GSA Annual Meeting in Denver, Colorado, USA - 2016

Paper No. 161-9
Presentation Time: 9:00 AM-6:30 PM


AVNAIM-KATAV, Simona, UCLA Institute of the Environment and Sustainability (IoES) and the Department of Geography, University of California, Los Angeles, LA KRETZ HALL, SUITE 300 619 CHARLES E. YOUNG DR. EAST BOX 951496, Los Angeles, CA 90095, GEHRELS, W. Roland, Environment Department, University of York, Heslington, York, YO10 5NG, United Kingdom, BROWN, Lauren N., Geography, University of California, Los Angeles, 1255 Bunche Hall University of California, Los Angeles Box 951524, Los Angeles, CA 90095, FARD, Elizabeth, Geography, University of California, Los Angeles, 1255 Bunche Hall Box 951524, Los Angeles, CA 90095 and MACDONALD, Glen M., Department of Geography, University of California at Los Angeles, 1255 Bunche Hall, Los Angeles, CA 90095,

Salt-marsh foraminifera are proxies frequently used around the world in paleoenvironmental studies of sea-level change. Quantitative reconstructions of sea-level change use transfer functions which are based on the vertical zonation of salt-marsh foraminifera with respect to the tidal frame.

This paper explores for the first time the environmental factors that control the surface foraminiferal assemblages in Southern California marshes using samples from two marshes Seal Beach and Tijuana). The dead foraminiferal assemblages demonstrate distinct zonation across the salt-marsh surfaces which is primarily related to elevation. Other variables less important than elevation such as O2, temperature, salinity and pH additionally control the distribution pattern of these assemblages. The tidal flat and low marshes are characterized by high abundances of Miliammina fusca and calcareous species. The middle marsh is dominated by Jadammina macrescens and Trochammina inflata, while the high marsh zone is dominated by Trochamminita irregularis, Miliammina petila, J. macrescens and T. inflata.

Regression modelling was used for the development of a sea-level transfer function based on a combined training set of surface samples from the two study sites. The performance of the Weighted Average – Partial Least Squares (WA-PLS) transfer function suggests a robust relationship between the observed and estimated elevations (r2Jack = 0.72), and is capable of predicting former sea levels to a precision of ±0.09 m. Our results can be used for future paleoenvironmental reconstructions along the Southern California coast, an area that has experienced changes in sea level in the past and will be affected by future sea-level rise coupled with climate and anthropogenic changes, resulting in wide impacts on the natural coastal habitats in this region.