A quantitative inference model for conductivity using non-marine ostracode assemblages on San Salvador Island, Bahamas: Paleosalinity records from two lakes

Andrew V. Michelson, Lisa Park Boush

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Quantitative records of past environments are needed to understand natural variability in ecosystems and their responses to climate change. Changes in ostracode assemblages through time can provide such records as ostracode species are sensitive to changes in their local environments. Before they can be used to indicate past environments, however, is it necessary to understand how distributions of assemblages change across environmental gradients. To that end, thirty-two lakes on San Salvador Island, Bahamas were sampled for both ostracodes and nineteen limnological variables. Multivariate fuzzy set ordination indicates that change in ostracode assemblages is significantly and independently correlated with three environmental variables: electrical conductivity (salinity), dissolved oxygen and alkalinity. A transfer function was created to reconstruct past conductivity since changing conductivity of lakes on San Salvador is influenced by changes in climate and sea-level. A 2-component weighted-averaging partial least squares model performed best as a transfer function for conductivity with an apparent r2 of 0.76 and an r2 of 0.69 between observed and predicted conductivity, as assessed by leave-one-out cross validation. The resulting transfer function was then applied to two mid- to late-Holocene sediment cores from which ostracode assemblages were sampled. The late Holocene conductivity records show that changes in conductivity of lakes on San Salvador are broadly synchronous with times of enhanced ENSO activity corresponding to elevated conductivity in response to lower Atlantic hurricane occurrence. These results demonstrate that changing ostracode assemblages through time provide a reliable means to reconstruct past salinity and demonstrates the strong effect of ENSO on Bahamian aridity.

Original languageEnglish (US)
Pages (from-to)27-39
Number of pages13
JournalPalaeogeography, Palaeoclimatology, Palaeoecology
Volume477
DOIs
StatePublished - Jul 1 2017

Bibliographical note

Funding Information:
We would like to thank the late Dr. Donald T. Gerace, Chief Executive Officer, Tom Rothfus, Executive Director, and Erin Rothfus, Research Coordinator, of the Gerace Research Center, San Salvador, Bahamas. We would also like to thank Sara Bright, Mark Dalman, Emily Frank, and Emily Woodward for providing field assistance and Tom Quick and Krystal Kohlman for providing laboratory assistance. We also thank the National Lacustrine Core Facility (LacCore) at the University of Minnesota Twin Cities, Amy Myrbo, and Kristina Brady of LacCore for valuable field and logistical support. We are grateful to the Large Lake Observatory (LLO) at the University of Minnesota Duluth, Erik Brown, and Aaron Lingwall of LLO for the use of and assistance with the XRF. Thanks to Susan M. Kidwell, Jill Leonard-Pingel, Madeline Marshall, Peter Tierney, Kristen Jenkins Voorhies, Ian Boomer, Bosiljka Glumac, Michael Savarese, Ronald Lewis, and two anonymous reviewers for providing valuable comments on previous versions of this paper. Andrew V. Michelson received funding from the University of Akron Geology and Environmental Science Department, University of Akron Program in Integrated Bioscience, University of Akron Graduate Student Government, and the Gerace Research Centre. Lisa E. Park Boush received funding from NSF EAR 0851847. This work was done under Permit G234 and G235 to Park Boush and was supported by the National Science Foundation as part of the author's Individual Research Plan. She served as a Program Officer within SGP/EAR/GEO.

Publisher Copyright:
© 2017 Elsevier B.V.

Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

Keywords

  • Calibration
  • El Niño
  • Hurricane
  • Salinity
  • Transfer function

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