Salt-marsh reconstructions of relative sea-level change in the North Atlantic during the last 2000 years

Barlow, Natasha; Long, Antony J.; Saher, Margot; Gehrels, W. Roland; Garnett, Mark H.; Scaife, Rob

doi:10.1016/j.quascirev.2014.06.008

Cited by 42 publications

(40 citation statements)

References 55 publications

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“…Bradley et al, 2011;Kuchar et al, 2012;Milne et al, 2006;Peltier et al, 2002;Shennan et al, 2000;, improved modelling of changes in tidal range (Neill et al, 2010;Shennan et al, 2003;Uehara et al, 2006;Ward et al, 2016) and new field-based research to test research questions arising from the existing model-data comparisons (e.g. Barlow et al, 2014;Edwards et al, 2017;Massey et al, 2008). With the last major revisions of the databases from Britain and Ireland (Brooks and Edwards, 2006) more than a decade ago, our objective here is update and integrate these databases and address outstanding research questions.…”

Section: Introductionmentioning

confidence: 99%

Relative sea-level changes and crustal movements in Britain and Ireland since the Last Glacial Maximum

Shennan

Bradley

Edwards

2018

Quaternary Science Reviews

112

170

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Section: Introductionmentioning

confidence: 99%

Relative sea-level changes and crustal movements in Britain and Ireland since the Last Glacial Maximum

Shennan

Bradley

Edwards

2018

Quaternary Science Reviews

112

170

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“…We present these data as detrended signals since this is the format commonly used for comparison with models and between regions with differing background rates of RSL rise (e.g. Engelhart et al, 2009; Gehrels, 2010; Kemp et al, 2011;Barlow et al, 2014;Kopp et al, 2016). …”

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confidence: 99%

Reconstructing the accumulation history of a saltmarsh sediment core: Which age-depth model is best?

Wright

Edwards

Plassche

et al. 2017

Quaternary Geochronology

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Saltmarsh-based reconstructions of relative sea-level (RSL) change play a central role in current efforts seeking to quantify the relationship between climate and sea-level rise. The development of an accurate chronology is pivotal, since errors in age-depth relationships will propagate to the final record as alterations in both the timing and magnitude of reconstructed change. A range of age-depth modelling packages are available but differences in their theoretical basis and practical operation mean contrasting accumulation histories can be produced from the same dataset.We compare the performance of five age-depth modelling programs (Bacon, Bchron, Bpeat, Clam and OxCal) when applied to the kinds of data used in high resolution, saltmarsh-based RSL reconstructions.We investigate their relative performance by comparing modelled accumulation curves against known age-depth relationships generated from simulated stratigraphic sequences. Bpeat is particularly sensitive to non-linearities which, whilst maximising the detection of small rate changes, has the potential to generate spurious variations, particularly in the last 400 years. Bacon generally replicates the pattern and magnitude of change but with notable offsets in timing. Bchron and OxCal successfully constrain the known accumulation history within their error envelopes although the best-fit solutions tend to underestimate the magnitude of change. The best-fit solutions of Clam generally replicate the timing and magnitude of changes well, but are sensitive to the underlying shape of the calibration curve, performing poorly where plateaus in atmospheric 14 C concentration exist.We employ an ensemble of age-depth models to reconstruct a 1500 year accumulation history for a saltmarsh core recovered from Connecticut, USA based on a composite chronology comprising 26 AMS radiocarbon dates, 210 Pb, 137 Cs radionuclides and an historical pollen chronohorizon. The resulting record reveals non-linear accumulation during the late Holocene with a marked increase in rate around AD1800. With the exception of the interval between AD1500 and AD1800, all models produce accumulation curves that agree to within ~10 cm at the century-scale. The accumulation rate increase around AD1800 is associated with the transition from a radiocarbon-based to a 210 Pb-dominated chronology. Whilst repeat analysis excluding the 210 Pb data alters the precise timing and magnitude of this acceleration, a shift to faster accumulation compared to the long-term rate is a robust feature of the record and not simply an artefact of the switch in dating methods. Simulation indicates that a rise of similar magnitude to the post-AD1800 increase (detrended increase of ~16 cm) is theoretically constrained and detectable within the radiocarbon-dated portion of the record. The absence of such a Author's corrected version: Published in Quaternary Geochronology, Volume 39, April 2017, Pages 35-67, http://dx.doi.org/10.1016/j.quageo.2017 3 signal suggests that the recent rate of accumulation i...

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“…The B-TF provides an alternative to the (non-Bayesian) regression-based transfer functions commonly used for reconstructing RSL (e.g., Horton et al, 1999;Gehrels, 2000;Barlow et al, 2014) and in conjunction with the previously developed chronology and process modules enables RSL to be reconstructed in an entirely Bayesian framework. A key difference between the B-TF and existing transfer functions (e.g., the WA-TF) is the modeled relationship between species of foraminifera and tidal elevation.…”

Section: Discussionmentioning

confidence: 99%

“…These results highlight the specific utility of bulk sediment δ 13 C measurements as a sea-level indicator along the mid-and northeast Atlantic coast the USA and the general utility of employing a multi-proxy approach to reconstructing RSL where the goal is to produce reconstructions with the best possible precision. A practical and intuitive means to illustrate the improved performance of the multi-proxy B-TF over the WA-TF model is to compare RSL reconstructions with long-term measurements made by nearby tide gauges (e.g., Kemp et al, 2009bKemp et al, , 2013bBarlow et al, 2014;Long et al, 2014;Leorri et al, 2008). We compare the reconstruction provided by the WA-TF, B-TF and multi-proxy BTF with regional tide-gauge measurements from New Jersey (Fig.…”

Section: Discussionmentioning

confidence: 99%

“…The parameters in transfer functions are estimated using empirical data (a modern training set) from environments likely to be analogous to those encountered in core material (e.g., Juggins and Birks, 2012) and are treated as fixed and known. Studies seeking to reconstruct RSL from salt-marsh sediment employ transfer functions developed using a modern training set of paired observations of tidal elevation and microfossil assemblages (most commonly foraminifera or diatoms) to reconstruct RSL from their counterparts preserved in sediment cores (e.g., Horton et al, 1999;Gehrels, 2000;Edwards and Horton, 2006;Kemp et al, 2013b;Barlow et al, 2014). Although the different types of transfer function have advantages and weaknesses compared to one another, these regression-based techniques share the limitations of applying a single response form to all species and treating model parameters as fixed and known.…”

Section: Previous Calibration Methodsmentioning

confidence: 99%

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A Bayesian hierarchical model for reconstructing relative sea level: from raw data to rates of change

et al. 2016

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Abstract. We present a Bayesian hierarchical model for reconstructing the continuous and dynamic evolution of relative sea-level (RSL) change with quantified uncertainty. The reconstruction is produced from biological (foraminifera) and geochemical (δ 13 C) sea-level indicators preserved in dated cores of salt-marsh sediment. Our model is comprised of three modules: (1) a new Bayesian transfer (B-TF) function for the calibration of biological indicators into tidal elevation, which is flexible enough to formally accommodate additional proxies; (2) an existing chronology developed using the Bchron age-depth model, and (3) an existing ErrorsIn-Variables integrated Gaussian process (EIV-IGP) model for estimating rates of sea-level change. Our approach is illustrated using a case study of Common Era sea-level variability from New Jersey, USA We develop a new B-TF using foraminifera, with and without the additional (δ 13 C) proxy and compare our results to those from a widely used weighted-averaging transfer function (WA-TF). The formal incorporation of a second proxy into the B-TF model results in smaller vertical uncertainties and improved accuracy for reconstructed RSL. The vertical uncertainty from the multi-proxy B-TF is ∼ 28 % smaller on average compared to the WA-TF. When evaluated against historic tide-gauge measurements, the multi-proxy B-TF most accurately reconstructs the RSL changes observed in the instrumental record (mean square error = 0.003 m 2 ). The Bayesian hierarchical model provides a single, unifying framework for reconstructing and analyzing sea-level change through time. This approach is suitable for reconstructing other paleoenvironmental variables (e.g., temperature) using biological proxies.

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Salt-marsh reconstructions of relative sea-level change in the North Atlantic during the last 2000 years

Cited by 42 publications

References 55 publications

Relative sea-level changes and crustal movements in Britain and Ireland since the Last Glacial Maximum

Relative sea-level changes and crustal movements in Britain and Ireland since the Last Glacial Maximum

Reconstructing the accumulation history of a saltmarsh sediment core: Which age-depth model is best?

A Bayesian hierarchical model for reconstructing relative sea level: from raw data to rates of change

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