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Abstract Coastal ecosystems such as mangroves, salt marshes, and seagrasses sequester large amounts of carbon per unit area due to their high productivity and sediment accumulation rates. However, only a handful of studies have examined carbon sequestration in coastal dunes, which are shaped by biophysical feedback between aeolian sediment transport and burial-tolerant vegetation. The goal of this study was to measure carbon storage and identify the factors that influence its variability along the foredunes of the US Outer Banks barrier islands of North Carolina. Specifically, differences in carbon stocks (above- and belowground biomass and sand), dune grass abundance, and sand supply were measured among islands, cross-shore dune profile locations, and dune grass species. Carbon varied among aboveground grass biomass (0.1 ± 0.1 kg C m⁻²), belowground grass biomass (1.1 ± 1.6 kg C m⁻³), and sand (0.9 ± 0.6 kg C m⁻³), with the largest amount in belowground grass stocks. Aboveground grass carbon stocks were comparable to those in eelgrass beds and salt marshes on a per-area basis, while sediment carbon values in our study system were lower than those in other coastal systems, including other dune locations. Additionally, sand carbon density was positively related to patterns in dune sand supply and grass abundance, reflecting a self-reinforcing vegetation-sediment feedback at both high and low sand accumulation rates. 

While it remains uncertain whether excursions in the stable carbon isotopic composition of Ediacaran marine carbonate (δ13Ccarb) represent globally synchronous events (or a direct measure of ocean carbon cycling), the absence of widely distributed and readily preservable fauna, and the presence of several iconic carbon isotope excursions (CIEs), has sustained δ13Ccarb correlation as the primary means to establish relative time relationships for Ediacaran successions. Here we present an Ediacaran global δ13Ccarb composite built with a dynamic time warping (DTW) time-normalization algorithm that generates libraries of least-squares alignments between chemostratigraphic records of unequal length and distinct sediment accumulation rates. When developing a δ13Ccarb composite for each of 16 globally distributed Ediacaran paleo-depositional regions, we selected high Pearson r alignments that conformed with published geological guidance about the correlation of constituent sections. When applying DTW to align these regional algorithmic composites into one global δ13Ccarb stack, we selected alignments that allied the excursions that field workers have established (or speculated) are the Marinoan cap carbonate excursion, the Shuram excursion, and/or the basal Cambrian excursion. There are strengths and weaknesses to making explicit the temporal relationships (point-to-point correspondences) often left implicit in visual correlation. One strength is to extrapolate depositional ages by means of isotopic correlation, and here we explored this with a Bayesian Markov chain Monte Carlo age model that predicts a median age, and uncertainty, for every carbonate stratum in the global Ediacaran δ13Ccarb composite. Yet, one must caution against a false accuracy that can arise from selecting one alignment among many possibilities––the likelihood that time-uncertain time series can be stretched and squeezed into one unequivocal alignment is low. Thus, while these alignments are grounded in the expert assessment of the field worker, this global Ediacaran δ13Ccarb–Bayesian age model should be viewed as a working hypothesis to enrich, but not arbitrate, discussions of the correlation, synchrony, and completeness of Ediacaran successions. 

SUMMARY We present and make publicly available a dynamic programming algorithm to simultaneously align the inclination and declination vector directions of sedimentary palaeomagnetic secular variation data. This algorithm generates a library of possible alignments through the systematic variation of assumptions about the relative accumulation rate and shared temporal overlap of two or more time-series. The palaeomagnetist can then evaluate this library of reproducible and objective alignments using available geological constraints, statistical methods and expert knowledge. We apply the algorithm to align previously (visually) correlated medium to high accumulation rate northern North Atlantic Holocene deposits (101–102 cm ka–1) with strong radiocarbon control. The algorithm generates plausible alignments that largely conform with radiocarbon and magnetic acquisition process uncertainty. These alignments illustrate the strengths and limitations of this numerical approach.