Geographic Information Systems (GIS) provide a powerful tool for the investigation of
species-habitat relationships and the development of wildlife management and conservation
programs. However the relative ease of data manipulation and analysis using GIS associated
landscape metrics packages and sophisticated statistical tests may sometimes cause
investigators to overlook important species-habitat functional relationships. Additionally
underlying assumptions of the study design or technology may have unrecognized consequences.
This volume examines how initial researcher choices of image resolution scale(s) of analysis
response and explanatory variables and location and area of samples can influence analysis
results interpretation predictive capability and study-derived management prescriptions.
Overall most studies in this realm employ relatively low resolution imagery that allows
neither identification nor accurate classification of habitat components. Additionally the
landscape metrics typically employed do not adequately quantify component spatial arrangement
associated with species occupation. To address this latter issue the authors introduce two
novel landscape metrics that measure the functional size and location in the landscape of
taxon-specific 'solid' and 'edge' habitat types. Keller and Smith conclude that investigators
conducting GIS-based analyses of species-habitat relationships should more carefully 1) match
the resolution of remotely sensed imagery to the scale of habitat functional relationships of
the focal taxon 2) identify attributes (explanatory variables) of habitat architecture size
configuration quality and context that reflect the way the focal taxon uses the subset of the
landscape it occupies and 3) match the location and scale of habitat samples whether GIS- or
ground-based to corresponding species' detection locations and scales of habitat use.
