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Modeling the restoration of a metapopulation : implications for resource management

A simulation model was developed to test the effects of alternative management actions on the restoration of a metapopulation. The probability of extinction was modeled as a function of population growth, environmental stochasticity, and dispersal. Population growth rates varied between patches so source-sink dynamics could be modeled. Environmental stochasticity had two components, one shared by all patches and one unique to each patch. Dispersal rates varied between pairs of patches. Results showed that metapopulation viability was highly sensitive to the dispersal rate between patches, the distribution of growth rates among patches, and the proportion of common to independent environmental variation experienced by patches. Small amounts of dispersal provided sharply increased viability to the metapopulation as compared to identical cases without dispersal. Viability increased as the proportion of enviromnental effects that were independent between patches increased. Fragmentation decreased viability by blocking dispersal corridors, removing opportunities for recolonization, augmentation, and buffering. Results of simulations showed that management intervention, such as moving ammals between fragmented populations, recolonizing a “source” patch, or moving animals to ensure dispersal increased metapopulation viability. Improving patches with high growth rates increased viability more than improving low growth rate patches. Using these results, a strategy to restore metapopulations was developed. The goal was to maximize the overall population growth rate, using a subdivided population to provide buffering. The strategy suggests selecting a number of strong patches possessing buffering capabilities, recolonizing any that are vacant, ensuring dispersal and focusing improvements on them. The simplicity of the simulations and resulting strategy improves one’s understanding of metapopulation restoration, but also limits its application to any specific case. The ability to apply these results would be strengthened by using spatially structured population viability analysis, simulations of added complexity and/or an adaptive management strategy. * Endangered Snake River spring/summer Chinook salmon, a metapopulation provided an illustration of the study’s application. Applying the suggested strategy requires greater levels of management intervention than is common in salmon management and is likely to be the subject o f great debate. Adaptive management experiments are required to test the benefits of suggested methods.