Northeastern Section - 53rd Annual Meeting - 2018

Paper No. 23-7
Presentation Time: 1:30 PM-5:30 PM


BRUSH, Jared, Earth and Environment, Franklin and Marshall College, 415 Harrisburg Ave, Lancaster, PA 17603, DEWET, Andrew P., Earth & Environment, Franklin & Marshall College, PO Box 3003, Lancaster, PA 17604-3003, DE WET, Gregory, Department of Geological Sciences, University of Colorado Boulder, UCB 399, Boulder, CO, BRADLEY, Raymond S., Northeast Climate Science Center, University of Massachusetts - Amherst, 611 North Pleasant St, 134 Morrill Science Center, Amherst, MA 01003 and ZHAO, Boyang, Department of Geosciences, University of Massachusetts Amherst, 611 North Pleasant Street, Amherst, MA 01003

Sometime before the late 1400’s, the Norse population of Greenland disappeared. Various causes for this disappearance have been proposed, including climate change, disease, and economic factors. In using both field and lab data, we hope to determine which factor was most impactful. This project is part of a larger ongoing initiative to better understand the local climate conditions at the Eastern settlement in modern Qassiarsuk, Sillisit, and Igaliku, Greenland.

Our work involved collecting field observations and samples from four lakes and their associated watersheds where abandoned Norse settlements are located. Field methods included using time-interval sediment loggers, sediment traps, hydrolab profiles (pH, DO, T), groundcover mapping, and drone imaging. Using the data gathered from the Hydrolab, we were able to plota number of parameters (dissolved oxygen, temperature) against the depth, generating lake profiles, and allowing for the comparison between lakes. This data was then integrated into a GIS database and combined with satellite imagery to generate thematic maps and 3D models of the Norse ruins and surrounding areas.

The drainage basins of these four lakes were delineated based on ground observations and DEM’s (4m resolution) derived from the Polar Geospatial Center’s ArcticDEM data. By utilizing ground based training fields and high resolution multispectral imagery, the land cover, vegetation, and distribution can be defined and used to inform downcore reconstructions of paleo-vegetation and temperature from lake sediments This data will better constrain biomarker paleoclimate data from high latitude lakes and watersheds, better allowing s to understand how climate has changed over time.