Mangrove pollen of Indonesia and its suitability as a sea-level indicator

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1016/j.margeo.2007.02.020. This is version 1 of this Preprint.

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Authors

Simon Engelhart, Benjamin Horton, David H. Roberts, Charlotte L. Bryant, D. Reide Corbett

Abstract

We investigated the mangroves of Southeast Sulawesi, Indonesia, to assess their potential as proxies for reconstructing sea level during the Holocene. Initial investigations confirmed that the mangrove species demonstrate zonations parallel to the shoreline and are dominated by the family Rhizophoraceae with Avicennia, Heritiera and Sonneratia also important constituents of the mangroves.
We investigated the vertical distributions of pollen assemblages at three sites. Partial CCA analysis demonstrated that at all three sites, elevation was a significant control on the distribution of pollen assemblages in surface samples. We combined the three contemporary transects to develop a regional transfer function to explain the relationship between the surface assemblages and elevations using the Maximum Likelihood (ML) method. The developed transfer function indicated mangrove pollen can be used as a precise indicator of past sea levels with an error of ±0.22 m. The transfer function was applied to two fossil cores from the Wakatobi Marine National Park and evaluated using the Modern Analogue Technique. Both cores showed similar patterns in changes of palaeo mangrove elevation and had modern analogues in the contemporary training set. We conclude that mangrove pollen is a suitable proxy for reconstructing sea level in tropical environments.

DOI

https://doi.org/10.31223/osf.io/76tvu

Subjects

Earth Sciences, Environmental Sciences, Geography, Physical and Environmental Geography, Physical Sciences and Mathematics, Social and Behavioral Sciences

Keywords

Sea level, mangrove, paleoenvironmental change, palynology

Dates

Published: 2018-10-26 12:35

License

CC BY Attribution 4.0 International