The difficulty of detecting inbreeding depression and its effect on conservation decisions

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College of Forest Resources and Environmental Science


Statistical inferences about inbreeding depression are often derived from analyses with low power and a high risk of failing to detect inbreeding depression. That risk is widely appreciated by scientists familiar with the relevant statistical and genetical theory, but may be overlooked and underappreciated by decision-makers. Consequently, there is value in demonstrating this risk using a real example. We use data from the wolf population on Isle Royale to demonstrate the difficulty of making reliable statistical inferences about inbreeding depression. This wolf population is known - by other methods - to have gone effectively extinct due to deleterious genetic processes associated with inbreeding. Beyond that demonstration, we use two case studies - wolves on Isle Royale and vaquita (porpoises) from the Gulf of California, Mexico - to show how statistical inferences about inbreeding depression can affect conservation decisions. According to most decision theory, decisions depend importantly on (i) probabilities that certain states exist (e.g., inbreeding depression is present) and (ii) the utility assigned to various outcomes (e.g., the value of acting to mitigate inbreeding when it is present). The probabilities are provided by statistical inference whereas utilities are almost entirely determined by normative values and judgement. Our analysis suggests that decisions to mitigate inbreeding depression are often driven more by utilities (normative values) than probabilities (statistical inferences). As such, advocates for mitigating inbreeding depression will benefit from better communicating to decision-makers the value of populations persisting and the extent to which decisions should depend on normative values.

Publication Title

The Journal of heredity