Problem Context

Habitat loss is a growing issue that affects the home ranges of Algonquin wolves (Canis lycaon) in Algonquin Provincial Park. As the adverse effects of climate change on the Earth's populations, communities, and ecosystems present themselves in complex ways, a sustainable wolf population becomes harder to maintain. Due to being seen as a nuisance species and nonexistent hunting restrictions, the Algonquin wolf population shrank drastically up until 1993 (Musiani and Paquet 2004), when the provincial government imposed a ban on hunting wolves in the park (Forbes and Theberge 1996). Nonetheless, Algonquin wolves were classified as threatened in 2013 (Ontario 2014). As apex predators, wolves play a massively important role in their ecosystems (Benson et al. 2017); community structure is controlled mainly by apex predators, as they provide top-down control affecting both density and behaviour of their prey (Beschta and Ripple 2012). This top-down control affects herbivore densities, and in turn, vegetation densities (Beschta and Ripple 2012). Certain population management strategies, such as reintroduction in Yellowstone National Park (Beschta and Ripple 2012) and a hunting ban in Algonquin since 1993 (Algonquin Provincial Park Management Plan 1998) have been implemented to attempt to help the wolf population recover, and there have been many successes. Models such as the Approximate Bayesian Computation (ABC) have been applied to wolf populations to model factors such as reproduction, habitat range, and pack composition to study how certain changes can affect the wolf population now and in the future (Chapron et al. 2016).  

While wolf mortality is largely caused by anthropogenic activities (Forbes and Theberge 1996; Musiani and Paquet 2004), forest fires are devastating events that can destroy much of an area that a denning animal has carefully selected (Richardson et al. 2007; Gaudreau et al. 2015). In an attempt to conserve ecological communities, there have been management efforts put in place to help regulate the wolf population in Algonquin (Algonquin Provincial Park Management Plan 1998) as well as model the possible spread of forest fires, such as BorealFireSim (Gaudreau et al. 2015). However, further research and studies are needed in order to fully understand the impacts of forest fires on wolf populations in the region. Fire management plans in the past focused on completely suppressing forest fires, but by the 1970s, different levels of fire suppression were implemented (Natural Resources Canada 2016). Various ecological benefits arise due to forest fires, including allowing fire-origin tree species, such as Jack Pine, to grow (Gaudreau et al. 2015). However, wolves avoid using open fields (Carlyle et al. 2008), so it can be assumed that after a forest fire, a wolf will have to relocate. This means that wolves must select a new den site, which is based off a few different criteria (Benson and Patterson 2015). 

While research has been done on both wolf populations and the effects of fire, information about the effects of fire on wolf populations is lacking. More research needs to be conducted, as management options for threatened wolf populations need to be explored. A GIS (geographic information system) uses information gathered to analyze, structure, manipulate, interpolate, and display data in a geospatial context (Swanson 2001); therefore, it is a very useful tool in this study. Other studies have used multi-criteria evaluations (MCE) to successfully identify reintroduction sites for Japanese scallops (Radiarta et al. 2008). Additionally, Beschta and Ripple (2012) have shown through a linear regression that the reintroduction of wolves to Yellowstone National Park has been successful. These kinds of strategies could be applied to Algonquin to help the wolf population recover. This suggests that using a MCE approach to isolate den site suitability is effective in addressing the objectives of this study. The outcomes of this study will provide information about wolf response to habitat loss due to fire. This will be useful in terms of predicting where wolves will most likely choose to position a new den following a fire event, aiding in wolf conservation efforts and allowing optimal management policies to be implemented. 

Purpose of Research

The purpose of this research is to develop a GIS model that predicts areas of suitable habitat for Algonquin wolves within Algonquin Provincial Park to determine the proportion of viable habitat at low risk for loss due to wildfire.

Research Objectives

1. To identify factors related to habitat suitability for Algonquin wolves and wildfire risk.
2. To develop a GIS-based multi-criteria evaluation model for suitable habitat prediction.
3. To apply the model to predict areas of suitable habitat at low risk for wildfires in Algonquin Provincial Park.
4. To evaluate the strengths and limitations of the GIS-based habitat suitability model.