Using location data

Location data can be used for purposes other than home range definition. For example, resources can be estimated in circles or ellipses of a size that either reflect uncertainty or define availability (Arthur et al. 1996). Interactions can be determined solely from the distances between animals. However, home range outlines also provide overlap indices, identify neighbors for sociality analyses and estimate 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 standard 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 ( Animal Movement tools ( 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

Alternatively, there is specialized software for radio locations, of which the most comprehensive is Ranges (, see the biotelemetry clearing house for other software). Ranges (costing GB£300-590) is designed for use in pilot studies and provides automated 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.,

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).

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