Why use GIS?
Geographic Information Systems (GIS) include a number of tools to apply a spatial analysis approach, improving one’s understanding of moose habitats relative to key factors that influence their decisions. With this platform, one can analyze and model relationships between forest fires and moose habitats, while also providing a real-world geospatial representation of the data (Dangermond, 2007). GIS is used in this study to show how each spatial variable effects moose migration to new habitats upon the occurrence of a forest fire. A spatial variable is defined as information that gives the locations and shapes of geographic features and is able to describe the relationship between features through different mapping techniques (ESRI, 2017). The analysis of moose habitat is done using spatial analysis because the problem looks at the size, shape, and location of different land covers (geographic features), to determine how their proximity and availability will affect the likelihood that moose will make a certain area their new habitat after forced migration (relationship). GIS provides a framework for integrating all considerable factors in relation to one another, making this topic of research highly dependent on spatial variables.
Throughout this section, each research objective is highlighted and discussed. The first objective is the identification of relevant constraints and criteria. The most critical factors contributing to moose habitat are locations of previous fire occurrence, forest cover for shelter, water availability, ecosites for preferred vegetation, and restricted areas due to human infrastructure (Ardea Biological Consulting, 2004). It is important to consider all suitable locations of moose habitats within and around the chosen study area, keeping in mind the criteria and constraints for moose habitat (Seiler, Cederlund, Jernelid, Grangstedt & Ringaby, 2003). The second objective identifies the need to develop a Multi-Criteria Evaluation (MCE) model. Relating to objective three, the constraints and criteria will create an MCE model that is run from each origin of the ten fires in the Big Tracadie River Wildlife Management Zone of New Brunswick. Since moose typically migrate within a 150 km2 area, locations that meet all criteria and constraints within this range are considered in the suitability ranking (Fisher & Wilkinson, 2005). After completing the MCE analysis for each fire, the six most suitable habitat regions for moose relocation are determined and presented as a map. These six regions are chosen based on the highest suitability scores and to avoid bias when presenting the data. As moose reside in areas which are between 5 and 10km2, these six regions must contatin sites that are within this size range. Finally, objective four discusses the strengths and limitations of the MCE model.
Objective 1: To Identify all social and biophysical variables related to moose habitat.
Objective 2: To develop a GIS-based MCE model to site new moose habitats.
Objective 3: To apply an MCE model that determines the most suitable moose habitats post fire.
Objective 4: To evaluate the possible strengths and limitations of this MCE model.