Aggregate statistical measures and metapopulation dynamics.
There are two main types of metapopulation models. Spatially implicit models are analytically tractable but neglect spatial heterogeneities. Spatially explicit models are more realistic but too complex. In this paper, I build a bridge between both approximations. I derive a new metapopulation model using a well-known technique in population genetics. Spatial heterogeneities are captured by an aggregate statistical measure of spatial correlation. When this correlation is zero, i.e., space is homogeneous, the model becomes the well-known Levins' model. As spatial correlation increases, equilibrium patch occupancy decreases from what would be expected under the spatially homogeneous assumption. I proceed by testing how well spatial complexities from a spatially explicit simulation can be encapsulated by such an aggregate statistical measure.
Bascompte
J
J
National Center for Ecological Analysis and Synthesis, University of California at Santa Barbara, 735 State St. Suite 300, Santa Barbara, CA 93101-3351, U.S.A. bascompte@ebd.csic.es
D000818:Animals; D004463:Ecology; D008954:Models, Biological; D015233:Models, Statistical; D011157:Population Dynamics