The Inseparability of Spatial and Temporal Clustering in a Population Model with Spatially Correlated Disturbances
by
David Hiebeler
Dept. of Mathematics and Statistics, University of Maine
Coauthors: Isaac Michaud (University of Maine) Nicholas Millett (University of Maine)

Our prior work studied the effects of large-scale disturbance events in a locally-dispersing spatial patch-occupancy population model, where contiguous blocks of sites were simultaneously disturbed in such a way that the per-site disturbance rate was kept fixed. Results indicated that increasing the spatial scale of disturbance events had a negative effect on equilibrium population density. However, the reason for this effect was speculated to be possibly due to different factors, such as slow recolonization of disturbed regions via only local dispersal, or the increased temporal variability that accompanied the increased spatial scale of disturbances. Here, several variations of the model are explored via simulations, to further explore why spatially correlated disturbances adversely affect a locally-dispersing population, and to try to separate the effects of spatial and temporal clustering in such disturbances. Some issues related to efficient simulation of such models will also be discussed.

Date received: May 15, 2008