Paleolandform Reconstruction Offshore of the Channel Islands Using Sediment Cores and High-Resolution Seismic Data
Rising sea levels following the last glacial maximum (LGM) submerged vast subaerial landscapes on continental shelves around the world. Offshore southern California, the four northern Channel Islands were connected by land bridges into a super island known as Santarosae during the LGM. Evidence from terrestrial archaeological sites indicates that people lived on Santarosae beginning at least 13,000 years ago. Reconstructing the paleolandscape of drowned portions of Santarosae could be instrumental in the search for terminal Pleistocene and Early Holocene archaeological sites. Here, we present interpretations based on analysis of sediment cores and seismic data from the northern Channel Islands platform, providing a more robust understanding of the paleolandscape and geologic history of the northern Channel Islands. During two research cruises, twenty-six sediment cores were collected using a Rossfelder P-5 vibracore. Computed tomography (CT) scans, photos, radiocarbon dates, and geologic logs of cores were used to characterize sediment core geology and interpret depositional environments. The core geology was correlated to seismic facies, which were mapped using Kingdom Suite through a Chirp dataset collected in 2016. The combined data revealed paleoenvironments interpreted as highstand marine, coastal to estuarine, and fluvial-alluvial. These data show that some parts of the paleolandscape deposited during lower sea level are preserved around the northern Channel Islands, despite a very high energy coastal ocean. This study contributes to a larger project by San Diego State University, the Bureau of Ocean Energy Management, and partner institutions which aims to develop a methodology to better identify potential submerged archaeological resources in the Pacific Outer Continental Shelf using geophysical surveys, radiometrically dated cores, analysis of terrestrial archaeological sites, biological surveys, and ArcGIS modeling.