Reproducibility of trace element profiles in a specimen of the deep-water bamboo coral Keratoisis sp.

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Geochimica et Cosmochimica Acta 75 (2011) 5101–5121 www.elsevier.com/locate/gca

Reproducibility of trace element profiles in a specimen of the deep-water bamboo coral Keratoisis sp. Daniel J. Sinclair a,⇑,1, B. Williams a,2, G. Allard a, B. Ghaleb a, S. Fallon b, S.W. Ross c, M. Risk d a

GEOTOP, Universite´ du Que´bec a` Montre´al, C.P. 8888 Succ. Centre-Ville, Montre´al, Que., Canada H3C 3P8 b Research School of Earth Sciences, The Australian National University, Canberra, ACT 0200, Australia c University of North Carolina – Wilmington, Center for Marine Science, 5600 Marvin Moss Ln., Wilmington, NC 28409, USA d School of Geography and Geology, McMaster University, Hamilton, ON, Canada Received 3 December 2010; accepted in revised form 22 April 2011; available online 18 May 2011

Abstract Bamboo corals (Order Gorgonacea, Family Isididae) are attractive prospects for deep-sea paleoceanographic reconstruction, capturing trace elements in their calcitic skeletons that may serve as environmental proxies with subdecadal resolution over multi-century timescales. We study the reproducibility and fidelity of trace-element profiles (Ba, Mg, Sr, Mn, U, Pb) in a 420-year-old specimen of the bamboo coral Keratoisis sp. from the SE USA. Using laser-ablation ICP-MS to obtain multiple replicate profiles, we use spectral techniques to distinguish noise and irreproducible variations from fully reproducible geochemical fluctuations that are candidates for environmental signals. By quantifying variability between profiles, we assess the fidelity with which the corals potentially record environmental information. Barium is the most reproducible element in the skeleton, with large fluctuations along different growth radii reproducing to within 4%. Both Mg and Sr have very uniform levels within the coral, but display low-amplitude irreproducible variations that might represent an internal biological process. In the case of Mg, which has been proposed as a paleotemperature proxy, this irreproducibility would represent an intrinsic uncertainty of ±0.1 to 0.4 °C. Both Mn and Pb contain some irreproducibility superimposed upon broad reproducible profiles that may be environmental signals. Some of the irreproducible Pb fluctuations correlate with cracks and dark bands in the sample suggesting detrital or surface contamination. Uranium displays large amplitude variations which are not reproducible along different radii. This suggests that uranium cannot be used for paleoenvironmental reconstruction, and may show signs of early diagenesis – a possibility that could complicate attempts to date young Keratoisis sp. samples by U-series geochemistry. The highly reproducible Ba signal allows precise alignment of profiles and thus we can show that growth rate along one radius can vary by a factor of two relative to growth along a different radius. There is no evidence that this large variation in relative growth rate affects either the Mg or Sr incorporation. In addition, geochemical anomalies in Ba and Mg indicate that the very central axis of the specimen may represent a different mode of growth. This study suggests that Keratoisis sp. corals are imperfect recorders of geochemical information, but do contain reproducible variations which are good candidates for environmental signals. Ó 2011 Elsevier Ltd. All rights reserved.

⇑ Corresponding author. Present address: Institute for Coastal and Marine Sciences, Rutgers University, 71 Dudley Road, New Brunswick,

NJ 08901, USA. Tel.: +1 732 932 6555x234. E-mail address: [email protected] (D.J. Sinclair). 1 Former affiliations: Jackson School of Geosciences, Institute for Geophysics, University of Texas in Austin, J.J. Pickle Research Campus, Bldg. 196, 10100 Burnet Road (R2200), Austin, TX 78758-4445, USA and Scottish Alliance for Geosciences Environment and Society, UK. 2 Present address: Department of Chemical and Physical Sciences, University of Toronto, Mississauga, ON, Canada L5L 1C6. 0016-7037/$ - see front matter Ó 2011 Elsevier Ltd. All rights reserved. doi:10.1016/j.gca.2011.05.012

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D.J. Sinclair et al. / Geochimica et Cosmochimica Acta 75 (2011) 5101–5121

1. INTRODUCTION With the awareness that human induced climate change could potentially affect oceanic circulation (e.g. Stocker and Schmittner, 1997), there is a growing interest in natural archives which can provide information about the deep-ocean on decadal timescales, allowing anthropogenic changes to be resolved from natural variability. Sediment cores are the most widely used archives of the deep-ocean, but rarely record information at decadal resolution due to slow accumulation and bioturbation. Slow growing deep-sea corals show great promise as high-resolution deep ocean archives: they are long lived (Druffel et al., 1990, 1995; Roark et al., 2006, 2009; Sherwood and Risk, 2007), are found in a broad depth and geographic range (Freiwald et al., 2004), and their organic/carbonaceous skeletons can be used for U-series and 14C dating (Smith et al., 1997; Adkins et al., 1998; Risk et al., 2002; Sa´nchez et al., 2004; Andrews et al., 2005, 2009; Pons-Branchu et al., 2005; Roark et al., 2005, 2006; Tracey et al., 2005, 2007; Noe´ and Dullo, 2006; Thresher et al., 2009). Bamboo corals are attractive prospects for paleoceanographic reconstruction. Their trunks grow radially by between 33 and 300 lm/year (Sa´nchez et al., 2004; Thresher et al., 2004, 2009; Roark et al., 2005; Noe´ and Dullo, 2006; Andrews et al., 2009; Sherwood and Edinger, 2009; Sherwood et al., 2009; Thresher, 2009), and individuals can live for centuries (Thresher et al., 2004). Most importantly, the internodes are primarily calcite and lack the alternating organic layers that make analysing and interpreting the skeletons of Primnoidae coral skeletons more complex (Bond et al., 2005; Sherwood et al., 2005b; Williams et al., 2007). Trace element inclusions in the calcite are beginning to find application as decadal-resolution paleoceanographic tracers (Hill et al., 2005; Roark et al., 2005; Sherwood et al., 2009; Thresher, 2009; Thresher et al., 2009, 2010). Any new geochemical archive, however, needs to be tested to demonstrate the fidelity of its chemical records. Only then can environmental interpretations can be made with confidence. Biological proxies should especially be treated with caution: recent studies of vital effects in tropical and deep-sea scleractinian corals (Sinclair, 2005; Sinclair and Risk, 2006; Sinclair et al., 2006) demonstrate that they have the potential to be disrupted by endogenous/physiological processes and are thus imperfect recorders of environmental information. At the most fundamental level, any geochemical profile that cannot be reproduced within a sample cannot contain environmentally interpretable information. There exists the potential for profiles to be partially reproducible, containing environmental information that is overwritten by biological or other non-environmental fluctuations (Sinclair et al., 2005). Quantifying the relative amplitude and timescales of reproducible and irreproducible variations allows us to rigorously calculate how precisely environmental signals could be resolved and the spatial (hence temporal) resolution at which information can be interpreted. Continuous-scan laser-ablation ICP-MS (e.g. Sinclair et al., 1998) is an ideal technique for analysis of slow-grow-

ing corals. It allows data to be collected at subdecadal resolution and analysis is rapid, facilitating replication of geochemical profiles for reproducibility testing. Sinclair et al. (2005) presented analytical and numerical strategies for quantifying optimal analytical resolution and testing the fidelity of deep-coral specimens. That study uncovered evidence for non-reproducible variations in Mg/Ca (a temperature proxy) in the deep-sea gorgonian Primnoa resedaeformis which potentially constrains the precision with which temperature can be reconstructed. These methods were applied to a bamboo coral (Allard et al., 2005), providing preliminary evidence that similar variability exists in this genus. Others have applied similar methods and concluded that both environmental and endogenous biological factors can influence geochemical records in bamboo corals (Thresher et al., 2007; Thresher, 2009). Here we present LA-ICP-MS analysis of a suite of trace elements (Ba, Mg, Sr, Mn, U, Pb) in a live-sampled 420year-old specimen of the bamboo coral Keratoisis sp. from the Jacksonville Lithoherms (SE USA). In this paper we focus specifically on testing the fidelity of trace element profiles. We apply the methodology described in Sinclair et al. (2005) to quantify reproducibility in the specimen and discuss the limitations that non-reproducible variations might impose upon environmental records. We explore the possible environmental factors affecting each element, but we do not present detailed interpretations of the geochemical profiles here. A thorough investigation of the correlation between our geochemical profiles and candidate environmental records will be presented in another paper. We also describe in detail the laser-ablation ICP-MS methodology, and critically review the performance of our technique based on a compilation of 4 years analytical statistics. A rigorous mathematical treatment of the numerical analysis methodology is presented in Supporting Online Material. 2. SAMPLES AND METHODOLOGY

2.1. Sample collection The bamboo coral used in this study was collected live from the Jacksonville Lithoherms (30°30.9740 N; 79°39.7250 W) at a depth of 549 m on 10 June 2004 (JSL dive 4683). The sample was recovered using the Johnson-Sea-Link (JSL, Harbor Branch Oceanographic Institute) submersible as part of a larger study of deep coral habitats on the southeastern US slope. On the basis of the branching pattern (branching from calcitic internodes) the sample is identified as Keratoisis sp. following the classification scheme of Bayer (1981). No soft tissue was preserved for this specimen, and gross skeletal morphology alone is insufficient for a species-level identification. 2.2.

210

Pb and

14

C dating

210 Pb was measured in four milled powder subsamples of the coral taken from a slab cut parallel to the section analysed by LAICP-MS (Section 2.3). Approximately 10–20 mg samples were dissolved after the addition of a 3 dpm 209Po spike, and Po was plated onto silver discs. 210Po (in secular equilibrium with 210Pb) and 209Po activities were measured by alpha counting on an EGGORTIC 476 in the Radioisotope Geochemistry Lab at GEOTOP

Reproducibility of trace element profiles in a bamboo coral (Universite´ du Que´bec a` Montreal). 14C was measured in a series of five subsamples (10 mg each) taken from layers estimated to predate the bomb 14C spike. Radiocarbon measurements were carried out at the Australian National University Single Stage Accelerator Mass Spectrometer facility. Calcite samples were reacted in individual chambers, evacuated, and acidified with orthophosphoric acid at 90 °C to evolve CO2 (Guilderson et al., 1998). The CO2 was purified, trapped and converted to graphite using an iron catalyst in the presence of hydrogen as described in Vogel et al. (1987). The graphite targets were analysed at the Australian National University Radiocarbon Laboratory on a NEC Single Stage Accelerator Mass Spectrometer (Fallon et al., 2010). Radiocarbon calculations include d13C correction for isotope fractionation and a blank subtraction based on 14C-free calcite followed by age conversion following the conventions of Stuiver and Polach (1977). 2.3. Laser ablation ICP-MS A 100 lm polished thin section was prepared from an internode near the base of the bamboo coral specimen. This was analysed by LA-ICP-MS at McGill University (Montreal, Canada) on a NewWave UP-213 Laser Ablation System (with the standard box ablation cell) coupled to a Perkin-Elmer/SCIEX ELAN 6100 DRCplus ICP-MS. Platinum-coated cones were used in the ICPMS. The sample was ablated in He (flow rate of 800 cc/min) and mixed with Ar downstream of the sample cell. The beam energy was held at 80% for an average energy density on the sample of around 9 mJ/cm2 for a 60 lm diameter spot and 7.5 mJ/cm2 for an 80 lm diameter spot. Each laser track was pre-ablated with an 80 lm diameter laser spot at a rep-rate of 50 Hz scanning at 100 lm/s. The analytical pass was conducted with a 60 lm diameter spot with the laser pulsing at 10 Hz and scanning at 10 lm/s. Laser tracks spanned the centre to the outside of the section – a distance of approximately 14 mm. Data were collected in time-resolved mode with one data point being recorded every 1.1 s, giving a spatial resolution of 11 lm/data point. The washout time of the ablation cell was approximately 5 s for an order of magnitude decay in signal. Three different radial traverses (labelled Tracks 1–3) were analysed to compare the overall compositional homogeneity within the sample (Fig. 1). Within each radial traverse, 2 or 3 closely spaced (100 lm) parallel tracks were run to verify the reproducibility of the method giving a total of 7 profiles, labelled 1a, 1b, 1c, 2a, 2b, 3a and 3c. (Due to an alignment error, Track 3b was

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aborted prior to data collection.) The isotopes monitored were 25 Mg, 43Ca, 55Mn, 87Sr, 138Ba, 208Pb and 238U. All element data were background subtracted and normalised to 43Ca to correct for variations in ablation efficiency. TE/Ca ratios were later converted into concentrations (weight ratios) assuming a constant Ca concentration of 37 wt%. Three standards were analysed at the end of the LA-ICP-MS run of the bamboo coral: the synthetic glasses NIST 610 and NIST 612 and a pressed-powder pellet made from MACS-1 synthetic carbonate. Two additional standards (for which no concentration numbers are presently available) were run as reproducibility/drift checks. These were MACS-2 (synthetic carbonate) and an in-house pressed-powder standard (‘PP’) made by re-precipitating a solution of dissolved aragonitic deep-water coral (Lophelia pertusa) which had been spiked with a suite of trace elements. Each standard was analysed by line-scan (Sinclair et al., 1998, 2005), with data collected in time resolved mode and processed by hand. Standard analyses typically consisted of around 60 data points, which were averaged to produce a single value. Coral data were calibrated against NIST 610 because this standard produced the largest and most stable signals for most of the masses monitored. The exception is 87Sr which was calibrated using MACS-1 to avoid an 87Rb interference in the NIST glasses. 2.4. Solution ICP-MS Trace elements in the Keratoisis sample were independently measured by solution ICP-MS. The polished slab was rigorously cleaned with Micro surfactant and 18 MX water and four 5 mg powder subsamples were taken. Powders were dissolved in duplicate using 2% quartz-distiled HNO3 and analysed at 2000 dilution on an Agilent 7500ce Quadrupole ICP-MS at the University of Texas at Austin. Solutions were calibrated using a dilution series of gravimetric standards, and checked against solutions of NIST 1646, 1643e and an in-house standard made from a speleothem. For comparison of trace element concentrations, 15 subsamples of a specimen of P. resedaeformis from the Grand Banks (Newfoundland) were also analysed for trace elements by solution ICPMS as described in Sinclair et al. (2005).

3. ANALYTICAL STATISTICS

3.1. Detection limits All of the laser-ablation signals were clearly resolved above background (Table 1). The least resolved signal was that for Mn, with a signal/background ratio of 1.9 and a concentration/detection-limit (C/DL) ratio of 1.2. Signal smoothing increases the C/ p DL ratio by a factor of n, where n is the width of the windowed average used. For example, the optimally-smoothed Mn signal (see Section 4.4) has a C/DL of 5.0. Detection limits for the unsmoothed signals (Table 1) are in the low ppm to low ppb range; reflecting very low background count rates in the ICP-MS. The high DL for Ca (300 ppm) is due to the fact that we are monitoring a minor isotope of this element (43Ca). 3.2. Within-run reproducibility

Fig. 1. Replicate LA-ICP-MS tracks on the specimen of Keratoisis. Seven laser-ablation ICP-MS profiles were run along three different radial tracks in the Keratoisis thin section. Track 1 consists of three profiles, separated by an average of 100 lm. Tracks 2 and 3 consist of two profiles each.

Standards were measured once at the end of each LA-ICP-MS track. In the past, it has been necessary to bracket analytical runs with standards to correct for in-run drift (Sinclair et al., 1998). However, the LA-ICP-MS system used in this study is very stable and reproducible within a run (as demonstrated by the very reproducible average concentrations shown in the trace element

0.02 200 1 0.009 0.004

All uncertainties listed as 1 SD. This includes real variations in the signal. A better estimate of inherent noise is listed in Table 7. p c Calculated as the concentration equivalent of 3 the standard deviation of the background. Note: Detection limits decrease with smoothing by a factor of n, where n is the size of the smoothing window. d An average concentration for all runs, calculated assuming Ca = 37 wt%. e An average of the long term reproducibility listed in Table 4. Note that this is a minimum uncertainty, and does not include any constant offset factors that might apply. f Completely independent estimate made from multiple drill subsamples of the coral slab from which the thin section was made. g There were 8 subsamples. Mg and Ca concentrations were estimated using two different isotopes. Of the 8 subsamples, one was clearly contaminated with respect to minor elements and was excluded from the estimates for Mn, Pb and U. Two of the U estimates were below detection limits.

a

b

18,400 355,000 0.49 2310 14 0.07 0.05 6200 1200 1.2 2200 200 1.6 6 57,000 2800 1.9 12,000 2200 13 47 17,000 370,000 0.39 2800 12 0.055 0.033 0.1 3 4 1 0.2 0.1 0.2 Mg25 Ca43 Mn55 Sr87 Ba138 Pb208 U238

0.4 2 2 3 1 0.4 0.4

7100 7900 8 8400 470 2 8

700 700 4 800 80 1 4

3 300 0.3 1 0.1 0.03 0.005

1300

Conc. measured by solution ICP-MSf (ppm) Conc./ DL Signal/ BG Calibration uncertaintya,e (ppm) Conc.d (ppm) Detection limitc (ppm) Signal SDb (counts/pt) Signal (BG subtracted) (counts/pt) BG SDa (counts/pt) BG (counts/ pt) Element

Table 1 Statistics for coral analysis by laser-ablation ICP-MS and solution ICP-MS.

600 (n = 16) 8000 (n = 16) 0.07 (n = 7) 50 (n = 8) 4 (n = 8) 0.04 (n = 7) 0.03 (n = 5)

D.J. Sinclair et al. / Geochimica et Cosmochimica Acta 75 (2011) 5101–5121 Solution ICPMS SDg (ppm)

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profiles – see Section 5.3). A minor (<5%) progressive decrease in the Mg/Ca ratio of one analytical track was present, suggesting that a small degree of instrumental drift can potentially occur throughout the course of a day. However, such drift was not present for any of the other trace-elements and within a day analytical tracks were reproducible within 2% (Table 2). 3.3. Day to day reproducibility, calibration and accuracy Day-to-day ‘external’ reproducibility for the LA-ICP-MS was quantified by comparing intensity ratios of the ‘unknown’ standards (PP and MACS-2) with ‘known’ standards (NIST 610, NIST 612 and MACS-1) (Table 3). Replicate values of (TE/Ca)unknown measured/(TE/Ca)standard measured from several years of LA-ICP-MS measurement have been summarised in Table 2 (columns 1–6). Day-to-day reproducibility was significantly poorer than withinrun reproducibility, ranging from around 5% RSD (Mn), to >17% RSD (Ba, Pb, U) (Table 2). Calibration factors ((TE/Ca)known/(TE/Ca)measured) can be determined from each measurement of a ‘known’ standard. For different standards measured together in a ‘set’ (i.e. run one after another), these values would ideally be identical. In practice the numbers do not agree perfectly due to a combination of matrixeffects and uncertainty in the ‘known’ TE/Ca in each standard. Table 4 quantifies the %-agreement between the calibration factors for NIST 610, NIST 612 and MACS-1 (calculated for each set as the difference from the average divided by the average). The average difference between calibration factors from one day to the next is 10–15%, and can differ by up to 40% (Table 4). To test the overall accuracy of the calibration, LA-ICP-MS estimates were compared with the replicate measurements of the Keratoisis sample by solution ICP-MS. Despite the poor reproducibility for LA-ICP-MS, the solution and laser results agree within experimental uncertainty indicating that there is no systematic bias in the LA-ICP-MS calibration (Table 1). The exception is Sr which appears to be slightly overestimated in the LAICP-MS analyses.

4. RESULTS AND DATA PROCESSING 4.1. Bulk composition and comparison with other calcitic organisms Average values of trace-elements in isidid corals, other gorgonian corals, and foraminiferal calcite are compared in Table 5. Magnesium comprises around 1.7 wt% (7 mol%) of the skeleton, classifying the mineral as magnesian calcite. This concentration is similar to other bamboo corals. Our Sr content is lower than the bamboo coral measured by Roark et al. (2005), but falls within the range of values presented by Thresher et al. (2007, 2009, 2010). These are the first reported concentrations of Mn, Ba, Pb and U in bamboo corals. Despite a lack of external validation, we are confident in our trace-element concentrations because of the general agreement between the independent solution and laser-ablation ICP-MS measurements (Table 1). Other gorgonian corals contain similar Mg, Sr and Pb concentrations (Table 5). There are no published values for Ba, Mn or U in other gorgonian corals, so we compare our bamboo specimen with solution ICP-MS measurements of a sample of P. resedaeformis (Table 5). Barium concentrations are similar, but our Mn and U concentrations are

Reproducibility of trace element profiles in a bamboo coral

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Table 2 Reproducibility of ‘unknown’ standards (PP and MACS-2) calculated relative to ‘known’ standards. Unknown standard Element Mg/Ca Mn/Ca Sr/Ca Ba/Ca Pb/Ca U/Ca

a PP NIST 610

MACS-2 b NIST 610

Rep.c (%)

nd

Rep. (%)

7 5 9 17 17 18

10 9 9 11 11 9

–e 3 3 8 8 7

PP NIST 612

n

8 8 8 8 7

MACS-2 NIST 612

Rep. (%)

n

Rep. (%)

5 5 10 14 17 14

10 9 9 11 11 6

–e 6 9 8 11 9

PP MACS-1

n

8 8 8 8 6

MACS-2 MACS-1

Rep. (%)

n

Rep. (%)

9 2 7 8 23 –f

10 7 7 5 5

–e 5 5 7 12 –f

Average difference between paired runsg (%) n

6 6 3 3

1.2 2.1 0.2 0.3 1.4 0.8

a

PP = pressed powder standard. MACS-2 is treated as an unknown in his case, since there are no published numbers for this standard. c Reproducibility is expressed as 1 RSD in (TE/Ca)unknown + (TE/Ca)standard. d Ratios were excluded if there was no pairing with a suitable standard, or if the raw data showed any signs of anomalous behaviour: e.g. heterogeneity, low counts, no signal above background, or indications of drift in the data. e Mg in MACS-2 is highly variable. f U is below detection in MACS-1. g Calculated as follows: (run1  run2)  1/2(run1 + run2), where run1 and run2 are closely spaced replicate analyses of the Keratoisis sample. b

Table 3 Element concentrations in standards. Element

MACS-1 Concentration (ppm)

Mg Ca Mn Sr Ba Pb U a b c d e f g

10 393,000 126 249 130 115 0.006

NIST 612 Error

Ref.

1

a b

2 1 1 1 0.001

c c c c c

NIST 610

Concentration (ppm) 77 85,120 38 76 38 39 37

Error

Ref.

Concentration (ppm)

Error

Ref.

30 1570 1 2 1 2 1

d

465 84,527 433 497 424 413 457

27 1705 32 18 29 15 14

f

e d d d d d

g f f f f f

Lo-Yat et al. (2005). Recommended value Lo-Yat et al. (2005). Munksgaard et al. (2004) LA-ICP-MS calibrated against NIST 612. Pearce et al. (1997), Table 9. Pearce et al. (1997), Table 2 (oxides). Pearce et al. (1997), Table 8. Pearce et al. (1997), Table 1 (oxides).

lower. Foraminifera build skeletons of low-Mg calcite (average Mg content of 0.02–0.3 wt%), and this distinct crystal form may explain the very different affinity for trace elements (Table 5). Foraminiferal calcite is thus a poor analogue for the calcite of bamboo corals. We predict the same for bivalves which manipulate their extrapallial fluid to produce low-Mg calcite skeletons (Lorens and Bender, 1980). Our Mg values are closer to the concentrations found in echinoderm spicules (between 5 and 7 mol% – Dickson, 2004) which are also high-Mg calcite. Unfortunately, no other trace element data are available for echinoderms so further comparison is not possible. 4.2. Sample age and growth rate Growth rates were estimated by fitting a decay profile to the 210Pb data (Fig. 2a) and a linear fit to the

uncorrected 14C ages (Fig. 2b). The two independent growth-rate estimates were 50 ± 35 and 33 ± 19 lm/year, respectively (95% CIs). These estimates agree within error, but are imprecise because of measurement uncertainty and depletion of unsupported 210Pb in the oldest samples. Since the sample was alive when collected (June 2004), a more precise average growth rate can be determined by correcting 14C ages for the marine reservoir age and fitting a straight line growth rate through 0. To estimate the reservoir age, we extrapolated the deep (pre-bomb) 14C region of the North Atlantic GEOSECS profile (Stuiver et al., 1981) to 550 m to obtain a D14C of between 65& and 73&. Alternatively, the pre-bomb surface Atlantic measurements of Broecker et al. (1960) can be combined with ¨ stlund and Rooth (1990) to provide the depth profiles of O an estimate of 53& to 62& at 550 m. We therefore

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Table 4 Agreement between standards. Element

Difference between calibration factorsa (this run) (%)

Average difference between calibration factors (all analyses) (%)

Maximum difference between calibration factors (all analyses) (%)

Standards comparedb

Number of comparisons (all analyses)

Mg/Ca Mn/Ca Sr/Ca Ba/Ca Pb/Ca U/Ca

0.8 12 n/ac 27 17 7

9 11 n/ac 13 17 13

17 21 n/ac 37 37 27

(1), (2)d (1), (2), (3)

8 11

(1), (2), (3) (1), (2), (3) (2), (3)e

11 11 9

a Calibration factors were calculated for MACS-1, NIST 610 and NIST 612 using the numbers presented in Table 5. The difference between the largest and smallest of the calibration factors is presented here as a % of the average calibration factor. b (1) = MACS-1, (2) = NIST 610, (3) = NIST 612. c Only MACS-1 Sr/Ca analysis could be used because NIST analyses suffer from a 87Rb interference. No range could therefore be calculated. d NIST 612 was excluded because it has a poorly constrained Mg concentration. e MACS-1 was excluded because it has a very low U concentration.

Table 5 Trace element analyses in selected biogenic calcites. Element

Isididae corals

Other gorgonian corals (all concentrations in ppm)

Foraminiferal calcite

Mg

17,000 ± 1300a 15,700–20,800b 14,000–20,000c

200–3000m,n

Ca Mn Sr

370,000a 0.39 ± 0.02a 2800 ± 200a 2300–2700c 4400d

Ba Pb

12 ± 1a 0.055 ± 0.009a

U

0.033 ± 0.004a

15,500–19,000e 24,000–30,000f 14,000–22,000g 19,000–26,000i 14,000–40,000j 32,000–76,000k 300,000–360,000e 3–6e 2200–2500e 1000–2900f 1000–2000g 2500h 1600–2800k 7–8e 0.06–0.09e 0.048–0.286l 0.11–0.13e

a b c d e f g h i j k l m n o p q r s

0.56–11.53n,o,p 800–1200m

0.8–2.9o,q,r

0.013–0.020n,s

This study. Thresher et al. (2004). Thresher et al. (2007). Roark et al. (2005). Solution ICP-MS analysis of Primnoa resedaeformis – this study. Weinbauer et al. (2000) Corallium rubrum. Weinbauer and Velimirov (1995) various Mediterranean gorgonians. Heikoop et al. (2002) Primnoa resedaeformis. Sherwood et al. (2005a,b) Primnoa resedaeformis. Macintyre et al. (2000) various gorgonians. Bond et al. (2005) Plexurella dichotomata. Sherwood et al. (2006), Ph.D. thesis, Primnoa resedaeformis. Delaney (1985) various foraminifera. Russell et al. (1994) various foraminifera. Boyle (1981) various foraminifera. Boyle (1983) various foraminifera. Lea and Boyle (1991) various planktonic foraminifera. Hall and Chan (2004) various foraminifera. Russell et al. (2004) various foraminifera.

adopt a 14C value of 64 ± 9& which constrains the reservoir correction to be between 450 and 610 years (average

530 years). Using this range of reservoir ages, a line fitted through 0 years at the outside of the specimen constrains

Reproducibility of trace element profiles in a bamboo coral

(a)

210

Measured Pb Fitted Decay Curve 14 Range from C Dating

0.40

Best Fit 0.050 ± 0.035 µm/yr

0.35

0.30

0.25

210

Pb Concentration (arbitrary units)

0.45

5107

0.20 14

Constraint from C 0.033 ± 0.010 µm/yr 0

2

4

6

8

10

12

14

Distance from Outside Edge (mm) 14

14

C age corrected for reservoir age = 450 y C age corrected for reservoir age = 610 y C age corrected for reservoir age = 530 y

Uncalibrated C Age

14

Linear Fit (+ 95% CI)

900

500

Growth Rate from Linear Fit: 33 ± 19 µm/y

400

800 Minimum Growth Rate: 24 µm/y

300

Sampled in June 2004

700

200 Average Growth Rate: 33 µm/y

100 600

Maximum Growth Rate: 43 µm/y

(b) 0

2

4

6

8

10

12

Distance from Outside Edge (mm)

0

2

4

6

8

(c) 10

12

Radiocarbon Age (calibrated ybp)

Radiocarbon Age (uncalibrated ybp)

14

0 14

Distance from Outside Edge (mm)

Fig. 2. Growth rate estimation. (a) The growth rate of the Keratoisis sample was estimated by fitting an exponential decay curve with a halflife of 22.3 years to 4 measured 210Pb values. The vertical grey boxes indicate the width of samples taken for the 210Pb measurement. The shaded range represents the growth rates constrained by 14C measurements (see 1c). (b) 14C ages (uncorrected for reservoir age) are graphed against distance. Fitting a linear trend results in growth rates for this specimen of 30 ± 19 years. (c) 14C measurements (corrected for reservoir ages) plotted against distance. The filled triangles are the data corrected for the lower bound reservoir age of 450 years. The open circles are the data corrected for the upper bound reservoir age of 610 years. The point at 0 mm has an assumed age of 0 years as the specimen was alive when sampled. The shaded region represents the upper and lower bound growth rates, with the dark line representing the best estimate of 33 ± 10 lm/year.

the growth rate to between 24 and 43 lm/year (Fig. 2c), with a middle-bound estimate of 33 ± 10 lm/year. Thus the specimen is therefore between 330 and 580 years old (average 420 years). We are unable to resolve any significant non-linearity in average growth rate due to the few and uncertain 14C and 210 Pb data. Within the constraints of our ages, growth rate could have changed by up to a factor of 3 from the outside to inside of the specimen. Non-linearity in growth could be identified/corrected by counting periodic bands which have been reported for bamboo corals (Sa´nchez et al., 2004; Thresher et al., 2004; Roark et al., 2005). In our specimen,

however, banding was irregular and frequently ambiguous, preventing this approach. 4.3. Spatial calibration and relative growth rates Trace element profiles for the different tracks are presented in Fig. 3a–g, respectively. Tracks were first aligned (to the spatial scale of Track 1a) by matching visual bands on a photograph of the Keratoisis thin section (Fig. 1). Barium profiles were found to be remarkably reproducible and alignment was fine-tuned (precise to ±40 lm) by matching Ba peaks and troughs between tracks (Fig. 3a).

D.J. Sinclair et al. / Geochimica et Cosmochimica Acta 75 (2011) 5101–5121

Ba Concentration (ppm)

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Data smoothed with a 4 point running average

a)

30

Ba

25 20 15

Mg Concentration (wt%)

10 Data smoothed with a 16 point running average

2.0 1.5 1.0

Track 1 Track 2 Track 3

Mg

0.5

b)

Mg Concentration (wt%)

0.0

Mg (detail)

2.2 2.1 2.0 1.9 1.8 1.7

c)

Sr Concentration (wt%)

1.6 Data smoothed with a 128 point running average

d)

0.290

0.285

0.280

Sr

Pb Concentration (ppm)

0.275 Data smoothed with a 64 point running average

0.14

e)

Pb

0.12 0.10 0.08 0.06 0.04 0.02

Peak in Pb = ~1950 - 1965

U Concentration (ppm)

0.00

U

0.14

Data smoothed with a 16 point running average

f)

0.12 0.10 0.08 0.06 0.04

Mn Concentration (ppm)

0.02 0.8

Data smoothed with a 16 point running average

g)

Mn

0.6

0.4

0.2 2000

1900

1800

1700

1600

Year

Fig. 3. Trace element profiles. Laser ablation ICP-MS tracks for all elements are presented here interpolated to the spatial scale of Track 1. Distance/time conversion uses a linear growth rate of 33 lm/year. (a) Ba profiles are highly reproducible, and allow very precise alignment of the different tracks. Note: The central core of the coral (right) is characterised by very high Ba concentrations, suggesting a different geochemistry. (b) Mg values are very stable across the specimen except at the central core of the coral (right) which is characterised by very high Mg concentrations, suggesting a different geochemistry. (c) The same data on an expanded scale. Note that in this part of the figure, the profiles for Tracks 1 and 2 have been offset from Track 3 by 0.3 and 0.15 wt%, respectively. Profiles along the same track show reproducibility that is not shared with profiles from different tracks. (d) Sr profiles. Note the y-axis scale is very narrow. The Sr profiles are very uniform and do not vary more than 1.5%. (e) Pb profiles all show an increasing trend from old (right) to young (left). (f) U profiles. Note: For clarity, the profiles for Tracks 1 and 2 have been offset from Track 3 by 0.03 and 0.06 ppm, respectively. While profiles along the same track are very reproducible, there is essentially no reproducibility between the different radial tracks. (g) Mn profiles show a broad peak in the mid-1700s which is reproducible in all tracks. Some of the fine-detail is also reproducible. Note that the very outside edge of the coral contains very high Mn, possibly due to oxide coatings on the outside of the specimen.

Growth Rate / Growth Rate for Track 1a

Reproducibility of trace element profiles in a bamboo coral

2.0

Track 1 Track 2 Track 3

1.5

1.0

0.5 2

4

6

8

10

12

Distance from outside of coral (mm on track 1a) Fig. 4. Relative growth rates along different radial tracks. Growth rates, relative to Track 1a, have been calculated from the interpolated x-scales of Tracks 1b, 1c, 2a, 2b, 3a and 3c. The profiles presented here have been averaged for each track and smoothed with a 3 point box-filter. These profiles demonstrate that growth rates are not linear along all radial tracks, but can vary by up to a factor of 2 from one radial path to the next. Note that these growth-rate profiles do not include any non-linearity that might also exist in Track 1a.

The ability to accurately align the different radial tracks provides a unique opportunity to study the relative growthrate variations along the different radial tracks in the coral. Growth rates (relative to Track 1a) were determined from approximately 60 tie-points along the Ba profiles. The values for each track were averaged and the data were smoothed with a 3 point box filter to remove noise (Fig. 4). This reveals relative growth rates varying by over a factor of 2. For example, the growth rate along Track 3 appears to match the growth rate along Track 1a for the outside 1/3 of the record, but during the earlier portion of the coral’s life, it maintained an average 50% higher growth rate, with a few short periods of rapid growth that were up to double the rate along Track 1a. 4.4. Spatial resolution, smoothing and signal reproducibility One of the great advantages of the ‘continuous scanning’ LA-ICP-MS method over static spot analyses is that data for each element can be independently smoothed or averaged to find the optimal compromise between spatial resolution and noise propagation. Here, data were collected every 11 lm using a laser spot that was 60 lm in diameter. There are therefore roughly five redundant data points per independent observation. This over-sampling strategy allows us to quantify instrumental noise (i.e. noise inherent to the LA-ICP-MS system). Since real compositional variations in the coral should be ‘smoothed out’ over five data points, point-to-point variability must be being introduced by the instrument. Instrumental noise can be suppressed by windowed averaging of the signal. We define the optimal level of smoothing as being where the amplitude of instrumental white-noise falls below the amplitude of non-white-noise variations. The numerical methodology for quantifying noise and reproducibility is described in Sinclair et al.

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(2005) and a formal mathematical treatment is presented in Supporting Electronic Material of this paper. The optimal smoothing levels for each element are presented in Table 6 and graphs showing the raw, smoothed and decimated signals are presented in Supporting Electronic Material (Figs. S1–S6). In most cases, the relative standard deviation of the instrumental noise is close to that predicted by counting statistics (Table 6, columns 3 vs. 4). Mg and Sr may have some additional variance which probably represents instability in the plasma (possibly caused by poor ablation – see Section 5.1). The amplitude of this instrumental noise is typical of similar LA-ICP-MS systems (e.g. Sinclair et al., 2005). Having calculated instrumental noise, it is then possible to calculate different components of variability in the trace element signals by comparing and subtracting signals in closely spaced profiles vs. more distantly spaced profiles (see Supporting Online Material). We quantify the following different components of variability: (1) Instrumental noise – white noise introduced by the analytical method. In most cases this derives from uncertainty associated with counting statistics, but may also represent instability in the ICP-MS plasma (on 1 s timescales). (2) Fine scale noise – variations that are larger than can be accounted for by instrumental noise, but which do not reproduce in even closely spaced replicate profiles. These may represent components of instrumental noise that do not follow a white-noise spectrum, but may also represent irreproducibility in the composition of the coral on spatial scales that are smaller than the spacing between closely-spaced replicate tracks (approximately 100 lm). (3) Compositional heterogeneity – variations which are reproducible in closely spaced profiles (and thus are real geochemical variations), but are not reproduced between different radial tracks. These fluctuations represent compositional variations that are internal to the coral and do not originate from an external environmental signal. (4) Reproducible variations – variations which are shared in all tracks. These variations may represent external environmental signals. (5) Total variability – the total amplitude of variation in the signal at each timescale. Components 1–4 sum in quadrature to produce 5. These components of variation can be determined for different levels of signal smoothing allowing us to quantify both the amplitude and spatial/temporal scales of reproducible geochemical signals in the corals. The results of this analysis are presented in Table 7 and Fig. 5. Only reproducible variations (component 4) are candidates for environmental signals. Instrumental noise (component 1) is a function of the laser system/method, and can be improved by increasing the signal intensity (spot size, rep rate, energy, instrument sensitivity) and/or decreasing the scan rate (allowing more integrated counts

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Unsmoothed signal Variation in unsmoothed signala (%)

Mg/ Ca Mn/ Ca Sr/Ca Ba/Ca Pb/Ca U/Ca a b c d e f g h

Smoothed signal Estimated RSD of white noiseb (%)

RSD predicted from counting statsc (%)

Optimal smooth windowd (points)

Variation in smoothed signala (%)

Remaining RSD of white noisee (%)

Approx. no. of independent data points per profilef

Approx. spatial resolution (lm/data point)

Approx. temporal resolution (years)h

5

3

2

16

3

0.7

88

168

5

50

37

44

16

23

9.2

88

168

5

4 15 106 48

3 5 62 29

2 5 83 35

128 4 64 16

0.52 13 58 31

0.3 2.6 7.7 7.3

11 350 22 88

1341 41g 671 168

Average relative standard deviation of signals. Includes noise and compositional variations. This is instrumental noise. Estimated using spectral techniques (see text for details). Calculated using average signal in Table 1. Estimated using spectral techniques (see Section 4.4). p RSD decreases with box-smoothing by a factor of n, where n is the size of the smoothing window. This value is calculated for Tracks 1 and 2, and increases by a factor of 1.17 for Track 3, which is longer. Note: This is actually smaller than the theoretical minimum spatial resolution of 60 lm constrained by the width of the laser spot. Based on an average growth rate of 33 lm/year.

43 1.3 21 5

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Table 6 Inherent noise and effective spatial resolution.

Reproducibility of trace element profiles in a bamboo coral

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Table 7 Components of variation by spatial/temporal scale. Totalf (whole signal)

Totalg (optimally smoothed signal)

Spectral component Data points in window

0 1

1 2

2 4

3 8

4 16

5 32

6 64

7 128

8 256

9 512

Spatial resolution (lm) Temporal resolution (year)

11 0.3

22 0.7

44 1.3

88 2.7

176 5.3

352 11

704 21

1408 43

2816 85

5632 171

Manganese Instrumental noisea (%) Fine scale noiseb (%) Compositional heterogeneityc (%) Reproducible variationsd (%) Total variabilitye (%)

Data are expressed as percentages of average signal amplitude 36.7 26.0 18.4 13.0 9.2 6.5 4.6 3.2

2.3

2.3

52.0

9.2

0.0 9.6

3.9 7.8

5.4 6.9

6.7 4.8

4.8 6.3

4.6 4.0

2.1 3.8

2.1 4.9

1.2 4.9

2.4 7.0

12.2 19.8

6.1 11.3

0.0

0.0

0.0

0.0

3.1

3.6

3.7

3.6

6.8

14.1

17.2

16.9

36.7

26.9

20.0

15.4

12.5

9.6

7.3

7.2

8.8

16.1

58.3

23.1

2.9 0.0 1.0

2.0 0.5 0.8

1.4 0.5 0.6

1.0 0.3 0.3

0.7 0.2 0.2

0.5 0.2 0.2

0.4 0.2 0.0

0.3 0.2 0.1

0.2 0.2 0.2

0.2 0.1 0.5

4.1 0.9 1.6

0.3 0.2 0.5

0.0

0.0

0.0

0.0

0.0

0.0

0.1

0.2

0.3

0.0

0.4

0.3

2.9

2.1

1.5

1.1

0.8

0.6

0.4

0.4

0.4

0.5

4.2

0.6

5.2 0.0 1.5

3.7 0.0 1.2

2.6 1.5 1.6

1.9 1.9 2.1

1.3 1.4 1.6

0.9 1.0 1.0

0.7 0.8 1.0

0.5 0.7 0.8

0.3 0.5 0.7

0.3 0.4 2.8

7.4 3.2 4.9

2.6 2.8 4.2

0.0

0.0

0.0

3.1

5.1

4.7

4.2

3.1

2.1

0.0

9.5

9.5

5.2

3.7

3.4

4.6

5.7

5.0

4.5

3.3

2.3

2.6

13.2

11.0

2.8 0.0 0.8

2.0 0.0 0.7

1.4 0.4 0.4

1.0 0.2 0.4

0.7 0.5 0.4

0.5 0.5 0.4

0.3 0.4 0.5

0.2 0.3 0.5

0.2 0.2 0.6

0.2 0.7 1.9

4.0 1.2 2.5

0.7 1.0 2.1

0.0

0.3

0.0

0.2

0.3

0.4

0.4

0.3

0.6

0.0

1.0

0.9

2.8

2.1

1.5

1.1

1.0

0.9

0.8

0.8

0.9

1.6

4.7

2.3

29.1 10.9 13.2

20.6 9.5 10.5

14.6 7.4 7.5

10.3 5.8 7.4

7.3 5.3 7.6

5.2 4.5 9.1

3.6 3.9 10.5

2.6 3.4 13.1

1.8 2.9 13.2

1.8 2.4 24.6

41.2 19.7 40.0

7.3 7.8 33.8

0.0

0.0

0.0

0.0

0.0

0.0

3.8

0.0

0.0

0.0

3.8

3.8

29.1

22.0

16.1

12.4

11.0

10.8

12.4

12.9

11.3

22.8

54.3

32.9

61.7 18.1 0.0

43.7 17.8 0.0

30.9 16.5 0.0

21.8 11.8 0.0

15.4 9.6 0.0

10.9 6.4 3.2

7.7 4.7 5.4

5.5 2.8 5.0

3.9 1.5 6.0

3.9 8.2 0.0

87.3 35.8 10.1

7.7 8.8 7.9

20.3

9.5

10.3

9.9

6.0

2.0

4.3

6.1

4.2

101.2

105.2

101.5

61.7

44.9

33.8

24.9

18.1

13.2

11.4

10.0

8.4

101.5

136.8

102.4

Strontium Instrumental noise (%) Fine scale noise (%) Compositional heterogeneity (%) Reproducible variations (%) Total variability (%) Barium Instrumental noise (%) Fine scale noise (%) Compositional heterogeneity (%) Reproducible variations (%) Total variability (%) Magnesium Instrumental noise (%) Fine scale noise (%) Compositional heterogeneity (%) Reproducible variations (%) Total variability (%) Uranium Instrumental noise (%) Fine scale noise (%) Compositional heterogeneity (%) Reproducible variations (%) Total variability (%) Lead Instrumental noise (%) Fine scale noise (%) Compositional heterogeneity (%) Reproducible variations (%) Total variability (%) a

Instrumental noise is white noise generated by the analytical method. It is estimated from the total variability at spectral component 0, and p calculated for the other spectral components based on the theoretical properties of a white noise spectrum (which predicts a (1/ 2)n decay, where n is the spectral component).

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Ba (% of signal)

b Fine scale noise represents fluctuations that are larger than instrumental noise can account for (implying that they might be real compositional variations), but which are not reproduced in any profiles. They are calculated by subtracting in quadrature the instrumental noise spectrum from the average difference spectrum for closely spaced replicates. c Compositional heterogeneity represents real compositional fluctuations that are reproducible in closely spaced replicate profiles, but are not reproduced along different radial tracks. These variations cannot therefore represent environmental signals. They are calculated by subtracting in quadrature the average difference spectrum for closely spaced replicates from the average difference spectrum for different radial tracks. d Reproducible variations are compositional fluctuations that are reproduced along each radius. These are candidates for environmental signals. Reproducible variations are calculated by subtracting in quadrature the average difference spectrum for different radial tracks from the total variability (which is the average normal spectrum for the profiles). e Total variability is obtained by averaging the normal spectra for each of the profiles. Note: The total variability should be the sum-inquadrature of the other components. The calculation is not exact because we are working with averages and different profiles. f Totals are calculated by summing in quadrature contributions from each spectral component. The total variability estimated this way approximately matches the values in Table 6 but this is not an exact method. The data in Table 6 are calculated directly from the analytical signals and are therefore more reliable. g Totals are calculated by summing in quadrature contributions from each spectral component in the optimally smoothed signal. The optimally smoothed signal is one where the amplitude of instrumental noise component of the signal has been reduced to  the amplitude of the non-white-noise component (‘fine scale noise’) of the signal.

Ba

5 4 3 2 1 0

2.0 1.5 1.0 0.5

Mg (% of signal)

2.5

Mg

Sr (% of signal)

0.0

Sr

2.5 2.0 1.5

Instrumental Noise Fine Scale Noise Compositional Heterogeneity Reproducible Variations Total Variability

1.0 0.5 0.0 60 40 20

Pb (% of signal)

Pb

Mn (% of signal)

0

Mn

30 20 10 0

0

1

25 20 15 10 5 0 2

3

4

5

6

7

8

U (% of signal)

U

9

Log2 of Smoothing Window

Fig. 5. Components of variation. This graph presents the data in Table 7, showing the relative magnitude of the different components of variation calculated from the replicate trace-element profiles. Note: Individual components of variation sum in quadrature to produce the total variation. Grey shaded regions indicate spatial scales which are below the optimal smoothing window (see Section 4.4, Table 6).

Reproducibility of trace element profiles in a bamboo coral

per lm of coral scanned). Non-reproducible chemical variations (components 2 and 3) are intrinsic to the coral, and impose a fundamental constraint on the ability of this and (potentially) other corals to accurately record environmental information. The discussion in Section 5.3 focuses on these non-reproducible variations. 5. DISCUSSION 5.1. Analytical method, matrix effects and laser wavelength The poor day-to-day reproducibility of intensity ratios and calibration factors (Section 3.3) represents a significant restriction on the ability to quantify absolute trace element concentrations using the LA-ICP-MS method described here. We believe that this results from the poor matrix match between standards and sample: NIST glasses are silicates with significantly lower Ca and Mg, and higher Sr than the calcitic Keratoisis. The pressed-powder carbonate standards are a closer chemical matrix match to bamboo corals but are not a good physical match as pressed powders ablate quite differently than crystalline calcite. Despite this, the poor day-to-day calibration reproducibility seen here was unexpected given the relatively good reproducibility reported for a similar LA-ICP-MS method published previously (Sinclair et al., 1998; Sinclair, 1999). One major difference between the two systems is that here we use a 213 nm laser rather than a 193 nm laser. While

5113

CaCO3 minerals are opaque to wavelengths of 193 nm, they are partially transparent to wavelengths of 213 nm (McCarthy, 1967). This results in the 213 nm laser coupling poorly with CaCO3 samples compared with the 193 nm laser, resulting in ragged ablation (Fig. 6), and hence a larger less even size-distribution of particles in the ablation plume. This may result in a very high sensitivity to plasma condition and therefore physical and chemical matrix (Russo et al., 2000; Horn et al., 2001). Without homogeneous matrix-matched standards, dayto-day reproducibility and accuracy of carbonate analysis by 213 nm LA-ICP-MS will be poor, and the LA-ICP-MS method described here should be regarded as semi-quantitative. However, the strength of LA-ICP-MS has always been the ability to rapidly and precisely quantify relative trace-element variations. Excellent within-day reproducibility allows precise comparison between measurements made during one analytical session (as is the case for all profiles presented within this paper). 5.2. Change in growth near the central axis In the bamboo coral specimen, Ba and Mg are elevated over the inner 300–500 lm of the sample adjacent to the axial hole (Fig. 3a and b). Similar elevations in Mg are reported for other bamboo coral specimens (e.g. Thresher et al., 2007). Since no similar enrichment is seen at the outside edge of the coral, it does not appear to be associated

Fig. 6. SEM image of 193 and 213 nm laser ablation tracks. (A) Multiple laser-ablation ICP-MS tracks. The right-hand track was ablated with an ArF Excimer laser (wavelength 193 nm), while the other tracks were ablated using a quintupled Nd YAG laser (wavelength 213 nm). (B) Enlargement of the white box in (A) showing the top section of the 193 nm track (right) and 3 of the 213 nm tracks (left). (C) An enlargement of the left-hand white box in (B), showing details of the bottom of the trench ablated by the 213 nm laser. Note the uneven bottom to the trench indicating uneven ablation. (D) An enlargement of the right-hand white box in (B), showing details of the bottom of the trench ablated by the 193 nm laser. Note the even ablation.

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with seawater exposure (contamination, ion exchange or diagenesis) along external surfaces. It is possible that this central calcite might have been deposited in a different manner to the majority of the skeleton. There are indications that the hole at the axial core of the coral becomes smaller with older specimens implying some kind of active internal deposition occurs (Tracey et al., 2007). If so, this should be taken as a caution when subsampling for dating as the very inside of the coral may not represent the oldest part of the skeleton. 5.3. Reproducibility in the trace element records In the following discussion, we analyse the different properties of each element signal, focusing on reproducibility and the implications for climate reconstruction. Because instrumental noise (and derivative statistics such as optimal signal smoothing) are a function of our analytical system, these parameters are specific to our laser and method. Conversely, the reproducible variations, which are candidates for environmental signals, are likely to be specific to this particular bamboo coral sample. Of greatest general interest is the amplitude of non-reproducible variations. While different bamboo coral specimens may respond differently, the irreproducibility we quantify potentially represents a fundamental limit on the fidelity with which any bamboo coral records environmental information. 5.3.1. Barium In calcitic foraminifera (Lea and Boyle, 1989, 1990, 1991; Hall and Chan, 2004) and bivalves (Gillikin et al., 2006), Ba is shown to reflect the ambient Ba/Ca concentration in the water. Although untested, if the same holds true of calcitic deep-sea corals, Ba could potentially find application as a tracer of a diversity of oceanic processes including upwelling (Lea et al., 1989), riverine/sediment input (Sinclair, 1999; Sinclair and McCulloch, 2004), sediment disturbance (Fallon et al., 2002; Esslemont et al., 2004), surface productivity (Lea and Boyle, 1990) or groundwater input (Moore and Shaw, 1998; Shaw et al., 1998). Analysis of reproducibility shows that the coral contains low-amplitude non-reproducible variations that range from 1% to 2% of the average signal (±0.2 ppm) across all spatial scales (Table 7 and Fig. 5). The combined amplitude of these variations in the optimally-smoothed signal is 5% (±0.7 ppm). This small irreproducibility would generally not impose significant constraints on the interpretation of Ba except in cases of very subtle environmental changes. This particular specimen contains a relatively largeamplitude ‘real’ signal and Ba profiles are remarkably reproducible (Fig. 5). Since instrumental noise is relatively low, only minor (4 point) smoothing is required. The spatial resolution of the data is limited by the diameter of the laser spot (60 lm) rather than the optimal smoothing window (40 lm). In theory, data could be interpreted at near biannual resolution, but the non-reproducible variations limit the practical resolution to around 4 years. Above this, the profiles are highly reproducible and individual Ba peaks typically reproduce to better than 4%. Further studies are needed, but the excellent reproducibility marks

Ba as a good potential candidate for a paleoceanographic proxy. We note, however, that reproducibility does not prove that Ba is an environmental signal. Calcitic internodes of bamboo corals contain a fibrillar organic matrix (Ehrlich et al., 2006) and other gorgonians are rich in organic material (e.g. Sherwood, 2002). Marine organics have been shown to contain high concentrations of barium (Martin and Knauer, 1973) and represent a potentially significant source of contaminants for marine carbonates (Lea and Boyle, 1993). Coherent Ba variations may therefore reflect the presence of rings of organic-rich skeleton. 5.3.2. Magnesium Magnesium is a strong candidate for a paleotemperature proxy in calcitic corals (Thresher et al., 2004, 2005, 2010; Sherwood et al., 2005a). Thresher et al. (2010) present a temperature calibration for isidid corals with a slope of 0.048 °C/mmol/mol (equivalent to 21% change in Mg/ Ca for a 1 °C change). This slope is not tightly constrained by the scattered data, and is significantly shallower than slopes for other calcitic organisms: Sherwood et al. (2005a) published a temperature calibration for the gorgonian coral Primnoa with a slope of 0.192 °C/mmol/mol (equivalent to 6% change in Mg/Ca per °C), which is similar to the temperature sensitivity in other gorgonian corals (Weinbauer and Velimirov, 1995; Weinbauer et al., 2000) and foraminifera (Lea et al., 1999). The ability to reconstruct temperature will be constrained by non-reproducible variations in the coral. We observe a relatively constant irreproducibility in the Mg signal with an amplitude of 0.5% (±90 ppm) across most spatial scales (Figs. 3c, 5 and Table 7). Similar heterogeneities are present in other isidid corals (Thresher et al., 2007) and a sample of the deep-water coral Corallium secundum (Fallon et al., 2005), and are attributed to vital effects and/or growth rate variation. There does not appear to be any relationship between non-reproducible variations and visible structures in the coral. Optimum smoothing is 176 lm (Fig. 5), but reproducible variations remain lower than irreproducible variations below spatial scales above 350 lm (approximately decadal). The combined amplitude of non-reproducible variations above decadal resolution is around 2.5% (±450 ppm). This represents a temperature uncertainty of approximately 0.1 °C (using the calibration of Thresher et al., 2010) or 0.4 °C (using the calibration of Sherwood et al., 2005a). In our specimen, total Mg/Ca ratios show very little variation (Fig. 3b) which contrasts with Mg profiles observed in other bamboo coral specimens where systematic changes of up to 25% have been observed (Thresher et al., 2004, 2007, 2010; Thresher, 2009). In fact, in the context of those other studies, Mg in our specimen is remarkably stable, varying by at most around 4% implying that the coral has experienced very stable temperatures during its life. 5.3.3. Strontium Inorganic Sr partitioning into calcite is dependent on precipitation rate (Zhong and Mucci, 1989), and empirical observations of Sr partitioning in gorgonian corals suggest

Reproducibility of trace element profiles in a bamboo coral

a growth-rate dependence for Sr/Ca incorporation (Weinbauer and Velimirov, 1995; Weinbauer et al., 2000). In bamboo corals, Sr/Ca is therefore interpreted as a proxy for growth rates (Hill et al., 2005; Roark et al., 2005; Thresher et al., 2007). Hill et al. (2005), for example, report decadal Sr/Ca cycles of about ±1%, which they attribute to fluctuations in growth rate caused by the Pacific Decadal Oscillation, while Roark et al. (2005) propose that annual cycles in Sr/Ca reflect seasonal variation in food supply affecting growth rate. The Sr signal in our coral is very stable and reproducible (Table 7 and Figs. 3d, 5), changing by at most 1.5% across the specimen. For this reason, variations are dominated by instrumental noise below spatial scales of around 1.4 mm (42 years). Resolvable above this is a very low-amplitude (0.1–0.5%; 3–14 ppm) non-reproducible component of variation (Figs. 3d and 5) which is similar to that reported by Thresher et al. (2007). The very stable Sr signal accords with the stability in the Mg signal, and if Sr and Mg are responding to an exogenous signal this would imply that the external environment is very stable. However, our results call into doubt the prevailing hypothesis that growth rate affects Sr/Ca in bamboo corals. We show (Fig. 4) that growth along Track 3 was up to a factor of 2 faster than along other radii. The inorganic rate-dependence of Sr/Ca found by Zhong and Mucci (1989) would predict that a factor of 2 increase in growth rate should produce a 5–7% higher Sr/Ca. Our analysis is easily able to resolve this magnitude of change, but no such enrichment is observed (Fig. 3d), implying that the Sr sensitivity to growth rate is at least 3 smaller than the inorganic dependence. We are able to resolve a low amplitude (<1%) reproducible cycle in Sr comprising 3 roughly sinusoidal cycles with a 100-year periodicity (Fig. 3d). It is not known what causes these cycles. In the gorgonian coral Corallum rubrum, Sr varied with alternating dark/light bands (Weinbauer et al., 2000). We do not observe consistent banding in our specimen, but translucency (quantified as greyscale profiles from the thin-section image) varies with a low amplitude oscillation with roughly three cycles (see Supporting Electronic Material, Fig. S7). This did not, however, convincingly correlate with the Sr profiles (or any other of the other elements). The corals may be capturing a long-wavelength climatic oscillation, but further work is needed to establish correlations with candidate environmental signals. 5.3.4. Lead Lead is a widespread industrial contaminant, with anthropogenic sources deriving from power generation (especially coal burning), ore smelting and the combustion of leaded fuel in vehicles. Evidence for increasing environmental Pb concentrations has been found in a wide range of proxies including ice cores (Murozumi et al., 1969; Boutron et al., 1994), terrestrial and marine sediments (Lee and Tallis, 1973; Veron et al., 1987; Renberg et al., 1994) tropical corals (Shen and Boyle, 1987), sclerosponges (Lazareth et al., 2000), and deep sea corals (Sherwood, 2006). These records document contamination beginning as early as 2600 years ago during Greek and Roman cultures (Renberg

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et al., 1994). More recently the European industrial revolution (Murozumi et al., 1969; Boutron et al., 1994) and then American industrial revolution (Shen and Boyle, 1987; Lazareth et al., 2000) resulted in significant increases in Pb contamination, with declines in recent decades due to cleaner industrial practices and the phasing out of alkyl-lead derivatives in vehicles. Measurement of Pb profiles in natural archives potentially allows quantitative treatment of ocean mixing and transport (Shen and Boyle, 1987). In our specimen, low counts for Pb result in noisy data (Fig. 3e), but because backgrounds are very low we are still able to clearly identify a real signal (Table 1). Smoothing the signal to 64 points (700 lm 20 years) resolves a trend of increasing Pb, with evidence for a non-reproducible component of variation equivalent to 6–8% of the average signal (5–7 ppb) at any spatial scale (Table 7 and Fig. 5). Given the large reproducible trend (see below), this irreproducibility would have only minor impact on environmental interpretation. The compositional heterogeneity for Pb manifests as several partially reproducible peaks in closely-spaced replicate profiles along each track. Visual inspection of the thin section shows that a number of peaks are associated with narrow dark bands within the coral. In some cases these represent circumferential cracks (Fig. 7 and see also Supporting Electronic Material, Figs. S8–S10) which are clearly open to seawater percolation as they contain a range of detritus from brown micritic material (interpreted to be organic debris) to sponge spicules and even small foraminifera. We speculate that the irreproducible Pb peaks here are associated with detrital phases or Pb adsorption onto surfaces exposed to the ambient water (a hypothesis supported

Fig. 7. Pb variations in Track 2 matched to image. Lead displays peaks corresponding to cracks and dark bands within the skeleton. Bands that appear dark in the greyscale image are often characterised by an opaque yellow/brown colour which might indicate that these are regions where the coral may have stopped growing allowing detrital material to accumulate. Graphs of Pb variations in Tracks 1 and 3 can be found in Supporting Electronic Material. Image resolution is 200 pixels/mm. See Fig. 1 for scale bar.

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by the fact that Pb is also elevated at the very outside edge of the coral in several of the profiles). Interestingly, none of these regions of Pb enrichment are associated with elevated Mn levels (Section 5.3.6) so the Pb is clearly not adsorbing to a Fe/Mn oxide coating. There is also no Pb enrichment in the central hole, suggesting it must be protected from seawater exposure. At the largest spatial scales, the lead signal is dominated by a reproducible broad trend towards increasing concentration at the outside edge of the coral (Fig. 3e), reaching a maximum at about 1960. Lead has been increasing from as early as 1600, well before the American industrial revolution, and does not display the rapid increase in the 1940s that accompanied the increasing use of alkyl-Pb fuel additives in the USA (e.g. Shen and Boyle, 1987; Lazareth et al., 2000; Sherwood, 2006). This suggests that our specimen may be capturing Pb sources primarily from Europe rather than North America. 5.3.5. Uranium This is the first time Uranium profiles have been reported in an isidid coral. Uranium is a conservative element in the ocean (Ku et al., 1977) but in seawater is strongly complexed by carbonate ions (Langmuir, 1978). In tropical corals, U/Ca ratios (in aragonite) have been proposed as a paleotemperature proxy (Min et al., 1995; Shen and Dunbar, 1995; Sinclair et al., 1998), as a salinity proxy (Shen and Dunbar, 1995), an indicator of oceanic carbonate concentrations (Swart and Hubbard, 1982; Min et al., 1995; Shen and Dunbar, 1995) and therefore potentially pH. The same parameters have been proposed as proxies in calcitic foraminifera (Russell et al., 1996, 2004). Closely spaced U/Ca profiles in our Keratoisis sp. specimen are very reproducible (Fig. 3f). However, the reproducibility between different radial transects is essentially zero at all spatial scales (Fig. 5). Uranium is dominated by a large amplitude (7–25%; 2–7 ppb) compositional heterogeneity which is quite remarkable given how well closely spaced tracks reproduce. The magnitude of this non-reproducible component of variability means that U is unlikely to be useable as a paleoenvironmental proxy for any except the very largest environmental signals. The large amplitude fluctuations in the U profile show some correlation with major cracks and discolouration in the coral skeleton (Fig. 8 and see also Supporting Electronic Material, Figs. S11–S13). The pattern is most evident in Track 1, but unlike Pb, there is not a simple correspondence between visual features and elevated U. Cracks correlate with U peaks in some places and troughs in others, while the largest non-reproducible variation in the U profiles (the large peak in Track 2 centred on 1920) does not match the location of any major feature in the skeleton (Fig. S12). The poor reproducibility of U seen in our sample may be a sign of early diagenesis which can both increase and decrease uranium concentrations. Uranium is readily leachable from calcite: the large UO22+ cation is a poor fit within the tight calcite, and Reeder et al. (2000) note a disordered arrangement for U in calcite that could make U more mobile. Conversely, early diagenesis of CaCO3 minerals often results in U uptake (Kaufman et al., 1971, 1996;

Fig. 8. U variations in Track 1 matched to image. Some of the U peaks appear to correspond to cracks and dark features within the skeleton. The correlations are not always consistent, as illustrated by the dark band at pixel 1800 which corresponds to a trough in the U profile, rather than a peak. Graphs of U variations in Tracks 1 and 3 can be found in Supporting Electronic Material. Image resolution is 200 pixels/mm. See Fig. 1 for scale bar.

Swart and Hubbard, 1982; Hillaire-Marcel et al., 1995; Labonne and Hillaire-Marcel, 2000; Pons-Branchu et al., 2005; Robinson et al., 2006). A possible mechanism is the formation of micro-domains where breakdown of organic-rich skeleton creates localised highly reducing zones. In these zones, dissolved UO22+ (from seawater in pores) would be reduced to the insoluble U4+ ion, possibly mediated by U-reducing bacteria (Mohagheghi et al., 1985; Suzuki and Banfield, 1999; Rasbury et al., 2000). The sample was carefully examined under a petrographic microscope to search for signs of recrystallization or diagenesis. The skeleton is a relatively disordered mosaic of more and less translucent crystal over distances of a few hundred microns up to a millimetre. Translucent regions of crystal sometimes display synchronous extinction, indicating that growth was syntaxial. This appears to be a primary feature since the crystals do not obscure fine circumferential bands in the skeleton, although neomorphism does not necessarily result in destruction of the original crystal fabric (Bathurst, 1975). Further study is warranted (e.g. petrography, XRD, SEM) to determine if diagenesis is responsible for U variations. If so, this represents a potential problem for establishing chronologies in young isidid corals by Useries dating as our study shows that this can occur even in live-collected specimens. That said, the only study to date which has applied U/Th dating to bamboo corals (Thresher et al., 2004) reported results broadly consistent with 210Pb dating and band counting. 5.3.6. Manganese Manganese potentially reflects a number of processes in the ocean. In oxic waters, Mn (in its IV oxidation state) is insoluble and associated with particulates, but can be remobilised through biological processes (e.g. Jones, 1992). Manganese peaks in tropical corals and bivalves have therefore been attributed to algal blooms and increased biological

Reproducibility of trace element profiles in a bamboo coral

activity (Alibert et al., 2003; Lazareth et al., 2003; Wyndham et al., 2004). In oceanic settings, Mn has been associated with aeolian inputs, hydrothermal vents, and continental inputs (Klinkhammer et al., 1985; Statham and Burton, 1986; Shiller, 1997). Along the eastern coast of the USA, dissolved Mn is strongly influenced by continental sources (Shiller, 1997) while aeolian sources (mostly African dust) are important in the Caribbean (where it impacts surface coral communities – Shinn et al., 2000). Manganese is very reactive in sediments, and fluxes of Mn from Pacific shelf sediments were driven by dissolution of CaCO3 (through CO2 released during respiration) and the breakdown of POC at the sediment/water interface, both of which were linked with the flux of organic carbon from the surface (Johnson et al., 1992). Manganese profiles in deep sea corals could potentially capture any of these environmental processes. The intensity of the Mn signal in our coral is relatively low, and counting statistics noise is a significant component of the total variability up to spatial scales of around 700 lm (roughly 20-year timescales). Real variations in composition can be detected on spatial scales above 300 lm; however, these are dominated by non-reproducible fluctuations with amplitude of between 4% and 7% (12–21 ppb) at any particular spatial scale (Table 7 and Figs. 3g, 5). This irreproducibility overwrites decadal-scale patterns in the specimen. Above 2–3 mm spatial scales (approximately 50- to 100-year timescales) we resolve a reproducible broad-scale century-wide peak centred on 1750 (Fig. 3g). Some finerscale (1 mm, 30 years) features also reproduce between different profiles, but the non-reproducible variations make it difficult to determine how consistent this pattern is. Thus there is some evidence for a reproducible Mn pattern which may have an environmental origin. Determining which environmental parameter this may be will be the subject of further study. 6. CONCLUSIONS We have presented solution and laser-ablation ICP-MS analysis of trace elements (Ba, Mg, Sr, Mn, U, Pb) in a 420-year-old specimen of the bamboo coral Keratoisis. This represents the first measurement of Ba, Mn, U and Pb in bamboo corals. The geochemical composition of our sample is roughly similar to other gorgonian corals and magnesian calcites, but quite different from low-Mg calcites such as foraminifera suggesting that there might be a crystallographic control on bulk trace-element compositions. The continuous-scan laser-ablation ICP-MS method employed here offers only semi-quantitative analysis (dayto-day reproducibility up to 20–30%), but allows rapid replication of high-resolution relative element profiles (within-run reproducibility 2%). We have applied numerical analysis techniques (Sinclair et al., 2005, and see also Supporting Online Material) to quantify and analyse noise and reproducibility of element profiles along different radial tracks within the sample. We find that:  Barium profiles are highly reproducible in almost all details. Our ability to measure/interpret Ba is limited in spatial resolution only by the width of the laser beam.











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The highly reproducible Ba variations allow us to accurately align different profiles, and to therefore calculate relative variations in growth rate within the sample. Growth rates are variable over a factor of 2 both between and within tracks. Magnesium, a potential paleotemperature proxy, is very stable and instrumental noise is the main contributor to variation. There is, however, some evidence for real, but non-reproducible, fluctuations within the coral that will ultimately limit our ability to reconstruct temperature to 0.1–0.4 °C. Strontium is also very stable. Low amplitude real geochemical variations are detected, only some of which are reproducible. The amplitude of these fluctuations are small – and if they relate to variations in growth rate (as suggested by others), the sensitivity must be very low given the large magnitude of relative growth rate changes detected in the sample. Lead profiles are dominated by counting-statistics noise, but all show an increasing trend from old to young sample that likely reflects anthropogenic Pb contamination. There are some irreproducible compositional variations, which correlate with cracks/dark bands in the sample and which are believed to be detrital or surface contamination. Uranium has clearly-resolved compositional variations; however, essentially none of the signal reproduces along different radii, and U (at least in this specimen) therefore has no potential for environmental reconstruction. The irreproducible fluctuations may indicate early diagenesis of the sample, and this open system behaviour represents a potential problem for dating of young (e.g. live-collected) samples by U-series geochemistry. Manganese profiles are noisy, with significant irreproducible compositional variations. However, a broad reproducible pattern is detectable which potentially represents an environmental signal.

Overall this study provides strong evidence that the Keratoisis sp. corals are imperfect recorders, with internal processes adding irreproducible variations to geochemical signals which can range from insignificant (in the case of Ba) to severe (in the case of U). It is clear that geochemical profiles in bamboo corals must be interpreted carefully and, ideally, replicated to quantify reproducibility before fluctuations can be confidently ascribed to environmental processes. ACKNOWLEDGEMENTS We thank B. Minarik for help with LA-ICP-MS analyses. The logistical and financial assistance of GEOTOP, the Jackson School of Geosciences, the Scottish Alliance for Geoscience Environment and Society, and the IMCS Rutgers University are gratefully acknowledged, as are the inputs of C. Hillaire-Marcel, K. Juniper, F. Taylor, J. Banner, and R. Sherrell. We are also grateful for advice and discussions from O. Sherwood, D. Tracey, S. Cairns, F. Bayer, M. LaVigne, and E. Anagnostou. Thanks are also extended to H. Neil and seven anonymous reviewers who offered insightful comments on the current and earlier versions of this manuscript. This work was funded by an NSERC grant held by M. Risk. Anal-

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yses were undertaken as an undergraduate research project by G. Allard funded by GEOTOP (UQAM). The sample was collected during deep coral surveys and NOAA Office of Ocean Exploration (grants to S.W. Ross, lead PI) largely supported this field work. USGS Florida Integrated Science Center provided some logistical support for field operations. We thank Harbor Branch Oceanographic Inst. ship, submersible and shore-based personnel for assisting with cruises.

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