Browsing by Subject "XRF scans"

Now showing 1 - 1 of 1
  • Thumbnail Image
    Item
    High Resolution geochemical XRF data from Elk Lake, Minnesota: A Holocene paleoclimate record from varved lacustrine sediments.
    (2010-09) Rush, Robert Allen
    The study of Holocene climate change is vital to understanding present and future climate conditions in the Upper Midwest region of the United States. Varved sediments from Elk Lake, Clearwater County, Minnesota provide an archive of multiple climate sensitive proxies and past climate conditions, particularly related to the balance of precipitation and evaporation (available moisture) for the North Central United States. Studies conducted in the past using Elk Lake sediments have established large scale and long term changes in the climate history of the region, but were done at a resolution that only allowed for a discussion of events on time scales of hundreds to thousands of years. Scanning XRF is a new analytical technique that allows for much higher resolution, geochemical data to be gathered from sediment cores for the characterization of climate variability with resolution on the order of decades to inter-annual changes. This study seeks to repeat, using new analytical and higher resolution methods, the work done by previous researchers. One centimeter resolution XRF scans were used to describe changes that occurred during the Holocene, and 200 micron scans were used to identify the nature of varve deposition during major periods in the Holocene and to characterize the timing and relationships between the laminations that make up individual varves. With higher resolution data with which to work, time series analysis provides insight into high frequency cycles during the Holocene record including El Nino Southern Oscillation (ENSO) and solar activity cycles. With the addition of the first known geophysical data set from Elk Lake, this study also illustrates the usefulness of obtaining multiple records from an individual lake. Through the use of both geochemical and geophysical data, it is shown that events seen separately in each data set can be correlated to one another and an accurate estimate for the timing of major climate events can be obtained.