Dispersal of Ruffed Grouse: A Large-Scale Individual-Based Model

We present an efficient data structure enabling us to model, in a microcomputer environment, as many as 10 000 individual ruffed grouse on a landscape subdivided into 9216 contiguous, 10-acre (4 ha) sites. The model is fully stochastic both in a demographic and in an environmental sense. It features use of geographic information about habitat quality and hunting pressure to define site-specific natural and hunting mortality. It combines factors describing the time-specific social landscape, i.e., local density constraints and other social interactions, together with habitat quality, into a site-suitability function. This information is then used to guide the individual movements that in aggregate simulate the dispersal process. Values for parameters controlling the dispersal submodel were determined interactively by comparing model predictions of dispersal distance and duration with actual research findings from a study conducted in central Wisconsin. Additional geographic inputs to the model specify the starting distribution of grouse on the landscape and identify potential metapopulations (habitat islands) and other geographic units such as parcels of land ownership or study areas. Storage of the population state of each subarea enables later analyses of population dynamics in terms of patch attributes. Complete life histories of the individuals in the model are available as model outputs, as are snapshots of the distribution of grouse on the landscape at any user-specified time.