �C (Table 3). Clumpedisotope temperatures at face value suggest a larger amplitude ofglacialeinterglacial temperature change (up to 10 �C), but thisvalue is strongly affected by the uncertain estimate of the inter-glacial temperature for MIS 11 (WR5-318), where one replicatemeasurement yielded a very high temperature (Fig. 7b). We didnot compute the amplitude of temperature change suggested forTermination IV (from MIS 10 to MIS 9), as the topmost samplesmight not have reached into full interglacial conditions. However,most methods yielded similar temperature variations for thestudied parts of the two interglacials (MIS 11 and MIS 9) and alsofor the two glacials (MIS 12 and MIS 10) covered by this study(Fig. 8).


Fig. 8. Comparison of the temperatures derived with the different methods for the recent samples and the WR5 stalagmite. Note that for better legibility, data points plotting at thesample positions were slightly shifted against each other. For fluid inclusion isotope temperatures and clumped isotope temperatures, equations from Tremaine et al. (2011) andZiegler et al. (in prep.), respectively, were used. The IRMS results are based on d18Ow calculated from dD using the cave drip water relationship, whereas CRDS results are based onmeasured d18Ow. The CRDS results would be similar to those from IRMS if they were also based on dD (c.f. Fig. 7a). No noble gas temperatures are available for the recent samples(see Section 3.3). The dark gray line depicts the present-day temperature in Lang's Cave. Marine isotope stages (MIS) and glacial terminations (T-) are indicated at the top.


4.3. Disequilibrium effects on clumped isotope and fluid inclusionisotope temperatures?

Previous studies using clumped isotopes to determine temper-atures in speleothems have observed offsets towards higher tem-peratures (Affek et al., 2008; Wainer et al., 2011), which have beeninterpreted as kinetic fractionation effects inherent to calcite pre-cipitation in speleothems (Affek et al., 2014; Da€eron et al., 2011). Ifcalcite precipitation outpaces the isotopic exchange between DICand water under conditions of CO2 degassing, the DIC remaining insolution does not fully re-equilibrate, leading to an imprint of ki-netic fractionation from degassing on both calcite D47 and d18Occ. Ithas also been proposed that kinetic fractionation of oxygen isotopesoccurs during rapid mineral formation (Coplen, 2007; Tremaineet al., 2011).

Synthetic calcite calibrations can similarly be affected by kineticfractionation (e.g., Affek and Zaarur, 2014; Tremaine et al., 2011). Itis therefore not clear whether calibrations exist that reflect trueequilibrium conditions. Comparing our results obtained withdifferent calibrations therefore only allows us to assess whichcalibration reflects a similar degree of disequilibrium as observed inour speleothem samples. The temperatures we obtained with thecalibration of Tremaine et al. (2011) and the constant additionsynthetic calcite calibration from ETH (Ziegler et al., in prep.) yieldtemperatures closest to homogenization and noble gas tempera-tures, implying that these calibrations most closely resemble theextent of disequilibrium in our stalagmites.

For clumped isotopes, we obtain similarly plausible temper-atures with the calibration of Zaarur et al. (2013), whereas thesurface precipitation calibration (Affek and Zaarur, 2014)


apparently reflects larger disequilibrium compared to our sam-ples. This suggests that the Borneo speleothems are closer toequilibrium than other speleothems analyzed so far (Affek et al.,2014; Da€eron et al., 2011; Kluge et al., 2013; Wainer et al., 2011).Although we caution that this line of evidence strongly dependson the applied inter-laboratory correction, it is corroborated bythe fact that the synthetic calibration from ETH, where calcite isprecipitated slowly in the bulk solution, also yields reasonabletemperatures.

The combination of clumped isotope and fluid inclusion isotopedata has been suggested as a tool to assess and correct fordisequilibrium (Da€eron et al., 2011; Kluge and Affek, 2012). Thisapproach relies on the assumption that kinetic effects on both pa-rameters are related systematically, leading to a cold bias in d18O-based temperature estimates and a warm bias in D47 temperatures(Da€eron et al., 2011; Kluge and Affek, 2012). However, this proposedrelationship requires further investigation and may be specific tothe cave setting (Affek and Zaarur, 2014).

In our results we do not observe a systematic divergence/convergence of fluid inclusion isotope and clumped isotope tem-peratures, compared to the other methods, as would be expected ifvariable disequilibrium occurred over time (assuming a systematicrelationship as found in other locations). A possible exception issample WR5-346, where clumped isotope and fluid inclusionisotope temperatures (especially when based on calculated d18Ow)diverge in opposite directions from the results of the other twomethods. Sample WR5-346 is located within the transition be-tween glacial MIS 12 and interglacial MIS 11 (Termination V; Fig. 8).In this case the clumped isotope temperature is around 3.1 �Cwarmer, and the fluid inclusion isotope temperature up to 8.8 �C



colder (2.6 �C if the measured d18Ow is used), compared to theerror-weighted average of the noble gas and homogenizationtemperatures (21.1 �C). The divergence could hence reflectincreased influence of kinetic fractionation effects, potentiallyrelated to the inferred drier conditions during glacial terminations(Meckler et al., 2012). However, even in this case the offset of theclumped isotope to the noble gas and homogenization temperatureestimates is small compared to offsets observed in other studies,suggesting a comparativelyminor influence of kinetic fractionation.We further note that part of the temperature offsets could also berelated to sampling biases in this section of the stalagmite that ischaracterized by sloping growth layers and a potential growth hi-atus and formed during a glacial termination with large and rapiddifferences in paleoclimatic conditions. Termination IV is notcharacterized by diverging temperature estimates, implying thatthe divergence does not seem to be a common feature of glacialterminations.

Considering all evidence currently available, our data suggestthat disequilibrium effects play a much smaller role in Borneothan in previous studies using clumped isotopes in speleothems.We might speculate that this could be related to slow growthrates (see Section 2.1) or to the comparatively high temperaturesin our caves, if disequilibrium effects on D47 are more important atcolder temperatures (Affek and Zaarur, 2014). Until the factorsinfluencing clumped isotope and d18O signals in speleothems aswell as potential disequilibrium effects in the Borneo caves arebetter understood, we conclude that the two equations we haveused here yield temperatures that for most samples are in closeagreement with calibration-independent methods, showing thatin settings like Borneo fairly reliable temperature reconstructionscan be obtained from clumped isotopes and fluid inclusionisotopes.

4.4. Potential biases in noble gas and homogenization temperatures

Noble gas and homogenization temperatures are not affectedby kinetic isotope fractionation and do not rely on any assump-tions about fractionation coefficients, as these methods are basedon well-constrained physico-chemical properties. While thetemperature estimates from these two methods for stalagmiteWR5 agree within 2 SD errors, the slight but apparently system-atic offset between the results point to a bias in one or both ofthese methods. As explained in Section 2.4.3, a challenge for thenoble gas measurements is the accurate determination of wateramounts, as adsorption of water on stainless steel constrainswater determination. While this adsorption is monitored andcorrected for, and the related uncertainty is included in the errorestimates, even the most adequately carried out correction mayadd some bias. For instance, if estimated water amounts are toohigh, the calculated temperatures are also too high, and viceversa. At this time, however, we do not have sufficient evidence todetermine whether NGTs are systematically too high as temper-ature determination from recent stalagmite samples was notfeasible (see Section 3.3).

Homogenization temperatures can be affected by post-entrapment alterations of the inclusion volume. As discussed inSection 3.2, the formation of cracks during sample preparation canlead to a decrease of the water density and hence an increase intemperature. In some cases, it is possible that too many datapoints were considered as affected by such artifacts, but includingthese temperatures would have only a minor effect on the averagetemperatures (Section 3.2). Whereas experimentally inducedwarm biases are common, it is much more difficult to explainbiases towards colder homogenization temperatures. As outlinedin Section 3.2, we see no evidence for tensile stress-related plastic


deformation of inclusion walls, which would increase the fluiddensity. Furthermore we have no evidence that continuousdissolution and re-precipitation of calcite at the inclusion walls,driven by the minimization of the inclusion's surface energy, couldresult in a volume change of the inclusions. For fluid inclusions inquartz Aud�etat and Günther (1999) have demonstrated that re-crystallization of the inclusion walls can result in volume andcompositional changes and even migration of the inclusions if thecrystal lattice of the host mineral is under high internal stress, e.g.due to a high density of lattice defects or high trace elementconcentrations. However, in this case we would expect highlyvariable density changes among individual inclusions and asmaller temperature variability in fluid inclusion assemblages ofmodern samples, compared to old ones, which was not observedfor the two samples from Whiterock Cave. At present we do nothave any indication of natural processes that could have increasedthe water density in the inclusions after entrapment, and thuswould explain the systematic deviation from NGTs towards coldertemperatures.

4.5. Strengths and weaknesses of the different methods

The successful application of the different paleo-thermometersdepends mostly on the sample material (Table 4). All methodsbased on fluid inclusions depend on the primary nature andsufficient abundance of fluid inclusions. Particularly liquidevaporhomogenization and noble gas thermometry strongly depend onthe integrity of the fluid inclusions and their constraining walls.Noble gas thermometry currently requires the most sample ma-terial of all methods and is a complex and time-consumingtechnique (~2 samples per week; Table 4). In addition it seemsthat, at least for the Borneo caves, the technique cannot be appliedto reliably determine NGTs in young stalagmite samples (seeSection 3.3). However, noble gas thermometry has the advantagethat it does not require assumptions concerning equilibriumcalcite precipitation, as the method is based on strictly definedbasic physical principles (i.e. Henry's Law describing air (noblegas)/water partitioning), and does not depend on any calibrationexercise.

The same applies to liquidevapor homogenization thermom-etry. This method requires only a small, but optically visible,number of fluid inclusions per temperature estimate (15e20),which can all be measured in duplicate in one day. Furthermore,this method delivers a higher temporal resolution compared tobulk measurements of fluid inclusion isotopes or noble gases, andcan be applied even when fluid inclusions are rare. However, thehomogenization method poses strict requirements on the selec-tion, handling and preparation of the stalagmite samples (Krügeret al., 2011), and can only be applied on speleothems that grew attemperatures >9 �C (Marti et al., 2012). In contrast, the othermethods can be used to reconstruct stalagmite formation temper-atures down to the freezing point of water.

Fluid inclusion water isotope thermometry appears to be themost robust with respect to the nature of the fluid inclusions,although as for the other methods they have to be primary, wellsealed, and sufficiently abundant. In the case of the CRDSmethod, ifit holds true that both d18Ow and dDw can be determined withadequate confidence, additional information about hydrologicalprocesses could be gained. For this method, the choice of the cali-bration scheme to convert d18Ow into temperatures strongly affectstemperature estimates (Fig. 7a). Relative changes in temperatureare less affected, as the calibration slopes do not differ greatly. Ifcalcite precipitates rapidly, d18Occ can additionally be affected bynon-equilibrium processes (e.g., kinetic fractionation during CO2degassing and/or mineral formation), and the degree of



disequilibrium can vary over time. If d18Ow is estimated frommeasured dDw, another inherent uncertainty of this method arisesfrom assumptions about the relationship between dD and d18O,which may change over time.

Clumped isotope thermometry requires the smallest sampleamounts and does not depend on the nature or abundance of fluidinclusions. However, the method is analytically challenging andtime-consuming. Like fluid inclusion isotope thermometry, themethod currently suffers from calibration uncertainties, andadditionally from uncertainties regarding the comparability ofresults obtained with different analytical setups. Clumped isotopetemperature estimates are even more sensitive to disequilibriumeffects compared to fluid inclusion water isotope thermometry.However, our results from Borneo show that speleothems existwith a similar extent of disequilibrium as synthetic calcite frombulk solution precipitation, allowing for reliable temperatureestimates.

Analytical uncertainties were slightly larger for clumped isotopeand noble gas temperatures than for the other methods (Table 4).

5. Paleotemperatures

5.1. Glacialeinterglacial climate changes

Most of our data suggest significant glacialeinterglacial tem-perature differences in the Indo-Pacific Warm Pool of 4e5 �C be-tween glacial MIS 12 and MIS 10 and interglacial MIS 11 (Table 3).The temperature change from MIS 12 to MIS 11 indicated byclumped isotopes seems larger, but is associated with a large error(see Section 4.2).

Due to glacial sea level lowering and thus increase in the cave'saltitude, the observed glacialeinterglacial variation in cave tem-perature should be amplified compared to temperature variationsat sea level. During the LGM, sea level was lower by ~120 m (e.g.,Fairbanks, 1989; Grant et al., 2014), and it was likely even lowerduring MIS 12 and MIS 10 according to the benthic d18O record(Lisiecki and Raymo, 2005), which suggests larger global ice volumeduring these earlier glacial periods. The adiabatic lapse rate couldalso change with time. However, a recent study has inferred thatboth today and during the LGM, the lapse rate in the Warm Poolregion is/was ~1 �C/100 m at 0e300 m a.s.l. (Tripati et al., 2014 andpers. comm.). The glacialeinterglacial temperature changes in thecave environment are therefore expected to have been at least ~1 �Clarger than the temperature change at sea level. Thus, based on ourdata we would expect SST to have varied by 3e4 �C for the inves-tigated time interval.

Table 3Comparison of estimates for glacialeinterglacial temperature change duringMIS 12e10. Mthe peak interglacial. Proxy data from this study are averaged over the intervals indicatedProjected cave temperatures are calculated from the reconstructed SST from both availabCave, and a glacial increase in cave elevation of 120e130 m with a lapse rate of 0.65e1.0terglacials and 5.8e6.3 �C for glacials). Whiterock Cave is around 130 m higher than Laperature data are available for this cave.

Proxy Glacial MIS 10 Interglac

Homogenization temperature 18.7 ± 0.7 23.4 ± 1Noble gas temperature 22.7 ± 1.0 25.4 ± 1Fluid inclusion isotopes (CRDS, measured d18Ow) 19.7 ± 0.6 25.8 ± 0Fluid inclusion isotopes (dD-based, IRMS) 17.7 ± 1.5 22.0 ± 0Clumped isotope temperature 16.9 ± 1.9 27.4 ± 3Combined stalagmite record 19.6 ± 0.5 24.0 ± 0Mg/Ca SST ODP 806a 25.5 30.2Mg/Ca SST MD97-2140b 26.5 29.5Projected cave temperature 19.2e20.7 24.5e25

a Medina-Elizalde and Lea, 2005.b de Garidel-Thoron et al., 2005.


The only other available temperature estimates from the WestPacific Warm Pool for the analyzed time period are the Mg/Ca-basedSST records plotted in Fig. 9 (de Garidel-Thoron et al., 2005; Medina-Elizalde and Lea, 2005). As introduced above, discrepancies existbetween different SST proxies, with Mg/Ca estimates suggesting alarger warming during Termination I compared to other SST proxies.However, the glacialeinterglacial amplitudes in the Mg/Ca recordsfor MIS 10e12 are very similar to our estimates after accounting forsea level-related altitude changes (Table 3).

Terminations V and VI, covered by our data, might not bedirectly comparable to the Termination I, for which more paleo-temperature data are available, as they show the largest ampli-tude of ice volume and atmospheric CO2 changes among the lateQuaternary terminations (Lisiecki and Raymo, 2005; Siegenthaleret al., 2005). Acknowledging these differences, the amplitude ofour reconstructed temperature changes during MIS 12e9 is notonly in agreement with the Mg/Ca records, but is also in line withestimates for LGM cooling based on snowline elevations (Porter,2001), noble gas concentrations in groundwater (Edmunds et al.,1999; Stute et al., 1995), and Warm Pool SST reconstructionsbased on clumped isotopes in foraminifera (Tripati et al., 2014). Wenote, however, that the observed amplitude is substantially largerthan for pollen-based reconstructions of LGM cooling in the WarmPool area (Farrera et al., 1999) and some of the otherWarm Pool SSTreconstructions (e.g., Waelbroeck et al., 2009).

The glacial-to-interglacial variation in the WR5 temperaturerecord is not reflected in d18Occ (Fig. 8), which only records an in-crease in the latest phase of glacial MIS 10 (more obvious in thehigher resolution record from another Borneo stalagmite, seeMeckler et al., 2012). This discrepancy confirms the dominantcontrol of precipitation on d18Occ (Meckler et al., 2012). The newtemperature reconstruction aids in refining the interpretation ofthe d18Occ record. For the early part of MIS 10, our new data clearlyreveal cooling, whereas d18Occ remains at interglacial level withcontinued shorter-term fluctuations. The inferred cooling in com-bination with glacial ice volume growth should have worked toincrease d18Occ. The lack of such a change implies that regionalhydroclimate was likely wetter during early glacial MIS10compared to MIS 11, lowering rainwater d18O and compensatingtemperature and ice volume effects. The latest part of the glacial onthe other hand seems to have been characterized by similar orslightly drier hydroclimate compared to the preceding interglacial,as inferred previously (Meckler et al., 2012). The glacial terminationT-IV, finally, was probably considerably drier, as can be inferredfrom high d18Occ coinciding with increasing cave temperatures(Fig. 8) as well as decreasing global ice volume.

IS 9 is not included as the topmost samples we analyzedmight not have reached intoin Table 2. In these cases, errors represent the combined error of the averaged data.le records, the present-day temperature offset of 5 �C from Warm Pool SST in Lang's�C/100 m (i.e., the offset between cave and sea surface is estimated as 5 �C for in-

ng's Cave, which could result in colder cave temperature, but no present-day tem-

ial MIS 11 Glacial MIS 12 DMIS 12eMIS 11 DMIS 11eMIS 10

.0 19.0 ± 0.6 4.4 ± 1.1 4.7 ± 1.2

.0 21.1 ± 0.9 4.3 ± 1.3 2.7 ± 1.4

.9 20.4 ± 0.7 5.4 ± 1.1 6.1 ± 1.1

.8 17.5 ± 0.9 4.5 ± 1.2 4.3 ± 1.7

.2 19.7 ± 0.9 7.7 ± 3.3 10.5 ± 3.7

.6 19.7 ± 0.4 4.3 ± 0.7 4.4 ± 0.825.5 4.7 4.725.9 3.6 3.0

.2 19.2e20.1 4.4e6.0 3.8e6.0


Table

4Com

parison

ofthedifferentpaleo

-thermom

etry

method

s.

Sample

size

Sample

requ

irem

ents

Sample

through

put

Errors

(asob

served

here)

Additional

uncertainties

orbiases

Other

commen

ts

Liqu

ideva

por

hom

ogen

ization

15e20

inclusion

s30

0mm

thicksections;

Mechan

ical

stress

during

preparationmust

beke

pt

tominim

um.S

amples

shou

ldbe

han

dledclose

tocave

temperature.

5e6samplesper

wee

k(15e

20inclusion

sin

duplic

ateea

ch)

0.5e

1.0

� C(1

SDof

analyz

edgrou

ps)

Post-entrap

men

tden

sity

alteration

sinducedby

sample

preparation.

Naturalp

rocesses

causingartifacts

seem

tobe

unlik

elybu

tcannot

beex

cluded

Req

uires

femtoseco

nd

lasersystem

Not

applic

able

<~9

� C.

Cav

etemperature

variationssh

ould

be<10

� Cdueto

highintern

alfluid

over-pressure

Nob

lega

ses

0.1e

2mL,

fluid

inclusion

water

afterpre-crush

ing

Calcite

bloc

ks;noco

ntact

withsolven

ts;Inclusion

ssu

fficien

tlysealed

2e3samplesper

wee

k0.9e

3.3

� CAir

contentin

thesamples;

Determinationof

water

amou

nts;

Potential

nob

lega

sfraction

ation

inyo

ungsamples

Pre-crush

ing(inorder

toreduce

airportion

insamples)

lead

sto

low

yieldof

water

extraction

Fluid

inclusion

isotop

esTC

/EAIRMS

>0.1mLfluid

inclusion

water

Calcite

bloc

ks5e

6samplesper

wee

k(3

replic

ates

each

)<0.9e

2.1

� C(0.9

� Cis

the

long-term

reproducibility)

Possible

kinetic

fraction

ationeffects;

temperature

equationcu

rren

tly

deb

ated

;d1

8Ownee

dsto

beestimated

from

MW

L

Potential

oxyg

enisotop

efraction

ationduring

sample

processing

Fluid

inclusion

isotop

esCRDS

>0.4mLfluid

inclusion

water

Calcite

bloc

ks~8

samplesper

wee

k(3

replic

ates

each

)<0.9e

2.5

� C(0.9

� Cis

the

long-term

reproducibility)

Possible

kinetic

fraction

ationeffects;

temperature

equationcu

rren

tly

deb

ated

Offsets

from

MW

Lnot

yetex

plained

Clumped

isotop

es5e

10mgcalcite

Calcite

pow

der

2e3samplesper

wee

k(5

replic

ates

each

)1.2e

3.2

� C(1

SEof

themea

n)

Possible

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ationeffects;

temperature

equationcu

rren

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deb

ated

Low

precision

ofindividual

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suremen

ts;

requ

ires

numerou

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ates



5.2. Regional comparison

The offsets we observe between Borneo cave temperature andthe SST records are very similar to the present-day offset. Thisholds true for interglacial estimates as well as for glacial estimatesafter accounting for sea level-related changes in altitude. Cavetemperatures that would be expected when taking the Mg/Ca-based SST estimates at face value, subtracting the present-dayoffset of 5 �C between Lang's Cave and SST, and accounting foraltitude changes during glacial times are ~25 �C for interglacialMIS 11, and 19e20 �C and 19e21 �C for MIS 12 and MIS 10,respectively (Table 3). As Whiterock Cave, where WR5 was ob-tained, is located at a higher elevation, a slightly lower tempera-ture could be expected (Section 4.1). The reconstructed cavetemperatures compare well with these estimates, whereby noblegas temperatures are slightly higher and homogenization tem-peratures slightly lower (Table 3).

This comparison suggests that the present-day temperatureoffset between the caves and the sea surface was approximatelysimilar in the past, both during glacial and interglacialclimate states. The temperature offset between sea surfaceand cave interior is probably due to radiation shielding andevapotranspiration by the rainforest vegetation and possiblyevaporative cooling in the caves. The latter process has beenshown to significantly decrease temperatures by 1.5 �C in semi-arid settings (Cuthbert et al., 2014). It can be expected that theeffect is much reduced in a humid, tropical environment such asBorneo (measured humidity was always near or at 100% inthe caves, between 80 and 100 % outside the caves, and inmost cases between 70 and 100 % at the Park HQ station).Nonetheless, good ventilation of the Mulu caves due to thelarge cave passages could cause some evaporative cooling. How-ever, the fact that the few temperature measurements fromoutside the caves were similar to those inside, and lowerthan temperatures at Park HQ, suggests that the dense vegetationsurrounding the caves in contrast to the more open Park HQ ismostly responsible for the lower cave temperatures. During theLGM, the vegetation in northern Borneo was apparently similarto today, according to the carbon isotopic composition of insectcuticles preserved in guano in nearby Niah Cave (Wurster et al.,2010). This observation is in line with the similar glacialand interglacial temperature offsets between caves and SST ac-cording to our data and the Mg/Ca records (after altitudecorrection). We note that if vegetation was less extensive duringglacial times, the cooling effect from radiation shielding andevaporation might have been smaller, making our gla-cialeinterglacial temperature difference a minimum estimatewhen seen in a regional context.

If we ignore potential biases and treat all applied methodsequally, we can calculate error-weighted mean temperaturesfor each sample (Fig. 9). For the sample at TerminationV (WR5-346), where we suspect disequilibrium effects onclumped and fluid inclusion isotope temperatures, we only usednoble gas and homogenization temperatures for this calculation.The error of this combined temperature takes the errors of theindividual methods into account and was estimated with aMonte Carlo approach. The combined temperature estimatesvary between 19.0 ± 0.6 and 24.6 ± 1.0 �C, and average glacialand interglacial temperatures were around 19.6 ± 0.5 and24.0 ± 0.6 �C, respectively (Tables 2 and 3). We note, however,that some of the individual results are strongly subject to thechoice of the calibration scheme, which shifts the calculatedtemperatures and therefore affects the combined temperatureestimate.


Fig. 9. Comparison of the stalagmite-derived temperature record and the Warm Pool SST records (de Garidel-Thoron et al., 2005; Medina-Elizalde and Lea, 2005; Tachikawa et al.,2014). Results of the individual methods are plotted as in Fig. 8. The combined stalagmite record (light-blue circles) was derived from error-weighted average temperatures for eachsample, and the error envelope was derived from a Monte Carlo simulation. For the sample at 431 ka (Termination V), only homogenization and noble gas temperatures were takeninto account for the averaging. The dark gray line depicts the present-day temperature in Lang's Cave, and the black arrow on the left depicts the present-day annual mean SSTaround Borneo (Fig. 1). Marine isotope stages (MIS) and glacial terminations (T-) are indicated at the top. (For interpretation of the references to color in this figure legend, thereader is referred to the web version of this article.)


6. Conclusions

This comprehensive study shows that all of the currentlyavailable speleothem-based temperature proxies (fluid inclusionisotopes, liquidevapor homogenization, fluid inclusion noble gases,and clumped isotopes) can be applied to tropical stalagmites andyield consistent temperature estimates in stalagmite specimens asold as 460 ka. For the recent samples, our temperature estimatesare close to measured cave temperatures (Fig. 8).

Comparing the results from the different temperature proxies inall measured samples, a slight bias is observed in noble gas and/orhomogenization temperatures at the 1-sigma level, but vanishes atthe 2-sigma level. Fluid inclusion isotope temperatures, in absoluteterms, depend on assumptions about the relationship betweend18Ow and dDw in drip water at the time of speleothem formation,as well as on the choice of d18O-temperature calibration. dDwmeasurements were very consistent between the two differentmethods employed (CRDS and TC/EA IRMS). The equation ofTremaine et al. (2011) yielded temperature estimates consistentwith the measured cave temperature (in the case of the recentsamples) and with the other proxies. The clumped isotope tem-peratures were more variable than the other methods, and in mostcases were associated with larger errors. The degree of disequilib-rium in our samples appears to be considerably lower thanobserved in previous studies (Affek et al., 2014; Da€eron et al., 2011;Kluge and Affek, 2012). In contrast to these other cave settings,calibrations obtained from classical synthetic calcite precipitationmethods yielded plausible clumped isotope temperatures.

The data suggest glacialeinterglacial tropical cave temperaturechanges of 4e5 �C, which would correspond to 3e4 �C temperature


change at sea level, consistent with nearby Mg/Ca based SST esti-mates for the same time interval (de Garidel-Thoron et al., 2005;Medina-Elizalde and Lea, 2005) and for the last glacial termination(de Garidel-Thoron et al., 2007), as well as clumped isotope-basedLGM SST estimates (Tripati et al., 2014). The amplitude is, however,larger than some of the estimates for Termination I based on pollen(Farrera et al., 1999) or SST proxies other than Mg/Ca and clumpedisotopes (CLIMAP_Project_Members, 1976; Waelbroeck et al.,2009).

Our results add independent support for previous findings ofsubstantial glacialeinterglacial temperature change in the tropicalWest Pacific, underlining that climate in this tropical region hasresponded to greenhouse forcing in the past and is likely to do so inthe future.

Acknowledgments

We thank Syria Lejau, Jenny Malang, Jud Partin, Andrew Tuen,and Brian Clark for assistance with fieldwork. Stewart Bishop,Madalina Jaggi, Isabel Mill�an, Sebastian Breitenbach, and MartinZiegler helped with clumped isotope labwork and method devel-opment. We are grateful to Hagit Affek for providing standard dataand discussing inter-laboratory differences. Rita Hidalgo contrib-uted to homogenization temperature measurements. We thank theRoyal Society SE Rainforest Research Programme for provision ofthe climatic data at Danum Valley Field Centre used in this paper.This work was supported by the Swiss National Science Foundationthrough the Sinergia project StalClim (grant CRSI22_132646/1) andMarie-Heim-V€ogtlin grant PMPDP2_139701 to ANM.



Appendix

Fig. A.1. Sample positions in stalagmite WR5. Sample depths as reported in the tables are given on the left. Clumped isotope samples were sometimes milled out separately (greenshaded areas and sample depths with asterisk). The red stippled line indicates the transect milled previously for stable isotopes, along which sample depth was measured. Thed18Occ record (Meckler et al., 2012) is shown for comparison, and marine isotope stages (MIS) are indicated by brown and gray bars for interglacials and glacials, respectively.

Fig. A.2. Preparation of stalagmite WR5. a) Blocks of 20 mmwidth and a maximum length ofgrowth direction, the stalagmite was broken prior to sawing. Gray areas indicate material thinclusion microthermometry, removed from the glass substrate and broken into pieces. c) Stinclusion water. d) Diamond wire saw used for cutting along growth layers. Curved cuts wer


42 mmwere cut from the central part of the stalagmite half. Due to slight change in theat split off during preparation. b) Unpolished 300 mm thick stalagmite section for fluidalagmite sample cut along growth layers for isotope and noble gas analysis of the fluide achieved by horizontal displacement of the sample (white arrows) during the sawing.


Fig. A.3. Histograms illustrating the distribution of homogenization temperatures (Th∞) for each sample analyzed. Temperatures considered as affected by density alterations areplotted in light gray. Inclusions with Th(obs) > 27 �C were not analyzed to avoid high fluid overpressure in other inclusions in the same sample.



Fig. A.4. Isotopic composition of rainwater and drip waters in Mulu National Park (Moerman et al., 2014, 2013). The drip water sample set consists of data from three time seriessampled over ~6 years (the same time interval as the rainwater samples), as well as spatial sampling surveys conducted during three different field campaigns. Drip water samplesfrom caves used for this study are plotted as colored circles. One of the drip water time series is from Lang's Cave, and both Lang's and Whiterock (WR) cave were sampled duringdifferent field campaigns. Solid lines are regression lines through the rainwater (i.e., LMWL) and drip water (i.e., drip water line) data, as well as the GMWL. Note that rainwatersamples continue outside the range plotted here.

Table A.1Homogenization temperatures (Th∞). Temperatures from inclusions considered as altered are in italics and marked by asterisks and are not considered for statistics.

SampleDepth (mm)Age (ka)

WR-MC2top

LC-1atop

WR5

239 247 263 302 302 (ct'd) 318 331 346 363 388

333 336 362 396 396 (ct'd) 409 419 431 438 447

Th∞ 22.8 27.5* 21.42 21.78 18.73 21.70 22.16 24.36 22.88 24.17* 20.34 18.8822.4 23.9 23.08 22.20 18.43 22.26 20.81 26.48* 23.68 21.21 19.04 19.6622.5 23.7 22.64 21.49 19.64 22.32 20.08 22.23 22.27 21.35 19.54 18.9323.6 23.1 22.23 22.37 18.91 21.57 21.84 21.97 23.19 23.39 17.98 19.9824.1 23.3 23.35 22.49 18.63 21.59 20.30 22.53 23.53 20.47 18.66 19.2727.4* 24.2 23.72 22.40 18.04 21.35 22.51 23.70 22.94 21.84 18.41 18.4820.8 24.1 25.63* 21.54 18.79 21.48 22.62 27.00* 22.70 24.14* 19.75 19.2321.7 22.8 20.74 21.61 17.99 21.44 23.22 24.97 22.57 22.58 19.30 19.6922.5 23.1 23.87 23.45 18.38 22.00 21.74 24.13 24.33 20.86 18.86 18.4723.0 22.9 22.82 21.10 17.37 21.23 22.82 23.45 22.83 20.83 18.37 18.2425.9* 22.7 23.23 21.83 18.99 21.79 22.24 21.51 22.51 23.40 18.41 19.3122.7 23.4 23.23 24.59* 19.17 21.44 23.71 23.87 26.34* 21.97 19.37 17.8123.1 27.3* 22.92 23.23 23.89* 23.67 20.69 22.53 23.73 21.02 20.01 18.2821.7 25.2* 23.16 22.89 20.38 21.38 20.81 23.56 21.93 21.62 19.77 18.6621.7 22.6 24.12 22.40 18.75 20.91 20.77 23.89 22.68 20.71 17.58 18.5522.6 24.2 20.84 22.52 18.87 21.64 23.26 26.96* 18.67 18.7824.4 23.6 23.30 20.16 22.24* 22.53 24.56 21.05 20.38 20.6722.9 25.7* 21.83 22.73 24.03 21.00 17.96 18.9622.9 22.6 22.20 20.73 21.05 20.2022.5 23.5 22.14 21.97 21.97 17.6722.0 23.5 21.56 22.23 21.3821.9 22.8 22.69 21.7221.9 26.9* 24.0524.4 22.6822.7 20.4325.3* 21.1823.3 22.47

Inclusions Th(obs) > 27 �C 3 14 1 3 0 5 0 2 2 3 2

Average 22.7 23.4 22.8 22.1 18.6 21.9 23.4 23.0 21.6 19.0 19.0S.D. 0.9 0.5 1.0 0.7 0.7 0.9 1.0 0.7 0.8 0.9 0.7


Table A.2Noble gas concentrations (in 10�7 cm3STP / g water) and temperatures for the Borneo samples. The upper part of the table contains noble gas results from old WR5 samples, the lower part of the table contains noble gasconcentrations of recent samples. WR:Whiterock Cave, LC: Lang Cave, GC: Green Cathedral Cave. In some cases two aliquots were measured from a specific sample (a, b), and in the case of WR-MC2 and GC04 not only the coarsefraction (>500 mm), but also the medium fraction (500e300 mm) was analyzed (-c, -m). All other samples represent coarse fractions. NGTs determined for old Borneo samples are based on Ne, Kr, and Xe, the water amount, andsuitable solubility data (e.g., Kipfer et al., 2002). The underlying conceptual model for fitting refers to a binary mixture of noble gases from unfractionated air and unfractionated air-saturated water (regular numbers). Un-certainties of the temperatures include the propagated errors of all input parameters at the 1-sigma level. c2 values are a measure of the goodness of fit and should ideally be close to 1 (¼degrees of freedom).

Sample Water amount [g] ± Ne ± Ar ± Kr ± Xe ± Temp [�C; Ne, Kr, Xe] ± c2

WR5-247 3.6E-04 2.0E-05 3.75Eþ00 1.39E-01 4.03Eþ03 9.01Eþ01 7.28E-01 1.08E-02 9.31E-02 3.01E-03 23.8 2.1 0.7WR5-258 1.7E-03 3.1E-05 3.16Eþ00 7.58E-02 3.90Eþ03 8.72Eþ01 7.20E-01 1.17E-02 9.50E-02 4.33E-03 22.7 1.0 0.5WR5-277 4.5E-04 1.9E-05 4.24Eþ00 1.18E-01 4.33Eþ03 9.68Eþ01 7.67E-01 1.14E-02 9.74E-02 3.21E-03 23.1 1.7 1.1WR5-302 5.0E-04 1.9E-05 6.73Eþ00 1.85E-01 5.56Eþ03 1.24Eþ02 8.91E-01 1.31E-02 1.06E-01 3.45E-03 25.5 1.8 2.3WR5-320(a) 4.5E-04 1.5E-05 4.42Eþ00 1.26E-01 4.35Eþ03 9.72Eþ01 7.56E-01 1.10E-02 9.55E-02 3.03E-03 25.3 1.5 1.9WR5-320(b) 1.1E-03 3.1E-05 3.54Eþ00 7.03E-02 3.69Eþ03 5.27Eþ01 7.08E-01 7.60E-03 8.86E-02 3.29E-03 25.5 1.2 0.1WR5-346 1.3E-04 1.1E-05 2.08Eþ01 5.49E-01 1.32Eþ04 2.95Eþ02 1.88Eþ00 2.76E-02 1.84E-01 6.17E-03 19.1 3.3 0.1WR5-398 1.6E-03 3.1E-05 3.14Eþ00 7.59E-02 4.01Eþ03 8.98Eþ01 7.34E-01 1.05E-02 9.59E-02 2.74E-03 21.1 0.9 0.3

LC-1a(a) 6.8E-05 7.5E-06 8.26Eþ01 1.45Eþ00 5.70Eþ04 8.07Eþ02 6.78Eþ00 7.56E-02 6.35E-01 2.42E-02LC-1a(b) 6.8E-05 7.5E-06 4.35Eþ01 2.15Eþ00 3.23Eþ04 4.58Eþ02 3.85Eþ00 5.34E-02 7.69E-01 3.38E-02WR-MC2(a; c) 5.0E-05 7.4E-06 9.82Eþ00 2.48E-01 1.34Eþ04 1.89Eþ02 2.28Eþ00 2.70E-02 3.28E-01 2.95E-02WR-MC2(b; m) 2.7E-05 7.6E-06 6.78Eþ00 5.84E-01 1.09Eþ04 1.54Eþ02 1.86Eþ00 4.53E-02 2.98E-01 1.81E-02GC04 (a; c) 2.4E-04 1.9E-05 8.26Eþ01 1.45Eþ00 5.70Eþ04 8.07Eþ02 6.78Eþ00 7.56E-02 6.35E-01 2.42E-02GC04 (b; m) 5.1E-05 1.3E-05 4.35Eþ01 2.15Eþ00 3.23Eþ04 4.58Eþ02 3.85Eþ00 5.34E-02 7.69E-01 3.38E-02

Table A.3Fluid inclusion isotope results. Given are results obtained by CRDS in Bern (BE) and TC/EA IRMS in Innsbruck (IN), as well as calcite d18O and calculated temperatures using two different published equations. d18Ow was calculatedwith the cave drip water line for the IRMSmeasurements (as well as for the CRDS measurements for comparison). Standard deviations are given although the number of replicates was <3 in several cases. For this reason, we usethe long-term reproducibility of 0.9 �C for the reported temperatures where calculated errors are lower than 0.9 �C. The precision for the water amount estimation is ±0.08 mL.

Sample Age(ka)

N dDw (‰ vs. VSMOW) d18Ow (‰ vs. VSMOW) Mean waterconc. (mL/g)

d18Occ (‰ vs. VPDB) Temperature (�C)Tremaine et al. (2011)

Temp. (�C)Kim andO'Neil (1997)

BE IN BE SD IN SD BE SD BEa INa SD BE IN BE SD IN SD BE Error BEa Error INa Error BE INa

WR5-239 333 3 2 �51.0 1.0 �50.1 3.5 �7.5 0.3 �7.8 �7.6 0.4 8.1 3.8 �8.19 0.13 �8.19 0.15 23.3 1.7 20.3 0.9 21.0 2.5 18.2 16.2WR5-247 336 3 6 �37.7 2.1 �37.4 2.3 �5.9 0.3 �6.1 �6.0 0.3 6.8 8.0 �6.40 0.08 �6.43 0.02 22.2 1.3 20.0 1.5 20.3 1.6 17.2 15.6WR5-258 350 3 e �57.8 1.6 e e �8.3 0.1 �8.6 e e 14.8 e �8.28 0.12 e e 19.2 0.9 16.1 1.1 e e 14.7 e

WR5-263 362 3 2 �58.1 0.8 �57.5 2.2 �8.4 0.1 �8.7 �8.1 0.3 8.9 3.5 �8.53 0.03 �8.53 0.09 20.3 0.9 17.2 0.9 17.7 1.5 15.6 13.4WR5-277 372 3 2 �60.1 1.0 �60.1 2.4 �8.6 0.4 �8.9 �8.9 0.3 8.8 7.2 �8.70 0.20 �8.66 0.06 19.9 2.0 16.8 0.9 16.6 1.6 15.3 12.4WR5-302 396 3 3 �57.6 0.1 �60.3 0.5 �8.3 0.4 �8.6 �8.9 0.1 4.1 9.5 �8.87 0.05 �9.41 0.11 22.7 2.0 19.4 0.9 20.5 0.9 17.7 15.8WR5-318 409 3 2 �53.5 0.4 �53.7 1.8 �7.2 0.3 �8.1 �8.1 0.2 7.8 3.7 �8.77 0.08 �8.90 0.15 27.8 1.5 21.7 0.9 22.3 1.3 22.1 17.4WR5-320 411 3 2 �55.3 1.2 �55.1 0.3 �8.1 0.1 �8.3 �8.3 0.1 7.9 2.8 �8.90 0.14 �8.97 0.04 23.8 0.9 21.2 0.9 21.7 0.9 18.6 16.9WR5-331 419 3 e �53.2 0.5 e e �7.5 0.3 �8.0 e e 3.8 e �8.01 0.12 e e 21.9 1.4 17.8 0.9 e e 17.0 e

WR5-346 431 3 5 �48.9 2.1 �48.9 2.5 �6.6 0.4 �7.5 �7.5 0.3 12.7 4.6 �6.44 0.16 �6.37 0.19 18.5 1.9 12.6 1.4 12.2 1.7 14.1 8.6WR5-363 438 2 e �49.6 0.5 e e �7.3 0.2 �7.6 e e 8.8 e �7.61 0.15 e e 21.3 1.0 18.2 0.9 e e 16.5 e

WR5-388 447 3 4 �52.8 0.9 �52.9 0.7 �7.7 0.1 �8.0 �8.0 0.1 10.8 8.1 �7.78 0.03 �7.89 0.09 19.5 0.9 16.9 0.9 17.5 0.9 15.0 13.2

WR-MC2 Recent 4 2 �56.2 1.2 �57.3 0.8 �8.6 0.4 �8.4 �8.6 0.1 1.5 1.6 �9.54 0.16 �9.57 0.01 24.8 2.1 24.5 0.9 23.4 0.9 19.5 18.3LC-1a Recent 2 2 �54.1 0.4 �56.0 0.1 �7.9 1.3 �8.2 �8.1 0.1 0.8 0.5 �9.28 0.07 �9.22 0.01 27.1 7.2 24.1 0.9 22.5 0.9 21.5 17.5

a d18Ow calculated from dDw and local drip water line.

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Table A.4Clumped isotope (D47) results of all measured replicates and calculated temperatures derived from four different calibrations. Errors for individual replicate measurements arestandard errors of the mean derived from 8e12 analyses. Note that for calibrations performed with a different analytical setup at Yale University, an empirically defined inter-laboratory difference, which is highly uncertain, has been tentatively added to our D47. Additional data showing all correction steps are given in the Supplementaryinformation.

Sample Age (ka) D47 D47 error (1 SE) Synthetic calcite calibration ETH TravertinecalibrationETH

Other calibrations

Temp. (�C) Error pos Error neg Affek andZaarur, 2014D47 þ 0.025‰

Zaarur et al.,2013D47 þ 0.025‰

WR5-246 0.695 0.010 18.6 2.8 2.7 23.4 11.1 20.8WR5-246 0.658 0.012 29.7 3.8 3.7 35.4 22.2 29.7WR5-246 0.709 0.012 14.7 3.4 3.2 19.2 7.2 17.6WR5-246 0.686 0.009 21.1 2.6 2.6 26.1 13.6 22.8WR5-246 0.659 0.013 29.2 4.0 3.9 34.9 21.7 29.3Average 336 0.681 22.7 27.8 15.1 24.0SE 0.010 3.0 3.2 3.0 2.4



WR5-302 0.663 0.011 28.1 3.4 3.3 33.7 20.6 28.4WR5-302 0.706 0.011 15.5 3.1 3.0 20.0 7.9 18.2WR5-302 0.677 0.011 23.9 3.4 3.3 29.1 16.3 25.0WR5-302 0.659 0.012 29.2 3.8 3.7 34.9 21.7 29.3WR5-302 0.654 0.008 30.7 2.5 2.4 36.6 23.3 30.5WR5-302 0.682 0.011 22.3 3.2 3.1 27.4 14.8 23.8Average 397 0.674 24.9 30.3 17.4 25.9SE 0.008 2.3 2.5 2.3 1.9


WR5-347 0.666 0.011 27.0 3.4 3.3 32.5 19.5 27.6WR5-347 0.702 0.011 16.7 3.1 3.0 21.3 9.2 19.2WR5-347 0.666 0.011 27.2 3.4 3.3 32.8 19.7 27.7WR5-347 0.688 0.010 20.6 3.0 2.9 25.6 13.1 22.4WR5-347 0.654 0.009 30.8 3.0 2.9 36.6 23.3 30.6WR5-347 0.691 0.009 19.7 2.5 2.5 24.6 12.2 21.7WR5-347 0.665 0.010 27.5 3.1 3.0 33.1 20.0 28.0Average 430 0.676 24.2 29.5 16.7 25.3SE 0.007 2.0 2.1 2.0 1.6

WR5-364 0.697 0.015 18.1 4.3 4.1 22.8 10.6 20.4WR5-364 0.690 0.018 20.1 5.3 5.0 24.9 12.5 22.0WR5-364 0.698 0.016 17.8 4.4 4.2 22.4 10.2 20.1WR5-364 0.680 0.013 22.8 3.8 3.7 28.0 15.3 24.2Average 438 0.691 19.7 24.6 12.2 21.6SE 0.004 1.2 1.3 1.2 0.9


(continued on next page)



Table A.4 (continued )

Sample Age (ka) D47 D47 error (1 SE) Synthetic calcite calibration ETH TravertinecalibrationETH

Other calibrations

Temp. (�C) Error pos Error neg Affek andZaarur, 2014D47 þ 0.025‰

Zaarur et al.,2013D47 þ 0.025‰

LC-1a 0.689 0.013 20.4 3.8 3.6 25.3 12.8 22.2LC-1a 0.679 0.011 23.3 3.1 3.1 28.5 15.8 24.6LC-1a 0.695 0.013 18.5 3.7 3.6 23.3 11.0 20.7LC-1a 0.670 0.015 25.8 4.6 4.4 31.2 18.3 26.6LC-1a 0.684 0.014 21.7 4.1 4.0 26.7 14.2 23.3Average 0.683 21.9 27.0 14.4 23.5SE 0.004 1.2 1.3 1.2 1.0

WR-MC2 0.663 0.009 27.9 2.9 2.8 33.5 20.4 28.3WR-MC2 0.684 0.010 21.8 2.9 2.9 26.8 14.2 23.3WR-MC2 0.653 0.012 31.0 3.8 3.7 36.9 23.6 30.8WR-MC2 0.643 0.008 34.3 2.7 2.6 40.5 26.8 33.3WR-MC2 0.665 0.013 27.5 4.2 4.0 33.1 20.0 28.0WR-MC2 0.676 0.014 24.0 4.2 4.0 29.2 16.5 25.1WR-MC2 0.698 0.011 17.7 3.1 3.0 22.3 10.1 20.0Average 0.669 26.3 31.8 18.8 27.0SE 0.007 2.1 2.3 2.1 1.7


Supplementary data

Supplementary data related to this article can be found at http://dx.doi.org/10.1016/j.quascirev.2015.06.015.

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Documents

Quaternary Science ReviewsMulu National Park, northern Borneo (4.1 N, 114.9 E; Fig. 1), Whiterock Cave (WR) and Lang's Cave (LC). The Mulu caves are well-known for some of the largest