A New Approach to Understanding Canid Populations

Using an Individual-based Computer Model:

Preliminary Results

William C. Pitt

USDA/APHIS/WS, National Wildlife Research Center, Utah State University, Logan, UT, Utah State University, Logan,

Utah, 84322-5295; (435) 245-6091; ww@cc.usu.edu

Frederick F. Knowlton

USDA/APHIS/WS, National Wildlife Research Center, Utah State University, Logan, Utah, 84322-5295

Paul W. Box

Department of Geography and Earth Resources Department, Utah State University, Logan, Utah, 84322


Ensuring the welfare of wild canid populations depends upon the ability to integrate species

biology, the environmental aspects upon which those populations depend, and the factors controlling

species abundance. Toward this end, we developed an individual-based computer model

using Swarm to mimic natural coyote populations. Swarm is a software platform that allows the

user to describe individual behaviors for all individuals, link those behaviors in each concurrent

time step, and assemble behaviors and objects in a hierarchical framework. Our model stands

apart from previous modeling efforts because it relies on field data and explicitly incorporates

behavioral features, such as dominance and territoriality, as major determinates of species

demography. Individual variation, such as status within territorial social groups and age-based

reproduction are assumed, but assumptions typically associated with most demographic models

are not needed. The eventual goal is to incorporate other environmental components such

as prey abundance and/or competing carnivores. This type of model could also provide

insights into potential management alternatives for when the gray wolf is removed from

endangered status in Minnesota.