Matrix structure obscures the relationship between interpatch movement and patch size and isolation

Metapopulation models assume that local population size (in a habitat patch) and therefore local extinction probability, is a function of patch size, and that interpatch movement rate and therefore recolonization of local extinctions is a function of both patch size and patch isolation. We hypothesized that the predictive power of models that relate patch immigation rate to patch size and isolation will be reduced when spatial structure in the landscape matrix (the nonhabitat portion of the landscape) affects organism movernent through the landscape. We used a simulation model to evaluate this hypothesis for three different aspects of matrix spatial structure (contrast among matrix cover types, number of matrix cover types, and grain of matrix spatial pattern) and for two different types of movement behavior, representing a specialist and a generalist species. We tested the hypothesis for one aspect of matrix structure (number of matrix cover types) in a translocation field Study of the eastern chipmunk (Tamias striatus, a habitat specialist) and the white-footed mouse (Peromyscus leucopus, a habitat generalist). When the matrix was composed of a small number of cover types, patch size and isolation accounted for Lip to 75% of the variation in patch immigration rate in the simulation study, and for 61 % of the variation in interpatch movement in the field study. However, when the matrix was composed of a large number of cover types, the amount of explained variation dropped to as little as 33% for the simulation study and to 17% in the field study. Our results suggest that patch characteristics, such as patch size and isolation, may be poor predictors of interpatch movement when the landscape matrix is heterogeneous and when the organism responds to boundaries between different matrix cover types. These results imply that habitat patch-based models, such as those based on current metapopulation theory, will perform poorly in these situations.