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93 HIERARCHICAL MONOTHETIC AGGLOMERATIVE CLUSTERING 40 35.92 33.98 35 30 PERCENT SPECIES 25 20 17.48 15 10 6.80 5 3.88 1.94 0 0.16 1.07 3.05 7.15 10.71 >11 LINEAR DISTANCE DOMAINS (mi) Figure 36. Linear ( Home Range) dispersal domains for 103 mammalian species using hierarchical monothetic agglomerative clustering. using radio telemetry from 1999 to 2003 (Figure 37). Record- The relationship between median dispersal distance and daily ing of the relocations occurred at about 24-hour intervals. movement distance for all 10 species is quite loose, with a mean The data indicate that the majority of individual daily move- of 61.95, S.D. = 83.62, P = 0.05. Mean values for carnivores ments were short with 85.1% being 1,000 meters or less. alone = 42.66, S.D. = 84.45, P = 0.05, and for herbivores, mean = Certainly deer moved greater distances; however, recording 96.4, S.D. = 93.27, P = 0.05. The variation of the ratios between only two locations, one at the beginning of the period and one the median dispersal and daily movement distances is too large at the end, essentially straightens what is a much more tortu- to give a realistic and reasonable conversion factor. With a larger ous movement pathway. This movement oversimplification is sample, the results might be different. Alternatively, when accu- the major problem of using daily movement data. The most rate multiple daily movement distance estimates become avail- accurate method for assessing daily movement distances able for those large species that account for the greatest safety risk would measure the trajectory of the animal's pathway at short when WVCs occur, then a proper daily movement distance scal- intervals for several 24-hour periods using GPS collars set to ing can be developed for individual species. Additional work will record locations frequently, and then take a mean value. Sea- be necessary to see if those data exist. sonality affects daily movement patterns, so an adequate sam- ple is needed. Typical methods for collecting daily movement Interpretation, Appraisal, and Applications distance data include following the trajectory for a few hours and then extrapolating daily movement distance, or taking There are at least three potential options in spacing wildlife only a few (often as few as two) telemetry relocations over a crossings using allometric distance domains. All involve scaling 24-hour period and then measuring the straight-line distance to home range area and are (1) the median dispersal distance between relocations. This method seriously underestimates ( ) 7 * HR , (2) a linear dimension of home range ( HR), and daily movement distances. (3) a scaling measure related to daily dispersal distance. Using However, if there is a consistent relationship between daily the linear dimension of the species home range to develop scale movement distances and median dispersal distance, with prop- domains is most conservative and places crossings closest erly collected data (e.g., by using continuously monitoring GPS together. The implication is that crossings are no further apart radio transmitting collars), a conversion factor can be developed than the linear dimension of the largest home range in the scale for daily movement distance domains that might help inform domain. wildlife crossing distance. The research team initially found 10 Using the square root of the home range to establish scal- species for which daily movement data were available (Table 35). ing domains to inform the placement of wildlife crossings is Each individual movement represents the straight-line distance most reasonable because shorter dispersal distances by juve- between two relocations taken approximately 24 hours apart. niles are more frequent.227 Additionally, animal fidelity to