Abstract
<jats:p>The orange-bellied parrot (Neophema chrysogaster) is one of Australia’s most critically endangered birds, with low juvenile survival during annual migration hindering species recovery despite intensive conservation efforts. Understanding the genetic basis of migration success may improve management in this species and provide insight into the role of functional genomic variation in small, bottlenecked populations. Here, we combined demographic reconstruction, genome-wide diversity analyses, and functional genomic approaches to investigate the relationship between genomic variation and migratory survival in the last remaining wild population of orange-bellied parrots. Historical demographic analyses identified two distinct population bottlenecks: an older reduction in effective population size predating European settlement and a more recent severe collapse beginning in the mid-to-late 20th century. Contemporary individuals exhibited low genome-wide heterozygosity, extensive runs of homozygosity, and extremely low effective population size (Ne ≈ 31), however, neither genome-wide heterozygosity nor inbreeding were associated with migratory survival. In contrast, finer-scale analyses identified 43 loci associated with migration outcomes, including a nonsynonymous variant in PLEKHG5, a gene linked to motoneuron function and angiogenesis. Window-based scans also identified candidate regions under positive selection on chromosome 4, although these showed little spatial overlap with candidate SNPs detected through per-SNP analyses. Despite this, both approaches converged on similar functional pathways associated with cellular metabolism, signal transduction, and stress response, suggesting migration success is influenced by broad physiological processes with a polygenic basis. Together, our results demonstrate that broad measures of genetic diversity alone may fail to capture functionally important variation in critically endangered species and highlight the importance of integrating analyses across multiple genomic scales to identify genetic variation associated with fitness-related traits.</jats:p>