resource availability in a way needed for resource-area dependence analysis
(Kenward 2001). Dispersal detection can be defined statistically as departure
from a home range, and settling by the reverse process, though that will require
records over longer periods than home ranges. Indeed, home ranges are likely to
change from season to season. Techniques used in the short term to define a stand-
ard seasonal home range may also be used to define an annual home range.
With the development of Geographic Information Systems, detailed maps
have become more available for analyzing use of resources. This is an important
consideration when obtaining software for location analyses, because two options
are available. One option is to attempt all analyses within industry-standard
software, such as ESRI ArcView (www.esri.com). Animal Movement tools
(www.absc.usgs.gov/glba/gistools) calculate some types of range outline, so that
areas and resource use can be estimated. This software is free, but requires access
to ESRI software, including the Spatial Analyst extension (which alone costs
US$2495).
Alternatively, there is specialized software for radio locations, of which
the most comprehensive is Ranges (www.anatrack.com, see the biotelemetry
clearing house http://www.biotelem.org/software.htm for other software). Ranges
(costing GB£300–590) is designed for use in pilot studies and provides auto-
mated autocorrelation, incremental, and dispersal analyses, with other home
range and sociality analyses that are not present in the Animal Movement tools.
Ranges 6 has comprehensive on-line help for rapid learning and, unlike ESRI
software, also gives spreadsheet-ready results from automated repeating analyses
on multiple sets of location data. Maps can be prepared in Ranges if they are
simple or imported from ESRI or cheaper GIS (e.g. http://www.mapmaker.com,
http://www.sbg.ac.at/geo/idrisi)..)
Maps can be based on categories (e.g. habitats) in line-bounded polygons or in
an array of cells. If practical, they are best prepared initially as polygons (vector
format), because these require less space for storage and convert readily to cells
(rasters) at any scale. However, remote sensed maps (e.g. from Landsat images)
come as rasters of a particular resolution, for example, 25 m for the 25 categories
in the Landcover Map of Great Britain (Fuller et al. 1994).
6.4.4Demography
The advent of reliable long-life tags enables rapid modeling of population struc-
ture, from age-specific survival and breeding data. Such models can be used for
various purposes, including exploitation analyses (Chapter 13). Long-life tags
also enable work on how dispersal, survival, and breeding relate to resource use
and sociality. Survival rates can be estimated and compared with MARK (contact
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