COS 110-5
The inevitable partial collapse of an American pika metapopulation

Thursday, August 13, 2015: 9:20 AM
343, Baltimore Convention Center
Easton R White, Center for Population Biology, University of California - Davis, Davis, CA
John D. Nagy, School of Mathematical and Statistical Sciences, Arizona State University, Tempe, AZ

Conventionally, population biologists have tended to focus on deterministic properties of population dynamics, like equilibrium population sizes, minimum viable populations and cyclic population dynamics. Recently, however, there has been a shift toward incorporating stochastic processes into population models. Stochastic phenomena are likely to drive metapopulations---populations of disjoint habitat "patches" connected by dispersal---with small patches. Here we report on a newly developed computational model designed to evaluate the significance of random fluctuations and the role of spatial structure in driving population dynamics. The model is formulated as a stochastic process on a finite, spatially explicit array of patches. Probability of successful dispersal is modeled as a function of distance between patches.


As a test of the model, we apply it to the best-known mammalian metapopulation in North America: the American pika (Ochotona princeps) population living on the ore dumps in the ghost mining town of Bodie, California. The model was parameterized with demographic and spatial data from the Bodie metapopulation, which has been studied nearly continuously for 6 decades. Our model is able to describe many of the population dynamics (e.g. mean population size and percent occupancy of patches) of the Bodie population. In addition, we found that the spatial structure of patches and the heterogeneity (i.e. the number of territories per patch) of each are sufficient to correctly predict the collapse of the southern half of the Bodie metapopulation. This type of model is flexible enough to be applied to many systems with different spatial structures, dispersal strategies, or different life histories in general.