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Improving GIS-based Wildlife-Habitat Analysis (Paperback, 2014 ed.)
Loot Price: R1,426
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Improving GIS-based Wildlife-Habitat Analysis (Paperback, 2014 ed.)
Series: SpringerBriefs in Ecology
Expected to ship within 10 - 15 working days
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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.
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