Landscape pattern analysis related to forest wildlife resources

dc.contributor.authorTrani, Margaret Katherineen
dc.contributor.committeechairGiles Jr., Robert H.en
dc.contributor.committeememberAngermeier, Paul L.en
dc.contributor.committeememberGregoire, Timothy G.en
dc.contributor.committeememberSmith, James L.en
dc.contributor.committeememberStauffer, Dean F.en
dc.contributor.departmentFisheries and Wildlife Sciencesen
dc.description.abstractWildlife management and natural resource policy decisions are increasingly being made at the landscape level. Understanding the relationship between modification and the pattern of land classes may minimize potential impacts and enhance the complement of wildlife species. Twenty-four expressions were selected for landscape analysis that describe the spatial heterogeneity, fragmentation, edge characteristics, and connectivity of pattern. Metric relationships were characterized across a variety of landscapes. Cluster analysis organized the metrics into classes quite different from the classification categories used in the literature. Cluster membership reflected the number of land classes, the amount and distribution of forest cover, number of forest patches, patch position, patch shape, patch radius, and edge length. Cartographic modeling was used to determine how modification influenced landscape pattern. The models depicted spatial relationships resulting from proposed landscape changes. Timber harvest schemes with a few large units and those in clustered arrangements led to less fragmentation than those schemes with several small units or those dispersed across the landscape. The placement of roads had either an invasive or partitioning effect on landscape pattern. Discriminant analysis rated the effectiveness of pattern expressions for environmental assessment. Metric effectiveness differed among the timber harvest, road expansion, and deforestation modification schemes. The utility and limitations of each expression was discussed. Sensitivity analyses examined the effects of changing spatial scale on pattern description. Scale influence was dependent upon landscape complexity, distribution of land classes, and the size and shape of those classes. The loss of ability to detect localized variability, to differentiate among spatial patterns, and to represent boundary detail accompanied the use of large pixels (420m²). There was evidence that spatial scale influences habitat evaluation. Semivariogram analysis assessed the constancy of expression behavior during changes in scale and presented the limits of tolerance for using large pixels in pattern analyses. The variability observed suggested that pattern misrepresentation occurred at coarse resolution levels. The successful application of landscape analysis depends on the ability to quantify pattern. By analyzing and understanding selected aspects of landscape pattern, I have examined how wildlife management can be enhanced through a knowledge of the landscape.en
dc.description.degreePh. D.en
dc.format.extentix, 183 leavesen
dc.publisherVirginia Techen
dc.relation.isformatofOCLC# 35301154en
dc.rightsIn Copyrighten
dc.subjectforest wildlifeen
dc.subjectlandscape modificationen
dc.subjectlandscape patternen
dc.subjectspatial scaleen
dc.subjecthabitat assessmenten
dc.subjectlandscape analysisen
dc.subjectspatial heterogeneityen
dc.subject.lccLD5655.V856 1996.T736en
dc.titleLandscape pattern analysis related to forest wildlife resourcesen
dc.type.dcmitypeTexten and Wildlife Sciencesen Polytechnic Institute and State Universityen D.en
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