Improving GIS-based Wildlife-Habitat Analysis

  • Jeffrey K. Keller
  • Charles R. Smith

Part of the SpringerBriefs in Ecology book series (BRIEFSECOLOGY)

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Jeffrey K. Keller, Charles R. Smith
    Pages 1-17
  3. Jeffrey K. Keller, Charles R. Smith
    Pages 19-37
  4. Jeffrey K. Keller, Charles R. Smith
    Pages 39-56
  5. Jeffrey K. Keller, Charles R. Smith
    Pages 57-68
  6. Jeffrey K. Keller, Charles R. Smith
    Pages 69-80
  7. Jeffrey K. Keller, Charles R. Smith
    Pages 81-101
  8. Back Matter
    Pages 103-132

About this book


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.


GIS Geographic Information Systems Habitat Modeling Image Resolution Patch Specificity Wildlife Ecology

Authors and affiliations

  • Jeffrey K. Keller
    • 1
  • Charles R. Smith
    • 2
  1. 1.Habitat by DesignPipersvilleUSA
  2. 2.Cornell UniversityIthacaUSA

Bibliographic information