Earth and Planetary Science Letters 329-330 (2012) 150–161

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Earth and Planetary Science Letters

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Seawater transport during coral biomineralization

Alexander C. Gagnon a,⁎, Jess F. Adkins b, Jonathan Erez c

a Division of Chemistry, California Institute of Technology, Pasadena, California, USAb Division of Geological and Planetary Sciences, California Institute of Technology, Pasadena, California, USAc Earth Sciences Institute, Hebrew University, Jerusalem, Israel

⁎ Corresponding author at: Earth Science DivisionLawrence Berkeley National Laboratory, 1 Cyclotron RoadCA 94720, USA. Tel.: +1 510 486 7205.

E-mail addresses: acgagnon@lbl.gov (A.C. Gagnon), j(J.F. Adkins), erez@vms.huji.ac.il (J. Erez).

0012-821X/$ – see front matter. Published by Elsevier Bdoi:10.1016/j.epsl.2012.03.005

a b s t r a c t

a r t i c l e i n f o

Article history:Accepted 2 March 2012Available online xxxx

Editor: P. DeMenocal

Keywords:biomineralizationcoralNanoSIMSpaleoceanographyMe/Ca

Cation transport during skeletal growth is a key process controllingmetal/calcium (Me/Ca) paleoproxy behav-ior in coral. To characterize this transport, cultured corals were transferred into seawater enriched in the rareearth element Tb3+ as well as stable isotopes of calcium, strontium, and barium. Subsequent NanoSIMS ionimages of each coral skeleton were used to follow uptake dynamics. These images show a continuous regioncorresponding to new growth that is homogeneously enriched in each tracer. Isotope ratio profiles across thenew growth boundary transition rapidly from natural abundance ratios to a ratio matching the enriched cul-ture solution. The location of this transition is the same for each element, within analytical resolution. Thesynchronous incorporation of all these cations, including the dissimilar ion terbium, which has no known bi-ological function in coral, suggests that: (1) there is cation exchange between seawater and the calcifyingfluid, and (2) these elements are influenced by similar transport mechanisms consistent with direct andrapid seawater transport to the site of calcification. Measured using isotope ratio profiles, seawater transportrates differ from place to place on the growing coral skeleton, with calcifying fluid turnover times from 30 minto 5.7 h. Despite these differences, all the elements measured in this study show the same transport dynamicsat each location. Using an analytical geochemical model of biomineralization that includes direct seawatertransport we constrain the role of active calcium pumping during calcification and we show that the balancebetween seawater transport and precipitation can explain observed Me/Ca variability in deep-sea coral.

Published by Elsevier B.V.

1. Introduction

Skeletal metal/calcium (Me/Ca) ratios in coral can be used to recon-struct the past ocean environment (Alibert and McCulloch, 1997; Becket al., 1992; Shen and Boyle, 1988; Shen et al., 1987; Smith et al.,1979). However, biomineralization, the biologically mediated processof skeletal growth, can also influence Me/Ca ratios (Allison et al., 2001,2010; Cohen et al., 2002; DeVilliers et al., 1995; Gaetani and Cohen,2006; Gagnon et al., 2007; Meibom et al., 2008). A mechanistic under-standing of biomineralization that separates environmental and biolog-ical signals in a systematic way promises more accurate paleorecords.Despite significant progress towards this goal, debate remains regard-ing key mechanistic components of coral biomineralization, includingthe composition of the calcifying micro-environment and how changesin the surrounding seawater affect this micro-environment.

Most researchers agree that the coral skeleton is precipitated ex-tracellularly and that this process is mediated by the closely associat-ed tissue layer — the calicoblastic epithelium. (Allemand et al., 2004;

and The Molecular Foundry,, Mail Stop 67R3208, Berkeley,

ess@gps.caltech.edu

.V.

Clode, 2002; Johnston, 1980; Tambutte et al., 2007). Extracellular pre-cipitation necessarily invokes some calcifying fluid, however smallin volume or bio-molecule rich, where precipitation occurs. Wheremodels of coral biomineralization tend to differ is on the compositionof this fluid and the predominant transport mechanism of skeletalions to this fluid.

One class of models assumes that transcellular calcium transportdominates, as reviewed by Gattuso et al. (1999) and Allemand et al.(2004). In these models, the vast majority of skeletal calcium is trans-ported through cells of the calicoblastic epithelium. However, the ara-gonite coral skeleton contains many cations other than calcium. Themost abundant co-precipitant is strontium, at about 1 mol%. To explainthe presence of these other cations, transcellular transport modelseither rely on specific non-calcium transporters (Ip and Krishnaveni,1991; Ip and Lim, 1991) or suggest that calcium transport is promiscu-ous and also acts on a subset of similar ions.

If these models are accurate and transcellular cation transportdominates during calcification, then theMe/Ca composition of the cal-cifying fluid and the subsequently precipitated coral skeleton shouldbe sensitive to the transport process. The relevant transport proteinswould therefore be important targets to better understand environ-mental and biological controls on skeletal Me/Ca ratios and calcifica-tion in general (Ip et al., 1991; Zoccola et al., 2004). There are severaladditional and testable implications of the transcellular model: first,

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skeletal composition will be limited to those cations that can eitherfollow the same pathways as skeletal calcium or those cations thatcan cross biological membranes. Second, if different cations, calciumand strontium for instance, follow different ion pumps or pathwaysand each pathway is characterized by a distinct turnover time, thenthese cations will exhibit different ion dynamics. In particular, skeletalincorporation of calcium, strontium and other cations along a growthaxis should respond on different time scales to changes in surroundingseawater composition. This signal is qualified by an important consid-eration. If skeletal growth is much slower than the slowest ion trans-port pathway, then differences in ion dynamics will not be recorded.However, as we show later in the paper, growth rates and transportrates are closely matched in coral, making differences in ion dynamicsresolvable.

In contrast to transcellular transport, many geochemical models ofbiomineralization assume that skeletal cations arrive at the site ofcalcification primarily through direct seawater transport, possiblyvia paracellular pathways (Tambutte et al., 2011) or vacuoles. Evenotherwise closed system Rayleigh models typically assume the initialstep of biomineralization is the transport of seawater to the calcifyingfluid followed by precipitation (Cohen et al., 2006; Gaetani and Cohen,2006; Gagnon et al., 2007; Sinclair and Risk, 2006). In addition to geo-chemical arguments, direct seawater exchange is supported by recentexperiments showing the incorporation of membrane-impermeantfluorescent dyes from the surrounding seawater into growing coralskeletons (Erez and Braun, 2007; Tambutte et al., 2011).

The implications of direct seawater transport are quite differentfrom those of transcellular transport. Since skeletal composition is di-rectly linked to the surrounding seawater, aquatic chemistry becomesan important control, in addition to coral physiology. With regards torelative cation dynamics, direct seawater transport results in a simul-taneous skeletal response to changes in seawater composition. Final-ly, bulk seawater transport predicts the co-incorporation of ions thatcannot easily follow calcium specific transport pathways, includingthose of very different charge and size.

Previous research on cation dynamics during calcification largelystems from radio-tracer uptake experiments followed by bulk skeletalanalysis. Tambutte et al. (1996) followed 45Ca dynamics in the coralStylophora pistillata. One of the results from Tambutte et al. (1996),is that a small amount of 45Ca is found in the skeleton almost imme-diately after it is introduced into the growth media (b2 min). Thissupports some form of rapid calcium transport between the sur-rounding seawater and the site of calcification. Since the incorpora-tion of 45Ca into the coral skeleton is controlled by both calciumtransport and by skeletal growth rates, the kinetics of these separateprocesses cannot be resolved by measuring bulk skeletal 45Ca activity.

To distinguish between different transport mechanisms we quan-tify the uptake dynamics of several different enriched stable isotopesand the rare earth element Tb3+ during skeletal growth in culturedsurface coral. Terbium has a different charge, size and polarizabilityfrom Ca2+ and has no known biological role in coral. Direct seawatertransport predicts that all the isotopes and terbium should be incorpo-rated in the skeleton simultaneously, while transcellular transportwould likely result in asynchronous incorporation and possible dis-crimination against dissimilar cations like Tb3+. Although unlikely, atranscellular ion transport pathway could yield similar results if it iscompletely non-selective. However, if ions follow the same pathwaywith the same turnover time, then, as far as the composition of thecalcifying fluid is concerned, this is effectively identical to seawatertransport. In this study we look for signatures of ion dynamics thatdiffer from seawater transport.

While conceptually simple, this experimental approach is compli-cated by the slow growth rate and convoluted growth geometry ofcoral. To overcome these limitations we use the NanoSIMS, an instru-ment capable of accurate compositional and isotopic analysis withsub-micron spatial resolution. The NanoSIMS has been used previously

to map natural Me/Ca variability in coral (Meibom et al., 2004, 2008).Also, Houlbreque et al. (2009) incubated coral in 86Sr followed byNano-SIMS image mapping to resolve discrete regions of labeled skeletonalong a growth front. Building on these previous studies, we quantita-tively map the location, relative timing, and extent of incorporation ofseveral stable isotope tracers. Since ion transport mechanisms impactskeletal Me/Ca ratios and the environmental proxies based on these ra-tios, we alsomodel predicted skeletalMe/Ca ratios for variousmodes ofcation transport. This model is then tested against Me/Ca measure-ments in a modern deep-sea coral, a system where the compositionalsignature of biomineralization is isolated from confounding environ-mental variability. Together, our data and analyses test the relative im-portance of direct seawater transport during coral biomineralization.

2. Methods

2.1. Coral culture

Similarly sized branches of the surface coral S. pistillata were re-moved from a single wild colony and allowed to recover in an aquar-ium. Branches were covered by tissue on all surfaces except a smallregion at the bottom of the branch where each piece was cut fromthe colony. After 10 days of recovery these corals were fluorescentlylabeled during 6 h of growth in a seawater solution containing theCaCO3 binding probe calcein at a concentration of 20 μM. Labelingwas followed by an eight hour efflux into calcein free and naturalabundance seawater designed to remove calcein from any exchange-able seawater pools internal to the coral. Calcien was absent duringsubsequent coral growth.

The branches were then immediately cultured in Gulf of Eilat sea-water (salinity=41.7) enriched in 43Ca by 48% relative to naturalabundance, 87Sr by 28% , 136Ba by 30-fold, and with a terbium concen-tration of 1 μM (stable isotopes from Oak Ridge National Laboratory;Tb from High Purity Standards). Overall elemental concentrationswere kept near natural values, with negligible change to [Ca], [Sr] in-creased by 3%, and the trace element [Ba] doubled to ∼20 μM. Theenriched stable isotopes, typically purchased as solid carbonates,were reacted with excess HCl prior to mixing into the master culturesolution to ensure complete dissolution.

Each branch was cultured in a separate 215 mL flow-through,magnetically stirred, airtight and completely filled chamber. Isotopi-cally enriched seawater of constant composition was fed througheach chamber from airtight reservoirs yielding about one full ex-change of seawater per day. Outflows from each chamber were sepa-rately collected for regular analysis of isotope ratios, metal/calciumratios and the carbonate system. The carbonate system of each reser-voir was set at the beginning of the experiment through alkalinity ad-justments using HCl and freshly prepared NaOH (analytical grade).Each culture chamber was kept at a constant pH value, with differentchambers spanning a range of pHs centered on modern tropical sur-face ocean conditions. Chamber pHs ranged from 7.9 to 8.5, corre-sponding to aragonite oversaturations of 2.7 to 4.9. The effect ofseawater pH on the composition of the newly grown skeleton willbe presented elsewhere. The total duration of coral culture in theisotopically enriched solution was 133 h, or about 5.5 days, althoughthis study is primarily concerned with the initial response of thecoral skeleton to the change from natural abundance to enriched sea-water. As a mid-experiment time mark (∼49 h), the [Tb] of the culturesolution was doubled, although we only attempted to image this markin the slowest growing coral. Corals were exposed to a 12 hour diurnallight cycle andmaintained at 25±0.3 °C. Light level was approximately200 μmol m−2 s−1.

At the end of the growth experiment, coral pieces were rinsedwith several volumes of natural abundance seawater while still inthe growth chambers to limit non-specific isotope binding. The coralswere then removed and cleaned using an airbrush to remove tissue,

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rinsed in distilled water, dried in an oven at 50 °C, and stored forseveral months while awaiting analysis. Later, sub-samples of eachcoral were cleaned using dilute sodium hypochlorite to remove anyremaining tissue.

Using bulk isotope analysis of different skeletal regions, we deter-mined that the ∼100 μm long spines that decorate the coral surfacebetween polyps incorporate enriched isotopes from the culturemedia and exhibit a high proportion of new growth. To further charac-terize this new growth, spines were mounted in Araldite resin andpolished using diamond paste followed by colloidal silica. Calcein fluo-rescence was imaged using a Zeiss 510 confocal laser scanning micro-scope (excitation by Ar laser at 488 nm; emission collected between500 and 550 nm). After microscopy, the samples were coated with30 nm of gold and analyzed using the NanoSIMS at the Caltech Centerfor Microanalysis. In total four spines were imaged, one from eachcoral. In some cases a single spine was analyzed multiple times in dif-ferent locations.

Spine calcification rates were determined from confocal fluores-cence images of each polished spine. The calcein mark correspondsto the shape of the spine at the beginning of the culture experiment.This outline was used to generate a solid of revolution. Using the den-sity of pure aragonite this volume was turned into the initial spinemass. The process was repeated for the final outer growth surface ofthe same spine. The amount of new growth is simply the number ofmoles of calcium in the final spine minus the moles of calcium in thenew spine. Growth was averaged over the 133 hour growth experi-ment, normalized to the mean of the initial and final spine surfaceareas, and reported as μmol CaCO3 m−2 s−1.

2.2. Isotope ratio profiles and calcifying fluid dynamics

Details of isotope ratio mapping using NanoSIMS are included inAppendix A. To follow uptake dynamics isotope ratio profiles weretaken along a growth axis perpendicular to the new growth boundary.As is true of other SIMS instruments, the measured profile representsa convolution of the primary beam shape with the true compositionalsignal. Offline analysis was used to deconvolve the estimated beamsize from each coral profile. This process requires some constraints onthe functional form of the true compositional signal. We postulatethat the calcifying fluid can be modeled by a single box in exchangewith seawater. In this approximation seawater mixing is characterizedby a turnover half-life, τ1/2=calcifying fluid volume/seawater trans-port rate×ln(2). While simple, the one-box approximation results in ageneral solution since multiple boxes in series are mathematicallyequivalent to a single hypothetical box with an effective turnover time.

Profiles across the growth boundary capture the effect of an abruptchange in seawater 43Ca/42Ca as it mixes into the calcifying fluid.Treating the calcifying-fluid as a single box, this mixing can be mod-eled with the time dependent equation:

43Ca42Ca

!coral

tð Þ ¼43Ca42Ca

!natural

−43Ca42Ca

!spike

24

35e�ln 2ð Þ

τ1=2t þ

43Ca42Ca

!spike

; ð1Þ

which is algebraically equivalent to Eq. (1) of Tambutte et al. (1996).Assuming a constant growth rate, r=d/t, Eq. (1) is transformed intothe expected 43Ca/42Ca signal as a function of distance along a partic-ular growth axis,

43Ca42Ca

!coral

dð Þ ¼43Ca42Ca

!natural

−43Ca42Ca

!spike

24

35e−ln 2ð Þ

d1=2d þ

43Ca42Ca

!spike

;

ð2Þ

where d1/2=r×τ1/2 and represents the half-length of mixing for aparticular growth rate.

Using Eq. (2) and a particular d1/2 we can model the theoreticalshape of a calcium isotope profile due only to mixing. This shape isthen convolved with an 800 nm Gaussian distributed primary beamto yield a theoretical NanoSIMS profile with a characteristic and mea-surable response length (l1/2, defined as the distance perpendicular tothe boundary required for the convolved profile to rise from 16% to84% of the enriched value). Using a large range of possible d1/2 values,we constructed a calibration curve relating measurable NanoSIMSprofile response lengths (l1/2) to the corresponding d1/2 of mixing(calibration curve included in the Supplemental Information). Usingl1/2 values measured from each NanoSIMS profile and the calibrationcurve, we determined d1/2 values and then further converted theseinto calcifying fluid τ1/2 values using the linear growth rate of eachspine. Growth rates are assumed to be constant during the 133 hourculture experiment and are estimated using the length of new growthbetween the calcein mark and the outer part of the spine.

2.3. Me/Ca of deep-sea coral

As will be discussed bellow, seawater transport can affect skeletalmetal/calcium. To test these predictions new micro-milled sampleswere taken from the same septa of deep-sea coral Desmophyllumdianthus 47407 described in Gagnon et al. (2007). Where remainingmaterial allowed, archived dissolved samples from Gagnon et al.(2007) were also re-measured. Coral 47407 is a modern specimenfrom the Smithsonian collection and was recovered from 549 m inthe South Pacific (54° 49′ S, 129° 48′ E). Micro-samples were takenfrom outside the centers of calcification (COCs). New measurementsof Sr/Ca and Mg/Ca were analyzed at 20-fold and two-fold higherprecision, respectively, than Gagnon et al. (2007) using the isotope-dilution method of Fernandez et al. (2010) adapted for analysis on aNeptune multi-collector ICP-MS (ThermoFinniagn). The external pre-cision of the method is 0.1% for Sr/Ca (n=62, 18 months) and 0.5% forMg/Ca (n=50, 6 months) as assessed by the 2σ standard deviation ofa regularly analyzed deep-sea coral consistency standard with a com-position of roughly 10 mmol/mol Sr/Ca and 3 mmol/mol Mg/Ca.

3. Results

3.1. Calcein fluorescence

When present, calcien marks a clear interior growth surface corre-sponding to the boundary between the pre-experiment skeleton andnewly cultured growth (Fig. 1). Two additional control experimentssupport this interpretation: (1) spines prepared from a coral neverexposed to calcein show no calcein fluorescence, and (2) in coral sacri-ficed just after the calcein labeling experiment, several spines fluo-resce on their outer surface with no evidence of additional growth.

In total several hundred spines were mounted, polished and sur-veyed for calcein fluorescence yielding 15 spines with measurable newgrowth beyond a clear calcein label. The relative scarcity of candidatespines suggests that coral calcification is regionally segregated, at leastduring the calcein labeling period. While the effect of aragonite oversa-turation (Ω) on spine growth rate will be presented in detail elsewhere,our data suggest that at the 100 μm scale of a spine, linear growth ratesare spatially heterogeneous at all oversaturations, ranging from no mea-surable growth to microns per day in each coral. Linear growth in the 15candidate spines ranges from 5 to 90 μm. Estimated calcification ratesfor these 15 spines mostly cluster around 0.3 μmol CaCO3 m−2 s−1,but ranged from 0.06 to 2.3 μmol CaCO3 m−2 s−1. Among the fourspines analyzed by the NanoSIMS, calcification rates ranged from 0.2to 1.5 μmol CaCO3 m−2 s−1. Apart from the low Ω coral, which showedthe lowest growth rates, linear growth rates in the candidate spines donot vary systematically with oversaturation.

Fig. 1. (A) SEM image of the Stylophora pistillata skeletal surface. Individual coral polyps sit in each pit-like calyx. Regions between polyps are decorated with spines. Scale bar is200 μm. (B) SEM image of a typical spine broken from the coral surface. Scale bar is 20 μm. (C) Transmitted light image of another mounted and sectioned spine in the plane ofthe polished surface. This spine is ∼90 μm long. (D) A confocal fluorescence image of the same spine reveals bright green calcein fluorescence marking the interior junction betweeninitial skeletal material and new cultured growth. A faint green line reflected from the edge of the coral marks the outside of the spine. Faint edge effects are probably seen becauseexcitation and emission wavelengths are similar resulting in some leakage of reflected light through the filters into the detector. This reflected background signal is clearly distin-guishable from the more intense calcein fluorescence. (E) A series of fluorescent images taken successively deeper into the coral spine were used to construct a 3-D projection of thelabeled calcein surface. This convex down surface marks what the spine looked like at the beginning of the coral culture experiment. Bright regions on the surface match the ex-ternal texture of spines from SEM images and suggest that over short periods of time growth may occur in spatially discrete units. (For interpretation of the references to color inthis figure legend, the reader is referred to the web version of this article.)

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3.2. NanoSIMS isotope images

Guided by maps of calcein fluorescence, NanoSIMS ion imageswere made of the new growth boundary. Images of 43Ca/42Ca, 87Sr/88Sr and 136Ba show a clear and continuous boundary marking thestart of isotopically enriched skeletal material (Fig. 2). Control imagesof 42Ca intensity and images of the unenriched ratio 86Sr/88Sr show noevidence of a growth boundary (Fig. 3). These negative controls dem-onstrate that we are measuring a real signal rather than an analyticalartifact due to charging or sample topography. Ion imageswere placedin relation to calcien fluorescence using post-analysis SEM images ofNanoSIMS burn marks. In each spine the new growth boundary qual-itativelymatches the calcein label. Tb countswere not collected for theimage in Fig. 2 as physical limits on the arrangement of the collectorsin the NanoSIMS preclude the simultaneous collection of all the spikedratios and Tb. However, in other images where the instrument wastuned to collect Tb but only a subset of spiked ratios, profiles of Tbalso follow the spike 43Ca/42Ca boundary (described in more detailbelow).

Isotope ratios are homogeneous in the region of new skeletalgrowth. Histograms of pixel ratios from each image are distributedbetween a natural abundance population and an isotopically enrichedpopulation with histogram width entirely attributable to instrumen-tal uncertainty (Fig. 4). Five additional isotope images exhibit similarresults and are included in the Supplementary data.

3.3. Isotope ratio profiles across the new growth boundary

Profiles of 43Ca/42Ca across the new growth boundary show a rapidtransition between natural abundance ratios and a ratio matching theenriched culture solution (Fig. 5), suggesting we have identified thepure new growth end-member. The 87Sr/88Sr ratio of the newly

grown region is slightly lower than the culture ratio in this and severalother spines. However, one coral spine image was an exception, withan 87Sr/88Sr slightly higher than the culture value. It is easy to imaginerelevant coral biomineralization processes that would cause 87Sr/88Srto be lower than the culture solution, like mixing with a slow turn-over internal pool. However, isotope ratios higher than the culturemedia are physically impossible as fractionation of this magnitudecannot be caused by natural mass-dependent processes, thus the dif-ference points to analytical uncertainty. Subsequent higher precisionand externally standardized spot measurements of the 87Sr/88Srratio in the new growth region generally agree with the solution iso-tope ratios, as will be detailed elsewhere. We interpret these data tosuggest that the minor disagreement between NanoSIMS imagebased 87Sr/88Sr and solution 87Sr/88Sr are probably due to an uncor-rected second-order mass fractionation during image analysis.

The 43Ca/42Ca response lengths (l1/2) of seven profiles from fourspines range from 0.9 to 1.8 μm. When an 800 nm NanoSIMS spot sizeis deconvolved from these measured response lengths, d1/2 valuesrange from 160 nm to 640 nm. Assuming constant growth rates duringthe whole culture experiment, these d1/2 values corresponding to calci-fying fluid mixing times (τ1/2) of 30 min to 5.7 h. Response lengths donot vary systematically with culture solution carbonate chemistry.

Other metal cations also behave like 43Ca. In Figs. 5–6, the profilepoints between 16%–84% of the 43Ca/42Ca response are marked inusing filled points. These same points, defined only using 43Ca/42Ca,are also filled for all the other isotope ratios. Using these points as aguide, we see that the transition between natural abundance andenriched ratios occurs at the same location for each element. Thusenriched isotopes of several elements are all incorporated synchro-nously with calcium, despite their different chemical properties. Fur-thermore, even Tb3+ is incorporated synchronously with Ca2+, asshown in an additional NanoSIMS profile (Fig. 6).

0.15

0.2

0.25

0.3

0.35

0.4

43Ca/42Ca

0.06

0.07

0.08

0.09

0.1

0.11

0.12

87Sr/88Sr 136Ba Intensity

0

0.5

1

1.5

2

2.5

3

3.5

4

Fig. 2.A 20×20 μmNanoSIMS ion image shows a clear and continuous boundary in 43Ca/42Ca and 87Sr/88Sr ratios aswell as 136Ba intensity at the junction between initial skeleton andnew growth in a coral spine. Top left: this boundary corresponds to the calcein margin as demonstrated when the post-analysis image burn mark (square box) is placed on a map ofcalcein fluorescence (scale bar 20 μm). The 43Ca/42Ca images were processed using a 5×5 pixel averaging filter; while a 9×9 pixel filter was applied to the 87Sr/88Sr ion image. Blackmargins mask edges effects from the filter. An intensity map is used for 136Ba because low counts yield unreliable ratios. In the 136Ba image the scale is in counts per pixel.

154 A.C. Gagnon et al. / Earth and Planetary Science Letters 329-330 (2012) 150–161

4. Discussion

4.1. Isotope incorporation in the growing coral skeleton

We have shown that we can predictably isolate and characterizeexperimentally grown skeletal material during a short coral culture

Fig. 3. Images of 42Ca intensity and the unenriched isotope ratio 87Sr/88Sr are homogenoussuring a true boundary rather than analytical artifacts or topography.

experiment. Furthermore, stable isotopes from the culture solutionare incorporated abruptly along a sharp and continuous boundary.This boundary defines two isotopically homogenous regions: the ini-tial skeleton and an isotopically labeled region corresponding togrowth during the culture experiment. Histograms show that devia-tions in the measured ratio about each end-member are completely

with no evidence of a growth boundary. These negative controls suggest we are mea-

0.15 0.2 0.25 0.3 0.35 0.4

100

200

300

400

500

600

700

43Ca/ 42Ca

Num

ber

of P

ixel

s

0.07 0.09 0.11

100

200

300

400

87Sr/ 88Sr

Num

ber

of P

ixel

s

Fig. 4. Histograms of 43Ca/42Ca and 87Sr/88Sr for each pixel in Fig. 2 are bi-modal and represent two homogenous end-members: a natural abundance population and an isotopicallyenriched population. The distribution of 87Sr/88Sr about each mean is relatively wider than for 43Ca/42Ca due to lower ion counts and therefore lower ratio precision. Indeed, thewidth of each distribution can be explained entirely by Poisson distributed counting error, the theoretical minimum limit of instrumental uncertainty in this class of ion countingexperiment (gray overlaid model histogram).

155A.C. Gagnon et al. / Earth and Planetary Science Letters 329-330 (2012) 150–161

consistent with instrumental uncertainty rather than reflecting arange of skeletal isotope ratios. We therefore detect no evidence fora large and/or slowly exchanging internal cation pool, as this reser-voir would result in a range of lower than culture solution isotope ra-tios that would evolve along a growth axis in the cultured skeleton.

In a previous experiment Houlbreque et al. (2009) used NanoSIMSto map 86Sr incorporation after a 72 hour incubation, revealing dis-crete 5–10 μm regions of labeled skeleton organized along a growthfront. While our results are generally in agreement with Houlbrequeet al. (2009), the growth region in our study is continuous. Duringour longer experiment, it is possible that the space between differentgrowth units was filled by the coral. Alternatively, by choosing toanalyze spines, with a clear growth axis and simplified geometry,we may have avoided the complicated growth surface sectioned byHoulbreque et al. (2009) — a section which may have intersected dif-ferent regions and directions of growth. It should be noted that manyspines in our survey show no calcein mark. Therefore, both studiessuggest that coral growth is patchy in time and space on a scale greaterthan tens of microns.

4.2. Cation transport dynamics

Treating the calcifying fluid as a single box, 43Ca/42Ca responselengths correspond to calcifying fluid turnover times (τ1/2) from30 min to 5.7 h. Thus both our study and Tambutte et al. (1996) pro-vide examples of rapid cation transport from seawater to the site ofcalcification, although our data suggest that this mixing can also beas slow as several hours.

Linear growth rates vary by more than a factor of five between dif-ferent corals and spines in our study. This means that the small rangeof measured 43Ca/42Ca response lengths result in a large range of re-sponse times. Thus uncertainty in the age model may be contributingto our response time estimates; growth may not have been constantover the entire experiment for all spines. Speculatively, this mayoccur if discrete units of growth like those imaged in calcein surfacemaps (Fig. 1) and described by Houlbreque et al. (2009) are used tobuild the coral skeleton. Over several days, precipitating differentnumbers of these units would then yield different apparent lineargrowth rates at spatial scales >10 μm even if the growth kinetics ofeach unit, and thus the kinetics governing cation incorporation foreach unit, are similar. One piece of information, however, supports aconstant growth rate for at least one spine. A mid-experiment dou-bling of [Tb] seems to have been captured in the slowest growingspine at about the location predicted for a constant growth rate. Asother spines grew too quickly for a 20×20 μm image to capture boththe initial isotope boundary and the mid-experiment Tb enrichment,we do not have any additional constraints on growth rate. Faster

growth rates would tend to result in actual τ1/2 values that are lowerthanwhatwe report, suggesting that our turnover time estimates rep-resent an upper limit.

Image profiles show that changes to culture solution 87Sr, 136Baand Terbium are all incorporated in the coral skeleton synchronouslywith 43Ca. Even in samples with 43Ca/42Ca response times on theorder of hours, spatial differences in strontium, barium and terbiumbehavior would be evident when comparing the infection point ofeach profile. We observe no differences greater than a few pixels(Figs. 5–6). While the possibility of different dynamics over shortertime scales cannot be excluded entirely, the resolvable evidence sup-ports similar dynamics for each enriched element. The existence ofshort response times, synchronous incorporation of elements withdifferent size, and especially the simultaneous incorporation of Ca2+

with the dissimilar ion Tb3+, which has no known biological functionin coral, are all consistent with direct seawater transport to the site ofcalcification. To better understand the implication of this ion transportmode on skeletal composition and proxies, we examine models forMe/Ca behavior during biomineralization under the influence of directseawater exchange.

4.3. Seawater exchange and skeletal metal/calcium ratios

Direct seawater transport can follow one of at least two differentmodes: batch transport or steady-state seawater delivery. In a batchprocess, parcels of seawater are transported to the site of calcifica-tion, the coral increases the local aragonite saturation and then pre-cipitation occurs. During our experiment a batch process could only“gulp” either natural abundance seawater or, subsequently, isotopi-cally enriched seawater. Thus, with only two distinct batch composi-tions, we might predict an infinitely sharp transition in 43Ca/42Caacross the growth boundary.

Within the framework of a batch transport model, we explain theobservation of longer d1/2 values, on the order of 100 s of nm, by postu-lating (1) each parcel of seawater yields a b100 nm unit of growth and(2) different batches of seawater have different lifetimes. Parcels withboth natural abundance and enriched seawater could then co-exist fora short time at the start of the culture experiment, precipitating side-by-side at the sub-micron scale. In this model we assume that the calci-fying space is dynamic and spatially discontinuous along the undersideof the calicoblastic epithelium. As natural abundance seawater batchesare replaced, skeletal 43Ca/42Ca will rise. Thus, in the batch scenario,τ1/2 values correspond to the average lifetime of seawater batches asthey travel to the site of calcification and then presumably returntheir remaining contents to seawater after precipitation.

The model assumes that each batch of seawater is independent,thus we can treat a parcel of seawater as closed to cation transport

Fig. 5. Profiles of the enriched isotopes 87Sr/88Sr and 136Ba show synchronous behavioracross the new growth boundary in the images from Fig. 2. The points corresponding tothe 43Ca/42Ca transition region are filled. These same filled points also fall within thetransition of 87Sr/88Sr from natural to enriched abundance and correspond to the risein 136Ba. Dashed lines mark natural and spike isotope ratios calculated from ICP-MSmeasurements of the culture solution. The 16%–84% width of the boundary inthe 43Ca/42Ca profile is 1.3 μm. Profile step size is ∼150 nm. Error bars are 1σ basedon counting statistics.

Fig. 6. In a second spine, the dissimilar ion Tb3+ exhibits dynamics like that of calciumand strontium. Counts due to incorporation of the element Tb raise above low naturallevels at the same location as 43Ca and 87Sr. Again the filled points are chosen based onthe 43Ca/42Ca transition. Due to the geometry of the NanoSIMS magnet and the finitewidth of each detector, it is not possible to collect all isotopes of interest during a singleanalysis. For this reason either Tb or Ba isotopes were collected during different analyt-ical sessions. In this image the 16%–84% width of 43Ca/42Ca across the boundary is again1.3 μm.

156 A.C. Gagnon et al. / Earth and Planetary Science Letters 329-330 (2012) 150–161

during precipitation. Precipitation from a closed-system followsRayleigh behavior and affects skeletal Me/Ca ratios in a testable way.These predictions have been the subject of extensive research — Me/Ca ratios measured in several different corals are indeed consistentwith precipitation from a closed-system (Cohen et al., 2006; Gaetaniand Cohen, 2006; Gagnon et al., 2007). Thus our ion transport studyand geochemical measurements agree with a batch-like model of bio-mineralization where the initial calcifying fluid is directly derivedfrom seawater and subsequent precipitation is closed to cation trans-port. Interpreted using this model, non-environmental Me/Ca vari-ability in coral is driven by different extents of calcification indifferent batches of seawater. The presence of Me/Ca variability incoral grown under near constant-environmental conditions (Gagnonet al., 2007) suggests that calcification “efficiency” varies from placeto place in coral even though temperature and many other environ-mental parameters are constant during growth.

Alternatively, direct seawater transport could occur through asteady-state process, where the seawater exchange rate (k=s−1=ln(2)/τ1/2 balances precipitation (P=mol Ca m−2 s−1) at the site ofcalcification. The impact of this scenario on skeletal Me/Ca ratioscan be described using a box-model (Fig. 7). To explore a widerange of model conditions we also allow for the presence or absenceof calcium specific pumping (F=mol Ca m−2 s−1). Appendix B in-cludes a derivation of the analytical model. Steady-state solutionsare used to predict skeletal Me/Ca ratios for a given set of conditionsand we then compare these Me/Ca ratios to both the batch model andgeochemical measurements in coral.

In the box model, skeletal Me/Ca ratios are affected by the rate ofprecipitation relative to the rate of seawater exchange (P/kzρ[Ca]sw),and by the relative rate of calcium pumping, if calcium pumping ispresent (Fig. 8). The later effect is parameterized as γ=F/P. Usingthe model we can also predict the relationship between different

Fig. 7. Calcifying fluid box model with fluxes for precipitation (P), seawater exchange(kzρ[Ca]), and calcium pumping (F). Precipitation and pumping are area normalizedsince they occur through the bottom calcifying surface or the top cell layer, respectively,while turnover (k=ln(2)/τ1/2) affects the whole calcifying fluid volume. The shape ofthe calcifying space influences the relative strength of these processes, parameterized asz, the ratio of the calcifying fluid volume to the calcifying surface area. The parameter zcan also be thought of as the vertical dimension of an idealized calcifying space inmeters.Since concentration units are molal (mol kg−1) calcifying fluid volume is converted fromm3 to kg using the density of seawater, ρ.

12

10

8

6

4

2

0-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

10.9

10.7

10.5

10.3

10.1

9.9

9.7

9.51.0 1.5 2.0 2.5 3.0 3.5 4.0

130

125

120

115

110

105

100

95

90400 450 500 550 600 650 700 750

1/(Mg/Ca)

Skeletal Mg/Ca (mmol/mol)

Ske

leta

l Sr/

Ca

(mm

ol/m

ol)

Ske

leta

l Sr/

Ca

(mm

ol/m

ol)

1/(S

r/C

a)

Log10 (P/kzp [Ca]sw)

gamma=

0.01

0.05

0.1

0.5

Fig. 8. Plots of predicted skeletal Me/Ca ratios for a steady-state calcifying fluid underthe influence of seawater exchange, calcium pumping and precipitation. Top: skeletalSr/Ca is controlled by the two dimensionless parameters: P/kzρ[Ca]SW and γ. The firstparameter represents the balance between precipitation rate and seawater transport,similar to a Damköhler number. Different curves represent different amounts of pump-ing relative to precipitation, γ=F/P, where higher γ means more of the skeletal calci-um arrives via pumping. Middle: model results for Sr/Ca and Mg/Ca are compared tomicro-sampled deep-sea coral data (square symbols). Error bars for coral measure-ments are smaller than the plotted symbols. Coral data are consistent with a steady-state seawater transport model where calcium pumping is small. See Appendix B andthe main text for model details. Movement along a particular curve represents differ-ences in the balance between seawater exchange and precipitation, with the relativestrength of precipitation rate increasing from the top-left to bottom-right. Bottom: thecompanion inverse ratio plot. Contours of constant γ plot as straight lines in this space.All plots modeled assuming seawater Sr/Ca=8.6 mmol/mol and Mg/Ca=5.131 mol/mol. We also make the operational assumption that the deep-sea coral measurementwith both the highest Sr/Ca and lowest Mg/Ca corresponds to direct precipitation fromseawater, i.e. seawater exchange is so rapid for this point that the calcifying fluid is similarin composition to seawater. This assumption sets (Sr/Ca)o and (Mg/Ca)o. The resultingDSr=1.257 is within error of the inorganic relationships reviewed in Gagnon et al.(2007). DMg=2.74×10−4. (For interpretation of the references to color in this figurelegend, the reader is referred to the web version of this article.)

157A.C. Gagnon et al. / Earth and Planetary Science Letters 329-330 (2012) 150–161

Me/Ca ratios. For example, if calcium pumping is either absent or con-stant, then skeletal (Sr/Ca)−1 vs. (Mg/Ca)−1 should be linearly related(Fig. 8 bottom).

To test these predictions we use high precision co-located Sr/Caand Mg/Ca ratios micro-sampled from a modern deep-sea coral(Fig. 8). Modern deep-sea coral collected from constant environmen-tal conditions are useful model systems to study biomineralization(Adkins et al., 2003; Gagnon et al., 2007). In the absence of environ-mental variability, compositional heterogeneity is completely attrib-utable to biomineralization — yielding a mechanistic fingerprint.Here we re-measure, at significantly improved precision, one of thecoral used by Gagnon et al. (2007). In the previous study this coralwas used to test a batch-transport and Rayleigh model of coral bio-mineralization. Using the more precise data, we demonstrate thatthese Me/Ca ratios show both improved agreement with the previousRayleigh model and that the data can be alternatively explained by asteady-state model of seawater transport.

The deep-sea coral data are nearly linear when plotted as (Sr/Ca)−1

vs. (Mg/Ca)−1, with an R2=0.9 (Fig. 8 middle and bottom). Movementalong a curve in Fig. 8 is governed by the balance between seawatertransport and precipitation, the dimensionless quantity P/kzρ[Ca]sw.Prescribing different γ values yields a series of curves. The values ofthese two dynamical parameters in deep-sea coral can be constrainedby comparing coupled Mg/Ca and Sr/Ca measurements to Fig. 8 andusing Eqs. (B.5)–(B.6). The lowest measured Sr/Ca points correspondto an upper limit of P/kzρ[Ca]sw=0.4. Furthermore, as seen in the twobottom panels of Fig. 8, γ=0.1 is the highest value that agrees withour data. Interpreted within a steady-state model, these Me/Ca ratioscorrespond to model states where seawater exchange delivers morecations than are precipitated (P/kzρ[Ca]swb0.4) and with low relativeamounts of pumping (γb0.1). Under these conditions, much of the cal-cium transported into the calcifying fluid as seawater is replaced beforebecoming part of the coral skeleton.

For a given mass of calcifying fluid, F/zρ is the rate of calciumpumping, while k[Ca]SW is the gross inward rate of seawater calciumtransport. The ratio of these two quantities represents the relativerate of pumping compared to seawater transport of Ca2+,

mol Ca pumped kg−1s−1

mol Ca seawater transport kg−1 s−1 ¼ Fzρ

� �1

k Ca½ �SW

� �¼ γ

Pkzρ Ca½ �SW

:

ð3Þ

Individual estimates of P, k and z are unnecessary for this calcula-tion since both P/kzρ[Ca]sw and γ come directly from the Me/Ca data.These data set as a rough upper limit that 5% of the calcium entering

the calcifying fluid in deep-sea coral can be attributed to pumping,while the rest of the calcium cations arrive from seawater transport.

NanoSIMS profiles and calcein image measurements yield inde-pendent estimates of seawater exchange rates (k=(ln(2)/τ1/2) andprecipitation rates (P). As an additional test of the steady-statemodel we compare these growth parameters in surface coral to the

158 A.C. Gagnon et al. / Earth and Planetary Science Letters 329-330 (2012) 150–161

P/kzρ[Ca]sw values necessary to reproduce deep-sea coral Me/Ca ra-tios. While there are certainly differences between deep-sea and sur-face coral, this comparison roughly gauges the agreement betweendirectly measured transport parameters and geochemical models.

Using data from the four spines where both P and k were mea-sured yields values of 1.2×10−4 mbP/kρ[Ca]swb5.8×10−4 m. Thisdynamic quantity has units of meters and cannot be directly com-pared to P/kzρ[Ca]sw without knowing the value of z. Thus z, whichrepresents the volume to surface area ratio of the calcifying fluid,and which can also be thought of as the idealized thickness of the cal-cifying space, is the one freely tunable parameter in this comparison.Estimates that P/kzρ[Ca]swb0.4 from Me/Ca ratios in deep-sea coralagree with the surface coral results if we assume z is 300 μm to1.5 mm for the deep-sea coral. While physically possible, these zvalues are somewhat large. Deep-sea coral typically grows slowly,with gross linear extension rates of mm/yr (Adkins et al., 2004) com-pared to cm/yr in some surface corals (Dea'th et al., 2009). Prescribingten-fold slower precipitation rates in deep-sea coral while still as-suming similar turnover times for the calcifying fluid as found in sur-face coral results in more reasonable z values of 30 to 150 μm. Thesearguments show that a steady-state model can be consistent withboth dynamic and compositional data collected using very differentmethods while also highlighting the need to better characterize thegeometry of the calcifying space in living coral.

High precision Me/Ca ratios from deep-sea coral also agree withthe completely closed-system (Rayleigh) batch model derived inGagnon et al. (2007), with an R2=0.9 when plotted as ln(Sr/Ca) vsln(Mg/Ca). Thus, our Me/Ca data cannot distinguish between thetwo models. In fact, Me/Ca ratios behave similarly for the two modelsover a large range of conditions. This similarity is predicted even foralternative pairs of Me/Ca ratios with different partition coefficients(DMe), for example Pb/Ca and Mg/Ca. The agreement between thetwo models is not surprising; both are based on reservoir effects inthe calcifying fluid.

4.4. The role of alkalinity and calcium pumping

Both NanoSIMS profiles and Me/Ca data suggest calcium pumpingplays a limited role in transporting skeletal calcium. However, calciumpumping at even low rates can act as an important control on calcifyingfluid chemistry. Indeed many geochemical models of biomineralizationinvoke alkalinity pumping to create a chemical driving force for precipi-tation (McConnaughey, 1989a,b; Adkins et al., 2003). This alkalinitypumping is commonly postulated to result from active Ca2+–H+

exchange.Two pieces of direct evidence support Ca2+–H+ exchange: (1)

genes for a Ca-ATPase were identified in the calicoblastic epitheliumof S. pistillata (Zoccola et al., 2004), and (2) calcium specific electrodessurgically inserted against a coral skeleton record calcium concentra-tions up to 6% higher than seawater (Al-Horani et al., 2003). Whilequestions remain regarding the physiological state of the dissectedcoral, themicro electrodework agrees with the approximately 5% calci-um enrichment required for alkalinity pumping to shift dissolved inor-ganic carbon (DIC) frompredominately HCO3

− to predominately CO32−

at pH=pKa2, thereby increasing local aragonite saturation (calculatedassuming initial seawater with alkalinity=2.3 mmol equiv/kg andDIC=2.0 mmol/kg at 25 °C and salinity=35). Consistent with theidea of alkalinity pumping, above ambient pH values have been directlyobserved in coral calcifyingfluid bymicro-electrodemeasurements (Al-Horani et al., 2003) and via a pH-sensitive fluorescent dye (Venn et al.,2011).

Alkalinity and calcium concentrations in the calcifying fluid are di-rectly linked by Ca2+–H+ exchange. Building on the steady-state bio-mineralization box model developed in the Appendix,

ΔALKFluid−SW ¼ 2 ΔCaFluid−SW ; ð4Þ

where the factor of 2 comes from the calcium's +2 charge. Alterna-tive modes of alkalinity pumping that transport different cationscan relax this link between calcium and alkalinity — the 1:2 relation-ship is an upper bound.

Calcium concentrations in the calcifying fluid must be less than thatof seawater to allow a gradient for effective calcium transport via sea-water exchange and to explain deep-sea coral Me/Ca data. If calciumconcentrations are lower than that of seawater, then, by Eq. (3), alkalin-ity must also be lower than seawater. How then do corals elevate over-saturation and drive precipitation?

We offer several possible solutions to this problem. First, low alka-linity values can still result in elevated aragonite saturation if thedissolved inorganic carbon (DIC) of the calcifying fluid is also lowerthan seawater. Low DIC has the added advantage of building a gradi-ent for carbon transport, possibly interacting with hypothesized car-bon concentrating mechanisms (Bentov et al., 2009). Alternatively,alkalinity can be uncoupled from calcium through a number of differ-ent alkalinity pumping strategies, for example Na+–H+ exchange orK+–H+ exchange (Zeebe and Sanyal, 2002). Both these explanationsare plausible, but do not address the enriched [Ca2+] concentrationsof Al-Horani et al. (2003). If these micro-electrode data represent truecalcifying fluid values, we must rely on the batch model, where alka-linity pumping occurs before closed-system precipitation. In this sce-nario, only the initial calcifying fluid Me/Ca ratios are perturbed byalkalinity pumping.

In summary, both batch and steady-state seawater transportmodels are consistent with NanoSIMS profiles of cation dynamicsand can explain observed Me/Ca behavior. Differences betweenthese models exist during the postulated process of alkalinity pump-ing, where Ca2+–H+ exchange links calcium concentrations and al-kalinity in the steady-state model. This link between alkalinity andcalcium concentrations represents a general constraint on calcifyingfluid chemistry inherent to many biomineralization models.

5. Conclusion

Both calcein fluorescence and ion images were used to identifynew skeletal growth during a short coral culture experiment. Syn-chronous incorporation of calcium, strontium, barium and especiallyterbium across the new growth boundary suggests that: (1) thereis cation exchange between seawater and the calcifying fluid, and(2) these elements are influenced by similar transport mechanisms.It is unlikely that a selective and active transport mechanism, involv-ing separate transcellular pathways or different reservoir sizes, wouldact on all these elements similarly, especially considering the range ofsize, polarizability and charge they span. Thus our results are consis-tent with direct seawater transport to the site of calcification, a keyassumption of many geochemical biomineralization models (Adkinset al., 2003; Cohen et al., 2006; Gaetani and Cohen, 2006; Gagnon etal., 2007; McConnaughey, 1989a,b) that is also supported by recentbiological observations (Erez and Braun, 2007; Tambutte et al.,2011). Building upon our observations we develop models to predictskeletal Me/Ca ratios during calcification in the presence of seawaterexchange. These general models can explain Mg/Ca and Sr/Ca co-variability during coral biomineralization, providing a framework to un-derstand paleoproxy behavior.

Acknowledgments

NanoSIMS analysis was conducted using an instrument at the Cal-tech Center for Microanalysis which is supported in part by the Gordonand BettyMoore Foundation. The confocal laser-scanningmicroscope ishoused and maintained by the Caltech Biological Imaging Center. Thismanuscript benefited from constructive suggestions by two anonymousreviewers.

159A.C. Gagnon et al. / Earth and Planetary Science Letters 329-330 (2012) 150–161

Appendix A. NanoSIMS analysis

Appendix A.1. NanoSIMS image collection

NanoSIMS images are 20×20 μm with 128×128 pixels, unlessotherwise noted. As described below, beam size during analysis was∼800 nm at 5 pA using an oxygen primary beam. Dwell time at eachof the 128×128 pixels was between 0.015 and 0.1 s. Six or more se-quential image planes were collected in each location. The first fewplanes usually show uneven intensity maps due to incomplete pre-sputtering, as monitored using the unenriched isotope 42Ca. Laterplanes eventually become uneven due to charge accumulation. Onlythe subset of 2–4 planes that yield even and homogenous 42Ca+ ionintensity images were used.

The rawest data output by the NanoSIMS corresponds to the inte-ger number of counts collected at each pixel of each plane. Thesedata were processed offline using custom scripts in Matlab. At eachpixel, counts from all planes with homogenous 42Ca intensity werefirst summed. An averaging filter centered on each pixel was then ap-plied to the summed intensity image (5×5 pixel regions averaged forevery isotope except 87Sr and 88Sr where a 9×9 pixel region was useddue to low counts). Ratio images were then calculated from the aver-aged intensity data by referencing enriched isotopes like 43Ca to anunenriched isotope like 42Ca. The ratio at each pixel is simply theratio of the numerator isotope counts at that location divided by thedenominator isotope counts at that same pixel. Finally, instrumentalmass fractionation was corrected by referencing to natural abundanceregions within each image. The same correction was used throughouteach image, however, slightly different fractionation factorswere usedbetween different images due to differences in pre-sputter conditions.

Isotope ratio profiles were generated from raw image data to avoidartificial smoothing (an averaging filter was not applied). First thecompositional boundary was identified using a 43Ca/42Ca image. Aprofile was then taken perpendicular to this boundary in one pixelsteps. Using integer pixel steps eliminates interpolation and simplifieserror propagation.

Appendix A.2. Image derived isotope ratio histograms

The distribution of isotope ratios measured in an image can beplotted as a histogram (Fig. 4). Peaks in the histogram have a finitewidth. This width could represent analytical uncertainty in the mea-sured isotope ratios about a mean value, or this width could representa true range of isotope ratios present in the coral. To test if instrumen-tal uncertainty can explain histogram peak width, we modeled theeffect of Poisson distributed random noise (e.g. counting statisticslimited error) on a hypothetical image. Model histograms were gen-erated using a synthetic raw image split into two homogeneous andequal area regions. The two regions represent natural and enrichedisotope end-members, respectively. The boundary between thesetwo regions is assumed to be infinitely sharp (b1 pixel). Beam sizeis also assumed to be infinitely small (b1 pixel) to isolate the effectof analytical counting error from other parameters. To model the ef-fect of instrumental uncertainty on the histogram, the value of eachpixel was sampled from a Poisson distribution with a mean equalto the idealized pixel value. This idealized pixel value matches theaverage counts/pixel measured in either a natural abundance or anenriched region for a real NanoSIMS image. Image processing wasthen conducted on the synthetic data identical to that of a real Nano-SIMS image. The process was repeated 200 times to produce a meanmodeled histogram, where width is solely attributable to random in-strumental error. Minor differences in the mean ratio between themodel and the data simply result from uncertainty in the initialchoice of synthetic counts/pixel and have little effect on modeled his-togram width.

Appendix A.3. Primary beam spot size

To deconvolve themeasured signal from the primary beamwe firstestimated spot size under our experimental conditions. Using back-scattered SEM imageswe identified small inclusionswith abrupt com-positional boundaries in another CaCO3 sample on the same mount,Oka carbonatite. NanoSIMS images of these inclusions were used toconstruct profiles of a sharp compositional boundary. We assumethat this profile is a convolution of the Gaussian distributed primarybeamwith an abrupt compositional step-function. Under these condi-tions, the distance it takes for the measured profile to rise from 16%–84% equals the 2σ width of the primary beam (Senoner et al., 2005).Using this method we were able to demonstrate beam sizes as smallas ∼500 nm at 0.5 pA primary ion current; however, the smallestbeam size with a useful beam current was ∼800 nm at 5 pA. All imagespresented in this study were collected with an 800 nm spot size (2σwidth).

Appendix B. Relationship between multiple metal/calcium ratiosduring calcification with seawater exchange

If we imagine a semi-closed calcifying fluid (Fig. 7), then cation con-centrations are set by the balance between the precipitation rate (P=mol Ca m−2 s−1), the seawater exchange rate (k=ln(2)/τ1/2=s−1),and calcium pumping (F=mol Ca m−2 s−1). F is any form of calciumspecific transport, which may or may not be related to alkalinitypumping. The set of differential equations governing cation behaviorduring strontium co-precipitation are:

d Ca½ �Fluiddt

¼ − Pzρ

þ Fzρ

þ k Ca½ �SW−k Ca½ �Fluid;d Sr½ �Fluid

dt¼ − P

zρDSr

SrCa

� �Fluid

þ k Sr½ �SW−k Sr½ �Fluid;

using the effective partition coefficient:

DSr ¼SrCa

� �Coral

SrCa

� �Calcif ying Fluid

:

Assuming steady-state, then d[Ca]Fluid/dt=0,d[Sr]Fluid/dt=0, andthe above differential equations become:

Ca½ �Fluid ¼ Ca½ �SW− P−Fkzρ

ðB:1Þ

Pkzρ

DSrSrCa

� �Fluid

¼ Sr½ �SW− Sr½ �Fluid ¼ Sr½ �SW− Ca½ �FluidSrCa

� �Fluid

ðB:2Þ

Defining the dimensionless parameter γ as the relative proportionof pumping to precipitation, γ=F/P, Eq. (B.1) becomes:

Ca½ �Fluid ¼ Ca½ �SW− 1−γð ÞPkzρ

: ðB:3Þ

Since P and kzρ are positive quantities, γ determines the sign ofthe right most term in Eq. (B.3). If pumping is greater than precipita-tion rate, then F>P, γ>1, and [Ca]Fluid is elevated with respect to sea-water; alternatively, if PbF then γb1 and [Ca]Fluid is less thanseawater.

Back to the problem at hand, dividing Eq. (B.2) by (Sr/Ca)Fluid andsubstituting Eq. (B.3) yields

Pkzρ

DSr ¼ Sr½ �SWSrCa

� �−1

Fluid− Ca½ �SW þ P 1−γð Þ

kzρ:

160 A.C. Gagnon et al. / Earth and Planetary Science Letters 329-330 (2012) 150–161

Dividing by [Ca]SW and solving for P/kzρ[Ca]SW,

DSr−1þ γð Þ Pkzρ Ca½ �SW

¼ SrCa

� �SW

SrCa

� �−1

Fluid−1:

� �

Finally, we define (Sr/Ca)o as the composition of the skeleton thatwould be directly precipitated from seawater, (Sr/Ca)o=DSr(Sr/Ca)SW,thus,

SrCa

� �SW

SrCa

� �−1

Fluid¼ DSr

DSr

SrCa

� �SW

SrCa

� �−1

Fluid¼ Sr

Ca

� �o

SrCa

� �−1

Coral:

This simplification yields an expression relating the skeletal Sr/Caratio precipitated at any instant to the flux balance and the partitioncoefficient,

SrCa

� �Coral

¼ SrCa

� �o

DSr−1þ γð Þ Pkzρ Ca½ �SW

þ 1� �−1

: ðB:4Þ

The flux parameters are isolated to one side of the equation,

Pkzρ Ca½ �SW

¼ 1DSr−1þ γ

SrCa

� �o

SrCa

� �−1

Coral−1

� �: ðB:5Þ

An analogous set of equations can be solved to determine Mg/Cabehavior,

Pkzρ Ca½ �SW

¼ 1DMg−1þ γ

MgCa

� �o

MgCa

� �−1

Coral−1

� �: ðB:6Þ

Combining Eqs. (B.5) and (B.6) to eliminate P/kzρ[Ca]SW and sim-plification yields a general expression relating Sr/Ca and Mg/Ca ratiosduring precipitation from a semi-closed calcifying fluid at steady-state and in exchange with seawater.

SrCa

� �−1¼ DSr−1þ γ

DMg−1þ γ

" #Mg=Cað ÞoSr=Cað Þo

� �MgCa

� �−1

þ SrCa

� �−1

o1− DSr−1þ γ

DMg−1þ γ

" #:

ðB:7Þ

Appendix B.1. Negligible pumping scenario (γ=0)

In the absence of calcium pumping, Eq. (B.7) becomes

SrCa

� �−1¼ DSr−1

DMg−1

" #Mg=Cað ÞoSr=Cað Þo

� �MgCa

� �−1

þ SrCa

� �−1

o1− DSr−1

DMg−1

" #:

ðB:8Þ

Eq. (B.8) predicts a linear relationship between skeletal (Sr/Ca)−1

and (Mg/Ca)−1. The slope of this relationship is completely depen-dent on the partition coefficients and seawater metal/calcium ratios,which implies a constant slope at a given temperature for long seawa-ter residence time ratios like Sr/Ca and Mg/Ca. Movement along thisline is controlled by differences in the balance between precipitationrate and seawater transport.

Appendix B.2. Appreciable pumping Scenario (γ>0)

Calcification with pumping can be thought of as a more generalcase of the above scenario. In a (Sr/Ca)−1 vs (Mg/Ca)−1 plot, each γvalue contours as a straight line, where the slope eventually con-verges towards 1 if γ becomes very large. Changing γ results in move-ment between these contours.

Appendix C. Supplementary data

Supplementary data to this article can be found online at doi:10.1016/j.epsl.2012.03.005.

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