The Relationship Between Wildlife Biodiversity and Landscape Characteristics in Virginia
| dc.contributor.author | Stein, Beth Rachel | en |
| dc.contributor.committeechair | Thomas, Valerie A. | en |
| dc.contributor.committeemember | Wynne, Randolph H. | en |
| dc.contributor.committeemember | Stauffer, Dean F. | en |
| dc.contributor.department | Forestry | en |
| dc.date.accessioned | 2014-03-14T21:36:16Z | en |
| dc.date.adate | 2012-06-28 | en |
| dc.date.available | 2014-03-14T21:36:16Z | en |
| dc.date.issued | 2012-05-10 | en |
| dc.date.rdate | 2012-06-28 | en |
| dc.date.sdate | 2012-05-16 | en |
| dc.description.abstract | Wildlife biodiversity provides a variety of ecosystem services and is an important indicator of overall ecosystem health. This research investigates the relationship between wildlife biodiversity and landscape characteristics in Virginia. The goal is to produce predictive models of biodiversity within the Commonwealth using environmental characteristics, including fragmentation metrics at the class- and landscape-levels, as well as other environmental variables. The 1248 12-digit watersheds in Virginia are the sampling units for the analyses, with the state stratified into the seven US Environmental Protection Agency's Level III classification. Data on wildlife alpha diversity is based on two sets of species data maintained by the Virginia Dept. of Game & Inland Fisheries (VDGIF). The first chapter provides an introduction to the issue of biodiversity conservation and the background information for this work. The second chapter describes the study using the 2001 National Land Cover Data to calculate class- and landscape-level fragmentation metrics. Best subset regression is used to determine the best predictors for wildlife biodiversity using these metrics. Final selected models range in predictive power from R2 = 0.41 to 0.73 for each of the 7 ecoregions. The third chapter analyzes the relationship between wildlife biodiversity and various environmental variables in order to determine the strength of these factors as drivers for alpha diversity. These variables are then incorporated with the fragmentation metrics in an attempt to improve the biodiversity models. The environmental variable models had R2 = 0.22 to 0.65 across the ecoregions, while R2 = 0.28 to 0.72 when the environmental and fragmentation variables are combined. The last chapter focuses on the conclusions of the studies, the limitations of the data, and the benefits of this work. Overall, our results underline the importance of using fragmentation metrics in Virginia's wildlife models. | en |
| dc.description.degree | Master of Science | en |
| dc.identifier.other | etd-05162012-213801 | en |
| dc.identifier.sourceurl | http://scholar.lib.vt.edu/theses/available/etd-05162012-213801/ | en |
| dc.identifier.uri | http://hdl.handle.net/10919/42690 | en |
| dc.publisher | Virginia Tech | en |
| dc.relation.haspart | Stein_BR_T_2012.pdf | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.subject | species-habitat relationships | en |
| dc.subject | fragmentation | en |
| dc.subject | biodiversity | en |
| dc.subject | wildlife | en |
| dc.title | The Relationship Between Wildlife Biodiversity and Landscape Characteristics in Virginia | en |
| dc.type | Thesis | en |
| thesis.degree.discipline | Forestry | en |
| thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
| thesis.degree.level | masters | en |
| thesis.degree.name | Master of Science | en |
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