Dissertation/Thesis Abstract

Presettlement Forest Composition in the Connecticut Tract of Western New York
by Brister, Evelyn, M.S., Rochester Institute of Technology, 2012, 68; 10020365
Abstract (Summary)

This study of the vegetation of the 100,000-acre Connecticut Tract in western New York examines the presettlement characteristics of the forest, including the tree species composition, tree density, and wetland extent. Presettlement vegetation studies add to what is known about the forests of this region before European settlement in the early 1800s brought widespread changes to these forests. The ecological data in original private land surveys from 1811 were transcribed and then analyzed using ArcGIS and IDRISI GIS software. The surveys contained both witness tree data and line descriptions, which were analyzed for species composition and community type and were compared with Forest Inventory and Analysis (FIA) data about the contemporary forest in the study area. The community type results together with surveyor notes were used to extrapolate wetland coverage, which was compared with the 2006 National Wetlands Inventory Database.

This study fills in missing historical data between the two largest land purchases in western New York and examines forest composition at a finer-grained scale than surveys of those land purchases. Comparing past and present vegetation clarifies past causes of temporal and spatial variability and provides a reference point for land managers who need to understand the effects of land-use history for ongoing restoration efforts.

Indexing (document details)
Advisor: Hane, Elizabeth N.
Commitee: Keiner, Christine M., Korfmacher, Karl F.
School: Rochester Institute of Technology
Department: Environmental Science
School Location: United States -- New York
Source: MAI 55/03M(E), Masters Abstracts International
Source Type: DISSERTATION
Subjects: Ecology, Geography, Environmental science
Keywords: Ecological data, Geographical information systems, Historical ecology, Land use, Presettlement surveys
Publication Number: 10020365
ISBN: 9781339512600
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