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Soil moisture, forest productivity and ecological land classification in central Massachusetts

Throughout much of the United States, systems of ecological land classification are used to divide the forested landscape into units that are biologically and operationally meaningful. No such system currently exists in central Massachusetts, however, due to the extensive and prolonged effects of human land use. Initial research on a series of State Forests in central Massachusetts indicate that physical site characteristics such as the presence of a hardpan, soil texture and type of glacial deposition can be correlated with patterns in vegetation distribution. These factors are similar to those used by W. B. Leak in creating an ecological land type (ELT) classification for the White Mountain National Forest in New Hampshire. A system was created to adapt and transfer the White Mountain ELTs to central Massachusetts. The system was then applied to a variety of sites in central Massachusetts at two different scales. The habitat classification system reflected general trends of vegetation composition and productivity, particularly at a local landscape level, but further work is needed to better account for the effect of land use history and local ecological variation. An underlying assumption of ecological land classification is that vegetation is most strongly influenced by site factors that are related to soil moisture availability. Direct soil moisture measurements were made on a variety of sites throughout a season at Cadwell Memorial Forest in Pelham, Massachusetts. Analysis showed a relatively poor correlation between soil moisture measured that year and long-term site productivity. However, the pattern of short term (weekly) variation in soil moisture was related to general trends in productivity. The hydrologic model, TOPMODEL, was used to create a relative wetness potential index within a GIS framework to predict site productivity based on potential soil moisture availability. While this model showed some potential in predicting general soil moisture status, it was not well correlated with the direct soil moisture measurements.

Identiferoai:union.ndltd.org:UMASS/oai:scholarworks.umass.edu:dissertations-4073
Date01 January 2005
CreatorsLeighton, Adrian D
PublisherScholarWorks@UMass Amherst
Source SetsUniversity of Massachusetts, Amherst
LanguageEnglish
Detected LanguageEnglish
Typetext
SourceDoctoral Dissertations Available from Proquest

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