In general, the individual kākāpō that carried the highest number of SVs in one dataset also appeared to carry a relatively high number of SVs in other datasets (Figure 4). For example, the individual carrying the highest number of SVs in the Delly dataset (A), is the same individual carrying the second highest number of SVs in the Smoove dataset (D). Upon closer inspection we found that the three individuals that consistently carried the most SVs in the Delly and Smoove datasets were not read mapping outliers (22.8x, 23.12x and 26.5x). In addition, there appeared to be either high variability in the number of SVs per individual (Delly & Smoove), or relatively little variability (both Manta datasets, CuteSV and Sniffles). Another interesting note is variability in SV type underlying these individual differences. Specifically, inversions are the dominant SV type among individuals carrying the most SVs in the Delly datasets, whereas deletions dominate in both Manta datasets, CuteSV and Sniffles. For the Smoove data, inversions are the most common SV type in individuals carrying the most SVs, despite deletions being more consistently observed across the population.