The efficacy of fisheries management strategies depends on stock assessment and management actions being carried out at appropriate spatial scales. This requires understanding of spatial and temporal population structure and connectivity, which is challenging in weakly structured and highly connected marine populations. We carried out a population genomics study of the heavily exploited snapper (Chrysophrys auratus) along ~2600 km of the Australian coastline, with a focus on Western Australia (WA). We used 10,903 filtered SNPs in 341 individuals from eight sampling locations to characterize population structure and connectivity in snapper across WA and to assess if current spatial scales of stock assessment and management agree with evidence from population genomics. Our dataset also enabled us to investigate temporal stability in population structure as well as connectivity between WA and its nearest, eastern jurisdictional neighbour. As expected for a species influenced by the extensive ocean boundary current in the region, low genetic differentiation and high connectivity were uncovered across WA. However, we did detect strong isolation by distance and genetic discontinuities in the mid-west and south-east. The discontinuities correlate with boundaries between biogeographic regions, influenced by on-shelf oceanography, and the sites of important spawning aggregations. We also detected temporal instability in genetic structure at one of our sites, possibly due to interannual variability in recruitment in adjacent regions. Our results partly contrast with the current spatial management of snapper in WA, indicating the likely benefits of a review. This study supports the value of population genomic surveys in informing the management of weakly structured and wide-ranging marine fishery resources.
CITATION STYLE
Bertram, A., Fairclough, D., Sandoval-Castillo, J., Brauer, C., Fowler, A., Wellenreuther, M., & Beheregaray, L. B. (2022). Fisheries genomics of snapper (Chrysophrys auratus) along the west Australian coast. Evolutionary Applications, 15(7), 1099–1114. https://doi.org/10.1111/eva.13439
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