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for different habitat types. Kincaid and Bryant (1983) and Kincaid et al.
(1983) offered an alternative method that scores relative differences between
use and availability for habitats defined as geometric vectors.
Most studies using these tests pooled data among individuals, so that ani-
mal captures, sightings, radiolocations, and so on represented the sample
units. Aebischer et al. (1993b) pointed out that this constitutes pseudoreplica-
tion (Hurlbert 1984) and advised comparing use to availability for each animal
individually (i.e., so individuals are the sample units). Several methods have
been developed specifically to do this. Of these, the most commonly used is
Johnson's (1980), which is based on the difference between the rankings of
habitat use and the rankings of habitat availability. This method also provides
a means of detecting statistically significant differences among habitats, not
just a relative ordering of their selection. Moreover, because comparisons are
made on an individual-animal basis, habitat availability can be considered
either within each individual home range, or within the study area as a whole.
Johnson (1980) defined first-order selection as that which distinguishes the
geographic distribution of a species, second-order selection as that which
determines the composition of home ranges within a landscape, and third-
order selection as the relative use of habitats within a home range. Thus, both
second-order and third-order selection can be addressed with Johnson's (1980)
technique; with chi-square tests it is possible (Gese et al. 1988; Carey et al.
1990; Boitani et al. 1994) but more difficult (because of sample size con-
straints) to consider both of these levels of selection.
Alldredge and Ratti (1986, 1992) compared four methods (including the
chi-square, Johnson's, and two others based on individual-animal compar-
isons) in simulated conditions and found that none performed (with regard to
type I and type II error rates) consistently better than the others. However,
some methods are better suited for given situations. For example, because data
for all animals are generally pooled for chi-square tests, unequal sampling
among individuals could strongly affect the results if all individuals did not
make similar selections. Conversely, the methods that weight animals equally,
regardless of the amount of data collected on each, may be subject to spurious
results caused by small sample sizes and variability among individuals.
McClean et al. (1998) used real data on young turkeys ( Meleagris gallopavo ),
which have fairly narrow and well-known habitat requirements, to compare
results of six analytical techniques for assessing habitat selection. In this case,
the methods that treat individuals as sample units tended to be less apt to
detect habitat selection.
Aebischer et al. (1993b) offered what appears to be an improved procedure
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