Poster Sessions, pages 567-640 - ICOET

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Powell, J.W., J.W. Zimmerman, D.E. Seaman, and J.F. Gilliam. 1996. Demographic analysis of a hunted black bear population with access to a refuge. Conservation Biology 10(1): 224-234. Reynolds, D.G., and J.J. Beecham. 1980. Home range activities and reproduction of balck bears in west-central Idaho. In: Martinka, C.J., McArthur, K.L. (eds.) Bears-their biologu and management. Bear Biology Association Conference Series 3. U.S. Government Printing Office, Washington, D.C. pp.181-190. Rowland, M.M., M. Wisdom, B.K. Johnson, and M. A. Penninger. 2005. Effects of roads on elk: Implications for management in forested ecosystems. Pages 42-52 in Wisdom, M.J., technical editor, The Starkey Project: a synthesis of long-term studies of elk and mule deer. Reprinted from 2004 Transactions of the North American Wildlife and Natural Resources Conference, Alliance Communications Group, Lawrence, KS. Semlitsch, R.D., T.J. Ryan, K. Hamed, M. Chatfield, B. Brehman, N. Pekarek, M. Spath,and A. Watland. 2007. Salamander abundance alon road edges and within abandoned logging roads in Appalachian forests. Conservation Biology 21: 159-167. Servheen, C. 1989. The status and conservation of the bears of the world. International Conference on Bear Research and Management. Monograph Series 2: 1-32. Switalski, T.A., J.A. Bissonette, T.H. DeLuca, C.H. Luce, and M.A. Madej. 2004. Benefits and impacts of road removal. Frontiers in Ecology and the Environment 2(1): 21–28. Trombulak, S.C., and C.A. Frissell. 2000. Review of ecological effects of roads on terrestrial and aquatic communities. Conservation Biology 14: 18-30. US Fish and Wildlife Service (USFWS). 1993. Grizzly bear recovery plan. Missoula, MT. 181p. Wisdom, M.J., R.S. Holthausen, B.C. Wales, C.D. Hargis, V.A. Saab, D.C. Lee, W.J. Hann, T.D. Rich, M.M. Rowland, W.J. Murphy, and M.R. Eames. 2000. Source habitats for terrestrial vertebrates of focus in the interior Columbia basin: broad-scale trends and management implications. Volume 1 – Overview. Gen. Tech. Rep. PNW-GTR-485. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. Zar, J.H. Biostatistical Analysis. 1999. Prentice Hall, Inc. Upper Saddle River, New Jersey Posters 632 ICOET 2007 Proceedings
Abstract An Overview of Recent Deer-Vehicle Collision Research in Arkansas Philip A. Tappe (Phone: 870-460-1352, Email: tappe@uamont.edu), Michael C. Farrell (Phone: 719-524-5297, Email: mike.farrell2@us.army.mil), and Donald I.M. Enderle (Phone: 770-270-7678, Email: denderle@photoscience.com), Arkansas Forest Resources Center and School of Forest Resources, University of Arkansas, Monticello, AR 71656. An expanding human population combined with a growing white-tailed deer (Odocoileus virginianus) population has resulted in an escalation of the number of deer-vehicle collisions in Arkansas. In response to this increase, we initiated research to help understand the scope of the problem and to investigate factors contributing to deer-vehicle collisions (DVCs) on Arkansas highways. In Arkansas, vehicle accident reports filed with the Arkansas State Police are currently the most extensive and reliable source of information on DVCs. We used these reports to gather data on DVCs over a 4-year period, 1998 – 2001. A total of 5,858 reports of DVCs were obtained and used to document mean vehicle-damage estimates, mean numbers of human injuries and deer deaths, mean numbers of collisions by time of day and month, and proportions of bucks and does involved in collisions by month. The same 5,858 DVC reports were used to conduct an examination of the influence of county-level factors on the density (no. /1000 km) of reported DVCs in Arkansas. Principal components (PCA) and regression analyses were used to evaluate the importance of county-level factors, such as human population densities/urbanization, landcover composition and arrangement, timber harvest levels, deer density indices, and highway densities and characteristics. Of the 5,858 DVC reports, 3,170 were spatially referenced to specific locations on highways, thus allowing for an evaluation of site-specific factors that may influence the locations of DVC occurrences in Arkansas. We used logistic regression analyses to evaluated the importance of landcover patterns, landcover characteristics, and number of stream/highway intersections within 400, 800, and 1200 m of collision sites; landcover crossing types and maximum topographic relief within 100 m of collision sites; and distances to nearest forest and to nearest water. Furthermore, we developed models for each physiographic region of the state, as well as a state-wide model, to identify high risk areas along Arkansas highways. Collisions were documented in all months, but we found most (>50%) occurred during October – December with a peak in November. The number of collisions was greatest between 5:30 p.m. and midnight with a smaller peak occurring between 5:00 - 7:00 a.m. Most deer (67.5%) were killed as a result of the collisions; 32.5% were injured and fled the collision site. We do not know the ultimate fate of these animals. Overall, 48.3% of the collisions were with bucks and 51.7% were with does. However, we found this proportion varied by month, ranging from 24.1% bucks and 75.9% does in June to 64.7% bucks and 35.3% does in November (Fig. 3). Annually, the human injury rate averaged 0.7%. Reported, estimated damage to individual vehicles averaged almost $2.7 million/year with a mean of $1,926 per collision. Based on an assumed reporting rate of approximately 17%, we estimated that Arkansas could potentially have up to 18,000 DVCs annually with a loss of almost $35 million in vehicle damage. We found that deer-vehicle accident occurrence in Arkansas counties was influenced more by roadway features, level of urbanization, and human population densities than by deer densities or landscape characteristics. PCA indicated two important components contributing to DVC densities in Arkansas counties. 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 (r 2 = 0.55, P < 0.001), with Component 2 explaining the most variation (71.4%). Landcover characteristics of DVC sites were useful in predicting site-specific probabilities of deer-vehicle collisions. Based on 31 site-specific variables, correct classification rates of predictive models (DVC sites vs. non-DVC sites) ranged from 62% - 70%. Five groups of factors strongly correlated with DVC locations were the: (1) presence and amount of water; (2) presence of a diverse association of land cover types; (3) amount and size of urban area; (4) amount and size of forested area; and (5) density of pastures and agricultural crops. Information derived from these studies can aid land managers, agencies, and policy makers in making informed decisions related to DVC mitigation. Additionally, our results provide a foundation for future research targeted at increasing our knowledge of interactions between wildlife and roads, and for further research into DVC mitigation strategies. Biographical Sketch: Philip A. Tappe is a professor of wildlife ecology and management, Associate Director of the Arkansas Forest Resources Center, University of Arkansas Division of Agriculture; and Associate Dean of the School of Forest Resources, University of Arkansas at Monticello. He received his B.S. and M.S. from Stephen F. Austin State University, and his Ph.D. from Clemson University. Bridging the Gaps, Naturally 633 Posters
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Poster Sessions Introduction Ecolog
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metamorphs. Road mortality is likel
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eproductive abilities and survivors
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that the strongest stimuli for immo
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hectic and substantial task of crea
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Forman, R. T. T. 2000. Estimate of
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Lehtinen, R. M. S. M. Galatowitsch,
Page 15 and 16: Sealy, J. B. 2002. Ecology and beha
Page 17 and 18: Abstract Assessing the Stone Marten
Page 19 and 20: Abstract Lessons and Experiences Fr
Page 21 and 22: The Salmon Resource and Sensitive A
Page 23 and 24: Environmental Scoping Application E
Page 25 and 26: Recommendations for future research
Page 27 and 28: Use of a GIS-Based Model of Habitat
Page 29 and 30: Effects of a Purpose-Built Underpas
Page 31 and 32: Background Major Objectives for Roa
Page 33 and 34: Iuell, B., H. (G. J.) Bekker, R. Cu
Page 35 and 36: Forest Service Back Roads: Utilizat
Page 37 and 38: Abstract Development of a Bald Eagl
Page 39 and 40: An Alternative to the Openness Rati
Page 41 and 42: Abstract Effectiveness of Black Bea
Page 43 and 44: Highway Median Impacts on Wildlife
Page 45 and 46: Taxa groups (largely based on Calif
Page 47 and 48: Long-Term Consequences of Winter Ro
Page 49 and 50: Abstract Effects of a Highway Impro
Page 51 and 52: Introduction Roadkill and Landscape
Page 53 and 54: The fact that we have never met two
Page 55 and 56: Figure 3. Valley grassland unit, an
Page 57 and 58: Abstract An Analytical Framework fo
Page 59 and 60: Abstract Measuring Gene Flow Across
Page 61 and 62: Introduction Wildlife Use of Open a
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Page 65: Our track plates did not find any s
Page 69 and 70: Abstract Riparian Restoration Plan
Page 71 and 72: Relating Vehicle-Wildlife Crash Rat
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