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Relative sea-level change in South Florida during the past ~5 ka

Khan, N.S. and Ashe, E. and Moyer, R.P. and Kemp, A.C. and Engelhart, S.E. and Brain, M.J. and Toth, L.T. and Chappell, A. and Christie, M. and Kopp, R.E. and Horton, B.P. (2022) 'Relative sea-level change in South Florida during the past ~5 ka.', Global and Planetary Change, 216 . p. 103902.

Abstract

A paucity of detailed relative sea-level (RSL) reconstructions from low latitudes hinders efforts to understand the global, regional, and local processes that cause RSL change. We reconstruct RSL change during the past ~5 ka using cores of mangrove peat at two sites (Snipe Key and Swan Key) in the Florida Keys. Remote sensing and field surveys established the relationship between peat-forming mangroves and tidal elevation in South Florida. Core chronologies are developed from age-depth models applied to 72 radiocarbon dates (39 mangrove wood macrofossils and 33 fine-fraction bulk peat). RSL rose 3.7 m at Snipe Key and 5.0 m at Swan Key in the past 5 ka, with both sites recording the fastest century-scale rate of RSL rise since ~1900 CE (~2.1 mm/a). We demonstrate that it is feasible to produce near-continuous reconstructions of RSL from mangrove peat in regions with a microtidal regime and accommodation space created by millennial-scale RSL rise. Decomposition of RSL trends from a network of reconstructions across South Florida using a spatio-temporal model suggests that Snipe Key was representative of regional RSL trends, but Swan Key was influenced by an additional local-scale process acting over at least the past five millennia. Geotechnical analysis of modern and buried mangrove peat indicates that sediment compaction is not the local-scale process responsible for the exaggerated RSL rise at Swan Key. The substantial difference in RSL between two nearby sites highlights the critical need for within-region replication of RSL reconstructions to avoid misattribution of sea-level trends, which could also have implications for geophysical modeling studies using RSL data for model tuning and validation.

Item Type:Article
Full text:Publisher-imposed embargo until 30 July 2023.
(AM) Accepted Manuscript
Available under License - Creative Commons Attribution Non-commercial No Derivatives 4.0.
File format - PDF
(3640Kb)
Status:Peer-reviewed
Publisher Web site:https://doi.org/10.1016/j.gloplacha.2022.103902
Publisher statement:© 2022. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/
Date accepted:27 July 2022
Date deposited:02 August 2022
Date of first online publication:30 July 2022
Date first made open access:30 July 2023

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