Forest fragmentation in the Pacific Northwest: quantification and correlations [An article from: Forest Ecology and Management] Buy on Amazon

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Forest fragmentation in the Pacific Northwest: quantification and correlations [An article from: Forest Ecology and Management]

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PublisherElsevier
ISBN / ASINB000RR0Y98
ISBN-13978B000RR0Y95
AvailabilityAvailable for download now
MarketplaceUnited States  🇺🇸

Description

This digital document is a journal article from Forest Ecology and Management, published by Elsevier in 2004. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

Description:
A forest fragmentation index was produced for western Oregon and western Washington that combined measures of forested area, percentage edge, and interspersion. While natural, human land-cover, and human land-use processes contribute to forest fragmentation in the region, the drivers of these processes are categorically different. Here we examine forest fragmentation caused by human land-use decisions, which accounts for 20% of the total forest edge in the region. Using multiple linear regression, we developed a model with socio-economic and environmental predictor variables that explains 80% of the variance of the forest fragmentation index across the region. Population density, income, and percentage agriculture were all significant and positively correlated with the fragmentation index. Significantly negative correlations were found between the forest fragmentation index and distance to highway, percentage federal land, slope, and a dummy variable indicating land in Oregon. The three components of the fragmentation index were used as predictor variables in separate regression models and yielded results similar to the composite index. Models run separately for western Oregon and western Washington were similar to the regional model except that distance to highway was only significant in the western Oregon model and income was only significant in the western Washington model.
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