Setting spatial conservation priorities despite incomplete data for characterizing metapopulations.

Management of spatially structured species poses unique challenges. Despite a strong theoretical foundation, practitioners rarely have sufficient empirical data to evaluate how populations interact. Rather, assumptions about connectivity and source-sink dynamics are often based on incomplete, extrapolated, or modeled data, if such interactions are even considered at all. Therefore, it has been difficult to evaluate whether spatially structured species are meeting conservation goals. We evaluated how estimated metapopulation structure responded to estimates of population sizes and dispersal probabilities and to the set of populations included. We then compared outcomes of alternative management strategies that target conservation of metapopulation processes. We illustrated these concepts for Chinook salmon (Oncorhynchus tshawytscha) in the Snake River, USA. Our description of spatial structure for this metapopulation was consistent with previous characterizations. We found substantial differences in estimated metapopulation structure when we had incomplete information about all populations and when we used different sources of data (three empirical, two modeled) to estimate dispersal, whereas responses to population size estimates were more consistent. Together, these findings suggest that monitoring efforts should target all populations occasionally and populations that play key roles frequently and that multiple types of data should be collected when feasible. When empirical data are incomplete or of uneven quality, analyses using estimates produced from an ensemble of available datasets can help conservation planners and managers weigh near-term options. Doing so, we found trade-offs in connectivity and source dominance in metapopulation-level responses to alternative management strategies that suggest which types of approaches may be inherently less risky.