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    (3.1 MB pdf)
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Home Range

Home range calculations help interpret habitat use, social organization, reproductive dynamics, prey utilization, and limiting resources of a population (Powell 2000). Individual home ranges will be estimated with a kernel utilization distribution. Recent reviews (Powell 2000, Kernohan et al. 2001) have suggested that the nonparametric kernel density estimators may be one of the better home range estimators in current use. Home ranges and core areas estimated from a fixed kernel estimator will be classified at the 95% and 50% contour intervals respectively. The level of smoothing of these regions will be selected by least-squares cross-validation (Seaman et al. 1999). We will have over 50 locations from each VHF collared animal, and from 400 to over 1,200 locations from each GPS-collared animal from which to calculate home range size. Home range size was asymptotic at about 30 locations in other lynx studies when locations were obtained at approximately weekly intervals (Poole 1994, Squires and Laurion 2000). As with the testing of precision of VHF telemetry techniques with GPS collars, we will also compare home ranges calculated with animals with GPS collars using both the VHF telemetry locations and the GPS locations.

We will use the home range analysis extension available for ArcView to calculate home ranges. A 2-way analysis of variance (ANOVA) blocked by year will be the statistical procedure used to examine differences in the size of home ranges between sexes across seasons. Seasons will be defined by snow absence (April-September) and snow presence (October-March). Additional home range estimation techniques, such as the minimum convex polygon will also be used to standardize comparisons with past studies. We plan to use Ranges V for these calculations as well, for comparative purposes (Kenward and Hodder 1996, Squires and Laurion 2000).

The determination of home ranges will permit insights into the spatial organization of the Minnesota lynx population. Poole (1995) quantified the static and dynamic interactions for male and female lynx in the Northwest Territories using standardized definitions for these interactions (MacDonald et al. 1980, Kenward 1992, Aebischer et al. 1993). Similar methods will be applied to lynx in Minnesota. Home range interactions can also be evaluated by the proportional overlap obtained by superimposing the home ranges of adjacent animals of GIS layers in ARCVIEW (Chamberlain et al. 2003).