Artificial propagation programs that focus on production, such as commercial aquaculture, entail strong domestication selection. Spillover from such programs can cause unintended fitness and demographic consequences for wild conspecifics. The range of possible management practices to minimize such consequences vary in their control of genetic and demographic processes. Here we use a model of coupled genetic and demographic dynamics to evaluate alternative management approaches to minimizing unintended consequences of aquaculture escapees. With this quantitative framework, we compare the effect of (1) the degree of similarity or difference between artificial and natural selection, (2) constant low-level spillover versus rare, large pulses of escapees, (3) the amount of reduced reproductive success (sterilization efficacy) of aquaculture escapees in the wild, and (4) spillover of different life history stages.
Results/Conclusions
We find that, compared to reducing domestication selection as much as possible, the alternative of selecting for a phenotypically different aquaculture population unlikely to survive in the wild only works if a strong natural selection event occurs between escape and reproduction. Surprisingly, reducing escapees through low-level leakage is more effective at minimizing unintended fitness consequences than reducing an analogous number of escapees from large, rare pulses; this result is due to the ratcheting effect of low-level leakage on long-term time scales (i.e., migrational meltdown). Imperfect sterilization can still substantially reduce unintended fitness consequences. Finally, sensitivity to the stage of escape indicates a need for improved monitoring data on how the number of escapees varies across life cycle stages. For spillover from artificial production programs in general, our results indicate the central importance of understanding the relative timing of events within life cycles and the variability of spillover across time to the effective management of unintended fitness consequences.