86Sr) strontium isotopic composition of marine inputs

Accepted Manuscript Reassessing the stable (δ 88/86Sr) and radiogenic (87Sr/86Sr) strontium isotopic composition of marine inputs Christopher R. Pearce, Ian J. Parkinson, Jérôme Gaillardet, Bruce L.A. Charlier, Fatima Mokadem, Kevin W. Burton PII: DOI: Reference:

S0016-7037(15)00122-2 http://dx.doi.org/10.1016/j.gca.2015.02.029 GCA 9154

To appear in:

Geochimica et Cosmochimica Acta

Received Date: Accepted Date:

15 August 2014 22 February 2015

Please cite this article as: Pearce, C.R., Parkinson, I.J., Gaillardet, J., Charlier, B.L.A., Mokadem, F., Burton, K.W., Reassessing the stable (δ 88/86Sr) and radiogenic (87Sr/86Sr) strontium isotopic composition of marine inputs, Geochimica et Cosmochimica Acta (2015), doi: http://dx.doi.org/10.1016/j.gca.2015.02.029

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Reassessing the stable (88/86Sr) and radiogenic (87Sr/86Sr) strontium isotopic composition of marine inputs

Christopher R. Pearcea,b*, Ian J. Parkinsona,c, Jérôme Gaillardet d, Bruce L. A. Charliera, Fatima Mokademe and Kevin W. Burtonf

a

Department of Environment, Earth and Ecosystems, CEPSAR, The Open University,

Walton Hall, Milton Keynes, MK7 6AA, UK b

Present address: National Oceanography Centre Southampton, University of

Southampton Waterfront Campus, European Way, Southampton, SO14 3ZH, UK c

Present address: Department of Earth Sciences, University of Bristol, Wills

Memorial Building, Queen’s Road, Bristol, BS8 1RJ, UK d

Institut de Physique du Globe de Paris, CNRS and Sorbonne Paris Cité, 1 rue

Jussieu, 75238 Paris, France and Institut Universitaire de France e

Department of Earth Sciences, University of Oxford, South Parks Road, Oxford,

OX1 3AN, UK f

Department of Earth Sciences, Durham University, Science Labs, Durham, DH1

3LE, UK

*

Corresponding author. E-mail: [email protected]

Abstract The stable strontium isotope system (88/86Sr) has recently been suggested to be a suitable proxy for determining variations in the strength of the marine carbonate system, the principal output flux of oceanic Sr. However, in order to be able to

1

interpret carbonate-driven variations in 88/86Srseawater a robust understanding of 88/86Srinput is required. Surprisingly only a limited amount of 88/86Sr data currently exists for rivers and hydrothermal fluids, thus this study assesses the variability of 88/86Sr and

87

Sr/86Sr in global rivers, hydrothermal fluids and porewaters, as well as

minor marine Sr sources such as continental dust, rainwater and glacial ice. Our analyses broadly confirm the findings of Krabbenhöft et al. (2010) [Krabbenhöft, A., Eisenhauer, A., Böhm, F., Vollstaedt, H., Fietzke, J., Liebetrau, V., Augustin, N., Peucker-Ehrenbrink, B., Müller, M.N., Horn, C., Hansen, B.T., Nolte, N., Wallmann, K., 2010. Constraining the marine strontium budget with nautral strontium isotope fractionations (87Sr/86Sr*, 88/86Sr) of carbonates, hydrothermal solutions and river waters. Geochim. Cosmochim. Acta, 74, 4097-4109], and reveal flux-weighted 88/86Srriverine and

87

Sr/86Srriverine compositions of 0.32 ‰ and 0.71299 respectively.

The hydrothermal fluids analysed in this study are consistent with an end-member 88/86Srhydrothermal composition that is the same as the oceanic crust at ~0.24 ‰, although three samples that display 88/86Sr compositions offset from the seawaterhydrothermal mixing trend suggest that the precipitation of alteration phases such as anhydrite may drive 88/86Srhydrothermal to higher values. Porewater fluids obtained from sediment cores in the Atlantic and Pacific Oceans have 88/86Sr compositions within error of seawater (0.39 ‰), implying that the diagenetic flux of Sr may not significantly affect the 88/86Sr composition of seawater. Continental loess samples have 88/86Sr compositions that are consistently lighter than, or equal to, terrestrial silicates, with their tendency to lower values thought to reflect the preferential removal of heavier Sr isotopes into solution during weathering. Finally, rainwater and glacial ice samples have 88/86Sr compositions that are also isotopically lighter than their associated water sources, a factor that may be attributed to interaction with 2

isotopically light loess and additional Sr contributions from the bedrock. Together the principal marine inputs define flux-weighted oceanic 88/86Srinput and

87

Sr/86Srinput

compositions of 0.32 ‰ and 0.71161. These values are consistent with an elevated supply of riverine Sr to the oceans due to increased post-glacial weathering, but require the enhanced weathering of exposed carbonate shelves during glacial periods or significant changes in the rate of carbonate burial to match observed changes in the 87

Sr/86Sr ratio of seawater. Our results confirm that, providing a diagenetically robust

proxy can be found, the 88/86Sr and 87Sr/86Sr isotope systems should provide a useful proxy for investigating changes in the marine carbonate system through time.

1. Introduction Strontium is readily transferred to solution during continental weathering processes and is stable in dissolved form within the oceans. Relative to the marine input and output fluxes, this high solubility results in a uniform seawater Sr concentration of 89 mol/kg and residence time of ~2.5 Ma (Broecker and Peng, 1982). Continental discharge (riverine transport) is the dominant source of Sr to the oceans, with the remainder primarily entering the oceans via hydrothermal fluids (Allègre et al., 2010; Beck et al., 2013; Davis et al., 2003; Palmer and Edmond, 1989; Vance et al., 2009). Changes in the relative importance of these principal marine Sr fluxes throughout Earth’s history can be resolved using the radiogenic Sr isotope system (87Sr/86Sr); the decay of 87Rb to 87Sr over geological timescales causes the Rb-rich silicate continental crust to have an elevated (more radiogenic)

87

Sr/86Sr ratio of ~0.7136, whereas

mantle-derived Sr sources such as hydrothermal fluids and exposed oceanic basalts have lower Rb contents and correspondingly low

87

Sr/86Sr ratios of ~0.703 (Albarède

et al., 1981; Allègre et al., 2010; Gaillardet et al., 1999; Goldstein and Jacobsen,

3

1987; Palmer and Edmond, 1989; 1992; Peucker-Ehrenbrink et al., 2010). Because marine processes do not affect the proportion of radiogenic 87

87

Sr in solution, the

Sr/86Sr composition of seawater directly reflects the relative mixing of these inputs,

which results in a modern ocean composition of 0.70917 (e.g. Allègre et al., 2010; Palmer and Edmond, 1989). The normalisation procedure used to account for instrumental mass-dependant fractionation during radiogenic Sr isotopic analysis (Nier, 1938) means that the

87

Sr/86Sr composition of marine carbonate is identical to

the seawater in which it formed, enabling carbonate

87

Sr/86Sr records to be used to

identify changes in both the rate and nature of global continental weathering, as well as variations in the hydrothermal flux driven by changes in the rate of mid ocean ridge spreading (e.g. Hodell et al., 1990; McArthur, 1994; McArthur et al., 2001).

Whilst this two end-member source scenario is useful for assessing changes in Earth system processes, it is now well established that the thermally plausible flux of unradiogenic hydrothermal Sr is insufficient to balance the amount of radiogenic Sr transported to the oceans via rivers (e.g. Allègre et al., 2010; Beck et al., 2013; Davis et al., 2003; Jones et al., 2012a; 2012b; Vance et al., 2009). This imbalance means that the 87Sr/86Sr composition of seawater should actually be increasing faster than the current rate of 0.000054 Myr -1 (Vance et al., 2009). Possible explanations for this discrepancy include missing sources of unradiogenic Sr, such as off-axis hydrothermal fluids (Davis et al., 2003), particulate weathering (Jones et al., 2012a; 2012b) and volcanic islands and groundwater sources (Allègre et al., 2010; Beck et al., 2013), as well as variable rates of glacial-interglacial continental weathering (Krabbenhöft et al., 2010; Vance et al., 2009). Although each of these fluxes/processes are likely to play a significant role in controlling the

4

87

Sr/86Sr

composition of the oceans, their impact on the total Sr content of seawater is harder to establish as this also depends on the output flux of Sr into marine carbonates. In order to asses how this output flux (and hence Sr abundance) varied in the past it is necessary to use the stable Sr isotope system.

The stable Sr isotopic composition of seawater reflects the relative proportion of naturally occurring Sr isotopes (i.e. those not produced by the radiogenic decay of 87

Rb); 84Sr, 86Sr, 87Sr and 88Sr. As with other stable isotope systems, variations in the

relative proportion of the stable Sr isotopes are commonly reported in delta notation, with the accepted convention being: 88/86Sr = ((88Sr/86Sr)sample/(88Sr/86Sr)standard - 1) x 1000. The international standard used for normalising all 88/86Sr measurements is the National Institute of Standards and Technology SrCO3 standard reference material 987 (hereafter NIST987; Fietzke and Eisenhauer, 2006; Krabbenhöft et al., 2009; Ma et al., 2013; Neymark et al., 2014; Shalev et al., 2013).

Unlike internally normalised 87Sr/86Sr isotope ratios, the sensitivity of 88/86Sr to mass fractionation processes means that the composition of marine carbonates does not match that of seawater. In fact, carbonates have been shown to have significantly lower 88/86Sr compositions than the fluid in which they formed, with 88/86Srcarbonatefluid

offsets ranging between -0.02 and -0.37 ‰ (Böhm et al., 2012; Fietzke and

Eisenhauer, 2006; Halicz et al., 2008; Krabbenhöft et al., 2010; Ohno et al, 2008; Raddatz et al., 2013; Rüggeberg et al., 2008; Stevenson et al., 2014; Vollstaedt et al., 2014). This preferential incorporation of lighter Sr isotopes into the carbonate lattice is equivalent to trends observed in the Ca and Mg isotope systems (e.g. Fantle and Tipper, 2014; Saenger and Wang, 2014 and references therein), and has been

5

suggested to correlate with the rate of precipitation (Böhm et al., 2012; Stevenson et al., 2014). This sensitivity of 88/86Sr to carbonate formation indicates that variations in the 88/86Sr composition of seawater may help constrain past changes in the marine carbonate system if used in conjunction with other carbonate system parameters (e.g. Vollstaedt et al., 2014). However, before 88/86Sr can be used to assess how this marine Sr output flux has varied through time, it is essential to fully quantify potential variability in the 88/86Sr composition of the dominant marine inputs. Surprisingly, only a limited amount of 88/86Sr data currently exists for rivers and hydrothermal fluids (de Souza et al., 2010; Krabbenhöft et al., 2010 and Wei et al., 2013). In their initial assessment of the 88/86Sr composition of marine fluxes, Krabbenhöft et al. (2010) concluded that, as with the radiogenic Sr system, the modern stable Sr isotopic composition of riverine input is in disequilibrium as a result of non steady state weathering processes. This study assesses their interpretation by expanding the available river water dataset to account for ~50% of global riverine discharge, and by providing a more robust assessment of 88/86Sr variability in the other principal marine sources such as hydrothermal fluids and porewaters, as well as minor fluxes such as dust, ice and rainwater. This new 88/86Sr data is interpreted in conjunction with 87

Sr/86Sr ratios determined from the same samples and is used to reconsider our

current understanding of the relative balance between marine Sr sources.

2. Materials and methods 2.1 Sample sources Most of the samples analysed in this study come from archive collections, providing a background of information against which the new results can be compared. Details of these sample sources are specified below, with their locations summarised in Fig. 1.

6

2.1.1 River waters The measured river waters represent a combination of large rivers that integrate major continental outputs and smaller rivers that drain mono-lithological catchments (Fig. 1; Gaillardet et al., 1999; Pogge von Strandmann et al., 2010; Tipper et al., 2006; 2010; 2012). Where possible the samples representing large drainage basis were collected from the river mouth at the high water stage, and were filtered on collection through 0.2 m filters prior to being acidified and stored in a cool (<7 oC) environment (e.g. Tipper et al., 2006; 2010; 2012). Similarly, the river water samples from the Azores were filtered immediately after collection through a 0.2 m cellulose acetate filter before being acidified and stored (Pogge von Strandmann et al., 2010). A significant amount of geochemical data, including major and trace element concentrations as well as isotopic ratios has previously been published from these samples, some of which is included in Appendix 1.

2.1.2 Hydrothermal fluids, oceanic basalt and seawater Hydrothermal fluids were obtained from the TAG, Snakepit and Broken Spur fields located between 23oN and 29oN (Fig. 1). These vent sites lie on the slow spreading Mid Atlantic Ridge (MAR), and are characterised by large ‘beehive’ anhydrite mounds as well as chimneys and breccia formed from sulphide and other metaliferous precipitates (Campbell et al., 1998; James, 1995; James et al., 1995). The samples analysed from these sites were collected using Ti syringes at water depths of 31003700m during the 1993 RV Atlantis II Cruise. Fluid temperatures at the point of sampling ranged between 358oC and 369oC and revealed some evidence of supercritical phase separation (James et al., 1995). To compliment the hydrothermal

7

fluid data, we have analysed four open seawater samples from the Atlantic, Indian and Pacific Oceans and assessed the Sr isotopic composition of the basaltic crust by analysing a series of USGS basalt standards (BHVO2, BIR and BCR).

2.1.3 Porewater Near surface sediment porewater profiles were determined from three sites in the equatorial Pacific and Atlantic (Fig. 1). Sites JGOFS-48 and JGOFS-77 were sampled during the US Joint Global Ocean Flux Study equatorial Pacific cruise (TT013) that cored a series of stations across the equator on longitude 140 oW. Sites 48 and 77 were sampled at a water depth of ~4500 m at 0oN and 2oN respectively, and were found to primarily consist of carbonate ooze that had undergone slight dissolution (Hammond et al., 1996; McManus et al., 1995). The ANA samples were collected at a water depth of 3975 m from Station 5 during the 2010 ANACONDAS/ROCA cruise in the western tropical North Atlantic Ocean. These porewaters were extracted using a rhizon extraction process from sediments collected using a multi-corer (Chong et al., 2014).

2.1.4 Continental dust The samples of continental loess were originally collected and analysed by Taylor et al. (1983) and Smith et al. (2003). The Taylor et al. (1983) samples include loess deposits from: Banks Peninsula, New Zealand; Nanking, China; Kaiserstuhl in the Rhine Valley, Germany; and Kansas and Iowa in the USA (Fig. 1). The Smith et al. (2003) samples represent Argentinian loess deposits of various ages collected from 28-38oS. Together these loess samples provide a wide geographical sampling of continental dust from various geological sources.

8

2.1.5 Glacial ice and rainwater Two glacial ice samples were analysed from Langjökull glacier in W. Iceland (Pogge von Strandmann et al., 2006) and from Russell glacier in W. Greenland (Wimpenny et al., 2010; 2011). Rainwater samples from the Azores, Congo, and China were obtained from sample archives, having been collected, filtered through a 0.2 m membrane and acidified at the same time and location as the associated river samples.

2.2 Analytical techniques Major and trace element concentrations in the river, porewater and rainwater samples were determined via inductively coupled plasma mass spectrometry (ICP-MS) prior to isotopic analysis. Appropriate aliquots of each sample were evaporated to dryness then diluted in 3 % HNO3 ready for analysis. All measurements were performed on an Agilent ICP-MS at The Open University, with concentrations determined relative to a matrix-matched standard (either an in-house multi-element solution or an international reference material such as SLRS-4 or NIST 1640).

Samples were prepared for Sr isotopic analysis by either drying down (fluid samples) or digesting in HF/HNO3 (basalt and loess samples) an aliquot containing ~1000 ng of Sr. The dried residue was subsequently taken up in 2 ml of 2M HNO 3 and split to two 1 ml fractions each containing ~500 ng Sr. An appropriate amount of an

84

Sr-87Sr

double spike (chosen to optimise error propagation during the spike deconvolution process; Krabbenhöft et al., 2009; Neymark et al., 2014; Shalev et al., 2013) was then added to one of these aliquots, before Sr in both the ‘spiked’ and ‘unspiked’ fractions was purified using the Eichrom strontium specification ion exchange resin: 1 ml of

9

sample in 2M HNO3 was loaded onto a pre-cleaned column containing 150 l of resin in 200 l stages. The column was subsequently washed with an additional 0.4 ml of 2M HNO3 and 1 ml of 7M HNO3 before Sr was eluted in 1 ml of 0.05M HNO3. This Sr fraction was dried down at ~90oC prior to loading onto a single outgassed zonerefined Re filament. Filament loading followed the procedure described by Charlier et al. (2006), and involved dissolving and loading the sample in 1 l of conc. HNO3, adding 0.7 l of a TaF5 activator, then slowly drying down the mixture at a current of ~1 A. All isotopic analyses were performed using a ThermoFisher ‘Triton’ thermal ionisation mass spectrometer (TIMS) in positive ionisation mode at The Open University. The analytical routine is identical to that described in Stevenson et al. (2014), and involved a gradual filament warm-up and tuning process before analysing samples at a stable

88

Sr beam intensity of ~8V for 54 cycles of 10 block ratio

measurements with a 16.2 second integration time. In addition to the four Sr isotopes, mass 85 was measured in order to monitor and correct for any 87Rb interferences. The typical run time required for each measurement was 4½ hours.

Radiogenic fixed

86

87

Sr/86Sr ratios were determined by normalising unspiked TIMS data to a

Sr/88Sr ratio of 0.1194 (Nier, 1938). Analysis of 169 NIST987 standards over

the course of this study resulted in a long-term 87Sr/86Sr mean of 0.710246 (2 s.d. = 14 ppm), with the reproducibility of standard measurements within individual sessions varying between 5 and 30 ppm. Stable Sr isotope ratios were resolved by combining unspiked and spiked filament data then deconvolving using the exponential fractionation law and Newton-Raphson iteration technique in 87Sr denominator space. A variability of up to 0.09 ‰ was observed in NIST987 88/86Sr ratios between analytical sessions, thus in order to account for these offsets the average of all

10

standard measurements made in each session were normalised to the true NIST987 88/86Sr value of 0.0 ‰ and the resulting correction factor applied to all samples and standards analysed in that session. The NIST987 standards normalised in this manner gave an external 88/86Sr reproducibility (2 s.d.) of 0.025 ‰ (n = 33), with the reproducibility of individual sessions ranging between <0.01 ‰ and 0.06 ‰. A general decrease in 88/86Sr reproducibility observed throughout the study period is thought to reflect the gradual degradation of faraday cup collectors as a consequence of the long measurement times and high

88

Sr beam intensities. The average total

procedural blank measured via isotopic dilution using a pure

84

Sr spike during all

sample analyses was 35 pg, equivalent to <0.01 % of the total amount of Sr processed on each filament.

Finally, previous stable Sr studies have reported the

87

Sr/86Sr* or 87Sr/86Srtrue, ratio of

each sample (e.g. Krabbenhöft et al., 2010 and Wei et al., 2013). This 87Sr/86Sr* ratio differs from the ‘traditional’ radiogenic 87Sr/86Sr composition in that 87Sr/86Sr* defines a mass-dependant relationship with 88/86Sr. Although our deconvolution protocol also calculates the

87

Sr/86Sr* ratio for each sample, we avoid using this terminology in our

discussions as the differences between

87

Sr/86Sr* and

87

Sr/86Sr are very small and can

become confusing (c.f. Neymark et al., 2014). A more appropriate test of the massdependant relationship of the data is obtained by comparing the 88/86Sr and 84/86Sr values for each sample and confirming that both samples and standards plot along the theoretical fractionation line (Fig. 2).

3. Results 3.1 River water

11

The

88/86Sr,

87

Sr/86Sr and element abundance data obtained for all river samples

analysed in this study are presented in Table 1, with additional geochemical data previously published for the same samples (including 44/42Ca, 26/24Mg and 7/6Li isotopic compositions) summarised in Appendix 1. The total range of riverine 87

Sr/86Sr values determined in this study spans from 0.70438 to 0.73723, and results in

a flux-weighted mean composition of 0.71299. These

87

Sr/86Sr values compare well

with previously reported values from the same rivers (Allègre et al., 2010; Gaillardet et al., 1999; Tipper et al., 2006; 2010; Vance et al., 2009), with identical results obtained when the same sample was analysed (Fig. 3a). Slight discrepancies observed between

87

Sr/86Sr values obtained from different samples collected from the same

rivers most likely reflect a combination of seasonal changes in the composition of the river (i.e. differences in the time of sampling), heterogeneity of the river within the drainage basin (i.e. variations in sample location) and/or potential changes in anthropogenic contamination within the rivers.

The 88/86Sr composition of the analysed rivers ranges from 0.13 to 0.57 ‰, encompassing almost the full range of previously reported riverine values (Fig. 4a; Krabbenhöft et al., 2010; Wei et al., 2013). Five of the large river systems analysed in this study were previously measured by Krabbenhöft et al. (2010) and reveal slight variations in their 88/86Sr compositions (Fig. 3b) that again most likely reflect sample-specific differences caused by changes in sample location and method. The flux weighted mean 88/86Sr composition of global riverine input is 0.32 ‰ (Appendix 2), which is analytically unresolvable from the inferred average terrestrial silicate rock 88/86Sr value of 0.30 ‰ (representing the mean composition of various andesites, granodiorites and granites; Charlier et al., 2012; Moynier et al., 2010). Carbonate-

12

dominated riverine systems analysed in Europe have generally higher Ca/Sr ratios than the samples representative of larger catchments, and display a positive relationship with 88/86Sr (Fig. 5a). These European rivers also have significantly higher Sr/Na ratios than the rivers analysed from silicate dominated volcanic terrains, resulting in a negative Sr/Na versus 88/86Sr relationship (Fig. 5b). Finally, most of the large river systems analysed in this study conform to the positive Ca/Na versus Sr/Na relationship observed by Gaillardet et al. (1999), with only the carbonate-affected European rivers plotting significantly off this trend (Fig. 5c).

3.2 Hydrothermal fluids, oceanic basalt and seawater The hydrothermal fluids analysed in this study have

87

Sr/86Sr compositions that range

from 0.70362 to 0.70916, and 88/86Sr compositions that vary between 0.33 ‰ and 0.42 ‰. This range is comparable to that previously observed in Mid Atlantic Ridge hydrothermal fluids (Fig. 6a; Krabbenhöft et al., 2010) and is matched by a similar degree of variability in Mg/Sr concentrations (Fig. 6b). The basalts all have similar 87

Sr/86Sr and 88/86Sr compositions that range between 0.70310 and 0.70500 and 0.23

and 0.25 ‰ respectively (Table 2). The 88/86Sr composition of four replicate analyses of BHVO2 are all within error of each other, and agree with the value of 0.25 ‰ previously determined by Neymark et al. (2014). Even BCR (which is not a true oceanic basalt) has a similar 88/86Sr composition, supporting an average ocean crustal value of ~0.24 ‰. As expected, the four seawater samples have

87

Sr/86Sr and 88/86Sr

values that are identical within analytical uncertainty, with an average composition of 0.70918 and 0.39 ‰ respectively (Table 2).

3.3 Porewater

13

The three sediment porewater profiles reveal similar down-core 88/86Sr, 87Sr/86Sr and [Sr] compositions (Fig. 7; Table 2). In all cases the porewater fluids are compositionally similar to the average seawater values, with

87

Sr/86Sr ranging from

0.70916 to 0.70918 and 88/86Sr varying between 0.34 and 0.42 ‰. A slight downcore decrease in 87Sr/86Sr is observed at the two JGOFS sites, together with a peak in [Sr] at a depth of ~15 cm, although this is not matched by any equivalent variation in 88/86Sr. In contrast, the ANA samples from the tropical Atlantic do not show any systematic variations in either

87

Sr/86Sr or 88/86Sr, although the concentration of Sr is

generally higher than at the Pacific sites and appears to increase slightly with depth (Fig. 7).

3.4 Continental dust, rainwater and glacial ice The

87

Sr/86Sr compositions of the continental loess samples analysed in this study

range from 0.70752 to 0.71802. These

87

Sr/86Sr values reflect the broad range of

source rocks for these deposits and closely match the compositions determined in previous studies (Fig. 3a; Smith et al., 2003; Taylor et al., 1983). The 88/86Sr compositions of all loess samples vary between 0.18 ‰ and 0.29 ‰, meaning they are consistently lighter than, or equal to, the average composition of terrestrial silicate rocks (Fig. 8). Multiple samples analysed from the same site generally reveal similar 87

Sr/86Sr and 88/86Sr values (Table 2), with the large degree of variability between the

Argentinean sites being consistent with the difference sources of material in this region (Smith et al., 2003).

The

87

Sr/86Sr and 88/86Sr compositions of rainwater samples vary considerably with

location. Rainwater from the Congo (0.71258 and 0.05 ‰) is less radiogenic and has

14

a lighter 88/86Sr composition than the associated river water samples (~0.71910 and ~0.25 ‰), whereas rainwater from China reveals compositions that are both offset (0.71197, 0.19 ‰) and similar (0.71122, 0.31 ‰) to those of the nearby rivers (Fig. 8). Rainwater in the Azores was found to have a lighter 88/86Sr composition than the analysed river waters, and was also lighter than seawater. Glacial ice has 88/86Sr values that are lighter than both the terrestrial silicate average and seawater compositions, with values of 0.09 ‰ and 0.24 ‰ in samples from Greenland and Iceland respectively.

4. Discussion 4.1 The 88/86Sr composition of global rivers 4.1.1 Carbonate versus silicate weathering The majority of the large river systems analysed in this study have 88/86Sr values between 0.24 ‰ and 0.40 ‰ and show no clear relationship with

87

Sr/86Sr (Fig. 4a).

The only rivers with dissolved 88/86Sr compositions outside of this range come from the carbonate-rich catchments of Jura and Provence (i.e. the European rivers), and from rivers draining volcanic islands in the Caribbean, Réunion, Java and the Azores (Fig. 4a; Table 1). The contrasting 88/86Sr compositions of these carbonate and silicate dominated catchments suggests that the bedrock lithology of the drainage basin may significantly affect the 88/86Sr composition of the dissolved load.

Rivers analysed from the Jura mountains display some of the lowest 88/86Srriverine compositions (0.18 to 0.24 ‰) that most likely reflect the contribution of isotopically light Sr from the weathering of limestones and other carbonates in the region. Higher 88/86Sr compositions observed in samples collected from Provence (0.33 to 0.42 ‰)

15

are attributed to the removal of isotopically light Sr into carbonates that are actively precipitating in these catchments. For example; sample PR 7-29 was collected downstream of PR 7-30, and its lower Ca and HCO3- concentrations support the hypothesis that carbonate precipitation drove the observed increase in 88/86Sr. However, despite the importance of carbonate precipitation/dissolution processes in determining the 88/86Sr composition of rivers, no significant co-variation is observed between the 88/86Sr and 44/40Ca or 26/24Mg compositions of the analysed samples (Figs. 4b, and 4c; Appendix 1). Mutual variability between these isotope systems is expected based on the similar isotopic fractionation of all three cations into the carbonate structure (Böhm et al., 2012; Fantle and Tipper, 2014; Saenger and Wang, 2014; Stevenson et al., 2014), thus the absence of any significant correlation most likely reflects the fact that most multi-isotope data comes from large river systems that drain multi-lithological catchments. A more notable degree of co-variation may be expected between riverine 88/86Sr, 44/40Ca and 26/24Mg isotopic ratios within individual drainage systems, supported by the apparent negative 44/40Ca versus 88/86Sr relationship observed in samples from the Jura mountains (Fig. 4b).

Rivers draining volcanic terrains have 88/86Sr compositions that are generally higher than the inferred average composition of terrestrial silicate rocks (Charlier et al., 2012; Moynier et al., 2010); only sample P20 from Java has a lower 88/86Sr ratio of 0.13 ‰ which may be related to local factors such as carbonate dissolution, hydrothermal input and/or anthropogenic contamination. The tendency towards higher 88/86Sr compositions in silicate dominated catchments cannot be attributed to the weathering of an isotopically heavy bedrock, as these islands are predominantly formed of basalt that has a 88/86Sr composition of ~0.24 ‰ (Table 2). Consequently

16

the 88/86Sr variation observed in these rivers is most likely caused by isotopic fractionation occurring during the weathering process, either as a result of incongruent weathering that preferentially releases isotopically heavy Sr into solution, or via the re-incorporation of isotopically light Sr into secondary phases that precipitate during weathering (or some combination of the two). Although more detailed studies are required to determine the relative importance of these potential fractionation mechanisms (e.g. Wei et al., 2013), the apparent increase in riverine 88/86Sr as the fluid Sr/Na ratio decreases (Fig. 5b) is consistent with the removal of isotopically light Sr from the dissolved phase. Finally, whilst we are unable to fully assess what secondary phases may be forming in these particular volcanic catchments, we note that the direction of fractionation (i.e. the preferential incorporation of isotopically light Sr) is the same as observed during carbonate precipitation (Böhm et al., 2012; Stevenson et al., 2014), suggesting that any secondary mineralisation that occurs during continental weathering and riverine transportation is likely to drive 88/86Srriverine to higher compositions.

4.1.2 The 88/86Sr composition of the global riverine flux The rivers analysed in this study represent >42% of global water discharge into the oceans, and >30% of the total riverine Sr flux. Combined with previously published 88/86Sr data from other rivers (Krabbenhöft et al., 2010 and Wei et al., 2013), this enables us to account for almost 50 % of total water discharge and ~40% of the global riverine Sr flux (Appendix 2). The flux-weighted

87

Sr/86Srriverine and 88/86Srriverine

compositions of this combined dataset are 0.71299 and 0.32 ‰ respectively. This 87

Sr/86Srriverine input composition is similar to that reported by Allègre et al. (2010)

(0.7136), but higher than the values of 0.7111 to 0.7119 proposed by Vance et al.

17

(2009), Krabbenhöft et al. (2010) and Peucker-Ehrenbrink et al. (2010). These different averages most likely reflect contrasting

87

Sr/86Sr values determined for the

same river systems caused by different sampling times and/or localities (e.g. Fig. 3), and provide some measure of the inherent difficulties when estimating any global flux from a limited sample set. In contrast, the flux-weighted 88/86Srriverine input composition is identical to that previously reported by Krabbenhöft et al. (2010), with both values being central to the range of 0.24 ‰ to 0.40 ‰ observed in most large river systems (Fig. 4). This supports evidence of little compositional difference between the large rivers draining glacial and non-glacial terrains (Appendix 2), and suggests that the net 88/86Srriverine input value is unlikely to change significantly with the addition of data from other major drainage basins.

It is well established that

87

Sr/86Srriverine compositions are sensitive to the extent of

water mixing between carbonate and silicate catchments (e.g. Allègre et al., 2010; Gaillardet et al., 1999; Peucker-Ehrenbrink et al., 2010), thus it is likely that 88/86Srriverine compositions also reflect the relative proportion of Sr derived from these end-members. Assuming carbonate and silicate 87Sr/86Srriverine compositions of 0.7080 and 0.7210 respectively (Allègre et al., 2010), the flux-weighted

87

Sr/86Srriverine

composition of 0.71299 determined in this study implies an Sr contribution of 61 % and 39 % from the weathering of carbonate and silicate terrains, consistent with endmember 88/86Srriverine compositions of 0.16 ‰ and 0.56 ‰ respectively. This is similar to the interpretation by Gaillardet et al. (1999) that as much as 69 % of dissolved Sr may originate from non-silicate catchments, which would suggest slightly higher carbonate and silicate end-member 88/86Sr and

87

Sr/86Sr compositions

of 0.19 ‰ and 0.7085 or 0.60 ‰ and 0.7230 respectively. Although these values are

18

within the range of analysed riverine compositions, it is recognised that the composition of individual rivers is likely to significantly differ from these endmember scenarios according to the composition of the bedrock lithology being weathered. Nevertheless, the inferred silicate 88/86Srriverine end-member compositions of ~0.56 ‰ or ~0.60 ‰ are resolvably higher than the average 88/86Sr composition of silicate rocks (~0.30 ‰; Charlier et al., 2012; Moynier et al., 2010), thus support catchment-specific evidence for the fractionation of Sr isotopes (Wei et al., 2013) and confirm that heavier Sr isotopes are preferentially transferred to solution during silicate weathering processes.

4.2 The 88/86Sr composition of other marine sources 4.2.1 Hydrothermal fluids and porewater The hydrothermal fluids measured in this study generally support the hydrothermalseawater mixing trend reported by Krabbenhöft et al. (2010). Two samples analysed from the TAG (BS02) and Broken Spur (BS12) vent sites display the greatest seawater influence (as indicated by their

87

Sr/86Sr ratios) and plot on the same mixing

line as the Krabbenhöft et al. (2010) data from the Comfortless Cove, Turtle Pits and Red Lion fields (Fig. 6a). This relationship suggests a hydrothermal fluid end-member composition of ~0.24 ‰, which is consistent with the 88/86Sr composition of pure hydrothermal fluids being indistinguishable from the composition of the oceanic crust (indicated by the average composition of the analysed basalts; Fig. 6a). However, three of the hydrothermal samples analysed in this study (obtained from the Snakepit and Broken Spur vent sites) are offset by ~0.1 ‰ from this seawater-hydrothermal fluid mixing trend. Given the comparatively low [Sr] of these samples (Table 2; James, 1995; James et al., 1995), it appears likely that this shift to higher 88/86Sr

19

values is caused by the preferential incorporation of lighter Sr isotopes into a secondary phase. Large negative 88/86Sr fractionation factors have recently been observed in barite (BaSO4) crystals, with experimentally determined 88/86Srsolid-solution values ranging between -0.11 and -0.41 ‰ (Widanagamage et al., 2014). The presence of large anhydrite (CaSO4) mounds at the vent sites analysed in this study (Campbell et al., 1988) differs to the previously investigated hydrothermal fields (Haase et al., 2007; Krabbenhöft et al., 2010), and suggests that lighter Sr isotopes may also be preferentially incorporated during the precipitation of anhydrite, and that this may significantly affect the composition of the fluid entering seawater. Although further analyses are required to verify this hypothesis and determine whether similar isotopic offsets occur in other hydrothermal fields, these results imply that the 88/86Srhydrothermal end-member composition of 0.24 ‰ should be treated as a minimum, as the true 88/86Sr composition of the hydrothermal input flux may be shifted to higher values as a result of anhydrite precipitation and/or the formation of other secondary phases within the hydrothermal system.

The sedimentary porewater profiles determined in this study reveal relatively little variation away from the composition of overlying seawater; bottom water 88/86Sr and 87

Sr/86Sr compositions from both JGOFS and ANA sites are identical (within

analytical uncertainty) to that of seawater, and no significant down-core trends are observed within the porewater samples (Fig. 7; Table 2). Porewater Sr concentrations are more variable, with Pacific JGOFS sites 48 and 77 revealing a down core [Sr] maximum at ~15 cm that is consistent with Sr release from carbonate dissolution at these sites (Hammond et al., 1996; McManus et al., 1995), while higher Sr concentrations in the ANA porewaters may reflect a faster rate of Sr release from the

20

particulate and nutrient-rich waters of the Amazon. The fact that these variations in [Sr] are not matched by equivalent changes in 88/86Sr and

87

Sr/86Sr suggests that

sediment dissolution does not affect the composition of the associated porewaters over the sediment depths and compositions investigated in this study. Higher porewater 88/86Sr compositions of between 0.43 ‰ and 0.70 ‰ were recently reported from deep equatorial Pacific sediments (Voigt et al., 2015), with an increase in 88/86Sr with depth being attributed to the precipitation of isotopically light secondary calcite during the recrystallization process. The absence of this relationship in our samples most likely reflects the shallow depth of the porewaters investigated in this study (~30 cm) relative to the reactive length-scale of Sr in marine sediments (~100m; Fantle and DePaolo, 2006; Fantle et al., 2010), and implies that secondary calcite precipitation is unlikely to have been occurring near the sediment-water interface of the JGOFS cores 48 and 77 or ANACONDAS site 5. Further investigation is required to establish whether return flux of Sr from marine sediments to the oceans is influenced by the isotopically heavy porewater compositions recorded at depth, thus although we assume that the diagenetic Sr flux is indistinguishable from the 88/86Sr composition of seawater (Table 3), we recognise that this represents a minimum estimate for 88/86Srporewater.

4.2.2 Continental dust, rainwater and glacial ice Unlike the riverine, hydrothermal and diagenetic (porewater) fluxes, atmospheric inputs represent a minor component of marine Sr inputs. Nevertheless, the loess, rainwater and glacial ice samples analysed in this study reveal some of the largest 88/86Sr variations observed in natural samples (Fig. 8). The fact that the 88/86Sr composition of loess is consistently lower than, or equal to, the average composition

21

of terrestrial silicate rocks is not thought to reflect a bias in source lithology, as no clear trend is observed between 88/86Sr and

87

Sr/86Sr (Fig. 8). Consequently the

tendency towards isotopically light 88/86Sr compositions in loess is attributed to the preferential removal of isotopically heavy Sr during weathering. An incongruent weathering scenario (where mineral phases with higher 88/86Sr compositions weather faster than those with lower 88/86Sr values) is consistent with an inferred increase in the dominance of Rb-rich mica clays in fine grained samples (Dasch, 1969) and with the tendency of more evolved silicates to have lighter 88/86Sr compositions (Charlier et al., 2012). Alternatively it is possible that continental dust contains a larger proportion of the isotopically light secondary phases produced during weathering (as has been proposed for 7/6Li variations observed in riverine sediments; Dellinger et al., 2014). Further analyses are required to confirm which process is the dominant control on the 88/86Sr composition of loess, although it appears likely that a combination of differences in the extent of weathering and the nature of the secondary phases precipitated contribute to a large degree of 88/86Sr variability in continental dust.

The 88/86Sr composition of rainwater samples from the Azores, China and Congo are all isotopically lighter than seawater, with precipitation in the Congo providing the lightest 88/86Sr composition measured in this study (0.05 ‰). The fact that these rainwater samples also have lighter 88/86Sr compositions than the nearby rivers (Fig. 8) indicates that the composition of precipitation does not simply reflect that of the dominant local water source. It is possible that lighter Sr isotopes are preferentially evaporated from seawater, but such fractionation is not observed in other isotopic systems and is inconsistent with the inferred preferential mobility of heavier Sr 22

isotopes during weathering. Our preferred interpretation for this observation is therefore that the 88/86Sr composition of rainwater is driven to lower values via the dissolution of isotopically light dust in the atmosphere and/or as a consequence of contamination from anthropogenic sources. These results imply that the 88/86Sr composition of rainwater is likely to vary significantly both spatially and temporally.

Given the isotopically light 88/86Sr compositions of both loess and rainwater, it is unsurprising that the glacial ice samples also have relatively low 88/86Sr values of 0.09 ‰ (Russell Glacier) and 0.24 ‰ (Langjökull Glacier) (Fig. 8). That the 87Sr/86Sr composition of glacial ice from Greenland is more radiogenic than that from Iceland reflects the different ages and lithologies of the associated bedrock, and suggests that some of the Sr within the ice is sourced locally (i.e. it is not just derived from precipitation). This is also supported by the fact that the 88/86Sr composition of Langjökull Glacier is very similar to that determined for Icelandic basalt (BIR = 0.23 ‰; Table 2). The lower 88/86Sr composition of Russell Glacier may therefore reflect lower 88/86Sr ratios of the bedrock in that region, or a greater contribution of Sr from isotopically light dust.

4.3 Implications for global marine 88/86Sr and 87Sr/86Sr fluxes The range of samples analysed in this study enable the net 88/86Sr composition of Sr entering the oceans to be reassessed (Table 3; Fig. 9). This 88/86Sr budget builds on the original characterisation made by Krabbenhöft et al. (2010), with improved constraints on the variability of global riverine and hydrothermal 88/86Sr compositions, as well as new data for the porewater Sr flux. Only the 88/86Sr composition of Sr entering the oceans in groundwater remains loosely characterised, 23

with the average value of 0.35 ‰ measured in groundwaters from North Dakota (Neymark et al., 2014) appearing to support previous assumptions that this flux is likely to be similar to the composition of riverine input (Krabbenhöft et al., 2010). Using the Sr input fluxes estimated by Palmer and Edmond (1989), Davis et al. (2003) and Beck et al. (2013), and assuming that 88/86Srporewater is equivalent to 88/86Srseawater, our data imply a net flux-weighted 88/86Srinput composition of 0.32 ‰ and

87

Sr/86Srinput ratio of 0.71161 (Table 3; Fig. 9). These Sr input values are slightly

higher than those previously proposed by Krabbenhöft et al. (2010), and reflect the higher average

87

Sr/86Srriverine composition determined in this study as well as the

addition of the groundwater and porewater 88/86Sr components. However, despite this slight increase, the implications for the global Sr input composition remain the same as inferred by Krabbenhöft et al. (2010), with both Sr isotope ratios dominated by the composition of riverine discharge.

Assuming an average 88/86Srcarbonate-seawater fractionation factor of -0.24 ‰ (Vollstaedt et al., 2014), the mean marine 88/86Srcarbonate output flux composition is inferred to be 0.15 ‰ (Table 3; Fig. 9). This is lower than the burial composition defined by Krabbenhöft et al. (2010) (0.21‰) as it takes into account the results of more recent studies that have investigated 88/86Sr fractionation into carbonates (with 88/86Sr compositions as low as 0.03 ‰ observed in foraminifera, coccolithophores and corals; Böhm et al., 2012; Raddatz et al., 2013; Stevenson et al., 2014). The intercept point between the carbonate-seawater 88/86Sr fractionation line (line 1; Fig. 9) and the river-hydrothermal

87

Sr/86Sr binary mixing line (line 2; Fig. 9) has values of 0.29 ‰

and 0.70918 respectively and represents the input value required if Sr isotopes were in steady-state. The fact that the actual global input Sr isotopic composition does not

24

coincide with this intercept point has previously been attributed to a short term weathering pulse during deglaciation (Krabbenhöft et al., 2010; Vance et al., 2009). High-precision foraminifera 87

87

Sr/86Sr records reveal glacial-interglacial seawater

Sr/86Sr variations of ±4.9 ppm, equivalent to ±12 % shifts in the riverine Sr flux

relative to the Quaternary average (Mokadem et al., 2015). This degree of variation in seawater

87

Sr/86Sr is considerably smaller than would be observed if the modern Sr

input compositions were maintained for a prolonged period of time (~20 ppm over 18 kyr), thus support the hypothesis that the current riverine Sr fluxes are higher than the long-term mean. The fact that the 87Sr/86Srinput composition determined in this study is more radiogenic then previous estimations (e.g. Allegre et al., 2010; Krabenhöft et al., 2010; Peucker-Ehrenbrink et al., 2010; Vance et al., 2010) requires that exposed carbonate shelves were preferentially weathered during glacial periods, or that significant changes have occurred in the rate of Sr removal into carbonates, in order to account for the observed changes in 87Sr/86Srseawater.

It has also previously been suggested that in order for the complete marine Sr system to be in isotopic equilibrium, the long-term 88/86Srinput (i.e. intercept) composition should match the 88/86Sroutput composition of marine carbonates (Krabbenhöft et al., 2010). The apparent offset between these values (Table 3; Fig. 9) might therefore indicate isotopic disequilibrium in the modern Sr system as a consequence of either: (1) A significantly higher modern 88/86Srinput composition relative to the average flux value over the last ~1 Ma (i.e. the long-term 88/86Srinput flux has a composition closer to the 88/86Srcarbonate burial flux of 0.15 ‰); (2) A larger 88/86Srcarbonate-seawater fractionation factor in modern seawater than during the last ~1 Ma (i.e. the long-term 88/86Srcarbonate output composition is actually closer to modern 88/86Srinput at ~0.29

25

‰); (3) A decrease in the 88/86Sr composition of seawater coupled with an increase in Sr concentration, such that both 88/86Srseawater and 88/86Srcarbonate have shifted to lighter values (i.e. line 1 in Fig. 9 has moved to the left). All three mechanisms are consistent with available 88/86Sr data, as the weathering of exposed carbonate shelves may have decreased 88/86Srinput during glacial periods (Krabbenhöft et al., 2010), slow forming inorganic carbonates have smaller 88/86Srcarbonate-seawater fractionation factors (Böhm et al., 2012), and higher 88/86Srseawater compositions of up to ~0.55 ‰ have been suggested for the Phanerozoic (Vollstaedt et al., 2014). However, although isotopic equilibrium under such conditions is therefore theoretically attainable, it is not required in order for the marine Sr system to be considered at steady-state as the carbonate-seawater fractionation factor coupled with the long residence time of marine Sr enables a constant isotopic composition and abundance to be maintained with various 88/86Srinput, 88/86Sroutput and 88/86Srseawater values.

Finally, if 88/86Srcarbonate-seawater is assumed to be invariant through time (e.g. Vollstaedt et al., 2014), then the relationships shown in Fig. 9 indicate that changes in seawater 88/86Sr and 87Sr/86Sr can be used to establish variations in the strength of the marine carbonate system: A shift in 88/86Srinput driven by the weathering of exposed carbonate shelves would be accompanied by a coincident change in

87

Sr/86Srseawater,

whereas varying the strength of carbonate burial would affect both 88/86Sroutput and 88/86Srseawater without changing

87

Sr/86Srseawater (e.g. a reduction in carbonate burial

would leave more isotopically light Sr in seawater and cause Sr abundances to increase). Consequently, by establishing how 88/86Sr and

26

87

Sr/86Sr have varied

through time it should be possible to assess changes in both continental weathering and the rate/extent of global carbonate burial (e.g. Vollstaedt et al., 2014).

5. Conclusions This study presents new 88/86Sr and

87

Sr/86Sr isotopic data for the principal marine

inputs; river water, hydrothermal fluids and porewater. Data is also presented for several minor sources of marine Sr, including continental dust, rainwater and glacial ice. These results are used in conjunction with riverine values reported by Krabbenhöft et al. (2010) and Wei et al. (2013) to assess the isotopic composition of Sr entering the oceans. The principal findings for each marine Sr input are:

(1) The flux weighted 88/86Sr and 87Sr/86Sr compositions of riverine input are 0.32 ‰ and 0.71299 respectively. No clear relationship is observed between the 88/86Sr, 44/40Ca and 26/24Mg composition of selected global rivers, although different 88/86Sr compositions observed within carbonate and volcanic terrains suggest that variations in the proportion of carbonate to silicate weathering may play a significant role in determining 88/86Srriverine values. Evidence that silicatedominated 88/86Srriverine compositions are resolvably higher than the average composition of terrestrial silicates (0.30 ‰; Charlier et al., 2012; Moynier et al., 2010) implies that stable Sr isotopes are fractionated during continental weathering processes. This fractionation may occur via the preferential release of isotopically heavier Sr into solution during incongruent weathering, or as the result of isotopically light Sr isotopes being incorporated into secondary minerals produced during weathering.

27

(2) Hydrothermal fluids analysed from vent sites along the Mid Atlantic Ridge (TAG, Snakepit and Broken Spur) are consistent with 88/86Srhydrothermal and 87

Sr/86Srhydrothermal end-member compositions of 0.24 ‰ and 0.70366. These

values agree with hydrothermal fluids obtained from other MAR sites and imply that the average composition of Sr released to the oceans via hydrothermal fluids is similar to the bulk composition of the oceanic crust. However, a shift to higher 88/86Sr values observed in three samples from the Snakepit and Broken Spur hydrothermal fields suggests that mineral precipitates such as anhydrite preferentially incorporate isotopically light Sr, and may affect the composition of Sr returning to seawater. (3) Porewater fluids sampled from sediment cores collected in the equatorial Pacific (JGOFS sites 44 and 77) and Atlantic (ANACONDAS site 5) display no significant variation from the isotopic composition of overlying seawater (88/86Srseawater = 0.39 ‰ and 87Sr/86Srseawater = 0.70918), suggesting that variations in the diagenetic return flux of Sr are unlikely to significantly affect the 88/86Sr composition of the oceans. (4) Continental loess has 88/86Sr compositions that are consistently lighter than, or equal to, terrestrial silicate rocks, with 88/86Sr values ranging between 0.18 ‰ and 0.29 ‰. This 88/86Sr variability does not appear to be related to the lithology of the loess, thus the tendency to lower 88/86Sr values is attributed to the dominance of isotopically light secondary phases within the loess, or the preferential removal of heavier Sr isotopes into solution during weathering (i.e. incongruent weathering). (5) Rainwater samples from China, Congo and the Azores have 88/86Sr compositions that are isotopically lighter than their associated water sources, with 88/86Sr

28

values varying between 0.05 ‰ and 0.32 ‰. Glacial ice also has an isotopically light 88/86Sr composition, with values of 0.09 ‰ and 0.24 ‰ measured from Russell Glacier in Greenland and Langjökull Glacier in Iceland respectively. These lighter 88/86Sr compositions in both rainwater and glacial ice may be attributed to interaction with isotopically light loess, although glacial 88/86Sr compositions are also consistent with significant contribution from the bedrock.

Together the principal marine inputs define flux-weighted 88/86Srinput and 87Sr/86Srinput compositions of 0.32 ‰ and 0.71161 respectively. This is consistent with an enhanced post-glacial supply of riverine Sr to the oceans, but requires the enhanced weathering of exposed carbonate shelves during glacial periods or significant changes in the rate of carbonate burial in order to match observed changes in the 87Sr/86Sr ratio of seawater. These results indicate that, providing a diagenetically robust proxy can be found, combined 88/86Sr and 87Sr/86Sr isotopic analyses should provide a useful proxy for investigating changes in the marine carbonate system through time.

Acknowledgements We gratefully acknowledge Bernard Peucker-Ehrenbrink and two anonymous reviewers for their comments, as well as Andrew Jacobson for editorial handling. We also thank Rachael James for providing the hydrothermal fluid samples, Josh West and Doug Hammond for providing the porewater samples and Roberta Rudnick for the provision of the Taylor et al. (1983) loess samples. Sam Hammond is thanked for her assistance with the ICP-MS analyses, and Emily Stevenson and Rachael James are thanked for their advice and discussions. This work was supported by NERC grant NE/F018126/1 and a University of Southampton Research Fellowship to CRP.

29

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Hodell, D.A., Mead, G.A. and Mueller, P.A. (1990). Variation in the strontium isotopic composition of seawater (8Ma to present): Implications for chemical weathering rates and dissolved fluxes to the oceans. Chem. Geol., 80, 291-307. James, R.H. (1995). Chemical processes in submarine hydrothermal systems at the Mid-Atlantic Ridge. PhD Thesis, University of Cambridge, UK. James, R.H., Elderfield, H. and Palmer, M.R. (1995). The chemistry of hydrothermal fluids from the Broken Spur site, 29oN Mid-Atlantic Ridge. Geochim. Cosmochim. Acta, 59, 651-659. Jones, M.T., Pearce C.R. and Oelkers E.H. (2012a). An experimental study of the interaction of basaltic riverine particulate material and seawater. Geochim. Cosmochim. Acta, 77, 108-120. Jones, M.T., Pearce C.R., Jeandel, C., Gislason, S.R., Eiriksdottir, E.S., Mavromatis, V. and Oelkers, E.H. (2012b). Riverine particulate material dissolution as a significant flux of strontium to the oceans. Earth Planet. Sci. Lett., 355-356, 5159. Krabbenhöft, A., J. Fietzke, Eisenhauer, A., Liebetrau, V., Böhm, F. and Vollstaedt, H. (2009). Determination of radiogenic and stable strontium isotope ratios (87Sr/86Sr, 88/86Sr) by thermal ionisation mass spectrometry applying an 87Sr/84Sr double spike. J. Anal. At. Spec., 24, 1267-1271. Krabbenhöft, A., Eisenhauer, A., Böhm, F., Vollstaedt, H., Fietzke, J., Liebetrau, V., Augustin, N., Peucker-Ehrenbrink, B., Müller, M.N., Horn, C., Hansen, B.T., Nolte, N., Wallmann, K., 2010. Constraining the marine strontium budget with nautral strontium isotope fractionations (87Sr/86Sr*, 88/86Sr) of carbonates, hydrothermal solutions and river waters. Geochim. Cosmochim. Acta, 74, 40974109.

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Ma, J.L., Wei, G.J., Liu, Y., Ren, Z.Y., Xu, Y.G. and Yang, Y.H. (2013). Precise measurement of stable (88/86Sr) and radiogenic (87Sr/86Sr) strontium isotope ratios in geological standard reference materials using MC-ICP-MS. Chin. Sci. Bull., 58, 3111-3118. McArthur, J.M. (1994). Recent trends in strontium isotope stratigraphy. Terr. Nova, 6, 331-358. McArthur, J.M., Howarth, R.J. and Bailey, T.R. (2001). Strontium isotope stratigraphy: LOWES version 3: best fit to the marine Sr-isotope curve for 0-509 Ma and accompanying look-up table for deriving numerical ager. J. Geology, 109, 155-170. McManus, J., Berelson, W.M., Hammond, D.E., Kilgore, T.E., Demaster, D.J., Ragueneau, O.G. and Collier, R.W. (1995). Early diagenesis of biogenic opal: dissolution rates, kinetics and paleoceanographic implications. Deep-Sea Res. II, 42, 871-903. Mokadem, F., Parkinson, I.J., Hathorne, E.C., Anand, P., Allen, J.T. and Burton, K.B. (2015). High-precision radiogenic strontium isotope measurements of the modern and glacial ocean: Limits on glacial-interglacial variations in continental weathering. Earth Planet. Sci. Lett. 415, 111-120. Moynier, F., Agrainer, A., Hezel, D.C. and Bouvier, A. (2010). Sr stable isotope composition of Earth, the Moon, Mars, Vesta and meteorites. Earth Planet. Sci. Lett. 300, 359-366. Neymark, L.A., Premo, W.R., Mel’nikov, N.N. and Emsbo, P. (2014). Precise determination of 88Sr in rocks, minerals, and waters by double-spike TIMS: a powerful tool in the study of geological, hydrological and biological processes. J. Anal. At. Spectrom. 29, 65-75.

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Nier, A.O. (1938). The isotopic constitution of strontium, barium, bismuth, thallium and mercury. Phys. Rev., 5, 275-279. Ohno, T., Komiya, T., Ueno, Y., Hirata, T. and Maruyama, S. (2008). Determination of 88Sr/86Sr mass-dependent isotopic and radiogenic isotope variation of 87Sr/86Sr in the neoproterozoic doushantuo formation. Gondwana Res., 14, 126-133. Palmer, M.R. and Edmond, J.M. (1989). The strontium isotope budget of the modern ocean. Earth Planet. Sci. Lett., 92, 11-26. Palmer, M.R. and Edmond, J.M. (1992). Controls over the strontium isotope composition of river water. Geochim. Cosmochim. Acta, 56, 2099-2111. Peucker-Ehrenbrink, B., Miller, M.W., Arsouze, T. and Jeandel, C. (2010). Continental bedrock and riverine fluxes of strontium and neodymium isotopes to the oceans. Geochem. Geophy. Geosy., 11, Q03016, 10.1029/2009GC002869. Pogge von Strandmann, P.A.E., Burton, K.W., James, R.H., van Calsteren, P., Gislason, S.R. and Mokadem, F. (2006). Riverine behaviour of uranium and lithium isotopes in an actively glaciated basaltic terrain. Earth Planet. Sci. Lett., 251, 134-147. Pogge von Strandmann, P.A.E., Burton, K.W., James, R.H., van Calsteren, P. and Gislason, S.R. (2010). Assesing the role of climate on uranium and lithium isotope behaviour in rivers draining a basaltic terrain. Chem. Geol., 270, 227-239. Raddatz, J., Liebetrau, V., Rüggeberg, A., Hathorne, E., Krabbenhöft, A., Eisenhauer, A., Böhm, F., Vollstaedt, H., Fietzke, J., López Correa, M., Freiwald, A. and Dullo, W.C. (2013). Stable Sr-isotope, Sr/Ca, Mg/Ca, Li/Ca and Mg/Li ratios in the scleractinian cold-water coral Lophelia pertusa. Chem. Geol., 352, 143-152. Rüggeberg, A., Fietzke, J., Liebetrau, V., Eisenhauer, A., Dullo, W.C., Freiwald, A., (2008). Stable strontium isotopes (88/86Sr) in cold-water corals - A new proxy for

35

reconstruction of intermediate ocean water temperatures. Earth Planet. Sci. Lett., 269, 569-574. Saenger, C. and Wang, Z. (2014). Magnesium isotope fractionation in biogenic and abiogenic carbonates: Implications for paleoenvironmental proxies. Quat. Sci. Rev., 90, 1-21. Shalev, N., Segal, I., Lazar, B., Gavrieli, I., Fietzke, J., Eisenhauer, A. and Halicz, L. (2013). Precise determination of 88/86Sr in natural samples by double-spike MCICP-MS and its TIMS verification. J. Anal. At. Spec., 28, 940-944. Smith, J., Vance, D., Kemp, R.A., Archer, C., Toms, P., King, M. and Zárate, M. (2003). Isotopic constraints on the source of Argentinian loess – with implications for atmospheric circulation and the provenance of Antarctic dust during recent glacial maxima. Earth Planet. Sci. Lett., 212, 181-196. Stevenson, E.I., Hermoso, M., Rickaby, R.E.M., Tyler, J.J., Minoletti, F., Parkinson, I.J., Mokadem, F. and Burton, K.W. (2014). Controls on stable strontium isotope fractionation in coccolithophores with implications for the marine Sr cycle. Geochim. Cosmochim. Acta, 128, 225-235. Taylor, S.R., McLennan, S.M. and McCulloch, M.T. (1983). Geochemistry of loess, continental crustal composition and crustal model ages. Geochim. Cosmochim. Acta, 47, 1897-1905. Tipper, E.T., Galy, A., Gaillardet, J., Bickle, M.J., Elderfield, H. and Carder, E.A. (2006). The magnesium isotope budget of the modern ocean: Constraints from riverine magnesium isotope ratios. Earth Planet. Sci. Lett., 250, 241-253. Tipper, E.T., Gaillardet, J., Galy, A., Louvat, P., Bickle, M.J. and Capmas, F. (2010). Calcium isotope ratios in the world’s largest rivers: A constraint on the maximum

36

imbalance of oceanic calcium fluxes. Glob. Biogeochem. Cyc., 24, GB3019, 10.1029/2009GB003574 Tipper, E.T., Calmels, D., Gaillardet, J., Louvat, P., Capmas, F. and Dubacq, B. (2012). Positive correlation between Li and Mg isotope ratios in the river waters of the Mackenzie Basin challenges the interpretation of apparent isotopic fractionation during weathering. Earth Planet. Sci. Lett., 333-334, 35-45. Vance, D., Teagle, D. and Foster, G. (2009). Variable Quaternary chemical weathering fluxes and imbalances in marine geochemical budgets. Nature, 458, 493-496. Voigt, J., Hathorne, E.C., Frank, M., Vollstaedt, H. and Eisenhauer, A. (2015). Variability of carbonate diagenesis in equatorial Pacific sediments deduced from radiogenic and stable Sr isotopes. Geochim. Cosmochim. Acta, 148, 360-377. Vollstaedt, H., Eisenhauer, A., Wallmann, K., Böhm, F., Fietzke, J., Liebetrau, V., Krabbenhöft, A., Farkaš, J., Tomašovych, A., Raddatz, J. and Veizer, J. (2014). The Phanerozoic 88/86Sr record of seawater: New constraints on past changes in oceanic carbonate fluxes. Geochim. Cosmochim. Acta, 128, 249-265. Wei, G.J., Ma, J.L., Liu, Y., Xie, L., Lu, W.J., Deng, W.F., Ren, Z.Y., Zeng, T. and Yang, Y.H. (2013). Seasonal changes in the radiogenic and stable strontium isotopic composition of Xijiang River water: Implications for chemical weathering. Chem. Geol., 343, 67-75. Widanagamage, I.H., Schauble, E.A., Scher, H.D. and Griffith, E.M. (2014). Stable strontium isotope fractionation in synthetic barite. Geochim. Cosmochim. Acta., 147, 58-75. Wimpenny, J., James, R.H., Burton, K.W., Gannoun, A., Mokadem, F. and Gislason, S.R. (2010). Glacial effects on weathering processes: New insights from the

37

elemental and lithium isotopic composition of West Greenland rivers. Earth Planet. Sci. Lett., 290, 427-437. Wimpenny, J., Burton, K.W., James, R.H., Gannoun, A., Mokadem, F. and Gislason, S.R. (2011). The behaviour of magnesium and its isotopes during glacial weathering in an ancient shield terrain in West Greenland. Earth Planet. Sci. Lett., 304, 260-269.

Table Captions Table 1: Sample information, major element concentrations and 88/86Sr and 87Sr/86Sr data for all river waters analysed in this study.

Table 2: Sample information, major element concentrations and 88/86Sr and 87Sr/86Sr data for the seawater, porewater, hydrothermal fluid, basalt, continental dust, glacial ice and rainwater samples analysed in this study.

Table 3: Summary of the Sr marine input and output flux compositions determined in this study. The flux-weighted 88/86Srriverine and

87

Sr/86Srriverine compositions were

calculated following the method described in Tipper et al. (2010), with the associated uncertainties taking into account the river systems that have not been analysed (assuming that the compositional distribution of the unsampled rivers is similar to those that have been analysed). The hydrothermal fluid end member represents the average composition of the basalts analysed in this study, while the porewater flux is assumed to have the same composition as seawater (see text for details). The uncertainty on both of these fluxes arbitrarily reflects the standard deviation (1 s.d.) of the samples analysed in this study. Groundwater discharge uses the

38

87

Sr/86Sr

composition recently estimated by Beck et al. (2013) together with the average 88/86Sr composition of four groundwater samples reported by Neymark et al. (2014). The net 88/86Srinput and

87

Sr/86Srinput compositions of marine Sr reflect the flux-

weighted average of these four end members, with estimated flux sizes taken from Beck et al. (2013), Davis et al. (2003) and Palmer and Edmond (1989). The 88/86Sr composition of carbonate burial is defined by the average 88/86Srcarbonate-seawater fractionation factor of -0.24 ‰ (Vollstaedt et al., 2014), with both the size and uncertainty of this flux taken from Krabbenhöft et al. (2010).

Appendix 1: Additional geochemical data available for the rivers analysed in this study, including published

87

Sr/86Sr, 44/42Ca, 26/24Mg and 7/6Li isotopic data from

the same samples (from Pogge von Strandmann et al., 2010 and Tipper et al., 2006; 2010). Also shown are 88/86Sr and

87

Sr/86Sr data from the rivers analysed by

Krabbenhöft et al. (2010) (indicated by *) and Wei et al. (2013) (indicated by §).

Appendix 2: Summary of river systems used to calculate the flux-weighted average 88/86Srriverine and

87

Sr/86Srriverine compositions, including an assessment of the

compositional variability between rivers that would have been glaciated and nonglaciated during the last glacial maximum (c.f. Vance et al., 2009). Where appropriate the average composition of multiple analyses on the same river system is used (see Appendix 1 for details).

Figure Captions Figure 1: Location of all samples analysed in this study, including additional drainage basins and hydrothermal samples previously analysed by Krabbenhöft et al. (2010).

39

Shaded regions indicate the drainage basins from which river water samples have been analysed and numbers refer to which rivers have been analysed (see Table 1 for river name and sample details). Small river catchments within Europe and on volcanic islands are not shown. Hatched regions and locations in italics indicate the drainage basins and hydrothermal samples analysed by Krabbenhöft et al. (2010) that have not been duplicated in this study.

Figure 2: Confirmation of the mass-dependant fractionation relationship observed in the samples analysed in this study, with most samples plotting within error of the theoretical 88/86Sr versus 84/86Sr trend (dashed line). The long-term analytical reproducibility is defined by repeat analyses (n=33) of the NIST987 Sr standard, with all sample and standard values normalised to the mean NIST987 value of the analytical session.

Figure 3: Comparison between the

87

Sr/86Sr (A) and 88/86Sr (B) composition of

samples analysed in this study with previously reported values taken from: Krabbenhöft et al. (2010) and Tipper et al. (2010) [river waters]; James (1995) and James et al. (1995) [hydrothermal fluids]; Neymark et al. (2014) [BHVO2 basalt]; Shalev et al. (2013) [IAPSO seawater]; Taylor et al. (1983) and Smith et al. (2003) [continental loess]. As expected, virtually identical Sr isotope compositions were obtained when the same sample or standard was analysed (coloured symbols). However, significant differences were observed when comparing the

87

Sr/86Sr and

88/86Sr ratios of different samples collected from the same river (open symbols), which may reflect a combination of changes in the time and location of sampling as

40

well as variations in anthropogenic contamination within the river system. See Figure 2 for key.

Figure 4: (A) 88/86Sr and

87

Sr/86Sr data for all river waters, including those analysed

by Krabbenhöft et al. (2010) and Wei et al. (2013). The vertical dashed line represents the average terrestrial silicate rock 88/86Sr composition of 0.30 ‰ (Charlier et al., 2012; Moynier et al., 2010), while the shaded region indicates the range of 88/86Sr values observed in the river systems draining large catchments rivers (0.24 ‰ to 0.40 ‰). Only rivers draining carbonate or basalt-dominated regions (i.e. those with

87

Sr/86Sr ratios <0.7100) display 88/86Sr compositions outside of this

range, with the increased variability attributed to the formation and/or dissolution of carbonates and other secondary phases within these terrains. (B) Comparison between the 88/86Sr and 44/42Ca compositions of rivers analysed in this study. No clear relationship is observed between all samples, although a negative trend in samples collected from the Jura mountains (Europe) suggest that some degree of co-variation may be expected within individual drainage basins that are actively forming or dissolving carbonates. (C) Comparison between the 88/86Sr and 26/24Mg compositions of rivers analysed in this study, again showing no clear correlation. Both 44/42Ca and 26/24Mg compositions were determined using the same samples as analysed in this study (Appendix 1), with all data (including the flux-weighted 44/42Cariverine and 26/24Mgriverine values of 0.38 ‰ and -1.09 ‰ respectively) taken from Tipper et al. (2006) and Tipper et al. (2010).

Figure 5: (A) Ca/Sr versus 88/86Sr in the river systems analysed in this study. The carbonate-dominated European rivers have some of the highest Ca/Sr ratios and

41

display a positive relationship with 88/86Sr that is consistent with the enhanced removal of isotopically light Sr in carbonate-forming regions. (B) Comparison between riverine Sr/Na and 88/86Sr ratios. Rivers draining carbonate and volcanic terrains define a negative trend, supporting the hypothesis that the lighter Sr isotopes are preferentially incorporated into secondary phases produced during weathering. (C) Relationship between Ca/Na and Sr/Na in the rivers analysed in this study. Most samples define the same positive relationship as observed in other large river systems (Gaillardet et al., 1999); only the carbonate-affected European rivers plot off this trend as a result of mixing with the pure-carbonate end-member (Ca/Na ~ 50 and Sr/Na ~35 x 10-3; Gaillardet et al., 1999). See Figure 4 for key.

Figure 6: (A) Hydrothermal 88/86Sr and

87

Sr/86Sr data from vent fluids analysed in

this study and by Krabbenhöft et al. (2010). Most samples lie on a progressive mixing line between seawater and the hydrothermal fluid end-member, which is inferred to have 88/86Sr and

87

Sr/86Sr compositions of 0.24 ‰ and 0.70366 respectively. This

88/86Srhydrothermal value is consistent with hydrothermal fluids being isotopically indistinguishable from the oceanic crust, as defined by the composition of the basalts analysed in this study. Three fluid samples analysed from the Snakepit (BS04) and Broken Spur (BS07 and BS13) vent sites are slightly offset from the inferred seawater-hydrothermal mixing trend, with the shift to higher 88/86Sr compositions attributed to the incorporation of light Sr isotopes into precipitating anhydrite. (B) Comparison between 88/86Sr and Mg/Sr ratios supports the inference that pure hydrothermal fluids (i.e. those without Mg) have a 88/86Sr composition of ~0.24 ‰, although the seawater-hydrothermal mixing trend is less clearly defined.

42

Figure 7: 88/86Sr,

87

Sr/86Sr and [Sr] depth profiles for porewaters collected from

JGOFS sites 48 and 77 (Equatorial Pacific), as well as ANACONDAS site 5 (Equatorial Atlantic). Neither 88/86Sr nor

87

Sr/86Sr show any significant down-core

variations at any site, with both compositions generally remaining within analytical uncertainty of overlying seawater. Strontium concentrations in both JGOFS cores display a maximum at ~15 cm, which may be attributed to carbonate dissolution. The Sr abundances in ANACONDAS porewaters are generally higher than the JGOFS sites, and may reflect a higher degree of Sr release from the particulates and nutrients transported by the nearby Amazon.

Figure 8:88/86Sr and

87

Sr/86Sr variability in continental loess, rainwater and glacial

ice. The 88/86Sr composition of loess is consistently lower than, or equal to, the average composition of terrestrial silicate rocks, but shows no relationship with 87

Sr/86Sr, suggesting that this does not reflect a lithological bias within the dust

samples. Lighter 88/86Sr values in the loess are consequently attributed to the preferential removal of isotopically heavier Sr via incongruent weathering or leaching, or the dominance of isotopically light secondary phases within the dust. The fact that the rainwater and glacial ice samples also have 88/86Sr values that are lower than the inferred source waters (i.e. seawater and/or local rivers) may be attributed to the dissolution of isotopically light dust and/or anthropogenic contamination, as well as additional Sr contribution from the bedrock in glacial ice.

Figure 9: Summary of the 88/86Sr and

87

Sr/86Sr compositions of the principal marine

fluxes and reservoirs. The dashed line indicates the average 88/86Sr composition of terrestrial silicates, while the shaded region reflects the extent of 88/86Sr variability in

43

large river systems. The various flux 88/86Sr and

87

Sr/86Sr compositions define a

fractionation (line 1) and mixing (line 2) relationship between the carbonate and seawater, and hydrothermal and river water end-members respectively. The fact that the flux-weighted 88/86Srinput and

87

Sr/86Srinput composition does not fall on the

intercept point between these fractionation and mixing lines is consistent with an elevated supply of riverine Sr to the oceans due to post-glacial weathering.

44

45

46

47

48

49

50

Table 1

River North & South America 1 Yukon 2 Peel 3 MacKenzie 4 Red Arctic 5 Fraser 6 Nass 7 Stikine 8 Solimoes 9 Madeira 10 Amazon (Obidos) 11 Orinoco

Sample ID

Date

Stage

Discharge (km3/yr)

Can 96-4 Can 96-5 Can 96-6 Can 96-7 Can 99-21 Can 99-31 Can 99-39 AM 6/1-01 AM 6/1-03 AM 6/1-14 or451

Aug-96 Aug-96 Aug-96 Aug-96 Jun-99 Jun-99 Jun-99 May-01 May-01 May-01 Mar-83

H

200

H H

308 123 112 26 24

Nov-93 Aug-94 Nov-93 Aug-94 Jun-98

L H L H H

Aug-92

H H H H H

Nov-89 Nov-89

H H

Asia 12 Changjiang (Nanjing) CH 93-1 13 Changjiang (Nanjing) CH 94-1 14 Huang He (Jinan) CH 93-6 15 Huang He (Jinan) CH 94-6 16 Narmada IND 98-2 17 Ganga IND 98-29 18 Ganges IND 99-19 19 Brahmaputra IND 99-20 20 Salween 21 Irrawaddy 22 Mekong 92-1 23 Red River (Hanoi) 92-5 Africa 24 25 26

Congo Congo Niger

Europe 27 Seine 28 Provence 29 Provence 30 Provence l'Huveane 31 Jura Ain 32 Jura Tacon 33 Jura Doubs Volcanic Islands 34 Bras David 35 Capesterre 36 Riviere de Galets 37 Java 38 Ribeira do Guilherme 39 Ribeira das Lagos

C 89-24 C 89-32

H H H H H L

SP30 PR 7-29 PR 7-30 PR 7-42 Ju 1-14 Ju 2-10 Ju 2-24

Feb-07 Feb-07 Feb-07 Nov-01 Apr-02 Nov-02

L L L M L H

AN03-17

Feb-03

H

P 20 Az2 Az3

Oct-04 Oct-04

Li

Concentration (mmol/l) Na Mg K Ca

87

Sr

Sr/86Sr

2 s.e.

d88/86Sr (‰)

2 s.e.

0.80 1.10 1.11 1.72 0.18 0.20 0.22 0.27 0.22 0.19 0.13

117.34 172.83 292.21 173.86 28.30 49.07 59.40 121.75 369.24 349.26 27.93

338.04 569.89 375.05 730.96 117.88 76.76 104.41 46.63 63.04 39.09 14.63

23.03 12.78 21.42 18.24 7.38 5.96 8.95 24.24 31.11 21.56 15.59

684.40 975.83 816.98 1238.58 401.89 211.69 222.59 218.79 98.48 136.03 35.49

1.67 1.56 2.54 2.12 0.86 0.86 0.81 0.54 0.27 0.35 0.09

0.7169408 0.7160198 0.7113664 0.7130192 0.7188562 0.7052317 0.7054814 0.7089808 0.7193634 0.7111129 0.7204937

2.42E-06 2.54E-06 2.53E-06 2.32E-06 2.36E-06 2.52E-06 2.66E-06 2.44E-06 2.65E-06 2.41E-06 2.41E-06

0.352 0.258 0.300 0.337 0.256 0.296 0.269 0.290 0.346 0.354 0.354

0.007 0.007 0.007 0.007 0.007 0.007 0.007 0.008 0.007 0.008 0.006

928 928 41 41 98 493 1003 510 211 486 467

0.77 0.66 2.69 3.00 0.50 0.63 0.53 0.39 1.78 0.27 0.84 0.43

309.61 264.11 220.28 200.65 2870.53 1038.85 2469.01 741.76 354.32 322.41 72.50 97.01 353.40 208.08 86.91 97.47 233.71 546.25 418.02 348.41 238.97 165.03 116.83 149.05

44.25 43.09 72.00 75.25 36.32 41.68 81.80 54.05 41.37 34.98 34.16 30.89

709.18 646.44 1282.17 972.69 565.68 317.56 562.37 334.49 840.49 419.76 493.01 505.25

1.86 1.63 9.78 8.17 1.08 0.44 0.97 0.53 1.47 1.18 1.42 0.74

0.7107560 0.7106519 0.7111799 0.7110898 0.7113439 0.7372323 0.7267289 0.7178790 0.7140514 0.7107564 0.7105168 0.7122183

2.35E-06 2.26E-06 2.34E-06 2.38E-06 2.66E-06 2.61E-06 2.53E-06 2.63E-06 2.58E-06 2.81E-06 3.16E-06 2.37E-06

0.260 0.292 0.291 0.304 0.302 0.327 0.316 0.397 0.283 0.261 0.338 0.298

0.008 0.007 0.008 0.008 0.007 0.007 0.012 0.007 0.007 0.007 0.007 0.006

1200 1200 154

0.55 0.55 0.12

78.54 77.09 149.04

28.81 27.09 50.50

76.08 74.76 98.17

0.23 0.22 0.51

0.7190579 0.7191849 0.7145876

2.48E-06 2.48E-06 2.58E-06

0.236 0.264 0.283

0.007 0.005 0.008

13

0.14 1.32 1.33 1.67 1.51 0.91 0.81

145.368 118.91 241.30 1339.07 235.64 1317.53 258.06 146.80 145.00 288.42 177.45 141.66 74.29 94.98

29.41 1.34 2.93 9.26 9.00 8.99 4.73

2292.78 1813.81 1864.29 2611.55 1226.17 1185.19 1259.94

1.74 0.47 0.46 2.16 1.70 1.69 0.53

0.7079670 0.7082014 0.7081967 0.7077813 0.7073630 0.7073320 0.7073537

2.47E-06 2.33E-06 2.75E-06 2.67E-06 2.70E-06 2.64E-06 2.49E-06

0.273 0.417 0.401 0.333 0.175 0.189 0.242

0.007 0.006 0.006 0.007 0.007 0.007 0.006

0.11 0.07 0.08 2.37 0.01 0.07

308.07 154.75 686.85 67.36 322.00 520.00

16.25 10.10 33.64 105.57 32.80 84.80

123.98 65.19 250.41 59.78 73.90 132.00

0.28 0.12 0.22 0.44 0.30 0.49

0.7047842 0.7047103 0.7043819 0.7080142 0.7061789 0.7058375

2.46E-06 2.42E-06 2.46E-06 2.51E-06 2.42E-06 3.08E-06

0.326 0.357 0.566 0.126 0.475 0.451

0.007 0.007 0.007 0.007 0.006 0.008

6590 1135

47.21 46.40 62.37

77.51 31.18 167.75 135.45 66.50 113.00

Table 2

Sample

Concentration (mmol/l) Na Mg K Ca

2 s.e.

d88/86Sr (‰)

2 s.e.

0.7091702 0.7091752 0.7091820 0.7091824

3.45E-06 3.31E-06 2.43E-06 2.45E-06

0.391 0.390 0.382 0.398

0.009 0.010 0.006 0.006

86.22 88.11 84.80 85.94 93.47 99.29 84.68 87.14 83.54 87.54 91.82 84.51 101.46 98.09 104.94 104.60 90.50 101.80 113.04

0.7091744 0.7091707 0.7091680 0.7091612 0.7091663 0.7091635 0.7091581 0.7091628 0.7091643 0.7091603 0.7091720 0.7091563 0.7091646 0.7091713 0.7091739 0.7091663 0.7091812 0.7091635 0.7091701

2.56E-06 2.22E-06 2.41E-06 2.52E-06 4.27E-06 2.59E-06 2.40E-06 2.66E-06 2.78E-06 2.59E-06 2.43E-06 2.35E-06 2.65E-06 2.69E-06 2.38E-06 2.66E-06 1.27E-06 2.42E-06 2.51E-06

0.398 0.368 0.369 0.338 0.385 0.346 0.353 0.338 0.398 0.351 0.418 0.346 0.412 0.361 0.421 0.372 0.422 0.355 0.396

0.007 0.006 0.007 0.006 0.008 0.007 0.006 0.007 0.006 0.006 0.008 0.006 0.008 0.006 0.008 0.006 0.007 0.006 0.008

89.6 57.9 40.7 85.3 43.7

0.7083608 0.7054710 0.7036223 0.7091579 0.7038693

2.51E-06 2.51E-06 2.93E-06 2.44E-06 2.46E-06

0.371 0.422 0.328 0.376 0.362

0.006 0.013 0.011 0.014 0.006

BHVO2 (1) BHVO2 (2) BHVO2 (3) BHVO2 (4) BIR BCR

0.7034742 0.7034648 0.7034687 0.7034726 0.7030960 0.7050029

2.77E-06 2.32E-06 2.42E-06 2.20E-06 3.80E-06 2.65E-06

0.228 0.238 0.244 0.249 0.232 0.242

0.015 0.014 0.014 0.014 0.014 0.014

BP-1 BP-2 BP-3 BP-4 BP-5 CY-4a-A Kaiserstuhl 1 Kaiserstuhl 2 Mascatine "P" Composite B2 E1 G1-C L1

0.7096810 0.7095729 0.7091233 0.7096935 0.7098367 0.7180153 0.7095331 0.7100140 0.7151155 0.7167512 0.7133533 0.7099110 0.7117797 0.7075192 0.7081234

2.49E-06 2.34E-06 2.80E-06 2.47E-06 2.57E-06 2.42E-06 3.16E-06 2.41E-06 2.53E-06 2.36E-06 2.49E-06 2.42E-06 3.16E-06 2.52E-06 2.37E-06

0.249 0.289 0.253 0.251 0.255 0.177 0.206 0.200 0.264 0.203 0.218 0.264 0.255 0.270 0.285

0.007 0.007 0.007 0.007 0.008 0.008 0.007 0.007 0.011 0.007 0.006 0.007 0.009 0.007 0.007

Sample ID/Depth

Li

87

Sr

Sr/86Sr

Seawater IAPSO Atlantic Ocean Indian Ocean Pacific Ocean

Batch 148

Porewater STA 119 Bottom Water JGOFS 48-1 JGOFS 48-3 JGOFS 48-7 JGOFS 48-9 JGOFS 48-11 JGOFS 48-13 JGOFS 77-1 JGOFS 77-7 JGOFS 77-10 JGOFS 77-12 JGOFS 77-15 ANA-OLW ANA-1 ANA-3 ANA-4 ANA-5 ANA-7 ANA-11

0.00 cm 0.25 cm 1.50 cm 6.00 cm 10.00 cm 14.00 cm 20.50 cm 0.25 cm 6.00 cm 12.00 cm 17.50 cm 28.00 cm 0.00 cm 1.00 cm 6.72 cm 9.57 cm 12.43 cm 18.15 cm 29.58 cm

Hydrothermal fluid TAG Snakepit Broken Spur (site 3,3) Broken Spur (site 4,1) Broken Spur (site 4,2)

BS 02 BS 04 BS 07 BS 12 BS 13

Basalt USGS standard USGS standard USGS standard USGS standard USGS standard USGS standard Continental dust Banks Peninsula, NZ Banks Peninsula, NZ Banks Peninsula, NZ Banks Peninsula, NZ Banks Peninsula, NZ Kansas, USA Rhine Valley, Germany Rhine Valley, Germany Nanking, China Iowa, USA Hungary Baradero, Argentina El Lambedero, Argentina Gorina, Argentina Lozada, Argentina Glacial ice Langjökull Glacier Russell Glacier Rainwater Azores Congo China China

22.73 23.65 23.33 23.27 24.87 27.78 23.34 23.22 22.68 25.08 26.42 25.40 25.98 26.54 28.21 27.63 23.75 25.86 28.66

50216 53446 51882 51882 56161 61860 52541 52376 51697 54166 57354 52767 60276 59144 63300 62621 54886 60893 67250

9534 10316 10338 10213 10978 12348 10209 10365 10181 10928 11371 10533 11667 11388 12166 12061 10501 11781 12942

9862 10064 9911 9816 11078 11340 9725 10068 9957 10436 11145 10018 11524 11379 12433 12488 10707 12056 13374

43300 14000 850 52800 1910

GR3

0.01 0.01

191.39 140.93

7.97 1.92

8.65 27.19

3.04 1.52

0.02 0.01

0.7100639 0.7150679

2.91E-06 3.00E-06

0.241 0.089

0.008 0.007

C89 (P1-4) CH94 (6-7:20) CH94 (8-13:00)

0.02 0.01 0.05

160.20 66.94 155.20

16.79 1.23 3.77

13.82 3.14 26.52

11.44 2.21 24.71

0.06 0.02 0.23

0.7072687 0.7125862 0.7119698 0.7112161

2.47E-06 3.60E-06 3.72E-06 2.44E-06

0.317 0.052 0.192 0.310

0.007 0.006 0.007 0.006

Table 3

Flux Component Riverine discharge Hydrothermal fluids Porewater fluids Groundwater discharge Net Input

Sr Flux (109 mol/yr) 33.30 2.33 3.40 7.10 46.13

Seawater Carbonate burial

174.00

87

Sr/86Sr

d88/86Sr (‰)

0.71299 0.70366 0.70918 0.70890 0.71161

6.54E-04 6.73E-04 6.22E-06 n.d. 5.93E-04

0.317 0.240 0.390 0.354 0.324

0.005 0.008 0.029 0.028 0.015

0.70918

5.85E-06

0.390

0.007

0.70918

2.00E-05

0.150

0.020

Appendix A1

River North & South America Yukon Peel MacKenzie MacKenzie* MacKenzie avg. Red Arctic Fraser Fraser* Fraser avg. Nass Stikine Solimoes Madeira Amazon (Obidos) Orinoco Hudson* Maipo* St Lawrence* Asia Changjiang (Nanjing) Changjiang (Nanjing) Changjiang* Changjiang avg. Huang He (Jinan) Huang He (Jinan) Huang He avg. Narmada Ganga Ganga* Ganga avg. Ganges Brahmaputra Brahmaputra* Brahmaputra avg. Salween Irrawaddy Mekong Red River (Hanoi) Indus* Lena* Xijiang§

Sample ID/depth

Date

Stage

Discharge (km3/yr)

Can 96-4 Can 96-5 Can 96-6

Aug-96 Aug-96 Aug-96 Apr-07

H

200

H

Can 96-7 Can 99-21

Aug-96 Jun-99 Aug-06

H

Can 99-31 Can 99-39 AM 6/1-01 AM 6/1-03 AM 6/1-14 or451

Jun-99 Jun-99 May-01 May-01 May-01 Mar-83 Jul-08 Jan-07 May-08

H H H H H L

308 308 308 123 112 112 112 26 24

Nov-93 Aug-94 2007

L H

CH 93-1 CH 94-1

CH 93-6 CH 94-6 IND 98-2 IND 98-29

H H H

98 493 493 493 1003 510 510 510 211 486 467

2010

-

90 525 363

Nov-89 Nov-89

H H 1200 154

0.23 0.22 0.23 0.51

12.9 207 69.4

0.47 0.46 2.16 1.70 1.69 0.53 1.74 2.76 6.23

Nov-93 Aug-94 Jun-98

L H H

H H

IND 99-19 IND 99-20 Jun-06

Aug-92 Feb-07

928 928 900 919

1.67 1.56 2.54 2.37 2.46 2.12 0.86 0.85 0.86 0.86 0.81 0.54 0.27 0.35 0.09 1.45 31.85 1.48 1.86 1.63 2.23 1.91 9.78 8.17 8.98 1.08 0.44 0.66 0.55 0.97 0.53 0.64 0.59 1.47 1.18 1.42 0.74 3.33 1.10 1.00

Aug-07

92-1 92-5

6590 1135 12 3.6 337

(108 [Sr] (mmol/l) Sr Flux mol/yr)

2 s.e.

d88/86Sr (‰)

2 s.e.

d44/42Ca (‰)

2 s.e.

d26/24Mg (‰)

2 s.e.

d7/6Li (‰)

2 s.e.

0.7169408 0.7160198 0.7113664 0.7114420 0.7114042 0.7130192 0.7188562 0.7186620 0.7187591 0.7052317 0.7054814 0.7089808 0.7193634 0.7111129 0.7204937 0.7103280

2.42E-06 2.54E-06 2.53E-06 8.00E-06 4.20E-06 2.32E-06 2.36E-06 1.00E-06 1.28E-06 2.52E-06 2.66E-06 2.44E-06 2.65E-06 2.41E-06 2.41E-06 1.00E-06

0.020 0.030

0.113 0.008 0.023

17.9 13.3 15

0.2 0.1 0.2

0.7137

0.370

-0.860 -1.543 -1.393

0.320

0.030

-1.584

0.066

13.8 17.5

0.1 0.1

0.7114 0.7116

0.350 0.460 0.250 0.340 0.310 0.310

0.060 0.020 0.000 0.020 0.020 0.070

-0.860

0.080

21.6 21.7

0.1 0.1

0.7054 0.7054

-1.030 -0.650

0.070 0.100

7.00E-06

0.007 0.007 0.007 0.020 0.011 0.007 0.007 0.020 0.011 0.007 0.007 0.008 0.007 0.008 0.006 0.001 0.020 0.030

0.390

0.7103620

0.352 0.258 0.300 0.320 0.310 0.337 0.256 0.310 0.283 0.296 0.269 0.290 0.346 0.354 0.354 0.260 0.420 0.340

3.00 5.78 3.63

0.7107560 0.7106519 0.7105870 0.7106650 0.7111799 0.7110898 0.7111348 0.7113439 0.7372323 0.7277020 0.7324672 0.7267289 0.7178790 0.7192180 0.7185485 0.7140514 0.7107564 0.7105168 0.7122183 0.7110030 0.7095360 0.7096000

2.35E-06 2.26E-06 7.00E-06 2.57E-06 2.34E-06 2.38E-06 1.67E-06 2.66E-06 2.61E-06 9.00E-06 4.69E-06 2.53E-06 2.63E-06 2.60E-05 1.31E-05 2.58E-06 2.81E-06 3.16E-06 2.37E-06 2.40E-05 2.00E-05

0.260 0.292 0.380 0.311 0.291 0.304 0.297 0.302 0.327 0.250 0.288 0.316 0.397 0.317 0.357 0.283 0.261 0.338 0.298 0.310 0.243 0.380

0.008 0.007 0.050 0.017 0.008 0.008 0.006 0.007 0.007 0.020 0.011 0.012 0.007 0.001 0.003 0.007 0.007 0.007 0.006 0.010 0.006

2.72 0.78

0.7190579 0.7191849 0.7191214 0.7145876

2.48E-06 2.48E-06 1.75E-06 2.58E-06

0.236 0.264 0.250 0.283

0.007 0.005 0.004 0.008

0.22 5.71 4.32

0.7082014 0.7081967 0.7077813 0.7073630 0.7073320 0.7073537 0.7079670 0.7127230 0.7093770

2.33E-06 2.75E-06 2.67E-06 2.70E-06 2.64E-06 2.49E-06 2.47E-06 7.00E-06 9.00E-06

0.417 0.401 0.333 0.175 0.189 0.242 0.273 0.254 0.240

0.006 0.006 0.007 0.007 0.007 0.006 0.007 0.004 0.010

0.7047842

2.46E-06

0.326

0.007

3.34 7.82 7.30 7.56 2.61 0.96 0.96 0.96 0.22 0.19

23.28 1.04 0.17 1.15 4.99 17.28 15.08 20.08 17.48

1.05 2.15 3.25 2.70 9.77 2.73 3.25 2.99 3.09 5.74 6.65

87

Sr/86Sr

87

Sr/86Sr

0.7112

0.7112 0.7183

0.7108 0.7108

0.450

0.080

0.450 0.360 0.690 0.525 0.570 0.380

0.080 0.080 0.050 0.047 0.030 0.070

-1.450

0.030

-1.450 -1.160 -0.530

0.030 0.060 0.090

0.380

0.035

-0.530

0.090

-1.390

0.060 0.060 0.020 0.050 0.040 0.020

0.714 0.7101 0.7102

0.7192

0.310 0.390 0.430 0.440

0.030 0.040 0.040 0.010

-1.390 -0.980 -0.820 -0.860 -1.120

0.270

0.100

-0.590

0.090

0.270

0.100

-0.590

0.090

0.7112 0.7111 0.7125

0.7306 0.7179

Africa Congo Congo Congo avg. Niger

C 89-24 C 89-32

0.714

Europe Provence Provence Provence Jura Ain Jura Tacon Jura Doubs Seine Danube* Rhine* Volcanic Islands Bras David

PR 7-29 PR 7-30 PR 7-42 Ju 1-14 Ju 2-10 Ju 2-24 SP30

Feb-07 Feb-07 Feb-07 Nov-01 Apr-02 Nov-02

L L L M L H

May-07 Aug-07 AN03-17

Feb-03

H

0.28

0.320 0.440 0.590 0.410

0.070 0.070 0.080 0.060

0.400

0.060

0.7073 0.7073 0.7074

-0.500

0.020

2 s.e.

Appendix A2

River

Discharge (km3/yr)

[Sr] (mmol/l)

Sr Flux (108 mol/yr)

Amazon Orinoco Maipo* Changjiang Huang He Narmada Ganga Ganges Brahmaputra Salween Irrawaddy Mekong Indus* Lena* Xijiang** Congo Niger Seine Danube* Rhine* Indonesia

6590 1135 4 919 41 98 493 1003 510 211 486 467 90 525 363 1200 154 13 207 69 1734

0.35 0.09 31.85 1.91 8.98 1.08 0.55 0.97 0.59 1.47 1.18 1.42 3.33 1.10 1 0.23 0.51 1.74 2.76 6.23 0.36

23.28 1.04 1.15 17.48 3.68 1.05 2.70 9.77 2.99 3.09 5.74 6.65 3.00 5.78 3.63 2.72 0.78 0.22 5.71 4.32 6.23

Yukon MacKenzie Red Arctic Fraser Nass Stikine St Lawrence* Hudson*

200 308 123 112 26 24 337 12

1.67 2.46 2.12 0.86 0.86 0.81 1.48 1.45

2 s.e.

d88/86Sr (‰)

2 s.e.

0.711113 0.720494 n.d. 0.710665 0.711135 0.711344 0.732467 0.726729 0.718549 0.714051 0.710756 0.710517 0.711003 0.709536 0.709600 0.719121 0.714588 0.707967 0.712723 0.709377 0.706061

2.41E-06 2.41E-06 n.d. 2.57E-06 1.67E-06 2.66E-06 4.69E-06 2.53E-06 1.31E-05 2.58E-06 2.81E-06 3.16E-06 2.40E-05 2.00E-05 n.d. 1.75E-06 2.58E-06 2.47E-06 7.00E-06 9.00E-06 1.21E-06

0.354 0.354 0.420 0.311 0.297 0.302 0.288 0.316 0.357 0.283 0.261 0.338 0.310 0.243 0.380 0.250 0.283 0.273 0.254 0.240 0.386

0.008 0.006 0.020 0.017 0.006 0.007 0.011 0.012 0.003 0.007 0.007 0.007 0.010 0.006 n.d. 0.004 0.008 0.007 0.004 0.010 0.004

3.34 7.56 2.61 0.96 0.22 0.19 4.99 0.17

0.716941 0.711404 0.713019 0.718759 0.705232 0.705481 0.710362 0.710328

2.42E-06 4.20E-06 2.32E-06 1.28E-06 2.52E-06 2.66E-06 7.00E-06 1.00E-06

0.352 0.310 0.337 0.283 0.296 0.269 0.340 0.260

0.007 0.011 0.007 0.011 0.007 0.007 0.030 0.001

Non-glaciated rivers Glaciated rivers

111.01 20.05

0.713085 0.712493

n.d. n.d.

0.316 0.326

n.d. n.d.

All analysed rivers

131.06

0.712994

6.54E-04

0.317

0.005

87

Sr/86Sr