title: Locally dispersing populations in heterogeneous dynamic landscapes with spatiotemporal correlations. II. Habitat driven by voter dynamics.
abstract: We examine a spatially explicit population model on a dynamic landscape with suitable and unsuitable habitat driven by voter or contagion dynamics. We consider four cases, consisting of all combinations of local and global interactions for both population dispersal and habitat dynamics. For both local and global population dispersal, using local habitat dynamics always increases population density relative to the case with global habitat dynamics, due to the resulting segregation of habitat turnover, decrease in effective habitat turnover rate, and presence of stable habitat corridors. With global habitat dynamics, a population using local dispersal exhibits lower density than one with global dispersal due to local crowding as well as frequent disturbance due to habitat transitions. On the other hand, with local habitat dynamics, a population using local dispersal can exploit suitable habitat patches and use dynamic corridors to colonize new regions. The latter effect is not seen with static landscapes, where clustered habitat can lead to the isolation of suitable patches due to surrounding unsuitable habitat.
authors.affiliation: Department of Mathematics and Statistics, University of Maine, Orono, ME 04469, United States. Electronic address: hiebeler@math.umaine.edu.
authors.forename: David E
authors.initials: DE
authors.lastname: Hiebeler
authors.affiliation: Department of Mathematics and Statistics, University of Maine, Orono, ME 04469, United States.
authors.forename: Jack L
authors.initials: JL
authors.lastname: Hill
mesh_terms: D003198:Computer Simulation; D017753:Ecosystem; D007091:Image Processing, Computer-Assisted; D008954:Models, Biological; D011157:Population Dynamics; D012111:Residence Characteristics; D062211:Spatio-Temporal Analysis
keywords: Cellular automata voter model; Dynamic habitat; Habitat loss and fragmentation; Spatiotemporal structure; Stochastic spatial simulation