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94 Figure 37. Distribution of daily movement distances of 46 telemetered mule deer from 1999 to 2003. home range areas suggests that shorter individual movement lometric domains can be developed to inform the placement distances predominate among all sexes and ages. Thus, the of wildlife crossings. The sample given in Table 35, however, linear scale approach would appear to promote greatest suggests that a large sample will be needed to extract the rela- permeability (Figure 38, Table 36). A less conservative tionship, if it exists. approach uses the median dispersal distance,33 i.e., seven times the linear dimension of home range, as the criteria for developing the scale domains. Longer distance dispersal does Conclusions occur less frequently but is important for recolonizing areas Placing Crossings for Large Mammals as well as gene flow.227 An intermediate approach might use daily movement distances to develop distance domains. Typ- The involvement of large terrestrial mammals in ically, one might expect that mammals would travel signifi- wildlifevehicle collisions tends to result in greater vehicle cantly longer distances in their search for resources. To the damage and greater potential for human injury and death extent that daily movement data are available for species, al- than the involvement of smaller body-sized animals. Large- Table 35. Daily movement distances for 10 mammalian species. Species TLa MedDDb (m) DMDc (m) Ratio Swift fox (Vulpes velox)d C 19,712 18,500 1.07 European marten (Martes martes)e C 8,573 5,100 1.68 Eurasian lynx (Lynx lynx)f C 30,128 3,800 7.93 Polecat (Mustela putorius)g C 9,899 1,097 9.02 Wolverine (Gulo gulo)h C 271,109 1,400 193.60 Lemming (Dicrostonyx groenlandicus)i H 213 15 14.08 Mule deer (Odocoileus hemionus)j H 11,823 311 38.02 Moose (Alces alces)k H 24,400 220 111.90 Cotton rat (Sigmodon hispidus)l H 4,670 21 221.60 Wild boar (Sus scrofa)m O 274,485 13,280 20.67 a trophic level: C = carnivore, H = herbivore, O = omnivore; bmedian dispersal distance; cdaily movement d 64 e 250 f 173 g 39 h 198 distance; Covell et al. ; Zalewski et al. ; Moa et al. ; Brzezinski et al. ; Renzhu et al. ; i Schmidt et al.207; jKrausman, unpublished data; kCourtois et al.63; lSulok et al.226; mSpitz and Janeau218.
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95 essential additional information to inform the location of wildlife crossings. Caveats Figure 38. Degree of landscape permeability Clustering techniques, such as the hierarchical mono- for mammalian species is dependent upon thetic agglomerative clustering method, make no considera- which distance domain (linear home range tion for topography, land form, or landscape structure. They distance, daily movement or median dispersal simply group similar clusters of animals based on specified distance) is used to develop the scaling criteria. When the clusters are used to group species by allo- domains, and hence the spacing between metric distances, one implicit assumption is that all species wildlife crossings. use all parts of the landscape in a homogeneous manner. This clearly is not the case. Additionally, all measurements bodied animals are a greater safety risk on the road. It are derived ultimately from published home range areas. The appears that to achieve the kind of landscape permeability home range of an animal is an area traversed by the individ- that will help ensure the health of large-mammal popula- ual in its normal activities of food gathering, mating, and tions (i.e., deer, moose, elk, and bear) and to minimize caring for young.171 Home range area is a measure that WVCs, placement of wildlife crossings in areas where pop- implicitly assumes that the animal uses all parts of its range. ulations of these animals exist will entail at least a multistep Although there are some home range measurement tech- decision process. The first involves deciding which allo- niques (i.e., the center of activitykernel method249 and the metric scaling domain is appropriate and feasible. Highest non-parametric method, e.g., area determination by GPS permeability will be obtained when crossings of appropri- Cartesian coordinates and analyzed with map software) that ate type and design are placed using the LHRD (the HR measure not only the extent of the area used by the animal (mi) column in Table 36). Crossings placed according to but also concentrations of activity within the home range, the MedDD domains are clearly too far apart to create high the oldest and most commonly used method is the mini- permeability of the landscape. However, placing wildlife mum convex polygon home range estimator175 that estimates crossings using the LHRD domain for white-tailed deer and only area of use. A clearer and more concise measure of mule deer at about 1 mi (1.6 km) apart in areas where these resource use can be obtained by following an animal's move- animals cross the road frequently, and are often hit by ment trajectory and assessing what resources it is using, but vehicles, would certainly improve highway safety and help this method is seldom done and large datasets are unavail- ensure ease of movement, improving landscape permeabil- able. An advantage of following animal trajectories is that ity for these animals. Using the MedDD values of 6.1 to 7.4 daily movement distances could be estimated. mi to space the crossings for these deer species clearly is in- In summary, using home range area to establish allometric appropriate and will do little to reduce WVCs or facilitate distance domains can be problematic; however, other consis- movement. Similar arguments are appropriate for the other tently collected and reliable data are not widely available. species listed in Table 36 and for all species in general. A clear need is the gathering of a sufficient sample of accurate However, using scaling domains represents only the first home range information. The use of the linear home range step in ensuring landscape permeability and improving dimension, coupled with local knowledge of animal move- highway safety. Local information about migration path- ments across the road and with animal crash and carcass data, ways, areas of local animal movement across roads, provides an ecologically sound approach to inform the place- hotspots of WVCs, and carcass data on the road provides ment of animal crossings. Table 36. Home range of large mammals and derived scaling domains for wildlife crossing placement. Species HR (mi2) HR (mi) MedDD (mi) White-tailed deer (Odocoileus virginianus) 0.8 0.9 6.1 Mule deer (Odocoileus hemionus) 1.1 1.1 7.4 Pronghorn antelope (Antilocapra americana) 4.1 2.0 14.2 Moose (Alces alces) 5.0 2.2 15.2 Elk (Cervus canadensis) 5.0 2.2 15.6 Bighorn sheep (Ovis canadensis) 5.5 2.4 16.5 Black bear (Ursus americanus) 9.3 3.1 21.4 Grizzly bear (Ursus arctos) 35.8 6.0 41.9