Assessing the impact of bioturbation on sedimentary isotopic records through numerical models

Hülse, Dominik; Vervoort, Pam; Velde, Sebastiaan van de; Kanzaki, Yoshiki; Boudreau, Bernard P.; Arndt, Sandra; Bottjer, David J.; Hoogakker, Babette A A; Kuderer, Matthias; Middelburg, Jack J.; Volkenborn, Nils; Turner, Sandra Kirtland; Ridgwell, Andy

doi:10.1016/j.earscirev.2022.104213

Cited by 10 publications

(11 citation statements)

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“…Pyrite can be removed from surficial sediments through biodiffusive burial into deeper layers and/or through oxidative dissolution. Biodiffusion tends to homogenize surficial signals (Hülse et al., 2022), while oxidative dissolution may partially reset them on an annual basis. Oxygen penetration depths never exceeded 0.4 cm at either site during the sampling interval (Malkin et al., 2022), but other electron acceptors may still contribute to oxidative dissolution of pyrite below this depth (Schippers & Jørgensen, 2002).…”

Section: Discussionmentioning

confidence: 99%

Sedimentary Pyrite Formation in a Seasonally Oxygen‐Stressed Estuary: Potential Imprints of Microbial Ecology and Position‐Specific Isotope Fractionation

et al. 2023

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Sulfur-cycling microorganisms are fundamental agents in sedimentary pyrite formation. The compounds that form pyrite include iron monosulfide (FeS), hydrogen sulfide (H 2 S), and polysulfide (S n 2−) (Butler et al., 2004), which are formed and consumed by microbially catalyzed reactions (sulfate reduction, sulfide oxidation, and elemental sulfur disproportionation) along with abiotic reactions. However, the role of microbes in pyrite precipitation also likely extends beyond simply generating the necessary reactant compounds (Picard et al., 2016;Wacey et al., 2015). For example, pyrite formation proceeds in some cases via the activity of microbial consortia (Thiel Abstract Sedimentary pyrite records are essential for reconstructing paleoenvironmental conditions, but these records may be affected by seasonal fluctuations in oxygen concentration and temperature, which can impact bioturbation, sulfide fluxes, and distributions of sulfide oxidizing microbes (SOMs). To investigate how seasonal oxygen stress influences surficial (<2 cm) pyrite formation, we measured time-series concentrations and sulfur isotope (δ 34 S) compositions of pyrite sulfur along with those of potential precursor compounds at a bioturbated shoal site and an oxygen-deficient channel site in Chesapeake Bay. We also measured radioisotope depth profiles to estimate sedimentation rates and bioturbation intensities. Results show that net pyrite precipitation was restricted to summer and early autumn at both sites. Pyrite concentration was higher and apparently more responsive to precursor compound concentration at the mildly bioturbated site than at the non-bioturbated site. This disparity may be driven by differences in the dominant SOM communities between the two sites. Despite this, the sites' similar pyrite δ 34 S values imply that changes in SOM communities have limited effects on surficial pyrite δ 34 S values here. However, we found that pyrite δ 34 S values are consistently and anomalously lower than coeval precursor compounds at both sites. A steady-state model demonstrates that equilibrium position-specific isotope fractionation (PSIF) effects in the S 8 -polysulfide pool can create a 4.3-7.3‰ gap between δ 34 S values of pyrite and zero-valent sulfur. This study suggests that SOM communities may have distinct effects on pyrite accumulation in seasonally dynamic systems, and that PSIF in the polysulfide pool may leave an imprint in pyrite isotope records.Plain Language Summary Formation of the iron sulfide mineral pyrite in sediments has contributed to long-term oxygen accumulation on Earth, and pyrite's sulfur isotope composition in ancient sediments offers a lens onto low-oxygen intervals in Earth's past. However, seasonal environmental changes in low-oxygen waters can lead to complex relationships between animal burrowing activity, microbial processing of sulfur compounds, and the formation of pyrite. To understand controls on pyrite accumulation and sulfur isotope composition under seasonally dynamic, low-oxygen waters, we analyzed shal...

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Section: Discussionmentioning

confidence: 99%

Sedimentary Pyrite Formation in a Seasonally Oxygen‐Stressed Estuary: Potential Imprints of Microbial Ecology and Position‐Specific Isotope Fractionation

et al. 2023

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“…Previous work has also simulated the mixing of individual particles (e.g., foraminiferal shells) by bioturbation in sediment core archives, for example, the TURBO2 (Trauth, 2013), sedproxy (Dolman & Laepple, 2018), SEAMUS (Lougheed, 2020), and iTURBO2 (Hülse et al., 2022) algorithms. Bioturbated sediment archives feature an apparent heterogeneity in the ages of individual foraminifera (Dolman et al., 2021; Lougheed et al., 2018), calling for IFA reconstructions that account for sediment‐mixing processes in their noise estimation routine and interpretative framework.…”

Section: Introductionmentioning

confidence: 99%

Shell Reworking Impacts on Climate Variability Reconstructions Using Individual Foraminiferal Analyses

Bienzobas Montávez,

Thirumalai,

Marino

2024

Paleoceanog and Paleoclimatol

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Particle mixing by benthic fauna beneath the sediment‐water interface (or bioturbation) fundamentally challenges the proxy based retrieval of past climatic conditions from deep‐sea sediment cores. Previous efforts targeted the impacts of bioturbation on the nature of paleoceanographic changes gleaned from the proxy record, whereas impacts on seasonal and/or interannual variability reconstructions have received less attention. We present TurbIFA (Tracking uncertainty of reworking & bioturbation on IFA), a software that adapts and combines existing algorithms to quantitatively estimate the impact of sediment reworking and other uncertainties and assess significance of ocean and climate variability reconstructions based on individual foraminiferal analyses (IFA). Building upon previous idealized investigations of bioturbation using hydroclimate‐sediment simulations, TurbIFA advances the IFA proxy system modeling such that users may directly assess the sensitivity of their data to various local parameters related to shell reworking across the global ocean. Using the output of state‐of‐the‐art coupled atmosphere‐ocean general circulation models, TurbIFA simulates planktic foraminiferal δ18O or Mg/Ca‐temperature signal carriers and evaluates uncertainties in the sample size, analytical protocols along with as those arising from bioturbation. Application of TurbIFA to synthetic and existing data sets indicates that the significance of IFA‐based reconstructions can be assessed once the impacts of sediment accumulation rates, sediment mixed layer depths, length of time integrated by the chosen IFA sampling interval, and changes in the amplitude of climate variability (i.e., the targeted environmental signal) are comprehensively evaluated. We contend that TurbIFA can aid quantitative assessments of past seasonal and interannual variability gleaned from the paleoceanographic record.

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“…The time averaging of fossil assemblages—that is, their temporal resolution or acuity—and the temporal overlaps or gaps between them in stratigraphic records (their temporal distinctness) affect our ability to infer the rate and magnitude of changes in the composition and diversity of past ecosystems (Berger and Heath 1968; Schink and Guinasso 1977; Fürsich 1978; Kowalewski 1996; Kidwell and Tomašových 2013; Stegner et al 2019); the same issues apply to the age-frequency distribution of any assemblage of targeted particles (e.g., Kemp et al 2018; Straub and Foreman 2018). Variability in temporal resolution creates potential for stratigraphic variability in the degree of smearing of paleobiological variables such as species diversity, relative abundance, and morphologic disparity (Kowalewski et al 1998; Bush et al 2002; Martin et al 2002; Tomašových and Kidwell 2010), along with proxies that fossils carry about paleoenvironments (e.g., isotopes and elemental ratios; Kunz et al 2020; Liu et al 2021; Hülse et al 2022; Lougheed and Metcalfe 2022). Understanding how and why time averaging changes during the earliest phases of burial is thus essential in analyzing ecosystem changes within the Holocene and Anthropocene, given our reliance on various combinations of fully buried assemblages, still-accumulating death assemblages, and historic observations of living assemblages, each with different temporal resolution (Flessa and Kowalewski 1994; Yanes et al 2007; Terry 2010; Miller et al 2014; Leshno et al 2015; Ritter et al 2017; Hyman et al 2019; Parker et al 2020; Ryan et al 2020; Hohmann 2021).…”

Section: Introductionmentioning

confidence: 99%

A downcore increase in time averaging is the null expectation from the transit of death assemblages through a mixed layer

Tomášových¹,

Kidwell²,

Dai³

2023

Paleobiology

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Understanding how time averaging changes during burial is essential for using Holocene and Anthropocene cores to analyze ecosystem change, given the many ways in which time averaging affects biodiversity measures. Here, we use transition-rate matrices to explore how the extent of time averaging changes downcore as shells transit through a taphonomically complex mixed layer into permanently buried historical layers: this is a null model, without any temporal changes in rates of sedimentation or bioturbation, to contrast with downcore patterns that might be produced by human activity. Assuming stochastic burial and exhumation movements of shells between increments within the mixed layer and stochastic disintegration within increments, we find that almost all combinations of net sedimentation, mixing, and disintegration produce a downcore increase in time averaging (interquartile range [IQR] of shell ages), this trend is typically associated with a decrease in kurtosis and skewness and by a shift from right-skewed to symmetrical age distributions. A downcore increase in time averaging is thus the null expectation wherever bioturbation generates an internally structured mixed layer (i.e., a surface, well-mixed layer is underlain by an incompletely mixed layer): under these conditions, shells are mixed throughout the entire mixed layer at a slower rate than they are buried below it by sedimentation. This downcore trend created by mixing is further amplified by the downcore decline in disintegration rate. We find that transition-rate matrices accurately reproduce the downcore changes in IQR, skewness, and kurtosis observed in bivalve assemblages from the southern California shelf. The right-skewed shell age-frequency distributions typical of surface death assemblages—the focus of most actualistic research—might be fossilized under exceptional conditions of episodic anoxia or sudden burial. However, such right-skewed assemblages will typically not survive transit through the surface mixed layer into subsurface historical layers: they are geologically transient. The deep-time fossil record will be dominated instead by the more time-averaged assemblages with weakly skewed age distributions that form in the lower parts of the mixed layer.

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Assessing the impact of bioturbation on sedimentary isotopic records through numerical models

Cited by 10 publications

References 121 publications

Sedimentary Pyrite Formation in a Seasonally Oxygen‐Stressed Estuary: Potential Imprints of Microbial Ecology and Position‐Specific Isotope Fractionation

Sedimentary Pyrite Formation in a Seasonally Oxygen‐Stressed Estuary: Potential Imprints of Microbial Ecology and Position‐Specific Isotope Fractionation

Shell Reworking Impacts on Climate Variability Reconstructions Using Individual Foraminiferal Analyses

A downcore increase in time averaging is the null expectation from the transit of death assemblages through a mixed layer

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