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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
