Understanding behavioral mechanisms of population dynamics

The processes behind a species’ spatio-temporal population dynamics can be traced back to how individual animals move across the landscape and make decisions about where to eat, what to eat, and how much time should be devoted to things like searching, traveling, and avoiding predators.  In other words, when we see a population range distribution map and/or a graph of population dynamics over time, what we are seeing is the culmination of the outcome of every individual’s behavior in the population.  Surprisingly however, the mechanisms that link fine scale behaviors to population level processes are relatively unknown.

As technology continues to develop, researchers are now equipped to answer these questions.  Using GPS-based radio collars, we are able to track just about every step of an animal as it moves across the landscape.  This fine scale movement information, coupled with increasingly precise satellite images that allow us to classify the landscape with great detail, provide the building blocks to understand the processes behind population dynamics.  We can now begin to understand why an animal turns right here, walks 10 meters, then stops for 1 hour to eat.  Using a movement based framework we can mathematically translate the movement path of just a few individuals into how the entire population should look now, and 10 years or more into the future.

My research capitalizes on the detailed knowledge of the plains bison population in Prince Albert National Parks, Saskatchewan.  Since 1995, the park, along with University collaborators, has been monitoring the bison population using aerial surveys during winter, GPS collars, and field observation.  The bison range is mostly forested, but is scattered with open meadows where grass, sedges, and rushes (the food source for bison) grow abundantly.  Using this detailed history, we are developing models that explain the movement patterns of bison, particularly as it relates to the exploration of new areas (i.e., range expansion).   What we learn from these models can be then translated into landscape scale, time and spatially based predictions of what the population may look like in the future.  Our predictions will be very useful for the park to anticipate where the bison population will move to, and how many there might be.

Collaborators: Daniel Fortin, Departement de Biologie at Université Laval, Parks Canada, Centre d’étude de la forêt

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