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Trends in the Index of Use <br />The change in the frequency of use of the study area by whooping cranes throughout the CA <br />period was estimated with the observed trend in an index of use. The index of crane use was <br />defined as the number of crane groups observed per number of flights (PRESP 2005) and was <br />calculated for each monitoring season. Survey detection rates were incorporated into this <br />analysis through adjustment of the observed number of cranes by the estimated probability of <br />detection during the flight, based on the predictive detectability model (Thompson 1992) and the <br />recalculation of the index of use with the adjusted number of crane groups. Simple linear <br />regression with normal errors was used to estimate the change in the index through time. Time <br />was represented by the year and the proportion of year at the midpoint of the survey. The winter <br />peak count of the Aransas-Wood Buffalo population was included as a covariate. <br />Activity Summary <br />The percentage of time a crane group was engaged in each activity was calculated for an <br />observation session, where an observation session is defined as all the time a crane group was <br />observed during a day. These percentages were averaged across all observation sessions recorded <br />and the variance of this average was used to calculate confidence intervals. The summaries were <br />made by migration season (spring and fall) and for both migration seasons combined and <br />represent diurnal activities. <br />Habitat Selection <br />Characteristics of whooping crane habitat selection in the central Platte River was modeled <br />through the development of resource selection functions (RSF). The basic premise of resource <br />selection modeling (Manly et al. 2002) is that resources (which may be food items, land cover <br />types, or any quantifiable habitat characteristic) that are important to animals will be "used" <br />disproportionately to the availability of those resources in the environment. The RSF model uses <br />an exponential function to model and predict the relative probability of use from the landscape <br />characteristics. In this analysis, the characteristics at the used locations were contrasted to <br />characteristics at randomly selected "available" locations in the same region. <br />There were two sets of used locations for the RSF analyses: all locations (in and out of channel) <br />for summarizing study area selection, and the subset of in-channel locations for summarizing in- <br />channel selection. A location is defined as a point in space used by a crane group at one point in <br />time. These locations represent multiple re-locations of the same group of birds but since <br />individual cranes were not identifiable in the field and observations of whooping cranes are rare, <br />we have maintained all the observations in the dataset we analyzed. <br />For the models relating landscape level characteristics to crane group selection in the entire study <br />area, we defined the available set of points with a 500x500m grid randomly placed over the <br />entire study area. The intersection of the gridlines results in 6,420 available points. A subset of <br />189 points were in the 'wetted channel' or "barren beach/bar" designation of the 1998 land <br />cover/use GIS layer and comprised the available points for the in-channel analysis. <br />4