Testing carbonate-associated sulfate (CAS) extraction methods for sulfur isotope stratigraphy: A case study of a Lower–Middle Ordovician carbonate succession, Shingle Pass, Nevada, USA

Chemical Geology 529 (2019) 119297

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Testing carbonate-associated sulfate (CAS) extraction methods for sulfur isotope stratigraphy: A case study of a Lower–Middle Ordovician carbonate succession, Shingle Pass, Nevada, USA

T

⁎

Cole T. Edwardsa,b, , David A. Fikeb, Matthew R. Saltzmanc a

Department of Geological and Environmental Sciences, Appalachian State University, Boone, NC 28608, United States of America Department of Earth and Planetary Sciences, Washington University in Saint Louis, Saint Louis, MO 63130, United States of America c School of Earth Sciences, The Ohio State University, Columbus, OH 43210, United States of America b

A R T I C LE I N FO

A B S T R A C T

Editor: Michael E. Böttcher

Sulfur isotopes measured from sedimentary rocks are used to reconstruct the global sulfur cycle and chemostratigraphic correlation. Relative and absolute changes in the sulfur isotopic composition of the ocean (δ34Sseawater) are essential for estimating changes in redox conditions in ancient environments, particularly for geochemical models that utilize isotope mass balance. Thus, accurate estimates of δ34Sseawater must be measured using a laboratory protocol optimized for the extraction of primary sulfate (preserved as carbonate-associated sulfate; CAS) by removing any contaminant secondary sulfate (e.g., from diagenetic pyrite oxidation). Here we use two CAS-extraction protocols on Lower–Middle Ordovician carbonate rocks to test the degree to which similar absolute values and stratigraphic trends in δ34SCAS are produced by different CAS extraction methods. One method processes carbonate powders once with a single rinse of a 10% NaCl solution to remove sulfate minerals or weakly bonded sulfate ions, followed by a rinse in 5–6% bleach to remove organically bound sulfur before dissolution in hydrochloric acid (HCl). The second method treats carbonate powders with three rinses of NaCl, without a bleach rinse, to more aggressively remove secondary sulfate before dissolution in HCl. Isotopic results show that samples treated in three NaCl rinses produce δ34SCAS values that are on average 7‰ more positive than samples treated with a single NaCl rinse, but a similar stratigraphic trend is preserved in samples processed with either method. We interpret the difference in δ34SCAS between methods to reflect the incomplete removal of secondary sulfate derived from the oxidation of 32S-enriched pyrite when employing only a single NaCl rinse. Surprisingly, rocks with low CAS concentrations (≤10 mg/kg) using both methods show no significant difference in δ34SCAS values, as well as no significant difference in pyrite concentrations and pyrite δ34S (δ34SPY) between methods. Samples with low CAS concentrations are likely altered and secondary sulfate sourced from pyrite oxidation has likely become incorporated into recrystallized carbonate minerals or incorporated into pore-filling calcite cement, all of which is captured as CAS. Results suggest that both CASextraction protocols can produce broadly similar δ34SCAS trends, but a single NaCl rinse may not completely remove contaminant sulfate sorbed onto carbonate grains and thus will not yield meaningful data for reconstructing δ34Sseawater. This has clear implications for modeling studies aimed at reconstructing paleo-redox conditions using δ34S data assumed to record global δ34Sseawater trends if these δ34S data are generated using a non-optimized CAS protocol.

Keywords: Sulfur isotopes Carbonate-associated sulfate Sedimentary pyrite Ordovician

1. Introduction The sulfur isotopic composition (δ34S) of the global ocean reservoir has varied throughout Earth history due to changes in sulfur fluxes (and their isotopic compositions) into and out of the marine sulfate reservoir. These isotopic data as preserved in the rock record are used to

⁎

document regional to global changes in seawater δ34S and reconstruct global sulfur cycling, as well as for chemostratigraphic studies to correlate stratigraphic sections within and between basins (e.g., Gill et al., 2011; Gomes et al., 2016; Hurtgen et al., 2006; Jones and Fike, 2013; Kampschulte and Strauss, 2004; Marenco et al., 2008b; Newton et al., 2004; Owens et al., 2013; Strauss, 1999; Thompson and Kah, 2012;

Corresponding author at: Department of Geological and Environmental Sciences, Appalachian State University, Boone, NC 28608, United States of America. E-mail address: [email protected] (C.T. Edwards).

https://doi.org/10.1016/j.chemgeo.2019.119297 Received 28 February 2019; Received in revised form 5 September 2019; Accepted 6 September 2019 Available online 07 September 2019 0009-2541/ © 2019 Elsevier B.V. All rights reserved.

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of these data relative to that of other δ34Sseawater proxies. Carbonate cementation within sediment during lithification and early diagenesis can incorporate CAS with a δ34S signature that has diverged from δ34Sseawater, if for example, cementation in porewaters incorporates 34Senriched sulfate during microbial sulfate reduction (Fike et al., 2015). Further, CAS abundance and isotopic composition can be reset by exchange of sulfate with diagenetic fluids during later-stage carbonate recrystallization. While resetting or alteration during recent meteoric diagenesis of modern carbonate systems does not always impact δ34SCAS (though CAS concentrations are lowered; e.g., Gill et al., 2008), this is not always true in deep time. A recent study by Present et al. (2015) micro-drilled individual phases of calcitic fossils, micrite, and bulk carbonate rock from a single Late Ordovician carbonate succession and demonstrate that large (~20‰) variations in δ34SCAS between carbonate phases are preserved. In some instances δ34SCAS values are more positive than well-preserved brachiopods, which cannot be explained by pyrite oxidation and would require incorporation of chemically evolved (distilled) porewater sulfate. This wide variation is likely due to diagenetic processes occurring on a microscale, particularly if pyrite oxidation occurs in micritic sediment to produce lower δ34SCAS values relative to individual well-preserved brachiopods. Finally, in addition to CAS, carbonate rocks can also contain several other sulfur sources, including secondary sulfate minerals, organic-bound sulfur, and sulfide minerals (e.g., pyrite or metastable metal-sulfides) that each can have unique δ34S signatures. Depending on diagenetic conditions and laboratory extraction protocols, these phases may be inadvertently sampled during CAS extraction (Marenco et al., 2008a; Peng et al., 2014; Wotte et al., 2012a). For example, weathering effects on carbonate rocks exposed in some arid or heavily polluted environments have also been shown to decrease apparent δ34SCAS values via contamination by isotopically light secondary atmospheric sulfate (from oxidized atmospheric SO2 enriched in 17O; Peng et al., 2014). These potential alteration effects must be considered when interpreting low δ34S values as reflective of the marine sulfate reservoir. Sedimentary pyrite, in particular, is important to isolate from CAS during the extraction process because it can have δ34S values as much as 70‰ offset from primary δ34Sseawater (Sim et al., 2011; Wing and Halevy, 2014; Wortmann et al., 2001). In general, post-deposition sulfide oxidation, which can occur at any point between early diagenesis and laboratory CAS extraction, can produce sulfate that could be included in the extracted CAS pool, resulting in lower δ34SCAS values and therefore inaccurate estimates of δ34Sseawater. Thus it is essential to use a protocol that captures CAS most representative of coeval seawater sulfate (i.e., δ34SCAS ≈ δ34Sseawater) by removing any sulfate component arising from post-depositional sulfide oxidation during extraction. It should be noted that no protocol for bulk carbonate rock δ34S can distinguish CAS preserved in a potential range of CaCO3 cements (precipitated from chemically evolved porewaters) from primary carbonate grains. As such, all CAS-bearing carbonate cement that forms between grains would be collected along with the CAS preserved in carbonate grains, thus representing a bulk value. Here we present paired δ34SCAS and δ34SPY data from a single stratigraphic section at Shingle Pass, NV in the Great Basin region (USA) processed using two different CAS protocols, each thought to be capable of reproducing δ34Sseawater values (cf. Gill et al., 2011; Wotte et al., 2012a). Some of the δ34SCAS and δ34SPY values presented here were previously published (Edwards et al., 2018) to study regional chemostratigraphic correlation focused on a paired extinction and positive δ13C excursion event, but the purpose of this study is to compare δ34SCAS and δ34SPY values measured from a single section using two CAS protocols to see how lithology impacts δ34SCAS preservation. Our sampling protocol targeted the relatively dominant fine-grained lithologies because high-resolution sampling of potentially well-preserved bioclasts is not always possible (cf. Present et al., 2015; Rennie et al., 2018), but other lithologies were sampled to maintain a consistent sampling frequency. Though micritic components in hand-sample can potentially exhibit

Wotte et al., 2012b; Wotte and Strauss, 2015) Understanding the relative and absolute magnitude of δ34S variation is particularly important for studies that model the global sulfur cycle and atmospheric oxygen (O2) levels using isotope mass balance (Berner, 2006). Other studies model the size of the ocean sulfate reservoir using the magnitude (and inferred rate) of δ34S variation from a single stratigraphic section (Kah et al., 2004; Thompson and Kah, 2012) as well as the magnitude and duration of δ34S excursions in the rock record (Gill et al., 2011). For this style of modeling it is critical to use proxies that accurately record the isotopic composition of seawater sulfate (δ34Sseawater) because even slight differences in δ34S values can affect estimates of the sulfate reservoir size and inferred atmospheric O2 levels. This is particularly true for much of Earth's history when the sulfate reservoir was smaller compared to the (near-) modern ocean (Wortmann and Paytan, 2012) or late Paleozoic (Gill et al., 2007) and local effects (e.g., higher pyrite burial/weathering into a restricted basin) could more easily overprint a global signal. When trying to reconstruct δ34Sseawater, it is paramount to use a laboratory protocol optimized to extract sulfate that most accurately reflects primary δ34Sseawater, minimizing contamination from other sulfur sources throughout the extraction process. Traditional δ34Sseawater proxies include marine barite (Paytan and Kastner, 1998) and sulfate evaporites (gypsum and anhydrite; Claypool et al., 1980) because these minerals precipitate directly from seawater, are relatively straightforward to isolate for δ34S analysis, and the fractionation effect associated with their formation is relatively small (1–2‰; Raab and Spiro, 1991; Thode and Monster, 1965). However, evaporites are by definition chemically evolved from seawater and also temporally and spatially sparse in the geologic record, whereas the barite record, based on deep-sea sediment records, has not been extended into strata older than the Cretaceous (Paytan et al., 2004). For pre-Jurassic strata where deep-sea sediment records are not preserved, one must use other approaches to reconstruct seawater sulfate δ34S trends. Carbonate-associated sulfate (CAS), sulfate incorporated into the carbonate mineral lattice, can preserve δ34S trends in deep time similar to other δ34Sseawater proxies (Kampschulte and Strauss, 2004; Rennie et al., 2018; Strauss, 2004, 1999). CAS is becoming regularly used for δ34S stratigraphy and reconstructing high-resolution records of δ34Sseawater because carbonate successions typically have superior temporal resolution, and for Phanerozoic successions with previously published biostratigraphic age control, the ages of these units are well calibrated in comparison to non-fossil bearing Precambrian successions (Fike et al., 2006; Fike and Grotzinger, 2008; Gill et al., 2011; Gomes et al., 2016; Kampschulte and Strauss, 2004; Owens et al., 2013; Strauss, 2004; Wotte et al., 2012b; Wotte and Strauss, 2015; Young et al., 2016). Records of δ34SCAS isolated from individually picked foraminifera from non-lithified sediment have minimal sample-to-sample variability within a single stratigraphic section (Burdett et al., 1989; Rennie et al., 2018), consistent with reflecting a marine sulfate signal. However, this kind of approach cannot be used for most deep-time studies where only lithified shallow water carbonate facies are available for sampling. Furthermore, many of the deep-time bulk rock δ34SCAS data are often characterized by high-frequency variability ( ± 5‰; e.g., Kampschulte and Strauss, 2004; Young et al., 2016) that are hard to reconcile with changes in the marine sulfate reservoir (e.g., Jones and Fike, 2013). It is difficult to determine whether variable δ34SCAS values reflect an environmentally meaningful signal (i.e., acquired during deposition) versus diagenetic alteration unless other in situ techniques are used (Richardson et al., 2019). Integrating petrographic study and other geochemical proxies (e.g., isotopic and elemental abundance crossplots) may identify intervals that may be severely altered and potentially explain some δ34SCAS variation, but the absence of alteration based on other approaches (e.g., δ13C-δ18O, Mn/Sr) does not necessarily mean that seawater δ34S is preserved. There are many additional factors in marine carbonate formation that can give rise to variations in δ34SCAS and complicate interpretation 2

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41ºN

Salt Lake City

Ely NEVADA

39ºN

Shingle Pass Las Vegas

UTAH 37ºN

ARIZONA

CALIFORNIA 120ºW

117ºW

300 km 114ºW

111ºW

Late Ordovician 450 Ma Fig. 1. Paleogeographic reconstruction of the Late Ordovician (450 Ma) showing the approximate location of where Shingle Pass (SP) was located along the margin of Laurentia. Modified from Blakey and Ranney (2018). Inset: location map of Great Basin region, western USA, with location of the Shingle Pass section (see Edwards and Saltzman (2014) for more locality details).

highly variable δ34SCAS values (Present et al., 2015), it is also possible that bulk micrite sampling can preserve values similar to what wellpreserved skeletal grains record (Present et al., 2015, their fig. 10). As such, in addition to testing how CAS extraction protocols can affect δ34SCAS trends, we are also interested in the wider question of the impact of lithology on δ34SCAS values, not just from the fine-grained facies. We show that both protocols yield similar trends and variability in δ34SCAS and δ34SPY, but the magnitude of δ34SCAS can be up to 12.5‰ different between the two protocols. For samples processed with both methods and with respect to CAS yield, a majority of samples processed using a single rinse in 10% NaCl and bleach broadly correlates to lower δ34SCAS values and large δ34SCAS variability compared to samples processed using three rinses in NaCl and no bleach rinse. We suggest this difference in CAS yield and δ34SCAS values reflects incomplete removal of sulfate derived from late-stage sulfide oxidation and therefore a less faithful record of a δ34Sseawater signal in methods using a single NaCl rinse. The degree of variation between these methods was also dependent on facies: fine-grained facies (namely lime mudstone) generally produces more stratigraphically coherent δ34SCAS values, seemingly more representative of what δ34Sseawater trends may be, whereas coarsegrained, reworked or recrystallized facies (e.g., flat-pebble conglomerate and wacke–packstone) are commonly associated with increased scatter or lower δ34SCAS values and may therefore be less ideal for reconstructing δ34Sseawater.

2. Background 2.1. Sulfur cycle – fluxes, reservoirs, and isotopic values The global sulfur cycle is generally controlled by 1) fluxes of riverine sulfate from weathered sulfur-bearing minerals delivered into the oceans and 2) sulfate removal from the ocean reservoir via burial of sulfate minerals and sulfides (predominantly pyrite and organic S) (Berner and Raiswell, 1983; Bottrell and Newton, 2006; Canfield, 2004; Garrels and Lerman, 1984; Halevy et al., 2012; Raven et al., 2016; Strauss, 1997), as well as fluctuations in volcanic outgassing of sulfur (as SO2) from the mantle (Canfield, 2004). Each of these fluxes can have a unique δ34S signature, but the greatest factor responsible for the isotopic variation of the marine sulfate reservoir throughout the Phanerozoic is the expression of the isotopic fractionation effect associated with microbial sulfate reduction (MSR) and its subsequent incorporation into 32S-enriched pyrite minerals (Berner and Raiswell, 1983). Sedimentary pyrite forms primarily via MSR in marine sediments where sulfate-reducing microbes metabolize sulfate (SO4) to hydrogen sulfide (H2S), which forms metastable iron sulfides and eventually pyrite (FeS2) in the presence of available reactive iron. Microbial sulfate reduction preferentially enriches the H2S product in 32S and causes δ34S in the remaining sulfate reservoir to increase with continued MSR and pyrite burial. Experimental studies of pure cultures in the laboratory have measured a fractionation difference between 2 and 70‰ from this microbial reduction (Canfield, 2001a; Detmers et al., 2001; Habicht et al., 2005; Leavitt et al., 2013; Sim et al., 2011), although modeling

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contains a greater fraction of siliciclastic mud that forms thin-medium wavy-bedded silty lime mudstone in the lower half (Edwards and Saltzman, 2014). Lithologies gradually contain less siliciclastic mud in the upper half of the Parker Spring Formation and have increasingly abundant signs of wave influence and winnowing with the abundance of flat-pebble conglomerate and lime mudstone–wackestone interbeds increasing upsection. The upper contact of the Parker Spring Formation is sharp where flat-pebble conglomerate and silty limestone lithologies are overlain by medium-bedded burrowed and stromatolitic lime mudstone of the Shingle Limestone. The Shingle Limestone contains two prominent cliff-forming units of massive-bedded lime mudstone–wackestone with occasional flat-pebble conglomerate, fossiliferous packstone, sponge-algal buildups, and oncolitic shoals (Ross et al., 1989). The contact between the Shingle Limestone and overlying Kanosh Shale is gradational over several meters where increasing amounts of red-orange silty lime mudstone–packstone and siltstone interbeds are present. The siliciclastic content of the Kanosh Shale increases upsection where the poorly exposed upper half is composed of red-orange shale and calcareous siltstone. The upper contact with the Lehman Formation is a gradational lithologic change over several meters with decreasing red-orange silty limestone and increasing amounts of massive gray-blue bioturbated lime mudstone. The lithologies of the lower Lehman Formation grade into fossiliferous wackestone–packstone with thin silty interbeds that form wavy-nodular bedding (“ribbon limestone”). Fossil content increases upsection where ostracods, tabulate corals, nautiloid cephalopods, and trilobites (Isotelus sp.) are common in the uppermost 50 m. The overlying contact with the Eureka Quartzite is gradational where thin quartz sand interbeds increase upsection in abundance and thickness in the uppermost 5–10 m of the Lehman Formation. The basal beds of the Eureka Quartzite are medium-bedded quartz arenite lithologies with evidence of shallow subtidal conditions with the presence of ripple cross-bedding and bioturbation (ichnogenera Planolites). Regional mapping of facies associations near Shingle Pass indicates that the strata comprising the Pogonip Group accumulated under shallow subtidal conditions near fair-weather wave base and were influenced by passing tropical storms near the paleo-equator (Fig. 1; Ross et al., 1989; Finnegan and Droser, 2005), which were possibly also responsible for the highly reworked flat-pebble conglomerate facies in the Parker Spring Formation and Shingle Limestone. Carbonate production ceased when nearshore reworked quartz sand of the Eureka

suggests that a biological fractionation close to the ~70‰ thermodynamic limit is representative of most marine environments (Wing and Halevy, 2014). This prediction stands in stark contrast to the observation that the offset between sulfate and pyrite is typically ~30–40‰ in many natural environments (Canfield, 2001b; Gomes and Hurtgen, 2015; Habicht and Canfield, 2001). This apparent contrast could be explained by more substantial variation in biological fractionation than is generally believed, possibly associated with intervals of sulfate limitation deeper in the geologic record (e.g., Habicht et al., 2002). A more likely explanation relies on the fact that pyrite that forms within the sediment column can have elevated δ34S signatures as the result of progressive distillation of the sulfate during partial closed system behavior (Claypool, 2004; Gomes and Hurtgen, 2013; Ku et al., 1999). Other potential factors that can influence δ34S values during MSR can include environmental factors such as sulfate concentrations, labile organic matter availability, temperature, and nutrients (Gomes and Hurtgen, 2015), in addition to biological controls like cellular growth rates (Leavitt et al., 2013). Changes in these processes are thought to contribute to some variation in δ34S trends on short-term geologic timescales (< 1–2 Myr) (Gomes et al., 2016; Jones and Fike, 2013), but whether these drivers can be sustained on multi-million year timescales has yet to be shown.

2.2. Geologic setting Lower–Middle Ordovician strata of the Great Basin region record mixed carbonate and siliciclastic sedimentation on a carbonate ramp (Ross et al., 1989). The Shingle Pass section (Fig. 1; 38° 31′21″ N, 114° 57′29″ W) has been previously studied for its conodont biostratigraphy (Sweet and Tolbert, 1997; which can provide interpolated age estimates for the measured section when precise radiometric ages from zirconbearning volcanic bentonites are not available) and δ13C record, which is interpreted to record a global carbon isotopic signal based on chemostratigraphic correlation (Edwards and Saltzman, 2014, 2016). The studied interval includes the Pogonip Group that comprises (from base to top) the House Limestone, Parker Spring Formation, Shingle Limestone, Kanosh Shale, Lehman Formation, and Eureka Quartzite (Fig. 2). The House Limestone is primarily composed of sparsely fossiliferous lime mudstone, siliciclastic mud-laminated beds, and is marked by occasional bioturbation and chert nodules. The overlying Parker Spring Formation has a sharp but apparently conformable basal contact and Period

Series

Stage

Conodont Zone

Lithostratigraphy

Darriwilian

Reutterodus andinus

-2

-1

0

1

2

Lehman Fm.

Shale Lime mudstone– wackestone Silty limestone

10

20

30

40

0

100

200

300 -20

-10

0

10

20

30

0

100

200

300

Kanosh Shale

Bioturbated limestone Reworked limestone with FPG Cherty limestone

Shingle Limestone

Diaphorodus deltatus/ Oneotodus costatus

Parker Spring Fm.

Macerodus dianae Low Diversity Interval

I

C. proavus

1x NaCl rinse 3x NaCl rinse

100 m

House Limestone

L

0m

C. intermedius

not defined

Stage 10

-3

Dolomite

Pogonip Group

Dapingian

Tripodus laevis

A

Furon.

-4

Histiodella altifrons

Oepikodus communis

Tremadocian

Lower Ordovician

Histiodella holodentata

Rossodus manitouensis

Camb.

-5

Sandstone

Histiodella sinuosa

Floian

Ordovician

Middle Ordovician

Eureka Quartzite Phragmodus polonicus

Whipple Cave Fm.

-5

-4

-3 13

-2

-1

0

1

Ccarb (‰ – VPDB)

2

10

20 34

30

40

0

SCAS (‰ – VCDT)

100

200

CAS (mg/kg)

300 -20

-10

0 34

10

20

SPY (‰ – VCDT)

30

0

100

200

300

Pyrite (mg/kg)

Fig. 2. δ13Ccarb and δ34S data from Shingle Pass, NV. Black line through δ13Ccarb data represents a three-point moving average (average of that and adjacent values). δ13C data, conodont biostratigraphy (originally from Sweet and Tolbert (1997) at Shingle Pass), and measured section ranges are from Edwards and Saltzman (2014). δ34S values and CAS concentrations generated using a single NaCl rinse (yellow circles) generally have lower δ34S values and greater CAS concentrations than samples treated with three or more NaCl rinses (blue diamonds). Pyrite δ34S values are overall similar between methods and sometimes exhibit significant sample-tosample variability (≤29‰). Though pyrite-S concentrations are higher for samples treated with several NaCl rinses, this may record incomplete sulfide capture during extraction (see main text for further discussion). Furon. = Furongian, VPDB = Vienna Pee Dee Belemnite, FPG = Flat-pebble conglomerate, A = Cordylodus angulatus, I = Iapetognathus, L = Cordylodus lindstromi. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.) 4

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Table 1 Facies descriptions for carbonates sampled for δ34SCAS study, ranked in order in terms of least (#1) to most likely (#8) to have δ34SCAS values altered via fluid interactions. Facies #

Lithology

Rationale for preference for δ34SCAS study

1 2 3

Lime mudstone Lime mudstone with clay laminae FPG* with micritic matrix

4

FPG with wacke–packstone matrix

5 6

Recrystallized lime mudstone FPG with recrystallized micritic matrix

7 8

Fossil-rich wacke–packstone Recrystallized wacke–packstone

Fine-grained, fluid flow between grains is minimal, possibly enhanced by early cementation between grains Fine-grained, fluid flow between grains is minimal, but some clay layers may serve as conduits for fluid flow Fine-grained, fluid flow between grains is minimal in micritic matrix, but clear signs of reworking present, possibly representing a mixture of δ34SCAS values Fine-grained clasts, clear signs of reworking (similar to #3), but fluid flow between clasts could be enhanced due to coarser grained matrix Fine-grained, fluid flow between grains is minimal, but recrystallization indicates some grain-fluid interaction has occurred Fine-grained, fluid flow between grains is minimal in micritic matrix (see #3), but recrystallization indicates some grainfluid interaction has occurred Mixture of skeletal grains could represent mixed δ34SCAS values, fluid flow between skeletal grains is likely Mixture of skeletal grains could represent mixed δ34SCAS values, recrystallization of matrix and grains indicates some grainfluid interaction has occurred

FPG* = Flat pebble conglomerate.

otherwise later be measured as CAS. The amount of carbonate material that was processed by Wotte et al. (2012a) was at least 250 g (which also required only three NaCl rinses to remove soluble sulfate), which is far more than what was used here per sample (40–50 g). Based on the data reported by Wotte et al. (2012a) and our preliminary testing, we do not think residual soluble sulfate significantly contaminated our samples. In our study using both methods mentioned above, a total of 75 samples were measured using the 1× NaCl method and 118 using the 3× NaCl method, 31 of which were processed with both methods to assess how methodology can impact paired δ34SCAS and δ34SPY values (Table S2). Hand samples previously micro-drilled for δ13C (Edwards and Saltzman, 2014) and free of visible alteration and secondary vein-filling mineralization were cut using a diamond-saw to remove weathered surfaces (admittedly most of these samples are not pristine and have experienced some degree of alteration, either via recrystallization of mud grains or matrix, or with pore-filling cementation). Samples were then cleaned in three rinses of deionized water in a sonicating water bath to remove any particulates. Cleaned samples were crushed and pulverized into a powder using an alumina ceramic puck mill. For the 1× NaCl method, approximately 60–100 g of powder (usually about 80 g) was weighed and treated in a series of solutions using similar methods of Gill et al. (2011) to remove any non-CAS sulfate prior to dissolution. Powders were treated with 300 mL of a 10% NaCl solution and periodically stirred during a 24 hr period to remove any soluble sulfate minerals (e.g., gypsum or anhydrite). Samples were rinsed twice with 500 mL of Milli-Q water before being treated in 400 mL of a 5–6% NaOCl (bleach) solution to dissolve any organic-bound sulfur-bearing compounds, but this step can potentially leach pyrite and affect δ34SPY values (cf. Wotte et al., 2012a). Treated samples were rinsed three times in Milli-Q water before dissolution in 6 N HCl. Hydrochloric acid was slowly added to keep the pH above 3–4 to prevent any oxidation of sulfide minerals until complete dissolution of carbonate was achieved. The total time samples were exposed to acidic conditions was < 2–3 h. Insoluble residues were separated via centrifuge and rinsed several times with Milli-Q water, dried, and prepared for pyrite reduction. The pH of the acidified solutions was raised to 9–10 using NaOH pellets (cf. Kozik et al., 2019) and left overnight to allow for the precipitation of any aqueous metals (e.g., Fe or Cr). Purified solutions were centrifuged to remove the precipitate, after which the pH was lowered to ~4 using several drops of HNO3. Approximately 30 mL of 1 M Ba(NO3) was added and allowed to react for several days to precipitate BaSO4. Precipitates were isolated via centrifuge, dried, and weighed to gravimetrically determine the CAS concentration (Table S1). A subset of 31 samples that had been processed using the above 1× NaCl method were reprocessed following the 3× NaCl method, along with 87 additional samples only processed using the 3× NaCl method. About 40 g of carbonate powder was rinsed in 400 mL of 10% NaCl for

Quartzite was deposited, which has been interpreted to reflect the progradation of intertidal and eolian sands during a regional sea-level fall during the Middle Ordovician (McBride, 2012), marking a eustatic sea level low of the Sauk–Tippecanoe Megasequence boundary (Saltzman and Young, 2005; Keller and Lehnert, 2010; Miller et al., 2012). 3. Materials and methods Hand samples are classified based on their lithology and evidence for recrystallization, which can be used to assess their potential fidelity to preserve an original δ34Sseawater record. Facies are broadly assigned based on grain size, CaCO3 content, and evidence for reworking and/or diagenetic alteration, which ranges from fine-grained lime mudstone (Facies 1), to recrystallized wacke–packstone (Facies 8) (Table 1). Two protocols for CAS extraction were followed here to compare how methodology might impact δ34S values and stratigraphic trends. Traditional methods for CAS extraction from bulk carbonate rocks or skeletal material require samples be rinsed in either a NaCl solution (Kampschulte et al., 2001) or sodium hypochlorite (bleach; Burdett et al., 1989) to remove any secondary soluble sulfur products from evaporitic sulfate minerals (e.g., CaSO4) or organic C-rich sediment (Burdett et al., 1989), respectively. Further refinement of this method was made by Gellatly and Lyons (2005), and Gill et al. (2007, 2008) by first rinsing carbonate powders in two deionized water (DI) rinses to remove soluble sulfate prior to a bleach rinse to remove organic-bound sulfur. Continued modification of the CAS extraction protocol was made by Gill et al. (2011) where samples were first rinsed once in 10% NaCl prior to two rinses in DI, followed by a 48-hr-long bath in bleach. A recent modification of the CAS protocol was conducted by Wotte et al. (2011; building upon the methods of Kampschulte et al. (2001)) attempting to fully remove non-CAS sulfate that was not incorporated into the carbonate mineral structure using multiple NaCl rinses, with and without bleach rinses. In this study we used CAS-extraction methods similar to those most recently published by Gill et al. (2011; using a single 10% NaCl and bleach rinse) and Wotte et al. (2012a; using multiple 10% NaCl rinses). Samples that received a single rinse of 10% NaCl and a single bleach rinse are referred to herein as the 1× NaCl method, and samples that were treated with multiple (three) 10% NaCl rinses are referred to as the 3× NaCl method. In our early testing on a range of lithologies of relatively small sample sizes (< 50 g), we found that no measurable BaSO4 would precipitate after a third NaCl rinse. This included passing the rinsate solution through a glass filter and adding 1 M BaCl2 (1–2 mL) and several drops of 6 M HCl to prevent carbonate precipitation, and verifying no visible BaSO4 precipitate formed after 24–48 h. However, it may be possible that for some samples more NaCl rinses could have removed residual soluble sulfate, which would 5

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Parker Spring Formation that contains facies that show evidence of syndepositional reworking (i.e., flat-pebble conglomerate; Facies 6). δ34SCAS trends using both protocols exhibit similar characteristics with respect to the timing of stratigraphic excursions and the location of intervals with higher sample-to-sample variability, but the magnitude of δ34SCAS varies by an average of 7‰ between the two protocols, where the 3× NaCl samples have increased δ34SCAS values relative to those processed with the 1× NaCl method (Fig. 2). In the lower portion of the House Limestone, δ34SCAS steadily decreases from ~35‰ to 23–25‰, but in the uppermost portion of the formation δ34SCAS sharply increases by 12–15‰ and reaches a maximum value of 35‰ and 41‰ (for the 1× NaCl and 3× NaCl methods, respectively) before returning to less positive values just below the contact with the Parker Spring Formation. This maximum is coincident with a positive excursion in δ13Ccarb (Fig. 2) where both δ13Ccarb and δ34SCAS excursions are regionally correlative across the Great Basin (Edwards et al., 2018). Overall δ34SCAS values steadily decrease from these maximum values, with some exceptions (some samples processed using the 3× NaCl method again reach 41‰; Fig. 2), throughout the Parker Spring Formation and into the lowermost Shingle Limestone before returning to pre-excursion values (~29‰ and 34‰ for the 1× NaCl and 3× NaCl methods, respectively). Throughout the Shingle Limestone δ34SCAS values are highly variable (up to 10–15‰ between adjacent samples) using both methods; this broadly corresponds to samples with very low CAS concentrations (≤10 mg/kg SO4; Fig. 2). Within ~40 m of section, δ34SCAS values sharply decrease from 24 to 29‰ in the uppermost Shingle Limestone and reach a minimum of ~10‰ in the lower Kanosh Shale during a major lithologic change to poorly exposed shale-rich facies. Following this drop, δ34SCAS values steadily increase throughout the upper Kanosh Shale and lower Lehman Formation to new maxima of 36 and 42‰ (for the 1× NaCl and 3× NaCl methods, respectively), followed by a gradual decrease of 8–10‰ until the measured section ends at the contact with the Eureka Quartzite.

12 h three successive times (note that this is less than the 24 hr duration in Wotte et al. (2012a)). Samples were then rinsed in DI water three times and dissolved in 6 M HCl (see above), omitting the bleach step because these samples are organic poor (≪1 wt% C) and preliminary test were inconclusive regarding whether the bleach had oxidized some pyrite (Fig. S1), thus contaminating the δ34SCAS value. Insoluble residues were separated via vacuum filtration and glass fiber filters, rinsed with DI water, and dried for later pyrite reduction. Filtered solutions were kept at low pH (< 4) where 1–2 mL of 1 M BaCl2 was added to precipitate BaSO4 over several days. Pyrite sulfur was extracted using the chromium reduction method (Canfield et al., 1986), but different samples were processed in slightly different configurations in two laboratories (Ohio State University and Washington University in St. Louis), neither of which cross-checked the other method or configuration to confirm pyrite sulfur concentrations and isotopic values were similar (within error) between methods. At Ohio State insoluble residues were weighed and added to a boiling flask where ultrapure N2 gas was passed through the flask and an attached condensing coil for 15 min to create an anoxic atmosphere. While the system was being purged with N2 gas, 30 mL of 1 M CrCl2 and 60 mL of 12 N HCl were reacted with zinc shot until the reaction completed and formed bright blue reduced CrCl3 solution. A fritted bubbler with a Nacitrate buffer (to remove Cl−) was attached to the condenser in between another bubbler containing 100 mL of 0.01 N AgNO3 where Ag2S precipitate would collect during the pyrite reduction process. The insoluble residue was then reacted with the CrCl3 solution on a hotplate with a magnetic stirrer for 4 h or until the reaction was complete and no more Ag2S precipitate appeared to form. Precipitates were separated using a glass fiber filter and a vacuum pump, dried, and weighed to gravimetrically determine pyrite concentrations (Table S1). Reduction of pyrite samples conducted at Washington University in St. Louis proceeded in a similar fashion where dried insoluble residues were purged with ultrapure N2 gas (15 min) in a flask connected to a water trap (without a Na-citrate buffer) and bubbled through a silver trap (10 mL of 0.1 N AgNO3). Pyrite reduction occurred after adding 25 mL of pre-made reduced CrCl3 and 25 mL of 6 N HCl and heated to ~180 °C for 2–3 h. AgS2 precipitates were centrifuged and rinsed with DI water, dried, and weighed to gravimetrically determine pyrite concentrations (Table S2). Between 0.3 and 0.6 mg of BaSO4 and Ag2S samples were combined with excess V2O5 (2–5 mg) in tin capsules and measured for their δ34S isotopic values on a Costech ECS 4010 Elemental Analyzer coupled to a Thermo-Finnigan Delta V Advantage mass spectrometer via Conflo IV at Indiana University (Table S1) and at Washington University (Table S2). Isotopic results are reported in delta notation compared to the sulfur standard Vienna Canyon Diablo Troilite (VCDT). Analytical precision was determined to be < 0.3‰ using routine analysis of international δ34S standards (IAEA-S1, eS2, and eS3) and internal lab standards.

4.2. Pyrite trends (δ34SPY) Pyrite-sulfur concentrations extracted following the two CAS protocols are more similar to each other compared to CAS concentrations (Tables S1 and S2, Fig. 2), but the 1× NaCl method yields lower pyritesulfur yields compared to the 3× NaCl method. Pyrite-sulfur concentrations for the 1× NaCl method ranges between 3 and 113 mg/kg (avg. = 24 mg/kg), whereas the 3× NaCl method yields concentrations between 10 and 311 mg/kg (avg. = 64 mg/kg). Although theoretical pyrite trapping capacities were high for both pyrite reduction experimental setups (~6000 mg/kg pyrite-sulfur with 100% efficiency in the experimental setup), low pyrite concentrations from the 1× NaCl method may reflect incomplete conversion of all H2S in the AgNO3 trap after 4 h as the trapping solution in this extraction method remained cloudy, unlike what occurred when using the 10× more concentrated AgNO3 trap in the 3× NaCl method. Any systematic variation in pyrite yield between the two methods is likely due to differential efficiency of H2S capture during pyrite extraction (i.e., less efficient Ag2S capture using the 1× NaCl method), rather than the result of anything inherent in the different CAS extraction processes themselves. Though it is possible that differences in the NaCl and DI rinses and dissolution processes may have oxidized pyrite sulfur to different degrees before capture as Ag2S, given that the experimental steps had markedly different concentrations of AgNO3, it seems most likely that differences in pyrite-sulfur yields is simply an artifact of sulfide capture. Overall these concentrations are less than values reported from older Cambrian carbonates that interpreted to have formed under anoxic–euxinic oceanic conditions (Gill et al., 2011), but similar to other Ordovician successions (Young et al., 2016), possibly reflecting less pyrite preservation in a more oxygenated Ordovician environment. A subset of eleven samples processed using the 3× NaCl method was duplicated to assess the reproducibility of δ34SPY and pyrite-sulfur

4. Results 4.1. Carbonate-associated sulfate trends (δ34SCAS) Using the 1× NaCl method, CAS concentrations range from 7.67 to 712 mg/kg (avg. = 116 mg/kg, or ppm), similar to other reported sulfate concentrations (between ~100 to 1000 mg/kg SO4) from carbonate rocks (Staudt and Schoonen, 1995; Gill et al., 2011; Marenco et al., 2013). The 3× NaCl method yielded lower sulfate concentrations between 0.18 and 280 mg/kg (avg. 61.0 mg/kg). A subset of eleven samples processed using the 3× NaCl method was duplicated to assess the reproducibility of δ34SCAS and CAS mg/kg results. CAS yield from the eleven samples differed between each other between 2.39 and 59.4 mg/kg CAS (average: 22.5 mg/kg; Table S4). Nine of these samples were measured for δ34SCAS that differed from each other between 0.5 and 3.9‰ (average: 1.1‰; Table S4). Five of these duplicate samples, including the least reproducible δ34SCAS sample, are from the lowermost 6

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mg/kg results. Pyrite-sulfur yield from the eleven samples differed between each other between 1 and 51 mg/kg (average: 14 mg/kg; Table S4). Ten of these samples were measured for δ34SPY that differed from each other between 0.3 and 6.1‰ (average: 2.9‰; Table S4). δ34SPY values exhibit more sample-to-sample variability compared to paired δ34SCAS values. Stratigraphically adjacent samples can differ in δ34SPY by as much as 29‰ over a few meters of section (samples 7556 and 7557 in the lower Parker Spring Fm.; Fig. 2). Given the local nature of pyrite formation within sediment, such variation is not unexpected considering that rates of MSR can vary based on porewater sulfate concentrations and the kinds of organic substrates available for MSR, for example. However, trends in δ34SPY values between the two different extraction methods are more similar to each other than corresponding δ34SCAS data, which suggests that any methodological differences that impacted CAS yields did not have an appreciable effect on δ34SPY. At the base of the section in the House Limestone δ34SPY trends decrease upsection from ~15–20‰ to −10–0‰, parallel to the δ34SCAS trend. δ34SPY values return to more positive values in the upper House Limestone (reaching 10 and 35‰ for the 1× NaCl and 3× NaCl methods, respectively), coincident with δ34SCAS increase (Fig. 2). δ34SPY values remain high (between about +5 to +28‰) throughout the Parker Spring Formation and lowermost Shingle Limestone. A sharp decrease in δ34SPY occurs in the lower Shingle Limestone, where values decrease from ~+17 and 21‰ to −5 and −0.5‰ (for the 1× NaCl and 3× NaCl methods, respectively), and generally remain negative with similar variability throughout the lower–middle Shingle Limestone (Fig. 2). A brief positive δ34SPY shift to +18.5 and 26‰ (respectively) occurs in the middle Shingle Limestone within facies that show sediment reworking and contain flat-pebble conglomerate lithologies. Finally, throughout the upper Pogonip Group (Shingle to Lehman formations), δ34SPY gradually increases to ~+15‰ for samples using both

5. Discussion 5.1. Assessment of diagenesis The degree and effect of alteration on the rocks in any sedimentary succession must be first assessed before any meaningful interpretations can be drawn concerning the paleoenvironmental significance of geochemical trends. Techniques such as petrographic study using transmitted light and cathodoluminescence microscopy can reveal microscale evidence for diagenetic recrystallization of carbonates (e.g., Hiatt and Pufahl, 2014), trends in isotope crossplots may reveal evidence for isotopic exchange with porefluids (e.g., Banner and Hanson, 1990; Brand and Veizer, 1981; Metzger and Fike, 2013), as well as using crossplots of Ca and Mg isotopes to identify whether rocks have been altered under early or late burial conditions (Ahm et al., 2018). Diagenetic alteration of δ13Ccarb values at Shingle Pass is believed to be minimal based on petrographic thin section analysis, crossplots of δ13Ccarb and δ18Ocarb, and global correlations of isotope trends (Edwards et al., 2018; Edwards and Saltzman, 2014). Because δ18Ocarb values are commonly first to exhibit signs of alteration (Banner and Hanson, 1990), crossplots of δ18Ocarb values compared to δ34SCAS, δ34SPY, and CAS and pyrite concentrations could be used to identify clear diagenetic signals (cf. Wotte et al., 2012b). However, no strong correlation exists (Fig. S2) and thus the potential for the alteration of δ34S (CAS and PY) must still be assessed because the processes that affect the carbonate carbon or oxygen isotopic compositions of samples may be different than those that affect CAS and associated sedimentary pyrite, particularly during meteoric diagenesis and isotopic exchange with porefluids (Gill et al., 2008). Carbonate-associated sulfate 7

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completely filled in by cement with variable isotopic compositions (δ34Scement) of CAS derived from porewater but with a fixed concentration of 50 mg/kg CAS. This is lower than mean values (~250 mg/ kg) reported in other burial cements (Staudt and Schoonen, 1995), so we have also conducted a sensitivity test (Fig. S3) to explore how higher CAS concentrations in the cement would affect bulk δ34SCAS values. We expect that primary CAS concentrations will scale with ambient SO4 concentrations (both in primary carbonate grains and pore-filing cement), but for modeling purposes we simplify the model such that the cement has a CAS concentration of 50 mg/kg reasoning that more ordered CaCO3 cements will have low sulfate concentrations (and recently documented by Richardson et al., 2019). It should be noted that as the porespace is completely filled in with cement, the total mass of CAS per unit volume increases but the overall concentration will decrease if marine-derived carbonate CAS concentrations are ≥50 mg/kg. For rocks that are powdered without detailed examination of the proportion of primary grains and cement for each sample, as was done in this study, these two phases would be measured together and would represent a bulk value (δ34SCAS). Bulk δ34SCAS will become 34S-enriched if pore-filling cement precipitated during MSR incorporates evolved porewater sulfate (Fig. 4A–C). The effect of this addition of evolved sulfate only increases bulk δ34SCAS (primary carbonate grains + carbonate cement with CAS) by < 1.4‰ when < 90% of porewater sulfate is consumed and high initial CAS abundance (1000 mg/kg; blue line in Fig. 4C), and up to 5.9‰ with five times the CAS concentration in cement (i.e., 250 mg/kg; Fig. S3). Furthermore, bulk δ34SCAS will increase by < 2.6‰ if initial CAS concentrations of marine-derived carbonate grains are ≥500 mg/ kg SO4 (red line in Fig. 4C), which is within the range of replicate analysis of some samples. Rocks with primary carbonate grains with low CAS concentrations (≤100 mg/kg SO4) are most susceptible to this style of δ34SCAS alteration. For example, under closed-system conditions, a carbonate rock with primary CAS concentrations of 100 mg/kg SO4 can record a bulk δ34SCAS value that is 10.2‰ more positive than δ34Sseawater (set here at 21‰) with 90% or more porewater sulfate consumption (yellow line in Fig. 4C), and 24‰ more positive than δ34Sseawater when cement CAS concentrations are 250 mg/kg (Fig. S3). Finally, bulk δ34SCAS can increase by 15.9‰ or more with ≥90% porewater sulfate consumption when primary carbonate CAS concentrations are as low as 50 mg/kg CAS (green line in Fig. 4D). This process might be expected to yield pyrite that lines pores adjacent to carbonate grains (assuming the system is not iron-limited) as by MSR-produced sulfide. However, in our visual and petrographic examination of these rocks, we do not observe compelling evidence that pores were lined with pyrite in this way (intact or preserved as Feoxides, although Fe-oxides common as laminae in some samples), even in the facies with the highest pyrite-S yields (Fig. S4).

concentrations generally decrease as sulfate impurities are excluded from the carbonate mineral crystal lattice during recrystallization (Gill et al., 2008; Staudt and Schoonen, 1995). Studies on modern carbonate mud and skeletal grains show little to no isotopic alteration of δ34SCAS compared to δ34Sseawater (Gill et al., 2008; Lyons et al., 2004). The longterm effects on δ34SCAS from lithification, deep burial, recrystallization, or meteoric diagenesis since deposition, however, are not well constrained without independent means of estimating δ34Sseawater (e.g., marine barite (Paytan et al., 2004)) or hand-picked foraminifera (Rennie et al., 2018). Though samples with low CAS concentrations are likely more susceptible to contamination from minor contributions of sulfate derived from pyrite oxidation (Gill et al., 2008), an apparent lack of correlation between δ34SCAS and CAS concentration from this study (Fig. 3A) is consistent with the notion that these rocks have not been pervasively altered and may still preserve δ34S values similar to δ34Sseawater. However, in portions of the Pogonip Group where large sample-to-sample δ34SCAS variability exists (e.g., the Shingle Limestone; Fig. 2), a deviation of the δ34SCAS signal from coeval δ34Sseawater seems to be the most likely explanation of isotopic variability rather than it being caused by rapid changes in primary seawater δ34S. The specifics of the CAS protocol used can clearly impact both the resulting CAS concentrations and δ34SCAS (which can vary up to 12.5‰ between methods). This observation is important because similar approaches using both of these protocols have been used to produce chemostratigraphic δ34SCAS data inferred to reflect δ34Sseawater (Gill et al., 2011, 2007; Wotte and Strauss, 2015). The inference from these observations is that additional NaCl rinses are effective at removing a sulfate component with a δ34S composition that can be distinguished from δ34SCAS grains originally precipitated in marine settings (i.e., δ34Sseawater), but this does not always remove large sample-to-sample variability to produce a coherent δ34SCAS trend (e.g., the Shingle Limestone, see below for further discussion on why multiple NaCl rinses may not guarantee coherent δ34SCAS trends can be produced). Specifically, because the more effective removal of this sulfate using the 3× NaCl method resulted in more positive δ34SCAS values, the additional, contaminating phase must have a lower δ34S composition, consistent with it being derived from a 34Sdepleted sulfide source, such as pyrite oxidation. 5.2. Modeling a diagenetic component to CAS To explore how diagenetic processes can alter δ34SCAS from the original δ34Sseawater value, we use a simple closed-system model of Rayleigh distillation to show how porewater evolution from MSR or secondary pyrite oxidation could affect δ34SCAS, particularly for carbonate sediment with low primary CAS concentrations (Fig. 4). We do not necessarily advocate that either or both models best explain the observed variation of δ34SCAS values as a function of alteration, we simply present these scenarios as ways that could explain increases or decreases of δ34SCAS values (e.g., such as reported in Present et al. (2015)) after carbonate grains formed in contact with seawater. We also cannot rule out the possibility that both scenarios could have affected the same sample if the connectivity between pores varied over space or time (e.g., pores impacted by precipitation or dissolution of cement).

5.2.2. Decreasing δ34SCAS via pyrite oxidation and cementation An alternative scenario that can cause δ34SCAS values to decrease during diagenesis could be caused by post-deposition oxidation of sedimentary pyrite, which will release 32S-enriched sulfate to porewater that can become incorporated in pore-filling cements to lower bulk δ34SCAS. One potential such sedimentary system is where firm–hardground formation occurs as oxidizing fluids moves through sediment, oxidizing pyrite, followed by cementation with the resupply of dissolved calcium and bicarbonate. Seawater sulfate would presumably also be re-supplied in this manner (but equal to the δ34S value of the carbonate grains), but for simplicity in the model we assume porewaters to initially be devoid of sulfate and the oxidizing potential for these fluids to be capable of fully oxidizing all pyrite. However, complete pyrite oxidization did not occur for most samples in this study as pyrite-sulfur was captured in almost every sample (Tables S1, S2). However, to illustrate how bulk δ34SCAS values could be lowered in this scenario we assume complete oxidation before cementation initiated. Model results of the same sedimentary system, 30% porespace

5.2.1. Increasing δ34SCAS via microbial sulfate reduction and cementation in porewater This scenario assumes a fixed initial porosity of 30% with CAS concentrations of primary carbonate grains (e.g., bioclasts, peloids, ooids, lithoclasts, etc.) ranging from 50 to 1000 mg/kg, a δ34S value equal to 21‰ (δ34Scarbonate), and a sedimentary pyrite sulfur concentration of 100 mg/kg with a δ34S value of −9‰ (i.e., Δ34S = 30‰). [The term ‘primary carbonate’ herein refers to carbonate grains that formed in equilibrium with marine waters, but we acknowledge that carbonate with CAS that precipitated from evolved porewaters can also be a considered primary process]. The open porespace is assumed to be 8

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Fig. 4. Simulated effects of diagenesis and water evolution to bulk δ34SCAS (primary carbonate CAS + cement CAS). A) Diagrammatic view of effects of measured Cement: 60 30% (vol.) δ34SCAS, referred to as bulk δ34SCAS, which captures a Seawater 50 mg/kg CAS δ S mixture between primary carbonate (δ34Sseawater) and 40 Instantaneous Blocky sulfide pore-filling cement (assuming no fractionation occurs spar 20 during the incorporation of porewater sulfate into calcite ε Primary 0 cement). Modeled parameters for B–D shown using Cumulative carbonate: Syntaxial pyrite 70% (vol.) cement modern seawater conditions (δ34Sseawater = 21‰). B) δ S = 21‰ -20 50 to 1000 mg/kg CAS 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Simulated porewater evolution via Rayleigh distillation Fraction of porewater sulfate consumed under closed-system conditions. Continued sulfate con1 cm sumption via microbial sulfate reduction (ε = 30‰) increases the remaining porewater sulfate δ34S, which can C Cementation in evolved porewaters increases δ S D Cementation after pyrite oxidation decreases δ S 40 30 become incorporated into pore-filling cement. C) 1000 ppm CAS Modeled effects of bulk δ34SCAS that increases during 500 ppm CAS 36 100 ppm CAS alteration via Rayleigh distillation of pore water sulfate 50 ppm CAS 20 under closed-system conditions. For example, at 90% 32 consumption of porewater sulfate via MSR (gray vertical 28 bar), if the remaining porewater sulfate is captured as 1000 ppm CAS 10 500 ppm CAS CAS in cement, bulk δ34SCAS will be 34S-enriched by 24 100 ppm CAS 1–2‰ when primary carbonate CAS is ≥500 mg/kg SO4. 50 ppm CAS D) Modeled effects of bulk δ34SCAS that decreases with 20 0 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 alteration via continued oxidation of sedimentary pyrite Fraction of porewater sulfate consumed Fraction of oxidized pyrite (100 ppm) (100 mg/kg FeS2) that is captured as CAS in pore-filling by microbial sulfate reduction preserved in CaCO3 cement cement. At 90% oxidation of pyrite, bulk δ34SCAS can decrease by 0.6 to 8.4‰ for initial CAS concentrations between 1000 and 50 mg/kg SO4, respectively, with pore-filling cement capturing all of the sulfur derived from oxidized pyrite as CAS. (For interpretation of the references to colour in this figure, the reader is referred to the web version of this article.) Bulk δ34SCAS = δ34Scarbonate + δ34Scement

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without cement, and original pyrite concentrations (δ34SPY = −9‰) typical of carbonate rocks analyzed in this study (100 mg/kg pyrite S), show how a carbonate rock with varying original CAS concentrations can record lower bulk δ34SCAS values when the oxidized pyrite-derived sulfur is preserved as CAS in pore-filling cement (Fig. 4D). Recent work by Richardson et al. (2019) supports this scenario as they observe carbonate cements with low (near detection limit) and high (but less than neighboring bioclasts) sulfate concentrations, but unfortunately they could not assign a source of the sulfate nor do they report δ34SCAS values of those cement phases. In our model, the bulk δ34SCAS value of a carbonate rock with 500 mg/kg primary CAS will only be lowered by 2.1‰ if 90% of the initial pyrite is oxidized and preserved as porefilling cement (red line in Fig. 4D) and up to 8.2‰ for carbonate rocks with 100 mg/kg primary CAS (yellow line in Fig. 4D). We note that the intervals with some of the greatest δ34SCAS variability (including a deviation to relatively less positive δ34SCAS values) occur within the reworked successions abundant in flat-pebble conglomerate facies where firm–hardgrounds had formed and were subsequently reworked by high-energy conditions. Future work on exploring these facies in detail to document a range of in situ δ34SCAS values between primary carbonate grains and surrounding cements would confirm whether this scenario could explain the range of δ34SCAS variability in the Shingle Limestone. Based on these modeling results we assume that more positive δ34SCAS values are most likely to represent δ34Sseawater, but we acknowledge that δ34SCAS values can increase if, for example, 34S-enriched sulfate in porewaters is incorporated into cements and carbonate grains, such as seen elsewhere (Present et al., 2015). As partial pyrite oxidization occurs, possibly during sediment reworking events (i.e., the formation of flat-pebble conglomerate), it has a higher potential to alter δ34SCAS toward more negative values relative to the slight enrichment from porewater evolution via Rayleigh distillation, particularly for rocks with low CAS concentrations (Fig. 4C and D). An important issue to consider is that if sulfate derived from partial pyrite oxidation or from cements reflecting chemically evolved porewaters becomes incorporated into pore-filling cements, no amount of NaCl rinsing will remove this secondary sulfate. Without use of intensively time-consuming techniques (e.g., secondary ion mass spectrometry (SIMS) to map the grain-specific abundance and isotopic

composition of CAS, use of a synchrotron to map CAS abundances (Richardson et al., 2019; Rose et al., 2019), or cathodoluminesence (Fichtner et al., 2017)), there is currently no way to effectively screen samples prior to δ34SCAS analysis. Screening samples with obvious recrystallization fabrics seems to be the optimal approach to exclude samples with low CAS concentration for δ34SCAS analysis (Fig. 3C; see below for further discussion). We therefore suggest that limestone that has undergone substantial, especially late-stage, recrystallization with concomitant CAS removal is least likely to preserve a pristine δ34Sseawater signal if sulfate in CAS-bearing cements derived that sulfate from oxidized pyrite (Fig. 4).

5.3. Source of non-carbonate-bound sulfate that can be captured as CAS In addition to the above discussion about how carbonates can incorporate sulfate into the carbonate lattice that has an isotopic composition distinct from seawater sulfate, the CAS extraction protocol can also yield sulfate that was not bound into the carbonate lattice. Indeed, because the different CAS extraction methods employed here both fully dissolved their carbonate components, the origin of the difference in CAS abundance and isotopic composition must lie in a non-carbonate sulfate phase. The source of non-carbonate-bound sulfate is important to consider, particularly if it can be captured as CAS during extraction in the laboratory. If this non-carbonate-bound CAS is not isolated from unaltered rock, it will provide a mixed δ34S signal between primary CAS and secondary alteration products (i.e., bulk δ34SCAS). Partial pyrite oxidation should produce sulfate with more negative δ34S values compared to δ34SCAS (shown experimentally by Marenco et al. (2008a), or by contamination by secondary atmospheric sulfate; Peng et al., (2014)), and if this sulfate is not removed during the NaCl rinses, bulk δ34SCAS values will be lower than otherwise pristine δ34SCAS counterparts. The location of this non-primary CAS in carbonate rocks is not well constrained, but because a bleach rinse does not significantly or systematically change δ34SCAS or δ34SPY values (Fig. S1) and continued NaCl rinses appear to progressively remove sulfate, this suggests that this secondary sulfate is sorbed onto the surfaces of carbonate crystals.

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5.4. Comparing CAS protocols: toward measuring δ34Sseawater

(≤10 mg/kg) is currently the best predictable measure to take for selecting samples most likely to preserve a seawater δ34S trend. For example, though CAS concentrations are generally low for the 3× NaCl method, samples with CAS concentrations greater than ~20 mg/kg yields δ34SCAS values ≥4‰ more positive than the 1× NaCl method (Fig. 3C), suggesting that non-carbonate bound sulfate was not completely removed during the 1× NaCl treatment. Though these more positive values using three NaCl rinses may be more reflective of δ34Sseawater than a single NaCl rinse that did not remove secondary sulfate, primary δ34Sseawater values are not guaranteed, as evidenced by the large sample-to-sample variability in the Shingle Limestone, for example (Fig. 2). Curiously, the lower–middle portion of the Shingle Limestone with low CAS concentrations could be considered to be an acceptable candidate for δ34SCAS study as it exhibits less variation between successive δ13Ccarb values compared to the relatively pure carbonate facies of the upper Parker Spring Fm. (but low δ34SCAS variability; Fig. 2), as well as containing relatively similar lithologies and with fossil preservation. However, relying on these first-order approaches to screen for carbonate successions suitable for δ34SCAS study, or looking at crossplots with δ18Ocarb data (Fig. S2), does not guarantee stratigraphically coherent δ34SCAS values can be obtained. We recommend that samples with low CAS yields (≤10 mg/kg) after multiple NaCl rinses be avoided for δ34SCAS study, but samples with high CAS concentrations after multiple NaCl rinses (> 50 mg/kg) may yield promising results in efforts to reconstruct δ34Sseawater using δ34SCAS.

δ34SCAS values and CAS concentrations can vary significantly depending on which CAS protocol is used (Fig. 2), indicating that one or both of these methods captures multiple phases that do not necessarily reflect true (i.e., carbonate-bound) δ34SCAS. For samples processed using both CAS protocols (31 in total), δ34SCAS can differ by 0.5 to 12.5‰ (average offset of 7‰), where δ34SCAS using the 3× NaCl method is always more 34S-enriched (Fig. 3C and D). Such a large difference between methods has clear implications for studies that use δ34SCAS as a proxy for δ34Sseawater, particularly when modeling variations in δ34SCAS ≤ 12‰ as representative of regional- to global-scale changes to the sulfur cycle (e.g., Thompson and Kah, 2012). By using the difference in δ34SCAS of samples processed using both protocols (Δδ34SCAS = δ34S3× NaCl − δ34S1× NaCl), it may be possible to characterize under which conditions using a particular CAS protocol will yield δ34SCAS that is more likely to reflect true carbonate-bound CAS in the sample. When carbonate rocks undergo early diagenesis and recrystallization CAS concentrations typically decrease as more highly ordered lowMg calcite forms and excludes weakly bonded sulfate from the crystal lattice or from structural defects (Staudt and Schoonen, 1995). This early diagenesis has been shown to more likely occur when seawater flushes through unlithified sediment rather than during shallow burial (e.g., dewatering, compaction, and cementation; Present et al., in press). A comparison of CAS concentrations with Δδ34SCAS values (Fig. 3C) shows a weak correlation for both the 1× NaCl method (r2 = 0.19) and 3× NaCl methods (r2 = 0.17). [Two samples (a heavily silicified lime mudstone (SP-7590) and a clay-rich limestone (SP-7608) collected from a limestone lens in a shale-rich portion of the Kanosh Shale) are omitted from this comparison as they do not reflect limestone facies typically used for δ34SCAS study]. Because the 3× NaCl method is more efficient at removing ‘contaminant’ sulfate (i.e., non-carbonate sulfate), presumably derived from pyrite oxidation after deposition, CAS concentrations are typically lower and δ34SCAS values are more positive compared to the 1× NaCl method (Fig. 2). Carbonate rocks with low CAS concentrations (≤10 mg/kg) commonly have large sample-to-sample δ34SCAS variability, particularly within the Shingle Limestone. Rocks with CAS concentrations ≤10 mg/kg would be most susceptible to preserving a secondary δ34S signal if recrystallization processes incorporate small amounts of porewater sulfate into carbonate grains derived from pyrite oxidation (i.e., with low δ34Scement values) and lower the bulk δ34SCAS value (Fig. 4D). However, some workgroups have reported CAS data with low yields yet find no compelling evidence using crossplots of isotope data vs. trace element concentrations to indicate that measured δ34SCAS or δ34S PY data were significantly affected by diagenesis in their studies (e.g., Gill et al., 2008; Wotte et al., 2012b). We envision that some samples with low pyrite concentrations have artificially low Δδ34SCAS values due to some exchange of oxidized pyrite sulfur with CAS in primary carbonate grains or cements, but not significantly increase CAS concentrations as low Δδ34SCAS values tend to have low CAS concentrations (Fig. 3C). This phenomenon is most noticeable for samples that may have initially had low CAS concentrations such that even a small amount of exchange with 32S-enriched SO4 derived from pyrite oxidation can lower the bulk δ34SCAS value, which cannot be removed by multiple NaCl rinses. Pyrite oxidation would also be expected to be a source of non-carbonate-bound sulfate. Here the 1× NaCl method would not remove all of this sulfate, thus yielding artificially low δ34SCAS values. If true, samples that were affected by this process should have large Δδ34SCAS values due to the fact that the 3× NaCl method is more effective in removing non-carbonate-bound sulfate that was derived from 34S-depleated pyrite. However, a crossplot of δ34SCAS using a single NaCl rinse vs. Δδ34SCAS (Fig. 3D) shows that no correlation exists (r2 = 0.01). It appears that avoiding samples with low CAS concentrations

5.5. Comparing facies: testing the fidelity of fine-grained (micritic) lithologies for δ34SCAS study Fine-grained, homogeneous carbonate lithologies (lime mudstone or micrite) that are free of obvious alteration are regarded as an appropriate facies to sample for δ34SCAS study as a proxy for δ34Sseawater (e.g., Hurtgen et al., 2002; Kampschulte and Strauss, 2004; Lyons et al., 2004), but recent work suggests that bulk micrite may not always be the most pristine compared to bioclasts (Present et al., 2015). Present et al. (2015) suggest that these heterogeneous δ34SCAS values of micrite are caused by localized concentrations of sulfur-bearing organics, clay minerals, and disseminated pyrite, all of which can lead to a high potential for later sulfide oxidation and incorporation into secondary carbonate. Though locally the δ34SCAS value of micritic components can differ by up to 15‰ compared to well-preserved brachiopods, (fig. 10 of Present et al., 2015), in some samples the δ34SCAS values of micrite and brachiopods are nearly the same (< 1‰ difference). These authors also present bulk rock δ34SCAS values that are similar to brachiopod δ34SCAS values (even in beds with apparently altered micritic samples), as well as reproducing bulk rock δ34SCAS values measured by Jones and Fike (2013) in the same section. Present et al. (2015) recommend that sampling smaller samples whose preservation potential can be clearly characterized will produce more precise estimates of δ34Sseawater trends. However, it is rare that these kinds of facies with well-preserved bioclasts are available for high-resolution sampling within a single continuous stratigraphic section. Therefore, if one intends to reconstruct δ34Sseawater using δ34SCAS values, one must sample the best available lithologies and carefully characterize any diagenetic overprinting that may impact δ34SCAS, as well as compare δ34SCAS values between facies to identify any facies dependence or clear signs of alteration, prior to interpreting whether primary signatures are still preserved. This process can be prohibitively time consuming when generating large data sets and still may not ensure that only primary δ34SCAS values will be produced, especially if screening methods for likely diagenetic samples fail to reject a sample for δ34SCAS study. Convincing evidence that a δ34Sseawater signal is preserved comes from data sets where clear δ34SCAS trends within a stratigraphic section do not covary with changes in lithology or facies, as well as being reproducible in multiple locations within and ideally between basins (cf. Edwards et al., 2018). High-resolution sampling of several facies across the House 10

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moderately altered lithologies accurately represent δ34Sseawater, for correlative purposes they show potential for their utility if these δ34SCAS values yield coherent trends with low sample-to-sample variability between age-equivalent sections.

Formation 50 m

6. Conclusions

Parker Spring Fm.

0m

High-resolution paired CAS and pyrite δ34S trends measured from Shingle Pass, NV record similar δ34SCAS trends from Lower–Middle Ordovician carbonates measured using two CAS protocols. Though these samples yield similar δ34SCAS stratigraphic trends, the magnitude of δ34SCAS can vary by up to 12.5‰ between protocols. δ34SPY values do not appear to differ significantly with respect to the CAS protocol used (with or without bleach), but the concentration of AgNO3 does appear to make a small difference. This difference in methods has implications for modeling studies that use small-moderate changes in δ34S (< 12.5‰) to guide interpretations about what variations in δ34SCAS indicate about the ancient marine sulfur cycle. The 3× NaCl method consistently yields more positive δ34SCAS values compared to the 1× NaCl method, which we interpret to reflect more effective removal of weakly bonded secondary sulfate that is more 34S-depleted than primary CAS (e.g., arising from in situ oxidation of pyrite prior to sample collection). Samples with low CAS concentrations do not show a significant difference in δ34SCAS values if processed using both CAS methods (low Δδ34SCAS), suggesting that either 34S-depleted sulfate has either exchanged with primary grains or has become incorporated into pore-filling cements, or that these samples do in fact preserve a δ34Sseawater value despite the diagenetic effect of removing CAS during recrystallization. Though the 3× NaCl method is more effective at removing contaminant secondary sulfate, use of this method still does not ensure that a primary δ34Sseawater value can be captured as some 3×rinsed samples with low CAS concentrations still show great sample-tosample variability (e.g., lower–middle Shingle Limestone), more variability than is plausible for the marine sulfate reservoir. We interpret this large δ34SCAS variability to be the result of non-primary sulfate, derived from pyrite oxidation, which has either been incorporated into pore-filling cement or exchanged with CAS in primary grains, particularly for samples that originally had low (≤10 mg/kg) CAS concentrations, thus no longer recording δ34Sseawater. Results suggest that samples with the best chance of preserving a δ34Sseawater signal will have large CAS concentrations (> 50 mg/kg SO4) after several NaCl rinses. High-resolution δ34SCAS sampling may ultimately be the best evidence for seawater δ34S if clear trends can be reproduced and correlated to other sections regionally or globally, particularly if these trends cut across varying lithologies between sections. Supplementary data to this article can be found online at https:// doi.org/10.1016/j.chemgeo.2019.119297.

House Limestone

mw p g

25

30

35

40

45

δ34SCAS (‰ – VCDT) Sed. structures Chert Rip-ups Laminations

Lithology 1 - Lime mudstone 2 - Lime mudstone with clay laminae 3 - FPG with micritic matrix

Burrows Ripple cross-bedding Flat pebble conglomerate

4 - FPG with wacke–packstone matrix

Poor exposure

8 - Recrystallized wacke–packstone

5 - Recrystallized lime mudstone 6 - FPG with recrystallized micritic matrix 7 - Fossil-rich wacke–packstone

Fig. 5. High-resolution δ34SCAS data (3× NaCl method) plotted alongside detailed stratigraphic record. Data are shown with lithologic and facies information based on grain size and evidence for reworking or alteration (i.e., unlike to retain a δ34Sseawater value). m = mudstone, w = wackestone, p = packstone, g = grainstone.

Limestone–Parker Spring interval shows a clear δ34SCAS trend is preserved in a range of lithologies (Fig. 5). These lithologies vary with respect to grain size, CaCO3 content, and evidence for reworking or recrystallization after deposition (Table 1). Samples with altered lithologies (e.g., visible evidence of recrystallization; shaded red in Fig. 5) show no significant difference or more scatter among closely spaced samples when compared to fine-grained lime mudstone samples, indicating that fine-grained lime mudstone facies here are not more or less ideal to use for δ34SCAS study than other facies. This is somewhat surprising considering that Present et al. (2015) suggest that finegrained micritic facies are more likely than skeletal fragments to be altered by incorporating sulfate derived from pyrite oxidation. Though the average point-to-point difference (< 1.5‰) between δ34SCAS from adjacent lime mudstone lithologies is similar to the difference between δ34SCAS of replicate lime mudstone samples (Table S4), δ34SCAS values from these facies are not significantly different than values measured from samples with evidence of sediment reworking and transport (flatpebble conglomerate lithologies: circles in Fig. 5). Reworked carbonate sediment may not exhibit significant δ34SCAS variability if allochthonous grains formed under an isotopically homogeneous regional water column, or if 32S-enriched sulfate derived from pyrite oxidation or atmospheric deposition was fully removed during NaCl rinses in the lab. Though it may never be known whether δ34SCAS measured from

Acknowledgements We thank two anonymous reviewers for their constructive and helpful reviews to strengthen and clarify the manuscript. We also thank M. Edwards and N. Umholtz for fieldwork assistance and J. Houghton for valuable discussion on an earlier version of the manuscript. We are grateful for laboratory assistance from S. Young, B. Underwood, P. Sauer (Indiana University), and Dwight McCay and Stephanie Moore (Washington University in St. Louis). Funding was provided in part by Sigma Xi Grants-in-Aid (Edwards), a Friends of Orton Hall Research Grant (Edwards), the Paleontological Society Student Research Grant for the Allison R. “Pete” Palmer Award (Edwards), an Evolving Earth Foundation Student Grant (Edwards), and support from the David and Lucile Packard Foundation (Fike). References Ahm, A.C., Bjerrum, C.J., Bla, C.L., Swart, P.K., Higgins, J.A., 2018. Quantifying early

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