Abstract/Details

A modelling-based approach for detecting prehistoric anthropogenic fires in north-central Massachusetts


2004 2004

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Abstract (summary)

The importance of prehistoric anthropogenic fires to the landscape of the Northeast continues to be studied and debated by ecologists. Inferences about prehistoric anthropogenic fires are made using fossil pollen and charcoal evidence from sediment cores taken from ponds and bogs, but the results remain equivocal. I present a modelling-based strategy to locate sediment core sites so that the occurrence of prehistoric anthropogenic fires can be detected in the hilly uplands of north-central Massachusetts. I use a prehistoric human settlement model and ethnographic data about aboriginal fire-setting behavior to predict areas likely to have been burned, and to select suitable ponds for coring. I use a fine-scale, large-area, long-term forest growth model to simulate mid-Holocene vegetation to aid in the interpretation of fossil pollen data at the selected ponds. A list of ponds likely to contain evidence of fire and ponds not likely to contain evidence of fire are provided, along with vegetation patterns likely to be observed at each selected pond and across the study area.

Indexing (details)


Subject
Paleoecology;
Archaeology;
Ecology
Classification
0426: Paleoecology
0324: Archaeology
0329: Ecology
Identifier / keyword
Social sciences, Earth sciences, Biological sciences, Anthropogenic, Fires, Forests, Massachusetts, Prehistoric
Title
A modelling-based approach for detecting prehistoric anthropogenic fires in north-central Massachusetts
Author
Kim, John B.
Number of pages
162
Publication year
2004
Degree date
2004
School code
0118
Source
DAI-B 65/11, Dissertation Abstracts International
Place of publication
Ann Arbor
Country of publication
United States
ISBN
9780496132478, 0496132474
Advisor
Finn, John T.
University/institution
University of Massachusetts Amherst
University location
United States -- Massachusetts
Degree
Ph.D.
Source type
Dissertations & Theses
Language
English
Document type
Dissertation/Thesis
Dissertation/thesis number
3152714
ProQuest document ID
305176921
Copyright
Database copyright ProQuest LLC; ProQuest does not claim copyright in the individual underlying works.
Document URL
http://search.proquest.com/docview/305176921
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