Paleovegetational Reconstruction Based on Modern and Fossil Pollen Data: An Application of Discriminant Analysis

Abstract

This paper introduces the use of discriminant analysis as an aid in paleovegetational reconstruction based on modern and fossil pollen data. We derived a set of discriminant functions that correctly classifies 95 percent of 121 surface samples collected from different vegetation regions in northeastern North America. These functions were then applied to the pollen-stratigraphic data from Jack Lake to reconstruct the postglacial vegetational history of northern Ontario. The discriminant analysis results are summarized in two indices. A “vegetation zonal index'’directly translates each fossil pollen spectrum into its modern vegetational analogue. Paleovegetation types without modern analogue could be easily detected by computing the “probability of modern analogue.'’These results indicate explicitly that the early spruce-dominated boreal forest around Jack Lake does not have a modern analogue and that the boreal forest/Great Lakes—St. Lawrence Forest ecotone advanced far north of Jack Lake during the Hypsithermal (ca. 7,300–2,600 B.P.).

Key Words:

• discriminant analysis
• pollen data
• paleovegetational reconstruction
• classification
• vegetation zonal index
• modern analogue
• ecotone
• Ontario