County-Level Factors Contributing to Deer–Vehicle Collisions in Arkansas

Arkansas harbors a substantial white-tailed deer (Odocoileus virginianus) population, boasts an expanding human population, and both enjoys and suffers the resulting consequences. A highly visible negative consequence is the occurrence of deer–vehicle collisions (DVCs). Several studies have investig...

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Bibliographic Details
Published in:The Journal of wildlife management 2007-11, Vol.71 (8), p.2727-2731
Main Authors: FARRELL, MICHAEL C, TAPPE, PHILIP A
Format: Article
Language:English
Subjects:
accidents
Arkansas
Coniferous forests
Deciduous forests
Deer
deer-vehicle collisions
forests
highway
Highways
Human populations
Land cover
logging
Mixed forests
Modeling
Odocoileus virginianus
Population density
Regression analysis
Research s
roads
Roads & highways
Rural density
Studies
urban
urban areas
Urban density
Urban environments
Urban sprawl
urbanization
vehicles
white-tailed deer
wildlife management
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Summary:Arkansas harbors a substantial white-tailed deer (Odocoileus virginianus) population, boasts an expanding human population, and both enjoys and suffers the resulting consequences. A highly visible negative consequence is the occurrence of deer–vehicle collisions (DVCs). Several studies have investigated site-specific factors that may contribute to DVCs. However, few studies have explored the role of broader scale factors. In this study, we used an exploratory, multivariate approach to examine the influence of county-level factors on the density (no./1,000 km) of reported DVCs in Arkansas, USA, during 1998–2001. Factors considered to contribute to DVCs in Arkansas included human and deer population densities, urban growth, various roadway characteristics, daily traffic counts, timber harvests, and landcover composition and spatial characteristics. Using principal components and regression analysis we determined that there were 2 important components contributing to DVC densities in Arkansas. Component 1 represented a predominantly forested matrix with high edge density and contrast. Component 2 described an urban environment, with high road densities, human population densities, and average daily traffic counts. These 2 components were strongly related to DVCs (r2 = 0.55, P < 0.001), with component 2 explaining the most variation (71.4%). The identification and recognition of the contribution of these broad-scale factors to DVCs provide insight useful in making informed decisions related to DVC mitigation.
ISSN:0022-541X
1937-2817
DOI:10.2193/2006-085