Confidently identifying the correct K value using the Delta K method: When does K=2?

Populations delineated based on genetic data are commonly used for wildlife conservation and management. Many studies use the program structure combined with the Delta K method to identify the most probable number of populations (K). We recently found K = 2 was identified more often when studies used Delta K compared to studies that did not. We suggested two reasons for this: hierarchical population structure leads to underestimation, or the Delta K method does not evaluate K = 1 causing an overestimation. The present contribution aims to develop a better understanding of the limits of the method using one, two and three population simulations across migration scenarios. From these simulations we identified the best K using model likelihood and Delta K. Our findings show that mean probability plots and Delta K are unable to resolve the correct number of populations once migration rate exceeds 0.005. We also found a strong bias towards selecting K = 2 using the Delta K method. We used these data to identify the range of values where the Delta K statistic identifies a value of K that is not well supported. Finally, using the simulations and a review of empirical data, we found that the magnitude of Delta K corresponds to the level of divergence between populations. Based on our findings, we suggest researchers should use the Delta K method cautiously; they need to report all relevant data, including the magnitude of Delta K, and an estimate of connectivity for the research community to assess whether meaningful genetic structure exists within the context of management and conservation.