**4. Conclusion**

Data on wildlife locations are increasingly detailed in both space and time. Conversion to binary home range maps has been useful. However, the methods presented here take

Quantifying Wildlife Home Range Changes 279

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advantage of greater data detail and enable new spatial-temporal research questions to be addressed. There is a general dearth of temporal methods for geographical data, and efforts are underway to develop new methods for space-time analysis that will likely have applications and benefits in wildlife and ecological studies (e.g., Rey & Janikas, 2006). Spatially explicit methods will be increasingly important as data sets continue to increase in size.

All the methods presented in this chapter are mappable and can be integrated with other GIS data sets. For instance, locations of change can be correlated to environmental variables (elevation or landscape fragmentation), resource selection functions (e.g., Boyce and McDonald, 1999), roads, or human disturbance data. Existing literature is useful for generating hypotheses on space-time home range patterns and changes in home range intensity. By quantifying observed patterns and integrating additional data, it is possible to determine if the patterns are different from or similar to our expectations. Linking patterns of change with additional data sets will enable testing of hypotheses on processes driving change.

Knowing where change is occurring is essential for conservation and management of wildlife and habitat. Methods that not only locate, classify, and quantify change, but that integrate change maps with data on environmental and human activities, are essential for conservation. The methods presented here are applicable to any wildlife research where home ranges are defined by kernel density estimation and two or more home ranges occur in a study area. While I have demonstrated approaches for detecting change between two time periods, these methods are also useful when comparing spatially overlapping home ranges of individuals or populations, such as analysis of predators and prey home ranges.

#### **5. Acknowledgement**

I am grateful to Mark Williams and the British Columbia Ministry of Environment for access to caribou data. This research is funded in part by the National Science and Engineering Research Council.

#### **6. References**


advantage of greater data detail and enable new spatial-temporal research questions to be addressed. There is a general dearth of temporal methods for geographical data, and efforts are underway to develop new methods for space-time analysis that will likely have applications and benefits in wildlife and ecological studies (e.g., Rey & Janikas, 2006). Spatially

All the methods presented in this chapter are mappable and can be integrated with other GIS data sets. For instance, locations of change can be correlated to environmental variables (elevation or landscape fragmentation), resource selection functions (e.g., Boyce and McDonald, 1999), roads, or human disturbance data. Existing literature is useful for generating hypotheses on space-time home range patterns and changes in home range intensity. By quantifying observed patterns and integrating additional data, it is possible to determine if the patterns are different from or similar to our expectations. Linking patterns of change with

Knowing where change is occurring is essential for conservation and management of wildlife and habitat. Methods that not only locate, classify, and quantify change, but that integrate change maps with data on environmental and human activities, are essential for conservation. The methods presented here are applicable to any wildlife research where home ranges are defined by kernel density estimation and two or more home ranges occur in a study area. While I have demonstrated approaches for detecting change between two time periods, these methods are also useful when comparing spatially overlapping home ranges of individuals or populations, such as analysis of predators and prey home ranges.

I am grateful to Mark Williams and the British Columbia Ministry of Environment for access to caribou data. This research is funded in part by the National Science and Engineering

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explicit methods will be increasingly important as data sets continue to increase in size.

additional data sets will enable testing of hypotheses on processes driving change.

**5. Acknowledgement** 

pp. 1875–1883

1405–1493

Research Council.

**6. References** 


**14** 

*Canada* 

**Use of Telemetry Data to** 

Marina Silva-Opps and Sheldon B. Opps

*Animal Movement and Resource Selection Research Group,* 

**Investigate Home Range and Habitat Selection in Mammalian Carnivores** 

*University of Prince Edward Island, Charlottetown, Prince Edward Island,* 

Management of mammalian carnivore populations, whether to conserve a threatened species or to control the abundance of a noxious one, requires a basic understanding of the ecology and behaviour of a given species. Habitat selection and home range are fundamental processes in the ecology and behaviour of most animals, explaining why most researchers generally investigate them when assessing a species' needs. Presumably, species should have a higher fitness in habitats that they select or allow them to accomplish basic activities such as foraging and reproduction. Once habitats can be ordered by their relative preference, they can be evaluated as to their relative importance in terms of fitness (Garshelis, 2000). Wildlife managers and conservation biologists can, then, make decisions regarding any habitat modification or population control requirement that may be needed

The assessment of either habitat selection or home range requires the collection of data on the animals' use of space. In theory, different approaches can be used to obtain the data needed to assess habitat selection and home range patterns. One approach may be to obtain the data by following an animal in order to observe its movements and habits. However, this approach is likely to prove very difficult, particularly in areas with thick vegetation or where the animal is active at night or when dealing with a species with secretive habits. There is also the risk that the close proximity of humans could affect the animal's behaviour resulting in an unrealistic outcome of the study or possibly having a negative effect on the studied animal, like interfering with the hunting success in mammalian carnivores. Another approach may involve obtaining data from transect surveys (Buckland et al., 1993). These surveys record animals in the vicinity of a set of sampling lines or points and therefore tend to yield relatively few sightings, particularly for rare species living in inaccessible environments. Telemetry is without any doubt the most common method to quantify either habitat selection or home range patterns, especially in mammalian carnivore species. Telemetry is a tool or technique used to research wild animal species in the field in order to gain a thorough understanding of that population and its dynamics as well as to identify any potential threats to its survival (White & Garrott, 1990). It is typically used to gather data from distant, inaccessible locations, or when data collection would be dangerous or difficult for a variety of reasons. Wildlife telemetry concerns the use of telemetry techniques

**1. Introduction** 

to deal with the species in question.

